In [1]:
import numpy as np
To get the new matplotlib colorbars into IDL, we need to write each out as a text file. Because they are few, we can do this by hand, pasting the RGB colormap data into this notebook and using numpy to write a CSV.
In [2]:
cm_data = [[ 0.0, 0.0, 0.0],
[ 1.23208396e-03, 9.55473090e-04, 1.39798823e-03],
[ 2.29615544e-03, 1.78942817e-03, 2.87482272e-03],
[ 3.65605723e-03, 2.83344018e-03, 4.92480921e-03],
[ 5.30551794e-03, 4.06778716e-03, 7.60691909e-03],
[ 7.23736344e-03, 5.48161371e-03, 1.09431791e-02],
[ 9.45254296e-03, 7.05778542e-03, 1.50171636e-02],
[ 1.19482347e-02, 8.78720053e-03, 1.98667312e-02],
[ 1.47228881e-02, 1.06611909e-02, 2.55349090e-02],
[ 1.77835018e-02, 1.26603657e-02, 3.21519132e-02],
[ 2.11220928e-02, 1.47877065e-02, 3.96871750e-02],
[ 2.47515394e-02, 1.70167645e-02, 4.78036366e-02],
[ 2.86638456e-02, 1.93519218e-02, 5.59687827e-02],
[ 3.28682397e-02, 2.17723779e-02, 6.42706842e-02],
[ 3.73641166e-02, 2.42719221e-02, 7.26898674e-02],
[ 4.21050647e-02, 2.68397654e-02, 8.12355395e-02],
[ 4.68284728e-02, 2.94586559e-02, 8.99433646e-02],
[ 5.15141518e-02, 3.21256410e-02, 9.87816900e-02],
[ 5.61710528e-02, 3.48169996e-02, 1.07806321e-01],
[ 6.07964611e-02, 3.75295002e-02, 1.16986953e-01],
[ 6.53942936e-02, 4.02451065e-02, 1.26350147e-01],
[ 6.99678963e-02, 4.28589320e-02, 1.35923729e-01],
[ 7.45082197e-02, 4.53694998e-02, 1.45639655e-01],
[ 7.90330506e-02, 4.77307435e-02, 1.55656679e-01],
[ 8.35202958e-02, 4.99952955e-02, 1.65809116e-01],
[ 8.79834474e-02, 5.21177479e-02, 1.76237541e-01],
[ 9.24150207e-02, 5.41059968e-02, 1.86915608e-01],
[ 9.68029626e-02, 5.59815865e-02, 1.97781923e-01],
[ 1.01151155e-01, 5.77100082e-02, 2.08936447e-01],
[ 1.05451837e-01, 5.92849001e-02, 2.20396438e-01],
[ 1.09686880e-01, 6.07326502e-02, 2.32095082e-01],
[ 1.13843713e-01, 6.20506875e-02, 2.44050536e-01],
[ 1.17904959e-01, 6.32397421e-02, 2.56278000e-01],
[ 1.21846598e-01, 6.43068710e-02, 2.68785988e-01],
[ 1.25635500e-01, 6.52701612e-02, 2.81570678e-01],
[ 1.29226271e-01, 6.61657005e-02, 2.94607743e-01],
[ 1.32557443e-01, 6.70572149e-02, 3.07841226e-01],
[ 1.35547409e-01, 6.80479794e-02, 3.21169632e-01],
[ 1.38091076e-01, 6.92926359e-02, 3.34430764e-01],
[ 1.40040521e-01, 7.09626931e-02, 3.47508660e-01],
[ 1.41240948e-01, 7.33731827e-02, 3.59972935e-01],
[ 1.41507741e-01, 7.68055544e-02, 3.71470975e-01],
[ 1.40750085e-01, 8.15085404e-02, 3.81459968e-01],
[ 1.38978078e-01, 8.75006802e-02, 3.89596616e-01],
[ 1.36328543e-01, 9.45637193e-02, 3.95783386e-01],
[ 1.33020255e-01, 1.02337765e-01, 4.00175258e-01],
[ 1.29250417e-01, 1.10478799e-01, 4.03074022e-01],
[ 1.25151398e-01, 1.18742158e-01, 4.04788627e-01],
[ 1.20897791e-01, 1.26928615e-01, 4.05612684e-01],
[ 1.16503773e-01, 1.34976096e-01, 4.05743218e-01],
[ 1.12091791e-01, 1.42800379e-01, 4.05380296e-01],
[ 1.07667720e-01, 1.50397779e-01, 4.04637066e-01],
[ 1.03261075e-01, 1.57763499e-01, 4.03610287e-01],
[ 9.89139075e-02, 1.64894349e-01, 4.02386180e-01],
[ 9.46605957e-02, 1.71795271e-01, 4.01032857e-01],
