matplotlib.cm
index
/astro-wise/AWEHOME/x86_64/AWBASE/common/lib/python2.5/site-packages/matplotlib/cm.py

This module contains the instantiations of color mapping classes

 
Modules
       
matplotlib.colors
matplotlib.numerix.ma

 
Classes
       
ScalarMappable

 
class ScalarMappable
    This is a mixin class to support scalar -> RGBA mapping.  Handles
normalization and colormapping
 
  Methods defined here:
__init__(self, norm=None, cmap=None)
norm is a colors.normalize instance to map luminance to 0-1
cmap is a cm colormap instance
add_observer(self, mappable)
whenever the norm, clim or cmap is set, call the notify
instance of the mappable observer with self.
 
This is designed to allow one image to follow changes in the
cmap of another image
autoscale(self)
Autoscale the scalar limits on the norm instance using the
current array
autoscale_None(self)
Autoscale the scalar limits on the norm instance using the
current array, changing only limits that are None
changed(self)
Call this whenever the mappable is changed so observers can
update state
get_array(self)
Return the array
get_clim(self)
return the min, max of the color limits for image scaling
notify(self, mappable)
If this is called then we are pegged to another mappable.
Update our cmap, norm, alpha from the other mappable.
set_array(self, A)
Set the image array from numeric/numarray A
set_clim(self, vmin=None, vmax=None)
set the norm limits for image scaling; if vmin is a length2
sequence, interpret it as (vmin, vmax) which is used to
support setp
 
ACCEPTS: a length 2 sequence of floats
set_cmap(self, cmap)
set the colormap for luminance data
 
ACCEPTS: a colormap
set_colorbar(self, im, ax)
set the colorbar image and axes associated with mappable
set_norm(self, norm)
set the normalization instance
to_rgba(self, x, alpha=1.0)
Return a normalized rgba array corresponding to x.
If x is already an rgb or rgba array, return it unchanged.

 
Functions
       
get_cmap(name=None, lut=None)
Get a colormap instance, defaulting to rc values if name is None

