/
fake_parula.py
282 lines (275 loc) · 12.9 KB
/
fake_parula.py
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from matplotlib.colors import LinearSegmentedColormap
from numpy import nan, inf
# Used to reconstruct the colormap in viscm
parameters = {'xp': [8.6840042204210732, -21.378780072752193, -13.715204596193757, -94.858944936224646, 53.679179741776352, -9.6],
'yp': [-36.497267048261136, -44.616177228232843, 10.381246780010315, 84.763008758371967, 6.324059763008762, 41],
'min_JK': 25.4069767442,
'max_JK': 95}
cm_data = [[ 0.26710521, 0.03311059, 0.6188155 ],
[ 0.26493929, 0.04780926, 0.62261795],
[ 0.26260545, 0.06084214, 0.62619176],
[ 0.26009691, 0.07264411, 0.62951561],
[ 0.25740785, 0.08360391, 0.63256745],
[ 0.25453369, 0.09395358, 0.63532497],
[ 0.25147146, 0.10384228, 0.6377661 ],
[ 0.24822014, 0.11337029, 0.6398697 ],
[ 0.24478105, 0.12260661, 0.64161629],
[ 0.24115816, 0.131599 , 0.6429888 ],
[ 0.23735836, 0.14038009, 0.64397346],
[ 0.23339166, 0.14897137, 0.64456048],
[ 0.22927127, 0.15738602, 0.64474476],
[ 0.22501278, 0.16563165, 0.64452595],
[ 0.22063349, 0.17371215, 0.64390834],
[ 0.21616055, 0.18162302, 0.64290515],
[ 0.21161851, 0.18936156, 0.64153295],
[ 0.20703353, 0.19692415, 0.63981287],
[ 0.20243273, 0.20430706, 0.63776986],
[ 0.19784363, 0.211507 , 0.63543183],
[ 0.19329361, 0.21852157, 0.63282872],
[ 0.18880937, 0.2253495 , 0.62999156],
[ 0.18442119, 0.23198815, 0.62695569],
[ 0.18014936, 0.23844124, 0.62374886],
[ 0.17601569, 0.24471172, 0.62040016],
[ 0.17204028, 0.25080356, 0.61693715],
[ 0.16824123, 0.25672163, 0.6133854 ],
[ 0.16463462, 0.26247158, 0.60976836],
[ 0.16123449, 0.26805963, 0.60610723],
[ 0.15805279, 0.27349243, 0.60242099],
[ 0.15509948, 0.27877688, 0.59872645],
[ 0.15238249, 0.28392004, 0.59503836],
[ 0.14990781, 0.28892902, 0.59136956],
[ 0.14767951, 0.29381086, 0.58773113],
[ 0.14569979, 0.29857245, 0.58413255],
[ 0.1439691 , 0.30322055, 0.58058191],
[ 0.14248613, 0.30776167, 0.57708599],
[ 0.14124797, 0.31220208, 0.57365049],
[ 0.14025018, 0.31654779, 0.57028011],
[ 0.13948691, 0.32080454, 0.5669787 ],
[ 0.13895174, 0.32497744, 0.56375063],
[ 0.13863958, 0.32907012, 0.56060453],
[ 0.138537 , 0.3330895 , 0.55753513],
[ 0.13863384, 0.33704026, 0.55454374],
[ 0.13891931, 0.34092684, 0.55163126],
[ 0.13938212, 0.34475344, 0.54879827],
[ 0.14001061, 0.34852402, 0.54604503],
[ 0.14079292, 0.35224233, 0.54337156],
[ 0.14172091, 0.35590982, 0.54078769],
[ 0.14277848, 0.35953205, 0.53828312],
[ 0.14395358, 0.36311234, 0.53585661],
[ 0.1452346 , 0.36665374, 0.5335074 ],
[ 0.14661019, 0.3701591 , 0.5312346 ],
[ 0.14807104, 0.37363011, 0.52904278],
[ 0.1496059 , 0.3770697 , 0.52692951],
[ 0.15120289, 0.3804813 , 0.52488853],
[ 0.15285214, 0.38386729, 0.52291854],
[ 0.15454421, 0.38722991, 0.52101815],
[ 0.15627225, 0.39056998, 0.5191937 ],
[ 0.15802555, 0.39389087, 0.5174364 ],
[ 0.15979549, 0.39719482, 0.51574311],
[ 0.16157425, 0.40048375, 0.51411214],
[ 0.16335571, 0.40375871, 0.51254622],
[ 0.16513234, 0.40702178, 0.51104174],
[ 0.1668964 , 0.41027528, 0.50959299],
[ 0.16864151, 0.41352084, 0.50819797],
[ 0.17036277, 0.41675941, 0.50685814],
[ 0.1720542 , 0.41999269, 0.50557008],
[ 0.17370932, 0.42322271, 0.50432818],
[ 0.17532301, 0.42645082, 0.50313007],
[ 0.17689176, 0.42967776, 0.50197686],
[ 0.17841013, 0.43290523, 0.5008633 ],
[ 0.17987314, 0.43613477, 0.49978492],
[ 0.18127676, 0.43936752, 0.49873901],
