On 2015/06/03 12:27 PM, Nathaniel Smith wrote:
We also tried tweaking it a bit to end on a more saturated yellow,
which I think helps increase contrast in the deuteranomalous version
in particular, and put this on the website as an "option D":
https://bids.github.io/colormap/images/screenshots/option_d.png
Thank you. To me, this is more comfortable to look at than A, B, and
especially C.
We also previously designed a colormap that follows parula's ideas
pretty closely, in terms of starting/ending points, overall
brightness, and the trick of kinking over through orange at the top
end. It ends up being much much more green than parula though:
https://bids.github.io/colormap/images/screenshots/fake_parula.png
Interesting. That kink comes through as a visible over-emphasis of the
orange range in the images.
Attached are two more variations on the clockwise dark-to-light theme.
They achieve more dynamic range, and perhaps "colorfulness", but at the
cost of more relative loss of contrast in the colorblind cases. Is the
tradeoff worthwhile?
Eric
from matplotlib.colors import LinearSegmentedColormap
from numpy import nan, inf
# Used to reconstruct the colormap in pycam02ucs.cm.viscm
parameters = {'xp': [28.782590300914933, 60.468890475434989, -24.282418425088565, -47.188177587392218, -34.590010048125208, -8.6301496641810616],
'yp': [16.928446771378731, -42.626527050610804, -74.312827225130874, -5.5955497382198871, 42.5065445026178, 39.070680628272271],
'min_JK': 18.0859375,
'max_JK': 95.0390625}
cm_data = [[ 0.30593816, 0.00266902, 0.0061051 ],
[ 0.31049445, 0.00281314, 0.01074331],
[ 0.31501841, 0.00297468, 0.01602065],
[ 0.3195184 , 0.00312249, 0.02204556],
[ 0.32398709, 0.00328294, 0.02880862],
[ 0.32843006, 0.00343291, 0.03641347],
[ 0.33284287, 0.00358919, 0.04466259],
[ 0.33722794, 0.00373997, 0.05287228],
[ 0.34158401, 0.00388914, 0.06102198],
[ 0.34591015, 0.0040397 , 0.06913597],
[ 0.35020835, 0.00417912, 0.07726788],
[ 0.35447435, 0.00432876, 0.08538353],
[ 0.35871326, 0.00445639, 0.09357214],
[ 0.36291947, 0.00459302, 0.10177173],
[ 0.36709555, 0.00471965, 0.11003439],
[ 0.37124003, 0.00484227, 0.11835335],
[ 0.37535139, 0.00496951, 0.12671589],
[ 0.37943182, 0.00507827, 0.13517718],
[ 0.38347763, 0.0051954 , 0.1436843 ],
[ 0.38748989, 0.00530563, 0.15227436],
[ 0.39146758, 0.00541166, 0.16094589],
[ 0.39540886, 0.00552783, 0.169674 ],
[ 0.3993146 , 0.00563205, 0.17850829],
[ 0.40318253, 0.00574449, 0.18741263],
[ 0.40701159, 0.00587141, 0.19638009],
[ 0.41080188, 0.00598896, 0.20546335],
[ 0.41455113, 0.0061258 , 0.21461195],
[ 0.41825834, 0.00628491, 0.22382709],
[ 0.42192262, 0.00644595, 0.23315539],
[ 0.42554221, 0.0066368 , 0.24255105],
[ 0.42911584, 0.00686223, 0.25201397],
[ 0.43264184, 0.00711059, 0.26157606],
[ 0.43611865, 0.00739991, 0.27121371],
[ 0.43954483, 0.00774183, 0.28091667],
