python-chaco 4.5.0-1 / usr / lib / python2.7 / dist-packages / chaco / default_colormaps.py

#------------------------------------------------------------------------------
# Copyright (c) 2005-2014, Enthought, Inc.
# All rights reserved.
#
# This software is provided without warranty under the terms of the BSD
# license included in LICENSE.txt and may be redistributed only
# under the conditions described in the aforementioned license.  The license
# is also available online at http://www.enthought.com/licenses/BSD.txt
# Thanks for using Enthought open source!
#
# Portions of this software are:
# Copyright (c) 2002-2004 John D. Hunter
# All Rights Reserved.
#------------------------------------------------------------------------------

"""
A collection of pre-defined colormap generator functions.

Each of the functions can be called with *min_value* and *max_value* parameters.
In that case, they produce a Colormap which linearly maps over the specified
range and has the color palette indicated by the function name.
"""

from numpy import array

# Local imports.
from .color_mapper import ColorMapper
from .colormap_generators import generate_cubehelix_palette, \
    generate_diverging_palette

# The colormaps will be added to this at the end of the file.
__all__ = ['reverse', 'center', 'color_map_functions', 'color_map_dict',
    'color_map_name_dict']


# Utility functions.

def reverse(func):
    """ Modify a colormap factory to reverse the color sequence

    Parameters
    ----------
    func : callable
        A colormap factory function like those provided in this module.

    Returns
    -------
    cmap : callable
        A wrapper factory function that can be used in place of the original
        factory function.
    """
    def cmap(range, **traits):
        cm = func(range, **traits)
        cm.reverse_colormap()
        return cm

    # Look a little like the wrapped function.
    cmap.__name__ = 'reversed_' + func.__name__
    if func.__doc__ is not None:
        cmap.__doc__ = 'Reversed: ' + func.__doc__
    else:
        cmap.__doc__ = 'Reversed: ' + func.__name__
    return cmap

def center(func, center=0.0):
    """ Modify the range of a colormap to be centered around the given value.

    For example, when passed a DataRange1D(low=-0.5, high=1.0), a colormap would
    usually have its lowest color at -0.5 and its highest at 1.0. Some colormaps
    are designed such that the middle color is special. Using this modifier, the
    example range would be modified to -1.0 and 1.0 to make 0.0 correspond with
    the middle color.

    Parameters
    ----------
    func : callable
        A colormap factory function like those provided in this module.
    center : float, optional
        The center value in dataspace.

    Returns
    -------
    cmap : callable
        A wrapper factory function that can be used in place of the original
        factory function.
    """
    def cmap(range, **traits):
        maxdev = max(abs(range.low - center), abs(range.high - center))
        range = range.clone_traits()
        range.low = center - maxdev
        range.high = center + maxdev
        return func(range, **traits)

    # Look a little like the wrapped function.
    cmap.__name__ = 'centered_' + func.__name__
    if func.__doc__ is not None:
        cmap.__doc__ = 'Centered: ' + func.__doc__
    else:
        cmap.__doc__ = 'Centered: ' + func.__name__
    return cmap

def fix(func, range):
    """ Apply the given range to a colormap rather than accept the one coming
    from the data.

    This is useful for colormaps intrinsically tied to a given scale, like
    bathymetry/elevation colormaps for GIS or for working around Chaco to
    implement custom behavior.

    Paramaters
    ----------
    func : callable
        A colormap factory function like those provided in this module.
    range : DataRange1D or (low, high) tuple.
        The range to apply.

    Returns
    -------
    cmap : callable
        A wrapper factory function that can be used in place of the original
        factory function.
    """
    if isinstance(range, tuple):
        # Adapt tuples to DataRange1D for convenience.
        from chaco.data_range_1d import DataRange1D
        range = DataRange1D(low=range[0], high=range[1])

    def cmap(dummy_range, **traits):
        # Use the range given to the fix() function, not the cmap() function.
        return func(range, **traits)

    # Look a little like the wrapped function.
    cmap.__name__ = 'fixed_' + func.__name__
    if func.__doc__ is not None:
        cmap.__doc__ = 'Fixed: ' + func.__doc__
    else:
        cmap.__doc__ = 'Fixed: ' + func.__name__
    return cmap


# Colormaps.


def autumn(range, **traits):
    """ Generator function for the 'autumn' colormap. """

    _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.))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)


def bone(range, **traits):
    """ Generator function for the 'bone' colormap. """

    _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))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def cool(range, **traits):
    """ Generator function for the 'cool' colormap. """

    _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.))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def copper(range, **traits):
    """ Generator function for the 'copper' colormap. """

    _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))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def flag(range, **traits):
    """ Generator function for the 'flag' colormap. """

    _data = {'red':   ((0., 1., 1.),(0.015873, 1.000000, 1.000000),
                       (0.031746, 0.000000, 0.000000),(0.047619, 0.000000, 0.000000),
                       (0.063492, 1.000000, 1.000000),(0.079365, 1.000000, 1.000000),
                       (0.095238, 0.000000, 0.000000),(0.111111, 0.000000, 0.000000),
                       (0.126984, 1.000000, 1.000000),(0.142857, 1.000000, 1.000000),
                       (0.158730, 0.000000, 0.000000),(0.174603, 0.000000, 0.000000),
                       (0.190476, 1.000000, 1.000000),(0.206349, 1.000000, 1.000000),
                       (0.222222, 0.000000, 0.000000),(0.238095, 0.000000, 0.000000),
                       (0.253968, 1.000000, 1.000000),(0.269841, 1.000000, 1.000000),
                       (0.285714, 0.000000, 0.000000),(0.301587, 0.000000, 0.000000),
                       (0.317460, 1.000000, 1.000000),(0.333333, 1.000000, 1.000000),
                       (0.349206, 0.000000, 0.000000),(0.365079, 0.000000, 0.000000),
                       (0.380952, 1.000000, 1.000000),(0.396825, 1.000000, 1.000000),
                       (0.412698, 0.000000, 0.000000),(0.428571, 0.000000, 0.000000),
                       (0.444444, 1.000000, 1.000000),(0.460317, 1.000000, 1.000000),
                       (0.476190, 0.000000, 0.000000),(0.492063, 0.000000, 0.000000),
                       (0.507937, 1.000000, 1.000000),(0.523810, 1.000000, 1.000000),
                       (0.539683, 0.000000, 0.000000),(0.555556, 0.000000, 0.000000),
                       (0.571429, 1.000000, 1.000000),(0.587302, 1.000000, 1.000000),
                       (0.603175, 0.000000, 0.000000),(0.619048, 0.000000, 0.000000),
                       (0.634921, 1.000000, 1.000000),(0.650794, 1.000000, 1.000000),
                       (0.666667, 0.000000, 0.000000),(0.682540, 0.000000, 0.000000),
                       (0.698413, 1.000000, 1.000000),(0.714286, 1.000000, 1.000000),
                       (0.730159, 0.000000, 0.000000),(0.746032, 0.000000, 0.000000),
                       (0.761905, 1.000000, 1.000000),(0.777778, 1.000000, 1.000000),
                       (0.793651, 0.000000, 0.000000),(0.809524, 0.000000, 0.000000),
                       (0.825397, 1.000000, 1.000000),(0.841270, 1.000000, 1.000000),
                       (0.857143, 0.000000, 0.000000),(0.873016, 0.000000, 0.000000),
                       (0.888889, 1.000000, 1.000000),(0.904762, 1.000000, 1.000000),
                       (0.920635, 0.000000, 0.000000),(0.936508, 0.000000, 0.000000),
                       (0.952381, 1.000000, 1.000000),(0.968254, 1.000000, 1.000000),
                       (0.984127, 0.000000, 0.000000),(1.0, 0., 0.)),
             'green': ((0., 0., 0.),(0.015873, 1.000000, 1.000000),
                       (0.031746, 0.000000, 0.000000),(0.063492, 0.000000, 0.000000),
                       (0.079365, 1.000000, 1.000000),(0.095238, 0.000000, 0.000000),
                       (0.126984, 0.000000, 0.000000),(0.142857, 1.000000, 1.000000),
                       (0.158730, 0.000000, 0.000000),(0.190476, 0.000000, 0.000000),
                       (0.206349, 1.000000, 1.000000),(0.222222, 0.000000, 0.000000),
                       (0.253968, 0.000000, 0.000000),(0.269841, 1.000000, 1.000000),
                       (0.285714, 0.000000, 0.000000),(0.317460, 0.000000, 0.000000),
                       (0.333333, 1.000000, 1.000000),(0.349206, 0.000000, 0.000000),
                       (0.380952, 0.000000, 0.000000),(0.396825, 1.000000, 1.000000),
                       (0.412698, 0.000000, 0.000000),(0.444444, 0.000000, 0.000000),
                       (0.460317, 1.000000, 1.000000),(0.476190, 0.000000, 0.000000),
                       (0.507937, 0.000000, 0.000000),(0.523810, 1.000000, 1.000000),
                       (0.539683, 0.000000, 0.000000),(0.571429, 0.000000, 0.000000),
                       (0.587302, 1.000000, 1.000000),(0.603175, 0.000000, 0.000000),
                       (0.634921, 0.000000, 0.000000),(0.650794, 1.000000, 1.000000),
                       (0.666667, 0.000000, 0.000000),(0.698413, 0.000000, 0.000000),
                       (0.714286, 1.000000, 1.000000),(0.730159, 0.000000, 0.000000),
                       (0.761905, 0.000000, 0.000000),(0.777778, 1.000000, 1.000000),
                       (0.793651, 0.000000, 0.000000),(0.825397, 0.000000, 0.000000),
                        (0.841270, 1.000000, 1.000000),(0.857143, 0.000000, 0.000000),
                       (0.888889, 0.000000, 0.000000),(0.904762, 1.000000, 1.000000),
                       (0.920635, 0.000000, 0.000000),(0.952381, 0.000000, 0.000000),
                       (0.968254, 1.000000, 1.000000),(0.984127, 0.000000, 0.000000),
                       (1.0, 0., 0.)),
             'blue':  ((0., 0., 0.),(0.015873, 1.000000, 1.000000),
                       (0.031746, 1.000000, 1.000000),(0.047619, 0.000000, 0.000000),
                       (0.063492, 0.000000, 0.000000),(0.079365, 1.000000, 1.000000),
                       (0.095238, 1.000000, 1.000000),(0.111111, 0.000000, 0.000000),
                       (0.126984, 0.000000, 0.000000),(0.142857, 1.000000, 1.000000),
                       (0.158730, 1.000000, 1.000000),(0.174603, 0.000000, 0.000000),
                       (0.190476, 0.000000, 0.000000),(0.206349, 1.000000, 1.000000),
                       (0.222222, 1.000000, 1.000000),(0.238095, 0.000000, 0.000000),
                       (0.253968, 0.000000, 0.000000),(0.269841, 1.000000, 1.000000),
                       (0.285714, 1.000000, 1.000000),(0.301587, 0.000000, 0.000000),
                       (0.317460, 0.000000, 0.000000),(0.333333, 1.000000, 1.000000),
                       (0.349206, 1.000000, 1.000000),(0.365079, 0.000000, 0.000000),
                       (0.380952, 0.000000, 0.000000),(0.396825, 1.000000, 1.000000),
                       (0.412698, 1.000000, 1.000000),(0.428571, 0.000000, 0.000000),
                       (0.444444, 0.000000, 0.000000),(0.460317, 1.000000, 1.000000),
                       (0.476190, 1.000000, 1.000000),(0.492063, 0.000000, 0.000000),
                       (0.507937, 0.000000, 0.000000),(0.523810, 1.000000, 1.000000),
                       (0.539683, 1.000000, 1.000000),(0.555556, 0.000000, 0.000000),
                       (0.571429, 0.000000, 0.000000),(0.587302, 1.000000, 1.000000),
                       (0.603175, 1.000000, 1.000000),(0.619048, 0.000000, 0.000000),
                       (0.634921, 0.000000, 0.000000),(0.650794, 1.000000, 1.000000),
                       (0.666667, 1.000000, 1.000000),(0.682540, 0.000000, 0.000000),
                       (0.698413, 0.000000, 0.000000),(0.714286, 1.000000, 1.000000),
                       (0.730159, 1.000000, 1.000000),(0.746032, 0.000000, 0.000000),
                       (0.761905, 0.000000, 0.000000),(0.777778, 1.000000, 1.000000),
                       (0.793651, 1.000000, 1.000000),(0.809524, 0.000000, 0.000000),
                       (0.825397, 0.000000, 0.000000),(0.841270, 1.000000, 1.000000),
                       (0.857143, 1.000000, 1.000000),(0.873016, 0.000000, 0.000000),
                       (0.888889, 0.000000, 0.000000),(0.904762, 1.000000, 1.000000),
                       (0.920635, 1.000000, 1.000000),(0.936508, 0.000000, 0.000000),
                       (0.952381, 0.000000, 0.000000),(0.968254, 1.000000, 1.000000),
                       (0.984127, 1.000000, 1.000000),(1.0, 0., 0.))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def gray(range, **traits):
    """ Generator function for the 'gray' colormap. """

    _data =  {'red':   ((0., 0, 0), (1., 1, 1)),
              'green': ((0., 0, 0), (1., 1, 1)),
              'blue':  ((0., 0, 0), (1., 1, 1))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def yarg(range, **traits):
    """ Generator function for the 'yarg' colormap. """

    _data =  {'red':   ((0., 1, 1), (1., 0, 0)),
              'green': ((0., 1, 1), (1., 0, 0)),
              'blue':  ((0., 1, 1), (1., 0, 0))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def hot(range, **traits):
    """ Generator function for the 'hot' colormap. """

    _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))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def hsv(range, **traits):
    """ Generator function for the 'hsv' colormap. """

    _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))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def jet(range, **traits):
    """ Generator function for the 'jet' colormap. """

    _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))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def pink(range, **traits):
    """ Generator function for the 'pink' colormap. """

    _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))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def prism(range, **traits):
    """ Generator function for the 'prism' colormap. """

    _data = {'red':   ((0., 1., 1.),(0.031746, 1.000000, 1.000000),
                       (0.047619, 0.000000, 0.000000),(0.063492, 0.000000, 0.000000),
                       (0.079365, 0.666667, 0.666667),(0.095238, 1.000000, 1.000000),
                       (0.126984, 1.000000, 1.000000),(0.142857, 0.000000, 0.000000),
                       (0.158730, 0.000000, 0.000000),(0.174603, 0.666667, 0.666667),
                       (0.190476, 1.000000, 1.000000),(0.222222, 1.000000, 1.000000),
                       (0.238095, 0.000000, 0.000000),(0.253968, 0.000000, 0.000000),
                       (0.269841, 0.666667, 0.666667),(0.285714, 1.000000, 1.000000),
                       (0.317460, 1.000000, 1.000000),(0.333333, 0.000000, 0.000000),
                       (0.349206, 0.000000, 0.000000),(0.365079, 0.666667, 0.666667),
                       (0.380952, 1.000000, 1.000000),(0.412698, 1.000000, 1.000000),
                       (0.428571, 0.000000, 0.000000),(0.444444, 0.000000, 0.000000),
                       (0.460317, 0.666667, 0.666667),(0.476190, 1.000000, 1.000000),
                       (0.507937, 1.000000, 1.000000),(0.523810, 0.000000, 0.000000),
                       (0.539683, 0.000000, 0.000000),(0.555556, 0.666667, 0.666667),
                       (0.571429, 1.000000, 1.000000),(0.603175, 1.000000, 1.000000),
                       (0.619048, 0.000000, 0.000000),(0.634921, 0.000000, 0.000000),
                       (0.650794, 0.666667, 0.666667),(0.666667, 1.000000, 1.000000),
                       (0.698413, 1.000000, 1.000000),(0.714286, 0.000000, 0.000000),
                       (0.730159, 0.000000, 0.000000),(0.746032, 0.666667, 0.666667),
                       (0.761905, 1.000000, 1.000000),(0.793651, 1.000000, 1.000000),
                       (0.809524, 0.000000, 0.000000),(0.825397, 0.000000, 0.000000),
                       (0.841270, 0.666667, 0.666667),(0.857143, 1.000000, 1.000000),
                       (0.888889, 1.000000, 1.000000),(0.904762, 0.000000, 0.000000),
                       (0.920635, 0.000000, 0.000000),(0.936508, 0.666667, 0.666667),
                       (0.952381, 1.000000, 1.000000),(0.984127, 1.000000, 1.000000),
                       (1.0, 0.0, 0.0)),
             'green': ((0., 0., 0.),(0.031746, 1.000000, 1.000000),
                       (0.047619, 1.000000, 1.000000),(0.063492, 0.000000, 0.000000),
                       (0.095238, 0.000000, 0.000000),(0.126984, 1.000000, 1.000000),
                       (0.142857, 1.000000, 1.000000),(0.158730, 0.000000, 0.000000),
                       (0.190476, 0.000000, 0.000000),(0.222222, 1.000000, 1.000000),
                       (0.238095, 1.000000, 1.000000),(0.253968, 0.000000, 0.000000),
                       (0.285714, 0.000000, 0.000000),(0.317460, 1.000000, 1.000000),
                       (0.333333, 1.000000, 1.000000),(0.349206, 0.000000, 0.000000),
                       (0.380952, 0.000000, 0.000000),(0.412698, 1.000000, 1.000000),
                       (0.428571, 1.000000, 1.000000),(0.444444, 0.000000, 0.000000),
                       (0.476190, 0.000000, 0.000000),(0.507937, 1.000000, 1.000000),
                       (0.523810, 1.000000, 1.000000),(0.539683, 0.000000, 0.000000),
                       (0.571429, 0.000000, 0.000000),(0.603175, 1.000000, 1.000000),
                       (0.619048, 1.000000, 1.000000),(0.634921, 0.000000, 0.000000),
                       (0.666667, 0.000000, 0.000000),(0.698413, 1.000000, 1.000000),
                       (0.714286, 1.000000, 1.000000),(0.730159, 0.000000, 0.000000),
                       (0.761905, 0.000000, 0.000000),(0.793651, 1.000000, 1.000000),
                       (0.809524, 1.000000, 1.000000),(0.825397, 0.000000, 0.000000),
                       (0.857143, 0.000000, 0.000000),(0.888889, 1.000000, 1.000000),
                       (0.904762, 1.000000, 1.000000),(0.920635, 0.000000, 0.000000),
                       (0.952381, 0.000000, 0.000000),(0.984127, 1.000000, 1.000000),
                       (1.0, 1.0, 1.0)),
             'blue':  ((0., 0., 0.),(0.047619, 0.000000, 0.000000),
                       (0.063492, 1.000000, 1.000000),(0.079365, 1.000000, 1.000000),
                       (0.095238, 0.000000, 0.000000),(0.142857, 0.000000, 0.000000),
                       (0.158730, 1.000000, 1.000000),(0.174603, 1.000000, 1.000000),
                       (0.190476, 0.000000, 0.000000),(0.238095, 0.000000, 0.000000),
                       (0.253968, 1.000000, 1.000000),(0.269841, 1.000000, 1.000000),
                       (0.285714, 0.000000, 0.000000),(0.333333, 0.000000, 0.000000),
                       (0.349206, 1.000000, 1.000000),(0.365079, 1.000000, 1.000000),
                       (0.380952, 0.000000, 0.000000),(0.428571, 0.000000, 0.000000),
                       (0.444444, 1.000000, 1.000000),(0.460317, 1.000000, 1.000000),
                       (0.476190, 0.000000, 0.000000),(0.523810, 0.000000, 0.000000),
                       (0.539683, 1.000000, 1.000000),(0.555556, 1.000000, 1.000000),
                       (0.571429, 0.000000, 0.000000),(0.619048, 0.000000, 0.000000),
                       (0.634921, 1.000000, 1.000000),(0.650794, 1.000000, 1.000000),
                       (0.666667, 0.000000, 0.000000),(0.714286, 0.000000, 0.000000),
                       (0.730159, 1.000000, 1.000000),(0.746032, 1.000000, 1.000000),
                       (0.761905, 0.000000, 0.000000),(0.809524, 0.000000, 0.000000),
                       (0.825397, 1.000000, 1.000000),(0.841270, 1.000000, 1.000000),
                       (0.857143, 0.000000, 0.000000),(0.904762, 0.000000, 0.000000),
                       (0.920635, 1.000000, 1.000000),(0.936508, 1.000000, 1.000000),
                       (0.952381, 0.000000, 0.000000),(1.0, 0.0, 0.0))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def spring(range, **traits):
    """ Generator function for the 'spring' colormap. """

    _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))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def summer(range, **traits):
    """ Generator function for the 'summer' colormap. """

    _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))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def winter(range, **traits):
    """ Generator function for the 'winter' colormap. """

    _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))}

    return ColorMapper.from_segment_map(_data, range=range, **traits)

def cw1_004(range, **traits):
    """ Generator function for the Crumblingwalls cw1-004 gradient """

    colors = array([(0.7176,0.6980,0.6118),
                  (0.8000,0.5373,0.7059),
                  (0.2510,0.4588,0.4902),
                  (0.0588,0.3176,0.5137)])

    return ColorMapper.from_palette_array(colors, range=range, **traits)

def cw1_005(range, **traits):
    """ Generator function for the Crumblingwalls cw1-005 gradient """
    colors = array([(0.7059,0.1686,0.0980),
                    (0.7961,0.5176,0.2039),
                    (0.2863,0.3255,0.1294)])

    return ColorMapper.from_palette_array(colors, range=range, **traits)

def cw1_006(range, **traits):
    """ Generator function for the Crumblingwalls cw1-006 gradient """

    colors = array([(0.4275,0.2824,0.4667),
                    (0.2039,0.1843,0.4667),
                    (0.0863,0.4078,0.2078)])

    return ColorMapper.from_palette_array(colors, range=range, **traits)

def cw1_028(range, **traits):
    """ Generator function for the Crumblingwalls cw1-058 gradient """

    colors = array([(0.2275, 0.2275, 0.4784),
                    (0.3294, 0.5137, 0.8588),
                    (0.4078, 0.8471, 0.8510)])

    return ColorMapper.from_palette_array(colors, range=range, **traits)

def gmt_drywet(range, **traits):

    _data = {'red': ((0.00000,0.5255,0.5255),
                    (0.16670,0.9333,0.9333),
                    (0.33330,0.7059,0.7059),
                    (0.50000,0.1961,0.1961),
                    (0.66670,0.0471,0.0471),
                    (0.83330,0.1490,0.1490),
                    (1.00000,0.0314,0.0314)),

             'green': ((0.00000,0.3804,0.3804),
                    (0.16670,0.7804,0.7804),
                    (0.33330,0.9333,0.9333),
                    (0.50000,0.9333,0.9333),
                    (0.66670,0.4706,0.4706),
                    (0.83330,0.0039,0.0039),
                    (1.00000,0.2000,0.2000)),

             'blue': ((0.00000,0.1647,0.1647),
                    (0.16670,0.3922,0.3922),
                    (0.33330,0.5294,0.5294),
                    (0.50000,0.9216,0.9216),
                    (0.66670,0.9333,0.9333),
                    (0.83330,0.7176,0.7176),
                    (1.00000,0.4431,0.4431)) }

    return ColorMapper.from_segment_map(_data, range=range, **traits)


# The following colormaps come from ColorBrewer.
# Only the 'Sequential' and 'Diverging' colormaps and not the 'Qualitative'
# colormaps since Chaco currently does not implement qualtitative colormaps.

def Blues(range, **traits):
    """ Generator for the 'Blues' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.96862745098, 0.96862745098),
            (0.125, 0.870588235294, 0.870588235294),
            (0.25, 0.776470588235, 0.776470588235),
            (0.375, 0.619607843137, 0.619607843137),
            (0.5, 0.419607843137, 0.419607843137),
            (0.625, 0.258823529412, 0.258823529412),
            (0.75, 0.129411764706, 0.129411764706),
            (0.875, 0.0313725490196, 0.0313725490196),
            (1.0, 0.0313725490196, 0.0313725490196)],
        green = [(0.0, 0.98431372549, 0.98431372549),
            (0.125, 0.921568627451, 0.921568627451),
            (0.25, 0.858823529412, 0.858823529412),
            (0.375, 0.792156862745, 0.792156862745),
            (0.5, 0.682352941176, 0.682352941176),
            (0.625, 0.572549019608, 0.572549019608),
            (0.75, 0.443137254902, 0.443137254902),
            (0.875, 0.317647058824, 0.317647058824),
            (1.0, 0.188235294118, 0.188235294118)],
        blue = [(0.0, 1.0, 1.0),
            (0.125, 0.96862745098, 0.96862745098),
            (0.25, 0.937254901961, 0.937254901961),
            (0.375, 0.882352941176, 0.882352941176),
            (0.5, 0.839215686275, 0.839215686275),
            (0.625, 0.776470588235, 0.776470588235),
            (0.75, 0.709803921569, 0.709803921569),
            (0.875, 0.611764705882, 0.611764705882),
            (1.0, 0.419607843137, 0.419607843137)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def BrBG(range, **traits):
    """ Generator for the 'BrBG' colormap from ColorBrewer.