[ 9.04966075e-02, 1.78488051e-01, 3.99581412e-01],
[ 8.64400964e-02, 1.84985184e-01, 3.98068674e-01],
[ 8.25068783e-02, 1.91299899e-01, 3.96523264e-01],
[ 7.87110863e-02, 1.97445454e-01, 3.94967383e-01],
[ 7.50656260e-02, 2.03434722e-01, 3.93418199e-01],
[ 7.15824638e-02, 2.09279955e-01, 3.91888928e-01],
[ 6.82727786e-02, 2.14992675e-01, 3.90389666e-01],
[ 6.51469969e-02, 2.20583627e-01, 3.88928035e-01],
[ 6.22147318e-02, 2.26062789e-01, 3.87509681e-01],
[ 5.94846413e-02, 2.31439400e-01, 3.86138652e-01],
[ 5.69642263e-02, 2.36722005e-01, 3.84817703e-01],
[ 5.46595872e-02, 2.41918503e-01, 3.83548521e-01],
[ 5.25751624e-02, 2.47036203e-01, 3.82331902e-01],
[ 5.07134751e-02, 2.52081870e-01, 3.81167890e-01],
[ 4.90749156e-02, 2.57061774e-01, 3.80055881e-01],
[ 4.76575847e-02, 2.61981734e-01, 3.78994708e-01],
[ 4.64572218e-02, 2.66847155e-01, 3.77982702e-01],
[ 4.54672343e-02, 2.71663063e-01, 3.77017741e-01],
[ 4.46840991e-02, 2.76433278e-01, 3.76100669e-01],
[ 4.40912972e-02, 2.81163132e-01, 3.75224852e-01],
[ 4.36760356e-02, 2.85856732e-01, 3.74386744e-01],
[ 4.34247319e-02, 2.90517832e-01, 3.73582732e-01],
[ 4.33230538e-02, 2.95149919e-01, 3.72808888e-01],
[ 4.33563883e-02, 2.99756226e-01, 3.72060986e-01],
[ 4.35103092e-02, 3.04339740e-01, 3.71334509e-01],
[ 4.37710212e-02, 3.08903211e-01, 3.70624672e-01],
[ 4.41282904e-02, 3.13448805e-01, 3.69928058e-01],
[ 4.45674054e-02, 3.17979294e-01, 3.69237225e-01],
[ 4.50786065e-02, 3.22496756e-01, 3.68546588e-01],
[ 4.56542782e-02, 3.27003032e-01, 3.67850463e-01],
[ 4.62889953e-02, 3.31499739e-01, 3.67142985e-01],
[ 4.69796908e-02, 3.35988283e-01, 3.66418129e-01],
[ 4.77257788e-02, 3.40469852e-01, 3.65669737e-01],
[ 4.85291489e-02, 3.44945431e-01, 3.64891487e-01],
[ 4.93936792e-02, 3.49415875e-01, 3.64076553e-01],
[ 5.03265816e-02, 3.53881729e-01, 3.63218552e-01],
[ 5.13376114e-02, 3.58343330e-01, 3.62311095e-01],
[ 5.24389267e-02, 3.62800809e-01, 3.61347801e-01],
[ 5.36449018e-02, 3.67254102e-01, 3.60322329e-01],
[ 5.49718276e-02, 3.71702955e-01, 3.59228375e-01],
[ 5.64358645e-02, 3.76147176e-01, 3.58058223e-01],
[ 5.80577474e-02, 3.80585934e-01, 3.56806935e-01],
[ 5.98575991e-02, 3.85018417e-01, 3.55468636e-01],
[ 6.18558200e-02, 3.89443647e-01, 3.54037625e-01],
[ 6.40725510e-02, 3.93860487e-01, 3.52508403e-01],
[ 6.65271332e-02, 3.98267655e-01, 3.50875686e-01],
[ 6.92375954e-02, 4.02663728e-01, 3.49134426e-01],
[ 7.22190954e-02, 4.07047379e-01, 3.47278053e-01],
[ 7.54864540e-02, 4.11416856e-01, 3.45302457e-01],
[ 7.90521742e-02, 4.15770242e-01, 3.43204352e-01],
[ 8.29254846e-02, 4.20105651e-01, 3.40979770e-01],
[ 8.71129773e-02, 4.24421110e-01, 3.38625025e-01],
[ 9.16186670e-02, 4.28714566e-01, 3.36136719e-01],
[ 9.64441393e-02, 4.32983895e-01, 3.33511739e-01],
[ 1.01588767e-01, 4.37226916e-01, 3.30747257e-01],
[ 1.07049974e-01, 4.41441396e-01, 3.27840728e-01],
[ 1.12823855e-01, 4.45625238e-01, 3.24786969e-01],
[ 1.18904971e-01, 4.49775948e-01, 3.21586143e-01],
[ 1.25286565e-01, 4.53891139e-01, 3.18237146e-01],
