""" Nothing here but dictionaries for generating LinearSegmentedColormaps, and a dictionary of these dictionaries. Documentation for each is in pyplot.colormaps(). Please update this with the purpose and type of your colormap if you add data for one here. """ from functools import partial import numpy as np _binary_data = { 'red': ((0., 1., 1.), (1., 0., 0.)), 'green': ((0., 1., 1.), (1., 0., 0.)), 'blue': ((0., 1., 1.), (1., 0., 0.)) } _autumn_data = {'red': ((0., 1.0, 1.0), (1.0, 1.0, 1.0)), 'green': ((0., 0., 0.), (1.0, 1.0, 1.0)), 'blue': ((0., 0., 0.), (1.0, 0., 0.))} _bone_data = {'red': ((0., 0., 0.), (0.746032, 0.652778, 0.652778), (1.0, 1.0, 1.0)), 'green': ((0., 0., 0.), (0.365079, 0.319444, 0.319444), (0.746032, 0.777778, 0.777778), (1.0, 1.0, 1.0)), 'blue': ((0., 0., 0.), (0.365079, 0.444444, 0.444444), (1.0, 1.0, 1.0))} _cool_data = {'red': ((0., 0., 0.), (1.0, 1.0, 1.0)), 'green': ((0., 1., 1.), (1.0, 0., 0.)), 'blue': ((0., 1., 1.), (1.0, 1., 1.))} _copper_data = {'red': ((0., 0., 0.), (0.809524, 1.000000, 1.000000), (1.0, 1.0, 1.0)), 'green': ((0., 0., 0.), (1.0, 0.7812, 0.7812)), 'blue': ((0., 0., 0.), (1.0, 0.4975, 0.4975))} def _flag_red(x): return 0.75 * np.sin((x * 31.5 + 0.25) * np.pi) + 0.5 def _flag_green(x): return np.sin(x * 31.5 * np.pi) def _flag_blue(x): return 0.75 * np.sin((x * 31.5 - 0.25) * np.pi) + 0.5 _flag_data = {'red': _flag_red, 'green': _flag_green, 'blue': _flag_blue} def _prism_red(x): return 0.75 * np.sin((x * 20.9 + 0.25) * np.pi) + 0.67 def _prism_green(x): return 0.75 * np.sin((x * 20.9 - 0.25) * np.pi) + 0.33 def _prism_blue(x): return -1.1 * np.sin((x * 20.9) * np.pi) _prism_data = {'red': _prism_red, 'green': _prism_green, 'blue': _prism_blue} def _ch_helper(gamma, s, r, h, p0, p1, x): """Helper function for generating picklable cubehelix colormaps.""" # Apply gamma factor to emphasise low or high intensity values xg = x ** gamma # Calculate amplitude and angle of deviation from the black to white # diagonal in the plane of constant perceived intensity. a = h * xg * (1 - xg) / 2 phi = 2 * np.pi * (s / 3 + r * x) return xg + a * (p0 * np.cos(phi) + p1 * np.sin(phi)) def cubehelix(gamma=1.0, s=0.5, r=-1.5, h=1.0): """ Return custom data dictionary of (r, g, b) conversion functions, which can be used with :func:`register_cmap`, for the cubehelix color scheme. Unlike most other color schemes cubehelix was designed by D.A. Green to be monotonically increasing in terms of perceived brightness. Also, when printed on a black and white postscript printer, the scheme results in a greyscale with monotonically increasing brightness. This color scheme is named cubehelix because the (r, g, b) values produced can be visualised as a squashed helix around the diagonal in the (r, g, b) color cube. For a unit color cube (i.e. 3D coordinates for (r, g, b) each in the range 0 to 1) the color scheme starts at (r, g, b) = (0, 0, 0), i.e. black, and finishes at (r, g, b) = (1, 1, 1), i.e. white. For some fraction *x*, between 0 and 1, the color is the corresponding grey value at that fraction along the black to white diagonal (x, x, x) plus a color element. This color element is calculated in a plane of constant perceived intensity and controlled by the following parameters. Parameters ---------- gamma : float, default: 1 Gamma factor emphasizing either low intensity values (gamma < 1), or high intensity values (gamma > 1). s : float, default: 0.5 (purple) The starting color. r : float, default: -1.5 The number of r, g, b rotations in color that are made from the start to the end of the color scheme. The default of -1.5 corresponds to -> B -> G -> R -> B. h : float, default: 1 The hue, i.e. how saturated the colors are. If this parameter is zero then the color scheme is purely a greyscale. """ return {'red': partial(_ch_helper, gamma, s, r, h, -0.14861, 1.78277), 'green': partial(_ch_helper, gamma, s, r, h, -0.29227, -0.90649), 'blue': partial(_ch_helper, gamma, s, r, h, 1.97294, 0.0)} _cubehelix_data = cubehelix() _bwr_data = ((0.0, 0.0, 1.0), (1.0, 1.0, 1.0), (1.0, 0.0, 0.0)) _brg_data = ((0.0, 0.0, 1.0), (1.0, 0.0, 0.0), (0.0, 1.0, 0.0)) # Gnuplot palette functions def _g0(x): return 0 def _g1(x): return 0.5 def _g2(x): return 1 def _g3(x): return x def _g4(x): return x ** 2 def _g5(x): return x ** 3 def _g6(x): return x ** 4 def _g7(x): return np.sqrt(x) def _g8(x): return np.sqrt(np.sqrt(x)) def _g9(x): return np.sin(x * np.pi / 2) def _g10(x): return np.cos(x * np.pi / 2) def _g11(x): return np.abs(x - 0.5) def _g12(x): return (2 * x - 1) ** 2 def _g13(x): return np.sin(x * np.pi) def _g14(x): return np.abs(np.cos(x * np.pi)) def _g15(x): return np.sin(x * 2 * np.pi) def _g16(x): return np.cos(x * 2 * np.pi) def _g17(x): return np.abs(np.sin(x * 2 * np.pi)) def _g18(x): return np.abs(np.cos(x * 2 * np.pi)) def _g19(x): return np.abs(np.sin(x * 4 * np.pi)) def _g20(x): return np.abs(np.cos(x * 4 * np.pi)) def _g21(x): return 3 * x def _g22(x): return 3 * x - 1 def _g23(x): return 3 * x - 2 def _g24(x): return np.abs(3 * x - 1) def _g25(x): return np.abs(3 * x - 2) def _g26(x): return (3 * x - 1) / 2 def _g27(x): return (3 * x - 2) / 2 def _g28(x): return np.abs((3 * x - 1) / 2) def _g29(x): return np.abs((3 * x - 2) / 2) def _g30(x): return x / 0.32 - 0.78125 def _g31(x): return 2 * x - 0.84 def _g32(x): ret = np.zeros(len(x)) m = (x < 0.25) ret[m] = 4 * x[m] m = (x >= 0.25) & (x < 0.92) ret[m] = -2 * x[m] + 1.84 m = (x >= 0.92) ret[m] = x[m] / 0.08 - 11.5 return ret def _g33(x): return np.abs(2 * x - 0.5) def _g34(x): return 2 * x def _g35(x): return 2 * x - 0.5 def _g36(x): return 2 * x - 1 gfunc = {i: globals()["_g{}".format(i)] for i in range(37)} _gnuplot_data = { 'red': gfunc[7], 'green': gfunc[5], 'blue': gfunc[15], } _gnuplot2_data = { 'red': gfunc[30], 'green': gfunc[31], 'blue': gfunc[32], } _ocean_data = { 'red': gfunc[23], 'green': gfunc[28], 'blue': gfunc[3], } _afmhot_data = { 'red': gfunc[34], 'green': gfunc[35], 'blue': gfunc[36], } _rainbow_data = { 'red': gfunc[33], 'green': gfunc[13], 'blue': gfunc[10], } _seismic_data = ( (0.0, 0.0, 0.3), (0.0, 0.0, 1.0), (1.0, 1.0, 1.0), (1.0, 0.0, 0.0), (0.5, 0.0, 0.0)) _terrain_data = ( (0.00, (0.2, 0.2, 0.6)), (0.15, (0.0, 0.6, 1.0)), (0.25, (0.0, 0.8, 0.4)), (0.50, (1.0, 1.0, 0.6)), (0.75, (0.5, 0.36, 0.33)), (1.00, (1.0, 1.0, 1.0))) _gray_data = {'red': ((0., 0, 0), (1., 1, 1)), 'green': ((0., 0, 0), (1., 1, 1)), 'blue': ((0., 0, 0), (1., 1, 1))} _hot_data = {'red': ((0., 0.0416, 0.0416), (0.365079, 1.000000, 1.000000), (1.0, 1.0, 1.0)), 'green': ((0., 0., 0.), (0.365079, 0.000000, 0.000000), (0.746032, 1.000000, 1.000000), (1.0, 1.0, 