    This is a diverging colormap. It is good for data which is centered around
    a "special" value, like 0.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.329411764706, 0.329411764706),
            (0.1, 0.549019607843, 0.549019607843),
            (0.2, 0.749019607843, 0.749019607843),
            (0.3, 0.874509803922, 0.874509803922),
            (0.4, 0.964705882353, 0.964705882353),
            (0.5, 0.960784313725, 0.960784313725),
            (0.6, 0.780392156863, 0.780392156863),
            (0.7, 0.501960784314, 0.501960784314),
            (0.8, 0.207843137255, 0.207843137255),
            (0.9, 0.00392156862745, 0.00392156862745),
            (1.0, 0.0, 0.0)],
        green = [(0.0, 0.188235294118, 0.188235294118),
            (0.1, 0.317647058824, 0.317647058824),
            (0.2, 0.505882352941, 0.505882352941),
            (0.3, 0.760784313725, 0.760784313725),
            (0.4, 0.909803921569, 0.909803921569),
            (0.5, 0.960784313725, 0.960784313725),
            (0.6, 0.917647058824, 0.917647058824),
            (0.7, 0.803921568627, 0.803921568627),
            (0.8, 0.592156862745, 0.592156862745),
            (0.9, 0.4, 0.4),
            (1.0, 0.235294117647, 0.235294117647)],
        blue = [(0.0, 0.0196078431373, 0.0196078431373),
            (0.1, 0.0392156862745, 0.0392156862745),
            (0.2, 0.176470588235, 0.176470588235),
            (0.3, 0.490196078431, 0.490196078431),
            (0.4, 0.764705882353, 0.764705882353),
            (0.5, 0.960784313725, 0.960784313725),
            (0.6, 0.898039215686, 0.898039215686),
            (0.7, 0.756862745098, 0.756862745098),
            (0.8, 0.560784313725, 0.560784313725),
            (0.9, 0.36862745098, 0.36862745098),
            (1.0, 0.188235294118, 0.188235294118)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def BuGn(range, **traits):
    """ Generator for the 'BuGn' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.96862745098, 0.96862745098),
            (0.125, 0.898039215686, 0.898039215686),
            (0.25, 0.8, 0.8),
            (0.375, 0.6, 0.6),
            (0.5, 0.4, 0.4),
            (0.625, 0.254901960784, 0.254901960784),
            (0.75, 0.137254901961, 0.137254901961),
            (0.875, 0.0, 0.0),
            (1.0, 0.0, 0.0)],
        green = [(0.0, 0.988235294118, 0.988235294118),
            (0.125, 0.960784313725, 0.960784313725),
            (0.25, 0.925490196078, 0.925490196078),
            (0.375, 0.847058823529, 0.847058823529),
            (0.5, 0.760784313725, 0.760784313725),
            (0.625, 0.682352941176, 0.682352941176),
            (0.75, 0.545098039216, 0.545098039216),
            (0.875, 0.427450980392, 0.427450980392),
            (1.0, 0.266666666667, 0.266666666667)],
        blue = [(0.0, 0.992156862745, 0.992156862745),
            (0.125, 0.976470588235, 0.976470588235),
            (0.25, 0.901960784314, 0.901960784314),
            (0.375, 0.788235294118, 0.788235294118),
            (0.5, 0.643137254902, 0.643137254902),
            (0.625, 0.462745098039, 0.462745098039),
            (0.75, 0.270588235294, 0.270588235294),
            (0.875, 0.172549019608, 0.172549019608),
            (1.0, 0.105882352941, 0.105882352941)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def BuPu(range, **traits):
    """ Generator for the 'BuPu' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.96862745098, 0.96862745098),
            (0.125, 0.878431372549, 0.878431372549),
            (0.25, 0.749019607843, 0.749019607843),
            (0.375, 0.619607843137, 0.619607843137),
            (0.5, 0.549019607843, 0.549019607843),
            (0.625, 0.549019607843, 0.549019607843),
            (0.75, 0.533333333333, 0.533333333333),
            (0.875, 0.505882352941, 0.505882352941),
            (1.0, 0.301960784314, 0.301960784314)],
        green = [(0.0, 0.988235294118, 0.988235294118),
            (0.125, 0.925490196078, 0.925490196078),
            (0.25, 0.827450980392, 0.827450980392),
            (0.375, 0.737254901961, 0.737254901961),
            (0.5, 0.588235294118, 0.588235294118),
            (0.625, 0.419607843137, 0.419607843137),
            (0.75, 0.254901960784, 0.254901960784),
            (0.875, 0.0588235294118, 0.0588235294118),
            (1.0, 0.0, 0.0)],
        blue = [(0.0, 0.992156862745, 0.992156862745),
            (0.125, 0.956862745098, 0.956862745098),
            (0.25, 0.901960784314, 0.901960784314),
            (0.375, 0.854901960784, 0.854901960784),
            (0.5, 0.776470588235, 0.776470588235),
            (0.625, 0.694117647059, 0.694117647059),
            (0.75, 0.61568627451, 0.61568627451),
            (0.875, 0.486274509804, 0.486274509804),
            (1.0, 0.294117647059, 0.294117647059)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def GnBu(range, **traits):
    """ Generator for the 'GnBu' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.96862745098, 0.96862745098),
            (0.125, 0.878431372549, 0.878431372549),
            (0.25, 0.8, 0.8),
            (0.375, 0.658823529412, 0.658823529412),
            (0.5, 0.482352941176, 0.482352941176),
            (0.625, 0.305882352941, 0.305882352941),
            (0.75, 0.16862745098, 0.16862745098),
            (0.875, 0.0313725490196, 0.0313725490196),
            (1.0, 0.0313725490196, 0.0313725490196)],
        green = [(0.0, 0.988235294118, 0.988235294118),
            (0.125, 0.952941176471, 0.952941176471),
            (0.25, 0.921568627451, 0.921568627451),
            (0.375, 0.866666666667, 0.866666666667),
            (0.5, 0.8, 0.8),
            (0.625, 0.701960784314, 0.701960784314),
            (0.75, 0.549019607843, 0.549019607843),
            (0.875, 0.407843137255, 0.407843137255),
            (1.0, 0.250980392157, 0.250980392157)],
        blue = [(0.0, 0.941176470588, 0.941176470588),
            (0.125, 0.858823529412, 0.858823529412),
            (0.25, 0.772549019608, 0.772549019608),
            (0.375, 0.709803921569, 0.709803921569),
            (0.5, 0.76862745098, 0.76862745098),
            (0.625, 0.827450980392, 0.827450980392),
            (0.75, 0.745098039216, 0.745098039216),
            (0.875, 0.674509803922, 0.674509803922),
            (1.0, 0.505882352941, 0.505882352941)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def Greens(range, **traits):
    """ Generator for the 'Greens' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.96862745098, 0.96862745098),
            (0.125, 0.898039215686, 0.898039215686),
            (0.25, 0.780392156863, 0.780392156863),
            (0.375, 0.63137254902, 0.63137254902),
            (0.5, 0.454901960784, 0.454901960784),
            (0.625, 0.254901960784, 0.254901960784),
            (0.75, 0.137254901961, 0.137254901961),
            (0.875, 0.0, 0.0),
            (1.0, 0.0, 0.0)],
        green = [(0.0, 0.988235294118, 0.988235294118),
            (0.125, 0.960784313725, 0.960784313725),
            (0.25, 0.913725490196, 0.913725490196),
            (0.375, 0.850980392157, 0.850980392157),
            (0.5, 0.76862745098, 0.76862745098),
            (0.625, 0.670588235294, 0.670588235294),
            (0.75, 0.545098039216, 0.545098039216),
            (0.875, 0.427450980392, 0.427450980392),
            (1.0, 0.266666666667, 0.266666666667)],
        blue = [(0.0, 0.960784313725, 0.960784313725),
            (0.125, 0.878431372549, 0.878431372549),
            (0.25, 0.752941176471, 0.752941176471),
            (0.375, 0.607843137255, 0.607843137255),
            (0.5, 0.462745098039, 0.462745098039),
            (0.625, 0.364705882353, 0.364705882353),
            (0.75, 0.270588235294, 0.270588235294),
            (0.875, 0.172549019608, 0.172549019608),
            (1.0, 0.105882352941, 0.105882352941)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def Greys(range, **traits):
    """ Generator for the 'Greys' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 0.941176470588, 0.941176470588),
            (0.25, 0.850980392157, 0.850980392157),
            (0.375, 0.741176470588, 0.741176470588),
            (0.5, 0.588235294118, 0.588235294118),
            (0.625, 0.450980392157, 0.450980392157),
            (0.75, 0.321568627451, 0.321568627451),
            (0.875, 0.145098039216, 0.145098039216),
            (1.0, 0.0, 0.0)],
        green = [(0.0, 1.0, 1.0),
            (0.125, 0.941176470588, 0.941176470588),
            (0.25, 0.850980392157, 0.850980392157),
            (0.375, 0.741176470588, 0.741176470588),
            (0.5, 0.588235294118, 0.588235294118),
            (0.625, 0.450980392157, 0.450980392157),
            (0.75, 0.321568627451, 0.321568627451),
            (0.875, 0.145098039216, 0.145098039216),
            (1.0, 0.0, 0.0)],
        blue = [(0.0, 1.0, 1.0),
            (0.125, 0.941176470588, 0.941176470588),
            (0.25, 0.850980392157, 0.850980392157),
            (0.375, 0.741176470588, 0.741176470588),
            (0.5, 0.588235294118, 0.588235294118),
            (0.625, 0.450980392157, 0.450980392157),
            (0.75, 0.321568627451, 0.321568627451),
            (0.875, 0.145098039216, 0.145098039216),
            (1.0, 0.0, 0.0)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def OrRd(range, **traits):
    """ Generator for the 'OrRd' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 0.996078431373, 0.996078431373),
            (0.25, 0.992156862745, 0.992156862745),
            (0.375, 0.992156862745, 0.992156862745),
            (0.5, 0.988235294118, 0.988235294118),
            (0.625, 0.937254901961, 0.937254901961),
            (0.75, 0.843137254902, 0.843137254902),
            (0.875, 0.701960784314, 0.701960784314),
            (1.0, 0.498039215686, 0.498039215686)],
        green = [(0.0, 0.96862745098, 0.96862745098),
            (0.125, 0.909803921569, 0.909803921569),
            (0.25, 0.83137254902, 0.83137254902),
            (0.375, 0.733333333333, 0.733333333333),
            (0.5, 0.552941176471, 0.552941176471),
            (0.625, 0.396078431373, 0.396078431373),
            (0.75, 0.188235294118, 0.188235294118),
            (0.875, 0.0, 0.0),
            (1.0, 0.0, 0.0)],
        blue = [(0.0, 0.925490196078, 0.925490196078),
            (0.125, 0.78431372549, 0.78431372549),
            (0.25, 0.619607843137, 0.619607843137),
            (0.375, 0.517647058824, 0.517647058824),
            (0.5, 0.349019607843, 0.349019607843),
            (0.625, 0.282352941176, 0.282352941176),
            (0.75, 0.121568627451, 0.121568627451),
            (0.875, 0.0, 0.0),
            (1.0, 0.0, 0.0)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def Oranges(range, **traits):
    """ Generator for the 'Oranges' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 0.996078431373, 0.996078431373),
            (0.25, 0.992156862745, 0.992156862745),
            (0.375, 0.992156862745, 0.992156862745),
            (0.5, 0.992156862745, 0.992156862745),
            (0.625, 0.945098039216, 0.945098039216),
            (0.75, 0.850980392157, 0.850980392157),
            (0.875, 0.650980392157, 0.650980392157),
            (1.0, 0.498039215686, 0.498039215686)],
        green = [(0.0, 0.960784313725, 0.960784313725),
            (0.125, 0.901960784314, 0.901960784314),
            (0.25, 0.81568627451, 0.81568627451),
            (0.375, 0.682352941176, 0.682352941176),
            (0.5, 0.552941176471, 0.552941176471),
            (0.625, 0.411764705882, 0.411764705882),
            (0.75, 0.282352941176, 0.282352941176),
            (0.875, 0.211764705882, 0.211764705882),
            (1.0, 0.152941176471, 0.152941176471)],
        blue = [(0.0, 0.921568627451, 0.921568627451),
            (0.125, 0.807843137255, 0.807843137255),
            (0.25, 0.635294117647, 0.635294117647),
            (0.375, 0.419607843137, 0.419607843137),
            (0.5, 0.235294117647, 0.235294117647),
            (0.625, 0.0745098039216, 0.0745098039216),
            (0.75, 0.00392156862745, 0.00392156862745),
            (0.875, 0.0117647058824, 0.0117647058824),
            (1.0, 0.0156862745098, 0.0156862745098)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def PRGn(range, **traits):
    """ Generator for the 'PRGn' colormap from ColorBrewer.

    This is a diverging colormap. It is good for data which is centered around
    a "special" value, like 0.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.250980392157, 0.250980392157),
            (0.1, 0.462745098039, 0.462745098039),
            (0.2, 0.6, 0.6),
            (0.3, 0.760784313725, 0.760784313725),
            (0.4, 0.905882352941, 0.905882352941),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.850980392157, 0.850980392157),
            (0.7, 0.650980392157, 0.650980392157),
            (0.8, 0.352941176471, 0.352941176471),
            (0.9, 0.105882352941, 0.105882352941),
            (1.0, 0.0, 0.0)],
        green = [(0.0, 0.0, 0.0),
            (0.1, 0.164705882353, 0.164705882353),
            (0.2, 0.439215686275, 0.439215686275),
            (0.3, 0.647058823529, 0.647058823529),
            (0.4, 0.83137254902, 0.83137254902),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.941176470588, 0.941176470588),
            (0.7, 0.858823529412, 0.858823529412),
            (0.8, 0.682352941176, 0.682352941176),
            (0.9, 0.470588235294, 0.470588235294),
            (1.0, 0.266666666667, 0.266666666667)],
        blue = [(0.0, 0.294117647059, 0.294117647059),
            (0.1, 0.513725490196, 0.513725490196),
            (0.2, 0.670588235294, 0.670588235294),
            (0.3, 0.811764705882, 0.811764705882),
            (0.4, 0.909803921569, 0.909803921569),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.827450980392, 0.827450980392),
            (0.7, 0.627450980392, 0.627450980392),
            (0.8, 0.380392156863, 0.380392156863),
            (0.9, 0.21568627451, 0.21568627451),
            (1.0, 0.105882352941, 0.105882352941)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def PiYG(range, **traits):
    """ Generator for the 'PiYG' colormap from ColorBrewer.

    This is a diverging colormap. It is good for data which is centered around
    a "special" value, like 0.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.556862745098, 0.556862745098),
            (0.1, 0.772549019608, 0.772549019608),
            (0.2, 0.870588235294, 0.870588235294),
            (0.3, 0.945098039216, 0.945098039216),
            (0.4, 0.992156862745, 0.992156862745),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.901960784314, 0.901960784314),
            (0.7, 0.721568627451, 0.721568627451),
            (0.8, 0.498039215686, 0.498039215686),
            (0.9, 0.301960784314, 0.301960784314),
            (1.0, 0.152941176471, 0.152941176471)],
        green = [(0.0, 0.00392156862745, 0.00392156862745),
            (0.1, 0.105882352941, 0.105882352941),
            (0.2, 0.466666666667, 0.466666666667),
            (0.3, 0.713725490196, 0.713725490196),
            (0.4, 0.878431372549, 0.878431372549),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.960784313725, 0.960784313725),
            (0.7, 0.882352941176, 0.882352941176),
            (0.8, 0.737254901961, 0.737254901961),
            (0.9, 0.572549019608, 0.572549019608),
            (1.0, 0.392156862745, 0.392156862745)],
        blue = [(0.0, 0.321568627451, 0.321568627451),
            (0.1, 0.490196078431, 0.490196078431),
            (0.2, 0.682352941176, 0.682352941176),
            (0.3, 0.854901960784, 0.854901960784),
            (0.4, 0.937254901961, 0.937254901961),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.81568627451, 0.81568627451),
            (0.7, 0.525490196078, 0.525490196078),
            (0.8, 0.254901960784, 0.254901960784),
            (0.9, 0.129411764706, 0.129411764706),
            (1.0, 0.0980392156863, 0.0980392156863)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def PuBu(range, **traits):
    """ Generator for the 'PuBu' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 0.925490196078, 0.925490196078),
            (0.25, 0.81568627451, 0.81568627451),
            (0.375, 0.650980392157, 0.650980392157),
            (0.5, 0.454901960784, 0.454901960784),
            (0.625, 0.211764705882, 0.211764705882),
            (0.75, 0.0196078431373, 0.0196078431373),
            (0.875, 0.0156862745098, 0.0156862745098),
            (1.0, 0.0078431372549, 0.0078431372549)],
        green = [(0.0, 0.96862745098, 0.96862745098),
            (0.125, 0.905882352941, 0.905882352941),
            (0.25, 0.819607843137, 0.819607843137),
            (0.375, 0.741176470588, 0.741176470588),
            (0.5, 0.662745098039, 0.662745098039),
            (0.625, 0.564705882353, 0.564705882353),
            (0.75, 0.439215686275, 0.439215686275),
            (0.875, 0.352941176471, 0.352941176471),
            (1.0, 0.219607843137, 0.219607843137)],
        blue = [(0.0, 0.98431372549, 0.98431372549),
            (0.125, 0.949019607843, 0.949019607843),
            (0.25, 0.901960784314, 0.901960784314),
            (0.375, 0.858823529412, 0.858823529412),
            (0.5, 0.811764705882, 0.811764705882),
            (0.625, 0.752941176471, 0.752941176471),
            (0.75, 0.690196078431, 0.690196078431),
            (0.875, 0.552941176471, 0.552941176471),
            (1.0, 0.345098039216, 0.345098039216)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def PuBuGn(range, **traits):
    """ Generator for the 'PuBuGn' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 0.925490196078, 0.925490196078),
            (0.25, 0.81568627451, 0.81568627451),
            (0.375, 0.650980392157, 0.650980392157),
            (0.5, 0.403921568627, 0.403921568627),
            (0.625, 0.211764705882, 0.211764705882),
            (0.75, 0.0078431372549, 0.0078431372549),
            (0.875, 0.00392156862745, 0.00392156862745),
            (1.0, 0.00392156862745, 0.00392156862745)],
        green = [(0.0, 0.96862745098, 0.96862745098),
            (0.125, 0.886274509804, 0.886274509804),
            (0.25, 0.819607843137, 0.819607843137),
            (0.375, 0.741176470588, 0.741176470588),
            (0.5, 0.662745098039, 0.662745098039),
            (0.625, 0.564705882353, 0.564705882353),
            (0.75, 0.505882352941, 0.505882352941),
            (0.875, 0.423529411765, 0.423529411765),
            (1.0, 0.274509803922, 0.274509803922)],
        blue = [(0.0, 0.98431372549, 0.98431372549),
            (0.125, 0.941176470588, 0.941176470588),
            (0.25, 0.901960784314, 0.901960784314),
            (0.375, 0.858823529412, 0.858823529412),
            (0.5, 0.811764705882, 0.811764705882),
            (0.625, 0.752941176471, 0.752941176471),
            (0.75, 0.541176470588, 0.541176470588),
            (0.875, 0.349019607843, 0.349019607843),
            (1.0, 0.211764705882, 0.211764705882)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def PuOr(range, **traits):
    """ Generator for the 'PuOr' colormap from ColorBrewer.

    This is a diverging colormap. It is good for data which is centered around
    a "special" value, like 0.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.498039215686, 0.498039215686),
            (0.1, 0.701960784314, 0.701960784314),
            (0.2, 0.878431372549, 0.878431372549),
            (0.3, 0.992156862745, 0.992156862745),
            (0.4, 0.996078431373, 0.996078431373),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.847058823529, 0.847058823529),
            (0.7, 0.698039215686, 0.698039215686),
            (0.8, 0.501960784314, 0.501960784314),
            (0.9, 0.329411764706, 0.329411764706),
            (1.0, 0.176470588235, 0.176470588235)],
        green = [(0.0, 0.23137254902, 0.23137254902),
            (0.1, 0.345098039216, 0.345098039216),
            (0.2, 0.509803921569, 0.509803921569),
            (0.3, 0.721568627451, 0.721568627451),
            (0.4, 0.878431372549, 0.878431372549),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.854901960784, 0.854901960784),
            (0.7, 0.670588235294, 0.670588235294),
            (0.8, 0.450980392157, 0.450980392157),
            (0.9, 0.152941176471, 0.152941176471),
            (1.0, 0.0, 0.0)],
        blue = [(0.0, 0.0313725490196, 0.0313725490196),
            (0.1, 0.0235294117647, 0.0235294117647),
            (0.2, 0.078431372549, 0.078431372549),
            (0.3, 0.388235294118, 0.388235294118),
            (0.4, 0.713725490196, 0.713725490196),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.921568627451, 0.921568627451),
            (0.7, 0.823529411765, 0.823529411765),
            (0.8, 0.674509803922, 0.674509803922),
            (0.9, 0.533333333333, 0.533333333333),
            (1.0, 0.294117647059, 0.294117647059)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def PuRd(range, **traits):
    """ Generator for the 'PuRd' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.96862745098, 0.96862745098),
            (0.125, 0.905882352941, 0.905882352941),
            (0.25, 0.83137254902, 0.83137254902),
            (0.375, 0.788235294118, 0.788235294118),
            (0.5, 0.874509803922, 0.874509803922),
            (0.625, 0.905882352941, 0.905882352941),
            (0.75, 0.807843137255, 0.807843137255),
            (0.875, 0.596078431373, 0.596078431373),
            (1.0, 0.403921568627, 0.403921568627)],
        green = [(0.0, 0.956862745098, 0.956862745098),
            (0.125, 0.882352941176, 0.882352941176),
            (0.25, 0.725490196078, 0.725490196078),
            (0.375, 0.580392156863, 0.580392156863),
            (0.5, 0.396078431373, 0.396078431373),
            (0.625, 0.160784313725, 0.160784313725),
            (0.75, 0.0705882352941, 0.0705882352941),
            (0.875, 0.0, 0.0),
            (1.0, 0.0, 0.0)],
        blue = [(0.0, 0.976470588235, 0.976470588235),
            (0.125, 0.937254901961, 0.937254901961),
            (0.25, 0.854901960784, 0.854901960784),
            (0.375, 0.780392156863, 0.780392156863),
            (0.5, 0.690196078431, 0.690196078431),
            (0.625, 0.541176470588, 0.541176470588),
            (0.75, 0.337254901961, 0.337254901961),
            (0.875, 0.262745098039, 0.262745098039),
            (1.0, 0.121568627451, 0.121568627451)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def Purples(range, **traits):
    """ Generator for the 'Purples' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.988235294118, 0.988235294118),
            (0.125, 0.937254901961, 0.937254901961),
            (0.25, 0.854901960784, 0.854901960784),
            (0.375, 0.737254901961, 0.737254901961),
            (0.5, 0.619607843137, 0.619607843137),
            (0.625, 0.501960784314, 0.501960784314),
            (0.75, 0.41568627451, 0.41568627451),
            (0.875, 0.329411764706, 0.329411764706),
            (1.0, 0.247058823529, 0.247058823529)],
        green = [(0.0, 0.98431372549, 0.98431372549),
            (0.125, 0.929411764706, 0.929411764706),
            (0.25, 0.854901960784, 0.854901960784),
            (0.375, 0.741176470588, 0.741176470588),
            (0.5, 0.603921568627, 0.603921568627),
            (0.625, 0.490196078431, 0.490196078431),
            (0.75, 0.317647058824, 0.317647058824),
            (0.875, 0.152941176471, 0.152941176471),
            (1.0, 0.0, 0.0)],
        blue = [(0.0, 0.992156862745, 0.992156862745),
            (0.125, 0.960784313725, 0.960784313725),
            (0.25, 0.921568627451, 0.921568627451),
            (0.375, 0.862745098039, 0.862745098039),
            (0.5, 0.78431372549, 0.78431372549),
            (0.625, 0.729411764706, 0.729411764706),
            (0.75, 0.639215686275, 0.639215686275),
            (0.875, 0.560784313725, 0.560784313725),
            (1.0, 0.490196078431, 0.490196078431)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def RdBu(range, **traits):
    """ Generator for the 'RdBu' colormap from ColorBrewer.

    This is a diverging colormap. It is good for data which is centered around
    a "special" value, like 0.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.403921568627, 0.403921568627),
            (0.1, 0.698039215686, 0.698039215686),
            (0.2, 0.839215686275, 0.839215686275),
            (0.3, 0.956862745098, 0.956862745098),
            (0.4, 0.992156862745, 0.992156862745),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.819607843137, 0.819607843137),
            (0.7, 0.572549019608, 0.572549019608),
            (0.8, 0.262745098039, 0.262745098039),
            (0.9, 0.129411764706, 0.129411764706),
            (1.0, 0.0196078431373, 0.0196078431373)],
        green = [(0.0, 0.0, 0.0),
            (0.1, 0.0941176470588, 0.0941176470588),
            (0.2, 0.376470588235, 0.376470588235),
            (0.3, 0.647058823529, 0.647058823529),
            (0.4, 0.858823529412, 0.858823529412),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.898039215686, 0.898039215686),
            (0.7, 0.772549019608, 0.772549019608),
            (0.8, 0.576470588235, 0.576470588235),
            (0.9, 0.4, 0.4),
            (1.0, 0.188235294118, 0.188235294118)],
        blue = [(0.0, 0.121568627451, 0.121568627451),
            (0.1, 0.16862745098, 0.16862745098),
            (0.2, 0.301960784314, 0.301960784314),
            (0.3, 0.509803921569, 0.509803921569),
            (0.4, 0.780392156863, 0.780392156863),
            (0.5, 0.96862745098, 0.96862745098),
            (0.6, 0.941176470588, 0.941176470588),
            (0.7, 0.870588235294, 0.870588235294),
            (0.8, 0.764705882353, 0.764705882353),
            (0.9, 0.674509803922, 0.674509803922),
            (1.0, 0.380392156863, 0.380392156863)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def RdGy(range, **traits):
    """ Generator for the 'RdGy' colormap from ColorBrewer.

