%global _empty_manifest_terminate_build 0 Name: python-distinctipy Version: 1.2.2 Release: 1 Summary: A lightweight package for generating visually distinct colours. License: MIT License URL: https://github.com/alan-turing-institute/distinctipy Source0: https://mirrors.nju.edu.cn/pypi/web/packages/3c/57/da49e941e26d0063b5d59c730f324ca72b4a693bf37543ae15016d48e18f/distinctipy-1.2.2.tar.gz BuildArch: noarch Requires: python3-numpy Requires: python3-numpy Requires: python3-black Requires: python3-codecov Requires: python3-coverage Requires: python3-flake8 Requires: python3-isort Requires: python3-pytest Requires: python3-pytest-cov Requires: python3-pandas Requires: python3-matplotlib Requires: python3-sphinx-rtd-theme Requires: python3-nbsphinx Requires: python3-sphinx-rtd-theme Requires: python3-nbsphinx Requires: python3-pandas Requires: python3-matplotlib Requires: python3-black Requires: python3-codecov Requires: python3-coverage Requires: python3-flake8 Requires: python3-isort Requires: python3-pytest Requires: python3-pytest-cov %description ![distinctipy logo](https://raw.githubusercontent.com/alan-turing-institute/distinctipy/main/distinctipy_logo.png) ![tests](https://github.com/alan-turing-institute/distinctipy/workflows/Tests/badge.svg) ![build](https://github.com/alan-turing-institute/distinctipy/workflows/Build/badge.svg) [![codecov](https://codecov.io/gh/alan-turing-institute/distinctipy/branch/main/graph/badge.svg)](https://codecov.io/gh/alan-turing-institute/distinctipy) [![DOI](https://zenodo.org/badge/188444660.svg)](https://zenodo.org/badge/latestdoi/188444660) [![Documentation Status](https://readthedocs.org/projects/distinctipy/badge/?version=latest)](https://distinctipy.readthedocs.io/en/latest/?badge=latest) *distinctipy* is a lightweight python package providing functions to generate colours that are visually distinct from one another. Commonly available qualitative colormaps provided by the likes of matplotlib generally have no more than 20 colours, but for some applications it is useful to have many more colours that are clearly different from one another. *distinctipy* can generate lists of colours of any length, with each new colour added to the list being as visually distinct from the pre-existing colours in the list as possible. ## Installation *distinctipy* is designed for Python 3 and can be installed with pip by running: ```shell pip install distinctipy ``` Alternatively clone the repo and install it locally: ```shell git clone https://github.com/alan-turing-institute/distinctipy.git cd distinctipy pip install . ``` ### Optional Dependencies Starting in version 1.2.1 `distinctipy` no longer bundles `matplotlib`, `pandas` or dev dependencies in the default installation. If you wish to view colours (e.g. with `distinctipy.color_swatch`) or examples you will need `matplotlib` and `pandas` installed. To do this, either install `distinctipy` with the optional flag: ```bash pip install distinctipy[optional] ``` Or install them separately: ```bash pip install matplotlib pandas ``` For developers, to install the stack needed to run tests, generate docs etc. use the `[all]` flag: ```bash pip install distinctipy[all] ``` ## Usage and Examples *distinctipy* can: * Generate N visually distinct colours: `distinctipy.get_colors(N)` * Generate colours that are distinct from an existing list of colours: `distinctipy.get_colors(N, existing_colors)` * Generate pastel colours: `distinctipy.get_colors(N, pastel_factor=0.7)` * Select black or white as the best font colour for any background colour: `distinctipy.get_text_color(background_color)` * Convert lists of colours into matplotlib colormaps: `distinctipy.get_colormap(colors)` * Invert colours: `distinctipy.invert_colors(colors)` * Nicely display generated colours: `distinctipy.color_swatch(colors)` * Compare distinctipy colours to other common colormaps: `examples.compare_clusters()` and `examples.compare_colors()` * Simulate how colours look for someone with colourblindness: `colorblind.simulate_colors(colors, colorblind_type='Deuteranomaly')` * Attempt to generate colours as distinct as possible for someone with colourblindness `distinctipy.get_colors(N, existing_colors, colorblind_type="Deuteranomaly")` For example, to create and then display N = 36 visually distinct colours: ```python from distinctipy import distinctipy # number of colours to generate N = 36 # generate N visually distinct colours colors = distinctipy.get_colors(N) # display the colours distinctipy.color_swatch(colors) ``` More detailed usage and example output can be found in the notebook **[examples.ipynb](https://github.com/alan-turing-institute/distinctipy/blob/main/examples.ipynb)** and **[examples gallery](https://github.com/alan-turing-institute/distinctipy/tree/main/examples)**. ## References *distinctipy* was heavily influenced and inspired by several web sources and stack overflow answers. In particular: * **Random generation of distinct colours:** [Andrew Dewes on GitHub](https://gist.github.com/adewes/5884820) * **Colour distance metric:** [Thiadmer Riemersma