क्या किसी ने Matplotlib में Parula colormap बनाया है?

Question

मुझे पता है कि कुछ discussion of Matlab copywriting their new default colormap रहे हैं, लेकिन मुझे आश्चर्य है कि किसी भी निडर उपयोगकर्ता ने Matplotlib में colormap बनाया है।

Viridis बहुत अच्छा है, लेकिन मैं जो करने की कोशिश कर रहा हूं उसके लिए थोड़ा सा अंधेरा है।

Answer 1

मामले में कड़ी @tom कि टूट जाता है यहाँ यह है प्रदान की,:

from matplotlib.colors import LinearSegmentedColormap 

cm_data = [[0.2081, 0.1663, 0.5292], [0.2116238095, 0.1897809524, 0.5776761905], 
[0.212252381, 0.2137714286, 0.6269714286], [0.2081, 0.2386, 0.6770857143], 
[0.1959047619, 0.2644571429, 0.7279], [0.1707285714, 0.2919380952, 
    0.779247619], [0.1252714286, 0.3242428571, 0.8302714286], 
[0.0591333333, 0.3598333333, 0.8683333333], [0.0116952381, 0.3875095238, 
    0.8819571429], [0.0059571429, 0.4086142857, 0.8828428571], 
[0.0165142857, 0.4266, 0.8786333333], [0.032852381, 0.4430428571, 
    0.8719571429], [0.0498142857, 0.4585714286, 0.8640571429], 
[0.0629333333, 0.4736904762, 0.8554380952], [0.0722666667, 0.4886666667, 
    0.8467], [0.0779428571, 0.5039857143, 0.8383714286], 
[0.079347619, 0.5200238095, 0.8311809524], [0.0749428571, 0.5375428571, 
    0.8262714286], [0.0640571429, 0.5569857143, 0.8239571429], 
[0.0487714286, 0.5772238095, 0.8228285714], [0.0343428571, 0.5965809524, 
    0.819852381], [0.0265, 0.6137, 0.8135], [0.0238904762, 0.6286619048, 
    0.8037619048], [0.0230904762, 0.6417857143, 0.7912666667], 
[0.0227714286, 0.6534857143, 0.7767571429], [0.0266619048, 0.6641952381, 
    0.7607190476], [0.0383714286, 0.6742714286, 0.743552381], 
[0.0589714286, 0.6837571429, 0.7253857143], 
[0.0843, 0.6928333333, 0.7061666667], [0.1132952381, 0.7015, 0.6858571429], 
[0.1452714286, 0.7097571429, 0.6646285714], [0.1801333333, 0.7176571429, 
    0.6424333333], [0.2178285714, 0.7250428571, 0.6192619048], 
[0.2586428571, 0.7317142857, 0.5954285714], [0.3021714286, 0.7376047619, 
    0.5711857143], [0.3481666667, 0.7424333333, 0.5472666667], 
[0.3952571429, 0.7459, 0.5244428571], [0.4420095238, 0.7480809524, 
    0.5033142857], [0.4871238095, 0.7490619048, 0.4839761905], 
[0.5300285714, 0.7491142857, 0.4661142857], [0.5708571429, 0.7485190476, 
    0.4493904762], [0.609852381, 0.7473142857, 0.4336857143], 
[0.6473, 0.7456, 0.4188], [0.6834190476, 0.7434761905, 0.4044333333], 
[0.7184095238, 0.7411333333, 0.3904761905], 
[0.7524857143, 0.7384, 0.3768142857], [0.7858428571, 0.7355666667, 
    0.3632714286], [0.8185047619, 0.7327333333, 0.3497904762], 
[0.8506571429, 0.7299, 0.3360285714], [0.8824333333, 0.7274333333, 0.3217], 
[0.9139333333, 0.7257857143, 0.3062761905], [0.9449571429, 0.7261142857, 
    0.2886428571], [0.9738952381, 0.7313952381, 0.266647619], 
[0.9937714286, 0.7454571429, 0.240347619], [0.9990428571, 0.7653142857, 
    0.2164142857], [0.9955333333, 0.7860571429, 0.196652381], 
[0.988, 0.8066, 0.1793666667], [0.9788571429, 0.8271428571, 0.1633142857], 
[0.9697, 0.8481380952, 0.147452381], [0.9625857143, 0.8705142857, 0.1309], 
[0.9588714286, 0.8949, 0.1132428571], [0.9598238095, 0.9218333333, 
    0.0948380952], [0.9661, 0.9514428571, 0.0755333333], 
[0.9763, 0.9831, 0.0538]] 

parula_map = LinearSegmentedColormap.from_list('parula', cm_data) 
# For use of "viscm view" 
test_cm = parula_map 

if __name__ == "__main__": 
    import matplotlib.pyplot as plt 
    import numpy as np 

    try: 
     from viscm import viscm 
     viscm(parula_map) 
    except ImportError: 
     print("viscm not found, falling back on simple display") 
     plt.imshow(np.linspace(0, 100, 256)[None, :], aspect='auto', 
        cmap=parula_map) 
    plt.show()