1.0)), 'blue': ((0., 0., 0.), (0.746032, 0.000000, 0.000000), (1.0, 1.0, 1.0))} _hsv_data = {'red': ((0., 1., 1.), (0.158730, 1.000000, 1.000000), (0.174603, 0.968750, 0.968750), (0.333333, 0.031250, 0.031250), (0.349206, 0.000000, 0.000000), (0.666667, 0.000000, 0.000000), (0.682540, 0.031250, 0.031250), (0.841270, 0.968750, 0.968750), (0.857143, 1.000000, 1.000000), (1.0, 1.0, 1.0)), 'green': ((0., 0., 0.), (0.158730, 0.937500, 0.937500), (0.174603, 1.000000, 1.000000), (0.507937, 1.000000, 1.000000), (0.666667, 0.062500, 0.062500), (0.682540, 0.000000, 0.000000), (1.0, 0., 0.)), 'blue': ((0., 0., 0.), (0.333333, 0.000000, 0.000000), (0.349206, 0.062500, 0.062500), (0.507937, 1.000000, 1.000000), (0.841270, 1.000000, 1.000000), (0.857143, 0.937500, 0.937500), (1.0, 0.09375, 0.09375))} _jet_data = {'red': ((0.00, 0, 0), (0.35, 0, 0), (0.66, 1, 1), (0.89, 1, 1), (1.00, 0.5, 0.5)), 'green': ((0.000, 0, 0), (0.125, 0, 0), (0.375, 1, 1), (0.640, 1, 1), (0.910, 0, 0), (1.000, 0, 0)), 'blue': ((0.00, 0.5, 0.5), (0.11, 1, 1), (0.34, 1, 1), (0.65, 0, 0), (1.00, 0, 0))} _pink_data = {'red': ((0., 0.1178, 0.1178), (0.015873, 0.195857, 0.195857), (0.031746, 0.250661, 0.250661), (0.047619, 0.295468, 0.295468), (0.063492, 0.334324, 0.334324), (0.079365, 0.369112, 0.369112), (0.095238, 0.400892, 0.400892), (0.111111, 0.430331, 0.430331), (0.126984, 0.457882, 0.457882), (0.142857, 0.483867, 0.483867), (0.158730, 0.508525, 0.508525), (0.174603, 0.532042, 0.532042), (0.190476, 0.554563, 0.554563), (0.206349, 0.576204, 0.576204), (0.222222, 0.597061, 0.597061), (0.238095, 0.617213, 0.617213), (0.253968, 0.636729, 0.636729), (0.269841, 0.655663, 0.655663), (0.285714, 0.674066, 0.674066), (0.301587, 0.691980, 0.691980), (0.317460, 0.709441, 0.709441), (0.333333, 0.726483, 0.726483), (0.349206, 0.743134, 0.743134), (0.365079, 0.759421, 0.759421), (0.380952, 0.766356, 0.766356), (0.396825, 0.773229, 0.773229), (0.412698, 0.780042, 0.780042), (0.428571, 0.786796, 0.786796), (0.444444, 0.793492, 0.793492), (0.460317, 0.800132, 0.800132), (0.476190, 0.806718, 0.806718), (0.492063, 0.813250, 0.813250), (0.507937, 0.819730, 0.819730), (0.523810, 0.826160, 0.826160), (0.539683, 0.832539, 0.832539), (0.555556, 0.838870, 0.838870), (0.571429, 0.845154, 0.845154), (0.587302, 0.851392, 0.851392), (0.603175, 0.857584, 0.857584), (0.619048, 0.863731, 0.863731), (0.634921, 0.869835, 0.869835), (0.650794, 0.875897, 0.875897), (0.666667, 0.881917, 0.881917), (0.682540, 0.887896, 0.887896), (0.698413, 0.893835, 0.893835), (0.714286, 0.899735, 0.899735), (0.730159, 0.905597, 0.905597), (0.746032, 0.911421, 0.911421), (0.761905, 0.917208, 0.917208), (0.777778, 0.922958, 0.922958), (0.793651, 0.928673, 0.928673), (0.809524, 0.934353, 0.934353), (0.825397, 0.939999, 0.939999), (0.841270, 0.945611, 0.945611), (0.857143, 0.951190, 0.951190), (0.873016, 0.956736, 0.956736), (0.888889, 0.962250, 0.962250), (0.904762, 0.967733, 0.967733), (0.920635, 0.973185, 0.973185), (0.936508, 0.978607, 0.978607), (0.952381, 0.983999, 0.983999), (0.968254, 0.989361, 0.989361), (0.984127, 0.994695, 0.994695), (1.0, 1.0, 1.0)), 'green': ((0., 0., 0.), (0.015873, 0.102869, 0.102869), (0.031746, 0.145479, 0.145479), (0.047619, 0.178174, 0.178174), (0.063492, 0.205738, 0.205738), (0.079365, 0.230022, 0.230022), (0.095238, 0.251976, 0.251976), (0.111111, 0.272166, 0.272166), (0.126984, 0.290957, 0.290957), (0.142857, 0.308607, 0.308607), (0.158730, 0.325300, 0.325300), (0.174603, 0.341178, 0.341178), (0.190476, 0.356348, 0.356348), (0.206349, 0.370899, 0.370899), (0.222222, 0.384900, 0.384900), (0.238095, 0.398410, 0.398410), (0.253968, 0.411476, 0.411476), (0.269841, 0.424139, 0.424139), (0.285714, 0.436436, 0.436436), (0.301587, 0.448395, 0.448395), (0.317460, 0.460044, 0.460044), (0.333333, 0.471405, 0.471405), (0.349206, 0.482498, 0.482498), (0.365079, 0.493342, 0.493342), (0.380952, 0.517549, 0.517549), (0.396825, 0.540674, 0.540674), (0.412698, 0.562849, 0.562849), (0.428571, 0.584183, 0.584183), (0.444444, 0.604765, 0.604765), (0.460317, 0.624669, 0.624669), (0.476190, 0.643958, 0.643958), (0.492063, 0.662687, 0.662687), (0.507937, 0.680900, 0.680900), (0.523810, 0.698638, 0.698638), (0.539683, 0.715937, 0.715937), (0.555556, 0.732828, 0.732828), (0.571429, 0.749338, 0.749338), (0.587302, 0.765493, 0.765493), (0.603175, 0.781313, 0.781313), (0.619048, 0.796819, 0.796819), (0.634921, 0.812029, 0.812029), (0.650794, 0.826960, 0.826960), (0.666667, 0.841625, 0.841625), (0.682540, 0.856040, 0.856040), (0.698413, 0.870216, 0.870216), (0.714286, 0.884164, 0.884164), (0.730159, 0.897896, 0.897896), (0.746032, 0.911421, 0.911421), (0.761905, 0.917208, 0.917208), (0.777778, 0.922958, 0.922958), (0.793651, 0.928673, 0.928673), (0.809524, 0.934353, 0.934353), (0.825397, 0.939999, 0.939999), (0.841270, 0.945611, 0.945611), (0.857143, 0.951190, 0.951190), (0.873016, 0.956736, 0.956736), (0.888889, 0.962250, 0.962250), (0.904762, 0.967733, 0.967733), (0.920635, 0.973185, 0.973185), (0.936508, 0.978607, 0.978607), (0.952381, 0.983999, 0.983999), (0.968254, 0.989361, 0.989361), (0.984127, 0.994695, 0.994695), (1.0, 1.0, 1.0)), 'blue': ((0., 0., 0.), (0.015873, 0.102869, 0.102869), (0.031746, 0.145479, 0.145479), (0.047619, 0.178174, 0.178174), (0.063492, 0.205738, 0.205738), (0.079365, 0.230022, 0.230022), (0.095238, 0.251976, 0.251976), (0.111111, 0.272166, 0.272166), (0.126984, 0.290957, 0.290957), (0.142857, 0.308607, 0.308607), (0.158730, 0.325300, 0.325300), (0.174603, 0.341178, 0.341178), (0.190476, 0.356348, 0.356348), (0.206349, 0.370899, 0.370899), (0.222222, 0.384900, 0.384900), (0.238095, 0.398410, 0.398410), (0.253968, 0.411476, 0.411476), (0.269841, 0.424139, 0.424139), (0.285714, 0.436436, 0.436436), (0.301587, 0.448395, 0.448395), (0.317460, 0.460044, 0.460044), (0.333333, 0.471405, 0.471405), (0.349206, 0.482498, 0.482498), (0.365079, 0.493342, 0.493342), (0.380952, 0.503953, 0.503953), (0.396825, 0.514344, 0.514344), (0.412698, 0.524531, 0.524531), (0.428571, 0.534522, 0.534522), (0.444444, 0.544331, 0.544331), (0.460317, 0.553966, 0.553966), (0.476190, 0.563436, 0.563436), (0.492063, 0.572750, 0.572750), (0.507937, 0.581914, 0.581914), (0.523810, 0.590937, 0.590937), (0.539683, 0.599824, 0.599824), (0.555556, 0.608581, 0.608581), (0.571429, 0.617213, 0.617213), (0.587302, 0.625727, 0.625727), (0.603175, 0.634126, 0.634126), (0.619048, 0.642416, 0.642416), (0.634921, 0.650600, 0.650600), (0.650794, 0.658682, 0.658682), (0.666667, 0.666667, 0.666667), (0.682540, 0.674556, 0.674556), (0.698413, 0.682355, 0.682355), (0.714286, 0.690066, 0.690066), (0.730159, 0.697691, 0.697691), (0.746032, 