在写如下代码的时候，matplotlib模块引起了我的兴趣。

#!/usr/bin/env python
# -*- coding: utf-8 -*-import matplotlib as mpl
import matplotlib.cm
import matplotlib.colorsdef color_image(image, num_classes=20):norm = mpl.colors.Normalize(vmin=0., vmax=num_classes)mycm = mpl.cm.get_cmap('coolwarm')return mycm(norm(image))

  因为想进一步了解该模块的使用，我开始阅读matplotlib模块对应的实现源码。matplotlib模块实现源码的位置在 ./anaconda2/lib/python2.7/site-packages/matplotlib/cm.py 。

"""
Nothing here but dictionaries for generating LinearSegmentedColormaps,
and a dictionary of these dictionaries.Documentation for each is in pyplot.colormaps()
"""from __future__ import (absolute_import, division, print_function,unicode_literals)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))}_flag_data = {'red': lambda x: 0.75 * np.sin((x * 31.5 + 0.25) * np.pi) + 0.5,'green': lambda x: np.sin(x * 31.5 * np.pi),'blue': lambda x: 0.75 * np.sin((x * 31.5 - 0.25) * np.pi) + 0.5,
}_prism_data = {'red': lambda x: 0.75 * np.sin((x * 20.9 + 0.25) * np.pi) + 0.67,'green': lambda x: 0.75 * np.sin((x * 20.9 - 0.25) * np.pi) + 0.33,'blue': lambda x: -1.1 * np.sin((x * 20.9) * np.pi),
}def cubehelix(gamma=1.0, s=0.5, r=-1.5, h=1.0):"""Return custom data dictionary of (r,g,b) conversion functions, whichcan be used with :func:`register_cmap`, for the cubehelix color scheme.Unlike most other color schemes cubehelix was designed by D.A. Green tobe monotonically increasing in terms of perceived brightness.Also, when printed on a black and white postscript printer, the schemeresults in a greyscale with monotonically increasing brightness.This color scheme is named cubehelix because the r,g,b values producedcan be visualised as a squashed helix around the diagonal in ther,g,b color cube.For a unit color cube (i.e. 3-D coordinates for r,g,b each in therange 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 thatfraction along the black to white diagonal (x,x,x) plus a colorelement. This color element is calculated in a plane of constantperceived intensity and controlled by the following parameters.Optional keyword arguments:=========   =======================================================Keyword     Description=========   =======================================================gamma       gamma factor to emphasise either low intensity values(gamma < 1), or high intensity values (gamma > 1);defaults to 1.0.s           the start color; defaults to 0.5 (i.e. purple).r           the number of r,g,b rotations in color that are madefrom the start to the end of the color scheme; defaultsto -1.5 (i.e. -> B -> G -> R -> B).h           the hue parameter which controls how saturated thecolors are. If this parameter is zero then the colorscheme is purely a greyscale; defaults to 1.0.=========   ======================================================="""def get_color_function(p0, p1):def color(x):# Apply gamma factor to emphasise low or high intensity valuesxg = 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) / 2phi = 2 * np.pi * (s / 3 + r * x)return xg + a * (p0 * np.cos(phi) + p1 * np.sin(phi))return colorreturn {'red': get_color_function(-0.14861, 1.78277),'green': get_color_function(-0.29227, -0.90649),'blue': get_color_function(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
gfunc = {0: lambda x: 0,1: lambda x: 0.5,2: lambda x: 1,3: lambda x: x,4: lambda x: x ** 2,5: lambda x: x ** 3,6: lambda x: x ** 4,7: lambda x: np.sqrt(x),8: lambda x: np.sqrt(np.sqrt(x)),9: lambda x: np.sin(x * np.pi / 2),10: lambda x: np.cos(x * np.pi / 2),11: lambda x: np.abs(x - 0.5),12: lambda x: (2 * x - 1) ** 2,13: lambda x: np.sin(x * np.pi),14: lambda x: np.abs(np.cos(x * np.pi)),15: lambda x: np.sin(x * 2 * np.pi),16: lambda x: np.cos(x * 2 * np.pi),17: lambda x: np.abs(np.sin(x * 2 * np.pi)),18: lambda x: np.abs(np.cos(x * 2 * np.pi)),19: lambda x: np.abs(np.sin(x * 4 * np.pi)),20: lambda x: np.abs(np.cos(x * 4 * np.pi)),21: lambda x: 3 * x,22: lambda x: 3 * x - 1,23: lambda x: 3 * x - 2,24: lambda x: np.abs(3 * x - 1),25: lambda x: np.abs(3 * x - 2),26: lambda x: (3 * x - 1) / 2,27: lambda x: (3 * x - 2) / 2,28: lambda x: np.abs((3 * x - 1) / 2),29: lambda x: np.abs((3 * x - 2) / 2),30: lambda x: x / 0.32 - 0.78125,31: lambda x: 2 * x - 0.84,32: lambda x: gfunc32(x),33: lambda x: np.abs(2 * x - 0.5),34: lambda x: 2 * x,35: lambda x: 2 * x - 0.5,36: lambda x: 2 * x - 1.
