Make it easier to use user defined colormaps in matplotlib. Default colormaps are from NCL website.
Users can define a environmental variable CMAP_DIR pointing to the folder containing the self-defined rgb files.
Special thanks to Dr. Shen: for suggestions and the help of uploading this package to Pypi and anaconda cloud.
Installation:
pip install cmaps
or:
conda install -c conda-forge cmaps
or:
git clone https://github.com/hhuangwx/cmaps.git cd cmaps python setup.py install
Usage:
import matplotlib.pyplot as plt import cmaps import numpy as np x = y = np.arange(-3.0, 3.01, 0.05) X, Y = np.meshgrid(x, y) sigmax = sigmay = 1.0 mux = muy = sigmaxy=0.0 Xmu = X-mux Ymu = Y-muy rho = sigmaxy/(sigmax*sigmay) z = Xmu**2/sigmax**2 + Ymu**2/sigmay**2 - 2*rho*Xmu*Ymu/(sigmax*sigmay) denom = 2*np.pi*sigmax*sigmay*np.sqrt(1-rho**2) Z = np.exp(-z/(2*(1-rho**2))) / denom plt.pcolormesh(X,Y,Z,cmap=cmaps.WhiteBlueGreenYellowRed) plt.colorbar()
List the colormaps using the code in the examples:
import cmaps import numpy as np import inspect import matplotlib.pyplot as plt import matplotlib matplotlib.rc('text', usetex=False) def list_cmaps(): attributes = inspect.getmembers(cmaps, lambda _: not (inspect.isroutine(_))) colors = [_[0] for _ in attributes if not (_[0].startswith('__') and _[0].endswith('__'))] return colors if __name__ == '__main__': color = list_cmaps() a = np.outer(np.arange(0, 1, 0.001), np.ones(10)) plt.figure(figsize=(20, 20)) plt.subplots_adjust(top=0.95, bottom=0.05, left=0.01, right=0.99) ncmaps = len(color) nrows = 8 for i, k in enumerate(color): plt.subplot(nrows, ncmaps // nrows + 1, i + 1) plt.axis('off') plt.imshow(a, aspect='auto', cmap=getattr(cmaps, k), origin='lower') plt.title(k, rotation=90, fontsize=10) plt.title(k, fontsize=10) plt.savefig('colormaps.png', dpi=300)