Metadata-Version: 2.1
Name: SecretColors
Version: 0.0.5
Summary: A small package for fantastic color palette
Home-page: https://github.com/secretBiology/SecretColors
Author: Rohit Suratekar
Author-email: rohitsuratekar@gmail.com
License: MIT License
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown

# Secret Colors

[![PyPI version](https://badge.fury.io/py/SecretColors.svg)](https://badge.fury.io/py/SecretColors)

Library generated for making plots with better color palette. It uses 
famous color palettes 
and adds few helpful functions. 

Few sample plots and inspiration behind this library can be found in 
[WeirdData blog](https://weirddata.github.io/2018/09/10/secret-colors.html). 


### Installation 

    pip install SecretColors

### Usage
Select different Palettes

    from SecretColors.palette import Palette
    ibm = Palette("ibm")  # IBM Palette
    material = Palette("material")  # Material Palette

Get Common Colors

    ibm.red()  # Default Red color from IBM palette (#008673)
    ibm.cerulean()  # Default Cerulean color from IBM palette (#009bef)

Shades of colors

    ibm.red(grade=10)  # Light Red with grade 10 (#fccec7)
    ibm.red(grade=80)  # Dark Red with grade 80 (#5c1f1b)
    ibm.red(grade=10000)  # Maximum/Minimum will be automatically adjusted (#3e1d1b)

Number of colors

    reds = ibm.red(no_of_colors=5)  # List of 3 Red colors from IBM palette
    dark_reds = ibm.red(no_of_colors=5, start_from=40)  # List of 3 Red 
    colors from IBM palettes starting from grade 40

Random Colors

    ibm.random()  # Random color from IBM Palette
    ibm.random(grade=60)  # Random color from grade 60
    ibm.random(no_of_colors=10)  # 10 Random colors
    ibm.random(no_of_colors=10, grade=30)  # Random colors with grade

Gradients between colors

    ibm.gradient_between(ibm.red(), ibm.blue(), no_of_colors=5)
    # Gradient between your own custom colors
    ibm.gradient_between("#b73752", "#2d74da", no_of_colors=5)

Palette output in other color-spaces

    ibm.change_color_mode("rgb")
    ibm.red()  # (0.90, 0.13, 0.14)

General Conversion Functions

    from SecretColors.palette import hex_to_rgb, hex_to_hsv, rgb_to_hex
    hex_to_rgb("#b73752")  # (0.71, 0.21, 0.32)
    hex_to_hsv("#b73752")  # (0.96, 0.69, 183.0)
    rgb_to_hex((0.71, 0.21, 0.32))  # #b53551

Text contrast on background color

    from SecretColors.palette import text_color
    text_color("#e62325")  # Returns #ffffff. This suggest white color text will
    # have good contrast on given color
    text_color("#eabbbc")  # Returns #000000. Suggesting black color text will have
    #  good contrast on given color

Simple Usage with `matplotlib`

    import matplotlib.pylab as plt
    import numpy as np

    data = np.random.randint(10, 50, 5)
    plt.bar(range(len(data)), data, color=ibm.blue(no_of_colors=len(data), start_from=30))
    plt.show()

Custom ColorMaps

    import matplotlib
    import matplotlib.pylab as plt
    from SecretColors.palette import ColorMap
    a = np.random.random((16, 16))
    cmap = ColorMap(matplotlib)
    plt.imshow(a, cmap=cmap.warm(), interpolation='nearest')
    plt.colorbar()
    plt.show()

    #Similarly
    plt.imshow(a, cmap=cmap.cool(), interpolation='nearest')
    plt.imshow(a, cmap=cmap.greens(), interpolation='nearest')
    plt.imshow(a, cmap=cmap.ibm(), interpolation='nearest')
    plt.imshow(a, cmap=cmap.material(), interpolation='nearest')

    # Qualitative maps
     plt.imshow(a, cmap=cmap.greens(is_qualitative=True), interpolation='nearest')

    # Definite Divisions
    plt.imshow(a, cmap=cmap.greens(is_qualitative=True, no_of_divisions=5), interpolation='nearest')

More color maps will be added in next release !


### TODO

- [x] IBM Color Palette
- [x] Color gradients
- [x] Google Material Design Palette
- [x] Text contrast detection
- [x] Matplotlib `cmap` helper functions
- [ ] ColorBrewer Palette
- [ ] VMware Palette

### Acknowledgments
Colors used in this library are partly taken from [IBM Design Language](https://www.ibm.com/design/language/resources/color-library/) and [Google 
Material Design](https://material.io/design/color/the-color-system.html)  