    This is a diverging colormap. It is good for data which is centered around
    a "special" value, like 0.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.403921568627, 0.403921568627),
            (0.1, 0.698039215686, 0.698039215686),
            (0.2, 0.839215686275, 0.839215686275),
            (0.3, 0.956862745098, 0.956862745098),
            (0.4, 0.992156862745, 0.992156862745),
            (0.5, 1.0, 1.0),
            (0.6, 0.878431372549, 0.878431372549),
            (0.7, 0.729411764706, 0.729411764706),
            (0.8, 0.529411764706, 0.529411764706),
            (0.9, 0.301960784314, 0.301960784314),
            (1.0, 0.101960784314, 0.101960784314)],
        green = [(0.0, 0.0, 0.0),
            (0.1, 0.0941176470588, 0.0941176470588),
            (0.2, 0.376470588235, 0.376470588235),
            (0.3, 0.647058823529, 0.647058823529),
            (0.4, 0.858823529412, 0.858823529412),
            (0.5, 1.0, 1.0),
            (0.6, 0.878431372549, 0.878431372549),
            (0.7, 0.729411764706, 0.729411764706),
            (0.8, 0.529411764706, 0.529411764706),
            (0.9, 0.301960784314, 0.301960784314),
            (1.0, 0.101960784314, 0.101960784314)],
        blue = [(0.0, 0.121568627451, 0.121568627451),
            (0.1, 0.16862745098, 0.16862745098),
            (0.2, 0.301960784314, 0.301960784314),
            (0.3, 0.509803921569, 0.509803921569),
            (0.4, 0.780392156863, 0.780392156863),
            (0.5, 1.0, 1.0),
            (0.6, 0.878431372549, 0.878431372549),
            (0.7, 0.729411764706, 0.729411764706),
            (0.8, 0.529411764706, 0.529411764706),
            (0.9, 0.301960784314, 0.301960784314),
            (1.0, 0.101960784314, 0.101960784314)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def RdPu(range, **traits):
    """ Generator for the 'RdPu' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 0.992156862745, 0.992156862745),
            (0.25, 0.988235294118, 0.988235294118),
            (0.375, 0.980392156863, 0.980392156863),
            (0.5, 0.96862745098, 0.96862745098),
            (0.625, 0.866666666667, 0.866666666667),
            (0.75, 0.682352941176, 0.682352941176),
            (0.875, 0.478431372549, 0.478431372549),
            (1.0, 0.286274509804, 0.286274509804)],
        green = [(0.0, 0.96862745098, 0.96862745098),
            (0.125, 0.878431372549, 0.878431372549),
            (0.25, 0.772549019608, 0.772549019608),
            (0.375, 0.623529411765, 0.623529411765),
            (0.5, 0.407843137255, 0.407843137255),
            (0.625, 0.203921568627, 0.203921568627),
            (0.75, 0.00392156862745, 0.00392156862745),
            (0.875, 0.00392156862745, 0.00392156862745),
            (1.0, 0.0, 0.0)],
        blue = [(0.0, 0.952941176471, 0.952941176471),
            (0.125, 0.866666666667, 0.866666666667),
            (0.25, 0.752941176471, 0.752941176471),
            (0.375, 0.709803921569, 0.709803921569),
            (0.5, 0.63137254902, 0.63137254902),
            (0.625, 0.592156862745, 0.592156862745),
            (0.75, 0.494117647059, 0.494117647059),
            (0.875, 0.466666666667, 0.466666666667),
            (1.0, 0.41568627451, 0.41568627451)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def RdYlBu(range, **traits):
    """ Generator for the 'RdYlBu' colormap from ColorBrewer.

    This is a diverging colormap. It is good for data which is centered around
    a "special" value, like 0.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.647058823529, 0.647058823529),
            (0.1, 0.843137254902, 0.843137254902),
            (0.2, 0.956862745098, 0.956862745098),
            (0.3, 0.992156862745, 0.992156862745),
            (0.4, 0.996078431373, 0.996078431373),
            (0.5, 1.0, 1.0),
            (0.6, 0.878431372549, 0.878431372549),
            (0.7, 0.670588235294, 0.670588235294),
            (0.8, 0.454901960784, 0.454901960784),
            (0.9, 0.270588235294, 0.270588235294),
            (1.0, 0.192156862745, 0.192156862745)],
        green = [(0.0, 0.0, 0.0),
            (0.1, 0.188235294118, 0.188235294118),
            (0.2, 0.427450980392, 0.427450980392),
            (0.3, 0.682352941176, 0.682352941176),
            (0.4, 0.878431372549, 0.878431372549),
            (0.5, 1.0, 1.0),
            (0.6, 0.952941176471, 0.952941176471),
            (0.7, 0.850980392157, 0.850980392157),
            (0.8, 0.678431372549, 0.678431372549),
            (0.9, 0.458823529412, 0.458823529412),
            (1.0, 0.211764705882, 0.211764705882)],
        blue = [(0.0, 0.149019607843, 0.149019607843),
            (0.1, 0.152941176471, 0.152941176471),
            (0.2, 0.262745098039, 0.262745098039),
            (0.3, 0.380392156863, 0.380392156863),
            (0.4, 0.564705882353, 0.564705882353),
            (0.5, 0.749019607843, 0.749019607843),
            (0.6, 0.972549019608, 0.972549019608),
            (0.7, 0.913725490196, 0.913725490196),
            (0.8, 0.819607843137, 0.819607843137),
            (0.9, 0.705882352941, 0.705882352941),
            (1.0, 0.58431372549, 0.58431372549)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def RdYlGn(range, **traits):
    """ Generator for the 'RdYlGn' colormap from ColorBrewer.

    This is a diverging colormap. It is good for data which is centered around
    a "special" value, like 0.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.647058823529, 0.647058823529),
            (0.1, 0.843137254902, 0.843137254902),
            (0.2, 0.956862745098, 0.956862745098),
            (0.3, 0.992156862745, 0.992156862745),
            (0.4, 0.996078431373, 0.996078431373),
            (0.5, 1.0, 1.0),
            (0.6, 0.850980392157, 0.850980392157),
            (0.7, 0.650980392157, 0.650980392157),
            (0.8, 0.4, 0.4),
            (0.9, 0.101960784314, 0.101960784314),
            (1.0, 0.0, 0.0)],
        green = [(0.0, 0.0, 0.0),
            (0.1, 0.188235294118, 0.188235294118),
            (0.2, 0.427450980392, 0.427450980392),
            (0.3, 0.682352941176, 0.682352941176),
            (0.4, 0.878431372549, 0.878431372549),
            (0.5, 1.0, 1.0),
            (0.6, 0.937254901961, 0.937254901961),
            (0.7, 0.850980392157, 0.850980392157),
            (0.8, 0.741176470588, 0.741176470588),
            (0.9, 0.596078431373, 0.596078431373),
            (1.0, 0.407843137255, 0.407843137255)],
        blue = [(0.0, 0.149019607843, 0.149019607843),
            (0.1, 0.152941176471, 0.152941176471),
            (0.2, 0.262745098039, 0.262745098039),
            (0.3, 0.380392156863, 0.380392156863),
            (0.4, 0.545098039216, 0.545098039216),
            (0.5, 0.749019607843, 0.749019607843),
            (0.6, 0.545098039216, 0.545098039216),
            (0.7, 0.41568627451, 0.41568627451),
            (0.8, 0.388235294118, 0.388235294118),
            (0.9, 0.313725490196, 0.313725490196),
            (1.0, 0.21568627451, 0.21568627451)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def Reds(range, **traits):
    """ Generator for the 'Reds' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 0.996078431373, 0.996078431373),
            (0.25, 0.988235294118, 0.988235294118),
            (0.375, 0.988235294118, 0.988235294118),
            (0.5, 0.98431372549, 0.98431372549),
            (0.625, 0.937254901961, 0.937254901961),
            (0.75, 0.796078431373, 0.796078431373),
            (0.875, 0.647058823529, 0.647058823529),
            (1.0, 0.403921568627, 0.403921568627)],
        green = [(0.0, 0.960784313725, 0.960784313725),
            (0.125, 0.878431372549, 0.878431372549),
            (0.25, 0.733333333333, 0.733333333333),
            (0.375, 0.572549019608, 0.572549019608),
            (0.5, 0.41568627451, 0.41568627451),
            (0.625, 0.23137254902, 0.23137254902),
            (0.75, 0.0941176470588, 0.0941176470588),
            (0.875, 0.0588235294118, 0.0588235294118),
            (1.0, 0.0, 0.0)],
        blue = [(0.0, 0.941176470588, 0.941176470588),
            (0.125, 0.823529411765, 0.823529411765),
            (0.25, 0.63137254902, 0.63137254902),
            (0.375, 0.447058823529, 0.447058823529),
            (0.5, 0.290196078431, 0.290196078431),
            (0.625, 0.172549019608, 0.172549019608),
            (0.75, 0.113725490196, 0.113725490196),
            (0.875, 0.0823529411765, 0.0823529411765),
            (1.0, 0.0509803921569, 0.0509803921569)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def Spectral(range, **traits):
    """ Generator for the 'Spectral' colormap from ColorBrewer.

    This is a diverging colormap. It is good for data which is centered around
    a "special" value, like 0.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 0.619607843137, 0.619607843137),
            (0.1, 0.835294117647, 0.835294117647),
            (0.2, 0.956862745098, 0.956862745098),
            (0.3, 0.992156862745, 0.992156862745),
            (0.4, 0.996078431373, 0.996078431373),
            (0.5, 1.0, 1.0),
            (0.6, 0.901960784314, 0.901960784314),
            (0.7, 0.670588235294, 0.670588235294),
            (0.8, 0.4, 0.4),
            (0.9, 0.196078431373, 0.196078431373),
            (1.0, 0.36862745098, 0.36862745098)],
        green = [(0.0, 0.00392156862745, 0.00392156862745),
            (0.1, 0.243137254902, 0.243137254902),
            (0.2, 0.427450980392, 0.427450980392),
            (0.3, 0.682352941176, 0.682352941176),
            (0.4, 0.878431372549, 0.878431372549),
            (0.5, 1.0, 1.0),
            (0.6, 0.960784313725, 0.960784313725),
            (0.7, 0.866666666667, 0.866666666667),
            (0.8, 0.760784313725, 0.760784313725),
            (0.9, 0.533333333333, 0.533333333333),
            (1.0, 0.309803921569, 0.309803921569)],
        blue = [(0.0, 0.258823529412, 0.258823529412),
            (0.1, 0.309803921569, 0.309803921569),
            (0.2, 0.262745098039, 0.262745098039),
            (0.3, 0.380392156863, 0.380392156863),
            (0.4, 0.545098039216, 0.545098039216),
            (0.5, 0.749019607843, 0.749019607843),
            (0.6, 0.596078431373, 0.596078431373),
            (0.7, 0.643137254902, 0.643137254902),
            (0.8, 0.647058823529, 0.647058823529),
            (0.9, 0.741176470588, 0.741176470588),
            (1.0, 0.635294117647, 0.635294117647)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def YlGn(range, **traits):
    """ Generator for the 'YlGn' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 0.96862745098, 0.96862745098),
            (0.25, 0.850980392157, 0.850980392157),
            (0.375, 0.678431372549, 0.678431372549),
            (0.5, 0.470588235294, 0.470588235294),
            (0.625, 0.254901960784, 0.254901960784),
            (0.75, 0.137254901961, 0.137254901961),
            (0.875, 0.0, 0.0),
            (1.0, 0.0, 0.0)],
        green = [(0.0, 1.0, 1.0),
            (0.125, 0.988235294118, 0.988235294118),
            (0.25, 0.941176470588, 0.941176470588),
            (0.375, 0.866666666667, 0.866666666667),
            (0.5, 0.776470588235, 0.776470588235),
            (0.625, 0.670588235294, 0.670588235294),
            (0.75, 0.517647058824, 0.517647058824),
            (0.875, 0.407843137255, 0.407843137255),
            (1.0, 0.270588235294, 0.270588235294)],
        blue = [(0.0, 0.898039215686, 0.898039215686),
            (0.125, 0.725490196078, 0.725490196078),
            (0.25, 0.639215686275, 0.639215686275),
            (0.375, 0.556862745098, 0.556862745098),
            (0.5, 0.474509803922, 0.474509803922),
            (0.625, 0.364705882353, 0.364705882353),
            (0.75, 0.262745098039, 0.262745098039),
            (0.875, 0.21568627451, 0.21568627451),
            (1.0, 0.160784313725, 0.160784313725)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def YlGnBu(range, **traits):
    """ Generator for the 'YlGnBu' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 0.929411764706, 0.929411764706),
            (0.25, 0.780392156863, 0.780392156863),
            (0.375, 0.498039215686, 0.498039215686),
            (0.5, 0.254901960784, 0.254901960784),
            (0.625, 0.113725490196, 0.113725490196),
            (0.75, 0.133333333333, 0.133333333333),
            (0.875, 0.145098039216, 0.145098039216),
            (1.0, 0.0313725490196, 0.0313725490196)],
        green = [(0.0, 1.0, 1.0),
            (0.125, 0.972549019608, 0.972549019608),
            (0.25, 0.913725490196, 0.913725490196),
            (0.375, 0.803921568627, 0.803921568627),
            (0.5, 0.713725490196, 0.713725490196),
            (0.625, 0.56862745098, 0.56862745098),
            (0.75, 0.36862745098, 0.36862745098),
            (0.875, 0.203921568627, 0.203921568627),
            (1.0, 0.113725490196, 0.113725490196)],
        blue = [(0.0, 0.850980392157, 0.850980392157),
            (0.125, 0.694117647059, 0.694117647059),
            (0.25, 0.705882352941, 0.705882352941),
            (0.375, 0.733333333333, 0.733333333333),
            (0.5, 0.76862745098, 0.76862745098),
            (0.625, 0.752941176471, 0.752941176471),
            (0.75, 0.658823529412, 0.658823529412),
            (0.875, 0.580392156863, 0.580392156863),
            (1.0, 0.345098039216, 0.345098039216)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def YlOrBr(range, **traits):
    """ Generator for the 'YlOrBr' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 1.0, 1.0),
            (0.25, 0.996078431373, 0.996078431373),
            (0.375, 0.996078431373, 0.996078431373),
            (0.5, 0.996078431373, 0.996078431373),
            (0.625, 0.925490196078, 0.925490196078),
            (0.75, 0.8, 0.8),
            (0.875, 0.6, 0.6),
            (1.0, 0.4, 0.4)],
        green = [(0.0, 1.0, 1.0),
            (0.125, 0.96862745098, 0.96862745098),
            (0.25, 0.890196078431, 0.890196078431),
            (0.375, 0.76862745098, 0.76862745098),
            (0.5, 0.6, 0.6),
            (0.625, 0.439215686275, 0.439215686275),
            (0.75, 0.298039215686, 0.298039215686),
            (0.875, 0.203921568627, 0.203921568627),
            (1.0, 0.145098039216, 0.145098039216)],
        blue = [(0.0, 0.898039215686, 0.898039215686),
            (0.125, 0.737254901961, 0.737254901961),
            (0.25, 0.56862745098, 0.56862745098),
            (0.375, 0.309803921569, 0.309803921569),
            (0.5, 0.160784313725, 0.160784313725),
            (0.625, 0.078431372549, 0.078431372549),
            (0.75, 0.0078431372549, 0.0078431372549),
            (0.875, 0.0156862745098, 0.0156862745098),
            (1.0, 0.0235294117647, 0.0235294117647)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def YlOrRd(range, **traits):
    """ Generator for the 'YlOrRd' colormap from ColorBrewer.

    Although the ColorBrewer colormaps are defined as discrete colormaps, we
    create continuous colormaps from them by linear interpolation in RGB
    colorspace.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.125, 1.0, 1.0),
            (0.25, 0.996078431373, 0.996078431373),
            (0.375, 0.996078431373, 0.996078431373),
            (0.5, 0.992156862745, 0.992156862745),
            (0.625, 0.988235294118, 0.988235294118),
            (0.75, 0.890196078431, 0.890196078431),
            (0.875, 0.741176470588, 0.741176470588),
            (1.0, 0.501960784314, 0.501960784314)],
        green = [(0.0, 1.0, 1.0),
            (0.125, 0.929411764706, 0.929411764706),
            (0.25, 0.850980392157, 0.850980392157),
            (0.375, 0.698039215686, 0.698039215686),
            (0.5, 0.552941176471, 0.552941176471),
            (0.625, 0.305882352941, 0.305882352941),
            (0.75, 0.101960784314, 0.101960784314),
            (0.875, 0.0, 0.0),
            (1.0, 0.0, 0.0)],
        blue = [(0.0, 0.8, 0.8),
            (0.125, 0.627450980392, 0.627450980392),
            (0.25, 0.462745098039, 0.462745098039),
            (0.375, 0.298039215686, 0.298039215686),
            (0.5, 0.235294117647, 0.235294117647),
            (0.625, 0.164705882353, 0.164705882353),
            (0.75, 0.109803921569, 0.109803921569),
            (0.875, 0.149019607843, 0.149019607843),
            (1.0, 0.149019607843, 0.149019607843)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)