0.705234, 0.705234), (0.761905, 0.727166, 0.727166), (0.777778, 0.748455, 0.748455), (0.793651, 0.769156, 0.769156), (0.809524, 0.789314, 0.789314), (0.825397, 0.808969, 0.808969), (0.841270, 0.828159, 0.828159), (0.857143, 0.846913, 0.846913), (0.873016, 0.865261, 0.865261), (0.888889, 0.883229, 0.883229), (0.904762, 0.900837, 0.900837), (0.920635, 0.918109, 0.918109), (0.936508, 0.935061, 0.935061), (0.952381, 0.951711, 0.951711), (0.968254, 0.968075, 0.968075), (0.984127, 0.984167, 0.984167), (1.0, 1.0, 1.0))} _spring_data = {'red': ((0., 1., 1.), (1.0, 1.0, 1.0)), 'green': ((0., 0., 0.), (1.0, 1.0, 1.0)), 'blue': ((0., 1., 1.), (1.0, 0.0, 0.0))} _summer_data = {'red': ((0., 0., 0.), (1.0, 1.0, 1.0)), 'green': ((0., 0.5, 0.5), (1.0, 1.0, 1.0)), 'blue': ((0., 0.4, 0.4), (1.0, 0.4, 0.4))} _winter_data = {'red': ((0., 0., 0.), (1.0, 0.0, 0.0)), 'green': ((0., 0., 0.), (1.0, 1.0, 1.0)), 'blue': ((0., 1., 1.), (1.0, 0.5, 0.5))} _nipy_spectral_data = { 'red': [(0.0, 0.0, 0.0), (0.05, 0.4667, 0.4667), (0.10, 0.5333, 0.5333), (0.15, 0.0, 0.0), (0.20, 0.0, 0.0), (0.25, 0.0, 0.0), (0.30, 0.0, 0.0), (0.35, 0.0, 0.0), (0.40, 0.0, 0.0), (0.45, 0.0, 0.0), (0.50, 0.0, 0.0), (0.55, 0.0, 0.0), (0.60, 0.0, 0.0), (0.65, 0.7333, 0.7333), (0.70, 0.9333, 0.9333), (0.75, 1.0, 1.0), (0.80, 1.0, 1.0), (0.85, 1.0, 1.0), (0.90, 0.8667, 0.8667), (0.95, 0.80, 0.80), (1.0, 0.80, 0.80)], 'green': [(0.0, 0.0, 0.0), (0.05, 0.0, 0.0), (0.10, 0.0, 0.0), (0.15, 0.0, 0.0), (0.20, 0.0, 0.0), (0.25, 0.4667, 0.4667), (0.30, 0.6000, 0.6000), (0.35, 0.6667, 0.6667), (0.40, 0.6667, 0.6667), (0.45, 0.6000, 0.6000), (0.50, 0.7333, 0.7333), (0.55, 0.8667, 0.8667), (0.60, 1.0, 1.0), (0.65, 1.0, 1.0), (0.70, 0.9333, 0.9333), (0.75, 0.8000, 0.8000), (0.80, 0.6000, 0.6000), (0.85, 0.0, 0.0), (0.90, 0.0, 0.0), (0.95, 0.0, 0.0), (1.0, 0.80, 0.80)], 'blue': [(0.0, 0.0, 0.0), (0.05, 0.5333, 0.5333), (0.10, 0.6000, 0.6000), (0.15, 0.6667, 0.6667), (0.20, 0.8667, 0.8667), (0.25, 0.8667, 0.8667), (0.30, 0.8667, 0.8667), (0.35, 0.6667, 0.6667), (0.40, 0.5333, 0.5333), (0.45, 0.0, 0.0), (0.5, 0.0, 0.0), (0.55, 0.0, 0.0), (0.60, 0.0, 0.0), (0.65, 0.0, 0.0), (0.70, 0.0, 0.0), (0.75, 0.0, 0.0), (0.80, 0.0, 0.0), (0.85, 0.0, 0.0), (0.90, 0.0, 0.0), (0.95, 0.0, 0.0), (1.0, 0.80, 0.80)], } # 34 colormaps based on color specifications and designs # developed by Cynthia Brewer (http://colorbrewer.org). # The ColorBrewer palettes have been included under the terms # of an Apache-stype license (for details, see the file # LICENSE_COLORBREWER in the license directory of the matplotlib # source distribution). # RGB values taken from Brewer's Excel sheet, divided by 255 _Blues_data = ( (0.96862745098039216, 0.98431372549019602, 1.0 ), (0.87058823529411766, 0.92156862745098034, 0.96862745098039216), (0.77647058823529413, 0.85882352941176465, 0.93725490196078431), (0.61960784313725492, 0.792156862745098 , 0.88235294117647056), (0.41960784313725491, 0.68235294117647061, 0.83921568627450982), (0.25882352941176473, 0.5725490196078431 , 0.77647058823529413), (0.12941176470588237, 0.44313725490196076, 0.70980392156862748), (0.03137254901960784, 0.31764705882352939, 0.61176470588235299), (0.03137254901960784, 0.18823529411764706, 0.41960784313725491) ) _BrBG_data = ( (0.32941176470588235, 0.18823529411764706, 0.0196078431372549 ), (0.5490196078431373 , 0.31764705882352939, 0.0392156862745098 ), (0.74901960784313726, 0.50588235294117645, 0.17647058823529413), (0.87450980392156863, 0.76078431372549016, 0.49019607843137253), (0.96470588235294119, 0.90980392156862744, 0.76470588235294112), (0.96078431372549022, 0.96078431372549022, 0.96078431372549022), (0.7803921568627451 , 0.91764705882352937, 0.89803921568627454), (0.50196078431372548, 0.80392156862745101, 0.75686274509803919), (0.20784313725490197, 0.59215686274509804, 0.5607843137254902 ), (0.00392156862745098, 0.4 , 0.36862745098039218), (0.0 , 0.23529411764705882, 0.18823529411764706) ) _BuGn_data = ( (0.96862745098039216, 0.9882352941176471 , 0.99215686274509807), (0.89803921568627454, 0.96078431372549022, 0.97647058823529409), (0.8 , 0.92549019607843142, 0.90196078431372551), (0.6 , 0.84705882352941175, 0.78823529411764703), (0.4 , 0.76078431372549016, 0.64313725490196083), (0.25490196078431371, 0.68235294117647061, 0.46274509803921571), (0.13725490196078433, 0.54509803921568623, 0.27058823529411763), (0.0 , 0.42745098039215684, 0.17254901960784313), (0.0 , 0.26666666666666666, 0.10588235294117647) ) _BuPu_data = ( (0.96862745098039216, 0.9882352941176471 , 0.99215686274509807), (0.8784313725490196 , 0.92549019607843142, 0.95686274509803926), (0.74901960784313726, 0.82745098039215681, 0.90196078431372551), (0.61960784313725492, 0.73725490196078436, 0.85490196078431369), (0.5490196078431373 , 0.58823529411764708, 0.77647058823529413), (0.5490196078431373 , 0.41960784313725491, 0.69411764705882351), (0.53333333333333333, 0.25490196078431371, 0.61568627450980395), (0.50588235294117645, 0.05882352941176471, 0.48627450980392156), (0.30196078431372547, 0.0 , 0.29411764705882354) ) _GnBu_data = ( (0.96862745098039216, 0.9882352941176471 , 0.94117647058823528), (0.8784313725490196 , 0.95294117647058818, 0.85882352941176465), (0.8 , 0.92156862745098034, 0.77254901960784317), (0.6588235294117647 , 0.8666666666666667 , 0.70980392156862748), (0.4823529411764706 , 0.8 , 0.7686274509803922 ), (0.30588235294117649, 0.70196078431372544, 0.82745098039215681), (0.16862745098039217, 0.5490196078431373 , 0.74509803921568629), (0.03137254901960784, 0.40784313725490196, 0.67450980392156867), (0.03137254901960784, 0.25098039215686274, 0.50588235294117645) ) _Greens_data = ( (0.96862745098039216, 0.9882352941176471 , 0.96078431372549022), (0.89803921568627454, 0.96078431372549022, 0.8784313725490196 ), (0.7803921568627451 , 0.9137254901960784 , 0.75294117647058822), (0.63137254901960782, 0.85098039215686272, 0.60784313725490191), (0.45490196078431372, 0.7686274509803922 , 0.46274509803921571), (0.25490196078431371, 0.6705882352941176 , 0.36470588235294116), (0.13725490196078433, 0.54509803921568623, 0.27058823529411763), (0.0 , 0.42745098039215684, 0.17254901960784313), (0.0 , 0.26666666666666666, 0.10588235294117647) ) _Greys_data = ( (1.0 , 1.0 , 1.0 ), (0.94117647058823528, 0.94117647058823528, 0.94117647058823528), (0.85098039215686272, 0.85098039215686272, 0.85098039215686272), (0.74117647058823533, 0.74117647058823533, 0.74117647058823533), (0.58823529411764708, 0.58823529411764708, 0.58823529411764708), (0.45098039215686275, 0.45098039215686275, 0.45098039215686275), (0.32156862745098042, 0.32156862745098042, 0.32156862745098042), (0.14509803921568629, 