[ 0.44291849, 0.0081382 , 0.29069433],
[ 0.44623724, 0.00858895, 0.30056102],
[ 0.4494999 , 0.00911734, 0.31048822],
[ 0.45270459, 0.00973307, 0.32047446],
[ 0.45584867, 0.0104402 , 0.33053061],
[ 0.45892961, 0.01124886, 0.34065775],
[ 0.46194612, 0.01218144, 0.35083506],
[ 0.46489594, 0.01325186, 0.3610596 ],
[ 0.46777666, 0.01447465, 0.37132922],
[ 0.47058405, 0.01585603, 0.38166101],
[ 0.47331737, 0.01742581, 0.39202674],
[ 0.47597409, 0.01920295, 0.40242192],
[ 0.47855157, 0.02120777, 0.41284165],
[ 0.48104715, 0.02346196, 0.42328061],
[ 0.48345624, 0.02598275, 0.43374728],
[ 0.48577749, 0.02880089, 0.44422203],
[ 0.48800839, 0.03194345, 0.45469593],
[ 0.49014605, 0.03543786, 0.46516216],
[ 0.49218758, 0.03931295, 0.47561354],
[ 0.49413003, 0.04347853, 0.48604251],
[ 0.49597027, 0.04779536, 0.49644208],
[ 0.49770377, 0.05226892, 0.50681131],
[ 0.49932935, 0.05689842, 0.51713227],
[ 0.50084406, 0.06168052, 0.52739632],
[ 0.50224498, 0.06661185, 0.53759456],
[ 0.50352922, 0.07168902, 0.54771787],
[ 0.50469393, 0.07690861, 0.55775699],
[ 0.50573632, 0.0822671 , 0.56770249],
[ 0.50665366, 0.0877609 , 0.57754487],
[ 0.50744331, 0.09338632, 0.58727454],
[ 0.5081027 , 0.09913955, 0.59688191],
[ 0.50862938, 0.10501665, 0.6063574 ],
[ 0.50902102, 0.11101356, 0.61569147],
[ 0.5092751 , 0.11712627, 0.62487537],
[ 0.50938958, 0.12335046, 0.63389967],
[ 0.50936297, 0.12968134, 0.64275439],
[ 0.50919354, 0.13611425, 0.65143072],
[ 0.50887974, 0.1426444 , 0.65992011],
[ 0.50842022, 0.14926685, 0.66821431],
[ 0.50781383, 0.15597655, 0.67630542],
[ 0.50705966, 0.16276831, 0.68418591],
[ 0.50615699, 0.16963687, 0.69184866],
[ 0.50510539, 0.17657683, 0.69928701],
[ 0.50390464, 0.18358274, 0.70649474],
[ 0.5025548 , 0.19064905, 0.71346616],
[ 0.50105621, 0.19777018, 0.72019609],
[ 0.49940946, 0.2049405 , 0.72667991],
[ 0.49761526, 0.2121545 , 0.73291365],
[ 0.49567458, 0.21940666, 0.73889392],
[ 0.49358924, 0.22669104, 0.74461755],
[ 0.49136101, 0.234002 , 0.75008223],
[ 0.48899197, 0.24133394, 0.75528627],
[ 0.48648446, 0.24868133, 0.76022859],
[ 0.48384116, 0.2560387 , 0.76490869],
[ 0.48106503, 0.26340071, 0.7693267 ],
[ 0.4781593 , 0.27076208, 0.77348331],
[ 0.47512752, 0.2781177 , 0.77737983],
[ 0.4719735 , 0.28546258, 0.78101811],
[ 0.46870133, 0.29279188, 0.78440055],
[ 0.46531539, 0.30010094, 0.78753008],
[ 0.46182028, 0.30738527, 0.79041016],
[ 0.45822089, 0.31464057, 0.7930447 ],
[ 0.45452231, 0.32186273, 0.79543808],
[ 0.45072988, 0.32904785, 0.79759511],
[ 0.44684916, 0.33619226, 0.79952102],
[ 0.44288567, 0.34329262, 0.80122132],
[ 0.43884568, 0.3503455 , 0.802702 ],
[ 0.43473532, 0.35734787, 0.80396929],
[ 0.43056086, 0.36429696, 0.80502972],
[ 0.42632872, 0.37119022, 0.80589002],
[ 0.42204544, 0.37802533, 0.80655715],
[ 0.41771766, 0.38480021, 0.80703824],
[ 0.41335213, 0.39151301, 0.80734056],
