diff --git a/butterflow-ui/AboutWindow.xaml b/butterflow-ui/AboutWindow.xaml
index 587a98f..79cb7c7 100644
--- a/butterflow-ui/AboutWindow.xaml
+++ b/butterflow-ui/AboutWindow.xaml
@@ -17,7 +17,7 @@
             </StackPanel>
             <WrapPanel HorizontalAlignment="Center">
                 <TextBlock Text="{x:Static loc:Localization.VersionLabel}" />
-                <TextBlock Text=" - "/>
+                <TextBlock Text=" - " />
                 <TextBlock Name="txtVersion" Text="0.0.0.0" />
             </WrapPanel>
             <TextBlock Text="{x:Static loc:Localization.AboutWindowDescription}" TextAlignment="Center" />
@@ -34,23 +34,25 @@
                 <Label Grid.Row="0" Grid.Column="0" VerticalAlignment="Center" Content="{x:Static loc:Localization.DevelopersLabel}" />
                 <StackPanel Grid.Row="0" Grid.Column="1" VerticalAlignment="Center">
                     <TextBlock HorizontalAlignment="Center">
-                            <Hyperlink NavigateUri="https://github.com/wagesj45" RequestNavigate="Hyperlink_RequestNavigate">Jordan Wages</Hyperlink>
+                        <Hyperlink NavigateUri="https://github.com/wagesj45" RequestNavigate="Hyperlink_RequestNavigate">Jordan Wages</Hyperlink>
+                        |
+                        <Hyperlink NavigateUri="https://www.paypal.me/wagesj45" RequestNavigate="Hyperlink_RequestNavigate"><TextBlock Text="{x:Static loc:Localization.DonateLabel}" /></Hyperlink>
                     </TextBlock>
                 </StackPanel>
                 <Label Grid.Row="1" Grid.Column="0" VerticalAlignment="Center" Content="{x:Static loc:Localization.OpenSourceCreditsLabel}" />
                 <StackPanel Grid.Row="1" Grid.Column="1" VerticalAlignment="Center">
                     <TextBlock HorizontalAlignment="Center">
-                        butterflow 
+                        butterflow
                         | <Hyperlink NavigateUri="https://github.com/dthpham/butterflow" RequestNavigate="Hyperlink_RequestNavigate"><TextBlock Text="{x:Static loc:Localization.AboutWindowGithubLinkLabel}" /></Hyperlink>
                         | <Hyperlink NavigateUri="https://github.com/dthpham/butterflow/blob/master/LICENSE" RequestNavigate="Hyperlink_RequestNavigate"><TextBlock Text="{x:Static loc:Localization.AboutWindowLicenseLinkLabel}" /></Hyperlink>
                     </TextBlock>
                     <TextBlock HorizontalAlignment="Center">
-                        cs-mic 
+                        cs-mic
                         | <Hyperlink NavigateUri="https://github.com/wagesj45/cs-mic" RequestNavigate="Hyperlink_RequestNavigate"><TextBlock Text="{x:Static loc:Localization.AboutWindowGithubLinkLabel}" /></Hyperlink>
                         | <Hyperlink NavigateUri="https://github.com/wagesj45/cs-mic/blob/master/LICENSE" RequestNavigate="Hyperlink_RequestNavigate"><TextBlock Text="{x:Static loc:Localization.AboutWindowLicenseLinkLabel}" /></Hyperlink>
                     </TextBlock>
                     <TextBlock HorizontalAlignment="Center">
-                        Gu.Wpf.Media 
+                        Gu.Wpf.Media
                         | <Hyperlink NavigateUri="https://github.com/JohanLarsson/Gu.Wpf.Media" RequestNavigate="Hyperlink_RequestNavigate"><TextBlock Text="{x:Static loc:Localization.AboutWindowGithubLinkLabel}" /></Hyperlink>
                         | <Hyperlink NavigateUri="https://github.com/JohanLarsson/Gu.Wpf.Media/blob/master/LICENSE.md" RequestNavigate="Hyperlink_RequestNavigate"><TextBlock Text="{x:Static loc:Localization.AboutWindowLicenseLinkLabel}" /></Hyperlink>
                     </TextBlock>
@@ -63,7 +65,7 @@
             </Grid>
             <Separator Margin="0,10" />
             <TextBlock Text="{x:Static butterflow_ui:OctokitWrapper.CurrentVersionStatusDescription}" TextAlignment="Center" Margin="0,10" />
-            <Button Name="btnOK" MaxWidth="50" Content="{x:Static loc:Localization.OKLabel}" Click="btnOK_Click"/>
+            <Button Name="btnOK" MaxWidth="50" Content="{x:Static loc:Localization.OKLabel}" Click="btnOK_Click" />
         </StackPanel>
     </DockPanel>
-</Window>
+</Window>
\ No newline at end of file
diff --git a/butterflow-ui/App.config b/butterflow-ui/App.config
index 2f4bad6..c741964 100644
--- a/butterflow-ui/App.config
+++ b/butterflow-ui/App.config
@@ -14,7 +14,10 @@
                 <value>en-US</value>
             </setting>
             <setting name="Device" serializeAs="String">
-                <value>-1</value>
+                <value>0</value>
+            </setting>
+            <setting name="UseDefaultDevice" serializeAs="String">
+                <value>True</value>
             </setting>
         </butterflow_ui.Properties.Settings>
     </userSettings>
diff --git a/butterflow-ui/Localization/Localization.Designer.cs b/butterflow-ui/Localization/Localization.Designer.cs
index 8328b9f..565606c 100644
--- a/butterflow-ui/Localization/Localization.Designer.cs
+++ b/butterflow-ui/Localization/Localization.Designer.cs
@@ -312,6 +312,15 @@ namespace butterflow_ui.Localization {
             }
         }
         
+        /// <summary>
+        ///   Looks up a localized string similar to donate.
+        /// </summary>
+        public static string DonateLabel {
+            get {
+                return ResourceManager.GetString("DonateLabel", resourceCulture);
+            }
+        }
+        
         /// <summary>
         ///   Looks up a localized string similar to _Edit.
         /// </summary>
@@ -861,6 +870,15 @@ namespace butterflow_ui.Localization {
             }
         }
         
+        /// <summary>
+        ///   Looks up a localized string similar to Use Default Compute Device.
+        /// </summary>
+        public static string UseDefaultDeviceLabel {
+            get {
+                return ResourceManager.GetString("UseDefaultDeviceLabel", resourceCulture);
+            }
+        }
+        
         /// <summary>
         ///   Looks up a localized string similar to Version.
         /// </summary>
diff --git a/butterflow-ui/Localization/Localization.resx b/butterflow-ui/Localization/Localization.resx
index ca249b7..6e62e78 100644
--- a/butterflow-ui/Localization/Localization.resx
+++ b/butterflow-ui/Localization/Localization.resx
@@ -396,4 +396,10 @@
   <data name="ForceCPU" xml:space="preserve">
     <value>Force CPU</value>
   </data>
+  <data name="UseDefaultDeviceLabel" xml:space="preserve">
+    <value>Use Default Compute Device</value>
+  </data>
+  <data name="DonateLabel" xml:space="preserve">
+    <value>donate</value>
+  </data>
 </root>
\ No newline at end of file
diff --git a/butterflow-ui/MainWindow.xaml b/butterflow-ui/MainWindow.xaml
index 5125954..52cc499 100644
--- a/butterflow-ui/MainWindow.xaml
+++ b/butterflow-ui/MainWindow.xaml
@@ -15,13 +15,13 @@
         <ObjectDataProvider x:Key="enumRegionTypeDataProvider" MethodName="GetValues"
                             ObjectType="{x:Type System:Enum}">
             <ObjectDataProvider.MethodParameters>
-                <x:Type TypeName="butterflow_ui:RegionType"/>
+                <x:Type TypeName="butterflow_ui:RegionType" />
             </ObjectDataProvider.MethodParameters>
         </ObjectDataProvider>
         <ObjectDataProvider x:Key="enumFlowFilterTypeDataProvider" MethodName="GetValues"
                             ObjectType="{x:Type System:Enum}">
             <ObjectDataProvider.MethodParameters>
-                <x:Type TypeName="butterflow_ui:FlowFilterType"/>
+                <x:Type TypeName="butterflow_ui:FlowFilterType" />
             </ObjectDataProvider.MethodParameters>
         </ObjectDataProvider>
         <butterflow_ui:InverseBoolConverter x:Key="InverseBoolConverter" />
@@ -56,7 +56,7 @@
                 </MenuItem>
             </MenuItem>
             <MenuItem Header="{x:Static loc:Localization.HelpMenu}">
-                <MenuItem Name="menuButterflowGithub" Header="{x:Static loc:Localization.AboutButterflowMenu}" Click="menuButterflowGithub_Click" >
+                <MenuItem Name="menuButterflowGithub" Header="{x:Static loc:Localization.AboutButterflowMenu}" Click="menuButterflowGithub_Click">
                     <MenuItem.Icon>
                         <ContentControl Template="{StaticResource LinkIcon}" />
                     </MenuItem.Icon>
@@ -83,7 +83,7 @@
             </Grid.RowDefinitions>
             <Grid.ColumnDefinitions>
                 <ColumnDefinition Width="0.5*" />
-                <ColumnDefinition Width="0.5*"/>
+                <ColumnDefinition Width="0.5*" />
                 <ColumnDefinition Width="*" />
                 <ColumnDefinition Width="Auto" />
             </Grid.ColumnDefinitions>
@@ -95,8 +95,8 @@
                             <ColumnDefinition Width="*" />
                             <ColumnDefinition Width="Auto" />
                         </Grid.ColumnDefinitions>
-                        <Label Grid.Column="0" Content="{x:Static loc:Localization.FileLabel}"/>
-                        <TextBox Name="txtFileName" Grid.Column="1" IsReadOnly="True"/>
+                        <Label Grid.Column="0" Content="{x:Static loc:Localization.FileLabel}" />
+                        <TextBox Name="txtFileName" Grid.Column="1" IsReadOnly="True" />
                         <Button Grid.Column="2" MinWidth="25" Name="btnFilePicker" Click="btnFilePicker_Click">...</Button>
                     </Grid>
                 </GroupBox>
@@ -107,8 +107,8 @@
                             <ColumnDefinition Width="*" />
                             <ColumnDefinition Width="Auto" />
                         </Grid.ColumnDefinitions>
-                        <Label Grid.Column="0" Content="{x:Static loc:Localization.FileLabel}"/>
-                        <TextBox Name="txtFileOutputName" Grid.Column="1" IsReadOnly="True" Text="{Binding OptionsConfiguration.VideoOutput, Mode=OneWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}, UpdateSourceTrigger=PropertyChanged}"/>
+                        <Label Grid.Column="0" Content="{x:Static loc:Localization.FileLabel}" />
+                        <TextBox Name="txtFileOutputName" Grid.Column="1" IsReadOnly="True" Text="{Binding OptionsConfiguration.VideoOutput, Mode=OneWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}, UpdateSourceTrigger=PropertyChanged}" />
                         <Button Grid.Column="2" MinWidth="25" Name="btnFileOutputPicker" Click="btnFileOutputPicker_Click">...</Button>
                     </Grid>
                 </GroupBox>
@@ -134,7 +134,7 @@
             <GroupBox Grid.Row="1" Grid.Column="0" Grid.ColumnSpan="2" Header="{x:Static loc:Localization.CommonOptionsGroupBox}">
                 <ScrollViewer>
                     <StackPanel>
-                        <butterflow_ui:ButterflowOption LabelValue="{x:Static loc:Localization.PlaybackRateLabel}" >
+                        <butterflow_ui:ButterflowOption LabelValue="{x:Static loc:Localization.PlaybackRateLabel}">
                             <StackPanel Orientation="Vertical">
                                 <butterflow_ui:ButterflowOption LabelValue="">
                                     <RadioButton GroupName="PlaybackRate" Checked="PlaybackRateRadioButton_Checked" Content="{x:Static loc:Localization._2xLabel}" Tag="2x" />
@@ -146,7 +146,7 @@
                                     <RadioButton GroupName="PlaybackRate" Checked="PlaybackRateRadioButton_Checked" Content="{x:Static loc:Localization._4xLabel}" Tag="4x" />
                                 </butterflow_ui:ButterflowOption>
                                 <butterflow_ui:ButterflowOption LabelValue="">
-                                    <RadioButton GroupName="PlaybackRate" Checked="PlaybackRateRadioButton_Checked" Content="{x:Static loc:Localization._24fpsLabel}" Tag="24"/>
+                                    <RadioButton GroupName="PlaybackRate" Checked="PlaybackRateRadioButton_Checked" Content="{x:Static loc:Localization._24fpsLabel}" Tag="24" />
                                 </butterflow_ui:ButterflowOption>
                                 <butterflow_ui:ButterflowOption LabelValue="">
                                     <RadioButton GroupName="PlaybackRate" Checked="PlaybackRateRadioButton_Checked" Content="{x:Static loc:Localization._30fpsLabel}" Tag="30" />
@@ -158,7 +158,7 @@
                                     <RadioButton GroupName="PlaybackRate" Checked="PlaybackRateRadioButton_Checked" Content="{x:Static loc:Localization._120fpsLabel}" Tag="120" />
                                 </butterflow_ui:ButterflowOption>
                                 <butterflow_ui:ButterflowOption LabelValue="{x:Static loc:Localization.CustomPlaybackRateLabel}" DescriptionValue="{x:Static loc:Localization.PlaybackRateDescription}">
-                                    <TextBox Name="txtPlaybackRate" Text="{Binding OptionsConfiguration.PlaybackRate, Mode=TwoWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}, UpdateSourceTrigger=PropertyChanged}" GotFocus="txtPlaybackRate_GotFocus"  />
+                                    <TextBox Name="txtPlaybackRate" Text="{Binding OptionsConfiguration.PlaybackRate, Mode=TwoWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}, UpdateSourceTrigger=PropertyChanged}" GotFocus="txtPlaybackRate_GotFocus" />
                                 </butterflow_ui:ButterflowOption>
                             </StackPanel>
                         </butterflow_ui:ButterflowOption>
@@ -203,7 +203,6 @@
                                     </ToggleButton.Style>
                                 </ToggleButton>
                                 <Button BorderThickness="0" Style="{StaticResource {x:Static ToolBar.ButtonStyleKey}}" Click="bntVideoStop_Click">
-
                                 </Button>
                                 <butterflow_ui:ButterflowOption Grid.Column="2" LabelValue="{x:Static loc:Localization.HeightLabel}">
                                     <TextBox Text="{Binding OptionsConfiguration.Height, Mode=TwoWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}, UpdateSourceTrigger=LostFocus}" IsReadOnly="{Binding OptionsConfiguration.LockAspectRatio, Mode=OneWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}, UpdateSourceTrigger=PropertyChanged}">
@@ -233,10 +232,10 @@
                                     <DataTemplate>
                                         <DockPanel MaxHeight="24">
                                             <TextBlock VerticalAlignment="Center" Text="{x:Static loc:Localization.StartLabel}" />
-                                            <TextBlock VerticalAlignment="Center" Text="{Binding Start, Converter={x:Static gu:TimeSpanToStringConverter.Default}}" ToolTip="{Binding Start}"/>
+                                            <TextBlock VerticalAlignment="Center" Text="{Binding Start, Converter={x:Static gu:TimeSpanToStringConverter.Default}}" ToolTip="{Binding Start}" />
                                             <TextBlock VerticalAlignment="Center" Text="{x:Static loc:Localization.EndLabel}" />
-                                            <TextBlock VerticalAlignment="Center" Text="{Binding End, Converter={x:Static gu:TimeSpanToStringConverter.Default}}" ToolTip="{Binding End}"/>
-                                            <ComboBox VerticalAlignment="Center" ItemsSource="{Binding Source={StaticResource enumRegionTypeDataProvider}}" SelectedItem="{Binding SubregionType, Mode=TwoWay}"/>
+                                            <TextBlock VerticalAlignment="Center" Text="{Binding End, Converter={x:Static gu:TimeSpanToStringConverter.Default}}" ToolTip="{Binding End}" />
+                                            <ComboBox VerticalAlignment="Center" ItemsSource="{Binding Source={StaticResource enumRegionTypeDataProvider}}" SelectedItem="{Binding SubregionType, Mode=TwoWay}" />
                                             <TextBox VerticalAlignment="Center" MinWidth="35" Text="{Binding Value, Mode=TwoWay}" />
                                             <TextBlock VerticalAlignment="Center" Text="{x:Static loc:Localization.ToEndLabel}" />
                                             <CheckBox VerticalAlignment="Center" IsChecked="{Binding ToEnd, Mode=TwoWay}" />
@@ -276,7 +275,7 @@
                             <TextBox Text="{Binding OptionsConfiguration.SmoothDerivativeStandardDeviation, Mode=TwoWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}, UpdateSourceTrigger=LostFocus}" />
                         </butterflow_ui:ButterflowOption>
                         <butterflow_ui:ButterflowOption LabelValue="{x:Static loc:Localization.FlowFilterLabel}" DescriptionValue="{x:Static loc:Localization.FlowFilterTooltip}">
-                            <ComboBox ItemsSource="{Binding Source={StaticResource enumFlowFilterTypeDataProvider}}" SelectedItem="{Binding OptionsConfiguration.FlowFilterType, Mode=TwoWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}, UpdateSourceTrigger=PropertyChanged}"/>
+                            <ComboBox ItemsSource="{Binding Source={StaticResource enumFlowFilterTypeDataProvider}}" SelectedItem="{Binding OptionsConfiguration.FlowFilterType, Mode=TwoWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}, UpdateSourceTrigger=PropertyChanged}" />
                         </butterflow_ui:ButterflowOption>
                     </StackPanel>
                 </ScrollViewer>
@@ -320,8 +319,8 @@
                         <ColumnDefinition Width="Auto" />
                     </Grid.ColumnDefinitions>
                     <Label Grid.Column="0" Content="{Binding ElementName=mediaPreview, Path=Position, Converter={x:Static gu:TimeSpanToStringConverter.Default}}" />
-                    <Slider Grid.Column="1" Name="sliderMedia" 
-                            Value="{Binding ElementName=mediaPreview, Path=Position, Converter={x:Static gu:NullableTimeSpanToSecondsConverter.Default}}" 
+                    <Slider Grid.Column="1" Name="sliderMedia"
+                            Value="{Binding ElementName=mediaPreview, Path=Position, Converter={x:Static gu:NullableTimeSpanToSecondsConverter.Default}}"
                             Maximum="{Binding Path=Length, ElementName=mediaPreview, Converter={x:Static gu:NullableTimeSpanToSecondsConverter.Default}}" />
                     <Label Grid.Column="2" Content="{Binding Path=Length, ElementName=mediaPreview, Converter={x:Static gu:TimeSpanToStringConverter.Default}}" />
                 </Grid>
@@ -360,9 +359,9 @@
                     </Button>
                 </StatusBarItem>
                 <StatusBarItem Grid.Column="1">
-                    <TextBlock Text="{Binding OptionsConfiguration.CommandLineOutput, Mode=OneWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}}"/>
+                    <TextBlock Text="{Binding OptionsConfiguration.CommandLineOutput, Mode=OneWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:MainWindow}}}" />
                 </StatusBarItem>
             </StatusBar>
         </Grid>
     </DockPanel>
-</Window>
+</Window>
\ No newline at end of file
diff --git a/butterflow-ui/OptionsConfiguration.cs b/butterflow-ui/OptionsConfiguration.cs
index f4d75ca..4781797 100644
--- a/butterflow-ui/OptionsConfiguration.cs
+++ b/butterflow-ui/OptionsConfiguration.cs
@@ -11,7 +11,6 @@ using csmic;
 
 namespace butterflow_ui
 {
-
     /// <summary> The butterflow options configuration. Contians all the options necessary to run butterflow and process a video. </summary>
     public class OptionsConfiguration : PropertyChangedAlerter
     {
@@ -19,67 +18,93 @@ namespace butterflow_ui
 
         /// <summary> The default pyramid scale setting. </summary>
         private const decimal DEFAULT_PYRAMID_SCALE = 0.5m;
+
         /// <summary> The default levels setting. </summary>
         private const int DEFAULT_LEVELS = 3;
+
         /// <summary> The default window size setting. </summary>
         private const int DEFAULT_WINDOW_SIZE = 25;
+
         /// <summary> The default iterations setting. </summary>
         private const int DEFAULT_ITERATIONS = 3;
+
         /// <summary> The default pixel neighborhood setting. </summary>
         private const int DEFAULT_PIXEL_NEIGHBORHOOD = 5;
+
         /// <summary> The default smooth derivative standard deviation setting. </summary>
         private const decimal DEFAULT_SMOOTH_DERIVATIVE_STANDARD_DEVIATION = 1.1m;
+
         /// <summary> The default flow filter type setting. </summary>
         private const FlowFilterType DEFAULT_FLOW_FILTER_TYPE = FlowFilterType.box;
+
         /// <summary> The output file format when operating on more than one video. </summary>
         private const string OUTPUT_FILE_FORMAT = "{0}_{1}";
 
         /// <summary> An input interpreter used for converting string values to numeric values. </summary>
         [NonSerialized]
         private InputInterpreter interpreter = new InputInterpreter();
+
         /// <summary> The aspect ratio used for calculating heights when the aspect ratio is locked. </summary>
         private decimal aspectRatio = 0;
 
         /// <summary> The playback rate. </summary>
         private string playbackRate;
+
         /// <summary> A value indicating whether or not to keep the original audio in the final video. </summary>
         private bool keepAudio;
+
         /// <summary> The width of the output video. </summary>
         private int width;
+
         /// <summary> The height of the output video. </summary>
         private int height;
+
         /// <summary> A value indicating whether or not to render unspecified subregions. </summary>
         private bool keepSubregions;
+
         /// <summary> A value indicating whether or not to render the final video with lossless quality. </summary>
         private bool losslessQuality;
+
         /// <summary> A value indicating whether or not to tune processing for smooth motion. </summary>
         private bool smoothMotion;
+
         /// <summary> A value indicating whether or not to lock the aspect ratio to the <seealso cref="width"/> of the video. </summary>
         private bool lockAspectRatio;
+
         /// <summary> The video input files. </summary>
         private IEnumerable<string> videoInput;
+
         /// <summary> The video output file. </summary>
         private string videoOutput;
+
         /// <summary> A value indicating whether or not to use fast pyramids when processing a video. </summary>
         private bool fastPyramid;
+
         /// <summary> The pyramid scale setting. </summary>
         private decimal pyramidScale;
+
         /// <summary> The level size setting. </summary>
         private int levels;
+
         /// <summary> Size of the windowing average. </summary>
         private int windowSize;
+
         /// <summary> The number of iterations per pyramid level. </summary>
         private int iterations;
+
         /// <summary> The size of pixel neighborhood. </summary>
         private int pixelNeighborhood;
+
         /// <summary> The standard deviation of smooth derivatives </summary>
         private decimal smoothDerivativeStandardDeviation;
+
         /// <summary> Type of the flow filter to use for processing. </summary>
         private FlowFilterType flowFilterType = FlowFilterType.box;
+
         /// <summary> The subregions of the video on which to process. </summary>
         private ObservableCollection<ButterflowSubregion> subregions = new ObservableCollection<ButterflowSubregion>();
 
-        #endregion
+        #endregion Members
 
         #region Properties
 
@@ -158,7 +183,7 @@ namespace butterflow_ui
             }
             set
             {
-                if (value && this.width != 0 && this.height != 0)
+                if(value && this.width != 0 && this.height != 0)
                 {
                     this.aspectRatio = Convert.ToDecimal(this.height) / Convert.ToDecimal(this.width);
                 }
@@ -185,7 +210,7 @@ namespace butterflow_ui
 
                 OnPropertyChanged();
 
-                if (this.lockAspectRatio)
+                if(this.lockAspectRatio)
                 {
                     interpreter.Interpret(string.Format("{0} * {1}", this.aspectRatio, this.width));
                     this.height = interpreter.Int;
@@ -364,7 +389,7 @@ namespace butterflow_ui
             {
                 interpreter.Interpret(value);
 
-                if (interpreter.Int >= 5 && interpreter.Int <= 7)
+                if(interpreter.Int >= 5 && interpreter.Int <= 7)
                 {
                     this.pixelNeighborhood = interpreter.Int;
                 }
@@ -419,7 +444,7 @@ namespace butterflow_ui
             }
         }
 
-        #endregion
+        #endregion Properties
 
         #region Contructors
 
@@ -445,16 +470,16 @@ namespace butterflow_ui
         /// <param name="e">      Notify collection changed event information. </param>
         private void Subregions_CollectionChanged(object sender, System.Collections.Specialized.NotifyCollectionChangedEventArgs e)
         {
-            if (e.NewItems != null)
+            if(e.NewItems != null)
             {
-                foreach (ButterflowSubregion newItem in e.NewItems)
+                foreach(ButterflowSubregion newItem in e.NewItems)
                 {
                     newItem.PropertyChanged += SubregionPropertyChanged;
                 }
             }
-            if (e.OldItems != null)
+            if(e.OldItems != null)
             {
-                foreach (ButterflowSubregion oldItem in e.OldItems)
+                foreach(ButterflowSubregion oldItem in e.OldItems)
                 {
                     oldItem.PropertyChanged -= SubregionPropertyChanged;
                 }
@@ -463,7 +488,7 @@ namespace butterflow_ui
             OnPropertyChanged("CommandLineOutput");
         }
 
-        #endregion
+        #endregion Contructors
 
         #region Methods
 
@@ -532,7 +557,7 @@ namespace butterflow_ui
         {
             var stringBuilder = new StringBuilder("-v "); // Verbose
 
-            if (this.LockAspectRatio)
+            if(this.LockAspectRatio)
             {
                 stringBuilder.AppendFormat("-vs {0}:-1 ", this.Width);
             }
@@ -541,37 +566,40 @@ namespace butterflow_ui
                 stringBuilder.AppendFormat("-vs {0}:{1} ", this.Width, this.Height);
             }
 
-            if(Settings.Default.Device == 0)
+            if(!Settings.Default.UseDefaultDevice)
             {
-                stringBuilder.Append("-sw ");
-            }
-            if(Settings.Default.Device > 0)
-            {
-                stringBuilder.AppendFormat("-device {0} ", Settings.Default.Device);
+                if(Settings.Default.Device == 0)
+                {
+                    stringBuilder.Append("-sw ");
+                }
+                if(Settings.Default.Device > 0)
+                {
+                    stringBuilder.AppendFormat("-device {0} ", Settings.Default.Device - 1);
+                }
             }
 
-            if (!string.IsNullOrWhiteSpace(this.PlaybackRate)) stringBuilder.AppendFormat("-r {0} ", this.PlaybackRate);
-            if (this.KeepAudio) stringBuilder.Append("-audio ");
-            if (this.LosslessQuality) stringBuilder.Append("-l ");
+            if(!string.IsNullOrWhiteSpace(this.PlaybackRate)) stringBuilder.AppendFormat("-r {0} ", this.PlaybackRate);
+            if(this.KeepAudio) stringBuilder.Append("-audio ");
+            if(this.LosslessQuality) stringBuilder.Append("-l ");
 
-            if (this.Subregions.Any())
+            if(this.Subregions.Any())
             {
                 stringBuilder.Append("-s ");
 
-                foreach (var anon in this.Subregions.Select((sr, index) => new { Index = index, Subregion = sr }))
+                foreach(var anon in this.Subregions.Select((sr, index) => new { Index = index, Subregion = sr }))
                 {
                     string format = "ss\\.fff";
 
-                    if (anon.Index > 0)
+                    if(anon.Index > 0)
                     {
                         stringBuilder.Append(":");
                     }
 
-                    if (anon.Subregion.Start.TotalHours > 1)
+                    if(anon.Subregion.Start.TotalHours > 1)
                     {
                         format = "h\\:m\\:s\\.fff";
                     }
-                    else if (anon.Subregion.Start.TotalMinutes > 1)
+                    else if(anon.Subregion.Start.TotalMinutes > 1)
                     {
                         format = "m\\:s\\.fff";
                     }
@@ -581,26 +609,26 @@ namespace butterflow_ui
                 stringBuilder.Append(" ");
             }
 
-            if (this.KeepSubregions) stringBuilder.Append("-k ");
-            if (this.SmoothMotion) stringBuilder.Append("-sm ");
-            if (this.FastPyramid) stringBuilder.Append("--fast-pyr ");
-            if (this.pyramidScale != DEFAULT_PYRAMID_SCALE) stringBuilder.AppendFormat("--pyr-scale {0} ", this.PyramidScale);
-            if (this.levels != DEFAULT_LEVELS) stringBuilder.AppendFormat("--levels {0} ", this.Levels);
-            if (this.windowSize != DEFAULT_WINDOW_SIZE) stringBuilder.AppendFormat("--winsize {0} ", this.WindowSize);
-            if (this.iterations != DEFAULT_ITERATIONS) stringBuilder.AppendFormat("--iters {0} ", this.Iterations);
-            if (this.pixelNeighborhood != DEFAULT_PIXEL_NEIGHBORHOOD) stringBuilder.AppendFormat("--poly-n {0} ", this.PixelNeighborhood);
-            if (this.smoothDerivativeStandardDeviation != DEFAULT_SMOOTH_DERIVATIVE_STANDARD_DEVIATION) stringBuilder.AppendFormat("--poly-s {0} ", this.SmoothDerivativeStandardDeviation);
-            if (this.FlowFilterType != DEFAULT_FLOW_FILTER_TYPE) stringBuilder.AppendFormat("-ff {0} ", this.FlowFilterType);
+            if(this.KeepSubregions) stringBuilder.Append("-k ");
+            if(this.SmoothMotion) stringBuilder.Append("-sm ");
+            if(this.FastPyramid) stringBuilder.Append("--fast-pyr ");
+            if(this.pyramidScale != DEFAULT_PYRAMID_SCALE) stringBuilder.AppendFormat("--pyr-scale {0} ", this.PyramidScale);
+            if(this.levels != DEFAULT_LEVELS) stringBuilder.AppendFormat("--levels {0} ", this.Levels);
+            if(this.windowSize != DEFAULT_WINDOW_SIZE) stringBuilder.AppendFormat("--winsize {0} ", this.WindowSize);
+            if(this.iterations != DEFAULT_ITERATIONS) stringBuilder.AppendFormat("--iters {0} ", this.Iterations);
+            if(this.pixelNeighborhood != DEFAULT_PIXEL_NEIGHBORHOOD) stringBuilder.AppendFormat("--poly-n {0} ", this.PixelNeighborhood);
+            if(this.smoothDerivativeStandardDeviation != DEFAULT_SMOOTH_DERIVATIVE_STANDARD_DEVIATION) stringBuilder.AppendFormat("--poly-s {0} ", this.SmoothDerivativeStandardDeviation);
+            if(this.FlowFilterType != DEFAULT_FLOW_FILTER_TYPE) stringBuilder.AppendFormat("-ff {0} ", this.FlowFilterType);
 
-            if (!string.IsNullOrWhiteSpace(this.VideoOutput))
+            if(!string.IsNullOrWhiteSpace(this.VideoOutput))
             {
                 string videoOutputFile = string.Empty;
 
-                if (this.MultipleFiles)
+                if(this.MultipleFiles)
                 {
                     var format = new StringBuilder(Path.GetFileNameWithoutExtension(this.VideoOutput));
                     format.Append("_{0:");
-                    for (int i = 0; i < this.videoInput.Count().ToString().Length; i++)
+                    for(int i = 0; i < this.videoInput.Count().ToString().Length; i++)
                     {
                         format.Append("0");
                     }
@@ -619,7 +647,7 @@ namespace butterflow_ui
                 stringBuilder.AppendFormat("-o \"{0}\" ", videoOutputFile);
             }
 
-            if (this.VideoInput.Any())
+            if(this.VideoInput.Any())
             {
                 stringBuilder.AppendFormat("\"{0}\"", this.VideoInput.ElementAt(videoInputIndex));
             }
@@ -634,6 +662,6 @@ namespace butterflow_ui
             return ToButterflowArguments();
         }
 
-        #endregion
+        #endregion Methods
     }
-}
+}
\ No newline at end of file
diff --git a/butterflow-ui/OptionsWindow.xaml b/butterflow-ui/OptionsWindow.xaml
index 3f80d03..0f644b5 100644
--- a/butterflow-ui/OptionsWindow.xaml
+++ b/butterflow-ui/OptionsWindow.xaml
@@ -8,19 +8,26 @@
         xmlns:loc="clr-namespace:butterflow_ui.Localization"
         mc:Ignorable="d"
         Title="{x:Static loc:Localization.OptionsWindowTitle}" SizeToContent="WidthAndHeight">
+    <Window.Resources>
+        <butterflow_ui:InverseBoolVisibilityConverter x:Key="InverseBoolVisibilityConverter" />
+    </Window.Resources>
     <DockPanel Margin="32">
         <StackPanel>
             <WrapPanel>
                 <Label Content="{x:Static loc:Localization.LanguageLabel}" />
-                <ComboBox DisplayMemberPath="DisplayName" ItemsSource="{Binding SupportedLanguages, Mode=TwoWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:OptionsWindow}}, UpdateSourceTrigger=PropertyChanged}" SelectedItem="{Binding Source={x:Static settings:Settings.Default}, Path=Language}" />
+                <ComboBox DisplayMemberPath="DisplayName" ItemsSource="{Binding SupportedLanguages, Mode=TwoWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:OptionsWindow}}, UpdateSourceTrigger=PropertyChanged}" SelectedItem="{Binding Source={x:Static settings:Settings.Default}, Path=Language}" VerticalAlignment="Center" />
             </WrapPanel>
             <TextBlock Text="{x:Static loc:Localization.OptionsWindowLanguageChangeNotice}" Foreground="Gray" />
             <WrapPanel>
+                <Label Content="{x:Static loc:Localization.UseDefaultDeviceLabel}" />
+                <CheckBox Name="chkUseDefaultDevice" IsChecked="{Binding Source={x:Static settings:Settings.Default}, Path=UseDefaultDevice}" VerticalAlignment="Center" />
+            </WrapPanel>
+            <WrapPanel Visibility="{Binding Source={x:Static settings:Settings.Default}, Path=UseDefaultDevice, Converter={StaticResource InverseBoolVisibilityConverter}}">
                 <Label Content="{x:Static loc:Localization.DeviceLabel}" />
-                <ComboBox Name="comboDeviceList" DisplayMemberPath="Value" ItemsSource="{Binding ButterflowWrapper.Devices, Mode=OneWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:OptionsWindow}}, UpdateSourceTrigger=PropertyChanged}" SelectedIndex="{Binding Source={x:Static settings:Settings.Default}, Path=Device}" />
+                <ComboBox Name="comboDeviceList" DisplayMemberPath="Value" ItemsSource="{Binding ButterflowWrapper.Devices, Mode=OneWay, RelativeSource={RelativeSource FindAncestor, AncestorType={x:Type butterflow_ui:OptionsWindow}}, UpdateSourceTrigger=PropertyChanged}" SelectedIndex="{Binding Source={x:Static settings:Settings.Default}, Path=Device}" VerticalAlignment="Center" />
             </WrapPanel>
             <Separator Margin="0,10" />
             <Button Name="btnSave" MaxWidth="45" Content="{x:Static loc:Localization.SaveLabel}" Click="btnSave_Click" />
         </StackPanel>
     </DockPanel>
-</Window>
+</Window>
\ No newline at end of file
diff --git a/butterflow-ui/OptionsWindow.xaml.cs b/butterflow-ui/OptionsWindow.xaml.cs
index 616064d..68691e4 100644
--- a/butterflow-ui/OptionsWindow.xaml.cs
+++ b/butterflow-ui/OptionsWindow.xaml.cs
@@ -37,7 +37,7 @@ namespace butterflow_ui
             CultureInfo.CreateSpecificCulture("zh-CN"),
         });
 
-        #endregion
+        #endregion Properties
 
         #region Constructors
 
@@ -49,7 +49,7 @@ namespace butterflow_ui
             InitializeComponent();
         }
 
-        #endregion
+        #endregion Constructors
 
         #region Methods
 
@@ -68,7 +68,7 @@ namespace butterflow_ui
         /// <param name="e">      The ButterflowExitArgs to process. </param>
         private void ButterflowWrapper_ButterflowExited(object sender, ButterflowWrapper.ButterflowExitArgs e)
         {
-            if (Settings.Default.Device >= 0)
+            if(Settings.Default.Device >= 0)
             {
                 this.comboDeviceList.Dispatcher.Invoke(() => this.comboDeviceList.SelectedIndex = Settings.Default.Device);
             }
@@ -78,6 +78,6 @@ namespace butterflow_ui
             }
         }
 
-        #endregion
+        #endregion Methods
     }
-}
+}
\ No newline at end of file
diff --git a/butterflow-ui/Properties/AssemblyInfo.cs b/butterflow-ui/Properties/AssemblyInfo.cs
index 95dd2cc..dbef8a3 100644
--- a/butterflow-ui/Properties/AssemblyInfo.cs
+++ b/butterflow-ui/Properties/AssemblyInfo.cs
@@ -30,7 +30,6 @@ using System.Windows;
 
 //[assembly: NeutralResourcesLanguage("en-US", UltimateResourceFallbackLocation.Satellite)]
 
-
 [assembly: ThemeInfo(
     ResourceDictionaryLocation.None, //where theme specific resource dictionaries are located
                                      //(used if a resource is not found in the page,
@@ -40,7 +39,6 @@ using System.Windows;
                                               // app, or any theme specific resource dictionaries)
 )]
 
-
 // Version information for an assembly consists of the following four values:
 //
 //      Major Version
@@ -51,5 +49,5 @@ using System.Windows;
 // You can specify all the values or you can default the Build and Revision Numbers
 // by using the '*' as shown below:
 // [assembly: AssemblyVersion("1.0.*")]
-[assembly: AssemblyVersion("1.0.5.*")]
-[assembly: AssemblyFileVersion("1.0.0.0")]
+[assembly: AssemblyVersion("1.1.0.*")]
+[assembly: AssemblyFileVersion("1.0.0.0")]
\ No newline at end of file
diff --git a/butterflow-ui/Properties/Settings.Designer.cs b/butterflow-ui/Properties/Settings.Designer.cs
index 066ab23..a7c9735 100644
--- a/butterflow-ui/Properties/Settings.Designer.cs
+++ b/butterflow-ui/Properties/Settings.Designer.cs
@@ -37,7 +37,7 @@ namespace butterflow_ui.Properties {
         