0.14509803921568629, 0.14509803921568629), (0.0 , 0.0 , 0.0 ) ) _Oranges_data = ( (1.0 , 0.96078431372549022, 0.92156862745098034), (0.99607843137254903, 0.90196078431372551, 0.80784313725490198), (0.99215686274509807, 0.81568627450980391, 0.63529411764705879), (0.99215686274509807, 0.68235294117647061, 0.41960784313725491), (0.99215686274509807, 0.55294117647058827, 0.23529411764705882), (0.94509803921568625, 0.41176470588235292, 0.07450980392156863), (0.85098039215686272, 0.28235294117647058, 0.00392156862745098), (0.65098039215686276, 0.21176470588235294, 0.01176470588235294), (0.49803921568627452, 0.15294117647058825, 0.01568627450980392) ) _OrRd_data = ( (1.0 , 0.96862745098039216, 0.92549019607843142), (0.99607843137254903, 0.90980392156862744, 0.78431372549019607), (0.99215686274509807, 0.83137254901960789, 0.61960784313725492), (0.99215686274509807, 0.73333333333333328, 0.51764705882352946), (0.9882352941176471 , 0.55294117647058827, 0.34901960784313724), (0.93725490196078431, 0.396078431372549 , 0.28235294117647058), (0.84313725490196079, 0.18823529411764706, 0.12156862745098039), (0.70196078431372544, 0.0 , 0.0 ), (0.49803921568627452, 0.0 , 0.0 ) ) _PiYG_data = ( (0.55686274509803924, 0.00392156862745098, 0.32156862745098042), (0.77254901960784317, 0.10588235294117647, 0.49019607843137253), (0.87058823529411766, 0.46666666666666667, 0.68235294117647061), (0.94509803921568625, 0.71372549019607845, 0.85490196078431369), (0.99215686274509807, 0.8784313725490196 , 0.93725490196078431), (0.96862745098039216, 0.96862745098039216, 0.96862745098039216), (0.90196078431372551, 0.96078431372549022, 0.81568627450980391), (0.72156862745098038, 0.88235294117647056, 0.52549019607843139), (0.49803921568627452, 0.73725490196078436, 0.25490196078431371), (0.30196078431372547, 0.5725490196078431 , 0.12941176470588237), (0.15294117647058825, 0.39215686274509803, 0.09803921568627451) ) _PRGn_data = ( (0.25098039215686274, 0.0 , 0.29411764705882354), (0.46274509803921571, 0.16470588235294117, 0.51372549019607838), (0.6 , 0.4392156862745098 , 0.6705882352941176 ), (0.76078431372549016, 0.6470588235294118 , 0.81176470588235294), (0.90588235294117647, 0.83137254901960789, 0.90980392156862744), (0.96862745098039216, 0.96862745098039216, 0.96862745098039216), (0.85098039215686272, 0.94117647058823528, 0.82745098039215681), (0.65098039215686276, 0.85882352941176465, 0.62745098039215685), (0.35294117647058826, 0.68235294117647061, 0.38039215686274508), (0.10588235294117647, 0.47058823529411764, 0.21568627450980393), (0.0 , 0.26666666666666666, 0.10588235294117647) ) _PuBu_data = ( (1.0 , 0.96862745098039216, 0.98431372549019602), (0.92549019607843142, 0.90588235294117647, 0.94901960784313721), (0.81568627450980391, 0.81960784313725488, 0.90196078431372551), (0.65098039215686276, 0.74117647058823533, 0.85882352941176465), (0.45490196078431372, 0.66274509803921566, 0.81176470588235294), (0.21176470588235294, 0.56470588235294117, 0.75294117647058822), (0.0196078431372549 , 0.4392156862745098 , 0.69019607843137254), (0.01568627450980392, 0.35294117647058826, 0.55294117647058827), (0.00784313725490196, 0.2196078431372549 , 0.34509803921568627) ) _PuBuGn_data = ( (1.0 , 0.96862745098039216, 0.98431372549019602), (0.92549019607843142, 0.88627450980392153, 0.94117647058823528), (0.81568627450980391, 0.81960784313725488, 0.90196078431372551), (0.65098039215686276, 0.74117647058823533, 0.85882352941176465), (0.40392156862745099, 0.66274509803921566, 0.81176470588235294), (0.21176470588235294, 0.56470588235294117, 0.75294117647058822), (0.00784313725490196, 0.50588235294117645, 0.54117647058823526), (0.00392156862745098, 0.42352941176470588, 0.34901960784313724), (0.00392156862745098, 0.27450980392156865, 0.21176470588235294) ) _PuOr_data = ( (0.49803921568627452, 0.23137254901960785, 0.03137254901960784), (0.70196078431372544, 0.34509803921568627, 0.02352941176470588), (0.8784313725490196 , 0.50980392156862742, 0.07843137254901961), (0.99215686274509807, 0.72156862745098038, 0.38823529411764707), (0.99607843137254903, 0.8784313725490196 , 0.71372549019607845), (0.96862745098039216, 0.96862745098039216, 0.96862745098039216), (0.84705882352941175, 0.85490196078431369, 0.92156862745098034), (0.69803921568627447, 0.6705882352941176 , 0.82352941176470584), (0.50196078431372548, 0.45098039215686275, 0.67450980392156867), (0.32941176470588235, 0.15294117647058825, 0.53333333333333333), (0.17647058823529413, 0.0 , 0.29411764705882354) ) _PuRd_data = ( (0.96862745098039216, 0.95686274509803926, 0.97647058823529409), (0.90588235294117647, 0.88235294117647056, 0.93725490196078431), (0.83137254901960789, 0.72549019607843135, 0.85490196078431369), (0.78823529411764703, 0.58039215686274515, 0.7803921568627451 ), (0.87450980392156863, 0.396078431372549 , 0.69019607843137254), (0.90588235294117647, 0.16078431372549021, 0.54117647058823526), (0.80784313725490198, 0.07058823529411765, 0.33725490196078434), (0.59607843137254901, 0.0 , 0.2627450980392157 ), (0.40392156862745099, 0.0 , 0.12156862745098039) ) _Purples_data = ( (0.9882352941176471 , 0.98431372549019602, 0.99215686274509807), (0.93725490196078431, 0.92941176470588238, 0.96078431372549022), (0.85490196078431369, 0.85490196078431369, 0.92156862745098034), (0.73725490196078436, 0.74117647058823533, 0.86274509803921573), (0.61960784313725492, 0.60392156862745094, 0.78431372549019607), (0.50196078431372548, 0.49019607843137253, 0.72941176470588232), (0.41568627450980394, 0.31764705882352939, 0.63921568627450975), (0.32941176470588235, 0.15294117647058825, 0.5607843137254902 ), (0.24705882352941178, 0.0 , 0.49019607843137253) ) _RdBu_data = ( (0.40392156862745099, 0.0 , 0.12156862745098039), (0.69803921568627447, 0.09411764705882353, 0.16862745098039217), (0.83921568627450982, 0.37647058823529411, 0.30196078431372547), (0.95686274509803926, 0.6470588235294118 , 0.50980392156862742), (0.99215686274509807, 0.85882352941176465, 0.7803921568627451 ), (0.96862745098039216, 0.96862745098039216, 0.96862745098039216), (0.81960784313725488, 0.89803921568627454, 0.94117647058823528), (0.5725490196078431 , 0.77254901960784317, 0.87058823529411766), (0.2627450980392157 , 0.57647058823529407, 0.76470588235294112), (0.12941176470588237, 0.4 , 0.67450980392156867), (0.0196078431372549 , 0.18823529411764706, 0.38039215686274508) ) _RdGy_data = ( (0.40392156862745099, 0.0 , 0.12156862745098039), (0.69803921568627447, 0.09411764705882353, 0.16862745098039217), (0.83921568627450982, 0.37647058823529411, 0.30196078431372547), (0.95686274509803926, 0.6470588235294118 , 0.50980392156862742), (0.99215686274509807, 0.85882352941176465, 