[ 0.40895566, 0.39816209, 0.8074715 ],
[ 0.40453513, 0.40474605, 0.8074385 ],
[ 0.40009746, 0.4112637 , 0.8072491 ],
[ 0.39564958, 0.41771406, 0.80691081],
[ 0.39119843, 0.42409636, 0.80643115],
[ 0.38675107, 0.43040998, 0.8058177 ],
[ 0.3823147 , 0.43665438, 0.80507805],
[ 0.37789581, 0.44282955, 0.80421938],
[ 0.37350115, 0.44893549, 0.80324892],
[ 0.3691374 , 0.45497233, 0.80217381],
[ 0.36481112, 0.46094041, 0.80100101],
[ 0.36052875, 0.46684018, 0.79973734],
[ 0.35629656, 0.47267226, 0.79838945],
[ 0.35212066, 0.47843739, 0.79696377],
[ 0.34800697, 0.48413643, 0.79546656],
[ 0.34396121, 0.48977038, 0.79390384],
[ 0.33998883, 0.49534031, 0.79228142],
[ 0.33609505, 0.50084744, 0.79060487],
[ 0.33228481, 0.50629304, 0.7888795 ],
[ 0.32856276, 0.51167848, 0.78711041],
[ 0.32493321, 0.51700519, 0.78530242],
[ 0.32140017, 0.52227471, 0.78346009],
[ 0.31796726, 0.52748859, 0.78158772],
[ 0.31463776, 0.53264846, 0.77968936],
[ 0.31141453, 0.537756 , 0.77776877],
[ 0.30830029, 0.54281285, 0.77582965],
[ 0.30529701, 0.54782078, 0.77387515],
[ 0.30240618, 0.55278164, 0.77190811],
[ 0.299629 , 0.55769722, 0.76993121],
[ 0.29696628, 0.56256933, 0.76794687],
[ 0.29441839, 0.5673998 , 0.76595727],
[ 0.29198527, 0.57219047, 0.76396427],
[ 0.28966643, 0.57694317, 0.76196953],
[ 0.28746101, 0.58165974, 0.75997439],
[ 0.28536773, 0.586342 , 0.75797996],
[ 0.28338495, 0.59099176, 0.7559871 ],
[ 0.28151069, 0.59561083, 0.7539964 ],
[ 0.27974263, 0.60020097, 0.7520082 ],
[ 0.27807817, 0.60476394, 0.75002261],
[ 0.27651446, 0.60930147, 0.74803947],
[ 0.27504843, 0.61381525, 0.74605839],
[ 0.27367681, 0.61830693, 0.74407875],
[ 0.27239621, 0.62277814, 0.74209971],
[ 0.27120315, 0.62723044, 0.74012017],
[ 0.2700941 , 0.63166536, 0.73813883],
[ 0.26906553, 0.63608438, 0.73615419],
[ 0.26811396, 0.64048893, 0.7341645 ],
[ 0.267236 , 0.64488036, 0.73216784],
[ 0.26642845, 0.64925999, 0.73016208],
[ 0.26568825, 0.65362905, 0.7281449 ],
[ 0.26501263, 0.65798873, 0.72611382],
[ 0.2643991 , 0.66234012, 0.72406616],
[ 0.26384553, 0.66668426, 0.72199908],
[ 0.26335016, 0.67102211, 0.7199096 ],
[ 0.26291166, 0.67535454, 0.7177946 ],
[ 0.26252925, 0.67968235, 0.71565087],
[ 0.26220252, 0.68400627, 0.71347494],
[ 0.26193168, 0.68832694, 0.71126329],
[ 0.26171752, 0.6926449 , 0.70901233],
[ 0.26156145, 0.69696062, 0.70671835],
[ 0.26146552, 0.70127446, 0.70437758],
[ 0.26143241, 0.70558672, 0.70198618],
[ 0.26146552, 0.70989759, 0.69954026],
[ 0.26156889, 0.71420716, 0.69703589],
[ 0.26174728, 0.71851546, 0.6944691 ],
[ 0.26200613, 0.72282241, 0.69183591],
[ 0.26235155, 0.72712783, 0.68913235],
[ 0.26279032, 0.73143149, 0.68635442],
[ 0.26332987, 0.73573302, 0.68349817],
[ 0.26397823, 0.74003201, 0.68055967],
[ 0.26474399, 0.74432795, 0.67753502],
[ 0.26563628, 0.74862022, 0.67442037],
[ 0.26666467, 0.75290817, 0.67121195],