         [global::System.Configuration.UserScopedSettingAttribute()]
         [global::System.Diagnostics.DebuggerNonUserCodeAttribute()]
-        [global::System.Configuration.DefaultSettingValueAttribute("-1")]
+        [global::System.Configuration.DefaultSettingValueAttribute("0")]
         public int Device {
             get {
                 return ((int)(this["Device"]));
@@ -46,5 +46,17 @@ namespace butterflow_ui.Properties {
                 this["Device"] = value;
             }
         }
+        
+        [global::System.Configuration.UserScopedSettingAttribute()]
+        [global::System.Diagnostics.DebuggerNonUserCodeAttribute()]
+        [global::System.Configuration.DefaultSettingValueAttribute("True")]
+        public bool UseDefaultDevice {
+            get {
+                return ((bool)(this["UseDefaultDevice"]));
+            }
+            set {
+                this["UseDefaultDevice"] = value;
+            }
+        }
     }
 }
diff --git a/butterflow-ui/Properties/Settings.settings b/butterflow-ui/Properties/Settings.settings
index f444b12..176b61b 100644
--- a/butterflow-ui/Properties/Settings.settings
+++ b/butterflow-ui/Properties/Settings.settings
@@ -6,7 +6,10 @@
       <Value Profile="(Default)">en-US</Value>
     </Setting>
     <Setting Name="Device" Type="System.Int32" Scope="User">
-      <Value Profile="(Default)">-1</Value>
+      <Value Profile="(Default)">0</Value>
+    </Setting>
+    <Setting Name="UseDefaultDevice" Type="System.Boolean" Scope="User">
+      <Value Profile="(Default)">True</Value>
     </Setting>
   </Settings>
 </SettingsFile>
\ No newline at end of file
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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index 6d95e9a..0bb6c86 100644
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diff --git a/butterflow-ui/ThirdPartyCompiled/butterflow.motion.pyd b/butterflow-ui/ThirdPartyCompiled/butterflow.motion.pyd
deleted file mode 100644
index dcb00a7..0000000
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diff --git a/butterflow-ui/ThirdPartyCompiled/butterflow.ocl.pyd b/butterflow-ui/ThirdPartyCompiled/butterflow.ocl.pyd
deleted file mode 100644
index 8b13786..0000000
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diff --git a/butterflow-ui/ThirdPartyCompiled/butterflow_commands.txt b/butterflow-ui/ThirdPartyCompiled/butterflow_commands.txt
deleted file mode 100644
index 9deadf2..0000000
--- a/butterflow-ui/ThirdPartyCompiled/butterflow_commands.txt
+++ /dev/null
@@ -1,81 +0,0 @@
-usage: butterflow [options] [video]
-
-Required arguments:
-  video                 Specify the input video
-
-General options:
-  -h, --help            Show this help message and exit
-  --version             Show program's version number and exit
-  --cache-dir CACHE_DIR
-                        Specify path to the cache directory
-  -c, --cache           Show cache information and exit
-  --rm-cache            Set to clear the cache and exit
-  -prb, --probe         Show media file information and exit
-  -v, --verbosity       Set to increase output verbosity
-  -q, --quiet           Set to suppress console output
-
-Device options:
-  -d, --show-devices    Show detected OpenCL devices and exit
-  -device DEVICE        Specify the preferred OpenCL device to use as an
-                        integer. Device numbers can be listed with the `-d`
-                        option. The device will be chosen automatically if
-                        nothing is specified.
-  -sw                   Set to force software rendering
-
-Display options:
-  -p, --show-preview    Set to show video preview
-  -e, --embed-info      Set to embed debugging info into the output video
-  -tt {light,dark,stroke}, --text-type {light,dark,stroke}
-                        Specify text type for embedded debugging info,
-                        (default: light)
-  -m, --mark-frames     Set to mark interpolated frames
-
-Video options:
-  -o OUTPUT_PATH, --output-path OUTPUT_PATH
-                        Specify path to the output video
-  -r PLAYBACK_RATE, --playback-rate PLAYBACK_RATE
-                        Specify the playback rate as an integer or a float.
-                        Fractional forms are acceptable, e.g., 24/1.001 is the
-                        same as 23.976. To use a multiple of the source
-                        video's rate, follow a number with `x`, e.g., "2x"
-                        will double the frame rate. The original rate will be
-                        used by default if nothing is specified.
-  -s SUBREGIONS, --subregions SUBREGIONS
-                        Specify rendering subregions in the form:
-                        "a=TIME,b=TIME,TARGET=VALUE" where TARGET is either
-                        `spd`, `dur`, `fps`. Valid TIME syntaxes are [hr:m:s],
-                        [m:s], [s], [s.xxx], or `end`, which signifies to the
-                        end the video. You can specify multiple subregions by
-                        separating them with a colon `:`. A special subregion
-                        format that conveniently describes the entire clip is
-                        available in the form: "full,TARGET=VALUE".
-  -k, --keep-subregions
-                        Set to render subregions that are not explicitly
-                        specified
-  -vs VIDEO_SCALE, --video-scale VIDEO_SCALE
-                        Specify output video size in the form: "WIDTH:HEIGHT"
-                        or by using a factor. To keep the aspect ratio only
-                        specify one component, either width or height, and set
-                        the other component to -1, (default: 1.0)
-  -l, --lossless        Set to use lossless encoding settings
-  -sm, --smooth-motion  Set to tune for smooth motion. This mode yields
-                        artifact-less frames by emphasizing blended frames
-                        over warping pixels.
-
-Muxing options:
-  -audio                Set to add the source audio to the output video
-
-Advanced options:
-  --fast-pyr            Set to use fast pyramids
-  --pyr-scale PYR_SCALE
-                        Specify pyramid scale factor, (default: 0.5)
-  --levels LEVELS       Specify number of pyramid layers, (default: 3)
-  --winsize WINSIZE     Specify averaging window size, (default: 25)
-  --iters ITERS         Specify number of iterations at each pyramid level,
-                        (default: 3)
-  --poly-n {5,7}        Specify size of pixel neighborhood, (default: 5)
-  --poly-s POLY_S       Specify standard deviation to smooth derivatives,
-                        (default: 1.1)
-  -ff {box,gaussian}, --flow-filter {box,gaussian}
-                        Specify which filter to use for optical flow
-                        estimation, (default: box)
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similarity index 81%
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diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/LICENSE.txt b/butterflow-ui/ThirdPartyCompiled/lib/numpy/LICENSE.txt
new file mode 100644
index 0000000..b9731f7
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/LICENSE.txt
@@ -0,0 +1,60 @@
+Copyright (c) 2005-2019, NumPy Developers.
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+    * Redistributions of source code must retain the above copyright
+       notice, this list of conditions and the following disclaimer.
+
+    * Redistributions in binary form must reproduce the above
+       copyright notice, this list of conditions and the following
+       disclaimer in the documentation and/or other materials provided
+       with the distribution.
+
+    * Neither the name of the NumPy Developers nor the names of any
+       contributors may be used to endorse or promote products derived
+       from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+
+The NumPy repository and source distributions bundle several libraries that are
+compatibly licensed.  We list these here.
+
+Name: Numpydoc
+Files: doc/sphinxext/numpydoc/*
+License: 2-clause BSD
+  For details, see doc/sphinxext/LICENSE.txt
+
+Name: scipy-sphinx-theme
+Files: doc/scipy-sphinx-theme/*
+License: 3-clause BSD, PSF and Apache 2.0
+  For details, see doc/scipy-sphinx-theme/LICENSE.txt
+
+Name: lapack-lite
+Files: numpy/linalg/lapack_lite/*
+License: 3-clause BSD
+  For details, see numpy/linalg/lapack_lite/LICENSE.txt
+
+Name: tempita
+Files: tools/npy_tempita/*
+License: BSD derived
+  For details, see tools/npy_tempita/license.txt
+
+Name: dragon4
+Files: numpy/core/src/multiarray/dragon4.c
+License: One of a kind
+  For license text, see numpy/core/src/multiarray/dragon4.c
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diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/__multiarray_api.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/__multiarray_api.h
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--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/__multiarray_api.h
@@ -0,0 +1,1554 @@
+
+#if defined(_MULTIARRAYMODULE) || defined(WITH_CPYCHECKER_STEALS_REFERENCE_TO_ARG_ATTRIBUTE)
+
+typedef struct {
+        PyObject_HEAD
+        npy_bool obval;
+} PyBoolScalarObject;
+
+extern NPY_NO_EXPORT PyTypeObject PyArrayMapIter_Type;
+extern NPY_NO_EXPORT PyTypeObject PyArrayNeighborhoodIter_Type;
+extern NPY_NO_EXPORT PyBoolScalarObject _PyArrayScalar_BoolValues[2];
+
+NPY_NO_EXPORT  unsigned int PyArray_GetNDArrayCVersion \
+       (void);
+extern NPY_NO_EXPORT PyTypeObject PyBigArray_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyArray_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyArrayDescr_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyArrayFlags_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyArrayIter_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyArrayMultiIter_Type;
+
+extern NPY_NO_EXPORT int NPY_NUMUSERTYPES;
+
+extern NPY_NO_EXPORT PyTypeObject PyBoolArrType_Type;
+
+extern NPY_NO_EXPORT PyBoolScalarObject _PyArrayScalar_BoolValues[2];
+
+extern NPY_NO_EXPORT PyTypeObject PyGenericArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyNumberArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyIntegerArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PySignedIntegerArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyUnsignedIntegerArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyInexactArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyFloatingArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyComplexFloatingArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyFlexibleArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyCharacterArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyByteArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyShortArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyIntArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyLongArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyLongLongArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyUByteArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyUShortArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyUIntArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyULongArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyULongLongArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyFloatArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyDoubleArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyLongDoubleArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyCFloatArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyCDoubleArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyCLongDoubleArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyObjectArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyStringArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyUnicodeArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyVoidArrType_Type;
+
+NPY_NO_EXPORT  int PyArray_SetNumericOps \
+       (PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_GetNumericOps \
+       (void);
+NPY_NO_EXPORT  int PyArray_INCREF \
+       (PyArrayObject *);
+NPY_NO_EXPORT  int PyArray_XDECREF \
+       (PyArrayObject *);
+NPY_NO_EXPORT  void PyArray_SetStringFunction \
+       (PyObject *, int);
+NPY_NO_EXPORT  PyArray_Descr * PyArray_DescrFromType \
+       (int);
+NPY_NO_EXPORT  PyObject * PyArray_TypeObjectFromType \
+       (int);
+NPY_NO_EXPORT  char * PyArray_Zero \
+       (PyArrayObject *);
+NPY_NO_EXPORT  char * PyArray_One \
+       (PyArrayObject *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) NPY_GCC_NONNULL(2) PyObject * PyArray_CastToType \
+       (PyArrayObject *, PyArray_Descr *, int);
+NPY_NO_EXPORT  int PyArray_CastTo \
+       (PyArrayObject *, PyArrayObject *);
+NPY_NO_EXPORT  int PyArray_CastAnyTo \
+       (PyArrayObject *, PyArrayObject *);
+NPY_NO_EXPORT  int PyArray_CanCastSafely \
+       (int, int);
+NPY_NO_EXPORT  npy_bool PyArray_CanCastTo \
+       (PyArray_Descr *, PyArray_Descr *);
+NPY_NO_EXPORT  int PyArray_ObjectType \
+       (PyObject *, int);
+NPY_NO_EXPORT  PyArray_Descr * PyArray_DescrFromObject \
+       (PyObject *, PyArray_Descr *);
+NPY_NO_EXPORT  PyArrayObject ** PyArray_ConvertToCommonType \
+       (PyObject *, int *);
+NPY_NO_EXPORT  PyArray_Descr * PyArray_DescrFromScalar \
+       (PyObject *);
+NPY_NO_EXPORT  PyArray_Descr * PyArray_DescrFromTypeObject \
+       (PyObject *);
+NPY_NO_EXPORT  npy_intp PyArray_Size \
+       (PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Scalar \
+       (void *, PyArray_Descr *, PyObject *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) PyObject * PyArray_FromScalar \
+       (PyObject *, PyArray_Descr *);
+NPY_NO_EXPORT  void PyArray_ScalarAsCtype \
+       (PyObject *, void *);
+NPY_NO_EXPORT  int PyArray_CastScalarToCtype \
+       (PyObject *, void *, PyArray_Descr *);
+NPY_NO_EXPORT  int PyArray_CastScalarDirect \
+       (PyObject *, PyArray_Descr *, void *, int);
+NPY_NO_EXPORT  PyObject * PyArray_ScalarFromObject \
+       (PyObject *);
+NPY_NO_EXPORT  PyArray_VectorUnaryFunc * PyArray_GetCastFunc \
+       (PyArray_Descr *, int);
+NPY_NO_EXPORT  PyObject * PyArray_FromDims \
+       (int, int *, int);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(3) PyObject * PyArray_FromDimsAndDataAndDescr \
+       (int, int *, PyArray_Descr *, char *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) PyObject * PyArray_FromAny \
+       (PyObject *, PyArray_Descr *, int, int, int, PyObject *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(1) PyObject * PyArray_EnsureArray \
+       (PyObject *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(1) PyObject * PyArray_EnsureAnyArray \
+       (PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_FromFile \
+       (FILE *, PyArray_Descr *, npy_intp, char *);
+NPY_NO_EXPORT  PyObject * PyArray_FromString \
+       (char *, npy_intp, PyArray_Descr *, npy_intp, char *);
+NPY_NO_EXPORT  PyObject * PyArray_FromBuffer \
+       (PyObject *, PyArray_Descr *, npy_intp, npy_intp);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) PyObject * PyArray_FromIter \
+       (PyObject *, PyArray_Descr *, npy_intp);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(1) PyObject * PyArray_Return \
+       (PyArrayObject *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) NPY_GCC_NONNULL(2) PyObject * PyArray_GetField \
+       (PyArrayObject *, PyArray_Descr *, int);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) NPY_GCC_NONNULL(2) int PyArray_SetField \
+       (PyArrayObject *, PyArray_Descr *, int, PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Byteswap \
+       (PyArrayObject *, npy_bool);
+NPY_NO_EXPORT  PyObject * PyArray_Resize \
+       (PyArrayObject *, PyArray_Dims *, int, NPY_ORDER);
+NPY_NO_EXPORT  int PyArray_MoveInto \
+       (PyArrayObject *, PyArrayObject *);
+NPY_NO_EXPORT  int PyArray_CopyInto \
+       (PyArrayObject *, PyArrayObject *);
+NPY_NO_EXPORT  int PyArray_CopyAnyInto \
+       (PyArrayObject *, PyArrayObject *);
+NPY_NO_EXPORT  int PyArray_CopyObject \
+       (PyArrayObject *, PyObject *);
+NPY_NO_EXPORT NPY_GCC_NONNULL(1) PyObject * PyArray_NewCopy \
+       (PyArrayObject *, NPY_ORDER);
+NPY_NO_EXPORT  PyObject * PyArray_ToList \
+       (PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_ToString \
+       (PyArrayObject *, NPY_ORDER);
+NPY_NO_EXPORT  int PyArray_ToFile \
+       (PyArrayObject *, FILE *, char *, char *);
+NPY_NO_EXPORT  int PyArray_Dump \
+       (PyObject *, PyObject *, int);
+NPY_NO_EXPORT  PyObject * PyArray_Dumps \
+       (PyObject *, int);
+NPY_NO_EXPORT  int PyArray_ValidType \
+       (int);
+NPY_NO_EXPORT  void PyArray_UpdateFlags \
+       (PyArrayObject *, int);
+NPY_NO_EXPORT NPY_GCC_NONNULL(1) PyObject * PyArray_New \
+       (PyTypeObject *, int, npy_intp *, int, npy_intp *, void *, int, int, PyObject *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) NPY_GCC_NONNULL(1) NPY_GCC_NONNULL(2) PyObject * PyArray_NewFromDescr \
+       (PyTypeObject *, PyArray_Descr *, int, npy_intp *, npy_intp *, void *, int, PyObject *);
+NPY_NO_EXPORT  PyArray_Descr * PyArray_DescrNew \
+       (PyArray_Descr *);
+NPY_NO_EXPORT  PyArray_Descr * PyArray_DescrNewFromType \
+       (int);
+NPY_NO_EXPORT  double PyArray_GetPriority \
+       (PyObject *, double);
+NPY_NO_EXPORT  PyObject * PyArray_IterNew \
+       (PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_MultiIterNew \
+       (int, ...);
+NPY_NO_EXPORT  int PyArray_PyIntAsInt \
+       (PyObject *);
+NPY_NO_EXPORT  npy_intp PyArray_PyIntAsIntp \
+       (PyObject *);
+NPY_NO_EXPORT  int PyArray_Broadcast \
+       (PyArrayMultiIterObject *);
+NPY_NO_EXPORT  void PyArray_FillObjectArray \
+       (PyArrayObject *, PyObject *);
+NPY_NO_EXPORT  int PyArray_FillWithScalar \
+       (PyArrayObject *, PyObject *);
+NPY_NO_EXPORT  npy_bool PyArray_CheckStrides \
+       (int, int, npy_intp, npy_intp, npy_intp *, npy_intp *);
+NPY_NO_EXPORT  PyArray_Descr * PyArray_DescrNewByteorder \
+       (PyArray_Descr *, char);
+NPY_NO_EXPORT  PyObject * PyArray_IterAllButAxis \
+       (PyObject *, int *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) PyObject * PyArray_CheckFromAny \
+       (PyObject *, PyArray_Descr *, int, int, int, PyObject *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) PyObject * PyArray_FromArray \
+       (PyArrayObject *, PyArray_Descr *, int);
+NPY_NO_EXPORT  PyObject * PyArray_FromInterface \
+       (PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_FromStructInterface \
+       (PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_FromArrayAttr \
+       (PyObject *, PyArray_Descr *, PyObject *);
+NPY_NO_EXPORT  NPY_SCALARKIND PyArray_ScalarKind \
+       (int, PyArrayObject **);
+NPY_NO_EXPORT  int PyArray_CanCoerceScalar \
+       (int, int, NPY_SCALARKIND);
+NPY_NO_EXPORT  PyObject * PyArray_NewFlagsObject \
+       (PyObject *);
+NPY_NO_EXPORT  npy_bool PyArray_CanCastScalar \
+       (PyTypeObject *, PyTypeObject *);
+NPY_NO_EXPORT  int PyArray_CompareUCS4 \
+       (npy_ucs4 *, npy_ucs4 *, size_t);
+NPY_NO_EXPORT  int PyArray_RemoveSmallest \
+       (PyArrayMultiIterObject *);
+NPY_NO_EXPORT  int PyArray_ElementStrides \
+       (PyObject *);
+NPY_NO_EXPORT  void PyArray_Item_INCREF \
+       (char *, PyArray_Descr *);
+NPY_NO_EXPORT  void PyArray_Item_XDECREF \
+       (char *, PyArray_Descr *);
+NPY_NO_EXPORT  PyObject * PyArray_FieldNames \
+       (PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Transpose \
+       (PyArrayObject *, PyArray_Dims *);
+NPY_NO_EXPORT  PyObject * PyArray_TakeFrom \
+       (PyArrayObject *, PyObject *, int, PyArrayObject *, NPY_CLIPMODE);
+NPY_NO_EXPORT  PyObject * PyArray_PutTo \
+       (PyArrayObject *, PyObject*, PyObject *, NPY_CLIPMODE);
+NPY_NO_EXPORT  PyObject * PyArray_PutMask \
+       (PyArrayObject *, PyObject*, PyObject*);
+NPY_NO_EXPORT  PyObject * PyArray_Repeat \
+       (PyArrayObject *, PyObject *, int);
+NPY_NO_EXPORT  PyObject * PyArray_Choose \
+       (PyArrayObject *, PyObject *, PyArrayObject *, NPY_CLIPMODE);
+NPY_NO_EXPORT  int PyArray_Sort \
+       (PyArrayObject *, int, NPY_SORTKIND);
+NPY_NO_EXPORT  PyObject * PyArray_ArgSort \
+       (PyArrayObject *, int, NPY_SORTKIND);
+NPY_NO_EXPORT  PyObject * PyArray_SearchSorted \
+       (PyArrayObject *, PyObject *, NPY_SEARCHSIDE, PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_ArgMax \
+       (PyArrayObject *, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_ArgMin \
+       (PyArrayObject *, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Reshape \
+       (PyArrayObject *, PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Newshape \
+       (PyArrayObject *, PyArray_Dims *, NPY_ORDER);
+NPY_NO_EXPORT  PyObject * PyArray_Squeeze \
+       (PyArrayObject *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) PyObject * PyArray_View \
+       (PyArrayObject *, PyArray_Descr *, PyTypeObject *);
+NPY_NO_EXPORT  PyObject * PyArray_SwapAxes \
+       (PyArrayObject *, int, int);
+NPY_NO_EXPORT  PyObject * PyArray_Max \
+       (PyArrayObject *, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Min \
+       (PyArrayObject *, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Ptp \
+       (PyArrayObject *, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Mean \
+       (PyArrayObject *, int, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Trace \
+       (PyArrayObject *, int, int, int, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Diagonal \
+       (PyArrayObject *, int, int, int);
+NPY_NO_EXPORT  PyObject * PyArray_Clip \
+       (PyArrayObject *, PyObject *, PyObject *, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Conjugate \
+       (PyArrayObject *, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Nonzero \
+       (PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Std \
+       (PyArrayObject *, int, int, PyArrayObject *, int);
+NPY_NO_EXPORT  PyObject * PyArray_Sum \
+       (PyArrayObject *, int, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_CumSum \
+       (PyArrayObject *, int, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Prod \
+       (PyArrayObject *, int, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_CumProd \
+       (PyArrayObject *, int, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_All \
+       (PyArrayObject *, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Any \
+       (PyArrayObject *, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Compress \
+       (PyArrayObject *, PyObject *, int, PyArrayObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Flatten \
+       (PyArrayObject *, NPY_ORDER);
+NPY_NO_EXPORT  PyObject * PyArray_Ravel \
+       (PyArrayObject *, NPY_ORDER);
+NPY_NO_EXPORT  npy_intp PyArray_MultiplyList \
+       (npy_intp *, int);
+NPY_NO_EXPORT  int PyArray_MultiplyIntList \
+       (int *, int);
+NPY_NO_EXPORT  void * PyArray_GetPtr \
+       (PyArrayObject *, npy_intp*);
+NPY_NO_EXPORT  int PyArray_CompareLists \
+       (npy_intp *, npy_intp *, int);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(5) int PyArray_AsCArray \
+       (PyObject **, void *, npy_intp *, int, PyArray_Descr*);
+NPY_NO_EXPORT  int PyArray_As1D \
+       (PyObject **, char **, int *, int);
+NPY_NO_EXPORT  int PyArray_As2D \
+       (PyObject **, char ***, int *, int *, int);
+NPY_NO_EXPORT  int PyArray_Free \
+       (PyObject *, void *);
+NPY_NO_EXPORT  int PyArray_Converter \
+       (PyObject *, PyObject **);
+NPY_NO_EXPORT  int PyArray_IntpFromSequence \
+       (PyObject *, npy_intp *, int);
+NPY_NO_EXPORT  PyObject * PyArray_Concatenate \
+       (PyObject *, int);
+NPY_NO_EXPORT  PyObject * PyArray_InnerProduct \
+       (PyObject *, PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_MatrixProduct \
+       (PyObject *, PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_CopyAndTranspose \
+       (PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Correlate \
+       (PyObject *, PyObject *, int);
+NPY_NO_EXPORT  int PyArray_TypestrConvert \
+       (int, int);
+NPY_NO_EXPORT  int PyArray_DescrConverter \
+       (PyObject *, PyArray_Descr **);
+NPY_NO_EXPORT  int PyArray_DescrConverter2 \
+       (PyObject *, PyArray_Descr **);
+NPY_NO_EXPORT  int PyArray_IntpConverter \
+       (PyObject *, PyArray_Dims *);
+NPY_NO_EXPORT  int PyArray_BufferConverter \
+       (PyObject *, PyArray_Chunk *);
+NPY_NO_EXPORT  int PyArray_AxisConverter \
+       (PyObject *, int *);
+NPY_NO_EXPORT  int PyArray_BoolConverter \
+       (PyObject *, npy_bool *);
+NPY_NO_EXPORT  int PyArray_ByteorderConverter \
+       (PyObject *, char *);
+NPY_NO_EXPORT  int PyArray_OrderConverter \
+       (PyObject *, NPY_ORDER *);
+NPY_NO_EXPORT  unsigned char PyArray_EquivTypes \
+       (PyArray_Descr *, PyArray_Descr *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(3) PyObject * PyArray_Zeros \
+       (int, npy_intp *, PyArray_Descr *, int);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(3) PyObject * PyArray_Empty \
+       (int, npy_intp *, PyArray_Descr *, int);
+NPY_NO_EXPORT  PyObject * PyArray_Where \
+       (PyObject *, PyObject *, PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_Arange \
+       (double, double, double, int);
+NPY_NO_EXPORT  PyObject * PyArray_ArangeObj \
+       (PyObject *, PyObject *, PyObject *, PyArray_Descr *);
+NPY_NO_EXPORT  int PyArray_SortkindConverter \
+       (PyObject *, NPY_SORTKIND *);
+NPY_NO_EXPORT  PyObject * PyArray_LexSort \
+       (PyObject *, int);
+NPY_NO_EXPORT  PyObject * PyArray_Round \
+       (PyArrayObject *, int, PyArrayObject *);
+NPY_NO_EXPORT  unsigned char PyArray_EquivTypenums \
+       (int, int);
+NPY_NO_EXPORT  int PyArray_RegisterDataType \
+       (PyArray_Descr *);
+NPY_NO_EXPORT  int PyArray_RegisterCastFunc \
+       (PyArray_Descr *, int, PyArray_VectorUnaryFunc *);
+NPY_NO_EXPORT  int PyArray_RegisterCanCast \
+       (PyArray_Descr *, int, NPY_SCALARKIND);
+NPY_NO_EXPORT  void PyArray_InitArrFuncs \
+       (PyArray_ArrFuncs *);
+NPY_NO_EXPORT  PyObject * PyArray_IntTupleFromIntp \
+       (int, npy_intp *);
+NPY_NO_EXPORT  int PyArray_TypeNumFromName \
+       (char *);
+NPY_NO_EXPORT  int PyArray_ClipmodeConverter \
+       (PyObject *, NPY_CLIPMODE *);
+NPY_NO_EXPORT  int PyArray_OutputConverter \
+       (PyObject *, PyArrayObject **);
+NPY_NO_EXPORT  PyObject * PyArray_BroadcastToShape \
+       (PyObject *, npy_intp *, int);
+NPY_NO_EXPORT  void _PyArray_SigintHandler \
+       (int);
+NPY_NO_EXPORT  void* _PyArray_GetSigintBuf \
+       (void);
+NPY_NO_EXPORT  int PyArray_DescrAlignConverter \
+       (PyObject *, PyArray_Descr **);
+NPY_NO_EXPORT  int PyArray_DescrAlignConverter2 \
+       (PyObject *, PyArray_Descr **);
+NPY_NO_EXPORT  int PyArray_SearchsideConverter \
+       (PyObject *, void *);
+NPY_NO_EXPORT  PyObject * PyArray_CheckAxis \
+       (PyArrayObject *, int *, int);
+NPY_NO_EXPORT  npy_intp PyArray_OverflowMultiplyList \
+       (npy_intp *, int);
+NPY_NO_EXPORT  int PyArray_CompareString \
+       (char *, char *, size_t);
+NPY_NO_EXPORT  PyObject * PyArray_MultiIterFromObjects \
+       (PyObject **, int, int, ...);
+NPY_NO_EXPORT  int PyArray_GetEndianness \
+       (void);
+NPY_NO_EXPORT  unsigned int PyArray_GetNDArrayCFeatureVersion \
+       (void);
+NPY_NO_EXPORT  PyObject * PyArray_Correlate2 \
+       (PyObject *, PyObject *, int);
+NPY_NO_EXPORT  PyObject* PyArray_NeighborhoodIterNew \
+       (PyArrayIterObject *, npy_intp *, int, PyArrayObject*);
+extern NPY_NO_EXPORT PyTypeObject PyTimeIntegerArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyDatetimeArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyTimedeltaArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyHalfArrType_Type;
+
+extern NPY_NO_EXPORT PyTypeObject NpyIter_Type;
+
+NPY_NO_EXPORT  void PyArray_SetDatetimeParseFunction \
+       (PyObject *);
+NPY_NO_EXPORT  void PyArray_DatetimeToDatetimeStruct \
+       (npy_datetime, NPY_DATETIMEUNIT, npy_datetimestruct *);
+NPY_NO_EXPORT  void PyArray_TimedeltaToTimedeltaStruct \
+       (npy_timedelta, NPY_DATETIMEUNIT, npy_timedeltastruct *);
+NPY_NO_EXPORT  npy_datetime PyArray_DatetimeStructToDatetime \
+       (NPY_DATETIMEUNIT, npy_datetimestruct *);
+NPY_NO_EXPORT  npy_datetime PyArray_TimedeltaStructToTimedelta \
+       (NPY_DATETIMEUNIT, npy_timedeltastruct *);
+NPY_NO_EXPORT  NpyIter * NpyIter_New \
+       (PyArrayObject *, npy_uint32, NPY_ORDER, NPY_CASTING, PyArray_Descr*);
+NPY_NO_EXPORT  NpyIter * NpyIter_MultiNew \
+       (int, PyArrayObject **, npy_uint32, NPY_ORDER, NPY_CASTING, npy_uint32 *, PyArray_Descr **);
+NPY_NO_EXPORT  NpyIter * NpyIter_AdvancedNew \
+       (int, PyArrayObject **, npy_uint32, NPY_ORDER, NPY_CASTING, npy_uint32 *, PyArray_Descr **, int, int **, npy_intp *, npy_intp);
+NPY_NO_EXPORT  NpyIter * NpyIter_Copy \
+       (NpyIter *);
+NPY_NO_EXPORT  int NpyIter_Deallocate \
+       (NpyIter *);
+NPY_NO_EXPORT  npy_bool NpyIter_HasDelayedBufAlloc \
+       (NpyIter *);
+NPY_NO_EXPORT  npy_bool NpyIter_HasExternalLoop \
+       (NpyIter *);
+NPY_NO_EXPORT  int NpyIter_EnableExternalLoop \
+       (NpyIter *);
+NPY_NO_EXPORT  npy_intp * NpyIter_GetInnerStrideArray \
+       (NpyIter *);
+NPY_NO_EXPORT  npy_intp * NpyIter_GetInnerLoopSizePtr \
+       (NpyIter *);
+NPY_NO_EXPORT  int NpyIter_Reset \
+       (NpyIter *, char **);
+NPY_NO_EXPORT  int NpyIter_ResetBasePointers \
+       (NpyIter *, char **, char **);
+NPY_NO_EXPORT  int NpyIter_ResetToIterIndexRange \
+       (NpyIter *, npy_intp, npy_intp, char **);
+NPY_NO_EXPORT  int NpyIter_GetNDim \
+       (NpyIter *);
+NPY_NO_EXPORT  int NpyIter_GetNOp \
+       (NpyIter *);
+NPY_NO_EXPORT  NpyIter_IterNextFunc * NpyIter_GetIterNext \
+       (NpyIter *, char **);
+NPY_NO_EXPORT  npy_intp NpyIter_GetIterSize \
+       (NpyIter *);
+NPY_NO_EXPORT  void NpyIter_GetIterIndexRange \
+       (NpyIter *, npy_intp *, npy_intp *);
+NPY_NO_EXPORT  npy_intp NpyIter_GetIterIndex \
+       (NpyIter *);
+NPY_NO_EXPORT  int NpyIter_GotoIterIndex \
+       (NpyIter *, npy_intp);
+NPY_NO_EXPORT  npy_bool NpyIter_HasMultiIndex \
+       (NpyIter *);
+NPY_NO_EXPORT  int NpyIter_GetShape \
+       (NpyIter *, npy_intp *);
+NPY_NO_EXPORT  NpyIter_GetMultiIndexFunc * NpyIter_GetGetMultiIndex \
+       (NpyIter *, char **);
+NPY_NO_EXPORT  int NpyIter_GotoMultiIndex \
+       (NpyIter *, npy_intp *);
+NPY_NO_EXPORT  int NpyIter_RemoveMultiIndex \
+       (NpyIter *);
+NPY_NO_EXPORT  npy_bool NpyIter_HasIndex \
+       (NpyIter *);
+NPY_NO_EXPORT  npy_bool NpyIter_IsBuffered \
+       (NpyIter *);
+NPY_NO_EXPORT  npy_bool NpyIter_IsGrowInner \
+       (NpyIter *);
+NPY_NO_EXPORT  npy_intp NpyIter_GetBufferSize \
+       (NpyIter *);
+NPY_NO_EXPORT  npy_intp * NpyIter_GetIndexPtr \
+       (NpyIter *);
+NPY_NO_EXPORT  int NpyIter_GotoIndex \
+       (NpyIter *, npy_intp);
+NPY_NO_EXPORT  char ** NpyIter_GetDataPtrArray \
+       (NpyIter *);
+NPY_NO_EXPORT  PyArray_Descr ** NpyIter_GetDescrArray \
+       (NpyIter *);
+NPY_NO_EXPORT  PyArrayObject ** NpyIter_GetOperandArray \
+       (NpyIter *);
+NPY_NO_EXPORT  PyArrayObject * NpyIter_GetIterView \
+       (NpyIter *, npy_intp);
+NPY_NO_EXPORT  void NpyIter_GetReadFlags \
+       (NpyIter *, char *);
+NPY_NO_EXPORT  void NpyIter_GetWriteFlags \
+       (NpyIter *, char *);
+NPY_NO_EXPORT  void NpyIter_DebugPrint \
+       (NpyIter *);
+NPY_NO_EXPORT  npy_bool NpyIter_IterationNeedsAPI \
+       (NpyIter *);
+NPY_NO_EXPORT  void NpyIter_GetInnerFixedStrideArray \
+       (NpyIter *, npy_intp *);
+NPY_NO_EXPORT  int NpyIter_RemoveAxis \
+       (NpyIter *, int);
+NPY_NO_EXPORT  npy_intp * NpyIter_GetAxisStrideArray \
+       (NpyIter *, int);
+NPY_NO_EXPORT  npy_bool NpyIter_RequiresBuffering \
+       (NpyIter *);
+NPY_NO_EXPORT  char ** NpyIter_GetInitialDataPtrArray \
+       (NpyIter *);
+NPY_NO_EXPORT  int NpyIter_CreateCompatibleStrides \
+       (NpyIter *, npy_intp, npy_intp *);
+NPY_NO_EXPORT  int PyArray_CastingConverter \
+       (PyObject *, NPY_CASTING *);
+NPY_NO_EXPORT  npy_intp PyArray_CountNonzero \
+       (PyArrayObject *);
+NPY_NO_EXPORT  PyArray_Descr * PyArray_PromoteTypes \
+       (PyArray_Descr *, PyArray_Descr *);
+NPY_NO_EXPORT  PyArray_Descr * PyArray_MinScalarType \
+       (PyArrayObject *);
+NPY_NO_EXPORT  PyArray_Descr * PyArray_ResultType \
+       (npy_intp, PyArrayObject **, npy_intp, PyArray_Descr **);
+NPY_NO_EXPORT  npy_bool PyArray_CanCastArrayTo \
+       (PyArrayObject *, PyArray_Descr *, NPY_CASTING);
+NPY_NO_EXPORT  npy_bool PyArray_CanCastTypeTo \
+       (PyArray_Descr *, PyArray_Descr *, NPY_CASTING);
+NPY_NO_EXPORT  PyArrayObject * PyArray_EinsteinSum \
+       (char *, npy_intp, PyArrayObject **, PyArray_Descr *, NPY_ORDER, NPY_CASTING, PyArrayObject *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(3) NPY_GCC_NONNULL(1) PyObject * PyArray_NewLikeArray \
+       (PyArrayObject *, NPY_ORDER, PyArray_Descr *, int);
+NPY_NO_EXPORT  int PyArray_GetArrayParamsFromObject \
+       (PyObject *, PyArray_Descr *, npy_bool, PyArray_Descr **, int *, npy_intp *, PyArrayObject **, PyObject *);
+NPY_NO_EXPORT  int PyArray_ConvertClipmodeSequence \
+       (PyObject *, NPY_CLIPMODE *, int);
+NPY_NO_EXPORT  PyObject * PyArray_MatrixProduct2 \
+       (PyObject *, PyObject *, PyArrayObject*);
+NPY_NO_EXPORT  npy_bool NpyIter_IsFirstVisit \
+       (NpyIter *, int);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) int PyArray_SetBaseObject \
+       (PyArrayObject *, PyObject *);
+NPY_NO_EXPORT  void PyArray_CreateSortedStridePerm \
+       (int, npy_intp *, npy_stride_sort_item *);
+NPY_NO_EXPORT  void PyArray_RemoveAxesInPlace \
+       (PyArrayObject *, npy_bool *);
+NPY_NO_EXPORT  void PyArray_DebugPrint \
+       (PyArrayObject *);
+NPY_NO_EXPORT  int PyArray_FailUnlessWriteable \
+       (PyArrayObject *, const char *);
+NPY_NO_EXPORT NPY_STEALS_REF_TO_ARG(2) int PyArray_SetUpdateIfCopyBase \
+       (PyArrayObject *, PyArrayObject *);
+NPY_NO_EXPORT  void * PyDataMem_NEW \
+       (size_t);
+NPY_NO_EXPORT  void PyDataMem_FREE \
+       (void *);
+NPY_NO_EXPORT  void * PyDataMem_RENEW \
+       (void *, size_t);
+NPY_NO_EXPORT  PyDataMem_EventHookFunc * PyDataMem_SetEventHook \
+       (PyDataMem_EventHookFunc *, void *, void **);
+extern NPY_NO_EXPORT NPY_CASTING NPY_DEFAULT_ASSIGN_CASTING;
+
+NPY_NO_EXPORT  void PyArray_MapIterSwapAxes \
+       (PyArrayMapIterObject *, PyArrayObject **, int);
+NPY_NO_EXPORT  PyObject * PyArray_MapIterArray \
+       (PyArrayObject *, PyObject *);
+NPY_NO_EXPORT  void PyArray_MapIterNext \
+       (PyArrayMapIterObject *);
+NPY_NO_EXPORT  int PyArray_Partition \
+       (PyArrayObject *, PyArrayObject *, int, NPY_SELECTKIND);
+NPY_NO_EXPORT  PyObject * PyArray_ArgPartition \
+       (PyArrayObject *, PyArrayObject *, int, NPY_SELECTKIND);
+NPY_NO_EXPORT  int PyArray_SelectkindConverter \
+       (PyObject *, NPY_SELECTKIND *);
+NPY_NO_EXPORT  void * PyDataMem_NEW_ZEROED \
+       (size_t, size_t);
+NPY_NO_EXPORT NPY_GCC_NONNULL(1) int PyArray_CheckAnyScalarExact \
+       (PyObject *);
+NPY_NO_EXPORT  PyObject * PyArray_MapIterArrayCopyIfOverlap \
+       (PyArrayObject *, PyObject *, int, PyArrayObject *);
+NPY_NO_EXPORT  int PyArray_ResolveWritebackIfCopy \
+       (PyArrayObject *);
+NPY_NO_EXPORT  int PyArray_SetWritebackIfCopyBase \
+       (PyArrayObject *, PyArrayObject *);
+
+#else
+
+#if defined(PY_ARRAY_UNIQUE_SYMBOL)
+#define PyArray_API PY_ARRAY_UNIQUE_SYMBOL
+#endif
+
+#if defined(NO_IMPORT) || defined(NO_IMPORT_ARRAY)
+extern void **PyArray_API;
+#else
+#if defined(PY_ARRAY_UNIQUE_SYMBOL)
+void **PyArray_API;
+#else
+static void **PyArray_API=NULL;
+#endif
+#endif
+
+#define PyArray_GetNDArrayCVersion \
+        (*(unsigned int (*)(void)) \
+         PyArray_API[0])
+#define PyBigArray_Type (*(PyTypeObject *)PyArray_API[1])
+#define PyArray_Type (*(PyTypeObject *)PyArray_API[2])
+#define PyArrayDescr_Type (*(PyTypeObject *)PyArray_API[3])
+#define PyArrayFlags_Type (*(PyTypeObject *)PyArray_API[4])
+#define PyArrayIter_Type (*(PyTypeObject *)PyArray_API[5])
+#define PyArrayMultiIter_Type (*(PyTypeObject *)PyArray_API[6])
+#define NPY_NUMUSERTYPES (*(int *)PyArray_API[7])
+#define PyBoolArrType_Type (*(PyTypeObject *)PyArray_API[8])
+#define _PyArrayScalar_BoolValues ((PyBoolScalarObject *)PyArray_API[9])
+#define PyGenericArrType_Type (*(PyTypeObject *)PyArray_API[10])
+#define PyNumberArrType_Type (*(PyTypeObject *)PyArray_API[11])
+#define PyIntegerArrType_Type (*(PyTypeObject *)PyArray_API[12])
+#define PySignedIntegerArrType_Type (*(PyTypeObject *)PyArray_API[13])
+#define PyUnsignedIntegerArrType_Type (*(PyTypeObject *)PyArray_API[14])
+#define PyInexactArrType_Type (*(PyTypeObject *)PyArray_API[15])
+#define PyFloatingArrType_Type (*(PyTypeObject *)PyArray_API[16])
+#define PyComplexFloatingArrType_Type (*(PyTypeObject *)PyArray_API[17])
+#define PyFlexibleArrType_Type (*(PyTypeObject *)PyArray_API[18])
+#define PyCharacterArrType_Type (*(PyTypeObject *)PyArray_API[19])
+#define PyByteArrType_Type (*(PyTypeObject *)PyArray_API[20])
+#define PyShortArrType_Type (*(PyTypeObject *)PyArray_API[21])
+#define PyIntArrType_Type (*(PyTypeObject *)PyArray_API[22])
+#define PyLongArrType_Type (*(PyTypeObject *)PyArray_API[23])
+#define PyLongLongArrType_Type (*(PyTypeObject *)PyArray_API[24])
+#define PyUByteArrType_Type (*(PyTypeObject *)PyArray_API[25])
+#define PyUShortArrType_Type (*(PyTypeObject *)PyArray_API[26])
+#define PyUIntArrType_Type (*(PyTypeObject *)PyArray_API[27])
+#define PyULongArrType_Type (*(PyTypeObject *)PyArray_API[28])
+#define PyULongLongArrType_Type (*(PyTypeObject *)PyArray_API[29])
+#define PyFloatArrType_Type (*(PyTypeObject *)PyArray_API[30])
+#define PyDoubleArrType_Type (*(PyTypeObject *)PyArray_API[31])
+#define PyLongDoubleArrType_Type (*(PyTypeObject *)PyArray_API[32])
+#define PyCFloatArrType_Type (*(PyTypeObject *)PyArray_API[33])
+#define PyCDoubleArrType_Type (*(PyTypeObject *)PyArray_API[34])
+#define PyCLongDoubleArrType_Type (*(PyTypeObject *)PyArray_API[35])
+#define PyObjectArrType_Type (*(PyTypeObject *)PyArray_API[36])
+#define PyStringArrType_Type (*(PyTypeObject *)PyArray_API[37])
+#define PyUnicodeArrType_Type (*(PyTypeObject *)PyArray_API[38])
+#define PyVoidArrType_Type (*(PyTypeObject *)PyArray_API[39])
+#define PyArray_SetNumericOps \
+        (*(int (*)(PyObject *)) \
+         PyArray_API[40])
+#define PyArray_GetNumericOps \
+        (*(PyObject * (*)(void)) \
+         PyArray_API[41])
+#define PyArray_INCREF \
+        (*(int (*)(PyArrayObject *)) \
+         PyArray_API[42])
+#define PyArray_XDECREF \
+        (*(int (*)(PyArrayObject *)) \
+         PyArray_API[43])
+#define PyArray_SetStringFunction \
+        (*(void (*)(PyObject *, int)) \
+         PyArray_API[44])
+#define PyArray_DescrFromType \
+        (*(PyArray_Descr * (*)(int)) \
+         PyArray_API[45])
+#define PyArray_TypeObjectFromType \
+        (*(PyObject * (*)(int)) \
+         PyArray_API[46])
+#define PyArray_Zero \
+        (*(char * (*)(PyArrayObject *)) \
+         PyArray_API[47])
+#define PyArray_One \
+        (*(char * (*)(PyArrayObject *)) \
+         PyArray_API[48])
+#define PyArray_CastToType \
+        (*(PyObject * (*)(PyArrayObject *, PyArray_Descr *, int)) \
+         PyArray_API[49])
+#define PyArray_CastTo \
+        (*(int (*)(PyArrayObject *, PyArrayObject *)) \
+         PyArray_API[50])
+#define PyArray_CastAnyTo \
+        (*(int (*)(PyArrayObject *, PyArrayObject *)) \
+         PyArray_API[51])
+#define PyArray_CanCastSafely \
+        (*(int (*)(int, int)) \
+         PyArray_API[52])
+#define PyArray_CanCastTo \
+        (*(npy_bool (*)(PyArray_Descr *, PyArray_Descr *)) \
+         PyArray_API[53])
+#define PyArray_ObjectType \
+        (*(int (*)(PyObject *, int)) \
+         PyArray_API[54])
+#define PyArray_DescrFromObject \
+        (*(PyArray_Descr * (*)(PyObject *, PyArray_Descr *)) \
+         PyArray_API[55])
+#define PyArray_ConvertToCommonType \
+        (*(PyArrayObject ** (*)(PyObject *, int *)) \
+         PyArray_API[56])
+#define PyArray_DescrFromScalar \
+        (*(PyArray_Descr * (*)(PyObject *)) \
+         PyArray_API[57])
+#define PyArray_DescrFromTypeObject \
+        (*(PyArray_Descr * (*)(PyObject *)) \
+         PyArray_API[58])
+#define PyArray_Size \
+        (*(npy_intp (*)(PyObject *)) \
+         PyArray_API[59])
+#define PyArray_Scalar \
+        (*(PyObject * (*)(void *, PyArray_Descr *, PyObject *)) \
+         PyArray_API[60])
+#define PyArray_FromScalar \
+        (*(PyObject * (*)(PyObject *, PyArray_Descr *)) \
+         PyArray_API[61])
+#define PyArray_ScalarAsCtype \
+        (*(void (*)(PyObject *, void *)) \
+         PyArray_API[62])
+#define PyArray_CastScalarToCtype \
+        (*(int (*)(PyObject *, void *, PyArray_Descr *)) \
+         PyArray_API[63])
+#define PyArray_CastScalarDirect \
+        (*(int (*)(PyObject *, PyArray_Descr *, void *, int)) \
+         PyArray_API[64])
+#define PyArray_ScalarFromObject \
+        (*(PyObject * (*)(PyObject *)) \
+         PyArray_API[65])
+#define PyArray_GetCastFunc \
+        (*(PyArray_VectorUnaryFunc * (*)(PyArray_Descr *, int)) \
+         PyArray_API[66])
+#define PyArray_FromDims \
+        (*(PyObject * (*)(int, int *, int)) \
+         PyArray_API[67])
+#define PyArray_FromDimsAndDataAndDescr \
+        (*(PyObject * (*)(int, int *, PyArray_Descr *, char *)) \
+         PyArray_API[68])
+#define PyArray_FromAny \
+        (*(PyObject * (*)(PyObject *, PyArray_Descr *, int, int, int, PyObject *)) \
+         PyArray_API[69])
+#define PyArray_EnsureArray \
+        (*(PyObject * (*)(PyObject *)) \
+         PyArray_API[70])
+#define PyArray_EnsureAnyArray \
+        (*(PyObject * (*)(PyObject *)) \
+         PyArray_API[71])
+#define PyArray_FromFile \
+        (*(PyObject * (*)(FILE *, PyArray_Descr *, npy_intp, char *)) \
+         PyArray_API[72])
+#define PyArray_FromString \
+        (*(PyObject * (*)(char *, npy_intp, PyArray_Descr *, npy_intp, char *)) \
+         PyArray_API[73])
+#define PyArray_FromBuffer \
+        (*(PyObject * (*)(PyObject *, PyArray_Descr *, npy_intp, npy_intp)) \
+         PyArray_API[74])
+#define PyArray_FromIter \
+        (*(PyObject * (*)(PyObject *, PyArray_Descr *, npy_intp)) \
+         PyArray_API[75])
+#define PyArray_Return \
+        (*(PyObject * (*)(PyArrayObject *)) \
+         PyArray_API[76])
+#define PyArray_GetField \
+        (*(PyObject * (*)(PyArrayObject *, PyArray_Descr *, int)) \
+         PyArray_API[77])
+#define PyArray_SetField \
+        (*(int (*)(PyArrayObject *, PyArray_Descr *, int, PyObject *)) \
+         PyArray_API[78])
+#define PyArray_Byteswap \
+        (*(PyObject * (*)(PyArrayObject *, npy_bool)) \
+         PyArray_API[79])
+#define PyArray_Resize \
+        (*(PyObject * (*)(PyArrayObject *, PyArray_Dims *, int, NPY_ORDER)) \
+         PyArray_API[80])
+#define PyArray_MoveInto \
+        (*(int (*)(PyArrayObject *, PyArrayObject *)) \
+         PyArray_API[81])
+#define PyArray_CopyInto \
+        (*(int (*)(PyArrayObject *, PyArrayObject *)) \
+         PyArray_API[82])
+#define PyArray_CopyAnyInto \
+        (*(int (*)(PyArrayObject *, PyArrayObject *)) \
+         PyArray_API[83])
+#define PyArray_CopyObject \
+        (*(int (*)(PyArrayObject *, PyObject *)) \
+         PyArray_API[84])
+#define PyArray_NewCopy \
+        (*(PyObject * (*)(PyArrayObject *, NPY_ORDER)) \
+         PyArray_API[85])
+#define PyArray_ToList \
+        (*(PyObject * (*)(PyArrayObject *)) \
+         PyArray_API[86])
+#define PyArray_ToString \
+        (*(PyObject * (*)(PyArrayObject *, NPY_ORDER)) \
+         PyArray_API[87])
+#define PyArray_ToFile \
+        (*(int (*)(PyArrayObject *, FILE *, char *, char *)) \
+         PyArray_API[88])
+#define PyArray_Dump \
+        (*(int (*)(PyObject *, PyObject *, int)) \
+         PyArray_API[89])
+#define PyArray_Dumps \
+        (*(PyObject * (*)(PyObject *, int)) \
+         PyArray_API[90])
+#define PyArray_ValidType \
+        (*(int (*)(int)) \
+         PyArray_API[91])
+#define PyArray_UpdateFlags \
+        (*(void (*)(PyArrayObject *, int)) \
+         PyArray_API[92])
+#define PyArray_New \
+        (*(PyObject * (*)(PyTypeObject *, int, npy_intp *, int, npy_intp *, void *, int, int, PyObject *)) \
+         PyArray_API[93])
+#define PyArray_NewFromDescr \
+        (*(PyObject * (*)(PyTypeObject *, PyArray_Descr *, int, npy_intp *, npy_intp *, void *, int, PyObject *)) \
+         PyArray_API[94])
+#define PyArray_DescrNew \
+        (*(PyArray_Descr * (*)(PyArray_Descr *)) \
+         PyArray_API[95])
+#define PyArray_DescrNewFromType \
+        (*(PyArray_Descr * (*)(int)) \
+         PyArray_API[96])
+#define PyArray_GetPriority \
+        (*(double (*)(PyObject *, double)) \
+         PyArray_API[97])
+#define PyArray_IterNew \
+        (*(PyObject * (*)(PyObject *)) \
+         PyArray_API[98])
+#define PyArray_MultiIterNew \
+        (*(PyObject * (*)(int, ...)) \
+         PyArray_API[99])
+#define PyArray_PyIntAsInt \
+        (*(int (*)(PyObject *)) \
+         PyArray_API[100])
+#define PyArray_PyIntAsIntp \
+        (*(npy_intp (*)(PyObject *)) \
+         PyArray_API[101])
+#define PyArray_Broadcast \
+        (*(int (*)(PyArrayMultiIterObject *)) \
+         PyArray_API[102])
+#define PyArray_FillObjectArray \
+        (*(void (*)(PyArrayObject *, PyObject *)) \
+         PyArray_API[103])
+#define PyArray_FillWithScalar \
+        (*(int (*)(PyArrayObject *, PyObject *)) \
+         PyArray_API[104])
+#define PyArray_CheckStrides \
+        (*(npy_bool (*)(int, int, npy_intp, npy_intp, npy_intp *, npy_intp *)) \
+         PyArray_API[105])
+#define PyArray_DescrNewByteorder \
+        (*(PyArray_Descr * (*)(PyArray_Descr *, char)) \
+         PyArray_API[106])
+#define PyArray_IterAllButAxis \
+        (*(PyObject * (*)(PyObject *, int *)) \
+         PyArray_API[107])
+#define PyArray_CheckFromAny \
+        (*(PyObject * (*)(PyObject *, PyArray_Descr *, int, int, int, PyObject *)) \
+         PyArray_API[108])
+#define PyArray_FromArray \
+        (*(PyObject * (*)(PyArrayObject *, PyArray_Descr *, int)) \
+         PyArray_API[109])
+#define PyArray_FromInterface \
+        (*(PyObject * (*)(PyObject *)) \
+         PyArray_API[110])
+#define PyArray_FromStructInterface \
+        (*(PyObject * (*)(PyObject *)) \
+         PyArray_API[111])
+#define PyArray_FromArrayAttr \
+        (*(PyObject * (*)(PyObject *, PyArray_Descr *, PyObject *)) \
+         PyArray_API[112])
+#define PyArray_ScalarKind \
+        (*(NPY_SCALARKIND (*)(int, PyArrayObject **)) \
+         PyArray_API[113])
+#define PyArray_CanCoerceScalar \
+        (*(int (*)(int, int, NPY_SCALARKIND)) \
+         PyArray_API[114])
+#define PyArray_NewFlagsObject \
+        (*(PyObject * (*)(PyObject *)) \
+         PyArray_API[115])
+#define PyArray_CanCastScalar \
+        (*(npy_bool (*)(PyTypeObject *, PyTypeObject *)) \
+         PyArray_API[116])
+#define PyArray_CompareUCS4 \
+        (*(int (*)(npy_ucs4 *, npy_ucs4 *, size_t)) \
+         PyArray_API[117])
+#define PyArray_RemoveSmallest \
+        (*(int (*)(PyArrayMultiIterObject *)) \
+         PyArray_API[118])
+#define PyArray_ElementStrides \
+        (*(int (*)(PyObject *)) \
+         PyArray_API[119])
+#define PyArray_Item_INCREF \
+        (*(void (*)(char *, PyArray_Descr *)) \
+         PyArray_API[120])
+#define PyArray_Item_XDECREF \
+        (*(void (*)(char *, PyArray_Descr *)) \
+         PyArray_API[121])
+#define PyArray_FieldNames \
+        (*(PyObject * (*)(PyObject *)) \
+         PyArray_API[122])
+#define PyArray_Transpose \
+        (*(PyObject * (*)(PyArrayObject *, PyArray_Dims *)) \
+         PyArray_API[123])
+#define PyArray_TakeFrom \
+        (*(PyObject * (*)(PyArrayObject *, PyObject *, int, PyArrayObject *, NPY_CLIPMODE)) \
+         PyArray_API[124])
+#define PyArray_PutTo \
+        (*(PyObject * (*)(PyArrayObject *, PyObject*, PyObject *, NPY_CLIPMODE)) \
+         PyArray_API[125])
+#define PyArray_PutMask \
+        (*(PyObject * (*)(PyArrayObject *, PyObject*, PyObject*)) \
+         PyArray_API[126])
+#define PyArray_Repeat \
+        (*(PyObject * (*)(PyArrayObject *, PyObject *, int)) \
+         PyArray_API[127])
+#define PyArray_Choose \
+        (*(PyObject * (*)(PyArrayObject *, PyObject *, PyArrayObject *, NPY_CLIPMODE)) \
+         PyArray_API[128])
+#define PyArray_Sort \
+        (*(int (*)(PyArrayObject *, int, NPY_SORTKIND)) \
+         PyArray_API[129])
+#define PyArray_ArgSort \
+        (*(PyObject * (*)(PyArrayObject *, int, NPY_SORTKIND)) \
+         PyArray_API[130])
+#define PyArray_SearchSorted \
+        (*(PyObject * (*)(PyArrayObject *, PyObject *, NPY_SEARCHSIDE, PyObject *)) \
+         PyArray_API[131])
+#define PyArray_ArgMax \
+        (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \
+         PyArray_API[132])
+#define PyArray_ArgMin \
+        (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \
+         PyArray_API[133])
+#define PyArray_Reshape \
+        (*(PyObject * (*)(PyArrayObject *, PyObject *)) \
+         PyArray_API[134])
+#define PyArray_Newshape \
+        (*(PyObject * (*)(PyArrayObject *, PyArray_Dims *, NPY_ORDER)) \
+         PyArray_API[135])
+#define PyArray_Squeeze \
+        (*(PyObject * (*)(PyArrayObject *)) \
+         PyArray_API[136])
+#define PyArray_View \
+        (*(PyObject * (*)(PyArrayObject *, PyArray_Descr *, PyTypeObject *)) \
+         PyArray_API[137])
+#define PyArray_SwapAxes \
+        (*(PyObject * (*)(PyArrayObject *, int, int)) \
+         PyArray_API[138])
+#define PyArray_Max \
+        (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \
+         PyArray_API[139])
+#define PyArray_Min \
+        (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \
+         PyArray_API[140])
+#define PyArray_Ptp \
+        (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \
+         PyArray_API[141])
+#define PyArray_Mean \
+        (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *)) \
+         PyArray_API[142])
+#define PyArray_Trace \
+        (*(PyObject * (*)(PyArrayObject *, int, int, int, int, PyArrayObject *)) \
+         PyArray_API[143])
+#define PyArray_Diagonal \
+        (*(PyObject * (*)(PyArrayObject *, int, int, int)) \
+         PyArray_API[144])
+#define PyArray_Clip \
+        (*(PyObject * (*)(PyArrayObject *, PyObject *, PyObject *, PyArrayObject *)) \
+         PyArray_API[145])
+#define PyArray_Conjugate \
+        (*(PyObject * (*)(PyArrayObject *, PyArrayObject *)) \
+         PyArray_API[146])
+#define PyArray_Nonzero \
+        (*(PyObject * (*)(PyArrayObject *)) \
+         PyArray_API[147])
+#define PyArray_Std \
+        (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *, int)) \
+         PyArray_API[148])
+#define PyArray_Sum \
+        (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *)) \
+         PyArray_API[149])
+#define PyArray_CumSum \
+        (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *)) \
+         PyArray_API[150])
+#define PyArray_Prod \
+        (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *)) \
+         PyArray_API[151])
+#define PyArray_CumProd \
+        (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *)) \
+         PyArray_API[152])
+#define PyArray_All \
+        (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \
+         PyArray_API[153])
+#define PyArray_Any \
+        (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \
+         PyArray_API[154])
+#define PyArray_Compress \
+        (*(PyObject * (*)(PyArrayObject *, PyObject *, int, PyArrayObject *)) \
+         PyArray_API[155])
+#define PyArray_Flatten \
+        (*(PyObject * (*)(PyArrayObject *, NPY_ORDER)) \
+         PyArray_API[156])
+#define PyArray_Ravel \
+        (*(PyObject * (*)(PyArrayObject *, NPY_ORDER)) \
+         PyArray_API[157])
+#define PyArray_MultiplyList \
+        (*(npy_intp (*)(npy_intp *, int)) \
+         PyArray_API[158])
+#define PyArray_MultiplyIntList \
+        (*(int (*)(int *, int)) \
+         PyArray_API[159])
+#define PyArray_GetPtr \
+        (*(void * (*)(PyArrayObject *, npy_intp*)) \
+         PyArray_API[160])
+#define PyArray_CompareLists \
+        (*(int (*)(npy_intp *, npy_intp *, int)) \
+         PyArray_API[161])
+#define PyArray_AsCArray \
+        (*(int (*)(PyObject **, void *, npy_intp *, int, PyArray_Descr*)) \
+         PyArray_API[162])
+#define PyArray_As1D \
+        (*(int (*)(PyObject **, char **, int *, int)) \
+         PyArray_API[163])
+#define PyArray_As2D \
+        (*(int (*)(PyObject **, char ***, int *, int *, int)) \
+         PyArray_API[164])
+#define PyArray_Free \
+        (*(int (*)(PyObject *, void *)) \
+         PyArray_API[165])
+#define PyArray_Converter \
+        (*(int (*)(PyObject *, PyObject **)) \
+         PyArray_API[166])
+#define PyArray_IntpFromSequence \
+        (*(int (*)(PyObject *, npy_intp *, int)) \
+         PyArray_API[167])
+#define PyArray_Concatenate \
+        (*(PyObject * (*)(PyObject *, int)) \
+         PyArray_API[168])
+#define PyArray_InnerProduct \
+        (*(PyObject * (*)(PyObject *, PyObject *)) \
+         PyArray_API[169])
+#define PyArray_MatrixProduct \
+        (*(PyObject * (*)(PyObject *, PyObject *)) \
+         PyArray_API[170])
+#define PyArray_CopyAndTranspose \
+        (*(PyObject * (*)(PyObject *)) \
+         PyArray_API[171])
+#define PyArray_Correlate \
+        (*(PyObject * (*)(PyObject *, PyObject *, int)) \
+         PyArray_API[172])
+#define PyArray_TypestrConvert \
+        (*(int (*)(int, int)) \
+         PyArray_API[173])
+#define PyArray_DescrConverter \
+        (*(int (*)(PyObject *, PyArray_Descr **)) \
+         PyArray_API[174])
+#define PyArray_DescrConverter2 \
+        (*(int (*)(PyObject *, PyArray_Descr **)) \
+         PyArray_API[175])
+#define PyArray_IntpConverter \
+        (*(int (*)(PyObject *, PyArray_Dims *)) \
+         PyArray_API[176])
+#define PyArray_BufferConverter \
+        (*(int (*)(PyObject *, PyArray_Chunk *)) \
+         PyArray_API[177])
+#define PyArray_AxisConverter \
+        (*(int (*)(PyObject *, int *)) \
+         PyArray_API[178])
+#define PyArray_BoolConverter \
+        (*(int (*)(PyObject *, npy_bool *)) \
+         PyArray_API[179])
+#define PyArray_ByteorderConverter \
+        (*(int (*)(PyObject *, char *)) \
+         PyArray_API[180])
+#define PyArray_OrderConverter \
+        (*(int (*)(PyObject *, NPY_ORDER *)) \
+         PyArray_API[181])
+#define PyArray_EquivTypes \
+        (*(unsigned char (*)(PyArray_Descr *, PyArray_Descr *)) \
+         PyArray_API[182])
+#define PyArray_Zeros \
+        (*(PyObject * (*)(int, npy_intp *, PyArray_Descr *, int)) \
+         PyArray_API[183])
+#define PyArray_Empty \
+        (*(PyObject * (*)(int, npy_intp *, PyArray_Descr *, int)) \
+         PyArray_API[184])
+#define PyArray_Where \
+        (*(PyObject * (*)(PyObject *, PyObject *, PyObject *)) \
+         PyArray_API[185])
+#define PyArray_Arange \
+        (*(PyObject * (*)(double, double, double, int)) \
+         PyArray_API[186])
+#define PyArray_ArangeObj \
+        (*(PyObject * (*)(PyObject *, PyObject *, PyObject *, PyArray_Descr *)) \
+         PyArray_API[187])
+#define PyArray_SortkindConverter \
+        (*(int (*)(PyObject *, NPY_SORTKIND *)) \
+         PyArray_API[188])
+#define PyArray_LexSort \
+        (*(PyObject * (*)(PyObject *, int)) \
+         PyArray_API[189])
+#define PyArray_Round \
+        (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \
+         PyArray_API[190])
+#define PyArray_EquivTypenums \
+        (*(unsigned char (*)(int, int)) \
+         PyArray_API[191])
+#define PyArray_RegisterDataType \
+        (*(int (*)(PyArray_Descr *)) \
+         PyArray_API[192])
+#define PyArray_RegisterCastFunc \
+        (*(int (*)(PyArray_Descr *, int, PyArray_VectorUnaryFunc *)) \
+         PyArray_API[193])
+#define PyArray_RegisterCanCast \
+        (*(int (*)(PyArray_Descr *, int, NPY_SCALARKIND)) \
+         PyArray_API[194])
+#define PyArray_InitArrFuncs \
+        (*(void (*)(PyArray_ArrFuncs *)) \
+         PyArray_API[195])
+#define PyArray_IntTupleFromIntp \
+        (*(PyObject * (*)(int, npy_intp *)) \
+         PyArray_API[196])
+#define PyArray_TypeNumFromName \
+        (*(int (*)(char *)) \
+         PyArray_API[197])
+#define PyArray_ClipmodeConverter \
+        (*(int (*)(PyObject *, NPY_CLIPMODE *)) \
+         PyArray_API[198])
+#define PyArray_OutputConverter \
+        (*(int (*)(PyObject *, PyArrayObject **)) \
+         PyArray_API[199])
+#define PyArray_BroadcastToShape \
+        (*(PyObject * (*)(PyObject *, npy_intp *, int)) \
+         PyArray_API[200])
+#define _PyArray_SigintHandler \
+        (*(void (*)(int)) \
+         PyArray_API[201])
+#define _PyArray_GetSigintBuf \
+        (*(void* (*)(void)) \
+         PyArray_API[202])
+#define PyArray_DescrAlignConverter \
+        (*(int (*)(PyObject *, PyArray_Descr **)) \
+         PyArray_API[203])
+#define PyArray_DescrAlignConverter2 \
+        (*(int (*)(PyObject *, PyArray_Descr **)) \
+         PyArray_API[204])
+#define PyArray_SearchsideConverter \
+        (*(int (*)(PyObject *, void *)) \
+         PyArray_API[205])
+#define PyArray_CheckAxis \
+        (*(PyObject * (*)(PyArrayObject *, int *, int)) \
+         PyArray_API[206])
+#define PyArray_OverflowMultiplyList \
+        (*(npy_intp (*)(npy_intp *, int)) \
+         PyArray_API[207])
+#define PyArray_CompareString \
+        (*(int (*)(char *, char *, size_t)) \
+         PyArray_API[208])
+#define PyArray_MultiIterFromObjects \
+        (*(PyObject * (*)(PyObject **, int, int, ...)) \
+         PyArray_API[209])
+#define PyArray_GetEndianness \
+        (*(int (*)(void)) \
+         PyArray_API[210])
+#define PyArray_GetNDArrayCFeatureVersion \
+        (*(unsigned int (*)(void)) \
+         PyArray_API[211])
+#define PyArray_Correlate2 \
+        (*(PyObject * (*)(PyObject *, PyObject *, int)) \
+         PyArray_API[212])
+#define PyArray_NeighborhoodIterNew \
+        (*(PyObject* (*)(PyArrayIterObject *, npy_intp *, int, PyArrayObject*)) \
+         PyArray_API[213])
+#define PyTimeIntegerArrType_Type (*(PyTypeObject *)PyArray_API[214])
+#define PyDatetimeArrType_Type (*(PyTypeObject *)PyArray_API[215])
+#define PyTimedeltaArrType_Type (*(PyTypeObject *)PyArray_API[216])
+#define PyHalfArrType_Type (*(PyTypeObject *)PyArray_API[217])
+#define NpyIter_Type (*(PyTypeObject *)PyArray_API[218])
+#define PyArray_SetDatetimeParseFunction \
+        (*(void (*)(PyObject *)) \
+         PyArray_API[219])
+#define PyArray_DatetimeToDatetimeStruct \
+        (*(void (*)(npy_datetime, NPY_DATETIMEUNIT, npy_datetimestruct *)) \
+         PyArray_API[220])
+#define PyArray_TimedeltaToTimedeltaStruct \
+        (*(void (*)(npy_timedelta, NPY_DATETIMEUNIT, npy_timedeltastruct *)) \
+         PyArray_API[221])
+#define PyArray_DatetimeStructToDatetime \
+        (*(npy_datetime (*)(NPY_DATETIMEUNIT, npy_datetimestruct *)) \
+         PyArray_API[222])
+#define PyArray_TimedeltaStructToTimedelta \
+        (*(npy_datetime (*)(NPY_DATETIMEUNIT, npy_timedeltastruct *)) \
+         PyArray_API[223])
+#define NpyIter_New \
+        (*(NpyIter * (*)(PyArrayObject *, npy_uint32, NPY_ORDER, NPY_CASTING, PyArray_Descr*)) \
+         PyArray_API[224])
+#define NpyIter_MultiNew \
+        (*(NpyIter * (*)(int, PyArrayObject **, npy_uint32, NPY_ORDER, NPY_CASTING, npy_uint32 *, PyArray_Descr **)) \
+         PyArray_API[225])
+#define NpyIter_AdvancedNew \
+        (*(NpyIter * (*)(int, PyArrayObject **, npy_uint32, NPY_ORDER, NPY_CASTING, npy_uint32 *, PyArray_Descr **, int, int **, npy_intp *, npy_intp)) \
+         PyArray_API[226])
+#define NpyIter_Copy \
+        (*(NpyIter * (*)(NpyIter *)) \
+         PyArray_API[227])
+#define NpyIter_Deallocate \
+        (*(int (*)(NpyIter *)) \
+         PyArray_API[228])
+#define NpyIter_HasDelayedBufAlloc \
+        (*(npy_bool (*)(NpyIter *)) \
+         PyArray_API[229])
+#define NpyIter_HasExternalLoop \
+        (*(npy_bool (*)(NpyIter *)) \
+         PyArray_API[230])
+#define NpyIter_EnableExternalLoop \
+        (*(int (*)(NpyIter *)) \
+         PyArray_API[231])
+#define NpyIter_GetInnerStrideArray \
+        (*(npy_intp * (*)(NpyIter *)) \
+         PyArray_API[232])
+#define NpyIter_GetInnerLoopSizePtr \
+        (*(npy_intp * (*)(NpyIter *)) \
+         PyArray_API[233])
+#define NpyIter_Reset \
+        (*(int (*)(NpyIter *, char **)) \
+         PyArray_API[234])
+#define NpyIter_ResetBasePointers \
+        (*(int (*)(NpyIter *, char **, char **)) \
+         PyArray_API[235])
+#define NpyIter_ResetToIterIndexRange \
+        (*(int (*)(NpyIter *, npy_intp, npy_intp, char **)) \
+         PyArray_API[236])
+#define NpyIter_GetNDim \
+        (*(int (*)(NpyIter *)) \
+         PyArray_API[237])
+#define NpyIter_GetNOp \
+        (*(int (*)(NpyIter *)) \
+         PyArray_API[238])
+#define NpyIter_GetIterNext \
+        (*(NpyIter_IterNextFunc * (*)(NpyIter *, char **)) \
+         PyArray_API[239])
+#define NpyIter_GetIterSize \
+        (*(npy_intp (*)(NpyIter *)) \
+         PyArray_API[240])
+#define NpyIter_GetIterIndexRange \
+        (*(void (*)(NpyIter *, npy_intp *, npy_intp *)) \
+         PyArray_API[241])
+#define NpyIter_GetIterIndex \
+        (*(npy_intp (*)(NpyIter *)) \
+         PyArray_API[242])
+#define NpyIter_GotoIterIndex \
+        (*(int (*)(NpyIter *, npy_intp)) \
+         PyArray_API[243])
+#define NpyIter_HasMultiIndex \
+        (*(npy_bool (*)(NpyIter *)) \
+         PyArray_API[244])
+#define NpyIter_GetShape \
+        (*(int (*)(NpyIter *, npy_intp *)) \
+         PyArray_API[245])
+#define NpyIter_GetGetMultiIndex \
+        (*(NpyIter_GetMultiIndexFunc * (*)(NpyIter *, char **)) \
+         PyArray_API[246])
+#define NpyIter_GotoMultiIndex \
+        (*(int (*)(NpyIter *, npy_intp *)) \
+         PyArray_API[247])
+#define NpyIter_RemoveMultiIndex \
+        (*(int (*)(NpyIter *)) \
+         PyArray_API[248])
+#define NpyIter_HasIndex \
+        (*(npy_bool (*)(NpyIter *)) \
+         PyArray_API[249])
+#define NpyIter_IsBuffered \
+        (*(npy_bool (*)(NpyIter *)) \
+         PyArray_API[250])
+#define NpyIter_IsGrowInner \
+        (*(npy_bool (*)(NpyIter *)) \
+         PyArray_API[251])
+#define NpyIter_GetBufferSize \
+        (*(npy_intp (*)(NpyIter *)) \
+         PyArray_API[252])
+#define NpyIter_GetIndexPtr \
+        (*(npy_intp * (*)(NpyIter *)) \
+         PyArray_API[253])
+#define NpyIter_GotoIndex \
+        (*(int (*)(NpyIter *, npy_intp)) \
+         PyArray_API[254])
+#define NpyIter_GetDataPtrArray \
+        (*(char ** (*)(NpyIter *)) \
+         PyArray_API[255])
+#define NpyIter_GetDescrArray \
+        (*(PyArray_Descr ** (*)(NpyIter *)) \
+         PyArray_API[256])
+#define NpyIter_GetOperandArray \
+        (*(PyArrayObject ** (*)(NpyIter *)) \
+         PyArray_API[257])
+#define NpyIter_GetIterView \
+        (*(PyArrayObject * (*)(NpyIter *, npy_intp)) \
+         PyArray_API[258])
+#define NpyIter_GetReadFlags \
+        (*(void (*)(NpyIter *, char *)) \
+         PyArray_API[259])
+#define NpyIter_GetWriteFlags \
+        (*(void (*)(NpyIter *, char *)) \
+         PyArray_API[260])
+#define NpyIter_DebugPrint \
+        (*(void (*)(NpyIter *)) \
+         PyArray_API[261])
+#define NpyIter_IterationNeedsAPI \
+        (*(npy_bool (*)(NpyIter *)) \
+         PyArray_API[262])
+#define NpyIter_GetInnerFixedStrideArray \
+        (*(void (*)(NpyIter *, npy_intp *)) \
+         PyArray_API[263])
+#define NpyIter_RemoveAxis \
+        (*(int (*)(NpyIter *, int)) \
+         PyArray_API[264])
+#define NpyIter_GetAxisStrideArray \
+        (*(npy_intp * (*)(NpyIter *, int)) \
+         PyArray_API[265])
+#define NpyIter_RequiresBuffering \
+        (*(npy_bool (*)(NpyIter *)) \
+         PyArray_API[266])
+#define NpyIter_GetInitialDataPtrArray \
+        (*(char ** (*)(NpyIter *)) \
+         PyArray_API[267])
+#define NpyIter_CreateCompatibleStrides \
+        (*(int (*)(NpyIter *, npy_intp, npy_intp *)) \
+         PyArray_API[268])
+#define PyArray_CastingConverter \
+        (*(int (*)(PyObject *, NPY_CASTING *)) \
+         PyArray_API[269])
+#define PyArray_CountNonzero \
+        (*(npy_intp (*)(PyArrayObject *)) \
+         PyArray_API[270])
+#define PyArray_PromoteTypes \
+        (*(PyArray_Descr * (*)(PyArray_Descr *, PyArray_Descr *)) \
+         PyArray_API[271])
+#define PyArray_MinScalarType \
+        (*(PyArray_Descr * (*)(PyArrayObject *)) \
+         PyArray_API[272])
+#define PyArray_ResultType \
+        (*(PyArray_Descr * (*)(npy_intp, PyArrayObject **, npy_intp, PyArray_Descr **)) \
+         PyArray_API[273])
+#define PyArray_CanCastArrayTo \
+        (*(npy_bool (*)(PyArrayObject *, PyArray_Descr *, NPY_CASTING)) \
+         PyArray_API[274])
+#define PyArray_CanCastTypeTo \
+        (*(npy_bool (*)(PyArray_Descr *, PyArray_Descr *, NPY_CASTING)) \
+         PyArray_API[275])
+#define PyArray_EinsteinSum \
+        (*(PyArrayObject * (*)(char *, npy_intp, PyArrayObject **, PyArray_Descr *, NPY_ORDER, NPY_CASTING, PyArrayObject *)) \
+         PyArray_API[276])
+#define PyArray_NewLikeArray \
+        (*(PyObject * (*)(PyArrayObject *, NPY_ORDER, PyArray_Descr *, int)) \
+         PyArray_API[277])
+#define PyArray_GetArrayParamsFromObject \
+        (*(int (*)(PyObject *, PyArray_Descr *, npy_bool, PyArray_Descr **, int *, npy_intp *, PyArrayObject **, PyObject *)) \
+         PyArray_API[278])
+#define PyArray_ConvertClipmodeSequence \
+        (*(int (*)(PyObject *, NPY_CLIPMODE *, int)) \
+         PyArray_API[279])
+#define PyArray_MatrixProduct2 \
+        (*(PyObject * (*)(PyObject *, PyObject *, PyArrayObject*)) \
+         PyArray_API[280])
+#define NpyIter_IsFirstVisit \
+        (*(npy_bool (*)(NpyIter *, int)) \
+         PyArray_API[281])
+#define PyArray_SetBaseObject \
+        (*(int (*)(PyArrayObject *, PyObject *)) \
+         PyArray_API[282])
+#define PyArray_CreateSortedStridePerm \
+        (*(void (*)(int, npy_intp *, npy_stride_sort_item *)) \
+         PyArray_API[283])
+#define PyArray_RemoveAxesInPlace \
+        (*(void (*)(PyArrayObject *, npy_bool *)) \
+         PyArray_API[284])
+#define PyArray_DebugPrint \
+        (*(void (*)(PyArrayObject *)) \
+         PyArray_API[285])
+#define PyArray_FailUnlessWriteable \
+        (*(int (*)(PyArrayObject *, const char *)) \
+         PyArray_API[286])
+#define PyArray_SetUpdateIfCopyBase \
+        (*(int (*)(PyArrayObject *, PyArrayObject *)) \
+         PyArray_API[287])
+#define PyDataMem_NEW \
+        (*(void * (*)(size_t)) \
+         PyArray_API[288])
+#define PyDataMem_FREE \
+        (*(void (*)(void *)) \
+         PyArray_API[289])
+#define PyDataMem_RENEW \
+        (*(void * (*)(void *, size_t)) \
+         PyArray_API[290])
+#define PyDataMem_SetEventHook \
+        (*(PyDataMem_EventHookFunc * (*)(PyDataMem_EventHookFunc *, void *, void **)) \
+         PyArray_API[291])
+#define NPY_DEFAULT_ASSIGN_CASTING (*(NPY_CASTING *)PyArray_API[292])
+#define PyArray_MapIterSwapAxes \
+        (*(void (*)(PyArrayMapIterObject *, PyArrayObject **, int)) \
+         PyArray_API[293])
+#define PyArray_MapIterArray \
+        (*(PyObject * (*)(PyArrayObject *, PyObject *)) \
+         PyArray_API[294])
+#define PyArray_MapIterNext \
+        (*(void (*)(PyArrayMapIterObject *)) \
+         PyArray_API[295])
+#define PyArray_Partition \
+        (*(int (*)(PyArrayObject *, PyArrayObject *, int, NPY_SELECTKIND)) \
+         PyArray_API[296])
+#define PyArray_ArgPartition \
+        (*(PyObject * (*)(PyArrayObject *, PyArrayObject *, int, NPY_SELECTKIND)) \
+         PyArray_API[297])
+#define PyArray_SelectkindConverter \
+        (*(int (*)(PyObject *, NPY_SELECTKIND *)) \
+         PyArray_API[298])
+#define PyDataMem_NEW_ZEROED \
+        (*(void * (*)(size_t, size_t)) \
+         PyArray_API[299])
+#define PyArray_CheckAnyScalarExact \
+        (*(int (*)(PyObject *)) \
+         PyArray_API[300])
+#define PyArray_MapIterArrayCopyIfOverlap \
+        (*(PyObject * (*)(PyArrayObject *, PyObject *, int, PyArrayObject *)) \
+         PyArray_API[301])
+#define PyArray_ResolveWritebackIfCopy \
+        (*(int (*)(PyArrayObject *)) \
+         PyArray_API[302])
+#define PyArray_SetWritebackIfCopyBase \
+        (*(int (*)(PyArrayObject *, PyArrayObject *)) \
+         PyArray_API[303])
+
+#if !defined(NO_IMPORT_ARRAY) && !defined(NO_IMPORT)
+static int
+_import_array(void)
+{
+  int st;
+  PyObject *numpy = PyImport_ImportModule("numpy.core._multiarray_umath");
+  PyObject *c_api = NULL;
+
+  if (numpy == NULL) {
+      return -1;
+  }
+  c_api = PyObject_GetAttrString(numpy, "_ARRAY_API");
+  Py_DECREF(numpy);
+  if (c_api == NULL) {
+      PyErr_SetString(PyExc_AttributeError, "_ARRAY_API not found");
+      return -1;
+  }
+
+#if PY_VERSION_HEX >= 0x03000000
+  if (!PyCapsule_CheckExact(c_api)) {
+      PyErr_SetString(PyExc_RuntimeError, "_ARRAY_API is not PyCapsule object");
+      Py_DECREF(c_api);
+      return -1;
+  }
+  PyArray_API = (void **)PyCapsule_GetPointer(c_api, NULL);
+#else
+  if (!PyCObject_Check(c_api)) {
+      PyErr_SetString(PyExc_RuntimeError, "_ARRAY_API is not PyCObject object");
+      Py_DECREF(c_api);
+      return -1;
+  }
+  PyArray_API = (void **)PyCObject_AsVoidPtr(c_api);
+#endif
+  Py_DECREF(c_api);
+  if (PyArray_API == NULL) {
+      PyErr_SetString(PyExc_RuntimeError, "_ARRAY_API is NULL pointer");
+      return -1;
+  }
+
+  /* Perform runtime check of C API version */
+  if (NPY_VERSION != PyArray_GetNDArrayCVersion()) {
+      PyErr_Format(PyExc_RuntimeError, "module compiled against "\
+             "ABI version 0x%x but this version of numpy is 0x%x", \
+             (int) NPY_VERSION, (int) PyArray_GetNDArrayCVersion());
+      return -1;
+  }
+  if (NPY_FEATURE_VERSION > PyArray_GetNDArrayCFeatureVersion()) {
+      PyErr_Format(PyExc_RuntimeError, "module compiled against "\
+             "API version 0x%x but this version of numpy is 0x%x", \
+             (int) NPY_FEATURE_VERSION, (int) PyArray_GetNDArrayCFeatureVersion());
+      return -1;
+  }
+
+  /*
+   * Perform runtime check of endianness and check it matches the one set by
+   * the headers (npy_endian.h) as a safeguard
+   */
+  st = PyArray_GetEndianness();
+  if (st == NPY_CPU_UNKNOWN_ENDIAN) {
+      PyErr_Format(PyExc_RuntimeError, "FATAL: module compiled as unknown endian");
+      return -1;
+  }
+#if NPY_BYTE_ORDER == NPY_BIG_ENDIAN
+  if (st != NPY_CPU_BIG) {
+      PyErr_Format(PyExc_RuntimeError, "FATAL: module compiled as "\
+             "big endian, but detected different endianness at runtime");
+      return -1;
+  }
+#elif NPY_BYTE_ORDER == NPY_LITTLE_ENDIAN
+  if (st != NPY_CPU_LITTLE) {
+      PyErr_Format(PyExc_RuntimeError, "FATAL: module compiled as "\
+             "little endian, but detected different endianness at runtime");
+      return -1;
+  }
+#endif
+
+  return 0;
+}
+
+#if PY_VERSION_HEX >= 0x03000000
+#define NUMPY_IMPORT_ARRAY_RETVAL NULL
+#else
+#define NUMPY_IMPORT_ARRAY_RETVAL
+#endif
+
+#define import_array() {if (_import_array() < 0) {PyErr_Print(); PyErr_SetString(PyExc_ImportError, "numpy.core.multiarray failed to import"); return NUMPY_IMPORT_ARRAY_RETVAL; } }
+
+#define import_array1(ret) {if (_import_array() < 0) {PyErr_Print(); PyErr_SetString(PyExc_ImportError, "numpy.core.multiarray failed to import"); return ret; } }
+
+#define import_array2(msg, ret) {if (_import_array() < 0) {PyErr_Print(); PyErr_SetString(PyExc_ImportError, msg); return ret; } }
+
+#endif
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/__ufunc_api.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/__ufunc_api.h
new file mode 100644
index 0000000..22d2ba1
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/__ufunc_api.h
@@ -0,0 +1,326 @@
+
+#ifdef _UMATHMODULE
+
+extern NPY_NO_EXPORT PyTypeObject PyUFunc_Type;
+
+extern NPY_NO_EXPORT PyTypeObject PyUFunc_Type;
+
+NPY_NO_EXPORT  PyObject * PyUFunc_FromFuncAndData \
+       (PyUFuncGenericFunction *, void **, char *, int, int, int, int, const char *, const char *, int);
+NPY_NO_EXPORT  int PyUFunc_RegisterLoopForType \
+       (PyUFuncObject *, int, PyUFuncGenericFunction, int *, void *);
+NPY_NO_EXPORT  int PyUFunc_GenericFunction \
+       (PyUFuncObject *, PyObject *, PyObject *, PyArrayObject **);
+NPY_NO_EXPORT  void PyUFunc_f_f_As_d_d \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_d_d \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_f_f \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_g_g \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_F_F_As_D_D \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_F_F \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_D_D \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_G_G \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_O_O \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_ff_f_As_dd_d \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_ff_f \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_dd_d \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_gg_g \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_FF_F_As_DD_D \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_DD_D \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_FF_F \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_GG_G \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_OO_O \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_O_O_method \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_OO_O_method \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_On_Om \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  int PyUFunc_GetPyValues \
+       (char *, int *, int *, PyObject **);
+NPY_NO_EXPORT  int PyUFunc_checkfperr \
+       (int, PyObject *, int *);
+NPY_NO_EXPORT  void PyUFunc_clearfperr \
+       (void);
+NPY_NO_EXPORT  int PyUFunc_getfperr \
+       (void);
+NPY_NO_EXPORT  int PyUFunc_handlefperr \
+       (int, PyObject *, int, int *);
+NPY_NO_EXPORT  int PyUFunc_ReplaceLoopBySignature \
+       (PyUFuncObject *, PyUFuncGenericFunction, int *, PyUFuncGenericFunction *);
+NPY_NO_EXPORT  PyObject * PyUFunc_FromFuncAndDataAndSignature \
+       (PyUFuncGenericFunction *, void **, char *, int, int, int, int, const char *, const char *, int, const char *);
+NPY_NO_EXPORT  int PyUFunc_SetUsesArraysAsData \
+       (void **, size_t);
+NPY_NO_EXPORT  void PyUFunc_e_e \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_e_e_As_f_f \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_e_e_As_d_d \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_ee_e \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_ee_e_As_ff_f \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  void PyUFunc_ee_e_As_dd_d \
+       (char **, npy_intp *, npy_intp *, void *);
+NPY_NO_EXPORT  int PyUFunc_DefaultTypeResolver \
+       (PyUFuncObject *, NPY_CASTING, PyArrayObject **, PyObject *, PyArray_Descr **);
+NPY_NO_EXPORT  int PyUFunc_ValidateCasting \
+       (PyUFuncObject *, NPY_CASTING, PyArrayObject **, PyArray_Descr **);
+NPY_NO_EXPORT  int PyUFunc_RegisterLoopForDescr \
+       (PyUFuncObject *, PyArray_Descr *, PyUFuncGenericFunction, PyArray_Descr **, void *);
+NPY_NO_EXPORT  PyObject * PyUFunc_FromFuncAndDataAndSignatureAndIdentity \
+       (PyUFuncGenericFunction *, void **, char *, int, int, int, int, const char *, const char *, int, const char *, PyObject *);
+
+#else
+
+#if defined(PY_UFUNC_UNIQUE_SYMBOL)
+#define PyUFunc_API PY_UFUNC_UNIQUE_SYMBOL
+#endif
+
+#if defined(NO_IMPORT) || defined(NO_IMPORT_UFUNC)
+extern void **PyUFunc_API;
+#else
+#if defined(PY_UFUNC_UNIQUE_SYMBOL)
+void **PyUFunc_API;
+#else
+static void **PyUFunc_API=NULL;
+#endif
+#endif
+
+#define PyUFunc_Type (*(PyTypeObject *)PyUFunc_API[0])
+#define PyUFunc_FromFuncAndData \
+        (*(PyObject * (*)(PyUFuncGenericFunction *, void **, char *, int, int, int, int, const char *, const char *, int)) \
+         PyUFunc_API[1])
+#define PyUFunc_RegisterLoopForType \
+        (*(int (*)(PyUFuncObject *, int, PyUFuncGenericFunction, int *, void *)) \
+         PyUFunc_API[2])
+#define PyUFunc_GenericFunction \
+        (*(int (*)(PyUFuncObject *, PyObject *, PyObject *, PyArrayObject **)) \
+         PyUFunc_API[3])
+#define PyUFunc_f_f_As_d_d \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[4])
+#define PyUFunc_d_d \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[5])
+#define PyUFunc_f_f \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[6])
+#define PyUFunc_g_g \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[7])
+#define PyUFunc_F_F_As_D_D \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[8])
+#define PyUFunc_F_F \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[9])
+#define PyUFunc_D_D \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[10])
+#define PyUFunc_G_G \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[11])
+#define PyUFunc_O_O \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[12])
+#define PyUFunc_ff_f_As_dd_d \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[13])
+#define PyUFunc_ff_f \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[14])
+#define PyUFunc_dd_d \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[15])
+#define PyUFunc_gg_g \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[16])
+#define PyUFunc_FF_F_As_DD_D \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[17])
+#define PyUFunc_DD_D \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[18])
+#define PyUFunc_FF_F \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[19])
+#define PyUFunc_GG_G \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[20])
+#define PyUFunc_OO_O \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[21])
+#define PyUFunc_O_O_method \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[22])
+#define PyUFunc_OO_O_method \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[23])
+#define PyUFunc_On_Om \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[24])
+#define PyUFunc_GetPyValues \
+        (*(int (*)(char *, int *, int *, PyObject **)) \
+         PyUFunc_API[25])
+#define PyUFunc_checkfperr \
+        (*(int (*)(int, PyObject *, int *)) \
+         PyUFunc_API[26])
+#define PyUFunc_clearfperr \
+        (*(void (*)(void)) \
+         PyUFunc_API[27])
+#define PyUFunc_getfperr \
+        (*(int (*)(void)) \
+         PyUFunc_API[28])
+#define PyUFunc_handlefperr \
+        (*(int (*)(int, PyObject *, int, int *)) \
+         PyUFunc_API[29])
+#define PyUFunc_ReplaceLoopBySignature \
+        (*(int (*)(PyUFuncObject *, PyUFuncGenericFunction, int *, PyUFuncGenericFunction *)) \
+         PyUFunc_API[30])
+#define PyUFunc_FromFuncAndDataAndSignature \
+        (*(PyObject * (*)(PyUFuncGenericFunction *, void **, char *, int, int, int, int, const char *, const char *, int, const char *)) \
+         PyUFunc_API[31])
+#define PyUFunc_SetUsesArraysAsData \
+        (*(int (*)(void **, size_t)) \
+         PyUFunc_API[32])
+#define PyUFunc_e_e \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[33])
+#define PyUFunc_e_e_As_f_f \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[34])
+#define PyUFunc_e_e_As_d_d \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[35])
+#define PyUFunc_ee_e \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[36])
+#define PyUFunc_ee_e_As_ff_f \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[37])
+#define PyUFunc_ee_e_As_dd_d \
+        (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \
+         PyUFunc_API[38])
+#define PyUFunc_DefaultTypeResolver \
+        (*(int (*)(PyUFuncObject *, NPY_CASTING, PyArrayObject **, PyObject *, PyArray_Descr **)) \
+         PyUFunc_API[39])
+#define PyUFunc_ValidateCasting \
+        (*(int (*)(PyUFuncObject *, NPY_CASTING, PyArrayObject **, PyArray_Descr **)) \
+         PyUFunc_API[40])
+#define PyUFunc_RegisterLoopForDescr \
+        (*(int (*)(PyUFuncObject *, PyArray_Descr *, PyUFuncGenericFunction, PyArray_Descr **, void *)) \
+         PyUFunc_API[41])
+#define PyUFunc_FromFuncAndDataAndSignatureAndIdentity \
+        (*(PyObject * (*)(PyUFuncGenericFunction *, void **, char *, int, int, int, int, const char *, const char *, int, const char *, PyObject *)) \
+         PyUFunc_API[42])
+
+static NPY_INLINE int
+_import_umath(void)
+{
+  PyObject *numpy = PyImport_ImportModule("numpy.core._multiarray_umath");
+  PyObject *c_api = NULL;
+
+  if (numpy == NULL) {
+      PyErr_SetString(PyExc_ImportError,
+                      "numpy.core._multiarray_umath failed to import");
+      return -1;
+  }
+  c_api = PyObject_GetAttrString(numpy, "_UFUNC_API");
+  Py_DECREF(numpy);
+  if (c_api == NULL) {
+      PyErr_SetString(PyExc_AttributeError, "_UFUNC_API not found");
+      return -1;
+  }
+
+#if PY_VERSION_HEX >= 0x03000000
+  if (!PyCapsule_CheckExact(c_api)) {
+      PyErr_SetString(PyExc_RuntimeError, "_UFUNC_API is not PyCapsule object");
+      Py_DECREF(c_api);
+      return -1;
+  }
+  PyUFunc_API = (void **)PyCapsule_GetPointer(c_api, NULL);
+#else
+  if (!PyCObject_Check(c_api)) {
+      PyErr_SetString(PyExc_RuntimeError, "_UFUNC_API is not PyCObject object");
+      Py_DECREF(c_api);
+      return -1;
+  }
+  PyUFunc_API = (void **)PyCObject_AsVoidPtr(c_api);
+#endif
+  Py_DECREF(c_api);
+  if (PyUFunc_API == NULL) {
+      PyErr_SetString(PyExc_RuntimeError, "_UFUNC_API is NULL pointer");
+      return -1;
+  }
+  return 0;
+}
+
+#if PY_VERSION_HEX >= 0x03000000
+#define NUMPY_IMPORT_UMATH_RETVAL NULL
+#else
+#define NUMPY_IMPORT_UMATH_RETVAL
+#endif
+
+#define import_umath() \
+    do {\
+        UFUNC_NOFPE\
+        if (_import_umath() < 0) {\
+            PyErr_Print();\
+            PyErr_SetString(PyExc_ImportError,\
+                    "numpy.core.umath failed to import");\
+            return NUMPY_IMPORT_UMATH_RETVAL;\
+        }\
+    } while(0)
+
+#define import_umath1(ret) \
+    do {\
+        UFUNC_NOFPE\
+        if (_import_umath() < 0) {\
+            PyErr_Print();\
+            PyErr_SetString(PyExc_ImportError,\
+                    "numpy.core.umath failed to import");\
+            return ret;\
+        }\
+    } while(0)
+
+#define import_umath2(ret, msg) \
+    do {\
+        UFUNC_NOFPE\
+        if (_import_umath() < 0) {\
+            PyErr_Print();\
+            PyErr_SetString(PyExc_ImportError, msg);\
+            return ret;\
+        }\
+    } while(0)
+
+#define import_ufunc() \
+    do {\
+        UFUNC_NOFPE\
+        if (_import_umath() < 0) {\
+            PyErr_Print();\
+            PyErr_SetString(PyExc_ImportError,\
+                    "numpy.core.umath failed to import");\
+        }\
+    } while(0)
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/_neighborhood_iterator_imp.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/_neighborhood_iterator_imp.h
new file mode 100644
index 0000000..e8860cb
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/_neighborhood_iterator_imp.h
@@ -0,0 +1,90 @@
+#ifndef _NPY_INCLUDE_NEIGHBORHOOD_IMP
+#error You should not include this header directly
+#endif
+/*
+ * Private API (here for inline)
+ */
+static NPY_INLINE int
+_PyArrayNeighborhoodIter_IncrCoord(PyArrayNeighborhoodIterObject* iter);
+
+/*
+ * Update to next item of the iterator
+ *
+ * Note: this simply increment the coordinates vector, last dimension
+ * incremented first , i.e, for dimension 3
+ * ...
+ * -1, -1, -1
+ * -1, -1,  0
+ * -1, -1,  1
+ *  ....
+ * -1,  0, -1
+ * -1,  0,  0
+ *  ....
+ * 0,  -1, -1
+ * 0,  -1,  0
+ *  ....
+ */
+#define _UPDATE_COORD_ITER(c) \
+    wb = iter->coordinates[c] < iter->bounds[c][1]; \
+    if (wb) { \
+        iter->coordinates[c] += 1; \
+        return 0; \
+    } \
+    else { \
+        iter->coordinates[c] = iter->bounds[c][0]; \
+    }
+
+static NPY_INLINE int
+_PyArrayNeighborhoodIter_IncrCoord(PyArrayNeighborhoodIterObject* iter)
+{
+    npy_intp i, wb;
+
+    for (i = iter->nd - 1; i >= 0; --i) {
+        _UPDATE_COORD_ITER(i)
+    }
+
+    return 0;
+}
+
+/*
+ * Version optimized for 2d arrays, manual loop unrolling
+ */
+static NPY_INLINE int
+_PyArrayNeighborhoodIter_IncrCoord2D(PyArrayNeighborhoodIterObject* iter)
+{
+    npy_intp wb;
+
+    _UPDATE_COORD_ITER(1)
+    _UPDATE_COORD_ITER(0)
+
+    return 0;
+}
+#undef _UPDATE_COORD_ITER
+
+/*
+ * Advance to the next neighbour
+ */
+static NPY_INLINE int
+PyArrayNeighborhoodIter_Next(PyArrayNeighborhoodIterObject* iter)
+{
+    _PyArrayNeighborhoodIter_IncrCoord (iter);
+    iter->dataptr = iter->translate((PyArrayIterObject*)iter, iter->coordinates);
+
+    return 0;
+}
+
+/*
+ * Reset functions
+ */
+static NPY_INLINE int
+PyArrayNeighborhoodIter_Reset(PyArrayNeighborhoodIterObject* iter)
+{
+    npy_intp i;
+
+    for (i = 0; i < iter->nd; ++i) {
+        iter->coordinates[i] = iter->bounds[i][0];
+    }
+    iter->dataptr = iter->translate((PyArrayIterObject*)iter, iter->coordinates);
+
+    return 0;
+}
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/_numpyconfig.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/_numpyconfig.h
new file mode 100644
index 0000000..6c76b3b
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/_numpyconfig.h
@@ -0,0 +1,32 @@
+#define NPY_SIZEOF_SHORT SIZEOF_SHORT
+#define NPY_SIZEOF_INT SIZEOF_INT
+#define NPY_SIZEOF_LONG SIZEOF_LONG
+#define NPY_SIZEOF_FLOAT 4
+#define NPY_SIZEOF_COMPLEX_FLOAT 8
+#define NPY_SIZEOF_DOUBLE 8
+#define NPY_SIZEOF_COMPLEX_DOUBLE 16
+#define NPY_SIZEOF_LONGDOUBLE 16
+#define NPY_SIZEOF_COMPLEX_LONGDOUBLE 32
+#define NPY_SIZEOF_PY_INTPTR_T 8
+#define NPY_SIZEOF_OFF_T 4
+#define NPY_SIZEOF_PY_LONG_LONG 8
+#define NPY_SIZEOF_LONGLONG 8
+#define NPY_NO_SIGNAL 1
+#define NPY_NO_SMP 0
+#define NPY_HAVE_DECL_ISNAN
+#define NPY_HAVE_DECL_ISINF
+#define NPY_HAVE_DECL_ISFINITE
+#define NPY_HAVE_DECL_SIGNBIT
+#define NPY_USE_C99_COMPLEX 1
+#define NPY_HAVE_COMPLEX_DOUBLE 1
+#define NPY_HAVE_COMPLEX_FLOAT 1
+#define NPY_HAVE_COMPLEX_LONG_DOUBLE 1
+#define NPY_RELAXED_STRIDES_CHECKING 1
+#define NPY_USE_C99_FORMATS 1
+#define NPY_VISIBILITY_HIDDEN 
+#define NPY_ABI_VERSION 0x01000009
+#define NPY_API_VERSION 0x0000000D
+
+#ifndef __STDC_FORMAT_MACROS
+#define __STDC_FORMAT_MACROS 1
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/arrayobject.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/arrayobject.h
new file mode 100644
index 0000000..4f46d6b
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/arrayobject.h
@@ -0,0 +1,11 @@
+#ifndef Py_ARRAYOBJECT_H
+#define Py_ARRAYOBJECT_H
+
+#include "ndarrayobject.h"
+#include "npy_interrupt.h"
+
+#ifdef NPY_NO_PREFIX
+#include "noprefix.h"
+#endif
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/arrayscalars.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/arrayscalars.h
new file mode 100644
index 0000000..64450e7
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/arrayscalars.h
@@ -0,0 +1,175 @@
+#ifndef _NPY_ARRAYSCALARS_H_
+#define _NPY_ARRAYSCALARS_H_
+
+#ifndef _MULTIARRAYMODULE
+typedef struct {
+        PyObject_HEAD
+        npy_bool obval;
+} PyBoolScalarObject;
+#endif
+
+
+typedef struct {
+        PyObject_HEAD
+        signed char obval;
+} PyByteScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        short obval;
+} PyShortScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        int obval;
+} PyIntScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        long obval;
+} PyLongScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        npy_longlong obval;
+} PyLongLongScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        unsigned char obval;
+} PyUByteScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        unsigned short obval;
+} PyUShortScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        unsigned int obval;
+} PyUIntScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        unsigned long obval;
+} PyULongScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        npy_ulonglong obval;
+} PyULongLongScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        npy_half obval;
+} PyHalfScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        float obval;
+} PyFloatScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        double obval;
+} PyDoubleScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        npy_longdouble obval;
+} PyLongDoubleScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        npy_cfloat obval;
+} PyCFloatScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        npy_cdouble obval;
+} PyCDoubleScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        npy_clongdouble obval;
+} PyCLongDoubleScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        PyObject * obval;
+} PyObjectScalarObject;
+
+typedef struct {
+        PyObject_HEAD
+        npy_datetime obval;
+        PyArray_DatetimeMetaData obmeta;
+} PyDatetimeScalarObject;
+
+typedef struct {
+        PyObject_HEAD
+        npy_timedelta obval;
+        PyArray_DatetimeMetaData obmeta;
+} PyTimedeltaScalarObject;
+
+
+typedef struct {
+        PyObject_HEAD
+        char obval;
+} PyScalarObject;
+
+#define PyStringScalarObject PyStringObject
+#define PyUnicodeScalarObject PyUnicodeObject
+
+typedef struct {
+        PyObject_VAR_HEAD
+        char *obval;
+        PyArray_Descr *descr;
+        int flags;
+        PyObject *base;
+} PyVoidScalarObject;
+
+/* Macros
+     Py<Cls><bitsize>ScalarObject
+     Py<Cls><bitsize>ArrType_Type
+   are defined in ndarrayobject.h
+*/
+
+#define PyArrayScalar_False ((PyObject *)(&(_PyArrayScalar_BoolValues[0])))
+#define PyArrayScalar_True ((PyObject *)(&(_PyArrayScalar_BoolValues[1])))
+#define PyArrayScalar_FromLong(i) \
+        ((PyObject *)(&(_PyArrayScalar_BoolValues[((i)!=0)])))
+#define PyArrayScalar_RETURN_BOOL_FROM_LONG(i)                  \
+        return Py_INCREF(PyArrayScalar_FromLong(i)), \
+                PyArrayScalar_FromLong(i)
+#define PyArrayScalar_RETURN_FALSE              \
+        return Py_INCREF(PyArrayScalar_False),  \
+                PyArrayScalar_False
+#define PyArrayScalar_RETURN_TRUE               \
+        return Py_INCREF(PyArrayScalar_True),   \
+                PyArrayScalar_True
+
+#define PyArrayScalar_New(cls) \
+        Py##cls##ArrType_Type.tp_alloc(&Py##cls##ArrType_Type, 0)
+#define PyArrayScalar_VAL(obj, cls)             \
+        ((Py##cls##ScalarObject *)obj)->obval
+#define PyArrayScalar_ASSIGN(obj, cls, val) \
+        PyArrayScalar_VAL(obj, cls) = val
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/halffloat.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/halffloat.h
new file mode 100644
index 0000000..ab0d221
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/halffloat.h
@@ -0,0 +1,70 @@
+#ifndef __NPY_HALFFLOAT_H__
+#define __NPY_HALFFLOAT_H__
+
+#include <Python.h>
+#include <numpy/npy_math.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*
+ * Half-precision routines
+ */
+
+/* Conversions */
+float npy_half_to_float(npy_half h);
+double npy_half_to_double(npy_half h);
+npy_half npy_float_to_half(float f);
+npy_half npy_double_to_half(double d);
+/* Comparisons */
+int npy_half_eq(npy_half h1, npy_half h2);
+int npy_half_ne(npy_half h1, npy_half h2);
+int npy_half_le(npy_half h1, npy_half h2);
+int npy_half_lt(npy_half h1, npy_half h2);
+int npy_half_ge(npy_half h1, npy_half h2);
+int npy_half_gt(npy_half h1, npy_half h2);
+/* faster *_nonan variants for when you know h1 and h2 are not NaN */
+int npy_half_eq_nonan(npy_half h1, npy_half h2);
+int npy_half_lt_nonan(npy_half h1, npy_half h2);
+int npy_half_le_nonan(npy_half h1, npy_half h2);
+/* Miscellaneous functions */
+int npy_half_iszero(npy_half h);
+int npy_half_isnan(npy_half h);
+int npy_half_isinf(npy_half h);
+int npy_half_isfinite(npy_half h);
+int npy_half_signbit(npy_half h);
+npy_half npy_half_copysign(npy_half x, npy_half y);
+npy_half npy_half_spacing(npy_half h);
+npy_half npy_half_nextafter(npy_half x, npy_half y);
+npy_half npy_half_divmod(npy_half x, npy_half y, npy_half *modulus);
+
+/*
+ * Half-precision constants
+ */
+
+#define NPY_HALF_ZERO   (0x0000u)
+#define NPY_HALF_PZERO  (0x0000u)
+#define NPY_HALF_NZERO  (0x8000u)
+#define NPY_HALF_ONE    (0x3c00u)
+#define NPY_HALF_NEGONE (0xbc00u)
+#define NPY_HALF_PINF   (0x7c00u)
+#define NPY_HALF_NINF   (0xfc00u)
+#define NPY_HALF_NAN    (0x7e00u)
+
+#define NPY_MAX_HALF    (0x7bffu)
+
+/*
+ * Bit-level conversions
+ */
+
+npy_uint16 npy_floatbits_to_halfbits(npy_uint32 f);
+npy_uint16 npy_doublebits_to_halfbits(npy_uint64 d);
+npy_uint32 npy_halfbits_to_floatbits(npy_uint16 h);
+npy_uint64 npy_halfbits_to_doublebits(npy_uint16 h);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/multiarray_api.txt b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/multiarray_api.txt
new file mode 100644
index 0000000..7c45394
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/multiarray_api.txt
@@ -0,0 +1,2501 @@
+
+===========
+NumPy C-API
+===========
+::
+
+  unsigned int
+  PyArray_GetNDArrayCVersion(void )
+
+
+Included at the very first so not auto-grabbed and thus not labeled.
+
+::
+
+  int
+  PyArray_SetNumericOps(PyObject *dict)
+
+Set internal structure with number functions that all arrays will use
+
+::
+
+  PyObject *
+  PyArray_GetNumericOps(void )
+
+Get dictionary showing number functions that all arrays will use
+
+::
+
+  int
+  PyArray_INCREF(PyArrayObject *mp)
+
+For object arrays, increment all internal references.
+
+::
+
+  int
+  PyArray_XDECREF(PyArrayObject *mp)
+
+Decrement all internal references for object arrays.
+(or arrays with object fields)
+
+::
+
+  void
+  PyArray_SetStringFunction(PyObject *op, int repr)
+
+Set the array print function to be a Python function.
+
+::
+
+  PyArray_Descr *
+  PyArray_DescrFromType(int type)
+
+Get the PyArray_Descr structure for a type.
+
+::
+
+  PyObject *
+  PyArray_TypeObjectFromType(int type)
+
+Get a typeobject from a type-number -- can return NULL.
+
+New reference
+
+::
+
+  char *
+  PyArray_Zero(PyArrayObject *arr)
+
+Get pointer to zero of correct type for array.
+
+::
+
+  char *
+  PyArray_One(PyArrayObject *arr)
+
+Get pointer to one of correct type for array
+
+::
+
+  PyObject *
+  PyArray_CastToType(PyArrayObject *arr, PyArray_Descr *dtype, int
+                     is_f_order)
+
+For backward compatibility
+
+Cast an array using typecode structure.
+steals reference to dtype --- cannot be NULL
+
+This function always makes a copy of arr, even if the dtype
+doesn't change.
+
+::
+
+  int
+  PyArray_CastTo(PyArrayObject *out, PyArrayObject *mp)
+
+Cast to an already created array.
+
+::
+
+  int
+  PyArray_CastAnyTo(PyArrayObject *out, PyArrayObject *mp)
+
+Cast to an already created array.  Arrays don't have to be "broadcastable"
+Only requirement is they have the same number of elements.
+
+::
+
+  int
+  PyArray_CanCastSafely(int fromtype, int totype)
+
+Check the type coercion rules.
+
+::
+
+  npy_bool
+  PyArray_CanCastTo(PyArray_Descr *from, PyArray_Descr *to)
+
+leaves reference count alone --- cannot be NULL
+
+PyArray_CanCastTypeTo is equivalent to this, but adds a 'casting'
+parameter.
+
+::
+
+  int
+  PyArray_ObjectType(PyObject *op, int minimum_type)
+
+Return the typecode of the array a Python object would be converted to
+
+Returns the type number the result should have, or NPY_NOTYPE on error.
+
+::
+
+  PyArray_Descr *
+  PyArray_DescrFromObject(PyObject *op, PyArray_Descr *mintype)
+
+new reference -- accepts NULL for mintype
+
+::
+
+  PyArrayObject **
+  PyArray_ConvertToCommonType(PyObject *op, int *retn)
+
+
+::
+
+  PyArray_Descr *
+  PyArray_DescrFromScalar(PyObject *sc)
+
+Return descr object from array scalar.
+
+New reference
+
+::
+
+  PyArray_Descr *
+  PyArray_DescrFromTypeObject(PyObject *type)
+
+
+::
+
+  npy_intp
+  PyArray_Size(PyObject *op)
+
+Compute the size of an array (in number of items)
+
+::
+
+  PyObject *
+  PyArray_Scalar(void *data, PyArray_Descr *descr, PyObject *base)
+
+Get scalar-equivalent to a region of memory described by a descriptor.
+
+::
+
+  PyObject *
+  PyArray_FromScalar(PyObject *scalar, PyArray_Descr *outcode)
+
+Get 0-dim array from scalar
+
+0-dim array from array-scalar object
+always contains a copy of the data
+unless outcode is NULL, it is of void type and the referrer does
+not own it either.
+
+steals reference to outcode
+
+::
+
+  void
+  PyArray_ScalarAsCtype(PyObject *scalar, void *ctypeptr)
+
+Convert to c-type
+
+no error checking is performed -- ctypeptr must be same type as scalar
+in case of flexible type, the data is not copied
+into ctypeptr which is expected to be a pointer to pointer
+
+::
+
+  int
+  PyArray_CastScalarToCtype(PyObject *scalar, void
+                            *ctypeptr, PyArray_Descr *outcode)
+
+Cast Scalar to c-type
+
+The output buffer must be large-enough to receive the value
+Even for flexible types which is different from ScalarAsCtype
+where only a reference for flexible types is returned
+
+This may not work right on narrow builds for NumPy unicode scalars.
+
+::
+
+  int
+  PyArray_CastScalarDirect(PyObject *scalar, PyArray_Descr
+                           *indescr, void *ctypeptr, int outtype)
+
+Cast Scalar to c-type
+
+::
+
+  PyObject *
+  PyArray_ScalarFromObject(PyObject *object)
+
+Get an Array Scalar From a Python Object
+
+Returns NULL if unsuccessful but error is only set if another error occurred.
+Currently only Numeric-like object supported.
+
+::
+
+  PyArray_VectorUnaryFunc *
+  PyArray_GetCastFunc(PyArray_Descr *descr, int type_num)
+
+Get a cast function to cast from the input descriptor to the
+output type_number (must be a registered data-type).
+Returns NULL if un-successful.
+
+::
+
+  PyObject *
+  PyArray_FromDims(int nd, int *d, int type)
+
+Construct an empty array from dimensions and typenum
+
+::
+
+  PyObject *
+  PyArray_FromDimsAndDataAndDescr(int nd, int *d, PyArray_Descr
+                                  *descr, char *data)
+
+Like FromDimsAndData but uses the Descr structure instead of typecode
+as input.
+
+::
+
+  PyObject *
+  PyArray_FromAny(PyObject *op, PyArray_Descr *newtype, int
+                  min_depth, int max_depth, int flags, PyObject
+                  *context)
+
+Does not check for NPY_ARRAY_ENSURECOPY and NPY_ARRAY_NOTSWAPPED in flags
+Steals a reference to newtype --- which can be NULL
+
+::
+
+  PyObject *
+  PyArray_EnsureArray(PyObject *op)
+
+This is a quick wrapper around
+PyArray_FromAny(op, NULL, 0, 0, NPY_ARRAY_ENSUREARRAY, NULL)
+that special cases Arrays and PyArray_Scalars up front
+It *steals a reference* to the object
+It also guarantees that the result is PyArray_Type
+Because it decrefs op if any conversion needs to take place
+so it can be used like PyArray_EnsureArray(some_function(...))
+
+::
+
+  PyObject *
+  PyArray_EnsureAnyArray(PyObject *op)
+
+
+::
+
+  PyObject *
+  PyArray_FromFile(FILE *fp, PyArray_Descr *dtype, npy_intp num, char
+                   *sep)
+
+
+Given a ``FILE *`` pointer ``fp``, and a ``PyArray_Descr``, return an
+array corresponding to the data encoded in that file.
+
+If the dtype is NULL, the default array type is used (double).
+If non-null, the reference is stolen and if dtype->subarray is true dtype
+will be decrefed even on success.
+
+The number of elements to read is given as ``num``; if it is < 0, then
+then as many as possible are read.
+
+If ``sep`` is NULL or empty, then binary data is assumed, else
+text data, with ``sep`` as the separator between elements. Whitespace in
+the separator matches any length of whitespace in the text, and a match
+for whitespace around the separator is added.
+
+For memory-mapped files, use the buffer interface. No more data than
+necessary is read by this routine.
+
+::
+
+  PyObject *
+  PyArray_FromString(char *data, npy_intp slen, PyArray_Descr
+                     *dtype, npy_intp num, char *sep)
+
+
+Given a pointer to a string ``data``, a string length ``slen``, and
+a ``PyArray_Descr``, return an array corresponding to the data
+encoded in that string.
+
+If the dtype is NULL, the default array type is used (double).
+If non-null, the reference is stolen.
+
+If ``slen`` is < 0, then the end of string is used for text data.
+It is an error for ``slen`` to be < 0 for binary data (since embedded NULLs
+would be the norm).
+
+The number of elements to read is given as ``num``; if it is < 0, then
+then as many as possible are read.
+
+If ``sep`` is NULL or empty, then binary data is assumed, else
+text data, with ``sep`` as the separator between elements. Whitespace in
+the separator matches any length of whitespace in the text, and a match
+for whitespace around the separator is added.
+
+::
+
+  PyObject *
+  PyArray_FromBuffer(PyObject *buf, PyArray_Descr *type, npy_intp
+                     count, npy_intp offset)
+
+
+::
+
+  PyObject *
+  PyArray_FromIter(PyObject *obj, PyArray_Descr *dtype, npy_intp count)
+
+
+steals a reference to dtype (which cannot be NULL)
+
+::
+
+  PyObject *
+  PyArray_Return(PyArrayObject *mp)
+
+
+Return either an array or the appropriate Python object if the array
+is 0d and matches a Python type.
+steals reference to mp
+
+::
+
+  PyObject *
+  PyArray_GetField(PyArrayObject *self, PyArray_Descr *typed, int
+                   offset)
+
+Get a subset of bytes from each element of the array
+steals reference to typed, must not be NULL
+
+::
+
+  int
+  PyArray_SetField(PyArrayObject *self, PyArray_Descr *dtype, int
+                   offset, PyObject *val)
+
+Set a subset of bytes from each element of the array
+steals reference to dtype, must not be NULL
+
+::
+
+  PyObject *
+  PyArray_Byteswap(PyArrayObject *self, npy_bool inplace)
+
+
+::
+
+  PyObject *
+  PyArray_Resize(PyArrayObject *self, PyArray_Dims *newshape, int
+                 refcheck, NPY_ORDER order)
+
+Resize (reallocate data).  Only works if nothing else is referencing this
+array and it is contiguous.  If refcheck is 0, then the reference count is
+not checked and assumed to be 1.  You still must own this data and have no
+weak-references and no base object.
+
+::
+
+  int
+  PyArray_MoveInto(PyArrayObject *dst, PyArrayObject *src)
+
+Move the memory of one array into another, allowing for overlapping data.
+
+Returns 0 on success, negative on failure.
+
+::
+
+  int
+  PyArray_CopyInto(PyArrayObject *dst, PyArrayObject *src)
+
+Copy an Array into another array.
+Broadcast to the destination shape if necessary.
+
+Returns 0 on success, -1 on failure.
+
+::
+
+  int
+  PyArray_CopyAnyInto(PyArrayObject *dst, PyArrayObject *src)
+
+Copy an Array into another array -- memory must not overlap
+Does not require src and dest to have "broadcastable" shapes
+(only the same number of elements).
+
+TODO: For NumPy 2.0, this could accept an order parameter which
+only allows NPY_CORDER and NPY_FORDER.  Could also rename
+this to CopyAsFlat to make the name more intuitive.
+
+Returns 0 on success, -1 on error.
+
+::
+
+  int
+  PyArray_CopyObject(PyArrayObject *dest, PyObject *src_object)
+
+
+::
+
+  PyObject *
+  PyArray_NewCopy(PyArrayObject *obj, NPY_ORDER order)
+
+Copy an array.
+
+::
+
+  PyObject *
+  PyArray_ToList(PyArrayObject *self)
+
+To List
+
+::
+
+  PyObject *
+  PyArray_ToString(PyArrayObject *self, NPY_ORDER order)
+
+
+::
+
+  int
+  PyArray_ToFile(PyArrayObject *self, FILE *fp, char *sep, char *format)
+
+To File
+
+::
+
+  int
+  PyArray_Dump(PyObject *self, PyObject *file, int protocol)
+
+
+::
+
+  PyObject *
+  PyArray_Dumps(PyObject *self, int protocol)
+
+
+::
+
+  int
+  PyArray_ValidType(int type)
+
+Is the typenum valid?
+
+::
+
+  void
+  PyArray_UpdateFlags(PyArrayObject *ret, int flagmask)
+
+Update Several Flags at once.
+
+::
+
+  PyObject *
+  PyArray_New(PyTypeObject *subtype, int nd, npy_intp *dims, int
+              type_num, npy_intp *strides, void *data, int itemsize, int
+              flags, PyObject *obj)
+
+Generic new array creation routine.
+
+::
+
+  PyObject *
+  PyArray_NewFromDescr(PyTypeObject *subtype, PyArray_Descr *descr, int
+                       nd, npy_intp *dims, npy_intp *strides, void
+                       *data, int flags, PyObject *obj)
+
+Generic new array creation routine.
+
+steals a reference to descr. On failure or when dtype->subarray is
+true, dtype will be decrefed.
+
+::
+
+  PyArray_Descr *
+  PyArray_DescrNew(PyArray_Descr *base)
+
+base cannot be NULL
+
+::
+
+  PyArray_Descr *
+  PyArray_DescrNewFromType(int type_num)
+
+
+::
+
+  double
+  PyArray_GetPriority(PyObject *obj, double default_)
+
+Get Priority from object
+
+::
+
+  PyObject *
+  PyArray_IterNew(PyObject *obj)
+
+Get Iterator.
+
+::
+
+  PyObject *
+  PyArray_MultiIterNew(int n, ... )
+
+Get MultiIterator,
+
+::
+
+  int
+  PyArray_PyIntAsInt(PyObject *o)
+
+
+::
+
+  npy_intp
+  PyArray_PyIntAsIntp(PyObject *o)
+
+
+::
+
+  int
+  PyArray_Broadcast(PyArrayMultiIterObject *mit)
+
+
+::
+
+  void
+  PyArray_FillObjectArray(PyArrayObject *arr, PyObject *obj)
+
+Assumes contiguous
+
+::
+
+  int
+  PyArray_FillWithScalar(PyArrayObject *arr, PyObject *obj)
+
+
+::
+
+  npy_bool
+  PyArray_CheckStrides(int elsize, int nd, npy_intp numbytes, npy_intp
+                       offset, npy_intp *dims, npy_intp *newstrides)
+
+
+::
+
+  PyArray_Descr *
+  PyArray_DescrNewByteorder(PyArray_Descr *self, char newendian)
+
+
+returns a copy of the PyArray_Descr structure with the byteorder
+altered:
+no arguments:  The byteorder is swapped (in all subfields as well)
+single argument:  The byteorder is forced to the given state
+(in all subfields as well)
+
+Valid states:  ('big', '>') or ('little' or '<')
+('native', or '=')
+
+If a descr structure with | is encountered it's own
+byte-order is not changed but any fields are:
+
+
+Deep bytorder change of a data-type descriptor
+Leaves reference count of self unchanged --- does not DECREF self ***
+
+::
+
+  PyObject *
+  PyArray_IterAllButAxis(PyObject *obj, int *inaxis)
+
+Get Iterator that iterates over all but one axis (don't use this with
+PyArray_ITER_GOTO1D).  The axis will be over-written if negative
+with the axis having the smallest stride.
+
+::
+
+  PyObject *
+  PyArray_CheckFromAny(PyObject *op, PyArray_Descr *descr, int
+                       min_depth, int max_depth, int requires, PyObject
+                       *context)
+
+steals a reference to descr -- accepts NULL
+
+::
+
+  PyObject *
+  PyArray_FromArray(PyArrayObject *arr, PyArray_Descr *newtype, int
+                    flags)
+
+steals reference to newtype --- acc. NULL
+
+::
+
+  PyObject *
+  PyArray_FromInterface(PyObject *origin)
+
+
+::
+
+  PyObject *
+  PyArray_FromStructInterface(PyObject *input)
+
+
+::
+
+  PyObject *
+  PyArray_FromArrayAttr(PyObject *op, PyArray_Descr *typecode, PyObject
+                        *context)
+
+
+::
+
+  NPY_SCALARKIND
+  PyArray_ScalarKind(int typenum, PyArrayObject **arr)
+
+ScalarKind
+