# The following colormaps are from Yorick, a derivative of the GIST package.

def gist_earth(range, **traits):
    """ Generator for the 'gist_earth' colormap from GIST.
    """
    _data = dict(
        red = [(0.0, 0.0, 0.0),
            (0.0042016808874905109, 0.0, 0.0),
            (0.0084033617749810219, 0.0, 0.0),
            (0.012605042196810246, 0.0, 0.0),
            (0.016806723549962044, 0.0, 0.0),
            (0.021008403971791267, 0.0, 0.0),
            (0.025210084393620491, 0.0, 0.0),
            (0.029411764815449715, 0.0, 0.0),
            (0.033613447099924088, 0.0, 0.0),
            (0.037815127521753311, 0.0039215688593685627, 0.0039215688593685627),
            (0.042016807943582535, 0.0078431377187371254, 0.0078431377187371254),
            (0.046218488365411758, 0.0078431377187371254, 0.0078431377187371254),
            (0.050420168787240982, 0.011764706112444401, 0.011764706112444401),
            (0.054621849209070206, 0.015686275437474251, 0.015686275437474251),
            (0.058823529630899429, 0.019607843831181526, 0.019607843831181526),
            (0.063025213778018951, 0.019607843831181526, 0.019607843831181526),
            (0.067226894199848175, 0.023529412224888802, 0.023529412224888802),
            (0.071428574621677399, 0.027450980618596077, 0.027450980618596077),
            (0.075630255043506622, 0.031372550874948502, 0.031372550874948502),
            (0.079831935465335846, 0.031372550874948502, 0.031372550874948502),
            (0.08403361588716507, 0.035294119268655777, 0.035294119268655777),
            (0.088235296308994293, 0.039215687662363052, 0.039215687662363052),
            (0.092436976730823517, 0.043137256056070328, 0.043137256056070328),
            (0.09663865715265274, 0.043137256056070328, 0.043137256056070328),
            (0.10084033757448196, 0.047058824449777603, 0.047058824449777603),
            (0.10504201799631119, 0.050980392843484879, 0.050980392843484879),
            (0.10924369841814041, 0.054901961237192154, 0.054901961237192154),
            (0.11344537883996964, 0.058823529630899429, 0.058823529630899429),
            (0.11764705926179886, 0.058823529630899429, 0.058823529630899429),
            (0.12184873968362808, 0.062745101749897003, 0.062745101749897003),
            (0.1260504275560379, 0.066666670143604279, 0.066666670143604279),
            (0.13025210797786713, 0.070588238537311554, 0.070588238537311554),
            (0.13445378839969635, 0.070588238537311554, 0.070588238537311554),
            (0.13865546882152557, 0.074509806931018829, 0.074509806931018829),
            (0.1428571492433548, 0.078431375324726105, 0.078431375324726105),
            (0.14705882966518402, 0.08235294371843338, 0.08235294371843338),
            (0.15126051008701324, 0.086274512112140656, 0.086274512112140656),
            (0.15546219050884247, 0.086274512112140656, 0.086274512112140656),
            (0.15966387093067169, 0.090196080505847931, 0.090196080505847931),
            (0.16386555135250092, 0.094117648899555206, 0.094117648899555206),
            (0.16806723177433014, 0.098039217293262482, 0.098039217293262482),
            (0.17226891219615936, 0.10196078568696976, 0.10196078568696976),
            (0.17647059261798859, 0.10196078568696976, 0.10196078568696976),
            (0.18067227303981781, 0.10588235408067703, 0.10588235408067703),
            (0.18487395346164703, 0.10980392247438431, 0.10980392247438431),
            (0.18907563388347626, 0.11372549086809158, 0.11372549086809158),
            (0.19327731430530548, 0.11764705926179886, 0.11764705926179886),
            (0.1974789947271347, 0.12156862765550613, 0.12156862765550613),
            (0.20168067514896393, 0.12156862765550613, 0.12156862765550613),
            (0.20588235557079315, 0.12549020349979401, 0.12549020349979401),
            (0.21008403599262238, 0.12941177189350128, 0.12941177189350128),
            (0.2142857164144516, 0.13333334028720856, 0.13333334028720856),
            (0.21848739683628082, 0.13725490868091583, 0.13725490868091583),
            (0.22268907725811005, 0.14117647707462311, 0.14117647707462311),
            (0.22689075767993927, 0.14117647707462311, 0.14117647707462311),
            (0.23109243810176849, 0.14509804546833038, 0.14509804546833038),
            (0.23529411852359772, 0.14901961386203766, 0.14901961386203766),
            (0.23949579894542694, 0.15294118225574493, 0.15294118225574493),
            (0.24369747936725616, 0.15686275064945221, 0.15686275064945221),
            (0.24789915978908539, 0.16078431904315948, 0.16078431904315948),
            (0.25210085511207581, 0.16078431904315948, 0.16078431904315948),
            (0.25630253553390503, 0.16470588743686676, 0.16470588743686676),
            (0.26050421595573425, 0.16862745583057404, 0.16862745583057404),
            (0.26470589637756348, 0.17254902422428131, 0.17254902422428131),
            (0.2689075767993927, 0.17647059261798859, 0.17647059261798859),
            (0.27310925722122192, 0.18039216101169586, 0.18039216101169586),
            (0.27731093764305115, 0.18431372940540314, 0.18431372940540314),
            (0.28151261806488037, 0.18823529779911041, 0.18823529779911041),
            (0.28571429848670959, 0.18823529779911041, 0.18823529779911041),
            (0.28991597890853882, 0.18823529779911041, 0.18823529779911041),
            (0.29411765933036804, 0.19215686619281769, 0.19215686619281769),
            (0.29831933975219727, 0.19215686619281769, 0.19215686619281769),
            (0.30252102017402649, 0.19607843458652496, 0.19607843458652496),
            (0.30672270059585571, 0.19607843458652496, 0.19607843458652496),
            (0.31092438101768494, 0.20000000298023224, 0.20000000298023224),
            (0.31512606143951416, 0.20000000298023224, 0.20000000298023224),
            (0.31932774186134338, 0.20392157137393951, 0.20392157137393951),
            (0.32352942228317261, 0.20392157137393951, 0.20392157137393951),
            (0.32773110270500183, 0.20784313976764679, 0.20784313976764679),
            (0.33193278312683105, 0.20784313976764679, 0.20784313976764679),
            (0.33613446354866028, 0.21176470816135406, 0.21176470816135406),
            (0.3403361439704895, 0.21176470816135406, 0.21176470816135406),
            (0.34453782439231873, 0.21568627655506134, 0.21568627655506134),
            (0.34873950481414795, 0.21568627655506134, 0.21568627655506134),
            (0.35294118523597717, 0.21960784494876862, 0.21960784494876862),
            (0.3571428656578064, 0.21960784494876862, 0.21960784494876862),
            (0.36134454607963562, 0.22352941334247589, 0.22352941334247589),
            (0.36554622650146484, 0.22352941334247589, 0.22352941334247589),
            (0.36974790692329407, 0.22745098173618317, 0.22745098173618317),
            (0.37394958734512329, 0.22745098173618317, 0.22745098173618317),
            (0.37815126776695251, 0.23137255012989044, 0.23137255012989044),
            (0.38235294818878174, 0.23137255012989044, 0.23137255012989044),
            (0.38655462861061096, 0.23529411852359772, 0.23529411852359772),
            (0.39075630903244019, 0.23921568691730499, 0.23921568691730499),
            (0.39495798945426941, 0.23921568691730499, 0.23921568691730499),
            (0.39915966987609863, 0.24313725531101227, 0.24313725531101227),
            (0.40336135029792786, 0.24313725531101227, 0.24313725531101227),
            (0.40756303071975708, 0.24705882370471954, 0.24705882370471954),
            (0.4117647111415863, 0.24705882370471954, 0.24705882370471954),
            (0.41596639156341553, 0.25098040699958801, 0.25098040699958801),
            (0.42016807198524475, 0.25098040699958801, 0.25098040699958801),
            (0.42436975240707397, 0.25490197539329529, 0.25490197539329529),
            (0.4285714328289032, 0.25490197539329529, 0.25490197539329529),
            (0.43277311325073242, 0.25882354378700256, 0.25882354378700256),
            (0.43697479367256165, 0.26274511218070984, 0.26274511218070984),
            (0.44117647409439087, 0.26274511218070984, 0.26274511218070984),
            (0.44537815451622009, 0.26666668057441711, 0.26666668057441711),
            (0.44957983493804932, 0.26666668057441711, 0.26666668057441711),
            (0.45378151535987854, 0.27058824896812439, 0.27058824896812439),
            (0.45798319578170776, 0.27058824896812439, 0.27058824896812439),
            (0.46218487620353699, 0.27450981736183167, 0.27450981736183167),
            (0.46638655662536621, 0.27843138575553894, 0.27843138575553894),
            (0.47058823704719543, 0.28627452254295349, 0.28627452254295349),
            (0.47478991746902466, 0.29803922772407532, 0.29803922772407532),
            (0.47899159789085388, 0.30588236451148987, 0.30588236451148987),
            (0.48319327831268311, 0.31764706969261169, 0.31764706969261169),
            (0.48739495873451233, 0.32549020648002625, 0.32549020648002625),
            (0.49159663915634155, 0.33725491166114807, 0.33725491166114807),
            (0.49579831957817078, 0.34509804844856262, 0.34509804844856262),
            (0.5, 0.35686275362968445, 0.35686275362968445),
            (0.50420171022415161, 0.36862745881080627, 0.36862745881080627),
            (0.50840336084365845, 0.37647059559822083, 0.37647059559822083),
            (0.51260507106781006, 0.38823530077934265, 0.38823530077934265),
            (0.51680672168731689, 0.3960784375667572, 0.3960784375667572),
            (0.52100843191146851, 0.40784314274787903, 0.40784314274787903),
            (0.52521008253097534, 0.41568627953529358, 0.41568627953529358),
            (0.52941179275512695, 0.42745098471641541, 0.42745098471641541),
            (0.53361344337463379, 0.43529412150382996, 0.43529412150382996),
            (0.5378151535987854, 0.44705882668495178, 0.44705882668495178),
            (0.54201680421829224, 0.45882353186607361, 0.45882353186607361),
            (0.54621851444244385, 0.46666666865348816, 0.46666666865348816),
            (0.55042016506195068, 0.47450980544090271, 0.47450980544090271),
            (0.55462187528610229, 0.47843137383460999, 0.47843137383460999),
            (0.55882352590560913, 0.48627451062202454, 0.48627451062202454),
            (0.56302523612976074, 0.49411764740943909, 0.49411764740943909),
            (0.56722688674926758, 0.50196081399917603, 0.50196081399917603),
            (0.57142859697341919, 0.5058823823928833, 0.5058823823928833),
            (0.57563024759292603, 0.51372551918029785, 0.51372551918029785),
            (0.57983195781707764, 0.5215686559677124, 0.5215686559677124),
            (0.58403360843658447, 0.52941179275512695, 0.52941179275512695),
            (0.58823531866073608, 0.53333336114883423, 0.53333336114883423),
            (0.59243696928024292, 0.54117649793624878, 0.54117649793624878),
            (0.59663867950439453, 0.54901963472366333, 0.54901963472366333),
            (0.60084033012390137, 0.55294120311737061, 0.55294120311737061),
            (0.60504204034805298, 0.56078433990478516, 0.56078433990478516),
            (0.60924369096755981, 0.56862747669219971, 0.56862747669219971),
            (0.61344540119171143, 0.57647061347961426, 0.57647061347961426),
            (0.61764705181121826, 0.58431375026702881, 0.58431375026702881),
            (0.62184876203536987, 0.58823531866073608, 0.58823531866073608),
            (0.62605041265487671, 0.59607845544815063, 0.59607845544815063),
            (0.63025212287902832, 0.60392159223556519, 0.60392159223556519),
            (0.63445377349853516, 0.61176472902297974, 0.61176472902297974),
            (0.63865548372268677, 0.61568629741668701, 0.61568629741668701),
            (0.6428571343421936, 0.62352943420410156, 0.62352943420410156),
            (0.64705884456634521, 0.63137257099151611, 0.63137257099151611),
            (0.65126049518585205, 0.63921570777893066, 0.63921570777893066),
            (0.65546220541000366, 0.64705884456634521, 0.64705884456634521),
            (0.6596638560295105, 0.65098041296005249, 0.65098041296005249),
            (0.66386556625366211, 0.65882354974746704, 0.65882354974746704),
            (0.66806721687316895, 0.66666668653488159, 0.66666668653488159),
            (0.67226892709732056, 0.67450982332229614, 0.67450982332229614),
            (0.67647057771682739, 0.68235296010971069, 0.68235296010971069),
            (0.680672287940979, 0.68627452850341797, 0.68627452850341797),
            (0.68487393856048584, 0.69411766529083252, 0.69411766529083252),
            (0.68907564878463745, 0.70196080207824707, 0.70196080207824707),
            (0.69327729940414429, 0.70980393886566162, 0.70980393886566162),
            (0.6974790096282959, 0.71764707565307617, 0.71764707565307617),
            (0.70168066024780273, 0.71764707565307617, 0.71764707565307617),
            (0.70588237047195435, 0.72156864404678345, 0.72156864404678345),
            (0.71008402109146118, 0.72156864404678345, 0.72156864404678345),
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            (0.69327729940414429, 0.364705890417099, 0.364705890417099),
            (0.6974790096282959, 0.36862745881080627, 0.36862745881080627),
            (0.70168066024780273, 0.36862745881080627, 0.36862745881080627),
            (0.70588237047195435, 0.36862745881080627, 0.36862745881080627),
            (0.71008402109146118, 0.37254902720451355, 0.37254902720451355),
            (0.71428573131561279, 0.37254902720451355, 0.37254902720451355),
            (0.71848738193511963, 0.37254902720451355, 0.37254902720451355),
            (0.72268909215927124, 0.37647059559822083, 0.37647059559822083),
            (0.72689074277877808, 0.37647059559822083, 0.37647059559822083),
            (0.73109245300292969, 0.3803921639919281, 0.3803921639919281),
            (0.73529410362243652, 0.3803921639919281, 0.3803921639919281),
            (0.73949581384658813, 0.3803921639919281, 0.3803921639919281),
            (0.74369746446609497, 0.38431373238563538, 0.38431373238563538),
            (0.74789917469024658, 0.38431373238563538, 0.38431373238563538),
            (0.75210082530975342, 0.38431373238563538, 0.38431373238563538),
            (0.75630253553390503, 0.38823530077934265, 0.38823530077934265),
            (0.76050418615341187, 0.38823530077934265, 0.38823530077934265),
            (0.76470589637756348, 0.38823530077934265, 0.38823530077934265),
            (0.76890754699707031, 0.39215686917304993, 0.39215686917304993),
            (0.77310925722122192, 0.39215686917304993, 0.39215686917304993),
            (0.77731090784072876, 0.39215686917304993, 0.39215686917304993),
            (0.78151261806488037, 0.3960784375667572, 0.3960784375667572),
            (0.78571426868438721, 0.3960784375667572, 0.3960784375667572),
            (0.78991597890853882, 0.40784314274787903, 0.40784314274787903),
            (0.79411762952804565, 0.41568627953529358, 0.41568627953529358),
            (0.79831933975219727, 0.42352941632270813, 0.42352941632270813),
            (0.8025209903717041, 0.43529412150382996, 0.43529412150382996),
            (0.80672270059585571, 0.44313725829124451, 0.44313725829124451),
            (0.81092435121536255, 0.45490196347236633, 0.45490196347236633),
            (0.81512606143951416, 0.46274510025978088, 0.46274510025978088),
            (0.819327712059021, 0.47450980544090271, 0.47450980544090271),
            (0.82352942228317261, 0.48235294222831726, 0.48235294222831726),
            (0.82773107290267944, 0.49411764740943909, 0.49411764740943909),
            (0.83193278312683105, 0.5058823823928833, 0.5058823823928833),
            (0.83613443374633789, 0.51372551918029785, 0.51372551918029785),
            (0.8403361439704895, 0.52549022436141968, 0.52549022436141968),
            (0.84453779458999634, 0.5372549295425415, 0.5372549295425415),
            (0.84873950481414795, 0.54509806632995605, 0.54509806632995605),
            (0.85294115543365479, 0.55686277151107788, 0.55686277151107788),
            (0.8571428656578064, 0.56862747669219971, 0.56862747669219971),
            (0.86134451627731323, 0.58039218187332153, 0.58039218187332153),
            (0.86554622650146484, 0.58823531866073608, 0.58823531866073608),
            (0.86974787712097168, 0.60000002384185791, 0.60000002384185791),
            (0.87394958734512329, 0.61176472902297974, 0.61176472902297974),
            (0.87815123796463013, 0.62352943420410156, 0.62352943420410156),
            (0.88235294818878174, 0.63529413938522339, 0.63529413938522339),
            (0.88655459880828857, 0.64705884456634521, 0.64705884456634521),
            (0.89075630903244019, 0.65882354974746704, 0.65882354974746704),
            (0.89495795965194702, 0.66666668653488159, 0.66666668653488159),
            (0.89915966987609863, 0.67843139171600342, 0.67843139171600342),
            (0.90336132049560547, 0.69019609689712524, 0.69019609689712524),
            (0.90756303071975708, 0.70196080207824707, 0.70196080207824707),
            (0.91176468133926392, 0.7137255072593689, 0.7137255072593689),
            (0.91596639156341553, 0.72549021244049072, 0.72549021244049072),
            (0.92016804218292236, 0.74117648601531982, 0.74117648601531982),
            (0.92436975240707397, 0.75294119119644165, 0.75294119119644165),
            (0.92857140302658081, 0.76470589637756348, 0.76470589637756348),
            (0.93277311325073242, 0.7764706015586853, 0.7764706015586853),
            (0.93697476387023926, 0.78823530673980713, 0.78823530673980713),
            (0.94117647409439087, 0.80000001192092896, 0.80000001192092896),
            (0.94537812471389771, 0.81176471710205078, 0.81176471710205078),
            (0.94957983493804932, 0.82745099067687988, 0.82745099067687988),
            (0.95378148555755615, 0.83921569585800171, 0.83921569585800171),
            (0.95798319578170776, 0.85098040103912354, 0.85098040103912354),
            (0.9621848464012146, 0.86274510622024536, 0.86274510622024536),
            (0.96638655662536621, 0.87843137979507446, 0.87843137979507446),
            (0.97058820724487305, 0.89019608497619629, 0.89019608497619629),
            (0.97478991746902466, 0.90196079015731812, 0.90196079015731812),
            (0.97899156808853149, 0.91764706373214722, 0.91764706373214722),
            (0.98319327831268311, 0.92941176891326904, 0.92941176891326904),
            (0.98739492893218994, 0.94509804248809814, 0.94509804248809814),
            (0.99159663915634155, 0.95686274766921997, 0.95686274766921997),
            (0.99579828977584839, 0.97254902124404907, 0.97254902124404907),
            (1.0, 0.9843137264251709, 0.9843137264251709)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def gist_gray(range, **traits):
    """ Generator for the 'gist_gray' colormap from GIST.
    """
    _data = dict(
        red = [(0.0, 0.0, 0.0),
            (0.0042016808874905109, 0.0039215688593685627, 0.0039215688593685627),
            (0.0084033617749810219, 0.0078431377187371254, 0.0078431377187371254),
            (0.012605042196810246, 0.011764706112444401, 0.011764706112444401),
            (0.016806723549962044, 0.015686275437474251, 0.015686275437474251),
            (0.021008403971791267, 0.019607843831181526, 0.019607843831181526),
            (0.025210084393620491, 0.023529412224888802, 0.023529412224888802),
            (0.029411764815449715, 0.027450980618596077, 0.027450980618596077),
            (0.033613447099924088, 0.035294119268655777, 0.035294119268655777),
            (0.037815127521753311, 0.039215687662363052, 0.039215687662363052),
            (0.042016807943582535, 0.043137256056070328, 0.043137256056070328),
            (0.046218488365411758, 0.047058824449777603, 0.047058824449777603),
            (0.050420168787240982, 0.050980392843484879, 0.050980392843484879),
            (0.054621849209070206, 0.054901961237192154, 0.054901961237192154),
            (0.058823529630899429, 0.058823529630899429, 0.058823529630899429),
            (0.063025213778018951, 0.062745101749897003, 0.062745101749897003),
            (0.067226894199848175, 0.066666670143604279, 0.066666670143604279),
            (0.071428574621677399, 0.070588238537311554, 0.070588238537311554),
            (0.075630255043506622, 0.074509806931018829, 0.074509806931018829),
            (0.079831935465335846, 0.078431375324726105, 0.078431375324726105),
            (0.08403361588716507, 0.08235294371843338, 0.08235294371843338),
            (0.088235296308994293, 0.086274512112140656, 0.086274512112140656),
            (0.092436976730823517, 0.090196080505847931, 0.090196080505847931),
            (0.09663865715265274, 0.098039217293262482, 0.098039217293262482),
            (0.10084033757448196, 0.10196078568696976, 0.10196078568696976),
            (0.10504201799631119, 0.10588235408067703, 0.10588235408067703),
            (0.10924369841814041, 0.10980392247438431, 0.10980392247438431),
            (0.11344537883996964, 0.11372549086809158, 0.11372549086809158),
            (0.11764705926179886, 0.11764705926179886, 0.11764705926179886),
            (0.12184873968362808, 0.12156862765550613, 0.12156862765550613),
            (0.1260504275560379, 0.12549020349979401, 0.12549020349979401),
            (0.13025210797786713, 0.12941177189350128, 0.12941177189350128),
            (0.13445378839969635, 0.13333334028720856, 0.13333334028720856),
            (0.13865546882152557, 0.13725490868091583, 0.13725490868091583),
            (0.1428571492433548, 0.14117647707462311, 0.14117647707462311),
            (0.14705882966518402, 0.14509804546833038, 0.14509804546833038),
            (0.15126051008701324, 0.14901961386203766, 0.14901961386203766),
            (0.15546219050884247, 0.15294118225574493, 0.15294118225574493),
            (0.15966387093067169, 0.16078431904315948, 0.16078431904315948),
            (0.16386555135250092, 0.16470588743686676, 0.16470588743686676),
            (0.16806723177433014, 0.16862745583057404, 0.16862745583057404),
            (0.17226891219615936, 0.17254902422428131, 0.17254902422428131),
            (0.17647059261798859, 0.17647059261798859, 0.17647059261798859),
            (0.18067227303981781, 0.18039216101169586, 0.18039216101169586),
            (0.18487395346164703, 0.18431372940540314, 0.18431372940540314),
            (0.18907563388347626, 0.18823529779911041, 0.18823529779911041),
            (0.19327731430530548, 0.19215686619281769, 0.19215686619281769),
            (0.1974789947271347, 0.19607843458652496, 0.19607843458652496),
            (0.20168067514896393, 0.20000000298023224, 0.20000000298023224),
            (0.20588235557079315, 0.20392157137393951, 0.20392157137393951),
            (0.21008403599262238, 0.20784313976764679, 0.20784313976764679),
            (0.2142857164144516, 0.21176470816135406, 0.21176470816135406),
            (0.21848739683628082, 0.21568627655506134, 0.21568627655506134),
            (0.22268907725811005, 0.22352941334247589, 0.22352941334247589),
            (0.22689075767993927, 0.22745098173618317, 0.22745098173618317),
            (0.23109243810176849, 0.23137255012989044, 0.23137255012989044),
            (0.23529411852359772, 0.23529411852359772, 0.23529411852359772),
            (0.23949579894542694, 0.23921568691730499, 0.23921568691730499),
            (0.24369747936725616, 0.24313725531101227, 0.24313725531101227),
            (0.24789915978908539, 0.24705882370471954, 0.24705882370471954),
            (0.25210085511207581, 0.25098040699958801, 0.25098040699958801),
            (0.25630253553390503, 0.25490197539329529, 0.25490197539329529),
            (0.26050421595573425, 0.25882354378700256, 0.25882354378700256),
            (0.26470589637756348, 0.26274511218070984, 0.26274511218070984),
            (0.2689075767993927, 0.26666668057441711, 0.26666668057441711),
            (0.27310925722122192, 0.27058824896812439, 0.27058824896812439),
            (0.27731093764305115, 0.27450981736183167, 0.27450981736183167),
            (0.28151261806488037, 0.27843138575553894, 0.27843138575553894),
            (0.28571429848670959, 0.28627452254295349, 0.28627452254295349),
            (0.28991597890853882, 0.29019609093666077, 0.29019609093666077),
            (0.29411765933036804, 0.29411765933036804, 0.29411765933036804),
            (0.29831933975219727, 0.29803922772407532, 0.29803922772407532),
            (0.30252102017402649, 0.30196079611778259, 0.30196079611778259),
            (0.30672270059585571, 0.30588236451148987, 0.30588236451148987),
            (0.31092438101768494, 0.30980393290519714, 0.30980393290519714),
            (0.31512606143951416, 0.31372550129890442, 0.31372550129890442),
            (0.31932774186134338, 0.31764706969261169, 0.31764706969261169),
            (0.32352942228317261, 0.32156863808631897, 0.32156863808631897),
            (0.32773110270500183, 0.32549020648002625, 0.32549020648002625),
            (0.33193278312683105, 0.32941177487373352, 0.32941177487373352),
            (0.33613446354866028, 0.3333333432674408, 0.3333333432674408),
            (0.3403361439704895, 0.33725491166114807, 0.33725491166114807),
            (0.34453782439231873, 0.34117648005485535, 0.34117648005485535),
            (0.34873950481414795, 0.3490196168422699, 0.3490196168422699),
            (0.35294118523597717, 0.35294118523597717, 0.35294118523597717),
            (0.3571428656578064, 0.35686275362968445, 0.35686275362968445),
            (0.36134454607963562, 0.36078432202339172, 0.36078432202339172),
            (0.36554622650146484, 0.364705890417099, 0.364705890417099),
            (0.36974790692329407, 0.36862745881080627, 0.36862745881080627),
            (0.37394958734512329, 0.37254902720451355, 0.37254902720451355),
            (0.37815126776695251, 0.37647059559822083, 0.37647059559822083),
            (0.38235294818878174, 0.3803921639919281, 0.3803921639919281),
            (0.38655462861061096, 0.38431373238563538, 0.38431373238563538),
            (0.39075630903244019, 0.38823530077934265, 0.38823530077934265),
            (0.39495798945426941, 0.39215686917304993, 0.39215686917304993),
            (0.39915966987609863, 0.3960784375667572, 0.3960784375667572),
            (0.40336135029792786, 0.40000000596046448, 0.40000000596046448),
            (0.40756303071975708, 0.40392157435417175, 0.40392157435417175),
            (0.4117647111415863, 0.4117647111415863, 0.4117647111415863),
            (0.41596639156341553, 0.41568627953529358, 0.41568627953529358),
            (0.42016807198524475, 0.41960784792900085, 0.41960784792900085),
            (0.42436975240707397, 0.42352941632270813, 0.42352941632270813),
            (0.4285714328289032, 0.42745098471641541, 0.42745098471641541),
            (0.43277311325073242, 0.43137255311012268, 0.43137255311012268),
            (0.43697479367256165, 0.43529412150382996, 0.43529412150382996),
            (0.44117647409439087, 0.43921568989753723, 0.43921568989753723),
            (0.44537815451622009, 0.44313725829124451, 0.44313725829124451),
            (0.44957983493804932, 0.44705882668495178, 0.44705882668495178),
            (0.45378151535987854, 0.45098039507865906, 0.45098039507865906),
            (0.45798319578170776, 0.45490196347236633, 0.45490196347236633),
            (0.46218487620353699, 0.45882353186607361, 0.45882353186607361),
            (0.46638655662536621, 0.46274510025978088, 0.46274510025978088),
            (0.47058823704719543, 0.46666666865348816, 0.46666666865348816),
            (0.47478991746902466, 0.47450980544090271, 0.47450980544090271),
            (0.47899159789085388, 0.47843137383460999, 0.47843137383460999),
            (0.48319327831268311, 0.48235294222831726, 0.48235294222831726),
            (0.48739495873451233, 0.48627451062202454, 0.48627451062202454),
            (0.49159663915634155, 0.49019607901573181, 0.49019607901573181),
            (0.49579831957817078, 0.49411764740943909, 0.49411764740943909),
            (0.5, 0.49803921580314636, 0.49803921580314636),
            (0.50420171022415161, 0.50196081399917603, 0.50196081399917603),
            (0.50840336084365845, 0.5058823823928833, 0.5058823823928833),
            (0.51260507106781006, 0.50980395078659058, 0.50980395078659058),
            (0.51680672168731689, 0.51372551918029785, 0.51372551918029785),
            (0.52100843191146851, 0.51764708757400513, 0.51764708757400513),
            (0.52521008253097534, 0.5215686559677124, 0.5215686559677124),
            (0.52941179275512695, 0.52549022436141968, 0.52549022436141968),
            (0.53361344337463379, 0.52941179275512695, 0.52941179275512695),
            (0.5378151535987854, 0.5372549295425415, 0.5372549295425415),
            (0.54201680421829224, 0.54117649793624878, 0.54117649793624878),
            (0.54621851444244385, 0.54509806632995605, 0.54509806632995605),
            (0.55042016506195068, 0.54901963472366333, 0.54901963472366333),
            (0.55462187528610229, 0.55294120311737061, 0.55294120311737061),
            (0.55882352590560913, 0.55686277151107788, 0.55686277151107788),
            (0.56302523612976074, 0.56078433990478516, 0.56078433990478516),
            (0.56722688674926758, 0.56470590829849243, 0.56470590829849243),
            (0.57142859697341919, 0.56862747669219971, 0.56862747669219971),
            (0.57563024759292603, 0.57254904508590698, 0.57254904508590698),
            (0.57983195781707764, 0.57647061347961426, 0.57647061347961426),
            (0.58403360843658447, 0.58039218187332153, 0.58039218187332153),
            (0.58823531866073608, 0.58431375026702881, 0.58431375026702881),
            (0.59243696928024292, 0.58823531866073608, 0.58823531866073608),
            (0.59663867950439453, 0.59215688705444336, 0.59215688705444336),
            (0.60084033012390137, 0.60000002384185791, 0.60000002384185791),
            (0.60504204034805298, 0.60392159223556519, 0.60392159223556519),
            (0.60924369096755981, 0.60784316062927246, 0.60784316062927246),
            (0.61344540119171143, 0.61176472902297974, 0.61176472902297974),
            (0.61764705181121826, 0.61568629741668701, 0.61568629741668701),
            (0.62184876203536987, 0.61960786581039429, 0.61960786581039429),
            (0.62605041265487671, 0.62352943420410156, 0.62352943420410156),
            (0.63025212287902832, 0.62745100259780884, 0.62745100259780884),
            (0.63445377349853516, 0.63137257099151611, 0.63137257099151611),
            (0.63865548372268677, 0.63529413938522339, 0.63529413938522339),
            (0.6428571343421936, 0.63921570777893066, 0.63921570777893066),
            (0.64705884456634521, 0.64313727617263794, 0.64313727617263794),
            (0.65126049518585205, 0.64705884456634521, 0.64705884456634521),
            (0.65546220541000366, 0.65098041296005249, 0.65098041296005249),
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            (0.62605041265487671, 0.62352943420410156, 0.62352943420410156),
            (0.63025212287902832, 0.62745100259780884, 0.62745100259780884),
            (0.63445377349853516, 0.63137257099151611, 0.63137257099151611),
            (0.63865548372268677, 0.63529413938522339, 0.63529413938522339),
            (0.6428571343421936, 0.63921570777893066, 0.63921570777893066),
            (0.64705884456634521, 0.64313727617263794, 0.64313727617263794),
            (0.65126049518585205, 0.64705884456634521, 0.64705884456634521),
            (0.65546220541000366, 0.65098041296005249, 0.65098041296005249),
            (0.6596638560295105, 0.65490198135375977, 0.65490198135375977),
            (0.66386556625366211, 0.66274511814117432, 0.66274511814117432),
            (0.66806721687316895, 0.66666668653488159, 0.66666668653488159),
            (0.67226892709732056, 0.67058825492858887, 0.67058825492858887),
            (0.67647057771682739, 0.67450982332229614, 0.67450982332229614),
            (0.680672287940979, 0.67843139171600342, 0.67843139171600342),
            (0.68487393856048584, 0.68235296010971069, 0.68235296010971069),
            (0.68907564878463745, 0.68627452850341797, 0.68627452850341797),
            (0.69327729940414429, 0.69019609689712524, 0.69019609689712524),
            (0.6974790096282959, 0.69411766529083252, 0.69411766529083252),
            (0.70168066024780273, 0.69803923368453979, 0.69803923368453979),
            (0.70588237047195435, 0.70196080207824707, 0.70196080207824707),
            (0.71008402109146118, 0.70588237047195435, 0.70588237047195435),
            (0.71428573131561279, 0.70980393886566162, 0.70980393886566162),
            (0.71848738193511963, 0.7137255072593689, 0.7137255072593689),
            (0.72268909215927124, 0.71764707565307617, 0.71764707565307617),
            (0.72689074277877808, 0.72549021244049072, 0.72549021244049072),
            (0.73109245300292969, 0.729411780834198, 0.729411780834198),
            (0.73529410362243652, 0.73333334922790527, 0.73333334922790527),
            (0.73949581384658813, 0.73725491762161255, 0.73725491762161255),
            (0.74369746446609497, 0.74117648601531982, 0.74117648601531982),
            (0.74789917469024658, 0.7450980544090271, 0.7450980544090271),
            (0.75210082530975342, 0.74901962280273438, 0.74901962280273438),
            (0.75630253553390503, 0.75294119119644165, 0.75294119119644165),
            (0.76050418615341187, 0.75686275959014893, 0.75686275959014893),
            (0.76470589637756348, 0.7607843279838562, 0.7607843279838562),
            (0.76890754699707031, 0.76470589637756348, 0.76470589637756348),
            (0.77310925722122192, 0.76862746477127075, 0.76862746477127075),
            (0.77731090784072876, 0.77254903316497803, 0.77254903316497803),
            (0.78151261806488037, 0.7764706015586853, 0.7764706015586853),
            (0.78571426868438721, 0.78039216995239258, 0.78039216995239258),
            (0.78991597890853882, 0.78823530673980713, 0.78823530673980713),
            (0.79411762952804565, 0.7921568751335144, 0.7921568751335144),
            (0.79831933975219727, 0.79607844352722168, 0.79607844352722168),
            (0.8025209903717041, 0.80000001192092896, 0.80000001192092896),
            (0.80672270059585571, 0.80392158031463623, 0.80392158031463623),
            (0.81092435121536255, 0.80784314870834351, 0.80784314870834351),
            (0.81512606143951416, 0.81176471710205078, 0.81176471710205078),
            (0.819327712059021, 0.81568628549575806, 0.81568628549575806),