[ 0.26783915, 0.75719102, 0.66790602],
[ 0.26917 , 0.76146795, 0.66449895],
[ 0.27066777, 0.76573805, 0.66098717],
[ 0.27234313, 0.77000035, 0.6573672 ],
[ 0.27420683, 0.77425378, 0.65363566],
[ 0.27626956, 0.77849724, 0.64978928],
[ 0.2785419 , 0.78272954, 0.64582489],
[ 0.28103415, 0.78694946, 0.64173941],
[ 0.2837563 , 0.79115568, 0.63752989],
[ 0.28671789, 0.79534685, 0.63319351],
[ 0.28992795, 0.79952157, 0.62872753],
[ 0.29339489, 0.80367837, 0.62412938],
[ 0.29712646, 0.80781575, 0.61939656],
[ 0.30112967, 0.81193215, 0.61452672],
[ 0.30541076, 0.81602596, 0.60951765],
[ 0.30997513, 0.82009555, 0.60436723],
[ 0.31482736, 0.82413923, 0.59907348],
[ 0.31997118, 0.82815528, 0.59363455],
[ 0.32540947, 0.83214193, 0.58804873],
[ 0.33114429, 0.83609738, 0.58231439],
[ 0.33717691, 0.84001981, 0.57643009],
[ 0.3435078 , 0.84390735, 0.57039447],
[ 0.35013676, 0.84775809, 0.56420634],
[ 0.35706288, 0.8515701 , 0.55786461],
[ 0.36428465, 0.85534142, 0.55136836],
[ 0.37179997, 0.85907004, 0.5447168 ],
[ 0.37960764, 0.86275396, 0.53790608],
[ 0.38770397, 0.86639106, 0.53093767],
[ 0.39608533, 0.86997925, 0.52381182],
[ 0.404748 , 0.8735164 , 0.51652834],
[ 0.41368796, 0.87700037, 0.50908724],
[ 0.42290092, 0.88042896, 0.50148873],
[ 0.43238239, 0.88379999, 0.49373327],
[ 0.44212768, 0.88711122, 0.48582155],
[ 0.45213194, 0.89036041, 0.47775457],
[ 0.46239249, 0.89354509, 0.46952983],
[ 0.47290661, 0.8966627 , 0.4611454 ],
[ 0.48366544, 0.89971121, 0.45260956],
[ 0.4946637 , 0.90268831, 0.44392485],
[ 0.50589594, 0.90559166, 0.43509433],
[ 0.5173566 , 0.90841895, 0.42612172],
[ 0.52904678, 0.911167 , 0.4170014 ],
[ 0.54095942, 0.91383355, 0.40774077],
[ 0.55308405, 0.91641689, 0.39835269],
[ 0.56541433, 0.91891481, 0.38884459],
[ 0.57794756, 0.92132456, 0.37921977],
[ 0.59068532, 0.92364261, 0.36947702],
[ 0.60360889, 0.92586874, 0.3596447 ],
[ 0.61671039, 0.9280012 , 0.34973737],
[ 0.6299949 , 0.93003583, 0.33975421],
[ 0.64344639, 0.93197236, 0.32972537],
[ 0.65704942, 0.93381072, 0.31968252],
[ 0.67080705, 0.93554723, 0.3096364 ],
[ 0.68470183, 0.9371825 , 0.29962866],
[ 0.69871405, 0.93871806, 0.28970807],
[ 0.71284969, 0.94014982, 0.2798966 ],
[ 0.72707567, 0.94148299, 0.27027164],
[ 0.74138372, 0.94271735, 0.26088676],
[ 0.7557575 , 0.943855 , 0.25181386],
[ 0.77017105, 0.94490104, 0.24314461],
[ 0.78461467, 0.94585678, 0.23496111],
[ 0.79905507, 0.94673057, 0.2273802 ],
[ 0.81347933, 0.94752572, 0.22050384],
[ 0.82785668, 0.94825138, 0.21445687],
[ 0.8421664 , 0.94891453, 0.20935427],
[ 0.85638392, 0.94952403, 0.2053095 ],
[ 0.87048425, 0.95008971, 0.20242398],
[ 0.88444705, 0.95062061, 0.20077676],
[ 0.89824938, 0.9511274 , 0.200423 ],
[ 0.91187192, 0.95162019, 0.20138551],
[ 0.92530211, 0.95210721, 0.20365371],
[ 0.93851494, 0.95260192, 0.20718834],
[ 0.95151447, 0.9531072 , 0.21192152],
[ 0.9642739 , 0.95363819, 0.21776488],