}def gfunc32(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] + 1.84m = (x >= 0.92)ret[m] = x[m] / 0.08 - 11.5return ret_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., 0, 0), (0.35, 0, 0), (0.66, 1, 1), (0.89, 1, 1),(1, 0.5, 0.5)),'green': ((0., 0, 0), (0.125, 0, 0), (0.375, 1, 1), (0.64, 1, 1),(0.91, 0, 0), (1, 0, 0)),'blue':  ((0., 0.5, 0.5), (0.11, 1, 1), (0.34, 1, 1),(0.65, 0, 0), (1, 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)._Accent_data = {'blue': [(0.0, 0.49803921580314636,
0.49803921580314636), (0.14285714285714285, 0.83137255907058716,
0.83137255907058716), (0.2857142857142857, 0.52549022436141968,
0.52549022436141968), (0.42857142857142855, 0.60000002384185791,
0.60000002384185791), (0.5714285714285714, 0.69019609689712524,
0.69019609689712524), (0.7142857142857143, 0.49803921580314636,
0.49803921580314636), (0.8571428571428571, 0.090196080505847931,
0.090196080505847931), (1.0, 0.40000000596046448,
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(0.80000000000000004, 0.64705884456634521, 0.64705884456634521),
(0.90000000000000002, 0.74117648601531982, 0.74117648601531982), (1.0,
0.63529413938522339, 0.63529413938522339)],'green': [(0.0, 0.0039215688593685627, 0.0039215688593685627),(0.10000000000000001, 0.24313725531101227, 0.24313725531101227),(0.20000000000000001, 0.42745098471641541, 0.42745098471641541),(0.29999999999999999, 0.68235296010971069, 0.68235296010971069),(0.40000000000000002, 0.87843137979507446, 0.87843137979507446),(0.5, 1.0, 1.0), (0.59999999999999998, 0.96078431606292725,0.96078431606292725), (0.69999999999999996, 0.86666667461395264,0.86666667461395264), (0.80000000000000004, 0.7607843279838562,0.7607843279838562), (0.90000000000000002, 0.53333336114883423,0.53333336114883423), (1.0, 0.30980393290519714,0.30980393290519714)],'red': [(0.0, 0.61960786581039429, 0.61960786581039429),(0.10000000000000001, 0.83529412746429443, 0.83529412746429443),(0.20000000000000001, 0.95686274766921997, 0.95686274766921997),(0.29999999999999999, 0.99215686321258545, 0.99215686321258545),(0.40000000000000002, 0.99607843160629272, 0.99607843160629272),(0.5, 1.0, 1.0), (0.59999999999999998, 0.90196079015731812,0.90196079015731812), (0.69999999999999996, 0.67058825492858887,0.67058825492858887), (0.80000000000000004, 0.40000000596046448,0.40000000596046448), (0.90000000000000002, 0.19607843458652496,0.19607843458652496), (1.0, 0.36862745881080627,0.36862745881080627)]}_YlGn_data = {'blue': [(0.0, 0.89803922176361084,
0.89803922176361084), (0.125, 0.72549021244049072,
0.72549021244049072), (0.25, 0.63921570777893066,
0.63921570777893066), (0.375, 0.55686277151107788,
0.55686277151107788), (0.5, 0.47450980544090271, 0.47450980544090271),
(0.625, 0.364705890417099, 0.364705890417099), (0.75,
0.26274511218070984, 0.26274511218070984), (0.875,
0.21568627655506134, 0.21568627655506134), (1.0, 0.16078431904315948,
