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Consider a variable x containing a floating point number. I want to use matplotlib's colormaps to map this number to a color, but not plot anything. Basically, I want to be able to choose the colormap with mpl.cm.autumn for example, use mpl.colors.Normalize(vmin = -20, vmax = 10) to set the range, and then map x to the corresponding color. But I really don't get the documentation of mpl.cm, so if anyone could give me a hint.
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( cmaps.viridis is a matplotlib.colors.ListedColormap ) import matplotlib.pyplot as plt import matplotlib.image as mpimg import numpy as np import colormaps as cmaps img=mpimg.imread('stinkbug.png') lum_img = np.flipud(img[:,:,0]) imgplot = plt.pcolormesh(lum_img, cmap=cmaps.viridis)
MatPlotLib with PythonCreate x, y and c data points, using numpy. Create scatter points over the axes (closely so as to get a line), using the scatter() method with c and marker='_'. To display the figure, use the show() method.
It's as simple as cm.hot(0.3):
import matplotlib.cm as cm print(cm.hot(0.3)) (0.8240081481370484, 0.0, 0.0, 1.0) If you also want to have the normalizer, use
import matplotlib as mpl import matplotlib.cm as cm norm = mpl.colors.Normalize(vmin=-20, vmax=10) cmap = cm.hot x = 0.3 m = cm.ScalarMappable(norm=norm, cmap=cmap) print(m.to_rgba(x)) (1.0, 0.8225486412996345, 0.0, 1.0) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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