[ 0.9767993 , 0.95419746, 0.22461997],
[ 0.98909212, 0.95478923, 0.2323852 ]]
test_cm = LinearSegmentedColormap.from_list(__file__, cm_data)
if __name__ == "__main__":
import matplotlib.pyplot as plt
import numpy as np
try:
from pycam02ucs.cm.viscm import viscm
viscm(test_cm)
except ImportError:
print("pycam02ucs not found, falling back on simple display")
plt.imshow(np.linspace(0, 100, 256)[None, :], aspect='auto',
cmap=test_cm)
plt.show()
from matplotlib.colors import LinearSegmentedColormap
from numpy import nan, inf
# Used to reconstruct the colormap in pycam02ucs.cm.viscm
parameters = {'xp': [28.782590300914933, 59.705365170024862, -27.718282299434122, -58.259294515838988, -31.917671479189778, -2.9037098736051519],
'yp': [16.928446771378731, -47.207678883071537, -85.002181500872581, 2.4214659685864035, 64.64877835951134, 25.70898778359512],
'min_JK': 18.0859375,
'max_JK': 95.0390625}
cm_data = [[ 0.30593816, 0.00266902, 0.0061051 ],
[ 0.31042433, 0.00290942, 0.01120144],
[ 0.31487482, 0.00316892, 0.01705532],
[ 0.31929522, 0.0034243 , 0.02377678],
[ 0.32368145, 0.00369108, 0.03138252],
[ 0.32803605, 0.00395683, 0.03996463],
[ 0.33235797, 0.00422464, 0.04889124],
[ 0.33664671, 0.00449568, 0.05769627],
[ 0.34090418, 0.00475769, 0.06646696],
[ 0.34512721, 0.00502718, 0.07518485],
[ 0.34931976, 0.00527747, 0.08394564],
[ 0.35347816, 0.00552999, 0.09270339],
[ 0.35760415, 0.00577067, 0.10150609],
[ 0.36169739, 0.00599854, 0.11036215],
[ 0.36575644, 0.00622388, 0.11924992],
[ 0.36978375, 0.00641944, 0.12823988],
[ 0.37377653, 0.00660885, 0.13727486],
[ 0.37773556, 0.00677996, 0.14638528],
[ 0.38166083, 0.00692606, 0.15558655],
[ 0.38555095, 0.00706076, 0.16484709],
[ 0.38940658, 0.00716518, 0.17420925],
[ 0.39322665, 0.00724735, 0.18365416],
[ 0.39701037, 0.00731401, 0.19316726],
[ 0.40075782, 0.00734338, 0.20279477],
[ 0.40446776, 0.0073515 , 0.21250246],
[ 0.40813946, 0.00734193, 0.22228406],
[ 0.41177227, 0.00729445, 0.23218125],
[ 0.41536508, 0.00722533, 0.24216243],
[ 0.41891698, 0.00713925, 0.25222092],
[ 0.42242671, 0.00702265, 0.2623854 ],
[ 0.42589305, 0.00688324, 0.27264414],
[ 0.42931493, 0.00673171, 0.28298143],
[ 0.43269091, 0.00656683, 0.29340481],
[ 0.43601883, 0.00637817, 0.30393878],
[ 0.4392978 , 0.00618789, 0.31455025],
[ 0.44252616, 0.00600087, 0.32523894],
[ 0.44570162, 0.00581503, 0.33601771],
[ 0.44882183, 0.00563345, 0.34689141],
[ 0.45188553, 0.00547601, 0.35783771],
[ 0.45489058, 0.00535163, 0.36885498],
[ 0.45783445, 0.00526797, 0.37994531],
[ 0.46071339, 0.00522487, 0.39112549],
[ 0.46352625, 0.00525017, 0.40236761],
[ 0.46627033, 0.00535829, 0.4136684 ],
[ 0.46894281, 0.00556525, 0.42502414],
[ 0.47154041, 0.00588686, 0.43643389],
[ 0.47405858, 0.00633428, 0.44790711],
[ 0.47649567, 0.00694065, 0.45941943],
[ 0.47884828, 0.00772963, 0.4709651 ],
