@header@
 
 
matplotlib.cm		index
/usr/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.Norm 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
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
set_cmap(self, cmap)
set the colormap for luminance data
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 0x82ca4ec>
Accent_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x82caeac>
Blues = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca50c>
Blues_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8374a6c>
BrBG = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca52c>
BrBG_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83741cc>
BuGn = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca54c>
BuGn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x835486c>
BuPu = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca56c>
BuPu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x835458c>
Dark2 = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca58c>
Dark2_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x835462c>
GnBu = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca5ac>
GnBu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83745ac>
Greens = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca5cc>
Greens_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8354ccc>
Greys = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca5ec>
Greys_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83746cc>
LUTSIZE = 256
OrRd = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca62c>
OrRd_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x82caf4c>
Oranges = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca60c>
Oranges_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x835474c>
PRGn = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca6cc>
PRGn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8354d6c>
Paired = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca64c>
Paired_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8354fcc>
Pastel1 = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca66c>
Pastel1_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837448c>
Pastel2 = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca68c>
Pastel2_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837436c>
PiYG = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca6ac>
PiYG_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83549ac>
PuBu = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca6ec>
PuBuGn = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca70c>
PuBuGn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8374b0c>
PuBu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83541ec>
PuOr = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca72c>
PuOr_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83748ac>
PuRd = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca74c>
PuRd_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837494c>
Purples = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca76c>
Purples_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837424c>
RdBu = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca78c>
RdBu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x82cafec>
RdGy = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca7ac>
RdGy_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837476c>
RdPu = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca7cc>
RdPu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8354c2c>
RdYlBu = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca7ec>
RdYlBu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8354f2c>
RdYlGn = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca80c>
RdYlGn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x82cac2c>
Reds = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca82c>
Reds_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8354b8c>
Set1 = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca84c>
Set1_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x835414c>
Set2 = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca86c>
Set2_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x82caccc>
Set3 = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca88c>
Set3_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x835428c>
Spectral = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca8ac>
Spectral_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x82caa6c>
YlGn = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca8cc>
YlGnBu = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca8ec>
YlGnBu_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8354e8c>
YlGn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8354aec>
YlOrBr = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca90c>
YlOrBr_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8354a4c>
YlOrRd = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca92c>
YlOrRd_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837480c>
autumn = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b844c>
autumn_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83540ac>
bone = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b846c>
bone_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8374c2c>
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', 'winter', 'jet', 'BuPu', 'Dark2', 'prism', ...]
cool = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b848c>
cool_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83742ec>
copper = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b84ac>
copper_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x82cab8c>
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, 0.18823529779911041)], 'red': [(0.0, 0.0, 0.0), (0.099999999999999978, 0.0039215688593685627, 0.0039215688593685627), (0.19999999999999996, 0.20784313976764679, 0.20784313976764679), (0.30000000000000004, 0.50196081399917603, 0.50196081399917603), (0.40000000000000002, 0.78039216995239258, 0.78039216995239258), (0.5, 0.96078431606292725, 0.96078431606292725), (0.59999999999999998, 0.96470588445663452, 0.96470588445663452), (0.69999999999999996, 0.87450981140136719, 0.87450981140136719), (0.80000000000000004, 0.74901962280273438, 0.74901962280273438), (0.90000000000000002, 0.54901963472366333, 0.54901963472366333), (1.0, 0.32941177487373352, 0.32941177487373352)]}, 'BuGn': {'blue': [(0.0, 0.99215686321258545, 0.99215686321258545), (0.125, 0.97647058963775635, 0.97647058963775635), (0.25, 0.90196079015731812, 0.90196079015731812), (0.375, 0.78823530673980713, 0.78823530673980713), (0.5, 0.64313727617263794, 0.64313727617263794), (0.625, 0.46274510025978088, 0.46274510025978088), (0.75, 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0.87843137979507446), (1.0, 0.9686274528503418, 0.9686274528503418)]}, ...}
flag = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b84cc>
flag_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837408c>
gist_earth = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca94c>
gist_earth_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8374b8c>
gist_gray = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca96c>
gist_gray_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83749cc>
gist_heat = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca98c>
gist_heat_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x8354dec>
gist_ncar = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca9ac>
gist_ncar_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837462c>
gist_rainbow = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca9cc>
gist_rainbow_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x835430c>
gist_stern = <matplotlib.colors.LinearSegmentedColormap instance at 0x82ca9ec>
gist_stern_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837450c>
gist_yarg = <matplotlib.colors.LinearSegmentedColormap instance at 0x82caa0c>
gist_yarg_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83547cc>
gray = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b84ec>
gray_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837440c>
hot = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b850c>
hot_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x835490c>
hsv = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b852c>
hsv_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x837412c>
jet = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b854c>
jet_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83544ec>
nx = <matplotlib.numerix._sp_imports._TypeNamespace instance at 0x82395ec>
pink = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b856c>
pink_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83543ac>
prism = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b858c>
prism_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x83546cc>
rcParams = {'axes.axisbelow': False, 'axes.edgecolor': 'black', 'axes.facecolor': 'white', 'axes.grid': False, 'axes.hold': True, 'axes.labelcolor': 'black', 'axes.labelsize': 12.0, 'axes.linewidth': 1.0, 'axes.titlesize': 14.0, 'backend': 'Qt4Agg', ...}
spring = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b85ac>
spring_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x82cae0c>
summer = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b85cc>
summer_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x82cad6c>
verbose = <matplotlib.Verbose instance at 0x80f50ac>
winter = <matplotlib.colors.LinearSegmentedColormap instance at 0x82b85ec>
winter_r = <matplotlib.colors.LinearSegmentedColormap instance at 0x835444c>
@footer@