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%global _empty_manifest_terminate_build 0
Name: python-heatmapz
Version: 0.0.4
Release: 1
Summary: Create heatmaps with shapes and size as a parameter
License: BSD License
URL: https://github.com/drazenz/heatmap
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/4a/07/736df758be785db1f6f809945b96a1103af8d25b24419c4bd64f68ae3c60/heatmapz-0.0.4.tar.gz
BuildArch: noarch
Requires: python3-matplotlib
Requires: python3-pandas
Requires: python3-seaborn
%description
### **`heatmap(x, y, **kwargs)`**
**Parameters**:
**`x`** : A list, np.array or pandas.Series containing the values for the horizontal dimension
**`y`** : A list, np.array or pandas.Series containing the values for the vertical dimension
**Optional parameters**:
**`color`** : A list, np.array or pandas.Series containing values based on which to apply the heatmap color. Should have the same length as `x` and `y`.
**`palette`** : A list of colors to use as the heatmap palette. The values from `color` are mapped onto the palette so that `min(color) -> palette[0]` and `max(color) -> palette[len(palette)-1]`, and the values in between are linearly interpolated. A good way to choose or create a palette is to simply use Seaborn palettes (https://seaborn.pydata.org/tutorial/color_palettes.html).
**`color_range`** : A tuple `(color_min, color_max)` that enables capping the values of `color` being mapped to `palette`. All `color` values less than `color_min` are capped to `color_min`, and all `color` values larger than `color_max` are capped to `color_max`. Then those values are mapped to `palette` as described under `color`.
**`size`** : A list, np.array or pandas.Series containing values based on which to apply the size to the shapes in the plot. Should have the same length as `x` and `y`.
**`size_range`** : A tuple `(size_min, size_max)` that enables capping the values of `size` being applied to the shapes in the plot. Essentially controls min and max size of the shapes.
**`size_scale`** : Used to scale the size of the shapes in the plot to make them fit the size of the fields in the matrix. Default value is 500. You will likely need to fiddle with this parameter in order to find the right value for your figure size and the size range applied.
**`x_order`** : Should contain all distinct values of `x` ordered in the way you want them shown on the x-axis from left to right.
**`y_order`** : Should contain all distinct values of `y` ordered in the way you want them shown on the y-axis from bottom to top.
**`marker`** : Specify the shape to use in the plot. It can be any of the **matplotlib** marker shapes (https://matplotlib.org/api/markers_api.html). The default is 's' for square.
**`xlabel`** : Label for the x-axis. Default is none.
%package -n python3-heatmapz
Summary: Create heatmaps with shapes and size as a parameter
Provides: python-heatmapz
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-heatmapz
### **`heatmap(x, y, **kwargs)`**
**Parameters**:
**`x`** : A list, np.array or pandas.Series containing the values for the horizontal dimension
**`y`** : A list, np.array or pandas.Series containing the values for the vertical dimension
**Optional parameters**:
**`color`** : A list, np.array or pandas.Series containing values based on which to apply the heatmap color. Should have the same length as `x` and `y`.
**`palette`** : A list of colors to use as the heatmap palette. The values from `color` are mapped onto the palette so that `min(color) -> palette[0]` and `max(color) -> palette[len(palette)-1]`, and the values in between are linearly interpolated. A good way to choose or create a palette is to simply use Seaborn palettes (https://seaborn.pydata.org/tutorial/color_palettes.html).
**`color_range`** : A tuple `(color_min, color_max)` that enables capping the values of `color` being mapped to `palette`. All `color` values less than `color_min` are capped to `color_min`, and all `color` values larger than `color_max` are capped to `color_max`. Then those values are mapped to `palette` as described under `color`.
**`size`** : A list, np.array or pandas.Series containing values based on which to apply the size to the shapes in the plot. Should have the same length as `x` and `y`.
**`size_range`** : A tuple `(size_min, size_max)` that enables capping the values of `size` being applied to the shapes in the plot. Essentially controls min and max size of the shapes.
**`size_scale`** : Used to scale the size of the shapes in the plot to make them fit the size of the fields in the matrix. Default value is 500. You will likely need to fiddle with this parameter in order to find the right value for your figure size and the size range applied.
**`x_order`** : Should contain all distinct values of `x` ordered in the way you want them shown on the x-axis from left to right.
**`y_order`** : Should contain all distinct values of `y` ordered in the way you want them shown on the y-axis from bottom to top.
**`marker`** : Specify the shape to use in the plot. It can be any of the **matplotlib** marker shapes (https://matplotlib.org/api/markers_api.html). The default is 's' for square.
**`xlabel`** : Label for the x-axis. Default is none.
%package help
Summary: Development documents and examples for heatmapz
Provides: python3-heatmapz-doc
%description help
### **`heatmap(x, y, **kwargs)`**
**Parameters**:
**`x`** : A list, np.array or pandas.Series containing the values for the horizontal dimension
**`y`** : A list, np.array or pandas.Series containing the values for the vertical dimension
**Optional parameters**:
**`color`** : A list, np.array or pandas.Series containing values based on which to apply the heatmap color. Should have the same length as `x` and `y`.
**`palette`** : A list of colors to use as the heatmap palette. The values from `color` are mapped onto the palette so that `min(color) -> palette[0]` and `max(color) -> palette[len(palette)-1]`, and the values in between are linearly interpolated. A good way to choose or create a palette is to simply use Seaborn palettes (https://seaborn.pydata.org/tutorial/color_palettes.html).
**`color_range`** : A tuple `(color_min, color_max)` that enables capping the values of `color` being mapped to `palette`. All `color` values less than `color_min` are capped to `color_min`, and all `color` values larger than `color_max` are capped to `color_max`. Then those values are mapped to `palette` as described under `color`.
**`size`** : A list, np.array or pandas.Series containing values based on which to apply the size to the shapes in the plot. Should have the same length as `x` and `y`.
**`size_range`** : A tuple `(size_min, size_max)` that enables capping the values of `size` being applied to the shapes in the plot. Essentially controls min and max size of the shapes.
**`size_scale`** : Used to scale the size of the shapes in the plot to make them fit the size of the fields in the matrix. Default value is 500. You will likely need to fiddle with this parameter in order to find the right value for your figure size and the size range applied.
**`x_order`** : Should contain all distinct values of `x` ordered in the way you want them shown on the x-axis from left to right.
**`y_order`** : Should contain all distinct values of `y` ordered in the way you want them shown on the y-axis from bottom to top.
**`marker`** : Specify the shape to use in the plot. It can be any of the **matplotlib** marker shapes (https://matplotlib.org/api/markers_api.html). The default is 's' for square.
**`xlabel`** : Label for the x-axis. Default is none.
%prep
%autosetup -n heatmapz-0.0.4
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-heatmapz -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.4-1
- Package Spec generated
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