0.16078431904315948)],'green': [(0.0, 1.0, 1.0), (0.125, 0.98823529481887817,0.98823529481887817), (0.25, 0.94117647409439087,0.94117647409439087), (0.375, 0.86666667461395264,0.86666667461395264), (0.5, 0.7764706015586853,0.7764706015586853), (0.625, 0.67058825492858887,0.67058825492858887), (0.75, 0.51764708757400513,0.51764708757400513), (0.875, 0.40784314274787903,0.40784314274787903), (1.0, 0.27058824896812439,0.27058824896812439)],'red': [(0.0, 1.0, 1.0), (0.125, 0.9686274528503418,0.9686274528503418), (0.25, 0.85098040103912354,0.85098040103912354), (0.375, 0.67843139171600342,0.67843139171600342), (0.5, 0.47058823704719543,0.47058823704719543), (0.625, 0.25490197539329529,0.25490197539329529), (0.75, 0.13725490868091583,0.13725490868091583), (0.875, 0.0, 0.0), (1.0, 0.0, 0.0)]}_YlGnBu_data = {'blue': [(0.0, 0.85098040103912354,
0.85098040103912354), (0.125, 0.69411766529083252,
0.69411766529083252), (0.25, 0.70588237047195435,
0.70588237047195435), (0.375, 0.73333334922790527,
0.73333334922790527), (0.5, 0.76862746477127075, 0.76862746477127075),
(0.625, 0.75294119119644165, 0.75294119119644165), (0.75,
0.65882354974746704, 0.65882354974746704), (0.875,
0.58039218187332153, 0.58039218187332153), (1.0, 0.34509804844856262,
0.34509804844856262)],'green': [(0.0, 1.0, 1.0), (0.125, 0.97254902124404907,0.97254902124404907), (0.25, 0.91372549533843994,0.91372549533843994), (0.375, 0.80392158031463623,0.80392158031463623), (0.5, 0.7137255072593689,0.7137255072593689), (0.625, 0.56862747669219971,0.56862747669219971), (0.75, 0.36862745881080627,0.36862745881080627), (0.875, 0.20392157137393951,0.20392157137393951), (1.0, 0.11372549086809158,0.11372549086809158)],'red': [(0.0, 1.0, 1.0), (0.125, 0.92941176891326904,0.92941176891326904), (0.25, 0.78039216995239258,0.78039216995239258), (0.375, 0.49803921580314636,0.49803921580314636), (0.5, 0.25490197539329529,0.25490197539329529), (0.625, 0.11372549086809158,0.11372549086809158), (0.75, 0.13333334028720856,0.13333334028720856), (0.875, 0.14509804546833038,0.14509804546833038), (1.0, 0.031372550874948502,0.031372550874948502)]}_YlOrBr_data = {'blue': [(0.0, 0.89803922176361084,
0.89803922176361084), (0.125, 0.73725491762161255,
0.73725491762161255), (0.25, 0.56862747669219971,
0.56862747669219971), (0.375, 0.30980393290519714,
0.30980393290519714), (0.5, 0.16078431904315948, 0.16078431904315948),
(0.625, 0.078431375324726105, 0.078431375324726105), (0.75,
0.0078431377187371254, 0.0078431377187371254), (0.875,
0.015686275437474251, 0.015686275437474251), (1.0,
0.023529412224888802, 0.023529412224888802)],'green': [(0.0, 1.0, 1.0), (0.125, 0.9686274528503418,0.9686274528503418), (0.25, 0.89019608497619629,0.89019608497619629), (0.375, 0.76862746477127075,0.76862746477127075), (0.5, 0.60000002384185791,0.60000002384185791), (0.625, 0.43921568989753723,0.43921568989753723), (0.75, 0.29803922772407532,0.29803922772407532), (0.875, 0.20392157137393951,0.20392157137393951), (1.0, 0.14509804546833038,0.14509804546833038)],'red': [(0.0, 1.0, 1.0), (0.125, 1.0, 1.0), (0.25,0.99607843160629272, 0.99607843160629272), (0.375,0.99607843160629272, 0.99607843160629272), (0.5,0.99607843160629272, 0.99607843160629272), (0.625,0.92549020051956177, 0.92549020051956177), (0.75,0.80000001192092896, 0.80000001192092896), (0.875,0.60000002384185791, 0.60000002384185791), (1.0,0.40000000596046448, 0.40000000596046448)]}_YlOrRd_data = {'blue': [(0.0, 0.80000001192092896,
0.80000001192092896), (0.125, 0.62745100259780884,
0.62745100259780884), (0.25, 0.46274510025978088,
0.46274510025978088), (0.375, 0.29803922772407532,
0.29803922772407532), (0.5, 0.23529411852359772, 0.23529411852359772),
(0.625, 0.16470588743686676, 0.16470588743686676), (0.75,
0.10980392247438431, 0.10980392247438431), (0.875,
0.14901961386203766, 0.14901961386203766), (1.0, 0.14901961386203766,