+Returns the scalar kind of a type number, with an
+optional tweak based on the scalar value itself.
+If no scalar is provided, it returns INTPOS_SCALAR
+for both signed and unsigned integers, otherwise
+it checks the sign of any signed integer to choose
+INTNEG_SCALAR when appropriate.
+
+::
+
+  int
+  PyArray_CanCoerceScalar(int thistype, int neededtype, NPY_SCALARKIND
+                          scalar)
+
+
+Determines whether the data type 'thistype', with
+scalar kind 'scalar', can be coerced into 'neededtype'.
+
+::
+
+  PyObject *
+  PyArray_NewFlagsObject(PyObject *obj)
+
+
+Get New ArrayFlagsObject
+
+::
+
+  npy_bool
+  PyArray_CanCastScalar(PyTypeObject *from, PyTypeObject *to)
+
+See if array scalars can be cast.
+
+TODO: For NumPy 2.0, add a NPY_CASTING parameter.
+
+::
+
+  int
+  PyArray_CompareUCS4(npy_ucs4 *s1, npy_ucs4 *s2, size_t len)
+
+
+::
+
+  int
+  PyArray_RemoveSmallest(PyArrayMultiIterObject *multi)
+
+Adjusts previously broadcasted iterators so that the axis with
+the smallest sum of iterator strides is not iterated over.
+Returns dimension which is smallest in the range [0,multi->nd).
+A -1 is returned if multi->nd == 0.
+
+don't use with PyArray_ITER_GOTO1D because factors are not adjusted
+
+::
+
+  int
+  PyArray_ElementStrides(PyObject *obj)
+
+
+::
+
+  void
+  PyArray_Item_INCREF(char *data, PyArray_Descr *descr)
+
+XINCREF all objects in a single array item. This is complicated for
+structured datatypes where the position of objects needs to be extracted.
+The function is execute recursively for each nested field or subarrays dtype
+such as as `np.dtype([("field1", "O"), ("field2", "f,O", (3,2))])`
+
+::
+
+  void
+  PyArray_Item_XDECREF(char *data, PyArray_Descr *descr)
+
+
+XDECREF all objects in a single array item. This is complicated for
+structured datatypes where the position of objects needs to be extracted.
+The function is execute recursively for each nested field or subarrays dtype
+such as as `np.dtype([("field1", "O"), ("field2", "f,O", (3,2))])`
+
+::
+
+  PyObject *
+  PyArray_FieldNames(PyObject *fields)
+
+Return the tuple of ordered field names from a dictionary.
+
+::
+
+  PyObject *
+  PyArray_Transpose(PyArrayObject *ap, PyArray_Dims *permute)
+
+Return Transpose.
+
+::
+
+  PyObject *
+  PyArray_TakeFrom(PyArrayObject *self0, PyObject *indices0, int
+                   axis, PyArrayObject *out, NPY_CLIPMODE clipmode)
+
+Take
+
+::
+
+  PyObject *
+  PyArray_PutTo(PyArrayObject *self, PyObject*values0, PyObject
+                *indices0, NPY_CLIPMODE clipmode)
+
+Put values into an array
+
+::
+
+  PyObject *
+  PyArray_PutMask(PyArrayObject *self, PyObject*values0, PyObject*mask0)
+
+Put values into an array according to a mask.
+
+::
+
+  PyObject *
+  PyArray_Repeat(PyArrayObject *aop, PyObject *op, int axis)
+
+Repeat the array.
+
+::
+
+  PyObject *
+  PyArray_Choose(PyArrayObject *ip, PyObject *op, PyArrayObject
+                 *out, NPY_CLIPMODE clipmode)
+
+
+::
+
+  int
+  PyArray_Sort(PyArrayObject *op, int axis, NPY_SORTKIND which)
+
+Sort an array in-place
+
+::
+
+  PyObject *
+  PyArray_ArgSort(PyArrayObject *op, int axis, NPY_SORTKIND which)
+
+ArgSort an array
+
+::
+
+  PyObject *
+  PyArray_SearchSorted(PyArrayObject *op1, PyObject *op2, NPY_SEARCHSIDE
+                       side, PyObject *perm)
+
+
+Search the sorted array op1 for the location of the items in op2. The
+result is an array of indexes, one for each element in op2, such that if
+the item were to be inserted in op1 just before that index the array
+would still be in sorted order.
+
+Parameters
+----------
+op1 : PyArrayObject *
+Array to be searched, must be 1-D.
+op2 : PyObject *
+Array of items whose insertion indexes in op1 are wanted
+side : {NPY_SEARCHLEFT, NPY_SEARCHRIGHT}
+If NPY_SEARCHLEFT, return first valid insertion indexes
+If NPY_SEARCHRIGHT, return last valid insertion indexes
+perm : PyObject *
+Permutation array that sorts op1 (optional)
+
+Returns
+-------
+ret : PyObject *
+New reference to npy_intp array containing indexes where items in op2
+could be validly inserted into op1. NULL on error.
+
+Notes
+-----
+Binary search is used to find the indexes.
+
+::
+
+  PyObject *
+  PyArray_ArgMax(PyArrayObject *op, int axis, PyArrayObject *out)
+
+ArgMax
+
+::
+
+  PyObject *
+  PyArray_ArgMin(PyArrayObject *op, int axis, PyArrayObject *out)
+
+ArgMin
+
+::
+
+  PyObject *
+  PyArray_Reshape(PyArrayObject *self, PyObject *shape)
+
+Reshape
+
+::
+
+  PyObject *
+  PyArray_Newshape(PyArrayObject *self, PyArray_Dims *newdims, NPY_ORDER
+                   order)
+
+New shape for an array
+
+::
+
+  PyObject *
+  PyArray_Squeeze(PyArrayObject *self)
+
+
+return a new view of the array object with all of its unit-length
+dimensions squeezed out if needed, otherwise
+return the same array.
+
+::
+
+  PyObject *
+  PyArray_View(PyArrayObject *self, PyArray_Descr *type, PyTypeObject
+               *pytype)
+
+View
+steals a reference to type -- accepts NULL
+
+::
+
+  PyObject *
+  PyArray_SwapAxes(PyArrayObject *ap, int a1, int a2)
+
+SwapAxes
+
+::
+
+  PyObject *
+  PyArray_Max(PyArrayObject *ap, int axis, PyArrayObject *out)
+
+Max
+
+::
+
+  PyObject *
+  PyArray_Min(PyArrayObject *ap, int axis, PyArrayObject *out)
+
+Min
+
+::
+
+  PyObject *
+  PyArray_Ptp(PyArrayObject *ap, int axis, PyArrayObject *out)
+
+Ptp
+
+::
+
+  PyObject *
+  PyArray_Mean(PyArrayObject *self, int axis, int rtype, PyArrayObject
+               *out)
+
+Mean
+
+::
+
+  PyObject *
+  PyArray_Trace(PyArrayObject *self, int offset, int axis1, int
+                axis2, int rtype, PyArrayObject *out)
+
+Trace
+
+::
+
+  PyObject *
+  PyArray_Diagonal(PyArrayObject *self, int offset, int axis1, int
+                   axis2)
+
+Diagonal
+
+In NumPy versions prior to 1.7,  this function always returned a copy of
+the diagonal array. In 1.7, the code has been updated to compute a view
+onto 'self', but it still copies this array before returning, as well as
+setting the internal WARN_ON_WRITE flag. In a future version, it will
+simply return a view onto self.
+
+::
+
+  PyObject *
+  PyArray_Clip(PyArrayObject *self, PyObject *min, PyObject
+               *max, PyArrayObject *out)
+
+Clip
+
+::
+
+  PyObject *
+  PyArray_Conjugate(PyArrayObject *self, PyArrayObject *out)
+
+Conjugate
+
+::
+
+  PyObject *
+  PyArray_Nonzero(PyArrayObject *self)
+
+Nonzero
+
+TODO: In NumPy 2.0, should make the iteration order a parameter.
+
+::
+
+  PyObject *
+  PyArray_Std(PyArrayObject *self, int axis, int rtype, PyArrayObject
+              *out, int variance)
+
+Set variance to 1 to by-pass square-root calculation and return variance
+Std
+
+::
+
+  PyObject *
+  PyArray_Sum(PyArrayObject *self, int axis, int rtype, PyArrayObject
+              *out)
+
+Sum
+
+::
+
+  PyObject *
+  PyArray_CumSum(PyArrayObject *self, int axis, int rtype, PyArrayObject
+                 *out)
+
+CumSum
+
+::
+
+  PyObject *
+  PyArray_Prod(PyArrayObject *self, int axis, int rtype, PyArrayObject
+               *out)
+
+Prod
+
+::
+
+  PyObject *
+  PyArray_CumProd(PyArrayObject *self, int axis, int
+                  rtype, PyArrayObject *out)
+
+CumProd
+
+::
+
+  PyObject *
+  PyArray_All(PyArrayObject *self, int axis, PyArrayObject *out)
+
+All
+
+::
+
+  PyObject *
+  PyArray_Any(PyArrayObject *self, int axis, PyArrayObject *out)
+
+Any
+
+::
+
+  PyObject *
+  PyArray_Compress(PyArrayObject *self, PyObject *condition, int
+                   axis, PyArrayObject *out)
+
+Compress
+
+::
+
+  PyObject *
+  PyArray_Flatten(PyArrayObject *a, NPY_ORDER order)
+
+Flatten
+
+::
+
+  PyObject *
+  PyArray_Ravel(PyArrayObject *arr, NPY_ORDER order)
+
+Ravel
+Returns a contiguous array
+
+::
+
+  npy_intp
+  PyArray_MultiplyList(npy_intp *l1, int n)
+
+Multiply a List
+
+::
+
+  int
+  PyArray_MultiplyIntList(int *l1, int n)
+
+Multiply a List of ints
+
+::
+
+  void *
+  PyArray_GetPtr(PyArrayObject *obj, npy_intp*ind)
+
+Produce a pointer into array
+
+::
+
+  int
+  PyArray_CompareLists(npy_intp *l1, npy_intp *l2, int n)
+
+Compare Lists
+
+::
+
+  int
+  PyArray_AsCArray(PyObject **op, void *ptr, npy_intp *dims, int
+                   nd, PyArray_Descr*typedescr)
+
+Simulate a C-array
+steals a reference to typedescr -- can be NULL
+
+::
+
+  int
+  PyArray_As1D(PyObject **op, char **ptr, int *d1, int typecode)
+
+Convert to a 1D C-array
+
+::
+
+  int
+  PyArray_As2D(PyObject **op, char ***ptr, int *d1, int *d2, int
+               typecode)
+
+Convert to a 2D C-array
+
+::
+
+  int
+  PyArray_Free(PyObject *op, void *ptr)
+
+Free pointers created if As2D is called
+
+::
+
+  int
+  PyArray_Converter(PyObject *object, PyObject **address)
+
+
+Useful to pass as converter function for O& processing in PyArgs_ParseTuple.
+
+This conversion function can be used with the "O&" argument for
+PyArg_ParseTuple.  It will immediately return an object of array type
+or will convert to a NPY_ARRAY_CARRAY any other object.
+
+If you use PyArray_Converter, you must DECREF the array when finished
+as you get a new reference to it.
+
+::
+
+  int
+  PyArray_IntpFromSequence(PyObject *seq, npy_intp *vals, int maxvals)
+
+PyArray_IntpFromSequence
+Returns the number of integers converted or -1 if an error occurred.
+vals must be large enough to hold maxvals
+
+::
+
+  PyObject *
+  PyArray_Concatenate(PyObject *op, int axis)
+
+Concatenate
+
+Concatenate an arbitrary Python sequence into an array.
+op is a python object supporting the sequence interface.
+Its elements will be concatenated together to form a single
+multidimensional array. If axis is NPY_MAXDIMS or bigger, then
+each sequence object will be flattened before concatenation
+
+::
+
+  PyObject *
+  PyArray_InnerProduct(PyObject *op1, PyObject *op2)
+
+Numeric.innerproduct(a,v)
+
+::
+
+  PyObject *
+  PyArray_MatrixProduct(PyObject *op1, PyObject *op2)
+
+Numeric.matrixproduct(a,v)
+just like inner product but does the swapaxes stuff on the fly
+
+::
+
+  PyObject *
+  PyArray_CopyAndTranspose(PyObject *op)
+
+Copy and Transpose
+
+Could deprecate this function, as there isn't a speed benefit over
+calling Transpose and then Copy.
+
+::
+
+  PyObject *
+  PyArray_Correlate(PyObject *op1, PyObject *op2, int mode)
+
+Numeric.correlate(a1,a2,mode)
+
+::
+
+  int
+  PyArray_TypestrConvert(int itemsize, int gentype)
+
+Typestr converter
+
+::
+
+  int
+  PyArray_DescrConverter(PyObject *obj, PyArray_Descr **at)
+
+Get typenum from an object -- None goes to NPY_DEFAULT_TYPE
+This function takes a Python object representing a type and converts it
+to a the correct PyArray_Descr * structure to describe the type.
+
+Many objects can be used to represent a data-type which in NumPy is
+quite a flexible concept.
+
+This is the central code that converts Python objects to
+Type-descriptor objects that are used throughout numpy.
+
+Returns a new reference in *at, but the returned should not be
+modified as it may be one of the canonical immutable objects or
+a reference to the input obj.
+
+::
+
+  int
+  PyArray_DescrConverter2(PyObject *obj, PyArray_Descr **at)
+
+Get typenum from an object -- None goes to NULL
+
+::
+
+  int
+  PyArray_IntpConverter(PyObject *obj, PyArray_Dims *seq)
+
+Get intp chunk from sequence
+
+This function takes a Python sequence object and allocates and
+fills in an intp array with the converted values.
+
+Remember to free the pointer seq.ptr when done using
+PyDimMem_FREE(seq.ptr)**
+
+::
+
+  int
+  PyArray_BufferConverter(PyObject *obj, PyArray_Chunk *buf)
+
+Get buffer chunk from object
+
+this function takes a Python object which exposes the (single-segment)
+buffer interface and returns a pointer to the data segment
+
+You should increment the reference count by one of buf->base
+if you will hang on to a reference
+
+You only get a borrowed reference to the object. Do not free the
+memory...
+
+::
+
+  int
+  PyArray_AxisConverter(PyObject *obj, int *axis)
+
+Get axis from an object (possibly None) -- a converter function,
+
+See also PyArray_ConvertMultiAxis, which also handles a tuple of axes.
+
+::
+
+  int
+  PyArray_BoolConverter(PyObject *object, npy_bool *val)
+
+Convert an object to true / false
+
+::
+
+  int
+  PyArray_ByteorderConverter(PyObject *obj, char *endian)
+
+Convert object to endian
+
+::
+
+  int
+  PyArray_OrderConverter(PyObject *object, NPY_ORDER *val)
+
+Convert an object to FORTRAN / C / ANY / KEEP
+
+::
+
+  unsigned char
+  PyArray_EquivTypes(PyArray_Descr *type1, PyArray_Descr *type2)
+
+
+This function returns true if the two typecodes are
+equivalent (same basic kind and same itemsize).
+
+::
+
+  PyObject *
+  PyArray_Zeros(int nd, npy_intp *dims, PyArray_Descr *type, int
+                is_f_order)
+
+Zeros
+
+steals a reference to type. On failure or when dtype->subarray is
+true, dtype will be decrefed.
+accepts NULL type
+
+::
+
+  PyObject *
+  PyArray_Empty(int nd, npy_intp *dims, PyArray_Descr *type, int
+                is_f_order)
+
+Empty
+
+accepts NULL type
+steals referenct to type
+
+::
+
+  PyObject *
+  PyArray_Where(PyObject *condition, PyObject *x, PyObject *y)
+
+Where
+
+::
+
+  PyObject *
+  PyArray_Arange(double start, double stop, double step, int type_num)
+
+Arange,
+
+::
+
+  PyObject *
+  PyArray_ArangeObj(PyObject *start, PyObject *stop, PyObject
+                    *step, PyArray_Descr *dtype)
+
+
+ArangeObj,
+
+this doesn't change the references
+
+::
+
+  int
+  PyArray_SortkindConverter(PyObject *obj, NPY_SORTKIND *sortkind)
+
+Convert object to sort kind
+
+::
+
+  PyObject *
+  PyArray_LexSort(PyObject *sort_keys, int axis)
+
+LexSort an array providing indices that will sort a collection of arrays
+lexicographically.  The first key is sorted on first, followed by the second key
+-- requires that arg"merge"sort is available for each sort_key
+
+Returns an index array that shows the indexes for the lexicographic sort along
+the given axis.
+
+::
+
+  PyObject *
+  PyArray_Round(PyArrayObject *a, int decimals, PyArrayObject *out)
+
+Round
+
+::
+
+  unsigned char
+  PyArray_EquivTypenums(int typenum1, int typenum2)
+
+
+::
+
+  int
+  PyArray_RegisterDataType(PyArray_Descr *descr)
+
+Register Data type
+Does not change the reference count of descr
+
+::
+
+  int
+  PyArray_RegisterCastFunc(PyArray_Descr *descr, int
+                           totype, PyArray_VectorUnaryFunc *castfunc)
+
+Register Casting Function
+Replaces any function currently stored.
+
+::
+
+  int
+  PyArray_RegisterCanCast(PyArray_Descr *descr, int
+                          totype, NPY_SCALARKIND scalar)
+
+Register a type number indicating that a descriptor can be cast
+to it safely
+
+::
+
+  void
+  PyArray_InitArrFuncs(PyArray_ArrFuncs *f)
+
+Initialize arrfuncs to NULL
+
+::
+
+  PyObject *
+  PyArray_IntTupleFromIntp(int len, npy_intp *vals)
+
+PyArray_IntTupleFromIntp
+
+::
+
+  int
+  PyArray_TypeNumFromName(char *str)
+
+
+::
+
+  int
+  PyArray_ClipmodeConverter(PyObject *object, NPY_CLIPMODE *val)
+
+Convert an object to NPY_RAISE / NPY_CLIP / NPY_WRAP
+
+::
+
+  int
+  PyArray_OutputConverter(PyObject *object, PyArrayObject **address)
+
+Useful to pass as converter function for O& processing in
+PyArgs_ParseTuple for output arrays
+
+::
+
+  PyObject *
+  PyArray_BroadcastToShape(PyObject *obj, npy_intp *dims, int nd)
+
+Get Iterator broadcast to a particular shape
+
+::
+
+  void
+  _PyArray_SigintHandler(int signum)
+
+
+::
+
+  void*
+  _PyArray_GetSigintBuf(void )
+
+
+::
+
+  int
+  PyArray_DescrAlignConverter(PyObject *obj, PyArray_Descr **at)
+
+
+Get type-descriptor from an object forcing alignment if possible
+None goes to DEFAULT type.
+
+any object with the .fields attribute and/or .itemsize attribute (if the
+.fields attribute does not give the total size -- i.e. a partial record
+naming).  If itemsize is given it must be >= size computed from fields
+
+The .fields attribute must return a convertible dictionary if present.
+Result inherits from NPY_VOID.
+
+::
+
+  int
+  PyArray_DescrAlignConverter2(PyObject *obj, PyArray_Descr **at)
+
+
+Get type-descriptor from an object forcing alignment if possible
+None goes to NULL.
+
+::
+
+  int
+  PyArray_SearchsideConverter(PyObject *obj, void *addr)
+
+Convert object to searchsorted side
+
+::
+
+  PyObject *
+  PyArray_CheckAxis(PyArrayObject *arr, int *axis, int flags)
+
+PyArray_CheckAxis
+
+check that axis is valid
+convert 0-d arrays to 1-d arrays
+
+::
+
+  npy_intp
+  PyArray_OverflowMultiplyList(npy_intp *l1, int n)
+
+Multiply a List of Non-negative numbers with over-flow detection.
+
+::
+
+  int
+  PyArray_CompareString(char *s1, char *s2, size_t len)
+
+
+::
+
+  PyObject *
+  PyArray_MultiIterFromObjects(PyObject **mps, int n, int nadd, ... )
+
+Get MultiIterator from array of Python objects and any additional
+
+PyObject **mps -- array of PyObjects
+int n - number of PyObjects in the array
+int nadd - number of additional arrays to include in the iterator.
+
+Returns a multi-iterator object.
+
+::
+
+  int
+  PyArray_GetEndianness(void )
+
+
+::
+
+  unsigned int
+  PyArray_GetNDArrayCFeatureVersion(void )
+
+Returns the built-in (at compilation time) C API version
+
+::
+
+  PyObject *
+  PyArray_Correlate2(PyObject *op1, PyObject *op2, int mode)
+
+correlate(a1,a2,mode)
+
+This function computes the usual correlation (correlate(a1, a2) !=
+correlate(a2, a1), and conjugate the second argument for complex inputs
+
+::
+
+  PyObject*
+  PyArray_NeighborhoodIterNew(PyArrayIterObject *x, npy_intp
+                              *bounds, int mode, PyArrayObject*fill)
+
+A Neighborhood Iterator object.
+
+::
+
+  void
+  PyArray_SetDatetimeParseFunction(PyObject *op)
+
+This function is scheduled to be removed
+
+TO BE REMOVED - NOT USED INTERNALLY.
+
+::
+
+  void
+  PyArray_DatetimeToDatetimeStruct(npy_datetime val, NPY_DATETIMEUNIT
+                                   fr, npy_datetimestruct *result)
+
+Fill the datetime struct from the value and resolution unit.
+
+TO BE REMOVED - NOT USED INTERNALLY.
+
+::
+
+  void
+  PyArray_TimedeltaToTimedeltaStruct(npy_timedelta val, NPY_DATETIMEUNIT
+                                     fr, npy_timedeltastruct *result)
+
+Fill the timedelta struct from the timedelta value and resolution unit.
+
+TO BE REMOVED - NOT USED INTERNALLY.
+
+::
+
+  npy_datetime
+  PyArray_DatetimeStructToDatetime(NPY_DATETIMEUNIT
+                                   fr, npy_datetimestruct *d)
+
+Create a datetime value from a filled datetime struct and resolution unit.
+
+TO BE REMOVED - NOT USED INTERNALLY.
+
+::
+
+  npy_datetime
+  PyArray_TimedeltaStructToTimedelta(NPY_DATETIMEUNIT
+                                     fr, npy_timedeltastruct *d)
+
+Create a timdelta value from a filled timedelta struct and resolution unit.
+
+TO BE REMOVED - NOT USED INTERNALLY.
+
+::
+
+  NpyIter *
+  NpyIter_New(PyArrayObject *op, npy_uint32 flags, NPY_ORDER
+              order, NPY_CASTING casting, PyArray_Descr*dtype)
+
+Allocate a new iterator for one array object.
+
+::
+
+  NpyIter *
+  NpyIter_MultiNew(int nop, PyArrayObject **op_in, npy_uint32
+                   flags, NPY_ORDER order, NPY_CASTING
+                   casting, npy_uint32 *op_flags, PyArray_Descr
+                   **op_request_dtypes)
+
+Allocate a new iterator for more than one array object, using
+standard NumPy broadcasting rules and the default buffer size.
+
+::
+
+  NpyIter *
+  NpyIter_AdvancedNew(int nop, PyArrayObject **op_in, npy_uint32
+                      flags, NPY_ORDER order, NPY_CASTING
+                      casting, npy_uint32 *op_flags, PyArray_Descr
+                      **op_request_dtypes, int oa_ndim, int
+                      **op_axes, npy_intp *itershape, npy_intp
+                      buffersize)
+
+Allocate a new iterator for multiple array objects, and advanced
+options for controlling the broadcasting, shape, and buffer size.
+
+::
+
+  NpyIter *
+  NpyIter_Copy(NpyIter *iter)
+
+Makes a copy of the iterator
+
+::
+
+  int
+  NpyIter_Deallocate(NpyIter *iter)
+
+Deallocate an iterator
+
+::
+
+  npy_bool
+  NpyIter_HasDelayedBufAlloc(NpyIter *iter)
+
+Whether the buffer allocation is being delayed
+
+::
+
+  npy_bool
+  NpyIter_HasExternalLoop(NpyIter *iter)
+
+Whether the iterator handles the inner loop
+
+::
+
+  int
+  NpyIter_EnableExternalLoop(NpyIter *iter)
+
+Removes the inner loop handling (so HasExternalLoop returns true)
+
+::
+
+  npy_intp *
+  NpyIter_GetInnerStrideArray(NpyIter *iter)
+
+Get the array of strides for the inner loop (when HasExternalLoop is true)
+
+This function may be safely called without holding the Python GIL.
+
+::
+
+  npy_intp *
+  NpyIter_GetInnerLoopSizePtr(NpyIter *iter)
+
+Get a pointer to the size of the inner loop  (when HasExternalLoop is true)
+
+This function may be safely called without holding the Python GIL.
+
+::
+
+  int
+  NpyIter_Reset(NpyIter *iter, char **errmsg)
+
+Resets the iterator to its initial state
+
+If errmsg is non-NULL, it should point to a variable which will
+receive the error message, and no Python exception will be set.
+This is so that the function can be called from code not holding
+the GIL.
+
+::
+
+  int
+  NpyIter_ResetBasePointers(NpyIter *iter, char **baseptrs, char
+                            **errmsg)
+
+Resets the iterator to its initial state, with new base data pointers.
+This function requires great caution.
+
+If errmsg is non-NULL, it should point to a variable which will
+receive the error message, and no Python exception will be set.
+This is so that the function can be called from code not holding
+the GIL.
+
+::
+
+  int
+  NpyIter_ResetToIterIndexRange(NpyIter *iter, npy_intp istart, npy_intp
+                                iend, char **errmsg)
+
+Resets the iterator to a new iterator index range
+
+If errmsg is non-NULL, it should point to a variable which will
+receive the error message, and no Python exception will be set.
+This is so that the function can be called from code not holding
+the GIL.
+
+::
+
+  int
+  NpyIter_GetNDim(NpyIter *iter)
+
+Gets the number of dimensions being iterated
+
+::
+
+  int
+  NpyIter_GetNOp(NpyIter *iter)
+
+Gets the number of operands being iterated
+
+::
+
+  NpyIter_IterNextFunc *
+  NpyIter_GetIterNext(NpyIter *iter, char **errmsg)
+
+Compute the specialized iteration function for an iterator
+
+If errmsg is non-NULL, it should point to a variable which will
+receive the error message, and no Python exception will be set.
+This is so that the function can be called from code not holding
+the GIL.
+
+::
+
+  npy_intp
+  NpyIter_GetIterSize(NpyIter *iter)
+
+Gets the number of elements being iterated
+
+::
+
+  void
+  NpyIter_GetIterIndexRange(NpyIter *iter, npy_intp *istart, npy_intp
+                            *iend)
+
+Gets the range of iteration indices being iterated
+
+::
+
+  npy_intp
+  NpyIter_GetIterIndex(NpyIter *iter)
+
+Gets the current iteration index
+
+::
+
+  int
+  NpyIter_GotoIterIndex(NpyIter *iter, npy_intp iterindex)
+
+Sets the iterator position to the specified iterindex,
+which matches the iteration order of the iterator.
+
+Returns NPY_SUCCEED on success, NPY_FAIL on failure.
+
+::
+
+  npy_bool
+  NpyIter_HasMultiIndex(NpyIter *iter)
+
+Whether the iterator is tracking a multi-index
+
+::
+
+  int
+  NpyIter_GetShape(NpyIter *iter, npy_intp *outshape)
+
+Gets the broadcast shape if a multi-index is being tracked by the iterator,
+otherwise gets the shape of the iteration as Fortran-order
+(fastest-changing index first).
+
+The reason Fortran-order is returned when a multi-index
+is not enabled is that this is providing a direct view into how
+the iterator traverses the n-dimensional space. The iterator organizes
+its memory from fastest index to slowest index, and when
+a multi-index is enabled, it uses a permutation to recover the original
+order.
+
+Returns NPY_SUCCEED or NPY_FAIL.
+
+::
+
+  NpyIter_GetMultiIndexFunc *
+  NpyIter_GetGetMultiIndex(NpyIter *iter, char **errmsg)
+
+Compute a specialized get_multi_index function for the iterator
+
+If errmsg is non-NULL, it should point to a variable which will
+receive the error message, and no Python exception will be set.
+This is so that the function can be called from code not holding
+the GIL.
+
+::
+
+  int
+  NpyIter_GotoMultiIndex(NpyIter *iter, npy_intp *multi_index)
+
+Sets the iterator to the specified multi-index, which must have the
+correct number of entries for 'ndim'.  It is only valid
+when NPY_ITER_MULTI_INDEX was passed to the constructor.  This operation
+fails if the multi-index is out of bounds.
+
+Returns NPY_SUCCEED on success, NPY_FAIL on failure.
+
+::
+
+  int
+  NpyIter_RemoveMultiIndex(NpyIter *iter)
+
+Removes multi-index support from an iterator.
+
+Returns NPY_SUCCEED or NPY_FAIL.
+
+::
+
+  npy_bool
+  NpyIter_HasIndex(NpyIter *iter)
+
+Whether the iterator is tracking an index
+
+::
+
+  npy_bool
+  NpyIter_IsBuffered(NpyIter *iter)
+
+Whether the iterator is buffered
+
+::
+
+  npy_bool
+  NpyIter_IsGrowInner(NpyIter *iter)
+
+Whether the inner loop can grow if buffering is unneeded
+
+::
+
+  npy_intp
+  NpyIter_GetBufferSize(NpyIter *iter)
+
+Gets the size of the buffer, or 0 if buffering is not enabled
+
+::
+
+  npy_intp *
+  NpyIter_GetIndexPtr(NpyIter *iter)
+
+Get a pointer to the index, if it is being tracked
+
+::
+
+  int
+  NpyIter_GotoIndex(NpyIter *iter, npy_intp flat_index)
+
+If the iterator is tracking an index, sets the iterator
+to the specified index.
+
+Returns NPY_SUCCEED on success, NPY_FAIL on failure.
+
+::
+
+  char **
+  NpyIter_GetDataPtrArray(NpyIter *iter)
+
+Get the array of data pointers (1 per object being iterated)
+
+This function may be safely called without holding the Python GIL.
+
+::
+
+  PyArray_Descr **
+  NpyIter_GetDescrArray(NpyIter *iter)
+
+Get the array of data type pointers (1 per object being iterated)
+
+::
+
+  PyArrayObject **
+  NpyIter_GetOperandArray(NpyIter *iter)
+
+Get the array of objects being iterated
+
+::
+
+  PyArrayObject *
+  NpyIter_GetIterView(NpyIter *iter, npy_intp i)
+
+Returns a view to the i-th object with the iterator's internal axes
+
+::
+
+  void
+  NpyIter_GetReadFlags(NpyIter *iter, char *outreadflags)
+
+Gets an array of read flags (1 per object being iterated)
+
+::
+
+  void
+  NpyIter_GetWriteFlags(NpyIter *iter, char *outwriteflags)
+
+Gets an array of write flags (1 per object being iterated)
+
+::
+
+  void
+  NpyIter_DebugPrint(NpyIter *iter)
+
+For debugging
+
+::
+
+  npy_bool
+  NpyIter_IterationNeedsAPI(NpyIter *iter)
+
+Whether the iteration loop, and in particular the iternext()
+function, needs API access.  If this is true, the GIL must
+be retained while iterating.
+
+::
+
+  void
+  NpyIter_GetInnerFixedStrideArray(NpyIter *iter, npy_intp *out_strides)
+
+Get an array of strides which are fixed.  Any strides which may
+change during iteration receive the value NPY_MAX_INTP.  Once
+the iterator is ready to iterate, call this to get the strides
+which will always be fixed in the inner loop, then choose optimized
+inner loop functions which take advantage of those fixed strides.
+
+This function may be safely called without holding the Python GIL.
+
+::
+
+  int
+  NpyIter_RemoveAxis(NpyIter *iter, int axis)
+
+Removes an axis from iteration. This requires that NPY_ITER_MULTI_INDEX
+was set for iterator creation, and does not work if buffering is
+enabled. This function also resets the iterator to its initial state.
+
+Returns NPY_SUCCEED or NPY_FAIL.
+
+::
+
+  npy_intp *
+  NpyIter_GetAxisStrideArray(NpyIter *iter, int axis)
+
+Gets the array of strides for the specified axis.
+If the iterator is tracking a multi-index, gets the strides
+for the axis specified, otherwise gets the strides for
+the iteration axis as Fortran order (fastest-changing axis first).
+
+Returns NULL if an error occurs.
+
+::
+
+  npy_bool
+  NpyIter_RequiresBuffering(NpyIter *iter)
+
+Whether the iteration could be done with no buffering.
+
+::
+
+  char **
+  NpyIter_GetInitialDataPtrArray(NpyIter *iter)
+
+Get the array of data pointers (1 per object being iterated),
+directly into the arrays (never pointing to a buffer), for starting
+unbuffered iteration. This always returns the addresses for the
+iterator position as reset to iterator index 0.
+
+These pointers are different from the pointers accepted by
+NpyIter_ResetBasePointers, because the direction along some
+axes may have been reversed, requiring base offsets.
+
+This function may be safely called without holding the Python GIL.
+
+::
+
+  int
+  NpyIter_CreateCompatibleStrides(NpyIter *iter, npy_intp
+                                  itemsize, npy_intp *outstrides)
+
+Builds a set of strides which are the same as the strides of an
+output array created using the NPY_ITER_ALLOCATE flag, where NULL
+was passed for op_axes.  This is for data packed contiguously,
+but not necessarily in C or Fortran order. This should be used
+together with NpyIter_GetShape and NpyIter_GetNDim.
+
+A use case for this function is to match the shape and layout of
+the iterator and tack on one or more dimensions.  For example,
+in order to generate a vector per input value for a numerical gradient,
+you pass in ndim*itemsize for itemsize, then add another dimension to
+the end with size ndim and stride itemsize.  To do the Hessian matrix,
+you do the same thing but add two dimensions, or take advantage of
+the symmetry and pack it into 1 dimension with a particular encoding.
+
+This function may only be called if the iterator is tracking a multi-index
+and if NPY_ITER_DONT_NEGATE_STRIDES was used to prevent an axis from
+being iterated in reverse order.
+
+If an array is created with this method, simply adding 'itemsize'
+for each iteration will traverse the new array matching the
+iterator.
+
+Returns NPY_SUCCEED or NPY_FAIL.
+
+::
+
+  int
+  PyArray_CastingConverter(PyObject *obj, NPY_CASTING *casting)
+
+Convert any Python object, *obj*, to an NPY_CASTING enum.
+
+::
+
+  npy_intp
+  PyArray_CountNonzero(PyArrayObject *self)
+
+Counts the number of non-zero elements in the array.
+
+Returns -1 on error.
+
+::
+
+  PyArray_Descr *
+  PyArray_PromoteTypes(PyArray_Descr *type1, PyArray_Descr *type2)
+
+Produces the smallest size and lowest kind type to which both
+input types can be cast.
+
+::
+
+  PyArray_Descr *
+  PyArray_MinScalarType(PyArrayObject *arr)
+
+If arr is a scalar (has 0 dimensions) with a built-in number data type,
+finds the smallest type size/kind which can still represent its data.
+Otherwise, returns the array's data type.
+
+
+::
+
+  PyArray_Descr *
+  PyArray_ResultType(npy_intp narrs, PyArrayObject **arr, npy_intp
+                     ndtypes, PyArray_Descr **dtypes)
+
+Produces the result type of a bunch of inputs, using the UFunc
+type promotion rules. Use this function when you have a set of
+input arrays, and need to determine an output array dtype.
+
+If all the inputs are scalars (have 0 dimensions) or the maximum "kind"
+of the scalars is greater than the maximum "kind" of the arrays, does
+a regular type promotion.
+
+Otherwise, does a type promotion on the MinScalarType
+of all the inputs.  Data types passed directly are treated as array
+types.
+
+
+::
+
+  npy_bool
+  PyArray_CanCastArrayTo(PyArrayObject *arr, PyArray_Descr
+                         *to, NPY_CASTING casting)
+
+Returns 1 if the array object may be cast to the given data type using
+the casting rule, 0 otherwise.  This differs from PyArray_CanCastTo in
+that it handles scalar arrays (0 dimensions) specially, by checking
+their value.
+
+::
+
+  npy_bool
+  PyArray_CanCastTypeTo(PyArray_Descr *from, PyArray_Descr
+                        *to, NPY_CASTING casting)
+
+Returns true if data of type 'from' may be cast to data of type
+'to' according to the rule 'casting'.
+
+::
+
+  PyArrayObject *
+  PyArray_EinsteinSum(char *subscripts, npy_intp nop, PyArrayObject
+                      **op_in, PyArray_Descr *dtype, NPY_ORDER
+                      order, NPY_CASTING casting, PyArrayObject *out)
+
+This function provides summation of array elements according to
+the Einstein summation convention.  For example:
+- trace(a)        -> einsum("ii", a)
+- transpose(a)    -> einsum("ji", a)
+- multiply(a,b)   -> einsum(",", a, b)
+- inner(a,b)      -> einsum("i,i", a, b)
+- outer(a,b)      -> einsum("i,j", a, b)
+- matvec(a,b)     -> einsum("ij,j", a, b)
+- matmat(a,b)     -> einsum("ij,jk", a, b)
+
+subscripts: The string of subscripts for einstein summation.
+nop:        The number of operands
+op_in:      The array of operands
+dtype:      Either NULL, or the data type to force the calculation as.
+order:      The order for the calculation/the output axes.
+casting:    What kind of casts should be permitted.
+out:        Either NULL, or an array into which the output should be placed.
+
+By default, the labels get placed in alphabetical order
+at the end of the output. So, if c = einsum("i,j", a, b)
+then c[i,j] == a[i]*b[j], but if c = einsum("j,i", a, b)
+then c[i,j] = a[j]*b[i].
+
+Alternatively, you can control the output order or prevent
+an axis from being summed/force an axis to be summed by providing
+indices for the output. This allows us to turn 'trace' into
+'diag', for example.
+- diag(a)         -> einsum("ii->i", a)
+- sum(a, axis=0)  -> einsum("i...->", a)
+
+Subscripts at the beginning and end may be specified by
+putting an ellipsis "..." in the middle.  For example,
+the function einsum("i...i", a) takes the diagonal of
+the first and last dimensions of the operand, and
+einsum("ij...,jk...->ik...") takes the matrix product using
+the first two indices of each operand instead of the last two.
+
+When there is only one operand, no axes being summed, and
+no output parameter, this function returns a view
+into the operand instead of making a copy.
+
+::
+
+  PyObject *
+  PyArray_NewLikeArray(PyArrayObject *prototype, NPY_ORDER
+                       order, PyArray_Descr *dtype, int subok)
+
+Creates a new array with the same shape as the provided one,
+with possible memory layout order and data type changes.
+
+prototype - The array the new one should be like.
+order     - NPY_CORDER - C-contiguous result.
+NPY_FORTRANORDER - Fortran-contiguous result.
+NPY_ANYORDER - Fortran if prototype is Fortran, C otherwise.
+NPY_KEEPORDER - Keeps the axis ordering of prototype.
+dtype     - If not NULL, overrides the data type of the result.
+subok     - If 1, use the prototype's array subtype, otherwise
+always create a base-class array.
+
+NOTE: If dtype is not NULL, steals the dtype reference.  On failure or when
+dtype->subarray is true, dtype will be decrefed.
+
+::
+
+  int
+  PyArray_GetArrayParamsFromObject(PyObject *op, PyArray_Descr
+                                   *requested_dtype, npy_bool
+                                   writeable, PyArray_Descr
+                                   **out_dtype, int *out_ndim, npy_intp
+                                   *out_dims, PyArrayObject
+                                   **out_arr, PyObject *context)
+
+Retrieves the array parameters for viewing/converting an arbitrary
+PyObject* to a NumPy array. This allows the "innate type and shape"
+of Python list-of-lists to be discovered without
+actually converting to an array.
+
+In some cases, such as structured arrays and the __array__ interface,
+a data type needs to be used to make sense of the object.  When
+this is needed, provide a Descr for 'requested_dtype', otherwise
+provide NULL. This reference is not stolen. Also, if the requested
+dtype doesn't modify the interpretation of the input, out_dtype will
+still get the "innate" dtype of the object, not the dtype passed
+in 'requested_dtype'.
+
+If writing to the value in 'op' is desired, set the boolean
+'writeable' to 1.  This raises an error when 'op' is a scalar, list
+of lists, or other non-writeable 'op'.
+
+Result: When success (0 return value) is returned, either out_arr
+is filled with a non-NULL PyArrayObject and
+the rest of the parameters are untouched, or out_arr is
+filled with NULL, and the rest of the parameters are
+filled.
+
+Typical usage:
+
+PyArrayObject *arr = NULL;
+PyArray_Descr *dtype = NULL;
+int ndim = 0;
+npy_intp dims[NPY_MAXDIMS];
+
+if (PyArray_GetArrayParamsFromObject(op, NULL, 1, &dtype,
+&ndim, dims, &arr, NULL) < 0) {
+return NULL;
+}
+if (arr == NULL) {
+... validate/change dtype, validate flags, ndim, etc ...
+// Could make custom strides here too
+arr = PyArray_NewFromDescr(&PyArray_Type, dtype, ndim,
+dims, NULL,
+is_f_order ? NPY_ARRAY_F_CONTIGUOUS : 0,
+NULL);
+if (arr == NULL) {
+return NULL;
+}
+if (PyArray_CopyObject(arr, op) < 0) {
+Py_DECREF(arr);
+return NULL;
+}
+}
+else {
+... in this case the other parameters weren't filled, just
+validate and possibly copy arr itself ...
+}
+... use arr ...
+
+::
+
+  int
+  PyArray_ConvertClipmodeSequence(PyObject *object, NPY_CLIPMODE
+                                  *modes, int n)
+
+Convert an object to an array of n NPY_CLIPMODE values.
+This is intended to be used in functions where a different mode
+could be applied to each axis, like in ravel_multi_index.
+
+::
+
+  PyObject *
+  PyArray_MatrixProduct2(PyObject *op1, PyObject
+                         *op2, PyArrayObject*out)
+
+Numeric.matrixproduct2(a,v,out)
+just like inner product but does the swapaxes stuff on the fly
+
+::
+
+  npy_bool
+  NpyIter_IsFirstVisit(NpyIter *iter, int iop)
+
+Checks to see whether this is the first time the elements
+of the specified reduction operand which the iterator points at are
+being seen for the first time. The function returns
+a reasonable answer for reduction operands and when buffering is
+disabled. The answer may be incorrect for buffered non-reduction
+operands.
+
+This function is intended to be used in EXTERNAL_LOOP mode only,
+and will produce some wrong answers when that mode is not enabled.
+
+If this function returns true, the caller should also
+check the inner loop stride of the operand, because if
+that stride is 0, then only the first element of the innermost
+external loop is being visited for the first time.
+
+WARNING: For performance reasons, 'iop' is not bounds-checked,
+it is not confirmed that 'iop' is actually a reduction
+operand, and it is not confirmed that EXTERNAL_LOOP
+mode is enabled. These checks are the responsibility of
+the caller, and should be done outside of any inner loops.
+
+::
+
+  int
+  PyArray_SetBaseObject(PyArrayObject *arr, PyObject *obj)
+
+Sets the 'base' attribute of the array. This steals a reference
+to 'obj'.
+
+Returns 0 on success, -1 on failure.
+
+::
+
+  void
+  PyArray_CreateSortedStridePerm(int ndim, npy_intp
+                                 *strides, npy_stride_sort_item
+                                 *out_strideperm)
+
+
+This function populates the first ndim elements
+of strideperm with sorted descending by their absolute values.
+For example, the stride array (4, -2, 12) becomes
+[(2, 12), (0, 4), (1, -2)].
+
+::
+
+  void
+  PyArray_RemoveAxesInPlace(PyArrayObject *arr, npy_bool *flags)
+
+
+Removes the axes flagged as True from the array,
+modifying it in place. If an axis flagged for removal
+has a shape entry bigger than one, this effectively selects
+index zero for that axis.
+
+WARNING: If an axis flagged for removal has a shape equal to zero,
+the array will point to invalid memory. The caller must
+validate this!
+If an axis flagged for removal has a shape larger than one,
+the aligned flag (and in the future the contiguous flags),
+may need explicit update.
+(check also NPY_RELAXED_STRIDES_CHECKING)
+
+For example, this can be used to remove the reduction axes
+from a reduction result once its computation is complete.
+
+::
+
+  void
+  PyArray_DebugPrint(PyArrayObject *obj)
+
+Prints the raw data of the ndarray in a form useful for debugging
+low-level C issues.
+
+::
+
+  int
+  PyArray_FailUnlessWriteable(PyArrayObject *obj, const char *name)
+
+
+This function does nothing if obj is writeable, and raises an exception
+(and returns -1) if obj is not writeable. It may also do other
+house-keeping, such as issuing warnings on arrays which are transitioning
+to become views. Always call this function at some point before writing to
+an array.
+
+'name' is a name for the array, used to give better error
+messages. Something like "assignment destination", "output array", or even
+just "array".
+
+::
+
+  int
+  PyArray_SetUpdateIfCopyBase(PyArrayObject *arr, PyArrayObject *base)
+
+
+Precondition: 'arr' is a copy of 'base' (though possibly with different
+strides, ordering, etc.). This function sets the UPDATEIFCOPY flag and the
+->base pointer on 'arr', so that when 'arr' is destructed, it will copy any
+changes back to 'base'. DEPRECATED, use PyArray_SetWritebackIfCopyBase
+
+Steals a reference to 'base'.
+
+Returns 0 on success, -1 on failure.
+
+::
+
+  void *
+  PyDataMem_NEW(size_t size)
+
+Allocates memory for array data.
+
+::
+
+  void
+  PyDataMem_FREE(void *ptr)
+
+Free memory for array data.
+
+::
+
+  void *
+  PyDataMem_RENEW(void *ptr, size_t size)
+
+Reallocate/resize memory for array data.
+
+::
+
+  PyDataMem_EventHookFunc *
+  PyDataMem_SetEventHook(PyDataMem_EventHookFunc *newhook, void
+                         *user_data, void **old_data)
+
+Sets the allocation event hook for numpy array data.
+Takes a PyDataMem_EventHookFunc *, which has the signature:
+void hook(void *old, void *new, size_t size, void *user_data).
+Also takes a void *user_data, and void **old_data.
+
+Returns a pointer to the previous hook or NULL.  If old_data is
+non-NULL, the previous user_data pointer will be copied to it.
+
+If not NULL, hook will be called at the end of each PyDataMem_NEW/FREE/RENEW:
+result = PyDataMem_NEW(size)        -> (*hook)(NULL, result, size, user_data)
+PyDataMem_FREE(ptr)                 -> (*hook)(ptr, NULL, 0, user_data)
+result = PyDataMem_RENEW(ptr, size) -> (*hook)(ptr, result, size, user_data)
+
+When the hook is called, the GIL will be held by the calling
+thread.  The hook should be written to be reentrant, if it performs
+operations that might cause new allocation events (such as the
+creation/destruction numpy objects, or creating/destroying Python
+objects which might cause a gc)
+
+::
+
+  void
+  PyArray_MapIterSwapAxes(PyArrayMapIterObject *mit, PyArrayObject
+                          **ret, int getmap)
+
+
+::
+
+  PyObject *
+  PyArray_MapIterArray(PyArrayObject *a, PyObject *index)
+
+
+Use advanced indexing to iterate an array.
+
+::
+
+  void
+  PyArray_MapIterNext(PyArrayMapIterObject *mit)
+
+This function needs to update the state of the map iterator
+and point mit->dataptr to the memory-location of the next object
+
+Note that this function never handles an extra operand but provides
+compatibility for an old (exposed) API.
+
+::
+
+  int
+  PyArray_Partition(PyArrayObject *op, PyArrayObject *ktharray, int
+                    axis, NPY_SELECTKIND which)
+
+Partition an array in-place
+
+::
+
+  PyObject *
+  PyArray_ArgPartition(PyArrayObject *op, PyArrayObject *ktharray, int
+                       axis, NPY_SELECTKIND which)
+
+ArgPartition an array
+
+::
+
+  int
+  PyArray_SelectkindConverter(PyObject *obj, NPY_SELECTKIND *selectkind)
+
+Convert object to select kind
+
+::
+
+  void *
+  PyDataMem_NEW_ZEROED(size_t size, size_t elsize)
+
+Allocates zeroed memory for array data.
+
+::
+
+  int
+  PyArray_CheckAnyScalarExact(PyObject *obj)
+
+return true an object is exactly a numpy scalar
+
+::
+
+  PyObject *
+  PyArray_MapIterArrayCopyIfOverlap(PyArrayObject *a, PyObject
+                                    *index, int
+                                    copy_if_overlap, PyArrayObject
+                                    *extra_op)
+
+
+Same as PyArray_MapIterArray, but:
+
+If copy_if_overlap != 0, check if `a` has memory overlap with any of the
+arrays in `index` and with `extra_op`. If yes, make copies as appropriate
+to avoid problems if `a` is modified during the iteration.
+`iter->array` may contain a copied array (UPDATEIFCOPY/WRITEBACKIFCOPY set).
+
+::
+
+  int
+  PyArray_ResolveWritebackIfCopy(PyArrayObject *self)
+
+
+If WRITEBACKIFCOPY and self has data, reset the base WRITEABLE flag,
+copy the local data to base, release the local data, and set flags
+appropriately. Return 0 if not relevant, 1 if success, < 0 on failure
+
+::
+
+  int
+  PyArray_SetWritebackIfCopyBase(PyArrayObject *arr, PyArrayObject
+                                 *base)
+
+
+Precondition: 'arr' is a copy of 'base' (though possibly with different
+strides, ordering, etc.). This function sets the WRITEBACKIFCOPY flag and the
+->base pointer on 'arr', call PyArray_ResolveWritebackIfCopy to copy any
+changes back to 'base' before deallocating the array.
+
+Steals a reference to 'base'.
+
+Returns 0 on success, -1 on failure.
+
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ndarrayobject.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ndarrayobject.h
new file mode 100644
index 0000000..45f008b
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ndarrayobject.h
@@ -0,0 +1,285 @@
+/*
+ * DON'T INCLUDE THIS DIRECTLY.
+ */
+
+#ifndef NPY_NDARRAYOBJECT_H
+#define NPY_NDARRAYOBJECT_H
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+#include <Python.h>
+#include "ndarraytypes.h"
+
+/* Includes the "function" C-API -- these are all stored in a
+   list of pointers --- one for each file
+   The two lists are concatenated into one in multiarray.
+
+   They are available as import_array()
+*/
+
+#include "__multiarray_api.h"
+
+
+/* C-API that requires previous API to be defined */
+
+#define PyArray_DescrCheck(op) (((PyObject*)(op))->ob_type==&PyArrayDescr_Type)
+
+#define PyArray_Check(op) PyObject_TypeCheck(op, &PyArray_Type)
+#define PyArray_CheckExact(op) (((PyObject*)(op))->ob_type == &PyArray_Type)
+
+#define PyArray_HasArrayInterfaceType(op, type, context, out)                 \
+        ((((out)=PyArray_FromStructInterface(op)) != Py_NotImplemented) ||    \
+         (((out)=PyArray_FromInterface(op)) != Py_NotImplemented) ||          \
+         (((out)=PyArray_FromArrayAttr(op, type, context)) !=                 \
+          Py_NotImplemented))
+
+#define PyArray_HasArrayInterface(op, out)                                    \
+        PyArray_HasArrayInterfaceType(op, NULL, NULL, out)
+
+#define PyArray_IsZeroDim(op) (PyArray_Check(op) && \
+                               (PyArray_NDIM((PyArrayObject *)op) == 0))
+
+#define PyArray_IsScalar(obj, cls)                                            \
+        (PyObject_TypeCheck(obj, &Py##cls##ArrType_Type))
+
+#define PyArray_CheckScalar(m) (PyArray_IsScalar(m, Generic) ||               \
+                                PyArray_IsZeroDim(m))
+#if PY_MAJOR_VERSION >= 3
+#define PyArray_IsPythonNumber(obj)                                           \
+        (PyFloat_Check(obj) || PyComplex_Check(obj) ||                        \
+         PyLong_Check(obj) || PyBool_Check(obj))
+#define PyArray_IsIntegerScalar(obj) (PyLong_Check(obj)                       \
+              || PyArray_IsScalar((obj), Integer))
+#define PyArray_IsPythonScalar(obj)                                           \
+        (PyArray_IsPythonNumber(obj) || PyBytes_Check(obj) ||                 \
+         PyUnicode_Check(obj))
+#else
+#define PyArray_IsPythonNumber(obj)                                           \
+        (PyInt_Check(obj) || PyFloat_Check(obj) || PyComplex_Check(obj) ||    \
+         PyLong_Check(obj) || PyBool_Check(obj))
+#define PyArray_IsIntegerScalar(obj) (PyInt_Check(obj)                        \
+              || PyLong_Check(obj)                                            \
+              || PyArray_IsScalar((obj), Integer))
+#define PyArray_IsPythonScalar(obj)                                           \
+        (PyArray_IsPythonNumber(obj) || PyString_Check(obj) ||                \
+         PyUnicode_Check(obj))
+#endif
+
+#define PyArray_IsAnyScalar(obj)                                              \
+        (PyArray_IsScalar(obj, Generic) || PyArray_IsPythonScalar(obj))
+
+#define PyArray_CheckAnyScalar(obj) (PyArray_IsPythonScalar(obj) ||           \
+                                     PyArray_CheckScalar(obj))
+
+
+#define PyArray_GETCONTIGUOUS(m) (PyArray_ISCONTIGUOUS(m) ?                   \
+                                  Py_INCREF(m), (m) :                         \
+                                  (PyArrayObject *)(PyArray_Copy(m)))
+
+#define PyArray_SAMESHAPE(a1,a2) ((PyArray_NDIM(a1) == PyArray_NDIM(a2)) &&   \
+                                  PyArray_CompareLists(PyArray_DIMS(a1),      \
+                                                       PyArray_DIMS(a2),      \
+                                                       PyArray_NDIM(a1)))
+
+#define PyArray_SIZE(m) PyArray_MultiplyList(PyArray_DIMS(m), PyArray_NDIM(m))
+#define PyArray_NBYTES(m) (PyArray_ITEMSIZE(m) * PyArray_SIZE(m))
+#define PyArray_FROM_O(m) PyArray_FromAny(m, NULL, 0, 0, 0, NULL)
+
+#define PyArray_FROM_OF(m,flags) PyArray_CheckFromAny(m, NULL, 0, 0, flags,   \
+                                                      NULL)
+
+#define PyArray_FROM_OT(m,type) PyArray_FromAny(m,                            \
+                                PyArray_DescrFromType(type), 0, 0, 0, NULL)
+
+#define PyArray_FROM_OTF(m, type, flags) \
+        PyArray_FromAny(m, PyArray_DescrFromType(type), 0, 0, \
+                        (((flags) & NPY_ARRAY_ENSURECOPY) ? \
+                         ((flags) | NPY_ARRAY_DEFAULT) : (flags)), NULL)
+
+#define PyArray_FROMANY(m, type, min, max, flags) \
+        PyArray_FromAny(m, PyArray_DescrFromType(type), min, max, \
+                        (((flags) & NPY_ARRAY_ENSURECOPY) ? \
+                         (flags) | NPY_ARRAY_DEFAULT : (flags)), NULL)
+
+#define PyArray_ZEROS(m, dims, type, is_f_order) \
+        PyArray_Zeros(m, dims, PyArray_DescrFromType(type), is_f_order)
+
+#define PyArray_EMPTY(m, dims, type, is_f_order) \
+        PyArray_Empty(m, dims, PyArray_DescrFromType(type), is_f_order)
+
+#define PyArray_FILLWBYTE(obj, val) memset(PyArray_DATA(obj), val, \
+                                           PyArray_NBYTES(obj))
+#ifndef PYPY_VERSION
+#define PyArray_REFCOUNT(obj) (((PyObject *)(obj))->ob_refcnt)
+#define NPY_REFCOUNT PyArray_REFCOUNT
+#endif
+#define NPY_MAX_ELSIZE (2 * NPY_SIZEOF_LONGDOUBLE)
+
+#define PyArray_ContiguousFromAny(op, type, min_depth, max_depth) \
+        PyArray_FromAny(op, PyArray_DescrFromType(type), min_depth, \
+                              max_depth, NPY_ARRAY_DEFAULT, NULL)
+
+#define PyArray_EquivArrTypes(a1, a2) \
+        PyArray_EquivTypes(PyArray_DESCR(a1), PyArray_DESCR(a2))
+
+#define PyArray_EquivByteorders(b1, b2) \
+        (((b1) == (b2)) || (PyArray_ISNBO(b1) == PyArray_ISNBO(b2)))
+
+#define PyArray_SimpleNew(nd, dims, typenum) \
+        PyArray_New(&PyArray_Type, nd, dims, typenum, NULL, NULL, 0, 0, NULL)
+
+#define PyArray_SimpleNewFromData(nd, dims, typenum, data) \
+        PyArray_New(&PyArray_Type, nd, dims, typenum, NULL, \
+                    data, 0, NPY_ARRAY_CARRAY, NULL)
+
+#define PyArray_SimpleNewFromDescr(nd, dims, descr) \
+        PyArray_NewFromDescr(&PyArray_Type, descr, nd, dims, \
+                             NULL, NULL, 0, NULL)
+
+#define PyArray_ToScalar(data, arr) \
+        PyArray_Scalar(data, PyArray_DESCR(arr), (PyObject *)arr)
+
+
+/* These might be faster without the dereferencing of obj
+   going on inside -- of course an optimizing compiler should
+   inline the constants inside a for loop making it a moot point
+*/
+
+#define PyArray_GETPTR1(obj, i) ((void *)(PyArray_BYTES(obj) + \
+                                         (i)*PyArray_STRIDES(obj)[0]))
+
+#define PyArray_GETPTR2(obj, i, j) ((void *)(PyArray_BYTES(obj) + \
+                                            (i)*PyArray_STRIDES(obj)[0] + \
+                                            (j)*PyArray_STRIDES(obj)[1]))
+
+#define PyArray_GETPTR3(obj, i, j, k) ((void *)(PyArray_BYTES(obj) + \
+                                            (i)*PyArray_STRIDES(obj)[0] + \
+                                            (j)*PyArray_STRIDES(obj)[1] + \
+                                            (k)*PyArray_STRIDES(obj)[2]))
+
+#define PyArray_GETPTR4(obj, i, j, k, l) ((void *)(PyArray_BYTES(obj) + \
+                                            (i)*PyArray_STRIDES(obj)[0] + \
+                                            (j)*PyArray_STRIDES(obj)[1] + \
+                                            (k)*PyArray_STRIDES(obj)[2] + \
+                                            (l)*PyArray_STRIDES(obj)[3]))
+
+/* Move to arrayobject.c once PyArray_XDECREF_ERR is removed */
+static NPY_INLINE void
+PyArray_DiscardWritebackIfCopy(PyArrayObject *arr)
+{
+    PyArrayObject_fields *fa = (PyArrayObject_fields *)arr;
+    if (fa && fa->base) {
+        if ((fa->flags & NPY_ARRAY_UPDATEIFCOPY) ||
+                (fa->flags & NPY_ARRAY_WRITEBACKIFCOPY)) {
+            PyArray_ENABLEFLAGS((PyArrayObject*)fa->base, NPY_ARRAY_WRITEABLE);
+            Py_DECREF(fa->base);
+            fa->base = NULL;
+            PyArray_CLEARFLAGS(arr, NPY_ARRAY_WRITEBACKIFCOPY);
+            PyArray_CLEARFLAGS(arr, NPY_ARRAY_UPDATEIFCOPY);
+        }
+    }
+}
+
+#define PyArray_DESCR_REPLACE(descr) do { \
+                PyArray_Descr *_new_; \
+                _new_ = PyArray_DescrNew(descr); \
+                Py_XDECREF(descr); \
+                descr = _new_; \
+        } while(0)
+
+/* Copy should always return contiguous array */
+#define PyArray_Copy(obj) PyArray_NewCopy(obj, NPY_CORDER)
+
+#define PyArray_FromObject(op, type, min_depth, max_depth) \
+        PyArray_FromAny(op, PyArray_DescrFromType(type), min_depth, \
+                              max_depth, NPY_ARRAY_BEHAVED | \
+                                         NPY_ARRAY_ENSUREARRAY, NULL)
+
+#define PyArray_ContiguousFromObject(op, type, min_depth, max_depth) \
+        PyArray_FromAny(op, PyArray_DescrFromType(type), min_depth, \
+                              max_depth, NPY_ARRAY_DEFAULT | \
+                                         NPY_ARRAY_ENSUREARRAY, NULL)
+
+#define PyArray_CopyFromObject(op, type, min_depth, max_depth) \
+        PyArray_FromAny(op, PyArray_DescrFromType(type), min_depth, \
+                        max_depth, NPY_ARRAY_ENSURECOPY | \
+                                   NPY_ARRAY_DEFAULT | \
+                                   NPY_ARRAY_ENSUREARRAY, NULL)
+
+#define PyArray_Cast(mp, type_num)                                            \
+        PyArray_CastToType(mp, PyArray_DescrFromType(type_num), 0)
+
+#define PyArray_Take(ap, items, axis)                                         \
+        PyArray_TakeFrom(ap, items, axis, NULL, NPY_RAISE)
+
+#define PyArray_Put(ap, items, values)                                        \
+        PyArray_PutTo(ap, items, values, NPY_RAISE)
+
+/* Compatibility with old Numeric stuff -- don't use in new code */
+
+#define PyArray_FromDimsAndData(nd, d, type, data)                            \
+        PyArray_FromDimsAndDataAndDescr(nd, d, PyArray_DescrFromType(type),   \
+                                        data)
+
+
+/*
+   Check to see if this key in the dictionary is the "title"
+   entry of the tuple (i.e. a duplicate dictionary entry in the fields
+   dict.
+*/
+
+static NPY_INLINE int
+NPY_TITLE_KEY_check(PyObject *key, PyObject *value)
+{
+    PyObject *title;
+    if (PyTuple_GET_SIZE(value) != 3) {
+        return 0;
+    }
+    title = PyTuple_GET_ITEM(value, 2);
+    if (key == title) {
+        return 1;
+    }
+#ifdef PYPY_VERSION
+    /*
+     * On PyPy, dictionary keys do not always preserve object identity.
+     * Fall back to comparison by value.
+     */
+    if (PyUnicode_Check(title) && PyUnicode_Check(key)) {
+        return PyUnicode_Compare(title, key) == 0 ? 1 : 0;
+    }
+#if PY_VERSION_HEX < 0x03000000
+    if (PyString_Check(title) && PyString_Check(key)) {
+        return PyObject_Compare(title, key) == 0 ? 1 : 0;
+    }
+#endif
+#endif
+    return 0;
+}
+
+/* Macro, for backward compat with "if NPY_TITLE_KEY(key, value) { ..." */
+#define NPY_TITLE_KEY(key, value) (NPY_TITLE_KEY_check((key), (value)))
+
+#define DEPRECATE(msg) PyErr_WarnEx(PyExc_DeprecationWarning,msg,1)
+#define DEPRECATE_FUTUREWARNING(msg) PyErr_WarnEx(PyExc_FutureWarning,msg,1)
+
+#if !defined(NPY_NO_DEPRECATED_API) || \
+    (NPY_NO_DEPRECATED_API < NPY_1_14_API_VERSION)
+static NPY_INLINE void
+PyArray_XDECREF_ERR(PyArrayObject *arr)
+{
+    /* 2017-Nov-10 1.14 */
+    DEPRECATE("PyArray_XDECREF_ERR is deprecated, call "
+        "PyArray_DiscardWritebackIfCopy then Py_XDECREF instead");
+    PyArray_DiscardWritebackIfCopy(arr);
+    Py_XDECREF(arr);
+}
+#endif
+
+
+#ifdef __cplusplus
+}
+#endif
+
+
+#endif /* NPY_NDARRAYOBJECT_H */
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ndarraytypes.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ndarraytypes.h
new file mode 100644
index 0000000..b0b749c
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ndarraytypes.h
@@ -0,0 +1,1838 @@
+#ifndef NDARRAYTYPES_H
+#define NDARRAYTYPES_H
+
+#include "npy_common.h"
+#include "npy_endian.h"
+#include "npy_cpu.h"
+#include "utils.h"
+
+#define NPY_NO_EXPORT NPY_VISIBILITY_HIDDEN
+
+/* Only use thread if configured in config and python supports it */
+#if defined WITH_THREAD && !NPY_NO_SMP
+        #define NPY_ALLOW_THREADS 1
+#else
+        #define NPY_ALLOW_THREADS 0
+#endif
+
+#ifndef __has_extension
+#define __has_extension(x) 0
+#endif
+
+#if !defined(_NPY_NO_DEPRECATIONS) && \
+    ((defined(__GNUC__)&& __GNUC__ >= 6) || \
+     __has_extension(attribute_deprecated_with_message))
+#define NPY_ATTR_DEPRECATE(text) __attribute__ ((deprecated (text)))
+#else
+#define NPY_ATTR_DEPRECATE(text)
+#endif
+
+/*
+ * There are several places in the code where an array of dimensions
+ * is allocated statically.  This is the size of that static
+ * allocation.
+ *
+ * The array creation itself could have arbitrary dimensions but all
+ * the places where static allocation is used would need to be changed
+ * to dynamic (including inside of several structures)
+ */
+
+#define NPY_MAXDIMS 32
+#define NPY_MAXARGS 32
+
+/* Used for Converter Functions "O&" code in ParseTuple */
+#define NPY_FAIL 0
+#define NPY_SUCCEED 1
+
+/*
+ * Binary compatibility version number.  This number is increased
+ * whenever the C-API is changed such that binary compatibility is
+ * broken, i.e. whenever a recompile of extension modules is needed.
+ */
+#define NPY_VERSION NPY_ABI_VERSION
+
+/*
+ * Minor API version.  This number is increased whenever a change is
+ * made to the C-API -- whether it breaks binary compatibility or not.
+ * Some changes, such as adding a function pointer to the end of the
+ * function table, can be made without breaking binary compatibility.
+ * In this case, only the NPY_FEATURE_VERSION (*not* NPY_VERSION)
+ * would be increased.  Whenever binary compatibility is broken, both
+ * NPY_VERSION and NPY_FEATURE_VERSION should be increased.
+ */
+#define NPY_FEATURE_VERSION NPY_API_VERSION
+
+enum NPY_TYPES {    NPY_BOOL=0,
+                    NPY_BYTE, NPY_UBYTE,
+                    NPY_SHORT, NPY_USHORT,
+                    NPY_INT, NPY_UINT,
+                    NPY_LONG, NPY_ULONG,
+                    NPY_LONGLONG, NPY_ULONGLONG,
+                    NPY_FLOAT, NPY_DOUBLE, NPY_LONGDOUBLE,
+                    NPY_CFLOAT, NPY_CDOUBLE, NPY_CLONGDOUBLE,
+                    NPY_OBJECT=17,
+                    NPY_STRING, NPY_UNICODE,
+                    NPY_VOID,
+                    /*
+                     * New 1.6 types appended, may be integrated
+                     * into the above in 2.0.
+                     */
+                    NPY_DATETIME, NPY_TIMEDELTA, NPY_HALF,
+
+                    NPY_NTYPES,
+                    NPY_NOTYPE,
+                    NPY_CHAR NPY_ATTR_DEPRECATE("Use NPY_STRING"),
+                    NPY_USERDEF=256,  /* leave room for characters */
+
+                    /* The number of types not including the new 1.6 types */
+                    NPY_NTYPES_ABI_COMPATIBLE=21
+};
+#ifdef _MSC_VER
+#pragma deprecated(NPY_CHAR)
+#endif
+
+/* basetype array priority */
+#define NPY_PRIORITY 0.0
+
+/* default subtype priority */
+#define NPY_SUBTYPE_PRIORITY 1.0
+
+/* default scalar priority */
+#define NPY_SCALAR_PRIORITY -1000000.0
+
+/* How many floating point types are there (excluding half) */
+#define NPY_NUM_FLOATTYPE 3
+
+/*
+ * These characters correspond to the array type and the struct
+ * module
+ */
+
+enum NPY_TYPECHAR {
+        NPY_BOOLLTR = '?',
+        NPY_BYTELTR = 'b',
+        NPY_UBYTELTR = 'B',
+        NPY_SHORTLTR = 'h',
+        NPY_USHORTLTR = 'H',
+        NPY_INTLTR = 'i',
+        NPY_UINTLTR = 'I',
+        NPY_LONGLTR = 'l',
+        NPY_ULONGLTR = 'L',
+        NPY_LONGLONGLTR = 'q',
+        NPY_ULONGLONGLTR = 'Q',
+        NPY_HALFLTR = 'e',
+        NPY_FLOATLTR = 'f',
+        NPY_DOUBLELTR = 'd',
+        NPY_LONGDOUBLELTR = 'g',
+        NPY_CFLOATLTR = 'F',
+        NPY_CDOUBLELTR = 'D',
+        NPY_CLONGDOUBLELTR = 'G',
+        NPY_OBJECTLTR = 'O',
+        NPY_STRINGLTR = 'S',
+        NPY_STRINGLTR2 = 'a',
+        NPY_UNICODELTR = 'U',
+        NPY_VOIDLTR = 'V',
+        NPY_DATETIMELTR = 'M',
+        NPY_TIMEDELTALTR = 'm',
+        NPY_CHARLTR = 'c',
+
+        /*
+         * No Descriptor, just a define -- this let's
+         * Python users specify an array of integers
+         * large enough to hold a pointer on the
+         * platform
+         */
+        NPY_INTPLTR = 'p',
+        NPY_UINTPLTR = 'P',
+
+        /*
+         * These are for dtype 'kinds', not dtype 'typecodes'
+         * as the above are for.
+         */
+        NPY_GENBOOLLTR ='b',
+        NPY_SIGNEDLTR = 'i',
+        NPY_UNSIGNEDLTR = 'u',
+        NPY_FLOATINGLTR = 'f',
+        NPY_COMPLEXLTR = 'c'
+};
+
+typedef enum {
+        NPY_QUICKSORT=0,
+        NPY_HEAPSORT=1,
+        NPY_MERGESORT=2
+} NPY_SORTKIND;
+#define NPY_NSORTS (NPY_MERGESORT + 1)
+
+
+typedef enum {
+        NPY_INTROSELECT=0
+} NPY_SELECTKIND;
+#define NPY_NSELECTS (NPY_INTROSELECT + 1)
+
+
+typedef enum {
+        NPY_SEARCHLEFT=0,
+        NPY_SEARCHRIGHT=1
+} NPY_SEARCHSIDE;
+#define NPY_NSEARCHSIDES (NPY_SEARCHRIGHT + 1)
+
+
+typedef enum {
+        NPY_NOSCALAR=-1,
+        NPY_BOOL_SCALAR,
+        NPY_INTPOS_SCALAR,
+        NPY_INTNEG_SCALAR,
+        NPY_FLOAT_SCALAR,
+        NPY_COMPLEX_SCALAR,
+        NPY_OBJECT_SCALAR
+} NPY_SCALARKIND;
+#define NPY_NSCALARKINDS (NPY_OBJECT_SCALAR + 1)
+
+/* For specifying array memory layout or iteration order */
+typedef enum {
+        /* Fortran order if inputs are all Fortran, C otherwise */
+        NPY_ANYORDER=-1,
+        /* C order */
+        NPY_CORDER=0,
+        /* Fortran order */
+        NPY_FORTRANORDER=1,
+        /* An order as close to the inputs as possible */
+        NPY_KEEPORDER=2
+} NPY_ORDER;
+
+/* For specifying allowed casting in operations which support it */
+typedef enum {
+        /* Only allow identical types */
+        NPY_NO_CASTING=0,
+        /* Allow identical and byte swapped types */
+        NPY_EQUIV_CASTING=1,
+        /* Only allow safe casts */
+        NPY_SAFE_CASTING=2,
+        /* Allow safe casts or casts within the same kind */
+        NPY_SAME_KIND_CASTING=3,
+        /* Allow any casts */
+        NPY_UNSAFE_CASTING=4
+} NPY_CASTING;
+
+typedef enum {
+        NPY_CLIP=0,
+        NPY_WRAP=1,
+        NPY_RAISE=2
+} NPY_CLIPMODE;
+
+/* The special not-a-time (NaT) value */
+#define NPY_DATETIME_NAT NPY_MIN_INT64
+
+/*
+ * Upper bound on the length of a DATETIME ISO 8601 string
+ *   YEAR: 21 (64-bit year)
+ *   MONTH: 3
+ *   DAY: 3
+ *   HOURS: 3
+ *   MINUTES: 3
+ *   SECONDS: 3
+ *   ATTOSECONDS: 1 + 3*6
+ *   TIMEZONE: 5
+ *   NULL TERMINATOR: 1
+ */
+#define NPY_DATETIME_MAX_ISO8601_STRLEN (21 + 3*5 + 1 + 3*6 + 6 + 1)
+
+/* The FR in the unit names stands for frequency */
+typedef enum {
+        /* Force signed enum type, must be -1 for code compatibility */
+        NPY_FR_ERROR = -1,      /* error or undetermined */
+
+        /* Start of valid units */
+        NPY_FR_Y = 0,           /* Years */
+        NPY_FR_M = 1,           /* Months */
+        NPY_FR_W = 2,           /* Weeks */
+        /* Gap where 1.6 NPY_FR_B (value 3) was */
+        NPY_FR_D = 4,           /* Days */
+        NPY_FR_h = 5,           /* hours */
+        NPY_FR_m = 6,           /* minutes */
+        NPY_FR_s = 7,           /* seconds */
+        NPY_FR_ms = 8,          /* milliseconds */
+        NPY_FR_us = 9,          /* microseconds */
+        NPY_FR_ns = 10,         /* nanoseconds */
+        NPY_FR_ps = 11,         /* picoseconds */
+        NPY_FR_fs = 12,         /* femtoseconds */
+        NPY_FR_as = 13,         /* attoseconds */
+        NPY_FR_GENERIC = 14     /* unbound units, can convert to anything */
+} NPY_DATETIMEUNIT;
+
+/*
+ * NOTE: With the NPY_FR_B gap for 1.6 ABI compatibility, NPY_DATETIME_NUMUNITS
+ * is technically one more than the actual number of units.
+ */
+#define NPY_DATETIME_NUMUNITS (NPY_FR_GENERIC + 1)
+#define NPY_DATETIME_DEFAULTUNIT NPY_FR_GENERIC
+
+/*
+ * Business day conventions for mapping invalid business
+ * days to valid business days.
+ */
+typedef enum {
+    /* Go forward in time to the following business day. */
+    NPY_BUSDAY_FORWARD,
+    NPY_BUSDAY_FOLLOWING = NPY_BUSDAY_FORWARD,
+    /* Go backward in time to the preceding business day. */
+    NPY_BUSDAY_BACKWARD,
+    NPY_BUSDAY_PRECEDING = NPY_BUSDAY_BACKWARD,
+    /*
+     * Go forward in time to the following business day, unless it
+     * crosses a month boundary, in which case go backward
+     */
+    NPY_BUSDAY_MODIFIEDFOLLOWING,
+    /*
+     * Go backward in time to the preceding business day, unless it
+     * crosses a month boundary, in which case go forward.
+     */
+    NPY_BUSDAY_MODIFIEDPRECEDING,
+    /* Produce a NaT for non-business days. */
+    NPY_BUSDAY_NAT,
+    /* Raise an exception for non-business days. */
+    NPY_BUSDAY_RAISE
+} NPY_BUSDAY_ROLL;
+
+/************************************************************
+ * NumPy Auxiliary Data for inner loops, sort functions, etc.
+ ************************************************************/
+
+/*
+ * When creating an auxiliary data struct, this should always appear
+ * as the first member, like this:
+ *
+ * typedef struct {
+ *     NpyAuxData base;
+ *     double constant;
+ * } constant_multiplier_aux_data;
+ */
+typedef struct NpyAuxData_tag NpyAuxData;
+
+/* Function pointers for freeing or cloning auxiliary data */
+typedef void (NpyAuxData_FreeFunc) (NpyAuxData *);
+typedef NpyAuxData *(NpyAuxData_CloneFunc) (NpyAuxData *);
+
+struct NpyAuxData_tag {
+    NpyAuxData_FreeFunc *free;
+    NpyAuxData_CloneFunc *clone;
+    /* To allow for a bit of expansion without breaking the ABI */
+    void *reserved[2];
+};
+
+/* Macros to use for freeing and cloning auxiliary data */
+#define NPY_AUXDATA_FREE(auxdata) \
+    do { \
+        if ((auxdata) != NULL) { \
+            (auxdata)->free(auxdata); \
+        } \
+    } while(0)
+#define NPY_AUXDATA_CLONE(auxdata) \
+    ((auxdata)->clone(auxdata))
+
+#define NPY_ERR(str) fprintf(stderr, #str); fflush(stderr);
+#define NPY_ERR2(str) fprintf(stderr, str); fflush(stderr);
+
+#define NPY_STRINGIFY(x) #x
+#define NPY_TOSTRING(x) NPY_STRINGIFY(x)
+
+  /*
+   * Macros to define how array, and dimension/strides data is
+   * allocated.
+   */
+
+  /* Data buffer - PyDataMem_NEW/FREE/RENEW are in multiarraymodule.c */
+
+#define NPY_USE_PYMEM 1
+
+#if NPY_USE_PYMEM == 1
+   /* numpy sometimes calls PyArray_malloc() with the GIL released. On Python
+      3.3 and older, it was safe to call PyMem_Malloc() with the GIL released.
+      On Python 3.4 and newer, it's better to use PyMem_RawMalloc() to be able
+      to use tracemalloc. On Python 3.6, calling PyMem_Malloc() with the GIL
+      released is now a fatal error in debug mode. */
+#  if PY_VERSION_HEX >= 0x03040000
+#    define PyArray_malloc PyMem_RawMalloc
+#    define PyArray_free PyMem_RawFree
+#    define PyArray_realloc PyMem_RawRealloc
+#  else
+#    define PyArray_malloc PyMem_Malloc
+#    define PyArray_free PyMem_Free
+#    define PyArray_realloc PyMem_Realloc
+#  endif
+#else
+#define PyArray_malloc malloc
+#define PyArray_free free
+#define PyArray_realloc realloc
+#endif
+
+/* Dimensions and strides */
+#define PyDimMem_NEW(size)                                         \
+    ((npy_intp *)PyArray_malloc(size*sizeof(npy_intp)))
+
+#define PyDimMem_FREE(ptr) PyArray_free(ptr)
+
+#define PyDimMem_RENEW(ptr,size)                                   \
+        ((npy_intp *)PyArray_realloc(ptr,size*sizeof(npy_intp)))
+
+/* forward declaration */
+struct _PyArray_Descr;
+
+/* These must deal with unaligned and swapped data if necessary */
+typedef PyObject * (PyArray_GetItemFunc) (void *, void *);
+typedef int (PyArray_SetItemFunc)(PyObject *, void *, void *);
+
+typedef void (PyArray_CopySwapNFunc)(void *, npy_intp, void *, npy_intp,
+                                     npy_intp, int, void *);
+
+typedef void (PyArray_CopySwapFunc)(void *, void *, int, void *);
+typedef npy_bool (PyArray_NonzeroFunc)(void *, void *);
+
+
+/*
+ * These assume aligned and notswapped data -- a buffer will be used
+ * before or contiguous data will be obtained
+ */
+
+typedef int (PyArray_CompareFunc)(const void *, const void *, void *);
+typedef int (PyArray_ArgFunc)(void*, npy_intp, npy_intp*, void *);
+
+typedef void (PyArray_DotFunc)(void *, npy_intp, void *, npy_intp, void *,
+                               npy_intp, void *);
+
+typedef void (PyArray_VectorUnaryFunc)(void *, void *, npy_intp, void *,
+                                       void *);
+
+/*
+ * XXX the ignore argument should be removed next time the API version
+ * is bumped. It used to be the separator.
+ */
+typedef int (PyArray_ScanFunc)(FILE *fp, void *dptr,
+                               char *ignore, struct _PyArray_Descr *);
+typedef int (PyArray_FromStrFunc)(char *s, void *dptr, char **endptr,
+                                  struct _PyArray_Descr *);
+
+typedef int (PyArray_FillFunc)(void *, npy_intp, void *);
+
+typedef int (PyArray_SortFunc)(void *, npy_intp, void *);
+typedef int (PyArray_ArgSortFunc)(void *, npy_intp *, npy_intp, void *);
+typedef int (PyArray_PartitionFunc)(void *, npy_intp, npy_intp,
+                                    npy_intp *, npy_intp *,
+                                    void *);
+typedef int (PyArray_ArgPartitionFunc)(void *, npy_intp *, npy_intp, npy_intp,
+                                       npy_intp *, npy_intp *,
+                                       void *);
+
+typedef int (PyArray_FillWithScalarFunc)(void *, npy_intp, void *, void *);
+
+typedef int (PyArray_ScalarKindFunc)(void *);
+
+typedef void (PyArray_FastClipFunc)(void *in, npy_intp n_in, void *min,
+                                    void *max, void *out);
+typedef void (PyArray_FastPutmaskFunc)(void *in, void *mask, npy_intp n_in,
+                                       void *values, npy_intp nv);
+typedef int  (PyArray_FastTakeFunc)(void *dest, void *src, npy_intp *indarray,
+                                       npy_intp nindarray, npy_intp n_outer,
+                                       npy_intp m_middle, npy_intp nelem,
+                                       NPY_CLIPMODE clipmode);
+
+typedef struct {
+        npy_intp *ptr;
+        int len;
+} PyArray_Dims;
+
+typedef struct {
+        /*
+         * Functions to cast to most other standard types
+         * Can have some NULL entries. The types
+         * DATETIME, TIMEDELTA, and HALF go into the castdict
+         * even though they are built-in.
+         */
+        PyArray_VectorUnaryFunc *cast[NPY_NTYPES_ABI_COMPATIBLE];
+
+        /* The next four functions *cannot* be NULL */
+
+        /*
+         * Functions to get and set items with standard Python types
+         * -- not array scalars
+         */
+        PyArray_GetItemFunc *getitem;
+        PyArray_SetItemFunc *setitem;
+
+        /*
+         * Copy and/or swap data.  Memory areas may not overlap
+         * Use memmove first if they might
+         */
+        PyArray_CopySwapNFunc *copyswapn;
+        PyArray_CopySwapFunc *copyswap;
+
+        /*
+         * Function to compare items
+         * Can be NULL
+         */
+        PyArray_CompareFunc *compare;
+
+        /*
+         * Function to select largest
+         * Can be NULL
+         */
+        PyArray_ArgFunc *argmax;
+
+        /*
+         * Function to compute dot product
+         * Can be NULL
+         */
+        PyArray_DotFunc *dotfunc;
+
+        /*
+         * Function to scan an ASCII file and
+         * place a single value plus possible separator
+         * Can be NULL
+         */
+        PyArray_ScanFunc *scanfunc;
+
+        /*
+         * Function to read a single value from a string
+         * and adjust the pointer; Can be NULL
+         */
+        PyArray_FromStrFunc *fromstr;
+
+        /*
+         * Function to determine if data is zero or not
+         * If NULL a default version is
+         * used at Registration time.
+         */
+        PyArray_NonzeroFunc *nonzero;
+
+        /*
+         * Used for arange. Should return 0 on success
+         * and -1 on failure.
+         * Can be NULL.
+         */
+        PyArray_FillFunc *fill;
+
+        /*
+         * Function to fill arrays with scalar values
+         * Can be NULL
+         */
+        PyArray_FillWithScalarFunc *fillwithscalar;
+
+        /*
+         * Sorting functions
+         * Can be NULL
+         */
+        PyArray_SortFunc *sort[NPY_NSORTS];
+        PyArray_ArgSortFunc *argsort[NPY_NSORTS];
+
+        /*
+         * Dictionary of additional casting functions
+         * PyArray_VectorUnaryFuncs
+         * which can be populated to support casting
+         * to other registered types. Can be NULL
+         */
+        PyObject *castdict;
+
+        /*
+         * Functions useful for generalizing
+         * the casting rules.
+         * Can be NULL;
+         */
+        PyArray_ScalarKindFunc *scalarkind;
+        int **cancastscalarkindto;
+        int *cancastto;
+
+        PyArray_FastClipFunc *fastclip;
+        PyArray_FastPutmaskFunc *fastputmask;
+        PyArray_FastTakeFunc *fasttake;
+
+        /*
+         * Function to select smallest
+         * Can be NULL
+         */
+        PyArray_ArgFunc *argmin;
+
+} PyArray_ArrFuncs;
+
+/* The item must be reference counted when it is inserted or extracted. */
+#define NPY_ITEM_REFCOUNT   0x01
+/* Same as needing REFCOUNT */
+#define NPY_ITEM_HASOBJECT  0x01
+/* Convert to list for pickling */
+#define NPY_LIST_PICKLE     0x02
+/* The item is a POINTER  */
+#define NPY_ITEM_IS_POINTER 0x04
+/* memory needs to be initialized for this data-type */
+#define NPY_NEEDS_INIT      0x08
+/* operations need Python C-API so don't give-up thread. */
+#define NPY_NEEDS_PYAPI     0x10
+/* Use f.getitem when extracting elements of this data-type */
+#define NPY_USE_GETITEM     0x20
+/* Use f.setitem when setting creating 0-d array from this data-type.*/
+#define NPY_USE_SETITEM     0x40
+/* A sticky flag specifically for structured arrays */
+#define NPY_ALIGNED_STRUCT  0x80
+
+/*
+ *These are inherited for global data-type if any data-types in the
+ * field have them
+ */
+#define NPY_FROM_FIELDS    (NPY_NEEDS_INIT | NPY_LIST_PICKLE | \
+                            NPY_ITEM_REFCOUNT | NPY_NEEDS_PYAPI)
+
+#define NPY_OBJECT_DTYPE_FLAGS (NPY_LIST_PICKLE | NPY_USE_GETITEM | \
+                                NPY_ITEM_IS_POINTER | NPY_ITEM_REFCOUNT | \
+                                NPY_NEEDS_INIT | NPY_NEEDS_PYAPI)
+
+#define PyDataType_FLAGCHK(dtype, flag) \
+        (((dtype)->flags & (flag)) == (flag))
+
+#define PyDataType_REFCHK(dtype) \
+        PyDataType_FLAGCHK(dtype, NPY_ITEM_REFCOUNT)
+
+typedef struct _PyArray_Descr {
+        PyObject_HEAD
+        /*
+         * the type object representing an
+         * instance of this type -- should not
+         * be two type_numbers with the same type
+         * object.
+         */
+        PyTypeObject *typeobj;
+        /* kind for this type */
+        char kind;
+        /* unique-character representing this type */
+        char type;
+        /*
+         * '>' (big), '<' (little), '|'
+         * (not-applicable), or '=' (native).
+         */
+        char byteorder;
+        /* flags describing data type */
+        char flags;
+        /* number representing this type */
+        int type_num;
+        /* element size (itemsize) for this type */
+        int elsize;
+        /* alignment needed for this type */
+        int alignment;
+        /*
+         * Non-NULL if this type is
+         * is an array (C-contiguous)
+         * of some other type
+         */
+        struct _arr_descr *subarray;
+        /*
+         * The fields dictionary for this type
+         * For statically defined descr this
+         * is always Py_None
+         */
+        PyObject *fields;
+        /*
+         * An ordered tuple of field names or NULL
+         * if no fields are defined
+         */
+        PyObject *names;
+        /*
+         * a table of functions specific for each
+         * basic data descriptor
+         */
+        PyArray_ArrFuncs *f;
+        /* Metadata about this dtype */
+        PyObject *metadata;
+        /*
+         * Metadata specific to the C implementation
+         * of the particular dtype. This was added
+         * for NumPy 1.7.0.
+         */
+        NpyAuxData *c_metadata;
+        /* Cached hash value (-1 if not yet computed).
+         * This was added for NumPy 2.0.0.
+         */
+        npy_hash_t hash;
+} PyArray_Descr;
+
+typedef struct _arr_descr {
+        PyArray_Descr *base;
+        PyObject *shape;       /* a tuple */
+} PyArray_ArrayDescr;
+
+/*
+ * The main array object structure.
+ *
+ * It has been recommended to use the inline functions defined below
+ * (PyArray_DATA and friends) to access fields here for a number of
+ * releases. Direct access to the members themselves is deprecated.
+ * To ensure that your code does not use deprecated access,
+ * #define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
+ * (or NPY_1_8_API_VERSION or higher as required).
+ */
+/* This struct will be moved to a private header in a future release */
+typedef struct tagPyArrayObject_fields {
+    PyObject_HEAD
+    /* Pointer to the raw data buffer */
+    char *data;
+    /* The number of dimensions, also called 'ndim' */
+    int nd;
+    /* The size in each dimension, also called 'shape' */
+    npy_intp *dimensions;
+    /*
+     * Number of bytes to jump to get to the
+     * next element in each dimension
+     */
+    npy_intp *strides;
+    /*
+     * This object is decref'd upon
+     * deletion of array. Except in the
+     * case of WRITEBACKIFCOPY which has
+     * special handling.
+     *
+     * For views it points to the original
+     * array, collapsed so no chains of
+     * views occur.
+     *
+     * For creation from buffer object it
+     * points to an object that should be
+     * decref'd on deletion
+     *
+     * For WRITEBACKIFCOPY flag this is an
+     * array to-be-updated upon calling
+     * PyArray_ResolveWritebackIfCopy
+     */
+    PyObject *base;
+    /* Pointer to type structure */
+    PyArray_Descr *descr;
+    /* Flags describing array -- see below */
+    int flags;
+    /* For weak references */
+    PyObject *weakreflist;
+} PyArrayObject_fields;
+
+/*
+ * To hide the implementation details, we only expose
+ * the Python struct HEAD.
+ */
+#if !defined(NPY_NO_DEPRECATED_API) || \
+    (NPY_NO_DEPRECATED_API < NPY_1_7_API_VERSION)
+/*
+ * Can't put this in npy_deprecated_api.h like the others.
+ * PyArrayObject field access is deprecated as of NumPy 1.7.
+ */
+typedef PyArrayObject_fields PyArrayObject;
+#else
+typedef struct tagPyArrayObject {
+        PyObject_HEAD
+} PyArrayObject;
+#endif
+
+#define NPY_SIZEOF_PYARRAYOBJECT (sizeof(PyArrayObject_fields))
+
+/* Array Flags Object */
+typedef struct PyArrayFlagsObject {
+        PyObject_HEAD
+        PyObject *arr;
+        int flags;
+} PyArrayFlagsObject;
+
+/* Mirrors buffer object to ptr */
+
+typedef struct {
+        PyObject_HEAD
+        PyObject *base;
+        void *ptr;
+        npy_intp len;
+        int flags;
+} PyArray_Chunk;
+
+typedef struct {
+    NPY_DATETIMEUNIT base;
+    int num;
+} PyArray_DatetimeMetaData;
+
+typedef struct {
+    NpyAuxData base;
+    PyArray_DatetimeMetaData meta;
+} PyArray_DatetimeDTypeMetaData;
+
+/*
+ * This structure contains an exploded view of a date-time value.
+ * NaT is represented by year == NPY_DATETIME_NAT.
+ */
+typedef struct {
+        npy_int64 year;
+        npy_int32 month, day, hour, min, sec, us, ps, as;
+} npy_datetimestruct;
+
+/* This is not used internally. */
+typedef struct {
+        npy_int64 day;
+        npy_int32 sec, us, ps, as;
+} npy_timedeltastruct;
+
+typedef int (PyArray_FinalizeFunc)(PyArrayObject *, PyObject *);
+
+/*
+ * Means c-style contiguous (last index varies the fastest). The data
+ * elements right after each other.
+ *
+ * This flag may be requested in constructor functions.
+ * This flag may be tested for in PyArray_FLAGS(arr).
+ */
+#define NPY_ARRAY_C_CONTIGUOUS    0x0001
+
+/*
+ * Set if array is a contiguous Fortran array: the first index varies
+ * the fastest in memory (strides array is reverse of C-contiguous
+ * array)
+ *
+ * This flag may be requested in constructor functions.
+ * This flag may be tested for in PyArray_FLAGS(arr).
+ */
+#define NPY_ARRAY_F_CONTIGUOUS    0x0002
+
+/*
+ * Note: all 0-d arrays are C_CONTIGUOUS and F_CONTIGUOUS. If a
+ * 1-d array is C_CONTIGUOUS it is also F_CONTIGUOUS. Arrays with
+ * more then one dimension can be C_CONTIGUOUS and F_CONTIGUOUS
+ * at the same time if they have either zero or one element.
+ * If NPY_RELAXED_STRIDES_CHECKING is set, a higher dimensional
+ * array is always C_CONTIGUOUS and F_CONTIGUOUS if it has zero elements
+ * and the array is contiguous if ndarray.squeeze() is contiguous.
+ * I.e. dimensions for which `ndarray.shape[dimension] == 1` are
+ * ignored.
+ */
+
+/*
+ * If set, the array owns the data: it will be free'd when the array
+ * is deleted.
+ *
+ * This flag may be tested for in PyArray_FLAGS(arr).
+ */
+#define NPY_ARRAY_OWNDATA         0x0004
+
+/*
+ * An array never has the next four set; they're only used as parameter
+ * flags to the various FromAny functions
+ *
+ * This flag may be requested in constructor functions.
+ */
+
+/* Cause a cast to occur regardless of whether or not it is safe. */
+#define NPY_ARRAY_FORCECAST       0x0010
+
+/*
+ * Always copy the array. Returned arrays are always CONTIGUOUS,
+ * ALIGNED, and WRITEABLE.
+ *
+ * This flag may be requested in constructor functions.
+ */
+#define NPY_ARRAY_ENSURECOPY      0x0020
+
+/*
+ * Make sure the returned array is a base-class ndarray
+ *
+ * This flag may be requested in constructor functions.
+ */
+#define NPY_ARRAY_ENSUREARRAY     0x0040
+
+/*
+ * Make sure that the strides are in units of the element size Needed
+ * for some operations with record-arrays.
+ *
+ * This flag may be requested in constructor functions.
+ */
+#define NPY_ARRAY_ELEMENTSTRIDES  0x0080
+
+/*
+ * Array data is aligned on the appropriate memory address for the type
+ * stored according to how the compiler would align things (e.g., an
+ * array of integers (4 bytes each) starts on a memory address that's
+ * a multiple of 4)
+ *
+ * This flag may be requested in constructor functions.
+ * This flag may be tested for in PyArray_FLAGS(arr).
+ */
+#define NPY_ARRAY_ALIGNED         0x0100
+
+/*
+ * Array data has the native endianness
+ *
+ * This flag may be requested in constructor functions.
+ */
+#define NPY_ARRAY_NOTSWAPPED      0x0200
+
+/*
+ * Array data is writeable
+ *
+ * This flag may be requested in constructor functions.
+ * This flag may be tested for in PyArray_FLAGS(arr).
+ */
+#define NPY_ARRAY_WRITEABLE       0x0400
+
+/*
+ * If this flag is set, then base contains a pointer to an array of
+ * the same size that should be updated with the current contents of
+ * this array when PyArray_ResolveWritebackIfCopy is called.
+ *
+ * This flag may be requested in constructor functions.
+ * This flag may be tested for in PyArray_FLAGS(arr).
+ */
+#define NPY_ARRAY_UPDATEIFCOPY    0x1000 /* Deprecated in 1.14 */
+#define NPY_ARRAY_WRITEBACKIFCOPY 0x2000
+
+/*
+ * NOTE: there are also internal flags defined in multiarray/arrayobject.h,
+ * which start at bit 31 and work down.
+ */
+
+#define NPY_ARRAY_BEHAVED      (NPY_ARRAY_ALIGNED | \
+                                NPY_ARRAY_WRITEABLE)
+#define NPY_ARRAY_BEHAVED_NS   (NPY_ARRAY_ALIGNED | \
+                                NPY_ARRAY_WRITEABLE | \
+                                NPY_ARRAY_NOTSWAPPED)
+#define NPY_ARRAY_CARRAY       (NPY_ARRAY_C_CONTIGUOUS | \
+                                NPY_ARRAY_BEHAVED)
+#define NPY_ARRAY_CARRAY_RO    (NPY_ARRAY_C_CONTIGUOUS | \
+                                NPY_ARRAY_ALIGNED)
+#define NPY_ARRAY_FARRAY       (NPY_ARRAY_F_CONTIGUOUS | \
+                                NPY_ARRAY_BEHAVED)
+#define NPY_ARRAY_FARRAY_RO    (NPY_ARRAY_F_CONTIGUOUS | \
+                                NPY_ARRAY_ALIGNED)
+#define NPY_ARRAY_DEFAULT      (NPY_ARRAY_CARRAY)
+#define NPY_ARRAY_IN_ARRAY     (NPY_ARRAY_CARRAY_RO)
+#define NPY_ARRAY_OUT_ARRAY    (NPY_ARRAY_CARRAY)
+#define NPY_ARRAY_INOUT_ARRAY  (NPY_ARRAY_CARRAY | \
+                                NPY_ARRAY_UPDATEIFCOPY)
+#define NPY_ARRAY_INOUT_ARRAY2 (NPY_ARRAY_CARRAY | \
+                                NPY_ARRAY_WRITEBACKIFCOPY)
+#define NPY_ARRAY_IN_FARRAY    (NPY_ARRAY_FARRAY_RO)
+#define NPY_ARRAY_OUT_FARRAY   (NPY_ARRAY_FARRAY)
+#define NPY_ARRAY_INOUT_FARRAY (NPY_ARRAY_FARRAY | \
+                                NPY_ARRAY_UPDATEIFCOPY)
+#define NPY_ARRAY_INOUT_FARRAY2 (NPY_ARRAY_FARRAY | \
+                                NPY_ARRAY_WRITEBACKIFCOPY)
+
+#define NPY_ARRAY_UPDATE_ALL   (NPY_ARRAY_C_CONTIGUOUS | \
+                                NPY_ARRAY_F_CONTIGUOUS | \
+                                NPY_ARRAY_ALIGNED)
+
+/* This flag is for the array interface, not PyArrayObject */
+#define NPY_ARR_HAS_DESCR  0x0800
+
+
+
+
+/*
+ * Size of internal buffers used for alignment Make BUFSIZE a multiple
+ * of sizeof(npy_cdouble) -- usually 16 so that ufunc buffers are aligned
+ */
+#define NPY_MIN_BUFSIZE ((int)sizeof(npy_cdouble))
+#define NPY_MAX_BUFSIZE (((int)sizeof(npy_cdouble))*1000000)
+#define NPY_BUFSIZE 8192
+/* buffer stress test size: */
+/*#define NPY_BUFSIZE 17*/
+
+#define PyArray_MAX(a,b) (((a)>(b))?(a):(b))
+#define PyArray_MIN(a,b) (((a)<(b))?(a):(b))
+#define PyArray_CLT(p,q) ((((p).real==(q).real) ? ((p).imag < (q).imag) : \
+                               ((p).real < (q).real)))
+#define PyArray_CGT(p,q) ((((p).real==(q).real) ? ((p).imag > (q).imag) : \
+                               ((p).real > (q).real)))
+#define PyArray_CLE(p,q) ((((p).real==(q).real) ? ((p).imag <= (q).imag) : \
+                               ((p).real <= (q).real)))
+#define PyArray_CGE(p,q) ((((p).real==(q).real) ? ((p).imag >= (q).imag) : \
+                               ((p).real >= (q).real)))
+#define PyArray_CEQ(p,q) (((p).real==(q).real) && ((p).imag == (q).imag))
+#define PyArray_CNE(p,q) (((p).real!=(q).real) || ((p).imag != (q).imag))
+
+/*
+ * C API: consists of Macros and functions.  The MACROS are defined
+ * here.
+ */
+
+
+#define PyArray_ISCONTIGUOUS(m) PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS)
+#define PyArray_ISWRITEABLE(m) PyArray_CHKFLAGS(m, NPY_ARRAY_WRITEABLE)
+#define PyArray_ISALIGNED(m) PyArray_CHKFLAGS(m, NPY_ARRAY_ALIGNED)
+
+#define PyArray_IS_C_CONTIGUOUS(m) PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS)
+#define PyArray_IS_F_CONTIGUOUS(m) PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS)
+
+/* the variable is used in some places, so always define it */
+#define NPY_BEGIN_THREADS_DEF PyThreadState *_save=NULL;
+#if NPY_ALLOW_THREADS
+#define NPY_BEGIN_ALLOW_THREADS Py_BEGIN_ALLOW_THREADS
+#define NPY_END_ALLOW_THREADS Py_END_ALLOW_THREADS
+#define NPY_BEGIN_THREADS do {_save = PyEval_SaveThread();} while (0);
+#define NPY_END_THREADS   do { if (_save) \
+                { PyEval_RestoreThread(_save); _save = NULL;} } while (0);
+#define NPY_BEGIN_THREADS_THRESHOLDED(loop_size) do { if (loop_size > 500) \
+                { _save = PyEval_SaveThread();} } while (0);
+
+#define NPY_BEGIN_THREADS_DESCR(dtype) \
+        do {if (!(PyDataType_FLAGCHK(dtype, NPY_NEEDS_PYAPI))) \
+                NPY_BEGIN_THREADS;} while (0);
+
+#define NPY_END_THREADS_DESCR(dtype) \
+        do {if (!(PyDataType_FLAGCHK(dtype, NPY_NEEDS_PYAPI))) \
+                NPY_END_THREADS; } while (0);
+
+#define NPY_ALLOW_C_API_DEF  PyGILState_STATE __save__;
+#define NPY_ALLOW_C_API      do {__save__ = PyGILState_Ensure();} while (0);
+#define NPY_DISABLE_C_API    do {PyGILState_Release(__save__);} while (0);
+#else
+#define NPY_BEGIN_ALLOW_THREADS
+#define NPY_END_ALLOW_THREADS
+#define NPY_BEGIN_THREADS
+#define NPY_END_THREADS
+#define NPY_BEGIN_THREADS_THRESHOLDED(loop_size)
+#define NPY_BEGIN_THREADS_DESCR(dtype)
+#define NPY_END_THREADS_DESCR(dtype)
+#define NPY_ALLOW_C_API_DEF
+#define NPY_ALLOW_C_API
+#define NPY_DISABLE_C_API
+#endif
+
+/**********************************
+ * The nditer object, added in 1.6
+ **********************************/
+
+/* The actual structure of the iterator is an internal detail */
+typedef struct NpyIter_InternalOnly NpyIter;
+
+/* Iterator function pointers that may be specialized */
+typedef int (NpyIter_IterNextFunc)(NpyIter *iter);
+typedef void (NpyIter_GetMultiIndexFunc)(NpyIter *iter,
+                                      npy_intp *outcoords);
+
+/*** Global flags that may be passed to the iterator constructors ***/
+
+/* Track an index representing C order */
+#define NPY_ITER_C_INDEX                    0x00000001
+/* Track an index representing Fortran order */
+#define NPY_ITER_F_INDEX                    0x00000002
+/* Track a multi-index */
+#define NPY_ITER_MULTI_INDEX                0x00000004
+/* User code external to the iterator does the 1-dimensional innermost loop */
+#define NPY_ITER_EXTERNAL_LOOP              0x00000008
+/* Convert all the operands to a common data type */
+#define NPY_ITER_COMMON_DTYPE               0x00000010
+/* Operands may hold references, requiring API access during iteration */
+#define NPY_ITER_REFS_OK                    0x00000020
+/* Zero-sized operands should be permitted, iteration checks IterSize for 0 */
+#define NPY_ITER_ZEROSIZE_OK                0x00000040
+/* Permits reductions (size-0 stride with dimension size > 1) */
+#define NPY_ITER_REDUCE_OK                  0x00000080
+/* Enables sub-range iteration */
+#define NPY_ITER_RANGED                     0x00000100
+/* Enables buffering */
+#define NPY_ITER_BUFFERED                   0x00000200
+/* When buffering is enabled, grows the inner loop if possible */
+#define NPY_ITER_GROWINNER                  0x00000400
+/* Delay allocation of buffers until first Reset* call */
+#define NPY_ITER_DELAY_BUFALLOC             0x00000800
+/* When NPY_KEEPORDER is specified, disable reversing negative-stride axes */
+#define NPY_ITER_DONT_NEGATE_STRIDES        0x00001000
+/*
+ * If output operands overlap with other operands (based on heuristics that
+ * has false positives but no false negatives), make temporary copies to
+ * eliminate overlap.
+ */
+#define NPY_ITER_COPY_IF_OVERLAP            0x00002000
+
+/*** Per-operand flags that may be passed to the iterator constructors ***/
+
+/* The operand will be read from and written to */
+#define NPY_ITER_READWRITE                  0x00010000
+/* The operand will only be read from */
+#define NPY_ITER_READONLY                   0x00020000
+/* The operand will only be written to */
+#define NPY_ITER_WRITEONLY                  0x00040000
+/* The operand's data must be in native byte order */
+#define NPY_ITER_NBO                        0x00080000
+/* The operand's data must be aligned */
+#define NPY_ITER_ALIGNED                    0x00100000
+/* The operand's data must be contiguous (within the inner loop) */
+#define NPY_ITER_CONTIG                     0x00200000
+/* The operand may be copied to satisfy requirements */
+#define NPY_ITER_COPY                       0x00400000
+/* The operand may be copied with WRITEBACKIFCOPY to satisfy requirements */
+#define NPY_ITER_UPDATEIFCOPY               0x00800000
+/* Allocate the operand if it is NULL */
+#define NPY_ITER_ALLOCATE                   0x01000000
+/* If an operand is allocated, don't use any subtype */
+#define NPY_ITER_NO_SUBTYPE                 0x02000000
+/* This is a virtual array slot, operand is NULL but temporary data is there */
+#define NPY_ITER_VIRTUAL                    0x04000000
+/* Require that the dimension match the iterator dimensions exactly */
+#define NPY_ITER_NO_BROADCAST               0x08000000
+/* A mask is being used on this array, affects buffer -> array copy */
+#define NPY_ITER_WRITEMASKED                0x10000000
+/* This array is the mask for all WRITEMASKED operands */
+#define NPY_ITER_ARRAYMASK                  0x20000000
+/* Assume iterator order data access for COPY_IF_OVERLAP */
+#define NPY_ITER_OVERLAP_ASSUME_ELEMENTWISE 0x40000000
+
+#define NPY_ITER_GLOBAL_FLAGS               0x0000ffff
+#define NPY_ITER_PER_OP_FLAGS               0xffff0000
+
+
+/*****************************
+ * Basic iterator object
+ *****************************/
+
+/* FWD declaration */
+typedef struct PyArrayIterObject_tag PyArrayIterObject;
+
+/*
+ * type of the function which translates a set of coordinates to a
+ * pointer to the data
+ */
+typedef char* (*npy_iter_get_dataptr_t)(PyArrayIterObject* iter, npy_intp*);
+
+struct PyArrayIterObject_tag {
+        PyObject_HEAD
+        int               nd_m1;            /* number of dimensions - 1 */
+        npy_intp          index, size;
+        npy_intp          coordinates[NPY_MAXDIMS];/* N-dimensional loop */
+        npy_intp          dims_m1[NPY_MAXDIMS];    /* ao->dimensions - 1 */
+        npy_intp          strides[NPY_MAXDIMS];    /* ao->strides or fake */
+        npy_intp          backstrides[NPY_MAXDIMS];/* how far to jump back */
+        npy_intp          factors[NPY_MAXDIMS];     /* shape factors */
+        PyArrayObject     *ao;
+        char              *dataptr;        /* pointer to current item*/
+        npy_bool          contiguous;
+
+        npy_intp          bounds[NPY_MAXDIMS][2];
+        npy_intp          limits[NPY_MAXDIMS][2];
+        npy_intp          limits_sizes[NPY_MAXDIMS];
+        npy_iter_get_dataptr_t translate;
+} ;
+
+
+/* Iterator API */
+#define PyArrayIter_Check(op) PyObject_TypeCheck(op, &PyArrayIter_Type)
+
+#define _PyAIT(it) ((PyArrayIterObject *)(it))
+#define PyArray_ITER_RESET(it) do { \
+        _PyAIT(it)->index = 0; \
+        _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao); \
+        memset(_PyAIT(it)->coordinates, 0, \
+               (_PyAIT(it)->nd_m1+1)*sizeof(npy_intp)); \
+} while (0)
+
+#define _PyArray_ITER_NEXT1(it) do { \
+        (it)->dataptr += _PyAIT(it)->strides[0]; \
+        (it)->coordinates[0]++; \
+} while (0)
+
+#define _PyArray_ITER_NEXT2(it) do { \
+        if ((it)->coordinates[1] < (it)->dims_m1[1]) { \
+                (it)->coordinates[1]++; \
+                (it)->dataptr += (it)->strides[1]; \
+        } \
+        else { \
+                (it)->coordinates[1] = 0; \
+                (it)->coordinates[0]++; \
+                (it)->dataptr += (it)->strides[0] - \
+                        (it)->backstrides[1]; \
+        } \
+} while (0)
+
+#define PyArray_ITER_NEXT(it) do { \
+        _PyAIT(it)->index++; \
+        if (_PyAIT(it)->nd_m1 == 0) { \
+                _PyArray_ITER_NEXT1(_PyAIT(it)); \
+        } \
+        else if (_PyAIT(it)->contiguous) \
+                _PyAIT(it)->dataptr += PyArray_DESCR(_PyAIT(it)->ao)->elsize; \
+        else if (_PyAIT(it)->nd_m1 == 1) { \
+                _PyArray_ITER_NEXT2(_PyAIT(it)); \
+        } \
+        else { \
+                int __npy_i; \
+                for (__npy_i=_PyAIT(it)->nd_m1; __npy_i >= 0; __npy_i--) { \
+                        if (_PyAIT(it)->coordinates[__npy_i] < \
+                            _PyAIT(it)->dims_m1[__npy_i]) { \
+                                _PyAIT(it)->coordinates[__npy_i]++; \
+                                _PyAIT(it)->dataptr += \
+                                        _PyAIT(it)->strides[__npy_i]; \
+                                break; \
+                        } \
+                        else { \
+                                _PyAIT(it)->coordinates[__npy_i] = 0; \
+                                _PyAIT(it)->dataptr -= \
+                                        _PyAIT(it)->backstrides[__npy_i]; \
+                        } \
+                } \
+        } \
+} while (0)
+
+#define PyArray_ITER_GOTO(it, destination) do { \
+        int __npy_i; \
+        _PyAIT(it)->index = 0; \
+        _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao); \
+        for (__npy_i = _PyAIT(it)->nd_m1; __npy_i>=0; __npy_i--) { \
+                if (destination[__npy_i] < 0) { \
+                        destination[__npy_i] += \
+                                _PyAIT(it)->dims_m1[__npy_i]+1; \
+                } \
+                _PyAIT(it)->dataptr += destination[__npy_i] * \
+                        _PyAIT(it)->strides[__npy_i]; \
+                _PyAIT(it)->coordinates[__npy_i] = \
+                        destination[__npy_i]; \
+                _PyAIT(it)->index += destination[__npy_i] * \
+                        ( __npy_i==_PyAIT(it)->nd_m1 ? 1 : \
+                          _PyAIT(it)->dims_m1[__npy_i+1]+1) ; \
+        } \
+} while (0)
+
+#define PyArray_ITER_GOTO1D(it, ind) do { \
+        int __npy_i; \
+        npy_intp __npy_ind = (npy_intp) (ind); \
+        if (__npy_ind < 0) __npy_ind += _PyAIT(it)->size; \
+        _PyAIT(it)->index = __npy_ind; \
+        if (_PyAIT(it)->nd_m1 == 0) { \
+                _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao) + \
+                        __npy_ind * _PyAIT(it)->strides[0]; \
+        } \
+        else if (_PyAIT(it)->contiguous) \
+                _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao) + \
+                        __npy_ind * PyArray_DESCR(_PyAIT(it)->ao)->elsize; \
+        else { \
+                _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao); \
+                for (__npy_i = 0; __npy_i<=_PyAIT(it)->nd_m1; \
+                     __npy_i++) { \
+                        _PyAIT(it)->dataptr += \
+                                (__npy_ind / _PyAIT(it)->factors[__npy_i]) \
+                                * _PyAIT(it)->strides[__npy_i]; \
+                        __npy_ind %= _PyAIT(it)->factors[__npy_i]; \
+                } \
+        } \
+} while (0)
+
+#define PyArray_ITER_DATA(it) ((void *)(_PyAIT(it)->dataptr))
+
+#define PyArray_ITER_NOTDONE(it) (_PyAIT(it)->index < _PyAIT(it)->size)
+
+
+/*
+ * Any object passed to PyArray_Broadcast must be binary compatible
+ * with this structure.
+ */
+
+typedef struct {
+        PyObject_HEAD
+        int                  numiter;                 /* number of iters */
+        npy_intp             size;                    /* broadcasted size */
+        npy_intp             index;                   /* current index */
+        int                  nd;                      /* number of dims */
+        npy_intp             dimensions[NPY_MAXDIMS]; /* dimensions */
+        PyArrayIterObject    *iters[NPY_MAXARGS];     /* iterators */
+} PyArrayMultiIterObject;
+
+#define _PyMIT(m) ((PyArrayMultiIterObject *)(m))
+#define PyArray_MultiIter_RESET(multi) do {                                   \
+        int __npy_mi;                                                         \
+        _PyMIT(multi)->index = 0;                                             \
+        for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter;  __npy_mi++) {    \
+                PyArray_ITER_RESET(_PyMIT(multi)->iters[__npy_mi]);           \
+        }                                                                     \
+} while (0)
+
+#define PyArray_MultiIter_NEXT(multi) do {                                    \
+        int __npy_mi;                                                         \
+        _PyMIT(multi)->index++;                                               \
+        for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter;   __npy_mi++) {   \
+                PyArray_ITER_NEXT(_PyMIT(multi)->iters[__npy_mi]);            \
+        }                                                                     \
+} while (0)
+
+#define PyArray_MultiIter_GOTO(multi, dest) do {                            \
+        int __npy_mi;                                                       \
+        for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter; __npy_mi++) {   \
+                PyArray_ITER_GOTO(_PyMIT(multi)->iters[__npy_mi], dest);    \
+        }                                                                   \
+        _PyMIT(multi)->index = _PyMIT(multi)->iters[0]->index;              \
+} while (0)
+
+#define PyArray_MultiIter_GOTO1D(multi, ind) do {                          \
+        int __npy_mi;                                                      \
+        for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter; __npy_mi++) {  \
+                PyArray_ITER_GOTO1D(_PyMIT(multi)->iters[__npy_mi], ind);  \
+        }                                                                  \
+        _PyMIT(multi)->index = _PyMIT(multi)->iters[0]->index;             \
+} while (0)
+
+#define PyArray_MultiIter_DATA(multi, i)                \
+        ((void *)(_PyMIT(multi)->iters[i]->dataptr))
+
+#define PyArray_MultiIter_NEXTi(multi, i)               \
+        PyArray_ITER_NEXT(_PyMIT(multi)->iters[i])
+
+#define PyArray_MultiIter_NOTDONE(multi)                \
+        (_PyMIT(multi)->index < _PyMIT(multi)->size)
+
+
+/*
+ * Store the information needed for fancy-indexing over an array. The
+ * fields are slightly unordered to keep consec, dataptr and subspace
+ * where they were originally.
+ */
+typedef struct {
+        PyObject_HEAD
+        /*
+         * Multi-iterator portion --- needs to be present in this
+         * order to work with PyArray_Broadcast
+         */
+
+        int                   numiter;                 /* number of index-array
+                                                          iterators */
+        npy_intp              size;                    /* size of broadcasted
+                                                          result */
+        npy_intp              index;                   /* current index */
+        int                   nd;                      /* number of dims */
+        npy_intp              dimensions[NPY_MAXDIMS]; /* dimensions */
+        NpyIter               *outer;                  /* index objects
+                                                          iterator */
+        void                  *unused[NPY_MAXDIMS - 2];
+        PyArrayObject         *array;
+        /* Flat iterator for the indexed array. For compatibility solely. */
+        PyArrayIterObject     *ait;
+
+        /*
+         * Subspace array. For binary compatibility (was an iterator,
+         * but only the check for NULL should be used).
+         */
+        PyArrayObject         *subspace;
+
+        /*
+         * if subspace iteration, then this is the array of axes in
+         * the underlying array represented by the index objects
+         */
+        int                   iteraxes[NPY_MAXDIMS];
+        npy_intp              fancy_strides[NPY_MAXDIMS];
+
+        /* pointer when all fancy indices are 0 */
+        char                  *baseoffset;
+
+        /*
+         * after binding consec denotes at which axis the fancy axes
+         * are inserted.
+         */
+        int                   consec;
+        char                  *dataptr;
+
+        int                   nd_fancy;
+        npy_intp              fancy_dims[NPY_MAXDIMS];
+
+        /* Whether the iterator (any of the iterators) requires API */
+        int                   needs_api;
+
+        /*
+         * Extra op information.
+         */
+        PyArrayObject         *extra_op;
+        PyArray_Descr         *extra_op_dtype;         /* desired dtype */
+        npy_uint32            *extra_op_flags;         /* Iterator flags */
+
+        NpyIter               *extra_op_iter;
+        NpyIter_IterNextFunc  *extra_op_next;
+        char                  **extra_op_ptrs;
+
+        /*
+         * Information about the iteration state.
+         */
+        NpyIter_IterNextFunc  *outer_next;
+        char                  **outer_ptrs;
+        npy_intp              *outer_strides;
+
+        /*
+         * Information about the subspace iterator.
+         */
+        NpyIter               *subspace_iter;
+        NpyIter_IterNextFunc  *subspace_next;
+        char                  **subspace_ptrs;
+        npy_intp              *subspace_strides;
+
+        /* Count for the external loop (which ever it is) for API iteration */
+        npy_intp              iter_count;
+
+} PyArrayMapIterObject;
+
+enum {
+    NPY_NEIGHBORHOOD_ITER_ZERO_PADDING,
+    NPY_NEIGHBORHOOD_ITER_ONE_PADDING,
+    NPY_NEIGHBORHOOD_ITER_CONSTANT_PADDING,
+    NPY_NEIGHBORHOOD_ITER_CIRCULAR_PADDING,
+    NPY_NEIGHBORHOOD_ITER_MIRROR_PADDING
+};
+
+typedef struct {
+    PyObject_HEAD
+
+    /*
+     * PyArrayIterObject part: keep this in this exact order
+     */
+    int               nd_m1;            /* number of dimensions - 1 */
+    npy_intp          index, size;
+    npy_intp          coordinates[NPY_MAXDIMS];/* N-dimensional loop */
+    npy_intp          dims_m1[NPY_MAXDIMS];    /* ao->dimensions - 1 */
+    npy_intp          strides[NPY_MAXDIMS];    /* ao->strides or fake */
+    npy_intp          backstrides[NPY_MAXDIMS];/* how far to jump back */
+    npy_intp          factors[NPY_MAXDIMS];     /* shape factors */
+    PyArrayObject     *ao;
+    char              *dataptr;        /* pointer to current item*/
+    npy_bool          contiguous;
+
+    npy_intp          bounds[NPY_MAXDIMS][2];
+    npy_intp          limits[NPY_MAXDIMS][2];
+    npy_intp          limits_sizes[NPY_MAXDIMS];
+    npy_iter_get_dataptr_t translate;
+
+    /*
+     * New members
+     */
+    npy_intp nd;
+
+    /* Dimensions is the dimension of the array */
+    npy_intp dimensions[NPY_MAXDIMS];
+
+    /*
+     * Neighborhood points coordinates are computed relatively to the
+     * point pointed by _internal_iter