            (0.82352942228317261, 0.81960785388946533, 0.81960785388946533),
            (0.82773107290267944, 0.82352942228317261, 0.82352942228317261),
            (0.83193278312683105, 0.82745099067687988, 0.82745099067687988),
            (0.83613443374633789, 0.83137255907058716, 0.83137255907058716),
            (0.8403361439704895, 0.83529412746429443, 0.83529412746429443),
            (0.84453779458999634, 0.83921569585800171, 0.83921569585800171),
            (0.84873950481414795, 0.84313726425170898, 0.84313726425170898),
            (0.85294115543365479, 0.85098040103912354, 0.85098040103912354),
            (0.8571428656578064, 0.85490196943283081, 0.85490196943283081),
            (0.86134451627731323, 0.85882353782653809, 0.85882353782653809),
            (0.86554622650146484, 0.86274510622024536, 0.86274510622024536),
            (0.86974787712097168, 0.86666667461395264, 0.86666667461395264),
            (0.87394958734512329, 0.87058824300765991, 0.87058824300765991),
            (0.87815123796463013, 0.87450981140136719, 0.87450981140136719),
            (0.88235294818878174, 0.87843137979507446, 0.87843137979507446),
            (0.88655459880828857, 0.88235294818878174, 0.88235294818878174),
            (0.89075630903244019, 0.88627451658248901, 0.88627451658248901),
            (0.89495795965194702, 0.89019608497619629, 0.89019608497619629),
            (0.89915966987609863, 0.89411765336990356, 0.89411765336990356),
            (0.90336132049560547, 0.89803922176361084, 0.89803922176361084),
            (0.90756303071975708, 0.90196079015731812, 0.90196079015731812),
            (0.91176468133926392, 0.90588235855102539, 0.90588235855102539),
            (0.91596639156341553, 0.91372549533843994, 0.91372549533843994),
            (0.92016804218292236, 0.91764706373214722, 0.91764706373214722),
            (0.92436975240707397, 0.92156863212585449, 0.92156863212585449),
            (0.92857140302658081, 0.92549020051956177, 0.92549020051956177),
            (0.93277311325073242, 0.92941176891326904, 0.92941176891326904),
            (0.93697476387023926, 0.93333333730697632, 0.93333333730697632),
            (0.94117647409439087, 0.93725490570068359, 0.93725490570068359),
            (0.94537812471389771, 0.94117647409439087, 0.94117647409439087),
            (0.94957983493804932, 0.94509804248809814, 0.94509804248809814),
            (0.95378148555755615, 0.94901961088180542, 0.94901961088180542),
            (0.95798319578170776, 0.9529411792755127, 0.9529411792755127),
            (0.9621848464012146, 0.95686274766921997, 0.95686274766921997),
            (0.96638655662536621, 0.96078431606292725, 0.96078431606292725),
            (0.97058820724487305, 0.96470588445663452, 0.96470588445663452),
            (0.97478991746902466, 0.9686274528503418, 0.9686274528503418),
            (0.97899156808853149, 0.97647058963775635, 0.97647058963775635),
            (0.98319327831268311, 0.98039215803146362, 0.98039215803146362),
            (0.98739492893218994, 0.9843137264251709, 0.9843137264251709),
            (0.99159663915634155, 0.98823529481887817, 0.98823529481887817),
            (0.99579828977584839, 0.99215686321258545, 0.99215686321258545),
            (1.0, 0.99607843160629272, 0.99607843160629272)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def gist_heat(range, **traits):
    """ Generator for the 'gist_heat' colormap from GIST.
    """
    _data = dict(
        red = [(0.0, 0.0, 0.0),
            (0.0042016808874905109, 0.0039215688593685627, 0.0039215688593685627),
            (0.0084033617749810219, 0.0078431377187371254, 0.0078431377187371254),
            (0.012605042196810246, 0.015686275437474251, 0.015686275437474251),
            (0.016806723549962044, 0.019607843831181526, 0.019607843831181526),
            (0.021008403971791267, 0.027450980618596077, 0.027450980618596077),
            (0.025210084393620491, 0.031372550874948502, 0.031372550874948502),
            (0.029411764815449715, 0.039215687662363052, 0.039215687662363052),
            (0.033613447099924088, 0.043137256056070328, 0.043137256056070328),
            (0.037815127521753311, 0.050980392843484879, 0.050980392843484879),
            (0.042016807943582535, 0.058823529630899429, 0.058823529630899429),
            (0.046218488365411758, 0.066666670143604279, 0.066666670143604279),
            (0.050420168787240982, 0.070588238537311554, 0.070588238537311554),
            (0.054621849209070206, 0.078431375324726105, 0.078431375324726105),
            (0.058823529630899429, 0.08235294371843338, 0.08235294371843338),
            (0.063025213778018951, 0.090196080505847931, 0.090196080505847931),
            (0.067226894199848175, 0.094117648899555206, 0.094117648899555206),
            (0.071428574621677399, 0.10196078568696976, 0.10196078568696976),
            (0.075630255043506622, 0.10588235408067703, 0.10588235408067703),
            (0.079831935465335846, 0.10980392247438431, 0.10980392247438431),
            (0.08403361588716507, 0.11764705926179886, 0.11764705926179886),
            (0.088235296308994293, 0.12156862765550613, 0.12156862765550613),
            (0.092436976730823517, 0.12941177189350128, 0.12941177189350128),
            (0.09663865715265274, 0.13333334028720856, 0.13333334028720856),
            (0.10084033757448196, 0.14117647707462311, 0.14117647707462311),
            (0.10504201799631119, 0.14509804546833038, 0.14509804546833038),
            (0.10924369841814041, 0.15294118225574493, 0.15294118225574493),
            (0.11344537883996964, 0.15686275064945221, 0.15686275064945221),
            (0.11764705926179886, 0.16470588743686676, 0.16470588743686676),
            (0.12184873968362808, 0.16862745583057404, 0.16862745583057404),
            (0.1260504275560379, 0.18039216101169586, 0.18039216101169586),
            (0.13025210797786713, 0.18431372940540314, 0.18431372940540314),
            (0.13445378839969635, 0.19215686619281769, 0.19215686619281769),
            (0.13865546882152557, 0.19607843458652496, 0.19607843458652496),
            (0.1428571492433548, 0.20392157137393951, 0.20392157137393951),
            (0.14705882966518402, 0.20784313976764679, 0.20784313976764679),
            (0.15126051008701324, 0.21568627655506134, 0.21568627655506134),
            (0.15546219050884247, 0.21960784494876862, 0.21960784494876862),
            (0.15966387093067169, 0.22352941334247589, 0.22352941334247589),
            (0.16386555135250092, 0.23137255012989044, 0.23137255012989044),
            (0.16806723177433014, 0.23529411852359772, 0.23529411852359772),
            (0.17226891219615936, 0.24313725531101227, 0.24313725531101227),
            (0.17647059261798859, 0.24705882370471954, 0.24705882370471954),
            (0.18067227303981781, 0.25490197539329529, 0.25490197539329529),
            (0.18487395346164703, 0.25882354378700256, 0.25882354378700256),
            (0.18907563388347626, 0.26666668057441711, 0.26666668057441711),
            (0.19327731430530548, 0.27058824896812439, 0.27058824896812439),
            (0.1974789947271347, 0.27450981736183167, 0.27450981736183167),
            (0.20168067514896393, 0.28235295414924622, 0.28235295414924622),
            (0.20588235557079315, 0.28627452254295349, 0.28627452254295349),
            (0.21008403599262238, 0.29803922772407532, 0.29803922772407532),
            (0.2142857164144516, 0.30588236451148987, 0.30588236451148987),
            (0.21848739683628082, 0.30980393290519714, 0.30980393290519714),
            (0.22268907725811005, 0.31764706969261169, 0.31764706969261169),
            (0.22689075767993927, 0.32156863808631897, 0.32156863808631897),
            (0.23109243810176849, 0.32941177487373352, 0.32941177487373352),
            (0.23529411852359772, 0.3333333432674408, 0.3333333432674408),
            (0.23949579894542694, 0.33725491166114807, 0.33725491166114807),
            (0.24369747936725616, 0.34509804844856262, 0.34509804844856262),
            (0.24789915978908539, 0.3490196168422699, 0.3490196168422699),
            (0.25210085511207581, 0.36078432202339172, 0.36078432202339172),
            (0.25630253553390503, 0.36862745881080627, 0.36862745881080627),
            (0.26050421595573425, 0.37254902720451355, 0.37254902720451355),
            (0.26470589637756348, 0.3803921639919281, 0.3803921639919281),
            (0.2689075767993927, 0.38431373238563538, 0.38431373238563538),
            (0.27310925722122192, 0.38823530077934265, 0.38823530077934265),
            (0.27731093764305115, 0.3960784375667572, 0.3960784375667572),
            (0.28151261806488037, 0.40000000596046448, 0.40000000596046448),
            (0.28571429848670959, 0.40784314274787903, 0.40784314274787903),
            (0.28991597890853882, 0.4117647111415863, 0.4117647111415863),
            (0.29411765933036804, 0.42352941632270813, 0.42352941632270813),
            (0.29831933975219727, 0.43137255311012268, 0.43137255311012268),
            (0.30252102017402649, 0.43529412150382996, 0.43529412150382996),
            (0.30672270059585571, 0.44313725829124451, 0.44313725829124451),
            (0.31092438101768494, 0.44705882668495178, 0.44705882668495178),
            (0.31512606143951416, 0.45098039507865906, 0.45098039507865906),
            (0.31932774186134338, 0.45882353186607361, 0.45882353186607361),
            (0.32352942228317261, 0.46274510025978088, 0.46274510025978088),
            (0.32773110270500183, 0.47058823704719543, 0.47058823704719543),
            (0.33193278312683105, 0.47450980544090271, 0.47450980544090271),
            (0.33613446354866028, 0.48235294222831726, 0.48235294222831726),
            (0.3403361439704895, 0.48627451062202454, 0.48627451062202454),
            (0.34453782439231873, 0.49411764740943909, 0.49411764740943909),
            (0.34873950481414795, 0.49803921580314636, 0.49803921580314636),
            (0.35294118523597717, 0.50196081399917603, 0.50196081399917603),
            (0.3571428656578064, 0.50980395078659058, 0.50980395078659058),
            (0.36134454607963562, 0.51372551918029785, 0.51372551918029785),
            (0.36554622650146484, 0.5215686559677124, 0.5215686559677124),
            (0.36974790692329407, 0.52549022436141968, 0.52549022436141968),
            (0.37394958734512329, 0.53333336114883423, 0.53333336114883423),
            (0.37815126776695251, 0.54509806632995605, 0.54509806632995605),
            (0.38235294818878174, 0.54901963472366333, 0.54901963472366333),
            (0.38655462861061096, 0.55294120311737061, 0.55294120311737061),
            (0.39075630903244019, 0.56078433990478516, 0.56078433990478516),
            (0.39495798945426941, 0.56470590829849243, 0.56470590829849243),
            (0.39915966987609863, 0.57254904508590698, 0.57254904508590698),
            (0.40336135029792786, 0.57647061347961426, 0.57647061347961426),
            (0.40756303071975708, 0.58431375026702881, 0.58431375026702881),
            (0.4117647111415863, 0.58823531866073608, 0.58823531866073608),
            (0.41596639156341553, 0.59607845544815063, 0.59607845544815063),
            (0.42016807198524475, 0.60000002384185791, 0.60000002384185791),
            (0.42436975240707397, 0.60784316062927246, 0.60784316062927246),
            (0.4285714328289032, 0.61176472902297974, 0.61176472902297974),
            (0.43277311325073242, 0.61568629741668701, 0.61568629741668701),
            (0.43697479367256165, 0.62352943420410156, 0.62352943420410156),
            (0.44117647409439087, 0.62745100259780884, 0.62745100259780884),
            (0.44537815451622009, 0.63529413938522339, 0.63529413938522339),
            (0.44957983493804932, 0.63921570777893066, 0.63921570777893066),
            (0.45378151535987854, 0.64705884456634521, 0.64705884456634521),
            (0.45798319578170776, 0.65098041296005249, 0.65098041296005249),
            (0.46218487620353699, 0.66274511814117432, 0.66274511814117432),
            (0.46638655662536621, 0.66666668653488159, 0.66666668653488159),
            (0.47058823704719543, 0.67450982332229614, 0.67450982332229614),
            (0.47478991746902466, 0.67843139171600342, 0.67843139171600342),
            (0.47899159789085388, 0.68627452850341797, 0.68627452850341797),
            (0.48319327831268311, 0.69019609689712524, 0.69019609689712524),
            (0.48739495873451233, 0.69803923368453979, 0.69803923368453979),
            (0.49159663915634155, 0.70196080207824707, 0.70196080207824707),
            (0.49579831957817078, 0.70980393886566162, 0.70980393886566162),
            (0.5, 0.7137255072593689, 0.7137255072593689),
            (0.50420171022415161, 0.72549021244049072, 0.72549021244049072),
            (0.50840336084365845, 0.729411780834198, 0.729411780834198),
            (0.51260507106781006, 0.73725491762161255, 0.73725491762161255),
            (0.51680672168731689, 0.74117648601531982, 0.74117648601531982),
            (0.52100843191146851, 0.74901962280273438, 0.74901962280273438),
            (0.52521008253097534, 0.75294119119644165, 0.75294119119644165),
            (0.52941179275512695, 0.7607843279838562, 0.7607843279838562),
            (0.53361344337463379, 0.76470589637756348, 0.76470589637756348),
            (0.5378151535987854, 0.77254903316497803, 0.77254903316497803),
            (0.54201680421829224, 0.7764706015586853, 0.7764706015586853),
            (0.54621851444244385, 0.78823530673980713, 0.78823530673980713),
            (0.55042016506195068, 0.7921568751335144, 0.7921568751335144),
            (0.55462187528610229, 0.80000001192092896, 0.80000001192092896),
            (0.55882352590560913, 0.80392158031463623, 0.80392158031463623),
            (0.56302523612976074, 0.81176471710205078, 0.81176471710205078),
            (0.56722688674926758, 0.81568628549575806, 0.81568628549575806),
            (0.57142859697341919, 0.82352942228317261, 0.82352942228317261),
            (0.57563024759292603, 0.82745099067687988, 0.82745099067687988),
            (0.57983195781707764, 0.83137255907058716, 0.83137255907058716),
            (0.58403360843658447, 0.83921569585800171, 0.83921569585800171),
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            (0.86134451627731323, 0.72549021244049072, 0.72549021244049072),
            (0.86554622650146484, 0.73333334922790527, 0.73333334922790527),
            (0.86974787712097168, 0.73725491762161255, 0.73725491762161255),
            (0.87394958734512329, 0.7450980544090271, 0.7450980544090271),
            (0.87815123796463013, 0.75294119119644165, 0.75294119119644165),
            (0.88235294818878174, 0.76862746477127075, 0.76862746477127075),
            (0.88655459880828857, 0.7764706015586853, 0.7764706015586853),
            (0.89075630903244019, 0.78431373834609985, 0.78431373834609985),
            (0.89495795965194702, 0.7921568751335144, 0.7921568751335144),
            (0.89915966987609863, 0.80000001192092896, 0.80000001192092896),
            (0.90336132049560547, 0.80392158031463623, 0.80392158031463623),
            (0.90756303071975708, 0.81176471710205078, 0.81176471710205078),
            (0.91176468133926392, 0.81960785388946533, 0.81960785388946533),
            (0.91596639156341553, 0.82745099067687988, 0.82745099067687988),
            (0.92016804218292236, 0.83529412746429443, 0.83529412746429443),
            (0.92436975240707397, 0.84313726425170898, 0.84313726425170898),
            (0.92857140302658081, 0.85098040103912354, 0.85098040103912354),
            (0.93277311325073242, 0.85882353782653809, 0.85882353782653809),
            (0.93697476387023926, 0.86666667461395264, 0.86666667461395264),
            (0.94117647409439087, 0.87058824300765991, 0.87058824300765991),
            (0.94537812471389771, 0.87843137979507446, 0.87843137979507446),
            (0.94957983493804932, 0.88627451658248901, 0.88627451658248901),
            (0.95378148555755615, 0.89411765336990356, 0.89411765336990356),
            (0.95798319578170776, 0.90196079015731812, 0.90196079015731812),
            (0.9621848464012146, 0.90980392694473267, 0.90980392694473267),
            (0.96638655662536621, 0.92549020051956177, 0.92549020051956177),
            (0.97058820724487305, 0.93333333730697632, 0.93333333730697632),
            (0.97478991746902466, 0.93725490570068359, 0.93725490570068359),
            (0.97899156808853149, 0.94509804248809814, 0.94509804248809814),
            (0.98319327831268311, 0.9529411792755127, 0.9529411792755127),
            (0.98739492893218994, 0.96078431606292725, 0.96078431606292725),
            (0.99159663915634155, 0.9686274528503418, 0.9686274528503418),
            (0.99579828977584839, 0.97647058963775635, 0.97647058963775635),
            (1.0, 0.9843137264251709, 0.9843137264251709)],
        blue = [(0.0, 0.0, 0.0),
            (0.0042016808874905109, 0.0, 0.0),
            (0.0084033617749810219, 0.0, 0.0),
            (0.012605042196810246, 0.0, 0.0),
            (0.016806723549962044, 0.0, 0.0),
            (0.021008403971791267, 0.0, 0.0),
            (0.025210084393620491, 0.0, 0.0),
            (0.029411764815449715, 0.0, 0.0),
            (0.033613447099924088, 0.0, 0.0),
            (0.037815127521753311, 0.0, 0.0),
            (0.042016807943582535, 0.0, 0.0),
            (0.046218488365411758, 0.0, 0.0),
            (0.050420168787240982, 0.0, 0.0),
            (0.054621849209070206, 0.0, 0.0),
            (0.058823529630899429, 0.0, 0.0),
            (0.063025213778018951, 0.0, 0.0),
            (0.067226894199848175, 0.0, 0.0),
            (0.071428574621677399, 0.0, 0.0),
            (0.075630255043506622, 0.0, 0.0),
            (0.079831935465335846, 0.0, 0.0),
            (0.08403361588716507, 0.0, 0.0),
            (0.088235296308994293, 0.0, 0.0),
            (0.092436976730823517, 0.0, 0.0),
            (0.09663865715265274, 0.0, 0.0),
            (0.10084033757448196, 0.0, 0.0),
            (0.10504201799631119, 0.0, 0.0),
            (0.10924369841814041, 0.0, 0.0),
            (0.11344537883996964, 0.0, 0.0),
            (0.11764705926179886, 0.0, 0.0),
            (0.12184873968362808, 0.0, 0.0),
            (0.1260504275560379, 0.0, 0.0),
            (0.13025210797786713, 0.0, 0.0),
            (0.13445378839969635, 0.0, 0.0),
            (0.13865546882152557, 0.0, 0.0),
            (0.1428571492433548, 0.0, 0.0),
            (0.14705882966518402, 0.0, 0.0),
            (0.15126051008701324, 0.0, 0.0),
            (0.15546219050884247, 0.0, 0.0),
            (0.15966387093067169, 0.0, 0.0),
            (0.16386555135250092, 0.0, 0.0),
            (0.16806723177433014, 0.0, 0.0),
            (0.17226891219615936, 0.0, 0.0),
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            (0.30672270059585571, 0.0, 0.0),
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            (0.36554622650146484, 0.0, 0.0),
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            (0.5, 0.0, 0.0),
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            (0.60084033012390137, 0.0, 0.0),
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            (0.75210082530975342, 0.0, 0.0),
            (0.75630253553390503, 0.027450980618596077, 0.027450980618596077),
            (0.76050418615341187, 0.043137256056070328, 0.043137256056070328),
            (0.76470589637756348, 0.058823529630899429, 0.058823529630899429),
            (0.76890754699707031, 0.074509806931018829, 0.074509806931018829),
            (0.77310925722122192, 0.090196080505847931, 0.090196080505847931),
            (0.77731090784072876, 0.10588235408067703, 0.10588235408067703),
            (0.78151261806488037, 0.12156862765550613, 0.12156862765550613),
            (0.78571426868438721, 0.13725490868091583, 0.13725490868091583),
            (0.78991597890853882, 0.15294118225574493, 0.15294118225574493),
            (0.79411762952804565, 0.16862745583057404, 0.16862745583057404),
            (0.79831933975219727, 0.20000000298023224, 0.20000000298023224),
            (0.8025209903717041, 0.21176470816135406, 0.21176470816135406),
            (0.80672270059585571, 0.22745098173618317, 0.22745098173618317),
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            (0.81512606143951416, 0.25882354378700256, 0.25882354378700256),
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            (0.82773107290267944, 0.30588236451148987, 0.30588236451148987),
            (0.83193278312683105, 0.32156863808631897, 0.32156863808631897),
            (0.83613443374633789, 0.33725491166114807, 0.33725491166114807),
            (0.8403361439704895, 0.35294118523597717, 0.35294118523597717),
            (0.84453779458999634, 0.36862745881080627, 0.36862745881080627),
            (0.84873950481414795, 0.38431373238563538, 0.38431373238563538),
            (0.85294115543365479, 0.40000000596046448, 0.40000000596046448),
            (0.8571428656578064, 0.4117647111415863, 0.4117647111415863),
            (0.86134451627731323, 0.42745098471641541, 0.42745098471641541),
            (0.86554622650146484, 0.44313725829124451, 0.44313725829124451),
            (0.86974787712097168, 0.45882353186607361, 0.45882353186607361),
            (0.87394958734512329, 0.47450980544090271, 0.47450980544090271),
            (0.87815123796463013, 0.49019607901573181, 0.49019607901573181),
            (0.88235294818878174, 0.5215686559677124, 0.5215686559677124),
            (0.88655459880828857, 0.5372549295425415, 0.5372549295425415),
            (0.89075630903244019, 0.55294120311737061, 0.55294120311737061),
            (0.89495795965194702, 0.56862747669219971, 0.56862747669219971),
            (0.89915966987609863, 0.58431375026702881, 0.58431375026702881),
            (0.90336132049560547, 0.60000002384185791, 0.60000002384185791),
            (0.90756303071975708, 0.61176472902297974, 0.61176472902297974),
            (0.91176468133926392, 0.62745100259780884, 0.62745100259780884),
            (0.91596639156341553, 0.64313727617263794, 0.64313727617263794),
            (0.92016804218292236, 0.65882354974746704, 0.65882354974746704),
            (0.92436975240707397, 0.67450982332229614, 0.67450982332229614),
            (0.92857140302658081, 0.69019609689712524, 0.69019609689712524),
            (0.93277311325073242, 0.70588237047195435, 0.70588237047195435),
            (0.93697476387023926, 0.72156864404678345, 0.72156864404678345),
            (0.94117647409439087, 0.73725491762161255, 0.73725491762161255),
            (0.94537812471389771, 0.75294119119644165, 0.75294119119644165),
            (0.94957983493804932, 0.76862746477127075, 0.76862746477127075),
            (0.95378148555755615, 0.78431373834609985, 0.78431373834609985),
            (0.95798319578170776, 0.80000001192092896, 0.80000001192092896),
            (0.9621848464012146, 0.81176471710205078, 0.81176471710205078),
            (0.96638655662536621, 0.84313726425170898, 0.84313726425170898),
            (0.97058820724487305, 0.85882353782653809, 0.85882353782653809),
            (0.97478991746902466, 0.87450981140136719, 0.87450981140136719),
            (0.97899156808853149, 0.89019608497619629, 0.89019608497619629),
            (0.98319327831268311, 0.90588235855102539, 0.90588235855102539),
            (0.98739492893218994, 0.92156863212585449, 0.92156863212585449),
            (0.99159663915634155, 0.93725490570068359, 0.93725490570068359),
            (0.99579828977584839, 0.9529411792755127, 0.9529411792755127),
            (1.0, 0.9686274528503418, 0.9686274528503418)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def gist_ncar(range, **traits):
    """ Generator for the 'gist_ncar' colormap from GIST.
    """
    _data = dict(
        red = [(0.0, 0.0, 0.0),
            (0.0050505050458014011, 0.0, 0.0),
            (0.010101010091602802, 0.0, 0.0),
            (0.015151515603065491, 0.0, 0.0),
            (0.020202020183205605, 0.0, 0.0),
            (0.025252524763345718, 0.0, 0.0),
            (0.030303031206130981, 0.0, 0.0),
            (0.035353533923625946, 0.0, 0.0),
            (0.040404040366411209, 0.0, 0.0),
            (0.045454546809196472, 0.0, 0.0),
            (0.050505049526691437, 0.0, 0.0),
            (0.0555555559694767, 0.0, 0.0),
            (0.060606062412261963, 0.0, 0.0),
            (0.065656565129756927, 0.0, 0.0),
            (0.070707067847251892, 0.0, 0.0),
            (0.075757578015327454, 0.0, 0.0),
            (0.080808080732822418, 0.0, 0.0),
            (0.085858583450317383, 0.0, 0.0),
            (0.090909093618392944, 0.0, 0.0),
            (0.095959596335887909, 0.0, 0.0),
            (0.10101009905338287, 0.0, 0.0),
            (0.10606060922145844, 0.0, 0.0),
            (0.1111111119389534, 0.0, 0.0),
            (0.11616161465644836, 0.0, 0.0),
            (0.12121212482452393, 0.0, 0.0),
            (0.12626262009143829, 0.0, 0.0),
            (0.13131313025951385, 0.0, 0.0),
            (0.13636364042758942, 0.0, 0.0),
            (0.14141413569450378, 0.0, 0.0),
            (0.14646464586257935, 0.0, 0.0),
            (0.15151515603065491, 0.0, 0.0),
            (0.15656565129756927, 0.0, 0.0),
            (0.16161616146564484, 0.0, 0.0),
            (0.1666666716337204, 0.0, 0.0),
            (0.17171716690063477, 0.0, 0.0),
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            (0.8737373948097229, 0.96470588445663452, 0.96470588445663452),
            (0.87878787517547607, 0.95686274766921997, 0.95686274766921997),
            (0.88383835554122925, 0.94901961088180542, 0.94901961088180542),
            (0.8888888955116272, 0.94509804248809814, 0.94509804248809814),
            (0.89393937587738037, 0.93725490570068359, 0.93725490570068359),
            (0.89898991584777832, 0.93333333730697632, 0.93333333730697632),
            (0.90404039621353149, 0.93333333730697632, 0.93333333730697632),
            (0.90909093618392944, 0.93725490570068359, 0.93725490570068359),
            (0.91414141654968262, 0.93725490570068359, 0.93725490570068359),
            (0.91919189691543579, 0.94117647409439087, 0.94117647409439087),
            (0.92424243688583374, 0.94509804248809814, 0.94509804248809814),
            (0.92929291725158691, 0.94509804248809814, 0.94509804248809814),
            (0.93434345722198486, 0.94901961088180542, 0.94901961088180542),
            (0.93939393758773804, 0.9529411792755127, 0.9529411792755127),
            (0.94444441795349121, 0.9529411792755127, 0.9529411792755127),
            (0.94949495792388916, 0.95686274766921997, 0.95686274766921997),
            (0.95454543828964233, 0.96078431606292725, 0.96078431606292725),
            (0.95959597826004028, 0.96470588445663452, 0.96470588445663452),
            (0.96464645862579346, 0.9686274528503418, 0.9686274528503418),
            (0.96969699859619141, 0.97254902124404907, 0.97254902124404907),
            (0.97474747896194458, 0.97647058963775635, 0.97647058963775635),
            (0.97979795932769775, 0.98039215803146362, 0.98039215803146362),
            (0.9848484992980957, 0.9843137264251709, 0.9843137264251709),
            (0.98989897966384888, 0.98823529481887817, 0.98823529481887817),
            (0.99494951963424683, 0.99215686321258545, 0.99215686321258545),
            (1.0, 0.99607843160629272, 0.99607843160629272)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def gist_rainbow(range, **traits):
    """ Generator for the 'gist_rainbow' colormap from GIST.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.0042016808874905109, 1.0, 1.0),
            (0.0084033617749810219, 1.0, 1.0),
            (0.012605042196810246, 1.0, 1.0),
            (0.016806723549962044, 1.0, 1.0),
            (0.021008403971791267, 1.0, 1.0),
            (0.025210084393620491, 1.0, 1.0),
            (0.029411764815449715, 1.0, 1.0),
            (0.033613447099924088, 1.0, 1.0),
            (0.037815127521753311, 1.0, 1.0),
            (0.042016807943582535, 1.0, 1.0),
            (0.046218488365411758, 1.0, 1.0),
            (0.050420168787240982, 1.0, 1.0),
            (0.054621849209070206, 1.0, 1.0),
            (0.058823529630899429, 1.0, 1.0),
            (0.063025213778018951, 1.0, 1.0),
            (0.067226894199848175, 1.0, 1.0),
            (0.071428574621677399, 1.0, 1.0),
            (0.075630255043506622, 1.0, 1.0),
            (0.079831935465335846, 1.0, 1.0),
            (0.08403361588716507, 1.0, 1.0),
            (0.088235296308994293, 1.0, 1.0),
            (0.092436976730823517, 1.0, 1.0),
            (0.09663865715265274, 1.0, 1.0),
            (0.10084033757448196, 1.0, 1.0),
            (0.10504201799631119, 1.0, 1.0),
            (0.10924369841814041, 1.0, 1.0),
            (0.11344537883996964, 1.0, 1.0),
            (0.11764705926179886, 1.0, 1.0),
            (0.12184873968362808, 1.0, 1.0),
            (0.1260504275560379, 1.0, 1.0),
            (0.13025210797786713, 1.0, 1.0),
            (0.13445378839969635, 1.0, 1.0),
            (0.13865546882152557, 1.0, 1.0),
            (0.1428571492433548, 1.0, 1.0),
            (0.14705882966518402, 1.0, 1.0),
            (0.15126051008701324, 1.0, 1.0),
            (0.15546219050884247, 1.0, 1.0),
            (0.15966387093067169, 1.0, 1.0),
            (0.16386555135250092, 1.0, 1.0),
            (0.16806723177433014, 1.0, 1.0),
            (0.17226891219615936, 1.0, 1.0),
            (0.17647059261798859, 1.0, 1.0),
            (0.18067227303981781, 1.0, 1.0),
            (0.18487395346164703, 1.0, 1.0),
            (0.18907563388347626, 1.0, 1.0),
            (0.19327731430530548, 1.0, 1.0),
            (0.1974789947271347, 1.0, 1.0),
            (0.20168067514896393, 1.0, 1.0),
            (0.20588235557079315, 1.0, 1.0),
            (0.21008403599262238, 1.0, 1.0),
            (0.2142857164144516, 1.0, 1.0),
            (0.21848739683628082, 1.0, 1.0),
            (0.22268907725811005, 0.96078431606292725, 0.96078431606292725),
            (0.22689075767993927, 0.94117647409439087, 0.94117647409439087),
            (0.23109243810176849, 0.92156863212585449, 0.92156863212585449),
            (0.23529411852359772, 0.89803922176361084, 0.89803922176361084),
            (0.23949579894542694, 0.87843137979507446, 0.87843137979507446),
            (0.24369747936725616, 0.85882353782653809, 0.85882353782653809),
            (0.24789915978908539, 0.83529412746429443, 0.83529412746429443),
            (0.25210085511207581, 0.81568628549575806, 0.81568628549575806),
            (0.25630253553390503, 0.7921568751335144, 0.7921568751335144),
            (0.26050421595573425, 0.77254903316497803, 0.77254903316497803),
            (0.26470589637756348, 0.75294119119644165, 0.75294119119644165),
            (0.2689075767993927, 0.729411780834198, 0.729411780834198),
            (0.27310925722122192, 0.70980393886566162, 0.70980393886566162),
            (0.27731093764305115, 0.68627452850341797, 0.68627452850341797),
            (0.28151261806488037, 0.66666668653488159, 0.66666668653488159),
            (0.28571429848670959, 0.62352943420410156, 0.62352943420410156),
            (0.28991597890853882, 0.60392159223556519, 0.60392159223556519),
            (0.29411765933036804, 0.58431375026702881, 0.58431375026702881),
            (0.29831933975219727, 0.56078433990478516, 0.56078433990478516),
            (0.30252102017402649, 0.54117649793624878, 0.54117649793624878),
            (0.30672270059585571, 0.51764708757400513, 0.51764708757400513),
            (0.31092438101768494, 0.49803921580314636, 0.49803921580314636),
            (0.31512606143951416, 0.47843137383460999, 0.47843137383460999),
            (0.31932774186134338, 0.45490196347236633, 0.45490196347236633),
            (0.32352942228317261, 0.43529412150382996, 0.43529412150382996),
            (0.32773110270500183, 0.41568627953529358, 0.41568627953529358),
            (0.33193278312683105, 0.39215686917304993, 0.39215686917304993),
            (0.33613446354866028, 0.37254902720451355, 0.37254902720451355),
            (0.3403361439704895, 0.3490196168422699, 0.3490196168422699),
            (0.34453782439231873, 0.32941177487373352, 0.32941177487373352),
            (0.34873950481414795, 0.28627452254295349, 0.28627452254295349),
            (0.35294118523597717, 0.26666668057441711, 0.26666668057441711),
            (0.3571428656578064, 0.24705882370471954, 0.24705882370471954),
            (0.36134454607963562, 0.22352941334247589, 0.22352941334247589),
            (0.36554622650146484, 0.20392157137393951, 0.20392157137393951),
            (0.36974790692329407, 0.18039216101169586, 0.18039216101169586),
            (0.37394958734512329, 0.16078431904315948, 0.16078431904315948),
            (0.37815126776695251, 0.14117647707462311, 0.14117647707462311),
            (0.38235294818878174, 0.11764705926179886, 0.11764705926179886),
            (0.38655462861061096, 0.098039217293262482, 0.098039217293262482),
            (0.39075630903244019, 0.074509806931018829, 0.074509806931018829),
            (0.39495798945426941, 0.054901961237192154, 0.054901961237192154),
            (0.39915966987609863, 0.035294119268655777, 0.035294119268655777),
            (0.40336135029792786, 0.011764706112444401, 0.011764706112444401),
            (0.40756303071975708, 0.0, 0.0),
            (0.4117647111415863, 0.0, 0.0),
            (0.41596639156341553, 0.0, 0.0),
            (0.42016807198524475, 0.0, 0.0),
            (0.42436975240707397, 0.0, 0.0),
            (0.4285714328289032, 0.0, 0.0),
            (0.43277311325073242, 0.0, 0.0),
            (0.43697479367256165, 0.0, 0.0),
            (0.44117647409439087, 0.0, 0.0),
            (0.44537815451622009, 0.0, 0.0),
            (0.44957983493804932, 0.0, 0.0),
            (0.45378151535987854, 0.0, 0.0),
            (0.45798319578170776, 0.0, 0.0),
            (0.46218487620353699, 0.0, 0.0),
            (0.46638655662536621, 0.0, 0.0),
            (0.47058823704719543, 0.0, 0.0),
            (0.47478991746902466, 0.0, 0.0),
            (0.47899159789085388, 0.0, 0.0),
            (0.48319327831268311, 0.0, 0.0),
            (0.48739495873451233, 0.0, 0.0),
            (0.49159663915634155, 0.0, 0.0),
            (0.49579831957817078, 0.0, 0.0),
            (0.5, 0.0, 0.0),
            (0.50420171022415161, 0.0, 0.0),
            (0.50840336084365845, 0.0, 0.0),
            (0.51260507106781006, 0.0, 0.0),
            (0.51680672168731689, 0.0, 0.0),
            (0.52100843191146851, 0.0, 0.0),
            (0.52521008253097534, 0.0, 0.0),
            (0.52941179275512695, 0.0, 0.0),