at CompuPhase](https://www.compuphase.com/cmetric.htm) * **Best text colour for background:** [Mark Ransom on Stack Overflow](https://stackoverflow.com/a/3943023) * **Colourblindness Filters:** [Matthew Wickline and the Human-Computer Interaction Resource Network](http://web.archive.org/web/20090318054431/http://www.nofunc.com/Color_Blindness_Library) (web archive) ## Citing distinctipy If you would like to cite distinctipy, please refer to the upload of the package on Zenodo: https://doi.org/10.5281/zenodo.3985191 %package -n python3-distinctipy Summary: A lightweight package for generating visually distinct colours. Provides: python-distinctipy BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-distinctipy ![distinctipy logo](https://raw.githubusercontent.com/alan-turing-institute/distinctipy/main/distinctipy_logo.png) ![tests](https://github.com/alan-turing-institute/distinctipy/workflows/Tests/badge.svg) ![build](https://github.com/alan-turing-institute/distinctipy/workflows/Build/badge.svg) [![codecov](https://codecov.io/gh/alan-turing-institute/distinctipy/branch/main/graph/badge.svg)](https://codecov.io/gh/alan-turing-institute/distinctipy) [![DOI](https://zenodo.org/badge/188444660.svg)](https://zenodo.org/badge/latestdoi/188444660) [![Documentation Status](https://readthedocs.org/projects/distinctipy/badge/?version=latest)](https://distinctipy.readthedocs.io/en/latest/?badge=latest) *distinctipy* is a lightweight python package providing functions to generate colours that are visually distinct from one another. Commonly available qualitative colormaps provided by the likes of matplotlib generally have no more than 20 colours, but for some applications it is useful to have many more colours that are clearly different from one another. *distinctipy* can generate lists of colours of any length, with each new colour added to the list being as visually distinct from the pre-existing colours in the list as possible. ## Installation *distinctipy* is designed for Python 3 and can be installed with pip by running: ```shell pip install distinctipy ``` Alternatively clone the repo and install it locally: ```shell git clone https://github.com/alan-turing-institute/distinctipy.git cd distinctipy pip install . ``` ### Optional Dependencies Starting in version 1.2.1 `distinctipy` no longer bundles `matplotlib`, `pandas` or dev dependencies in the default installation. If you wish to view colours (e.g. with `distinctipy.color_swatch`) or examples you will need `matplotlib` and `pandas` installed. To do this, either install `distinctipy` with the optional flag: ```bash pip install distinctipy[optional] ``` Or install them separately: ```bash pip install matplotlib pandas ``` For developers, to install the stack needed to run tests, generate docs etc. use the `[all]` flag: ```bash pip install distinctipy[all] ``` ## Usage and Examples *distinctipy* can: * Generate N visually distinct colours: `distinctipy.get_colors(N)` * Generate colours that are distinct from an existing list of colours: `distinctipy.get_colors(N, existing_colors)` * Generate pastel colours: `distinctipy.get_colors(N, pastel_factor=0.7)` * Select black or white as the best font colour for any background colour: `distinctipy.get_text_color(background_color)` * Convert lists of colours into matplotlib colormaps: `distinctipy.get_colormap(colors)` * Invert colours: `distinctipy.invert_colors(colors)` * Nicely display generated colours: `distinctipy.color_swatch(colors)` * Compare distinctipy colours to other common colormaps: `examples.compare_clusters()` and `examples.compare_colors()` * Simulate how colours look for someone with colourblindness: `colorblind.simulate_colors(colors, colorblind_type='Deuteranomaly')` * Attempt to generate colours as distinct as possible for someone with colourblindness `distinctipy.get_colors(N, existing_colors, colorblind_type="Deuteranomaly")` For example, to create and then display N = 36 visually distinct colours: ```python from distinctipy import distinctipy # number of colours to generate N = 36 # generate N visually distinct colours colors = distinctipy.get_colors(N) # display the colours distinctipy.color_swatch(colors) ``` More detailed usage and example output can be found in the notebook **[examples.ipynb](https://github.com/alan-turing-institute/distinctipy/blob/main/examples.ipynb)** and **[examples gallery](https://github.com/alan-turing-institute/distinctipy/tree/main/examples)**. ## References *distinctipy* was heavily influenced and inspired by several web sources and stack overflow answers. In particular: * **Random generation of distinct colours:** [Andrew Dewes on GitHub](https://gist.github.com/adewes/5884820) * **Colour distance metric:** [Thiadmer Riemersma at CompuPhase](https://www.compuphase.com/cmetric.htm) * **Best text colour for background:** [Mark Ransom on Stack Overflow](https://stackoverflow.com/a/3943023) * **Colourblindness Filters:** [Matthew Wickline and the Human-Computer Interaction Resource Network](http://web.archive.org/web/20090318054431/http://www.nofunc.com/Color_Blindness_Library) (web