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/ _cm.py
"""
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 color maps."""
# 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. 3-D 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.
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 made
from the start to the end of the color scheme; defaults
to -1.5 (i.e. -> B -> G -> R -> B).
h the hue parameter which controls how saturated the
colors are. If this parameter is zero then the color
scheme is purely a greyscale; defaults to 1.0.
========= =======================================================
"""
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., 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).
# 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 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)],
}
# 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},
}