            (0.53361344337463379, 0.0, 0.0),
            (0.5378151535987854, 0.0, 0.0),
            (0.54201680421829224, 0.0, 0.0),
            (0.54621851444244385, 0.0, 0.0),
            (0.55042016506195068, 0.0, 0.0),
            (0.55462187528610229, 0.0, 0.0),
            (0.55882352590560913, 0.0, 0.0),
            (0.56302523612976074, 0.0, 0.0),
            (0.56722688674926758, 0.0, 0.0),
            (0.57142859697341919, 0.0, 0.0),
            (0.57563024759292603, 0.0, 0.0),
            (0.57983195781707764, 0.0, 0.0),
            (0.58403360843658447, 0.0, 0.0),
            (0.58823531866073608, 0.0, 0.0),
            (0.59243696928024292, 0.0, 0.0),
            (0.59663867950439453, 0.0, 0.0),
            (0.60084033012390137, 0.0, 0.0),
            (0.60504204034805298, 0.0, 0.0),
            (0.60924369096755981, 0.0, 0.0),
            (0.61344540119171143, 0.0, 0.0),
            (0.61764705181121826, 0.0, 0.0),
            (0.62184876203536987, 0.0, 0.0),
            (0.62605041265487671, 0.0, 0.0),
            (0.63025212287902832, 0.0, 0.0),
            (0.63445377349853516, 0.0, 0.0),
            (0.63865548372268677, 0.0, 0.0),
            (0.6428571343421936, 0.0, 0.0),
            (0.64705884456634521, 0.0, 0.0),
            (0.65126049518585205, 0.0, 0.0),
            (0.65546220541000366, 0.0, 0.0),
            (0.6596638560295105, 0.0, 0.0),
            (0.66386556625366211, 0.0, 0.0),
            (0.66806721687316895, 0.0, 0.0),
            (0.67226892709732056, 0.0, 0.0),
            (0.67647057771682739, 0.0, 0.0),
            (0.680672287940979, 0.0, 0.0),
            (0.68487393856048584, 0.0, 0.0),
            (0.68907564878463745, 0.0, 0.0),
            (0.69327729940414429, 0.0, 0.0),
            (0.6974790096282959, 0.0, 0.0),
            (0.70168066024780273, 0.0, 0.0),
            (0.70588237047195435, 0.0, 0.0),
            (0.71008402109146118, 0.0, 0.0),
            (0.71428573131561279, 0.0, 0.0),
            (0.71848738193511963, 0.0, 0.0),
            (0.72268909215927124, 0.0, 0.0),
            (0.72689074277877808, 0.0, 0.0),
            (0.73109245300292969, 0.0, 0.0),
            (0.73529410362243652, 0.0, 0.0),
            (0.73949581384658813, 0.0, 0.0),
            (0.74369746446609497, 0.0, 0.0),
            (0.74789917469024658, 0.0, 0.0),
            (0.75210082530975342, 0.0, 0.0),
            (0.75630253553390503, 0.0, 0.0),
            (0.76050418615341187, 0.0, 0.0),
            (0.76470589637756348, 0.0, 0.0),
            (0.76890754699707031, 0.0, 0.0),
            (0.77310925722122192, 0.0, 0.0),
            (0.77731090784072876, 0.0, 0.0),
            (0.78151261806488037, 0.0078431377187371254, 0.0078431377187371254),
            (0.78571426868438721, 0.027450980618596077, 0.027450980618596077),
            (0.78991597890853882, 0.070588238537311554, 0.070588238537311554),
            (0.79411762952804565, 0.094117648899555206, 0.094117648899555206),
            (0.79831933975219727, 0.11372549086809158, 0.11372549086809158),
            (0.8025209903717041, 0.13333334028720856, 0.13333334028720856),
            (0.80672270059585571, 0.15686275064945221, 0.15686275064945221),
            (0.81092435121536255, 0.17647059261798859, 0.17647059261798859),
            (0.81512606143951416, 0.19607843458652496, 0.19607843458652496),
            (0.819327712059021, 0.21960784494876862, 0.21960784494876862),
            (0.82352942228317261, 0.23921568691730499, 0.23921568691730499),
            (0.82773107290267944, 0.26274511218070984, 0.26274511218070984),
            (0.83193278312683105, 0.28235295414924622, 0.28235295414924622),
            (0.83613443374633789, 0.30196079611778259, 0.30196079611778259),
            (0.8403361439704895, 0.32549020648002625, 0.32549020648002625),
            (0.84453779458999634, 0.34509804844856262, 0.34509804844856262),
            (0.84873950481414795, 0.364705890417099, 0.364705890417099),
            (0.85294115543365479, 0.40784314274787903, 0.40784314274787903),
            (0.8571428656578064, 0.43137255311012268, 0.43137255311012268),
            (0.86134451627731323, 0.45098039507865906, 0.45098039507865906),
            (0.86554622650146484, 0.47058823704719543, 0.47058823704719543),
            (0.86974787712097168, 0.49411764740943909, 0.49411764740943909),
            (0.87394958734512329, 0.51372551918029785, 0.51372551918029785),
            (0.87815123796463013, 0.53333336114883423, 0.53333336114883423),
            (0.88235294818878174, 0.55686277151107788, 0.55686277151107788),
            (0.88655459880828857, 0.57647061347961426, 0.57647061347961426),
            (0.89075630903244019, 0.60000002384185791, 0.60000002384185791),
            (0.89495795965194702, 0.61960786581039429, 0.61960786581039429),
            (0.89915966987609863, 0.63921570777893066, 0.63921570777893066),
            (0.90336132049560547, 0.66274511814117432, 0.66274511814117432),
            (0.90756303071975708, 0.68235296010971069, 0.68235296010971069),
            (0.91176468133926392, 0.70588237047195435, 0.70588237047195435),
            (0.91596639156341553, 0.7450980544090271, 0.7450980544090271),
            (0.92016804218292236, 0.76862746477127075, 0.76862746477127075),
            (0.92436975240707397, 0.78823530673980713, 0.78823530673980713),
            (0.92857140302658081, 0.80784314870834351, 0.80784314870834351),
            (0.93277311325073242, 0.83137255907058716, 0.83137255907058716),
            (0.93697476387023926, 0.85098040103912354, 0.85098040103912354),
            (0.94117647409439087, 0.87450981140136719, 0.87450981140136719),
            (0.94537812471389771, 0.89411765336990356, 0.89411765336990356),
            (0.94957983493804932, 0.91372549533843994, 0.91372549533843994),
            (0.95378148555755615, 0.93725490570068359, 0.93725490570068359),
            (0.95798319578170776, 0.95686274766921997, 0.95686274766921997),
            (0.9621848464012146, 0.97647058963775635, 0.97647058963775635),
            (0.96638655662536621, 1.0, 1.0),
            (0.97058820724487305, 1.0, 1.0),
            (0.97478991746902466, 1.0, 1.0),
            (0.97899156808853149, 1.0, 1.0),
            (0.98319327831268311, 1.0, 1.0),
            (0.98739492893218994, 1.0, 1.0),
            (0.99159663915634155, 1.0, 1.0),
            (0.99579828977584839, 1.0, 1.0),
            (1.0, 1.0, 1.0)],
        green = [(0.0, 0.0, 0.0),
            (0.0042016808874905109, 0.0, 0.0),
            (0.0084033617749810219, 0.0, 0.0),
            (0.012605042196810246, 0.0, 0.0),
            (0.016806723549962044, 0.0, 0.0),
            (0.021008403971791267, 0.0, 0.0),
            (0.025210084393620491, 0.0, 0.0),
            (0.029411764815449715, 0.0, 0.0),
            (0.033613447099924088, 0.019607843831181526, 0.019607843831181526),
            (0.037815127521753311, 0.043137256056070328, 0.043137256056070328),
            (0.042016807943582535, 0.062745101749897003, 0.062745101749897003),
            (0.046218488365411758, 0.086274512112140656, 0.086274512112140656),
            (0.050420168787240982, 0.10588235408067703, 0.10588235408067703),
            (0.054621849209070206, 0.12549020349979401, 0.12549020349979401),
            (0.058823529630899429, 0.14901961386203766, 0.14901961386203766),
            (0.063025213778018951, 0.16862745583057404, 0.16862745583057404),
            (0.067226894199848175, 0.18823529779911041, 0.18823529779911041),
            (0.071428574621677399, 0.21176470816135406, 0.21176470816135406),
            (0.075630255043506622, 0.23137255012989044, 0.23137255012989044),
            (0.079831935465335846, 0.25490197539329529, 0.25490197539329529),
            (0.08403361588716507, 0.27450981736183167, 0.27450981736183167),
            (0.088235296308994293, 0.29411765933036804, 0.29411765933036804),
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            (0.43277311325073242, 0.15294118225574493, 0.15294118225574493),
            (0.43697479367256165, 0.17254902422428131, 0.17254902422428131),
            (0.44117647409439087, 0.19215686619281769, 0.19215686619281769),
            (0.44537815451622009, 0.21568627655506134, 0.21568627655506134),
            (0.44957983493804932, 0.23529411852359772, 0.23529411852359772),
            (0.45378151535987854, 0.25882354378700256, 0.25882354378700256),
            (0.45798319578170776, 0.27843138575553894, 0.27843138575553894),
            (0.46218487620353699, 0.29803922772407532, 0.29803922772407532),
            (0.46638655662536621, 0.32156863808631897, 0.32156863808631897),
            (0.47058823704719543, 0.34117648005485535, 0.34117648005485535),
            (0.47478991746902466, 0.38431373238563538, 0.38431373238563538),
            (0.47899159789085388, 0.40392157435417175, 0.40392157435417175),
            (0.48319327831268311, 0.42745098471641541, 0.42745098471641541),
            (0.48739495873451233, 0.44705882668495178, 0.44705882668495178),
            (0.49159663915634155, 0.46666666865348816, 0.46666666865348816),
            (0.49579831957817078, 0.49019607901573181, 0.49019607901573181),
            (0.5, 0.50980395078659058, 0.50980395078659058),
            (0.50420171022415161, 0.52941179275512695, 0.52941179275512695),
            (0.50840336084365845, 0.55294120311737061, 0.55294120311737061),
            (0.51260507106781006, 0.57254904508590698, 0.57254904508590698),
            (0.51680672168731689, 0.59607845544815063, 0.59607845544815063),
            (0.52100843191146851, 0.61568629741668701, 0.61568629741668701),
            (0.52521008253097534, 0.63529413938522339, 0.63529413938522339),
            (0.52941179275512695, 0.65882354974746704, 0.65882354974746704),
            (0.53361344337463379, 0.67843139171600342, 0.67843139171600342),
            (0.5378151535987854, 0.72156864404678345, 0.72156864404678345),
            (0.54201680421829224, 0.74117648601531982, 0.74117648601531982),
            (0.54621851444244385, 0.76470589637756348, 0.76470589637756348),
            (0.55042016506195068, 0.78431373834609985, 0.78431373834609985),
            (0.55462187528610229, 0.80392158031463623, 0.80392158031463623),
            (0.55882352590560913, 0.82745099067687988, 0.82745099067687988),
            (0.56302523612976074, 0.84705883264541626, 0.84705883264541626),
            (0.56722688674926758, 0.87058824300765991, 0.87058824300765991),
            (0.57142859697341919, 0.89019608497619629, 0.89019608497619629),
            (0.57563024759292603, 0.90980392694473267, 0.90980392694473267),
            (0.57983195781707764, 0.93333333730697632, 0.93333333730697632),
            (0.58403360843658447, 0.9529411792755127, 0.9529411792755127),
            (0.58823531866073608, 0.97254902124404907, 0.97254902124404907),
            (0.59243696928024292, 0.99607843160629272, 0.99607843160629272),
            (0.59663867950439453, 1.0, 1.0),
            (0.60084033012390137, 1.0, 1.0),
            (0.60504204034805298, 1.0, 1.0),
            (0.60924369096755981, 1.0, 1.0),
            (0.61344540119171143, 1.0, 1.0),
            (0.61764705181121826, 1.0, 1.0),
            (0.62184876203536987, 1.0, 1.0),
            (0.62605041265487671, 1.0, 1.0),
            (0.63025212287902832, 1.0, 1.0),
            (0.63445377349853516, 1.0, 1.0),
            (0.63865548372268677, 1.0, 1.0),
            (0.6428571343421936, 1.0, 1.0),
            (0.64705884456634521, 1.0, 1.0),
            (0.65126049518585205, 1.0, 1.0),
            (0.65546220541000366, 1.0, 1.0),
            (0.6596638560295105, 1.0, 1.0),
            (0.66386556625366211, 1.0, 1.0),
            (0.66806721687316895, 1.0, 1.0),
            (0.67226892709732056, 1.0, 1.0),
            (0.67647057771682739, 1.0, 1.0),
            (0.680672287940979, 1.0, 1.0),
            (0.68487393856048584, 1.0, 1.0),
            (0.68907564878463745, 1.0, 1.0),
            (0.69327729940414429, 1.0, 1.0),
            (0.6974790096282959, 1.0, 1.0),
            (0.70168066024780273, 1.0, 1.0),
            (0.70588237047195435, 1.0, 1.0),
            (0.71008402109146118, 1.0, 1.0),
            (0.71428573131561279, 1.0, 1.0),
            (0.71848738193511963, 1.0, 1.0),
            (0.72268909215927124, 1.0, 1.0),
            (0.72689074277877808, 1.0, 1.0),
            (0.73109245300292969, 1.0, 1.0),
            (0.73529410362243652, 1.0, 1.0),
            (0.73949581384658813, 1.0, 1.0),
            (0.74369746446609497, 1.0, 1.0),
            (0.74789917469024658, 1.0, 1.0),
            (0.75210082530975342, 1.0, 1.0),
            (0.75630253553390503, 1.0, 1.0),
            (0.76050418615341187, 1.0, 1.0),
            (0.76470589637756348, 1.0, 1.0),
            (0.76890754699707031, 1.0, 1.0),
            (0.77310925722122192, 1.0, 1.0),
            (0.77731090784072876, 1.0, 1.0),
            (0.78151261806488037, 1.0, 1.0),
            (0.78571426868438721, 1.0, 1.0),
            (0.78991597890853882, 1.0, 1.0),
            (0.79411762952804565, 1.0, 1.0),
            (0.79831933975219727, 1.0, 1.0),
            (0.8025209903717041, 1.0, 1.0),
            (0.80672270059585571, 1.0, 1.0),
            (0.81092435121536255, 1.0, 1.0),
            (0.81512606143951416, 1.0, 1.0),
            (0.819327712059021, 1.0, 1.0),
            (0.82352942228317261, 1.0, 1.0),
            (0.82773107290267944, 1.0, 1.0),
            (0.83193278312683105, 1.0, 1.0),
            (0.83613443374633789, 1.0, 1.0),
            (0.8403361439704895, 1.0, 1.0),
            (0.84453779458999634, 1.0, 1.0),
            (0.84873950481414795, 1.0, 1.0),
            (0.85294115543365479, 1.0, 1.0),
            (0.8571428656578064, 1.0, 1.0),
            (0.86134451627731323, 1.0, 1.0),
            (0.86554622650146484, 1.0, 1.0),
            (0.86974787712097168, 1.0, 1.0),
            (0.87394958734512329, 1.0, 1.0),
            (0.87815123796463013, 1.0, 1.0),
            (0.88235294818878174, 1.0, 1.0),
            (0.88655459880828857, 1.0, 1.0),
            (0.89075630903244019, 1.0, 1.0),
            (0.89495795965194702, 1.0, 1.0),
            (0.89915966987609863, 1.0, 1.0),
            (0.90336132049560547, 1.0, 1.0),
            (0.90756303071975708, 1.0, 1.0),
            (0.91176468133926392, 1.0, 1.0),
            (0.91596639156341553, 1.0, 1.0),
            (0.92016804218292236, 1.0, 1.0),
            (0.92436975240707397, 1.0, 1.0),
            (0.92857140302658081, 1.0, 1.0),
            (0.93277311325073242, 1.0, 1.0),
            (0.93697476387023926, 1.0, 1.0),
            (0.94117647409439087, 1.0, 1.0),
            (0.94537812471389771, 1.0, 1.0),
            (0.94957983493804932, 1.0, 1.0),
            (0.95378148555755615, 1.0, 1.0),
            (0.95798319578170776, 1.0, 1.0),
            (0.9621848464012146, 1.0, 1.0),
            (0.96638655662536621, 0.99607843160629272, 0.99607843160629272),
            (0.97058820724487305, 0.97647058963775635, 0.97647058963775635),
            (0.97478991746902466, 0.9529411792755127, 0.9529411792755127),
            (0.97899156808853149, 0.91372549533843994, 0.91372549533843994),
            (0.98319327831268311, 0.89019608497619629, 0.89019608497619629),
            (0.98739492893218994, 0.87058824300765991, 0.87058824300765991),
            (0.99159663915634155, 0.85098040103912354, 0.85098040103912354),
            (0.99579828977584839, 0.82745099067687988, 0.82745099067687988),
            (1.0, 0.80784314870834351, 0.80784314870834351)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def gist_stern(range, **traits):
    """ Generator for the 'gist_stern' colormap from GIST.
    """
    _data = dict(
        red = [(0.0, 0.0, 0.0),
            (0.0042016808874905109, 0.070588238537311554, 0.070588238537311554),
            (0.0084033617749810219, 0.14117647707462311, 0.14117647707462311),
            (0.012605042196810246, 0.21176470816135406, 0.21176470816135406),
            (0.016806723549962044, 0.28235295414924622, 0.28235295414924622),
            (0.021008403971791267, 0.35294118523597717, 0.35294118523597717),
            (0.025210084393620491, 0.42352941632270813, 0.42352941632270813),
            (0.029411764815449715, 0.49803921580314636, 0.49803921580314636),
            (0.033613447099924088, 0.56862747669219971, 0.56862747669219971),
            (0.037815127521753311, 0.63921570777893066, 0.63921570777893066),
            (0.042016807943582535, 0.78039216995239258, 0.78039216995239258),
            (0.046218488365411758, 0.85098040103912354, 0.85098040103912354),
            (0.050420168787240982, 0.92156863212585449, 0.92156863212585449),
            (0.054621849209070206, 0.99607843160629272, 0.99607843160629272),
            (0.058823529630899429, 0.97647058963775635, 0.97647058963775635),
            (0.063025213778018951, 0.95686274766921997, 0.95686274766921997),
            (0.067226894199848175, 0.93725490570068359, 0.93725490570068359),
            (0.071428574621677399, 0.91764706373214722, 0.91764706373214722),
            (0.075630255043506622, 0.89803922176361084, 0.89803922176361084),
            (0.079831935465335846, 0.87450981140136719, 0.87450981140136719),
            (0.08403361588716507, 0.85490196943283081, 0.85490196943283081),
            (0.088235296308994293, 0.83529412746429443, 0.83529412746429443),
            (0.092436976730823517, 0.81568628549575806, 0.81568628549575806),
            (0.09663865715265274, 0.79607844352722168, 0.79607844352722168),
            (0.10084033757448196, 0.77254903316497803, 0.77254903316497803),
            (0.10504201799631119, 0.75294119119644165, 0.75294119119644165),
            (0.10924369841814041, 0.73333334922790527, 0.73333334922790527),
            (0.11344537883996964, 0.7137255072593689, 0.7137255072593689),
            (0.11764705926179886, 0.69411766529083252, 0.69411766529083252),
            (0.12184873968362808, 0.67450982332229614, 0.67450982332229614),
            (0.1260504275560379, 0.63137257099151611, 0.63137257099151611),
            (0.13025210797786713, 0.61176472902297974, 0.61176472902297974),
            (0.13445378839969635, 0.59215688705444336, 0.59215688705444336),
            (0.13865546882152557, 0.57254904508590698, 0.57254904508590698),
            (0.1428571492433548, 0.54901963472366333, 0.54901963472366333),
            (0.14705882966518402, 0.52941179275512695, 0.52941179275512695),
            (0.15126051008701324, 0.50980395078659058, 0.50980395078659058),
            (0.15546219050884247, 0.49019607901573181, 0.49019607901573181),
            (0.15966387093067169, 0.47058823704719543, 0.47058823704719543),
            (0.16386555135250092, 0.45098039507865906, 0.45098039507865906),
            (0.16806723177433014, 0.42745098471641541, 0.42745098471641541),
            (0.17226891219615936, 0.40784314274787903, 0.40784314274787903),
            (0.17647059261798859, 0.38823530077934265, 0.38823530077934265),
            (0.18067227303981781, 0.36862745881080627, 0.36862745881080627),
            (0.18487395346164703, 0.3490196168422699, 0.3490196168422699),
            (0.18907563388347626, 0.32549020648002625, 0.32549020648002625),
            (0.19327731430530548, 0.30588236451148987, 0.30588236451148987),
            (0.1974789947271347, 0.28627452254295349, 0.28627452254295349),
            (0.20168067514896393, 0.26666668057441711, 0.26666668057441711),
            (0.20588235557079315, 0.24705882370471954, 0.24705882370471954),
            (0.21008403599262238, 0.20392157137393951, 0.20392157137393951),
            (0.2142857164144516, 0.18431372940540314, 0.18431372940540314),
            (0.21848739683628082, 0.16470588743686676, 0.16470588743686676),
            (0.22268907725811005, 0.14509804546833038, 0.14509804546833038),
            (0.22689075767993927, 0.12549020349979401, 0.12549020349979401),
            (0.23109243810176849, 0.10196078568696976, 0.10196078568696976),
            (0.23529411852359772, 0.08235294371843338, 0.08235294371843338),
            (0.23949579894542694, 0.062745101749897003, 0.062745101749897003),
            (0.24369747936725616, 0.043137256056070328, 0.043137256056070328),
            (0.24789915978908539, 0.023529412224888802, 0.023529412224888802),
            (0.25210085511207581, 0.25098040699958801, 0.25098040699958801),
            (0.25630253553390503, 0.25490197539329529, 0.25490197539329529),
            (0.26050421595573425, 0.25882354378700256, 0.25882354378700256),
            (0.26470589637756348, 0.26274511218070984, 0.26274511218070984),
            (0.2689075767993927, 0.26666668057441711, 0.26666668057441711),
            (0.27310925722122192, 0.27058824896812439, 0.27058824896812439),
            (0.27731093764305115, 0.27450981736183167, 0.27450981736183167),
            (0.28151261806488037, 0.27843138575553894, 0.27843138575553894),
            (0.28571429848670959, 0.28235295414924622, 0.28235295414924622),
            (0.28991597890853882, 0.28627452254295349, 0.28627452254295349),
            (0.29411765933036804, 0.29411765933036804, 0.29411765933036804),
            (0.29831933975219727, 0.29803922772407532, 0.29803922772407532),
            (0.30252102017402649, 0.30196079611778259, 0.30196079611778259),
            (0.30672270059585571, 0.30588236451148987, 0.30588236451148987),
            (0.31092438101768494, 0.30980393290519714, 0.30980393290519714),
            (0.31512606143951416, 0.31372550129890442, 0.31372550129890442),
            (0.31932774186134338, 0.31764706969261169, 0.31764706969261169),
            (0.32352942228317261, 0.32156863808631897, 0.32156863808631897),
            (0.32773110270500183, 0.32549020648002625, 0.32549020648002625),
            (0.33193278312683105, 0.32941177487373352, 0.32941177487373352),
            (0.33613446354866028, 0.3333333432674408, 0.3333333432674408),
            (0.3403361439704895, 0.33725491166114807, 0.33725491166114807),
            (0.34453782439231873, 0.34117648005485535, 0.34117648005485535),
            (0.34873950481414795, 0.34509804844856262, 0.34509804844856262),
            (0.35294118523597717, 0.3490196168422699, 0.3490196168422699),
            (0.3571428656578064, 0.35294118523597717, 0.35294118523597717),
            (0.36134454607963562, 0.35686275362968445, 0.35686275362968445),
            (0.36554622650146484, 0.36078432202339172, 0.36078432202339172),
            (0.36974790692329407, 0.364705890417099, 0.364705890417099),
            (0.37394958734512329, 0.36862745881080627, 0.36862745881080627),
            (0.37815126776695251, 0.37647059559822083, 0.37647059559822083),
            (0.38235294818878174, 0.3803921639919281, 0.3803921639919281),
            (0.38655462861061096, 0.38431373238563538, 0.38431373238563538),
            (0.39075630903244019, 0.38823530077934265, 0.38823530077934265),
            (0.39495798945426941, 0.39215686917304993, 0.39215686917304993),
            (0.39915966987609863, 0.3960784375667572, 0.3960784375667572),
            (0.40336135029792786, 0.40000000596046448, 0.40000000596046448),
            (0.40756303071975708, 0.40392157435417175, 0.40392157435417175),
            (0.4117647111415863, 0.40784314274787903, 0.40784314274787903),
            (0.41596639156341553, 0.4117647111415863, 0.4117647111415863),
            (0.42016807198524475, 0.41568627953529358, 0.41568627953529358),
            (0.42436975240707397, 0.41960784792900085, 0.41960784792900085),
            (0.4285714328289032, 0.42352941632270813, 0.42352941632270813),
            (0.43277311325073242, 0.42745098471641541, 0.42745098471641541),
            (0.43697479367256165, 0.43137255311012268, 0.43137255311012268),
            (0.44117647409439087, 0.43529412150382996, 0.43529412150382996),
            (0.44537815451622009, 0.43921568989753723, 0.43921568989753723),
            (0.44957983493804932, 0.44313725829124451, 0.44313725829124451),
            (0.45378151535987854, 0.44705882668495178, 0.44705882668495178),
            (0.45798319578170776, 0.45098039507865906, 0.45098039507865906),
            (0.46218487620353699, 0.45882353186607361, 0.45882353186607361),
            (0.46638655662536621, 0.46274510025978088, 0.46274510025978088),
            (0.47058823704719543, 0.46666666865348816, 0.46666666865348816),
            (0.47478991746902466, 0.47058823704719543, 0.47058823704719543),
            (0.47899159789085388, 0.47450980544090271, 0.47450980544090271),
            (0.48319327831268311, 0.47843137383460999, 0.47843137383460999),
            (0.48739495873451233, 0.48235294222831726, 0.48235294222831726),
            (0.49159663915634155, 0.48627451062202454, 0.48627451062202454),
            (0.49579831957817078, 0.49019607901573181, 0.49019607901573181),
            (0.5, 0.49411764740943909, 0.49411764740943909),
            (0.50420171022415161, 0.50196081399917603, 0.50196081399917603),
            (0.50840336084365845, 0.5058823823928833, 0.5058823823928833),
            (0.51260507106781006, 0.50980395078659058, 0.50980395078659058),
            (0.51680672168731689, 0.51372551918029785, 0.51372551918029785),
            (0.52100843191146851, 0.51764708757400513, 0.51764708757400513),
            (0.52521008253097534, 0.5215686559677124, 0.5215686559677124),
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            (0.49579831957817078, 0.97647058963775635, 0.97647058963775635),
            (0.5, 0.9843137264251709, 0.9843137264251709),
            (0.50420171022415161, 1.0, 1.0),
            (0.50840336084365845, 0.9843137264251709, 0.9843137264251709),
            (0.51260507106781006, 0.9686274528503418, 0.9686274528503418),
            (0.51680672168731689, 0.9529411792755127, 0.9529411792755127),
            (0.52100843191146851, 0.93333333730697632, 0.93333333730697632),
            (0.52521008253097534, 0.91764706373214722, 0.91764706373214722),
            (0.52941179275512695, 0.90196079015731812, 0.90196079015731812),
            (0.53361344337463379, 0.88627451658248901, 0.88627451658248901),
            (0.5378151535987854, 0.86666667461395264, 0.86666667461395264),
            (0.54201680421829224, 0.85098040103912354, 0.85098040103912354),
            (0.54621851444244385, 0.81960785388946533, 0.81960785388946533),
            (0.55042016506195068, 0.80000001192092896, 0.80000001192092896),
            (0.55462187528610229, 0.78431373834609985, 0.78431373834609985),
            (0.55882352590560913, 0.76862746477127075, 0.76862746477127075),
            (0.56302523612976074, 0.75294119119644165, 0.75294119119644165),
            (0.56722688674926758, 0.73333334922790527, 0.73333334922790527),
            (0.57142859697341919, 0.71764707565307617, 0.71764707565307617),
            (0.57563024759292603, 0.70196080207824707, 0.70196080207824707),
            (0.57983195781707764, 0.68627452850341797, 0.68627452850341797),
            (0.58403360843658447, 0.66666668653488159, 0.66666668653488159),
            (0.58823531866073608, 0.65098041296005249, 0.65098041296005249),
            (0.59243696928024292, 0.63529413938522339, 0.63529413938522339),
            (0.59663867950439453, 0.61960786581039429, 0.61960786581039429),
            (0.60084033012390137, 0.60000002384185791, 0.60000002384185791),
            (0.60504204034805298, 0.58431375026702881, 0.58431375026702881),
            (0.60924369096755981, 0.56862747669219971, 0.56862747669219971),
            (0.61344540119171143, 0.55294120311737061, 0.55294120311737061),
            (0.61764705181121826, 0.53333336114883423, 0.53333336114883423),
            (0.62184876203536987, 0.51764708757400513, 0.51764708757400513),
            (0.62605041265487671, 0.50196081399917603, 0.50196081399917603),
            (0.63025212287902832, 0.46666666865348816, 0.46666666865348816),
            (0.63445377349853516, 0.45098039507865906, 0.45098039507865906),
            (0.63865548372268677, 0.43529412150382996, 0.43529412150382996),
            (0.6428571343421936, 0.41960784792900085, 0.41960784792900085),
            (0.64705884456634521, 0.40000000596046448, 0.40000000596046448),
            (0.65126049518585205, 0.38431373238563538, 0.38431373238563538),
            (0.65546220541000366, 0.36862745881080627, 0.36862745881080627),
            (0.6596638560295105, 0.35294118523597717, 0.35294118523597717),
            (0.66386556625366211, 0.3333333432674408, 0.3333333432674408),
            (0.66806721687316895, 0.31764706969261169, 0.31764706969261169),
            (0.67226892709732056, 0.30196079611778259, 0.30196079611778259),
            (0.67647057771682739, 0.28627452254295349, 0.28627452254295349),
            (0.680672287940979, 0.26666668057441711, 0.26666668057441711),
            (0.68487393856048584, 0.25098040699958801, 0.25098040699958801),
            (0.68907564878463745, 0.23529411852359772, 0.23529411852359772),
            (0.69327729940414429, 0.21960784494876862, 0.21960784494876862),
            (0.6974790096282959, 0.20000000298023224, 0.20000000298023224),
            (0.70168066024780273, 0.18431372940540314, 0.18431372940540314),
            (0.70588237047195435, 0.16862745583057404, 0.16862745583057404),
            (0.71008402109146118, 0.15294118225574493, 0.15294118225574493),
            (0.71428573131561279, 0.11764705926179886, 0.11764705926179886),
            (0.71848738193511963, 0.10196078568696976, 0.10196078568696976),
            (0.72268909215927124, 0.086274512112140656, 0.086274512112140656),
            (0.72689074277877808, 0.066666670143604279, 0.066666670143604279),
            (0.73109245300292969, 0.050980392843484879, 0.050980392843484879),
            (0.73529410362243652, 0.035294119268655777, 0.035294119268655777),
            (0.73949581384658813, 0.019607843831181526, 0.019607843831181526),
            (0.74369746446609497, 0.0, 0.0),
            (0.74789917469024658, 0.011764706112444401, 0.011764706112444401),
            (0.75210082530975342, 0.027450980618596077, 0.027450980618596077),
            (0.75630253553390503, 0.058823529630899429, 0.058823529630899429),
            (0.76050418615341187, 0.074509806931018829, 0.074509806931018829),
            (0.76470589637756348, 0.086274512112140656, 0.086274512112140656),
            (0.76890754699707031, 0.10196078568696976, 0.10196078568696976),
            (0.77310925722122192, 0.11764705926179886, 0.11764705926179886),
            (0.77731090784072876, 0.13333334028720856, 0.13333334028720856),
            (0.78151261806488037, 0.14901961386203766, 0.14901961386203766),
            (0.78571426868438721, 0.16078431904315948, 0.16078431904315948),
            (0.78991597890853882, 0.17647059261798859, 0.17647059261798859),
            (0.79411762952804565, 0.19215686619281769, 0.19215686619281769),
            (0.79831933975219727, 0.22352941334247589, 0.22352941334247589),
            (0.8025209903717041, 0.23529411852359772, 0.23529411852359772),
            (0.80672270059585571, 0.25098040699958801, 0.25098040699958801),
            (0.81092435121536255, 0.26666668057441711, 0.26666668057441711),
            (0.81512606143951416, 0.28235295414924622, 0.28235295414924622),
            (0.819327712059021, 0.29803922772407532, 0.29803922772407532),
            (0.82352942228317261, 0.30980393290519714, 0.30980393290519714),
            (0.82773107290267944, 0.32549020648002625, 0.32549020648002625),
            (0.83193278312683105, 0.34117648005485535, 0.34117648005485535),
            (0.83613443374633789, 0.35686275362968445, 0.35686275362968445),
            (0.8403361439704895, 0.37254902720451355, 0.37254902720451355),
            (0.84453779458999634, 0.38431373238563538, 0.38431373238563538),
            (0.84873950481414795, 0.40000000596046448, 0.40000000596046448),
            (0.85294115543365479, 0.41568627953529358, 0.41568627953529358),
            (0.8571428656578064, 0.43137255311012268, 0.43137255311012268),
            (0.86134451627731323, 0.44705882668495178, 0.44705882668495178),
            (0.86554622650146484, 0.45882353186607361, 0.45882353186607361),
            (0.86974787712097168, 0.47450980544090271, 0.47450980544090271),
            (0.87394958734512329, 0.49019607901573181, 0.49019607901573181),
            (0.87815123796463013, 0.5058823823928833, 0.5058823823928833),
            (0.88235294818878174, 0.5372549295425415, 0.5372549295425415),
            (0.88655459880828857, 0.54901963472366333, 0.54901963472366333),
            (0.89075630903244019, 0.56470590829849243, 0.56470590829849243),
            (0.89495795965194702, 0.58039218187332153, 0.58039218187332153),
            (0.89915966987609863, 0.59607845544815063, 0.59607845544815063),
            (0.90336132049560547, 0.61176472902297974, 0.61176472902297974),
            (0.90756303071975708, 0.62352943420410156, 0.62352943420410156),
            (0.91176468133926392, 0.63921570777893066, 0.63921570777893066),
            (0.91596639156341553, 0.65490198135375977, 0.65490198135375977),
            (0.92016804218292236, 0.67058825492858887, 0.67058825492858887),
            (0.92436975240707397, 0.68627452850341797, 0.68627452850341797),
            (0.92857140302658081, 0.69803923368453979, 0.69803923368453979),
            (0.93277311325073242, 0.7137255072593689, 0.7137255072593689),
            (0.93697476387023926, 0.729411780834198, 0.729411780834198),
            (0.94117647409439087, 0.7450980544090271, 0.7450980544090271),
            (0.94537812471389771, 0.7607843279838562, 0.7607843279838562),
            (0.94957983493804932, 0.77254903316497803, 0.77254903316497803),
            (0.95378148555755615, 0.78823530673980713, 0.78823530673980713),
            (0.95798319578170776, 0.80392158031463623, 0.80392158031463623),
            (0.9621848464012146, 0.81960785388946533, 0.81960785388946533),
            (0.96638655662536621, 0.84705883264541626, 0.84705883264541626),
            (0.97058820724487305, 0.86274510622024536, 0.86274510622024536),
            (0.97478991746902466, 0.87843137979507446, 0.87843137979507446),
            (0.97899156808853149, 0.89411765336990356, 0.89411765336990356),
            (0.98319327831268311, 0.90980392694473267, 0.90980392694473267),
            (0.98739492893218994, 0.92156863212585449, 0.92156863212585449),
            (0.99159663915634155, 0.93725490570068359, 0.93725490570068359),
            (0.99579828977584839, 0.9529411792755127, 0.9529411792755127),
            (1.0, 0.9686274528503418, 0.9686274528503418)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)