+     */
+    PyArrayIterObject* _internal_iter;
+    /*
+     * To keep a reference to the representation of the constant value
+     * for constant padding
+     */
+    char* constant;
+
+    int mode;
+} PyArrayNeighborhoodIterObject;
+
+/*
+ * Neighborhood iterator API
+ */
+
+/* General: those work for any mode */
+static NPY_INLINE int
+PyArrayNeighborhoodIter_Reset(PyArrayNeighborhoodIterObject* iter);
+static NPY_INLINE int
+PyArrayNeighborhoodIter_Next(PyArrayNeighborhoodIterObject* iter);
+#if 0
+static NPY_INLINE int
+PyArrayNeighborhoodIter_Next2D(PyArrayNeighborhoodIterObject* iter);
+#endif
+
+/*
+ * Include inline implementations - functions defined there are not
+ * considered public API
+ */
+#define _NPY_INCLUDE_NEIGHBORHOOD_IMP
+#include "_neighborhood_iterator_imp.h"
+#undef _NPY_INCLUDE_NEIGHBORHOOD_IMP
+
+/* The default array type */
+#define NPY_DEFAULT_TYPE NPY_DOUBLE
+
+/*
+ * All sorts of useful ways to look into a PyArrayObject. It is recommended
+ * to use PyArrayObject * objects instead of always casting from PyObject *,
+ * for improved type checking.
+ *
+ * In many cases here the macro versions of the accessors are deprecated,
+ * but can't be immediately changed to inline functions because the
+ * preexisting macros accept PyObject * and do automatic casts. Inline
+ * functions accepting PyArrayObject * provides for some compile-time
+ * checking of correctness when working with these objects in C.
+ */
+
+#define PyArray_ISONESEGMENT(m) (PyArray_NDIM(m) == 0 || \
+                             PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS) || \
+                             PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS))
+
+#define PyArray_ISFORTRAN(m) (PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS) && \
+                             (!PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS)))
+
+#define PyArray_FORTRAN_IF(m) ((PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS) ? \
+                               NPY_ARRAY_F_CONTIGUOUS : 0))
+
+#if (defined(NPY_NO_DEPRECATED_API) && (NPY_1_7_API_VERSION <= NPY_NO_DEPRECATED_API))
+/*
+ * Changing access macros into functions, to allow for future hiding
+ * of the internal memory layout. This later hiding will allow the 2.x series
+ * to change the internal representation of arrays without affecting
+ * ABI compatibility.
+ */
+
+static NPY_INLINE int
+PyArray_NDIM(const PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->nd;
+}
+
+static NPY_INLINE void *
+PyArray_DATA(PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->data;
+}
+
+static NPY_INLINE char *
+PyArray_BYTES(PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->data;
+}
+
+static NPY_INLINE npy_intp *
+PyArray_DIMS(PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->dimensions;
+}
+
+static NPY_INLINE npy_intp *
+PyArray_STRIDES(PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->strides;
+}
+
+static NPY_INLINE npy_intp
+PyArray_DIM(const PyArrayObject *arr, int idim)
+{
+    return ((PyArrayObject_fields *)arr)->dimensions[idim];
+}
+
+static NPY_INLINE npy_intp
+PyArray_STRIDE(const PyArrayObject *arr, int istride)
+{
+    return ((PyArrayObject_fields *)arr)->strides[istride];
+}
+
+static NPY_INLINE NPY_RETURNS_BORROWED_REF PyObject *
+PyArray_BASE(PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->base;
+}
+
+static NPY_INLINE NPY_RETURNS_BORROWED_REF PyArray_Descr *
+PyArray_DESCR(PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->descr;
+}
+
+static NPY_INLINE int
+PyArray_FLAGS(const PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->flags;
+}
+
+static NPY_INLINE npy_intp
+PyArray_ITEMSIZE(const PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->descr->elsize;
+}
+
+static NPY_INLINE int
+PyArray_TYPE(const PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->descr->type_num;
+}
+
+static NPY_INLINE int
+PyArray_CHKFLAGS(const PyArrayObject *arr, int flags)
+{
+    return (PyArray_FLAGS(arr) & flags) == flags;
+}
+
+static NPY_INLINE PyObject *
+PyArray_GETITEM(const PyArrayObject *arr, const char *itemptr)
+{
+    return ((PyArrayObject_fields *)arr)->descr->f->getitem(
+                                        (void *)itemptr, (PyArrayObject *)arr);
+}
+
+static NPY_INLINE int
+PyArray_SETITEM(PyArrayObject *arr, char *itemptr, PyObject *v)
+{
+    return ((PyArrayObject_fields *)arr)->descr->f->setitem(
+                                                        v, itemptr, arr);
+}
+
+#else
+
+/* These macros are deprecated as of NumPy 1.7. */
+#define PyArray_NDIM(obj) (((PyArrayObject_fields *)(obj))->nd)
+#define PyArray_BYTES(obj) (((PyArrayObject_fields *)(obj))->data)
+#define PyArray_DATA(obj) ((void *)((PyArrayObject_fields *)(obj))->data)
+#define PyArray_DIMS(obj) (((PyArrayObject_fields *)(obj))->dimensions)
+#define PyArray_STRIDES(obj) (((PyArrayObject_fields *)(obj))->strides)
+#define PyArray_DIM(obj,n) (PyArray_DIMS(obj)[n])
+#define PyArray_STRIDE(obj,n) (PyArray_STRIDES(obj)[n])
+#define PyArray_BASE(obj) (((PyArrayObject_fields *)(obj))->base)
+#define PyArray_DESCR(obj) (((PyArrayObject_fields *)(obj))->descr)
+#define PyArray_FLAGS(obj) (((PyArrayObject_fields *)(obj))->flags)
+#define PyArray_CHKFLAGS(m, FLAGS) \
+        ((((PyArrayObject_fields *)(m))->flags & (FLAGS)) == (FLAGS))
+#define PyArray_ITEMSIZE(obj) \
+                    (((PyArrayObject_fields *)(obj))->descr->elsize)
+#define PyArray_TYPE(obj) \
+                    (((PyArrayObject_fields *)(obj))->descr->type_num)
+#define PyArray_GETITEM(obj,itemptr) \
+        PyArray_DESCR(obj)->f->getitem((char *)(itemptr), \
+                                     (PyArrayObject *)(obj))
+
+#define PyArray_SETITEM(obj,itemptr,v) \
+        PyArray_DESCR(obj)->f->setitem((PyObject *)(v), \
+                                     (char *)(itemptr), \
+                                     (PyArrayObject *)(obj))
+#endif
+
+static NPY_INLINE PyArray_Descr *
+PyArray_DTYPE(PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->descr;
+}
+
+static NPY_INLINE npy_intp *
+PyArray_SHAPE(PyArrayObject *arr)
+{
+    return ((PyArrayObject_fields *)arr)->dimensions;
+}
+
+/*
+ * Enables the specified array flags. Does no checking,
+ * assumes you know what you're doing.
+ */
+static NPY_INLINE void
+PyArray_ENABLEFLAGS(PyArrayObject *arr, int flags)
+{
+    ((PyArrayObject_fields *)arr)->flags |= flags;
+}
+
+/*
+ * Clears the specified array flags. Does no checking,
+ * assumes you know what you're doing.
+ */
+static NPY_INLINE void
+PyArray_CLEARFLAGS(PyArrayObject *arr, int flags)
+{
+    ((PyArrayObject_fields *)arr)->flags &= ~flags;
+}
+
+#define PyTypeNum_ISBOOL(type) ((type) == NPY_BOOL)
+
+#define PyTypeNum_ISUNSIGNED(type) (((type) == NPY_UBYTE) ||   \
+                                 ((type) == NPY_USHORT) ||     \
+                                 ((type) == NPY_UINT) ||       \
+                                 ((type) == NPY_ULONG) ||      \
+                                 ((type) == NPY_ULONGLONG))
+
+#define PyTypeNum_ISSIGNED(type) (((type) == NPY_BYTE) ||      \
+                               ((type) == NPY_SHORT) ||        \
+                               ((type) == NPY_INT) ||          \
+                               ((type) == NPY_LONG) ||         \
+                               ((type) == NPY_LONGLONG))
+
+#define PyTypeNum_ISINTEGER(type) (((type) >= NPY_BYTE) &&     \
+                                ((type) <= NPY_ULONGLONG))
+
+#define PyTypeNum_ISFLOAT(type) ((((type) >= NPY_FLOAT) && \
+                              ((type) <= NPY_LONGDOUBLE)) || \
+                              ((type) == NPY_HALF))
+
+#define PyTypeNum_ISNUMBER(type) (((type) <= NPY_CLONGDOUBLE) || \
+                                  ((type) == NPY_HALF))
+
+#define PyTypeNum_ISSTRING(type) (((type) == NPY_STRING) ||    \
+                                  ((type) == NPY_UNICODE))
+
+#define PyTypeNum_ISCOMPLEX(type) (((type) >= NPY_CFLOAT) &&   \
+                                ((type) <= NPY_CLONGDOUBLE))
+
+#define PyTypeNum_ISPYTHON(type) (((type) == NPY_LONG) ||      \
+                                  ((type) == NPY_DOUBLE) ||    \
+                                  ((type) == NPY_CDOUBLE) ||   \
+                                  ((type) == NPY_BOOL) ||      \
+                                  ((type) == NPY_OBJECT ))
+
+#define PyTypeNum_ISFLEXIBLE(type) (((type) >=NPY_STRING) &&  \
+                                    ((type) <=NPY_VOID))
+
+#define PyTypeNum_ISDATETIME(type) (((type) >=NPY_DATETIME) &&  \
+                                    ((type) <=NPY_TIMEDELTA))
+
+#define PyTypeNum_ISUSERDEF(type) (((type) >= NPY_USERDEF) && \
+                                   ((type) < NPY_USERDEF+     \
+                                    NPY_NUMUSERTYPES))
+
+#define PyTypeNum_ISEXTENDED(type) (PyTypeNum_ISFLEXIBLE(type) ||  \
+                                    PyTypeNum_ISUSERDEF(type))
+
+#define PyTypeNum_ISOBJECT(type) ((type) == NPY_OBJECT)
+
+
+#define PyDataType_ISBOOL(obj) PyTypeNum_ISBOOL(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISUNSIGNED(obj) PyTypeNum_ISUNSIGNED(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISSIGNED(obj) PyTypeNum_ISSIGNED(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISINTEGER(obj) PyTypeNum_ISINTEGER(((PyArray_Descr*)(obj))->type_num )
+#define PyDataType_ISFLOAT(obj) PyTypeNum_ISFLOAT(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISNUMBER(obj) PyTypeNum_ISNUMBER(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISSTRING(obj) PyTypeNum_ISSTRING(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISCOMPLEX(obj) PyTypeNum_ISCOMPLEX(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISPYTHON(obj) PyTypeNum_ISPYTHON(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISFLEXIBLE(obj) PyTypeNum_ISFLEXIBLE(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISDATETIME(obj) PyTypeNum_ISDATETIME(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISUSERDEF(obj) PyTypeNum_ISUSERDEF(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISEXTENDED(obj) PyTypeNum_ISEXTENDED(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_ISOBJECT(obj) PyTypeNum_ISOBJECT(((PyArray_Descr*)(obj))->type_num)
+#define PyDataType_HASFIELDS(obj) (((PyArray_Descr *)(obj))->names != NULL)
+#define PyDataType_HASSUBARRAY(dtype) ((dtype)->subarray != NULL)
+#define PyDataType_ISUNSIZED(dtype) ((dtype)->elsize == 0)
+#define PyDataType_MAKEUNSIZED(dtype) ((dtype)->elsize = 0)
+
+#define PyArray_ISBOOL(obj) PyTypeNum_ISBOOL(PyArray_TYPE(obj))
+#define PyArray_ISUNSIGNED(obj) PyTypeNum_ISUNSIGNED(PyArray_TYPE(obj))
+#define PyArray_ISSIGNED(obj) PyTypeNum_ISSIGNED(PyArray_TYPE(obj))
+#define PyArray_ISINTEGER(obj) PyTypeNum_ISINTEGER(PyArray_TYPE(obj))
+#define PyArray_ISFLOAT(obj) PyTypeNum_ISFLOAT(PyArray_TYPE(obj))
+#define PyArray_ISNUMBER(obj) PyTypeNum_ISNUMBER(PyArray_TYPE(obj))
+#define PyArray_ISSTRING(obj) PyTypeNum_ISSTRING(PyArray_TYPE(obj))
+#define PyArray_ISCOMPLEX(obj) PyTypeNum_ISCOMPLEX(PyArray_TYPE(obj))
+#define PyArray_ISPYTHON(obj) PyTypeNum_ISPYTHON(PyArray_TYPE(obj))
+#define PyArray_ISFLEXIBLE(obj) PyTypeNum_ISFLEXIBLE(PyArray_TYPE(obj))
+#define PyArray_ISDATETIME(obj) PyTypeNum_ISDATETIME(PyArray_TYPE(obj))
+#define PyArray_ISUSERDEF(obj) PyTypeNum_ISUSERDEF(PyArray_TYPE(obj))
+#define PyArray_ISEXTENDED(obj) PyTypeNum_ISEXTENDED(PyArray_TYPE(obj))
+#define PyArray_ISOBJECT(obj) PyTypeNum_ISOBJECT(PyArray_TYPE(obj))
+#define PyArray_HASFIELDS(obj) PyDataType_HASFIELDS(PyArray_DESCR(obj))
+
+    /*
+     * FIXME: This should check for a flag on the data-type that
+     * states whether or not it is variable length.  Because the
+     * ISFLEXIBLE check is hard-coded to the built-in data-types.
+     */
+#define PyArray_ISVARIABLE(obj) PyTypeNum_ISFLEXIBLE(PyArray_TYPE(obj))
+
+#define PyArray_SAFEALIGNEDCOPY(obj) (PyArray_ISALIGNED(obj) && !PyArray_ISVARIABLE(obj))
+
+
+#define NPY_LITTLE '<'
+#define NPY_BIG '>'
+#define NPY_NATIVE '='
+#define NPY_SWAP 's'
+#define NPY_IGNORE '|'
+
+#if NPY_BYTE_ORDER == NPY_BIG_ENDIAN
+#define NPY_NATBYTE NPY_BIG
+#define NPY_OPPBYTE NPY_LITTLE
+#else
+#define NPY_NATBYTE NPY_LITTLE
+#define NPY_OPPBYTE NPY_BIG
+#endif
+
+#define PyArray_ISNBO(arg) ((arg) != NPY_OPPBYTE)
+#define PyArray_IsNativeByteOrder PyArray_ISNBO
+#define PyArray_ISNOTSWAPPED(m) PyArray_ISNBO(PyArray_DESCR(m)->byteorder)
+#define PyArray_ISBYTESWAPPED(m) (!PyArray_ISNOTSWAPPED(m))
+
+#define PyArray_FLAGSWAP(m, flags) (PyArray_CHKFLAGS(m, flags) &&       \
+                                    PyArray_ISNOTSWAPPED(m))
+
+#define PyArray_ISCARRAY(m) PyArray_FLAGSWAP(m, NPY_ARRAY_CARRAY)
+#define PyArray_ISCARRAY_RO(m) PyArray_FLAGSWAP(m, NPY_ARRAY_CARRAY_RO)
+#define PyArray_ISFARRAY(m) PyArray_FLAGSWAP(m, NPY_ARRAY_FARRAY)
+#define PyArray_ISFARRAY_RO(m) PyArray_FLAGSWAP(m, NPY_ARRAY_FARRAY_RO)
+#define PyArray_ISBEHAVED(m) PyArray_FLAGSWAP(m, NPY_ARRAY_BEHAVED)
+#define PyArray_ISBEHAVED_RO(m) PyArray_FLAGSWAP(m, NPY_ARRAY_ALIGNED)
+
+
+#define PyDataType_ISNOTSWAPPED(d) PyArray_ISNBO(((PyArray_Descr *)(d))->byteorder)
+#define PyDataType_ISBYTESWAPPED(d) (!PyDataType_ISNOTSWAPPED(d))
+
+/************************************************************
+ * A struct used by PyArray_CreateSortedStridePerm, new in 1.7.
+ ************************************************************/
+
+typedef struct {
+    npy_intp perm, stride;
+} npy_stride_sort_item;
+
+/************************************************************
+ * This is the form of the struct that's returned pointed by the
+ * PyCObject attribute of an array __array_struct__. See
+ * https://docs.scipy.org/doc/numpy/reference/arrays.interface.html for the full
+ * documentation.
+ ************************************************************/
+typedef struct {
+    int two;              /*
+                           * contains the integer 2 as a sanity
+                           * check
+                           */
+
+    int nd;               /* number of dimensions */
+
+    char typekind;        /*
+                           * kind in array --- character code of
+                           * typestr
+                           */
+
+    int itemsize;         /* size of each element */
+
+    int flags;            /*
+                           * how should be data interpreted. Valid
+                           * flags are CONTIGUOUS (1), F_CONTIGUOUS (2),
+                           * ALIGNED (0x100), NOTSWAPPED (0x200), and
+                           * WRITEABLE (0x400).  ARR_HAS_DESCR (0x800)
+                           * states that arrdescr field is present in
+                           * structure
+                           */
+
+    npy_intp *shape;       /*
+                            * A length-nd array of shape
+                            * information
+                            */
+
+    npy_intp *strides;    /* A length-nd array of stride information */
+
+    void *data;           /* A pointer to the first element of the array */
+
+    PyObject *descr;      /*
+                           * A list of fields or NULL (ignored if flags
+                           * does not have ARR_HAS_DESCR flag set)
+                           */
+} PyArrayInterface;
+
+/*
+ * This is a function for hooking into the PyDataMem_NEW/FREE/RENEW functions.
+ * See the documentation for PyDataMem_SetEventHook.
+ */
+typedef void (PyDataMem_EventHookFunc)(void *inp, void *outp, size_t size,
+                                       void *user_data);
+
+/*
+ * Use the keyword NPY_DEPRECATED_INCLUDES to ensure that the header files
+ * npy_*_*_deprecated_api.h are only included from here and nowhere else.
+ */
+#ifdef NPY_DEPRECATED_INCLUDES
+#error "Do not use the reserved keyword NPY_DEPRECATED_INCLUDES."
+#endif
+#define NPY_DEPRECATED_INCLUDES
+#if !defined(NPY_NO_DEPRECATED_API) || \
+    (NPY_NO_DEPRECATED_API < NPY_1_7_API_VERSION)
+#include "npy_1_7_deprecated_api.h"
+#endif
+/*
+ * There is no file npy_1_8_deprecated_api.h since there are no additional
+ * deprecated API features in NumPy 1.8.
+ *
+ * Note to maintainers: insert code like the following in future NumPy
+ * versions.
+ *
+ * #if !defined(NPY_NO_DEPRECATED_API) || \
+ *     (NPY_NO_DEPRECATED_API < NPY_1_9_API_VERSION)
+ * #include "npy_1_9_deprecated_api.h"
+ * #endif
+ */
+#undef NPY_DEPRECATED_INCLUDES
+
+#endif /* NPY_ARRAYTYPES_H */
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/noprefix.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/noprefix.h
new file mode 100644
index 0000000..041f301
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/noprefix.h
@@ -0,0 +1,212 @@
+#ifndef NPY_NOPREFIX_H
+#define NPY_NOPREFIX_H
+
+/*
+ * You can directly include noprefix.h as a backward
+ * compatibility measure
+ */
+#ifndef NPY_NO_PREFIX
+#include "ndarrayobject.h"
+#include "npy_interrupt.h"
+#endif
+
+#define SIGSETJMP   NPY_SIGSETJMP
+#define SIGLONGJMP  NPY_SIGLONGJMP
+#define SIGJMP_BUF  NPY_SIGJMP_BUF
+
+#define MAX_DIMS NPY_MAXDIMS
+
+#define longlong    npy_longlong
+#define ulonglong   npy_ulonglong
+#define Bool        npy_bool
+#define longdouble  npy_longdouble
+#define byte        npy_byte
+
+#ifndef _BSD_SOURCE
+#define ushort      npy_ushort
+#define uint        npy_uint
+#define ulong       npy_ulong
+#endif
+
+#define ubyte       npy_ubyte
+#define ushort      npy_ushort
+#define uint        npy_uint
+#define ulong       npy_ulong
+#define cfloat      npy_cfloat
+#define cdouble     npy_cdouble
+#define clongdouble npy_clongdouble
+#define Int8        npy_int8
+#define UInt8       npy_uint8
+#define Int16       npy_int16
+#define UInt16      npy_uint16
+#define Int32       npy_int32
+#define UInt32      npy_uint32
+#define Int64       npy_int64
+#define UInt64      npy_uint64
+#define Int128      npy_int128
+#define UInt128     npy_uint128
+#define Int256      npy_int256
+#define UInt256     npy_uint256
+#define Float16     npy_float16
+#define Complex32   npy_complex32
+#define Float32     npy_float32
+#define Complex64   npy_complex64
+#define Float64     npy_float64
+#define Complex128  npy_complex128
+#define Float80     npy_float80
+#define Complex160  npy_complex160
+#define Float96     npy_float96
+#define Complex192  npy_complex192
+#define Float128    npy_float128
+#define Complex256  npy_complex256
+#define intp        npy_intp
+#define uintp       npy_uintp
+#define datetime    npy_datetime
+#define timedelta   npy_timedelta
+
+#define SIZEOF_LONGLONG         NPY_SIZEOF_LONGLONG
+#define SIZEOF_INTP             NPY_SIZEOF_INTP
+#define SIZEOF_UINTP            NPY_SIZEOF_UINTP
+#define SIZEOF_HALF             NPY_SIZEOF_HALF
+#define SIZEOF_LONGDOUBLE       NPY_SIZEOF_LONGDOUBLE
+#define SIZEOF_DATETIME         NPY_SIZEOF_DATETIME
+#define SIZEOF_TIMEDELTA        NPY_SIZEOF_TIMEDELTA
+
+#define LONGLONG_FMT NPY_LONGLONG_FMT
+#define ULONGLONG_FMT NPY_ULONGLONG_FMT
+#define LONGLONG_SUFFIX NPY_LONGLONG_SUFFIX
+#define ULONGLONG_SUFFIX NPY_ULONGLONG_SUFFIX
+
+#define MAX_INT8 127
+#define MIN_INT8 -128
+#define MAX_UINT8 255
+#define MAX_INT16 32767
+#define MIN_INT16 -32768
+#define MAX_UINT16 65535
+#define MAX_INT32 2147483647
+#define MIN_INT32 (-MAX_INT32 - 1)
+#define MAX_UINT32 4294967295U
+#define MAX_INT64 LONGLONG_SUFFIX(9223372036854775807)
+#define MIN_INT64 (-MAX_INT64 - LONGLONG_SUFFIX(1))
+#define MAX_UINT64 ULONGLONG_SUFFIX(18446744073709551615)
+#define MAX_INT128 LONGLONG_SUFFIX(85070591730234615865843651857942052864)
+#define MIN_INT128 (-MAX_INT128 - LONGLONG_SUFFIX(1))
+#define MAX_UINT128 ULONGLONG_SUFFIX(170141183460469231731687303715884105728)
+#define MAX_INT256 LONGLONG_SUFFIX(57896044618658097711785492504343953926634992332820282019728792003956564819967)
+#define MIN_INT256 (-MAX_INT256 - LONGLONG_SUFFIX(1))
+#define MAX_UINT256 ULONGLONG_SUFFIX(115792089237316195423570985008687907853269984665640564039457584007913129639935)
+
+#define MAX_BYTE NPY_MAX_BYTE
+#define MIN_BYTE NPY_MIN_BYTE
+#define MAX_UBYTE NPY_MAX_UBYTE
+#define MAX_SHORT NPY_MAX_SHORT
+#define MIN_SHORT NPY_MIN_SHORT
+#define MAX_USHORT NPY_MAX_USHORT
+#define MAX_INT   NPY_MAX_INT
+#define MIN_INT   NPY_MIN_INT
+#define MAX_UINT  NPY_MAX_UINT
+#define MAX_LONG  NPY_MAX_LONG
+#define MIN_LONG  NPY_MIN_LONG
+#define MAX_ULONG  NPY_MAX_ULONG
+#define MAX_LONGLONG NPY_MAX_LONGLONG
+#define MIN_LONGLONG NPY_MIN_LONGLONG
+#define MAX_ULONGLONG NPY_MAX_ULONGLONG
+#define MIN_DATETIME NPY_MIN_DATETIME
+#define MAX_DATETIME NPY_MAX_DATETIME
+#define MIN_TIMEDELTA NPY_MIN_TIMEDELTA
+#define MAX_TIMEDELTA NPY_MAX_TIMEDELTA
+
+#define BITSOF_BOOL       NPY_BITSOF_BOOL
+#define BITSOF_CHAR       NPY_BITSOF_CHAR
+#define BITSOF_SHORT      NPY_BITSOF_SHORT
+#define BITSOF_INT        NPY_BITSOF_INT
+#define BITSOF_LONG       NPY_BITSOF_LONG
+#define BITSOF_LONGLONG   NPY_BITSOF_LONGLONG
+#define BITSOF_HALF       NPY_BITSOF_HALF
+#define BITSOF_FLOAT      NPY_BITSOF_FLOAT
+#define BITSOF_DOUBLE     NPY_BITSOF_DOUBLE
+#define BITSOF_LONGDOUBLE NPY_BITSOF_LONGDOUBLE
+#define BITSOF_DATETIME   NPY_BITSOF_DATETIME
+#define BITSOF_TIMEDELTA   NPY_BITSOF_TIMEDELTA
+
+#define _pya_malloc PyArray_malloc
+#define _pya_free PyArray_free
+#define _pya_realloc PyArray_realloc
+
+#define BEGIN_THREADS_DEF NPY_BEGIN_THREADS_DEF
+#define BEGIN_THREADS     NPY_BEGIN_THREADS
+#define END_THREADS       NPY_END_THREADS
+#define ALLOW_C_API_DEF   NPY_ALLOW_C_API_DEF
+#define ALLOW_C_API       NPY_ALLOW_C_API
+#define DISABLE_C_API     NPY_DISABLE_C_API
+
+#define PY_FAIL NPY_FAIL
+#define PY_SUCCEED NPY_SUCCEED
+
+#ifndef TRUE
+#define TRUE NPY_TRUE
+#endif
+
+#ifndef FALSE
+#define FALSE NPY_FALSE
+#endif
+
+#define LONGDOUBLE_FMT NPY_LONGDOUBLE_FMT
+
+#define CONTIGUOUS         NPY_CONTIGUOUS
+#define C_CONTIGUOUS       NPY_C_CONTIGUOUS
+#define FORTRAN            NPY_FORTRAN
+#define F_CONTIGUOUS       NPY_F_CONTIGUOUS
+#define OWNDATA            NPY_OWNDATA
+#define FORCECAST          NPY_FORCECAST
+#define ENSURECOPY         NPY_ENSURECOPY
+#define ENSUREARRAY        NPY_ENSUREARRAY
+#define ELEMENTSTRIDES     NPY_ELEMENTSTRIDES
+#define ALIGNED            NPY_ALIGNED
+#define NOTSWAPPED         NPY_NOTSWAPPED
+#define WRITEABLE          NPY_WRITEABLE
+#define UPDATEIFCOPY       NPY_UPDATEIFCOPY
+#define WRITEBACKIFCOPY    NPY_ARRAY_WRITEBACKIFCOPY
+#define ARR_HAS_DESCR      NPY_ARR_HAS_DESCR
+#define BEHAVED            NPY_BEHAVED
+#define BEHAVED_NS         NPY_BEHAVED_NS
+#define CARRAY             NPY_CARRAY
+#define CARRAY_RO          NPY_CARRAY_RO
+#define FARRAY             NPY_FARRAY
+#define FARRAY_RO          NPY_FARRAY_RO
+#define DEFAULT            NPY_DEFAULT
+#define IN_ARRAY           NPY_IN_ARRAY
+#define OUT_ARRAY          NPY_OUT_ARRAY
+#define INOUT_ARRAY        NPY_INOUT_ARRAY
+#define IN_FARRAY          NPY_IN_FARRAY
+#define OUT_FARRAY         NPY_OUT_FARRAY
+#define INOUT_FARRAY       NPY_INOUT_FARRAY
+#define UPDATE_ALL         NPY_UPDATE_ALL
+
+#define OWN_DATA          NPY_OWNDATA
+#define BEHAVED_FLAGS     NPY_BEHAVED
+#define BEHAVED_FLAGS_NS  NPY_BEHAVED_NS
+#define CARRAY_FLAGS_RO   NPY_CARRAY_RO
+#define CARRAY_FLAGS      NPY_CARRAY
+#define FARRAY_FLAGS      NPY_FARRAY
+#define FARRAY_FLAGS_RO   NPY_FARRAY_RO
+#define DEFAULT_FLAGS     NPY_DEFAULT
+#define UPDATE_ALL_FLAGS  NPY_UPDATE_ALL_FLAGS
+
+#ifndef MIN
+#define MIN PyArray_MIN
+#endif
+#ifndef MAX
+#define MAX PyArray_MAX
+#endif
+#define MAX_INTP NPY_MAX_INTP
+#define MIN_INTP NPY_MIN_INTP
+#define MAX_UINTP NPY_MAX_UINTP
+#define INTP_FMT NPY_INTP_FMT
+
+#ifndef PYPY_VERSION
+#define REFCOUNT PyArray_REFCOUNT
+#define MAX_ELSIZE NPY_MAX_ELSIZE
+#endif
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_1_7_deprecated_api.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_1_7_deprecated_api.h
new file mode 100644
index 0000000..a6ee212
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_1_7_deprecated_api.h
@@ -0,0 +1,133 @@
+#ifndef _NPY_1_7_DEPRECATED_API_H
+#define _NPY_1_7_DEPRECATED_API_H
+
+#ifndef NPY_DEPRECATED_INCLUDES
+#error "Should never include npy_*_*_deprecated_api directly."
+#endif
+
+/* Emit a warning if the user did not specifically request the old API */
+#ifndef NPY_NO_DEPRECATED_API
+#if defined(_WIN32)
+#define _WARN___STR2__(x) #x
+#define _WARN___STR1__(x) _WARN___STR2__(x)
+#define _WARN___LOC__ __FILE__ "(" _WARN___STR1__(__LINE__) ") : Warning Msg: "
+#pragma message(_WARN___LOC__"Using deprecated NumPy API, disable it with " \
+                         "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION")
+#elif defined(__GNUC__)
+#warning "Using deprecated NumPy API, disable it with " \
+         "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION"
+#endif
+/* TODO: How to do this warning message for other compilers? */
+#endif
+
+/*
+ * This header exists to collect all dangerous/deprecated NumPy API
+ * as of NumPy 1.7.
+ *
+ * This is an attempt to remove bad API, the proliferation of macros,
+ * and namespace pollution currently produced by the NumPy headers.
+ */
+
+/* These array flags are deprecated as of NumPy 1.7 */
+#define NPY_CONTIGUOUS NPY_ARRAY_C_CONTIGUOUS
+#define NPY_FORTRAN NPY_ARRAY_F_CONTIGUOUS
+
+/*
+ * The consistent NPY_ARRAY_* names which don't pollute the NPY_*
+ * namespace were added in NumPy 1.7.
+ *
+ * These versions of the carray flags are deprecated, but
+ * probably should only be removed after two releases instead of one.
+ */
+#define NPY_C_CONTIGUOUS   NPY_ARRAY_C_CONTIGUOUS
+#define NPY_F_CONTIGUOUS   NPY_ARRAY_F_CONTIGUOUS
+#define NPY_OWNDATA        NPY_ARRAY_OWNDATA
+#define NPY_FORCECAST      NPY_ARRAY_FORCECAST
+#define NPY_ENSURECOPY     NPY_ARRAY_ENSURECOPY
+#define NPY_ENSUREARRAY    NPY_ARRAY_ENSUREARRAY
+#define NPY_ELEMENTSTRIDES NPY_ARRAY_ELEMENTSTRIDES
+#define NPY_ALIGNED        NPY_ARRAY_ALIGNED
+#define NPY_NOTSWAPPED     NPY_ARRAY_NOTSWAPPED
+#define NPY_WRITEABLE      NPY_ARRAY_WRITEABLE
+#define NPY_UPDATEIFCOPY   NPY_ARRAY_UPDATEIFCOPY
+#define NPY_BEHAVED        NPY_ARRAY_BEHAVED
+#define NPY_BEHAVED_NS     NPY_ARRAY_BEHAVED_NS
+#define NPY_CARRAY         NPY_ARRAY_CARRAY
+#define NPY_CARRAY_RO      NPY_ARRAY_CARRAY_RO
+#define NPY_FARRAY         NPY_ARRAY_FARRAY
+#define NPY_FARRAY_RO      NPY_ARRAY_FARRAY_RO
+#define NPY_DEFAULT        NPY_ARRAY_DEFAULT
+#define NPY_IN_ARRAY       NPY_ARRAY_IN_ARRAY
+#define NPY_OUT_ARRAY      NPY_ARRAY_OUT_ARRAY
+#define NPY_INOUT_ARRAY    NPY_ARRAY_INOUT_ARRAY
+#define NPY_IN_FARRAY      NPY_ARRAY_IN_FARRAY
+#define NPY_OUT_FARRAY     NPY_ARRAY_OUT_FARRAY
+#define NPY_INOUT_FARRAY   NPY_ARRAY_INOUT_FARRAY
+#define NPY_UPDATE_ALL     NPY_ARRAY_UPDATE_ALL
+
+/* This way of accessing the default type is deprecated as of NumPy 1.7 */
+#define PyArray_DEFAULT NPY_DEFAULT_TYPE
+
+/* These DATETIME bits aren't used internally */
+#if PY_VERSION_HEX >= 0x03000000
+#define PyDataType_GetDatetimeMetaData(descr)                                 \
+    ((descr->metadata == NULL) ? NULL :                                       \
+        ((PyArray_DatetimeMetaData *)(PyCapsule_GetPointer(                   \
+                PyDict_GetItemString(                                         \
+                    descr->metadata, NPY_METADATA_DTSTR), NULL))))
+#else
+#define PyDataType_GetDatetimeMetaData(descr)                                 \
+    ((descr->metadata == NULL) ? NULL :                                       \
+        ((PyArray_DatetimeMetaData *)(PyCObject_AsVoidPtr(                    \
+                PyDict_GetItemString(descr->metadata, NPY_METADATA_DTSTR)))))
+#endif
+
+/*
+ * Deprecated as of NumPy 1.7, this kind of shortcut doesn't
+ * belong in the public API.
+ */
+#define NPY_AO PyArrayObject
+
+/*
+ * Deprecated as of NumPy 1.7, an all-lowercase macro doesn't
+ * belong in the public API.
+ */
+#define fortran fortran_
+
+/*
+ * Deprecated as of NumPy 1.7, as it is a namespace-polluting
+ * macro.
+ */
+#define FORTRAN_IF PyArray_FORTRAN_IF
+
+/* Deprecated as of NumPy 1.7, datetime64 uses c_metadata instead */
+#define NPY_METADATA_DTSTR "__timeunit__"
+
+/*
+ * Deprecated as of NumPy 1.7.
+ * The reasoning:
+ *  - These are for datetime, but there's no datetime "namespace".
+ *  - They just turn NPY_STR_<x> into "<x>", which is just
+ *    making something simple be indirected.
+ */
+#define NPY_STR_Y "Y"
+#define NPY_STR_M "M"
+#define NPY_STR_W "W"
+#define NPY_STR_D "D"
+#define NPY_STR_h "h"
+#define NPY_STR_m "m"
+#define NPY_STR_s "s"
+#define NPY_STR_ms "ms"
+#define NPY_STR_us "us"
+#define NPY_STR_ns "ns"
+#define NPY_STR_ps "ps"
+#define NPY_STR_fs "fs"
+#define NPY_STR_as "as"
+
+/*
+ * The macros in old_defines.h are Deprecated as of NumPy 1.7 and will be
+ * removed in the next major release.
+ */
+#include "old_defines.h"
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_3kcompat.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_3kcompat.h
new file mode 100644
index 0000000..832bc05
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_3kcompat.h
@@ -0,0 +1,577 @@
+/*
+ * This is a convenience header file providing compatibility utilities
+ * for supporting Python 2 and Python 3 in the same code base.
+ *
+ * If you want to use this for your own projects, it's recommended to make a
+ * copy of it. Although the stuff below is unlikely to change, we don't provide
+ * strong backwards compatibility guarantees at the moment.
+ */
+
+#ifndef _NPY_3KCOMPAT_H_
+#define _NPY_3KCOMPAT_H_
+
+#include <Python.h>
+#include <stdio.h>
+
+#if PY_VERSION_HEX >= 0x03000000
+#ifndef NPY_PY3K
+#define NPY_PY3K 1
+#endif
+#endif
+
+#include "numpy/npy_common.h"
+#include "numpy/ndarrayobject.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*
+ * PyInt -> PyLong
+ */
+
+#if defined(NPY_PY3K)
+/* Return True only if the long fits in a C long */
+static NPY_INLINE int PyInt_Check(PyObject *op) {
+    int overflow = 0;
+    if (!PyLong_Check(op)) {
+        return 0;
+    }
+    PyLong_AsLongAndOverflow(op, &overflow);
+    return (overflow == 0);
+}
+
+#define PyInt_FromLong PyLong_FromLong
+#define PyInt_AsLong PyLong_AsLong
+#define PyInt_AS_LONG PyLong_AsLong
+#define PyInt_AsSsize_t PyLong_AsSsize_t
+
+/* NOTE:
+ *
+ * Since the PyLong type is very different from the fixed-range PyInt,
+ * we don't define PyInt_Type -> PyLong_Type.
+ */
+#endif /* NPY_PY3K */
+
+/* Py3 changes PySlice_GetIndicesEx' first argument's type to PyObject* */
+#ifdef NPY_PY3K
+#  define NpySlice_GetIndicesEx PySlice_GetIndicesEx
+#else
+#  define NpySlice_GetIndicesEx(op, nop, start, end, step, slicelength) \
+    PySlice_GetIndicesEx((PySliceObject *)op, nop, start, end, step, slicelength)
+#endif
+
+/* <2.7.11 and <3.4.4 have the wrong argument type for Py_EnterRecursiveCall */
+#if (PY_VERSION_HEX < 0x02070B00) || \
+    ((0x03000000 <= PY_VERSION_HEX) && (PY_VERSION_HEX < 0x03040400))
+    #define Npy_EnterRecursiveCall(x) Py_EnterRecursiveCall((char *)(x))
+#else
+    #define Npy_EnterRecursiveCall(x) Py_EnterRecursiveCall(x)
+#endif
+
+/* Py_SETREF was added in 3.5.2, and only if Py_LIMITED_API is absent */
+#if PY_VERSION_HEX < 0x03050200
+    #define Py_SETREF(op, op2)                      \
+        do {                                        \
+            PyObject *_py_tmp = (PyObject *)(op);   \
+            (op) = (op2);                           \
+            Py_DECREF(_py_tmp);                     \
+        } while (0)
+#endif
+
+/*
+ * PyString -> PyBytes
+ */
+
+#if defined(NPY_PY3K)
+
+#define PyString_Type PyBytes_Type
+#define PyString_Check PyBytes_Check
+#define PyStringObject PyBytesObject
+#define PyString_FromString PyBytes_FromString
+#define PyString_FromStringAndSize PyBytes_FromStringAndSize
+#define PyString_AS_STRING PyBytes_AS_STRING
+#define PyString_AsStringAndSize PyBytes_AsStringAndSize
+#define PyString_FromFormat PyBytes_FromFormat
+#define PyString_Concat PyBytes_Concat
+#define PyString_ConcatAndDel PyBytes_ConcatAndDel
+#define PyString_AsString PyBytes_AsString
+#define PyString_GET_SIZE PyBytes_GET_SIZE
+#define PyString_Size PyBytes_Size
+
+#define PyUString_Type PyUnicode_Type
+#define PyUString_Check PyUnicode_Check
+#define PyUStringObject PyUnicodeObject
+#define PyUString_FromString PyUnicode_FromString
+#define PyUString_FromStringAndSize PyUnicode_FromStringAndSize
+#define PyUString_FromFormat PyUnicode_FromFormat
+#define PyUString_Concat PyUnicode_Concat2
+#define PyUString_ConcatAndDel PyUnicode_ConcatAndDel
+#define PyUString_GET_SIZE PyUnicode_GET_SIZE
+#define PyUString_Size PyUnicode_Size
+#define PyUString_InternFromString PyUnicode_InternFromString
+#define PyUString_Format PyUnicode_Format
+
+#define PyBaseString_Check(obj) (PyUnicode_Check(obj))
+
+#else
+
+#define PyBytes_Type PyString_Type
+#define PyBytes_Check PyString_Check
+#define PyBytesObject PyStringObject
+#define PyBytes_FromString PyString_FromString
+#define PyBytes_FromStringAndSize PyString_FromStringAndSize
+#define PyBytes_AS_STRING PyString_AS_STRING
+#define PyBytes_AsStringAndSize PyString_AsStringAndSize
+#define PyBytes_FromFormat PyString_FromFormat
+#define PyBytes_Concat PyString_Concat
+#define PyBytes_ConcatAndDel PyString_ConcatAndDel
+#define PyBytes_AsString PyString_AsString
+#define PyBytes_GET_SIZE PyString_GET_SIZE
+#define PyBytes_Size PyString_Size
+
+#define PyUString_Type PyString_Type
+#define PyUString_Check PyString_Check
+#define PyUStringObject PyStringObject
+#define PyUString_FromString PyString_FromString
+#define PyUString_FromStringAndSize PyString_FromStringAndSize
+#define PyUString_FromFormat PyString_FromFormat
+#define PyUString_Concat PyString_Concat
+#define PyUString_ConcatAndDel PyString_ConcatAndDel
+#define PyUString_GET_SIZE PyString_GET_SIZE
+#define PyUString_Size PyString_Size
+#define PyUString_InternFromString PyString_InternFromString
+#define PyUString_Format PyString_Format
+
+#define PyBaseString_Check(obj) (PyBytes_Check(obj) || PyUnicode_Check(obj))
+
+#endif /* NPY_PY3K */
+
+
+static NPY_INLINE void
+PyUnicode_ConcatAndDel(PyObject **left, PyObject *right)
+{
+    Py_SETREF(*left, PyUnicode_Concat(*left, right));
+    Py_DECREF(right);
+}
+
+static NPY_INLINE void
+PyUnicode_Concat2(PyObject **left, PyObject *right)
+{
+    Py_SETREF(*left, PyUnicode_Concat(*left, right));
+}
+
+/*
+ * PyFile_* compatibility
+ */
+
+/*
+ * Get a FILE* handle to the file represented by the Python object
+ */
+static NPY_INLINE FILE*
+npy_PyFile_Dup2(PyObject *file, char *mode, npy_off_t *orig_pos)
+{
+    int fd, fd2, unbuf;
+    PyObject *ret, *os, *io, *io_raw;
+    npy_off_t pos;
+    FILE *handle;
+
+    /* For Python 2 PyFileObject, use PyFile_AsFile */
+#if !defined(NPY_PY3K)
+    if (PyFile_Check(file)) {
+        return PyFile_AsFile(file);
+    }
+#endif
+
+    /* Flush first to ensure things end up in the file in the correct order */
+    ret = PyObject_CallMethod(file, "flush", "");
+    if (ret == NULL) {
+        return NULL;
+    }
+    Py_DECREF(ret);
+    fd = PyObject_AsFileDescriptor(file);
+    if (fd == -1) {
+        return NULL;
+    }
+
+    /*
+     * The handle needs to be dup'd because we have to call fclose
+     * at the end
+     */
+    os = PyImport_ImportModule("os");
+    if (os == NULL) {
+        return NULL;
+    }
+    ret = PyObject_CallMethod(os, "dup", "i", fd);
+    Py_DECREF(os);
+    if (ret == NULL) {
+        return NULL;
+    }
+    fd2 = PyNumber_AsSsize_t(ret, NULL);
+    Py_DECREF(ret);
+
+    /* Convert to FILE* handle */
+#ifdef _WIN32
+    handle = _fdopen(fd2, mode);
+#else
+    handle = fdopen(fd2, mode);
+#endif
+    if (handle == NULL) {
+        PyErr_SetString(PyExc_IOError,
+                        "Getting a FILE* from a Python file object failed");
+        return NULL;
+    }
+
+    /* Record the original raw file handle position */
+    *orig_pos = npy_ftell(handle);
+    if (*orig_pos == -1) {
+        /* The io module is needed to determine if buffering is used */
+        io = PyImport_ImportModule("io");
+        if (io == NULL) {
+            fclose(handle);
+            return NULL;
+        }
+        /* File object instances of RawIOBase are unbuffered */
+        io_raw = PyObject_GetAttrString(io, "RawIOBase");
+        Py_DECREF(io);
+        if (io_raw == NULL) {
+            fclose(handle);
+            return NULL;
+        }
+        unbuf = PyObject_IsInstance(file, io_raw);
+        Py_DECREF(io_raw);
+        if (unbuf == 1) {
+            /* Succeed if the IO is unbuffered */
+            return handle;
+        }
+        else {
+            PyErr_SetString(PyExc_IOError, "obtaining file position failed");
+            fclose(handle);
+            return NULL;
+        }
+    }
+
+    /* Seek raw handle to the Python-side position */
+    ret = PyObject_CallMethod(file, "tell", "");
+    if (ret == NULL) {
+        fclose(handle);
+        return NULL;
+    }
+    pos = PyLong_AsLongLong(ret);
+    Py_DECREF(ret);
+    if (PyErr_Occurred()) {
+        fclose(handle);
+        return NULL;
+    }
+    if (npy_fseek(handle, pos, SEEK_SET) == -1) {
+        PyErr_SetString(PyExc_IOError, "seeking file failed");
+        fclose(handle);
+        return NULL;
+    }
+    return handle;
+}
+
+/*
+ * Close the dup-ed file handle, and seek the Python one to the current position
+ */
+static NPY_INLINE int
+npy_PyFile_DupClose2(PyObject *file, FILE* handle, npy_off_t orig_pos)
+{
+    int fd, unbuf;
+    PyObject *ret, *io, *io_raw;
+    npy_off_t position;
+
+    /* For Python 2 PyFileObject, do nothing */
+#if !defined(NPY_PY3K)
+    if (PyFile_Check(file)) {
+        return 0;
+    }
+#endif
+
+    position = npy_ftell(handle);
+
+    /* Close the FILE* handle */
+    fclose(handle);
+
+    /*
+     * Restore original file handle position, in order to not confuse
+     * Python-side data structures
+     */
+    fd = PyObject_AsFileDescriptor(file);
+    if (fd == -1) {
+        return -1;
+    }
+
+    if (npy_lseek(fd, orig_pos, SEEK_SET) == -1) {
+
+        /* The io module is needed to determine if buffering is used */
+        io = PyImport_ImportModule("io");
+        if (io == NULL) {
+            return -1;
+        }
+        /* File object instances of RawIOBase are unbuffered */
+        io_raw = PyObject_GetAttrString(io, "RawIOBase");
+        Py_DECREF(io);
+        if (io_raw == NULL) {
+            return -1;
+        }
+        unbuf = PyObject_IsInstance(file, io_raw);
+        Py_DECREF(io_raw);
+        if (unbuf == 1) {
+            /* Succeed if the IO is unbuffered */
+            return 0;
+        }
+        else {
+            PyErr_SetString(PyExc_IOError, "seeking file failed");
+            return -1;
+        }
+    }
+
+    if (position == -1) {
+        PyErr_SetString(PyExc_IOError, "obtaining file position failed");
+        return -1;
+    }
+
+    /* Seek Python-side handle to the FILE* handle position */
+    ret = PyObject_CallMethod(file, "seek", NPY_OFF_T_PYFMT "i", position, 0);
+    if (ret == NULL) {
+        return -1;
+    }
+    Py_DECREF(ret);
+    return 0;
+}
+
+static NPY_INLINE int
+npy_PyFile_Check(PyObject *file)
+{
+    int fd;
+    /* For Python 2, check if it is a PyFileObject */
+#if !defined(NPY_PY3K)
+    if (PyFile_Check(file)) {
+        return 1;
+    }
+#endif
+    fd = PyObject_AsFileDescriptor(file);
+    if (fd == -1) {
+        PyErr_Clear();
+        return 0;
+    }
+    return 1;
+}
+
+static NPY_INLINE PyObject*
+npy_PyFile_OpenFile(PyObject *filename, const char *mode)
+{
+    PyObject *open;
+    open = PyDict_GetItemString(PyEval_GetBuiltins(), "open");
+    if (open == NULL) {
+        return NULL;
+    }
+    return PyObject_CallFunction(open, "Os", filename, mode);
+}
+
+static NPY_INLINE int
+npy_PyFile_CloseFile(PyObject *file)
+{
+    PyObject *ret;
+
+    ret = PyObject_CallMethod(file, "close", NULL);
+    if (ret == NULL) {
+        return -1;
+    }
+    Py_DECREF(ret);
+    return 0;
+}
+
+
+/* This is a copy of _PyErr_ChainExceptions
+ */
+static NPY_INLINE void
+npy_PyErr_ChainExceptions(PyObject *exc, PyObject *val, PyObject *tb)
+{
+    if (exc == NULL)
+        return;
+
+    if (PyErr_Occurred()) {
+        /* only py3 supports this anyway */
+        #ifdef NPY_PY3K
+            PyObject *exc2, *val2, *tb2;
+            PyErr_Fetch(&exc2, &val2, &tb2);
+            PyErr_NormalizeException(&exc, &val, &tb);
+            if (tb != NULL) {
+                PyException_SetTraceback(val, tb);
+                Py_DECREF(tb);
+            }
+            Py_DECREF(exc);
+            PyErr_NormalizeException(&exc2, &val2, &tb2);
+            PyException_SetContext(val2, val);
+            PyErr_Restore(exc2, val2, tb2);
+        #endif
+    }
+    else {
+        PyErr_Restore(exc, val, tb);
+    }
+}
+
+
+/* This is a copy of _PyErr_ChainExceptions, with:
+ *  - a minimal implementation for python 2
+ *  - __cause__ used instead of __context__
+ */
+static NPY_INLINE void
+npy_PyErr_ChainExceptionsCause(PyObject *exc, PyObject *val, PyObject *tb)
+{
+    if (exc == NULL)
+        return;
+
+    if (PyErr_Occurred()) {
+        /* only py3 supports this anyway */
+        #ifdef NPY_PY3K
+            PyObject *exc2, *val2, *tb2;
+            PyErr_Fetch(&exc2, &val2, &tb2);
+            PyErr_NormalizeException(&exc, &val, &tb);
+            if (tb != NULL) {
+                PyException_SetTraceback(val, tb);
+                Py_DECREF(tb);
+            }
+            Py_DECREF(exc);
+            PyErr_NormalizeException(&exc2, &val2, &tb2);
+            PyException_SetCause(val2, val);
+            PyErr_Restore(exc2, val2, tb2);
+        #endif
+    }
+    else {
+        PyErr_Restore(exc, val, tb);
+    }
+}
+
+/*
+ * PyObject_Cmp
+ */
+#if defined(NPY_PY3K)
+static NPY_INLINE int
+PyObject_Cmp(PyObject *i1, PyObject *i2, int *cmp)
+{
+    int v;
+    v = PyObject_RichCompareBool(i1, i2, Py_LT);
+    if (v == 1) {
+        *cmp = -1;
+        return 1;
+    }
+    else if (v == -1) {
+        return -1;
+    }
+
+    v = PyObject_RichCompareBool(i1, i2, Py_GT);
+    if (v == 1) {
+        *cmp = 1;
+        return 1;
+    }
+    else if (v == -1) {
+        return -1;
+    }
+
+    v = PyObject_RichCompareBool(i1, i2, Py_EQ);
+    if (v == 1) {
+        *cmp = 0;
+        return 1;
+    }
+    else {
+        *cmp = 0;
+        return -1;
+    }
+}
+#endif
+
+/*
+ * PyCObject functions adapted to PyCapsules.
+ *
+ * The main job here is to get rid of the improved error handling
+ * of PyCapsules. It's a shame...
+ */
+#if PY_VERSION_HEX >= 0x03000000
+
+static NPY_INLINE PyObject *
+NpyCapsule_FromVoidPtr(void *ptr, void (*dtor)(PyObject *))
+{
+    PyObject *ret = PyCapsule_New(ptr, NULL, dtor);
+    if (ret == NULL) {
+        PyErr_Clear();
+    }
+    return ret;
+}
+
+static NPY_INLINE PyObject *
+NpyCapsule_FromVoidPtrAndDesc(void *ptr, void* context, void (*dtor)(PyObject *))
+{
+    PyObject *ret = NpyCapsule_FromVoidPtr(ptr, dtor);
+    if (ret != NULL && PyCapsule_SetContext(ret, context) != 0) {
+        PyErr_Clear();
+        Py_DECREF(ret);
+        ret = NULL;
+    }
+    return ret;
+}
+
+static NPY_INLINE void *
+NpyCapsule_AsVoidPtr(PyObject *obj)
+{
+    void *ret = PyCapsule_GetPointer(obj, NULL);
+    if (ret == NULL) {
+        PyErr_Clear();
+    }
+    return ret;
+}
+
+static NPY_INLINE void *
+NpyCapsule_GetDesc(PyObject *obj)
+{
+    return PyCapsule_GetContext(obj);
+}
+
+static NPY_INLINE int
+NpyCapsule_Check(PyObject *ptr)
+{
+    return PyCapsule_CheckExact(ptr);
+}
+
+#else
+
+static NPY_INLINE PyObject *
+NpyCapsule_FromVoidPtr(void *ptr, void (*dtor)(void *))
+{
+    return PyCObject_FromVoidPtr(ptr, dtor);
+}
+
+static NPY_INLINE PyObject *
+NpyCapsule_FromVoidPtrAndDesc(void *ptr, void* context,
+        void (*dtor)(void *, void *))
+{
+    return PyCObject_FromVoidPtrAndDesc(ptr, context, dtor);
+}
+
+static NPY_INLINE void *
+NpyCapsule_AsVoidPtr(PyObject *ptr)
+{
+    return PyCObject_AsVoidPtr(ptr);
+}
+
+static NPY_INLINE void *
+NpyCapsule_GetDesc(PyObject *obj)
+{
+    return PyCObject_GetDesc(obj);
+}
+
+static NPY_INLINE int
+NpyCapsule_Check(PyObject *ptr)
+{
+    return PyCObject_Check(ptr);
+}
+
+#endif
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif /* _NPY_3KCOMPAT_H_ */
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_common.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_common.h
new file mode 100644
index 0000000..fc88836
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_common.h
@@ -0,0 +1,1083 @@
+#ifndef _NPY_COMMON_H_
+#define _NPY_COMMON_H_
+
+/* numpconfig.h is auto-generated */
+#include "numpyconfig.h"
+#ifdef HAVE_NPY_CONFIG_H
+#include <npy_config.h>
+#endif
+
+/* need Python.h for npy_intp, npy_uintp */
+#include <Python.h>
+
+/*
+ * using static inline modifiers when defining npy_math functions
+ * allows the compiler to make optimizations when possible
+ */
+#if defined(NPY_INTERNAL_BUILD) && NPY_INTERNAL_BUILD
+#ifndef NPY_INLINE_MATH
+#define NPY_INLINE_MATH 1
+#endif
+#endif
+
+/*
+ * gcc does not unroll even with -O3
+ * use with care, unrolling on modern cpus rarely speeds things up
+ */
+#ifdef HAVE_ATTRIBUTE_OPTIMIZE_UNROLL_LOOPS
+#define NPY_GCC_UNROLL_LOOPS \
+    __attribute__((optimize("unroll-loops")))
+#else
+#define NPY_GCC_UNROLL_LOOPS
+#endif
+
+/* highest gcc optimization level, enabled autovectorizer */
+#ifdef HAVE_ATTRIBUTE_OPTIMIZE_OPT_3
+#define NPY_GCC_OPT_3 __attribute__((optimize("O3")))
+#else
+#define NPY_GCC_OPT_3
+#endif
+
+/* compile target attributes */
+#if defined HAVE_ATTRIBUTE_TARGET_AVX && defined HAVE_LINK_AVX
+#define NPY_GCC_TARGET_AVX __attribute__((target("avx")))
+#else
+#define NPY_GCC_TARGET_AVX
+#endif
+#if defined HAVE_ATTRIBUTE_TARGET_AVX2 && defined HAVE_LINK_AVX2
+#define NPY_GCC_TARGET_AVX2 __attribute__((target("avx2")))
+#else
+#define NPY_GCC_TARGET_AVX2
+#endif
+
+/*
+ * mark an argument (starting from 1) that must not be NULL and is not checked
+ * DO NOT USE IF FUNCTION CHECKS FOR NULL!! the compiler will remove the check
+ */
+#ifdef HAVE_ATTRIBUTE_NONNULL
+#define NPY_GCC_NONNULL(n) __attribute__((nonnull(n)))
+#else
+#define NPY_GCC_NONNULL(n)
+#endif
+
+#if defined HAVE_XMMINTRIN_H && defined HAVE__MM_LOAD_PS
+#define NPY_HAVE_SSE_INTRINSICS
+#endif
+
+#if defined HAVE_EMMINTRIN_H && defined HAVE__MM_LOAD_PD
+#define NPY_HAVE_SSE2_INTRINSICS
+#endif
+
+/*
+ * give a hint to the compiler which branch is more likely or unlikely
+ * to occur, e.g. rare error cases:
+ *
+ * if (NPY_UNLIKELY(failure == 0))
+ *    return NULL;
+ *
+ * the double !! is to cast the expression (e.g. NULL) to a boolean required by
+ * the intrinsic
+ */
+#ifdef HAVE___BUILTIN_EXPECT
+#define NPY_LIKELY(x) __builtin_expect(!!(x), 1)
+#define NPY_UNLIKELY(x) __builtin_expect(!!(x), 0)
+#else
+#define NPY_LIKELY(x) (x)
+#define NPY_UNLIKELY(x) (x)
+#endif
+
+#ifdef HAVE___BUILTIN_PREFETCH
+/* unlike _mm_prefetch also works on non-x86 */
+#define NPY_PREFETCH(x, rw, loc) __builtin_prefetch((x), (rw), (loc))
+#else
+#ifdef HAVE__MM_PREFETCH
+/* _MM_HINT_ET[01] (rw = 1) unsupported, only available in gcc >= 4.9 */
+#define NPY_PREFETCH(x, rw, loc) _mm_prefetch((x), loc == 0 ? _MM_HINT_NTA : \
+                                             (loc == 1 ? _MM_HINT_T2 : \
+                                              (loc == 2 ? _MM_HINT_T1 : \
+                                               (loc == 3 ? _MM_HINT_T0 : -1))))
+#else
+#define NPY_PREFETCH(x, rw,loc)
+#endif
+#endif
+
+#if defined(_MSC_VER)
+        #define NPY_INLINE __inline
+#elif defined(__GNUC__)
+    #if defined(__STRICT_ANSI__)
+         #define NPY_INLINE __inline__
+    #else
+         #define NPY_INLINE inline
+    #endif
+#else
+    #define NPY_INLINE
+#endif
+
+#ifdef HAVE___THREAD
+    #define NPY_TLS __thread
+#else
+    #ifdef HAVE___DECLSPEC_THREAD_
+        #define NPY_TLS __declspec(thread)
+    #else
+        #define NPY_TLS
+    #endif
+#endif
+
+#ifdef WITH_CPYCHECKER_RETURNS_BORROWED_REF_ATTRIBUTE
+  #define NPY_RETURNS_BORROWED_REF \
+    __attribute__((cpychecker_returns_borrowed_ref))
+#else
+  #define NPY_RETURNS_BORROWED_REF
+#endif
+
+#ifdef WITH_CPYCHECKER_STEALS_REFERENCE_TO_ARG_ATTRIBUTE
+  #define NPY_STEALS_REF_TO_ARG(n) \
+   __attribute__((cpychecker_steals_reference_to_arg(n)))
+#else
+ #define NPY_STEALS_REF_TO_ARG(n)
+#endif
+
+/* 64 bit file position support, also on win-amd64. Ticket #1660 */
+#if defined(_MSC_VER) && defined(_WIN64) && (_MSC_VER > 1400) || \
+    defined(__MINGW32__) || defined(__MINGW64__)
+    #include <io.h>
+
+/* mingw based on 3.4.5 has lseek but not ftell/fseek */
+#if defined(__MINGW32__) && !defined(__MINGW64_VERSION_MAJOR)
+extern int __cdecl _fseeki64(FILE *, long long, int);
+extern long long __cdecl _ftelli64(FILE *);
+#endif
+
+    #define npy_fseek _fseeki64
+    #define npy_ftell _ftelli64
+    #define npy_lseek _lseeki64
+    #define npy_off_t npy_int64
+
+    #if NPY_SIZEOF_INT == 8
+        #define NPY_OFF_T_PYFMT "i"
+    #elif NPY_SIZEOF_LONG == 8
+        #define NPY_OFF_T_PYFMT "l"
+    #elif NPY_SIZEOF_LONGLONG == 8
+        #define NPY_OFF_T_PYFMT "L"
+    #else
+        #error Unsupported size for type off_t
+    #endif
+#else
+#ifdef HAVE_FSEEKO
+    #define npy_fseek fseeko
+#else
+    #define npy_fseek fseek
+#endif
+#ifdef HAVE_FTELLO
+    #define npy_ftell ftello
+#else
+    #define npy_ftell ftell
+#endif
+    #include <sys/types.h>
+    #define npy_lseek lseek
+    #define npy_off_t off_t
+
+    #if NPY_SIZEOF_OFF_T == NPY_SIZEOF_SHORT
+        #define NPY_OFF_T_PYFMT "h"
+    #elif NPY_SIZEOF_OFF_T == NPY_SIZEOF_INT
+        #define NPY_OFF_T_PYFMT "i"
+    #elif NPY_SIZEOF_OFF_T == NPY_SIZEOF_LONG
+        #define NPY_OFF_T_PYFMT "l"
+    #elif NPY_SIZEOF_OFF_T == NPY_SIZEOF_LONGLONG
+        #define NPY_OFF_T_PYFMT "L"
+    #else
+        #error Unsupported size for type off_t
+    #endif
+#endif
+
+/* enums for detected endianness */
+enum {
+        NPY_CPU_UNKNOWN_ENDIAN,
+        NPY_CPU_LITTLE,
+        NPY_CPU_BIG
+};
+
+/*
+ * This is to typedef npy_intp to the appropriate pointer size for this
+ * platform.  Py_intptr_t, Py_uintptr_t are defined in pyport.h.
+ */
+typedef Py_intptr_t npy_intp;
+typedef Py_uintptr_t npy_uintp;
+
+/*
+ * Define sizes that were not defined in numpyconfig.h.
+ */
+#define NPY_SIZEOF_CHAR 1
+#define NPY_SIZEOF_BYTE 1
+#define NPY_SIZEOF_DATETIME 8
+#define NPY_SIZEOF_TIMEDELTA 8
+#define NPY_SIZEOF_INTP NPY_SIZEOF_PY_INTPTR_T
+#define NPY_SIZEOF_UINTP NPY_SIZEOF_PY_INTPTR_T
+#define NPY_SIZEOF_HALF 2
+#define NPY_SIZEOF_CFLOAT NPY_SIZEOF_COMPLEX_FLOAT
+#define NPY_SIZEOF_CDOUBLE NPY_SIZEOF_COMPLEX_DOUBLE
+#define NPY_SIZEOF_CLONGDOUBLE NPY_SIZEOF_COMPLEX_LONGDOUBLE
+
+#ifdef constchar
+#undef constchar
+#endif
+
+#define NPY_SSIZE_T_PYFMT "n"
+#define constchar char
+
+/* NPY_INTP_FMT Note:
+ *      Unlike the other NPY_*_FMT macros which are used with
+ *      PyOS_snprintf, NPY_INTP_FMT is used with PyErr_Format and
+ *      PyString_Format. These functions use different formatting
+ *      codes which are portably specified according to the Python
+ *      documentation. See ticket #1795.
+ */
+#if NPY_SIZEOF_PY_INTPTR_T == NPY_SIZEOF_INT
+        #define NPY_INTP NPY_INT
+        #define NPY_UINTP NPY_UINT
+        #define PyIntpArrType_Type PyIntArrType_Type
+        #define PyUIntpArrType_Type PyUIntArrType_Type
+        #define NPY_MAX_INTP NPY_MAX_INT
+        #define NPY_MIN_INTP NPY_MIN_INT
+        #define NPY_MAX_UINTP NPY_MAX_UINT
+        #define NPY_INTP_FMT "d"
+#elif NPY_SIZEOF_PY_INTPTR_T == NPY_SIZEOF_LONG
+        #define NPY_INTP NPY_LONG
+        #define NPY_UINTP NPY_ULONG
+        #define PyIntpArrType_Type PyLongArrType_Type
+        #define PyUIntpArrType_Type PyULongArrType_Type
+        #define NPY_MAX_INTP NPY_MAX_LONG
+        #define NPY_MIN_INTP NPY_MIN_LONG
+        #define NPY_MAX_UINTP NPY_MAX_ULONG
+        #define NPY_INTP_FMT "ld"
+#elif defined(PY_LONG_LONG) && (NPY_SIZEOF_PY_INTPTR_T == NPY_SIZEOF_LONGLONG)
+        #define NPY_INTP NPY_LONGLONG
+        #define NPY_UINTP NPY_ULONGLONG
+        #define PyIntpArrType_Type PyLongLongArrType_Type
+        #define PyUIntpArrType_Type PyULongLongArrType_Type
+        #define NPY_MAX_INTP NPY_MAX_LONGLONG
+        #define NPY_MIN_INTP NPY_MIN_LONGLONG
+        #define NPY_MAX_UINTP NPY_MAX_ULONGLONG
+        #define NPY_INTP_FMT "lld"
+#endif
+
+/*
+ * We can only use C99 formats for npy_int_p if it is the same as
+ * intp_t, hence the condition on HAVE_UNITPTR_T
+ */
+#if (NPY_USE_C99_FORMATS) == 1 \
+        && (defined HAVE_UINTPTR_T) \
+        && (defined HAVE_INTTYPES_H)
+        #include <inttypes.h>
+        #undef NPY_INTP_FMT
+        #define NPY_INTP_FMT PRIdPTR
+#endif
+
+
+/*
+ * Some platforms don't define bool, long long, or long double.
+ * Handle that here.
+ */
+#define NPY_BYTE_FMT "hhd"
+#define NPY_UBYTE_FMT "hhu"
+#define NPY_SHORT_FMT "hd"
+#define NPY_USHORT_FMT "hu"
+#define NPY_INT_FMT "d"
+#define NPY_UINT_FMT "u"
+#define NPY_LONG_FMT "ld"
+#define NPY_ULONG_FMT "lu"
+#define NPY_HALF_FMT "g"
+#define NPY_FLOAT_FMT "g"
+#define NPY_DOUBLE_FMT "g"
+
+
+#ifdef PY_LONG_LONG
+typedef PY_LONG_LONG npy_longlong;
+typedef unsigned PY_LONG_LONG npy_ulonglong;
+#  ifdef _MSC_VER
+#    define NPY_LONGLONG_FMT         "I64d"
+#    define NPY_ULONGLONG_FMT        "I64u"
+#  else
+#    define NPY_LONGLONG_FMT         "lld"
+#    define NPY_ULONGLONG_FMT        "llu"
+#  endif
+#  ifdef _MSC_VER
+#    define NPY_LONGLONG_SUFFIX(x)   (x##i64)
+#    define NPY_ULONGLONG_SUFFIX(x)  (x##Ui64)
+#  else
+#    define NPY_LONGLONG_SUFFIX(x)   (x##LL)
+#    define NPY_ULONGLONG_SUFFIX(x)  (x##ULL)
+#  endif
+#else
+typedef long npy_longlong;
+typedef unsigned long npy_ulonglong;
+#  define NPY_LONGLONG_SUFFIX(x)  (x##L)
+#  define NPY_ULONGLONG_SUFFIX(x) (x##UL)
+#endif
+
+
+typedef unsigned char npy_bool;
+#define NPY_FALSE 0
+#define NPY_TRUE 1
+
+
+#if NPY_SIZEOF_LONGDOUBLE == NPY_SIZEOF_DOUBLE
+        typedef double npy_longdouble;
+        #define NPY_LONGDOUBLE_FMT "g"
+#else
+        typedef long double npy_longdouble;
+        #define NPY_LONGDOUBLE_FMT "Lg"
+#endif
+
+#ifndef Py_USING_UNICODE
+#error Must use Python with unicode enabled.
+#endif
+
+
+typedef signed char npy_byte;
+typedef unsigned char npy_ubyte;
+typedef unsigned short npy_ushort;
+typedef unsigned int npy_uint;
+typedef unsigned long npy_ulong;
+
+/* These are for completeness */
+typedef char npy_char;
+typedef short npy_short;
+typedef int npy_int;
+typedef long npy_long;
+typedef float npy_float;
+typedef double npy_double;
+
+/*
+ * Hash value compatibility.
+ * As of Python 3.2 hash values are of type Py_hash_t.
+ * Previous versions use C long.
+ */
+#if PY_VERSION_HEX < 0x03020000
+typedef long npy_hash_t;
+#define NPY_SIZEOF_HASH_T NPY_SIZEOF_LONG
+#else
+typedef Py_hash_t npy_hash_t;
+#define NPY_SIZEOF_HASH_T NPY_SIZEOF_INTP
+#endif
+
+/*
+ * Disabling C99 complex usage: a lot of C code in numpy/scipy rely on being
+ * able to do .real/.imag. Will have to convert code first.
+ */
+#if 0
+#if defined(NPY_USE_C99_COMPLEX) && defined(NPY_HAVE_COMPLEX_DOUBLE)
+typedef complex npy_cdouble;
+#else
+typedef struct { double real, imag; } npy_cdouble;
+#endif
+
+#if defined(NPY_USE_C99_COMPLEX) && defined(NPY_HAVE_COMPLEX_FLOAT)
+typedef complex float npy_cfloat;
+#else
+typedef struct { float real, imag; } npy_cfloat;
+#endif
+
+#if defined(NPY_USE_C99_COMPLEX) && defined(NPY_HAVE_COMPLEX_LONG_DOUBLE)
+typedef complex long double npy_clongdouble;
+#else
+typedef struct {npy_longdouble real, imag;} npy_clongdouble;
+#endif
+#endif
+#if NPY_SIZEOF_COMPLEX_DOUBLE != 2 * NPY_SIZEOF_DOUBLE
+#error npy_cdouble definition is not compatible with C99 complex definition ! \
+        Please contact NumPy maintainers and give detailed information about your \
+        compiler and platform
+#endif
+typedef struct { double real, imag; } npy_cdouble;
+
+#if NPY_SIZEOF_COMPLEX_FLOAT != 2 * NPY_SIZEOF_FLOAT
+#error npy_cfloat definition is not compatible with C99 complex definition ! \
+        Please contact NumPy maintainers and give detailed information about your \
+        compiler and platform
+#endif
+typedef struct { float real, imag; } npy_cfloat;
+
+#if NPY_SIZEOF_COMPLEX_LONGDOUBLE != 2 * NPY_SIZEOF_LONGDOUBLE
+#error npy_clongdouble definition is not compatible with C99 complex definition ! \
+        Please contact NumPy maintainers and give detailed information about your \
+        compiler and platform
+#endif
+typedef struct { npy_longdouble real, imag; } npy_clongdouble;
+
+/*
+ * numarray-style bit-width typedefs
+ */
+#define NPY_MAX_INT8 127
+#define NPY_MIN_INT8 -128
+#define NPY_MAX_UINT8 255
+#define NPY_MAX_INT16 32767
+#define NPY_MIN_INT16 -32768
+#define NPY_MAX_UINT16 65535
+#define NPY_MAX_INT32 2147483647
+#define NPY_MIN_INT32 (-NPY_MAX_INT32 - 1)
+#define NPY_MAX_UINT32 4294967295U
+#define NPY_MAX_INT64 NPY_LONGLONG_SUFFIX(9223372036854775807)
+#define NPY_MIN_INT64 (-NPY_MAX_INT64 - NPY_LONGLONG_SUFFIX(1))
+#define NPY_MAX_UINT64 NPY_ULONGLONG_SUFFIX(18446744073709551615)
+#define NPY_MAX_INT128 NPY_LONGLONG_SUFFIX(85070591730234615865843651857942052864)
+#define NPY_MIN_INT128 (-NPY_MAX_INT128 - NPY_LONGLONG_SUFFIX(1))
+#define NPY_MAX_UINT128 NPY_ULONGLONG_SUFFIX(170141183460469231731687303715884105728)
+#define NPY_MAX_INT256 NPY_LONGLONG_SUFFIX(57896044618658097711785492504343953926634992332820282019728792003956564819967)
+#define NPY_MIN_INT256 (-NPY_MAX_INT256 - NPY_LONGLONG_SUFFIX(1))
+#define NPY_MAX_UINT256 NPY_ULONGLONG_SUFFIX(115792089237316195423570985008687907853269984665640564039457584007913129639935)
+#define NPY_MIN_DATETIME NPY_MIN_INT64
+#define NPY_MAX_DATETIME NPY_MAX_INT64
+#define NPY_MIN_TIMEDELTA NPY_MIN_INT64
+#define NPY_MAX_TIMEDELTA NPY_MAX_INT64
+
+        /* Need to find the number of bits for each type and
+           make definitions accordingly.
+
+           C states that sizeof(char) == 1 by definition
+
+           So, just using the sizeof keyword won't help.
+
+           It also looks like Python itself uses sizeof(char) quite a
+           bit, which by definition should be 1 all the time.
+
+           Idea: Make Use of CHAR_BIT which should tell us how many
+           BITS per CHARACTER
+        */
+
+        /* Include platform definitions -- These are in the C89/90 standard */
+#include <limits.h>
+#define NPY_MAX_BYTE SCHAR_MAX
+#define NPY_MIN_BYTE SCHAR_MIN
+#define NPY_MAX_UBYTE UCHAR_MAX
+#define NPY_MAX_SHORT SHRT_MAX
+#define NPY_MIN_SHORT SHRT_MIN
+#define NPY_MAX_USHORT USHRT_MAX
+#define NPY_MAX_INT   INT_MAX
+#ifndef INT_MIN
+#define INT_MIN (-INT_MAX - 1)
+#endif
+#define NPY_MIN_INT   INT_MIN
+#define NPY_MAX_UINT  UINT_MAX
+#define NPY_MAX_LONG  LONG_MAX
+#define NPY_MIN_LONG  LONG_MIN
+#define NPY_MAX_ULONG  ULONG_MAX
+
+#define NPY_BITSOF_BOOL (sizeof(npy_bool) * CHAR_BIT)
+#define NPY_BITSOF_CHAR CHAR_BIT
+#define NPY_BITSOF_BYTE (NPY_SIZEOF_BYTE * CHAR_BIT)
+#define NPY_BITSOF_SHORT (NPY_SIZEOF_SHORT * CHAR_BIT)
+#define NPY_BITSOF_INT (NPY_SIZEOF_INT * CHAR_BIT)
+#define NPY_BITSOF_LONG (NPY_SIZEOF_LONG * CHAR_BIT)
+#define NPY_BITSOF_LONGLONG (NPY_SIZEOF_LONGLONG * CHAR_BIT)
+#define NPY_BITSOF_INTP (NPY_SIZEOF_INTP * CHAR_BIT)
+#define NPY_BITSOF_HALF (NPY_SIZEOF_HALF * CHAR_BIT)
+#define NPY_BITSOF_FLOAT (NPY_SIZEOF_FLOAT * CHAR_BIT)
+#define NPY_BITSOF_DOUBLE (NPY_SIZEOF_DOUBLE * CHAR_BIT)
+#define NPY_BITSOF_LONGDOUBLE (NPY_SIZEOF_LONGDOUBLE * CHAR_BIT)
+#define NPY_BITSOF_CFLOAT (NPY_SIZEOF_CFLOAT * CHAR_BIT)
+#define NPY_BITSOF_CDOUBLE (NPY_SIZEOF_CDOUBLE * CHAR_BIT)
+#define NPY_BITSOF_CLONGDOUBLE (NPY_SIZEOF_CLONGDOUBLE * CHAR_BIT)
+#define NPY_BITSOF_DATETIME (NPY_SIZEOF_DATETIME * CHAR_BIT)
+#define NPY_BITSOF_TIMEDELTA (NPY_SIZEOF_TIMEDELTA * CHAR_BIT)
+
+#if NPY_BITSOF_LONG == 8
+#define NPY_INT8 NPY_LONG
+#define NPY_UINT8 NPY_ULONG
+        typedef long npy_int8;
+        typedef unsigned long npy_uint8;
+#define PyInt8ScalarObject PyLongScalarObject
+#define PyInt8ArrType_Type PyLongArrType_Type
+#define PyUInt8ScalarObject PyULongScalarObject
+#define PyUInt8ArrType_Type PyULongArrType_Type
+#define NPY_INT8_FMT NPY_LONG_FMT
+#define NPY_UINT8_FMT NPY_ULONG_FMT
+#elif NPY_BITSOF_LONG == 16
+#define NPY_INT16 NPY_LONG
+#define NPY_UINT16 NPY_ULONG
+        typedef long npy_int16;
+        typedef unsigned long npy_uint16;
+#define PyInt16ScalarObject PyLongScalarObject
+#define PyInt16ArrType_Type PyLongArrType_Type
+#define PyUInt16ScalarObject PyULongScalarObject
+#define PyUInt16ArrType_Type PyULongArrType_Type
+#define NPY_INT16_FMT NPY_LONG_FMT
+#define NPY_UINT16_FMT NPY_ULONG_FMT
+#elif NPY_BITSOF_LONG == 32
+#define NPY_INT32 NPY_LONG
+#define NPY_UINT32 NPY_ULONG
+        typedef long npy_int32;
+        typedef unsigned long npy_uint32;
+        typedef unsigned long npy_ucs4;
+#define PyInt32ScalarObject PyLongScalarObject
+#define PyInt32ArrType_Type PyLongArrType_Type
+#define PyUInt32ScalarObject PyULongScalarObject
+#define PyUInt32ArrType_Type PyULongArrType_Type
+#define NPY_INT32_FMT NPY_LONG_FMT
+#define NPY_UINT32_FMT NPY_ULONG_FMT
+#elif NPY_BITSOF_LONG == 64
+#define NPY_INT64 NPY_LONG
+#define NPY_UINT64 NPY_ULONG
+        typedef long npy_int64;
+        typedef unsigned long npy_uint64;
+#define PyInt64ScalarObject PyLongScalarObject
+#define PyInt64ArrType_Type PyLongArrType_Type
+#define PyUInt64ScalarObject PyULongScalarObject
+#define PyUInt64ArrType_Type PyULongArrType_Type
+#define NPY_INT64_FMT NPY_LONG_FMT
+#define NPY_UINT64_FMT NPY_ULONG_FMT
+#define MyPyLong_FromInt64 PyLong_FromLong
+#define MyPyLong_AsInt64 PyLong_AsLong
+#elif NPY_BITSOF_LONG == 128
+#define NPY_INT128 NPY_LONG
+#define NPY_UINT128 NPY_ULONG
+        typedef long npy_int128;
+        typedef unsigned long npy_uint128;
+#define PyInt128ScalarObject PyLongScalarObject
+#define PyInt128ArrType_Type PyLongArrType_Type
+#define PyUInt128ScalarObject PyULongScalarObject
+#define PyUInt128ArrType_Type PyULongArrType_Type
+#define NPY_INT128_FMT NPY_LONG_FMT
+#define NPY_UINT128_FMT NPY_ULONG_FMT
+#endif
+
+#if NPY_BITSOF_LONGLONG == 8
+#  ifndef NPY_INT8
+#    define NPY_INT8 NPY_LONGLONG
+#    define NPY_UINT8 NPY_ULONGLONG
+        typedef npy_longlong npy_int8;
+        typedef npy_ulonglong npy_uint8;
+#    define PyInt8ScalarObject PyLongLongScalarObject
+#    define PyInt8ArrType_Type PyLongLongArrType_Type
+#    define PyUInt8ScalarObject PyULongLongScalarObject
+#    define PyUInt8ArrType_Type PyULongLongArrType_Type
+#define NPY_INT8_FMT NPY_LONGLONG_FMT
+#define NPY_UINT8_FMT NPY_ULONGLONG_FMT
+#  endif
+#  define NPY_MAX_LONGLONG NPY_MAX_INT8
+#  define NPY_MIN_LONGLONG NPY_MIN_INT8
+#  define NPY_MAX_ULONGLONG NPY_MAX_UINT8
+#elif NPY_BITSOF_LONGLONG == 16
+#  ifndef NPY_INT16
+#    define NPY_INT16 NPY_LONGLONG
+#    define NPY_UINT16 NPY_ULONGLONG
+        typedef npy_longlong npy_int16;
+        typedef npy_ulonglong npy_uint16;
+#    define PyInt16ScalarObject PyLongLongScalarObject
+#    define PyInt16ArrType_Type PyLongLongArrType_Type
+#    define PyUInt16ScalarObject PyULongLongScalarObject
+#    define PyUInt16ArrType_Type PyULongLongArrType_Type
+#define NPY_INT16_FMT NPY_LONGLONG_FMT
+#define NPY_UINT16_FMT NPY_ULONGLONG_FMT
+#  endif
+#  define NPY_MAX_LONGLONG NPY_MAX_INT16
+#  define NPY_MIN_LONGLONG NPY_MIN_INT16
+#  define NPY_MAX_ULONGLONG NPY_MAX_UINT16
+#elif NPY_BITSOF_LONGLONG == 32
+#  ifndef NPY_INT32
+#    define NPY_INT32 NPY_LONGLONG
+#    define NPY_UINT32 NPY_ULONGLONG
+        typedef npy_longlong npy_int32;
+        typedef npy_ulonglong npy_uint32;
+        typedef npy_ulonglong npy_ucs4;
+#    define PyInt32ScalarObject PyLongLongScalarObject
+#    define PyInt32ArrType_Type PyLongLongArrType_Type
+#    define PyUInt32ScalarObject PyULongLongScalarObject
+#    define PyUInt32ArrType_Type PyULongLongArrType_Type
+#define NPY_INT32_FMT NPY_LONGLONG_FMT
+#define NPY_UINT32_FMT NPY_ULONGLONG_FMT
+#  endif
+#  define NPY_MAX_LONGLONG NPY_MAX_INT32
+#  define NPY_MIN_LONGLONG NPY_MIN_INT32
+#  define NPY_MAX_ULONGLONG NPY_MAX_UINT32
+#elif NPY_BITSOF_LONGLONG == 64
+#  ifndef NPY_INT64
+#    define NPY_INT64 NPY_LONGLONG
+#    define NPY_UINT64 NPY_ULONGLONG
+        typedef npy_longlong npy_int64;
+        typedef npy_ulonglong npy_uint64;
+#    define PyInt64ScalarObject PyLongLongScalarObject
+#    define PyInt64ArrType_Type PyLongLongArrType_Type
+#    define PyUInt64ScalarObject PyULongLongScalarObject
+#    define PyUInt64ArrType_Type PyULongLongArrType_Type
+#define NPY_INT64_FMT NPY_LONGLONG_FMT
+#define NPY_UINT64_FMT NPY_ULONGLONG_FMT
+#    define MyPyLong_FromInt64 PyLong_FromLongLong
+#    define MyPyLong_AsInt64 PyLong_AsLongLong
+#  endif
+#  define NPY_MAX_LONGLONG NPY_MAX_INT64
+#  define NPY_MIN_LONGLONG NPY_MIN_INT64
+#  define NPY_MAX_ULONGLONG NPY_MAX_UINT64
+#elif NPY_BITSOF_LONGLONG == 128
+#  ifndef NPY_INT128
+#    define NPY_INT128 NPY_LONGLONG
+#    define NPY_UINT128 NPY_ULONGLONG
+        typedef npy_longlong npy_int128;
+        typedef npy_ulonglong npy_uint128;
+#    define PyInt128ScalarObject PyLongLongScalarObject
+#    define PyInt128ArrType_Type PyLongLongArrType_Type
+#    define PyUInt128ScalarObject PyULongLongScalarObject
+#    define PyUInt128ArrType_Type PyULongLongArrType_Type
+#define NPY_INT128_FMT NPY_LONGLONG_FMT
+#define NPY_UINT128_FMT NPY_ULONGLONG_FMT
+#  endif
+#  define NPY_MAX_LONGLONG NPY_MAX_INT128
+#  define NPY_MIN_LONGLONG NPY_MIN_INT128
+#  define NPY_MAX_ULONGLONG NPY_MAX_UINT128
+#elif NPY_BITSOF_LONGLONG == 256
+#  define NPY_INT256 NPY_LONGLONG
+#  define NPY_UINT256 NPY_ULONGLONG
+        typedef npy_longlong npy_int256;
+        typedef npy_ulonglong npy_uint256;
+#  define PyInt256ScalarObject PyLongLongScalarObject
+#  define PyInt256ArrType_Type PyLongLongArrType_Type
+#  define PyUInt256ScalarObject PyULongLongScalarObject
+#  define PyUInt256ArrType_Type PyULongLongArrType_Type
+#define NPY_INT256_FMT NPY_LONGLONG_FMT
+#define NPY_UINT256_FMT NPY_ULONGLONG_FMT
+#  define NPY_MAX_LONGLONG NPY_MAX_INT256
+#  define NPY_MIN_LONGLONG NPY_MIN_INT256
+#  define NPY_MAX_ULONGLONG NPY_MAX_UINT256
+#endif
+
+#if NPY_BITSOF_INT == 8
+#ifndef NPY_INT8
+#define NPY_INT8 NPY_INT
+#define NPY_UINT8 NPY_UINT
+        typedef int npy_int8;
+        typedef unsigned int npy_uint8;
+#    define PyInt8ScalarObject PyIntScalarObject
+#    define PyInt8ArrType_Type PyIntArrType_Type
+#    define PyUInt8ScalarObject PyUIntScalarObject
+#    define PyUInt8ArrType_Type PyUIntArrType_Type
+#define NPY_INT8_FMT NPY_INT_FMT
+#define NPY_UINT8_FMT NPY_UINT_FMT
+#endif
+#elif NPY_BITSOF_INT == 16
+#ifndef NPY_INT16
+#define NPY_INT16 NPY_INT
+#define NPY_UINT16 NPY_UINT
+        typedef int npy_int16;
+        typedef unsigned int npy_uint16;
+#    define PyInt16ScalarObject PyIntScalarObject
+#    define PyInt16ArrType_Type PyIntArrType_Type
+#    define PyUInt16ScalarObject PyIntUScalarObject
+#    define PyUInt16ArrType_Type PyIntUArrType_Type
+#define NPY_INT16_FMT NPY_INT_FMT
+#define NPY_UINT16_FMT NPY_UINT_FMT
+#endif
+#elif NPY_BITSOF_INT == 32
+#ifndef NPY_INT32
+#define NPY_INT32 NPY_INT
+#define NPY_UINT32 NPY_UINT
+        typedef int npy_int32;
+        typedef unsigned int npy_uint32;
+        typedef unsigned int npy_ucs4;
+#    define PyInt32ScalarObject PyIntScalarObject
+#    define PyInt32ArrType_Type PyIntArrType_Type
+#    define PyUInt32ScalarObject PyUIntScalarObject
+#    define PyUInt32ArrType_Type PyUIntArrType_Type
+#define NPY_INT32_FMT NPY_INT_FMT
+#define NPY_UINT32_FMT NPY_UINT_FMT
+#endif
+#elif NPY_BITSOF_INT == 64
+#ifndef NPY_INT64
+#define NPY_INT64 NPY_INT
+#define NPY_UINT64 NPY_UINT
+        typedef int npy_int64;
+        typedef unsigned int npy_uint64;
+#    define PyInt64ScalarObject PyIntScalarObject
+#    define PyInt64ArrType_Type PyIntArrType_Type
+#    define PyUInt64ScalarObject PyUIntScalarObject
+#    define PyUInt64ArrType_Type PyUIntArrType_Type
+#define NPY_INT64_FMT NPY_INT_FMT
+#define NPY_UINT64_FMT NPY_UINT_FMT
+#    define MyPyLong_FromInt64 PyLong_FromLong
+#    define MyPyLong_AsInt64 PyLong_AsLong
+#endif
+#elif NPY_BITSOF_INT == 128
+#ifndef NPY_INT128
+#define NPY_INT128 NPY_INT
+#define NPY_UINT128 NPY_UINT
+        typedef int npy_int128;
+        typedef unsigned int npy_uint128;
+#    define PyInt128ScalarObject PyIntScalarObject
+#    define PyInt128ArrType_Type PyIntArrType_Type
+#    define PyUInt128ScalarObject PyUIntScalarObject
+#    define PyUInt128ArrType_Type PyUIntArrType_Type
+#define NPY_INT128_FMT NPY_INT_FMT
+#define NPY_UINT128_FMT NPY_UINT_FMT
+#endif
+#endif
+
+#if NPY_BITSOF_SHORT == 8
+#ifndef NPY_INT8
+#define NPY_INT8 NPY_SHORT
+#define NPY_UINT8 NPY_USHORT
+        typedef short npy_int8;
+        typedef unsigned short npy_uint8;
+#    define PyInt8ScalarObject PyShortScalarObject
+#    define PyInt8ArrType_Type PyShortArrType_Type
+#    define PyUInt8ScalarObject PyUShortScalarObject
+#    define PyUInt8ArrType_Type PyUShortArrType_Type
+#define NPY_INT8_FMT NPY_SHORT_FMT
+#define NPY_UINT8_FMT NPY_USHORT_FMT
+#endif
+#elif NPY_BITSOF_SHORT == 16
+#ifndef NPY_INT16
+#define NPY_INT16 NPY_SHORT
+#define NPY_UINT16 NPY_USHORT
+        typedef short npy_int16;
+        typedef unsigned short npy_uint16;
+#    define PyInt16ScalarObject PyShortScalarObject
+#    define PyInt16ArrType_Type PyShortArrType_Type
+#    define PyUInt16ScalarObject PyUShortScalarObject
+#    define PyUInt16ArrType_Type PyUShortArrType_Type
+#define NPY_INT16_FMT NPY_SHORT_FMT
+#define NPY_UINT16_FMT NPY_USHORT_FMT
+#endif
+#elif NPY_BITSOF_SHORT == 32
+#ifndef NPY_INT32
+#define NPY_INT32 NPY_SHORT
+#define NPY_UINT32 NPY_USHORT
+        typedef short npy_int32;
+        typedef unsigned short npy_uint32;
+        typedef unsigned short npy_ucs4;
+#    define PyInt32ScalarObject PyShortScalarObject
+#    define PyInt32ArrType_Type PyShortArrType_Type
+#    define PyUInt32ScalarObject PyUShortScalarObject
+#    define PyUInt32ArrType_Type PyUShortArrType_Type
+#define NPY_INT32_FMT NPY_SHORT_FMT
+#define NPY_UINT32_FMT NPY_USHORT_FMT
+#endif
+#elif NPY_BITSOF_SHORT == 64
+#ifndef NPY_INT64
+#define NPY_INT64 NPY_SHORT
+#define NPY_UINT64 NPY_USHORT
+        typedef short npy_int64;
+        typedef unsigned short npy_uint64;
+#    define PyInt64ScalarObject PyShortScalarObject
+#    define PyInt64ArrType_Type PyShortArrType_Type
+#    define PyUInt64ScalarObject PyUShortScalarObject
+#    define PyUInt64ArrType_Type PyUShortArrType_Type
+#define NPY_INT64_FMT NPY_SHORT_FMT
+#define NPY_UINT64_FMT NPY_USHORT_FMT
+#    define MyPyLong_FromInt64 PyLong_FromLong
+#    define MyPyLong_AsInt64 PyLong_AsLong
+#endif
+#elif NPY_BITSOF_SHORT == 128
+#ifndef NPY_INT128
+#define NPY_INT128 NPY_SHORT
+#define NPY_UINT128 NPY_USHORT
+        typedef short npy_int128;
+        typedef unsigned short npy_uint128;
+#    define PyInt128ScalarObject PyShortScalarObject
+#    define PyInt128ArrType_Type PyShortArrType_Type
+#    define PyUInt128ScalarObject PyUShortScalarObject
+#    define PyUInt128ArrType_Type PyUShortArrType_Type
+#define NPY_INT128_FMT NPY_SHORT_FMT
+#define NPY_UINT128_FMT NPY_USHORT_FMT
+#endif
+#endif
+
+
+#if NPY_BITSOF_CHAR == 8
+#ifndef NPY_INT8
+#define NPY_INT8 NPY_BYTE
+#define NPY_UINT8 NPY_UBYTE
+        typedef signed char npy_int8;
+        typedef unsigned char npy_uint8;
+#    define PyInt8ScalarObject PyByteScalarObject
+#    define PyInt8ArrType_Type PyByteArrType_Type
+#    define PyUInt8ScalarObject PyUByteScalarObject
+#    define PyUInt8ArrType_Type PyUByteArrType_Type
+#define NPY_INT8_FMT NPY_BYTE_FMT
+#define NPY_UINT8_FMT NPY_UBYTE_FMT
+#endif
+#elif NPY_BITSOF_CHAR == 16
+#ifndef NPY_INT16
+#define NPY_INT16 NPY_BYTE
+#define NPY_UINT16 NPY_UBYTE
+        typedef signed char npy_int16;
+        typedef unsigned char npy_uint16;
+#    define PyInt16ScalarObject PyByteScalarObject
+#    define PyInt16ArrType_Type PyByteArrType_Type
+#    define PyUInt16ScalarObject PyUByteScalarObject
+#    define PyUInt16ArrType_Type PyUByteArrType_Type
+#define NPY_INT16_FMT NPY_BYTE_FMT
+#define NPY_UINT16_FMT NPY_UBYTE_FMT
+#endif
+#elif NPY_BITSOF_CHAR == 32
+#ifndef NPY_INT32
+#define NPY_INT32 NPY_BYTE
+#define NPY_UINT32 NPY_UBYTE
+        typedef signed char npy_int32;
+        typedef unsigned char npy_uint32;
+        typedef unsigned char npy_ucs4;
+#    define PyInt32ScalarObject PyByteScalarObject
+#    define PyInt32ArrType_Type PyByteArrType_Type
+#    define PyUInt32ScalarObject PyUByteScalarObject
+#    define PyUInt32ArrType_Type PyUByteArrType_Type
+#define NPY_INT32_FMT NPY_BYTE_FMT
+#define NPY_UINT32_FMT NPY_UBYTE_FMT
+#endif
+#elif NPY_BITSOF_CHAR == 64
+#ifndef NPY_INT64
+#define NPY_INT64 NPY_BYTE
+#define NPY_UINT64 NPY_UBYTE
+        typedef signed char npy_int64;
+        typedef unsigned char npy_uint64;
+#    define PyInt64ScalarObject PyByteScalarObject
+#    define PyInt64ArrType_Type PyByteArrType_Type
+#    define PyUInt64ScalarObject PyUByteScalarObject
+#    define PyUInt64ArrType_Type PyUByteArrType_Type
+#define NPY_INT64_FMT NPY_BYTE_FMT
+#define NPY_UINT64_FMT NPY_UBYTE_FMT
+#    define MyPyLong_FromInt64 PyLong_FromLong
+#    define MyPyLong_AsInt64 PyLong_AsLong
+#endif
+#elif NPY_BITSOF_CHAR == 128
+#ifndef NPY_INT128
+#define NPY_INT128 NPY_BYTE
+#define NPY_UINT128 NPY_UBYTE
+        typedef signed char npy_int128;
+        typedef unsigned char npy_uint128;
+#    define PyInt128ScalarObject PyByteScalarObject
+#    define PyInt128ArrType_Type PyByteArrType_Type
+#    define PyUInt128ScalarObject PyUByteScalarObject
+#    define PyUInt128ArrType_Type PyUByteArrType_Type
+#define NPY_INT128_FMT NPY_BYTE_FMT
+#define NPY_UINT128_FMT NPY_UBYTE_FMT
+#endif
+#endif
+
+
+
+#if NPY_BITSOF_DOUBLE == 32
+#ifndef NPY_FLOAT32
+#define NPY_FLOAT32 NPY_DOUBLE
+#define NPY_COMPLEX64 NPY_CDOUBLE
+        typedef double npy_float32;
+        typedef npy_cdouble npy_complex64;
+#    define PyFloat32ScalarObject PyDoubleScalarObject
+#    define PyComplex64ScalarObject PyCDoubleScalarObject
+#    define PyFloat32ArrType_Type PyDoubleArrType_Type
+#    define PyComplex64ArrType_Type PyCDoubleArrType_Type
+#define NPY_FLOAT32_FMT NPY_DOUBLE_FMT
+#define NPY_COMPLEX64_FMT NPY_CDOUBLE_FMT
+#endif
+#elif NPY_BITSOF_DOUBLE == 64
+#ifndef NPY_FLOAT64
+#define NPY_FLOAT64 NPY_DOUBLE
+#define NPY_COMPLEX128 NPY_CDOUBLE
+        typedef double npy_float64;
+        typedef npy_cdouble npy_complex128;
+#    define PyFloat64ScalarObject PyDoubleScalarObject
+#    define PyComplex128ScalarObject PyCDoubleScalarObject
+#    define PyFloat64ArrType_Type PyDoubleArrType_Type
+#    define PyComplex128ArrType_Type PyCDoubleArrType_Type
+#define NPY_FLOAT64_FMT NPY_DOUBLE_FMT
+#define NPY_COMPLEX128_FMT NPY_CDOUBLE_FMT
+#endif
+#elif NPY_BITSOF_DOUBLE == 80
+#ifndef NPY_FLOAT80
+#define NPY_FLOAT80 NPY_DOUBLE
+#define NPY_COMPLEX160 NPY_CDOUBLE
+        typedef double npy_float80;
+        typedef npy_cdouble npy_complex160;
+#    define PyFloat80ScalarObject PyDoubleScalarObject
+#    define PyComplex160ScalarObject PyCDoubleScalarObject
+#    define PyFloat80ArrType_Type PyDoubleArrType_Type
+#    define PyComplex160ArrType_Type PyCDoubleArrType_Type
+#define NPY_FLOAT80_FMT NPY_DOUBLE_FMT
+#define NPY_COMPLEX160_FMT NPY_CDOUBLE_FMT
+#endif
+#elif NPY_BITSOF_DOUBLE == 96
+#ifndef NPY_FLOAT96
+#define NPY_FLOAT96 NPY_DOUBLE
+#define NPY_COMPLEX192 NPY_CDOUBLE
+        typedef double npy_float96;
+        typedef npy_cdouble npy_complex192;
+#    define PyFloat96ScalarObject PyDoubleScalarObject
+#    define PyComplex192ScalarObject PyCDoubleScalarObject
+#    define PyFloat96ArrType_Type PyDoubleArrType_Type
+#    define PyComplex192ArrType_Type PyCDoubleArrType_Type
+#define NPY_FLOAT96_FMT NPY_DOUBLE_FMT
+#define NPY_COMPLEX192_FMT NPY_CDOUBLE_FMT
+#endif
+#elif NPY_BITSOF_DOUBLE == 128
+#ifndef NPY_FLOAT128
+#define NPY_FLOAT128 NPY_DOUBLE
+#define NPY_COMPLEX256 NPY_CDOUBLE
+        typedef double npy_float128;
+        typedef npy_cdouble npy_complex256;
+#    define PyFloat128ScalarObject PyDoubleScalarObject
+#    define PyComplex256ScalarObject PyCDoubleScalarObject
+#    define PyFloat128ArrType_Type PyDoubleArrType_Type
+#    define PyComplex256ArrType_Type PyCDoubleArrType_Type
+#define NPY_FLOAT128_FMT NPY_DOUBLE_FMT
+#define NPY_COMPLEX256_FMT NPY_CDOUBLE_FMT
+#endif
+#endif
+
+
+
+#if NPY_BITSOF_FLOAT == 32
+#ifndef NPY_FLOAT32
+#define NPY_FLOAT32 NPY_FLOAT
+#define NPY_COMPLEX64 NPY_CFLOAT
+        typedef float npy_float32;
+        typedef npy_cfloat npy_complex64;
+#    define PyFloat32ScalarObject PyFloatScalarObject
+#    define PyComplex64ScalarObject PyCFloatScalarObject
+#    define PyFloat32ArrType_Type PyFloatArrType_Type
+#    define PyComplex64ArrType_Type PyCFloatArrType_Type
+#define NPY_FLOAT32_FMT NPY_FLOAT_FMT
+#define NPY_COMPLEX64_FMT NPY_CFLOAT_FMT
+#endif
+#elif NPY_BITSOF_FLOAT == 64
+#ifndef NPY_FLOAT64
+#define NPY_FLOAT64 NPY_FLOAT
+#define NPY_COMPLEX128 NPY_CFLOAT
+        typedef float npy_float64;
+        typedef npy_cfloat npy_complex128;
+#    define PyFloat64ScalarObject PyFloatScalarObject
+#    define PyComplex128ScalarObject PyCFloatScalarObject
+#    define PyFloat64ArrType_Type PyFloatArrType_Type
+#    define PyComplex128ArrType_Type PyCFloatArrType_Type
+#define NPY_FLOAT64_FMT NPY_FLOAT_FMT
+#define NPY_COMPLEX128_FMT NPY_CFLOAT_FMT
+#endif
+#elif NPY_BITSOF_FLOAT == 80
+#ifndef NPY_FLOAT80
+#define NPY_FLOAT80 NPY_FLOAT
+#define NPY_COMPLEX160 NPY_CFLOAT
+        typedef float npy_float80;
+        typedef npy_cfloat npy_complex160;
+#    define PyFloat80ScalarObject PyFloatScalarObject
+#    define PyComplex160ScalarObject PyCFloatScalarObject
+#    define PyFloat80ArrType_Type PyFloatArrType_Type
+#    define PyComplex160ArrType_Type PyCFloatArrType_Type
+#define NPY_FLOAT80_FMT NPY_FLOAT_FMT
+#define NPY_COMPLEX160_FMT NPY_CFLOAT_FMT
+#endif
+#elif NPY_BITSOF_FLOAT == 96
+#ifndef NPY_FLOAT96
+#define NPY_FLOAT96 NPY_FLOAT
+#define NPY_COMPLEX192 NPY_CFLOAT
+        typedef float npy_float96;
+        typedef npy_cfloat npy_complex192;
+#    define PyFloat96ScalarObject PyFloatScalarObject
+#    define PyComplex192ScalarObject PyCFloatScalarObject
+#    define PyFloat96ArrType_Type PyFloatArrType_Type
+#    define PyComplex192ArrType_Type PyCFloatArrType_Type
+#define NPY_FLOAT96_FMT NPY_FLOAT_FMT
+#define NPY_COMPLEX192_FMT NPY_CFLOAT_FMT
+#endif
+#elif NPY_BITSOF_FLOAT == 128
+#ifndef NPY_FLOAT128
+#define NPY_FLOAT128 NPY_FLOAT
+#define NPY_COMPLEX256 NPY_CFLOAT
+        typedef float npy_float128;
+        typedef npy_cfloat npy_complex256;
+#    define PyFloat128ScalarObject PyFloatScalarObject
+#    define PyComplex256ScalarObject PyCFloatScalarObject
+#    define PyFloat128ArrType_Type PyFloatArrType_Type
+#    define PyComplex256ArrType_Type PyCFloatArrType_Type
+#define NPY_FLOAT128_FMT NPY_FLOAT_FMT
+#define NPY_COMPLEX256_FMT NPY_CFLOAT_FMT
+#endif
+#endif
+
+/* half/float16 isn't a floating-point type in C */
+#define NPY_FLOAT16 NPY_HALF
+typedef npy_uint16 npy_half;
+typedef npy_half npy_float16;
+
+#if NPY_BITSOF_LONGDOUBLE == 32
+#ifndef NPY_FLOAT32
+#define NPY_FLOAT32 NPY_LONGDOUBLE
+#define NPY_COMPLEX64 NPY_CLONGDOUBLE
+        typedef npy_longdouble npy_float32;
+        typedef npy_clongdouble npy_complex64;
+#    define PyFloat32ScalarObject PyLongDoubleScalarObject
+#    define PyComplex64ScalarObject PyCLongDoubleScalarObject
+#    define PyFloat32ArrType_Type PyLongDoubleArrType_Type
+#    define PyComplex64ArrType_Type PyCLongDoubleArrType_Type
+#define NPY_FLOAT32_FMT NPY_LONGDOUBLE_FMT
+#define NPY_COMPLEX64_FMT NPY_CLONGDOUBLE_FMT
+#endif
+#elif NPY_BITSOF_LONGDOUBLE == 64
+#ifndef NPY_FLOAT64
+#define NPY_FLOAT64 NPY_LONGDOUBLE
+#define NPY_COMPLEX128 NPY_CLONGDOUBLE
+        typedef npy_longdouble npy_float64;
+        typedef npy_clongdouble npy_complex128;
+#    define PyFloat64ScalarObject PyLongDoubleScalarObject
+#    define PyComplex128ScalarObject PyCLongDoubleScalarObject
+#    define PyFloat64ArrType_Type PyLongDoubleArrType_Type
+#    define PyComplex128ArrType_Type PyCLongDoubleArrType_Type
+#define NPY_FLOAT64_FMT NPY_LONGDOUBLE_FMT
+#define NPY_COMPLEX128_FMT NPY_CLONGDOUBLE_FMT
+#endif
+#elif NPY_BITSOF_LONGDOUBLE == 80
+#ifndef NPY_FLOAT80
+#define NPY_FLOAT80 NPY_LONGDOUBLE
+#define NPY_COMPLEX160 NPY_CLONGDOUBLE
+        typedef npy_longdouble npy_float80;
+        typedef npy_clongdouble npy_complex160;
+#    define PyFloat80ScalarObject PyLongDoubleScalarObject
+#    define PyComplex160ScalarObject PyCLongDoubleScalarObject
+#    define PyFloat80ArrType_Type PyLongDoubleArrType_Type
+#    define PyComplex160ArrType_Type PyCLongDoubleArrType_Type
+#define NPY_FLOAT80_FMT NPY_LONGDOUBLE_FMT
+#define NPY_COMPLEX160_FMT NPY_CLONGDOUBLE_FMT
+#endif
+#elif NPY_BITSOF_LONGDOUBLE == 96
+#ifndef NPY_FLOAT96
+#define NPY_FLOAT96 NPY_LONGDOUBLE
+#define NPY_COMPLEX192 NPY_CLONGDOUBLE
+        typedef npy_longdouble npy_float96;
+        typedef npy_clongdouble npy_complex192;
+#    define PyFloat96ScalarObject PyLongDoubleScalarObject
+#    define PyComplex192ScalarObject PyCLongDoubleScalarObject
+#    define PyFloat96ArrType_Type PyLongDoubleArrType_Type
+#    define PyComplex192ArrType_Type PyCLongDoubleArrType_Type
+#define NPY_FLOAT96_FMT NPY_LONGDOUBLE_FMT
+#define NPY_COMPLEX192_FMT NPY_CLONGDOUBLE_FMT
+#endif
+#elif NPY_BITSOF_LONGDOUBLE == 128
+#ifndef NPY_FLOAT128
+#define NPY_FLOAT128 NPY_LONGDOUBLE
+#define NPY_COMPLEX256 NPY_CLONGDOUBLE
+        typedef npy_longdouble npy_float128;
+        typedef npy_clongdouble npy_complex256;
+#    define PyFloat128ScalarObject PyLongDoubleScalarObject
+#    define PyComplex256ScalarObject PyCLongDoubleScalarObject
+#    define PyFloat128ArrType_Type PyLongDoubleArrType_Type
+#    define PyComplex256ArrType_Type PyCLongDoubleArrType_Type
+#define NPY_FLOAT128_FMT NPY_LONGDOUBLE_FMT
+#define NPY_COMPLEX256_FMT NPY_CLONGDOUBLE_FMT
+#endif
+#elif NPY_BITSOF_LONGDOUBLE == 256
+#define NPY_FLOAT256 NPY_LONGDOUBLE
+#define NPY_COMPLEX512 NPY_CLONGDOUBLE
+        typedef npy_longdouble npy_float256;
+        typedef npy_clongdouble npy_complex512;
+#    define PyFloat256ScalarObject PyLongDoubleScalarObject
+#    define PyComplex512ScalarObject PyCLongDoubleScalarObject
+#    define PyFloat256ArrType_Type PyLongDoubleArrType_Type
+#    define PyComplex512ArrType_Type PyCLongDoubleArrType_Type
+#define NPY_FLOAT256_FMT NPY_LONGDOUBLE_FMT
+#define NPY_COMPLEX512_FMT NPY_CLONGDOUBLE_FMT
+#endif
+
+/* datetime typedefs */
+typedef npy_int64 npy_timedelta;
+typedef npy_int64 npy_datetime;
+#define NPY_DATETIME_FMT NPY_INT64_FMT
+#define NPY_TIMEDELTA_FMT NPY_INT64_FMT
+
+/* End of typedefs for numarray style bit-width names */
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_cpu.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_cpu.h
new file mode 100644
index 0000000..5edd8f4
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_cpu.h
@@ -0,0 +1,118 @@
+/*
+ * This set (target) cpu specific macros:
+ *      - Possible values:
+ *              NPY_CPU_X86
+ *              NPY_CPU_AMD64
+ *              NPY_CPU_PPC
+ *              NPY_CPU_PPC64
+ *              NPY_CPU_PPC64LE
+ *              NPY_CPU_SPARC
+ *              NPY_CPU_S390
+ *              NPY_CPU_IA64
+ *              NPY_CPU_HPPA
+ *              NPY_CPU_ALPHA
+ *              NPY_CPU_ARMEL
+ *              NPY_CPU_ARMEB
+ *              NPY_CPU_SH_LE
+ *              NPY_CPU_SH_BE
+ *              NPY_CPU_ARCEL
+ *              NPY_CPU_ARCEB
+ *              NPY_CPU_RISCV64
+ */
+#ifndef _NPY_CPUARCH_H_
+#define _NPY_CPUARCH_H_
+
+#include "numpyconfig.h"
+#include <string.h> /* for memcpy */
+
+#if defined( __i386__ ) || defined(i386) || defined(_M_IX86)
+    /*
+     * __i386__ is defined by gcc and Intel compiler on Linux,
+     * _M_IX86 by VS compiler,
+     * i386 by Sun compilers on opensolaris at least
+     */
+    #define NPY_CPU_X86
+#elif defined(__x86_64__) || defined(__amd64__) || defined(__x86_64) || defined(_M_AMD64)
+    /*
+     * both __x86_64__ and __amd64__ are defined by gcc
+     * __x86_64 defined by sun compiler on opensolaris at least
+     * _M_AMD64 defined by MS compiler
+     */
+    #define NPY_CPU_AMD64
+#elif defined(__powerpc64__) && defined(__LITTLE_ENDIAN__)
+    #define NPY_CPU_PPC64LE
+#elif defined(__powerpc64__) && defined(__BIG_ENDIAN__)
+    #define NPY_CPU_PPC64
+#elif defined(__ppc__) || defined(__powerpc__) || defined(_ARCH_PPC)
+    /*
+     * __ppc__ is defined by gcc, I remember having seen __powerpc__ once,
+     * but can't find it ATM
+     * _ARCH_PPC is used by at least gcc on AIX
+     * As __powerpc__ and _ARCH_PPC are also defined by PPC64 check
+     * for those specifically first before defaulting to ppc
+     */
+    #define NPY_CPU_PPC
+#elif defined(__sparc__) || defined(__sparc)
+    /* __sparc__ is defined by gcc and Forte (e.g. Sun) compilers */
+    #define NPY_CPU_SPARC
+#elif defined(__s390__)
+    #define NPY_CPU_S390
+#elif defined(__ia64)
+    #define NPY_CPU_IA64
+#elif defined(__hppa)
+    #define NPY_CPU_HPPA
+#elif defined(__alpha__)
+    #define NPY_CPU_ALPHA
+#elif defined(__arm__) || defined(__aarch64__)
+    #if defined(__ARMEB__) || defined(__AARCH64EB__)
+        #if defined(__ARM_32BIT_STATE)
+            #define NPY_CPU_ARMEB_AARCH32
+        #elif defined(__ARM_64BIT_STATE)
+            #define NPY_CPU_ARMEB_AARCH64
+        #else
+            #define NPY_CPU_ARMEB
+        #endif
+    #elif defined(__ARMEL__) || defined(__AARCH64EL__)
+        #if defined(__ARM_32BIT_STATE)
+            #define NPY_CPU_ARMEL_AARCH32
+        #elif defined(__ARM_64BIT_STATE)
+            #define NPY_CPU_ARMEL_AARCH64
+        #else
+            #define NPY_CPU_ARMEL
+        #endif
+    #else
+        # error Unknown ARM CPU, please report this to numpy maintainers with \
+	information about your platform (OS, CPU and compiler)
+    #endif
+#elif defined(__sh__) && defined(__LITTLE_ENDIAN__)
+    #define NPY_CPU_SH_LE
+#elif defined(__sh__) && defined(__BIG_ENDIAN__)
+    #define NPY_CPU_SH_BE
+#elif defined(__MIPSEL__)
+    #define NPY_CPU_MIPSEL
+#elif defined(__MIPSEB__)
+    #define NPY_CPU_MIPSEB
+#elif defined(__or1k__)
+    #define NPY_CPU_OR1K
+#elif defined(__mc68000__)
+    #define NPY_CPU_M68K
+#elif defined(__arc__) && defined(__LITTLE_ENDIAN__)
+    #define NPY_CPU_ARCEL
+#elif defined(__arc__) && defined(__BIG_ENDIAN__)
+    #define NPY_CPU_ARCEB
+#elif defined(__riscv) && defined(__riscv_xlen) && __riscv_xlen == 64
+    #define NPY_CPU_RISCV64
+#else
+    #error Unknown CPU, please report this to numpy maintainers with \
+    information about your platform (OS, CPU and compiler)
+#endif
+
+#define NPY_COPY_PYOBJECT_PTR(dst, src) memcpy(dst, src, sizeof(PyObject *))
+
+#if (defined(NPY_CPU_X86) || defined(NPY_CPU_AMD64))
+#define NPY_CPU_HAVE_UNALIGNED_ACCESS 1
+#else
+#define NPY_CPU_HAVE_UNALIGNED_ACCESS 0
+#endif
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_endian.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_endian.h
new file mode 100644
index 0000000..44cdffd
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_endian.h
@@ -0,0 +1,72 @@
+#ifndef _NPY_ENDIAN_H_
+#define _NPY_ENDIAN_H_
+
+/*
+ * NPY_BYTE_ORDER is set to the same value as BYTE_ORDER set by glibc in
+ * endian.h
+ */
+
+#if defined(NPY_HAVE_ENDIAN_H) || defined(NPY_HAVE_SYS_ENDIAN_H)
+    /* Use endian.h if available */
+
+    #if defined(NPY_HAVE_ENDIAN_H)
+    #include <endian.h>
+    #elif defined(NPY_HAVE_SYS_ENDIAN_H)
+    #include <sys/endian.h>
+    #endif
+
+    #if defined(BYTE_ORDER) && defined(BIG_ENDIAN) && defined(LITTLE_ENDIAN)
+        #define NPY_BYTE_ORDER    BYTE_ORDER
+        #define NPY_LITTLE_ENDIAN LITTLE_ENDIAN
+        #define NPY_BIG_ENDIAN    BIG_ENDIAN
+    #elif defined(_BYTE_ORDER) && defined(_BIG_ENDIAN) && defined(_LITTLE_ENDIAN)
+        #define NPY_BYTE_ORDER    _BYTE_ORDER
+        #define NPY_LITTLE_ENDIAN _LITTLE_ENDIAN
+        #define NPY_BIG_ENDIAN    _BIG_ENDIAN
+    #elif defined(__BYTE_ORDER) && defined(__BIG_ENDIAN) && defined(__LITTLE_ENDIAN)
+        #define NPY_BYTE_ORDER    __BYTE_ORDER
+        #define NPY_LITTLE_ENDIAN __LITTLE_ENDIAN
+        #define NPY_BIG_ENDIAN    __BIG_ENDIAN
+    #endif
+#endif
+
+#ifndef NPY_BYTE_ORDER
+    /* Set endianness info using target CPU */
+    #include "npy_cpu.h"
+
+    #define NPY_LITTLE_ENDIAN 1234
+    #define NPY_BIG_ENDIAN 4321
+
+    #if defined(NPY_CPU_X86)                  \
+            || defined(NPY_CPU_AMD64)         \
+            || defined(NPY_CPU_IA64)          \
+            || defined(NPY_CPU_ALPHA)         \
+            || defined(NPY_CPU_ARMEL)         \
+            || defined(NPY_CPU_ARMEL_AARCH32) \
+            || defined(NPY_CPU_ARMEL_AARCH64) \
+            || defined(NPY_CPU_SH_LE)         \
+            || defined(NPY_CPU_MIPSEL)        \
+            || defined(NPY_CPU_PPC64LE)       \
+            || defined(NPY_CPU_ARCEL)         \
+            || defined(NPY_CPU_RISCV64)
+        #define NPY_BYTE_ORDER NPY_LITTLE_ENDIAN
+    #elif defined(NPY_CPU_PPC)                \
+            || defined(NPY_CPU_SPARC)         \
+            || defined(NPY_CPU_S390)          \
+            || defined(NPY_CPU_HPPA)          \
+            || defined(NPY_CPU_PPC64)         \
+            || defined(NPY_CPU_ARMEB)         \
+            || defined(NPY_CPU_ARMEB_AARCH32) \
+            || defined(NPY_CPU_ARMEB_AARCH64) \
+            || defined(NPY_CPU_SH_BE)         \
+            || defined(NPY_CPU_MIPSEB)        \
+            || defined(NPY_CPU_OR1K)          \
+            || defined(NPY_CPU_M68K)          \
+            || defined(NPY_CPU_ARCEB)
+        #define NPY_BYTE_ORDER NPY_BIG_ENDIAN
+    #else
+        #error Unknown CPU: can not set endianness
+    #endif
+#endif
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_interrupt.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_interrupt.h
new file mode 100644
index 0000000..40cb7ac
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_interrupt.h
@@ -0,0 +1,117 @@
+
+/* Signal handling:
+
+This header file defines macros that allow your code to handle
+interrupts received during processing.  Interrupts that
+could reasonably be handled:
+
+SIGINT, SIGABRT, SIGALRM, SIGSEGV
+
+****Warning***************
+
+Do not allow code that creates temporary memory or increases reference
+counts of Python objects to be interrupted unless you handle it
+differently.
+
+**************************
+
+The mechanism for handling interrupts is conceptually simple:
+
+  - replace the signal handler with our own home-grown version
+     and store the old one.
+  - run the code to be interrupted -- if an interrupt occurs
+     the handler should basically just cause a return to the
+     calling function for finish work.
+  - restore the old signal handler
+
+Of course, every code that allows interrupts must account for
+returning via the interrupt and handle clean-up correctly.  But,
+even still, the simple paradigm is complicated by at least three
+factors.
+
+ 1) platform portability (i.e. Microsoft says not to use longjmp
+     to return from signal handling.  They have a __try  and __except
+     extension to C instead but what about mingw?).
+
+ 2) how to handle threads: apparently whether signals are delivered to
+    every thread of the process or the "invoking" thread is platform
+    dependent. --- we don't handle threads for now.
+
+ 3) do we need to worry about re-entrance.  For now, assume the
+    code will not call-back into itself.
+
+Ideas:
+
+ 1) Start by implementing an approach that works on platforms that
+    can use setjmp and longjmp functionality and does nothing
+    on other platforms.
+
+ 2) Ignore threads --- i.e. do not mix interrupt handling and threads
+
+ 3) Add a default signal_handler function to the C-API but have the rest
+    use macros.
+
+
+Simple Interface:
+
+
+In your C-extension: around a block of code you want to be interruptible
+with a SIGINT
+
+NPY_SIGINT_ON
+[code]
+NPY_SIGINT_OFF
+
+In order for this to work correctly, the
+[code] block must not allocate any memory or alter the reference count of any
+Python objects.  In other words [code] must be interruptible so that continuation
+after NPY_SIGINT_OFF will only be "missing some computations"
+
+Interrupt handling does not work well with threads.
+
+*/
+
+/* Add signal handling macros
+   Make the global variable and signal handler part of the C-API
+*/
+
+#ifndef NPY_INTERRUPT_H
+#define NPY_INTERRUPT_H
+
+#ifndef NPY_NO_SIGNAL
+
+#include <setjmp.h>
+#include <signal.h>
+
+#ifndef sigsetjmp
+
+#define NPY_SIGSETJMP(arg1, arg2) setjmp(arg1)
+#define NPY_SIGLONGJMP(arg1, arg2) longjmp(arg1, arg2)
+#define NPY_SIGJMP_BUF jmp_buf
+
+#else
+
+#define NPY_SIGSETJMP(arg1, arg2) sigsetjmp(arg1, arg2)
+#define NPY_SIGLONGJMP(arg1, arg2) siglongjmp(arg1, arg2)
+#define NPY_SIGJMP_BUF sigjmp_buf
+
+#endif
+
+#    define NPY_SIGINT_ON {                                             \
+                   PyOS_sighandler_t _npy_sig_save;                     \
+                   _npy_sig_save = PyOS_setsig(SIGINT, _PyArray_SigintHandler); \
+                   if (NPY_SIGSETJMP(*((NPY_SIGJMP_BUF *)_PyArray_GetSigintBuf()), \
+                                 1) == 0) {                             \
+
+#    define NPY_SIGINT_OFF }                                      \
+        PyOS_setsig(SIGINT, _npy_sig_save);                       \
+        }
+
+#else /* NPY_NO_SIGNAL  */
+
+#define NPY_SIGINT_ON
+#define NPY_SIGINT_OFF
+
+#endif /* HAVE_SIGSETJMP */
+
+#endif /* NPY_INTERRUPT_H */
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_math.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_math.h
new file mode 100644
index 0000000..582390c
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_math.h
@@ -0,0 +1,551 @@
+#ifndef __NPY_MATH_C99_H_
+#define __NPY_MATH_C99_H_
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+#include <math.h>
+#ifdef __SUNPRO_CC
+#include <sunmath.h>
+#endif
+#ifdef HAVE_NPY_CONFIG_H
+#include <npy_config.h>
+#endif
+#include <numpy/npy_common.h>
+
+/* By adding static inline specifiers to npy_math function definitions when
+   appropriate, compiler is given the opportunity to optimize */
+#if NPY_INLINE_MATH
+#define NPY_INPLACE NPY_INLINE static
+#else
+#define NPY_INPLACE
+#endif
+
+
+/*
+ * NAN and INFINITY like macros (same behavior as glibc for NAN, same as C99
+ * for INFINITY)
+ *
+ * XXX: I should test whether INFINITY and NAN are available on the platform
+ */
+NPY_INLINE static float __npy_inff(void)
+{
+    const union { npy_uint32 __i; float __f;} __bint = {0x7f800000UL};
+    return __bint.__f;
+}
+
+NPY_INLINE static float __npy_nanf(void)
+{
+    const union { npy_uint32 __i; float __f;} __bint = {0x7fc00000UL};
+    return __bint.__f;
+}
+
+NPY_INLINE static float __npy_pzerof(void)
+{
+    const union { npy_uint32 __i; float __f;} __bint = {0x00000000UL};
+    return __bint.__f;
+}
+
+NPY_INLINE static float __npy_nzerof(void)
+{
+    const union { npy_uint32 __i; float __f;} __bint = {0x80000000UL};
+    return __bint.__f;
+}
+
+#define NPY_INFINITYF __npy_inff()
+#define NPY_NANF __npy_nanf()
+#define NPY_PZEROF __npy_pzerof()
+#define NPY_NZEROF __npy_nzerof()
+
+#define NPY_INFINITY ((npy_double)NPY_INFINITYF)
+#define NPY_NAN ((npy_double)NPY_NANF)
+#define NPY_PZERO ((npy_double)NPY_PZEROF)
+#define NPY_NZERO ((npy_double)NPY_NZEROF)
+
+#define NPY_INFINITYL ((npy_longdouble)NPY_INFINITYF)
+#define NPY_NANL ((npy_longdouble)NPY_NANF)
+#define NPY_PZEROL ((npy_longdouble)NPY_PZEROF)
+#define NPY_NZEROL ((npy_longdouble)NPY_NZEROF)
+
+/*
+ * Useful constants
+ */
+#define NPY_E         2.718281828459045235360287471352662498  /* e */
+#define NPY_LOG2E     1.442695040888963407359924681001892137  /* log_2 e */
+#define NPY_LOG10E    0.434294481903251827651128918916605082  /* log_10 e */
+#define NPY_LOGE2     0.693147180559945309417232121458176568  /* log_e 2 */
+#define NPY_LOGE10    2.302585092994045684017991454684364208  /* log_e 10 */
+#define NPY_PI        3.141592653589793238462643383279502884  /* pi */
+#define NPY_PI_2      1.570796326794896619231321691639751442  /* pi/2 */
+#define NPY_PI_4      0.785398163397448309615660845819875721  /* pi/4 */
+#define NPY_1_PI      0.318309886183790671537767526745028724  /* 1/pi */
+#define NPY_2_PI      0.636619772367581343075535053490057448  /* 2/pi */
+#define NPY_EULER     0.577215664901532860606512090082402431  /* Euler constant */
+#define NPY_SQRT2     1.414213562373095048801688724209698079  /* sqrt(2) */
+#define NPY_SQRT1_2   0.707106781186547524400844362104849039  /* 1/sqrt(2) */
+
+#define NPY_Ef        2.718281828459045235360287471352662498F /* e */
+#define NPY_LOG2Ef    1.442695040888963407359924681001892137F /* log_2 e */
+#define NPY_LOG10Ef   0.434294481903251827651128918916605082F /* log_10 e */
+#define NPY_LOGE2f    0.693147180559945309417232121458176568F /* log_e 2 */
+#define NPY_LOGE10f   2.302585092994045684017991454684364208F /* log_e 10 */
+#define NPY_PIf       3.141592653589793238462643383279502884F /* pi */
+#define NPY_PI_2f     1.570796326794896619231321691639751442F /* pi/2 */
+#define NPY_PI_4f     0.785398163397448309615660845819875721F /* pi/4 */
+#define NPY_1_PIf     0.318309886183790671537767526745028724F /* 1/pi */
+#define NPY_2_PIf     0.636619772367581343075535053490057448F /* 2/pi */
+#define NPY_EULERf    0.577215664901532860606512090082402431F /* Euler constant */
+#define NPY_SQRT2f    1.414213562373095048801688724209698079F /* sqrt(2) */
+#define NPY_SQRT1_2f  0.707106781186547524400844362104849039F /* 1/sqrt(2) */
+
+#define NPY_El        2.718281828459045235360287471352662498L /* e */
+#define NPY_LOG2El    1.442695040888963407359924681001892137L /* log_2 e */
+#define NPY_LOG10El   0.434294481903251827651128918916605082L /* log_10 e */
+#define NPY_LOGE2l    0.693147180559945309417232121458176568L /* log_e 2 */
+#define NPY_LOGE10l   2.302585092994045684017991454684364208L /* log_e 10 */
+#define NPY_PIl       3.141592653589793238462643383279502884L /* pi */
+#define NPY_PI_2l     1.570796326794896619231321691639751442L /* pi/2 */
+#define NPY_PI_4l     0.785398163397448309615660845819875721L /* pi/4 */
+#define NPY_1_PIl     0.318309886183790671537767526745028724L /* 1/pi */
+#define NPY_2_PIl     0.636619772367581343075535053490057448L /* 2/pi */
+#define NPY_EULERl    0.577215664901532860606512090082402431L /* Euler constant */
+#define NPY_SQRT2l    1.414213562373095048801688724209698079L /* sqrt(2) */
+#define NPY_SQRT1_2l  0.707106781186547524400844362104849039L /* 1/sqrt(2) */
+
+/*
+ * C99 double math funcs
+ */
+NPY_INPLACE double npy_sin(double x);
+NPY_INPLACE double npy_cos(double x);
+NPY_INPLACE double npy_tan(double x);
+NPY_INPLACE double npy_sinh(double x);
+NPY_INPLACE double npy_cosh(double x);
+NPY_INPLACE double npy_tanh(double x);
+
+NPY_INPLACE double npy_asin(double x);
+NPY_INPLACE double npy_acos(double x);
+NPY_INPLACE double npy_atan(double x);
+
+NPY_INPLACE double npy_log(double x);
+NPY_INPLACE double npy_log10(double x);
+NPY_INPLACE double npy_exp(double x);
+NPY_INPLACE double npy_sqrt(double x);
+NPY_INPLACE double npy_cbrt(double x);
+
+NPY_INPLACE double npy_fabs(double x);
+NPY_INPLACE double npy_ceil(double x);
+NPY_INPLACE double npy_fmod(double x, double y);
+NPY_INPLACE double npy_floor(double x);
+
+NPY_INPLACE double npy_expm1(double x);
+NPY_INPLACE double npy_log1p(double x);
+NPY_INPLACE double npy_hypot(double x, double y);
+NPY_INPLACE double npy_acosh(double x);
+NPY_INPLACE double npy_asinh(double xx);
+NPY_INPLACE double npy_atanh(double x);
+NPY_INPLACE double npy_rint(double x);
+NPY_INPLACE double npy_trunc(double x);
+NPY_INPLACE double npy_exp2(double x);
+NPY_INPLACE double npy_log2(double x);
+
+NPY_INPLACE double npy_atan2(double x, double y);
+NPY_INPLACE double npy_pow(double x, double y);
+NPY_INPLACE double npy_modf(double x, double* y);
+NPY_INPLACE double npy_frexp(double x, int* y);
+NPY_INPLACE double npy_ldexp(double n, int y);
+
+NPY_INPLACE double npy_copysign(double x, double y);
+double npy_nextafter(double x, double y);
+double npy_spacing(double x);
+
+/*
+ * IEEE 754 fpu handling. Those are guaranteed to be macros
+ */
+
+/* use builtins to avoid function calls in tight loops
+ * only available if npy_config.h is available (= numpys own build) */
+#if HAVE___BUILTIN_ISNAN
+    #define npy_isnan(x) __builtin_isnan(x)
+#else
+    #ifndef NPY_HAVE_DECL_ISNAN
+        #define npy_isnan(x) ((x) != (x))
+    #else
+        #if defined(_MSC_VER) && (_MSC_VER < 1900)
+            #define npy_isnan(x) _isnan((x))
+        #else
+            #define npy_isnan(x) isnan(x)
+        #endif
+    #endif
+#endif
+
+
+/* only available if npy_config.h is available (= numpys own build) */
+#if HAVE___BUILTIN_ISFINITE
+    #define npy_isfinite(x) __builtin_isfinite(x)
+#else
+    #ifndef NPY_HAVE_DECL_ISFINITE
+        #ifdef _MSC_VER
+            #define npy_isfinite(x) _finite((x))
+        #else
+            #define npy_isfinite(x) !npy_isnan((x) + (-x))
+        #endif
+    #else
+        #define npy_isfinite(x) isfinite((x))
+    #endif
+#endif
+
+/* only available if npy_config.h is available (= numpys own build) */
+#if HAVE___BUILTIN_ISINF
+    #define npy_isinf(x) __builtin_isinf(x)
+#else
+    #ifndef NPY_HAVE_DECL_ISINF
+        #define npy_isinf(x) (!npy_isfinite(x) && !npy_isnan(x))
+    #else
+        #if defined(_MSC_VER) && (_MSC_VER < 1900)
+            #define npy_isinf(x) (!_finite((x)) && !_isnan((x)))
+        #else
+            #define npy_isinf(x) isinf((x))
+        #endif
+    #endif
+#endif
+
+#ifndef NPY_HAVE_DECL_SIGNBIT
+    int _npy_signbit_f(float x);
+    int _npy_signbit_d(double x);
+    int _npy_signbit_ld(long double x);
+    #define npy_signbit(x) \
+        (sizeof (x) == sizeof (long double) ? _npy_signbit_ld (x) \
+         : sizeof (x) == sizeof (double) ? _npy_signbit_d (x) \
+         : _npy_signbit_f (x))
+#else
+    #define npy_signbit(x) signbit((x))
+#endif
+
+/*
+ * float C99 math functions
+ */
+NPY_INPLACE float npy_sinf(float x);
+NPY_INPLACE float npy_cosf(float x);
+NPY_INPLACE float npy_tanf(float x);
+NPY_INPLACE float npy_sinhf(float x);
+NPY_INPLACE float npy_coshf(float x);
+NPY_INPLACE float npy_tanhf(float x);
+NPY_INPLACE float npy_fabsf(float x);
+NPY_INPLACE float npy_floorf(float x);
+NPY_INPLACE float npy_ceilf(float x);
+NPY_INPLACE float npy_rintf(float x);
+NPY_INPLACE float npy_truncf(float x);
+NPY_INPLACE float npy_sqrtf(float x);
+NPY_INPLACE float npy_cbrtf(float x);
+NPY_INPLACE float npy_log10f(float x);
+NPY_INPLACE float npy_logf(float x);
+NPY_INPLACE float npy_expf(float x);
+NPY_INPLACE float npy_expm1f(float x);
+NPY_INPLACE float npy_asinf(float x);
+NPY_INPLACE float npy_acosf(float x);
+NPY_INPLACE float npy_atanf(float x);
+NPY_INPLACE float npy_asinhf(float x);
+NPY_INPLACE float npy_acoshf(float x);
+NPY_INPLACE float npy_atanhf(float x);
+NPY_INPLACE float npy_log1pf(float x);
+NPY_INPLACE float npy_exp2f(float x);
+NPY_INPLACE float npy_log2f(float x);
+
+NPY_INPLACE float npy_atan2f(float x, float y);
+NPY_INPLACE float npy_hypotf(float x, float y);
+NPY_INPLACE float npy_powf(float x, float y);
+NPY_INPLACE float npy_fmodf(float x, float y);
+
+NPY_INPLACE float npy_modff(float x, float* y);
+NPY_INPLACE float npy_frexpf(float x, int* y);
+NPY_INPLACE float npy_ldexpf(float x, int y);
+
+NPY_INPLACE float npy_copysignf(float x, float y);
+float npy_nextafterf(float x, float y);
+float npy_spacingf(float x);
+
+/*
+ * long double C99 math functions
+ */
+NPY_INPLACE npy_longdouble npy_sinl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_cosl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_tanl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_sinhl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_coshl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_tanhl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_fabsl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_floorl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_ceill(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_rintl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_truncl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_sqrtl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_cbrtl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_log10l(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_logl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_expl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_expm1l(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_asinl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_acosl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_atanl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_asinhl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_acoshl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_atanhl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_log1pl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_exp2l(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_log2l(npy_longdouble x);
+
+NPY_INPLACE npy_longdouble npy_atan2l(npy_longdouble x, npy_longdouble y);
+NPY_INPLACE npy_longdouble npy_hypotl(npy_longdouble x, npy_longdouble y);
+NPY_INPLACE npy_longdouble npy_powl(npy_longdouble x, npy_longdouble y);
+NPY_INPLACE npy_longdouble npy_fmodl(npy_longdouble x, npy_longdouble y);
+
+NPY_INPLACE npy_longdouble npy_modfl(npy_longdouble x, npy_longdouble* y);
+NPY_INPLACE npy_longdouble npy_frexpl(npy_longdouble x, int* y);
+NPY_INPLACE npy_longdouble npy_ldexpl(npy_longdouble x, int y);
+
+NPY_INPLACE npy_longdouble npy_copysignl(npy_longdouble x, npy_longdouble y);
+npy_longdouble npy_nextafterl(npy_longdouble x, npy_longdouble y);
+npy_longdouble npy_spacingl(npy_longdouble x);
+
+/*
+ * Non standard functions
+ */
+NPY_INPLACE double npy_deg2rad(double x);
+NPY_INPLACE double npy_rad2deg(double x);
+NPY_INPLACE double npy_logaddexp(double x, double y);
+NPY_INPLACE double npy_logaddexp2(double x, double y);
+NPY_INPLACE double npy_divmod(double x, double y, double *modulus);
+NPY_INPLACE double npy_heaviside(double x, double h0);
+
+NPY_INPLACE float npy_deg2radf(float x);
+NPY_INPLACE float npy_rad2degf(float x);
+NPY_INPLACE float npy_logaddexpf(float x, float y);
+NPY_INPLACE float npy_logaddexp2f(float x, float y);
+NPY_INPLACE float npy_divmodf(float x, float y, float *modulus);
+NPY_INPLACE float npy_heavisidef(float x, float h0);
+
+NPY_INPLACE npy_longdouble npy_deg2radl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_rad2degl(npy_longdouble x);
+NPY_INPLACE npy_longdouble npy_logaddexpl(npy_longdouble x, npy_longdouble y);
+NPY_INPLACE npy_longdouble npy_logaddexp2l(npy_longdouble x, npy_longdouble y);
+NPY_INPLACE npy_longdouble npy_divmodl(npy_longdouble x, npy_longdouble y,
+                           npy_longdouble *modulus);