[ 0.48111287, 0.008727 , 0.48253784],
[ 0.48328575, 0.00996081, 0.49413082],
[ 0.48536308, 0.01146143, 0.50573662],
[ 0.48733949, 0.01325656, 0.51735676],
[ 0.48921171, 0.01538581, 0.5289754 ],
[ 0.49097605, 0.01788916, 0.5405796 ],
[ 0.49262816, 0.02080706, 0.55215963],
[ 0.49416356, 0.02418258, 0.5637052 ],
[ 0.49557768, 0.02806141, 0.57520544],
[ 0.49686584, 0.03249183, 0.58664893],
[ 0.49802326, 0.03752463, 0.59802371],
[ 0.49904511, 0.04311441, 0.60931731],
[ 0.49992649, 0.0489259 , 0.62051677],
[ 0.50066244, 0.05493755, 0.63160869],
[ 0.50124802, 0.0611424 , 0.64257928],
[ 0.50167805, 0.06753394, 0.65341504],
[ 0.50194745, 0.07410605, 0.66410175],
[ 0.50205186, 0.08085257, 0.67462323],
[ 0.50198648, 0.08776732, 0.68496474],
[ 0.50174664, 0.09484406, 0.69511141],
[ 0.50132778, 0.10207645, 0.70504838],
[ 0.50072556, 0.10945796, 0.71476088],
[ 0.4999358 , 0.11698182, 0.72423428],
[ 0.4989546 , 0.124641 , 0.7334542 ],
[ 0.49777787, 0.13242856, 0.74240728],
[ 0.49640237, 0.14033686, 0.75107968],
[ 0.49482544, 0.14835776, 0.75945791],
[ 0.49304454, 0.15648302, 0.76752951],
[ 0.49105756, 0.16470409, 0.7752828 ],
[ 0.48886287, 0.17301214, 0.78270692],
[ 0.48645935, 0.18139813, 0.78979192],
[ 0.48384638, 0.18985275, 0.79652888],
[ 0.48102392, 0.19836655, 0.80290995],
[ 0.47799249, 0.20692994, 0.80892843],
[ 0.47475321, 0.21553323, 0.8145788 ],
[ 0.47130781, 0.2241667 , 0.81985683],
[ 0.46765864, 0.23282061, 0.82475954],
[ 0.46380866, 0.24148532, 0.82928527],
[ 0.45976146, 0.25015129, 0.83343365],
[ 0.45552028, 0.25880983, 0.83720573],
[ 0.45109112, 0.26745087, 0.84060357],
[ 0.44647941, 0.27606548, 0.84363073],
[ 0.44169113, 0.28464506, 0.846292 ],
[ 0.43673279, 0.29318136, 0.84859337],
[ 0.43161138, 0.30166653, 0.8505419 ],
[ 0.42633438, 0.31009317, 0.85214573],
[ 0.42090971, 0.3184543 , 0.85341395],
[ 0.41534564, 0.32674346, 0.85435652],
[ 0.40965092, 0.3349546 , 0.85498422],
[ 0.40383518, 0.34308189, 0.85530874],
[ 0.39790721, 0.35112065, 0.85534204],
[ 0.39187644, 0.35906651, 0.85509668],
[ 0.38575248, 0.36691561, 0.85458563],
[ 0.37954506, 0.37466461, 0.85382216],
[ 0.37326401, 0.3823107 , 0.85281975],
[ 0.36691922, 0.38985158, 0.85159201],
[ 0.3605206 , 0.3972854 , 0.85015258],
[ 0.35407804, 0.4046108 , 0.84851507],
[ 0.34760137, 0.41182688, 0.84669298],
[ 0.34110068, 0.418933 , 0.84469981],
[ 0.33458695, 0.42592852, 0.84254941],
[ 0.32806815, 0.43281442, 0.84025373],
[ 0.32155363, 0.43959135, 0.83782518],
[ 0.31505256, 0.44626026, 0.83527582],
[ 0.30857391, 0.45282241, 0.83261726],
[ 0.30212647, 0.45927932, 0.82986069],
[ 0.29571876, 0.46563275, 0.82701682],
[ 0.28935907, 0.47188468, 0.82409585],
[ 0.28305542, 0.47803728, 0.8211075 ],
[ 0.27681555, 0.48409289, 0.81806095],
[ 0.2706469 , 0.490054 , 0.81496488],
[ 0.26455658, 0.49592324, 0.81182741],
[ 0.25855138, 0.50170333, 0.80865617],
[ 0.25263771, 0.50739708, 0.80545824],