0.14901961386203766)],'green': [(0.0, 1.0, 1.0), (0.125, 0.92941176891326904,0.92941176891326904), (0.25, 0.85098040103912354,0.85098040103912354), (0.375, 0.69803923368453979,0.69803923368453979), (0.5, 0.55294120311737061,0.55294120311737061), (0.625, 0.30588236451148987,0.30588236451148987), (0.75, 0.10196078568696976,0.10196078568696976), (0.875, 0.0, 0.0), (1.0, 0.0, 0.0)],'red': [(0.0, 1.0, 1.0), (0.125, 1.0, 1.0), (0.25,0.99607843160629272, 0.99607843160629272), (0.375,0.99607843160629272, 0.99607843160629272), (0.5,0.99215686321258545, 0.99215686321258545), (0.625,0.98823529481887817, 0.98823529481887817), (0.75,0.89019608497619629, 0.89019608497619629), (0.875,0.74117648601531982, 0.74117648601531982), (1.0,0.50196081399917603, 0.50196081399917603)]}# The next 7 palettes are from the Yorick scientific visalisation 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],
}_gist_heat_data = {'red': lambda x: 1.5 * x,'green': lambda x: 2 * x - 1,'blue': lambda x: 4 * x - 3,
}_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))
}_gist_yarg_data = {'red': lambda x: 1 - x,'green': lambda x: 1 - x,'blue': lambda x: 1 - x,
}# This bipolar color map was generated from CoolWarmFloat33.csv of
# "Diverging Color Maps for Scientific Visualization" by Kenneth Moreland.
# <http://www.kennethmoreland.com/color-maps/>
_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)],
}datad = {'afmhot': _afmhot_data,'autumn': _autumn_data,'bone':   _bone_data,'binary': _binary_data,'bwr':    _bwr_data,'brg':    _brg_data,'CMRmap': _CMRmap_data,'cool':   _cool_data,'copper': _copper_data,'cubehelix': _cubehelix_data,'flag':   _flag_data,'gnuplot': _gnuplot_data,'gnuplot2': _gnuplot2_data,'gray':  _gray_data,'hot':    _hot_data,'hsv':    _hsv_data,'jet':   _jet_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,'nipy_spectral': _nipy_spectral_data,'spectral': _nipy_spectral_data, # alias for backward compatibility}datad['Accent'] = _Accent_data
datad['Blues'] = _Blues_data
datad['BrBG'] = _BrBG_data
datad['BuGn'] = _BuGn_data
datad['BuPu'] = _BuPu_data
datad['Dark2'] = _Dark2_data
datad['GnBu'] = _GnBu_data
datad['Greens'] = _Greens_data
datad['Greys'] = _Greys_data
datad['Oranges'] = _Oranges_data
datad['OrRd'] = _OrRd_data
datad['Paired'] = _Paired_data
datad['Pastel1'] = _Pastel1_data
datad['Pastel2'] = _Pastel2_data
datad['PiYG'] = _PiYG_data
datad['PRGn'] = _PRGn_data
datad['PuBu'] = _PuBu_data
datad['PuBuGn'] = _PuBuGn_data
datad['PuOr'] = _PuOr_data
datad['PuRd'] = _PuRd_data
datad['Purples'] = _Purples_data
datad['RdBu'] = _RdBu_data
datad['RdGy'] = _RdGy_data
datad['RdPu'] = _RdPu_data
datad['RdYlBu'] = _RdYlBu_data
datad['RdYlGn'] = _RdYlGn_data
datad['Reds'] = _Reds_data
datad['Set1'] = _Set1_data
datad['Set2'] = _Set2_data
datad['Set3'] = _Set3_data
datad['Spectral'] = _Spectral_data
datad['YlGn'] = _YlGn_data
datad['YlGnBu'] = _YlGnBu_data
datad['YlOrBr'] = _YlOrBr_data
datad['YlOrRd'] = _YlOrRd_data
datad['gist_earth'] = _gist_earth_data
datad['gist_gray'] = _gist_gray_data
datad['gist_heat'] = _gist_heat_data
datad['gist_ncar'] = _gist_ncar_data
datad['gist_rainbow'] = _gist_rainbow_data
datad['gist_stern'] = _gist_stern_data
datad['gist_yarg'] = _gist_yarg_data
datad['coolwarm'] = _coolwarm_data
datad['Wistia'] = _wistia_data

  阅读以上源码可知，有以下颜色映射模式可选：

Possible values are: Accent, Accent_r, Blues, Blues_r, BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens, Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy, RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn, autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cool, cool_r, coolwarm, coolwarm_r, copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat, gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r, gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma, magma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, seismic, seismic_r, spectral, spectral_r, spring, spring_r, summer, summer_r, terrain, terrain_r, viridis, viridis_r, winter, winter_r

  其中，我最喜欢的是 ‘coolwarm’ 风格类型。

---

---

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