Metadata-Version: 2.1
Name: xycmap
Version: 1.0.0
Summary: Bivariate colormap solutions
Home-page: https://github.com/rbjansen/xycmap
Author: Remco Bastiaan Jansen
Author-email: r.b.jansen.uu@gmail.com
License: MIT
Description: # xycmap
        > Bivariate colormap solutions.
        
        This package makes it easy to create custom two-dimensional colormaps, apply them to your series, and add bivariate color legends to your plots.
        
        ![example](https://user-images.githubusercontent.com/31345940/109506935-7b7ad100-7a9e-11eb-868f-899804e05bf6.png)
        
        ## Installation
        
        `pip install xycmap`
        
        ## Usage
        
        Make a custom interpolated colormap by specifying four corner colors (see recognized formats [here](https://matplotlib.org/stable/api/colors_api.html)), and dimensions `n`:
        
        ```python
        corner_colors = ("lightgrey", "green", "blue", "red")
        n = (5, 5)  # x, y
        cmap = xycmap.custom_xycmap(corner_colors=corner_colors, n=n)
        ```
        
        ![custom_xycmap](https://user-images.githubusercontent.com/31345940/109507925-8c781200-7a9f-11eb-9a2d-32c19b07a1c0.png)
        
        Or make a colormap by mixing two matplotlib colormaps, and specifying dimensions `n`:
        
        ```python
        import matplotlib.pyplot as plt
        xcmap = plt.cm.rainbow
        ycmap = plt.cm.Greys
        n = (5, 5)  # x, y
        cmap = xycmap.custom_xycmap(xcmap=xcmap, ycmap=ycmap, n=n)
        ```
        
        ![mean_xycmap](https://user-images.githubusercontent.com/31345940/109420855-d647f600-79d4-11eb-8b3a-f50505fcc44a.png)
        
        With that in place, apply the colormap to two series that are numeric or categorical:
        
        ```python
        colors = xycmap.bivariate_color(sx=sx, sy=sy, cmap=cmap)
        ```
        
        Note that you can apply limits to the axes, as well as pass custom bins for the axes (if numerical). See the docstring for details.
        
        Then simply pass `colors` to your plot. To add a legend, create a new ax and run `bivariate_legend()` into the ax with the same parameters as `bivariate_color()`, e.g.:
        
        ```python
        cax = fig.add_axes([1, 0.25, 0.5, 0.5])
        cax = xycmap.bivariate_legend(ax=cax, sx=sx, sy=sy, cmap=cmap)
        ```
        
        ## Meta
        
        Remco Bastiaan Jansen – r.b.jansen.uu@gmail.com - [https://github.com/rbjansen](https://github.com/rbjansen)
        
        Distributed under the MIT license. See `LICENSE` for more information.
        
Keywords: visualization,colormap,color,bivariate,two-dimensional
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.8
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Visualization
Description-Content-Type: text/markdown