+NPY_INPLACE npy_longdouble npy_heavisidel(npy_longdouble x, npy_longdouble h0);
+
+#define npy_degrees npy_rad2deg
+#define npy_degreesf npy_rad2degf
+#define npy_degreesl npy_rad2degl
+
+#define npy_radians npy_deg2rad
+#define npy_radiansf npy_deg2radf
+#define npy_radiansl npy_deg2radl
+
+/*
+ * Complex declarations
+ */
+
+/*
+ * C99 specifies that complex numbers have the same representation as
+ * an array of two elements, where the first element is the real part
+ * and the second element is the imaginary part.
+ */
+#define __NPY_CPACK_IMP(x, y, type, ctype)   \
+    union {                                  \
+        ctype z;                             \
+        type a[2];                           \
+    } z1;;                                   \
+                                             \
+    z1.a[0] = (x);                           \
+    z1.a[1] = (y);                           \
+                                             \
+    return z1.z;
+
+static NPY_INLINE npy_cdouble npy_cpack(double x, double y)
+{
+    __NPY_CPACK_IMP(x, y, double, npy_cdouble);
+}
+
+static NPY_INLINE npy_cfloat npy_cpackf(float x, float y)
+{
+    __NPY_CPACK_IMP(x, y, float, npy_cfloat);
+}
+
+static NPY_INLINE npy_clongdouble npy_cpackl(npy_longdouble x, npy_longdouble y)
+{
+    __NPY_CPACK_IMP(x, y, npy_longdouble, npy_clongdouble);
+}
+#undef __NPY_CPACK_IMP
+
+/*
+ * Same remark as above, but in the other direction: extract first/second
+ * member of complex number, assuming a C99-compatible representation
+ *
+ * Those are defineds as static inline, and such as a reasonable compiler would
+ * most likely compile this to one or two instructions (on CISC at least)
+ */
+#define __NPY_CEXTRACT_IMP(z, index, type, ctype)   \
+    union {                                         \
+        ctype z;                                    \
+        type a[2];                                  \
+    } __z_repr;                                     \
+    __z_repr.z = z;                                 \
+                                                    \
+    return __z_repr.a[index];
+
+static NPY_INLINE double npy_creal(npy_cdouble z)
+{
+    __NPY_CEXTRACT_IMP(z, 0, double, npy_cdouble);
+}
+
+static NPY_INLINE double npy_cimag(npy_cdouble z)
+{
+    __NPY_CEXTRACT_IMP(z, 1, double, npy_cdouble);
+}
+
+static NPY_INLINE float npy_crealf(npy_cfloat z)
+{
+    __NPY_CEXTRACT_IMP(z, 0, float, npy_cfloat);
+}
+
+static NPY_INLINE float npy_cimagf(npy_cfloat z)
+{
+    __NPY_CEXTRACT_IMP(z, 1, float, npy_cfloat);
+}
+
+static NPY_INLINE npy_longdouble npy_creall(npy_clongdouble z)
+{
+    __NPY_CEXTRACT_IMP(z, 0, npy_longdouble, npy_clongdouble);
+}
+
+static NPY_INLINE npy_longdouble npy_cimagl(npy_clongdouble z)
+{
+    __NPY_CEXTRACT_IMP(z, 1, npy_longdouble, npy_clongdouble);
+}
+#undef __NPY_CEXTRACT_IMP
+
+/*
+ * Double precision complex functions
+ */
+double npy_cabs(npy_cdouble z);
+double npy_carg(npy_cdouble z);
+
+npy_cdouble npy_cexp(npy_cdouble z);
+npy_cdouble npy_clog(npy_cdouble z);
+npy_cdouble npy_cpow(npy_cdouble x, npy_cdouble y);
+
+npy_cdouble npy_csqrt(npy_cdouble z);
+
+npy_cdouble npy_ccos(npy_cdouble z);
+npy_cdouble npy_csin(npy_cdouble z);
+npy_cdouble npy_ctan(npy_cdouble z);
+
+npy_cdouble npy_ccosh(npy_cdouble z);
+npy_cdouble npy_csinh(npy_cdouble z);
+npy_cdouble npy_ctanh(npy_cdouble z);
+
+npy_cdouble npy_cacos(npy_cdouble z);
+npy_cdouble npy_casin(npy_cdouble z);
+npy_cdouble npy_catan(npy_cdouble z);
+
+npy_cdouble npy_cacosh(npy_cdouble z);
+npy_cdouble npy_casinh(npy_cdouble z);
+npy_cdouble npy_catanh(npy_cdouble z);
+
+/*
+ * Single precision complex functions
+ */
+float npy_cabsf(npy_cfloat z);
+float npy_cargf(npy_cfloat z);
+
+npy_cfloat npy_cexpf(npy_cfloat z);
+npy_cfloat npy_clogf(npy_cfloat z);
+npy_cfloat npy_cpowf(npy_cfloat x, npy_cfloat y);
+
+npy_cfloat npy_csqrtf(npy_cfloat z);
+
+npy_cfloat npy_ccosf(npy_cfloat z);
+npy_cfloat npy_csinf(npy_cfloat z);
+npy_cfloat npy_ctanf(npy_cfloat z);
+
+npy_cfloat npy_ccoshf(npy_cfloat z);
+npy_cfloat npy_csinhf(npy_cfloat z);
+npy_cfloat npy_ctanhf(npy_cfloat z);
+
+npy_cfloat npy_cacosf(npy_cfloat z);
+npy_cfloat npy_casinf(npy_cfloat z);
+npy_cfloat npy_catanf(npy_cfloat z);
+
+npy_cfloat npy_cacoshf(npy_cfloat z);
+npy_cfloat npy_casinhf(npy_cfloat z);
+npy_cfloat npy_catanhf(npy_cfloat z);
+
+
+/*
+ * Extended precision complex functions
+ */
+npy_longdouble npy_cabsl(npy_clongdouble z);
+npy_longdouble npy_cargl(npy_clongdouble z);
+
+npy_clongdouble npy_cexpl(npy_clongdouble z);
+npy_clongdouble npy_clogl(npy_clongdouble z);
+npy_clongdouble npy_cpowl(npy_clongdouble x, npy_clongdouble y);
+
+npy_clongdouble npy_csqrtl(npy_clongdouble z);
+
+npy_clongdouble npy_ccosl(npy_clongdouble z);
+npy_clongdouble npy_csinl(npy_clongdouble z);
+npy_clongdouble npy_ctanl(npy_clongdouble z);
+
+npy_clongdouble npy_ccoshl(npy_clongdouble z);
+npy_clongdouble npy_csinhl(npy_clongdouble z);
+npy_clongdouble npy_ctanhl(npy_clongdouble z);
+
+npy_clongdouble npy_cacosl(npy_clongdouble z);
+npy_clongdouble npy_casinl(npy_clongdouble z);
+npy_clongdouble npy_catanl(npy_clongdouble z);
+
+npy_clongdouble npy_cacoshl(npy_clongdouble z);
+npy_clongdouble npy_casinhl(npy_clongdouble z);
+npy_clongdouble npy_catanhl(npy_clongdouble z);
+
+
+/*
+ * Functions that set the floating point error
+ * status word.
+ */
+
+/*
+ * platform-dependent code translates floating point
+ * status to an integer sum of these values
+ */
+#define NPY_FPE_DIVIDEBYZERO  1
+#define NPY_FPE_OVERFLOW      2
+#define NPY_FPE_UNDERFLOW     4
+#define NPY_FPE_INVALID       8
+
+int npy_clear_floatstatus_barrier(char*);
+int npy_get_floatstatus_barrier(char*);
+/*
+ * use caution with these - clang and gcc8.1 are known to reorder calls
+ * to this form of the function which can defeat the check. The _barrier
+ * form of the call is preferable, where the argument is
+ * (char*)&local_variable
+ */
+int npy_clear_floatstatus(void);
+int npy_get_floatstatus(void);
+
+void npy_set_floatstatus_divbyzero(void);
+void npy_set_floatstatus_overflow(void);
+void npy_set_floatstatus_underflow(void);
+void npy_set_floatstatus_invalid(void);
+
+#ifdef __cplusplus
+}
+#endif
+
+#if NPY_INLINE_MATH
+#include "npy_math_internal.h"
+#endif
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_no_deprecated_api.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_no_deprecated_api.h
new file mode 100644
index 0000000..6183dc2
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_no_deprecated_api.h
@@ -0,0 +1,19 @@
+/*
+ * This include file is provided for inclusion in Cython *.pyd files where
+ * one would like to define the NPY_NO_DEPRECATED_API macro. It can be
+ * included by
+ *
+ * cdef extern from "npy_no_deprecated_api.h": pass
+ *
+ */
+#ifndef NPY_NO_DEPRECATED_API
+
+/* put this check here since there may be multiple includes in C extensions. */
+#if defined(NDARRAYTYPES_H) || defined(_NPY_DEPRECATED_API_H) || \
+    defined(OLD_DEFINES_H)
+#error "npy_no_deprecated_api.h" must be first among numpy includes.
+#else
+#define NPY_NO_DEPRECATED_API NPY_API_VERSION
+#endif
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_os.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_os.h
new file mode 100644
index 0000000..9228c39
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/npy_os.h
@@ -0,0 +1,30 @@
+#ifndef _NPY_OS_H_
+#define _NPY_OS_H_
+
+#if defined(linux) || defined(__linux) || defined(__linux__)
+    #define NPY_OS_LINUX
+#elif defined(__FreeBSD__) || defined(__NetBSD__) || \
+            defined(__OpenBSD__) || defined(__DragonFly__)
+    #define NPY_OS_BSD
+    #ifdef __FreeBSD__
+        #define NPY_OS_FREEBSD
+    #elif defined(__NetBSD__)
+        #define NPY_OS_NETBSD
+    #elif defined(__OpenBSD__)
+        #define NPY_OS_OPENBSD
+    #elif defined(__DragonFly__)
+        #define NPY_OS_DRAGONFLY
+    #endif
+#elif defined(sun) || defined(__sun)
+    #define NPY_OS_SOLARIS
+#elif defined(__CYGWIN__)
+    #define NPY_OS_CYGWIN
+#elif defined(_WIN32) || defined(__WIN32__) || defined(WIN32)
+    #define NPY_OS_WIN32
+#elif defined(__APPLE__)
+    #define NPY_OS_DARWIN
+#else
+    #define NPY_OS_UNKNOWN
+#endif
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/numpyconfig.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/numpyconfig.h
new file mode 100644
index 0000000..ab198f3
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/numpyconfig.h
@@ -0,0 +1,41 @@
+#ifndef _NPY_NUMPYCONFIG_H_
+#define _NPY_NUMPYCONFIG_H_
+
+#include "_numpyconfig.h"
+
+/*
+ * On Mac OS X, because there is only one configuration stage for all the archs
+ * in universal builds, any macro which depends on the arch needs to be
+ * hardcoded
+ */
+#ifdef __APPLE__
+    #undef NPY_SIZEOF_LONG
+    #undef NPY_SIZEOF_PY_INTPTR_T
+
+    #ifdef __LP64__
+        #define NPY_SIZEOF_LONG         8
+        #define NPY_SIZEOF_PY_INTPTR_T  8
+    #else
+        #define NPY_SIZEOF_LONG         4
+        #define NPY_SIZEOF_PY_INTPTR_T  4
+    #endif
+#endif
+
+/**
+ * To help with the NPY_NO_DEPRECATED_API macro, we include API version
+ * numbers for specific versions of NumPy. To exclude all API that was
+ * deprecated as of 1.7, add the following before #including any NumPy
+ * headers:
+ *   #define NPY_NO_DEPRECATED_API  NPY_1_7_API_VERSION
+ */
+#define NPY_1_7_API_VERSION 0x00000007
+#define NPY_1_8_API_VERSION 0x00000008
+#define NPY_1_9_API_VERSION 0x00000008
+#define NPY_1_10_API_VERSION 0x00000008
+#define NPY_1_11_API_VERSION 0x00000008
+#define NPY_1_12_API_VERSION 0x00000008
+#define NPY_1_13_API_VERSION 0x00000008
+#define NPY_1_14_API_VERSION 0x00000008
+#define NPY_1_15_API_VERSION 0x00000008
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/old_defines.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/old_defines.h
new file mode 100644
index 0000000..abf8159
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/old_defines.h
@@ -0,0 +1,187 @@
+/* This header is deprecated as of NumPy 1.7 */
+#ifndef OLD_DEFINES_H
+#define OLD_DEFINES_H
+
+#if defined(NPY_NO_DEPRECATED_API) && NPY_NO_DEPRECATED_API >= NPY_1_7_API_VERSION
+#error The header "old_defines.h" is deprecated as of NumPy 1.7.
+#endif
+
+#define NDARRAY_VERSION NPY_VERSION
+
+#define PyArray_MIN_BUFSIZE NPY_MIN_BUFSIZE
+#define PyArray_MAX_BUFSIZE NPY_MAX_BUFSIZE
+#define PyArray_BUFSIZE NPY_BUFSIZE
+
+#define PyArray_PRIORITY NPY_PRIORITY
+#define PyArray_SUBTYPE_PRIORITY NPY_PRIORITY
+#define PyArray_NUM_FLOATTYPE NPY_NUM_FLOATTYPE
+
+#define NPY_MAX PyArray_MAX
+#define NPY_MIN PyArray_MIN
+
+#define PyArray_TYPES       NPY_TYPES
+#define PyArray_BOOL        NPY_BOOL
+#define PyArray_BYTE        NPY_BYTE
+#define PyArray_UBYTE       NPY_UBYTE
+#define PyArray_SHORT       NPY_SHORT
+#define PyArray_USHORT      NPY_USHORT
+#define PyArray_INT         NPY_INT
+#define PyArray_UINT        NPY_UINT
+#define PyArray_LONG        NPY_LONG
+#define PyArray_ULONG       NPY_ULONG
+#define PyArray_LONGLONG    NPY_LONGLONG
+#define PyArray_ULONGLONG   NPY_ULONGLONG
+#define PyArray_HALF        NPY_HALF
+#define PyArray_FLOAT       NPY_FLOAT
+#define PyArray_DOUBLE      NPY_DOUBLE
+#define PyArray_LONGDOUBLE  NPY_LONGDOUBLE
+#define PyArray_CFLOAT      NPY_CFLOAT
+#define PyArray_CDOUBLE     NPY_CDOUBLE
+#define PyArray_CLONGDOUBLE NPY_CLONGDOUBLE
+#define PyArray_OBJECT      NPY_OBJECT
+#define PyArray_STRING      NPY_STRING
+#define PyArray_UNICODE     NPY_UNICODE
+#define PyArray_VOID        NPY_VOID
+#define PyArray_DATETIME    NPY_DATETIME
+#define PyArray_TIMEDELTA   NPY_TIMEDELTA
+#define PyArray_NTYPES      NPY_NTYPES
+#define PyArray_NOTYPE      NPY_NOTYPE
+#define PyArray_CHAR        NPY_CHAR
+#define PyArray_USERDEF     NPY_USERDEF
+#define PyArray_NUMUSERTYPES NPY_NUMUSERTYPES
+
+#define PyArray_INTP        NPY_INTP
+#define PyArray_UINTP       NPY_UINTP
+
+#define PyArray_INT8    NPY_INT8
+#define PyArray_UINT8   NPY_UINT8
+#define PyArray_INT16   NPY_INT16
+#define PyArray_UINT16  NPY_UINT16
+#define PyArray_INT32   NPY_INT32
+#define PyArray_UINT32  NPY_UINT32
+
+#ifdef NPY_INT64
+#define PyArray_INT64   NPY_INT64
+#define PyArray_UINT64  NPY_UINT64
+#endif
+
+#ifdef NPY_INT128
+#define PyArray_INT128 NPY_INT128
+#define PyArray_UINT128 NPY_UINT128
+#endif
+
+#ifdef NPY_FLOAT16
+#define PyArray_FLOAT16  NPY_FLOAT16
+#define PyArray_COMPLEX32  NPY_COMPLEX32
+#endif
+
+#ifdef NPY_FLOAT80
+#define PyArray_FLOAT80  NPY_FLOAT80
+#define PyArray_COMPLEX160  NPY_COMPLEX160
+#endif
+
+#ifdef NPY_FLOAT96
+#define PyArray_FLOAT96  NPY_FLOAT96
+#define PyArray_COMPLEX192  NPY_COMPLEX192
+#endif
+
+#ifdef NPY_FLOAT128
+#define PyArray_FLOAT128  NPY_FLOAT128
+#define PyArray_COMPLEX256  NPY_COMPLEX256
+#endif
+
+#define PyArray_FLOAT32    NPY_FLOAT32
+#define PyArray_COMPLEX64  NPY_COMPLEX64
+#define PyArray_FLOAT64    NPY_FLOAT64
+#define PyArray_COMPLEX128 NPY_COMPLEX128
+
+
+#define PyArray_TYPECHAR        NPY_TYPECHAR
+#define PyArray_BOOLLTR         NPY_BOOLLTR
+#define PyArray_BYTELTR         NPY_BYTELTR
+#define PyArray_UBYTELTR        NPY_UBYTELTR
+#define PyArray_SHORTLTR        NPY_SHORTLTR
+#define PyArray_USHORTLTR       NPY_USHORTLTR
+#define PyArray_INTLTR          NPY_INTLTR
+#define PyArray_UINTLTR         NPY_UINTLTR
+#define PyArray_LONGLTR         NPY_LONGLTR
+#define PyArray_ULONGLTR        NPY_ULONGLTR
+#define PyArray_LONGLONGLTR     NPY_LONGLONGLTR
+#define PyArray_ULONGLONGLTR    NPY_ULONGLONGLTR
+#define PyArray_HALFLTR         NPY_HALFLTR
+#define PyArray_FLOATLTR        NPY_FLOATLTR
+#define PyArray_DOUBLELTR       NPY_DOUBLELTR
+#define PyArray_LONGDOUBLELTR   NPY_LONGDOUBLELTR
+#define PyArray_CFLOATLTR       NPY_CFLOATLTR
+#define PyArray_CDOUBLELTR      NPY_CDOUBLELTR
+#define PyArray_CLONGDOUBLELTR  NPY_CLONGDOUBLELTR
+#define PyArray_OBJECTLTR       NPY_OBJECTLTR
+#define PyArray_STRINGLTR       NPY_STRINGLTR
+#define PyArray_STRINGLTR2      NPY_STRINGLTR2
+#define PyArray_UNICODELTR      NPY_UNICODELTR
+#define PyArray_VOIDLTR         NPY_VOIDLTR
+#define PyArray_DATETIMELTR     NPY_DATETIMELTR
+#define PyArray_TIMEDELTALTR    NPY_TIMEDELTALTR
+#define PyArray_CHARLTR         NPY_CHARLTR
+#define PyArray_INTPLTR         NPY_INTPLTR
+#define PyArray_UINTPLTR        NPY_UINTPLTR
+#define PyArray_GENBOOLLTR      NPY_GENBOOLLTR
+#define PyArray_SIGNEDLTR       NPY_SIGNEDLTR
+#define PyArray_UNSIGNEDLTR     NPY_UNSIGNEDLTR
+#define PyArray_FLOATINGLTR     NPY_FLOATINGLTR
+#define PyArray_COMPLEXLTR      NPY_COMPLEXLTR
+
+#define PyArray_QUICKSORT   NPY_QUICKSORT
+#define PyArray_HEAPSORT    NPY_HEAPSORT
+#define PyArray_MERGESORT   NPY_MERGESORT
+#define PyArray_SORTKIND    NPY_SORTKIND
+#define PyArray_NSORTS      NPY_NSORTS
+
+#define PyArray_NOSCALAR       NPY_NOSCALAR
+#define PyArray_BOOL_SCALAR    NPY_BOOL_SCALAR
+#define PyArray_INTPOS_SCALAR  NPY_INTPOS_SCALAR
+#define PyArray_INTNEG_SCALAR  NPY_INTNEG_SCALAR
+#define PyArray_FLOAT_SCALAR   NPY_FLOAT_SCALAR
+#define PyArray_COMPLEX_SCALAR NPY_COMPLEX_SCALAR
+#define PyArray_OBJECT_SCALAR  NPY_OBJECT_SCALAR
+#define PyArray_SCALARKIND     NPY_SCALARKIND
+#define PyArray_NSCALARKINDS   NPY_NSCALARKINDS
+
+#define PyArray_ANYORDER     NPY_ANYORDER
+#define PyArray_CORDER       NPY_CORDER
+#define PyArray_FORTRANORDER NPY_FORTRANORDER
+#define PyArray_ORDER        NPY_ORDER
+
+#define PyDescr_ISBOOL      PyDataType_ISBOOL
+#define PyDescr_ISUNSIGNED  PyDataType_ISUNSIGNED
+#define PyDescr_ISSIGNED    PyDataType_ISSIGNED
+#define PyDescr_ISINTEGER   PyDataType_ISINTEGER
+#define PyDescr_ISFLOAT     PyDataType_ISFLOAT
+#define PyDescr_ISNUMBER    PyDataType_ISNUMBER
+#define PyDescr_ISSTRING    PyDataType_ISSTRING
+#define PyDescr_ISCOMPLEX   PyDataType_ISCOMPLEX
+#define PyDescr_ISPYTHON    PyDataType_ISPYTHON
+#define PyDescr_ISFLEXIBLE  PyDataType_ISFLEXIBLE
+#define PyDescr_ISUSERDEF   PyDataType_ISUSERDEF
+#define PyDescr_ISEXTENDED  PyDataType_ISEXTENDED
+#define PyDescr_ISOBJECT    PyDataType_ISOBJECT
+#define PyDescr_HASFIELDS   PyDataType_HASFIELDS
+
+#define PyArray_LITTLE NPY_LITTLE
+#define PyArray_BIG NPY_BIG
+#define PyArray_NATIVE NPY_NATIVE
+#define PyArray_SWAP NPY_SWAP
+#define PyArray_IGNORE NPY_IGNORE
+
+#define PyArray_NATBYTE NPY_NATBYTE
+#define PyArray_OPPBYTE NPY_OPPBYTE
+
+#define PyArray_MAX_ELSIZE NPY_MAX_ELSIZE
+
+#define PyArray_USE_PYMEM NPY_USE_PYMEM
+
+#define PyArray_RemoveLargest PyArray_RemoveSmallest
+
+#define PyArray_UCS4 npy_ucs4
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/oldnumeric.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/oldnumeric.h
new file mode 100644
index 0000000..38530fa
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/oldnumeric.h
@@ -0,0 +1,25 @@
+#include "arrayobject.h"
+
+#ifndef PYPY_VERSION
+#ifndef REFCOUNT
+#  define REFCOUNT NPY_REFCOUNT
+#  define MAX_ELSIZE 16
+#endif
+#endif
+
+#define PyArray_UNSIGNED_TYPES
+#define PyArray_SBYTE NPY_BYTE
+#define PyArray_CopyArray PyArray_CopyInto
+#define _PyArray_multiply_list PyArray_MultiplyIntList
+#define PyArray_ISSPACESAVER(m) NPY_FALSE
+#define PyScalarArray_Check PyArray_CheckScalar
+
+#define CONTIGUOUS NPY_CONTIGUOUS
+#define OWN_DIMENSIONS 0
+#define OWN_STRIDES 0
+#define OWN_DATA NPY_OWNDATA
+#define SAVESPACE 0
+#define SAVESPACEBIT 0
+
+#undef import_array
+#define import_array() { if (_import_array() < 0) {PyErr_Print(); PyErr_SetString(PyExc_ImportError, "numpy.core.multiarray failed to import"); } }
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ufunc_api.txt b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ufunc_api.txt
new file mode 100644
index 0000000..883fb77
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ufunc_api.txt
@@ -0,0 +1,337 @@
+
+=================
+NumPy Ufunc C-API
+=================
+::
+
+  PyObject *
+  PyUFunc_FromFuncAndData(PyUFuncGenericFunction *func, void
+                          **data, char *types, int ntypes, int nin, int
+                          nout, int identity, const char *name, const
+                          char *doc, int unused)
+
+
+::
+
+  int
+  PyUFunc_RegisterLoopForType(PyUFuncObject *ufunc, int
+                              usertype, PyUFuncGenericFunction
+                              function, int *arg_types, void *data)
+
+
+::
+
+  int
+  PyUFunc_GenericFunction(PyUFuncObject *ufunc, PyObject *args, PyObject
+                          *kwds, PyArrayObject **op)
+
+
+This generic function is called with the ufunc object, the arguments to it,
+and an array of (pointers to) PyArrayObjects which are NULL.
+
+'op' is an array of at least NPY_MAXARGS PyArrayObject *.
+
+::
+
+  void
+  PyUFunc_f_f_As_d_d(char **args, npy_intp *dimensions, npy_intp
+                     *steps, void *func)
+
+
+::
+
+  void
+  PyUFunc_d_d(char **args, npy_intp *dimensions, npy_intp *steps, void
+              *func)
+
+
+::
+
+  void
+  PyUFunc_f_f(char **args, npy_intp *dimensions, npy_intp *steps, void
+              *func)
+
+
+::
+
+  void
+  PyUFunc_g_g(char **args, npy_intp *dimensions, npy_intp *steps, void
+              *func)
+
+
+::
+
+  void
+  PyUFunc_F_F_As_D_D(char **args, npy_intp *dimensions, npy_intp
+                     *steps, void *func)
+
+
+::
+
+  void
+  PyUFunc_F_F(char **args, npy_intp *dimensions, npy_intp *steps, void
+              *func)
+
+
+::
+
+  void
+  PyUFunc_D_D(char **args, npy_intp *dimensions, npy_intp *steps, void
+              *func)
+
+
+::
+
+  void
+  PyUFunc_G_G(char **args, npy_intp *dimensions, npy_intp *steps, void
+              *func)
+
+
+::
+
+  void
+  PyUFunc_O_O(char **args, npy_intp *dimensions, npy_intp *steps, void
+              *func)
+
+
+::
+
+  void
+  PyUFunc_ff_f_As_dd_d(char **args, npy_intp *dimensions, npy_intp
+                       *steps, void *func)
+
+
+::
+
+  void
+  PyUFunc_ff_f(char **args, npy_intp *dimensions, npy_intp *steps, void
+               *func)
+
+
+::
+
+  void
+  PyUFunc_dd_d(char **args, npy_intp *dimensions, npy_intp *steps, void
+               *func)
+
+
+::
+
+  void
+  PyUFunc_gg_g(char **args, npy_intp *dimensions, npy_intp *steps, void
+               *func)
+
+
+::
+
+  void
+  PyUFunc_FF_F_As_DD_D(char **args, npy_intp *dimensions, npy_intp
+                       *steps, void *func)
+
+
+::
+
+  void
+  PyUFunc_DD_D(char **args, npy_intp *dimensions, npy_intp *steps, void
+               *func)
+
+
+::
+
+  void
+  PyUFunc_FF_F(char **args, npy_intp *dimensions, npy_intp *steps, void
+               *func)
+
+
+::
+
+  void
+  PyUFunc_GG_G(char **args, npy_intp *dimensions, npy_intp *steps, void
+               *func)
+
+
+::
+
+  void
+  PyUFunc_OO_O(char **args, npy_intp *dimensions, npy_intp *steps, void
+               *func)
+
+
+::
+
+  void
+  PyUFunc_O_O_method(char **args, npy_intp *dimensions, npy_intp
+                     *steps, void *func)
+
+
+::
+
+  void
+  PyUFunc_OO_O_method(char **args, npy_intp *dimensions, npy_intp
+                      *steps, void *func)
+
+
+::
+
+  void
+  PyUFunc_On_Om(char **args, npy_intp *dimensions, npy_intp *steps, void
+                *func)
+
+
+::
+
+  int
+  PyUFunc_GetPyValues(char *name, int *bufsize, int *errmask, PyObject
+                      **errobj)
+
+
+On return, if errobj is populated with a non-NULL value, the caller
+owns a new reference to errobj.
+
+::
+
+  int
+  PyUFunc_checkfperr(int errmask, PyObject *errobj, int *first)
+
+
+::
+
+  void
+  PyUFunc_clearfperr()
+
+
+::
+
+  int
+  PyUFunc_getfperr(void )
+
+
+::
+
+  int
+  PyUFunc_handlefperr(int errmask, PyObject *errobj, int retstatus, int
+                      *first)
+
+
+::
+
+  int
+  PyUFunc_ReplaceLoopBySignature(PyUFuncObject
+                                 *func, PyUFuncGenericFunction
+                                 newfunc, int
+                                 *signature, PyUFuncGenericFunction
+                                 *oldfunc)
+
+
+::
+
+  PyObject *
+  PyUFunc_FromFuncAndDataAndSignature(PyUFuncGenericFunction *func, void
+                                      **data, char *types, int
+                                      ntypes, int nin, int nout, int
+                                      identity, const char *name, const
+                                      char *doc, int unused, const char
+                                      *signature)
+
+
+::
+
+  int
+  PyUFunc_SetUsesArraysAsData(void **data, size_t i)
+
+
+::
+
+  void
+  PyUFunc_e_e(char **args, npy_intp *dimensions, npy_intp *steps, void
+              *func)
+
+
+::
+
+  void
+  PyUFunc_e_e_As_f_f(char **args, npy_intp *dimensions, npy_intp
+                     *steps, void *func)
+
+
+::
+
+  void
+  PyUFunc_e_e_As_d_d(char **args, npy_intp *dimensions, npy_intp
+                     *steps, void *func)
+
+
+::
+
+  void
+  PyUFunc_ee_e(char **args, npy_intp *dimensions, npy_intp *steps, void
+               *func)
+
+
+::
+
+  void
+  PyUFunc_ee_e_As_ff_f(char **args, npy_intp *dimensions, npy_intp
+                       *steps, void *func)
+
+
+::
+
+  void
+  PyUFunc_ee_e_As_dd_d(char **args, npy_intp *dimensions, npy_intp
+                       *steps, void *func)
+
+
+::
+
+  int
+  PyUFunc_DefaultTypeResolver(PyUFuncObject *ufunc, NPY_CASTING
+                              casting, PyArrayObject
+                              **operands, PyObject
+                              *type_tup, PyArray_Descr **out_dtypes)
+
+
+This function applies the default type resolution rules
+for the provided ufunc.
+
+Returns 0 on success, -1 on error.
+
+::
+
+  int
+  PyUFunc_ValidateCasting(PyUFuncObject *ufunc, NPY_CASTING
+                          casting, PyArrayObject
+                          **operands, PyArray_Descr **dtypes)
+
+
+Validates that the input operands can be cast to
+the input types, and the output types can be cast to
+the output operands where provided.
+
+Returns 0 on success, -1 (with exception raised) on validation failure.
+
+::
+
+  int
+  PyUFunc_RegisterLoopForDescr(PyUFuncObject *ufunc, PyArray_Descr
+                               *user_dtype, PyUFuncGenericFunction
+                               function, PyArray_Descr
+                               **arg_dtypes, void *data)
+
+
+::
+
+  PyObject *
+  PyUFunc_FromFuncAndDataAndSignatureAndIdentity(PyUFuncGenericFunction
+                                                 *func, void
+                                                 **data, char
+                                                 *types, int ntypes, int
+                                                 nin, int nout, int
+                                                 identity, const char
+                                                 *name, const char
+                                                 *doc, int unused, const
+                                                 char
+                                                 *signature, PyObject
+                                                 *identity_value)
+
+
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ufuncobject.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ufuncobject.h
new file mode 100644
index 0000000..90d837a
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/ufuncobject.h
@@ -0,0 +1,377 @@
+#ifndef Py_UFUNCOBJECT_H
+#define Py_UFUNCOBJECT_H
+
+#include <numpy/npy_math.h>
+#include <numpy/npy_common.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*
+ * The legacy generic inner loop for a standard element-wise or
+ * generalized ufunc.
+ */
+typedef void (*PyUFuncGenericFunction)
+            (char **args,
+             npy_intp *dimensions,
+             npy_intp *strides,
+             void *innerloopdata);
+
+/*
+ * The most generic one-dimensional inner loop for
+ * a masked standard element-wise ufunc. "Masked" here means that it skips
+ * doing calculations on any items for which the maskptr array has a true
+ * value.
+ */
+typedef void (PyUFunc_MaskedStridedInnerLoopFunc)(
+                char **dataptrs, npy_intp *strides,
+                char *maskptr, npy_intp mask_stride,
+                npy_intp count,
+                NpyAuxData *innerloopdata);
+
+/* Forward declaration for the type resolver and loop selector typedefs */
+struct _tagPyUFuncObject;
+
+/*
+ * Given the operands for calling a ufunc, should determine the
+ * calculation input and output data types and return an inner loop function.
+ * This function should validate that the casting rule is being followed,
+ * and fail if it is not.
+ *
+ * For backwards compatibility, the regular type resolution function does not
+ * support auxiliary data with object semantics. The type resolution call
+ * which returns a masked generic function returns a standard NpyAuxData
+ * object, for which the NPY_AUXDATA_FREE and NPY_AUXDATA_CLONE macros
+ * work.
+ *
+ * ufunc:             The ufunc object.
+ * casting:           The 'casting' parameter provided to the ufunc.
+ * operands:          An array of length (ufunc->nin + ufunc->nout),
+ *                    with the output parameters possibly NULL.
+ * type_tup:          Either NULL, or the type_tup passed to the ufunc.
+ * out_dtypes:        An array which should be populated with new
+ *                    references to (ufunc->nin + ufunc->nout) new
+ *                    dtypes, one for each input and output. These
+ *                    dtypes should all be in native-endian format.
+ *
+ * Should return 0 on success, -1 on failure (with exception set),
+ * or -2 if Py_NotImplemented should be returned.
+ */
+typedef int (PyUFunc_TypeResolutionFunc)(
+                                struct _tagPyUFuncObject *ufunc,
+                                NPY_CASTING casting,
+                                PyArrayObject **operands,
+                                PyObject *type_tup,
+                                PyArray_Descr **out_dtypes);
+
+/*
+ * Given an array of DTypes as returned by the PyUFunc_TypeResolutionFunc,
+ * and an array of fixed strides (the array will contain NPY_MAX_INTP for
+ * strides which are not necessarily fixed), returns an inner loop
+ * with associated auxiliary data.
+ *
+ * For backwards compatibility, there is a variant of the inner loop
+ * selection which returns an inner loop irrespective of the strides,
+ * and with a void* static auxiliary data instead of an NpyAuxData *
+ * dynamically allocatable auxiliary data.
+ *
+ * ufunc:             The ufunc object.
+ * dtypes:            An array which has been populated with dtypes,
+ *                    in most cases by the type resolution function
+ *                    for the same ufunc.
+ * fixed_strides:     For each input/output, either the stride that
+ *                    will be used every time the function is called
+ *                    or NPY_MAX_INTP if the stride might change or
+ *                    is not known ahead of time. The loop selection
+ *                    function may use this stride to pick inner loops
+ *                    which are optimized for contiguous or 0-stride
+ *                    cases.
+ * out_innerloop:     Should be populated with the correct ufunc inner
+ *                    loop for the given type.
+ * out_innerloopdata: Should be populated with the void* data to
+ *                    be passed into the out_innerloop function.
+ * out_needs_api:     If the inner loop needs to use the Python API,
+ *                    should set the to 1, otherwise should leave
+ *                    this untouched.
+ */
+typedef int (PyUFunc_LegacyInnerLoopSelectionFunc)(
+                            struct _tagPyUFuncObject *ufunc,
+                            PyArray_Descr **dtypes,
+                            PyUFuncGenericFunction *out_innerloop,
+                            void **out_innerloopdata,
+                            int *out_needs_api);
+typedef int (PyUFunc_MaskedInnerLoopSelectionFunc)(
+                            struct _tagPyUFuncObject *ufunc,
+                            PyArray_Descr **dtypes,
+                            PyArray_Descr *mask_dtype,
+                            npy_intp *fixed_strides,
+                            npy_intp fixed_mask_stride,
+                            PyUFunc_MaskedStridedInnerLoopFunc **out_innerloop,
+                            NpyAuxData **out_innerloopdata,
+                            int *out_needs_api);
+
+typedef struct _tagPyUFuncObject {
+        PyObject_HEAD
+        /*
+         * nin: Number of inputs
+         * nout: Number of outputs
+         * nargs: Always nin + nout (Why is it stored?)
+         */
+        int nin, nout, nargs;
+
+        /* Identity for reduction, either PyUFunc_One or PyUFunc_Zero */
+        int identity;
+
+        /* Array of one-dimensional core loops */
+        PyUFuncGenericFunction *functions;
+        /* Array of funcdata that gets passed into the functions */
+        void **data;
+        /* The number of elements in 'functions' and 'data' */
+        int ntypes;
+
+        /* Used to be unused field 'check_return' */
+        int reserved1;
+
+        /* The name of the ufunc */
+        const char *name;
+
+        /* Array of type numbers, of size ('nargs' * 'ntypes') */
+        char *types;
+
+        /* Documentation string */
+        const char *doc;
+
+        void *ptr;
+        PyObject *obj;
+        PyObject *userloops;
+
+        /* generalized ufunc parameters */
+
+        /* 0 for scalar ufunc; 1 for generalized ufunc */
+        int core_enabled;
+        /* number of distinct dimension names in signature */
+        int core_num_dim_ix;
+
+        /*
+         * dimension indices of input/output argument k are stored in
+         * core_dim_ixs[core_offsets[k]..core_offsets[k]+core_num_dims[k]-1]
+         */
+
+        /* numbers of core dimensions of each argument */
+        int *core_num_dims;
+        /*
+         * dimension indices in a flatted form; indices
+         * are in the range of [0,core_num_dim_ix)
+         */
+        int *core_dim_ixs;
+        /*
+         * positions of 1st core dimensions of each
+         * argument in core_dim_ixs, equivalent to cumsum(core_num_dims)
+         */
+        int *core_offsets;
+        /* signature string for printing purpose */
+        char *core_signature;
+
+        /*
+         * A function which resolves the types and fills an array
+         * with the dtypes for the inputs and outputs.
+         */
+        PyUFunc_TypeResolutionFunc *type_resolver;
+        /*
+         * A function which returns an inner loop written for
+         * NumPy 1.6 and earlier ufuncs. This is for backwards
+         * compatibility, and may be NULL if inner_loop_selector
+         * is specified.
+         */
+        PyUFunc_LegacyInnerLoopSelectionFunc *legacy_inner_loop_selector;
+        /*
+         * This was blocked off to be the "new" inner loop selector in 1.7,
+         * but this was never implemented. (This is also why the above
+         * selector is called the "legacy" selector.)
+         */
+        void *reserved2;
+        /*
+         * A function which returns a masked inner loop for the ufunc.
+         */
+        PyUFunc_MaskedInnerLoopSelectionFunc *masked_inner_loop_selector;
+
+        /*
+         * List of flags for each operand when ufunc is called by nditer object.
+         * These flags will be used in addition to the default flags for each
+         * operand set by nditer object.
+         */
+        npy_uint32 *op_flags;
+
+        /*
+         * List of global flags used when ufunc is called by nditer object.
+         * These flags will be used in addition to the default global flags
+         * set by nditer object.
+         */
+        npy_uint32 iter_flags;
+
+        /* New in NPY_API_VERSION 0x0000000D and above */
+
+        /*
+         * for each core_num_dim_ix distinct dimension names,
+         * the possible "frozen" size (-1 if not frozen).
+         */
+        npy_intp *core_dim_sizes;
+
+        /*
+         * for each distinct core dimension, a set of UFUNC_CORE_DIM* flags
+         */
+        npy_uint32 *core_dim_flags;
+
+        /* Identity for reduction, when identity == PyUFunc_IdentityValue */
+        PyObject *identity_value;
+
+} PyUFuncObject;
+
+#include "arrayobject.h"
+/* Generalized ufunc; 0x0001 reserved for possible use as CORE_ENABLED */
+/* the core dimension's size will be determined by the operands. */
+#define UFUNC_CORE_DIM_SIZE_INFERRED 0x0002
+/* the core dimension may be absent */
+#define UFUNC_CORE_DIM_CAN_IGNORE 0x0004
+/* flags inferred during execution */
+#define UFUNC_CORE_DIM_MISSING 0x00040000
+
+#define UFUNC_ERR_IGNORE 0
+#define UFUNC_ERR_WARN   1
+#define UFUNC_ERR_RAISE  2
+#define UFUNC_ERR_CALL   3
+#define UFUNC_ERR_PRINT  4
+#define UFUNC_ERR_LOG    5
+
+        /* Python side integer mask */
+
+#define UFUNC_MASK_DIVIDEBYZERO 0x07
+#define UFUNC_MASK_OVERFLOW 0x3f
+#define UFUNC_MASK_UNDERFLOW 0x1ff
+#define UFUNC_MASK_INVALID 0xfff
+
+#define UFUNC_SHIFT_DIVIDEBYZERO 0
+#define UFUNC_SHIFT_OVERFLOW     3
+#define UFUNC_SHIFT_UNDERFLOW    6
+#define UFUNC_SHIFT_INVALID      9
+
+
+#define UFUNC_OBJ_ISOBJECT      1
+#define UFUNC_OBJ_NEEDS_API     2
+
+   /* Default user error mode */
+#define UFUNC_ERR_DEFAULT                               \
+        (UFUNC_ERR_WARN << UFUNC_SHIFT_DIVIDEBYZERO) +  \
+        (UFUNC_ERR_WARN << UFUNC_SHIFT_OVERFLOW) +      \
+        (UFUNC_ERR_WARN << UFUNC_SHIFT_INVALID)
+
+#if NPY_ALLOW_THREADS
+#define NPY_LOOP_BEGIN_THREADS do {if (!(loop->obj & UFUNC_OBJ_NEEDS_API)) _save = PyEval_SaveThread();} while (0);
+#define NPY_LOOP_END_THREADS   do {if (!(loop->obj & UFUNC_OBJ_NEEDS_API)) PyEval_RestoreThread(_save);} while (0);
+#else
+#define NPY_LOOP_BEGIN_THREADS
+#define NPY_LOOP_END_THREADS
+#endif
+
+/*
+ * UFunc has unit of 0, and the order of operations can be reordered
+ * This case allows reduction with multiple axes at once.
+ */
+#define PyUFunc_Zero 0
+/*
+ * UFunc has unit of 1, and the order of operations can be reordered
+ * This case allows reduction with multiple axes at once.
+ */
+#define PyUFunc_One 1
+/*
+ * UFunc has unit of -1, and the order of operations can be reordered
+ * This case allows reduction with multiple axes at once. Intended for
+ * bitwise_and reduction.
+ */
+#define PyUFunc_MinusOne 2
+/*
+ * UFunc has no unit, and the order of operations cannot be reordered.
+ * This case does not allow reduction with multiple axes at once.
+ */
+#define PyUFunc_None -1
+/*
+ * UFunc has no unit, and the order of operations can be reordered
+ * This case allows reduction with multiple axes at once.
+ */
+#define PyUFunc_ReorderableNone -2
+/*
+ * UFunc unit is in identity_value, and the order of operations can be reordered
+ * This case allows reduction with multiple axes at once.
+ */
+#define PyUFunc_IdentityValue -3
+
+
+#define UFUNC_REDUCE 0
+#define UFUNC_ACCUMULATE 1
+#define UFUNC_REDUCEAT 2
+#define UFUNC_OUTER 3
+
+
+typedef struct {
+        int nin;
+        int nout;
+        PyObject *callable;
+} PyUFunc_PyFuncData;
+
+/* A linked-list of function information for
+   user-defined 1-d loops.
+ */
+typedef struct _loop1d_info {
+        PyUFuncGenericFunction func;
+        void *data;
+        int *arg_types;
+        struct _loop1d_info *next;
+        int nargs;
+        PyArray_Descr **arg_dtypes;
+} PyUFunc_Loop1d;
+
+
+#include "__ufunc_api.h"
+
+#define UFUNC_PYVALS_NAME "UFUNC_PYVALS"
+
+#define UFUNC_CHECK_ERROR(arg) \
+        do {if ((((arg)->obj & UFUNC_OBJ_NEEDS_API) && PyErr_Occurred()) || \
+            ((arg)->errormask && \
+             PyUFunc_checkfperr((arg)->errormask, \
+                                (arg)->errobj, \
+                                &(arg)->first))) \
+                goto fail;} while (0)
+
+/*
+ * THESE MACROS ARE DEPRECATED.
+ * Use npy_set_floatstatus_* in the npymath library.
+ */
+#define UFUNC_FPE_DIVIDEBYZERO  NPY_FPE_DIVIDEBYZERO
+#define UFUNC_FPE_OVERFLOW      NPY_FPE_OVERFLOW
+#define UFUNC_FPE_UNDERFLOW     NPY_FPE_UNDERFLOW
+#define UFUNC_FPE_INVALID       NPY_FPE_INVALID
+
+#define UFUNC_CHECK_STATUS(ret) \
+    { \
+       ret = npy_clear_floatstatus(); \
+    }
+#define generate_divbyzero_error() npy_set_floatstatus_divbyzero()
+#define generate_overflow_error() npy_set_floatstatus_overflow()
+
+  /* Make sure it gets defined if it isn't already */
+#ifndef UFUNC_NOFPE
+/* Clear the floating point exception default of Borland C++ */
+#if defined(__BORLANDC__)
+#define UFUNC_NOFPE _control87(MCW_EM, MCW_EM);
+#else
+#define UFUNC_NOFPE
+#endif
+#endif
+
+
+#ifdef __cplusplus
+}
+#endif
+#endif /* !Py_UFUNCOBJECT_H */
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/utils.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/utils.h
new file mode 100644
index 0000000..32218b8
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/include/numpy/utils.h
@@ -0,0 +1,21 @@
+#ifndef __NUMPY_UTILS_HEADER__
+#define __NUMPY_UTILS_HEADER__
+
+#ifndef __COMP_NPY_UNUSED
+        #if defined(__GNUC__)
+                #define __COMP_NPY_UNUSED __attribute__ ((__unused__))
+        # elif defined(__ICC)
+                #define __COMP_NPY_UNUSED __attribute__ ((__unused__))
+        # elif defined(__clang__)
+                #define __COMP_NPY_UNUSED __attribute__ ((unused))
+        #else
+                #define __COMP_NPY_UNUSED
+        #endif
+#endif
+
+/* Use this to tag a variable as not used. It will remove unused variable
+ * warning on support platforms (see __COM_NPY_UNUSED) and mangle the variable
+ * to avoid accidental use */
+#define NPY_UNUSED(x) (__NPY_UNUSED_TAGGED ## x) __COMP_NPY_UNUSED
+
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/lib/libnpymath.a b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/lib/libnpymath.a
new file mode 100644
index 0000000..ec2ef5f
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diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/lib/npy-pkg-config/mlib.ini b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/lib/npy-pkg-config/mlib.ini
new file mode 100644
index 0000000..1e70ccb
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/lib/npy-pkg-config/mlib.ini
@@ -0,0 +1,12 @@
+[meta]
+Name = mlib
+Description = Math library used with this version of numpy
+Version = 1.0
+
+[default]
+Libs=
+Cflags=
+
+[msvc]
+Libs=
+Cflags=
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/lib/npy-pkg-config/npymath.ini b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/lib/npy-pkg-config/npymath.ini
new file mode 100644
index 0000000..3e465ad
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/lib/npy-pkg-config/npymath.ini
@@ -0,0 +1,20 @@
+[meta]
+Name=npymath
+Description=Portable, core math library implementing C99 standard
+Version=0.1
+
+[variables]
+pkgname=numpy.core
+prefix=${pkgdir}
+libdir=${prefix}/lib
+includedir=${prefix}/include
+
+[default]
+Libs=-L${libdir} -lnpymath
+Cflags=-I${includedir}
+Requires=mlib
+
+[msvc]
+Libs=/LIBPATH:${libdir} npymath.lib
+Cflags=/INCLUDE:${includedir}
+Requires=mlib
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/libgfortran-5.dll b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/libgfortran-5.dll
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index 0000000..59a1e82
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diff --git a/butterflow-ui/ThirdPartyCompiled/libopenblas.dll b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/libopenblas.dll
similarity index 50%
rename from butterflow-ui/ThirdPartyCompiled/libopenblas.dll
rename to butterflow-ui/ThirdPartyCompiled/lib/numpy/core/libopenblas.dll
index 817c3ec..e1cbcb6 100644
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diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/libquadmath-0.dll b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/libquadmath-0.dll
new file mode 100644
index 0000000..b3c8edd
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diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/tests/data/astype_copy.pkl b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/tests/data/astype_copy.pkl
new file mode 100644
index 0000000..7397c97
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diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/tests/data/recarray_from_file.fits b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/tests/data/recarray_from_file.fits
new file mode 100644
index 0000000..ca48ee8
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diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/tests/test_multiarray.py.orig b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/tests/test_multiarray.py.orig
new file mode 100644
index 0000000..4550e30
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/core/tests/test_multiarray.py.orig
@@ -0,0 +1,8168 @@
+from __future__ import division, absolute_import, print_function
+
+try:
+    # Accessing collections abstract classes from collections
+    # has been deprecated since Python 3.3
+    import collections.abc as collections_abc
+except ImportError:
+    import collections as collections_abc
+import tempfile
+import sys
+import shutil
+import warnings
+import operator
+import io
+import itertools
+import functools
+import ctypes
+import os
+import gc
+import weakref
+import pytest
+from contextlib import contextmanager
+
+from numpy.core.numeric import pickle
+
+if sys.version_info[0] >= 3:
+    import builtins
+else:
+    import __builtin__ as builtins
+from decimal import Decimal
+
+import numpy as np
+from numpy.compat import strchar, unicode
+import numpy.core._multiarray_tests as _multiarray_tests
+from numpy.testing import (
+    assert_, assert_raises, assert_warns, assert_equal, assert_almost_equal,
+    assert_array_equal, assert_raises_regex, assert_array_almost_equal,
+    assert_allclose, IS_PYPY, HAS_REFCOUNT, assert_array_less, runstring,
+    temppath, suppress_warnings
+    )
+from numpy.core.tests._locales import CommaDecimalPointLocale
+
+# Need to test an object that does not fully implement math interface
+from datetime import timedelta, datetime
+
+
+if sys.version_info[:2] > (3, 2):
+    # In Python 3.3 the representation of empty shape, strides and sub-offsets
+    # is an empty tuple instead of None.
+    # https://docs.python.org/dev/whatsnew/3.3.html#api-changes
+    EMPTY = ()
+else:
+    EMPTY = None
+
+
+def _aligned_zeros(shape, dtype=float, order="C", align=None):
+    """
+    Allocate a new ndarray with aligned memory.
+
+    The ndarray is guaranteed *not* aligned to twice the requested alignment.
+    Eg, if align=4, guarantees it is not aligned to 8. If align=None uses
+    dtype.alignment."""
+    dtype = np.dtype(dtype)
+    if dtype == np.dtype(object):
+        # Can't do this, fall back to standard allocation (which
+        # should always be sufficiently aligned)
+        if align is not None:
+            raise ValueError("object array alignment not supported")
+        return np.zeros(shape, dtype=dtype, order=order)
+    if align is None:
+        align = dtype.alignment
+    if not hasattr(shape, '__len__'):
+        shape = (shape,)
+    size = functools.reduce(operator.mul, shape) * dtype.itemsize
+    buf = np.empty(size + 2*align + 1, np.uint8)
+
+    ptr = buf.__array_interface__['data'][0]
+    offset = ptr % align
+    if offset != 0:
+        offset = align - offset
+    if (ptr % (2*align)) == 0:
+        offset += align
+
+    # Note: slices producing 0-size arrays do not necessarily change
+    # data pointer --- so we use and allocate size+1
+    buf = buf[offset:offset+size+1][:-1]
+    data = np.ndarray(shape, dtype, buf, order=order)
+    data.fill(0)
+    return data
+
+
+class TestFlags(object):
+    def setup(self):
+        self.a = np.arange(10)
+
+    def test_writeable(self):
+        mydict = locals()
+        self.a.flags.writeable = False
+        assert_raises(ValueError, runstring, 'self.a[0] = 3', mydict)
+        assert_raises(ValueError, runstring, 'self.a[0:1].itemset(3)', mydict)
+        self.a.flags.writeable = True
+        self.a[0] = 5
+        self.a[0] = 0
+
+    def test_writeable_from_readonly(self):
+        # gh-9440 - make sure fromstring, from buffer on readonly buffers
+        # set writeable False
+        data = b'\x00' * 100
+        vals = np.frombuffer(data, 'B')
+        assert_raises(ValueError, vals.setflags, write=True)
+        types = np.dtype( [('vals', 'u1'), ('res3', 'S4')] )
+        values = np.core.records.fromstring(data, types)
+        vals = values['vals']
+        assert_raises(ValueError, vals.setflags, write=True)
+
+    def test_writeable_from_buffer(self):
+        data = bytearray(b'\x00' * 100)
+        vals = np.frombuffer(data, 'B')
+        assert_(vals.flags.writeable)
+        vals.setflags(write=False)
+        assert_(vals.flags.writeable is False)
+        vals.setflags(write=True)
+        assert_(vals.flags.writeable)
+        types = np.dtype( [('vals', 'u1'), ('res3', 'S4')] )
+        values = np.core.records.fromstring(data, types)
+        vals = values['vals']
+        assert_(vals.flags.writeable)
+        vals.setflags(write=False)
+        assert_(vals.flags.writeable is False)
+        vals.setflags(write=True)
+        assert_(vals.flags.writeable)
+
+    @pytest.mark.skipif(sys.version_info[0] < 3, reason="Python 2 always copies")
+    def test_writeable_pickle(self):
+        import pickle
+        # Small arrays will be copied without setting base.
+        # See condition for using PyArray_SetBaseObject in
+        # array_setstate.
+        a = np.arange(1000)
+        for v in range(pickle.HIGHEST_PROTOCOL):
+            vals = pickle.loads(pickle.dumps(a, v))
+            assert_(vals.flags.writeable)
+            assert_(isinstance(vals.base, bytes))
+
+    def test_writeable_from_c_data(self):
+        # Test that the writeable flag can be changed for an array wrapping
+        # low level C-data, but not owning its data.
+        # Also see that this is deprecated to change from python.
+        from numpy.core._multiarray_tests import get_c_wrapping_array
+
+        arr_writeable = get_c_wrapping_array(True)
+        assert not arr_writeable.flags.owndata
+        assert arr_writeable.flags.writeable
+        view = arr_writeable[...]
+
+        # Toggling the writeable flag works on the view:
+        view.flags.writeable = False
+        assert not view.flags.writeable
+        view.flags.writeable = True
+        assert view.flags.writeable
+        # Flag can be unset on the arr_writeable:
+        arr_writeable.flags.writeable = False
+
+        arr_readonly = get_c_wrapping_array(False)
+        assert not arr_readonly.flags.owndata
+        assert not arr_readonly.flags.writeable
+
+        for arr in [arr_writeable, arr_readonly]:
+            view = arr[...]
+            view.flags.writeable = False  # make sure it is readonly
+            arr.flags.writeable = False
+            assert not arr.flags.writeable
+
+            with assert_raises(ValueError):
+                view.flags.writeable = True
+
+            with warnings.catch_warnings():
+                warnings.simplefilter("error", DeprecationWarning)
+                with assert_raises(DeprecationWarning):
+                    arr.flags.writeable = True
+
+            with assert_warns(DeprecationWarning):
+                arr.flags.writeable = True
+
+
+    def test_otherflags(self):
+        assert_equal(self.a.flags.carray, True)
+        assert_equal(self.a.flags['C'], True)
+        assert_equal(self.a.flags.farray, False)
+        assert_equal(self.a.flags.behaved, True)
+        assert_equal(self.a.flags.fnc, False)
+        assert_equal(self.a.flags.forc, True)
+        assert_equal(self.a.flags.owndata, True)
+        assert_equal(self.a.flags.writeable, True)
+        assert_equal(self.a.flags.aligned, True)
+        with assert_warns(DeprecationWarning):
+            assert_equal(self.a.flags.updateifcopy, False)
+        with assert_warns(DeprecationWarning):
+            assert_equal(self.a.flags['U'], False)
+            assert_equal(self.a.flags['UPDATEIFCOPY'], False)
+        assert_equal(self.a.flags.writebackifcopy, False)
+        assert_equal(self.a.flags['X'], False)
+        assert_equal(self.a.flags['WRITEBACKIFCOPY'], False)
+
+    def test_string_align(self):
+        a = np.zeros(4, dtype=np.dtype('|S4'))
+        assert_(a.flags.aligned)
+        # not power of two are accessed byte-wise and thus considered aligned
+        a = np.zeros(5, dtype=np.dtype('|S4'))
+        assert_(a.flags.aligned)
+
+    def test_void_align(self):
+        a = np.zeros(4, dtype=np.dtype([("a", "i4"), ("b", "i4")]))
+        assert_(a.flags.aligned)
+
+
+class TestHash(object):
+    # see #3793
+    def test_int(self):
+        for st, ut, s in [(np.int8, np.uint8, 8),
+                          (np.int16, np.uint16, 16),
+                          (np.int32, np.uint32, 32),
+                          (np.int64, np.uint64, 64)]:
+            for i in range(1, s):
+                assert_equal(hash(st(-2**i)), hash(-2**i),
+                             err_msg="%r: -2**%d" % (st, i))
+                assert_equal(hash(st(2**(i - 1))), hash(2**(i - 1)),
+                             err_msg="%r: 2**%d" % (st, i - 1))
+                assert_equal(hash(st(2**i - 1)), hash(2**i - 1),
+                             err_msg="%r: 2**%d - 1" % (st, i))
+
+                i = max(i - 1, 1)
+                assert_equal(hash(ut(2**(i - 1))), hash(2**(i - 1)),
+                             err_msg="%r: 2**%d" % (ut, i - 1))
+                assert_equal(hash(ut(2**i - 1)), hash(2**i - 1),
+                             err_msg="%r: 2**%d - 1" % (ut, i))
+
+
+class TestAttributes(object):
+    def setup(self):
+        self.one = np.arange(10)
+        self.two = np.arange(20).reshape(4, 5)
+        self.three = np.arange(60, dtype=np.float64).reshape(2, 5, 6)
+
+    def test_attributes(self):
+        assert_equal(self.one.shape, (10,))
+        assert_equal(self.two.shape, (4, 5))
+        assert_equal(self.three.shape, (2, 5, 6))
+        self.three.shape = (10, 3, 2)
+        assert_equal(self.three.shape, (10, 3, 2))
+        self.three.shape = (2, 5, 6)
+        assert_equal(self.one.strides, (self.one.itemsize,))
+        num = self.two.itemsize
+        assert_equal(self.two.strides, (5*num, num))
+        num = self.three.itemsize
+        assert_equal(self.three.strides, (30*num, 6*num, num))
+        assert_equal(self.one.ndim, 1)
+        assert_equal(self.two.ndim, 2)
+        assert_equal(self.three.ndim, 3)
+        num = self.two.itemsize
+        assert_equal(self.two.size, 20)
+        assert_equal(self.two.nbytes, 20*num)
+        assert_equal(self.two.itemsize, self.two.dtype.itemsize)
+        assert_equal(self.two.base, np.arange(20))
+
+    def test_dtypeattr(self):
+        assert_equal(self.one.dtype, np.dtype(np.int_))
+        assert_equal(self.three.dtype, np.dtype(np.float_))
+        assert_equal(self.one.dtype.char, 'l')
+        assert_equal(self.three.dtype.char, 'd')
+        assert_(self.three.dtype.str[0] in '<>')
+        assert_equal(self.one.dtype.str[1], 'i')
+        assert_equal(self.three.dtype.str[1], 'f')
+
+    def test_int_subclassing(self):
+        # Regression test for https://github.com/numpy/numpy/pull/3526
+
+        numpy_int = np.int_(0)
+
+        if sys.version_info[0] >= 3:
+            # On Py3k int_ should not inherit from int, because it's not
+            # fixed-width anymore
+            assert_equal(isinstance(numpy_int, int), False)
+        else:
+            # Otherwise, it should inherit from int...
+            assert_equal(isinstance(numpy_int, int), True)
+
+            # ... and fast-path checks on C-API level should also work
+            from numpy.core._multiarray_tests import test_int_subclass
+            assert_equal(test_int_subclass(numpy_int), True)
+
+    def test_stridesattr(self):
+        x = self.one
+
+        def make_array(size, offset, strides):
+            return np.ndarray(size, buffer=x, dtype=int,
+                              offset=offset*x.itemsize,
+                              strides=strides*x.itemsize)
+
+        assert_equal(make_array(4, 4, -1), np.array([4, 3, 2, 1]))
+        assert_raises(ValueError, make_array, 4, 4, -2)
+        assert_raises(ValueError, make_array, 4, 2, -1)
+        assert_raises(ValueError, make_array, 8, 3, 1)
+        assert_equal(make_array(8, 3, 0), np.array([3]*8))
+        # Check behavior reported in gh-2503:
+        assert_raises(ValueError, make_array, (2, 3), 5, np.array([-2, -3]))
+        make_array(0, 0, 10)
+
+    def test_set_stridesattr(self):
+        x = self.one
+
+        def make_array(size, offset, strides):
+            try:
+                r = np.ndarray([size], dtype=int, buffer=x,
+                               offset=offset*x.itemsize)
+            except Exception as e:
+                raise RuntimeError(e)
+            r.strides = strides = strides*x.itemsize
+            return r
+
+        assert_equal(make_array(4, 4, -1), np.array([4, 3, 2, 1]))
+        assert_equal(make_array(7, 3, 1), np.array([3, 4, 5, 6, 7, 8, 9]))
+        assert_raises(ValueError, make_array, 4, 4, -2)
+        assert_raises(ValueError, make_array, 4, 2, -1)
+        assert_raises(RuntimeError, make_array, 8, 3, 1)
+        # Check that the true extent of the array is used.
+        # Test relies on as_strided base not exposing a buffer.
+        x = np.lib.stride_tricks.as_strided(np.arange(1), (10, 10), (0, 0))
+
+        def set_strides(arr, strides):
+            arr.strides = strides
+
+        assert_raises(ValueError, set_strides, x, (10*x.itemsize, x.itemsize))
+
+        # Test for offset calculations:
+        x = np.lib.stride_tricks.as_strided(np.arange(10, dtype=np.int8)[-1],
+                                                    shape=(10,), strides=(-1,))
+        assert_raises(ValueError, set_strides, x[::-1], -1)
+        a = x[::-1]
+        a.strides = 1
+        a[::2].strides = 2
+
+    def test_fill(self):
+        for t in "?bhilqpBHILQPfdgFDGO":
+            x = np.empty((3, 2, 1), t)
+            y = np.empty((3, 2, 1), t)
+            x.fill(1)
+            y[...] = 1
+            assert_equal(x, y)
+
+    def test_fill_max_uint64(self):
+        x = np.empty((3, 2, 1), dtype=np.uint64)
+        y = np.empty((3, 2, 1), dtype=np.uint64)
+        value = 2**64 - 1
+        y[...] = value
+        x.fill(value)
+        assert_array_equal(x, y)
+
+    def test_fill_struct_array(self):
+        # Filling from a scalar
+        x = np.array([(0, 0.0), (1, 1.0)], dtype='i4,f8')
+        x.fill(x[0])
+        assert_equal(x['f1'][1], x['f1'][0])
+        # Filling from a tuple that can be converted
+        # to a scalar
+        x = np.zeros(2, dtype=[('a', 'f8'), ('b', 'i4')])
+        x.fill((3.5, -2))
+        assert_array_equal(x['a'], [3.5, 3.5])
+        assert_array_equal(x['b'], [-2, -2])
+
+
+class TestArrayConstruction(object):
+    def test_array(self):
+        d = np.ones(6)
+        r = np.array([d, d])
+        assert_equal(r, np.ones((2, 6)))
+
+        d = np.ones(6)
+        tgt = np.ones((2, 6))
+        r = np.array([d, d])
+        assert_equal(r, tgt)
+        tgt[1] = 2
+        r = np.array([d, d + 1])
+        assert_equal(r, tgt)
+
+        d = np.ones(6)
+        r = np.array([[d, d]])
+        assert_equal(r, np.ones((1, 2, 6)))
+
+        d = np.ones(6)
+        r = np.array([[d, d], [d, d]])
+        assert_equal(r, np.ones((2, 2, 6)))
+
+        d = np.ones((6, 6))
+        r = np.array([d, d])
+        assert_equal(r, np.ones((2, 6, 6)))
+
+        d = np.ones((6, ))
+        r = np.array([[d, d + 1], d + 2])
+        assert_equal(len(r), 2)
+        assert_equal(r[0], [d, d + 1])
+        assert_equal(r[1], d + 2)
+
+        tgt = np.ones((2, 3), dtype=bool)
+        tgt[0, 2] = False
+        tgt[1, 0:2] = False
+        r = np.array([[True, True, False], [False, False, True]])
+        assert_equal(r, tgt)
+        r = np.array([[True, False], [True, False], [False, True]])
+        assert_equal(r, tgt.T)
+
+    def test_array_empty(self):
+        assert_raises(TypeError, np.array)
+
+    def test_array_copy_false(self):
+        d = np.array([1, 2, 3])
+        e = np.array(d, copy=False)
+        d[1] = 3
+        assert_array_equal(e, [1, 3, 3])
+        e = np.array(d, copy=False, order='F')
+        d[1] = 4
+        assert_array_equal(e, [1, 4, 3])
+        e[2] = 7
+        assert_array_equal(d, [1, 4, 7])
+
+    def test_array_copy_true(self):
+        d = np.array([[1,2,3], [1, 2, 3]])
+        e = np.array(d, copy=True)
+        d[0, 1] = 3
+        e[0, 2] = -7
+        assert_array_equal(e, [[1, 2, -7], [1, 2, 3]])
+        assert_array_equal(d, [[1, 3, 3], [1, 2, 3]])
+        e = np.array(d, copy=True, order='F')
+        d[0, 1] = 5
+        e[0, 2] = 7
+        assert_array_equal(e, [[1, 3, 7], [1, 2, 3]])
+        assert_array_equal(d, [[1, 5, 3], [1,2,3]])
+
+    def test_array_cont(self):
+        d = np.ones(10)[::2]
+        assert_(np.ascontiguousarray(d).flags.c_contiguous)
+        assert_(np.ascontiguousarray(d).flags.f_contiguous)
+        assert_(np.asfortranarray(d).flags.c_contiguous)
+        assert_(np.asfortranarray(d).flags.f_contiguous)
+        d = np.ones((10, 10))[::2,::2]
+        assert_(np.ascontiguousarray(d).flags.c_contiguous)
+        assert_(np.asfortranarray(d).flags.f_contiguous)
+
+
+class TestAssignment(object):
+    def test_assignment_broadcasting(self):
+        a = np.arange(6).reshape(2, 3)
+
+        # Broadcasting the input to the output
+        a[...] = np.arange(3)
+        assert_equal(a, [[0, 1, 2], [0, 1, 2]])
+        a[...] = np.arange(2).reshape(2, 1)
+        assert_equal(a, [[0, 0, 0], [1, 1, 1]])
+
+        # For compatibility with <= 1.5, a limited version of broadcasting
+        # the output to the input.
+        #
+        # This behavior is inconsistent with NumPy broadcasting
+        # in general, because it only uses one of the two broadcasting
+        # rules (adding a new "1" dimension to the left of the shape),
+        # applied to the output instead of an input. In NumPy 2.0, this kind
+        # of broadcasting assignment will likely be disallowed.
+        a[...] = np.arange(6)[::-1].reshape(1, 2, 3)
+        assert_equal(a, [[5, 4, 3], [2, 1, 0]])
+        # The other type of broadcasting would require a reduction operation.
+
+        def assign(a, b):
+            a[...] = b
+
+        assert_raises(ValueError, assign, a, np.arange(12).reshape(2, 2, 3))
+
+    def test_assignment_errors(self):
+        # Address issue #2276
+        class C:
+            pass
+        a = np.zeros(1)
+
+        def assign(v):
+            a[0] = v
+
+        assert_raises((AttributeError, TypeError), assign, C())
+        assert_raises(ValueError, assign, [1])
+
+    def test_unicode_assignment(self):
+        # gh-5049
+        from numpy.core.numeric import set_string_function
+
+        @contextmanager
+        def inject_str(s):
+            """ replace ndarray.__str__ temporarily """
+            set_string_function(lambda x: s, repr=False)
+            try:
+                yield
+            finally:
+                set_string_function(None, repr=False)
+
+        a1d = np.array([u'test'])
+        a0d = np.array(u'done')
+        with inject_str(u'bad'):
+            a1d[0] = a0d  # previously this would invoke __str__
+        assert_equal(a1d[0], u'done')
+
+        # this would crash for the same reason
+        np.array([np.array(u'\xe5\xe4\xf6')])
+
+    def test_stringlike_empty_list(self):
+        # gh-8902
+        u = np.array([u'done'])
+        b = np.array([b'done'])
+
+        class bad_sequence(object):
+            def __getitem__(self): pass
+            def __len__(self): raise RuntimeError
+
+        assert_raises(ValueError, operator.setitem, u, 0, [])
+        assert_raises(ValueError, operator.setitem, b, 0, [])
+
+        assert_raises(ValueError, operator.setitem, u, 0, bad_sequence())
+        assert_raises(ValueError, operator.setitem, b, 0, bad_sequence())
+
+    def test_longdouble_assignment(self):
+        # only relevant if longdouble is larger than float
+        # we're looking for loss of precision
+
+        for dtype in (np.longdouble, np.longcomplex):
+            # gh-8902
+            tinyb = np.nextafter(np.longdouble(0), 1).astype(dtype)
+            tinya = np.nextafter(np.longdouble(0), -1).astype(dtype)
+
+            # construction
+            tiny1d = np.array([tinya])
+            assert_equal(tiny1d[0], tinya)
+
+            # scalar = scalar
+            tiny1d[0] = tinyb
+            assert_equal(tiny1d[0], tinyb)
+
+            # 0d = scalar
+            tiny1d[0, ...] = tinya
+            assert_equal(tiny1d[0], tinya)
+
+            # 0d = 0d
+            tiny1d[0, ...] = tinyb[...]
+            assert_equal(tiny1d[0], tinyb)
+
+            # scalar = 0d
+            tiny1d[0] = tinyb[...]
+            assert_equal(tiny1d[0], tinyb)
+
+            arr = np.array([np.array(tinya)])
+            assert_equal(arr[0], tinya)
+
+    def test_cast_to_string(self):
+        # cast to str should do "str(scalar)", not "str(scalar.item())"
+        # Example: In python2, str(float) is truncated, so we want to avoid
+        # str(np.float64(...).item()) as this would incorrectly truncate.
+        a = np.zeros(1, dtype='S20')
+        a[:] = np.array(['1.12345678901234567890'], dtype='f8')
+        assert_equal(a[0], b"1.1234567890123457")
+
+
+class TestDtypedescr(object):
+    def test_construction(self):
+        d1 = np.dtype('i4')
+        assert_equal(d1, np.dtype(np.int32))
+        d2 = np.dtype('f8')
+        assert_equal(d2, np.dtype(np.float64))
+
+    def test_byteorders(self):
+        assert_(np.dtype('<i4') != np.dtype('>i4'))
+        assert_(np.dtype([('a', '<i4')]) != np.dtype([('a', '>i4')]))
+
+    def test_structured_non_void(self):
+        fields = [('a', '<i2'), ('b', '<i2')]
+        dt_int = np.dtype(('i4', fields))
+        assert_equal(str(dt_int), "(numpy.int32, [('a', '<i2'), ('b', '<i2')])")
+
+        # gh-9821
+        arr_int = np.zeros(4, dt_int)
+        assert_equal(repr(arr_int),
+            "array([0, 0, 0, 0], dtype=(numpy.int32, [('a', '<i2'), ('b', '<i2')]))")
+
+
+class TestZeroRank(object):
+    def setup(self):
+        self.d = np.array(0), np.array('x', object)
+
+    def test_ellipsis_subscript(self):
+        a, b = self.d
+        assert_equal(a[...], 0)
+        assert_equal(b[...], 'x')
+        assert_(a[...].base is a)  # `a[...] is a` in numpy <1.9.
+        assert_(b[...].base is b)  # `b[...] is b` in numpy <1.9.
+
+    def test_empty_subscript(self):
+        a, b = self.d
+        assert_equal(a[()], 0)
+        assert_equal(b[()], 'x')
+        assert_(type(a[()]) is a.dtype.type)
+        assert_(type(b[()]) is str)
+
+    def test_invalid_subscript(self):
+        a, b = self.d
+        assert_raises(IndexError, lambda x: x[0], a)
+        assert_raises(IndexError, lambda x: x[0], b)
+        assert_raises(IndexError, lambda x: x[np.array([], int)], a)
+        assert_raises(IndexError, lambda x: x[np.array([], int)], b)
+
+    def test_ellipsis_subscript_assignment(self):
+        a, b = self.d
+        a[...] = 42
+        assert_equal(a, 42)
+        b[...] = ''
+        assert_equal(b.item(), '')
+
+    def test_empty_subscript_assignment(self):
+        a, b = self.d
+        a[()] = 42
+        assert_equal(a, 42)
+        b[()] = ''
+        assert_equal(b.item(), '')
+
+    def test_invalid_subscript_assignment(self):
+        a, b = self.d
+
+        def assign(x, i, v):
+            x[i] = v
+
+        assert_raises(IndexError, assign, a, 0, 42)
+        assert_raises(IndexError, assign, b, 0, '')
+        assert_raises(ValueError, assign, a, (), '')
+
+    def test_newaxis(self):
+        a, b = self.d
+        assert_equal(a[np.newaxis].shape, (1,))
+        assert_equal(a[..., np.newaxis].shape, (1,))
+        assert_equal(a[np.newaxis, ...].shape, (1,))
+        assert_equal(a[..., np.newaxis].shape, (1,))
+        assert_equal(a[np.newaxis, ..., np.newaxis].shape, (1, 1))
+        assert_equal(a[..., np.newaxis, np.newaxis].shape, (1, 1))
+        assert_equal(a[np.newaxis, np.newaxis, ...].shape, (1, 1))
+        assert_equal(a[(np.newaxis,)*10].shape, (1,)*10)
+
+    def test_invalid_newaxis(self):
+        a, b = self.d
+
+        def subscript(x, i):
+            x[i]
+
+        assert_raises(IndexError, subscript, a, (np.newaxis, 0))
+        assert_raises(IndexError, subscript, a, (np.newaxis,)*50)
+
+    def test_constructor(self):
+        x = np.ndarray(())
+        x[()] = 5
+        assert_equal(x[()], 5)
+        y = np.ndarray((), buffer=x)
+        y[()] = 6
+        assert_equal(x[()], 6)
+
+    def test_output(self):
+        x = np.array(2)
+        assert_raises(ValueError, np.add, x, [1], x)
+
+    def test_real_imag(self):
+        # contiguity checks are for gh-11245
+        x = np.array(1j)
+        xr = x.real
+        xi = x.imag
+
+        assert_equal(xr, np.array(0))
+        assert_(type(xr) is np.ndarray)
+        assert_equal(xr.flags.contiguous, True)
+        assert_equal(xr.flags.f_contiguous, True)
+
+        assert_equal(xi, np.array(1))
+        assert_(type(xi) is np.ndarray)
+        assert_equal(xi.flags.contiguous, True)
+        assert_equal(xi.flags.f_contiguous, True)
+
+
+class TestScalarIndexing(object):
+    def setup(self):
+        self.d = np.array([0, 1])[0]
+
+    def test_ellipsis_subscript(self):
+        a = self.d
+        assert_equal(a[...], 0)
+        assert_equal(a[...].shape, ())
+
+    def test_empty_subscript(self):
+        a = self.d
+        assert_equal(a[()], 0)
+        assert_equal(a[()].shape, ())
+
+    def test_invalid_subscript(self):
+        a = self.d
+        assert_raises(IndexError, lambda x: x[0], a)
+        assert_raises(IndexError, lambda x: x[np.array([], int)], a)
+
+    def test_invalid_subscript_assignment(self):
+        a = self.d
+
+        def assign(x, i, v):
+            x[i] = v
+
+        assert_raises(TypeError, assign, a, 0, 42)
+
+    def test_newaxis(self):
+        a = self.d
+        assert_equal(a[np.newaxis].shape, (1,))
+        assert_equal(a[..., np.newaxis].shape, (1,))
+        assert_equal(a[np.newaxis, ...].shape, (1,))
+        assert_equal(a[..., np.newaxis].shape, (1,))
+        assert_equal(a[np.newaxis, ..., np.newaxis].shape, (1, 1))
+        assert_equal(a[..., np.newaxis, np.newaxis].shape, (1, 1))
+        assert_equal(a[np.newaxis, np.newaxis, ...].shape, (1, 1))
+        assert_equal(a[(np.newaxis,)*10].shape, (1,)*10)
+
+    def test_invalid_newaxis(self):
+        a = self.d
+
+        def subscript(x, i):
+            x[i]
+
+        assert_raises(IndexError, subscript, a, (np.newaxis, 0))
+        assert_raises(IndexError, subscript, a, (np.newaxis,)*50)
+
+    def test_overlapping_assignment(self):
+        # With positive strides
+        a = np.arange(4)
+        a[:-1] = a[1:]
+        assert_equal(a, [1, 2, 3, 3])
+
+        a = np.arange(4)
+        a[1:] = a[:-1]
+        assert_equal(a, [0, 0, 1, 2])
+
+        # With positive and negative strides
+        a = np.arange(4)
+        a[:] = a[::-1]
+        assert_equal(a, [3, 2, 1, 0])
+
+        a = np.arange(6).reshape(2, 3)
+        a[::-1,:] = a[:, ::-1]
+        assert_equal(a, [[5, 4, 3], [2, 1, 0]])
+
+        a = np.arange(6).reshape(2, 3)
+        a[::-1, ::-1] = a[:, ::-1]
+        assert_equal(a, [[3, 4, 5], [0, 1, 2]])
+
+        # With just one element overlapping
+        a = np.arange(5)
+        a[:3] = a[2:]
+        assert_equal(a, [2, 3, 4, 3, 4])
+
+        a = np.arange(5)
+        a[2:] = a[:3]
+        assert_equal(a, [0, 1, 0, 1, 2])
+
+        a = np.arange(5)
+        a[2::-1] = a[2:]
+        assert_equal(a, [4, 3, 2, 3, 4])
+
+        a = np.arange(5)
+        a[2:] = a[2::-1]
+        assert_equal(a, [0, 1, 2, 1, 0])
+
+        a = np.arange(5)
+        a[2::-1] = a[:1:-1]
+        assert_equal(a, [2, 3, 4, 3, 4])
+
+        a = np.arange(5)
+        a[:1:-1] = a[2::-1]
+        assert_equal(a, [0, 1, 0, 1, 2])
+
+
+class TestCreation(object):
+    """
+    Test the np.array constructor
+    """
+    def test_from_attribute(self):
+        class x(object):
+            def __array__(self, dtype=None):
+                pass
+
+        assert_raises(ValueError, np.array, x())
+
+    def test_from_string(self):
+        types = np.typecodes['AllInteger'] + np.typecodes['Float']
+        nstr = ['123', '123']
+        result = np.array([123, 123], dtype=int)
+        for type in types:
+            msg = 'String conversion for %s' % type
+            assert_equal(np.array(nstr, dtype=type), result, err_msg=msg)
+
+    def test_void(self):
+        arr = np.array([], dtype='V')
+        assert_equal(arr.dtype.kind, 'V')
+
+    def test_too_big_error(self):
+        # 45341 is the smallest integer greater than sqrt(2**31 - 1).
+        # 3037000500 is the smallest integer greater than sqrt(2**63 - 1).
+        # We want to make sure that the square byte array with those dimensions
+        # is too big on 32 or 64 bit systems respectively.
+        if np.iinfo('intp').max == 2**31 - 1:
+            shape = (46341, 46341)
+        elif np.iinfo('intp').max == 2**63 - 1:
+            shape = (3037000500, 3037000500)
+        else:
+            return
+        assert_raises(ValueError, np.empty, shape, dtype=np.int8)
+        assert_raises(ValueError, np.zeros, shape, dtype=np.int8)
+        assert_raises(ValueError, np.ones, shape, dtype=np.int8)
+
+    def test_zeros(self):
+        types = np.typecodes['AllInteger'] + np.typecodes['AllFloat']
+        for dt in types:
+            d = np.zeros((13,), dtype=dt)
+            assert_equal(np.count_nonzero(d), 0)
+            # true for ieee floats
+            assert_equal(d.sum(), 0)
+            assert_(not d.any())
+
+            d = np.zeros(2, dtype='(2,4)i4')
+            assert_equal(np.count_nonzero(d), 0)
+            assert_equal(d.sum(), 0)
+            assert_(not d.any())
+
+            d = np.zeros(2, dtype='4i4')
+            assert_equal(np.count_nonzero(d), 0)
+            assert_equal(d.sum(), 0)
+            assert_(not d.any())
+
+            d = np.zeros(2, dtype='(2,4)i4, (2,4)i4')
+            assert_equal(np.count_nonzero(d), 0)
+
+    @pytest.mark.slow
+    def test_zeros_big(self):
+        # test big array as they might be allocated different by the system
+        types = np.typecodes['AllInteger'] + np.typecodes['AllFloat']
+        for dt in types:
+            d = np.zeros((30 * 1024**2,), dtype=dt)
+            assert_(not d.any())
+            # This test can fail on 32-bit systems due to insufficient
+            # contiguous memory. Deallocating the previous array increases the
+            # chance of success.
+            del(d)
+
+    def test_zeros_obj(self):
+        # test initialization from PyLong(0)
+        d = np.zeros((13,), dtype=object)
+        assert_array_equal(d, [0] * 13)
+        assert_equal(np.count_nonzero(d), 0)
+
+    def test_zeros_obj_obj(self):
+        d = np.zeros(10, dtype=[('k', object, 2)])
+        assert_array_equal(d['k'], 0)
+
+    def test_zeros_like_like_zeros(self):
+        # test zeros_like returns the same as zeros
+        for c in np.typecodes['All']:
+            if c == 'V':
+                continue
+            d = np.zeros((3,3), dtype=c)
+            assert_array_equal(np.zeros_like(d), d)
+            assert_equal(np.zeros_like(d).dtype, d.dtype)
+        # explicitly check some special cases
+        d = np.zeros((3,3), dtype='S5')
+        assert_array_equal(np.zeros_like(d), d)
+        assert_equal(np.zeros_like(d).dtype, d.dtype)
+        d = np.zeros((3,3), dtype='U5')
+        assert_array_equal(np.zeros_like(d), d)
+        assert_equal(np.zeros_like(d).dtype, d.dtype)
+
+        d = np.zeros((3,3), dtype='<i4')
+        assert_array_equal(np.zeros_like(d), d)
+        assert_equal(np.zeros_like(d).dtype, d.dtype)
+        d = np.zeros((3,3), dtype='>i4')
+        assert_array_equal(np.zeros_like(d), d)
+        assert_equal(np.zeros_like(d).dtype, d.dtype)
+
+        d = np.zeros((3,3), dtype='<M8[s]')
+        assert_array_equal(np.zeros_like(d), d)
+        assert_equal(np.zeros_like(d).dtype, d.dtype)
+        d = np.zeros((3,3), dtype='>M8[s]')
+        assert_array_equal(np.zeros_like(d), d)
+        assert_equal(np.zeros_like(d).dtype, d.dtype)
+
+        d = np.zeros((3,3), dtype='f4,f4')
+        assert_array_equal(np.zeros_like(d), d)
+        assert_equal(np.zeros_like(d).dtype, d.dtype)
+
+    def test_empty_unicode(self):
+        # don't throw decode errors on garbage memory
+        for i in range(5, 100, 5):
+            d = np.empty(i, dtype='U')
+            str(d)
+
+    def test_sequence_non_homogenous(self):
+        assert_equal(np.array([4, 2**80]).dtype, object)
+        assert_equal(np.array([4, 2**80, 4]).dtype, object)
+        assert_equal(np.array([2**80, 4]).dtype, object)
+        assert_equal(np.array([2**80] * 3).dtype, object)
+        assert_equal(np.array([[1, 1],[1j, 1j]]).dtype, complex)
+        assert_equal(np.array([[1j, 1j],[1, 1]]).dtype, complex)
+        assert_equal(np.array([[1, 1, 1],[1, 1j, 1.], [1, 1, 1]]).dtype, complex)
+
+    @pytest.mark.skipif(sys.version_info[0] >= 3, reason="Not Python 2")
+    def test_sequence_long(self):
+        assert_equal(np.array([long(4), long(4)]).dtype, np.long)
+        assert_equal(np.array([long(4), 2**80]).dtype, object)
+        assert_equal(np.array([long(4), 2**80, long(4)]).dtype, object)
+        assert_equal(np.array([2**80, long(4)]).dtype, object)
+
+    def test_non_sequence_sequence(self):
+        """Should not segfault.
+
+        Class Fail breaks the sequence protocol for new style classes, i.e.,
+        those derived from object. Class Map is a mapping type indicated by
+        raising a ValueError. At some point we may raise a warning instead
+        of an error in the Fail case.
+
+        """
+        class Fail(object):
+            def __len__(self):
+                return 1
+
+            def __getitem__(self, index):
+                raise ValueError()
+
+        class Map(object):
+            def __len__(self):
+                return 1
+
+            def __getitem__(self, index):
+                raise KeyError()
+
+        a = np.array([Map()])
+        assert_(a.shape == (1,))
+        assert_(a.dtype == np.dtype(object))
+        assert_raises(ValueError, np.array, [Fail()])
+
+    def test_no_len_object_type(self):
+        # gh-5100, want object array from iterable object without len()
+        class Point2:
+            def __init__(self):
+                pass
+
+            def __getitem__(self, ind):
+                if ind in [0, 1]:
+                    return ind
+                else:
+                    raise IndexError()
+        d = np.array([Point2(), Point2(), Point2()])
+        assert_equal(d.dtype, np.dtype(object))
+
+    def test_false_len_sequence(self):
+        # gh-7264, segfault for this example
+        class C:
+            def __getitem__(self, i):
+                raise IndexError
+            def __len__(self):
+                return 42
+
+        assert_raises(ValueError, np.array, C()) # segfault?
+
+    def test_failed_len_sequence(self):
+        # gh-7393
+        class A(object):
+            def __init__(self, data):
+                self._data = data
+            def __getitem__(self, item):
+                return type(self)(self._data[item])
+            def __len__(self):
+                return len(self._data)
+
+        # len(d) should give 3, but len(d[0]) will fail
+        d = A([1,2,3])
+        assert_equal(len(np.array(d)), 3)
+
+    def test_array_too_big(self):
+        # Test that array creation succeeds for arrays addressable by intp
+        # on the byte level and fails for too large arrays.
+        buf = np.zeros(100)
+
+        max_bytes = np.iinfo(np.intp).max
+        for dtype in ["intp", "S20", "b"]:
+            dtype = np.dtype(dtype)
+            itemsize = dtype.itemsize
+
+            np.ndarray(buffer=buf, strides=(0,),
+                       shape=(max_bytes//itemsize,), dtype=dtype)
+            assert_raises(ValueError, np.ndarray, buffer=buf, strides=(0,),
+                          shape=(max_bytes//itemsize + 1,), dtype=dtype)
+
+    def test_jagged_ndim_object(self):
+        # Lists of mismatching depths are treated as object arrays
+        a = np.array([[1], 2, 3])
+        assert_equal(a.shape, (3,))
+        assert_equal(a.dtype, object)
+
+        a = np.array([1, [2], 3])
+        assert_equal(a.shape, (3,))
+        assert_equal(a.dtype, object)
+
+        a = np.array([1, 2, [3]])
+        assert_equal(a.shape, (3,))
+        assert_equal(a.dtype, object)
+
+    def test_jagged_shape_object(self):
+        # The jagged dimension of a list is turned into an object array
+        a = np.array([[1, 1], [2], [3]])
+        assert_equal(a.shape, (3,))
+        assert_equal(a.dtype, object)
+
+        a = np.array([[1], [2, 2], [3]])
+        assert_equal(a.shape, (3,))
+        assert_equal(a.dtype, object)
+
+        a = np.array([[1], [2], [3, 3]])
+        assert_equal(a.shape, (3,))
+        assert_equal(a.dtype, object)
+
+
+class TestStructured(object):
+    def test_subarray_field_access(self):
+        a = np.zeros((3, 5), dtype=[('a', ('i4', (2, 2)))])
+        a['a'] = np.arange(60).reshape(3, 5, 2, 2)
+
+        # Since the subarray is always in C-order, a transpose
+        # does not swap the subarray:
+        assert_array_equal(a.T['a'], a['a'].transpose(1, 0, 2, 3))
+
+        # In Fortran order, the subarray gets appended
+        # like in all other cases, not prepended as a special case
+        b = a.copy(order='F')
+        assert_equal(a['a'].shape, b['a'].shape)
+        assert_equal(a.T['a'].shape, a.T.copy()['a'].shape)
+
+    def test_subarray_comparison(self):
+        # Check that comparisons between record arrays with
+        # multi-dimensional field types work properly
+        a = np.rec.fromrecords(
+            [([1, 2, 3], 'a', [[1, 2], [3, 4]]), ([3, 3, 3], 'b', [[0, 0], [0, 0]])],
+            dtype=[('a', ('f4', 3)), ('b', object), ('c', ('i4', (2, 2)))])
+        b = a.copy()
+        assert_equal(a == b, [True, True])
+        assert_equal(a != b, [False, False])
+        b[1].b = 'c'
+        assert_equal(a == b, [True, False])
+        assert_equal(a != b, [False, True])
+        for i in range(3):
+            b[0].a = a[0].a
+            b[0].a[i] = 5
+            assert_equal(a == b, [False, False])
+            assert_equal(a != b, [True, True])
+        for i in range(2):
+            for j in range(2):
+                b = a.copy()
+                b[0].c[i, j] = 10
+                assert_equal(a == b, [False, True])
+                assert_equal(a != b, [True, False])
+
+        # Check that broadcasting with a subarray works
+        a = np.array([[(0,)], [(1,)]], dtype=[('a', 'f8')])
+        b = np.array([(0,), (0,), (1,)], dtype=[('a', 'f8')])
+        assert_equal(a == b, [[True, True, False], [False, False, True]])
+        assert_equal(b == a, [[True, True, False], [False, False, True]])
+        a = np.array([[(0,)], [(1,)]], dtype=[('a', 'f8', (1,))])
+        b = np.array([(0,), (0,), (1,)], dtype=[('a', 'f8', (1,))])
+        assert_equal(a == b, [[True, True, False], [False, False, True]])
+        assert_equal(b == a, [[True, True, False], [False, False, True]])
+        a = np.array([[([0, 0],)], [([1, 1],)]], dtype=[('a', 'f8', (2,))])
+        b = np.array([([0, 0],), ([0, 1],), ([1, 1],)], dtype=[('a', 'f8', (2,))])
+        assert_equal(a == b, [[True, False, False], [False, False, True]])
+        assert_equal(b == a, [[True, False, False], [False, False, True]])
+
+        # Check that broadcasting Fortran-style arrays with a subarray work
+        a = np.array([[([0, 0],)], [([1, 1],)]], dtype=[('a', 'f8', (2,))], order='F')
+        b = np.array([([0, 0],), ([0, 1],), ([1, 1],)], dtype=[('a', 'f8', (2,))])
+        assert_equal(a == b, [[True, False, False], [False, False, True]])
+        assert_equal(b == a, [[True, False, False], [False, False, True]])
+
+        # Check that incompatible sub-array shapes don't result to broadcasting
+        x = np.zeros((1,), dtype=[('a', ('f4', (1, 2))), ('b', 'i1')])
+        y = np.zeros((1,), dtype=[('a', ('f4', (2,))), ('b', 'i1')])
+        # This comparison invokes deprecated behaviour, and will probably
+        # start raising an error eventually. What we really care about in this
+        # test is just that it doesn't return True.
+        with suppress_warnings() as sup:
+            sup.filter(FutureWarning, "elementwise == comparison failed")
+            assert_equal(x == y, False)
+
+        x = np.zeros((1,), dtype=[('a', ('f4', (2, 1))), ('b', 'i1')])
+        y = np.zeros((1,), dtype=[('a', ('f4', (2,))), ('b', 'i1')])
+        # This comparison invokes deprecated behaviour, and will probably
+        # start raising an error eventually. What we really care about in this
+        # test is just that it doesn't return True.
+        with suppress_warnings() as sup:
+            sup.filter(FutureWarning, "elementwise == comparison failed")
+            assert_equal(x == y, False)
+
+        # Check that structured arrays that are different only in
+        # byte-order work
+        a = np.array([(5, 42), (10, 1)], dtype=[('a', '>i8'), ('b', '<f8')])
+        b = np.array([(5, 43), (10, 1)], dtype=[('a', '<i8'), ('b', '>f8')])
+        assert_equal(a == b, [False, True])
+
+    def test_casting(self):
+        # Check that casting a structured array to change its byte order
+        # works
+        a = np.array([(1,)], dtype=[('a', '<i4')])
+        assert_(np.can_cast(a.dtype, [('a', '>i4')], casting='unsafe'))
+        b = a.astype([('a', '>i4')])
+        assert_equal(b, a.byteswap().newbyteorder())
+        assert_equal(a['a'][0], b['a'][0])
+
+        # Check that equality comparison works on structured arrays if
+        # they are 'equiv'-castable
+        a = np.array([(5, 42), (10, 1)], dtype=[('a', '>i4'), ('b', '<f8')])
+        b = np.array([(5, 42), (10, 1)], dtype=[('a', '<i4'), ('b', '>f8')])
+        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
+        assert_equal(a == b, [True, True])
+
+        # Check that 'equiv' casting can change byte order
+        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
+        c = a.astype(b.dtype, casting='equiv')
+        assert_equal(a == c, [True, True])
+
+        # Check that 'safe' casting can change byte order and up-cast
+        # fields
+        t = [('a', '<i8'), ('b', '>f8')]
+        assert_(np.can_cast(a.dtype, t, casting='safe'))
+        c = a.astype(t, casting='safe')
+        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
+                     [True, True])
+
+        # Check that 'same_kind' casting can change byte order and
+        # change field widths within a "kind"
+        t = [('a', '<i4'), ('b', '>f4')]
+        assert_(np.can_cast(a.dtype, t, casting='same_kind'))
+        c = a.astype(t, casting='same_kind')
+        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
+                     [True, True])
+
+        # Check that casting fails if the casting rule should fail on
+        # any of the fields
+        t = [('a', '>i8'), ('b', '<f4')]
+        assert_(not np.can_cast(a.dtype, t, casting='safe'))
+        assert_raises(TypeError, a.astype, t, casting='safe')
+        t = [('a', '>i2'), ('b', '<f8')]
+        assert_(not np.can_cast(a.dtype, t, casting='equiv'))
+        assert_raises(TypeError, a.astype, t, casting='equiv')
+        t = [('a', '>i8'), ('b', '<i2')]
+        assert_(not np.can_cast(a.dtype, t, casting='same_kind'))
+        assert_raises(TypeError, a.astype, t, casting='same_kind')
+        assert_(not np.can_cast(a.dtype, b.dtype, casting='no'))
+        assert_raises(TypeError, a.astype, b.dtype, casting='no')
+
+        # Check that non-'unsafe' casting can't change the set of field names
+        for casting in ['no', 'safe', 'equiv', 'same_kind']:
+            t = [('a', '>i4')]
+            assert_(not np.can_cast(a.dtype, t, casting=casting))
+            t = [('a', '>i4'), ('b', '<f8'), ('c', 'i4')]
+            assert_(not np.can_cast(a.dtype, t, casting=casting))
+
+    def test_objview(self):
+        # https://github.com/numpy/numpy/issues/3286
+        a = np.array([], dtype=[('a', 'f'), ('b', 'f'), ('c', 'O')])
+        a[['a', 'b']]  # TypeError?
+
+        # https://github.com/numpy/numpy/issues/3253
+        dat2 = np.zeros(3, [('A', 'i'), ('B', '|O')])
+        dat2[['B', 'A']]  # TypeError?
+
+    def test_setfield(self):
+        # https://github.com/numpy/numpy/issues/3126
+        struct_dt = np.dtype([('elem', 'i4', 5),])
+        dt = np.dtype([('field', 'i4', 10),('struct', struct_dt)])
+        x = np.zeros(1, dt)
+        x[0]['field'] = np.ones(10, dtype='i4')
+        x[0]['struct'] = np.ones(1, dtype=struct_dt)
+        assert_equal(x[0]['field'], np.ones(10, dtype='i4'))
+
+    def test_setfield_object(self):
+        # make sure object field assignment with ndarray value
+        # on void scalar mimics setitem behavior
+        b = np.zeros(1, dtype=[('x', 'O')])
+        # next line should work identically to b['x'][0] = np.arange(3)
+        b[0]['x'] = np.arange(3)
+        assert_equal(b[0]['x'], np.arange(3))
+
+        # check that broadcasting check still works
+        c = np.zeros(1, dtype=[('x', 'O', 5)])
+
+        def testassign():
+            c[0]['x'] = np.arange(3)
+
+        assert_raises(ValueError, testassign)
+
+    def test_zero_width_string(self):
+        # Test for PR #6430 / issues #473, #4955, #2585
+
+        dt = np.dtype([('I', int), ('S', 'S0')])
+
+        x = np.zeros(4, dtype=dt)
+
+        assert_equal(x['S'], [b'', b'', b'', b''])
+        assert_equal(x['S'].itemsize, 0)
+
+        x['S'] = ['a', 'b', 'c', 'd']
+        assert_equal(x['S'], [b'', b'', b'', b''])
+        assert_equal(x['I'], [0, 0, 0, 0])
+
+        # Variation on test case from #4955
+        x['S'][x['I'] == 0] = 'hello'
+        assert_equal(x['S'], [b'', b'', b'', b''])
+        assert_equal(x['I'], [0, 0, 0, 0])
+
+        # Variation on test case from #2585
+        x['S'] = 'A'
+        assert_equal(x['S'], [b'', b'', b'', b''])
+        assert_equal(x['I'], [0, 0, 0, 0])
+
+        # Allow zero-width dtypes in ndarray constructor
+        y = np.ndarray(4, dtype=x['S'].dtype)
+        assert_equal(y.itemsize, 0)
+        assert_equal(x['S'], y)
+
+        # More tests for indexing an array with zero-width fields
+        assert_equal(np.zeros(4, dtype=[('a', 'S0,S0'),
+                                        ('b', 'u1')])['a'].itemsize, 0)
+        assert_equal(np.empty(3, dtype='S0,S0').itemsize, 0)
+        assert_equal(np.zeros(4, dtype='S0,u1')['f0'].itemsize, 0)
+
+        xx = x['S'].reshape((2, 2))
+        assert_equal(xx.itemsize, 0)
+        assert_equal(xx, [[b'', b''], [b'', b'']])
+        # check for no uninitialized memory due to viewing S0 array
+        assert_equal(xx[:].dtype, xx.dtype)
+        assert_array_equal(eval(repr(xx), dict(array=np.array)), xx)
+
+        b = io.BytesIO()
+        np.save(b, xx)
+
+        b.seek(0)
+        yy = np.load(b)
+        assert_equal(yy.itemsize, 0)
+        assert_equal(xx, yy)
+
+        with temppath(suffix='.npy') as tmp:
+            np.save(tmp, xx)
+            yy = np.load(tmp)
+            assert_equal(yy.itemsize, 0)
+            assert_equal(xx, yy)
+
+    def test_base_attr(self):
+        a = np.zeros(3, dtype='i4,f4')
+        b = a[0]
+        assert_(b.base is a)
+
+    def test_assignment(self):
+        def testassign(arr, v):
+            c = arr.copy()
+            c[0] = v  # assign using setitem
+            c[1:] = v # assign using "dtype_transfer" code paths
+            return c
+
+        dt = np.dtype([('foo', 'i8'), ('bar', 'i8')])
+        arr = np.ones(2, dt)
+        v1 = np.array([(2,3)], dtype=[('foo', 'i8'), ('bar', 'i8')])
+        v2 = np.array([(2,3)], dtype=[('bar', 'i8'), ('foo', 'i8')])
+        v3 = np.array([(2,3)], dtype=[('bar', 'i8'), ('baz', 'i8')])
+        v4 = np.array([(2,)],  dtype=[('bar', 'i8')])
+        v5 = np.array([(2,3)], dtype=[('foo', 'f8'), ('bar', 'f8')])
+        w = arr.view({'names': ['bar'], 'formats': ['i8'], 'offsets': [8]})
+
+        ans = np.array([(2,3),(2,3)], dtype=dt)
+        assert_equal(testassign(arr, v1), ans)
+        assert_equal(testassign(arr, v2), ans)
+        assert_equal(testassign(arr, v3), ans)
+        assert_raises(ValueError, lambda: testassign(arr, v4))
+        assert_equal(testassign(arr, v5), ans)
+        w[:] = 4
+        assert_equal(arr, np.array([(1,4),(1,4)], dtype=dt))
+
+        # test field-reordering, assignment by position, and self-assignment
+        a = np.array([(1,2,3)],
+                     dtype=[('foo', 'i8'), ('bar', 'i8'), ('baz', 'f4')])
+        a[['foo', 'bar']] = a[['bar', 'foo']]
+        assert_equal(a[0].item(), (2,1,3))
+
+        # test that this works even for 'simple_unaligned' structs
+        # (ie, that PyArray_EquivTypes cares about field order too)
+        a = np.array([(1,2)], dtype=[('a', 'i4'), ('b', 'i4')])
+        a[['a', 'b']] = a[['b', 'a']]
+        assert_equal(a[0].item(), (2,1))
+
+    def test_structuredscalar_indexing(self):
+        # test gh-7262
+        x = np.empty(shape=1, dtype="(2)3S,(2)3U")
+        assert_equal(x[["f0","f1"]][0], x[0][["f0","f1"]])
+        assert_equal(x[0], x[0][()])
+
+    def test_multiindex_titles(self):
+        a = np.zeros(4, dtype=[(('a', 'b'), 'i'), ('c', 'i'), ('d', 'i')])
+        assert_raises(KeyError, lambda : a[['a','c']])
+        assert_raises(KeyError, lambda : a[['a','a']])
+        assert_raises(ValueError, lambda : a[['b','b']])  # field exists, but repeated
+        a[['b','c']]  # no exception
+
+
+class TestBool(object):
+    def test_test_interning(self):
+        a0 = np.bool_(0)
+        b0 = np.bool_(False)
+        assert_(a0 is b0)
+        a1 = np.bool_(1)
+        b1 = np.bool_(True)
+        assert_(a1 is b1)
+        assert_(np.array([True])[0] is a1)
+        assert_(np.array(True)[()] is a1)
+
+    def test_sum(self):
+        d = np.ones(101, dtype=bool)
+        assert_equal(d.sum(), d.size)
+        assert_equal(d[::2].sum(), d[::2].size)
+        assert_equal(d[::-2].sum(), d[::-2].size)
+
+        d = np.frombuffer(b'\xff\xff' * 100, dtype=bool)
+        assert_equal(d.sum(), d.size)
+        assert_equal(d[::2].sum(), d[::2].size)
+        assert_equal(d[::-2].sum(), d[::-2].size)
+
+    def check_count_nonzero(self, power, length):
+        powers = [2 ** i for i in range(length)]
+        for i in range(2**power):
+            l = [(i & x) != 0 for x in powers]
+            a = np.array(l, dtype=bool)
+            c = builtins.sum(l)
+            assert_equal(np.count_nonzero(a), c)
+            av = a.view(np.uint8)
+            av *= 3
+            assert_equal(np.count_nonzero(a), c)
+            av *= 4
+            assert_equal(np.count_nonzero(a), c)
+            av[av != 0] = 0xFF
+            assert_equal(np.count_nonzero(a), c)
+
+    def test_count_nonzero(self):
+        # check all 12 bit combinations in a length 17 array
+        # covers most cases of the 16 byte unrolled code
+        self.check_count_nonzero(12, 17)
+
+    @pytest.mark.slow
+    def test_count_nonzero_all(self):
+        # check all combinations in a length 17 array
+        # covers all cases of the 16 byte unrolled code
+        self.check_count_nonzero(17, 17)
+
+    def test_count_nonzero_unaligned(self):
+        # prevent mistakes as e.g. gh-4060
+        for o in range(7):
+            a = np.zeros((18,), dtype=bool)[o+1:]
+            a[:o] = True
+            assert_equal(np.count_nonzero(a), builtins.sum(a.tolist()))
+            a = np.ones((18,), dtype=bool)[o+1:]
+            a[:o] = False
+            assert_equal(np.count_nonzero(a), builtins.sum(a.tolist()))
+
+    def _test_cast_from_flexible(self, dtype):
+        # empty string -> false
+        for n in range(3):
+            v = np.array(b'', (dtype, n))
+            assert_equal(bool(v), False)
+            assert_equal(bool(v[()]), False)
+            assert_equal(v.astype(bool), False)
+            assert_(isinstance(v.astype(bool), np.ndarray))
+            assert_(v[()].astype(bool) is np.False_)
+
+        # anything else -> true
+        for n in range(1, 4):
+            for val in [b'a', b'0', b' ']:
+                v = np.array(val, (dtype, n))
+                assert_equal(bool(v), True)
+                assert_equal(bool(v[()]), True)
+                assert_equal(v.astype(bool), True)
+                assert_(isinstance(v.astype(bool), np.ndarray))
+                assert_(v[()].astype(bool) is np.True_)
+
+    def test_cast_from_void(self):
+        self._test_cast_from_flexible(np.void)
+
+    @pytest.mark.xfail(reason="See gh-9847")
+    def test_cast_from_unicode(self):
+        self._test_cast_from_flexible(np.unicode_)
+
+    @pytest.mark.xfail(reason="See gh-9847")
+    def test_cast_from_bytes(self):
+        self._test_cast_from_flexible(np.bytes_)
+
+
+class TestZeroSizeFlexible(object):
+    @staticmethod
+    def _zeros(shape, dtype=str):
+        dtype = np.dtype(dtype)
+        if dtype == np.void:
+            return np.zeros(shape, dtype=(dtype, 0))
+
+        # not constructable directly
+        dtype = np.dtype([('x', dtype, 0)])
+        return np.zeros(shape, dtype=dtype)['x']
+
+    def test_create(self):
+        zs = self._zeros(10, bytes)
+        assert_equal(zs.itemsize, 0)
+        zs = self._zeros(10, np.void)
+        assert_equal(zs.itemsize, 0)
+        zs = self._zeros(10, unicode)
+        assert_equal(zs.itemsize, 0)
+
+    def _test_sort_partition(self, name, kinds, **kwargs):
+        # Previously, these would all hang
+        for dt in [bytes, np.void, unicode]:
+            zs = self._zeros(10, dt)
+            sort_method = getattr(zs, name)
+            sort_func = getattr(np, name)
+            for kind in kinds:
+                sort_method(kind=kind, **kwargs)
+                sort_func(zs, kind=kind, **kwargs)
+
+    def test_sort(self):
+        self._test_sort_partition('sort', kinds='qhm')
+
+    def test_argsort(self):
+        self._test_sort_partition('argsort', kinds='qhm')
+
+    def test_partition(self):
+        self._test_sort_partition('partition', kinds=['introselect'], kth=2)
+
+    def test_argpartition(self):
+        self._test_sort_partition('argpartition', kinds=['introselect'], kth=2)
+
+    def test_resize(self):
+        # previously an error
+        for dt in [bytes, np.void, unicode]:
+            zs = self._zeros(10, dt)
+            zs.resize(25)
+            zs.resize((10, 10))
+
+    def test_view(self):
+        for dt in [bytes, np.void, unicode]:
+            zs = self._zeros(10, dt)
+
+            # viewing as itself should be allowed
+            assert_equal(zs.view(dt).dtype, np.dtype(dt))
+
+            # viewing as any non-empty type gives an empty result
+            assert_equal(zs.view((dt, 1)).shape, (0,))
+
+    def test_pickle(self):
+        for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
+            for dt in [bytes, np.void, unicode]:
+                zs = self._zeros(10, dt)
+                p = pickle.dumps(zs, protocol=proto)
+                zs2 = pickle.loads(p)
+
+                assert_equal(zs.dtype, zs2.dtype)
+
+    @pytest.mark.skipif(pickle.HIGHEST_PROTOCOL < 5,
+                        reason="requires pickle protocol 5")
+    def test_pickle_with_buffercallback(self):
+        array = np.arange(10)
+        buffers = []
+        bytes_string = pickle.dumps(array, buffer_callback=buffers.append,
+                                    protocol=5)
+        array_from_buffer = pickle.loads(bytes_string, buffers=buffers)
+        # when using pickle protocol 5 with buffer callbacks,
+        # array_from_buffer is reconstructed from a buffer holding a view
+        # to the initial array's data, so modifying an element in array
+        # should modify it in array_from_buffer too.
+        array[0] = -1
+        assert array_from_buffer[0] == -1, array_from_buffer[0]
+
+
+class TestMethods(object):
+    def test_compress(self):
+        tgt = [[5, 6, 7, 8, 9]]
+        arr = np.arange(10).reshape(2, 5)
+        out = arr.compress([0, 1], axis=0)
+        assert_equal(out, tgt)
+
+        tgt = [[1, 3], [6, 8]]
+        out = arr.compress([0, 1, 0, 1, 0], axis=1)
+        assert_equal(out, tgt)
+
+        tgt = [[1], [6]]
+        arr = np.arange(10).reshape(2, 5)
+        out = arr.compress([0, 1], axis=1)
+        assert_equal(out, tgt)
+
+        arr = np.arange(10).reshape(2, 5)
+        out = arr.compress([0, 1])
+        assert_equal(out, 1)
+
+    def test_choose(self):
+        x = 2*np.ones((3,), dtype=int)
+        y = 3*np.ones((3,), dtype=int)
+        x2 = 2*np.ones((2, 3), dtype=int)
+        y2 = 3*np.ones((2, 3), dtype=int)
+        ind = np.array([0, 0, 1])
+
+        A = ind.choose((x, y))
+        assert_equal(A, [2, 2, 3])
+
+        A = ind.choose((x2, y2))
+        assert_equal(A, [[2, 2, 3], [2, 2, 3]])
+
+        A = ind.choose((x, y2))
+        assert_equal(A, [[2, 2, 3], [2, 2, 3]])
+
+        oned = np.ones(1)
+        # gh-12031, caused SEGFAULT
+        assert_raises(TypeError, oned.choose,np.void(0), [oned])
+
+    def test_prod(self):
+        ba = [1, 2, 10, 11, 6, 5, 4]
+        ba2 = [[1, 2, 3, 4], [5, 6, 7, 9], [10, 3, 4, 5]]
+
+        for ctype in [np.int16, np.uint16, np.int32, np.uint32,
+                      np.float32, np.float64, np.complex64, np.complex128]:
+            a = np.array(ba, ctype)
+            a2 = np.array(ba2, ctype)
+            if ctype in ['1', 'b']:
+                assert_raises(ArithmeticError, a.prod)
+                assert_raises(ArithmeticError, a2.prod, axis=1)
+            else:
+                assert_equal(a.prod(axis=0), 26400)
+                assert_array_equal(a2.prod(axis=0),
+                                   np.array([50, 36, 84, 180], ctype))
+                assert_array_equal(a2.prod(axis=-1),
+                                   np.array([24, 1890, 600], ctype))
+
+    def test_repeat(self):
+        m = np.array([1, 2, 3, 4, 5, 6])
+        m_rect = m.reshape((2, 3))
+
+        A = m.repeat([1, 3, 2, 1, 1, 2])
+        assert_equal(A, [1, 2, 2, 2, 3,
+                         3, 4, 5, 6, 6])
+
+        A = m.repeat(2)
+        assert_equal(A, [1, 1, 2, 2, 3, 3,
+                         4, 4, 5, 5, 6, 6])
+
+        A = m_rect.repeat([2, 1], axis=0)
+        assert_equal(A, [[1, 2, 3],
+                         [1, 2, 3],
+                         [4, 5, 6]])
+
+        A = m_rect.repeat([1, 3, 2], axis=1)
+        assert_equal(A, [[1, 2, 2, 2, 3, 3],
+                         [4, 5, 5, 5, 6, 6]])
+
+        A = m_rect.repeat(2, axis=0)
+        assert_equal(A, [[1, 2, 3],
+                         [1, 2, 3],
+                         [4, 5, 6],
+                         [4, 5, 6]])
+
+        A = m_rect.repeat(2, axis=1)
+        assert_equal(A, [[1, 1, 2, 2, 3, 3],
+                         [4, 4, 5, 5, 6, 6]])
+
+    def test_reshape(self):
+        arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]])
+
+        tgt = [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]]
+        assert_equal(arr.reshape(2, 6), tgt)
+
+        tgt = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
+        assert_equal(arr.reshape(3, 4), tgt)
+
+        tgt = [[1, 10, 8, 6], [4, 2, 11, 9], [7, 5, 3, 12]]
+        assert_equal(arr.reshape((3, 4), order='F'), tgt)
+
+        tgt = [[1, 4, 7, 10], [2, 5, 8, 11], [3, 6, 9, 12]]
+        assert_equal(arr.T.reshape((3, 4), order='C'), tgt)
+
+    def test_round(self):
+        def check_round(arr, expected, *round_args):
+            assert_equal(arr.round(*round_args), expected)
+            # With output array
+            out = np.zeros_like(arr)
+            res = arr.round(*round_args, out=out)
+            assert_equal(out, expected)
+            assert_equal(out, res)
+
+        check_round(np.array([1.2, 1.5]), [1, 2])
+        check_round(np.array(1.5), 2)
+        check_round(np.array([12.2, 15.5]), [10, 20], -1)
+        check_round(np.array([12.15, 15.51]), [12.2, 15.5], 1)
+        # Complex rounding
+        check_round(np.array([4.5 + 1.5j]), [4 + 2j])
+        check_round(np.array([12.5 + 15.5j]), [10 + 20j], -1)
+
+    def test_squeeze(self):
+        a = np.array([[[1], [2], [3]]])
+        assert_equal(a.squeeze(), [1, 2, 3])
+        assert_equal(a.squeeze(axis=(0,)), [[1], [2], [3]])
+        assert_raises(ValueError, a.squeeze, axis=(1,))
+        assert_equal(a.squeeze(axis=(2,)), [[1, 2, 3]])
+
+    def test_transpose(self):
+        a = np.array([[1, 2], [3, 4]])
+        assert_equal(a.transpose(), [[1, 3], [2, 4]])
+        assert_raises(ValueError, lambda: a.transpose(0))
+        assert_raises(ValueError, lambda: a.transpose(0, 0))
+        assert_raises(ValueError, lambda: a.transpose(0, 1, 2))
+
+    def test_sort(self):
+        # test ordering for floats and complex containing nans. It is only
+        # necessary to check the less-than comparison, so sorts that
+        # only follow the insertion sort path are sufficient. We only
+        # test doubles and complex doubles as the logic is the same.
+
+        # check doubles
+        msg = "Test real sort order with nans"
+        a = np.array([np.nan, 1, 0])
+        b = np.sort(a)
+        assert_equal(b, a[::-1], msg)
+        # check complex
+        msg = "Test complex sort order with nans"
+        a = np.zeros(9, dtype=np.complex128)
+        a.real += [np.nan, np.nan, np.nan, 1, 0, 1, 1, 0, 0]
+        a.imag += [np.nan, 1, 0, np.nan, np.nan, 1, 0, 1, 0]
+        b = np.sort(a)
+        assert_equal(b, a[::-1], msg)
+
+        # all c scalar sorts use the same code with different types
+        # so it suffices to run a quick check with one type. The number
+        # of sorted items must be greater than ~50 to check the actual
+        # algorithm because quick and merge sort fall over to insertion
+        # sort for small arrays.
+        a = np.arange(101)
+        b = a[::-1].copy()
+        for kind in ['q', 'm', 'h']:
+            msg = "scalar sort, kind=%s" % kind
+            c = a.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+            c = b.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+
+        # test complex sorts. These use the same code as the scalars
+        # but the compare function differs.
+        ai = a*1j + 1
+        bi = b*1j + 1
+        for kind in ['q', 'm', 'h']:
+            msg = "complex sort, real part == 1, kind=%s" % kind
+            c = ai.copy()
+            c.sort(kind=kind)
+            assert_equal(c, ai, msg)
+            c = bi.copy()
+            c.sort(kind=kind)
+            assert_equal(c, ai, msg)
+        ai = a + 1j
+        bi = b + 1j
+        for kind in ['q', 'm', 'h']:
+            msg = "complex sort, imag part == 1, kind=%s" % kind
+            c = ai.copy()
+            c.sort(kind=kind)
+            assert_equal(c, ai, msg)
+            c = bi.copy()
+            c.sort(kind=kind)
+            assert_equal(c, ai, msg)
+
+        # test sorting of complex arrays requiring byte-swapping, gh-5441
+        for endianness in '<>':
+            for dt in np.typecodes['Complex']:
+                arr = np.array([1+3.j, 2+2.j, 3+1.j], dtype=endianness + dt)
+                c = arr.copy()
+                c.sort()
+                msg = 'byte-swapped complex sort, dtype={0}'.format(dt)
+                assert_equal(c, arr, msg)
+
+        # test string sorts.
+        s = 'aaaaaaaa'
+        a = np.array([s + chr(i) for i in range(101)])
+        b = a[::-1].copy()
+        for kind in ['q', 'm', 'h']:
+            msg = "string sort, kind=%s" % kind
+            c = a.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+            c = b.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+
+        # test unicode sorts.
+        s = 'aaaaaaaa'
+        a = np.array([s + chr(i) for i in range(101)], dtype=np.unicode)
+        b = a[::-1].copy()
+        for kind in ['q', 'm', 'h']:
+            msg = "unicode sort, kind=%s" % kind
+            c = a.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+            c = b.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+
+        # test object array sorts.
+        a = np.empty((101,), dtype=object)
+        a[:] = list(range(101))
+        b = a[::-1]
+        for kind in ['q', 'h', 'm']:
+            msg = "object sort, kind=%s" % kind
+            c = a.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+            c = b.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+