def gist_yarg(range, **traits):
    """ Generator for the 'gist_yarg' colormap from GIST.
    """
    _data = dict(
        red = [(0.0, 1.0, 1.0),
            (0.0042016808874905109, 0.99607843160629272, 0.99607843160629272),
            (0.0084033617749810219, 0.99215686321258545, 0.99215686321258545),
            (0.012605042196810246, 0.98823529481887817, 0.98823529481887817),
            (0.016806723549962044, 0.9843137264251709, 0.9843137264251709),
            (0.021008403971791267, 0.98039215803146362, 0.98039215803146362),
            (0.025210084393620491, 0.97647058963775635, 0.97647058963775635),
            (0.029411764815449715, 0.97254902124404907, 0.97254902124404907),
            (0.033613447099924088, 0.96470588445663452, 0.96470588445663452),
            (0.037815127521753311, 0.96078431606292725, 0.96078431606292725),
            (0.042016807943582535, 0.95686274766921997, 0.95686274766921997),
            (0.046218488365411758, 0.9529411792755127, 0.9529411792755127),
            (0.050420168787240982, 0.94901961088180542, 0.94901961088180542),
            (0.054621849209070206, 0.94509804248809814, 0.94509804248809814),
            (0.058823529630899429, 0.94117647409439087, 0.94117647409439087),
            (0.063025213778018951, 0.93725490570068359, 0.93725490570068359),
            (0.067226894199848175, 0.93333333730697632, 0.93333333730697632),
            (0.071428574621677399, 0.92941176891326904, 0.92941176891326904),
            (0.075630255043506622, 0.92549020051956177, 0.92549020051956177),
            (0.079831935465335846, 0.92156863212585449, 0.92156863212585449),
            (0.08403361588716507, 0.91764706373214722, 0.91764706373214722),
            (0.088235296308994293, 0.91372549533843994, 0.91372549533843994),
            (0.092436976730823517, 0.90980392694473267, 0.90980392694473267),
            (0.09663865715265274, 0.90196079015731812, 0.90196079015731812),
            (0.10084033757448196, 0.89803922176361084, 0.89803922176361084),
            (0.10504201799631119, 0.89411765336990356, 0.89411765336990356),
            (0.10924369841814041, 0.89019608497619629, 0.89019608497619629),
            (0.11344537883996964, 0.88627451658248901, 0.88627451658248901),
            (0.11764705926179886, 0.88235294818878174, 0.88235294818878174),
            (0.12184873968362808, 0.87843137979507446, 0.87843137979507446),
            (0.1260504275560379, 0.87450981140136719, 0.87450981140136719),
            (0.13025210797786713, 0.87058824300765991, 0.87058824300765991),
            (0.13445378839969635, 0.86666667461395264, 0.86666667461395264),
            (0.13865546882152557, 0.86274510622024536, 0.86274510622024536),
            (0.1428571492433548, 0.85882353782653809, 0.85882353782653809),
            (0.14705882966518402, 0.85490196943283081, 0.85490196943283081),
            (0.15126051008701324, 0.85098040103912354, 0.85098040103912354),
            (0.15546219050884247, 0.84705883264541626, 0.84705883264541626),
            (0.15966387093067169, 0.83921569585800171, 0.83921569585800171),
            (0.16386555135250092, 0.83529412746429443, 0.83529412746429443),
            (0.16806723177433014, 0.83137255907058716, 0.83137255907058716),
            (0.17226891219615936, 0.82745099067687988, 0.82745099067687988),
            (0.17647059261798859, 0.82352942228317261, 0.82352942228317261),
            (0.18067227303981781, 0.81960785388946533, 0.81960785388946533),
            (0.18487395346164703, 0.81568628549575806, 0.81568628549575806),
            (0.18907563388347626, 0.81176471710205078, 0.81176471710205078),
            (0.19327731430530548, 0.80784314870834351, 0.80784314870834351),
            (0.1974789947271347, 0.80392158031463623, 0.80392158031463623),
            (0.20168067514896393, 0.80000001192092896, 0.80000001192092896),
            (0.20588235557079315, 0.79607844352722168, 0.79607844352722168),
            (0.21008403599262238, 0.7921568751335144, 0.7921568751335144),
            (0.2142857164144516, 0.78823530673980713, 0.78823530673980713),
            (0.21848739683628082, 0.78431373834609985, 0.78431373834609985),
            (0.22268907725811005, 0.7764706015586853, 0.7764706015586853),
            (0.22689075767993927, 0.77254903316497803, 0.77254903316497803),
            (0.23109243810176849, 0.76862746477127075, 0.76862746477127075),
            (0.23529411852359772, 0.76470589637756348, 0.76470589637756348),
            (0.23949579894542694, 0.7607843279838562, 0.7607843279838562),
            (0.24369747936725616, 0.75686275959014893, 0.75686275959014893),
            (0.24789915978908539, 0.75294119119644165, 0.75294119119644165),
            (0.25210085511207581, 0.74901962280273438, 0.74901962280273438),
            (0.25630253553390503, 0.7450980544090271, 0.7450980544090271),
            (0.26050421595573425, 0.74117648601531982, 0.74117648601531982),
            (0.26470589637756348, 0.73725491762161255, 0.73725491762161255),
            (0.2689075767993927, 0.73333334922790527, 0.73333334922790527),
            (0.27310925722122192, 0.729411780834198, 0.729411780834198),
            (0.27731093764305115, 0.72549021244049072, 0.72549021244049072),
            (0.28151261806488037, 0.72156864404678345, 0.72156864404678345),
            (0.28571429848670959, 0.7137255072593689, 0.7137255072593689),
            (0.28991597890853882, 0.70980393886566162, 0.70980393886566162),
            (0.29411765933036804, 0.70588237047195435, 0.70588237047195435),
            (0.29831933975219727, 0.70196080207824707, 0.70196080207824707),
            (0.30252102017402649, 0.69803923368453979, 0.69803923368453979),
            (0.30672270059585571, 0.69411766529083252, 0.69411766529083252),
            (0.31092438101768494, 0.69019609689712524, 0.69019609689712524),
            (0.31512606143951416, 0.68627452850341797, 0.68627452850341797),
            (0.31932774186134338, 0.68235296010971069, 0.68235296010971069),
            (0.32352942228317261, 0.67843139171600342, 0.67843139171600342),
            (0.32773110270500183, 0.67450982332229614, 0.67450982332229614),
            (0.33193278312683105, 0.67058825492858887, 0.67058825492858887),
            (0.33613446354866028, 0.66666668653488159, 0.66666668653488159),
            (0.3403361439704895, 0.66274511814117432, 0.66274511814117432),
            (0.34453782439231873, 0.65882354974746704, 0.65882354974746704),
            (0.34873950481414795, 0.65098041296005249, 0.65098041296005249),
            (0.35294118523597717, 0.64705884456634521, 0.64705884456634521),
            (0.3571428656578064, 0.64313727617263794, 0.64313727617263794),
            (0.36134454607963562, 0.63921570777893066, 0.63921570777893066),
            (0.36554622650146484, 0.63529413938522339, 0.63529413938522339),
            (0.36974790692329407, 0.63137257099151611, 0.63137257099151611),
            (0.37394958734512329, 0.62745100259780884, 0.62745100259780884),
            (0.37815126776695251, 0.62352943420410156, 0.62352943420410156),
            (0.38235294818878174, 0.61960786581039429, 0.61960786581039429),
            (0.38655462861061096, 0.61568629741668701, 0.61568629741668701),
            (0.39075630903244019, 0.61176472902297974, 0.61176472902297974),
            (0.39495798945426941, 0.60784316062927246, 0.60784316062927246),
            (0.39915966987609863, 0.60392159223556519, 0.60392159223556519),
            (0.40336135029792786, 0.60000002384185791, 0.60000002384185791),
            (0.40756303071975708, 0.59607845544815063, 0.59607845544815063),
            (0.4117647111415863, 0.58823531866073608, 0.58823531866073608),
            (0.41596639156341553, 0.58431375026702881, 0.58431375026702881),
            (0.42016807198524475, 0.58039218187332153, 0.58039218187332153),
            (0.42436975240707397, 0.57647061347961426, 0.57647061347961426),
            (0.4285714328289032, 0.57254904508590698, 0.57254904508590698),
            (0.43277311325073242, 0.56862747669219971, 0.56862747669219971),
            (0.43697479367256165, 0.56470590829849243, 0.56470590829849243),
            (0.44117647409439087, 0.56078433990478516, 0.56078433990478516),
            (0.44537815451622009, 0.55686277151107788, 0.55686277151107788),
            (0.44957983493804932, 0.55294120311737061, 0.55294120311737061),
            (0.45378151535987854, 0.54901963472366333, 0.54901963472366333),
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            (0.42436975240707397, 0.57647061347961426, 0.57647061347961426),
            (0.4285714328289032, 0.57254904508590698, 0.57254904508590698),
            (0.43277311325073242, 0.56862747669219971, 0.56862747669219971),
            (0.43697479367256165, 0.56470590829849243, 0.56470590829849243),
            (0.44117647409439087, 0.56078433990478516, 0.56078433990478516),
            (0.44537815451622009, 0.55686277151107788, 0.55686277151107788),
            (0.44957983493804932, 0.55294120311737061, 0.55294120311737061),
            (0.45378151535987854, 0.54901963472366333, 0.54901963472366333),
            (0.45798319578170776, 0.54509806632995605, 0.54509806632995605),
            (0.46218487620353699, 0.54117649793624878, 0.54117649793624878),
            (0.46638655662536621, 0.5372549295425415, 0.5372549295425415),
            (0.47058823704719543, 0.53333336114883423, 0.53333336114883423),
            (0.47478991746902466, 0.52549022436141968, 0.52549022436141968),
            (0.47899159789085388, 0.5215686559677124, 0.5215686559677124),
            (0.48319327831268311, 0.51764708757400513, 0.51764708757400513),
            (0.48739495873451233, 0.51372551918029785, 0.51372551918029785),
            (0.49159663915634155, 0.50980395078659058, 0.50980395078659058),
            (0.49579831957817078, 0.5058823823928833, 0.5058823823928833),
            (0.5, 0.50196081399917603, 0.50196081399917603),
            (0.50420171022415161, 0.49803921580314636, 0.49803921580314636),
            (0.50840336084365845, 0.49411764740943909, 0.49411764740943909),
            (0.51260507106781006, 0.49019607901573181, 0.49019607901573181),
            (0.51680672168731689, 0.48627451062202454, 0.48627451062202454),
            (0.52100843191146851, 0.48235294222831726, 0.48235294222831726),
            (0.52521008253097534, 0.47843137383460999, 0.47843137383460999),
            (0.52941179275512695, 0.47450980544090271, 0.47450980544090271),
            (0.53361344337463379, 0.47058823704719543, 0.47058823704719543),
            (0.5378151535987854, 0.46274510025978088, 0.46274510025978088),
            (0.54201680421829224, 0.45882353186607361, 0.45882353186607361),
            (0.54621851444244385, 0.45490196347236633, 0.45490196347236633),
            (0.55042016506195068, 0.45098039507865906, 0.45098039507865906),
            (0.55462187528610229, 0.44705882668495178, 0.44705882668495178),
            (0.55882352590560913, 0.44313725829124451, 0.44313725829124451),
            (0.56302523612976074, 0.43921568989753723, 0.43921568989753723),
            (0.56722688674926758, 0.43529412150382996, 0.43529412150382996),
            (0.57142859697341919, 0.43137255311012268, 0.43137255311012268),
            (0.57563024759292603, 0.42745098471641541, 0.42745098471641541),
            (0.57983195781707764, 0.42352941632270813, 0.42352941632270813),
            (0.58403360843658447, 0.41960784792900085, 0.41960784792900085),
            (0.58823531866073608, 0.41568627953529358, 0.41568627953529358),
            (0.59243696928024292, 0.4117647111415863, 0.4117647111415863),
            (0.59663867950439453, 0.40784314274787903, 0.40784314274787903),
            (0.60084033012390137, 0.40000000596046448, 0.40000000596046448),
            (0.60504204034805298, 0.3960784375667572, 0.3960784375667572),
            (0.60924369096755981, 0.39215686917304993, 0.39215686917304993),
            (0.61344540119171143, 0.38823530077934265, 0.38823530077934265),
            (0.61764705181121826, 0.38431373238563538, 0.38431373238563538),
            (0.62184876203536987, 0.3803921639919281, 0.3803921639919281),
            (0.62605041265487671, 0.37647059559822083, 0.37647059559822083),
            (0.63025212287902832, 0.37254902720451355, 0.37254902720451355),
            (0.63445377349853516, 0.36862745881080627, 0.36862745881080627),
            (0.63865548372268677, 0.364705890417099, 0.364705890417099),
            (0.6428571343421936, 0.36078432202339172, 0.36078432202339172),
            (0.64705884456634521, 0.35686275362968445, 0.35686275362968445),
            (0.65126049518585205, 0.35294118523597717, 0.35294118523597717),
            (0.65546220541000366, 0.3490196168422699, 0.3490196168422699),
            (0.6596638560295105, 0.34509804844856262, 0.34509804844856262),
            (0.66386556625366211, 0.33725491166114807, 0.33725491166114807),
            (0.66806721687316895, 0.3333333432674408, 0.3333333432674408),
            (0.67226892709732056, 0.32941177487373352, 0.32941177487373352),
            (0.67647057771682739, 0.32549020648002625, 0.32549020648002625),
            (0.680672287940979, 0.32156863808631897, 0.32156863808631897),
            (0.68487393856048584, 0.31764706969261169, 0.31764706969261169),
            (0.68907564878463745, 0.31372550129890442, 0.31372550129890442),
            (0.69327729940414429, 0.30980393290519714, 0.30980393290519714),
            (0.6974790096282959, 0.30588236451148987, 0.30588236451148987),
            (0.70168066024780273, 0.30196079611778259, 0.30196079611778259),
            (0.70588237047195435, 0.29803922772407532, 0.29803922772407532),
            (0.71008402109146118, 0.29411765933036804, 0.29411765933036804),
            (0.71428573131561279, 0.29019609093666077, 0.29019609093666077),
            (0.71848738193511963, 0.28627452254295349, 0.28627452254295349),
            (0.72268909215927124, 0.28235295414924622, 0.28235295414924622),
            (0.72689074277877808, 0.27450981736183167, 0.27450981736183167),
            (0.73109245300292969, 0.27058824896812439, 0.27058824896812439),
            (0.73529410362243652, 0.26666668057441711, 0.26666668057441711),
            (0.73949581384658813, 0.26274511218070984, 0.26274511218070984),
            (0.74369746446609497, 0.25882354378700256, 0.25882354378700256),
            (0.74789917469024658, 0.25490197539329529, 0.25490197539329529),
            (0.75210082530975342, 0.25098040699958801, 0.25098040699958801),
            (0.75630253553390503, 0.24705882370471954, 0.24705882370471954),
            (0.76050418615341187, 0.24313725531101227, 0.24313725531101227),
            (0.76470589637756348, 0.23921568691730499, 0.23921568691730499),
            (0.76890754699707031, 0.23529411852359772, 0.23529411852359772),
            (0.77310925722122192, 0.23137255012989044, 0.23137255012989044),
            (0.77731090784072876, 0.22745098173618317, 0.22745098173618317),
            (0.78151261806488037, 0.22352941334247589, 0.22352941334247589),
            (0.78571426868438721, 0.21960784494876862, 0.21960784494876862),
            (0.78991597890853882, 0.21176470816135406, 0.21176470816135406),
            (0.79411762952804565, 0.20784313976764679, 0.20784313976764679),
            (0.79831933975219727, 0.20392157137393951, 0.20392157137393951),
            (0.8025209903717041, 0.20000000298023224, 0.20000000298023224),
            (0.80672270059585571, 0.19607843458652496, 0.19607843458652496),
            (0.81092435121536255, 0.19215686619281769, 0.19215686619281769),
            (0.81512606143951416, 0.18823529779911041, 0.18823529779911041),
            (0.819327712059021, 0.18431372940540314, 0.18431372940540314),
            (0.82352942228317261, 0.18039216101169586, 0.18039216101169586),
            (0.82773107290267944, 0.17647059261798859, 0.17647059261798859),
            (0.83193278312683105, 0.17254902422428131, 0.17254902422428131),
            (0.83613443374633789, 0.16862745583057404, 0.16862745583057404),
            (0.8403361439704895, 0.16470588743686676, 0.16470588743686676),
            (0.84453779458999634, 0.16078431904315948, 0.16078431904315948),
            (0.84873950481414795, 0.15686275064945221, 0.15686275064945221),
            (0.85294115543365479, 0.14901961386203766, 0.14901961386203766),
            (0.8571428656578064, 0.14509804546833038, 0.14509804546833038),
            (0.86134451627731323, 0.14117647707462311, 0.14117647707462311),
            (0.86554622650146484, 0.13725490868091583, 0.13725490868091583),
            (0.86974787712097168, 0.13333334028720856, 0.13333334028720856),
            (0.87394958734512329, 0.12941177189350128, 0.12941177189350128),
            (0.87815123796463013, 0.12549020349979401, 0.12549020349979401),
            (0.88235294818878174, 0.12156862765550613, 0.12156862765550613),
            (0.88655459880828857, 0.11764705926179886, 0.11764705926179886),
            (0.89075630903244019, 0.11372549086809158, 0.11372549086809158),
            (0.89495795965194702, 0.10980392247438431, 0.10980392247438431),
            (0.89915966987609863, 0.10588235408067703, 0.10588235408067703),
            (0.90336132049560547, 0.10196078568696976, 0.10196078568696976),
            (0.90756303071975708, 0.098039217293262482, 0.098039217293262482),
            (0.91176468133926392, 0.094117648899555206, 0.094117648899555206),
            (0.91596639156341553, 0.086274512112140656, 0.086274512112140656),
            (0.92016804218292236, 0.08235294371843338, 0.08235294371843338),
            (0.92436975240707397, 0.078431375324726105, 0.078431375324726105),
            (0.92857140302658081, 0.074509806931018829, 0.074509806931018829),
            (0.93277311325073242, 0.070588238537311554, 0.070588238537311554),
            (0.93697476387023926, 0.066666670143604279, 0.066666670143604279),
            (0.94117647409439087, 0.062745101749897003, 0.062745101749897003),
            (0.94537812471389771, 0.058823529630899429, 0.058823529630899429),
            (0.94957983493804932, 0.054901961237192154, 0.054901961237192154),
            (0.95378148555755615, 0.050980392843484879, 0.050980392843484879),
            (0.95798319578170776, 0.047058824449777603, 0.047058824449777603),
            (0.9621848464012146, 0.043137256056070328, 0.043137256056070328),
            (0.96638655662536621, 0.039215687662363052, 0.039215687662363052),
            (0.97058820724487305, 0.035294119268655777, 0.035294119268655777),
            (0.97478991746902466, 0.031372550874948502, 0.031372550874948502),
            (0.97899156808853149, 0.023529412224888802, 0.023529412224888802),
            (0.98319327831268311, 0.019607843831181526, 0.019607843831181526),
            (0.98739492893218994, 0.015686275437474251, 0.015686275437474251),
            (0.99159663915634155, 0.011764706112444401, 0.011764706112444401),
            (0.99579828977584839, 0.0078431377187371254, 0.0078431377187371254),
            (1.0, 0.0039215688593685627, 0.0039215688593685627)],
    )
    return ColorMapper.from_segment_map(_data, range=range, **traits)


