は、誰かがmatplotlibの中Parulaのカラーマップを作っていますか？

Question

私はいくつかのdiscussion of Matlab copywriting their new default colormapがあったということを知っているが、いずれかの勇敢なユーザーはmatplotlibの中にカラーマップを作成している場合、私は思ったんだけど。

Viridisは素晴らしいですが、私がやろうとしていることは少し暗いです。

Answer 1

場合は休憩を提供@tomリンクは、ここにある：

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()