[ 0.18261885, 0.44260392, 0.49772638],
[ 0.18389409, 0.44584578, 0.49673978],
[ 0.18509911, 0.44909409, 0.49577605],
[ 0.18623135, 0.4523496 , 0.494833 ],
[ 0.18728844, 0.45561305, 0.49390803],
[ 0.18826671, 0.45888565, 0.49299567],
[ 0.18916393, 0.46216809, 0.49209268],
[ 0.18997879, 0.46546084, 0.49119678],
[ 0.19070881, 0.46876472, 0.49030328],
[ 0.19135221, 0.47208035, 0.48940827],
[ 0.19190791, 0.47540815, 0.48850845],
[ 0.19237491, 0.47874852, 0.4876002 ],
[ 0.19275204, 0.48210192, 0.48667935],
[ 0.19303899, 0.48546858, 0.48574251],
[ 0.19323526, 0.48884877, 0.48478573],
[ 0.19334062, 0.49224271, 0.48380506],
[ 0.19335574, 0.49565037, 0.4827974 ],
[ 0.19328143, 0.49907173, 0.48175948],
[ 0.19311664, 0.50250719, 0.48068559],
[ 0.192864 , 0.50595628, 0.47957408],
[ 0.19252521, 0.50941877, 0.47842186],
[ 0.19210087, 0.51289469, 0.47722441],
[ 0.19159194, 0.516384 , 0.47597744],
[ 0.19100267, 0.51988593, 0.47467988],
[ 0.19033595, 0.52340005, 0.47332894],
[ 0.18959113, 0.5269267 , 0.47191795],
[ 0.18877336, 0.530465 , 0.47044603],
[ 0.18788765, 0.53401416, 0.46891178],
[ 0.18693822, 0.53757359, 0.46731272],
[ 0.18592276, 0.54114404, 0.46563962],
[ 0.18485204, 0.54472367, 0.46389595],
[ 0.18373148, 0.5483118 , 0.46207951],
[ 0.18256585, 0.55190791, 0.4601871 ],
[ 0.18135481, 0.55551253, 0.45821002],
[ 0.18011172, 0.55912361, 0.45615277],
[ 0.17884392, 0.56274038, 0.45401341],
[ 0.17755858, 0.56636217, 0.45178933],
[ 0.17625543, 0.56998972, 0.44946971],
[ 0.174952 , 0.57362064, 0.44706119],
[ 0.17365805, 0.57725408, 0.44456198],
[ 0.17238403, 0.58088916, 0.4419703 ],
[ 0.17113321, 0.58452637, 0.43927576],
[ 0.1699221 , 0.58816399, 0.43648119],
[ 0.1687662 , 0.5918006 , 0.43358772],
[ 0.16767908, 0.59543526, 0.43059358],
[ 0.16667511, 0.59906699, 0.42749697],
[ 0.16575939, 0.60269653, 0.42428344],
[ 0.16495764, 0.6063212 , 0.42096245],
[ 0.16428695, 0.60993988, 0.41753246],
[ 0.16376481, 0.61355147, 0.41399151],
[ 0.16340924, 0.61715487, 0.41033757],
[ 0.16323549, 0.62074951, 0.40656329],
[ 0.16326148, 0.62433443, 0.40266378],
[ 0.16351136, 0.62790748, 0.39864431],
[ 0.16400433, 0.63146734, 0.39450263],
[ 0.16475937, 0.63501264, 0.39023638],
[ 0.16579502, 0.63854196, 0.38584309],
[ 0.16712921, 0.64205381, 0.38132023],
[ 0.168779 , 0.64554661, 0.37666513],
[ 0.17075915, 0.64901912, 0.37186962],
[ 0.17308572, 0.65246934, 0.36693299],
[ 0.1757732 , 0.65589512, 0.36185643],
[ 0.17883344, 0.65929449, 0.3566372 ],
[ 0.18227669, 0.66266536, 0.35127251],
[ 0.18611159, 0.66600553, 0.34575959],
[ 0.19034516, 0.66931265, 0.34009571],
[ 0.19498285, 0.67258423, 0.3342782 ],
[ 0.20002863, 0.67581761, 0.32830456],
[ 0.20548509, 0.67900997, 0.3221725 ],
[ 0.21135348, 0.68215834, 0.31587999],
[ 0.2176339 , 0.68525954, 0.30942543],
[ 0.22432532, 0.68831023, 0.30280771],
[ 0.23142568, 0.69130688, 0.29602636],
[ 0.23893914, 0.69424565, 0.28906643],
[ 0.2468574 , 0.69712255, 0.28194103],
[ 0.25517514, 0.69993351, 0.27465372],
[ 0.26388625, 0.70267437, 0.26720869],
[ 0.27298333, 0.70534087, 0.25961196],
[ 0.28246016, 0.70792854, 0.25186761],
[ 0.29232159, 0.71043184, 0.2439642 ],
[ 0.30253943, 0.71284765, 0.23594089],
[ 0.31309875, 0.71517209, 0.22781515],
[ 0.32399522, 0.71740028, 0.21959115],
[ 0.33520729, 0.71952906, 0.21129816],
[ 0.3467003 , 0.72155723, 0.20298257],
[ 0.35846225, 0.72348143, 0.19466318],
[ 0.3704552 , 0.72530195, 0.18639333],
[ 0.38264126, 0.72702007, 0.17822762],