[ 1.31961058e-01, 4.57968449e-01, 3.14738541e-01],
[ 1.38920254e-01, 4.62005502e-01, 3.11089142e-01],
[ 1.46155540e-01, 4.65999917e-01, 3.07288006e-01],
[ 1.53658052e-01, 4.69949317e-01, 3.03334418e-01],
[ 1.61418810e-01, 4.73851329e-01, 2.99227888e-01],
[ 1.69428819e-01, 4.77703598e-01, 2.94968134e-01],
[ 1.77679155e-01, 4.81503786e-01, 2.90555072e-01],
[ 1.86161019e-01, 4.85249581e-01, 2.85988805e-01],
[ 1.94865778e-01, 4.88938703e-01, 2.81269612e-01],
[ 2.03784988e-01, 4.92568909e-01, 2.76397933e-01],
[ 2.12910409e-01, 4.96137998e-01, 2.71374357e-01],
[ 2.22234002e-01, 4.99643819e-01, 2.66199611e-01],
[ 2.31747934e-01, 5.03084276e-01, 2.60874541e-01],
[ 2.41444557e-01, 5.06457333e-01, 2.55400105e-01],
[ 2.51316401e-01, 5.09761021e-01, 2.49777354e-01],
[ 2.61356155e-01, 5.12993445e-01, 2.44007420e-01],
[ 2.71556645e-01, 5.16152793e-01, 2.38091502e-01],
[ 2.81910816e-01, 5.19237338e-01, 2.32030849e-01],
[ 2.92411709e-01, 5.22245452e-01, 2.25826750e-01],
[ 3.03052439e-01, 5.25175609e-01, 2.19480519e-01],
[ 3.13826172e-01, 5.28026396e-01, 2.12993484e-01],
[ 3.24726102e-01, 5.30796524e-01, 2.06366974e-01],
[ 3.35745430e-01, 5.33484834e-01, 1.99602318e-01],
[ 3.46877341e-01, 5.36090309e-01, 1.92700836e-01],
[ 3.58114982e-01, 5.38612089e-01, 1.85663845e-01],
[ 3.69451439e-01, 5.41049476e-01, 1.78492672e-01],
[ 3.80879719e-01, 5.43401953e-01, 1.71188671e-01],
[ 3.92392725e-01, 5.45669194e-01, 1.63753271e-01],
[ 4.03983240e-01, 5.47851079e-01, 1.56188035e-01],
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[ 5.93441855e-01, 5.72076359e-01, 2.82747543e-02],
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[ 6.16587919e-01, 5.74021935e-01, 2.19268218e-02],
[ 6.28014050e-01, 5.74952422e-01, 2.13281856e-02],
[ 6.39327939e-01, 5.75863873e-01, 2.25506518e-02],
[ 6.50519264e-01, 5.76763426e-01, 2.56803655e-02],
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[ 6.83239371e-01, 5.79474363e-01, 4.70405860e-02],
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[ 7.62575552e-01, 5.88236442e-01, 1.37336358e-01],
[ 7.71552684e-01, 5.89627716e-01, 1.49737263e-01],
[ 7.80304203e-01, 5.91107689e-01, 1.62292912e-01],
[ 7.88827159e-01, 5.92682093e-01, 1.74992652e-01],
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[ 8.55254945e-01, 6.11672485e-01, 2.95010966e-01],
[ 8.61513837e-01, 6.14359877e-01, 3.08894128e-01],
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[ 9.56426557e-01, 8.53668016e-01, 9.14119954e-01],
[ 9.55450902e-01, 8.61000457e-01, 9.21988100e-01],
[ 9.54482975e-01, 8.68389760e-01, 9.29276063e-01],
[ 9.53544413e-01, 8.75831712e-01, 9.35942516e-01],
[ 9.52715057e-01, 8.83298026e-01, 9.41937385e-01],
[ 9.52060170e-01, 8.90765365e-01, 9.47234674e-01],
[ 9.51663891e-01, 8.98200733e-01, 9.51831906e-01],
[ 9.51600045e-01, 9.05573176e-01, 9.55758457e-01],
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[ 9.89906220e-01, 9.97424842e-01, 9.85544042e-01],
[ 1.0, 1.0, 1.0]]
In [4]:
np.savetxt("MPL_rainbow_BW.csv",cm_data,delimiter=",")