[ 0.24682158, 0.51300741, 0.80224018],
[ 0.24110863, 0.51853725, 0.79900805],
[ 0.23550404, 0.5239896 , 0.79576739],
[ 0.23001251, 0.5293675 , 0.79252325],
[ 0.22463828, 0.53467399, 0.78928019],
[ 0.21938504, 0.53991213, 0.78604229],
[ 0.21425593, 0.54508498, 0.78281317],
[ 0.20925351, 0.55019557, 0.77959598],
[ 0.20437973, 0.55524693, 0.77639345],
[ 0.1996359 , 0.56024206, 0.77320787],
[ 0.19502264, 0.56518393, 0.77004111],
[ 0.1905399 , 0.57007544, 0.76689464],
[ 0.18618694, 0.57491948, 0.76376952],
[ 0.18196229, 0.57971887, 0.76066644],
[ 0.17786378, 0.58447638, 0.75758571],
[ 0.17388852, 0.58919471, 0.75452729],
[ 0.17003294, 0.5938765 , 0.75149077],
[ 0.16629282, 0.59852432, 0.74847543],
[ 0.16266329, 0.60314065, 0.74548018],
[ 0.15913894, 0.60772792, 0.74250365],
[ 0.15571382, 0.61228846, 0.73954414],
[ 0.15238157, 0.61682451, 0.73659967],
[ 0.14913546, 0.62133823, 0.73366794],
[ 0.14596854, 0.62583169, 0.73074641],
[ 0.14287371, 0.63030686, 0.72783226],
[ 0.13984385, 0.63476561, 0.72492243],
[ 0.136872 , 0.63920971, 0.72201358],
[ 0.13395143, 0.64364082, 0.7191022 ],
[ 0.13107621, 0.64806046, 0.71618473],
[ 0.12824075, 0.65247006, 0.71325724],
[ 0.12543969, 0.65687103, 0.71031523],
[ 0.12266916, 0.66126459, 0.70735437],
[ 0.11992657, 0.66565184, 0.70437015],
[ 0.11721077, 0.67003376, 0.70135794],
[ 0.11452237, 0.6744112 , 0.69831295],
[ 0.11186399, 0.6787849 , 0.69523031],
[ 0.10924059, 0.68315548, 0.69210502],
[ 0.10665982, 0.68752341, 0.68893201],
[ 0.1041323 , 0.69188907, 0.68570614],
[ 0.10167206, 0.69625269, 0.6824222 ],
[ 0.09929685, 0.70061438, 0.67907498],
[ 0.09702849, 0.70497413, 0.67565922],
[ 0.09489316, 0.70933179, 0.67216965],
[ 0.09292157, 0.71368713, 0.66860104],
[ 0.09114857, 0.71803979, 0.66494786],
[ 0.08961373, 0.7223893 , 0.6612048 ],
[ 0.0883611 , 0.72673501, 0.65736696],
[ 0.08743755, 0.73107618, 0.65342925],
[ 0.0868919 , 0.73541198, 0.64938667],
[ 0.08677335, 0.73974145, 0.6452343 ],
[ 0.0871296 , 0.74406354, 0.64096731],
[ 0.08800467, 0.74837709, 0.63658099],
[ 0.08943689, 0.75268084, 0.63207074],
[ 0.09145705, 0.75697343, 0.62743205],
[ 0.09408706, 0.76125342, 0.62266056],
[ 0.09733931, 0.76551925, 0.61775204],
[ 0.10121671, 0.76976931, 0.61270239],
[ 0.10571346, 0.77400187, 0.60750764],
[ 0.11081631, 0.77821515, 0.60216396],
[ 0.11650607, 0.78240726, 0.59666767],
[ 0.12275934, 0.78657624, 0.59101523],
[ 0.12955007, 0.79072007, 0.58520325],
[ 0.13685091, 0.79483663, 0.57922847],
[ 0.14463436, 0.79892374, 0.5730878 ],
[ 0.15287364, 0.80297914, 0.56677828],
[ 0.16154321, 0.80700049, 0.56029714],
[ 0.17061924, 0.8109854 , 0.55364172],
[ 0.18007975, 0.81493137, 0.54680956],
[ 0.18990469, 0.81883585, 0.53979837],
[ 0.20007598, 0.82269619, 0.53260603],
[ 0.21057737, 0.82650969, 0.52523062],
[ 0.22139437, 0.83027354, 0.51767044],
[ 0.23251411, 0.83398486, 0.50992404],