+        # test record array sorts.
+        dt = np.dtype([('f', float), ('i', int)])
+        a = np.array([(i, i) for i in range(101)], dtype=dt)
+        b = a[::-1]
+        for kind in ['q', 'h', 'm']:
+            msg = "object sort, kind=%s" % kind
+            c = a.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+            c = b.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+
+        # test datetime64 sorts.
+        a = np.arange(0, 101, dtype='datetime64[D]')
+        b = a[::-1]
+        for kind in ['q', 'h', 'm']:
+            msg = "datetime64 sort, kind=%s" % kind
+            c = a.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+            c = b.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+
+        # test timedelta64 sorts.
+        a = np.arange(0, 101, dtype='timedelta64[D]')
+        b = a[::-1]
+        for kind in ['q', 'h', 'm']:
+            msg = "timedelta64 sort, kind=%s" % kind
+            c = a.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+            c = b.copy()
+            c.sort(kind=kind)
+            assert_equal(c, a, msg)
+
+        # check axis handling. This should be the same for all type
+        # specific sorts, so we only check it for one type and one kind
+        a = np.array([[3, 2], [1, 0]])
+        b = np.array([[1, 0], [3, 2]])
+        c = np.array([[2, 3], [0, 1]])
+        d = a.copy()
+        d.sort(axis=0)
+        assert_equal(d, b, "test sort with axis=0")
+        d = a.copy()
+        d.sort(axis=1)
+        assert_equal(d, c, "test sort with axis=1")
+        d = a.copy()
+        d.sort()
+        assert_equal(d, c, "test sort with default axis")
+
+        # check axis handling for multidimensional empty arrays
+        a = np.array([])
+        a.shape = (3, 2, 1, 0)
+        for axis in range(-a.ndim, a.ndim):
+            msg = 'test empty array sort with axis={0}'.format(axis)
+            assert_equal(np.sort(a, axis=axis), a, msg)
+        msg = 'test empty array sort with axis=None'
+        assert_equal(np.sort(a, axis=None), a.ravel(), msg)
+
+        # test generic class with bogus ordering,
+        # should not segfault.
+        class Boom(object):
+            def __lt__(self, other):
+                return True
+
+        a = np.array([Boom()]*100, dtype=object)
+        for kind in ['q', 'm', 'h']:
+            msg = "bogus comparison object sort, kind=%s" % kind
+            c.sort(kind=kind)
+
+    def test_void_sort(self):
+        # gh-8210 - previously segfaulted
+        for i in range(4):
+            rand = np.random.randint(256, size=4000, dtype=np.uint8)
+            arr = rand.view('V4')
+            arr[::-1].sort()
+
+        dt = np.dtype([('val', 'i4', (1,))])
+        for i in range(4):
+            rand = np.random.randint(256, size=4000, dtype=np.uint8)
+            arr = rand.view(dt)
+            arr[::-1].sort()
+
+    def test_sort_raises(self):
+        #gh-9404
+        arr = np.array([0, datetime.now(), 1], dtype=object)
+        for kind in ['q', 'm', 'h']:
+            assert_raises(TypeError, arr.sort, kind=kind)
+        #gh-3879
+        class Raiser(object):
+            def raises_anything(*args, **kwargs):
+                raise TypeError("SOMETHING ERRORED")
+            __eq__ = __ne__ = __lt__ = __gt__ = __ge__ = __le__ = raises_anything
+        arr = np.array([[Raiser(), n] for n in range(10)]).reshape(-1)
+        np.random.shuffle(arr)
+        for kind in ['q', 'm', 'h']:
+            assert_raises(TypeError, arr.sort, kind=kind)
+
+    def test_sort_degraded(self):
+        # test degraded dataset would take minutes to run with normal qsort
+        d = np.arange(1000000)
+        do = d.copy()
+        x = d
+        # create a median of 3 killer where each median is the sorted second
+        # last element of the quicksort partition
+        while x.size > 3:
+            mid = x.size // 2
+            x[mid], x[-2] = x[-2], x[mid]
+            x = x[:-2]
+
+        assert_equal(np.sort(d), do)
+        assert_equal(d[np.argsort(d)], do)
+
+    def test_copy(self):
+        def assert_fortran(arr):
+            assert_(arr.flags.fortran)
+            assert_(arr.flags.f_contiguous)
+            assert_(not arr.flags.c_contiguous)
+
+        def assert_c(arr):
+            assert_(not arr.flags.fortran)
+            assert_(not arr.flags.f_contiguous)
+            assert_(arr.flags.c_contiguous)
+
+        a = np.empty((2, 2), order='F')
+        # Test copying a Fortran array
+        assert_c(a.copy())
+        assert_c(a.copy('C'))
+        assert_fortran(a.copy('F'))
+        assert_fortran(a.copy('A'))
+
+        # Now test starting with a C array.
+        a = np.empty((2, 2), order='C')
+        assert_c(a.copy())
+        assert_c(a.copy('C'))
+        assert_fortran(a.copy('F'))
+        assert_c(a.copy('A'))
+
+    def test_sort_order(self):
+        # Test sorting an array with fields
+        x1 = np.array([21, 32, 14])
+        x2 = np.array(['my', 'first', 'name'])
+        x3 = np.array([3.1, 4.5, 6.2])
+        r = np.rec.fromarrays([x1, x2, x3], names='id,word,number')
+
+        r.sort(order=['id'])
+        assert_equal(r.id, np.array([14, 21, 32]))
+        assert_equal(r.word, np.array(['name', 'my', 'first']))
+        assert_equal(r.number, np.array([6.2, 3.1, 4.5]))
+
+        r.sort(order=['word'])
+        assert_equal(r.id, np.array([32, 21, 14]))
+        assert_equal(r.word, np.array(['first', 'my', 'name']))
+        assert_equal(r.number, np.array([4.5, 3.1, 6.2]))
+
+        r.sort(order=['number'])
+        assert_equal(r.id, np.array([21, 32, 14]))
+        assert_equal(r.word, np.array(['my', 'first', 'name']))
+        assert_equal(r.number, np.array([3.1, 4.5, 6.2]))
+
+        assert_raises_regex(ValueError, 'duplicate',
+            lambda: r.sort(order=['id', 'id']))
+
+        if sys.byteorder == 'little':
+            strtype = '>i2'
+        else:
+            strtype = '<i2'
+        mydtype = [('name', strchar + '5'), ('col2', strtype)]
+        r = np.array([('a', 1), ('b', 255), ('c', 3), ('d', 258)],
+                     dtype=mydtype)
+        r.sort(order='col2')
+        assert_equal(r['col2'], [1, 3, 255, 258])
+        assert_equal(r, np.array([('a', 1), ('c', 3), ('b', 255), ('d', 258)],
+                                 dtype=mydtype))
+
+    def test_argsort(self):
+        # all c scalar argsorts use the same code with different types
+        # so it suffices to run a quick check with one type. The number
+        # of sorted items must be greater than ~50 to check the actual
+        # algorithm because quick and merge sort fall over to insertion
+        # sort for small arrays.
+        a = np.arange(101)
+        b = a[::-1].copy()
+        for kind in ['q', 'm', 'h']:
+            msg = "scalar argsort, kind=%s" % kind
+            assert_equal(a.copy().argsort(kind=kind), a, msg)
+            assert_equal(b.copy().argsort(kind=kind), b, msg)
+
+        # test complex argsorts. These use the same code as the scalars
+        # but the compare function differs.
+        ai = a*1j + 1
+        bi = b*1j + 1
+        for kind in ['q', 'm', 'h']:
+            msg = "complex argsort, kind=%s" % kind
+            assert_equal(ai.copy().argsort(kind=kind), a, msg)
+            assert_equal(bi.copy().argsort(kind=kind), b, msg)
+        ai = a + 1j
+        bi = b + 1j
+        for kind in ['q', 'm', 'h']:
+            msg = "complex argsort, kind=%s" % kind
+            assert_equal(ai.copy().argsort(kind=kind), a, msg)
+            assert_equal(bi.copy().argsort(kind=kind), b, msg)
+
+        # test argsort of complex arrays requiring byte-swapping, gh-5441
+        for endianness in '<>':
+            for dt in np.typecodes['Complex']:
+                arr = np.array([1+3.j, 2+2.j, 3+1.j], dtype=endianness + dt)
+                msg = 'byte-swapped complex argsort, dtype={0}'.format(dt)
+                assert_equal(arr.argsort(),
+                             np.arange(len(arr), dtype=np.intp), msg)
+
+        # test string argsorts.
+        s = 'aaaaaaaa'
+        a = np.array([s + chr(i) for i in range(101)])
+        b = a[::-1].copy()
+        r = np.arange(101)
+        rr = r[::-1]
+        for kind in ['q', 'm', 'h']:
+            msg = "string argsort, kind=%s" % kind
+            assert_equal(a.copy().argsort(kind=kind), r, msg)
+            assert_equal(b.copy().argsort(kind=kind), rr, msg)
+
+        # test unicode argsorts.
+        s = 'aaaaaaaa'
+        a = np.array([s + chr(i) for i in range(101)], dtype=np.unicode)
+        b = a[::-1]
+        r = np.arange(101)
+        rr = r[::-1]
+        for kind in ['q', 'm', 'h']:
+            msg = "unicode argsort, kind=%s" % kind
+            assert_equal(a.copy().argsort(kind=kind), r, msg)
+            assert_equal(b.copy().argsort(kind=kind), rr, msg)
+
+        # test object array argsorts.
+        a = np.empty((101,), dtype=object)
+        a[:] = list(range(101))
+        b = a[::-1]
+        r = np.arange(101)
+        rr = r[::-1]
+        for kind in ['q', 'm', 'h']:
+            msg = "object argsort, kind=%s" % kind
+            assert_equal(a.copy().argsort(kind=kind), r, msg)
+            assert_equal(b.copy().argsort(kind=kind), rr, msg)
+
+        # test structured array argsorts.
+        dt = np.dtype([('f', float), ('i', int)])
+        a = np.array([(i, i) for i in range(101)], dtype=dt)
+        b = a[::-1]
+        r = np.arange(101)
+        rr = r[::-1]
+        for kind in ['q', 'm', 'h']:
+            msg = "structured array argsort, kind=%s" % kind
+            assert_equal(a.copy().argsort(kind=kind), r, msg)
+            assert_equal(b.copy().argsort(kind=kind), rr, msg)
+
+        # test datetime64 argsorts.
+        a = np.arange(0, 101, dtype='datetime64[D]')
+        b = a[::-1]
+        r = np.arange(101)
+        rr = r[::-1]
+        for kind in ['q', 'h', 'm']:
+            msg = "datetime64 argsort, kind=%s" % kind
+            assert_equal(a.copy().argsort(kind=kind), r, msg)
+            assert_equal(b.copy().argsort(kind=kind), rr, msg)
+
+        # test timedelta64 argsorts.
+        a = np.arange(0, 101, dtype='timedelta64[D]')
+        b = a[::-1]
+        r = np.arange(101)
+        rr = r[::-1]
+        for kind in ['q', 'h', 'm']:
+            msg = "timedelta64 argsort, kind=%s" % kind
+            assert_equal(a.copy().argsort(kind=kind), r, msg)
+            assert_equal(b.copy().argsort(kind=kind), rr, msg)
+
+        # check axis handling. This should be the same for all type
+        # specific argsorts, so we only check it for one type and one kind
+        a = np.array([[3, 2], [1, 0]])
+        b = np.array([[1, 1], [0, 0]])
+        c = np.array([[1, 0], [1, 0]])
+        assert_equal(a.copy().argsort(axis=0), b)
+        assert_equal(a.copy().argsort(axis=1), c)
+        assert_equal(a.copy().argsort(), c)
+
+        # check axis handling for multidimensional empty arrays
+        a = np.array([])
+        a.shape = (3, 2, 1, 0)
+        for axis in range(-a.ndim, a.ndim):
+            msg = 'test empty array argsort with axis={0}'.format(axis)
+            assert_equal(np.argsort(a, axis=axis),
+                         np.zeros_like(a, dtype=np.intp), msg)
+        msg = 'test empty array argsort with axis=None'
+        assert_equal(np.argsort(a, axis=None),
+                     np.zeros_like(a.ravel(), dtype=np.intp), msg)
+
+        # check that stable argsorts are stable
+        r = np.arange(100)
+        # scalars
+        a = np.zeros(100)
+        assert_equal(a.argsort(kind='m'), r)
+        # complex
+        a = np.zeros(100, dtype=complex)
+        assert_equal(a.argsort(kind='m'), r)
+        # string
+        a = np.array(['aaaaaaaaa' for i in range(100)])
+        assert_equal(a.argsort(kind='m'), r)
+        # unicode
+        a = np.array(['aaaaaaaaa' for i in range(100)], dtype=np.unicode)
+        assert_equal(a.argsort(kind='m'), r)
+
+    def test_sort_unicode_kind(self):
+        d = np.arange(10)
+        k = b'\xc3\xa4'.decode("UTF8")
+        assert_raises(ValueError, d.sort, kind=k)
+        assert_raises(ValueError, d.argsort, kind=k)
+
+    def test_searchsorted(self):
+        # test for floats and complex containing nans. The logic is the
+        # same for all float types so only test double types for now.
+        # The search sorted routines use the compare functions for the
+        # array type, so this checks if that is consistent with the sort
+        # order.
+
+        # check double
+        a = np.array([0, 1, np.nan])
+        msg = "Test real searchsorted with nans, side='l'"
+        b = a.searchsorted(a, side='l')
+        assert_equal(b, np.arange(3), msg)
+        msg = "Test real searchsorted with nans, side='r'"
+        b = a.searchsorted(a, side='r')
+        assert_equal(b, np.arange(1, 4), msg)
+        # check double complex
+        a = np.zeros(9, dtype=np.complex128)
+        a.real += [0, 0, 1, 1, 0, 1, np.nan, np.nan, np.nan]
+        a.imag += [0, 1, 0, 1, np.nan, np.nan, 0, 1, np.nan]
+        msg = "Test complex searchsorted with nans, side='l'"
+        b = a.searchsorted(a, side='l')
+        assert_equal(b, np.arange(9), msg)
+        msg = "Test complex searchsorted with nans, side='r'"
+        b = a.searchsorted(a, side='r')
+        assert_equal(b, np.arange(1, 10), msg)
+        msg = "Test searchsorted with little endian, side='l'"
+        a = np.array([0, 128], dtype='<i4')
+        b = a.searchsorted(np.array(128, dtype='<i4'))
+        assert_equal(b, 1, msg)
+        msg = "Test searchsorted with big endian, side='l'"
+        a = np.array([0, 128], dtype='>i4')
+        b = a.searchsorted(np.array(128, dtype='>i4'))
+        assert_equal(b, 1, msg)
+
+        # Check 0 elements
+        a = np.ones(0)
+        b = a.searchsorted([0, 1, 2], 'l')
+        assert_equal(b, [0, 0, 0])
+        b = a.searchsorted([0, 1, 2], 'r')
+        assert_equal(b, [0, 0, 0])
+        a = np.ones(1)
+        # Check 1 element
+        b = a.searchsorted([0, 1, 2], 'l')
+        assert_equal(b, [0, 0, 1])
+        b = a.searchsorted([0, 1, 2], 'r')
+        assert_equal(b, [0, 1, 1])
+        # Check all elements equal
+        a = np.ones(2)
+        b = a.searchsorted([0, 1, 2], 'l')
+        assert_equal(b, [0, 0, 2])
+        b = a.searchsorted([0, 1, 2], 'r')
+        assert_equal(b, [0, 2, 2])
+
+        # Test searching unaligned array
+        a = np.arange(10)
+        aligned = np.empty(a.itemsize * a.size + 1, 'uint8')
+        unaligned = aligned[1:].view(a.dtype)
+        unaligned[:] = a
+        # Test searching unaligned array
+        b = unaligned.searchsorted(a, 'l')
+        assert_equal(b, a)
+        b = unaligned.searchsorted(a, 'r')
+        assert_equal(b, a + 1)
+        # Test searching for unaligned keys
+        b = a.searchsorted(unaligned, 'l')
+        assert_equal(b, a)
+        b = a.searchsorted(unaligned, 'r')
+        assert_equal(b, a + 1)
+
+        # Test smart resetting of binsearch indices
+        a = np.arange(5)
+        b = a.searchsorted([6, 5, 4], 'l')
+        assert_equal(b, [5, 5, 4])
+        b = a.searchsorted([6, 5, 4], 'r')
+        assert_equal(b, [5, 5, 5])
+
+        # Test all type specific binary search functions
+        types = ''.join((np.typecodes['AllInteger'], np.typecodes['AllFloat'],
+                         np.typecodes['Datetime'], '?O'))
+        for dt in types:
+            if dt == 'M':
+                dt = 'M8[D]'
+            if dt == '?':
+                a = np.arange(2, dtype=dt)
+                out = np.arange(2)
+            else:
+                a = np.arange(0, 5, dtype=dt)
+                out = np.arange(5)
+            b = a.searchsorted(a, 'l')
+            assert_equal(b, out)
+            b = a.searchsorted(a, 'r')
+            assert_equal(b, out + 1)
+            # Test empty array, use a fresh array to get warnings in
+            # valgrind if access happens.
+            e = np.ndarray(shape=0, buffer=b'', dtype=dt)
+            b = e.searchsorted(a, 'l')
+            assert_array_equal(b, np.zeros(len(a), dtype=np.intp))
+            b = a.searchsorted(e, 'l')
+            assert_array_equal(b, np.zeros(0, dtype=np.intp))
+
+    def test_searchsorted_unicode(self):
+        # Test searchsorted on unicode strings.
+
+        # 1.6.1 contained a string length miscalculation in
+        # arraytypes.c.src:UNICODE_compare() which manifested as
+        # incorrect/inconsistent results from searchsorted.
+        a = np.array(['P:\\20x_dapi_cy3\\20x_dapi_cy3_20100185_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100186_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100187_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100189_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100190_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100191_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100192_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100193_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100194_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100195_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100196_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100197_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100198_1',
+                      'P:\\20x_dapi_cy3\\20x_dapi_cy3_20100199_1'],
+                     dtype=np.unicode)
+        ind = np.arange(len(a))
+        assert_equal([a.searchsorted(v, 'left') for v in a], ind)
+        assert_equal([a.searchsorted(v, 'right') for v in a], ind + 1)
+        assert_equal([a.searchsorted(a[i], 'left') for i in ind], ind)
+        assert_equal([a.searchsorted(a[i], 'right') for i in ind], ind + 1)
+
+    def test_searchsorted_with_sorter(self):
+        a = np.array([5, 2, 1, 3, 4])
+        s = np.argsort(a)
+        assert_raises(TypeError, np.searchsorted, a, 0, sorter=(1, (2, 3)))
+        assert_raises(TypeError, np.searchsorted, a, 0, sorter=[1.1])
+        assert_raises(ValueError, np.searchsorted, a, 0, sorter=[1, 2, 3, 4])
+        assert_raises(ValueError, np.searchsorted, a, 0, sorter=[1, 2, 3, 4, 5, 6])
+
+        # bounds check
+        assert_raises(ValueError, np.searchsorted, a, 4, sorter=[0, 1, 2, 3, 5])
+        assert_raises(ValueError, np.searchsorted, a, 0, sorter=[-1, 0, 1, 2, 3])
+        assert_raises(ValueError, np.searchsorted, a, 0, sorter=[4, 0, -1, 2, 3])
+
+        a = np.random.rand(300)
+        s = a.argsort()
+        b = np.sort(a)
+        k = np.linspace(0, 1, 20)
+        assert_equal(b.searchsorted(k), a.searchsorted(k, sorter=s))
+
+        a = np.array([0, 1, 2, 3, 5]*20)
+        s = a.argsort()
+        k = [0, 1, 2, 3, 5]
+        expected = [0, 20, 40, 60, 80]
+        assert_equal(a.searchsorted(k, side='l', sorter=s), expected)
+        expected = [20, 40, 60, 80, 100]
+        assert_equal(a.searchsorted(k, side='r', sorter=s), expected)
+
+        # Test searching unaligned array
+        keys = np.arange(10)
+        a = keys.copy()
+        np.random.shuffle(s)
+        s = a.argsort()
+        aligned = np.empty(a.itemsize * a.size + 1, 'uint8')
+        unaligned = aligned[1:].view(a.dtype)
+        # Test searching unaligned array
+        unaligned[:] = a
+        b = unaligned.searchsorted(keys, 'l', s)
+        assert_equal(b, keys)
+        b = unaligned.searchsorted(keys, 'r', s)
+        assert_equal(b, keys + 1)
+        # Test searching for unaligned keys
+        unaligned[:] = keys
+        b = a.searchsorted(unaligned, 'l', s)
+        assert_equal(b, keys)
+        b = a.searchsorted(unaligned, 'r', s)
+        assert_equal(b, keys + 1)
+
+        # Test all type specific indirect binary search functions
+        types = ''.join((np.typecodes['AllInteger'], np.typecodes['AllFloat'],
+                         np.typecodes['Datetime'], '?O'))
+        for dt in types:
+            if dt == 'M':
+                dt = 'M8[D]'
+            if dt == '?':
+                a = np.array([1, 0], dtype=dt)
+                # We want the sorter array to be of a type that is different
+                # from np.intp in all platforms, to check for #4698
+                s = np.array([1, 0], dtype=np.int16)
+                out = np.array([1, 0])
+            else:
+                a = np.array([3, 4, 1, 2, 0], dtype=dt)
+                # We want the sorter array to be of a type that is different
+                # from np.intp in all platforms, to check for #4698
+                s = np.array([4, 2, 3, 0, 1], dtype=np.int16)
+                out = np.array([3, 4, 1, 2, 0], dtype=np.intp)
+            b = a.searchsorted(a, 'l', s)
+            assert_equal(b, out)
+            b = a.searchsorted(a, 'r', s)
+            assert_equal(b, out + 1)
+            # Test empty array, use a fresh array to get warnings in
+            # valgrind if access happens.
+            e = np.ndarray(shape=0, buffer=b'', dtype=dt)
+            b = e.searchsorted(a, 'l', s[:0])
+            assert_array_equal(b, np.zeros(len(a), dtype=np.intp))
+            b = a.searchsorted(e, 'l', s)
+            assert_array_equal(b, np.zeros(0, dtype=np.intp))
+
+        # Test non-contiguous sorter array
+        a = np.array([3, 4, 1, 2, 0])
+        srt = np.empty((10,), dtype=np.intp)
+        srt[1::2] = -1
+        srt[::2] = [4, 2, 3, 0, 1]
+        s = srt[::2]
+        out = np.array([3, 4, 1, 2, 0], dtype=np.intp)
+        b = a.searchsorted(a, 'l', s)
+        assert_equal(b, out)
+        b = a.searchsorted(a, 'r', s)
+        assert_equal(b, out + 1)
+
+    def test_searchsorted_return_type(self):
+        # Functions returning indices should always return base ndarrays
+        class A(np.ndarray):
+            pass
+        a = np.arange(5).view(A)
+        b = np.arange(1, 3).view(A)
+        s = np.arange(5).view(A)
+        assert_(not isinstance(a.searchsorted(b, 'l'), A))
+        assert_(not isinstance(a.searchsorted(b, 'r'), A))
+        assert_(not isinstance(a.searchsorted(b, 'l', s), A))
+        assert_(not isinstance(a.searchsorted(b, 'r', s), A))
+
+    def test_argpartition_out_of_range(self):
+        # Test out of range values in kth raise an error, gh-5469
+        d = np.arange(10)
+        assert_raises(ValueError, d.argpartition, 10)
+        assert_raises(ValueError, d.argpartition, -11)
+        # Test also for generic type argpartition, which uses sorting
+        # and used to not bound check kth
+        d_obj = np.arange(10, dtype=object)
+        assert_raises(ValueError, d_obj.argpartition, 10)
+        assert_raises(ValueError, d_obj.argpartition, -11)
+
+    def test_partition_out_of_range(self):
+        # Test out of range values in kth raise an error, gh-5469
+        d = np.arange(10)
+        assert_raises(ValueError, d.partition, 10)
+        assert_raises(ValueError, d.partition, -11)
+        # Test also for generic type partition, which uses sorting
+        # and used to not bound check kth
+        d_obj = np.arange(10, dtype=object)
+        assert_raises(ValueError, d_obj.partition, 10)
+        assert_raises(ValueError, d_obj.partition, -11)
+
+    def test_argpartition_integer(self):
+        # Test non-integer values in kth raise an error/
+        d = np.arange(10)
+        assert_raises(TypeError, d.argpartition, 9.)
+        # Test also for generic type argpartition, which uses sorting
+        # and used to not bound check kth
+        d_obj = np.arange(10, dtype=object)
+        assert_raises(TypeError, d_obj.argpartition, 9.)
+
+    def test_partition_integer(self):
+        # Test out of range values in kth raise an error, gh-5469
+        d = np.arange(10)
+        assert_raises(TypeError, d.partition, 9.)
+        # Test also for generic type partition, which uses sorting
+        # and used to not bound check kth
+        d_obj = np.arange(10, dtype=object)
+        assert_raises(TypeError, d_obj.partition, 9.)
+
+    def test_partition_empty_array(self):
+        # check axis handling for multidimensional empty arrays
+        a = np.array([])
+        a.shape = (3, 2, 1, 0)
+        for axis in range(-a.ndim, a.ndim):
+            msg = 'test empty array partition with axis={0}'.format(axis)
+            assert_equal(np.partition(a, 0, axis=axis), a, msg)
+        msg = 'test empty array partition with axis=None'
+        assert_equal(np.partition(a, 0, axis=None), a.ravel(), msg)
+
+    def test_argpartition_empty_array(self):
+        # check axis handling for multidimensional empty arrays
+        a = np.array([])
+        a.shape = (3, 2, 1, 0)
+        for axis in range(-a.ndim, a.ndim):
+            msg = 'test empty array argpartition with axis={0}'.format(axis)
+            assert_equal(np.partition(a, 0, axis=axis),
+                         np.zeros_like(a, dtype=np.intp), msg)
+        msg = 'test empty array argpartition with axis=None'
+        assert_equal(np.partition(a, 0, axis=None),
+                     np.zeros_like(a.ravel(), dtype=np.intp), msg)
+
+    def test_partition(self):
+        d = np.arange(10)
+        assert_raises(TypeError, np.partition, d, 2, kind=1)
+        assert_raises(ValueError, np.partition, d, 2, kind="nonsense")
+        assert_raises(ValueError, np.argpartition, d, 2, kind="nonsense")
+        assert_raises(ValueError, d.partition, 2, axis=0, kind="nonsense")
+        assert_raises(ValueError, d.argpartition, 2, axis=0, kind="nonsense")
+        for k in ("introselect",):
+            d = np.array([])
+            assert_array_equal(np.partition(d, 0, kind=k), d)
+            assert_array_equal(np.argpartition(d, 0, kind=k), d)
+            d = np.ones(1)
+            assert_array_equal(np.partition(d, 0, kind=k)[0], d)
+            assert_array_equal(d[np.argpartition(d, 0, kind=k)],
+                               np.partition(d, 0, kind=k))
+
+            # kth not modified
+            kth = np.array([30, 15, 5])
+            okth = kth.copy()
+            np.partition(np.arange(40), kth)
+            assert_array_equal(kth, okth)
+
+            for r in ([2, 1], [1, 2], [1, 1]):
+                d = np.array(r)
+                tgt = np.sort(d)
+                assert_array_equal(np.partition(d, 0, kind=k)[0], tgt[0])
+                assert_array_equal(np.partition(d, 1, kind=k)[1], tgt[1])
+                assert_array_equal(d[np.argpartition(d, 0, kind=k)],
+                                   np.partition(d, 0, kind=k))
+                assert_array_equal(d[np.argpartition(d, 1, kind=k)],
+                                   np.partition(d, 1, kind=k))
+                for i in range(d.size):
+                    d[i:].partition(0, kind=k)
+                assert_array_equal(d, tgt)
+
+            for r in ([3, 2, 1], [1, 2, 3], [2, 1, 3], [2, 3, 1],
+                      [1, 1, 1], [1, 2, 2], [2, 2, 1], [1, 2, 1]):
+                d = np.array(r)
+                tgt = np.sort(d)
+                assert_array_equal(np.partition(d, 0, kind=k)[0], tgt[0])
+                assert_array_equal(np.partition(d, 1, kind=k)[1], tgt[1])
+                assert_array_equal(np.partition(d, 2, kind=k)[2], tgt[2])
+                assert_array_equal(d[np.argpartition(d, 0, kind=k)],
+                                   np.partition(d, 0, kind=k))
+                assert_array_equal(d[np.argpartition(d, 1, kind=k)],
+                                   np.partition(d, 1, kind=k))
+                assert_array_equal(d[np.argpartition(d, 2, kind=k)],
+                                   np.partition(d, 2, kind=k))
+                for i in range(d.size):
+                    d[i:].partition(0, kind=k)
+                assert_array_equal(d, tgt)
+
+            d = np.ones(50)
+            assert_array_equal(np.partition(d, 0, kind=k), d)
+            assert_array_equal(d[np.argpartition(d, 0, kind=k)],
+                               np.partition(d, 0, kind=k))
+
+            # sorted
+            d = np.arange(49)
+            assert_equal(np.partition(d, 5, kind=k)[5], 5)
+            assert_equal(np.partition(d, 15, kind=k)[15], 15)
+            assert_array_equal(d[np.argpartition(d, 5, kind=k)],
+                               np.partition(d, 5, kind=k))
+            assert_array_equal(d[np.argpartition(d, 15, kind=k)],
+                               np.partition(d, 15, kind=k))
+
+            # rsorted
+            d = np.arange(47)[::-1]
+            assert_equal(np.partition(d, 6, kind=k)[6], 6)
+            assert_equal(np.partition(d, 16, kind=k)[16], 16)
+            assert_array_equal(d[np.argpartition(d, 6, kind=k)],
+                               np.partition(d, 6, kind=k))
+            assert_array_equal(d[np.argpartition(d, 16, kind=k)],
+                               np.partition(d, 16, kind=k))
+
+            assert_array_equal(np.partition(d, -6, kind=k),
+                               np.partition(d, 41, kind=k))
+            assert_array_equal(np.partition(d, -16, kind=k),
+                               np.partition(d, 31, kind=k))
+            assert_array_equal(d[np.argpartition(d, -6, kind=k)],
+                               np.partition(d, 41, kind=k))
+
+            # median of 3 killer, O(n^2) on pure median 3 pivot quickselect
+            # exercises the median of median of 5 code used to keep O(n)
+            d = np.arange(1000000)
+            x = np.roll(d, d.size // 2)
+            mid = x.size // 2 + 1
+            assert_equal(np.partition(x, mid)[mid], mid)
+            d = np.arange(1000001)
+            x = np.roll(d, d.size // 2 + 1)
+            mid = x.size // 2 + 1
+            assert_equal(np.partition(x, mid)[mid], mid)
+
+            # max
+            d = np.ones(10)
+            d[1] = 4
+            assert_equal(np.partition(d, (2, -1))[-1], 4)
+            assert_equal(np.partition(d, (2, -1))[2], 1)
+            assert_equal(d[np.argpartition(d, (2, -1))][-1], 4)
+            assert_equal(d[np.argpartition(d, (2, -1))][2], 1)
+            d[1] = np.nan
+            assert_(np.isnan(d[np.argpartition(d, (2, -1))][-1]))
+            assert_(np.isnan(np.partition(d, (2, -1))[-1]))
+
+            # equal elements
+            d = np.arange(47) % 7
+            tgt = np.sort(np.arange(47) % 7)
+            np.random.shuffle(d)
+            for i in range(d.size):
+                assert_equal(np.partition(d, i, kind=k)[i], tgt[i])
+            assert_array_equal(d[np.argpartition(d, 6, kind=k)],
+                               np.partition(d, 6, kind=k))
+            assert_array_equal(d[np.argpartition(d, 16, kind=k)],
+                               np.partition(d, 16, kind=k))
+            for i in range(d.size):
+                d[i:].partition(0, kind=k)
+            assert_array_equal(d, tgt)
+
+            d = np.array([0, 1, 2, 3, 4, 5, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7,
+                          7, 7, 7, 7, 7, 9])
+            kth = [0, 3, 19, 20]
+            assert_equal(np.partition(d, kth, kind=k)[kth], (0, 3, 7, 7))
+            assert_equal(d[np.argpartition(d, kth, kind=k)][kth], (0, 3, 7, 7))
+
+            d = np.array([2, 1])
+            d.partition(0, kind=k)
+            assert_raises(ValueError, d.partition, 2)
+            assert_raises(np.AxisError, d.partition, 3, axis=1)
+            assert_raises(ValueError, np.partition, d, 2)
+            assert_raises(np.AxisError, np.partition, d, 2, axis=1)
+            assert_raises(ValueError, d.argpartition, 2)
+            assert_raises(np.AxisError, d.argpartition, 3, axis=1)
+            assert_raises(ValueError, np.argpartition, d, 2)
+            assert_raises(np.AxisError, np.argpartition, d, 2, axis=1)
+            d = np.arange(10).reshape((2, 5))
+            d.partition(1, axis=0, kind=k)
+            d.partition(4, axis=1, kind=k)
+            np.partition(d, 1, axis=0, kind=k)
+            np.partition(d, 4, axis=1, kind=k)
+            np.partition(d, 1, axis=None, kind=k)
+            np.partition(d, 9, axis=None, kind=k)
+            d.argpartition(1, axis=0, kind=k)
+            d.argpartition(4, axis=1, kind=k)
+            np.argpartition(d, 1, axis=0, kind=k)
+            np.argpartition(d, 4, axis=1, kind=k)
+            np.argpartition(d, 1, axis=None, kind=k)
+            np.argpartition(d, 9, axis=None, kind=k)
+            assert_raises(ValueError, d.partition, 2, axis=0)
+            assert_raises(ValueError, d.partition, 11, axis=1)
+            assert_raises(TypeError, d.partition, 2, axis=None)
+            assert_raises(ValueError, np.partition, d, 9, axis=1)
+            assert_raises(ValueError, np.partition, d, 11, axis=None)
+            assert_raises(ValueError, d.argpartition, 2, axis=0)
+            assert_raises(ValueError, d.argpartition, 11, axis=1)
+            assert_raises(ValueError, np.argpartition, d, 9, axis=1)
+            assert_raises(ValueError, np.argpartition, d, 11, axis=None)
+
+            td = [(dt, s) for dt in [np.int32, np.float32, np.complex64]
+                  for s in (9, 16)]
+            for dt, s in td:
+                aae = assert_array_equal
+                at = assert_
+
+                d = np.arange(s, dtype=dt)
+                np.random.shuffle(d)
+                d1 = np.tile(np.arange(s, dtype=dt), (4, 1))
+                map(np.random.shuffle, d1)
+                d0 = np.transpose(d1)
+                for i in range(d.size):
+                    p = np.partition(d, i, kind=k)
+                    assert_equal(p[i], i)
+                    # all before are smaller
+                    assert_array_less(p[:i], p[i])
+                    # all after are larger
+                    assert_array_less(p[i], p[i + 1:])
+                    aae(p, d[np.argpartition(d, i, kind=k)])
+
+                    p = np.partition(d1, i, axis=1, kind=k)
+                    aae(p[:, i], np.array([i] * d1.shape[0], dtype=dt))
+                    # array_less does not seem to work right
+                    at((p[:, :i].T <= p[:, i]).all(),
+                       msg="%d: %r <= %r" % (i, p[:, i], p[:, :i].T))
+                    at((p[:, i + 1:].T > p[:, i]).all(),
+                       msg="%d: %r < %r" % (i, p[:, i], p[:, i + 1:].T))
+                    aae(p, d1[np.arange(d1.shape[0])[:, None],
+                        np.argpartition(d1, i, axis=1, kind=k)])
+
+                    p = np.partition(d0, i, axis=0, kind=k)
+                    aae(p[i, :], np.array([i] * d1.shape[0], dtype=dt))
+                    # array_less does not seem to work right
+                    at((p[:i, :] <= p[i, :]).all(),
+                       msg="%d: %r <= %r" % (i, p[i, :], p[:i, :]))
+                    at((p[i + 1:, :] > p[i, :]).all(),
+                       msg="%d: %r < %r" % (i, p[i, :], p[:, i + 1:]))
+                    aae(p, d0[np.argpartition(d0, i, axis=0, kind=k),
+                        np.arange(d0.shape[1])[None, :]])
+
+                    # check inplace
+                    dc = d.copy()
+                    dc.partition(i, kind=k)
+                    assert_equal(dc, np.partition(d, i, kind=k))
+                    dc = d0.copy()
+                    dc.partition(i, axis=0, kind=k)
+                    assert_equal(dc, np.partition(d0, i, axis=0, kind=k))
+                    dc = d1.copy()
+                    dc.partition(i, axis=1, kind=k)
+                    assert_equal(dc, np.partition(d1, i, axis=1, kind=k))
+
+    def assert_partitioned(self, d, kth):
+        prev = 0
+        for k in np.sort(kth):
+            assert_array_less(d[prev:k], d[k], err_msg='kth %d' % k)
+            assert_((d[k:] >= d[k]).all(),
+                    msg="kth %d, %r not greater equal %d" % (k, d[k:], d[k]))
+            prev = k + 1
+
+    def test_partition_iterative(self):
+            d = np.arange(17)
+            kth = (0, 1, 2, 429, 231)
+            assert_raises(ValueError, d.partition, kth)
+            assert_raises(ValueError, d.argpartition, kth)
+            d = np.arange(10).reshape((2, 5))
+            assert_raises(ValueError, d.partition, kth, axis=0)
+            assert_raises(ValueError, d.partition, kth, axis=1)
+            assert_raises(ValueError, np.partition, d, kth, axis=1)
+            assert_raises(ValueError, np.partition, d, kth, axis=None)
+
+            d = np.array([3, 4, 2, 1])
+            p = np.partition(d, (0, 3))
+            self.assert_partitioned(p, (0, 3))
+            self.assert_partitioned(d[np.argpartition(d, (0, 3))], (0, 3))
+
+            assert_array_equal(p, np.partition(d, (-3, -1)))
+            assert_array_equal(p, d[np.argpartition(d, (-3, -1))])
+
+            d = np.arange(17)
+            np.random.shuffle(d)
+            d.partition(range(d.size))
+            assert_array_equal(np.arange(17), d)
+            np.random.shuffle(d)
+            assert_array_equal(np.arange(17), d[d.argpartition(range(d.size))])
+
+            # test unsorted kth
+            d = np.arange(17)
+            np.random.shuffle(d)
+            keys = np.array([1, 3, 8, -2])
+            np.random.shuffle(d)
+            p = np.partition(d, keys)
+            self.assert_partitioned(p, keys)
+            p = d[np.argpartition(d, keys)]
+            self.assert_partitioned(p, keys)
+            np.random.shuffle(keys)
+            assert_array_equal(np.partition(d, keys), p)
+            assert_array_equal(d[np.argpartition(d, keys)], p)
+
+            # equal kth
+            d = np.arange(20)[::-1]
+            self.assert_partitioned(np.partition(d, [5]*4), [5])
+            self.assert_partitioned(np.partition(d, [5]*4 + [6, 13]),
+                                    [5]*4 + [6, 13])
+            self.assert_partitioned(d[np.argpartition(d, [5]*4)], [5])
+            self.assert_partitioned(d[np.argpartition(d, [5]*4 + [6, 13])],
+                                    [5]*4 + [6, 13])
+
+            d = np.arange(12)
+            np.random.shuffle(d)
+            d1 = np.tile(np.arange(12), (4, 1))
+            map(np.random.shuffle, d1)
+            d0 = np.transpose(d1)
+
+            kth = (1, 6, 7, -1)
+            p = np.partition(d1, kth, axis=1)
+            pa = d1[np.arange(d1.shape[0])[:, None],
+                    d1.argpartition(kth, axis=1)]
+            assert_array_equal(p, pa)
+            for i in range(d1.shape[0]):
+                self.assert_partitioned(p[i,:], kth)
+            p = np.partition(d0, kth, axis=0)
+            pa = d0[np.argpartition(d0, kth, axis=0),
+                    np.arange(d0.shape[1])[None,:]]
+            assert_array_equal(p, pa)
+            for i in range(d0.shape[1]):
+                self.assert_partitioned(p[:, i], kth)
+
+    def test_partition_cdtype(self):
+        d = np.array([('Galahad', 1.7, 38), ('Arthur', 1.8, 41),
+                   ('Lancelot', 1.9, 38)],
+                  dtype=[('name', '|S10'), ('height', '<f8'), ('age', '<i4')])
+
+        tgt = np.sort(d, order=['age', 'height'])
+        assert_array_equal(np.partition(d, range(d.size),
+                                        order=['age', 'height']),
+                           tgt)
+        assert_array_equal(d[np.argpartition(d, range(d.size),
+                                             order=['age', 'height'])],
+                           tgt)
+        for k in range(d.size):
+            assert_equal(np.partition(d, k, order=['age', 'height'])[k],
+                        tgt[k])
+            assert_equal(d[np.argpartition(d, k, order=['age', 'height'])][k],
+                         tgt[k])
+
+        d = np.array(['Galahad', 'Arthur', 'zebra', 'Lancelot'])
+        tgt = np.sort(d)
+        assert_array_equal(np.partition(d, range(d.size)), tgt)
+        for k in range(d.size):
+            assert_equal(np.partition(d, k)[k], tgt[k])
+            assert_equal(d[np.argpartition(d, k)][k], tgt[k])
+
+    def test_partition_unicode_kind(self):
+        d = np.arange(10)
+        k = b'\xc3\xa4'.decode("UTF8")
+        assert_raises(ValueError, d.partition, 2, kind=k)
+        assert_raises(ValueError, d.argpartition, 2, kind=k)
+
+    def test_partition_fuzz(self):
+        # a few rounds of random data testing
+        for j in range(10, 30):
+            for i in range(1, j - 2):
+                d = np.arange(j)
+                np.random.shuffle(d)
+                d = d % np.random.randint(2, 30)
+                idx = np.random.randint(d.size)
+                kth = [0, idx, i, i + 1]
+                tgt = np.sort(d)[kth]
+                assert_array_equal(np.partition(d, kth)[kth], tgt,
+                                   err_msg="data: %r\n kth: %r" % (d, kth))
+
+    def test_argpartition_gh5524(self):
+        #  A test for functionality of argpartition on lists.
+        d = [6,7,3,2,9,0]
+        p = np.argpartition(d,1)
+        self.assert_partitioned(np.array(d)[p],[1])
+
+    def test_flatten(self):
+        x0 = np.array([[1, 2, 3], [4, 5, 6]], np.int32)
+        x1 = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]], np.int32)
+        y0 = np.array([1, 2, 3, 4, 5, 6], np.int32)
+        y0f = np.array([1, 4, 2, 5, 3, 6], np.int32)
+        y1 = np.array([1, 2, 3, 4, 5, 6, 7, 8], np.int32)
+        y1f = np.array([1, 5, 3, 7, 2, 6, 4, 8], np.int32)
+        assert_equal(x0.flatten(), y0)
+        assert_equal(x0.flatten('F'), y0f)
+        assert_equal(x0.flatten('F'), x0.T.flatten())
+        assert_equal(x1.flatten(), y1)
+        assert_equal(x1.flatten('F'), y1f)
+        assert_equal(x1.flatten('F'), x1.T.flatten())
+
+    @pytest.mark.parametrize('func', (np.dot, np.matmul))
+    def test_arr_mult(self, func):
+        a = np.array([[1, 0], [0, 1]])
+        b = np.array([[0, 1], [1, 0]])
+        c = np.array([[9, 1], [1, -9]])
+        d = np.arange(24).reshape(4, 6)
+        ddt = np.array(
+            [[  55,  145,  235,  325],
+             [ 145,  451,  757, 1063],
+             [ 235,  757, 1279, 1801],
+             [ 325, 1063, 1801, 2539]]
+        )
+        dtd = np.array(
+            [[504, 540, 576, 612, 648, 684],
+             [540, 580, 620, 660, 700, 740],
+             [576, 620, 664, 708, 752, 796],
+             [612, 660, 708, 756, 804, 852],
+             [648, 700, 752, 804, 856, 908],
+             [684, 740, 796, 852, 908, 964]]
+        )
+
+
+        # gemm vs syrk optimizations
+        for et in [np.float32, np.float64, np.complex64, np.complex128]:
+            eaf = a.astype(et)
+            assert_equal(func(eaf, eaf), eaf)
+            assert_equal(func(eaf.T, eaf), eaf)
+            assert_equal(func(eaf, eaf.T), eaf)
+            assert_equal(func(eaf.T, eaf.T), eaf)
+            assert_equal(func(eaf.T.copy(), eaf), eaf)
+            assert_equal(func(eaf, eaf.T.copy()), eaf)
+            assert_equal(func(eaf.T.copy(), eaf.T.copy()), eaf)
+
+        # syrk validations
+        for et in [np.float32, np.float64, np.complex64, np.complex128]:
+            eaf = a.astype(et)
+            ebf = b.astype(et)
+            assert_equal(func(ebf, ebf), eaf)
+            assert_equal(func(ebf.T, ebf), eaf)
+            assert_equal(func(ebf, ebf.T), eaf)
+            assert_equal(func(ebf.T, ebf.T), eaf)
+
+        # syrk - different shape, stride, and view validations
+        for et in [np.float32, np.float64, np.complex64, np.complex128]:
+            edf = d.astype(et)
+            assert_equal(
+                func(edf[::-1, :], edf.T),
+                func(edf[::-1, :].copy(), edf.T.copy())
+            )
+            assert_equal(
+                func(edf[:, ::-1], edf.T),
+                func(edf[:, ::-1].copy(), edf.T.copy())
+            )
+            assert_equal(
+                func(edf, edf[::-1, :].T),
+                func(edf, edf[::-1, :].T.copy())
+            )
+            assert_equal(
+                func(edf, edf[:, ::-1].T),
+                func(edf, edf[:, ::-1].T.copy())
+            )
+            assert_equal(
+                func(edf[:edf.shape[0] // 2, :], edf[::2, :].T),
+                func(edf[:edf.shape[0] // 2, :].copy(), edf[::2, :].T.copy())
+            )
+            assert_equal(
+                func(edf[::2, :], edf[:edf.shape[0] // 2, :].T),
+                func(edf[::2, :].copy(), edf[:edf.shape[0] // 2, :].T.copy())
+            )
+
+        # syrk - different shape
+        for et in [np.float32, np.float64, np.complex64, np.complex128]:
+            edf = d.astype(et)
+            eddtf = ddt.astype(et)
+            edtdf = dtd.astype(et)
+            assert_equal(func(edf, edf.T), eddtf)
+            assert_equal(func(edf.T, edf), edtdf)
+
+    @pytest.mark.parametrize('func', (np.dot, np.matmul))
+    @pytest.mark.parametrize('dtype', 'ifdFD')
+    def test_no_dgemv(self, func, dtype):
+        # check vector arg for contiguous before gemv
+        # gh-12156
+        a = np.arange(8.0, dtype=dtype).reshape(2, 4)
+        b = np.broadcast_to(1., (4, 1))
+        ret1 = func(a, b)
+        ret2 = func(a, b.copy())
+        assert_equal(ret1, ret2)
+
+        ret1 = func(b.T, a.T)
+        ret2 = func(b.T.copy(), a.T)
+        assert_equal(ret1, ret2)
+
+        # check for unaligned data
+        dt = np.dtype(dtype)
+        a = np.zeros(8 * dt.itemsize // 2 + 1, dtype='int16')[1:].view(dtype)
+        a = a.reshape(2, 4)
+        b = a[0]
+        # make sure it is not aligned
+        assert_(a.__array_interface__['data'][0] % dt.itemsize != 0)
+        ret1 = func(a, b)
+        ret2 = func(a.copy(), b.copy())
+        assert_equal(ret1, ret2)
+
+        ret1 = func(b.T, a.T)
+        ret2 = func(b.T.copy(), a.T.copy())
+        assert_equal(ret1, ret2)
+
+    def test_dot(self):
+        a = np.array([[1, 0], [0, 1]])
+        b = np.array([[0, 1], [1, 0]])
+        c = np.array([[9, 1], [1, -9]])
+        # function versus methods
+        assert_equal(np.dot(a, b), a.dot(b))
+        assert_equal(np.dot(np.dot(a, b), c), a.dot(b).dot(c))
+
+        # test passing in an output array
+        c = np.zeros_like(a)
+        a.dot(b, c)
+        assert_equal(c, np.dot(a, b))
+
+        # test keyword args
+        c = np.zeros_like(a)
+        a.dot(b=b, out=c)
+        assert_equal(c, np.dot(a, b))
+
+    def test_dot_type_mismatch(self):
+        c = 1.
+        A = np.array((1,1), dtype='i,i')
+
+        assert_raises(TypeError, np.dot, c, A)
+        assert_raises(TypeError, np.dot, A, c)
+
+    def test_dot_out_mem_overlap(self):
+        np.random.seed(1)
+
+        # Test BLAS and non-BLAS code paths, including all dtypes
+        # that dot() supports
+        dtypes = [np.dtype(code) for code in np.typecodes['All']
+                  if code not in 'USVM']
+        for dtype in dtypes:
+            a = np.random.rand(3, 3).astype(dtype)
+
+            # Valid dot() output arrays must be aligned
+            b = _aligned_zeros((3, 3), dtype=dtype)
+            b[...] = np.random.rand(3, 3)
+
+            y = np.dot(a, b)
+            x = np.dot(a, b, out=b)
+            assert_equal(x, y, err_msg=repr(dtype))
+
+            # Check invalid output array
+            assert_raises(ValueError, np.dot, a, b, out=b[::2])
+            assert_raises(ValueError, np.dot, a, b, out=b.T)
+
+    def test_dot_matmul_out(self):
+        # gh-9641
+        class Sub(np.ndarray):
+            pass
+        a = np.ones((2, 2)).view(Sub)
+        b = np.ones((2, 2)).view(Sub)
+        out = np.ones((2, 2))
+
+        # make sure out can be any ndarray (not only subclass of inputs)
+        np.dot(a, b, out=out)
+        np.matmul(a, b, out=out)
+
+    def test_dot_matmul_inner_array_casting_fails(self):
+
+        class A(object):
+            def __array__(self, *args, **kwargs):
+                raise NotImplementedError
+
+        # Don't override the error from calling __array__()
+        assert_raises(NotImplementedError, np.dot, A(), A())
+        assert_raises(NotImplementedError, np.matmul, A(), A())
+        assert_raises(NotImplementedError, np.inner, A(), A())
+
+    def test_matmul_out(self):
+        # overlapping memory
+        a = np.arange(18).reshape(2, 3, 3)
+        b = np.matmul(a, a)
+        c = np.matmul(a, a, out=a)
+        assert_(c is a)
+        assert_equal(c, b)
+        a = np.arange(18).reshape(2, 3, 3)
+        c = np.matmul(a, a, out=a[::-1, ...])
+        assert_(c.base is a.base)
+        assert_equal(c, b)
+
+    def test_diagonal(self):
+        a = np.arange(12).reshape((3, 4))
+        assert_equal(a.diagonal(), [0, 5, 10])
+        assert_equal(a.diagonal(0), [0, 5, 10])
+        assert_equal(a.diagonal(1), [1, 6, 11])
+        assert_equal(a.diagonal(-1), [4, 9])
+        assert_raises(np.AxisError, a.diagonal, axis1=0, axis2=5)
+        assert_raises(np.AxisError, a.diagonal, axis1=5, axis2=0)
+        assert_raises(np.AxisError, a.diagonal, axis1=5, axis2=5)
+        assert_raises(ValueError, a.diagonal, axis1=1, axis2=1)
+
+        b = np.arange(8).reshape((2, 2, 2))
+        assert_equal(b.diagonal(), [[0, 6], [1, 7]])
+        assert_equal(b.diagonal(0), [[0, 6], [1, 7]])
+        assert_equal(b.diagonal(1), [[2], [3]])
+        assert_equal(b.diagonal(-1), [[4], [5]])
+        assert_raises(ValueError, b.diagonal, axis1=0, axis2=0)
+        assert_equal(b.diagonal(0, 1, 2), [[0, 3], [4, 7]])
+        assert_equal(b.diagonal(0, 0, 1), [[0, 6], [1, 7]])
+        assert_equal(b.diagonal(offset=1, axis1=0, axis2=2), [[1], [3]])
+        # Order of axis argument doesn't matter:
+        assert_equal(b.diagonal(0, 2, 1), [[0, 3], [4, 7]])
+
+    def test_diagonal_view_notwriteable(self):
+        # this test is only for 1.9, the diagonal view will be
+        # writeable in 1.10.
+        a = np.eye(3).diagonal()
+        assert_(not a.flags.writeable)
+        assert_(not a.flags.owndata)
+
+        a = np.diagonal(np.eye(3))
+        assert_(not a.flags.writeable)
+        assert_(not a.flags.owndata)
+
+        a = np.diag(np.eye(3))
+        assert_(not a.flags.writeable)
+        assert_(not a.flags.owndata)
+
+    def test_diagonal_memleak(self):
+        # Regression test for a bug that crept in at one point
+        a = np.zeros((100, 100))
+        if HAS_REFCOUNT:
+            assert_(sys.getrefcount(a) < 50)
+        for i in range(100):
+            a.diagonal()
+        if HAS_REFCOUNT:
+            assert_(sys.getrefcount(a) < 50)
+
+    def test_size_zero_memleak(self):
+        # Regression test for issue 9615
+        # Exercises a special-case code path for dot products of length
+        # zero in cblasfuncs (making it is specific to floating dtypes).
+        a = np.array([], dtype=np.float64)
+        x = np.array(2.0)
+        for _ in range(100):
+            np.dot(a, a, out=x)
+        if HAS_REFCOUNT:
+            assert_(sys.getrefcount(x) < 50)
+
+    def test_trace(self):
+        a = np.arange(12).reshape((3, 4))
+        assert_equal(a.trace(), 15)
+        assert_equal(a.trace(0), 15)
+        assert_equal(a.trace(1), 18)
+        assert_equal(a.trace(-1), 13)
+
+        b = np.arange(8).reshape((2, 2, 2))
+        assert_equal(b.trace(), [6, 8])
+        assert_equal(b.trace(0), [6, 8])
+        assert_equal(b.trace(1), [2, 3])
+        assert_equal(b.trace(-1), [4, 5])
+        assert_equal(b.trace(0, 0, 1), [6, 8])
+        assert_equal(b.trace(0, 0, 2), [5, 9])
+        assert_equal(b.trace(0, 1, 2), [3, 11])
+        assert_equal(b.trace(offset=1, axis1=0, axis2=2), [1, 3])
+
+    def test_trace_subclass(self):
+        # The class would need to overwrite trace to ensure single-element
+        # output also has the right subclass.
+        class MyArray(np.ndarray):
+            pass
+
+        b = np.arange(8).reshape((2, 2, 2)).view(MyArray)
+        t = b.trace()
+        assert_(isinstance(t, MyArray))
+
+    def test_put(self):
+        icodes = np.typecodes['AllInteger']
+        fcodes = np.typecodes['AllFloat']
+        for dt in icodes + fcodes + 'O':
+            tgt = np.array([0, 1, 0, 3, 0, 5], dtype=dt)
+
+            # test 1-d
+            a = np.zeros(6, dtype=dt)
+            a.put([1, 3, 5], [1, 3, 5])
+            assert_equal(a, tgt)
+
+            # test 2-d
+            a = np.zeros((2, 3), dtype=dt)
+            a.put([1, 3, 5], [1, 3, 5])
+            assert_equal(a, tgt.reshape(2, 3))
+
+        for dt in '?':
+            tgt = np.array([False, True, False, True, False, True], dtype=dt)
+
+            # test 1-d
+            a = np.zeros(6, dtype=dt)
+            a.put([1, 3, 5], [True]*3)
+            assert_equal(a, tgt)
+
+            # test 2-d
+            a = np.zeros((2, 3), dtype=dt)
+            a.put([1, 3, 5], [True]*3)
+            assert_equal(a, tgt.reshape(2, 3))
+
+        # check must be writeable
+        a = np.zeros(6)
+        a.flags.writeable = False
+        assert_raises(ValueError, a.put, [1, 3, 5], [1, 3, 5])
+
+        # when calling np.put, make sure a
+        # TypeError is raised if the object
+        # isn't an ndarray
+        bad_array = [1, 2, 3]
+        assert_raises(TypeError, np.put, bad_array, [0, 2], 5)
+
+    def test_ravel(self):
+        a = np.array([[0, 1], [2, 3]])
+        assert_equal(a.ravel(), [0, 1, 2, 3])
+        assert_(not a.ravel().flags.owndata)
+        assert_equal(a.ravel('F'), [0, 2, 1, 3])
+        assert_equal(a.ravel(order='C'), [0, 1, 2, 3])
+        assert_equal(a.ravel(order='F'), [0, 2, 1, 3])
+        assert_equal(a.ravel(order='A'), [0, 1, 2, 3])
+        assert_(not a.ravel(order='A').flags.owndata)
+        assert_equal(a.ravel(order='K'), [0, 1, 2, 3])
+        assert_(not a.ravel(order='K').flags.owndata)
+        assert_equal(a.ravel(), a.reshape(-1))
+
+        a = np.array([[0, 1], [2, 3]], order='F')
+        assert_equal(a.ravel(), [0, 1, 2, 3])
+        assert_equal(a.ravel(order='A'), [0, 2, 1, 3])
+        assert_equal(a.ravel(order='K'), [0, 2, 1, 3])
+        assert_(not a.ravel(order='A').flags.owndata)
+        assert_(not a.ravel(order='K').flags.owndata)
+        assert_equal(a.ravel(), a.reshape(-1))
+        assert_equal(a.ravel(order='A'), a.reshape(-1, order='A'))
+
+        a = np.array([[0, 1], [2, 3]])[::-1, :]
+        assert_equal(a.ravel(), [2, 3, 0, 1])
+        assert_equal(a.ravel(order='C'), [2, 3, 0, 1])
+        assert_equal(a.ravel(order='F'), [2, 0, 3, 1])
+        assert_equal(a.ravel(order='A'), [2, 3, 0, 1])
+        # 'K' doesn't reverse the axes of negative strides
+        assert_equal(a.ravel(order='K'), [2, 3, 0, 1])
+        assert_(a.ravel(order='K').flags.owndata)
+
+        # Test simple 1-d copy behaviour:
+        a = np.arange(10)[::2]
+        assert_(a.ravel('K').flags.owndata)
+        assert_(a.ravel('C').flags.owndata)
+        assert_(a.ravel('F').flags.owndata)
+
+        # Not contiguous and 1-sized axis with non matching stride
+        a = np.arange(2**3 * 2)[::2]
+        a = a.reshape(2, 1, 2, 2).swapaxes(-1, -2)
+        strides = list(a.strides)
+        strides[1] = 123
+        a.strides = strides
+        assert_(a.ravel(order='K').flags.owndata)
+        assert_equal(a.ravel('K'), np.arange(0, 15, 2))
+
+        # contiguous and 1-sized axis with non matching stride works:
+        a = np.arange(2**3)
+        a = a.reshape(2, 1, 2, 2).swapaxes(-1, -2)
+        strides = list(a.strides)
+        strides[1] = 123
+        a.strides = strides
+        assert_(np.may_share_memory(a.ravel(order='K'), a))
+        assert_equal(a.ravel(order='K'), np.arange(2**3))
+
+        # Test negative strides (not very interesting since non-contiguous):
+        a = np.arange(4)[::-1].reshape(2, 2)
+        assert_(a.ravel(order='C').flags.owndata)
+        assert_(a.ravel(order='K').flags.owndata)
+        assert_equal(a.ravel('C'), [3, 2, 1, 0])
+        assert_equal(a.ravel('K'), [3, 2, 1, 0])
+
+        # 1-element tidy strides test (NPY_RELAXED_STRIDES_CHECKING):
+        a = np.array([[1]])
+        a.strides = (123, 432)
+        # If the stride is not 8, NPY_RELAXED_STRIDES_CHECKING is messing
+        # them up on purpose:
+        if np.ones(1).strides == (8,):
+            assert_(np.may_share_memory(a.ravel('K'), a))
+            assert_equal(a.ravel('K').strides, (a.dtype.itemsize,))
+
+        for order in ('C', 'F', 'A', 'K'):
+            # 0-d corner case:
+            a = np.array(0)
+            assert_equal(a.ravel(order), [0])
+            assert_(np.may_share_memory(a.ravel(order), a))
+
+        # Test that certain non-inplace ravels work right (mostly) for 'K':
+        b = np.arange(2**4 * 2)[::2].reshape(2, 2, 2, 2)
+        a = b[..., ::2]
+        assert_equal(a.ravel('K'), [0, 4, 8, 12, 16, 20, 24, 28])
+        assert_equal(a.ravel('C'), [0, 4, 8, 12, 16, 20, 24, 28])
+        assert_equal(a.ravel('A'), [0, 4, 8, 12, 16, 20, 24, 28])
+        assert_equal(a.ravel('F'), [0, 16, 8, 24, 4, 20, 12, 28])
+
+        a = b[::2, ...]
+        assert_equal(a.ravel('K'), [0, 2, 4, 6, 8, 10, 12, 14])
+        assert_equal(a.ravel('C'), [0, 2, 4, 6, 8, 10, 12, 14])
+        assert_equal(a.ravel('A'), [0, 2, 4, 6, 8, 10, 12, 14])
+        assert_equal(a.ravel('F'), [0, 8, 4, 12, 2, 10, 6, 14])
+
+    def test_ravel_subclass(self):
+        class ArraySubclass(np.ndarray):
+            pass
+
+        a = np.arange(10).view(ArraySubclass)
+        assert_(isinstance(a.ravel('C'), ArraySubclass))
+        assert_(isinstance(a.ravel('F'), ArraySubclass))
+        assert_(isinstance(a.ravel('A'), ArraySubclass))
+        assert_(isinstance(a.ravel('K'), ArraySubclass))
+
+        a = np.arange(10)[::2].view(ArraySubclass)
+        assert_(isinstance(a.ravel('C'), ArraySubclass))
+        assert_(isinstance(a.ravel('F'), ArraySubclass))
+        assert_(isinstance(a.ravel('A'), ArraySubclass))
+        assert_(isinstance(a.ravel('K'), ArraySubclass))
+
+    def test_swapaxes(self):
+        a = np.arange(1*2*3*4).reshape(1, 2, 3, 4).copy()
+        idx = np.indices(a.shape)
+        assert_(a.flags['OWNDATA'])
+        b = a.copy()
+        # check exceptions
+        assert_raises(np.AxisError, a.swapaxes, -5, 0)
+        assert_raises(np.AxisError, a.swapaxes, 4, 0)
+        assert_raises(np.AxisError, a.swapaxes, 0, -5)
+        assert_raises(np.AxisError, a.swapaxes, 0, 4)
+
+        for i in range(-4, 4):
+            for j in range(-4, 4):
+                for k, src in enumerate((a, b)):
+                    c = src.swapaxes(i, j)
+                    # check shape
+                    shape = list(src.shape)
+                    shape[i] = src.shape[j]
+                    shape[j] = src.shape[i]
+                    assert_equal(c.shape, shape, str((i, j, k)))
+                    # check array contents
+                    i0, i1, i2, i3 = [dim-1 for dim in c.shape]
+                    j0, j1, j2, j3 = [dim-1 for dim in src.shape]
+                    assert_equal(src[idx[j0], idx[j1], idx[j2], idx[j3]],
+                                 c[idx[i0], idx[i1], idx[i2], idx[i3]],
+                                 str((i, j, k)))
+                    # check a view is always returned, gh-5260
+                    assert_(not c.flags['OWNDATA'], str((i, j, k)))
+                    # check on non-contiguous input array
+                    if k == 1:
+                        b = c
+
+    def test_conjugate(self):
+        a = np.array([1-1j, 1+1j, 23+23.0j])
+        ac = a.conj()
+        assert_equal(a.real, ac.real)
+        assert_equal(a.imag, -ac.imag)
+        assert_equal(ac, a.conjugate())
+        assert_equal(ac, np.conjugate(a))
+
+        a = np.array([1-1j, 1+1j, 23+23.0j], 'F')
+        ac = a.conj()
+        assert_equal(a.real, ac.real)
+        assert_equal(a.imag, -ac.imag)
+        assert_equal(ac, a.conjugate())
+        assert_equal(ac, np.conjugate(a))
+
+        a = np.array([1, 2, 3])
+        ac = a.conj()
+        assert_equal(a, ac)
+        assert_equal(ac, a.conjugate())
+        assert_equal(ac, np.conjugate(a))
+
+        a = np.array([1.0, 2.0, 3.0])
+        ac = a.conj()
+        assert_equal(a, ac)
+        assert_equal(ac, a.conjugate())
+        assert_equal(ac, np.conjugate(a))
+
+        a = np.array([1-1j, 1+1j, 1, 2.0], object)
+        ac = a.conj()
+        assert_equal(ac, [k.conjugate() for k in a])
+        assert_equal(ac, a.conjugate())
+        assert_equal(ac, np.conjugate(a))
+
+        a = np.array([1-1j, 1, 2.0, 'f'], object)
+        assert_raises(AttributeError, lambda: a.conj())
+        assert_raises(AttributeError, lambda: a.conjugate())
+
+    def test__complex__(self):
+        dtypes = ['i1', 'i2', 'i4', 'i8',
+                  'u1', 'u2', 'u4', 'u8',
+                  'f', 'd', 'g', 'F', 'D', 'G',
+                  '?', 'O']
+        for dt in dtypes:
+            a = np.array(7, dtype=dt)
+            b = np.array([7], dtype=dt)
+            c = np.array([[[[[7]]]]], dtype=dt)
+
+            msg = 'dtype: {0}'.format(dt)
+            ap = complex(a)
+            assert_equal(ap, a, msg)
+            bp = complex(b)
+            assert_equal(bp, b, msg)
+            cp = complex(c)
+            assert_equal(cp, c, msg)
+
+    def test__complex__should_not_work(self):
+        dtypes = ['i1', 'i2', 'i4', 'i8',
+                  'u1', 'u2', 'u4', 'u8',
+                  'f', 'd', 'g', 'F', 'D', 'G',
+                  '?', 'O']
+        for dt in dtypes:
+            a = np.array([1, 2, 3], dtype=dt)
+            assert_raises(TypeError, complex, a)
+
+        dt = np.dtype([('a', 'f8'), ('b', 'i1')])
+        b = np.array((1.0, 3), dtype=dt)
+        assert_raises(TypeError, complex, b)
+
+        c = np.array([(1.0, 3), (2e-3, 7)], dtype=dt)
+        assert_raises(TypeError, complex, c)
+
+        d = np.array('1+1j')
+        assert_raises(TypeError, complex, d)
+
+        e = np.array(['1+1j'], 'U')
+        assert_raises(TypeError, complex, e)
+
+class TestCequenceMethods(object):
+    def test_array_contains(self):
+        assert_(4.0 in np.arange(16.).reshape(4,4))
+        assert_(20.0 not in np.arange(16.).reshape(4,4))
+
+class TestBinop(object):
+    def test_inplace(self):
+        # test refcount 1 inplace conversion
+        assert_array_almost_equal(np.array([0.5]) * np.array([1.0, 2.0]),
+                                  [0.5, 1.0])
+
+        d = np.array([0.5, 0.5])[::2]
+        assert_array_almost_equal(d * (d * np.array([1.0, 2.0])),
+                                  [0.25, 0.5])
+
+        a = np.array([0.5])
+        b = np.array([0.5])
+        c = a + b
+        c = a - b
+        c = a * b
+        c = a / b
+        assert_equal(a, b)
+        assert_almost_equal(c, 1.)
+
+        c = a + b * 2. / b * a - a / b
+        assert_equal(a, b)
+        assert_equal(c, 0.5)
+
+        # true divide
+        a = np.array([5])
+        b = np.array([3])
+        c = (a * a) / b
+
+        assert_almost_equal(c, 25 / 3)
+        assert_equal(a, 5)
+        assert_equal(b, 3)
+
+    # ndarray.__rop__ always calls ufunc
+    # ndarray.__iop__ always calls ufunc
+    # ndarray.__op__, __rop__:
+    #   - defer if other has __array_ufunc__ and it is None
+    #           or other is not a subclass and has higher array priority
+    #   - else, call ufunc
+    def test_ufunc_binop_interaction(self):
+        # Python method name (without underscores)
+        #   -> (numpy ufunc, has_in_place_version, preferred_dtype)
+        ops = {
+            'add':      (np.add, True, float),
+            'sub':      (np.subtract, True, float),
+            'mul':      (np.multiply, True, float),
+            'truediv':  (np.true_divide, True, float),
+            'floordiv': (np.floor_divide, True, float),
+            'mod':      (np.remainder, True, float),
+            'divmod':   (np.divmod, False, float),
+            'pow':      (np.power, True, int),
+            'lshift':   (np.left_shift, True, int),
+            'rshift':   (np.right_shift, True, int),
+            'and':      (np.bitwise_and, True, int),
+            'xor':      (np.bitwise_xor, True, int),
+            'or':       (np.bitwise_or, True, int),
+            # 'ge':       (np.less_equal, False),
+            # 'gt':       (np.less, False),
+            # 'le':       (np.greater_equal, False),
+            # 'lt':       (np.greater, False),
+            # 'eq':       (np.equal, False),
+            # 'ne':       (np.not_equal, False),
+        }
+        if sys.version_info >= (3, 5):
+            ops['matmul'] = (np.matmul, False, float)
+
+        class Coerced(Exception):
+            pass
+
+        def array_impl(self):
+            raise Coerced
+
+        def op_impl(self, other):
+            return "forward"
+
+        def rop_impl(self, other):
+            return "reverse"
+
+        def iop_impl(self, other):
+            return "in-place"
+
+        def array_ufunc_impl(self, ufunc, method, *args, **kwargs):
+            return ("__array_ufunc__", ufunc, method, args, kwargs)
+
+        # Create an object with the given base, in the given module, with a
+        # bunch of placeholder __op__ methods, and optionally a
+        # __array_ufunc__ and __array_priority__.
+        def make_obj(base, array_priority=False, array_ufunc=False,
+                     alleged_module="__main__"):
+            class_namespace = {"__array__": array_impl}
+            if array_priority is not False:
+                class_namespace["__array_priority__"] = array_priority
+            for op in ops:
+                class_namespace["__{0}__".format(op)] = op_impl
+                class_namespace["__r{0}__".format(op)] = rop_impl
+                class_namespace["__i{0}__".format(op)] = iop_impl
+            if array_ufunc is not False:
+                class_namespace["__array_ufunc__"] = array_ufunc
+            eval_namespace = {"base": base,
+                              "class_namespace": class_namespace,
+                              "__name__": alleged_module,
+                              }
+            MyType = eval("type('MyType', (base,), class_namespace)",
+                          eval_namespace)
+            if issubclass(MyType, np.ndarray):
+                # Use this range to avoid special case weirdnesses around
+                # divide-by-0, pow(x, 2), overflow due to pow(big, big), etc.
+                return np.arange(3, 7).reshape(2, 2).view(MyType)
+            else:
+                return MyType()
+
+        def check(obj, binop_override_expected, ufunc_override_expected,
+                  inplace_override_expected, check_scalar=True):
+            for op, (ufunc, has_inplace, dtype) in ops.items():
+                err_msg = ('op: %s, ufunc: %s, has_inplace: %s, dtype: %s'
+                           % (op, ufunc, has_inplace, dtype))
+                check_objs = [np.arange(3, 7, dtype=dtype).reshape(2, 2)]
+                if check_scalar:
+                    check_objs.append(check_objs[0][0])
+                for arr in check_objs:
+                    arr_method = getattr(arr, "__{0}__".format(op))
+
+                    def first_out_arg(result):
+                        if op == "divmod":
+                            assert_(isinstance(result, tuple))
+                            return result[0]
+                        else:
+                            return result
+
+                    # arr __op__ obj
+                    if binop_override_expected:
+                        assert_equal(arr_method(obj), NotImplemented, err_msg)
+                    elif ufunc_override_expected:
+                        assert_equal(arr_method(obj)[0], "__array_ufunc__",
+                                     err_msg)
+                    else:
+                        if (isinstance(obj, np.ndarray) and
+                            (type(obj).__array_ufunc__ is
+                             np.ndarray.__array_ufunc__)):
+                            # __array__ gets ignored
+                            res = first_out_arg(arr_method(obj))
+                            assert_(res.__class__ is obj.__class__, err_msg)
+                        else:
+                            assert_raises((TypeError, Coerced),
+                                          arr_method, obj, err_msg=err_msg)
+                    # obj __op__ arr
+                    arr_rmethod = getattr(arr, "__r{0}__".format(op))
+                    if ufunc_override_expected:
+                        res = arr_rmethod(obj)
+                        assert_equal(res[0], "__array_ufunc__",
+                                     err_msg=err_msg)
+                        assert_equal(res[1], ufunc, err_msg=err_msg)
+                    else:
+                        if (isinstance(obj, np.ndarray) and
+                                (type(obj).__array_ufunc__ is
+                                 np.ndarray.__array_ufunc__)):
+                            # __array__ gets ignored
+                            res = first_out_arg(arr_rmethod(obj))
+                            assert_(res.__class__ is obj.__class__, err_msg)
+                        else:
+                            # __array_ufunc__ = "asdf" creates a TypeError
+                            assert_raises((TypeError, Coerced),
+                                          arr_rmethod, obj, err_msg=err_msg)
+
+                    # arr __iop__ obj
+                    # array scalars don't have in-place operators
+                    if has_inplace and isinstance(arr, np.ndarray):
+                        arr_imethod = getattr(arr, "__i{0}__".format(op))
+                        if inplace_override_expected:
+                            assert_equal(arr_method(obj), NotImplemented,
+                                         err_msg=err_msg)
+                        elif ufunc_override_expected:
+                            res = arr_imethod(obj)
+                            assert_equal(res[0], "__array_ufunc__", err_msg)
+                            assert_equal(res[1], ufunc, err_msg)
+                            assert_(type(res[-1]["out"]) is tuple, err_msg)
+                            assert_(res[-1]["out"][0] is arr, err_msg)
+                        else:
+                            if (isinstance(obj, np.ndarray) and
+                                    (type(obj).__array_ufunc__ is
+                                    np.ndarray.__array_ufunc__)):
+                                # __array__ gets ignored
+                                assert_(arr_imethod(obj) is arr, err_msg)
+                            else:
+                                assert_raises((TypeError, Coerced),
+                                              arr_imethod, obj,
+                                              err_msg=err_msg)
+
+                    op_fn = getattr(operator, op, None)
+                    if op_fn is None:
+                        op_fn = getattr(operator, op + "_", None)
+                    if op_fn is None:
+                        op_fn = getattr(builtins, op)
+                    assert_equal(op_fn(obj, arr), "forward", err_msg)
+                    if not isinstance(obj, np.ndarray):
+                        if binop_override_expected:
+                            assert_equal(op_fn(arr, obj), "reverse", err_msg)
+                        elif ufunc_override_expected:
+                            assert_equal(op_fn(arr, obj)[0], "__array_ufunc__",
+                                         err_msg)
+                    if ufunc_override_expected:
+                        assert_equal(ufunc(obj, arr)[0], "__array_ufunc__",
+                                     err_msg)
+
+        # No array priority, no array_ufunc -> nothing called
+        check(make_obj(object), False, False, False)
+        # Negative array priority, no array_ufunc -> nothing called
+        # (has to be very negative, because scalar priority is -1000000.0)
+        check(make_obj(object, array_priority=-2**30), False, False, False)
+        # Positive array priority, no array_ufunc -> binops and iops only
+        check(make_obj(object, array_priority=1), True, False, True)
+        # ndarray ignores array_priority for ndarray subclasses
+        check(make_obj(np.ndarray, array_priority=1), False, False, False,
+              check_scalar=False)
+        # Positive array_priority and array_ufunc -> array_ufunc only
+        check(make_obj(object, array_priority=1,
+                       array_ufunc=array_ufunc_impl), False, True, False)
+        check(make_obj(np.ndarray, array_priority=1,
+                       array_ufunc=array_ufunc_impl), False, True, False)
+        # array_ufunc set to None -> defer binops only
+        check(make_obj(object, array_ufunc=None), True, False, False)
+        check(make_obj(np.ndarray, array_ufunc=None), True, False, False,
+              check_scalar=False)
+
+    def test_ufunc_override_normalize_signature(self):
+        # gh-5674
+        class SomeClass(object):
+            def __array_ufunc__(self, ufunc, method, *inputs, **kw):
+                return kw
+
+        a = SomeClass()
+        kw = np.add(a, [1])
+        assert_('sig' not in kw and 'signature' not in kw)
+        kw = np.add(a, [1], sig='ii->i')
+        assert_('sig' not in kw and 'signature' in kw)
+        assert_equal(kw['signature'], 'ii->i')
+        kw = np.add(a, [1], signature='ii->i')
+        assert_('sig' not in kw and 'signature' in kw)
+        assert_equal(kw['signature'], 'ii->i')
+
+    def test_array_ufunc_index(self):
+        # Check that index is set appropriately, also if only an output
+        # is passed on (latter is another regression tests for github bug 4753)
+        # This also checks implicitly that 'out' is always a tuple.
+        class CheckIndex(object):
+            def __array_ufunc__(self, ufunc, method, *inputs, **kw):
+                for i, a in enumerate(inputs):
+                    if a is self:
+                        return i
+                # calls below mean we must be in an output.
+                for j, a in enumerate(kw['out']):
+                    if a is self:
+                        return (j,)
+
+        a = CheckIndex()
+        dummy = np.arange(2.)
+        # 1 input, 1 output
+        assert_equal(np.sin(a), 0)
+        assert_equal(np.sin(dummy, a), (0,))
+        assert_equal(np.sin(dummy, out=a), (0,))
+        assert_equal(np.sin(dummy, out=(a,)), (0,))
+        assert_equal(np.sin(a, a), 0)
+        assert_equal(np.sin(a, out=a), 0)
+        assert_equal(np.sin(a, out=(a,)), 0)
+        # 1 input, 2 outputs
+        assert_equal(np.modf(dummy, a), (0,))
+        assert_equal(np.modf(dummy, None, a), (1,))
+        assert_equal(np.modf(dummy, dummy, a), (1,))
+        assert_equal(np.modf(dummy, out=(a, None)), (0,))
+        assert_equal(np.modf(dummy, out=(a, dummy)), (0,))
+        assert_equal(np.modf(dummy, out=(None, a)), (1,))
+        assert_equal(np.modf(dummy, out=(dummy, a)), (1,))
+        assert_equal(np.modf(a, out=(dummy, a)), 0)
+        with warnings.catch_warnings(record=True) as w:
+            warnings.filterwarnings('always', '', DeprecationWarning)
+            assert_equal(np.modf(dummy, out=a), (0,))
+            assert_(w[0].category is DeprecationWarning)
+        assert_raises(ValueError, np.modf, dummy, out=(a,))
+
+        # 2 inputs, 1 output
+        assert_equal(np.add(a, dummy), 0)
+        assert_equal(np.add(dummy, a), 1)
+        assert_equal(np.add(dummy, dummy, a), (0,))
+        assert_equal(np.add(dummy, a, a), 1)
+        assert_equal(np.add(dummy, dummy, out=a), (0,))
+        assert_equal(np.add(dummy, dummy, out=(a,)), (0,))
+        assert_equal(np.add(a, dummy, out=a), 0)
+
+    def test_out_override(self):
+        # regression test for github bug 4753
+        class OutClass(np.ndarray):
+            def __array_ufunc__(self, ufunc, method, *inputs, **kw):
+                if 'out' in kw:
+                    tmp_kw = kw.copy()
+                    tmp_kw.pop('out')
+                    func = getattr(ufunc, method)
+                    kw['out'][0][...] = func(*inputs, **tmp_kw)
+
+        A = np.array([0]).view(OutClass)
+        B = np.array([5])
+        C = np.array([6])
+        np.multiply(C, B, A)
+        assert_equal(A[0], 30)
+        assert_(isinstance(A, OutClass))
+        A[0] = 0
+        np.multiply(C, B, out=A)
+        assert_equal(A[0], 30)
+        assert_(isinstance(A, OutClass))
+
+    def test_pow_override_with_errors(self):
+        # regression test for gh-9112
+        class PowerOnly(np.ndarray):
+            def __array_ufunc__(self, ufunc, method, *inputs, **kw):
+                if ufunc is not np.power:
+                    raise NotImplementedError
+                return "POWER!"
+        # explicit cast to float, to ensure the fast power path is taken.
+        a = np.array(5., dtype=np.float64).view(PowerOnly)
+        assert_equal(a ** 2.5, "POWER!")
+        with assert_raises(NotImplementedError):
+            a ** 0.5
+        with assert_raises(NotImplementedError):
+            a ** 0
+        with assert_raises(NotImplementedError):
+            a ** 1
+        with assert_raises(NotImplementedError):
+            a ** -1
+        with assert_raises(NotImplementedError):
+            a ** 2
+
+    def test_pow_array_object_dtype(self):
+        # test pow on arrays of object dtype
+        class SomeClass(object):
+            def __init__(self, num=None):
+                self.num = num
+
+            # want to ensure a fast pow path is not taken
+            def __mul__(self, other):
+                raise AssertionError('__mul__ should not be called')
+
+            def __div__(self, other):
+                raise AssertionError('__div__ should not be called')
+
+            def __pow__(self, exp):
+                return SomeClass(num=self.num ** exp)
+
+            def __eq__(self, other):
+                if isinstance(other, SomeClass):
+                    return self.num == other.num
+
+            __rpow__ = __pow__
+
+        def pow_for(exp, arr):
+            return np.array([x ** exp for x in arr])
+
+        obj_arr = np.array([SomeClass(1), SomeClass(2), SomeClass(3)])
+
+        assert_equal(obj_arr ** 0.5, pow_for(0.5, obj_arr))
+        assert_equal(obj_arr ** 0, pow_for(0, obj_arr))
+        assert_equal(obj_arr ** 1, pow_for(1, obj_arr))
+        assert_equal(obj_arr ** -1, pow_for(-1, obj_arr))
+        assert_equal(obj_arr ** 2, pow_for(2, obj_arr))
+
+    def test_pos_array_ufunc_override(self):
+        class A(np.ndarray):
+            def __array_ufunc__(self, ufunc, method, *inputs, **kwargs):
+                return getattr(ufunc, method)(*[i.view(np.ndarray) for
+                                                i in inputs], **kwargs)
+        tst = np.array('foo').view(A)
+        with assert_raises(TypeError):
+            +tst
+
+
+class TestTemporaryElide(object):
+    # elision is only triggered on relatively large arrays
+
+    def test_extension_incref_elide(self):
+        # test extension (e.g. cython) calling PyNumber_* slots without
+        # increasing the reference counts
+        #
+        # def incref_elide(a):
+        #    d = input.copy() # refcount 1
+        #    return d, d + d # PyNumber_Add without increasing refcount
+        from numpy.core._multiarray_tests import incref_elide
+        d = np.ones(100000)
+        orig, res = incref_elide(d)
+        d + d
+        # the return original should not be changed to an inplace operation
+        assert_array_equal(orig, d)
+        assert_array_equal(res, d + d)
+
+    def test_extension_incref_elide_stack(self):
+        # scanning if the refcount == 1 object is on the python stack to check
+        # that we are called directly from python is flawed as object may still
+        # be above the stack pointer and we have no access to the top of it
+        #
+        # def incref_elide_l(d):
+        #    return l[4] + l[4] # PyNumber_Add without increasing refcount
+        from numpy.core._multiarray_tests import incref_elide_l
+        # padding with 1 makes sure the object on the stack is not overwritten
+        l = [1, 1, 1, 1, np.ones(100000)]
+        res = incref_elide_l(l)
+        # the return original should not be changed to an inplace operation
+        assert_array_equal(l[4], np.ones(100000))
+        assert_array_equal(res, l[4] + l[4])
+
+    def test_temporary_with_cast(self):
+        # check that we don't elide into a temporary which would need casting
+        d = np.ones(200000, dtype=np.int64)
+        assert_equal(((d + d) + 2**222).dtype, np.dtype('O'))
+
+        r = ((d + d) / 2)
+        assert_equal(r.dtype, np.dtype('f8'))
+
+        r = np.true_divide((d + d), 2)
+        assert_equal(r.dtype, np.dtype('f8'))
+
+        r = ((d + d) / 2.)
+        assert_equal(r.dtype, np.dtype('f8'))
+
+        r = ((d + d) // 2)
+        assert_equal(r.dtype, np.dtype(np.int64))
+
+        # commutative elision into the astype result
+        f = np.ones(100000, dtype=np.float32)
+        assert_equal(((f + f) + f.astype(np.float64)).dtype, np.dtype('f8'))
+
+        # no elision into lower type
+        d = f.astype(np.float64)
+        assert_equal(((f + f) + d).dtype, d.dtype)
+        l = np.ones(100000, dtype=np.longdouble)
+        assert_equal(((d + d) + l).dtype, l.dtype)
+
+        # test unary abs with different output dtype
+        for dt in (np.complex64, np.complex128, np.clongdouble):
+            c = np.ones(100000, dtype=dt)
+            r = abs(c * 2.0)
+            assert_equal(r.dtype, np.dtype('f%d' % (c.itemsize // 2)))
+
+    def test_elide_broadcast(self):
+        # test no elision on broadcast to higher dimension
+        # only triggers elision code path in debug mode as triggering it in
+        # normal mode needs 256kb large matching dimension, so a lot of memory
+        d = np.ones((2000, 1), dtype=int)
+        b = np.ones((2000), dtype=bool)
+        r = (1 - d) + b
+        assert_equal(r, 1)
+        assert_equal(r.shape, (2000, 2000))
+
+    def test_elide_scalar(self):
+        # check inplace op does not create ndarray from scalars
+        a = np.bool_()
+        assert_(type(~(a & a)) is np.bool_)
+
+    def test_elide_scalar_readonly(self):
+        # The imaginary part of a real array is readonly. This needs to go
+        # through fast_scalar_power which is only called for powers of
+        # +1, -1, 0, 0.5, and 2, so use 2. Also need valid refcount for
+        # elision which can be gotten for the imaginary part of a real
+        # array. Should not error.
+        a = np.empty(100000, dtype=np.float64)
+        a.imag ** 2
+
+    def test_elide_readonly(self):
+        # don't try to elide readonly temporaries
+        r = np.asarray(np.broadcast_to(np.zeros(1), 100000).flat) * 0.0
+        assert_equal(r, 0)
+
+    def test_elide_updateifcopy(self):
+        a = np.ones(2**20)[::2]
+        b = a.flat.__array__() + 1
+        del b
+        assert_equal(a, 1)
+
+
+class TestCAPI(object):
+    def test_IsPythonScalar(self):
+        from numpy.core._multiarray_tests import IsPythonScalar
+        assert_(IsPythonScalar(b'foobar'))
+        assert_(IsPythonScalar(1))
+        assert_(IsPythonScalar(2**80))
+        assert_(IsPythonScalar(2.))
+        assert_(IsPythonScalar("a"))
+
+
+class TestSubscripting(object):
+    def test_test_zero_rank(self):
+        x = np.array([1, 2, 3])
+        assert_(isinstance(x[0], np.int_))
+        if sys.version_info[0] < 3:
+            assert_(isinstance(x[0], int))
+        assert_(type(x[0, ...]) is np.ndarray)
+
+
+class TestPickling(object):
+    def test_highest_available_pickle_protocol(self):
+        try:
+            import pickle5
+        except ImportError:
+            pickle5 = None
+
+        if sys.version_info[:2] >= (3, 8) or pickle5 is not None:
+            assert pickle.HIGHEST_PROTOCOL >= 5
+        else:
+            assert pickle.HIGHEST_PROTOCOL < 5
+
+    @pytest.mark.skipif(pickle.HIGHEST_PROTOCOL >= 5,
+                        reason=('this tests the error messages when trying to'
+                                'protocol 5 although it is not available'))
+    def test_correct_protocol5_error_message(self):
+        array = np.arange(10)
+
+        if sys.version_info[:2] in ((3, 6), (3, 7)):
+            # For the specific case of python3.6 and 3.7, raise a clear import
+            # error about the pickle5 backport when trying to use protocol=5
+            # without the pickle5 package
+            with pytest.raises(ImportError):
+                array.__reduce_ex__(5)
+
+        elif sys.version_info[:2] < (3, 6):
+            # when calling __reduce_ex__ explicitly with protocol=5 on python
+            # raise a ValueError saying that protocol 5 is not available for
+            # this python version
+            with pytest.raises(ValueError):
+                array.__reduce_ex__(5)
+
+    def test_record_array_with_object_dtype(self):
+        my_object = object()
+
+        arr_with_object = np.array(
+                [(my_object, 1, 2.0)],
+                dtype=[('a', object), ('b', int), ('c', float)])
+        arr_without_object = np.array(
+                [('xxx', 1, 2.0)],
+                dtype=[('a', str), ('b', int), ('c', float)])
+
+        for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
+            depickled_arr_with_object = pickle.loads(
+                    pickle.dumps(arr_with_object, protocol=proto))
+            depickled_arr_without_object = pickle.loads(
+                    pickle.dumps(arr_without_object, protocol=proto))
+
+            assert_equal(arr_with_object.dtype,
+                         depickled_arr_with_object.dtype)
+            assert_equal(arr_without_object.dtype,
+                         depickled_arr_without_object.dtype)
+
+    @pytest.mark.skipif(pickle.HIGHEST_PROTOCOL < 5,
+                        reason="requires pickle protocol 5")
+    def test_f_contiguous_array(self):
+        f_contiguous_array = np.array([[1, 2, 3], [4, 5, 6]], order='F')
+        buffers = []
+
+        # When using pickle protocol 5, Fortran-contiguous arrays can be
+        # serialized using out-of-band buffers
+        bytes_string = pickle.dumps(f_contiguous_array, protocol=5,
+                                    buffer_callback=buffers.append)
+
+        assert len(buffers) > 0
+
+        depickled_f_contiguous_array = pickle.loads(bytes_string,
+                                                    buffers=buffers)
+
+        assert_equal(f_contiguous_array, depickled_f_contiguous_array)
+
+    def test_non_contiguous_array(self):
+        non_contiguous_array = np.arange(12).reshape(3, 4)[:, :2]
+        assert not non_contiguous_array.flags.c_contiguous
+        assert not non_contiguous_array.flags.f_contiguous
+
+        # make sure non-contiguous arrays can be pickled-depickled
+        # using any protocol
+        for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
+            depickled_non_contiguous_array = pickle.loads(
+                    pickle.dumps(non_contiguous_array, protocol=proto))
+
+            assert_equal(non_contiguous_array, depickled_non_contiguous_array)
+
+    def test_roundtrip(self):
+        for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
+            carray = np.array([[2, 9], [7, 0], [3, 8]])
+            DATA = [
+                carray,
+                np.transpose(carray),
+                np.array([('xxx', 1, 2.0)], dtype=[('a', (str, 3)), ('b', int),
+                                                   ('c', float)])
+            ]
+
+            refs = [weakref.ref(a) for a in DATA]
+            for a in DATA:
+                assert_equal(
+                        a, pickle.loads(pickle.dumps(a, protocol=proto)),
+                        err_msg="%r" % a)
+            del a, DATA, carray
+            gc.collect()
+            # check for reference leaks (gh-12793)
+            for ref in refs:
+                assert ref() is None
+
+    def _loads(self, obj):
+        if sys.version_info[0] >= 3:
+            return pickle.loads(obj, encoding='latin1')
+        else:
+            return pickle.loads(obj)
+
+    # version 0 pickles, using protocol=2 to pickle
+    # version 0 doesn't have a version field
+    def test_version0_int8(self):
+        s = b'\x80\x02cnumpy.core._internal\n_reconstruct\nq\x01cnumpy\nndarray\nq\x02K\x00\x85U\x01b\x87Rq\x03(K\x04\x85cnumpy\ndtype\nq\x04U\x02i1K\x00K\x01\x87Rq\x05(U\x01|NNJ\xff\xff\xff\xffJ\xff\xff\xff\xfftb\x89U\x04\x01\x02\x03\x04tb.'
+        a = np.array([1, 2, 3, 4], dtype=np.int8)
+        p = self._loads(s)
+        assert_equal(a, p)
+
+    def test_version0_float32(self):
+        s = b'\x80\x02cnumpy.core._internal\n_reconstruct\nq\x01cnumpy\nndarray\nq\x02K\x00\x85U\x01b\x87Rq\x03(K\x04\x85cnumpy\ndtype\nq\x04U\x02f4K\x00K\x01\x87Rq\x05(U\x01<NNJ\xff\xff\xff\xffJ\xff\xff\xff\xfftb\x89U\x10\x00\x00\x80?\x00\x00\x00@\x00\x00@@\x00\x00\x80@tb.'
+        a = np.array([1.0, 2.0, 3.0, 4.0], dtype=np.float32)
+        p = self._loads(s)
+        assert_equal(a, p)
+
+    def test_version0_object(self):
+        s = b'\x80\x02cnumpy.core._internal\n_reconstruct\nq\x01cnumpy\nndarray\nq\x02K\x00\x85U\x01b\x87Rq\x03(K\x02\x85cnumpy\ndtype\nq\x04U\x02O8K\x00K\x01\x87Rq\x05(U\x01|NNJ\xff\xff\xff\xffJ\xff\xff\xff\xfftb\x89]q\x06(}q\x07U\x01aK\x01s}q\x08U\x01bK\x02setb.'
+        a = np.array([{'a': 1}, {'b': 2}])
+        p = self._loads(s)
+        assert_equal(a, p)
+
+    # version 1 pickles, using protocol=2 to pickle
+    def test_version1_int8(self):
+        s = b'\x80\x02cnumpy.core._internal\n_reconstruct\nq\x01cnumpy\nndarray\nq\x02K\x00\x85U\x01b\x87Rq\x03(K\x01K\x04\x85cnumpy\ndtype\nq\x04U\x02i1K\x00K\x01\x87Rq\x05(K\x01U\x01|NNJ\xff\xff\xff\xffJ\xff\xff\xff\xfftb\x89U\x04\x01\x02\x03\x04tb.'
+        a = np.array([1, 2, 3, 4], dtype=np.int8)
+        p = self._loads(s)
+        assert_equal(a, p)
+
+    def test_version1_float32(self):
+        s = b'\x80\x02cnumpy.core._internal\n_reconstruct\nq\x01cnumpy\nndarray\nq\x02K\x00\x85U\x01b\x87Rq\x03(K\x01K\x04\x85cnumpy\ndtype\nq\x04U\x02f4K\x00K\x01\x87Rq\x05(K\x01U\x01<NNJ\xff\xff\xff\xffJ\xff\xff\xff\xfftb\x89U\x10\x00\x00\x80?\x00\x00\x00@\x00\x00@@\x00\x00\x80@tb.'
+        a = np.array([1.0, 2.0, 3.0, 4.0], dtype=np.float32)
+        p = self._loads(s)
+        assert_equal(a, p)
+
+    def test_version1_object(self):
+        s = b'\x80\x02cnumpy.core._internal\n_reconstruct\nq\x01cnumpy\nndarray\nq\x02K\x00\x85U\x01b\x87Rq\x03(K\x01K\x02\x85cnumpy\ndtype\nq\x04U\x02O8K\x00K\x01\x87Rq\x05(K\x01U\x01|NNJ\xff\xff\xff\xffJ\xff\xff\xff\xfftb\x89]q\x06(}q\x07U\x01aK\x01s}q\x08U\x01bK\x02setb.'
+        a = np.array([{'a': 1}, {'b': 2}])
+        p = self._loads(s)
+        assert_equal(a, p)
+
+    def test_subarray_int_shape(self):
+        s = b"cnumpy.core.multiarray\n_reconstruct\np0\n(cnumpy\nndarray\np1\n(I0\ntp2\nS'b'\np3\ntp4\nRp5\n(I1\n(I1\ntp6\ncnumpy\ndtype\np7\n(S'V6'\np8\nI0\nI1\ntp9\nRp10\n(I3\nS'|'\np11\nN(S'a'\np12\ng3\ntp13\n(dp14\ng12\n(g7\n(S'V4'\np15\nI0\nI1\ntp16\nRp17\n(I3\nS'|'\np18\n(g7\n(S'i1'\np19\nI0\nI1\ntp20\nRp21\n(I3\nS'|'\np22\nNNNI-1\nI-1\nI0\ntp23\nb(I2\nI2\ntp24\ntp25\nNNI4\nI1\nI0\ntp26\nbI0\ntp27\nsg3\n(g7\n(S'V2'\np28\nI0\nI1\ntp29\nRp30\n(I3\nS'|'\np31\n(g21\nI2\ntp32\nNNI2\nI1\nI0\ntp33\nbI4\ntp34\nsI6\nI1\nI0\ntp35\nbI00\nS'\\x01\\x01\\x01\\x01\\x01\\x02'\np36\ntp37\nb."
+        a = np.array([(1, (1, 2))], dtype=[('a', 'i1', (2, 2)), ('b', 'i1', 2)])
+        p = self._loads(s)
+        assert_equal(a, p)
+
+
+class TestFancyIndexing(object):
+    def test_list(self):
+        x = np.ones((1, 1))
+        x[:, [0]] = 2.0
+        assert_array_equal(x, np.array([[2.0]]))
+
+        x = np.ones((1, 1, 1))
+        x[:, :, [0]] = 2.0
+        assert_array_equal(x, np.array([[[2.0]]]))
+
+    def test_tuple(self):
+        x = np.ones((1, 1))
+        x[:, (0,)] = 2.0
+        assert_array_equal(x, np.array([[2.0]]))
+        x = np.ones((1, 1, 1))
+        x[:, :, (0,)] = 2.0
+        assert_array_equal(x, np.array([[[2.0]]]))
+
+    def test_mask(self):
+        x = np.array([1, 2, 3, 4])
+        m = np.array([0, 1, 0, 0], bool)
+        assert_array_equal(x[m], np.array([2]))
+
+    def test_mask2(self):
+        x = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
+        m = np.array([0, 1], bool)
+        m2 = np.array([[0, 1, 0, 0], [1, 0, 0, 0]], bool)
+        m3 = np.array([[0, 1, 0, 0], [0, 0, 0, 0]], bool)
+        assert_array_equal(x[m], np.array([[5, 6, 7, 8]]))
+        assert_array_equal(x[m2], np.array([2, 5]))
+        assert_array_equal(x[m3], np.array([2]))
+
+    def test_assign_mask(self):
+        x = np.array([1, 2, 3, 4])
+        m = np.array([0, 1, 0, 0], bool)
+        x[m] = 5
+        assert_array_equal(x, np.array([1, 5, 3, 4]))
+
+    def test_assign_mask2(self):
+        xorig = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
+        m = np.array([0, 1], bool)
+        m2 = np.array([[0, 1, 0, 0], [1, 0, 0, 0]], bool)
+        m3 = np.array([[0, 1, 0, 0], [0, 0, 0, 0]], bool)
+        x = xorig.copy()
+        x[m] = 10
+        assert_array_equal(x, np.array([[1, 2, 3, 4], [10, 10, 10, 10]]))
+        x = xorig.copy()
+        x[m2] = 10
+        assert_array_equal(x, np.array([[1, 10, 3, 4], [10, 6, 7, 8]]))
+        x = xorig.copy()
+        x[m3] = 10
+        assert_array_equal(x, np.array([[1, 10, 3, 4], [5, 6, 7, 8]]))
+
+
+class TestStringCompare(object):
+    def test_string(self):
+        g1 = np.array(["This", "is", "example"])
+        g2 = np.array(["This", "was", "example"])
+        assert_array_equal(g1 == g2, [g1[i] == g2[i] for i in [0, 1, 2]])
+        assert_array_equal(g1 != g2, [g1[i] != g2[i] for i in [0, 1, 2]])
+        assert_array_equal(g1 <= g2, [g1[i] <= g2[i] for i in [0, 1, 2]])
+        assert_array_equal(g1 >= g2, [g1[i] >= g2[i] for i in [0, 1, 2]])
+        assert_array_equal(g1 < g2, [g1[i] < g2[i] for i in [0, 1, 2]])
+        assert_array_equal(g1 > g2, [g1[i] > g2[i] for i in [0, 1, 2]])
+
+    def test_mixed(self):
+        g1 = np.array(["spam", "spa", "spammer", "and eggs"])
+        g2 = "spam"
+        assert_array_equal(g1 == g2, [x == g2 for x in g1])
+        assert_array_equal(g1 != g2, [x != g2 for x in g1])
+        assert_array_equal(g1 < g2, [x < g2 for x in g1])
+        assert_array_equal(g1 > g2, [x > g2 for x in g1])
+        assert_array_equal(g1 <= g2, [x <= g2 for x in g1])
+        assert_array_equal(g1 >= g2, [x >= g2 for x in g1])
+
+    def test_unicode(self):
+        g1 = np.array([u"This", u"is", u"example"])
+        g2 = np.array([u"This", u"was", u"example"])
+        assert_array_equal(g1 == g2, [g1[i] == g2[i] for i in [0, 1, 2]])
+        assert_array_equal(g1 != g2, [g1[i] != g2[i] for i in [0, 1, 2]])
+        assert_array_equal(g1 <= g2, [g1[i] <= g2[i] for i in [0, 1, 2]])
+        assert_array_equal(g1 >= g2, [g1[i] >= g2[i] for i in [0, 1, 2]])
+        assert_array_equal(g1 < g2,  [g1[i] < g2[i] for i in [0, 1, 2]])
+        assert_array_equal(g1 > g2,  [g1[i] > g2[i] for i in [0, 1, 2]])
+
+
+class TestArgmax(object):
+
+    nan_arr = [
+        ([0, 1, 2, 3, np.nan], 4),
+        ([0, 1, 2, np.nan, 3], 3),
+        ([np.nan, 0, 1, 2, 3], 0),
+        ([np.nan, 0, np.nan, 2, 3], 0),
+        ([0, 1, 2, 3, complex(0, np.nan)], 4),
+        ([0, 1, 2, 3, complex(np.nan, 0)], 4),
+        ([0, 1, 2, complex(np.nan, 0), 3], 3),
+        ([0, 1, 2, complex(0, np.nan), 3], 3),
+        ([complex(0, np.nan), 0, 1, 2, 3], 0),
+        ([complex(np.nan, np.nan), 0, 1, 2, 3], 0),
+        ([complex(np.nan, 0), complex(np.nan, 2), complex(np.nan, 1)], 0),
+        ([complex(np.nan, np.nan), complex(np.nan, 2), complex(np.nan, 1)], 0),
+        ([complex(np.nan, 0), complex(np.nan, 2), complex(np.nan, np.nan)], 0),
+
+        ([complex(0, 0), complex(0, 2), complex(0, 1)], 1),
+        ([complex(1, 0), complex(0, 2), complex(0, 1)], 0),
+        ([complex(1, 0), complex(0, 2), complex(1, 1)], 2),
+
+        ([np.datetime64('1923-04-14T12:43:12'),
+          np.datetime64('1994-06-21T14:43:15'),
+          np.datetime64('2001-10-15T04:10:32'),
+          np.datetime64('1995-11-25T16:02:16'),
+          np.datetime64('2005-01-04T03:14:12'),
+          np.datetime64('2041-12-03T14:05:03')], 5),
+        ([np.datetime64('1935-09-14T04:40:11'),
+          np.datetime64('1949-10-12T12:32:11'),
+          np.datetime64('2010-01-03T05:14:12'),
+          np.datetime64('2015-11-20T12:20:59'),
+          np.datetime64('1932-09-23T10:10:13'),
+          np.datetime64('2014-10-10T03:50:30')], 3),
+        # Assorted tests with NaTs
+        ([np.datetime64('NaT'),
+          np.datetime64('NaT'),
+          np.datetime64('2010-01-03T05:14:12'),
+          np.datetime64('NaT'),
+          np.datetime64('2015-09-23T10:10:13'),
+          np.datetime64('1932-10-10T03:50:30')], 4),
+        ([np.datetime64('2059-03-14T12:43:12'),
+          np.datetime64('1996-09-21T14:43:15'),
+          np.datetime64('NaT'),
+          np.datetime64('2022-12-25T16:02:16'),
+          np.datetime64('1963-10-04T03:14:12'),
+          np.datetime64('2013-05-08T18:15:23')], 0),
+        ([np.timedelta64(2, 's'),
+          np.timedelta64(1, 's'),
+          np.timedelta64('NaT', 's'),
+          np.timedelta64(3, 's')], 3),
+        ([np.timedelta64('NaT', 's')] * 3, 0),
+
+        ([timedelta(days=5, seconds=14), timedelta(days=2, seconds=35),
+          timedelta(days=-1, seconds=23)], 0),
+        ([timedelta(days=1, seconds=43), timedelta(days=10, seconds=5),
+          timedelta(days=5, seconds=14)], 1),
+        ([timedelta(days=10, seconds=24), timedelta(days=10, seconds=5),
+          timedelta(days=10, seconds=43)], 2),
+
+        ([False, False, False, False, True], 4),
+        ([False, False, False, True, False], 3),
+        ([True, False, False, False, False], 0),
+        ([True, False, True, False, False], 0),
+    ]
+
+    def test_all(self):
+        a = np.random.normal(0, 1, (4, 5, 6, 7, 8))
+        for i in range(a.ndim):
+            amax = a.max(i)
+            aargmax = a.argmax(i)
+            axes = list(range(a.ndim))
+            axes.remove(i)
+            assert_(np.all(amax == aargmax.choose(*a.transpose(i,*axes))))
+
+    def test_combinations(self):
+        for arr, pos in self.nan_arr:
+            with suppress_warnings() as sup:
+                sup.filter(RuntimeWarning,
+                           "invalid value encountered in reduce")
+                max_val = np.max(arr)
+
+            assert_equal(np.argmax(arr), pos, err_msg="%r" % arr)
+            assert_equal(arr[np.argmax(arr)], max_val, err_msg="%r" % arr)
+
+    def test_output_shape(self):
+        # see also gh-616
+        a = np.ones((10, 5))
+        # Check some simple shape mismatches
+        out = np.ones(11, dtype=np.int_)
+        assert_raises(ValueError, a.argmax, -1, out)
+
+        out = np.ones((2, 5), dtype=np.int_)
+        assert_raises(ValueError, a.argmax, -1, out)
+
+        # these could be relaxed possibly (used to allow even the previous)
+        out = np.ones((1, 10), dtype=np.int_)
+        assert_raises(ValueError, a.argmax, -1, out)
+
+        out = np.ones(10, dtype=np.int_)
+        a.argmax(-1, out=out)
+        assert_equal(out, a.argmax(-1))
+
+    def test_argmax_unicode(self):
+        d = np.zeros(6031, dtype='<U9')
+        d[5942] = "as"
+        assert_equal(d.argmax(), 5942)
+
+    def test_np_vs_ndarray(self):
+        # make sure both ndarray.argmax and numpy.argmax support out/axis args
+        a = np.random.normal(size=(2,3))
+
+        # check positional args
+        out1 = np.zeros(2, dtype=int)
+        out2 = np.zeros(2, dtype=int)
+        assert_equal(a.argmax(1, out1), np.argmax(a, 1, out2))
+        assert_equal(out1, out2)
+
+        # check keyword args
+        out1 = np.zeros(3, dtype=int)
+        out2 = np.zeros(3, dtype=int)
+        assert_equal(a.argmax(out=out1, axis=0), np.argmax(a, out=out2, axis=0))
+        assert_equal(out1, out2)
+
+    def test_object_argmax_with_NULLs(self):
+        # See gh-6032
+        a = np.empty(4, dtype='O')
+        ctypes.memset(a.ctypes.data, 0, a.nbytes)
+        assert_equal(a.argmax(), 0)
+        a[3] = 10
+        assert_equal(a.argmax(), 3)
+        a[1] = 30
+        assert_equal(a.argmax(), 1)
+
+
+class TestArgmin(object):
+
+    nan_arr = [
+        ([0, 1, 2, 3, np.nan], 4),
+        ([0, 1, 2, np.nan, 3], 3),
+        ([np.nan, 0, 1, 2, 3], 0),
+        ([np.nan, 0, np.nan, 2, 3], 0),
+        ([0, 1, 2, 3, complex(0, np.nan)], 4),
+        ([0, 1, 2, 3, complex(np.nan, 0)], 4),
+        ([0, 1, 2, complex(np.nan, 0), 3], 3),
+        ([0, 1, 2, complex(0, np.nan), 3], 3),
+        ([complex(0, np.nan), 0, 1, 2, 3], 0),
+        ([complex(np.nan, np.nan), 0, 1, 2, 3], 0),
+        ([complex(np.nan, 0), complex(np.nan, 2), complex(np.nan, 1)], 0),
+        ([complex(np.nan, np.nan), complex(np.nan, 2), complex(np.nan, 1)], 0),
+        ([complex(np.nan, 0), complex(np.nan, 2), complex(np.nan, np.nan)], 0),
+
+        ([complex(0, 0), complex(0, 2), complex(0, 1)], 0),
+        ([complex(1, 0), complex(0, 2), complex(0, 1)], 2),
+        ([complex(1, 0), complex(0, 2), complex(1, 1)], 1),
+
+        ([np.datetime64('1923-04-14T12:43:12'),
+          np.datetime64('1994-06-21T14:43:15'),
+          np.datetime64('2001-10-15T04:10:32'),
+          np.datetime64('1995-11-25T16:02:16'),
+          np.datetime64('2005-01-04T03:14:12'),
+          np.datetime64('2041-12-03T14:05:03')], 0),
+        ([np.datetime64('1935-09-14T04:40:11'),
+          np.datetime64('1949-10-12T12:32:11'),
+          np.datetime64('2010-01-03T05:14:12'),
+          np.datetime64('2014-11-20T12:20:59'),
+          np.datetime64('2015-09-23T10:10:13'),
+          np.datetime64('1932-10-10T03:50:30')], 5),
+        # Assorted tests with NaTs
+        ([np.datetime64('NaT'),
+          np.datetime64('NaT'),
+          np.datetime64('2010-01-03T05:14:12'),
+          np.datetime64('NaT'),
+          np.datetime64('2015-09-23T10:10:13'),
+          np.datetime64('1932-10-10T03:50:30')], 5),
+        ([np.datetime64('2059-03-14T12:43:12'),
+          np.datetime64('1996-09-21T14:43:15'),
+          np.datetime64('NaT'),
+          np.datetime64('2022-12-25T16:02:16'),
+          np.datetime64('1963-10-04T03:14:12'),
+          np.datetime64('2013-05-08T18:15:23')], 4),
+        ([np.timedelta64(2, 's'),
+          np.timedelta64(1, 's'),
+          np.timedelta64('NaT', 's'),
+          np.timedelta64(3, 's')], 1),
+        ([np.timedelta64('NaT', 's')] * 3, 0),
+
+        ([timedelta(days=5, seconds=14), timedelta(days=2, seconds=35),
+          timedelta(days=-1, seconds=23)], 2),
+        ([timedelta(days=1, seconds=43), timedelta(days=10, seconds=5),
+          timedelta(days=5, seconds=14)], 0),
+        ([timedelta(days=10, seconds=24), timedelta(days=10, seconds=5),
+          timedelta(days=10, seconds=43)], 1),
+
+        ([True, True, True, True, False], 4),
+        ([True, True, True, False, True], 3),
+        ([False, True, True, True, True], 0),
+        ([False, True, False, True, True], 0),
+    ]
+
+    def test_all(self):
+        a = np.random.normal(0, 1, (4, 5, 6, 7, 8))
+        for i in range(a.ndim):
+            amin = a.min(i)
+            aargmin = a.argmin(i)
+            axes = list(range(a.ndim))
+            axes.remove(i)
+            assert_(np.all(amin == aargmin.choose(*a.transpose(i,*axes))))
+
+    def test_combinations(self):
+        for arr, pos in self.nan_arr:
+            with suppress_warnings() as sup:
+                sup.filter(RuntimeWarning,
+                           "invalid value encountered in reduce")
+                min_val = np.min(arr)
+
+            assert_equal(np.argmin(arr), pos, err_msg="%r" % arr)
+            assert_equal(arr[np.argmin(arr)], min_val, err_msg="%r" % arr)
+
+    def test_minimum_signed_integers(self):
+
+        a = np.array([1, -2**7, -2**7 + 1], dtype=np.int8)
+        assert_equal(np.argmin(a), 1)
+
+        a = np.array([1, -2**15, -2**15 + 1], dtype=np.int16)
+        assert_equal(np.argmin(a), 1)
+
+        a = np.array([1, -2**31, -2**31 + 1], dtype=np.int32)
+        assert_equal(np.argmin(a), 1)
+
+        a = np.array([1, -2**63, -2**63 + 1], dtype=np.int64)
+        assert_equal(np.argmin(a), 1)
+
+    def test_output_shape(self):
+        # see also gh-616
+        a = np.ones((10, 5))
+        # Check some simple shape mismatches
+        out = np.ones(11, dtype=np.int_)
+        assert_raises(ValueError, a.argmin, -1, out)
+
+        out = np.ones((2, 5), dtype=np.int_)
+        assert_raises(ValueError, a.argmin, -1, out)
+
+        # these could be relaxed possibly (used to allow even the previous)
+        out = np.ones((1, 10), dtype=np.int_)
+        assert_raises(ValueError, a.argmin, -1, out)
+
+        out = np.ones(10, dtype=np.int_)
+        a.argmin(-1, out=out)
+        assert_equal(out, a.argmin(-1))
+
+    def test_argmin_unicode(self):
+        d = np.ones(6031, dtype='<U9')
+        d[6001] = "0"
+        assert_equal(d.argmin(), 6001)
+
+    def test_np_vs_ndarray(self):
+        # make sure both ndarray.argmin and numpy.argmin support out/axis args
+        a = np.random.normal(size=(2, 3))
+
+        # check positional args
+        out1 = np.zeros(2, dtype=int)
+        out2 = np.ones(2, dtype=int)
+        assert_equal(a.argmin(1, out1), np.argmin(a, 1, out2))
+        assert_equal(out1, out2)
+
+        # check keyword args
+        out1 = np.zeros(3, dtype=int)
+        out2 = np.ones(3, dtype=int)
+        assert_equal(a.argmin(out=out1, axis=0), np.argmin(a, out=out2, axis=0))
+        assert_equal(out1, out2)
+
+    def test_object_argmin_with_NULLs(self):
+        # See gh-6032
+        a = np.empty(4, dtype='O')
+        ctypes.memset(a.ctypes.data, 0, a.nbytes)
+        assert_equal(a.argmin(), 0)
+        a[3] = 30
+        assert_equal(a.argmin(), 3)
+        a[1] = 10
+        assert_equal(a.argmin(), 1)
+
+
+class TestMinMax(object):
+
+    def test_scalar(self):
+        assert_raises(np.AxisError, np.amax, 1, 1)
+        assert_raises(np.AxisError, np.amin, 1, 1)
+
+        assert_equal(np.amax(1, axis=0), 1)
+        assert_equal(np.amin(1, axis=0), 1)
+        assert_equal(np.amax(1, axis=None), 1)
+        assert_equal(np.amin(1, axis=None), 1)
+
+    def test_axis(self):
+        assert_raises(np.AxisError, np.amax, [1, 2, 3], 1000)
+        assert_equal(np.amax([[1, 2, 3]], axis=1), 3)
+
+    def test_datetime(self):
+        # NaTs are ignored
+        for dtype in ('m8[s]', 'm8[Y]'):
+            a = np.arange(10).astype(dtype)
+            a[3] = 'NaT'
+            assert_equal(np.amin(a), a[0])
+            assert_equal(np.amax(a), a[9])
+            a[0] = 'NaT'
+            assert_equal(np.amin(a), a[1])
+            assert_equal(np.amax(a), a[9])
+            a.fill('NaT')
+            assert_equal(np.amin(a), a[0])
+            assert_equal(np.amax(a), a[0])
+
+
+class TestNewaxis(object):
