Birisi Matplotlib'de Parula renk haritasını yaptı mı?

Question

Bazı discussion of Matlab copywriting their new default colormap olduğunu biliyorum, ancak herhangi bir cesur kullanıcının Matplotlib'de colormap'i yaratıp yaratmadığını merak ediyorum.

Viridis harika, ama yapmaya çalıştığım şey için biraz karanlık. durumda

Answer 1

işte burada, sonları sağlanan @tom link: [burada]

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()