[ 0.24392516, 0.83764066, 0.50199022],
[ 0.25561743, 0.8412379 , 0.4938681 ],
[ 0.26758204, 0.84477341, 0.48555716],
[ 0.2798111 , 0.84824393, 0.47705727],
[ 0.29229769, 0.8516461 , 0.46836882],
[ 0.30503911, 0.85497633, 0.45948804],
[ 0.31803459, 0.85823075, 0.45041063],
[ 0.3312734 , 0.86140581, 0.4411472 ],
[ 0.34475123, 0.86449765, 0.43170106],
[ 0.35846408, 0.86750233, 0.42207673],
[ 0.37240817, 0.87041578, 0.41228026],
[ 0.38658826, 0.87323309, 0.40230911],
[ 0.40100945, 0.87594898, 0.39216307],
[ 0.41565394, 0.87856011, 0.3818722 ],
[ 0.4305174 , 0.88106203, 0.37145274],
[ 0.44560988, 0.88344846, 0.36090778],
[ 0.46093466, 0.88571342, 0.35025332],
[ 0.4764647 , 0.88785471, 0.33954538],
[ 0.49220945, 0.88986546, 0.32880446],
[ 0.50817213, 0.89173917, 0.31806706],
[ 0.52431221, 0.89347602, 0.30742727],
[ 0.54066232, 0.89506473, 0.29691207],
[ 0.55716338, 0.89650912, 0.28666067],
[ 0.57382757, 0.89780123, 0.27675452],
[ 0.59059978, 0.89894578, 0.26736171],
[ 0.60747495, 0.89993864, 0.25862194],
[ 0.62437986, 0.90079066, 0.25075587],
[ 0.64129372, 0.90150303, 0.2439532 ],
[ 0.65813362, 0.9020926 , 0.23845876],
[ 0.67483995, 0.90257348, 0.23448842],
[ 0.69134066, 0.90296535, 0.232238 ],
[ 0.7075586 , 0.90329222, 0.231855 ],
[ 0.72342267, 0.90357961, 0.23341551],
[ 0.73886245, 0.90385588, 0.23691527],
[ 0.75384169, 0.90414168, 0.2422736 ],
[ 0.76828873, 0.90447092, 0.24933693],
[ 0.78221676, 0.90485188, 0.25792794],
[ 0.79558008, 0.90531303, 0.26782053],
[ 0.80842177, 0.90585258, 0.27883421],
[ 0.8207006 , 0.90649867, 0.29072839],
[ 0.83248598, 0.90723837, 0.30337614],
[ 0.84378474, 0.90808079, 0.31661371],
[ 0.85460273, 0.90903543, 0.33028474],
[ 0.86499688, 0.91008983, 0.3443259 ],
[ 0.87499154, 0.91124343, 0.35865065],
[ 0.88461129, 0.91249469, 0.3731879 ],
[ 0.89387855, 0.91384221, 0.38787579],
[ 0.90281044, 0.9152864 , 0.4026516 ],
[ 0.9114428 , 0.91681782, 0.41750661],
[ 0.91979668, 0.91843305, 0.43241222],
[ 0.9278919 , 0.92012856, 0.44734592],
[ 0.93574701, 0.9219008 , 0.46229025],
[ 0.94337929, 0.92374622, 0.47723183],
[ 0.95080035, 0.92566398, 0.49214548],
[ 0.95802315, 0.92765211, 0.50701436],
[ 0.96506661, 0.92970447, 0.52184916],
[ 0.97194366, 0.93181788, 0.53664677],
[ 0.97866617, 0.93398929, 0.55140545],
[ 0.98524501, 0.93621585, 0.56612453],
[ 0.99169013, 0.93849488, 0.58080418]]
test_cm = LinearSegmentedColormap.from_list(__file__, cm_data)
if __name__ == "__main__":
import matplotlib.pyplot as plt
import numpy as np
try:
from pycam02ucs.cm.viscm import viscm
viscm(test_cm)
except ImportError:
print("pycam02ucs not found, falling back on simple display")
plt.imshow(np.linspace(0, 100, 256)[None, :], aspect='auto',
cmap=test_cm)
plt.show()
------------------------------------------------------------------------------
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