+    def test_basic(self):
+        sk = np.array([0, -0.1, 0.1])
+        res = 250*sk[:, np.newaxis]
+        assert_almost_equal(res.ravel(), 250*sk)
+
+
+class TestClip(object):
+    def _check_range(self, x, cmin, cmax):
+        assert_(np.all(x >= cmin))
+        assert_(np.all(x <= cmax))
+
+    def _clip_type(self, type_group, array_max,
+                   clip_min, clip_max, inplace=False,
+                   expected_min=None, expected_max=None):
+        if expected_min is None:
+            expected_min = clip_min
+        if expected_max is None:
+            expected_max = clip_max
+
+        for T in np.sctypes[type_group]:
+            if sys.byteorder == 'little':
+                byte_orders = ['=', '>']
+            else:
+                byte_orders = ['<', '=']
+
+            for byteorder in byte_orders:
+                dtype = np.dtype(T).newbyteorder(byteorder)
+
+                x = (np.random.random(1000) * array_max).astype(dtype)
+                if inplace:
+                    x.clip(clip_min, clip_max, x)
+                else:
+                    x = x.clip(clip_min, clip_max)
+                    byteorder = '='
+
+                if x.dtype.byteorder == '|':
+                    byteorder = '|'
+                assert_equal(x.dtype.byteorder, byteorder)
+                self._check_range(x, expected_min, expected_max)
+        return x
+
+    def test_basic(self):
+        for inplace in [False, True]:
+            self._clip_type(
+                'float', 1024, -12.8, 100.2, inplace=inplace)
+            self._clip_type(
+                'float', 1024, 0, 0, inplace=inplace)
+
+            self._clip_type(
+                'int', 1024, -120, 100.5, inplace=inplace)
+            self._clip_type(
+                'int', 1024, 0, 0, inplace=inplace)
+
+            self._clip_type(
+                'uint', 1024, 0, 0, inplace=inplace)
+            self._clip_type(
+                'uint', 1024, -120, 100, inplace=inplace, expected_min=0)
+
+    def test_record_array(self):
+        rec = np.array([(-5, 2.0, 3.0), (5.0, 4.0, 3.0)],
+                       dtype=[('x', '<f8'), ('y', '<f8'), ('z', '<f8')])
+        y = rec['x'].clip(-0.3, 0.5)
+        self._check_range(y, -0.3, 0.5)
+
+    def test_max_or_min(self):
+        val = np.array([0, 1, 2, 3, 4, 5, 6, 7])
+        x = val.clip(3)
+        assert_(np.all(x >= 3))
+        x = val.clip(min=3)
+        assert_(np.all(x >= 3))
+        x = val.clip(max=4)
+        assert_(np.all(x <= 4))
+
+    def test_nan(self):
+        input_arr = np.array([-2., np.nan, 0.5, 3., 0.25, np.nan])
+        result = input_arr.clip(-1, 1)
+        expected = np.array([-1., np.nan, 0.5, 1., 0.25, np.nan])
+        assert_array_equal(result, expected)
+
+
+class TestCompress(object):
+    def test_axis(self):
+        tgt = [[5, 6, 7, 8, 9]]
+        arr = np.arange(10).reshape(2, 5)
+        out = np.compress([0, 1], arr, axis=0)
+        assert_equal(out, tgt)
+
+        tgt = [[1, 3], [6, 8]]
+        out = np.compress([0, 1, 0, 1, 0], arr, axis=1)
+        assert_equal(out, tgt)
+
+    def test_truncate(self):
+        tgt = [[1], [6]]
+        arr = np.arange(10).reshape(2, 5)
+        out = np.compress([0, 1], arr, axis=1)
+        assert_equal(out, tgt)
+
+    def test_flatten(self):
+        arr = np.arange(10).reshape(2, 5)
+        out = np.compress([0, 1], arr)
+        assert_equal(out, 1)
+
+
+class TestPutmask(object):
+    def tst_basic(self, x, T, mask, val):
+        np.putmask(x, mask, val)
+        assert_equal(x[mask], T(val))
+        assert_equal(x.dtype, T)
+
+    def test_ip_types(self):
+        unchecked_types = [bytes, unicode, np.void, object]
+
+        x = np.random.random(1000)*100
+        mask = x < 40
+
+        for val in [-100, 0, 15]:
+            for types in np.sctypes.values():
+                for T in types:
+                    if T not in unchecked_types:
+                        self.tst_basic(x.copy().astype(T), T, mask, val)
+
+    def test_mask_size(self):
+        assert_raises(ValueError, np.putmask, np.array([1, 2, 3]), [True], 5)
+
+    @pytest.mark.parametrize('dtype', ('>i4', '<i4'))
+    def test_byteorder(self, dtype):
+        x = np.array([1, 2, 3], dtype)
+        np.putmask(x, [True, False, True], -1)
+        assert_array_equal(x, [-1, 2, -1])
+
+    def test_record_array(self):
+        # Note mixed byteorder.
+        rec = np.array([(-5, 2.0, 3.0), (5.0, 4.0, 3.0)],
+                      dtype=[('x', '<f8'), ('y', '>f8'), ('z', '<f8')])
+        np.putmask(rec['x'], [True, False], 10)
+        assert_array_equal(rec['x'], [10, 5])
+        assert_array_equal(rec['y'], [2, 4])
+        assert_array_equal(rec['z'], [3, 3])
+        np.putmask(rec['y'], [True, False], 11)
+        assert_array_equal(rec['x'], [10, 5])
+        assert_array_equal(rec['y'], [11, 4])
+        assert_array_equal(rec['z'], [3, 3])
+
+
+class TestTake(object):
+    def tst_basic(self, x):
+        ind = list(range(x.shape[0]))
+        assert_array_equal(x.take(ind, axis=0), x)
+
+    def test_ip_types(self):
+        unchecked_types = [bytes, unicode, np.void, object]
+
+        x = np.random.random(24)*100
+        x.shape = 2, 3, 4
+        for types in np.sctypes.values():
+            for T in types:
+                if T not in unchecked_types:
+                    self.tst_basic(x.copy().astype(T))
+
+    def test_raise(self):
+        x = np.random.random(24)*100
+        x.shape = 2, 3, 4
+        assert_raises(IndexError, x.take, [0, 1, 2], axis=0)
+        assert_raises(IndexError, x.take, [-3], axis=0)
+        assert_array_equal(x.take([-1], axis=0)[0], x[1])
+
+    def test_clip(self):
+        x = np.random.random(24)*100
+        x.shape = 2, 3, 4
+        assert_array_equal(x.take([-1], axis=0, mode='clip')[0], x[0])
+        assert_array_equal(x.take([2], axis=0, mode='clip')[0], x[1])
+
+    def test_wrap(self):
+        x = np.random.random(24)*100
+        x.shape = 2, 3, 4
+        assert_array_equal(x.take([-1], axis=0, mode='wrap')[0], x[1])
+        assert_array_equal(x.take([2], axis=0, mode='wrap')[0], x[0])
+        assert_array_equal(x.take([3], axis=0, mode='wrap')[0], x[1])
+
+    @pytest.mark.parametrize('dtype', ('>i4', '<i4'))
+    def test_byteorder(self, dtype):
+        x = np.array([1, 2, 3], dtype)
+        assert_array_equal(x.take([0, 2, 1]), [1, 3, 2])
+
+    def test_record_array(self):
+        # Note mixed byteorder.
+        rec = np.array([(-5, 2.0, 3.0), (5.0, 4.0, 3.0)],
+                      dtype=[('x', '<f8'), ('y', '>f8'), ('z', '<f8')])
+        rec1 = rec.take([1])
+        assert_(rec1['x'] == 5.0 and rec1['y'] == 4.0)
+
+
+class TestLexsort(object):
+    def test_basic(self):
+        a = [1, 2, 1, 3, 1, 5]
+        b = [0, 4, 5, 6, 2, 3]
+        idx = np.lexsort((b, a))
+        expected_idx = np.array([0, 4, 2, 1, 3, 5])
+        assert_array_equal(idx, expected_idx)
+
+        x = np.vstack((b, a))
+        idx = np.lexsort(x)
+        assert_array_equal(idx, expected_idx)
+
+        assert_array_equal(x[1][idx], np.sort(x[1]))
+
+    def test_datetime(self):
+        a = np.array([0,0,0], dtype='datetime64[D]')
+        b = np.array([2,1,0], dtype='datetime64[D]')
+        idx = np.lexsort((b, a))
+        expected_idx = np.array([2, 1, 0])
+        assert_array_equal(idx, expected_idx)
+
+        a = np.array([0,0,0], dtype='timedelta64[D]')
+        b = np.array([2,1,0], dtype='timedelta64[D]')
+        idx = np.lexsort((b, a))
+        expected_idx = np.array([2, 1, 0])
+        assert_array_equal(idx, expected_idx)
+
+    def test_object(self):  # gh-6312
+        a = np.random.choice(10, 1000)
+        b = np.random.choice(['abc', 'xy', 'wz', 'efghi', 'qwst', 'x'], 1000)
+
+        for u in a, b:
+            left = np.lexsort((u.astype('O'),))
+            right = np.argsort(u, kind='mergesort')
+            assert_array_equal(left, right)
+
+        for u, v in (a, b), (b, a):
+            idx = np.lexsort((u, v))
+            assert_array_equal(idx, np.lexsort((u.astype('O'), v)))
+            assert_array_equal(idx, np.lexsort((u, v.astype('O'))))
+            u, v = np.array(u, dtype='object'), np.array(v, dtype='object')
+            assert_array_equal(idx, np.lexsort((u, v)))
+
+    def test_invalid_axis(self): # gh-7528
+        x = np.linspace(0., 1., 42*3).reshape(42, 3)
+        assert_raises(np.AxisError, np.lexsort, x, axis=2)
+
+class TestIO(object):
+    """Test tofile, fromfile, tobytes, and fromstring"""
+
+    def setup(self):
+        shape = (2, 4, 3)
+        rand = np.random.random
+        self.x = rand(shape) + rand(shape).astype(complex)*1j
+        self.x[0,:, 1] = [np.nan, np.inf, -np.inf, np.nan]
+        self.dtype = self.x.dtype
+        self.tempdir = tempfile.mkdtemp()
+        self.filename = tempfile.mktemp(dir=self.tempdir)
+
+    def teardown(self):
+        shutil.rmtree(self.tempdir)
+
+    def test_nofile(self):
+        # this should probably be supported as a file
+        # but for now test for proper errors
+        b = io.BytesIO()
+        assert_raises(IOError, np.fromfile, b, np.uint8, 80)
+        d = np.ones(7)
+        assert_raises(IOError, lambda x: x.tofile(b), d)
+
+    def test_bool_fromstring(self):
+        v = np.array([True, False, True, False], dtype=np.bool_)
+        y = np.fromstring('1 0 -2.3 0.0', sep=' ', dtype=np.bool_)
+        assert_array_equal(v, y)
+
+    def test_uint64_fromstring(self):
+        d = np.fromstring("9923372036854775807 104783749223640",
+                          dtype=np.uint64, sep=' ')
+        e = np.array([9923372036854775807, 104783749223640], dtype=np.uint64)
+        assert_array_equal(d, e)
+
+    def test_int64_fromstring(self):
+        d = np.fromstring("-25041670086757 104783749223640",
+                          dtype=np.int64, sep=' ')
+        e = np.array([-25041670086757, 104783749223640], dtype=np.int64)
+        assert_array_equal(d, e)
+
+    def test_empty_files_binary(self):
+        f = open(self.filename, 'w')
+        f.close()
+        y = np.fromfile(self.filename)
+        assert_(y.size == 0, "Array not empty")
+
+    def test_empty_files_text(self):
+        f = open(self.filename, 'w')
+        f.close()
+        y = np.fromfile(self.filename, sep=" ")
+        assert_(y.size == 0, "Array not empty")
+
+    def test_roundtrip_file(self):
+        f = open(self.filename, 'wb')
+        self.x.tofile(f)
+        f.close()
+        # NB. doesn't work with flush+seek, due to use of C stdio
+        f = open(self.filename, 'rb')
+        y = np.fromfile(f, dtype=self.dtype)
+        f.close()
+        assert_array_equal(y, self.x.flat)
+
+    def test_roundtrip_filename(self):
+        self.x.tofile(self.filename)
+        y = np.fromfile(self.filename, dtype=self.dtype)
+        assert_array_equal(y, self.x.flat)
+
+    def test_roundtrip_binary_str(self):
+        s = self.x.tobytes()
+        y = np.frombuffer(s, dtype=self.dtype)
+        assert_array_equal(y, self.x.flat)
+
+        s = self.x.tobytes('F')
+        y = np.frombuffer(s, dtype=self.dtype)
+        assert_array_equal(y, self.x.flatten('F'))
+
+    def test_roundtrip_str(self):
+        x = self.x.real.ravel()
+        s = "@".join(map(str, x))
+        y = np.fromstring(s, sep="@")
+        # NB. str imbues less precision
+        nan_mask = ~np.isfinite(x)
+        assert_array_equal(x[nan_mask], y[nan_mask])
+        assert_array_almost_equal(x[~nan_mask], y[~nan_mask], decimal=5)
+
+    def test_roundtrip_repr(self):
+        x = self.x.real.ravel()
+        s = "@".join(map(repr, x))
+        y = np.fromstring(s, sep="@")
+        assert_array_equal(x, y)
+
+    def test_unseekable_fromfile(self):
+        # gh-6246
+        self.x.tofile(self.filename)
+
+        def fail(*args, **kwargs):
+            raise IOError('Can not tell or seek')
+
+        with io.open(self.filename, 'rb', buffering=0) as f:
+            f.seek = fail
+            f.tell = fail
+            assert_raises(IOError, np.fromfile, f, dtype=self.dtype)
+
+    def test_io_open_unbuffered_fromfile(self):
+        # gh-6632
+        self.x.tofile(self.filename)
+        with io.open(self.filename, 'rb', buffering=0) as f:
+            y = np.fromfile(f, dtype=self.dtype)
+            assert_array_equal(y, self.x.flat)
+
+    def test_largish_file(self):
+        # check the fallocate path on files > 16MB
+        d = np.zeros(4 * 1024 ** 2)
+        d.tofile(self.filename)
+        assert_equal(os.path.getsize(self.filename), d.nbytes)
+        assert_array_equal(d, np.fromfile(self.filename))
+        # check offset
+        with open(self.filename, "r+b") as f:
+            f.seek(d.nbytes)
+            d.tofile(f)
+            assert_equal(os.path.getsize(self.filename), d.nbytes * 2)
+        # check append mode (gh-8329)
+        open(self.filename, "w").close() # delete file contents
+        with open(self.filename, "ab") as f:
+            d.tofile(f)
+        assert_array_equal(d, np.fromfile(self.filename))
+        with open(self.filename, "ab") as f:
+            d.tofile(f)
+        assert_equal(os.path.getsize(self.filename), d.nbytes * 2)
+
+    def test_io_open_buffered_fromfile(self):
+        # gh-6632
+        self.x.tofile(self.filename)
+        with io.open(self.filename, 'rb', buffering=-1) as f:
+            y = np.fromfile(f, dtype=self.dtype)
+        assert_array_equal(y, self.x.flat)
+
+    def test_file_position_after_fromfile(self):
+        # gh-4118
+        sizes = [io.DEFAULT_BUFFER_SIZE//8,
+                 io.DEFAULT_BUFFER_SIZE,
+                 io.DEFAULT_BUFFER_SIZE*8]
+
+        for size in sizes:
+            f = open(self.filename, 'wb')
+            f.seek(size-1)
+            f.write(b'\0')
+            f.close()
+
+            for mode in ['rb', 'r+b']:
+                err_msg = "%d %s" % (size, mode)
+
+                f = open(self.filename, mode)
+                f.read(2)
+                np.fromfile(f, dtype=np.float64, count=1)
+                pos = f.tell()
+                f.close()
+                assert_equal(pos, 10, err_msg=err_msg)
+
+    def test_file_position_after_tofile(self):
+        # gh-4118
+        sizes = [io.DEFAULT_BUFFER_SIZE//8,
+                 io.DEFAULT_BUFFER_SIZE,
+                 io.DEFAULT_BUFFER_SIZE*8]
+
+        for size in sizes:
+            err_msg = "%d" % (size,)
+
+            f = open(self.filename, 'wb')
+            f.seek(size-1)
+            f.write(b'\0')
+            f.seek(10)
+            f.write(b'12')
+            np.array([0], dtype=np.float64).tofile(f)
+            pos = f.tell()
+            f.close()
+            assert_equal(pos, 10 + 2 + 8, err_msg=err_msg)
+
+            f = open(self.filename, 'r+b')
+            f.read(2)
+            f.seek(0, 1)  # seek between read&write required by ANSI C
+            np.array([0], dtype=np.float64).tofile(f)
+            pos = f.tell()
+            f.close()
+            assert_equal(pos, 10, err_msg=err_msg)
+
+    def test_load_object_array_fromfile(self):
+        # gh-12300
+        with open(self.filename, 'w') as f:
+            # Ensure we have a file with consistent contents
+            pass
+
+        with open(self.filename, 'rb') as f:
+            assert_raises_regex(ValueError, "Cannot read into object array",
+                                np.fromfile, f, dtype=object)
+
+        assert_raises_regex(ValueError, "Cannot read into object array",
+                            np.fromfile, self.filename, dtype=object)
+
+    def _check_from(self, s, value, **kw):
+        if 'sep' not in kw:
+            y = np.frombuffer(s, **kw)
+        else:
+            y = np.fromstring(s, **kw)
+        assert_array_equal(y, value)
+
+        f = open(self.filename, 'wb')
+        f.write(s)
+        f.close()
+        y = np.fromfile(self.filename, **kw)
+        assert_array_equal(y, value)
+
+    def test_nan(self):
+        self._check_from(
+            b"nan +nan -nan NaN nan(foo) +NaN(BAR) -NAN(q_u_u_x_)",
+            [np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan],
+            sep=' ')
+
+    def test_inf(self):
+        self._check_from(
+            b"inf +inf -inf infinity -Infinity iNfInItY -inF",
+            [np.inf, np.inf, -np.inf, np.inf, -np.inf, np.inf, -np.inf],
+            sep=' ')
+
+    def test_numbers(self):
+        self._check_from(b"1.234 -1.234 .3 .3e55 -123133.1231e+133",
+                         [1.234, -1.234, .3, .3e55, -123133.1231e+133], sep=' ')
+
+    def test_binary(self):
+        self._check_from(b'\x00\x00\x80?\x00\x00\x00@\x00\x00@@\x00\x00\x80@',
+                         np.array([1, 2, 3, 4]),
+                         dtype='<f4')
+
+    @pytest.mark.slow  # takes > 1 minute on mechanical hard drive
+    def test_big_binary(self):
+        """Test workarounds for 32-bit limited fwrite, fseek, and ftell
+        calls in windows. These normally would hang doing something like this.
+        See http://projects.scipy.org/numpy/ticket/1660"""
+        if sys.platform != 'win32':
+            return
+        try:
+            # before workarounds, only up to 2**32-1 worked
+            fourgbplus = 2**32 + 2**16
+            testbytes = np.arange(8, dtype=np.int8)
+            n = len(testbytes)
+            flike = tempfile.NamedTemporaryFile()
+            f = flike.file
+            np.tile(testbytes, fourgbplus // testbytes.nbytes).tofile(f)
+            flike.seek(0)
+            a = np.fromfile(f, dtype=np.int8)
+            flike.close()
+            assert_(len(a) == fourgbplus)
+            # check only start and end for speed:
+            assert_((a[:n] == testbytes).all())
+            assert_((a[-n:] == testbytes).all())
+        except (MemoryError, ValueError):
+            pass
+
+    def test_string(self):
+        self._check_from(b'1,2,3,4', [1., 2., 3., 4.], sep=',')
+
+    def test_counted_string(self):
+        self._check_from(b'1,2,3,4', [1., 2., 3., 4.], count=4, sep=',')
+        self._check_from(b'1,2,3,4', [1., 2., 3.], count=3, sep=',')
+        self._check_from(b'1,2,3,4', [1., 2., 3., 4.], count=-1, sep=',')
+
+    def test_string_with_ws(self):
+        self._check_from(b'1 2  3     4   ', [1, 2, 3, 4], dtype=int, sep=' ')
+
+    def test_counted_string_with_ws(self):
+        self._check_from(b'1 2  3     4   ', [1, 2, 3], count=3, dtype=int,
+                         sep=' ')
+
+    def test_ascii(self):
+        self._check_from(b'1 , 2 , 3 , 4', [1., 2., 3., 4.], sep=',')
+        self._check_from(b'1,2,3,4', [1., 2., 3., 4.], dtype=float, sep=',')
+
+    def test_malformed(self):
+        self._check_from(b'1.234 1,234', [1.234, 1.], sep=' ')
+
+    def test_long_sep(self):
+        self._check_from(b'1_x_3_x_4_x_5', [1, 3, 4, 5], sep='_x_')
+
+    def test_dtype(self):
+        v = np.array([1, 2, 3, 4], dtype=np.int_)
+        self._check_from(b'1,2,3,4', v, sep=',', dtype=np.int_)
+
+    def test_dtype_bool(self):
+        # can't use _check_from because fromstring can't handle True/False
+        v = np.array([True, False, True, False], dtype=np.bool_)
+        s = b'1,0,-2.3,0'
+        f = open(self.filename, 'wb')
+        f.write(s)
+        f.close()
+        y = np.fromfile(self.filename, sep=',', dtype=np.bool_)
+        assert_(y.dtype == '?')
+        assert_array_equal(y, v)
+
+    def test_tofile_sep(self):
+        x = np.array([1.51, 2, 3.51, 4], dtype=float)
+        f = open(self.filename, 'w')
+        x.tofile(f, sep=',')
+        f.close()
+        f = open(self.filename, 'r')
+        s = f.read()
+        f.close()
+        #assert_equal(s, '1.51,2.0,3.51,4.0')
+        y = np.array([float(p) for p in s.split(',')])
+        assert_array_equal(x,y)
+
+    def test_tofile_format(self):
+        x = np.array([1.51, 2, 3.51, 4], dtype=float)
+        f = open(self.filename, 'w')
+        x.tofile(f, sep=',', format='%.2f')
+        f.close()
+        f = open(self.filename, 'r')
+        s = f.read()
+        f.close()
+        assert_equal(s, '1.51,2.00,3.51,4.00')
+
+    def test_locale(self):
+        with CommaDecimalPointLocale():
+            self.test_numbers()
+            self.test_nan()
+            self.test_inf()
+            self.test_counted_string()
+            self.test_ascii()
+            self.test_malformed()
+            self.test_tofile_sep()
+            self.test_tofile_format()
+
+
+class TestFromBuffer(object):
+    @pytest.mark.parametrize('byteorder', ['<', '>'])
+    @pytest.mark.parametrize('dtype', [float, int, complex])
+    def test_basic(self, byteorder, dtype):
+        dt = np.dtype(dtype).newbyteorder(byteorder)
+        x = (np.random.random((4, 7)) * 5).astype(dt)
+        buf = x.tobytes()
+        assert_array_equal(np.frombuffer(buf, dtype=dt), x.flat)
+
+    def test_empty(self):
+        assert_array_equal(np.frombuffer(b''), np.array([]))
+
+
+class TestFlat(object):
+    def setup(self):
+        a0 = np.arange(20.0)
+        a = a0.reshape(4, 5)
+        a0.shape = (4, 5)
+        a.flags.writeable = False
+        self.a = a
+        self.b = a[::2, ::2]
+        self.a0 = a0
+        self.b0 = a0[::2, ::2]
+
+    def test_contiguous(self):
+        testpassed = False
+        try:
+            self.a.flat[12] = 100.0
+        except ValueError:
+            testpassed = True
+        assert_(testpassed)
+        assert_(self.a.flat[12] == 12.0)
+
+    def test_discontiguous(self):
+        testpassed = False
+        try:
+            self.b.flat[4] = 100.0
+        except ValueError:
+            testpassed = True
+        assert_(testpassed)
+        assert_(self.b.flat[4] == 12.0)
+
+    def test___array__(self):
+        c = self.a.flat.__array__()
+        d = self.b.flat.__array__()
+        e = self.a0.flat.__array__()
+        f = self.b0.flat.__array__()
+
+        assert_(c.flags.writeable is False)
+        assert_(d.flags.writeable is False)
+        # for 1.14 all are set to non-writeable on the way to replacing the
+        # UPDATEIFCOPY array returned for non-contiguous arrays.
+        assert_(e.flags.writeable is True)
+        assert_(f.flags.writeable is False)
+        with assert_warns(DeprecationWarning):
+            assert_(c.flags.updateifcopy is False)
+        with assert_warns(DeprecationWarning):
+            assert_(d.flags.updateifcopy is False)
+        with assert_warns(DeprecationWarning):
+            assert_(e.flags.updateifcopy is False)
+        with assert_warns(DeprecationWarning):
+            # UPDATEIFCOPY is removed.
+            assert_(f.flags.updateifcopy is False)
+        assert_(c.flags.writebackifcopy is False)
+        assert_(d.flags.writebackifcopy is False)
+        assert_(e.flags.writebackifcopy is False)
+        assert_(f.flags.writebackifcopy is False)
+
+    @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
+    def test_refcount(self):
+        # includes regression test for reference count error gh-13165
+        inds = [np.intp(0), np.array([True]*self.a.size), np.array([0]), None]
+        indtype = np.dtype(np.intp)
+        rc_indtype = sys.getrefcount(indtype)
+        for ind in inds:
+            rc_ind = sys.getrefcount(ind)
+            for _ in range(100):
+                try:
+                    self.a.flat[ind]
+                except IndexError:
+                    pass
+            assert_(abs(sys.getrefcount(ind) - rc_ind) < 50)
+            assert_(abs(sys.getrefcount(indtype) - rc_indtype) < 50)
+
+
+class TestResize(object):
+    def test_basic(self):
+        x = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+        if IS_PYPY:
+            x.resize((5, 5), refcheck=False)
+        else:
+            x.resize((5, 5))
+        assert_array_equal(x.flat[:9],
+                np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]).flat)
+        assert_array_equal(x[9:].flat, 0)
+
+    def test_check_reference(self):
+        x = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+        y = x
+        assert_raises(ValueError, x.resize, (5, 1))
+        del y  # avoid pyflakes unused variable warning.
+
+    def test_int_shape(self):
+        x = np.eye(3)
+        if IS_PYPY:
+            x.resize(3, refcheck=False)
+        else:
+            x.resize(3)
+        assert_array_equal(x, np.eye(3)[0,:])
+
+    def test_none_shape(self):
+        x = np.eye(3)
+        x.resize(None)
+        assert_array_equal(x, np.eye(3))
+        x.resize()
+        assert_array_equal(x, np.eye(3))
+
+    def test_0d_shape(self):
+        # to it multiple times to test it does not break alloc cache gh-9216
+        for i in range(10):
+            x = np.empty((1,))
+            x.resize(())
+            assert_equal(x.shape, ())
+            assert_equal(x.size, 1)
+            x = np.empty(())
+            x.resize((1,))
+            assert_equal(x.shape, (1,))
+            assert_equal(x.size, 1)
+
+    def test_invalid_arguments(self):
+        assert_raises(TypeError, np.eye(3).resize, 'hi')
+        assert_raises(ValueError, np.eye(3).resize, -1)
+        assert_raises(TypeError, np.eye(3).resize, order=1)
+        assert_raises(TypeError, np.eye(3).resize, refcheck='hi')
+
+    def test_freeform_shape(self):
+        x = np.eye(3)
+        if IS_PYPY:
+            x.resize(3, 2, 1, refcheck=False)
+        else:
+            x.resize(3, 2, 1)
+        assert_(x.shape == (3, 2, 1))
+
+    def test_zeros_appended(self):
+        x = np.eye(3)
+        if IS_PYPY:
+            x.resize(2, 3, 3, refcheck=False)
+        else:
+            x.resize(2, 3, 3)
+        assert_array_equal(x[0], np.eye(3))
+        assert_array_equal(x[1], np.zeros((3, 3)))
+
+    def test_obj_obj(self):
+        # check memory is initialized on resize, gh-4857
+        a = np.ones(10, dtype=[('k', object, 2)])
+        if IS_PYPY:
+            a.resize(15, refcheck=False)
+        else:
+            a.resize(15,)
+        assert_equal(a.shape, (15,))
+        assert_array_equal(a['k'][-5:], 0)
+        assert_array_equal(a['k'][:-5], 1)
+
+    def test_empty_view(self):
+        # check that sizes containing a zero don't trigger a reallocate for
+        # already empty arrays
+        x = np.zeros((10, 0), int)
+        x_view = x[...]
+        x_view.resize((0, 10))
+        x_view.resize((0, 100))
+
+    def test_check_weakref(self):
+        x = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+        xref = weakref.ref(x)
+        assert_raises(ValueError, x.resize, (5, 1))
+        del xref  # avoid pyflakes unused variable warning.
+
+
+class TestRecord(object):
+    def test_field_rename(self):
+        dt = np.dtype([('f', float), ('i', int)])
+        dt.names = ['p', 'q']
+        assert_equal(dt.names, ['p', 'q'])
+
+    def test_multiple_field_name_occurrence(self):
+        def test_dtype_init():
+            np.dtype([("A", "f8"), ("B", "f8"), ("A", "f8")])
+
+        # Error raised when multiple fields have the same name
+        assert_raises(ValueError, test_dtype_init)
+
+    @pytest.mark.skipif(sys.version_info[0] < 3, reason="Not Python 3")
+    def test_bytes_fields(self):
+        # Bytes are not allowed in field names and not recognized in titles
+        # on Py3
+        assert_raises(TypeError, np.dtype, [(b'a', int)])
+        assert_raises(TypeError, np.dtype, [(('b', b'a'), int)])
+
+        dt = np.dtype([((b'a', 'b'), int)])
+        assert_raises(TypeError, dt.__getitem__, b'a')
+
+        x = np.array([(1,), (2,), (3,)], dtype=dt)
+        assert_raises(IndexError, x.__getitem__, b'a')
+
+        y = x[0]
+        assert_raises(IndexError, y.__getitem__, b'a')
+
+    @pytest.mark.skipif(sys.version_info[0] < 3, reason="Not Python 3")
+    def test_multiple_field_name_unicode(self):
+        def test_dtype_unicode():
+            np.dtype([("\u20B9", "f8"), ("B", "f8"), ("\u20B9", "f8")])
+
+        # Error raised when multiple fields have the same name(unicode included)
+        assert_raises(ValueError, test_dtype_unicode)
+
+    @pytest.mark.skipif(sys.version_info[0] >= 3, reason="Not Python 2")
+    def test_unicode_field_titles(self):
+        # Unicode field titles are added to field dict on Py2
+        title = u'b'
+        dt = np.dtype([((title, 'a'), int)])
+        dt[title]
+        dt['a']
+        x = np.array([(1,), (2,), (3,)], dtype=dt)
+        x[title]
+        x['a']
+        y = x[0]
+        y[title]
+        y['a']
+
+    @pytest.mark.skipif(sys.version_info[0] >= 3, reason="Not Python 2")
+    def test_unicode_field_names(self):
+        # Unicode field names are converted to ascii on Python 2:
+        encodable_name = u'b'
+        assert_equal(np.dtype([(encodable_name, int)]).names[0], b'b')
+        assert_equal(np.dtype([(('a', encodable_name), int)]).names[0], b'b')
+
+        # But raises UnicodeEncodeError if it can't be encoded:
+        nonencodable_name = u'\uc3bc'
+        assert_raises(UnicodeEncodeError, np.dtype, [(nonencodable_name, int)])
+        assert_raises(UnicodeEncodeError, np.dtype, [(('a', nonencodable_name), int)])
+
+    def test_fromarrays_unicode(self):
+        # A single name string provided to fromarrays() is allowed to be unicode
+        # on both Python 2 and 3:
+        x = np.core.records.fromarrays([[0], [1]], names=u'a,b', formats=u'i4,i4')
+        assert_equal(x['a'][0], 0)
+        assert_equal(x['b'][0], 1)
+
+    def test_unicode_order(self):
+        # Test that we can sort with order as a unicode field name in both Python 2 and
+        # 3:
+        name = u'b'
+        x = np.array([1, 3, 2], dtype=[(name, int)])
+        x.sort(order=name)
+        assert_equal(x[u'b'], np.array([1, 2, 3]))
+
+    def test_field_names(self):
+        # Test unicode and 8-bit / byte strings can be used
+        a = np.zeros((1,), dtype=[('f1', 'i4'),
+                                  ('f2', 'i4'),
+                                  ('f3', [('sf1', 'i4')])])
+        is_py3 = sys.version_info[0] >= 3
+        if is_py3:
+            funcs = (str,)
+            # byte string indexing fails gracefully
+            assert_raises(IndexError, a.__setitem__, b'f1', 1)
+            assert_raises(IndexError, a.__getitem__, b'f1')
+            assert_raises(IndexError, a['f1'].__setitem__, b'sf1', 1)
+            assert_raises(IndexError, a['f1'].__getitem__, b'sf1')
+        else:
+            funcs = (str, unicode)
+        for func in funcs:
+            b = a.copy()
+            fn1 = func('f1')
+            b[fn1] = 1
+            assert_equal(b[fn1], 1)
+            fnn = func('not at all')
+            assert_raises(ValueError, b.__setitem__, fnn, 1)
+            assert_raises(ValueError, b.__getitem__, fnn)
+            b[0][fn1] = 2
+            assert_equal(b[fn1], 2)
+            # Subfield
+            assert_raises(ValueError, b[0].__setitem__, fnn, 1)
+            assert_raises(ValueError, b[0].__getitem__, fnn)
+            # Subfield
+            fn3 = func('f3')
+            sfn1 = func('sf1')
+            b[fn3][sfn1] = 1
+            assert_equal(b[fn3][sfn1], 1)
+            assert_raises(ValueError, b[fn3].__setitem__, fnn, 1)
+            assert_raises(ValueError, b[fn3].__getitem__, fnn)
+            # multiple subfields
+            fn2 = func('f2')
+            b[fn2] = 3
+
+            assert_equal(b[['f1', 'f2']][0].tolist(), (2, 3))
+            assert_equal(b[['f2', 'f1']][0].tolist(), (3, 2))
+            assert_equal(b[['f1', 'f3']][0].tolist(), (2, (1,)))
+
+        # non-ascii unicode field indexing is well behaved
+        if not is_py3:
+            pytest.skip('non ascii unicode field indexing skipped; '
+                        'raises segfault on python 2.x')
+        else:
+            assert_raises(ValueError, a.__setitem__, u'\u03e0', 1)
+            assert_raises(ValueError, a.__getitem__, u'\u03e0')
+
+    def test_record_hash(self):
+        a = np.array([(1, 2), (1, 2)], dtype='i1,i2')
+        a.flags.writeable = False
+        b = np.array([(1, 2), (3, 4)], dtype=[('num1', 'i1'), ('num2', 'i2')])
+        b.flags.writeable = False
+        c = np.array([(1, 2), (3, 4)], dtype='i1,i2')
+        c.flags.writeable = False
+        assert_(hash(a[0]) == hash(a[1]))
+        assert_(hash(a[0]) == hash(b[0]))
+        assert_(hash(a[0]) != hash(b[1]))
+        assert_(hash(c[0]) == hash(a[0]) and c[0] == a[0])
+
+    def test_record_no_hash(self):
+        a = np.array([(1, 2), (1, 2)], dtype='i1,i2')
+        assert_raises(TypeError, hash, a[0])
+
+    def test_empty_structure_creation(self):
+        # make sure these do not raise errors (gh-5631)
+        np.array([()], dtype={'names': [], 'formats': [],
+                           'offsets': [], 'itemsize': 12})
+        np.array([(), (), (), (), ()], dtype={'names': [], 'formats': [],
+                                           'offsets': [], 'itemsize': 12})
+
+    def test_multifield_indexing_view(self):
+        a = np.ones(3, dtype=[('a', 'i4'), ('b', 'f4'), ('c', 'u4')])
+        v = a[['a', 'c']]
+        assert_(v.base is a)
+        assert_(v.dtype == np.dtype({'names': ['a', 'c'],
+                                     'formats': ['i4', 'u4'],
+                                     'offsets': [0, 8]}))
+        v[:] = (4,5)
+        assert_equal(a[0].item(), (4, 1, 5))
+
+class TestView(object):
+    def test_basic(self):
+        x = np.array([(1, 2, 3, 4), (5, 6, 7, 8)],
+                     dtype=[('r', np.int8), ('g', np.int8),
+                            ('b', np.int8), ('a', np.int8)])
+        # We must be specific about the endianness here:
+        y = x.view(dtype='<i4')
+        # ... and again without the keyword.
+        z = x.view('<i4')
+        assert_array_equal(y, z)
+        assert_array_equal(y, [67305985, 134678021])
+
+
+def _mean(a, **args):
+    return a.mean(**args)
+
+
+def _var(a, **args):
+    return a.var(**args)
+
+
+def _std(a, **args):
+    return a.std(**args)
+
+
+class TestStats(object):
+
+    funcs = [_mean, _var, _std]
+
+    def setup(self):
+        np.random.seed(range(3))
+        self.rmat = np.random.random((4, 5))
+        self.cmat = self.rmat + 1j * self.rmat
+        self.omat = np.array([Decimal(repr(r)) for r in self.rmat.flat])
+        self.omat = self.omat.reshape(4, 5)
+
+    def test_python_type(self):
+        for x in (np.float16(1.), 1, 1., 1+0j):
+            assert_equal(np.mean([x]), 1.)
+            assert_equal(np.std([x]), 0.)
+            assert_equal(np.var([x]), 0.)
+
+    def test_keepdims(self):
+        mat = np.eye(3)
+        for f in self.funcs:
+            for axis in [0, 1]:
+                res = f(mat, axis=axis, keepdims=True)
+                assert_(res.ndim == mat.ndim)
+                assert_(res.shape[axis] == 1)
+            for axis in [None]:
+                res = f(mat, axis=axis, keepdims=True)
+                assert_(res.shape == (1, 1))
+
+    def test_out(self):
+        mat = np.eye(3)
+        for f in self.funcs:
+            out = np.zeros(3)
+            tgt = f(mat, axis=1)
+            res = f(mat, axis=1, out=out)
+            assert_almost_equal(res, out)
+            assert_almost_equal(res, tgt)
+        out = np.empty(2)
+        assert_raises(ValueError, f, mat, axis=1, out=out)
+        out = np.empty((2, 2))
+        assert_raises(ValueError, f, mat, axis=1, out=out)
+
+    def test_dtype_from_input(self):
+
+        icodes = np.typecodes['AllInteger']
+        fcodes = np.typecodes['AllFloat']
+
+        # object type
+        for f in self.funcs:
+            mat = np.array([[Decimal(1)]*3]*3)
+            tgt = mat.dtype.type
+            res = f(mat, axis=1).dtype.type
+            assert_(res is tgt)
+            # scalar case
+            res = type(f(mat, axis=None))
+            assert_(res is Decimal)
+
+        # integer types
+        for f in self.funcs:
+            for c in icodes:
+                mat = np.eye(3, dtype=c)
+                tgt = np.float64
+                res = f(mat, axis=1).dtype.type
+                assert_(res is tgt)
+                # scalar case
+                res = f(mat, axis=None).dtype.type
+                assert_(res is tgt)
+
+        # mean for float types
+        for f in [_mean]:
+            for c in fcodes:
+                mat = np.eye(3, dtype=c)
+                tgt = mat.dtype.type
+                res = f(mat, axis=1).dtype.type
+                assert_(res is tgt)
+                # scalar case
+                res = f(mat, axis=None).dtype.type
+                assert_(res is tgt)
+
+        # var, std for float types
+        for f in [_var, _std]:
+            for c in fcodes:
+                mat = np.eye(3, dtype=c)
+                # deal with complex types
+                tgt = mat.real.dtype.type
+                res = f(mat, axis=1).dtype.type
+                assert_(res is tgt)
+                # scalar case
+                res = f(mat, axis=None).dtype.type
+                assert_(res is tgt)
+
+    def test_dtype_from_dtype(self):
+        mat = np.eye(3)
+
+        # stats for integer types
+        # FIXME:
+        # this needs definition as there are lots places along the line
+        # where type casting may take place.
+
+        # for f in self.funcs:
+        #    for c in np.typecodes['AllInteger']:
+        #        tgt = np.dtype(c).type
+        #        res = f(mat, axis=1, dtype=c).dtype.type
+        #        assert_(res is tgt)
+        #        # scalar case
+        #        res = f(mat, axis=None, dtype=c).dtype.type
+        #        assert_(res is tgt)
+
+        # stats for float types
+        for f in self.funcs:
+            for c in np.typecodes['AllFloat']:
+                tgt = np.dtype(c).type
+                res = f(mat, axis=1, dtype=c).dtype.type
+                assert_(res is tgt)
+                # scalar case
+                res = f(mat, axis=None, dtype=c).dtype.type
+                assert_(res is tgt)
+
+    def test_ddof(self):
+        for f in [_var]:
+            for ddof in range(3):
+                dim = self.rmat.shape[1]
+                tgt = f(self.rmat, axis=1) * dim
+                res = f(self.rmat, axis=1, ddof=ddof) * (dim - ddof)
+        for f in [_std]:
+            for ddof in range(3):
+                dim = self.rmat.shape[1]
+                tgt = f(self.rmat, axis=1) * np.sqrt(dim)
+                res = f(self.rmat, axis=1, ddof=ddof) * np.sqrt(dim - ddof)
+                assert_almost_equal(res, tgt)
+                assert_almost_equal(res, tgt)
+
+    def test_ddof_too_big(self):
+        dim = self.rmat.shape[1]
+        for f in [_var, _std]:
+            for ddof in range(dim, dim + 2):
+                with warnings.catch_warnings(record=True) as w:
+                    warnings.simplefilter('always')
+                    res = f(self.rmat, axis=1, ddof=ddof)
+                    assert_(not (res < 0).any())
+                    assert_(len(w) > 0)
+                    assert_(issubclass(w[0].category, RuntimeWarning))
+
+    def test_empty(self):
+        A = np.zeros((0, 3))
+        for f in self.funcs:
+            for axis in [0, None]:
+                with warnings.catch_warnings(record=True) as w:
+                    warnings.simplefilter('always')
+                    assert_(np.isnan(f(A, axis=axis)).all())
+                    assert_(len(w) > 0)
+                    assert_(issubclass(w[0].category, RuntimeWarning))
+            for axis in [1]:
+                with warnings.catch_warnings(record=True) as w:
+                    warnings.simplefilter('always')
+                    assert_equal(f(A, axis=axis), np.zeros([]))
+
+    def test_mean_values(self):
+        for mat in [self.rmat, self.cmat, self.omat]:
+            for axis in [0, 1]:
+                tgt = mat.sum(axis=axis)
+                res = _mean(mat, axis=axis) * mat.shape[axis]
+                assert_almost_equal(res, tgt)
+            for axis in [None]:
+                tgt = mat.sum(axis=axis)
+                res = _mean(mat, axis=axis) * np.prod(mat.shape)
+                assert_almost_equal(res, tgt)
+
+    def test_mean_float16(self):
+        # This fail if the sum inside mean is done in float16 instead
+        # of float32.
+        assert_(_mean(np.ones(100000, dtype='float16')) == 1)
+
+    def test_var_values(self):
+        for mat in [self.rmat, self.cmat, self.omat]:
+            for axis in [0, 1, None]:
+                msqr = _mean(mat * mat.conj(), axis=axis)
+                mean = _mean(mat, axis=axis)
+                tgt = msqr - mean * mean.conjugate()
+                res = _var(mat, axis=axis)
+                assert_almost_equal(res, tgt)
+
+    def test_std_values(self):
+        for mat in [self.rmat, self.cmat, self.omat]:
+            for axis in [0, 1, None]:
+                tgt = np.sqrt(_var(mat, axis=axis))
+                res = _std(mat, axis=axis)
+                assert_almost_equal(res, tgt)
+
+    def test_subclass(self):
+        class TestArray(np.ndarray):
+            def __new__(cls, data, info):
+                result = np.array(data)
+                result = result.view(cls)
+                result.info = info
+                return result
+
+            def __array_finalize__(self, obj):
+                self.info = getattr(obj, "info", '')
+
+        dat = TestArray([[1, 2, 3, 4], [5, 6, 7, 8]], 'jubba')
+        res = dat.mean(1)
+        assert_(res.info == dat.info)
+        res = dat.std(1)
+        assert_(res.info == dat.info)
+        res = dat.var(1)
+        assert_(res.info == dat.info)
+
+class TestVdot(object):
+    def test_basic(self):
+        dt_numeric = np.typecodes['AllFloat'] + np.typecodes['AllInteger']
+        dt_complex = np.typecodes['Complex']
+
+        # test real
+        a = np.eye(3)
+        for dt in dt_numeric + 'O':
+            b = a.astype(dt)
+            res = np.vdot(b, b)
+            assert_(np.isscalar(res))
+            assert_equal(np.vdot(b, b), 3)
+
+        # test complex
+        a = np.eye(3) * 1j
+        for dt in dt_complex + 'O':
+            b = a.astype(dt)
+            res = np.vdot(b, b)
+            assert_(np.isscalar(res))
+            assert_equal(np.vdot(b, b), 3)
+
+        # test boolean
+        b = np.eye(3, dtype=bool)
+        res = np.vdot(b, b)
+        assert_(np.isscalar(res))
+        assert_equal(np.vdot(b, b), True)
+
+    def test_vdot_array_order(self):
+        a = np.array([[1, 2], [3, 4]], order='C')
+        b = np.array([[1, 2], [3, 4]], order='F')
+        res = np.vdot(a, a)
+
+        # integer arrays are exact
+        assert_equal(np.vdot(a, b), res)
+        assert_equal(np.vdot(b, a), res)
+        assert_equal(np.vdot(b, b), res)
+
+    def test_vdot_uncontiguous(self):
+        for size in [2, 1000]:
+            # Different sizes match different branches in vdot.
+            a = np.zeros((size, 2, 2))
+            b = np.zeros((size, 2, 2))
+            a[:, 0, 0] = np.arange(size)
+            b[:, 0, 0] = np.arange(size) + 1
+            # Make a and b uncontiguous:
+            a = a[..., 0]
+            b = b[..., 0]
+
+            assert_equal(np.vdot(a, b),
+                         np.vdot(a.flatten(), b.flatten()))
+            assert_equal(np.vdot(a, b.copy()),
+                         np.vdot(a.flatten(), b.flatten()))
+            assert_equal(np.vdot(a.copy(), b),
+                         np.vdot(a.flatten(), b.flatten()))
+            assert_equal(np.vdot(a.copy('F'), b),
+                         np.vdot(a.flatten(), b.flatten()))
+            assert_equal(np.vdot(a, b.copy('F')),
+                         np.vdot(a.flatten(), b.flatten()))
+
+
+class TestDot(object):
+    def setup(self):
+        np.random.seed(128)
+        self.A = np.random.rand(4, 2)
+        self.b1 = np.random.rand(2, 1)
+        self.b2 = np.random.rand(2)
+        self.b3 = np.random.rand(1, 2)
+        self.b4 = np.random.rand(4)
+        self.N = 7
+
+    def test_dotmatmat(self):
+        A = self.A
+        res = np.dot(A.transpose(), A)
+        tgt = np.array([[1.45046013, 0.86323640],
+                        [0.86323640, 0.84934569]])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotmatvec(self):
+        A, b1 = self.A, self.b1
+        res = np.dot(A, b1)
+        tgt = np.array([[0.32114320], [0.04889721],
+                        [0.15696029], [0.33612621]])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotmatvec2(self):
+        A, b2 = self.A, self.b2
+        res = np.dot(A, b2)
+        tgt = np.array([0.29677940, 0.04518649, 0.14468333, 0.31039293])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotvecmat(self):
+        A, b4 = self.A, self.b4
+        res = np.dot(b4, A)
+        tgt = np.array([1.23495091, 1.12222648])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotvecmat2(self):
+        b3, A = self.b3, self.A
+        res = np.dot(b3, A.transpose())
+        tgt = np.array([[0.58793804, 0.08957460, 0.30605758, 0.62716383]])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotvecmat3(self):
+        A, b4 = self.A, self.b4
+        res = np.dot(A.transpose(), b4)
+        tgt = np.array([1.23495091, 1.12222648])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotvecvecouter(self):
+        b1, b3 = self.b1, self.b3
+        res = np.dot(b1, b3)
+        tgt = np.array([[0.20128610, 0.08400440], [0.07190947, 0.03001058]])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotvecvecinner(self):
+        b1, b3 = self.b1, self.b3
+        res = np.dot(b3, b1)
+        tgt = np.array([[ 0.23129668]])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotcolumnvect1(self):
+        b1 = np.ones((3, 1))
+        b2 = [5.3]
+        res = np.dot(b1, b2)
+        tgt = np.array([5.3, 5.3, 5.3])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotcolumnvect2(self):
+        b1 = np.ones((3, 1)).transpose()
+        b2 = [6.2]
+        res = np.dot(b2, b1)
+        tgt = np.array([6.2, 6.2, 6.2])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotvecscalar(self):
+        np.random.seed(100)
+        b1 = np.random.rand(1, 1)
+        b2 = np.random.rand(1, 4)
+        res = np.dot(b1, b2)
+        tgt = np.array([[0.15126730, 0.23068496, 0.45905553, 0.00256425]])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_dotvecscalar2(self):
+        np.random.seed(100)
+        b1 = np.random.rand(4, 1)
+        b2 = np.random.rand(1, 1)
+        res = np.dot(b1, b2)
+        tgt = np.array([[0.00256425],[0.00131359],[0.00200324],[ 0.00398638]])
+        assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_all(self):
+        dims = [(), (1,), (1, 1)]
+        dout = [(), (1,), (1, 1), (1,), (), (1,), (1, 1), (1,), (1, 1)]
+        for dim, (dim1, dim2) in zip(dout, itertools.product(dims, dims)):
+            b1 = np.zeros(dim1)
+            b2 = np.zeros(dim2)
+            res = np.dot(b1, b2)
+            tgt = np.zeros(dim)
+            assert_(res.shape == tgt.shape)
+            assert_almost_equal(res, tgt, decimal=self.N)
+
+    def test_vecobject(self):
+        class Vec(object):
+            def __init__(self, sequence=None):
+                if sequence is None:
+                    sequence = []
+                self.array = np.array(sequence)
+
+            def __add__(self, other):
+                out = Vec()
+                out.array = self.array + other.array
+                return out
+
+            def __sub__(self, other):
+                out = Vec()
+                out.array = self.array - other.array
+                return out
+
+            def __mul__(self, other):  # with scalar
+                out = Vec(self.array.copy())
+                out.array *= other
+                return out
+
+            def __rmul__(self, other):
+                return self*other
+
+        U_non_cont = np.transpose([[1., 1.], [1., 2.]])
+        U_cont = np.ascontiguousarray(U_non_cont)
+        x = np.array([Vec([1., 0.]), Vec([0., 1.])])
+        zeros = np.array([Vec([0., 0.]), Vec([0., 0.])])
+        zeros_test = np.dot(U_cont, x) - np.dot(U_non_cont, x)
+        assert_equal(zeros[0].array, zeros_test[0].array)
+        assert_equal(zeros[1].array, zeros_test[1].array)
+
+    def test_dot_2args(self):
+        from numpy.core.multiarray import dot
+
+        a = np.array([[1, 2], [3, 4]], dtype=float)
+        b = np.array([[1, 0], [1, 1]], dtype=float)
+        c = np.array([[3, 2], [7, 4]], dtype=float)
+
+        d = dot(a, b)
+        assert_allclose(c, d)
+
+    def test_dot_3args(self):
+        from numpy.core.multiarray import dot
+
+        np.random.seed(22)
+        f = np.random.random_sample((1024, 16))
+        v = np.random.random_sample((16, 32))
+
+        r = np.empty((1024, 32))
+        for i in range(12):
+            dot(f, v, r)
+        if HAS_REFCOUNT:
+            assert_equal(sys.getrefcount(r), 2)
+        r2 = dot(f, v, out=None)
+        assert_array_equal(r2, r)
+        assert_(r is dot(f, v, out=r))
+
+        v = v[:, 0].copy()  # v.shape == (16,)
+        r = r[:, 0].copy()  # r.shape == (1024,)
+        r2 = dot(f, v)
+        assert_(r is dot(f, v, r))
+        assert_array_equal(r2, r)
+
+    def test_dot_3args_errors(self):
+        from numpy.core.multiarray import dot
+
+        np.random.seed(22)
+        f = np.random.random_sample((1024, 16))
+        v = np.random.random_sample((16, 32))
+
+        r = np.empty((1024, 31))
+        assert_raises(ValueError, dot, f, v, r)
+
+        r = np.empty((1024,))
+        assert_raises(ValueError, dot, f, v, r)
+
+        r = np.empty((32,))
+        assert_raises(ValueError, dot, f, v, r)
+
+        r = np.empty((32, 1024))
+        assert_raises(ValueError, dot, f, v, r)
+        assert_raises(ValueError, dot, f, v, r.T)
+
+        r = np.empty((1024, 64))
+        assert_raises(ValueError, dot, f, v, r[:, ::2])
+        assert_raises(ValueError, dot, f, v, r[:, :32])
+
+        r = np.empty((1024, 32), dtype=np.float32)
+        assert_raises(ValueError, dot, f, v, r)
+
+        r = np.empty((1024, 32), dtype=int)
+        assert_raises(ValueError, dot, f, v, r)
+
+    def test_dot_array_order(self):
+        a = np.array([[1, 2], [3, 4]], order='C')
+        b = np.array([[1, 2], [3, 4]], order='F')
+        res = np.dot(a, a)
+
+        # integer arrays are exact
+        assert_equal(np.dot(a, b), res)
+        assert_equal(np.dot(b, a), res)
+        assert_equal(np.dot(b, b), res)
+
+    def test_accelerate_framework_sgemv_fix(self):
+
+        def aligned_array(shape, align, dtype, order='C'):
+            d = dtype(0)
+            N = np.prod(shape)
+            tmp = np.zeros(N * d.nbytes + align, dtype=np.uint8)
+            address = tmp.__array_interface__["data"][0]
+            for offset in range(align):
+                if (address + offset) % align == 0:
+                    break
+            tmp = tmp[offset:offset+N*d.nbytes].view(dtype=dtype)
+            return tmp.reshape(shape, order=order)
+
+        def as_aligned(arr, align, dtype, order='C'):
+            aligned = aligned_array(arr.shape, align, dtype, order)
+            aligned[:] = arr[:]
+            return aligned
+
+        def assert_dot_close(A, X, desired):
+            assert_allclose(np.dot(A, X), desired, rtol=1e-5, atol=1e-7)
+
+        m = aligned_array(100, 15, np.float32)
+        s = aligned_array((100, 100), 15, np.float32)
+        np.dot(s, m)  # this will always segfault if the bug is present
+
+        testdata = itertools.product((15,32), (10000,), (200,89), ('C','F'))
+        for align, m, n, a_order in testdata:
+            # Calculation in double precision
+            A_d = np.random.rand(m, n)
+            X_d = np.random.rand(n)
+            desired = np.dot(A_d, X_d)
+            # Calculation with aligned single precision
+            A_f = as_aligned(A_d, align, np.float32, order=a_order)
+            X_f = as_aligned(X_d, align, np.float32)
+            assert_dot_close(A_f, X_f, desired)
+            # Strided A rows
+            A_d_2 = A_d[::2]
+            desired = np.dot(A_d_2, X_d)
+            A_f_2 = A_f[::2]
+            assert_dot_close(A_f_2, X_f, desired)
+            # Strided A columns, strided X vector
+            A_d_22 = A_d_2[:, ::2]
+            X_d_2 = X_d[::2]
+            desired = np.dot(A_d_22, X_d_2)
+            A_f_22 = A_f_2[:, ::2]
+            X_f_2 = X_f[::2]
+            assert_dot_close(A_f_22, X_f_2, desired)
+            # Check the strides are as expected
+            if a_order == 'F':
+                assert_equal(A_f_22.strides, (8, 8 * m))
+            else:
+                assert_equal(A_f_22.strides, (8 * n, 8))
+            assert_equal(X_f_2.strides, (8,))
+            # Strides in A rows + cols only
+            X_f_2c = as_aligned(X_f_2, align, np.float32)
+            assert_dot_close(A_f_22, X_f_2c, desired)
+            # Strides just in A cols
+            A_d_12 = A_d[:, ::2]
+            desired = np.dot(A_d_12, X_d_2)
+            A_f_12 = A_f[:, ::2]
+            assert_dot_close(A_f_12, X_f_2c, desired)
+            # Strides in A cols and X
+            assert_dot_close(A_f_12, X_f_2, desired)
+
+
+class MatmulCommon(object):
+    """Common tests for '@' operator and numpy.matmul.
+
+    """
+    # Should work with these types. Will want to add
+    # "O" at some point
+    types = "?bhilqBHILQefdgFDG"
+
+    def test_exceptions(self):
+        dims = [
+            ((1,), (2,)),            # mismatched vector vector
+            ((2, 1,), (2,)),         # mismatched matrix vector
+            ((2,), (1, 2)),          # mismatched vector matrix
+            ((1, 2), (3, 1)),        # mismatched matrix matrix
+            ((1,), ()),              # vector scalar
+            ((), (1)),               # scalar vector
+            ((1, 1), ()),            # matrix scalar
+            ((), (1, 1)),            # scalar matrix
+            ((2, 2, 1), (3, 1, 2)),  # cannot broadcast
+            ]
+
+        for dt, (dm1, dm2) in itertools.product(self.types, dims):
+            a = np.ones(dm1, dtype=dt)
+            b = np.ones(dm2, dtype=dt)
+            assert_raises(ValueError, self.matmul, a, b)
+
+    def test_shapes(self):
+        dims = [
+            ((1, 1), (2, 1, 1)),     # broadcast first argument
+            ((2, 1, 1), (1, 1)),     # broadcast second argument
+            ((2, 1, 1), (2, 1, 1)),  # matrix stack sizes match
+            ]
+
+        for dt, (dm1, dm2) in itertools.product(self.types, dims):
+            a = np.ones(dm1, dtype=dt)
+            b = np.ones(dm2, dtype=dt)
+            res = self.matmul(a, b)
+            assert_(res.shape == (2, 1, 1))
+
+        # vector vector returns scalars.
+        for dt in self.types:
+            a = np.ones((2,), dtype=dt)
+            b = np.ones((2,), dtype=dt)
+            c = self.matmul(a, b)
+            assert_(np.array(c).shape == ())
+
+    def test_result_types(self):
+        mat = np.ones((1,1))
+        vec = np.ones((1,))
+        for dt in self.types:
+            m = mat.astype(dt)
+            v = vec.astype(dt)
+            for arg in [(m, v), (v, m), (m, m)]:
+                res = self.matmul(*arg)
+                assert_(res.dtype == dt)
+
+            # vector vector returns scalars
+            res = self.matmul(v, v)
+            assert_(type(res) is np.dtype(dt).type)
+
+    def test_scalar_output(self):
+        vec1 = np.array([2])
+        vec2 = np.array([3, 4]).reshape(1, -1)
+        tgt = np.array([6, 8])
+        for dt in self.types[1:]:
+            v1 = vec1.astype(dt)
+            v2 = vec2.astype(dt)
+            res = self.matmul(v1, v2)
+            assert_equal(res, tgt)
+            res = self.matmul(v2.T, v1)
+            assert_equal(res, tgt)
+
+        # boolean type
+        vec = np.array([True, True], dtype='?').reshape(1, -1)
+        res = self.matmul(vec[:, 0], vec)
+        assert_equal(res, True)
+
+    def test_vector_vector_values(self):
+        vec1 = np.array([1, 2])
+        vec2 = np.array([3, 4]).reshape(-1, 1)
+        tgt1 = np.array([11])
+        tgt2 = np.array([[3, 6], [4, 8]])
+        for dt in self.types[1:]:
+            v1 = vec1.astype(dt)
+            v2 = vec2.astype(dt)
+            res = self.matmul(v1, v2)
+            assert_equal(res, tgt1)
+            # no broadcast, we must make v1 into a 2d ndarray
+            res = self.matmul(v2, v1.reshape(1, -1))
+            assert_equal(res, tgt2)
+
+        # boolean type
+        vec = np.array([True, True], dtype='?')
+        res = self.matmul(vec, vec)
+        assert_equal(res, True)
+
+    def test_vector_matrix_values(self):
+        vec = np.array([1, 2])
+        mat1 = np.array([[1, 2], [3, 4]])
+        mat2 = np.stack([mat1]*2, axis=0)
+        tgt1 = np.array([7, 10])
+        tgt2 = np.stack([tgt1]*2, axis=0)
+        for dt in self.types[1:]:
+            v = vec.astype(dt)
+            m1 = mat1.astype(dt)
+            m2 = mat2.astype(dt)
+            res = self.matmul(v, m1)
+            assert_equal(res, tgt1)
+            res = self.matmul(v, m2)
+            assert_equal(res, tgt2)
+
+        # boolean type
+        vec = np.array([True, False])
+        mat1 = np.array([[True, False], [False, True]])
+        mat2 = np.stack([mat1]*2, axis=0)
+        tgt1 = np.array([True, False])
+        tgt2 = np.stack([tgt1]*2, axis=0)
+
+        res = self.matmul(vec, mat1)
+        assert_equal(res, tgt1)
+        res = self.matmul(vec, mat2)
+        assert_equal(res, tgt2)
+
+    def test_matrix_vector_values(self):
+        vec = np.array([1, 2])
+        mat1 = np.array([[1, 2], [3, 4]])
+        mat2 = np.stack([mat1]*2, axis=0)
+        tgt1 = np.array([5, 11])
+        tgt2 = np.stack([tgt1]*2, axis=0)
+        for dt in self.types[1:]:
+            v = vec.astype(dt)
+            m1 = mat1.astype(dt)
+            m2 = mat2.astype(dt)
+            res = self.matmul(m1, v)
+            assert_equal(res, tgt1)
+            res = self.matmul(m2, v)
+            assert_equal(res, tgt2)
+
+        # boolean type
+        vec = np.array([True, False])
+        mat1 = np.array([[True, False], [False, True]])
+        mat2 = np.stack([mat1]*2, axis=0)
+        tgt1 = np.array([True, False])
+        tgt2 = np.stack([tgt1]*2, axis=0)
+
+        res = self.matmul(vec, mat1)
+        assert_equal(res, tgt1)
+        res = self.matmul(vec, mat2)
+        assert_equal(res, tgt2)
+
+    def test_matrix_matrix_values(self):
+        mat1 = np.array([[1, 2], [3, 4]])
+        mat2 = np.array([[1, 0], [1, 1]])
+        mat12 = np.stack([mat1, mat2], axis=0)
+        mat21 = np.stack([mat2, mat1], axis=0)
+        tgt11 = np.array([[7, 10], [15, 22]])
+        tgt12 = np.array([[3, 2], [7, 4]])
+        tgt21 = np.array([[1, 2], [4, 6]])
+        tgt12_21 = np.stack([tgt12, tgt21], axis=0)
+        tgt11_12 = np.stack((tgt11, tgt12), axis=0)
+        tgt11_21 = np.stack((tgt11, tgt21), axis=0)
+        for dt in self.types[1:]:
+            m1 = mat1.astype(dt)
+            m2 = mat2.astype(dt)
+            m12 = mat12.astype(dt)
+            m21 = mat21.astype(dt)
+
+            # matrix @ matrix
+            res = self.matmul(m1, m2)
+            assert_equal(res, tgt12)
+            res = self.matmul(m2, m1)
+            assert_equal(res, tgt21)
+
+            # stacked @ matrix
+            res = self.matmul(m12, m1)
+            assert_equal(res, tgt11_21)
+
+            # matrix @ stacked
+            res = self.matmul(m1, m12)
+            assert_equal(res, tgt11_12)
+
+            # stacked @ stacked
+            res = self.matmul(m12, m21)
+            assert_equal(res, tgt12_21)
+
+        # boolean type
+        m1 = np.array([[1, 1], [0, 0]], dtype=np.bool_)
+        m2 = np.array([[1, 0], [1, 1]], dtype=np.bool_)
+        m12 = np.stack([m1, m2], axis=0)
+        m21 = np.stack([m2, m1], axis=0)
+        tgt11 = m1
+        tgt12 = m1
+        tgt21 = np.array([[1, 1], [1, 1]], dtype=np.bool_)
+        tgt12_21 = np.stack([tgt12, tgt21], axis=0)
+        tgt11_12 = np.stack((tgt11, tgt12), axis=0)
+        tgt11_21 = np.stack((tgt11, tgt21), axis=0)
+
+        # matrix @ matrix
+        res = self.matmul(m1, m2)
+        assert_equal(res, tgt12)
+        res = self.matmul(m2, m1)
+        assert_equal(res, tgt21)
+
+        # stacked @ matrix
+        res = self.matmul(m12, m1)
+        assert_equal(res, tgt11_21)
+
+        # matrix @ stacked
+        res = self.matmul(m1, m12)
+        assert_equal(res, tgt11_12)
+
+        # stacked @ stacked
+        res = self.matmul(m12, m21)
+        assert_equal(res, tgt12_21)
+
+
+class TestMatmul(MatmulCommon):
+    matmul = np.matmul
+
+    def test_out_arg(self):
+        a = np.ones((5, 2), dtype=float)
+        b = np.array([[1, 3], [5, 7]], dtype=float)
+        tgt = np.dot(a, b)
+
+        # test as positional argument
+        msg = "out positional argument"
+        out = np.zeros((5, 2), dtype=float)
+        self.matmul(a, b, out)
+        assert_array_equal(out, tgt, err_msg=msg)
+
+        # test as keyword argument
+        msg = "out keyword argument"
+        out = np.zeros((5, 2), dtype=float)
+        self.matmul(a, b, out=out)
+        assert_array_equal(out, tgt, err_msg=msg)
+
+        # test out with not allowed type cast (safe casting)
+        msg = "Cannot cast ufunc matmul output"
+        out = np.zeros((5, 2), dtype=np.int32)
+        assert_raises_regex(TypeError, msg, self.matmul, a, b, out=out)
+
+        # test out with type upcast to complex
+        out = np.zeros((5, 2), dtype=np.complex128)
+        c = self.matmul(a, b, out=out)
+        assert_(c is out)
+        with suppress_warnings() as sup:
+            sup.filter(np.ComplexWarning, '')
+            c = c.astype(tgt.dtype)
+        assert_array_equal(c, tgt)
+
+    def test_out_contiguous(self):
+        a = np.ones((5, 2), dtype=float)
+        b = np.array([[1, 3], [5, 7]], dtype=float)
+        v = np.array([1, 3], dtype=float)
+        tgt = np.dot(a, b)
+        tgt_mv = np.dot(a, v)
+
+        # test out non-contiguous
+        out = np.ones((5, 2, 2), dtype=float)
+        c = self.matmul(a, b, out=out[..., 0])
+        assert c.base is out
+        assert_array_equal(c, tgt)
+        c = self.matmul(a, v, out=out[:, 0, 0])
+        assert_array_equal(c, tgt_mv)
+        c = self.matmul(v, a.T, out=out[:, 0, 0])
+        assert_array_equal(c, tgt_mv)
+
+        # test out contiguous in only last dim
+        out = np.ones((10, 2), dtype=float)
+        c = self.matmul(a, b, out=out[::2, :])
+        assert_array_equal(c, tgt)
+
+        # test transposes of out, args
+        out = np.ones((5, 2), dtype=float)
+        c = self.matmul(b.T, a.T, out=out.T)
+        assert_array_equal(out, tgt)
+
+    m1 = np.arange(15.).reshape(5, 3)
+    m2 = np.arange(21.).reshape(3, 7)
+    m3 = np.arange(30.).reshape(5, 6)[:, ::2]  # non-contiguous
+    vc = np.arange(10.)
+    vr = np.arange(6.)
+    m0 = np.zeros((3, 0))
+    @pytest.mark.parametrize('args', (
+            # matrix-matrix
+            (m1, m2), (m2.T, m1.T), (m2.T.copy(), m1.T), (m2.T, m1.T.copy()),
+            # matrix-matrix-transpose, contiguous and non
+            (m1, m1.T), (m1.T, m1), (m1, m3.T), (m3, m1.T),
+            (m3, m3.T), (m3.T, m3),
+            # matrix-matrix non-contiguous
+            (m3, m2), (m2.T, m3.T), (m2.T.copy(), m3.T),
+            # vector-matrix, matrix-vector, contiguous
+            (m1, vr[:3]), (vc[:5], m1), (m1.T, vc[:5]), (vr[:3], m1.T),
+            # vector-matrix, matrix-vector, vector non-contiguous
+            (m1, vr[::2]), (vc[::2], m1), (m1.T, vc[::2]), (vr[::2], m1.T),
+            # vector-matrix, matrix-vector, matrix non-contiguous
+            (m3, vr[:3]), (vc[:5], m3), (m3.T, vc[:5]), (vr[:3], m3.T),
+            # vector-matrix, matrix-vector, both non-contiguous
+            (m3, vr[::2]), (vc[::2], m3), (m3.T, vc[::2]), (vr[::2], m3.T),
+            # size == 0
+            (m0, m0.T), (m0.T, m0), (m1, m0), (m0.T, m1.T),
+        ))
+    def test_dot_equivalent(self, args):
+        r1 = np.matmul(*args)
+        r2 = np.dot(*args)
+        assert_equal(r1, r2)
+
+        r3 = np.matmul(args[0].copy(), args[1].copy())
+        assert_equal(r1, r3)
+        
+
+
+if sys.version_info[:2] >= (3, 5):
+    class TestMatmulOperator(MatmulCommon):
+        import operator
+        matmul = operator.matmul
+
+        def test_array_priority_override(self):
+
+            class A(object):
+                __array_priority__ = 1000
+
+                def __matmul__(self, other):
+                    return "A"
+
+                def __rmatmul__(self, other):
+                    return "A"
+
+            a = A()
+            b = np.ones(2)
+            assert_equal(self.matmul(a, b), "A")
+            assert_equal(self.matmul(b, a), "A")
+
+        def test_matmul_raises(self):
+            assert_raises(TypeError, self.matmul, np.int8(5), np.int8(5))
+            assert_raises(TypeError, self.matmul, np.void(b'abc'), np.void(b'abc'))
+            assert_raises(ValueError, self.matmul, np.arange(10), np.void(b'abc'))
+
+    def test_matmul_inplace():
+        # It would be nice to support in-place matmul eventually, but for now
+        # we don't have a working implementation, so better just to error out
+        # and nudge people to writing "a = a @ b".
+        a = np.eye(3)
+        b = np.eye(3)
+        assert_raises(TypeError, a.__imatmul__, b)
+        import operator
+        assert_raises(TypeError, operator.imatmul, a, b)
+        # we avoid writing the token `exec` so as not to crash python 2's
+        # parser
+        exec_ = getattr(builtins, "exec")
+        assert_raises(TypeError, exec_, "a @= b", globals(), locals())
+
+    def test_matmul_axes():
+        a = np.arange(3*4*5).reshape(3, 4, 5)
+        c = np.matmul(a, a, axes=[(-2, -1), (-1, -2), (1, 2)])
+        assert c.shape == (3, 4, 4)
+        d = np.matmul(a, a, axes=[(-2, -1), (-1, -2), (0, 1)])
+        assert d.shape == (4, 4, 3)
+        e = np.swapaxes(d, 0, 2)
+        assert_array_equal(e, c)
+        f = np.matmul(a, np.arange(3), axes=[(1, 0), (0), (0)])
+        assert f.shape == (4, 5)
+
+
+class TestInner(object):
+
+    def test_inner_type_mismatch(self):
+        c = 1.
+        A = np.array((1,1), dtype='i,i')
+
+        assert_raises(TypeError, np.inner, c, A)
+        assert_raises(TypeError, np.inner, A, c)
+
+    def test_inner_scalar_and_vector(self):
+        for dt in np.typecodes['AllInteger'] + np.typecodes['AllFloat'] + '?':
+            sca = np.array(3, dtype=dt)[()]
+            vec = np.array([1, 2], dtype=dt)
+            desired = np.array([3, 6], dtype=dt)
+            assert_equal(np.inner(vec, sca), desired)
+            assert_equal(np.inner(sca, vec), desired)
+
+    def test_vecself(self):
+        # Ticket 844.
+        # Inner product of a vector with itself segfaults or give
+        # meaningless result
+        a = np.zeros(shape=(1, 80), dtype=np.float64)
+        p = np.inner(a, a)
+        assert_almost_equal(p, 0, decimal=14)
+
+    def test_inner_product_with_various_contiguities(self):
+        # github issue 6532
+        for dt in np.typecodes['AllInteger'] + np.typecodes['AllFloat'] + '?':
+            # check an inner product involving a matrix transpose
+            A = np.array([[1, 2], [3, 4]], dtype=dt)
+            B = np.array([[1, 3], [2, 4]], dtype=dt)
+            C = np.array([1, 1], dtype=dt)
+            desired = np.array([4, 6], dtype=dt)
+            assert_equal(np.inner(A.T, C), desired)
+            assert_equal(np.inner(C, A.T), desired)
+            assert_equal(np.inner(B, C), desired)
+            assert_equal(np.inner(C, B), desired)
+            # check a matrix product
+            desired = np.array([[7, 10], [15, 22]], dtype=dt)
+            assert_equal(np.inner(A, B), desired)
+            # check the syrk vs. gemm paths
+            desired = np.array([[5, 11], [11, 25]], dtype=dt)
+            assert_equal(np.inner(A, A), desired)
+            assert_equal(np.inner(A, A.copy()), desired)
+            # check an inner product involving an aliased and reversed view
+            a = np.arange(5).astype(dt)
+            b = a[::-1]
+            desired = np.array(10, dtype=dt).item()
+            assert_equal(np.inner(b, a), desired)
+
+    def test_3d_tensor(self):
+        for dt in np.typecodes['AllInteger'] + np.typecodes['AllFloat'] + '?':
+            a = np.arange(24).reshape(2,3,4).astype(dt)
+            b = np.arange(24, 48).reshape(2,3,4).astype(dt)
+            desired = np.array(
+                [[[[ 158,  182,  206],
+                   [ 230,  254,  278]],
+
+                  [[ 566,  654,  742],
+                   [ 830,  918, 1006]],
+
+                  [[ 974, 1126, 1278],
+                   [1430, 1582, 1734]]],
+
+                 [[[1382, 1598, 1814],
+                   [2030, 2246, 2462]],
+
+                  [[1790, 2070, 2350],
+                   [2630, 2910, 3190]],
+
+                  [[2198, 2542, 2886],
+                   [3230, 3574, 3918]]]],
+                dtype=dt
+            )
+            assert_equal(np.inner(a, b), desired)
+            assert_equal(np.inner(b, a).transpose(2,3,0,1), desired)
+
+
+class TestAlen(object):
+    def test_basic(self):
+        m = np.array([1, 2, 3])
+        assert_equal(np.alen(m), 3)
+
+        m = np.array([[1, 2, 3], [4, 5, 7]])
+        assert_equal(np.alen(m), 2)
+
+        m = [1, 2, 3]
+        assert_equal(np.alen(m), 3)
+
+        m = [[1, 2, 3], [4, 5, 7]]
+        assert_equal(np.alen(m), 2)
+
+    def test_singleton(self):
+        assert_equal(np.alen(5), 1)
+
+
+class TestChoose(object):
+    def setup(self):
+        self.x = 2*np.ones((3,), dtype=int)
+        self.y = 3*np.ones((3,), dtype=int)
+        self.x2 = 2*np.ones((2, 3), dtype=int)
+        self.y2 = 3*np.ones((2, 3), dtype=int)
+        self.ind = [0, 0, 1]
+
+    def test_basic(self):
+        A = np.choose(self.ind, (self.x, self.y))
+        assert_equal(A, [2, 2, 3])
+
+    def test_broadcast1(self):
+        A = np.choose(self.ind, (self.x2, self.y2))
+        assert_equal(A, [[2, 2, 3], [2, 2, 3]])
+
+    def test_broadcast2(self):
+        A = np.choose(self.ind, (self.x, self.y2))
+        assert_equal(A, [[2, 2, 3], [2, 2, 3]])
+
+
+class TestRepeat(object):
+    def setup(self):
+        self.m = np.array([1, 2, 3, 4, 5, 6])
+        self.m_rect = self.m.reshape((2, 3))
+
+    def test_basic(self):
+        A = np.repeat(self.m, [1, 3, 2, 1, 1, 2])
+        assert_equal(A, [1, 2, 2, 2, 3,
+                         3, 4, 5, 6, 6])
+
+    def test_broadcast1(self):
+        A = np.repeat(self.m, 2)
+        assert_equal(A, [1, 1, 2, 2, 3, 3,
+                         4, 4, 5, 5, 6, 6])
+
+    def test_axis_spec(self):
+        A = np.repeat(self.m_rect, [2, 1], axis=0)
+        assert_equal(A, [[1, 2, 3],
+                         [1, 2, 3],
+                         [4, 5, 6]])
+
+        A = np.repeat(self.m_rect, [1, 3, 2], axis=1)
+        assert_equal(A, [[1, 2, 2, 2, 3, 3],
+                         [4, 5, 5, 5, 6, 6]])
+
+    def test_broadcast2(self):
+        A = np.repeat(self.m_rect, 2, axis=0)
+        assert_equal(A, [[1, 2, 3],
+                         [1, 2, 3],
+                         [4, 5, 6],
+                         [4, 5, 6]])
+
+        A = np.repeat(self.m_rect, 2, axis=1)
+        assert_equal(A, [[1, 1, 2, 2, 3, 3],
+                         [4, 4, 5, 5, 6, 6]])
+
+
+# TODO: test for multidimensional
+NEIGH_MODE = {'zero': 0, 'one': 1, 'constant': 2, 'circular': 3, 'mirror': 4}
+
+
+@pytest.mark.parametrize('dt', [float, Decimal], ids=['float', 'object'])
+class TestNeighborhoodIter(object):
+    # Simple, 2d tests
+    def test_simple2d(self, dt):
+        # Test zero and one padding for simple data type
+        x = np.array([[0, 1], [2, 3]], dtype=dt)
+        r = [np.array([[0, 0, 0], [0, 0, 1]], dtype=dt),
+             np.array([[0, 0, 0], [0, 1, 0]], dtype=dt),
+             np.array([[0, 0, 1], [0, 2, 3]], dtype=dt),
+             np.array([[0, 1, 0], [2, 3, 0]], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator(
+                x, [-1, 0, -1, 1], x[0], NEIGH_MODE['zero'])
+        assert_array_equal(l, r)
+
+        r = [np.array([[1, 1, 1], [1, 0, 1]], dtype=dt),
+             np.array([[1, 1, 1], [0, 1, 1]], dtype=dt),
+             np.array([[1, 0, 1], [1, 2, 3]], dtype=dt),
+             np.array([[0, 1, 1], [2, 3, 1]], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator(
+                x, [-1, 0, -1, 1], x[0], NEIGH_MODE['one'])
+        assert_array_equal(l, r)
+
+        r = [np.array([[4, 4, 4], [4, 0, 1]], dtype=dt),
+             np.array([[4, 4, 4], [0, 1, 4]], dtype=dt),
+             np.array([[4, 0, 1], [4, 2, 3]], dtype=dt),
+             np.array([[0, 1, 4], [2, 3, 4]], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator(
+                x, [-1, 0, -1, 1], 4, NEIGH_MODE['constant'])
+        assert_array_equal(l, r)
+
+    def test_mirror2d(self, dt):
+        x = np.array([[0, 1], [2, 3]], dtype=dt)
+        r = [np.array([[0, 0, 1], [0, 0, 1]], dtype=dt),
+             np.array([[0, 1, 1], [0, 1, 1]], dtype=dt),
+             np.array([[0, 0, 1], [2, 2, 3]], dtype=dt),
+             np.array([[0, 1, 1], [2, 3, 3]], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator(
+                x, [-1, 0, -1, 1], x[0], NEIGH_MODE['mirror'])
+        assert_array_equal(l, r)
+
+    # Simple, 1d tests
+    def test_simple(self, dt):
+        # Test padding with constant values
+        x = np.linspace(1, 5, 5).astype(dt)
+        r = [[0, 1, 2], [1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, 0]]
+        l = _multiarray_tests.test_neighborhood_iterator(
+                x, [-1, 1], x[0], NEIGH_MODE['zero'])
+        assert_array_equal(l, r)
+
+        r = [[1, 1, 2], [1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, 1]]
+        l = _multiarray_tests.test_neighborhood_iterator(
+                x, [-1, 1], x[0], NEIGH_MODE['one'])
+        assert_array_equal(l, r)
+
+        r = [[x[4], 1, 2], [1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, x[4]]]
+        l = _multiarray_tests.test_neighborhood_iterator(
+                x, [-1, 1], x[4], NEIGH_MODE['constant'])
+        assert_array_equal(l, r)
+
+    # Test mirror modes
+    def test_mirror(self, dt):
+        x = np.linspace(1, 5, 5).astype(dt)
+        r = np.array([[2, 1, 1, 2, 3], [1, 1, 2, 3, 4], [1, 2, 3, 4, 5],
+                [2, 3, 4, 5, 5], [3, 4, 5, 5, 4]], dtype=dt)
+        l = _multiarray_tests.test_neighborhood_iterator(
+                x, [-2, 2], x[1], NEIGH_MODE['mirror'])
+        assert_([i.dtype == dt for i in l])
+        assert_array_equal(l, r)
+
+    # Circular mode
+    def test_circular(self, dt):
+        x = np.linspace(1, 5, 5).astype(dt)
+        r = np.array([[4, 5, 1, 2, 3], [5, 1, 2, 3, 4], [1, 2, 3, 4, 5],
+                [2, 3, 4, 5, 1], [3, 4, 5, 1, 2]], dtype=dt)
+        l = _multiarray_tests.test_neighborhood_iterator(
+                x, [-2, 2], x[0], NEIGH_MODE['circular'])
+        assert_array_equal(l, r)
+
+
+# Test stacking neighborhood iterators
+class TestStackedNeighborhoodIter(object):
+    # Simple, 1d test: stacking 2 constant-padded neigh iterators
+    def test_simple_const(self):
+        dt = np.float64
+        # Test zero and one padding for simple data type
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([0], dtype=dt),
+             np.array([0], dtype=dt),
+             np.array([1], dtype=dt),
+             np.array([2], dtype=dt),
+             np.array([3], dtype=dt),
+             np.array([0], dtype=dt),
+             np.array([0], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [-2, 4], NEIGH_MODE['zero'], [0, 0], NEIGH_MODE['zero'])
+        assert_array_equal(l, r)
+
+        r = [np.array([1, 0, 1], dtype=dt),
+             np.array([0, 1, 2], dtype=dt),
+             np.array([1, 2, 3], dtype=dt),
+             np.array([2, 3, 0], dtype=dt),
+             np.array([3, 0, 1], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [-1, 3], NEIGH_MODE['zero'], [-1, 1], NEIGH_MODE['one'])
+        assert_array_equal(l, r)
+
+    # 2nd simple, 1d test: stacking 2 neigh iterators, mixing const padding and
+    # mirror padding
+    def test_simple_mirror(self):
+        dt = np.float64
+        # Stacking zero on top of mirror
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([0, 1, 1], dtype=dt),
+             np.array([1, 1, 2], dtype=dt),
+             np.array([1, 2, 3], dtype=dt),
+             np.array([2, 3, 3], dtype=dt),
+             np.array([3, 3, 0], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [-1, 3], NEIGH_MODE['mirror'], [-1, 1], NEIGH_MODE['zero'])
+        assert_array_equal(l, r)
+
+        # Stacking mirror on top of zero
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([1, 0, 0], dtype=dt),
+             np.array([0, 0, 1], dtype=dt),
+             np.array([0, 1, 2], dtype=dt),
+             np.array([1, 2, 3], dtype=dt),
+             np.array([2, 3, 0], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [-1, 3], NEIGH_MODE['zero'], [-2, 0], NEIGH_MODE['mirror'])
+        assert_array_equal(l, r)
+
+        # Stacking mirror on top of zero: 2nd
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([0, 1, 2], dtype=dt),
+             np.array([1, 2, 3], dtype=dt),
+             np.array([2, 3, 0], dtype=dt),
+             np.array([3, 0, 0], dtype=dt),
+             np.array([0, 0, 3], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [-1, 3], NEIGH_MODE['zero'], [0, 2], NEIGH_MODE['mirror'])
+        assert_array_equal(l, r)
+
+        # Stacking mirror on top of zero: 3rd
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([1, 0, 0, 1, 2], dtype=dt),
+             np.array([0, 0, 1, 2, 3], dtype=dt),
+             np.array([0, 1, 2, 3, 0], dtype=dt),
+             np.array([1, 2, 3, 0, 0], dtype=dt),
+             np.array([2, 3, 0, 0, 3], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [-1, 3], NEIGH_MODE['zero'], [-2, 2], NEIGH_MODE['mirror'])
+        assert_array_equal(l, r)
+
+    # 3rd simple, 1d test: stacking 2 neigh iterators, mixing const padding and
+    # circular padding
+    def test_simple_circular(self):
+        dt = np.float64
+        # Stacking zero on top of mirror
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([0, 3, 1], dtype=dt),
+             np.array([3, 1, 2], dtype=dt),
+             np.array([1, 2, 3], dtype=dt),
+             np.array([2, 3, 1], dtype=dt),
+             np.array([3, 1, 0], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [-1, 3], NEIGH_MODE['circular'], [-1, 1], NEIGH_MODE['zero'])
+        assert_array_equal(l, r)
+
+        # Stacking mirror on top of zero
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([3, 0, 0], dtype=dt),
+             np.array([0, 0, 1], dtype=dt),
+             np.array([0, 1, 2], dtype=dt),
+             np.array([1, 2, 3], dtype=dt),
+             np.array([2, 3, 0], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [-1, 3], NEIGH_MODE['zero'], [-2, 0], NEIGH_MODE['circular'])
+        assert_array_equal(l, r)
+
+        # Stacking mirror on top of zero: 2nd
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([0, 1, 2], dtype=dt),
+             np.array([1, 2, 3], dtype=dt),
+             np.array([2, 3, 0], dtype=dt),
+             np.array([3, 0, 0], dtype=dt),
+             np.array([0, 0, 1], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [-1, 3], NEIGH_MODE['zero'], [0, 2], NEIGH_MODE['circular'])
+        assert_array_equal(l, r)
+
+        # Stacking mirror on top of zero: 3rd
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([3, 0, 0, 1, 2], dtype=dt),
+             np.array([0, 0, 1, 2, 3], dtype=dt),
+             np.array([0, 1, 2, 3, 0], dtype=dt),
+             np.array([1, 2, 3, 0, 0], dtype=dt),
+             np.array([2, 3, 0, 0, 1], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [-1, 3], NEIGH_MODE['zero'], [-2, 2], NEIGH_MODE['circular'])
+        assert_array_equal(l, r)
+
+    # 4th simple, 1d test: stacking 2 neigh iterators, but with lower iterator
+    # being strictly within the array
+    def test_simple_strict_within(self):
+        dt = np.float64
+        # Stacking zero on top of zero, first neighborhood strictly inside the
+        # array
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([1, 2, 3, 0], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [1, 1], NEIGH_MODE['zero'], [-1, 2], NEIGH_MODE['zero'])
+        assert_array_equal(l, r)
+
+        # Stacking mirror on top of zero, first neighborhood strictly inside the
+        # array
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([1, 2, 3, 3], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [1, 1], NEIGH_MODE['zero'], [-1, 2], NEIGH_MODE['mirror'])
+        assert_array_equal(l, r)
+
+        # Stacking mirror on top of zero, first neighborhood strictly inside the
+        # array
+        x = np.array([1, 2, 3], dtype=dt)
+        r = [np.array([1, 2, 3, 1], dtype=dt)]
+        l = _multiarray_tests.test_neighborhood_iterator_oob(
+                x, [1, 1], NEIGH_MODE['zero'], [-1, 2], NEIGH_MODE['circular'])
+        assert_array_equal(l, r)
+
+class TestWarnings(object):
+
+    def test_complex_warning(self):
+        x = np.array([1, 2])
+        y = np.array([1-2j, 1+2j])
+
+        with warnings.catch_warnings():
+            warnings.simplefilter("error", np.ComplexWarning)
+            assert_raises(np.ComplexWarning, x.__setitem__, slice(None), y)
+            assert_equal(x, [1, 2])
+
+
+class TestMinScalarType(object):
+
+    def test_usigned_shortshort(self):
+        dt = np.min_scalar_type(2**8-1)
+        wanted = np.dtype('uint8')
+        assert_equal(wanted, dt)
+
+    def test_usigned_short(self):
+        dt = np.min_scalar_type(2**16-1)
+        wanted = np.dtype('uint16')
+        assert_equal(wanted, dt)
+
+    def test_usigned_int(self):
+        dt = np.min_scalar_type(2**32-1)
+        wanted = np.dtype('uint32')
+        assert_equal(wanted, dt)
+
+    def test_usigned_longlong(self):
+        dt = np.min_scalar_type(2**63-1)
+        wanted = np.dtype('uint64')
+        assert_equal(wanted, dt)
+
+    def test_object(self):
+        dt = np.min_scalar_type(2**64)
+        wanted = np.dtype('O')
+        assert_equal(wanted, dt)
+
+
+from numpy.core._internal import _dtype_from_pep3118
+
+
+class TestPEP3118Dtype(object):
+    def _check(self, spec, wanted):
+        dt = np.dtype(wanted)
+        actual = _dtype_from_pep3118(spec)
+        assert_equal(actual, dt,
+                     err_msg="spec %r != dtype %r" % (spec, wanted))
+
+    def test_native_padding(self):
+        align = np.dtype('i').alignment
+        for j in range(8):
+            if j == 0:
+                s = 'bi'
+            else:
+                s = 'b%dxi' % j
+            self._check('@'+s, {'f0': ('i1', 0),
+                                'f1': ('i', align*(1 + j//align))})
+            self._check('='+s, {'f0': ('i1', 0),
+                                'f1': ('i', 1+j)})
+
+    def test_native_padding_2(self):
+        # Native padding should work also for structs and sub-arrays
+        self._check('x3T{xi}', {'f0': (({'f0': ('i', 4)}, (3,)), 4)})
+        self._check('^x3T{xi}', {'f0': (({'f0': ('i', 1)}, (3,)), 1)})
+
+    def test_trailing_padding(self):
+        # Trailing padding should be included, *and*, the item size
+        # should match the alignment if in aligned mode
+        align = np.dtype('i').alignment
+        size = np.dtype('i').itemsize
+
+        def aligned(n):
+            return align*(1 + (n-1)//align)
+
+        base = dict(formats=['i'], names=['f0'])
+
+        self._check('ix',    dict(itemsize=aligned(size + 1), **base))
+        self._check('ixx',   dict(itemsize=aligned(size + 2), **base))
+        self._check('ixxx',  dict(itemsize=aligned(size + 3), **base))
+        self._check('ixxxx', dict(itemsize=aligned(size + 4), **base))
+        self._check('i7x',   dict(itemsize=aligned(size + 7), **base))
+
+        self._check('^ix',    dict(itemsize=size + 1, **base))
+        self._check('^ixx',   dict(itemsize=size + 2, **base))
+        self._check('^ixxx',  dict(itemsize=size + 3, **base))
+        self._check('^ixxxx', dict(itemsize=size + 4, **base))
+        self._check('^i7x',   dict(itemsize=size + 7, **base))
+
+    def test_native_padding_3(self):
+        dt = np.dtype(
+                [('a', 'b'), ('b', 'i'),
+                    ('sub', np.dtype('b,i')), ('c', 'i')],
+                align=True)
+        self._check("T{b:a:xxxi:b:T{b:f0:=i:f1:}:sub:xxxi:c:}", dt)
+
+        dt = np.dtype(
+                [('a', 'b'), ('b', 'i'), ('c', 'b'), ('d', 'b'),
+                    ('e', 'b'), ('sub', np.dtype('b,i', align=True))])
+        self._check("T{b:a:=i:b:b:c:b:d:b:e:T{b:f0:xxxi:f1:}:sub:}", dt)
+
+    def test_padding_with_array_inside_struct(self):
+        dt = np.dtype(
+                [('a', 'b'), ('b', 'i'), ('c', 'b', (3,)),
+                    ('d', 'i')],
+                align=True)
+        self._check("T{b:a:xxxi:b:3b:c:xi:d:}", dt)
+
+    def test_byteorder_inside_struct(self):
+        # The byte order after @T{=i} should be '=', not '@'.
+        # Check this by noting the absence of native alignment.
+        self._check('@T{^i}xi', {'f0': ({'f0': ('i', 0)}, 0),
+                                 'f1': ('i', 5)})
+
+    def test_intra_padding(self):
+        # Natively aligned sub-arrays may require some internal padding
+        align = np.dtype('i').alignment
+        size = np.dtype('i').itemsize
+
+        def aligned(n):
+            return (align*(1 + (n-1)//align))
+
+        self._check('(3)T{ix}', (dict(
+            names=['f0'],
+            formats=['i'],
+            offsets=[0],
+            itemsize=aligned(size + 1)
+        ), (3,)))
+
+    def test_char_vs_string(self):
+        dt = np.dtype('c')
+        self._check('c', dt)
+
+        dt = np.dtype([('f0', 'S1', (4,)), ('f1', 'S4')])
+        self._check('4c4s', dt)
+
+    def test_field_order(self):
+        # gh-9053 - previously, we relied on dictionary key order
+        self._check("(0)I:a:f:b:", [('a', 'I', (0,)), ('b', 'f')])
+        self._check("(0)I:b:f:a:", [('b', 'I', (0,)), ('a', 'f')])
+
+    def test_unnamed_fields(self):
+        self._check('ii',     [('f0', 'i'), ('f1', 'i')])
+        self._check('ii:f0:', [('f1', 'i'), ('f0', 'i')])
+
+        self._check('i', 'i')
+        self._check('i:f0:', [('f0', 'i')])
+
+
+class TestNewBufferProtocol(object):
+    """ Test PEP3118 buffers """
+
+    def _check_roundtrip(self, obj):
+        obj = np.asarray(obj)
+        x = memoryview(obj)
+        y = np.asarray(x)
+        y2 = np.array(x)
+        assert_(not y.flags.owndata)
+        assert_(y2.flags.owndata)
+
+        assert_equal(y.dtype, obj.dtype)
+        assert_equal(y.shape, obj.shape)
+        assert_array_equal(obj, y)
+
+        assert_equal(y2.dtype, obj.dtype)
+        assert_equal(y2.shape, obj.shape)
+        assert_array_equal(obj, y2)
+
+    def test_roundtrip(self):
+        x = np.array([1, 2, 3, 4, 5], dtype='i4')
+        self._check_roundtrip(x)
+
+        x = np.array([[1, 2], [3, 4]], dtype=np.float64)
+        self._check_roundtrip(x)
+
+        x = np.zeros((3, 3, 3), dtype=np.float32)[:, 0,:]
+        self._check_roundtrip(x)
+
+        dt = [('a', 'b'),
+              ('b', 'h'),
+              ('c', 'i'),
+              ('d', 'l'),
+              ('dx', 'q'),
+              ('e', 'B'),
+              ('f', 'H'),
+              ('g', 'I'),
+              ('h', 'L'),
+              ('hx', 'Q'),
+              ('i', np.single),
+              ('j', np.double),
+              ('k', np.longdouble),
+              ('ix', np.csingle),
+              ('jx', np.cdouble),
+              ('kx', np.clongdouble),
+              ('l', 'S4'),
+              ('m', 'U4'),
+              ('n', 'V3'),
+              ('o', '?'),
+              ('p', np.half),
+              ]
+        x = np.array(
+                [(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
+                    b'aaaa', 'bbbb', b'xxx', True, 1.0)],
+                dtype=dt)
+        self._check_roundtrip(x)
+
+        x = np.array(([[1, 2], [3, 4]],), dtype=[('a', (int, (2, 2)))])
+        self._check_roundtrip(x)
+
+        x = np.array([1, 2, 3], dtype='>i2')
+        self._check_roundtrip(x)
+
+        x = np.array([1, 2, 3], dtype='<i2')
+        self._check_roundtrip(x)
+
+        x = np.array([1, 2, 3], dtype='>i4')
+        self._check_roundtrip(x)
+
+        x = np.array([1, 2, 3], dtype='<i4')
+        self._check_roundtrip(x)
+
+        # check long long can be represented as non-native
+        x = np.array([1, 2, 3], dtype='>q')
+        self._check_roundtrip(x)
+
+        # Native-only data types can be passed through the buffer interface
+        # only in native byte order
+        if sys.byteorder == 'little':
+            x = np.array([1, 2, 3], dtype='>g')
+            assert_raises(ValueError, self._check_roundtrip, x)
+            x = np.array([1, 2, 3], dtype='<g')
+            self._check_roundtrip(x)
+        else:
+            x = np.array([1, 2, 3], dtype='>g')
+            self._check_roundtrip(x)
+            x = np.array([1, 2, 3], dtype='<g')
+            assert_raises(ValueError, self._check_roundtrip, x)
+
+    def test_roundtrip_half(self):
+        half_list = [
+            1.0,
+            -2.0,
+            6.5504 * 10**4,  # (max half precision)
+            2**-14,  # ~= 6.10352 * 10**-5 (minimum positive normal)
+            2**-24,  # ~= 5.96046 * 10**-8 (minimum strictly positive subnormal)
+            0.0,
+            -0.0,
+            float('+inf'),
+            float('-inf'),
+            0.333251953125,  # ~= 1/3
+        ]
+
+        x = np.array(half_list, dtype='>e')
+        self._check_roundtrip(x)
+        x = np.array(half_list, dtype='<e')
+        self._check_roundtrip(x)
+
+    def test_roundtrip_single_types(self):
+        for typ in np.typeDict.values():
+            dtype = np.dtype(typ)
+
+            if dtype.char in 'Mm':
+                # datetimes cannot be used in buffers
+                continue
+            if dtype.char == 'V':
+                # skip void
+                continue
+
+            x = np.zeros(4, dtype=dtype)
+            self._check_roundtrip(x)
+
+            if dtype.char not in 'qQgG':
+                dt = dtype.newbyteorder('<')
+                x = np.zeros(4, dtype=dt)
+                self._check_roundtrip(x)
+
+                dt = dtype.newbyteorder('>')
+                x = np.zeros(4, dtype=dt)
+                self._check_roundtrip(x)
+
+    def test_roundtrip_scalar(self):
+        # Issue #4015.
+        self._check_roundtrip(0)
+
+    def test_invalid_buffer_format(self):
+        # datetime64 cannot be used fully in a buffer yet
+        # Should be fixed in the next Numpy major release
+        dt = np.dtype([('a', 'uint16'), ('b', 'M8[s]')])
+        a = np.empty(3, dt)
+        assert_raises((ValueError, BufferError), memoryview, a)
+        assert_raises((ValueError, BufferError), memoryview, np.array((3), 'M8[D]'))
+
+    def test_export_simple_1d(self):
+        x = np.array([1, 2, 3, 4, 5], dtype='i')
+        y = memoryview(x)
+        assert_equal(y.format, 'i')
+        assert_equal(y.shape, (5,))
+        assert_equal(y.ndim, 1)
+        assert_equal(y.strides, (4,))
+        assert_equal(y.suboffsets, EMPTY)
+        assert_equal(y.itemsize, 4)
+
+    def test_export_simple_nd(self):
+        x = np.array([[1, 2], [3, 4]], dtype=np.float64)
+        y = memoryview(x)
+        assert_equal(y.format, 'd')
+        assert_equal(y.shape, (2, 2))
+        assert_equal(y.ndim, 2)
+        assert_equal(y.strides, (16, 8))
+        assert_equal(y.suboffsets, EMPTY)
+        assert_equal(y.itemsize, 8)
+
+    def test_export_discontiguous(self):
+        x = np.zeros((3, 3, 3), dtype=np.float32)[:, 0,:]
+        y = memoryview(x)
+        assert_equal(y.format, 'f')
+        assert_equal(y.shape, (3, 3))
+        assert_equal(y.ndim, 2)
+        assert_equal(y.strides, (36, 4))
+        assert_equal(y.suboffsets, EMPTY)
+        assert_equal(y.itemsize, 4)
+
+    def test_export_record(self):
+        dt = [('a', 'b'),
+              ('b', 'h'),
+              ('c', 'i'),
+              ('d', 'l'),
+              ('dx', 'q'),
+              ('e', 'B'),
+              ('f', 'H'),
+              ('g', 'I'),
+              ('h', 'L'),
+              ('hx', 'Q'),
+              ('i', np.single),
+              ('j', np.double),
+              ('k', np.longdouble),
+              ('ix', np.csingle),
+              ('jx', np.cdouble),
+              ('kx', np.clongdouble),
+              ('l', 'S4'),
+              ('m', 'U4'),
+              ('n', 'V3'),
+              ('o', '?'),
+              ('p', np.half),
+              ]
+        x = np.array(
+                [(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
+                    b'aaaa', 'bbbb', b'   ', True, 1.0)],
+                dtype=dt)
+        y = memoryview(x)
+        assert_equal(y.shape, (1,))
+        assert_equal(y.ndim, 1)
+        assert_equal(y.suboffsets, EMPTY)
+
+        sz = sum([np.dtype(b).itemsize for a, b in dt])
+        if np.dtype('l').itemsize == 4:
+            assert_equal(y.format, 'T{b:a:=h:b:i:c:l:d:q:dx:B:e:@H:f:=I:g:L:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}')
+        else:
+            assert_equal(y.format, 'T{b:a:=h:b:i:c:q:d:q:dx:B:e:@H:f:=I:g:Q:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}')
+        # Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides
+        if not (np.ones(1).strides[0] == np.iinfo(np.intp).max):
+            assert_equal(y.strides, (sz,))
+        assert_equal(y.itemsize, sz)
+
+    def test_export_subarray(self):
+        x = np.array(([[1, 2], [3, 4]],), dtype=[('a', ('i', (2, 2)))])
+        y = memoryview(x)
+        assert_equal(y.format, 'T{(2,2)i:a:}')
+        assert_equal(y.shape, EMPTY)
+        assert_equal(y.ndim, 0)
+        assert_equal(y.strides, EMPTY)
+        assert_equal(y.suboffsets, EMPTY)
+        assert_equal(y.itemsize, 16)
+
+    def test_export_endian(self):
+        x = np.array([1, 2, 3], dtype='>i')
+        y = memoryview(x)
+        if sys.byteorder == 'little':
+            assert_equal(y.format, '>i')
+        else:
+            assert_equal(y.format, 'i')
+
+        x = np.array([1, 2, 3], dtype='<i')
+        y = memoryview(x)
+        if sys.byteorder == 'little':
+            assert_equal(y.format, 'i')
+        else:
+            assert_equal(y.format, '<i')
+
+    def test_export_flags(self):
+        # Check SIMPLE flag, see also gh-3613 (exception should be BufferError)
+        assert_raises(ValueError,
+                      _multiarray_tests.get_buffer_info,
+                       np.arange(5)[::2], ('SIMPLE',))
+
+    def test_padding(self):
+        for j in range(8):
+            x = np.array([(1,), (2,)], dtype={'f0': (int, j)})
+            self._check_roundtrip(x)
+
+    def test_reference_leak(self):
+        if HAS_REFCOUNT:
+            count_1 = sys.getrefcount(np.core._internal)
+        a = np.zeros(4)
+        b = memoryview(a)
+        c = np.asarray(b)
+        if HAS_REFCOUNT:
+            count_2 = sys.getrefcount(np.core._internal)
+            assert_equal(count_1, count_2)
+        del c  # avoid pyflakes unused variable warning.
+
+    def test_padded_struct_array(self):
+        dt1 = np.dtype(
+                [('a', 'b'), ('b', 'i'), ('sub', np.dtype('b,i')), ('c', 'i')],
+                align=True)
+        x1 = np.arange(dt1.itemsize, dtype=np.int8).view(dt1)
+        self._check_roundtrip(x1)
+
+        dt2 = np.dtype(
+                [('a', 'b'), ('b', 'i'), ('c', 'b', (3,)), ('d', 'i')],
+                align=True)
+        x2 = np.arange(dt2.itemsize, dtype=np.int8).view(dt2)
+        self._check_roundtrip(x2)
+
+        dt3 = np.dtype(
+                [('a', 'b'), ('b', 'i'), ('c', 'b'), ('d', 'b'),
+                    ('e', 'b'), ('sub', np.dtype('b,i', align=True))])
+        x3 = np.arange(dt3.itemsize, dtype=np.int8).view(dt3)
+        self._check_roundtrip(x3)
+
+    def test_relaxed_strides(self):
+        # Test that relaxed strides are converted to non-relaxed
+        c = np.ones((1, 10, 10), dtype='i8')
+
+        # Check for NPY_RELAXED_STRIDES_CHECKING:
+        if np.ones((10, 1), order="C").flags.f_contiguous:
+            c.strides = (-1, 80, 8)
+
+        assert_(memoryview(c).strides == (800, 80, 8))
+
+        # Writing C-contiguous data to a BytesIO buffer should work
+        fd = io.BytesIO()
+        fd.write(c.data)
+
+        fortran = c.T
+        assert_(memoryview(fortran).strides == (8, 80, 800))
+
+        arr = np.ones((1, 10))
+        if arr.flags.f_contiguous:
+            shape, strides = _multiarray_tests.get_buffer_info(
+                    arr, ['F_CONTIGUOUS'])
+            assert_(strides[0] == 8)
+            arr = np.ones((10, 1), order='F')
+            shape, strides = _multiarray_tests.get_buffer_info(
+                    arr, ['C_CONTIGUOUS'])
+            assert_(strides[-1] == 8)
+
+    def test_out_of_order_fields(self):
+        dt = np.dtype(dict(
+            formats=['<i4', '<i4'],
+            names=['one', 'two'],
+            offsets=[4, 0],
+            itemsize=8
+        ))
+
+        # overlapping fields cannot be represented by PEP3118
+        arr = np.empty(1, dt)
+        with assert_raises(ValueError):
+            memoryview(arr)
+
+    def test_max_dims(self):
+        a = np.empty((1,) * 32)
+        self._check_roundtrip(a)
+
+    @pytest.mark.skipif(sys.version_info < (2, 7, 7), reason="See gh-11115")
+    def test_error_too_many_dims(self):
+        def make_ctype(shape, scalar_type):
+            t = scalar_type
+            for dim in shape[::-1]:
+                t = dim * t
+            return t
+
+        # construct a memoryview with 33 dimensions
+        c_u8_33d = make_ctype((1,)*33, ctypes.c_uint8)
+        m = memoryview(c_u8_33d())
+        assert_equal(m.ndim, 33)
+
+        assert_raises_regex(
+            RuntimeError, "ndim",
+            np.array, m)
+
+    def test_error_pointer_type(self):
+        # gh-6741
+        m = memoryview(ctypes.pointer(ctypes.c_uint8()))
+        assert_('&' in m.format)
+
+        assert_raises_regex(
+            ValueError, "format string",
+            np.array, m)
+
+    def test_error_message_unsupported(self):
+        # wchar has no corresponding numpy type - if this changes in future, we
+        # need a better way to construct an invalid memoryview format.
+        t = ctypes.c_wchar * 4
+        with assert_raises(ValueError) as cm:
+            np.array(t())
+
+        exc = cm.exception
+        if sys.version_info.major > 2:
+            with assert_raises_regex(
+                NotImplementedError,
+                r"Unrepresentable .* 'u' \(UCS-2 strings\)"
+            ):
+                raise exc.__cause__
+
+    def test_ctypes_integer_via_memoryview(self):
+        # gh-11150, due to bpo-10746
+        for c_integer in {ctypes.c_int, ctypes.c_long, ctypes.c_longlong}:
+            value = c_integer(42)
+            with warnings.catch_warnings(record=True):
+                warnings.filterwarnings('always', r'.*\bctypes\b', RuntimeWarning)
+                np.asarray(value)
+
+    def test_ctypes_struct_via_memoryview(self):
+        # gh-10528
+        class foo(ctypes.Structure):
+            _fields_ = [('a', ctypes.c_uint8), ('b', ctypes.c_uint32)]
+        f = foo(a=1, b=2)
+
+        with warnings.catch_warnings(record=True):
+            warnings.filterwarnings('always', r'.*\bctypes\b', RuntimeWarning)
+            arr = np.asarray(f)
+
+        assert_equal(arr['a'], 1)
+        assert_equal(arr['b'], 2)
+        f.a = 3
+        assert_equal(arr['a'], 3)
+
+
+class TestArrayAttributeDeletion(object):
+
+    def test_multiarray_writable_attributes_deletion(self):
+        # ticket #2046, should not seqfault, raise AttributeError
+        a = np.ones(2)
+        attr = ['shape', 'strides', 'data', 'dtype', 'real', 'imag', 'flat']
+        with suppress_warnings() as sup:
+            sup.filter(DeprecationWarning, "Assigning the 'data' attribute")
+            for s in attr:
+                assert_raises(AttributeError, delattr, a, s)
+
+    def test_multiarray_not_writable_attributes_deletion(self):
+        a = np.ones(2)
+        attr = ["ndim", "flags", "itemsize", "size", "nbytes", "base",
+                "ctypes", "T", "__array_interface__", "__array_struct__",
+                "__array_priority__", "__array_finalize__"]
+        for s in attr:
+            assert_raises(AttributeError, delattr, a, s)
+
+    def test_multiarray_flags_writable_attribute_deletion(self):
+        a = np.ones(2).flags
+        attr = ['writebackifcopy', 'updateifcopy', 'aligned', 'writeable']
+        for s in attr:
+            assert_raises(AttributeError, delattr, a, s)
+
+    def test_multiarray_flags_not_writable_attribute_deletion(self):
+        a = np.ones(2).flags
+        attr = ["contiguous", "c_contiguous", "f_contiguous", "fortran",
+                "owndata", "fnc", "forc", "behaved", "carray", "farray",
+                "num"]
+        for s in attr:
+            assert_raises(AttributeError, delattr, a, s)
+
+
+class TestArrayInterface():
+    class Foo(object):
+        def __init__(self, value):
+            self.value = value
+            self.iface = {'typestr': 'f8'}
+
+        def __float__(self):
+            return float(self.value)
+
+        @property
+        def __array_interface__(self):
+            return self.iface
+
+
+    f = Foo(0.5)
+
+    @pytest.mark.parametrize('val, iface, expected', [
+        (f, {}, 0.5),
+        ([f], {}, [0.5]),
+        ([f, f], {}, [0.5, 0.5]),
+        (f, {'shape': ()}, 0.5),
+        (f, {'shape': None}, TypeError),
+        (f, {'shape': (1, 1)}, [[0.5]]),
+        (f, {'shape': (2,)}, ValueError),
+        (f, {'strides': ()}, 0.5),
+        (f, {'strides': (2,)}, ValueError),
+        (f, {'strides': 16}, TypeError),
+        ])
+    def test_scalar_interface(self, val, iface, expected):
+        # Test scalar coercion within the array interface
+        self.f.iface = {'typestr': 'f8'}
+        self.f.iface.update(iface)
+        if HAS_REFCOUNT:
+            pre_cnt = sys.getrefcount(np.dtype('f8'))
+        if isinstance(expected, type):
+            assert_raises(expected, np.array, val)
+        else:
+            result = np.array(val)
+            assert_equal(np.array(val), expected)
+            assert result.dtype == 'f8'
+            del result
+        if HAS_REFCOUNT:
+            post_cnt = sys.getrefcount(np.dtype('f8'))
+            assert_equal(pre_cnt, post_cnt)
+
+def test_interface_no_shape():
+    class ArrayLike(object):
+        array = np.array(1)
+        __array_interface__ = array.__array_interface__
+    assert_equal(np.array(ArrayLike()), 1)
+
+
+def test_array_interface_itemsize():
+    # See gh-6361
+    my_dtype = np.dtype({'names': ['A', 'B'], 'formats': ['f4', 'f4'],
+                         'offsets': [0, 8], 'itemsize': 16})
+    a = np.ones(10, dtype=my_dtype)
+    descr_t = np.dtype(a.__array_interface__['descr'])
+    typestr_t = np.dtype(a.__array_interface__['typestr'])
+    assert_equal(descr_t.itemsize, typestr_t.itemsize)
+
+
+def test_array_interface_empty_shape():
+    # See gh-7994
+    arr = np.array([1, 2, 3])
+    interface1 = dict(arr.__array_interface__)
+    interface1['shape'] = ()
+
+    class DummyArray1(object):
+        __array_interface__ = interface1
+
+    # NOTE: Because Py2 str/Py3 bytes supports the buffer interface, setting
+    # the interface data to bytes would invoke the bug this tests for, that
+    # __array_interface__ with shape=() is not allowed if the data is an object
+    # exposing the buffer interface
+    interface2 = dict(interface1)
+    interface2['data'] = arr[0].tobytes()
+
+    class DummyArray2(object):
+        __array_interface__ = interface2
+
+    arr1 = np.asarray(DummyArray1())
+    arr2 = np.asarray(DummyArray2())
+    arr3 = arr[:1].reshape(())
+    assert_equal(arr1, arr2)
+    assert_equal(arr1, arr3)
+
+def test_array_interface_offset():
+    arr = np.array([1, 2, 3], dtype='int32')
+    interface = dict(arr.__array_interface__)
+    if sys.version_info[0] < 3:
+        interface['data'] = buffer(arr)
+    else:
+        interface['data'] = memoryview(arr)
+    interface['shape'] = (2,)
+    interface['offset'] = 4
+
+
+    class DummyArray(object):
+        __array_interface__ = interface
+
+    arr1 = np.asarray(DummyArray())
+    assert_equal(arr1, arr[1:])
+
+def test_flat_element_deletion():
+    it = np.ones(3).flat
+    try:
+        del it[1]
+        del it[1:2]
+    except TypeError:
+        pass
+    except Exception:
+        raise AssertionError
+
+
+def test_scalar_element_deletion():
+    a = np.zeros(2, dtype=[('x', 'int'), ('y', 'int')])
+    assert_raises(ValueError, a[0].__delitem__, 'x')
+
+
+class TestMemEventHook(object):
+    def test_mem_seteventhook(self):
+        # The actual tests are within the C code in
+        # multiarray/_multiarray_tests.c.src
+        _multiarray_tests.test_pydatamem_seteventhook_start()
+        # force an allocation and free of a numpy array
+        # needs to be larger then limit of small memory cacher in ctors.c
+        a = np.zeros(1000)
+        del a
+        gc.collect()
+        _multiarray_tests.test_pydatamem_seteventhook_end()
+
+class TestMapIter(object):
+    def test_mapiter(self):
+        # The actual tests are within the C code in
+        # multiarray/_multiarray_tests.c.src
+
+        a = np.arange(12).reshape((3, 4)).astype(float)
+        index = ([1, 1, 2, 0],
+                 [0, 0, 2, 3])
+        vals = [50, 50, 30, 16]
+
+        _multiarray_tests.test_inplace_increment(a, index, vals)
+        assert_equal(a, [[0.00, 1., 2.0, 19.],
+                         [104., 5., 6.0, 7.0],
+                         [8.00, 9., 40., 11.]])
+
+        b = np.arange(6).astype(float)
+        index = (np.array([1, 2, 0]),)
+        vals = [50, 4, 100.1]
+        _multiarray_tests.test_inplace_increment(b, index, vals)
+        assert_equal(b, [100.1,  51.,   6.,   3.,   4.,   5.])
+
+
+class TestAsCArray(object):
+    def test_1darray(self):
+        array = np.arange(24, dtype=np.double)
+        from_c = _multiarray_tests.test_as_c_array(array, 3)
+        assert_equal(array[3], from_c)
+
+    def test_2darray(self):
+        array = np.arange(24, dtype=np.double).reshape(3, 8)
+        from_c = _multiarray_tests.test_as_c_array(array, 2, 4)
+        assert_equal(array[2, 4], from_c)
+
+    def test_3darray(self):
+        array = np.arange(24, dtype=np.double).reshape(2, 3, 4)