archive) ## Citing distinctipy If you would like to cite distinctipy, please refer to the upload of the package on Zenodo: https://doi.org/10.5281/zenodo.3985191 %package help Summary: Development documents and examples for distinctipy Provides: python3-distinctipy-doc %description help ![distinctipy logo](https://raw.githubusercontent.com/alan-turing-institute/distinctipy/main/distinctipy_logo.png) ![tests](https://github.com/alan-turing-institute/distinctipy/workflows/Tests/badge.svg) ![build](https://github.com/alan-turing-institute/distinctipy/workflows/Build/badge.svg) [![codecov](https://codecov.io/gh/alan-turing-institute/distinctipy/branch/main/graph/badge.svg)](https://codecov.io/gh/alan-turing-institute/distinctipy) [![DOI](https://zenodo.org/badge/188444660.svg)](https://zenodo.org/badge/latestdoi/188444660) [![Documentation Status](https://readthedocs.org/projects/distinctipy/badge/?version=latest)](https://distinctipy.readthedocs.io/en/latest/?badge=latest) *distinctipy* is a lightweight python package providing functions to generate colours that are visually distinct from one another. Commonly available qualitative colormaps provided by the likes of matplotlib generally have no more than 20 colours, but for some applications it is useful to have many more colours that are clearly different from one another. *distinctipy* can generate lists of colours of any length, with each new colour added to the list being as visually distinct from the pre-existing colours in the list as possible. ## Installation *distinctipy* is designed for Python 3 and can be installed with pip by running: ```shell pip install distinctipy ``` Alternatively clone the repo and install it locally: ```shell git clone https://github.com/alan-turing-institute/distinctipy.git cd distinctipy pip install . ``` ### Optional Dependencies Starting in version 1.2.1 `distinctipy` no longer bundles `matplotlib`, `pandas` or dev dependencies in the default installation. If you wish to view colours (e.g. with `distinctipy.color_swatch`) or examples you will need `matplotlib` and `pandas` installed. To do this, either install `distinctipy` with the optional flag: ```bash pip install distinctipy[optional] ``` Or install them separately: ```bash pip install matplotlib pandas ``` For developers, to install the stack needed to run tests, generate docs etc. use the `[all]` flag: ```bash pip install distinctipy[all] ``` ## Usage and Examples *distinctipy* can: * Generate N visually distinct colours: `distinctipy.get_colors(N)` * Generate colours that are distinct from an existing list of colours: `distinctipy.get_colors(N, existing_colors)` * Generate pastel colours: `distinctipy.get_colors(N, pastel_factor=0.7)` * Select black or white as the best font colour for any background colour: `distinctipy.get_text_color(background_color)` * Convert lists of colours into matplotlib colormaps: `distinctipy.get_colormap(colors)` * Invert colours: `distinctipy.invert_colors(colors)` * Nicely display generated colours: `distinctipy.color_swatch(colors)` * Compare distinctipy colours to other common colormaps: `examples.compare_clusters()` and `examples.compare_colors()` * Simulate how colours look for someone with colourblindness: `colorblind.simulate_colors(colors, colorblind_type='Deuteranomaly')` * Attempt to generate colours as distinct as possible for someone with colourblindness `distinctipy.get_colors(N, existing_colors, colorblind_type="Deuteranomaly")` For example, to create and then display N = 36 visually distinct colours: ```python from distinctipy import distinctipy # number of colours to generate N = 36 # generate N visually distinct colours colors = distinctipy.get_colors(N) # display the colours distinctipy.color_swatch(colors) ``` More detailed usage and example output can be found in the notebook **[examples.ipynb](https://github.com/alan-turing-institute/distinctipy/blob/main/examples.ipynb)** and **[examples gallery](https://github.com/alan-turing-institute/distinctipy/tree/main/examples)**. ## References *distinctipy* was heavily influenced and inspired by several web sources and stack overflow answers. In particular: * **Random generation of distinct colours:** [Andrew Dewes on GitHub](https://gist.github.com/adewes/5884820) * **Colour distance metric:** [Thiadmer Riemersma at CompuPhase](https://www.compuphase.com/cmetric.htm) * **Best text colour for background:** [Mark Ransom on Stack Overflow](https://stackoverflow.com/a/3943023) * **Colourblindness Filters:** [Matthew Wickline and the Human-Computer Interaction Resource Network](http://web.archive.org/web/20090318054431/http://www.nofunc.com/Color_Blindness_Library) (web archive) ## Citing distinctipy If you would like to cite distinctipy, please refer to the upload of the package on Zenodo: https://doi.org/10.5281/zenodo.3985191 %prep %autosetup -n distinctipy-1.2.2 %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-distinctipy -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Wed May 10 2023 Python_Bot - 1.2.2-1 - Package Spec generated