[ 0.39499483, 0.72863609, 0.17020921],
[ 0.40746591, 0.73015499, 0.1624122 ],
[ 0.42001969, 0.73158058, 0.15489659],
[ 0.43261504, 0.73291878, 0.14773267],
[ 0.44521378, 0.73417623, 0.14099043],
[ 0.45777768, 0.73536072, 0.13474173],
[ 0.47028295, 0.73647823, 0.1290455 ],
[ 0.48268544, 0.73753985, 0.12397794],
[ 0.49497773, 0.73854983, 0.11957878],
[ 0.5071369 , 0.73951621, 0.11589589],
[ 0.51913764, 0.74044827, 0.11296861],
[ 0.53098624, 0.74134823, 0.11080237],
[ 0.5426701 , 0.74222288, 0.10940411],
[ 0.55417235, 0.74308049, 0.10876749],
[ 0.56550904, 0.74392086, 0.10885609],
[ 0.57667994, 0.74474781, 0.10963233],
[ 0.58767906, 0.74556676, 0.11105089],
[ 0.59850723, 0.74638125, 0.1130567 ],
[ 0.609179 , 0.74719067, 0.11558918],
[ 0.61969877, 0.74799703, 0.11859042],
[ 0.63007148, 0.74880206, 0.12200388],
[ 0.64030249, 0.74960714, 0.12577596],
[ 0.65038997, 0.75041586, 0.12985641],
[ 0.66034774, 0.75122659, 0.1342004 ],
[ 0.67018264, 0.75203968, 0.13876817],
[ 0.67990043, 0.75285567, 0.14352456],
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[ 0.69900745, 0.75449768, 0.15348445],
[ 0.70840781, 0.75532408, 0.15863839],
[ 0.71771325, 0.75615416, 0.16388098],
[ 0.72692898, 0.75698787, 0.1691954 ],
[ 0.73606001, 0.75782508, 0.17456729],
[ 0.74511119, 0.75866562, 0.17998443],
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[ 0.76299247, 0.76035568, 0.19091446],
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[ 0.78060815, 0.76205561, 0.20191973],
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[ 0.91550775, 0.77553893, 0.28875751],
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[ 0.95686038, 0.7793949 , 0.31397459],
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[ 0.98227405, 0.78134549, 0.32678728],
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[ 0.99505988, 0.78542889, 0.32106514],
[ 0.99594185, 0.79046888, 0.31648808],
[ 0.99646635, 0.79566972, 0.31244662],
[ 0.99681528, 0.80094905, 0.30858532],
[ 0.9970578 , 0.80627441, 0.30479247],
[ 0.99724883, 0.81161757, 0.30105328],
[ 0.99736711, 0.81699344, 0.29725528],
[ 0.99742254, 0.82239736, 0.29337235],
[ 0.99744736, 0.82781159, 0.28943391],
[ 0.99744951, 0.83323244, 0.28543062],
[ 0.9973953 , 0.83867931, 0.2812767 ],
[ 0.99727248, 0.84415897, 0.27692897],
[ 0.99713953, 0.84963903, 0.27248698],
[ 0.99698641, 0.85512544, 0.26791703],
[ 0.99673736, 0.86065927, 0.26304767],
[ 0.99652358, 0.86616957, 0.25813608],
[ 0.99622774, 0.87171946, 0.25292044],
[ 0.99590494, 0.87727931, 0.24750009],
[ 0.99555225, 0.88285068, 0.2418514 ],
[ 0.99513763, 0.8884501 , 0.23588062],
[ 0.99471252, 0.89405076, 0.2296837 ],
[ 0.99421873, 0.89968246, 0.2230963 ],
[ 0.99370185, 0.90532165, 0.21619768],
[ 0.99313786, 0.91098038, 0.2088926 ],
[ 0.99250707, 0.91666811, 0.20108214],
[ 0.99187888, 0.92235023, 0.19290417],
[ 0.99110991, 0.92809686, 0.18387963],
[ 0.99042108, 0.93379995, 0.17458127],
[ 0.98958484, 0.93956962, 0.16420166],
[ 0.98873988, 0.94533859, 0.15303117],
[ 0.98784836, 0.95112482, 0.14074826],
[ 0.98680727, 0.95697596, 0.12661626]]
test_cm = LinearSegmentedColormap.from_list(__file__, cm_data)
if __name__ == "__main__":
import matplotlib.pyplot as plt
import numpy as np
try:
from viscm import viscm
viscm(test_cm)
except ImportError:
print("viscm not found, falling back on simple display")
plt.imshow(np.linspace(0, 100, 256)[None, :], aspect='auto',
cmap=test_cm)
plt.show()