 
Data
        Accent = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47878>
Accent_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeaecf8>
Blues = <matplotlib.colors.LinearSegmentedColormap instance at 0xe478c0>
Blues_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf443f8>
BrBG = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47908>
BrBG_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2e2d8>
BuGn = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47950>
BuGn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedb098>
BuPu = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47998>
BuPu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2ab8>
Dark2 = <matplotlib.colors.LinearSegmentedColormap instance at 0xe479e0>
Dark2_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2bd8>
GnBu = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47a28>
GnBu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2eab8>
Greens = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47a70>
Greens_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedb878>
Greys = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47ab8>
Greys_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2ecf8>
LUTSIZE = 256
OrRd = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47b48>
OrRd_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeaee18>
Oranges = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47b00>
Oranges_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2e18>
PRGn = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47cb0>
PRGn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedbab8>
Paired = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47b90>
Paired_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedbf38>
Pastel1 = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47bd8>
Pastel1_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2e878>
Pastel2 = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47c20>
Pastel2_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2e638>
PiYG = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47c68>
PiYG_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedb2d8>
PuBu = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47cf8>
PuBuGn = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47d40>
PuBuGn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf44518>
PuBu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb22d8>
PuOr = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47d88>
PuOr_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf44098>
PuRd = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47dd0>
PuRd_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf441b8>
Purples = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47e18>
Purples_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2e3f8>
RdBu = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47e60>
RdBu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeaef38>
RdGy = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47ea8>
RdGy_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2ee18>
RdPu = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47ef0>
RdPu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedb758>
RdYlBu = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47f38>
RdYlBu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedbe18>
RdYlGn = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47f80>
RdYlGn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae878>
Reds = <matplotlib.colors.LinearSegmentedColormap instance at 0xe47fc8>
Reds_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedb518>
Set1 = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae050>
Set1_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb21b8>
Set2 = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae098>
Set2_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae998>
Set3 = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae0e0>
Set3_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb23f8>
Spectral = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae128>
Spectral_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae638>
YlGn = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae170>
YlGnBu = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae1b8>
YlGnBu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedbcf8>
YlGn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2ebd8>
YlOrBr = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae200>
YlOrBr_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedb3f8>
YlOrRd = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae248>
YlOrRd_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2ef38>
autumn = <matplotlib.colors.LinearSegmentedColormap instance at 0xa7c3b0>
autumn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2098>
binary = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd0050>
binary_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2758>
bone = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd0170>
bone_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf44758>
cmapdat_r = {'blue': [(0.0, 1.0, 1.0), (0.63492100000000007, 0.44444400000000001, 0.44444400000000001), (1.0, 0.0, 0.0)], 'green': [(0.0, 1.0, 1.0), (0.25396799999999997, 0.77777799999999997, 0.77777799999999997), (0.63492100000000007, 0.31944400000000001, 0.31944400000000001), (1.0, 0.0, 0.0)], 'red': [(0.0, 1.0, 1.0), (0.25396799999999997, 0.65277799999999997, 0.65277799999999997), (1.0, 0.0, 0.0)]}
cmapname = 'bone'
cmapname_r = 'bone_r'
cmapnames = ['Spectral', 'copper', 'RdYlGn', 'Set2', 'summer', 'spring', 'Accent', 'OrRd', 'RdBu', 'autumn', 'Set1', 'PuBu', 'Set3', 'gist_rainbow', 'pink', 'binary', 'winter', 'jet', 'BuPu', 'Dark2', ...]
cool = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd0248>
cool_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2e518>
copper = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd0290>
