ColorTools

A personal project to simplify the way I work with custom colors and colormaps in Matplotlib.

Features

• Interpolate Colors: Generate smooth gradients between two colors.
• Color Conversion: Switch between hex and RGB color formats.
• Trim Colormaps: Create custom colormaps by limiting their color range.

Note: All of this functionality exists in matplotlib. For example:

• Convert Format: matplotlib.colors.to_hex()
• Interpolate: LinearSegmentedColormap.from_list()

Installation

Just copy ColorTools.py into your project directory and import it.

Alternatively, use a relative import if you have it in a package

Usage Examples

Import

from ColorTools import interpolate_colors, rgb_to_hex, hex_to_rgb, trim_cmap

Interpolation

from ColorTools import interpolate_colors

# Generate a gradient between red and blue with 5 colors
colors = interpolate_colors("#FF0000", "#0000FF", 5)
print(colors)
# Output: ['#ff0000', '#bf003f', '#80007f', '#4000bf', '#0000ff']

Convert Formats

from ColorTools import hex_to_rgb, rgb_to_hex

# Convert hex to RGB
rgb = hex_to_rgb("#1E90FF")
print(rgb)  # Output: (30, 144, 255)

# Convert RGB to hex
hex_color = rgb_to_hex((30, 144, 255))
print(hex_color)  # Output: '#1e90ff'

Trim Colormaps

from ColorTools import trim_cmap
import matplotlib.pyplot as plt
import numpy as np

cmap = 'viridis'
trimmed_cmap = trim_cmap('viridis', 0.2, 0.8)

fig, axs = plt.subplots(1, 2, figsize=(6, 3), sharey=True)
arr = np.random.random((10, 10))
axs[0].imshow(arr, cmap=cmap)
axs[1].imshow(arr, cmap=trimmed_cmap)

axs[0].set_title("Normal Viridis")
axs[1].set_title("Trimmed Viridis")


plt.tight_layout()
plt.savefig("plotdemo.png")
plt.close()

License

This project is free to use for any purpose.