0.7803921568627451 ), (1.0 , 1.0 , 1.0 ), (0.8784313725490196 , 0.8784313725490196 , 0.8784313725490196 ), (0.72941176470588232, 0.72941176470588232, 0.72941176470588232), (0.52941176470588236, 0.52941176470588236, 0.52941176470588236), (0.30196078431372547, 0.30196078431372547, 0.30196078431372547), (0.10196078431372549, 0.10196078431372549, 0.10196078431372549) ) _RdPu_data = ( (1.0 , 0.96862745098039216, 0.95294117647058818), (0.99215686274509807, 0.8784313725490196 , 0.86666666666666667), (0.9882352941176471 , 0.77254901960784317, 0.75294117647058822), (0.98039215686274506, 0.62352941176470589, 0.70980392156862748), (0.96862745098039216, 0.40784313725490196, 0.63137254901960782), (0.86666666666666667, 0.20392156862745098, 0.59215686274509804), (0.68235294117647061, 0.00392156862745098, 0.49411764705882355), (0.47843137254901963, 0.00392156862745098, 0.46666666666666667), (0.28627450980392155, 0.0 , 0.41568627450980394) ) _RdYlBu_data = ( (0.6470588235294118 , 0.0 , 0.14901960784313725), (0.84313725490196079, 0.18823529411764706 , 0.15294117647058825), (0.95686274509803926, 0.42745098039215684 , 0.2627450980392157 ), (0.99215686274509807, 0.68235294117647061 , 0.38039215686274508), (0.99607843137254903, 0.8784313725490196 , 0.56470588235294117), (1.0 , 1.0 , 0.74901960784313726), (0.8784313725490196 , 0.95294117647058818 , 0.97254901960784312), (0.6705882352941176 , 0.85098039215686272 , 0.9137254901960784 ), (0.45490196078431372, 0.67843137254901964 , 0.81960784313725488), (0.27058823529411763, 0.45882352941176469 , 0.70588235294117652), (0.19215686274509805, 0.21176470588235294 , 0.58431372549019611) ) _RdYlGn_data = ( (0.6470588235294118 , 0.0 , 0.14901960784313725), (0.84313725490196079, 0.18823529411764706 , 0.15294117647058825), (0.95686274509803926, 0.42745098039215684 , 0.2627450980392157 ), (0.99215686274509807, 0.68235294117647061 , 0.38039215686274508), (0.99607843137254903, 0.8784313725490196 , 0.54509803921568623), (1.0 , 1.0 , 0.74901960784313726), (0.85098039215686272, 0.93725490196078431 , 0.54509803921568623), (0.65098039215686276, 0.85098039215686272 , 0.41568627450980394), (0.4 , 0.74117647058823533 , 0.38823529411764707), (0.10196078431372549, 0.59607843137254901 , 0.31372549019607843), (0.0 , 0.40784313725490196 , 0.21568627450980393) ) _Reds_data = ( (1.0 , 0.96078431372549022 , 0.94117647058823528), (0.99607843137254903, 0.8784313725490196 , 0.82352941176470584), (0.9882352941176471 , 0.73333333333333328 , 0.63137254901960782), (0.9882352941176471 , 0.5725490196078431 , 0.44705882352941179), (0.98431372549019602, 0.41568627450980394 , 0.29019607843137257), (0.93725490196078431, 0.23137254901960785 , 0.17254901960784313), (0.79607843137254897, 0.094117647058823528, 0.11372549019607843), (0.6470588235294118 , 0.058823529411764705, 0.08235294117647058), (0.40392156862745099, 0.0 , 0.05098039215686274) ) _Spectral_data = ( (0.61960784313725492, 0.003921568627450980, 0.25882352941176473), (0.83529411764705885, 0.24313725490196078 , 0.30980392156862746), (0.95686274509803926, 0.42745098039215684 , 0.2627450980392157 ), (0.99215686274509807, 0.68235294117647061 , 0.38039215686274508), (0.99607843137254903, 0.8784313725490196 , 0.54509803921568623), (1.0 , 1.0 , 0.74901960784313726), (0.90196078431372551, 0.96078431372549022 , 0.59607843137254901), (0.6705882352941176 , 0.8666666666666667 , 0.64313725490196083), (0.4 , 0.76078431372549016 , 0.6470588235294118 ), (0.19607843137254902, 0.53333333333333333 , 0.74117647058823533), (0.36862745098039218, 0.30980392156862746 , 0.63529411764705879) ) _YlGn_data = ( (1.0 , 1.0 , 0.89803921568627454), (0.96862745098039216, 0.9882352941176471 , 0.72549019607843135), (0.85098039215686272, 0.94117647058823528 , 0.63921568627450975), (0.67843137254901964, 0.8666666666666667 , 0.55686274509803924), (0.47058823529411764, 0.77647058823529413 , 0.47450980392156861), (0.25490196078431371, 0.6705882352941176 , 0.36470588235294116), (0.13725490196078433, 0.51764705882352946 , 0.2627450980392157 ), (0.0 , 0.40784313725490196 , 0.21568627450980393), (0.0 , 0.27058823529411763 , 0.16078431372549021) ) _YlGnBu_data = ( (1.0 , 1.0 , 0.85098039215686272), (0.92941176470588238, 0.97254901960784312 , 0.69411764705882351), (0.7803921568627451 , 0.9137254901960784 , 0.70588235294117652), (0.49803921568627452, 0.80392156862745101 , 0.73333333333333328), (0.25490196078431371, 0.71372549019607845 , 0.7686274509803922 ), (0.11372549019607843, 0.56862745098039214 , 0.75294117647058822), (0.13333333333333333, 0.36862745098039218 , 0.6588235294117647 ), (0.14509803921568629, 0.20392156862745098 , 0.58039215686274515), (0.03137254901960784, 0.11372549019607843 , 0.34509803921568627) ) _YlOrBr_data = ( (1.0 , 1.0 , 0.89803921568627454), (1.0 , 0.96862745098039216 , 0.73725490196078436), (0.99607843137254903, 0.8901960784313725 , 0.56862745098039214), (0.99607843137254903, 0.7686274509803922 , 0.30980392156862746), (0.99607843137254903, 0.6 , 0.16078431372549021), (0.92549019607843142, 0.4392156862745098 , 0.07843137254901961), (0.8 , 0.29803921568627451 , 0.00784313725490196), (0.6 , 0.20392156862745098 , 0.01568627450980392), (0.4 , 0.14509803921568629 , 0.02352941176470588) ) _YlOrRd_data = ( (1.0 , 1.0 , 0.8 ), (1.0 , 0.92941176470588238 , 0.62745098039215685), (0.99607843137254903, 0.85098039215686272 , 0.46274509803921571), (0.99607843137254903, 0.69803921568627447 , 0.29803921568627451), (0.99215686274509807, 0.55294117647058827 , 0.23529411764705882), (0.9882352941176471 , 0.30588235294117649 , 0.16470588235294117), (0.8901960784313725 , 0.10196078431372549 , 0.10980392156862745), (0.74117647058823533, 0.0 , 0.14901960784313725), (0.50196078431372548, 0.0 , 0.14901960784313725) ) # ColorBrewer's qualitative maps, implemented using ListedColormap # for use with mpl.colors.NoNorm _Accent_data = ( (0.49803921568627452, 0.78823529411764703, 0.49803921568627452), (0.74509803921568629, 0.68235294117647061, 0.83137254901960789), (0.99215686274509807, 0.75294117647058822, 0.52549019607843139), (1.0, 1.0, 0.6 ), (0.2196078431372549, 0.42352941176470588, 0.69019607843137254), (0.94117647058823528, 0.00784313725490196, 0.49803921568627452), (0.74901960784313726, 0.35686274509803922, 0.09019607843137254), (0.4, 0.4, 0.4 ), ) _Dark2_data = ( (0.10588235294117647, 0.61960784313725492, 0.46666666666666667), (0.85098039215686272, 0.37254901960784315, 0.00784313725490196), (0.45882352941176469, 0.4392156862745098, 0.70196078431372544), (0.90588235294117647, 0.16078431372549021, 0.54117647058823526), (0.4, 0.65098039215686276, 0.11764705882352941), (0.90196078431372551, 0.6705882352941176, 