copper_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae758>
datad = {'Accent': {'blue': [(0.0, 0.49803921580314636, 0.49803921580314636), (0.14285714285714285, 0.83137255907058716, 0.83137255907058716), (0.2857142857142857, 0.52549022436141968, 0.52549022436141968), (0.42857142857142855, 0.60000002384185791, 0.60000002384185791), (0.5714285714285714, 0.69019609689712524, 0.69019609689712524), (0.7142857142857143, 0.49803921580314636, 0.49803921580314636), (0.8571428571428571, 0.090196080505847931, 0.090196080505847931), (1.0, 0.40000000596046448, 0.40000000596046448)], 'green': [(0.0, 0.78823530673980713, 0.78823530673980713), (0.14285714285714285, 0.68235296010971069, 0.68235296010971069), (0.2857142857142857, 0.75294119119644165, 0.75294119119644165), (0.42857142857142855, 1.0, 1.0), (0.5714285714285714, 0.42352941632270813, 0.42352941632270813), (0.7142857142857143, 0.0078431377187371254, 0.0078431377187371254), (0.8571428571428571, 0.35686275362968445, 0.35686275362968445), (1.0, 0.40000000596046448, 0.40000000596046448)], 'red': [(0.0, 0.49803921580314636, 0.49803921580314636), (0.14285714285714285, 0.7450980544090271, 0.7450980544090271), (0.2857142857142857, 0.99215686321258545, 0.99215686321258545), (0.42857142857142855, 1.0, 1.0), (0.5714285714285714, 0.21960784494876862, 0.21960784494876862), (0.7142857142857143, 0.94117647409439087, 0.94117647409439087), (0.8571428571428571, 0.74901962280273438, 0.74901962280273438), (1.0, 0.40000000596046448, 0.40000000596046448)]}, 'Accent_r': {'blue': [(0.0, 0.40000000596046448, 0.40000000596046448), (0.1428571428571429, 0.090196080505847931, 0.090196080505847931), (0.2857142857142857, 0.49803921580314636, 0.49803921580314636), (0.4285714285714286, 0.69019609689712524, 0.69019609689712524), (0.5714285714285714, 0.60000002384185791, 0.60000002384185791), (0.7142857142857143, 0.52549022436141968, 0.52549022436141968), (0.85714285714285721, 0.83137255907058716, 0.83137255907058716), (1.0, 0.49803921580314636, 0.49803921580314636)], 'green': [(0.0, 0.40000000596046448, 0.40000000596046448), (0.1428571428571429, 0.35686275362968445, 0.35686275362968445), (0.2857142857142857, 0.0078431377187371254, 0.0078431377187371254), (0.4285714285714286, 0.42352941632270813, 0.42352941632270813), (0.5714285714285714, 1.0, 1.0), (0.7142857142857143, 0.75294119119644165, 0.75294119119644165), (0.85714285714285721, 0.68235296010971069, 0.68235296010971069), (1.0, 0.78823530673980713, 0.78823530673980713)], 'red': [(0.0, 0.40000000596046448, 0.40000000596046448), (0.1428571428571429, 0.74901962280273438, 0.74901962280273438), (0.2857142857142857, 0.94117647409439087, 0.94117647409439087), (0.4285714285714286, 0.21960784494876862, 0.21960784494876862), (0.5714285714285714, 1.0, 1.0), (0.7142857142857143, 0.99215686321258545, 0.99215686321258545), (0.85714285714285721, 0.7450980544090271, 0.7450980544090271), (1.0, 0.49803921580314636, 0.49803921580314636)]}, 'Blues': {'blue': [(0.0, 1.0, 1.0), (0.125, 0.9686274528503418, 0.9686274528503418), (0.25, 0.93725490570068359, 0.93725490570068359), (0.375, 0.88235294818878174, 0.88235294818878174), (0.5, 0.83921569585800171, 0.83921569585800171), (0.625, 0.7764706015586853, 0.7764706015586853), (0.75, 0.70980393886566162, 0.70980393886566162), (0.875, 0.61176472902297974, 0.61176472902297974), (1.0, 0.41960784792900085, 0.41960784792900085)], 'green': [(0.0, 0.9843137264251709, 0.9843137264251709), (0.125, 0.92156863212585449, 0.92156863212585449), (0.25, 0.85882353782653809, 0.85882353782653809), (0.375, 0.7921568751335144, 0.7921568751335144), (0.5, 0.68235296010971069, 0.68235296010971069), (0.625, 0.57254904508590698, 0.57254904508590698), (0.75, 0.44313725829124451, 0.44313725829124451), (0.875, 0.31764706969261169, 0.31764706969261169), (1.0, 0.18823529779911041, 0.18823529779911041)], 'red': [(0.0, 0.9686274528503418, 0.9686274528503418), (0.125, 0.87058824300765991, 0.87058824300765991), (0.25, 0.7764706015586853, 0.7764706015586853), (0.375, 0.61960786581039429, 0.61960786581039429), (0.5, 0.41960784792900085, 0.41960784792900085), (0.625, 0.25882354378700256, 0.25882354378700256), (0.75, 0.12941177189350128, 0.12941177189350128), (0.875, 0.031372550874948502, 0.031372550874948502), (1.0, 0.031372550874948502, 0.031372550874948502)]}, 'Blues_r': {'blue': [(0.0, 0.41960784792900085, 0.41960784792900085), (0.125, 0.61176472902297974, 0.61176472902297974), (0.25, 0.70980393886566162, 0.70980393886566162), (0.375, 0.7764706015586853, 0.7764706015586853), (0.5, 0.83921569585800171, 0.83921569585800171), (0.625, 0.88235294818878174, 0.88235294818878174), (0.75, 0.93725490570068359, 0.93725490570068359), (0.875, 0.9686274528503418, 0.9686274528503418), (1.0, 1.0, 1.0)], 'green': [(0.0, 0.18823529779911041, 0.18823529779911041), (0.125, 0.31764706969261169, 0.31764706969261169), (0.25, 0.44313725829124451, 0.44313725829124451), (0.375, 0.57254904508590698, 0.57254904508590698), (0.5, 0.68235296010971069, 0.68235296010971069), (0.625, 0.7921568751335144, 0.7921568751335144), (0.75, 0.85882353782653809, 0.85882353782653809), (0.875, 0.92156863212585449, 0.92156863212585449), (1.0, 0.9843137264251709, 0.9843137264251709)], 'red': [(0.0, 0.031372550874948502, 0.031372550874948502), (0.125, 0.031372550874948502, 0.031372550874948502), (0.25, 0.12941177189350128, 0.12941177189350128), (0.375, 0.25882354378700256, 0.25882354378700256), (0.5, 0.41960784792900085, 0.41960784792900085), (0.625, 0.61960786581039429, 0.61960786581039429), (0.75, 0.7764706015586853, 0.7764706015586853), (0.875, 0.87058824300765991, 0.87058824300765991), (1.0, 0.9686274528503418, 0.9686274528503418)]}, 'BrBG': {'blue': [(0.0, 0.019607843831181526, 0.019607843831181526), (0.10000000000000001, 0.039215687662363052, 0.039215687662363052), (0.20000000000000001, 0.17647059261798859, 0.17647059261798859), (0.29999999999999999, 0.49019607901573181, 0.49019607901573181), (0.40000000000000002, 0.76470589637756348, 