def CubicYF(range, **traits):
    """ Generator of the 'CubicYF' colormap from Matteo Niccoli.

    Lab-based rainbow scheme with cubic-law luminance.

    http://mycarta.wordpress.com/color-palettes/
    """
    palette = array([
        [0.5151, 0.0482, 0.6697],
        [0.5199, 0.1762, 0.8083],
        [0.4884, 0.2912, 0.9234],
        [0.4297, 0.3855, 0.9921],
        [0.3893, 0.4792, 0.9775],
        [0.3337, 0.5650, 0.9056],
        [0.2795, 0.6419, 0.8287],
        [0.2210, 0.7123, 0.7258],
        [0.2468, 0.7612, 0.6248],
        [0.2833, 0.8125, 0.5069],
        [0.3198, 0.8492, 0.3956],
        [0.3602, 0.8896, 0.2919],
        [0.4568, 0.9136, 0.3018],
        [0.6033, 0.9255, 0.3295],
        [0.7066, 0.9255, 0.3414],
        [0.8000, 0.9255, 0.3529],
    ])
    return ColorMapper.from_palette_array(palette, range=range, **traits)


def CubicL(range, **traits):
    """ Generator of the 'CubicL' colormap from Matteo Niccoli.

    Lab-based rainbow scheme with cubic-law luminance, like `CubicYF`
    but with red at the high end, a modest deviation from being
    completely perceptual.

    http://mycarta.wordpress.com/color-palettes/
    """
    palette = array([
        [0.4706, 0.0000, 0.5216],
        [0.5137, 0.0527, 0.7096],
        [0.4942, 0.2507, 0.8781],
        [0.4296, 0.3858, 0.9922],
        [0.3691, 0.5172, 0.9495],
        [0.2963, 0.6191, 0.8515],
        [0.2199, 0.7134, 0.7225],
        [0.2643, 0.7836, 0.5756],
        [0.3094, 0.8388, 0.4248],
        [0.3623, 0.8917, 0.2858],
        [0.5200, 0.9210, 0.3137],
        [0.6800, 0.9255, 0.3386],
        [0.8000, 0.9255, 0.3529],
        [0.8706, 0.8549, 0.3608],
        [0.9514, 0.7466, 0.3686],
        [0.9765, 0.5887, 0.3569],
    ])
    return ColorMapper.from_palette_array(palette, range=range, **traits)


def LinearL(range, **traits):
    """ Generator of the 'LinearL' colormap from Matteo Niccoli.

    Lab-based linear lightness rainbow.

    http://mycarta.wordpress.com/color-palettes/
    """
    palette = array([
        [0.0143, 0.0143, 0.0143],
        [0.1413, 0.0555, 0.1256],
        [0.1761, 0.0911, 0.2782],
        [0.1710, 0.1314, 0.4540],
        [0.1074, 0.2234, 0.4984],
        [0.0686, 0.3044, 0.5068],
        [0.0008, 0.3927, 0.4267],
        [0.0000, 0.4763, 0.3464],
        [0.0000, 0.5565, 0.2469],
        [0.0000, 0.6381, 0.1638],
        [0.2167, 0.6966, 0.0000],
        [0.3898, 0.7563, 0.0000],
        [0.6912, 0.7795, 0.0000],
        [0.8548, 0.8041, 0.4555],
        [0.9712, 0.8429, 0.7287],
        [0.9692, 0.9273, 0.8961],
    ])
    return ColorMapper.from_palette_array(palette, range=range, **traits)


def LinearLHot(range, **traits):
    """ Generator of the 'LinearLHot' colormap from Matteo Niccoli.

    Linear lightness modification of the `hot` colormap.

    http://mycarta.wordpress.com/color-palettes/
    """
    palette = array([
        [0.0225, 0.0121, 0.0121],
        [0.1927, 0.0225, 0.0311],
        [0.3243, 0.0106, 0.0000],
        [0.4463, 0.0000, 0.0091],
        [0.5706, 0.0000, 0.0737],
        [0.6969, 0.0000, 0.1337],
        [0.8213, 0.0000, 0.1792],
        [0.8636, 0.0000, 0.0565],
        [0.8821, 0.2555, 0.0000],
        [0.8720, 0.4182, 0.0000],
        [0.8424, 0.5552, 0.0000],
        [0.8031, 0.6776, 0.0000],
        [0.7659, 0.7870, 0.0000],
        [0.8170, 0.8296, 0.0000],
        [0.8853, 0.8896, 0.4113],
        [0.9481, 0.9486, 0.7165],
    ])
    return ColorMapper.from_palette_array(palette, range=range, **traits)


def CoolWarm(range, **traits):
    """ Generator of Kenneth Moreland's CoolWarm colormap.

    Blue-White-Red with smooth lightness transitions. Good for applying to 3D
    surfaces or otherwise have extra shading applied.

    http://www.sandia.gov/~kmorel/documents/ColorMaps/ColorMapsExpanded.pdf
    """
    cool = array([59, 76, 192]) / 255.0
    warm = array([180, 4, 38]) / 255.0
    palette = generate_diverging_palette(cool, warm, 256)
    return ColorMapper.from_palette_array(palette, range=range, **traits)


def CubeHelix(range, **traits):
    """ Generator of Dave Green's CubeHelix colormap.

    Sequential colormap with a linear lightness increasing from black to white
    deviating away from gray in a tapered helix.

    https://www.mrao.cam.ac.uk/~dag/CUBEHELIX/
    """
    palette = generate_cubehelix_palette()
    return ColorMapper.from_palette_array(palette, range=range, **traits)


# Make the convenient list of all the function names as well as a dictionary
# of name->function mappings.  These are useful for UI editors.

color_map_functions = [
    jet,
    autumn,
    bone,
    cool,
    copper,
    flag,
    gray,
    yarg,
    hot,
    hsv,
    pink,
    prism,
    spring,
    summer,
    winter,
    cw1_004,
    cw1_005,
    cw1_006,
    cw1_028,
    gmt_drywet,
    Spectral,
    RdBu,
    RdPu,
    YlGnBu,
    RdYlBu,
    GnBu,
    RdYlGn,
    PuBu,
    BuGn,
    Greens,
    PRGn,
    BuPu,
    OrRd,
    Oranges,
    PiYG,
    YlGn,
    BrBG,
    Reds,
    RdGy,
    PuRd,
    Blues,
    Greys,
    YlOrRd,
    YlOrBr,
    Purples,
    PuOr,
    PuBuGn,
    gist_earth,
    gist_gray,
    gist_heat,
    gist_ncar,
    gist_rainbow,
    gist_stern,
    gist_yarg,
    CubicYF,
    CubicL,
    LinearL,
    LinearLHot,
    CoolWarm,
    CubeHelix,
]

color_map_dict = {}
for func in color_map_functions:
    color_map_dict[func] = func.__name__

color_map_name_dict = {}
for func in color_map_functions:
    color_map_name_dict[func.__name__] = func
    __all__.append(func.__name__)


#### EOF ######################################################################