0.00784313725490196), (0.65098039215686276, 0.46274509803921571, 0.11372549019607843), (0.4, 0.4, 0.4 ), ) _Paired_data = ( (0.65098039215686276, 0.80784313725490198, 0.8901960784313725 ), (0.12156862745098039, 0.47058823529411764, 0.70588235294117652), (0.69803921568627447, 0.87450980392156863, 0.54117647058823526), (0.2, 0.62745098039215685, 0.17254901960784313), (0.98431372549019602, 0.60392156862745094, 0.6 ), (0.8901960784313725, 0.10196078431372549, 0.10980392156862745), (0.99215686274509807, 0.74901960784313726, 0.43529411764705883), (1.0, 0.49803921568627452, 0.0 ), (0.792156862745098, 0.69803921568627447, 0.83921568627450982), (0.41568627450980394, 0.23921568627450981, 0.60392156862745094), (1.0, 1.0, 0.6 ), (0.69411764705882351, 0.34901960784313724, 0.15686274509803921), ) _Pastel1_data = ( (0.98431372549019602, 0.70588235294117652, 0.68235294117647061), (0.70196078431372544, 0.80392156862745101, 0.8901960784313725 ), (0.8, 0.92156862745098034, 0.77254901960784317), (0.87058823529411766, 0.79607843137254897, 0.89411764705882357), (0.99607843137254903, 0.85098039215686272, 0.65098039215686276), (1.0, 1.0, 0.8 ), (0.89803921568627454, 0.84705882352941175, 0.74117647058823533), (0.99215686274509807, 0.85490196078431369, 0.92549019607843142), (0.94901960784313721, 0.94901960784313721, 0.94901960784313721), ) _Pastel2_data = ( (0.70196078431372544, 0.88627450980392153, 0.80392156862745101), (0.99215686274509807, 0.80392156862745101, 0.67450980392156867), (0.79607843137254897, 0.83529411764705885, 0.90980392156862744), (0.95686274509803926, 0.792156862745098, 0.89411764705882357), (0.90196078431372551, 0.96078431372549022, 0.78823529411764703), (1.0, 0.94901960784313721, 0.68235294117647061), (0.94509803921568625, 0.88627450980392153, 0.8 ), (0.8, 0.8, 0.8 ), ) _Set1_data = ( (0.89411764705882357, 0.10196078431372549, 0.10980392156862745), (0.21568627450980393, 0.49411764705882355, 0.72156862745098038), (0.30196078431372547, 0.68627450980392157, 0.29019607843137257), (0.59607843137254901, 0.30588235294117649, 0.63921568627450975), (1.0, 0.49803921568627452, 0.0 ), (1.0, 1.0, 0.2 ), (0.65098039215686276, 0.33725490196078434, 0.15686274509803921), (0.96862745098039216, 0.50588235294117645, 0.74901960784313726), (0.6, 0.6, 0.6), ) _Set2_data = ( (0.4, 0.76078431372549016, 0.6470588235294118 ), (0.9882352941176471, 0.55294117647058827, 0.3843137254901961 ), (0.55294117647058827, 0.62745098039215685, 0.79607843137254897), (0.90588235294117647, 0.54117647058823526, 0.76470588235294112), (0.65098039215686276, 0.84705882352941175, 0.32941176470588235), (1.0, 0.85098039215686272, 0.18431372549019609), (0.89803921568627454, 0.7686274509803922, 0.58039215686274515), (0.70196078431372544, 0.70196078431372544, 0.70196078431372544), ) _Set3_data = ( (0.55294117647058827, 0.82745098039215681, 0.7803921568627451 ), (1.0, 1.0, 0.70196078431372544), (0.74509803921568629, 0.72941176470588232, 0.85490196078431369), (0.98431372549019602, 0.50196078431372548, 0.44705882352941179), (0.50196078431372548, 0.69411764705882351, 0.82745098039215681), (0.99215686274509807, 0.70588235294117652, 0.3843137254901961 ), (0.70196078431372544, 0.87058823529411766, 0.41176470588235292), (0.9882352941176471, 0.80392156862745101, 0.89803921568627454), (0.85098039215686272, 0.85098039215686272, 0.85098039215686272), (0.73725490196078436, 0.50196078431372548, 0.74117647058823533), (0.8, 0.92156862745098034, 0.77254901960784317), (1.0, 0.92941176470588238, 0.43529411764705883), ) # The next 7 palettes are from the Yorick scientific visualization package, # an evolution of the GIST package, both by David H. Munro. # They are released under a BSD-like license (see LICENSE_YORICK in # the license directory of the matplotlib source distribution). # # Most palette functions have been reduced to simple function descriptions # by Reinier Heeres, since the rgb components were mostly straight lines. # gist_earth_data and gist_ncar_data were simplified by a script and some # manual effort. _gist_earth_data = \ {'red': ( (0.0, 0.0, 0.0000), (0.2824, 0.1882, 0.1882), (0.4588, 0.2714, 0.2714), (0.5490, 0.4719, 0.4719), (0.6980, 0.7176, 0.7176), (0.7882, 0.7553, 0.7553), (1.0000, 0.9922, 0.9922), ), 'green': ( (0.0, 0.0, 0.0000), (0.0275, 0.0000, 0.0000), (0.1098, 0.1893, 0.1893), (0.1647, 0.3035, 0.3035), (0.2078, 0.3841, 0.3841), (0.2824, 0.5020, 0.5020), (0.5216, 0.6397, 0.6397), (0.6980, 0.7171, 0.7171), (0.7882, 0.6392, 0.6392), (0.7922, 0.6413, 0.6413), (0.8000, 0.6447, 0.6447), (0.8078, 0.6481, 0.6481), (0.8157, 0.6549, 0.6549), (0.8667, 0.6991, 0.6991), (0.8745, 0.7103, 0.7103), (0.8824, 0.7216, 0.7216), (0.8902, 0.7323, 0.7323), (0.8980, 0.7430, 0.7430), (0.9412, 0.8275, 0.8275), (0.9569, 0.8635, 0.8635), (0.9647, 0.8816, 0.8816), (0.9961, 0.9733, 0.9733), (1.0000, 0.9843, 0.9843), ), 'blue': ( (0.0, 0.0, 0.0000), (0.0039, 0.1684, 0.1684), (0.0078, 0.2212, 0.2212), (0.0275, 0.4329, 0.4329), (0.0314, 0.4549, 0.4549), (0.2824, 0.5004, 0.5004), (0.4667, 0.2748, 0.2748), (0.5451, 0.3205, 0.3205), (0.7843, 0.3961, 0.3961), (0.8941, 0.6651, 0.6651), (1.0000, 0.9843, 0.9843), )} _gist_gray_data = { 'red': gfunc[3], 'green': gfunc[3], 'blue': gfunc[3], } def _gist_heat_red(x): return 1.5 * x def _gist_heat_green(x): return 2 * x - 1 def _gist_heat_blue(x): return 4 * x - 3 _gist_heat_data = { 'red': _gist_heat_red, 'green': _gist_heat_green, 'blue': _gist_heat_blue} _gist_ncar_data = \ {'red': ( (0.0, 0.0, 0.0000), (0.3098, 0.0000, 0.0000), (0.3725, 0.3993, 0.3993), (0.4235, 0.5003, 0.5003), (0.5333, 1.0000, 1.0000), (0.7922, 1.0000, 1.0000), (0.8471, 0.6218, 0.6218), (0.8980, 0.9235, 0.9235), (1.0000, 0.9961, 0.9961), ), 'green': ( (0.0, 0.0, 0.0000), (0.0510, 0.3722, 0.3722), (0.1059, 0.0000, 0.0000), (0.1569, 0.7202, 0.7202), (0.1608, 0.7537, 0.7537), (0.1647, 0.7752, 0.7752), (0.2157, 1.0000, 1.0000), (0.2588, 0.9804, 0.9804), (0.2706, 0.9804, 0.9804), (0.3176, 1.0000, 1.0000), (0.3686, 0.8081, 0.8081), (0.4275, 1.0000, 1.0000), (0.5216, 1.0000, 1.0000), (0.6314, 0.7292, 0.7292), (0.6863, 0.2796, 0.2796), (0.7451, 0.0000, 0.0000), (0.7922, 0.0000, 0.0000), (0.8431, 0.1753, 0.1753), (0.8980, 0.5000, 0.5000), (1.0000, 0.9725, 0.9725), ), 'blue': ( (0.0, 0.5020, 0.5020), (0.0510, 0.0222, 0.0222), (0.1098, 1.0000, 1.0000), (0.2039, 1.0000, 1.0000), (0.2627, 0.6145, 0.6145), (0.3216, 0.0000, 0.0000), (0.4157, 0.0000, 0.0000), (0.4745, 0.2342, 0.2342), (0.5333, 0.0000, 0.0000), (0.5804, 0.0000, 0.0000), (0.6314, 0.0549, 0.0549), (0.6902, 0.0000, 0.0000), (0.7373, 0.0000, 0.0000), (0.7922, 0.9738, 0.9738), (0.8000, 1.0000, 1.0000), (0.8431, 1.0000, 1.0000), (0.8980, 0.9341, 0.9341), (1.0000, 