+        from_c = _multiarray_tests.test_as_c_array(array, 1, 2, 3)
+        assert_equal(array[1, 2, 3], from_c)
+
+
+class TestConversion(object):
+    def test_array_scalar_relational_operation(self):
+        # All integer
+        for dt1 in np.typecodes['AllInteger']:
+            assert_(1 > np.array(0, dtype=dt1), "type %s failed" % (dt1,))
+            assert_(not 1 < np.array(0, dtype=dt1), "type %s failed" % (dt1,))
+
+            for dt2 in np.typecodes['AllInteger']:
+                assert_(np.array(1, dtype=dt1) > np.array(0, dtype=dt2),
+                        "type %s and %s failed" % (dt1, dt2))
+                assert_(not np.array(1, dtype=dt1) < np.array(0, dtype=dt2),
+                        "type %s and %s failed" % (dt1, dt2))
+
+        # Unsigned integers
+        for dt1 in 'BHILQP':
+            assert_(-1 < np.array(1, dtype=dt1), "type %s failed" % (dt1,))
+            assert_(not -1 > np.array(1, dtype=dt1), "type %s failed" % (dt1,))
+            assert_(-1 != np.array(1, dtype=dt1), "type %s failed" % (dt1,))
+
+            # Unsigned vs signed
+            for dt2 in 'bhilqp':
+                assert_(np.array(1, dtype=dt1) > np.array(-1, dtype=dt2),
+                        "type %s and %s failed" % (dt1, dt2))
+                assert_(not np.array(1, dtype=dt1) < np.array(-1, dtype=dt2),
+                        "type %s and %s failed" % (dt1, dt2))
+                assert_(np.array(1, dtype=dt1) != np.array(-1, dtype=dt2),
+                        "type %s and %s failed" % (dt1, dt2))
+
+        # Signed integers and floats
+        for dt1 in 'bhlqp' + np.typecodes['Float']:
+            assert_(1 > np.array(-1, dtype=dt1), "type %s failed" % (dt1,))
+            assert_(not 1 < np.array(-1, dtype=dt1), "type %s failed" % (dt1,))
+            assert_(-1 == np.array(-1, dtype=dt1), "type %s failed" % (dt1,))
+
+            for dt2 in 'bhlqp' + np.typecodes['Float']:
+                assert_(np.array(1, dtype=dt1) > np.array(-1, dtype=dt2),
+                        "type %s and %s failed" % (dt1, dt2))
+                assert_(not np.array(1, dtype=dt1) < np.array(-1, dtype=dt2),
+                        "type %s and %s failed" % (dt1, dt2))
+                assert_(np.array(-1, dtype=dt1) == np.array(-1, dtype=dt2),
+                        "type %s and %s failed" % (dt1, dt2))
+
+    def test_to_bool_scalar(self):
+        assert_equal(bool(np.array([False])), False)
+        assert_equal(bool(np.array([True])), True)
+        assert_equal(bool(np.array([[42]])), True)
+        assert_raises(ValueError, bool, np.array([1, 2]))
+
+        class NotConvertible(object):
+            def __bool__(self):
+                raise NotImplementedError
+            __nonzero__ = __bool__  # python 2
+
+        assert_raises(NotImplementedError, bool, np.array(NotConvertible()))
+        assert_raises(NotImplementedError, bool, np.array([NotConvertible()]))
+
+        self_containing = np.array([None])
+        self_containing[0] = self_containing
+        try:
+            Error = RecursionError
+        except NameError:
+            Error = RuntimeError  # python < 3.5
+        assert_raises(Error, bool, self_containing)  # previously stack overflow
+        self_containing[0] = None  # resolve circular reference
+
+    def test_to_int_scalar(self):
+        # gh-9972 means that these aren't always the same
+        int_funcs = (int, lambda x: x.__int__())
+        for int_func in int_funcs:
+            assert_equal(int_func(np.array([1])), 1)
+            assert_equal(int_func(np.array([0])), 0)
+            assert_equal(int_func(np.array([[42]])), 42)
+            assert_raises(TypeError, int_func, np.array([1, 2]))
+
+            # gh-9972
+            assert_equal(4, int_func(np.array('4')))
+            assert_equal(5, int_func(np.bytes_(b'5')))
+            assert_equal(6, int_func(np.unicode_(u'6')))
+
+            class HasTrunc:
+                def __trunc__(self):
+                    return 3
+            assert_equal(3, int_func(np.array(HasTrunc())))
+            assert_equal(3, int_func(np.array([HasTrunc()])))
+
+            class NotConvertible(object):
+                def __int__(self):
+                    raise NotImplementedError
+            assert_raises(NotImplementedError,
+                int_func, np.array(NotConvertible()))
+            assert_raises(NotImplementedError,
+                int_func, np.array([NotConvertible()]))
+
+
+class TestWhere(object):
+    def test_basic(self):
+        dts = [bool, np.int16, np.int32, np.int64, np.double, np.complex128,
+               np.longdouble, np.clongdouble]
+        for dt in dts:
+            c = np.ones(53, dtype=bool)
+            assert_equal(np.where( c, dt(0), dt(1)), dt(0))
+            assert_equal(np.where(~c, dt(0), dt(1)), dt(1))
+            assert_equal(np.where(True, dt(0), dt(1)), dt(0))
+            assert_equal(np.where(False, dt(0), dt(1)), dt(1))
+            d = np.ones_like(c).astype(dt)
+            e = np.zeros_like(d)
+            r = d.astype(dt)
+            c[7] = False
+            r[7] = e[7]
+            assert_equal(np.where(c, e, e), e)
+            assert_equal(np.where(c, d, e), r)
+            assert_equal(np.where(c, d, e[0]), r)
+            assert_equal(np.where(c, d[0], e), r)
+            assert_equal(np.where(c[::2], d[::2], e[::2]), r[::2])
+            assert_equal(np.where(c[1::2], d[1::2], e[1::2]), r[1::2])
+            assert_equal(np.where(c[::3], d[::3], e[::3]), r[::3])
+            assert_equal(np.where(c[1::3], d[1::3], e[1::3]), r[1::3])
+            assert_equal(np.where(c[::-2], d[::-2], e[::-2]), r[::-2])
+            assert_equal(np.where(c[::-3], d[::-3], e[::-3]), r[::-3])
+            assert_equal(np.where(c[1::-3], d[1::-3], e[1::-3]), r[1::-3])
+
+    def test_exotic(self):
+        # object
+        assert_array_equal(np.where(True, None, None), np.array(None))
+        # zero sized
+        m = np.array([], dtype=bool).reshape(0, 3)
+        b = np.array([], dtype=np.float64).reshape(0, 3)
+        assert_array_equal(np.where(m, 0, b), np.array([]).reshape(0, 3))
+
+        # object cast
+        d = np.array([-1.34, -0.16, -0.54, -0.31, -0.08, -0.95, 0.000, 0.313,
+                      0.547, -0.18, 0.876, 0.236, 1.969, 0.310, 0.699, 1.013,
+                      1.267, 0.229, -1.39, 0.487])
+        nan = float('NaN')
+        e = np.array(['5z', '0l', nan, 'Wz', nan, nan, 'Xq', 'cs', nan, nan,
+                     'QN', nan, nan, 'Fd', nan, nan, 'kp', nan, '36', 'i1'],
+                     dtype=object)
+        m = np.array([0, 0, 1, 0, 1, 1, 0, 0, 1, 1,
+                      0, 1, 1, 0, 1, 1, 0, 1, 0, 0], dtype=bool)
+
+        r = e[:]
+        r[np.where(m)] = d[np.where(m)]
+        assert_array_equal(np.where(m, d, e), r)
+
+        r = e[:]
+        r[np.where(~m)] = d[np.where(~m)]
+        assert_array_equal(np.where(m, e, d), r)
+
+        assert_array_equal(np.where(m, e, e), e)
+
+        # minimal dtype result with NaN scalar (e.g required by pandas)
+        d = np.array([1., 2.], dtype=np.float32)
+        e = float('NaN')
+        assert_equal(np.where(True, d, e).dtype, np.float32)
+        e = float('Infinity')
+        assert_equal(np.where(True, d, e).dtype, np.float32)
+        e = float('-Infinity')
+        assert_equal(np.where(True, d, e).dtype, np.float32)
+        # also check upcast
+        e = float(1e150)
+        assert_equal(np.where(True, d, e).dtype, np.float64)
+
+    def test_ndim(self):
+        c = [True, False]
+        a = np.zeros((2, 25))
+        b = np.ones((2, 25))
+        r = np.where(np.array(c)[:,np.newaxis], a, b)
+        assert_array_equal(r[0], a[0])
+        assert_array_equal(r[1], b[0])
+
+        a = a.T
+        b = b.T
+        r = np.where(c, a, b)
+        assert_array_equal(r[:,0], a[:,0])
+        assert_array_equal(r[:,1], b[:,0])
+
+    def test_dtype_mix(self):
+        c = np.array([False, True, False, False, False, False, True, False,
+                     False, False, True, False])
+        a = np.uint32(1)
+        b = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.],
+                      dtype=np.float64)
+        r = np.array([5., 1., 3., 2., -1., -4., 1., -10., 10., 1., 1., 3.],
+                     dtype=np.float64)
+        assert_equal(np.where(c, a, b), r)
+
+        a = a.astype(np.float32)
+        b = b.astype(np.int64)
+        assert_equal(np.where(c, a, b), r)
+
+        # non bool mask
+        c = c.astype(int)
+        c[c != 0] = 34242324
+        assert_equal(np.where(c, a, b), r)
+        # invert
+        tmpmask = c != 0
+        c[c == 0] = 41247212
+        c[tmpmask] = 0
+        assert_equal(np.where(c, b, a), r)
+
+    def test_foreign(self):
+        c = np.array([False, True, False, False, False, False, True, False,
+                     False, False, True, False])
+        r = np.array([5., 1., 3., 2., -1., -4., 1., -10., 10., 1., 1., 3.],
+                     dtype=np.float64)
+        a = np.ones(1, dtype='>i4')
+        b = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.],
+                     dtype=np.float64)
+        assert_equal(np.where(c, a, b), r)
+
+        b = b.astype('>f8')
+        assert_equal(np.where(c, a, b), r)
+
+        a = a.astype('<i4')
+        assert_equal(np.where(c, a, b), r)
+
+        c = c.astype('>i4')
+        assert_equal(np.where(c, a, b), r)
+
+    def test_error(self):
+        c = [True, True]
+        a = np.ones((4, 5))
+        b = np.ones((5, 5))
+        assert_raises(ValueError, np.where, c, a, a)
+        assert_raises(ValueError, np.where, c[0], a, b)
+
+    def test_string(self):
+        # gh-4778 check strings are properly filled with nulls
+        a = np.array("abc")
+        b = np.array("x" * 753)
+        assert_equal(np.where(True, a, b), "abc")
+        assert_equal(np.where(False, b, a), "abc")
+
+        # check native datatype sized strings
+        a = np.array("abcd")
+        b = np.array("x" * 8)
+        assert_equal(np.where(True, a, b), "abcd")
+        assert_equal(np.where(False, b, a), "abcd")
+
+    def test_empty_result(self):
+        # pass empty where result through an assignment which reads the data of
+        # empty arrays, error detectable with valgrind, see gh-8922
+        x = np.zeros((1, 1))
+        ibad = np.vstack(np.where(x == 99.))
+        assert_array_equal(ibad,
+                           np.atleast_2d(np.array([[],[]], dtype=np.intp)))
+
+    def test_largedim(self):
+        # invalid read regression gh-9304
+        shape = [10, 2, 3, 4, 5, 6]
+        np.random.seed(2)
+        array = np.random.rand(*shape)
+
+        for i in range(10):
+            benchmark = array.nonzero()
+            result = array.nonzero()
+            assert_array_equal(benchmark, result)
+
+
+if not IS_PYPY:
+    # sys.getsizeof() is not valid on PyPy
+    class TestSizeOf(object):
+
+        def test_empty_array(self):
+            x = np.array([])
+            assert_(sys.getsizeof(x) > 0)
+
+        def check_array(self, dtype):
+            elem_size = dtype(0).itemsize
+
+            for length in [10, 50, 100, 500]:
+                x = np.arange(length, dtype=dtype)
+                assert_(sys.getsizeof(x) > length * elem_size)
+
+        def test_array_int32(self):
+            self.check_array(np.int32)
+
+        def test_array_int64(self):
+            self.check_array(np.int64)
+
+        def test_array_float32(self):
+            self.check_array(np.float32)
+
+        def test_array_float64(self):
+            self.check_array(np.float64)
+
+        def test_view(self):
+            d = np.ones(100)
+            assert_(sys.getsizeof(d[...]) < sys.getsizeof(d))
+
+        def test_reshape(self):
+            d = np.ones(100)
+            assert_(sys.getsizeof(d) < sys.getsizeof(d.reshape(100, 1, 1).copy()))
+
+        def test_resize(self):
+            d = np.ones(100)
+            old = sys.getsizeof(d)
+            d.resize(50)
+            assert_(old > sys.getsizeof(d))
+            d.resize(150)
+            assert_(old < sys.getsizeof(d))
+
+        def test_error(self):
+            d = np.ones(100)
+            assert_raises(TypeError, d.__sizeof__, "a")
+
+
+class TestHashing(object):
+
+    def test_arrays_not_hashable(self):
+        x = np.ones(3)
+        assert_raises(TypeError, hash, x)
+
+    def test_collections_hashable(self):
+        x = np.array([])
+        assert_(not isinstance(x, collections_abc.Hashable))
+
+
+class TestArrayPriority(object):
+    # This will go away when __array_priority__ is settled, meanwhile
+    # it serves to check unintended changes.
+    op = operator
+    binary_ops = [
+        op.pow, op.add, op.sub, op.mul, op.floordiv, op.truediv, op.mod,
+        op.and_, op.or_, op.xor, op.lshift, op.rshift, op.mod, op.gt,
+        op.ge, op.lt, op.le, op.ne, op.eq
+        ]
+
+    # See #7949. Don't use "/" operator With -3 switch, since python reports it
+    # as a DeprecationWarning
+    if sys.version_info[0] < 3 and not sys.py3kwarning:
+        binary_ops.append(op.div)
+
+    class Foo(np.ndarray):
+        __array_priority__ = 100.
+
+        def __new__(cls, *args, **kwargs):
+            return np.array(*args, **kwargs).view(cls)
+
+    class Bar(np.ndarray):
+        __array_priority__ = 101.
+
+        def __new__(cls, *args, **kwargs):
+            return np.array(*args, **kwargs).view(cls)
+
+    class Other(object):
+        __array_priority__ = 1000.
+
+        def _all(self, other):
+            return self.__class__()
+
+        __add__ = __radd__ = _all
+        __sub__ = __rsub__ = _all
+        __mul__ = __rmul__ = _all
+        __pow__ = __rpow__ = _all
+        __div__ = __rdiv__ = _all
+        __mod__ = __rmod__ = _all
+        __truediv__ = __rtruediv__ = _all
+        __floordiv__ = __rfloordiv__ = _all
+        __and__ = __rand__ = _all
+        __xor__ = __rxor__ = _all
+        __or__ = __ror__ = _all
+        __lshift__ = __rlshift__ = _all
+        __rshift__ = __rrshift__ = _all
+        __eq__ = _all
+        __ne__ = _all
+        __gt__ = _all
+        __ge__ = _all
+        __lt__ = _all
+        __le__ = _all
+
+    def test_ndarray_subclass(self):
+        a = np.array([1, 2])
+        b = self.Bar([1, 2])
+        for f in self.binary_ops:
+            msg = repr(f)
+            assert_(isinstance(f(a, b), self.Bar), msg)
+            assert_(isinstance(f(b, a), self.Bar), msg)
+
+    def test_ndarray_other(self):
+        a = np.array([1, 2])
+        b = self.Other()
+        for f in self.binary_ops:
+            msg = repr(f)
+            assert_(isinstance(f(a, b), self.Other), msg)
+            assert_(isinstance(f(b, a), self.Other), msg)
+
+    def test_subclass_subclass(self):
+        a = self.Foo([1, 2])
+        b = self.Bar([1, 2])
+        for f in self.binary_ops:
+            msg = repr(f)
+            assert_(isinstance(f(a, b), self.Bar), msg)
+            assert_(isinstance(f(b, a), self.Bar), msg)
+
+    def test_subclass_other(self):
+        a = self.Foo([1, 2])
+        b = self.Other()
+        for f in self.binary_ops:
+            msg = repr(f)
+            assert_(isinstance(f(a, b), self.Other), msg)
+            assert_(isinstance(f(b, a), self.Other), msg)
+
+
+class TestBytestringArrayNonzero(object):
+
+    def test_empty_bstring_array_is_falsey(self):
+        assert_(not np.array([''], dtype=str))
+
+    def test_whitespace_bstring_array_is_falsey(self):
+        a = np.array(['spam'], dtype=str)
+        a[0] = '  \0\0'
+        assert_(not a)
+
+    def test_all_null_bstring_array_is_falsey(self):
+        a = np.array(['spam'], dtype=str)
+        a[0] = '\0\0\0\0'
+        assert_(not a)
+
+    def test_null_inside_bstring_array_is_truthy(self):
+        a = np.array(['spam'], dtype=str)
+        a[0] = ' \0 \0'
+        assert_(a)
+
+
+class TestUnicodeArrayNonzero(object):
+
+    def test_empty_ustring_array_is_falsey(self):
+        assert_(not np.array([''], dtype=np.unicode))
+
+    def test_whitespace_ustring_array_is_falsey(self):
+        a = np.array(['eggs'], dtype=np.unicode)
+        a[0] = '  \0\0'
+        assert_(not a)
+
+    def test_all_null_ustring_array_is_falsey(self):
+        a = np.array(['eggs'], dtype=np.unicode)
+        a[0] = '\0\0\0\0'
+        assert_(not a)
+
+    def test_null_inside_ustring_array_is_truthy(self):
+        a = np.array(['eggs'], dtype=np.unicode)
+        a[0] = ' \0 \0'
+        assert_(a)
+
+
+class TestFormat(object):
+
+    def test_0d(self):
+        a = np.array(np.pi)
+        assert_equal('{:0.3g}'.format(a), '3.14')
+        assert_equal('{:0.3g}'.format(a[()]), '3.14')
+
+    def test_1d_no_format(self):
+        a = np.array([np.pi])
+        assert_equal('{}'.format(a), str(a))
+
+    def test_1d_format(self):
+        # until gh-5543, ensure that the behaviour matches what it used to be
+        a = np.array([np.pi])
+        if sys.version_info[:2] >= (3, 4):
+            assert_raises(TypeError, '{:30}'.format, a)
+        else:
+            with suppress_warnings() as sup:
+                sup.filter(PendingDeprecationWarning)
+                res = '{:30}'.format(a)
+                dst = object.__format__(a, '30')
+                assert_equal(res, dst)
+
+class TestCTypes(object):
+
+    def test_ctypes_is_available(self):
+        test_arr = np.array([[1, 2, 3], [4, 5, 6]])
+
+        assert_equal(ctypes, test_arr.ctypes._ctypes)
+        assert_equal(tuple(test_arr.ctypes.shape), (2, 3))
+
+    def test_ctypes_is_not_available(self):
+        from numpy.core import _internal
+        _internal.ctypes = None
+        try:
+            test_arr = np.array([[1, 2, 3], [4, 5, 6]])
+
+            assert_(isinstance(test_arr.ctypes._ctypes,
+                               _internal._missing_ctypes))
+            assert_equal(tuple(test_arr.ctypes.shape), (2, 3))
+        finally:
+            _internal.ctypes = ctypes
+
+    def _make_readonly(x):
+        x.flags.writeable = False
+        return x
+
+    @pytest.mark.parametrize('arr', [
+        np.array([1, 2, 3]),
+        np.array([['one', 'two'], ['three', 'four']]),
+        np.array((1, 2), dtype='i4,i4'),
+        np.zeros((2,), dtype=
+            np.dtype(dict(
+                formats=['<i4', '<i4'],
+                names=['a', 'b'],
+                offsets=[0, 2],
+                itemsize=6
+            ))
+        ),
+        np.array([None], dtype=object),
+        np.array([]),
+        np.empty((0, 0)),
+        _make_readonly(np.array([1, 2, 3])),
+    ], ids=[
+        '1d',
+        '2d',
+        'structured',
+        'overlapping',
+        'object',
+        'empty',
+        'empty-2d',
+        'readonly'
+    ])
+    def test_ctypes_data_as_holds_reference(self, arr):
+        # gh-9647
+        # create a copy to ensure that pytest does not mess with the refcounts
+        arr = arr.copy()
+
+        arr_ref = weakref.ref(arr)
+
+        ctypes_ptr = arr.ctypes.data_as(ctypes.c_void_p)
+
+        # `ctypes_ptr` should hold onto `arr`
+        del arr
+        gc.collect()
+        assert_(arr_ref() is not None, "ctypes pointer did not hold onto a reference")
+
+        # but when the `ctypes_ptr` object dies, so should `arr`
+        del ctypes_ptr
+        gc.collect()
+        assert_(arr_ref() is None, "unknowable whether ctypes pointer holds a reference")
+
+
+class TestWritebackIfCopy(object):
+    # all these tests use the WRITEBACKIFCOPY mechanism
+    def test_argmax_with_out(self):
+        mat = np.eye(5)
+        out = np.empty(5, dtype='i2')
+        res = np.argmax(mat, 0, out=out)
+        assert_equal(res, range(5))
+
+    def test_argmin_with_out(self):
+        mat = -np.eye(5)
+        out = np.empty(5, dtype='i2')
+        res = np.argmin(mat, 0, out=out)
+        assert_equal(res, range(5))
+
+    def test_clip_with_out(self):
+        mat = np.eye(5)
+        out = np.eye(5, dtype='i2')
+        res = np.clip(mat, a_min=-10, a_max=0, out=out)
+        assert_(res is out)
+        assert_equal(np.sum(out), 0)
+
+    def test_insert_noncontiguous(self):
+        a = np.arange(6).reshape(2,3).T # force non-c-contiguous
+        # uses arr_insert
+        np.place(a, a>2, [44, 55])
+        assert_equal(a, np.array([[0, 44], [1, 55], [2, 44]]))
+        # hit one of the failing paths
+        assert_raises(ValueError, np.place, a, a>20, [])
+
+    def test_put_noncontiguous(self):
+        a = np.arange(6).reshape(2,3).T # force non-c-contiguous
+        np.put(a, [0, 2], [44, 55])
+        assert_equal(a, np.array([[44, 3], [55, 4], [2, 5]]))
+
+    def test_putmask_noncontiguous(self):
+        a = np.arange(6).reshape(2,3).T # force non-c-contiguous
+        # uses arr_putmask
+        np.putmask(a, a>2, a**2)
+        assert_equal(a, np.array([[0, 9], [1, 16], [2, 25]]))
+
+    def test_take_mode_raise(self):
+        a = np.arange(6, dtype='int')
+        out = np.empty(2, dtype='int')
+        np.take(a, [0, 2], out=out, mode='raise')
+        assert_equal(out, np.array([0, 2]))
+
+    def test_choose_mod_raise(self):
+        a = np.array([[1, 0, 1], [0, 1, 0], [1, 0, 1]])
+        out = np.empty((3,3), dtype='int')
+        choices = [-10, 10]
+        np.choose(a, choices, out=out, mode='raise')
+        assert_equal(out, np.array([[ 10, -10,  10],
+                                    [-10,  10, -10],
+                                    [ 10, -10,  10]]))
+
+    def test_flatiter__array__(self):
+        a = np.arange(9).reshape(3,3)
+        b = a.T.flat
+        c = b.__array__()
+        # triggers the WRITEBACKIFCOPY resolution, assuming refcount semantics
+        del c
+
+    def test_dot_out(self):
+        # if HAVE_CBLAS, will use WRITEBACKIFCOPY
+        a = np.arange(9, dtype=float).reshape(3,3)
+        b = np.dot(a, a, out=a)
+        assert_equal(b, np.array([[15, 18, 21], [42, 54, 66], [69, 90, 111]]))
+
+    def test_view_assign(self):
+        from numpy.core._multiarray_tests import npy_create_writebackifcopy, npy_resolve
+
+        arr = np.arange(9).reshape(3, 3).T
+        arr_wb = npy_create_writebackifcopy(arr)
+        assert_(arr_wb.flags.writebackifcopy)
+        assert_(arr_wb.base is arr)
+        arr_wb[...] = -100
+        npy_resolve(arr_wb)
+        # arr changes after resolve, even though we assigned to arr_wb
+        assert_equal(arr, -100)
+        # after resolve, the two arrays no longer reference each other
+        assert_(arr_wb.ctypes.data != 0)
+        assert_equal(arr_wb.base, None)
+        # assigning to arr_wb does not get transferred to arr
+        arr_wb[...] = 100
+        assert_equal(arr, -100)
+
+    def test_dealloc_warning(self):
+        with suppress_warnings() as sup:
+            sup.record(RuntimeWarning)
+            arr = np.arange(9).reshape(3, 3)
+            v = arr.T
+            _multiarray_tests.npy_abuse_writebackifcopy(v)
+            assert len(sup.log) == 1
+
+    def test_view_discard_refcount(self):
+        from numpy.core._multiarray_tests import npy_create_writebackifcopy, npy_discard
+
+        arr = np.arange(9).reshape(3, 3).T
+        orig = arr.copy()
+        if HAS_REFCOUNT:
+            arr_cnt = sys.getrefcount(arr)
+        arr_wb = npy_create_writebackifcopy(arr)
+        assert_(arr_wb.flags.writebackifcopy)
+        assert_(arr_wb.base is arr)
+        arr_wb[...] = -100
+        npy_discard(arr_wb)
+        # arr remains unchanged after discard
+        assert_equal(arr, orig)
+        # after discard, the two arrays no longer reference each other
+        assert_(arr_wb.ctypes.data != 0)
+        assert_equal(arr_wb.base, None)
+        if HAS_REFCOUNT:
+            assert_equal(arr_cnt, sys.getrefcount(arr))
+        # assigning to arr_wb does not get transferred to arr
+        arr_wb[...] = 100
+        assert_equal(arr, orig)
+
+
+class TestArange(object):
+    def test_infinite(self):
+        assert_raises_regex(
+            ValueError, "size exceeded",
+            np.arange, 0, np.inf
+        )
+
+    def test_nan_step(self):
+        assert_raises_regex(
+            ValueError, "cannot compute length",
+            np.arange, 0, 1, np.nan
+        )
+
+    def test_zero_step(self):
+        assert_raises(ZeroDivisionError, np.arange, 0, 10, 0)
+        assert_raises(ZeroDivisionError, np.arange, 0.0, 10.0, 0.0)
+
+        # empty range
+        assert_raises(ZeroDivisionError, np.arange, 0, 0, 0)
+        assert_raises(ZeroDivisionError, np.arange, 0.0, 0.0, 0.0)
+
+
+class TestArrayFinalize(object):
+    """ Tests __array_finalize__ """
+
+    def test_receives_base(self):
+        # gh-11237
+        class SavesBase(np.ndarray):
+            def __array_finalize__(self, obj):
+                self.saved_base = self.base
+
+        a = np.array(1).view(SavesBase)
+        assert_(a.saved_base is a.base)
+
+    def test_lifetime_on_error(self):
+        # gh-11237
+        class RaisesInFinalize(np.ndarray):
+            def __array_finalize__(self, obj):
+                # crash, but keep this object alive
+                raise Exception(self)
+
+        # a plain object can't be weakref'd
+        class Dummy(object): pass
+
+        # get a weak reference to an object within an array
+        obj_arr = np.array(Dummy())
+        obj_ref = weakref.ref(obj_arr[()])
+
+        # get an array that crashed in __array_finalize__
+        with assert_raises(Exception) as e:
+            obj_arr.view(RaisesInFinalize)
+        if sys.version_info.major == 2:
+            # prevent an extra reference being kept
+            sys.exc_clear()
+
+        obj_subarray = e.exception.args[0]
+        del e
+        assert_(isinstance(obj_subarray, RaisesInFinalize))
+
+        # reference should still be held by obj_arr
+        gc.collect()
+        assert_(obj_ref() is not None, "object should not already be dead")
+
+        del obj_arr
+        gc.collect()
+        assert_(obj_ref() is not None, "obj_arr should not hold the last reference")
+
+        del obj_subarray
+        gc.collect()
+        assert_(obj_ref() is None, "no references should remain")
+
+
+def test_orderconverter_with_nonASCII_unicode_ordering():
+    # gh-7475
+    a = np.arange(5)
+    assert_raises(ValueError, a.flatten, order=u'\xe2')
+
+
+def test_equal_override():
+    # gh-9153: ndarray.__eq__ uses special logic for structured arrays, which
+    # did not respect overrides with __array_priority__ or __array_ufunc__.
+    # The PR fixed this for __array_priority__ and __array_ufunc__ = None.
+    class MyAlwaysEqual(object):
+        def __eq__(self, other):
+            return "eq"
+
+        def __ne__(self, other):
+            return "ne"
+
+    class MyAlwaysEqualOld(MyAlwaysEqual):
+        __array_priority__ = 10000
+
+    class MyAlwaysEqualNew(MyAlwaysEqual):
+        __array_ufunc__ = None
+
+    array = np.array([(0, 1), (2, 3)], dtype='i4,i4')
+    for my_always_equal_cls in MyAlwaysEqualOld, MyAlwaysEqualNew:
+        my_always_equal = my_always_equal_cls()
+        assert_equal(my_always_equal == array, 'eq')
+        assert_equal(array == my_always_equal, 'eq')
+        assert_equal(my_always_equal != array, 'ne')
+        assert_equal(array != my_always_equal, 'ne')
+
+
+def test_npymath_complex():
+    # Smoketest npymath functions
+    from numpy.core._multiarray_tests import (
+        npy_cabs, npy_carg)
+
+    funcs = {npy_cabs: np.absolute,
+             npy_carg: np.angle}
+    vals = (1, np.inf, -np.inf, np.nan)
+    types = (np.complex64, np.complex128, np.clongdouble)
+
+    for fun, npfun in funcs.items():
+        for x, y in itertools.product(vals, vals):
+            for t in types:
+                z = t(complex(x, y))
+                got = fun(z)
+                expected = npfun(z)
+                assert_allclose(got, expected)
+
+
+def test_npymath_real():
+    # Smoketest npymath functions
+    from numpy.core._multiarray_tests import (
+        npy_log10, npy_cosh, npy_sinh, npy_tan, npy_tanh)
+
+    funcs = {npy_log10: np.log10,
+             npy_cosh: np.cosh,
+             npy_sinh: np.sinh,
+             npy_tan: np.tan,
+             npy_tanh: np.tanh}
+    vals = (1, np.inf, -np.inf, np.nan)
+    types = (np.float32, np.float64, np.longdouble)
+
+    with np.errstate(all='ignore'):
+        for fun, npfun in funcs.items():
+            for x, t in itertools.product(vals, types):
+                z = t(x)
+                got = fun(z)
+                expected = npfun(z)
+                assert_allclose(got, expected)
+
+def test_uintalignment_and_alignment():
+    # alignment code needs to satisfy these requrements:
+    #  1. numpy structs match C struct layout
+    #  2. ufuncs/casting is safe wrt to aligned access
+    #  3. copy code is safe wrt to "uint alidned" access
+    #
+    # Complex types are the main problem, whose alignment may not be the same
+    # as their "uint alignment".
+    #
+    # This test might only fail on certain platforms, where uint64 alignment is
+    # not equal to complex64 alignment. The second 2 tests will only fail
+    # for DEBUG=1.
+
+    d1 = np.dtype('u1,c8', align=True)
+    d2 = np.dtype('u4,c8', align=True)
+    d3 = np.dtype({'names': ['a', 'b'], 'formats': ['u1', d1]}, align=True)
+
+    assert_equal(np.zeros(1, dtype=d1)['f1'].flags['ALIGNED'], True)
+    assert_equal(np.zeros(1, dtype=d2)['f1'].flags['ALIGNED'], True)
+    assert_equal(np.zeros(1, dtype='u1,c8')['f1'].flags['ALIGNED'], False)
+
+    # check that C struct matches numpy struct size
+    s = _multiarray_tests.get_struct_alignments()
+    for d, (alignment, size) in zip([d1,d2,d3], s):
+        assert_equal(d.alignment, alignment)
+        assert_equal(d.itemsize, size)
+
+    # check that ufuncs don't complain in debug mode
+    # (this is probably OK if the aligned flag is true above)
+    src = np.zeros((2,2), dtype=d1)['f1']  # 4-byte aligned, often
+    np.exp(src)  # assert fails?
+
+    # check that copy code doesn't complain in debug mode
+    dst = np.zeros((2,2), dtype='c8')
+    dst[:,1] = src[:,1]  # assert in lowlevel_strided_loops fails?
+
+class TestAlignment(object):
+    # adapted from scipy._lib.tests.test__util.test__aligned_zeros
+    # Checks that unusual memory alignments don't trip up numpy.
+    # In particular, check RELAXED_STRIDES don't trip alignment assertions in
+    # NDEBUG mode for size-0 arrays (gh-12503)
+
+    def check(self, shape, dtype, order, align):
+        err_msg = repr((shape, dtype, order, align))
+        x = _aligned_zeros(shape, dtype, order, align=align)
+        if align is None:
+            align = np.dtype(dtype).alignment
+        assert_equal(x.__array_interface__['data'][0] % align, 0)
+        if hasattr(shape, '__len__'):
+            assert_equal(x.shape, shape, err_msg)
+        else:
+            assert_equal(x.shape, (shape,), err_msg)
+        assert_equal(x.dtype, dtype)
+        if order == "C":
+            assert_(x.flags.c_contiguous, err_msg)
+        elif order == "F":
+            if x.size > 0:
+                assert_(x.flags.f_contiguous, err_msg)
+        elif order is None:
+            assert_(x.flags.c_contiguous, err_msg)
+        else:
+            raise ValueError()
+
+    def test_various_alignments(self):
+        for align in [1, 2, 3, 4, 8, 12, 16, 32, 64, None]:
+            for n in [0, 1, 3, 11]:
+                for order in ["C", "F", None]:
+                    for dtype in list(np.typecodes["All"]) + ['i4,i4,i4']:
+                        if dtype == 'O':
+                            # object dtype can't be misaligned
+                            continue
+                        for shape in [n, (1, 2, 3, n)]:
+                            self.check(shape, np.dtype(dtype), order, align)
+
+    def test_strided_loop_alignments(self):
+        # particularly test that complex64 and float128 use right alignment
+        # code-paths, since these are particularly problematic. It is useful to
+        # turn on USE_DEBUG for this test, so lowlevel-loop asserts are run.
+        for align in [1, 2, 4, 8, 12, 16, None]:
+            xf64 = _aligned_zeros(3, np.float64)
+
+            xc64 = _aligned_zeros(3, np.complex64, align=align)
+            xf128 = _aligned_zeros(3, np.longdouble, align=align)
+
+            # test casting, both to and from misaligned
+            with suppress_warnings() as sup:
+                sup.filter(np.ComplexWarning, "Casting complex values")
+                xc64.astype('f8')
+            xf64.astype(np.complex64)
+            test = xc64 + xf64
+
+            xf128.astype('f8')
+            xf64.astype(np.longdouble)
+            test = xf128 + xf64
+
+            test = xf128 + xc64
+
+            # test copy, both to and from misaligned
+            # contig copy
+            xf64[:] = xf64.copy()
+            xc64[:] = xc64.copy()
+            xf128[:] = xf128.copy()
+            # strided copy
+            xf64[::2] = xf64[::2].copy()
+            xc64[::2] = xc64[::2].copy()
+            xf128[::2] = xf128[::2].copy()
+
+def test_getfield():
+    a = np.arange(32, dtype='uint16')
+    if sys.byteorder == 'little':
+        i = 0
+        j = 1
+    else:
+        i = 1
+        j = 0
+    b = a.getfield('int8', i)
+    assert_equal(b, a)
+    b = a.getfield('int8', j)
+    assert_equal(b, 0)
+    pytest.raises(ValueError, a.getfield, 'uint8', -1)
+    pytest.raises(ValueError, a.getfield, 'uint8', 16)
+    pytest.raises(ValueError, a.getfield, 'uint64', 0)
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/distutils/mingw/gfortran_vs2003_hack.c b/butterflow-ui/ThirdPartyCompiled/lib/numpy/distutils/mingw/gfortran_vs2003_hack.c
new file mode 100644
index 0000000..485a675
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/distutils/mingw/gfortran_vs2003_hack.c
@@ -0,0 +1,6 @@
+int _get_output_format(void)
+{
+    return 0;
+}
+
+int _imp____lc_codepage = 0;
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/src/fortranobject.c b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/src/fortranobject.c
new file mode 100644
index 0000000..4a981bf
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/src/fortranobject.c
@@ -0,0 +1,1089 @@
+#define FORTRANOBJECT_C
+#include "fortranobject.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+#include <stdlib.h>
+#include <string.h>
+
+/*
+  This file implements: FortranObject, array_from_pyobj, copy_ND_array
+
+  Author: Pearu Peterson <pearu@cens.ioc.ee>
+  $Revision: 1.52 $
+  $Date: 2005/07/11 07:44:20 $
+*/
+
+int
+F2PyDict_SetItemString(PyObject *dict, char *name, PyObject *obj)
+{
+    if (obj==NULL) {
+        fprintf(stderr, "Error loading %s\n", name);
+        if (PyErr_Occurred()) {
+            PyErr_Print();
+            PyErr_Clear();
+        }
+        return -1;
+    }
+    return PyDict_SetItemString(dict, name, obj);
+}
+
+/************************* FortranObject *******************************/
+
+typedef PyObject *(*fortranfunc)(PyObject *,PyObject *,PyObject *,void *);
+
+PyObject *
+PyFortranObject_New(FortranDataDef* defs, f2py_void_func init) {
+    int i;
+    PyFortranObject *fp = NULL;
+    PyObject *v = NULL;
+    if (init!=NULL)                           /* Initialize F90 module objects */
+        (*(init))();
+    if ((fp = PyObject_New(PyFortranObject, &PyFortran_Type))==NULL) return NULL;
+    if ((fp->dict = PyDict_New())==NULL) return NULL;
+    fp->len = 0;
+    while (defs[fp->len].name != NULL) fp->len++;
+    if (fp->len == 0) goto fail;
+    fp->defs = defs;
+    for (i=0;i<fp->len;i++)
+        if (fp->defs[i].rank == -1) {                      /* Is Fortran routine */
+            v = PyFortranObject_NewAsAttr(&(fp->defs[i]));
+            if (v==NULL) return NULL;
+            PyDict_SetItemString(fp->dict,fp->defs[i].name,v);
+        } else
+            if ((fp->defs[i].data)!=NULL) { /* Is Fortran variable or array (not allocatable) */
+                if (fp->defs[i].type == NPY_STRING) {
+                    int n = fp->defs[i].rank-1;
+                    v = PyArray_New(&PyArray_Type, n, fp->defs[i].dims.d,
+                                    NPY_STRING, NULL, fp->defs[i].data, fp->defs[i].dims.d[n],
+                                    NPY_ARRAY_FARRAY, NULL);
+                }
+                else {
+                    v = PyArray_New(&PyArray_Type, fp->defs[i].rank, fp->defs[i].dims.d,
+                                    fp->defs[i].type, NULL, fp->defs[i].data, 0, NPY_ARRAY_FARRAY,
+                                    NULL);
+                }
+                if (v==NULL) return NULL;
+                PyDict_SetItemString(fp->dict,fp->defs[i].name,v);
+            }
+    Py_XDECREF(v);
+    return (PyObject *)fp;
+ fail:
+    Py_XDECREF(v);
+    return NULL;
+}
+
+PyObject *
+PyFortranObject_NewAsAttr(FortranDataDef* defs) { /* used for calling F90 module routines */
+    PyFortranObject *fp = NULL;
+    fp = PyObject_New(PyFortranObject, &PyFortran_Type);
+    if (fp == NULL) return NULL;
+    if ((fp->dict = PyDict_New())==NULL) return NULL;
+    fp->len = 1;
+    fp->defs = defs;
+    return (PyObject *)fp;
+}
+
+/* Fortran methods */
+
+static void
+fortran_dealloc(PyFortranObject *fp) {
+    Py_XDECREF(fp->dict);
+    PyMem_Del(fp);
+}
+
+
+#if PY_VERSION_HEX >= 0x03000000
+#else
+static PyMethodDef fortran_methods[] = {
+    {NULL,          NULL}           /* sentinel */
+};
+#endif
+
+
+/* Returns number of bytes consumed from buf, or -1 on error. */
+static Py_ssize_t
+format_def(char *buf, Py_ssize_t size, FortranDataDef def)
+{
+    char *p = buf;
+    int i, n;
+
+    n = PyOS_snprintf(p, size, "array(%" NPY_INTP_FMT, def.dims.d[0]);
+    if (n < 0 || n >= size) {
+        return -1;
+    }
+    p += n;
+    size -= n;
+
+    for (i = 1; i < def.rank; i++) {
+        n = PyOS_snprintf(p, size, ",%" NPY_INTP_FMT, def.dims.d[i]);
+        if (n < 0 || n >= size) {
+            return -1;
+        }
+        p += n;
+        size -= n;
+    }
+
+    if (size <= 0) {
+        return -1;
+    }
+
+    *p++ = ')';
+    size--;
+
+    if (def.data == NULL) {
+        static const char notalloc[] = ", not allocated";
+        if ((size_t) size < sizeof(notalloc)) {
+            return -1;
+        }
+        memcpy(p, notalloc, sizeof(notalloc));
+    }
+
+    return p - buf;
+}
+
+static PyObject *
+fortran_doc(FortranDataDef def)
+{
+    char *buf, *p;
+    PyObject *s = NULL;
+    Py_ssize_t n, origsize, size = 100;
+
+    if (def.doc != NULL) {
+        size += strlen(def.doc);
+    }
+    origsize = size;
+    buf = p = (char *)PyMem_Malloc(size);
+    if (buf == NULL) {
+        return PyErr_NoMemory();
+    }
+
+    if (def.rank == -1) {
+        if (def.doc) {
+            n = strlen(def.doc);
+            if (n > size) {
+                goto fail;
+            }
+            memcpy(p, def.doc, n);
+            p += n;
+            size -= n;
+        }
+        else {
+            n = PyOS_snprintf(p, size, "%s - no docs available", def.name);
+            if (n < 0 || n >= size) {
+                goto fail;
+            }
+            p += n;
+            size -= n;
+        }
+    }
+    else {
+        PyArray_Descr *d = PyArray_DescrFromType(def.type);
+        n = PyOS_snprintf(p, size, "'%c'-", d->type);
+        Py_DECREF(d);
+        if (n < 0 || n >= size) {
+            goto fail;
+        }
+        p += n;
+        size -= n;
+
+        if (def.data == NULL) {
+            n = format_def(p, size, def) == -1;
+            if (n < 0) {
+                goto fail;
+            }
+            p += n;
+            size -= n;
+        }
+        else if (def.rank > 0) {
+            n = format_def(p, size, def);
+            if (n < 0) {
+                goto fail;
+            }
+            p += n;
+            size -= n;
+        }
+        else {
+            n = strlen("scalar");
+            if (size < n) {
+                goto fail;
+            }
+            memcpy(p, "scalar", n);
+            p += n;
+            size -= n;
+        }
+    }
+    if (size <= 1) {
+        goto fail;
+    }
+    *p++ = '\n';
+    size--;
+
+    /* p now points one beyond the last character of the string in buf */
+#if PY_VERSION_HEX >= 0x03000000
+    s = PyUnicode_FromStringAndSize(buf, p - buf);
+#else
+    s = PyString_FromStringAndSize(buf, p - buf);
+#endif
+
+    PyMem_Free(buf);
+    return s;
+
+ fail:
+    fprintf(stderr, "fortranobject.c: fortran_doc: len(p)=%zd>%zd=size:"
+                    " too long docstring required, increase size\n",
+            p - buf, origsize);
+    PyMem_Free(buf);
+    return NULL;
+}
+
+static FortranDataDef *save_def; /* save pointer of an allocatable array */
+static void set_data(char *d,npy_intp *f) {  /* callback from Fortran */
+    if (*f)                                  /* In fortran f=allocated(d) */
+        save_def->data = d;
+    else
+        save_def->data = NULL;
+    /* printf("set_data: d=%p,f=%d\n",d,*f); */
+}
+
+static PyObject *
+fortran_getattr(PyFortranObject *fp, char *name) {
+    int i,j,k,flag;
+    if (fp->dict != NULL) {
+        PyObject *v = PyDict_GetItemString(fp->dict, name);
+        if (v != NULL) {
+            Py_INCREF(v);
+            return v;
+        }
+    }
+    for (i=0,j=1;i<fp->len && (j=strcmp(name,fp->defs[i].name));i++);
+    if (j==0)
+        if (fp->defs[i].rank!=-1) {                   /* F90 allocatable array */
+            if (fp->defs[i].func==NULL) return NULL;
+            for(k=0;k<fp->defs[i].rank;++k)
+                fp->defs[i].dims.d[k]=-1;
+            save_def = &fp->defs[i];
+            (*(fp->defs[i].func))(&fp->defs[i].rank,fp->defs[i].dims.d,set_data,&flag);
+            if (flag==2)
+                k = fp->defs[i].rank + 1;
+            else
+                k = fp->defs[i].rank;
+            if (fp->defs[i].data !=NULL) {              /* array is allocated */
+                PyObject *v = PyArray_New(&PyArray_Type, k, fp->defs[i].dims.d,
+                                          fp->defs[i].type, NULL, fp->defs[i].data, 0, NPY_ARRAY_FARRAY,
+                                          NULL);
+                if (v==NULL) return NULL;
+                /* Py_INCREF(v); */
+                return v;
+            } else {                                    /* array is not allocated */
+                Py_RETURN_NONE;
+            }
+        }
+    if (strcmp(name,"__dict__")==0) {
+        Py_INCREF(fp->dict);
+        return fp->dict;
+    }
+    if (strcmp(name,"__doc__")==0) {
+#if PY_VERSION_HEX >= 0x03000000
+        PyObject *s = PyUnicode_FromString(""), *s2, *s3;
+        for (i=0;i<fp->len;i++) {
+            s2 = fortran_doc(fp->defs[i]);
+            s3 = PyUnicode_Concat(s, s2);
+            Py_DECREF(s2);
+            Py_DECREF(s);
+            s = s3;
+        }
+#else
+        PyObject *s = PyString_FromString("");
+        for (i=0;i<fp->len;i++)
+            PyString_ConcatAndDel(&s,fortran_doc(fp->defs[i]));
+#endif
+        if (PyDict_SetItemString(fp->dict, name, s))
+            return NULL;
+        return s;
+    }
+    if ((strcmp(name,"_cpointer")==0) && (fp->len==1)) {
+        PyObject *cobj = F2PyCapsule_FromVoidPtr((void *)(fp->defs[0].data),NULL);
+        if (PyDict_SetItemString(fp->dict, name, cobj))
+            return NULL;
+        return cobj;
+    }
+#if PY_VERSION_HEX >= 0x03000000
+    if (1) {
+        PyObject *str, *ret;
+        str = PyUnicode_FromString(name);
+        ret = PyObject_GenericGetAttr((PyObject *)fp, str);
+        Py_DECREF(str);
+        return ret;
+    }
+#else
+    return Py_FindMethod(fortran_methods, (PyObject *)fp, name);
+#endif
+}
+
+static int
+fortran_setattr(PyFortranObject *fp, char *name, PyObject *v) {
+    int i,j,flag;
+    PyArrayObject *arr = NULL;
+    for (i=0,j=1;i<fp->len && (j=strcmp(name,fp->defs[i].name));i++);
+    if (j==0) {
+        if (fp->defs[i].rank==-1) {
+            PyErr_SetString(PyExc_AttributeError,"over-writing fortran routine");
+            return -1;
+        }
+        if (fp->defs[i].func!=NULL) { /* is allocatable array */
+            npy_intp dims[F2PY_MAX_DIMS];
+            int k;
+            save_def = &fp->defs[i];
+            if (v!=Py_None) {     /* set new value (reallocate if needed --
+                                     see f2py generated code for more
+                                     details ) */
+                for(k=0;k<fp->defs[i].rank;k++) dims[k]=-1;
+                if ((arr = array_from_pyobj(fp->defs[i].type,dims,fp->defs[i].rank,F2PY_INTENT_IN,v))==NULL)
+                    return -1;
+                (*(fp->defs[i].func))(&fp->defs[i].rank,PyArray_DIMS(arr),set_data,&flag);
+            } else {             /* deallocate */
+                for(k=0;k<fp->defs[i].rank;k++) dims[k]=0;
+                (*(fp->defs[i].func))(&fp->defs[i].rank,dims,set_data,&flag);
+                for(k=0;k<fp->defs[i].rank;k++) dims[k]=-1;
+            }
+            memcpy(fp->defs[i].dims.d,dims,fp->defs[i].rank*sizeof(npy_intp));
+        } else {                     /* not allocatable array */
+            if ((arr = array_from_pyobj(fp->defs[i].type,fp->defs[i].dims.d,fp->defs[i].rank,F2PY_INTENT_IN,v))==NULL)
+                return -1;
+        }
+        if (fp->defs[i].data!=NULL) { /* copy Python object to Fortran array */
+            npy_intp s = PyArray_MultiplyList(fp->defs[i].dims.d,PyArray_NDIM(arr));
+            if (s==-1)
+                s = PyArray_MultiplyList(PyArray_DIMS(arr),PyArray_NDIM(arr));
+            if (s<0 ||
+                (memcpy(fp->defs[i].data,PyArray_DATA(arr),s*PyArray_ITEMSIZE(arr)))==NULL) {
+                if ((PyObject*)arr!=v) {
+                    Py_DECREF(arr);
+                }
+                return -1;
+            }
+            if ((PyObject*)arr!=v) {
+                Py_DECREF(arr);
+            }
+        } else return (fp->defs[i].func==NULL?-1:0);
+        return 0; /* successful */
+    }
+    if (fp->dict == NULL) {
+        fp->dict = PyDict_New();
+        if (fp->dict == NULL)
+            return -1;
+    }
+    if (v == NULL) {
+        int rv = PyDict_DelItemString(fp->dict, name);
+        if (rv < 0)
+            PyErr_SetString(PyExc_AttributeError,"delete non-existing fortran attribute");
+        return rv;
+    }
+    else
+        return PyDict_SetItemString(fp->dict, name, v);
+}
+
+static PyObject*
+fortran_call(PyFortranObject *fp, PyObject *arg, PyObject *kw) {
+    int i = 0;
+    /*  printf("fortran call
+        name=%s,func=%p,data=%p,%p\n",fp->defs[i].name,
+        fp->defs[i].func,fp->defs[i].data,&fp->defs[i].data); */
+    if (fp->defs[i].rank==-1) {/* is Fortran routine */
+        if (fp->defs[i].func==NULL) {
+            PyErr_Format(PyExc_RuntimeError, "no function to call");
+            return NULL;
+        }
+        else if (fp->defs[i].data==NULL)
+            /* dummy routine */
+            return (*((fortranfunc)(fp->defs[i].func)))((PyObject *)fp,arg,kw,NULL);
+        else
+            return (*((fortranfunc)(fp->defs[i].func)))((PyObject *)fp,arg,kw,
+                                                        (void *)fp->defs[i].data);
+    }
+    PyErr_Format(PyExc_TypeError, "this fortran object is not callable");
+    return NULL;
+}
+
+static PyObject *
+fortran_repr(PyFortranObject *fp)
+{
+    PyObject *name = NULL, *repr = NULL;
+    name = PyObject_GetAttrString((PyObject *)fp, "__name__");
+    PyErr_Clear();
+#if PY_VERSION_HEX >= 0x03000000
+    if (name != NULL && PyUnicode_Check(name)) {
+        repr = PyUnicode_FromFormat("<fortran %U>", name);
+    }
+    else {
+        repr = PyUnicode_FromString("<fortran object>");
+    }
+#else
+    if (name != NULL && PyString_Check(name)) {
+        repr = PyString_FromFormat("<fortran %s>", PyString_AsString(name));
+    }
+    else {
+        repr = PyString_FromString("<fortran object>");
+    }
+#endif
+    Py_XDECREF(name);
+    return repr;
+}
+
+
+PyTypeObject PyFortran_Type = {
+#if PY_VERSION_HEX >= 0x03000000
+    PyVarObject_HEAD_INIT(NULL, 0)
+#else
+    PyObject_HEAD_INIT(0)
+    0,                            /*ob_size*/
+#endif
+    "fortran",                    /*tp_name*/
+    sizeof(PyFortranObject),      /*tp_basicsize*/
+    0,                            /*tp_itemsize*/
+    /* methods */
+    (destructor)fortran_dealloc,  /*tp_dealloc*/
+    0,                            /*tp_print*/
+    (getattrfunc)fortran_getattr, /*tp_getattr*/
+    (setattrfunc)fortran_setattr, /*tp_setattr*/
+    0,                            /*tp_compare/tp_reserved*/
+    (reprfunc)fortran_repr,       /*tp_repr*/
+    0,                            /*tp_as_number*/
+    0,                            /*tp_as_sequence*/
+    0,                            /*tp_as_mapping*/
+    0,                            /*tp_hash*/
+    (ternaryfunc)fortran_call,    /*tp_call*/
+};
+
+/************************* f2py_report_atexit *******************************/
+
+#ifdef F2PY_REPORT_ATEXIT
+static int passed_time = 0;
+static int passed_counter = 0;
+static int passed_call_time = 0;
+static struct timeb start_time;
+static struct timeb stop_time;
+static struct timeb start_call_time;
+static struct timeb stop_call_time;
+static int cb_passed_time = 0;
+static int cb_passed_counter = 0;
+static int cb_passed_call_time = 0;
+static struct timeb cb_start_time;
+static struct timeb cb_stop_time;
+static struct timeb cb_start_call_time;
+static struct timeb cb_stop_call_time;
+
+extern void f2py_start_clock(void) { ftime(&start_time); }
+extern
+void f2py_start_call_clock(void) {
+    f2py_stop_clock();
+    ftime(&start_call_time);
+}
+extern
+void f2py_stop_clock(void) {
+    ftime(&stop_time);
+    passed_time += 1000*(stop_time.time - start_time.time);
+    passed_time += stop_time.millitm - start_time.millitm;
+}
+extern
+void f2py_stop_call_clock(void) {
+    ftime(&stop_call_time);
+    passed_call_time += 1000*(stop_call_time.time - start_call_time.time);
+    passed_call_time += stop_call_time.millitm - start_call_time.millitm;
+    passed_counter += 1;
+    f2py_start_clock();
+}
+
+extern void f2py_cb_start_clock(void) { ftime(&cb_start_time); }
+extern
+void f2py_cb_start_call_clock(void) {
+    f2py_cb_stop_clock();
+    ftime(&cb_start_call_time);
+}
+extern
+void f2py_cb_stop_clock(void) {
+    ftime(&cb_stop_time);
+    cb_passed_time += 1000*(cb_stop_time.time - cb_start_time.time);
+    cb_passed_time += cb_stop_time.millitm - cb_start_time.millitm;
+}
+extern
+void f2py_cb_stop_call_clock(void) {
+    ftime(&cb_stop_call_time);
+    cb_passed_call_time += 1000*(cb_stop_call_time.time - cb_start_call_time.time);
+    cb_passed_call_time += cb_stop_call_time.millitm - cb_start_call_time.millitm;
+    cb_passed_counter += 1;
+    f2py_cb_start_clock();
+}
+
+static int f2py_report_on_exit_been_here = 0;
+extern
+void f2py_report_on_exit(int exit_flag,void *name) {
+    if (f2py_report_on_exit_been_here) {
+        fprintf(stderr,"             %s\n",(char*)name);
+        return;
+    }
+    f2py_report_on_exit_been_here = 1;
+    fprintf(stderr,"                      /-----------------------\\\n");
+    fprintf(stderr,"                     < F2PY performance report >\n");
+    fprintf(stderr,"                      \\-----------------------/\n");
+    fprintf(stderr,"Overall time spent in ...\n");
+    fprintf(stderr,"(a) wrapped (Fortran/C) functions           : %8d msec\n",
+            passed_call_time);
+    fprintf(stderr,"(b) f2py interface,           %6d calls  : %8d msec\n",
+            passed_counter,passed_time);
+    fprintf(stderr,"(c) call-back (Python) functions            : %8d msec\n",
+            cb_passed_call_time);
+    fprintf(stderr,"(d) f2py call-back interface, %6d calls  : %8d msec\n",
+            cb_passed_counter,cb_passed_time);
+
+    fprintf(stderr,"(e) wrapped (Fortran/C) functions (actual) : %8d msec\n\n",
+            passed_call_time-cb_passed_call_time-cb_passed_time);
+    fprintf(stderr,"Use -DF2PY_REPORT_ATEXIT_DISABLE to disable this message.\n");
+    fprintf(stderr,"Exit status: %d\n",exit_flag);
+    fprintf(stderr,"Modules    : %s\n",(char*)name);
+}
+#endif
+
+/********************** report on array copy ****************************/
+
+#ifdef F2PY_REPORT_ON_ARRAY_COPY
+static void f2py_report_on_array_copy(PyArrayObject* arr) {
+    const npy_intp arr_size = PyArray_Size((PyObject *)arr);
+    if (arr_size>F2PY_REPORT_ON_ARRAY_COPY) {
+        fprintf(stderr,"copied an array: size=%ld, elsize=%"NPY_INTP_FMT"\n",
+                arr_size, (npy_intp)PyArray_ITEMSIZE(arr));
+    }
+}
+static void f2py_report_on_array_copy_fromany(void) {
+    fprintf(stderr,"created an array from object\n");
+}
+
+#define F2PY_REPORT_ON_ARRAY_COPY_FROMARR f2py_report_on_array_copy((PyArrayObject *)arr)
+#define F2PY_REPORT_ON_ARRAY_COPY_FROMANY f2py_report_on_array_copy_fromany()
+#else
+#define F2PY_REPORT_ON_ARRAY_COPY_FROMARR
+#define F2PY_REPORT_ON_ARRAY_COPY_FROMANY
+#endif
+
+
+/************************* array_from_obj *******************************/
+
+/*
+ * File: array_from_pyobj.c
+ *
+ * Description:
+ * ------------
+ * Provides array_from_pyobj function that returns a contiguous array
+ * object with the given dimensions and required storage order, either
+ * in row-major (C) or column-major (Fortran) order. The function
+ * array_from_pyobj is very flexible about its Python object argument
+ * that can be any number, list, tuple, or array.
+ *
+ * array_from_pyobj is used in f2py generated Python extension
+ * modules.
+ *
+ * Author: Pearu Peterson <pearu@cens.ioc.ee>
+ * Created: 13-16 January 2002
+ * $Id: fortranobject.c,v 1.52 2005/07/11 07:44:20 pearu Exp $
+ */
+
+static int check_and_fix_dimensions(const PyArrayObject* arr,
+                                    const int rank,
+                                    npy_intp *dims);
+
+static int
+count_negative_dimensions(const int rank,
+                          const npy_intp *dims) {
+    int i=0,r=0;
+    while (i<rank) {
+        if (dims[i] < 0) ++r;
+        ++i;
+    }
+    return r;
+}
+
+#ifdef DEBUG_COPY_ND_ARRAY
+void dump_dims(int rank, npy_intp* dims) {
+    int i;
+    printf("[");
+    for(i=0;i<rank;++i) {
+        printf("%3" NPY_INTP_FMT, dims[i]);
+    }
+    printf("]\n");
+}
+void dump_attrs(const PyArrayObject* obj) {
+    const PyArrayObject_fields *arr = (const PyArrayObject_fields*) obj;
+    int rank = PyArray_NDIM(arr);
+    npy_intp size = PyArray_Size((PyObject *)arr);
+    printf("\trank = %d, flags = %d, size = %" NPY_INTP_FMT  "\n",
+           rank,arr->flags,size);
+    printf("\tstrides = ");
+    dump_dims(rank,arr->strides);
+    printf("\tdimensions = ");
+    dump_dims(rank,arr->dimensions);
+}
+#endif
+
+#define SWAPTYPE(a,b,t) {t c; c = (a); (a) = (b); (b) = c; }
+
+static int swap_arrays(PyArrayObject* obj1, PyArrayObject* obj2) {
+    PyArrayObject_fields *arr1 = (PyArrayObject_fields*) obj1,
+                         *arr2 = (PyArrayObject_fields*) obj2;
+    SWAPTYPE(arr1->data,arr2->data,char*);
+    SWAPTYPE(arr1->nd,arr2->nd,int);
+    SWAPTYPE(arr1->dimensions,arr2->dimensions,npy_intp*);
+    SWAPTYPE(arr1->strides,arr2->strides,npy_intp*);
+    SWAPTYPE(arr1->base,arr2->base,PyObject*);
+    SWAPTYPE(arr1->descr,arr2->descr,PyArray_Descr*);
+    SWAPTYPE(arr1->flags,arr2->flags,int);
+    /* SWAPTYPE(arr1->weakreflist,arr2->weakreflist,PyObject*); */
+    return 0;
+}
+
+#define ARRAY_ISCOMPATIBLE(arr,type_num)                                \
+    (  (PyArray_ISINTEGER(arr) && PyTypeNum_ISINTEGER(type_num))        \
+       ||(PyArray_ISFLOAT(arr) && PyTypeNum_ISFLOAT(type_num))          \
+       ||(PyArray_ISCOMPLEX(arr) && PyTypeNum_ISCOMPLEX(type_num))      \
+       ||(PyArray_ISBOOL(arr) && PyTypeNum_ISBOOL(type_num))            \
+       )
+
+extern
+PyArrayObject* array_from_pyobj(const int type_num,
+                                npy_intp *dims,
+                                const int rank,
+                                const int intent,
+                                PyObject *obj) {
+    /*
+     * Note about reference counting
+     *  -----------------------------
+     * If the caller returns the array to Python, it must be done with
+     * Py_BuildValue("N",arr).
+     * Otherwise, if obj!=arr then the caller must call Py_DECREF(arr).
+     *
+     * Note on intent(cache,out,..)
+     * ---------------------
+     * Don't expect correct data when returning intent(cache) array.
+     *
+     */
+    char mess[200];
+    PyArrayObject *arr = NULL;
+    PyArray_Descr *descr;
+    char typechar;
+    int elsize;
+
+    if ((intent & F2PY_INTENT_HIDE)
+        || ((intent & F2PY_INTENT_CACHE) && (obj==Py_None))
+        || ((intent & F2PY_OPTIONAL) && (obj==Py_None))
+        ) {
+        /* intent(cache), optional, intent(hide) */
+        if (count_negative_dimensions(rank,dims) > 0) {
+            int i;
+            strcpy(mess, "failed to create intent(cache|hide)|optional array"
+                   "-- must have defined dimensions but got (");
+            for(i=0;i<rank;++i)
+                sprintf(mess+strlen(mess),"%" NPY_INTP_FMT ",",dims[i]);
+            strcat(mess, ")");
+            PyErr_SetString(PyExc_ValueError,mess);
+            return NULL;
+        }
+        arr = (PyArrayObject *)
+            PyArray_New(&PyArray_Type, rank, dims, type_num,
+                        NULL,NULL,1,
+                        !(intent&F2PY_INTENT_C),
+                        NULL);
+        if (arr==NULL) return NULL;
+        if (!(intent & F2PY_INTENT_CACHE))
+            PyArray_FILLWBYTE(arr, 0);
+        return arr;
+    }
+
+    descr = PyArray_DescrFromType(type_num);
+    /* compatibility with NPY_CHAR */
+    if (type_num == NPY_STRING) {
+        PyArray_DESCR_REPLACE(descr);
+        if (descr == NULL) {
+            return NULL;
+        }
+        descr->elsize = 1;
+        descr->type = NPY_CHARLTR;
+    }
+    elsize = descr->elsize;
+    typechar = descr->type;
+    Py_DECREF(descr);
+    if (PyArray_Check(obj)) {
+        arr = (PyArrayObject *)obj;
+
+        if (intent & F2PY_INTENT_CACHE) {
+            /* intent(cache) */
+            if (PyArray_ISONESEGMENT(arr)
+                && PyArray_ITEMSIZE(arr)>=elsize) {
+                if (check_and_fix_dimensions(arr, rank, dims)) {
+                    return NULL;
+                }
+                if (intent & F2PY_INTENT_OUT)
+                    Py_INCREF(arr);
+                return arr;
+            }
+            strcpy(mess, "failed to initialize intent(cache) array");
+            if (!PyArray_ISONESEGMENT(arr))
+                strcat(mess, " -- input must be in one segment");
+            if (PyArray_ITEMSIZE(arr)<elsize)
+                sprintf(mess+strlen(mess),
+                        " -- expected at least elsize=%d but got %" NPY_INTP_FMT,
+                        elsize,
+                        (npy_intp)PyArray_ITEMSIZE(arr)
+                        );
+            PyErr_SetString(PyExc_ValueError,mess);
+            return NULL;
+        }
+
+        /* here we have always intent(in) or intent(inout) or intent(inplace) */
+
+        if (check_and_fix_dimensions(arr, rank, dims)) {
+            return NULL;
+        }
+        /*
+        printf("intent alignment=%d\n", F2PY_GET_ALIGNMENT(intent));
+        printf("alignment check=%d\n", F2PY_CHECK_ALIGNMENT(arr, intent));
+        int i;
+        for (i=1;i<=16;i++)
+          printf("i=%d isaligned=%d\n", i, ARRAY_ISALIGNED(arr, i));
+        */
+        if ((! (intent & F2PY_INTENT_COPY))
+            && PyArray_ITEMSIZE(arr)==elsize
+            && ARRAY_ISCOMPATIBLE(arr,type_num)
+            && F2PY_CHECK_ALIGNMENT(arr, intent)
+            ) {
+            if ((intent & F2PY_INTENT_C)?PyArray_ISCARRAY(arr):PyArray_ISFARRAY(arr)) {
+                if ((intent & F2PY_INTENT_OUT)) {
+                    Py_INCREF(arr);
+                }
+                /* Returning input array */
+                return arr;
+            }
+        }
+
+        if (intent & F2PY_INTENT_INOUT) {
+            strcpy(mess, "failed to initialize intent(inout) array");
+            if ((intent & F2PY_INTENT_C) && !PyArray_ISCARRAY(arr))
+                strcat(mess, " -- input not contiguous");
+            if (!(intent & F2PY_INTENT_C) && !PyArray_ISFARRAY(arr))
+                strcat(mess, " -- input not fortran contiguous");
+            if (PyArray_ITEMSIZE(arr)!=elsize)
+                sprintf(mess+strlen(mess),
+                        " -- expected elsize=%d but got %" NPY_INTP_FMT,
+                        elsize,
+                        (npy_intp)PyArray_ITEMSIZE(arr)
+                        );
+            if (!(ARRAY_ISCOMPATIBLE(arr,type_num)))
+                sprintf(mess+strlen(mess)," -- input '%c' not compatible to '%c'",
+                        PyArray_DESCR(arr)->type,typechar);
+            if (!(F2PY_CHECK_ALIGNMENT(arr, intent)))
+              sprintf(mess+strlen(mess)," -- input not %d-aligned", F2PY_GET_ALIGNMENT(intent));
+            PyErr_SetString(PyExc_ValueError,mess);
+            return NULL;
+        }
+
+        /* here we have always intent(in) or intent(inplace) */
+
+        {
+            PyArrayObject * retarr;
+            retarr = (PyArrayObject *) \
+                PyArray_New(&PyArray_Type, PyArray_NDIM(arr), PyArray_DIMS(arr), type_num,
+                            NULL,NULL,1,
+                            !(intent&F2PY_INTENT_C),
+                            NULL);
+            if (retarr==NULL)
+                return NULL;
+            F2PY_REPORT_ON_ARRAY_COPY_FROMARR;
+            if (PyArray_CopyInto(retarr, arr)) {
+                Py_DECREF(retarr);
+                return NULL;
+            }
+            if (intent & F2PY_INTENT_INPLACE) {
+                if (swap_arrays(arr,retarr))
+                    return NULL; /* XXX: set exception */
+                Py_XDECREF(retarr);
+                if (intent & F2PY_INTENT_OUT)
+                    Py_INCREF(arr);
+            } else {
+                arr = retarr;
+            }
+        }
+        return arr;
+    }
+
+    if ((intent & F2PY_INTENT_INOUT) ||
+            (intent & F2PY_INTENT_INPLACE) ||
+            (intent & F2PY_INTENT_CACHE)) {
+        PyErr_SetString(PyExc_TypeError,
+                        "failed to initialize intent(inout|inplace|cache) "
+                        "array, input not an array");
+        return NULL;
+    }
+
+    {
+        PyArray_Descr * descr = PyArray_DescrFromType(type_num);
+        /* compatibility with NPY_CHAR */
+        if (type_num == NPY_STRING) {
+            PyArray_DESCR_REPLACE(descr);
+            if (descr == NULL) {
+                return NULL;
+            }
+            descr->elsize = 1;
+            descr->type = NPY_CHARLTR;
+        }
+        F2PY_REPORT_ON_ARRAY_COPY_FROMANY;
+        arr = (PyArrayObject *) \
+            PyArray_FromAny(obj, descr, 0,0,
+                            ((intent & F2PY_INTENT_C)?NPY_ARRAY_CARRAY:NPY_ARRAY_FARRAY) \
+                            | NPY_ARRAY_FORCECAST, NULL);
+        if (arr==NULL)
+            return NULL;
+        if (check_and_fix_dimensions(arr, rank, dims)) {
+            return NULL;
+        }
+        return arr;
+    }
+
+}
+
+/*****************************************/
+/* Helper functions for array_from_pyobj */
+/*****************************************/
+
+static
+int check_and_fix_dimensions(const PyArrayObject* arr, const int rank, npy_intp *dims)
+{
+    /*
+     * This function fills in blanks (that are -1's) in dims list using
+     * the dimensions from arr. It also checks that non-blank dims will
+     * match with the corresponding values in arr dimensions.
+     *
+     * Returns 0 if the function is successful.
+     *
+     * If an error condition is detected, an exception is set and 1 is returned.
+     */
+    const npy_intp arr_size = (PyArray_NDIM(arr))?PyArray_Size((PyObject *)arr):1;
+#ifdef DEBUG_COPY_ND_ARRAY
+    dump_attrs(arr);
+    printf("check_and_fix_dimensions:init: dims=");
+    dump_dims(rank,dims);
+#endif
+    if (rank > PyArray_NDIM(arr)) { /* [1,2] -> [[1],[2]]; 1 -> [[1]]  */
+        npy_intp new_size = 1;
+        int free_axe = -1;
+        int i;
+        npy_intp d;
+        /* Fill dims where -1 or 0; check dimensions; calc new_size; */
+        for(i=0;i<PyArray_NDIM(arr);++i) {
+            d = PyArray_DIM(arr,i);
+            if (dims[i] >= 0) {
+                if (d>1 && dims[i]!=d) {
+                    PyErr_Format(PyExc_ValueError,
+                                 "%d-th dimension must be fixed to %"
+                                 NPY_INTP_FMT " but got %" NPY_INTP_FMT "\n",
+                                 i, dims[i], d);
+                    return 1;
+                }
+                if (!dims[i]) dims[i] = 1;
+            } else {
+                dims[i] = d ? d : 1;
+            }
+            new_size *= dims[i];
+        }
+        for(i=PyArray_NDIM(arr);i<rank;++i)
+            if (dims[i]>1) {
+                PyErr_Format(PyExc_ValueError,
+                             "%d-th dimension must be %" NPY_INTP_FMT
+                             " but got 0 (not defined).\n",
+                             i, dims[i]);
+                return 1;
+            } else if (free_axe<0)
+                free_axe = i;
+            else
+                dims[i] = 1;
+        if (free_axe>=0) {
+            dims[free_axe] = arr_size/new_size;
+            new_size *= dims[free_axe];
+        }
+        if (new_size != arr_size) {
+            PyErr_Format(PyExc_ValueError,
+                         "unexpected array size: new_size=%" NPY_INTP_FMT
+                         ", got array with arr_size=%" NPY_INTP_FMT
+                         " (maybe too many free indices)\n",
+                         new_size, arr_size);
+            return 1;
+        }
+    } else if (rank==PyArray_NDIM(arr)) {
+        npy_intp new_size = 1;
+        int i;
+        npy_intp d;
+        for (i=0; i<rank; ++i) {
+            d = PyArray_DIM(arr,i);
+            if (dims[i]>=0) {
+                if (d > 1 && d!=dims[i]) {
+                    PyErr_Format(PyExc_ValueError,
+                                 "%d-th dimension must be fixed to %"
+                                 NPY_INTP_FMT " but got %" NPY_INTP_FMT "\n",
+                                 i, dims[i], d);
+                    return 1;
+                }
+                if (!dims[i]) dims[i] = 1;
+            } else dims[i] = d;
+            new_size *= dims[i];
+        }
+        if (new_size != arr_size) {
+            PyErr_Format(PyExc_ValueError,
+                         "unexpected array size: new_size=%" NPY_INTP_FMT
+                         ", got array with arr_size=%" NPY_INTP_FMT "\n",
+                         new_size, arr_size);
+            return 1;
+        }
+    } else { /* [[1,2]] -> [[1],[2]] */
+        int i,j;
+        npy_intp d;
+        int effrank;
+        npy_intp size;
+        for (i=0,effrank=0;i<PyArray_NDIM(arr);++i)
+            if (PyArray_DIM(arr,i)>1) ++effrank;
+        if (dims[rank-1]>=0)
+            if (effrank>rank) {
+                PyErr_Format(PyExc_ValueError,
+                             "too many axes: %d (effrank=%d), "
+                             "expected rank=%d\n",
+                             PyArray_NDIM(arr), effrank, rank);
+                return 1;
+            }
+
+        for (i=0,j=0;i<rank;++i) {
+            while (j<PyArray_NDIM(arr) && PyArray_DIM(arr,j)<2) ++j;
+            if (j>=PyArray_NDIM(arr)) d = 1;
+            else d = PyArray_DIM(arr,j++);
+            if (dims[i]>=0) {
+                if (d>1 && d!=dims[i]) {
+                    PyErr_Format(PyExc_ValueError,
+                                 "%d-th dimension must be fixed to %"
+                                 NPY_INTP_FMT " but got %" NPY_INTP_FMT
+                                 " (real index=%d)\n",
+                                 i, dims[i], d, j-1);
+                    return 1;
+                }
+                if (!dims[i]) dims[i] = 1;
+            } else
+                dims[i] = d;
+        }
+
+        for (i=rank;i<PyArray_NDIM(arr);++i) { /* [[1,2],[3,4]] -> [1,2,3,4] */
+            while (j<PyArray_NDIM(arr) && PyArray_DIM(arr,j)<2) ++j;
+            if (j>=PyArray_NDIM(arr)) d = 1;
+            else d = PyArray_DIM(arr,j++);
+            dims[rank-1] *= d;
+        }
+        for (i=0,size=1;i<rank;++i) size *= dims[i];
+        if (size != arr_size) {
+            char msg[200];
+            int len;
+            snprintf(msg, sizeof(msg),
+                     "unexpected array size: size=%" NPY_INTP_FMT
+                     ", arr_size=%" NPY_INTP_FMT
+                     ", rank=%d, effrank=%d, arr.nd=%d, dims=[",
+                     size, arr_size, rank, effrank, PyArray_NDIM(arr));
+            for (i = 0; i < rank; ++i) {
+                len = strlen(msg);
+                snprintf(msg + len, sizeof(msg) - len,
+                         " %" NPY_INTP_FMT, dims[i]);
+            }
+            len = strlen(msg);
+            snprintf(msg + len, sizeof(msg) - len, " ], arr.dims=[");
+            for (i = 0; i < PyArray_NDIM(arr); ++i) {
+                len = strlen(msg);
+                snprintf(msg + len, sizeof(msg) - len,
+                         " %" NPY_INTP_FMT, PyArray_DIM(arr, i));
+            }
+            len = strlen(msg);
+            snprintf(msg + len, sizeof(msg) - len, " ]\n");
+            PyErr_SetString(PyExc_ValueError, msg);
+            return 1;
+        }
+    }
+#ifdef DEBUG_COPY_ND_ARRAY
+    printf("check_and_fix_dimensions:end: dims=");
+    dump_dims(rank,dims);
+#endif
+    return 0;
+}
+
+/* End of file: array_from_pyobj.c */
+
+/************************* copy_ND_array *******************************/
+
+extern
+int copy_ND_array(const PyArrayObject *arr, PyArrayObject *out)
+{
+    F2PY_REPORT_ON_ARRAY_COPY_FROMARR;
+    return PyArray_CopyInto(out, (PyArrayObject *)arr);
+}
+
+/*********************************************/
+/* Compatibility functions for Python >= 3.0 */
+/*********************************************/
+
+#if PY_VERSION_HEX >= 0x03000000
+
+PyObject *
+F2PyCapsule_FromVoidPtr(void *ptr, void (*dtor)(PyObject *))
+{
+    PyObject *ret = PyCapsule_New(ptr, NULL, dtor);
+    if (ret == NULL) {
+        PyErr_Clear();
+    }
+    return ret;
+}
+
+void *
+F2PyCapsule_AsVoidPtr(PyObject *obj)
+{
+    void *ret = PyCapsule_GetPointer(obj, NULL);
+    if (ret == NULL) {
+        PyErr_Clear();
+    }
+    return ret;
+}
+
+int
+F2PyCapsule_Check(PyObject *ptr)
+{
+    return PyCapsule_CheckExact(ptr);
+}
+
+#else
+
+PyObject *
+F2PyCapsule_FromVoidPtr(void *ptr, void (*dtor)(void *))
+{
+    return PyCObject_FromVoidPtr(ptr, dtor);
+}
+
+void *
+F2PyCapsule_AsVoidPtr(PyObject *ptr)
+{
+    return PyCObject_AsVoidPtr(ptr);
+}
+
+int
+F2PyCapsule_Check(PyObject *ptr)
+{
+    return PyCObject_Check(ptr);
+}
+
+#endif
+
+
+#ifdef __cplusplus
+}
+#endif
+/************************* EOF fortranobject.c *******************************/
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/src/fortranobject.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/src/fortranobject.h
new file mode 100644
index 0000000..5d0dcf6
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/src/fortranobject.h
@@ -0,0 +1,162 @@
+#ifndef Py_FORTRANOBJECT_H
+#define Py_FORTRANOBJECT_H
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+#include "Python.h"
+
+#ifdef FORTRANOBJECT_C
+#define NO_IMPORT_ARRAY
+#endif
+#define PY_ARRAY_UNIQUE_SYMBOL _npy_f2py_ARRAY_API
+#include "numpy/arrayobject.h"
+
+/*
+ * Python 3 support macros
+ */
+#if PY_VERSION_HEX >= 0x03000000
+#define PyString_Check PyBytes_Check
+#define PyString_GET_SIZE PyBytes_GET_SIZE
+#define PyString_AS_STRING PyBytes_AS_STRING
+#define PyString_FromString PyBytes_FromString
+#define PyUString_FromStringAndSize PyUnicode_FromStringAndSize
+#define PyString_ConcatAndDel PyBytes_ConcatAndDel
+#define PyString_AsString PyBytes_AsString
+
+#define PyInt_Check PyLong_Check
+#define PyInt_FromLong PyLong_FromLong
+#define PyInt_AS_LONG PyLong_AsLong
+#define PyInt_AsLong PyLong_AsLong
+
+#define PyNumber_Int PyNumber_Long
+
+#else
+
+#define PyUString_FromStringAndSize PyString_FromStringAndSize
+#endif
+
+
+#ifdef F2PY_REPORT_ATEXIT
+#include <sys/timeb.h>
+  extern void f2py_start_clock(void);
+  extern void f2py_stop_clock(void);
+  extern void f2py_start_call_clock(void);
+  extern void f2py_stop_call_clock(void);
+  extern void f2py_cb_start_clock(void);
+  extern void f2py_cb_stop_clock(void);
+  extern void f2py_cb_start_call_clock(void);
+  extern void f2py_cb_stop_call_clock(void);
+  extern void f2py_report_on_exit(int,void*);
+#endif
+
+#ifdef DMALLOC
+#include "dmalloc.h"
+#endif
+
+/* Fortran object interface */
+
+/*
+123456789-123456789-123456789-123456789-123456789-123456789-123456789-12
+
+PyFortranObject represents various Fortran objects:
+Fortran (module) routines, COMMON blocks, module data.
+
+Author: Pearu Peterson <pearu@cens.ioc.ee>
+*/
+
+#define F2PY_MAX_DIMS 40
+
+typedef void (*f2py_set_data_func)(char*,npy_intp*);
+typedef void (*f2py_void_func)(void);
+typedef void (*f2py_init_func)(int*,npy_intp*,f2py_set_data_func,int*);
+
+  /*typedef void* (*f2py_c_func)(void*,...);*/
+
+typedef void *(*f2pycfunc)(void);
+
+typedef struct {
+  char *name;                /* attribute (array||routine) name */
+  int rank;                  /* array rank, 0 for scalar, max is F2PY_MAX_DIMS,
+                                || rank=-1 for Fortran routine */
+  struct {npy_intp d[F2PY_MAX_DIMS];} dims; /* dimensions of the array, || not used */
+  int type;                  /* PyArray_<type> || not used */
+  char *data;                /* pointer to array || Fortran routine */
+  f2py_init_func func;       /* initialization function for
+                                allocatable arrays:
+                                func(&rank,dims,set_ptr_func,name,len(name))
+                                || C/API wrapper for Fortran routine */
+  char *doc;                 /* documentation string; only recommended
+                                for routines. */
+} FortranDataDef;
+
+typedef struct {
+  PyObject_HEAD
+  int len;                   /* Number of attributes */
+  FortranDataDef *defs;      /* An array of FortranDataDef's */
+  PyObject       *dict;      /* Fortran object attribute dictionary */
+} PyFortranObject;
+
+#define PyFortran_Check(op) (Py_TYPE(op) == &PyFortran_Type)
+#define PyFortran_Check1(op) (0==strcmp(Py_TYPE(op)->tp_name,"fortran"))
+
+  extern PyTypeObject PyFortran_Type;
+  extern int F2PyDict_SetItemString(PyObject* dict, char *name, PyObject *obj);
+  extern PyObject * PyFortranObject_New(FortranDataDef* defs, f2py_void_func init);
+  extern PyObject * PyFortranObject_NewAsAttr(FortranDataDef* defs);
+
+#if PY_VERSION_HEX >= 0x03000000
+
+PyObject * F2PyCapsule_FromVoidPtr(void *ptr, void (*dtor)(PyObject *));
+void * F2PyCapsule_AsVoidPtr(PyObject *obj);
+int F2PyCapsule_Check(PyObject *ptr);
+
+#else
+
+PyObject * F2PyCapsule_FromVoidPtr(void *ptr, void (*dtor)(void *));
+void * F2PyCapsule_AsVoidPtr(PyObject *ptr);
+int F2PyCapsule_Check(PyObject *ptr);
+
+#endif
+
+#define ISCONTIGUOUS(m) (PyArray_FLAGS(m) & NPY_ARRAY_C_CONTIGUOUS)
+#define F2PY_INTENT_IN 1
+#define F2PY_INTENT_INOUT 2
+#define F2PY_INTENT_OUT 4
+#define F2PY_INTENT_HIDE 8
+#define F2PY_INTENT_CACHE 16
+#define F2PY_INTENT_COPY 32
+#define F2PY_INTENT_C 64
+#define F2PY_OPTIONAL 128
+#define F2PY_INTENT_INPLACE 256
+#define F2PY_INTENT_ALIGNED4 512
+#define F2PY_INTENT_ALIGNED8 1024
+#define F2PY_INTENT_ALIGNED16 2048
+
+#define ARRAY_ISALIGNED(ARR, SIZE) ((size_t)(PyArray_DATA(ARR)) % (SIZE) == 0)
+#define F2PY_ALIGN4(intent) (intent & F2PY_INTENT_ALIGNED4)
+#define F2PY_ALIGN8(intent) (intent & F2PY_INTENT_ALIGNED8)
+#define F2PY_ALIGN16(intent) (intent & F2PY_INTENT_ALIGNED16)
+
+#define F2PY_GET_ALIGNMENT(intent) \
+        (F2PY_ALIGN4(intent) ? 4 : \
+         (F2PY_ALIGN8(intent) ? 8 : \
+          (F2PY_ALIGN16(intent) ? 16 : 1) ))
+#define F2PY_CHECK_ALIGNMENT(arr, intent) ARRAY_ISALIGNED(arr, F2PY_GET_ALIGNMENT(intent))
+
+  extern PyArrayObject* array_from_pyobj(const int type_num,
+                                         npy_intp *dims,
+                                         const int rank,
+                                         const int intent,
+                                         PyObject *obj);
+  extern int copy_ND_array(const PyArrayObject *in, PyArrayObject *out);
+
+#ifdef DEBUG_COPY_ND_ARRAY
+  extern void dump_attrs(const PyArrayObject* arr);
+#endif
+
+
+#ifdef __cplusplus
+}
+#endif
+#endif /* !Py_FORTRANOBJECT_H */
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/array_from_pyobj/wrapmodule.c b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/array_from_pyobj/wrapmodule.c
new file mode 100644
index 0000000..7f46303
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/array_from_pyobj/wrapmodule.c
@@ -0,0 +1,224 @@
+/* File: wrapmodule.c
+ * This file is auto-generated with f2py (version:2_1330).
+ * Hand edited by Pearu.
+ * f2py is a Fortran to Python Interface Generator (FPIG), Second Edition,
+ * written by Pearu Peterson <pearu@cens.ioc.ee>.
+ * See http://cens.ioc.ee/projects/f2py2e/
+ * Generation date: Fri Oct 21 22:41:12 2005
+ * $Revision:$
+ * $Date:$
+ * Do not edit this file directly unless you know what you are doing!!!
+ */
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*********************** See f2py2e/cfuncs.py: includes ***********************/
+#include "Python.h"
+#include "fortranobject.h"
+#include <math.h>
+
+static PyObject *wrap_error;
+static PyObject *wrap_module;
+
+/************************************ call ************************************/
+static char doc_f2py_rout_wrap_call[] = "\
+Function signature:\n\
+  arr = call(type_num,dims,intent,obj)\n\
+Required arguments:\n"
+"  type_num : input int\n"
+"  dims : input int-sequence\n"
+"  intent : input int\n"
+"  obj : input python object\n"
+"Return objects:\n"
+"  arr : array";
+static PyObject *f2py_rout_wrap_call(PyObject *capi_self,
+                                     PyObject *capi_args) {
+  PyObject * volatile capi_buildvalue = NULL;
+  int type_num = 0;
+  npy_intp *dims = NULL;
+  PyObject *dims_capi = Py_None;
+  int rank = 0;
+  int intent = 0;
+  PyArrayObject *capi_arr_tmp = NULL;
+  PyObject *arr_capi = Py_None;
+  int i;
+
+  if (!PyArg_ParseTuple(capi_args,"iOiO|:wrap.call",\
+                        &type_num,&dims_capi,&intent,&arr_capi))
+    return NULL;
+  rank = PySequence_Length(dims_capi);
+  dims = malloc(rank*sizeof(npy_intp));
+  for (i=0;i<rank;++i)
+    dims[i] = (npy_intp)PyInt_AsLong(PySequence_GetItem(dims_capi,i));
+
+  capi_arr_tmp = array_from_pyobj(type_num,dims,rank,intent|F2PY_INTENT_OUT,arr_capi);
+  if (capi_arr_tmp == NULL) {
+    free(dims);
+    return NULL;
+  }
+  capi_buildvalue = Py_BuildValue("N",capi_arr_tmp);
+  free(dims);
+  return capi_buildvalue;
+}
+
+static char doc_f2py_rout_wrap_attrs[] = "\
+Function signature:\n\
+  arr = array_attrs(arr)\n\
+Required arguments:\n"
+"  arr : input array object\n"
+"Return objects:\n"
+"  data : data address in hex\n"
+"  nd : int\n"
+"  dimensions : tuple\n"
+"  strides : tuple\n"
+"  base : python object\n"
+"  (kind,type,type_num,elsize,alignment) : 4-tuple\n"
+"  flags : int\n"
+"  itemsize : int\n"
+;
+static PyObject *f2py_rout_wrap_attrs(PyObject *capi_self,
+                                      PyObject *capi_args) {
+  PyObject *arr_capi = Py_None;
+  PyArrayObject *arr = NULL;
+  PyObject *dimensions = NULL;
+  PyObject *strides = NULL;
+  char s[100];
+  int i;
+  memset(s,0,100*sizeof(char));
+  if (!PyArg_ParseTuple(capi_args,"O!|:wrap.attrs",
+                        &PyArray_Type,&arr_capi))
+    return NULL;
+  arr = (PyArrayObject *)arr_capi;
+  sprintf(s,"%p",PyArray_DATA(arr));
+  dimensions = PyTuple_New(PyArray_NDIM(arr));
+  strides = PyTuple_New(PyArray_NDIM(arr));
+  for (i=0;i<PyArray_NDIM(arr);++i) {
+    PyTuple_SetItem(dimensions,i,PyInt_FromLong(PyArray_DIM(arr,i)));
+    PyTuple_SetItem(strides,i,PyInt_FromLong(PyArray_STRIDE(arr,i)));
+  }
+  return Py_BuildValue("siOOO(cciii)ii",s,PyArray_NDIM(arr),
+                       dimensions,strides,
+                       (PyArray_BASE(arr)==NULL?Py_None:PyArray_BASE(arr)),
+                       PyArray_DESCR(arr)->kind,
+                       PyArray_DESCR(arr)->type,
+                       PyArray_TYPE(arr),
+                       PyArray_ITEMSIZE(arr),
+                       PyArray_DESCR(arr)->alignment,
+                       PyArray_FLAGS(arr),
+                       PyArray_ITEMSIZE(arr));
+}
+
+static PyMethodDef f2py_module_methods[] = {
+
+  {"call",f2py_rout_wrap_call,METH_VARARGS,doc_f2py_rout_wrap_call},
+  {"array_attrs",f2py_rout_wrap_attrs,METH_VARARGS,doc_f2py_rout_wrap_attrs},
+  {NULL,NULL}
+};
+
+#if PY_VERSION_HEX >= 0x03000000
+static struct PyModuleDef moduledef = {
+    PyModuleDef_HEAD_INIT,
+    "test_array_from_pyobj_ext",
+    NULL,
+    -1,
+    f2py_module_methods,
+    NULL,
+    NULL,
+    NULL,
+    NULL
+};
+#endif
+
+#if PY_VERSION_HEX >= 0x03000000
+#define RETVAL m
+PyMODINIT_FUNC PyInit_test_array_from_pyobj_ext(void) {
+#else
+#define RETVAL
+PyMODINIT_FUNC inittest_array_from_pyobj_ext(void) {
+#endif
+  PyObject *m,*d, *s;
+#if PY_VERSION_HEX >= 0x03000000
+  m = wrap_module = PyModule_Create(&moduledef);
+#else
+  m = wrap_module = Py_InitModule("test_array_from_pyobj_ext", f2py_module_methods);
+#endif
+  Py_TYPE(&PyFortran_Type) = &PyType_Type;
+  import_array();
+  if (PyErr_Occurred())
+    Py_FatalError("can't initialize module wrap (failed to import numpy)");
+  d = PyModule_GetDict(m);
+  s = PyString_FromString("This module 'wrap' is auto-generated with f2py (version:2_1330).\nFunctions:\n"
+"  arr = call(type_num,dims,intent,obj)\n"
+".");
+  PyDict_SetItemString(d, "__doc__", s);
+  wrap_error = PyErr_NewException ("wrap.error", NULL, NULL);
+  Py_DECREF(s);
+  PyDict_SetItemString(d, "F2PY_INTENT_IN", PyInt_FromLong(F2PY_INTENT_IN));
+  PyDict_SetItemString(d, "F2PY_INTENT_INOUT", PyInt_FromLong(F2PY_INTENT_INOUT));
+  PyDict_SetItemString(d, "F2PY_INTENT_OUT", PyInt_FromLong(F2PY_INTENT_OUT));
+  PyDict_SetItemString(d, "F2PY_INTENT_HIDE", PyInt_FromLong(F2PY_INTENT_HIDE));
+  PyDict_SetItemString(d, "F2PY_INTENT_CACHE", PyInt_FromLong(F2PY_INTENT_CACHE));
+  PyDict_SetItemString(d, "F2PY_INTENT_COPY", PyInt_FromLong(F2PY_INTENT_COPY));
+  PyDict_SetItemString(d, "F2PY_INTENT_C", PyInt_FromLong(F2PY_INTENT_C));
+  PyDict_SetItemString(d, "F2PY_OPTIONAL", PyInt_FromLong(F2PY_OPTIONAL));
+  PyDict_SetItemString(d, "F2PY_INTENT_INPLACE", PyInt_FromLong(F2PY_INTENT_INPLACE));
+  PyDict_SetItemString(d, "NPY_BOOL", PyInt_FromLong(NPY_BOOL));
+  PyDict_SetItemString(d, "NPY_BYTE", PyInt_FromLong(NPY_BYTE));
+  PyDict_SetItemString(d, "NPY_UBYTE", PyInt_FromLong(NPY_UBYTE));
+  PyDict_SetItemString(d, "NPY_SHORT", PyInt_FromLong(NPY_SHORT));
+  PyDict_SetItemString(d, "NPY_USHORT", PyInt_FromLong(NPY_USHORT));
+  PyDict_SetItemString(d, "NPY_INT", PyInt_FromLong(NPY_INT));
+  PyDict_SetItemString(d, "NPY_UINT", PyInt_FromLong(NPY_UINT));
+  PyDict_SetItemString(d, "NPY_INTP", PyInt_FromLong(NPY_INTP));
+  PyDict_SetItemString(d, "NPY_UINTP", PyInt_FromLong(NPY_UINTP));
+  PyDict_SetItemString(d, "NPY_LONG", PyInt_FromLong(NPY_LONG));
+  PyDict_SetItemString(d, "NPY_ULONG", PyInt_FromLong(NPY_ULONG));
+  PyDict_SetItemString(d, "NPY_LONGLONG", PyInt_FromLong(NPY_LONGLONG));
+  PyDict_SetItemString(d, "NPY_ULONGLONG", PyInt_FromLong(NPY_ULONGLONG));
+  PyDict_SetItemString(d, "NPY_FLOAT", PyInt_FromLong(NPY_FLOAT));
+  PyDict_SetItemString(d, "NPY_DOUBLE", PyInt_FromLong(NPY_DOUBLE));
+  PyDict_SetItemString(d, "NPY_LONGDOUBLE", PyInt_FromLong(NPY_LONGDOUBLE));
+  PyDict_SetItemString(d, "NPY_CFLOAT", PyInt_FromLong(NPY_CFLOAT));
+  PyDict_SetItemString(d, "NPY_CDOUBLE", PyInt_FromLong(NPY_CDOUBLE));
+  PyDict_SetItemString(d, "NPY_CLONGDOUBLE", PyInt_FromLong(NPY_CLONGDOUBLE));
+  PyDict_SetItemString(d, "NPY_OBJECT", PyInt_FromLong(NPY_OBJECT));
+  PyDict_SetItemString(d, "NPY_STRING", PyInt_FromLong(NPY_STRING));
+  PyDict_SetItemString(d, "NPY_UNICODE", PyInt_FromLong(NPY_UNICODE));
+  PyDict_SetItemString(d, "NPY_VOID", PyInt_FromLong(NPY_VOID));
+  PyDict_SetItemString(d, "NPY_NTYPES", PyInt_FromLong(NPY_NTYPES));
+  PyDict_SetItemString(d, "NPY_NOTYPE", PyInt_FromLong(NPY_NOTYPE));
+  PyDict_SetItemString(d, "NPY_USERDEF", PyInt_FromLong(NPY_USERDEF));
+
+  PyDict_SetItemString(d, "CONTIGUOUS", PyInt_FromLong(NPY_ARRAY_C_CONTIGUOUS));
+  PyDict_SetItemString(d, "FORTRAN", PyInt_FromLong(NPY_ARRAY_F_CONTIGUOUS));
+  PyDict_SetItemString(d, "OWNDATA", PyInt_FromLong(NPY_ARRAY_OWNDATA));
+  PyDict_SetItemString(d, "FORCECAST", PyInt_FromLong(NPY_ARRAY_FORCECAST));
+  PyDict_SetItemString(d, "ENSURECOPY", PyInt_FromLong(NPY_ARRAY_ENSURECOPY));
+  PyDict_SetItemString(d, "ENSUREARRAY", PyInt_FromLong(NPY_ARRAY_ENSUREARRAY));
+  PyDict_SetItemString(d, "ALIGNED", PyInt_FromLong(NPY_ARRAY_ALIGNED));
+  PyDict_SetItemString(d, "WRITEABLE", PyInt_FromLong(NPY_ARRAY_WRITEABLE));
+  PyDict_SetItemString(d, "UPDATEIFCOPY", PyInt_FromLong(NPY_ARRAY_UPDATEIFCOPY));
+  PyDict_SetItemString(d, "WRITEBACKIFCOPY", PyInt_FromLong(NPY_ARRAY_WRITEBACKIFCOPY));
+
+  PyDict_SetItemString(d, "BEHAVED", PyInt_FromLong(NPY_ARRAY_BEHAVED));
+  PyDict_SetItemString(d, "BEHAVED_NS", PyInt_FromLong(NPY_ARRAY_BEHAVED_NS));
+  PyDict_SetItemString(d, "CARRAY", PyInt_FromLong(NPY_ARRAY_CARRAY));
+  PyDict_SetItemString(d, "FARRAY", PyInt_FromLong(NPY_ARRAY_FARRAY));
+  PyDict_SetItemString(d, "CARRAY_RO", PyInt_FromLong(NPY_ARRAY_CARRAY_RO));
+  PyDict_SetItemString(d, "FARRAY_RO", PyInt_FromLong(NPY_ARRAY_FARRAY_RO));
+  PyDict_SetItemString(d, "DEFAULT", PyInt_FromLong(NPY_ARRAY_DEFAULT));
+  PyDict_SetItemString(d, "UPDATE_ALL", PyInt_FromLong(NPY_ARRAY_UPDATE_ALL));
+
+  if (PyErr_Occurred())
+    Py_FatalError("can't initialize module wrap");
+
+#ifdef F2PY_REPORT_ATEXIT
+  on_exit(f2py_report_on_exit,(void*)"array_from_pyobj.wrap.call");
+#endif
+
+  return RETVAL;
+}
+#ifdef __cplusplus
+}
+#endif
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/.f2py_f2cmap b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/.f2py_f2cmap
new file mode 100644
index 0000000..2665f89
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/.f2py_f2cmap
@@ -0,0 +1 @@
+dict(real=dict(rk="double"))
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/foo_free.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/foo_free.f90
new file mode 100644
index 0000000..b301710
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/foo_free.f90
@@ -0,0 +1,34 @@
+
+subroutine sum(x, res)
+  implicit none
+  real, intent(in) :: x(:)
+  real, intent(out) :: res
+
+  integer :: i
+
+  !print *, "sum: size(x) = ", size(x)
+
+  res = 0.0
+
+  do i = 1, size(x)
+    res = res + x(i)
+  enddo
+
+end subroutine sum
+
+function fsum(x) result (res)
+  implicit none
+  real, intent(in) :: x(:)
+  real :: res
+
+  integer :: i
+
+  !print *, "fsum: size(x) = ", size(x)
+
+  res = 0.0
+
+  do i = 1, size(x)
+    res = res + x(i)
+  enddo
+
+end function fsum
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/foo_mod.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/foo_mod.f90
new file mode 100644
index 0000000..cbe6317
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/foo_mod.f90
@@ -0,0 +1,41 @@
+
+module mod
+
+contains
+
+subroutine sum(x, res)
+  implicit none
+  real, intent(in) :: x(:)
+  real, intent(out) :: res
+
+  integer :: i
+
+  !print *, "sum: size(x) = ", size(x)
+
+  res = 0.0
+
+  do i = 1, size(x)
+    res = res + x(i)
+  enddo
+
+end subroutine sum
+
+function fsum(x) result (res)
+  implicit none
+  real, intent(in) :: x(:)
+  real :: res
+
+  integer :: i
+
+  !print *, "fsum: size(x) = ", size(x)
+
+  res = 0.0
+
+  do i = 1, size(x)
+    res = res + x(i)
+  enddo
+
+end function fsum
+
+
+end module mod
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/foo_use.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/foo_use.f90
new file mode 100644
index 0000000..337465a
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/foo_use.f90
@@ -0,0 +1,19 @@
+subroutine sum_with_use(x, res)
+  use precision
+
+  implicit none
+
+  real(kind=rk), intent(in) :: x(:)
+  real(kind=rk), intent(out) :: res
+
+  integer :: i
+
+  !print *, "size(x) = ", size(x)
+
+  res = 0.0
+
+  do i = 1, size(x)
+    res = res + x(i)
+  enddo
+
+ end subroutine
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/precision.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/precision.f90
new file mode 100644
index 0000000..ed6c70c
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/assumed_shape/precision.f90
@@ -0,0 +1,4 @@
+module precision
+  integer, parameter :: rk = selected_real_kind(8)
+  integer, parameter :: ik = selected_real_kind(4)
+end module
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/common/block.f b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/common/block.f
new file mode 100644
index 0000000..7ea7968
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/common/block.f
@@ -0,0 +1,11 @@
+      SUBROUTINE INITCB
+      DOUBLE PRECISION LONG
+      CHARACTER        STRING
+      INTEGER          OK
+    
+      COMMON  /BLOCK/ LONG, STRING, OK
+      LONG = 1.0
+      STRING = '2'
+      OK = 3
+      RETURN
+      END
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/kind/foo.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/kind/foo.f90
new file mode 100644
index 0000000..d3d15cf
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/kind/foo.f90
@@ -0,0 +1,20 @@
+
+
+subroutine selectedrealkind(p, r, res)
+  implicit none
+  
+  integer, intent(in) :: p, r
+  !f2py integer :: r=0
+  integer, intent(out) :: res
+  res = selected_real_kind(p, r)
+
+end subroutine
+
+subroutine selectedintkind(p, res)
+  implicit none
+
+  integer, intent(in) :: p
+  integer, intent(out) :: res
+  res = selected_int_kind(p)
+
+end subroutine
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/mixed/foo.f b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/mixed/foo.f
new file mode 100644
index 0000000..c347425
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/mixed/foo.f
@@ -0,0 +1,5 @@
+      subroutine bar11(a)
+cf2py intent(out) a
+      integer a
+      a = 11
+      end
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/mixed/foo_fixed.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/mixed/foo_fixed.f90
new file mode 100644
index 0000000..7543a6a
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/mixed/foo_fixed.f90
@@ -0,0 +1,8 @@
+      module foo_fixed
+      contains
+        subroutine bar12(a)
+!f2py intent(out) a
+          integer a
+          a = 12
+        end subroutine bar12
+      end module foo_fixed
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/mixed/foo_free.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/mixed/foo_free.f90
new file mode 100644
index 0000000..c1b641f
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/mixed/foo_free.f90
@@ -0,0 +1,8 @@
+module foo_free
+contains
+  subroutine bar13(a)
+    !f2py intent(out) a
+    integer a
+    a = 13
+  end subroutine bar13
+end module foo_free
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_both.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_both.f90
new file mode 100644
index 0000000..ac90ced
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_both.f90
@@ -0,0 +1,57 @@
+! Check that parameters are correct intercepted.
+! Constants with comma separations are commonly
+! used, for instance Pi = 3._dp
+subroutine foo(x)
+  implicit none
+  integer, parameter :: sp = selected_real_kind(6)
+  integer, parameter :: dp = selected_real_kind(15)
+  integer, parameter :: ii = selected_int_kind(9)
+  integer, parameter :: il = selected_int_kind(18)
+  real(dp), intent(inout) :: x
+  dimension x(3)
+  real(sp), parameter :: three_s = 3._sp
+  real(dp), parameter :: three_d = 3._dp
+  integer(ii), parameter :: three_i = 3_ii
+  integer(il), parameter :: three_l = 3_il
+  x(1) = x(1) + x(2) * three_s * three_i + x(3) * three_d * three_l
+  x(2) = x(2) * three_s
+  x(3) = x(3) * three_l
+  return
+end subroutine
+
+
+subroutine foo_no(x)
+  implicit none
+  integer, parameter :: sp = selected_real_kind(6)
+  integer, parameter :: dp = selected_real_kind(15)
+  integer, parameter :: ii = selected_int_kind(9)
+  integer, parameter :: il = selected_int_kind(18)
+  real(dp), intent(inout) :: x
+  dimension x(3)
+  real(sp), parameter :: three_s = 3.
+  real(dp), parameter :: three_d = 3.
+  integer(ii), parameter :: three_i = 3
+  integer(il), parameter :: three_l = 3
+  x(1) = x(1) + x(2) * three_s * three_i + x(3) * three_d * three_l
+  x(2) = x(2) * three_s
+  x(3) = x(3) * three_l
+  return
+end subroutine
+
+subroutine foo_sum(x)
+  implicit none
+  integer, parameter :: sp = selected_real_kind(6)
+  integer, parameter :: dp = selected_real_kind(15)
+  integer, parameter :: ii = selected_int_kind(9)
+  integer, parameter :: il = selected_int_kind(18)
+  real(dp), intent(inout) :: x
+  dimension x(3)
+  real(sp), parameter :: three_s = 2._sp + 1._sp
+  real(dp), parameter :: three_d = 1._dp + 2._dp
+  integer(ii), parameter :: three_i = 2_ii + 1_ii
+  integer(il), parameter :: three_l = 1_il + 2_il
+  x(1) = x(1) + x(2) * three_s * three_i + x(3) * three_d * three_l
+  x(2) = x(2) * three_s
+  x(3) = x(3) * three_l
+  return
+end subroutine
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_compound.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_compound.f90
new file mode 100644
index 0000000..e51f5e9
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_compound.f90
@@ -0,0 +1,15 @@
+! Check that parameters are correct intercepted.
+! Constants with comma separations are commonly
+! used, for instance Pi = 3._dp
+subroutine foo_compound_int(x)
+  implicit none
+  integer, parameter :: ii = selected_int_kind(9)
+  integer(ii), intent(inout) :: x
+  dimension x(3)
+  integer(ii), parameter :: three = 3_ii
+  integer(ii), parameter :: two = 2_ii
+  integer(ii), parameter :: six = three * 1_ii * two
+
+  x(1) = x(1) + x(2) + x(3) * six
+  return
+end subroutine
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_integer.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_integer.f90
new file mode 100644
index 0000000..aaa83d2
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_integer.f90
@@ -0,0 +1,22 @@
+! Check that parameters are correct intercepted.
+! Constants with comma separations are commonly
+! used, for instance Pi = 3._dp
+subroutine foo_int(x)
+  implicit none
+  integer, parameter :: ii = selected_int_kind(9)
+  integer(ii), intent(inout) :: x
+  dimension x(3)
+  integer(ii), parameter :: three = 3_ii
+  x(1) = x(1) + x(2) + x(3) * three
+  return
+end subroutine
+
+subroutine foo_long(x)
+  implicit none
+  integer, parameter :: ii = selected_int_kind(18)
+  integer(ii), intent(inout) :: x
+  dimension x(3)
+  integer(ii), parameter :: three = 3_ii
+  x(1) = x(1) + x(2) + x(3) * three
+  return
+end subroutine
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_non_compound.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_non_compound.f90
new file mode 100644
index 0000000..62c9a5b
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_non_compound.f90
@@ -0,0 +1,23 @@
+! Check that parameters are correct intercepted.
+! Specifically that types of constants without 
+! compound kind specs are correctly inferred
+! adapted Gibbs iteration code from pymc 
+! for this test case 
+subroutine foo_non_compound_int(x)
+  implicit none
+  integer, parameter :: ii = selected_int_kind(9)
+
+  integer(ii)   maxiterates
+  parameter (maxiterates=2)
+
+  integer(ii)   maxseries
+  parameter (maxseries=2)
+
+  integer(ii)   wasize
+  parameter (wasize=maxiterates*maxseries)
+  integer(ii), intent(inout) :: x
+  dimension x(wasize)
+
+  x(1) = x(1) + x(2) + x(3) + x(4) * wasize
+  return
+end subroutine
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_real.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_real.f90
new file mode 100644
index 0000000..02ac9dd
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/parameter/constant_real.f90
@@ -0,0 +1,23 @@
+! Check that parameters are correct intercepted.
+! Constants with comma separations are commonly
+! used, for instance Pi = 3._dp
+subroutine foo_single(x)
+  implicit none
+  integer, parameter :: rp = selected_real_kind(6)
+  real(rp), intent(inout) :: x
+  dimension x(3)
+  real(rp), parameter :: three = 3._rp
+  x(1) = x(1) + x(2) + x(3) * three
+  return
+end subroutine
+
+subroutine foo_double(x)
+  implicit none
+  integer, parameter :: rp = selected_real_kind(15)
+  real(rp), intent(inout) :: x
+  dimension x(3)
+  real(rp), parameter :: three = 3._rp
+  x(1) = x(1) + x(2) + x(3) * three
+  return
+end subroutine
+
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/regression/inout.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/regression/inout.f90
new file mode 100644
index 0000000..80cdad9
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/regression/inout.f90
@@ -0,0 +1,9 @@
+! Check that intent(in out) translates as intent(inout).
+! The separation seems to be a common usage.
+      subroutine foo(x)
+          implicit none
+          real(4), intent(in out) :: x
+          dimension x(3)
+          x(1) = x(1) + x(2) + x(3)
+          return
+      end
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/size/foo.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/size/foo.f90
new file mode 100644
index 0000000..5b66f8c
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/size/foo.f90
@@ -0,0 +1,44 @@
+
+subroutine foo(a, n, m, b)
+  implicit none
+
+  real, intent(in) :: a(n, m)
+  integer, intent(in) :: n, m
+  real, intent(out) :: b(size(a, 1))
+
+  integer :: i
+
+  do i = 1, size(b)
+    b(i) = sum(a(i,:))
+  enddo
+end subroutine
+
+subroutine trans(x,y)
+  implicit none
+  real, intent(in), dimension(:,:) :: x
+  real, intent(out), dimension( size(x,2), size(x,1) ) :: y
+  integer :: N, M, i, j
+  N = size(x,1)
+  M = size(x,2)
+  DO i=1,N
+     do j=1,M
+        y(j,i) = x(i,j)
+     END DO
+  END DO
+end subroutine trans
+
+subroutine flatten(x,y)
+  implicit none
+  real, intent(in), dimension(:,:) :: x
+  real, intent(out), dimension( size(x) ) :: y
+  integer :: N, M, i, j, k
+  N = size(x,1)
+  M = size(x,2)
+  k = 1
+  DO i=1,N
+     do j=1,M
+        y(k) = x(i,j)
+        k = k + 1
+     END DO
+  END DO
+end subroutine flatten
diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/string/char.f90 b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/string/char.f90
new file mode 100644
index 0000000..bb7985c
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/f2py/tests/src/string/char.f90
@@ -0,0 +1,29 @@
+MODULE char_test
+
+CONTAINS
+
+SUBROUTINE change_strings(strings, n_strs, out_strings)
+    IMPLICIT NONE
+
+    ! Inputs
+    INTEGER, INTENT(IN) :: n_strs
+    CHARACTER, INTENT(IN), DIMENSION(2,n_strs) :: strings
+    CHARACTER, INTENT(OUT), DIMENSION(2,n_strs) :: out_strings
+
+!f2py INTEGER, INTENT(IN) :: n_strs
+!f2py CHARACTER, INTENT(IN), DIMENSION(2,n_strs) :: strings
+!f2py CHARACTER, INTENT(OUT), DIMENSION(2,n_strs) :: strings
+
+    ! Misc.
+    INTEGER*4 :: j
+
+
+    DO j=1, n_strs
+        out_strings(1,j) = strings(1,j)
+        out_strings(2,j) = 'A'
+    END DO
+
+END SUBROUTINE change_strings
+
+END MODULE char_test
+
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diff --git a/butterflow-ui/ThirdPartyCompiled/lib/numpy/random/randomkit.h b/butterflow-ui/ThirdPartyCompiled/lib/numpy/random/randomkit.h
new file mode 100644
index 0000000..a24dabe
--- /dev/null
+++ b/butterflow-ui/ThirdPartyCompiled/lib/numpy/random/randomkit.h
@@ -0,0 +1,226 @@
+/* Random kit 1.3 */
+
+/*
+ * Copyright (c) 2003-2005, Jean-Sebastien Roy (js@jeannot.org)
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a
+ * copy of this software and associated documentation files (the
+ * "Software"), to deal in the Software without restriction, including
+ * without limitation the rights to use, copy, modify, merge, publish,
+ * distribute, sublicense, and/or sell copies of the Software, and to
+ * permit persons to whom the Software is furnished to do so, subject to
+ * the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included
+ * in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
+ * OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+ * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+ * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
+ * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+ * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+ * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+/* @(#) $Jeannot: randomkit.h,v 1.24 2005/07/21 22:14:09 js Exp $ */
+
+/*
+ * Typical use:
+ *
+ * {
+ *  rk_state state;
+ *  unsigned long seed = 1, random_value;
+ *
+ *  rk_seed(seed, &state); // Initialize the RNG
+ *  ...
+ *  random_value = rk_random(&state); // Generate random values in [0..RK_MAX]
+ * }
+ *
+ * Instead of rk_seed, you can use rk_randomseed which will get a random seed
+ * from /dev/urandom (or the clock, if /dev/urandom is unavailable):
+ *
+ * {
+ *  rk_state state;
+ *  unsigned long random_value;
+ *
+ *  rk_randomseed(&state); // Initialize the RNG with a random seed
+ *  ...
+ *  random_value = rk_random(&state); // Generate random values in [0..RK_MAX]
+ * }
+ */
+
+/*
+ * Useful macro:
+ *  RK_DEV_RANDOM: the device used for random seeding.
+ *                 defaults to "/dev/urandom"
+ */
+
+#ifndef _RANDOMKIT_
+#define _RANDOMKIT_
+
+#include <stddef.h>
+#include <numpy/npy_common.h>
+
+
+#define RK_STATE_LEN 624
+
+typedef struct rk_state_
+{
+    unsigned long key[RK_STATE_LEN];
+    int pos;
+    int has_gauss; /* !=0: gauss contains a gaussian deviate */
+    double gauss;
+
+    /* The rk_state structure has been extended to store the following
+     * information for the binomial generator. If the input values of n or p
+     * are different than nsave and psave, then the other parameters will be
+     * recomputed. RTK 2005-09-02 */
+
+    int has_binomial; /* !=0: following parameters initialized for
+                              binomial */
+    double psave;
+    long nsave;
+    double r;
+    double q;
+    double fm;
+    long m;
+    double p1;
+    double xm;
+    double xl;
+    double xr;
+    double c;
+    double laml;
+    double lamr;
+    double p2;
+    double p3;
+    double p4;
+
+}
+rk_state;
+
+typedef enum {
+    RK_NOERR = 0, /* no error */
+    RK_ENODEV = 1, /* no RK_DEV_RANDOM device */
+    RK_ERR_MAX = 2
+} rk_error;
+
+/* error strings */
+extern char *rk_strerror[RK_ERR_MAX];
+
+/* Maximum generated random value */
+#define RK_MAX 0xFFFFFFFFUL
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*
+ * Initialize the RNG state using the given seed.
+ */
+extern void rk_seed(unsigned long seed, rk_state *state);
+
+/*
+ * Initialize the RNG state using a random seed.
+ * Uses /dev/random or, when unavailable, the clock (see randomkit.c).
+ * Returns RK_NOERR when no errors occurs.
+ * Returns RK_ENODEV when the use of RK_DEV_RANDOM failed (for example because
+ * there is no such device). In this case, the RNG was initialized using the
+ * clock.
+ */
+extern rk_error rk_randomseed(rk_state *state);
+
+/*
+ * Returns a random unsigned long between 0 and RK_MAX inclusive
+ */
+extern unsigned long rk_random(rk_state *state);
+
+/*
+ * Returns a random long between 0 and LONG_MAX inclusive
+ */
+extern long rk_long(rk_state *state);
+
+/*
+ * Returns a random unsigned long between 0 and ULONG_MAX inclusive
+ */
+extern unsigned long rk_ulong(rk_state *state);
+
+/*
+ * Returns a random unsigned long between 0 and max inclusive.
+ */
+extern unsigned long rk_interval(unsigned long max, rk_state *state);
+
+/*
+ * Fills an array with cnt random npy_uint64 between off and off + rng
+ * inclusive. The numbers wrap if rng is sufficiently large.
+ */
+extern void rk_random_uint64(npy_uint64 off, npy_uint64 rng, npy_intp cnt,
+                             npy_uint64 *out, rk_state *state);
+
+/*
+ * Fills an array with cnt random npy_uint32 between off and off + rng
+ * inclusive. The numbers wrap if rng is sufficiently large.
+ */
+extern void rk_random_uint32(npy_uint32 off, npy_uint32 rng, npy_intp cnt,
+                             npy_uint32 *out, rk_state *state);
+
+/*
+ * Fills an array with cnt random npy_uint16 between off and off + rng
+ * inclusive. The numbers wrap if rng is sufficiently large.
+ */
+extern void rk_random_uint16(npy_uint16 off, npy_uint16 rng, npy_intp cnt,
+                             npy_uint16 *out, rk_state *state);
+
+/*
+ * Fills an array with cnt random npy_uint8 between off and off + rng
+ * inclusive. The numbers wrap if rng is sufficiently large.
+ */
+extern void rk_random_uint8(npy_uint8 off, npy_uint8 rng, npy_intp cnt,
+                            npy_uint8 *out, rk_state *state);
+
+/*
+ * Fills an array with cnt random npy_bool between off and off + rng
+ * inclusive. It is assumed tha npy_bool as the same size as npy_uint8.
+ */
+extern void rk_random_bool(npy_bool off, npy_bool rng, npy_intp cnt,
+                           npy_bool *out, rk_state *state);
+
+/*
+ * Returns a random double between 0.0 and 1.0, 1.0 excluded.
+ */
+extern double rk_double(rk_state *state);
+
+/*
+ * fill the buffer with size random bytes
+ */
+extern void rk_fill(void *buffer, size_t size, rk_state *state);
+
+/*
+ * fill the buffer with randombytes from the random device
+ * Returns RK_ENODEV if the device is unavailable, or RK_NOERR if it is
+ * On Unix, if strong is defined, RK_DEV_RANDOM is used. If not, RK_DEV_URANDOM
+ * is used instead. This parameter has no effect on Windows.
+ * Warning: on most unixes RK_DEV_RANDOM will wait for enough entropy to answer
+ * which can take a very long time on quiet systems.
+ */
+extern rk_error rk_devfill(void *buffer, size_t size, int strong);
+
+/*
+ * fill the buffer using rk_devfill if the random device is available and using
+ * rk_fill if it is not
+ * parameters have the same meaning as rk_fill and rk_devfill
+ * Returns RK_ENODEV if the device is unavailable, or RK_NOERR if it is
+ */
+extern rk_error rk_altfill(void *buffer, size_t size, int strong,
+                            rk_state *state);
+
+/*
+ * return a random gaussian deviate with variance unity and zero mean.
+ */
+extern double rk_gauss(rk_state *state);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif /* _RANDOMKIT_ */
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