0.76470589637756348), (0.5, 0.96078431606292725, 0.96078431606292725), (0.59999999999999998, 0.89803922176361084, 0.89803922176361084), (0.69999999999999996, 0.75686275959014893, 0.75686275959014893), (0.80000000000000004, 0.56078433990478516, 0.56078433990478516), (0.90000000000000002, 0.36862745881080627, 0.36862745881080627), (1.0, 0.18823529779911041, 0.18823529779911041)], 'green': [(0.0, 0.18823529779911041, 0.18823529779911041), (0.10000000000000001, 0.31764706969261169, 0.31764706969261169), (0.20000000000000001, 0.5058823823928833, 0.5058823823928833), (0.29999999999999999, 0.7607843279838562, 0.7607843279838562), (0.40000000000000002, 0.90980392694473267, 0.90980392694473267), (0.5, 0.96078431606292725, 0.96078431606292725), (0.59999999999999998, 0.91764706373214722, 0.91764706373214722), (0.69999999999999996, 0.80392158031463623, 0.80392158031463623), (0.80000000000000004, 0.59215688705444336, 0.59215688705444336), (0.90000000000000002, 0.40000000596046448, 0.40000000596046448), (1.0, 0.23529411852359772, 0.23529411852359772)], 'red': [(0.0, 0.32941177487373352, 0.32941177487373352), (0.10000000000000001, 0.54901963472366333, 0.54901963472366333), (0.20000000000000001, 0.74901962280273438, 0.74901962280273438), (0.29999999999999999, 0.87450981140136719, 0.87450981140136719), (0.40000000000000002, 0.96470588445663452, 0.96470588445663452), (0.5, 0.96078431606292725, 0.96078431606292725), (0.59999999999999998, 0.78039216995239258, 0.78039216995239258), (0.69999999999999996, 0.50196081399917603, 0.50196081399917603), (0.80000000000000004, 0.20784313976764679, 0.20784313976764679), (0.90000000000000002, 0.0039215688593685627, 0.0039215688593685627), (1.0, 0.0, 0.0)]}, 'BrBG_r': {'blue': [(0.0, 0.18823529779911041, 0.18823529779911041), (0.099999999999999978, 0.36862745881080627, 0.36862745881080627), (0.19999999999999996, 0.56078433990478516, 0.56078433990478516), (0.30000000000000004, 0.75686275959014893, 0.75686275959014893), (0.40000000000000002, 0.89803922176361084, 0.89803922176361084), (0.5, 0.96078431606292725, 0.96078431606292725), (0.59999999999999998, 0.76470589637756348, 0.76470589637756348), (0.69999999999999996, 0.49019607901573181, 0.49019607901573181), (0.80000000000000004, 0.17647059261798859, 0.17647059261798859), (0.90000000000000002, 0.039215687662363052, 0.039215687662363052), (1.0, 0.019607843831181526, 0.019607843831181526)], 'green': [(0.0, 0.23529411852359772, 0.23529411852359772), (0.099999999999999978, 0.40000000596046448, 0.40000000596046448), (0.19999999999999996, 0.59215688705444336, 0.59215688705444336), (0.30000000000000004, 0.80392158031463623, 0.80392158031463623), (0.40000000000000002, 0.91764706373214722, 0.91764706373214722), (0.5, 0.96078431606292725, 0.96078431606292725), (0.59999999999999998, 0.90980392694473267, 0.90980392694473267), (0.69999999999999996, 0.7607843279838562, 0.7607843279838562), (0.80000000000000004, 0.5058823823928833, 0.5058823823928833), (0.90000000000000002, 0.31764706969261169, 0.31764706969261169), (1.0, 0.18823529779911041, 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flag = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd02d8>
flag_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2e098>
gist_earth = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae290>
gist_earth_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf44638>
gist_gray = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae2d8>
gist_gray_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf442d8>
gist_heat = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae320>
gist_heat_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedbbd8>
gist_ncar = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae368>
gist_ncar_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedb998>
gist_rainbow = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae3b0>
gist_rainbow_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2518>
gist_stern = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae3f8>
gist_stern_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2e998>
gist_yarg = <matplotlib.colors.LinearSegmentedColormap instance at 0xeae440>
gist_yarg_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2f38>
gray = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd0320>
gray_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2e758>
hot = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd0368>
hot_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedb1b8>
hsv = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd03b0>
hsv_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xf2e1b8>
jet = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd03f8>
jet_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2998>
nx = <matplotlib.numerix._sp_imports._TypeNamespace instance at 0xda10e0>
pink = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd0440>
pink_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2638>
prism = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd0488>
prism_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2cf8>
rcParams = {'axes.axisbelow': False, 'axes.edgecolor': 'k', 'axes.facecolor': 'w', 'axes.formatter.limits': (-7, 7), 'axes.grid': False, 'axes.hold': True, 'axes.labelcolor': 'k', 'axes.labelsize': 12, 'axes.linewidth': 1.0, 'axes.titlesize': 14, ...}
spectral = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd05a8>
spectral_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xedb638>
spring = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd04d0>
spring_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeaebd8>
summer = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd0518>
summer_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeaeab8>
verbose = <matplotlib.Verbose instance at 0xa5f950>
winter = <matplotlib.colors.LinearSegmentedColormap instance at 0xdd0560>
winter_r = <matplotlib.colors.LinearSegmentedColormap instance at 0xeb2878>