0.9961, 0.9961), )} _gist_rainbow_data = ( (0.000, (1.00, 0.00, 0.16)), (0.030, (1.00, 0.00, 0.00)), (0.215, (1.00, 1.00, 0.00)), (0.400, (0.00, 1.00, 0.00)), (0.586, (0.00, 1.00, 1.00)), (0.770, (0.00, 0.00, 1.00)), (0.954, (1.00, 0.00, 1.00)), (1.000, (1.00, 0.00, 0.75)) ) _gist_stern_data = { 'red': ( (0.000, 0.000, 0.000), (0.0547, 1.000, 1.000), (0.250, 0.027, 0.250), # (0.2500, 0.250, 0.250), (1.000, 1.000, 1.000)), 'green': ((0, 0, 0), (1, 1, 1)), 'blue': ( (0.000, 0.000, 0.000), (0.500, 1.000, 1.000), (0.735, 0.000, 0.000), (1.000, 1.000, 1.000)) } def _gist_yarg(x): return 1 - x _gist_yarg_data = {'red': _gist_yarg, 'green': _gist_yarg, 'blue': _gist_yarg} # This bipolar colormap was generated from CoolWarmFloat33.csv of # "Diverging Color Maps for Scientific Visualization" by Kenneth Moreland. # _coolwarm_data = { 'red': [ (0.0, 0.2298057, 0.2298057), (0.03125, 0.26623388, 0.26623388), (0.0625, 0.30386891, 0.30386891), (0.09375, 0.342804478, 0.342804478), (0.125, 0.38301334, 0.38301334), (0.15625, 0.424369608, 0.424369608), (0.1875, 0.46666708, 0.46666708), (0.21875, 0.509635204, 0.509635204), (0.25, 0.552953156, 0.552953156), (0.28125, 0.596262162, 0.596262162), (0.3125, 0.639176211, 0.639176211), (0.34375, 0.681291281, 0.681291281), (0.375, 0.722193294, 0.722193294), (0.40625, 0.761464949, 0.761464949), (0.4375, 0.798691636, 0.798691636), (0.46875, 0.833466556, 0.833466556), (0.5, 0.865395197, 0.865395197), (0.53125, 0.897787179, 0.897787179), (0.5625, 0.924127593, 0.924127593), (0.59375, 0.944468518, 0.944468518), (0.625, 0.958852946, 0.958852946), (0.65625, 0.96732803, 0.96732803), (0.6875, 0.969954137, 0.969954137), (0.71875, 0.966811177, 0.966811177), (0.75, 0.958003065, 0.958003065), (0.78125, 0.943660866, 0.943660866), (0.8125, 0.923944917, 0.923944917), (0.84375, 0.89904617, 0.89904617), (0.875, 0.869186849, 0.869186849), (0.90625, 0.834620542, 0.834620542), (0.9375, 0.795631745, 0.795631745), (0.96875, 0.752534934, 0.752534934), (1.0, 0.705673158, 0.705673158)], 'green': [ (0.0, 0.298717966, 0.298717966), (0.03125, 0.353094838, 0.353094838), (0.0625, 0.406535296, 0.406535296), (0.09375, 0.458757618, 0.458757618), (0.125, 0.50941904, 0.50941904), (0.15625, 0.558148092, 0.558148092), (0.1875, 0.604562568, 0.604562568), (0.21875, 0.648280772, 0.648280772), (0.25, 0.688929332, 0.688929332), (0.28125, 0.726149107, 0.726149107), (0.3125, 0.759599947, 0.759599947), (0.34375, 0.788964712, 0.788964712), (0.375, 0.813952739, 0.813952739), (0.40625, 0.834302879, 0.834302879), (0.4375, 0.849786142, 0.849786142), (0.46875, 0.860207984, 0.860207984), (0.5, 0.86541021, 0.86541021), (0.53125, 0.848937047, 0.848937047), (0.5625, 0.827384882, 0.827384882), (0.59375, 0.800927443, 0.800927443), (0.625, 0.769767752, 0.769767752), (0.65625, 0.734132809, 0.734132809), (0.6875, 0.694266682, 0.694266682), (0.71875, 0.650421156, 0.650421156), (0.75, 0.602842431, 0.602842431), (0.78125, 0.551750968, 0.551750968), (0.8125, 0.49730856, 0.49730856), (0.84375, 0.439559467, 0.439559467), (0.875, 0.378313092, 0.378313092), (0.90625, 0.312874446, 0.312874446), (0.9375, 0.24128379, 0.24128379), (0.96875, 0.157246067, 0.157246067), (1.0, 0.01555616, 0.01555616)], 'blue': [ (0.0, 0.753683153, 0.753683153), (0.03125, 0.801466763, 0.801466763), (0.0625, 0.84495867, 0.84495867), (0.09375, 0.883725899, 0.883725899), (0.125, 0.917387822, 0.917387822), (0.15625, 0.945619588, 0.945619588), (0.1875, 0.968154911, 0.968154911), (0.21875, 0.98478814, 0.98478814), (0.25, 0.995375608, 0.995375608), (0.28125, 0.999836203, 0.999836203), (0.3125, 0.998151185, 0.998151185), (0.34375, 0.990363227, 0.990363227), (0.375, 0.976574709, 0.976574709), (0.40625, 0.956945269, 0.956945269), (0.4375, 0.931688648, 0.931688648), (0.46875, 0.901068838, 0.901068838), (0.5, 0.865395561, 0.865395561), (0.53125, 0.820880546, 0.820880546), (0.5625, 0.774508472, 0.774508472), (0.59375, 0.726736146, 0.726736146), (0.625, 0.678007945, 0.678007945), (0.65625, 0.628751763, 0.628751763), (0.6875, 0.579375448, 0.579375448), (0.71875, 0.530263762, 0.530263762), (0.75, 0.481775914, 0.481775914), (0.78125, 0.434243684, 0.434243684), (0.8125, 0.387970225, 0.387970225), (0.84375, 0.343229596, 0.343229596), (0.875, 0.300267182, 0.300267182), (0.90625, 0.259301199, 0.259301199), (0.9375, 0.220525627, 0.220525627), (0.96875, 0.184115123, 0.184115123), (1.0, 0.150232812, 0.150232812)] } # Implementation of Carey Rappaport's CMRmap. # See `A Color Map for Effective Black-and-White Rendering of Color-Scale # Images' by Carey Rappaport # http://www.mathworks.com/matlabcentral/fileexchange/2662-cmrmap-m _CMRmap_data = {'red': ((0.000, 0.00, 0.00), (0.125, 0.15, 0.15), (0.250, 0.30, 0.30), (0.375, 0.60, 0.60), (0.500, 1.00, 1.00), (0.625, 0.90, 0.90), (0.750, 0.90, 0.90), (0.875, 0.90, 0.90), (1.000, 1.00, 1.00)), 'green': ((0.000, 0.00, 0.00), (0.125, 0.15, 0.15), (0.250, 0.15, 0.15), (0.375, 0.20, 0.20), (0.500, 0.25, 0.25), (0.625, 0.50, 0.50), (0.750, 0.75, 0.75), (0.875, 0.90, 0.90), (1.000, 1.00, 1.00)), 'blue': ((0.000, 0.00, 0.00), (0.125, 0.50, 0.50), (0.250, 0.75, 0.75), (0.375, 0.50, 0.50), (0.500, 0.15, 0.15), (0.625, 0.00, 0.00), (0.750, 0.10, 0.10), (0.875, 0.50, 0.50), (1.000, 1.00, 1.00))} # An MIT licensed, colorblind-friendly heatmap from Wistia: # https://github.com/wistia/heatmap-palette # http://wistia.com/blog/heatmaps-for-colorblindness # # >>> import matplotlib.colors as c # >>> colors = ["#e4ff7a", "#ffe81a", "#ffbd00", "#ffa000", "#fc7f00"] # >>> cm = c.LinearSegmentedColormap.from_list('wistia', colors) # >>> _wistia_data = cm._segmentdata # >>> del _wistia_data['alpha'] # _wistia_data = { 'red': [(0.0, 0.8941176470588236, 0.8941176470588236), (0.25, 1.0, 1.0), (0.5, 1.0, 1.0), (0.75, 1.0, 1.0), (1.0, 0.9882352941176471, 0.9882352941176471)], 'green': [(0.0, 1.0, 1.0), (0.25, 0.9098039215686274, 0.9098039215686274), (0.5, 0.7411764705882353, 0.7411764705882353), (0.75, 0.6274509803921569, 0.6274509803921569), (1.0, 0.4980392156862745, 0.4980392156862745)], 'blue': [(0.0, 0.47843137254901963, 0.47843137254901963), (0.25, 0.10196078431372549, 0.10196078431372549), (0.5, 0.0, 0.0), (0.75, 0.0, 0.0), (1.0, 0.0, 0.0)], } # Categorical palettes from Vega: # https://github.com/vega/vega/wiki/Scales # (divided by 255) # _tab10_data = ( (0.12156862745098039, 0.4666666666666667, 0.7058823529411765 ), # 1f77b4 (1.0, 0.4980392156862745, 0.054901960784313725), # ff7f0e (0.17254901960784313, 0.6274509803921569, 0.17254901960784313 ), # 2ca02c (0.8392156862745098, 0.15294117647058825, 0.1568627450980392 ), # d62728 (0.5803921568627451, 0.403921568627451, 0.7411764705882353 ), # 9467bd (0.5490196078431373, 0.33725490196078434, 0.29411764705882354 ), # 8c564b (0.8901960784313725, 0.4666666666666667, 0.7607843137254902 ), # e377c2 (0.4980392156862745, 0.4980392156862745, 0.4980392156862745 ), # 7f7f7f (0.7372549019607844, 0.7411764705882353, 0.13333333333333333 ), # bcbd22 (0.09019607843137255, 0.7450980392156863, 0.8117647058823529), # 17becf ) _tab20_data = ( (0.12156862745098039, 0.4666666666666667, 0.7058823529411765 ), # 1f77b4 (0.6823529411764706, 0.7803921568627451, 0.9098039215686274 ), # aec7e8 (1.0, 0.4980392156862745, 0.054901960784313725), # ff7f0e (1.0, 0.7333333333333333, 0.47058823529411764 ), # ffbb78 (0.17254901960784313, 0.6274509803921569, 0.17254901960784313 ), # 2ca02c (0.596078431372549, 0.8745098039215686, 0.5411764705882353 ), # 98df8a (0.8392156862745098, 0.15294117647058825, 0.1568627450980392 ), # d62728 (1.0, 0.596078431372549, 0.5882352941176471 ), # ff9896 (0.5803921568627451, 0.403921568627451, 0.7411764705882353 ), # 9467bd (0.7725490196078432, 0.6901960784313725, 0.8352941176470589 ), # c5b0d5 (0.5490196078431373, 0.33725490196078434, 0.29411764705882354 ), # 8c564b (0.7686274509803922, 0.611764705882353, 0.5803921568627451 ), # c49c94 (0.8901960784313725, 0.4666666666666667, 0.7607843137254902 ), # e377c2 (0.9686274509803922, 0.7137254901960784, 0.8235294117647058 ), # f7b6d2 (0.4980392156862745, 0.4980392156862745, 0.4980392156862745 ), # 7f7f7f (0.7803921568627451, 0.7803921568627451, 0.7803921568627451 ), # c7c7c7 (0.7372549019607844, 0.7411764705882353, 0.13333333333333333 ), # bcbd22 (0.8588235294117647, 0.8588235294117647, 0.5529411764705883 ), # dbdb8d (0.09019607843137255, 0.7450980392156863, 0.8117647058823529 ), # 17becf (0.6196078431372549, 0.8549019607843137, 0.8980392156862745), # 9edae5 ) _tab20b_data = ( (0.2235294117647059, 0.23137254901960785, 0.4745098039215686 ), # 393b79 (0.3215686274509804, 0.32941176470588235, 0.6392156862745098 ), # 5254a3 (0.4196078431372549, 0.43137254901960786, 0.8117647058823529 ), # 6b6ecf (0.611764705882353, 0.6196078431372549, 0.8705882352941177 ), # 9c9ede (0.38823529411764707, 0.4745098039215686, 0.2235294117647059 ), # 637939 (0.5490196078431373, 0.6352941176470588, 0.3215686274509804 ), # 8ca252 (0.7098039215686275, 0.8117647058823529, 0.4196078431372549 ), # b5cf6b (0.807843137254902, 0.8588235294117647, 0.611764705882353 ), # cedb9c (0.5490196078431373, 0.42745098039215684, 0.19215686274509805), # 8c6d31 (0.7411764705882353, 0.6196078431372549, 0.2235294117647059 ), # bd9e39 (0.9058823529411765, 0.7294117647058823, 0.3215686274509804 ), # e7ba52 (0.9058823529411765, 0.796078431372549, 0.5803921568627451 ), # e7cb94 (0.5176470588235295, 0.23529411764705882, 0.2235294117647059 ), # 843c39 (0.6784313725490196, 0.28627450980392155, 0.2901960784313726 ), # ad494a (0.8392156862745098, 0.3803921568627451, 0.4196078431372549 ), # d6616b (0.9058823529411765, 0.5882352941176471, 0.611764705882353 ), # e7969c (0.4823529411764706, 0.2549019607843137, 0.45098039215686275), # 7b4173 (0.6470588235294118, 0.3176470588235294, 0.5803921568627451 ), # a55194 (0.807843137254902, 0.42745098039215684, 0.7411764705882353 ), # ce6dbd (0.8705882352941177, 0.6196078431372549, 0.8392156862745098 ), # de9ed6 ) _tab20c_data = ( (0.19215686274509805, 0.5098039215686274, 0.7411764705882353 ), # 3182bd (0.4196078431372549, 0.6823529411764706, 0.8392156862745098 ), # 6baed6 (0.6196078431372549, 0.792156862745098, 0.8823529411764706 ), # 9ecae1 (0.7764705882352941, 0.8588235294117647, 0.9372549019607843 ), # c6dbef (0.9019607843137255, 0.3333333333333333, 0.050980392156862744), # e6550d (0.9921568627450981, 0.5529411764705883, 0.23529411764705882 ), # fd8d3c (0.9921568627450981, 0.6823529411764706, 0.4196078431372549 ), # fdae6b (0.9921568627450981, 0.8156862745098039, 0.6352941176470588 ), # fdd0a2 (0.19215686274509805, 0.6392156862745098, 0.32941176470588235 ), # 31a354 (0.4549019607843137, 0.7686274509803922, 0.4627450980392157 ), # 74c476 (0.6313725490196078, 0.8509803921568627, 0.6078431372549019 ), # a1d99b (0.7803921568627451, 0.9137254901960784, 0.7529411764705882 ), # c7e9c0 (0.4588235294117647, 0.4196078431372549, 0.6941176470588235 ), # 756bb1 (0.6196078431372549, 0.6039215686274509, 0.7843137254901961 ), # 9e9ac8 (0.7372549019607844, 0.7411764705882353, 0.8627450980392157 ), # bcbddc (0.8549019607843137, 0.8549019607843137, 0.9215686274509803 ), # dadaeb (0.38823529411764707, 0.38823529411764707, 0.38823529411764707 ), # 636363 (0.5882352941176471, 0.5882352941176471, 0.5882352941176471 ), # 969696 (0.7411764705882353, 0.7411764705882353, 0.7411764705882353 ), # bdbdbd (0.8509803921568627, 0.8509803921568627, 0.8509803921568627 ), # d9d9d9 ) datad = { 'Blues': _Blues_data, 'BrBG': _BrBG_data, 'BuGn': _BuGn_data, 'BuPu': _BuPu_data, 'CMRmap': _CMRmap_data, 'GnBu': _GnBu_data, 'Greens': _Greens_data, 'Greys': _Greys_data, 'OrRd': _OrRd_data, 'Oranges': _Oranges_data, 'PRGn': _PRGn_data, 'PiYG': _PiYG_data, 'PuBu': _PuBu_data, 'PuBuGn': _PuBuGn_data, 'PuOr': _PuOr_data, 'PuRd': _PuRd_data, 'Purples': _Purples_data, 'RdBu': _RdBu_data, 'RdGy': _RdGy_data, 'RdPu': _RdPu_data, 'RdYlBu': _RdYlBu_data, 'RdYlGn': _RdYlGn_data, 'Reds': _Reds_data, 'Spectral': _Spectral_data, 'Wistia': _wistia_data, 'YlGn': _YlGn_data, 'YlGnBu': _YlGnBu_data, 'YlOrBr': _YlOrBr_data, 'YlOrRd': _YlOrRd_data, 'afmhot': _afmhot_data, 'autumn': _autumn_data, 'binary': _binary_data, 'bone': _bone_data, 'brg': _brg_data, 'bwr': _bwr_data, 'cool': _cool_data, 'coolwarm': _coolwarm_data, 'copper': _copper_data, 'cubehelix': _cubehelix_data, 'flag': _flag_data, 'gist_earth': _gist_earth_data, 'gist_gray': _gist_gray_data, 'gist_heat': _gist_heat_data, 'gist_ncar': _gist_ncar_data, 'gist_rainbow': _gist_rainbow_data, 'gist_stern': _gist_stern_data, 'gist_yarg': _gist_yarg_data, 'gnuplot': _gnuplot_data, 'gnuplot2': _gnuplot2_data, 'gray': _gray_data, 'hot': _hot_data, 'hsv': _hsv_data, 'jet': _jet_data, 'nipy_spectral': _nipy_spectral_data, 'ocean': _ocean_data, 'pink': _pink_data, 'prism': _prism_data, 'rainbow': _rainbow_data, 'seismic': _seismic_data, 'spring': _spring_data, 'summer': _summer_data, 'terrain': _terrain_data, 'winter': _winter_data, # Qualitative 'Accent': {'listed': _Accent_data}, 'Dark2': {'listed': _Dark2_data}, 'Paired': {'listed': _Paired_data}, 'Pastel1': {'listed': _Pastel1_data}, 'Pastel2': {'listed': _Pastel2_data}, 'Set1': {'listed': _Set1_data}, 'Set2': {'listed': _Set2_data}, 'Set3': {'listed': _Set3_data}, 'tab10': {'listed': _tab10_data}, 'tab20': {'listed': _tab20_data}, 'tab20b': {'listed': _tab20b_data}, 'tab20c': {'listed': _tab20c_data}, }