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<font color="#ffffff" face="helvetica, arial"> <br><big><big><strong><a href="matplotlib.html"><font color="#ffffff">matplotlib</font></a>.cm</strong></big></big></font></td
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><font color="#ffffff" face="helvetica, arial"><a href=".">index</a><br><a href="file:/home/jdhunter/dev/lib64/python2.5/site-packages/matplotlib/cm.py">/home/jdhunter/dev/lib64/python2.5/site-packages/matplotlib/cm.py</a></font></td></tr></table>
<p><tt>This module contains the instantiations of color mapping classes</tt></p>
<p>
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<td colspan=3 valign=bottom> <br>
<font color="#fffff" face="helvetica, arial"><big><strong>Modules</strong></big></font></td></tr>
<tr><td bgcolor="#aa55cc"><tt> </tt></td><td> </td>
<td width="100%"><table width="100%" summary="list"><tr><td width="25%" valign=top><a href="matplotlib.cbook.html">matplotlib.cbook</a><br>
<a href="matplotlib.colors.html">matplotlib.colors</a><br>
</td><td width="25%" valign=top><a href="numpy.ma.html">numpy.ma</a><br>
<a href="matplotlib.html">matplotlib</a><br>
</td><td width="25%" valign=top><a href="numpy.html">numpy</a><br>
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<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ee77aa">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Classes</strong></big></font></td></tr>
<tr><td bgcolor="#ee77aa"><tt> </tt></td><td> </td>
<td width="100%"><dl>
<dt><font face="helvetica, arial"><a href="matplotlib.cm.html#ScalarMappable">ScalarMappable</a>
</font></dt></dl>
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<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="ScalarMappable">class <strong>ScalarMappable</strong></a></font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>This is a mixin class to support scalar -> RGBA mapping. Handles<br>
normalization and colormapping<br> </tt></td></tr>
<tr><td> </td>
<td width="100%">Methods defined here:<br>
<dl><dt><a name="ScalarMappable-__init__"><strong>__init__</strong></a>(self, norm<font color="#909090">=None</font>, cmap<font color="#909090">=None</font>)</dt><dd><tt>*norm* is an instance of :class:`colors.Normalize` or one of<br>
its subclasses, used to map luminance to 0-1. *cmap* is a<br>
:mod:`cm` colormap instance, for example :data:`cm.jet`</tt></dd></dl>
<dl><dt><a name="ScalarMappable-add_checker"><strong>add_checker</strong></a>(self, checker)</dt><dd><tt>Add an entry to a dictionary of boolean flags<br>
that are set to True when the mappable is changed.</tt></dd></dl>
<dl><dt><a name="ScalarMappable-autoscale"><strong>autoscale</strong></a>(self)</dt><dd><tt>Autoscale the scalar limits on the norm instance using the<br>
current array</tt></dd></dl>
<dl><dt><a name="ScalarMappable-autoscale_None"><strong>autoscale_None</strong></a>(self)</dt><dd><tt>Autoscale the scalar limits on the norm instance using the<br>
current array, changing only limits that are None</tt></dd></dl>
<dl><dt><a name="ScalarMappable-changed"><strong>changed</strong></a>(self)</dt><dd><tt>Call this whenever the mappable is changed to notify all the<br>
callbackSM listeners to the 'changed' signal</tt></dd></dl>
<dl><dt><a name="ScalarMappable-check_update"><strong>check_update</strong></a>(self, checker)</dt><dd><tt>If mappable has changed since the last check,<br>
return True; else return False</tt></dd></dl>
<dl><dt><a name="ScalarMappable-get_array"><strong>get_array</strong></a>(self)</dt><dd><tt>Return the array</tt></dd></dl>
<dl><dt><a name="ScalarMappable-get_clim"><strong>get_clim</strong></a>(self)</dt><dd><tt>return the min, max of the color limits for image scaling</tt></dd></dl>
<dl><dt><a name="ScalarMappable-get_cmap"><strong>get_cmap</strong></a>(self)</dt><dd><tt>return the colormap</tt></dd></dl>
<dl><dt><a name="ScalarMappable-set_array"><strong>set_array</strong></a>(self, A)</dt><dd><tt>Set the image array from numpy array *A*</tt></dd></dl>
<dl><dt><a name="ScalarMappable-set_clim"><strong>set_clim</strong></a>(self, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>)</dt><dd><tt>set the norm limits for image scaling; if *vmin* is a length2<br>
sequence, interpret it as ``(vmin, vmax)`` which is used to<br>
support setp<br>
<br>
ACCEPTS: a length 2 sequence of floats</tt></dd></dl>
<dl><dt><a name="ScalarMappable-set_cmap"><strong>set_cmap</strong></a>(self, cmap)</dt><dd><tt>set the colormap for luminance data<br>
<br>
ACCEPTS: a colormap</tt></dd></dl>
<dl><dt><a name="ScalarMappable-set_colorbar"><strong>set_colorbar</strong></a>(self, im, ax)</dt><dd><tt>set the colorbar image and axes associated with mappable</tt></dd></dl>
<dl><dt><a name="ScalarMappable-set_norm"><strong>set_norm</strong></a>(self, norm)</dt><dd><tt>set the normalization instance</tt></dd></dl>
<dl><dt><a name="ScalarMappable-to_rgba"><strong>to_rgba</strong></a>(self, x, alpha<font color="#909090">=1.0</font>, bytes<font color="#909090">=False</font>)</dt><dd><tt>Return a normalized rgba array corresponding to *x*. If *x*<br>
is already an rgb array, insert *alpha*; if it is already<br>
rgba, return it unchanged. If *bytes* is True, return rgba as<br>
4 uint8s instead of 4 floats.</tt></dd></dl>
</td></tr></table></td></tr></table><p>
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<tr bgcolor="#eeaa77">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Functions</strong></big></font></td></tr>
<tr><td bgcolor="#eeaa77"><tt> </tt></td><td> </td>
<td width="100%"><dl><dt><a name="-get_cmap"><strong>get_cmap</strong></a>(name<font color="#909090">=None</font>, lut<font color="#909090">=None</font>)</dt><dd><tt>Get a colormap instance, defaulting to rc values if *name* is None</tt></dd></dl>
</td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#55aa55">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Data</strong></big></font></td></tr>
<tr><td bgcolor="#55aa55"><tt> </tt></td><td> </td>
<td width="100%"><strong>Accent</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c248><br>
<strong>Accent_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134b638><br>
<strong>Blues</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c290><br>
<strong>Blues_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5cf8><br>
<strong>BrBG</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c2d8><br>
<strong>BrBG_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1bd8><br>
<strong>BuGn</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c320><br>
<strong>BuGn_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364998><br>
<strong>BuPu</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c368><br>
<strong>BuPu_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13643f8><br>
<strong>Dark2</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c3b0><br>
<strong>Dark2_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364518><br>
<strong>GnBu</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c3f8><br>
<strong>GnBu_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c53f8><br>
<strong>Greens</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c440><br>
<strong>Greens_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a11b8><br>
<strong>Greys</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c488><br>
<strong>Greys_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5638><br>
<strong>LUTSIZE</strong> = 256<br>
<strong>OrRd</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c518><br>
<strong>OrRd_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134b758><br>
<strong>Oranges</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c4d0><br>
<strong>Oranges_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364758><br>
<strong>PRGn</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c680><br>
<strong>PRGn_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a13f8><br>
<strong>Paired</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c560><br>
<strong>Paired_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1878><br>
<strong>Pastel1</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c5a8><br>
<strong>Pastel1_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c51b8><br>
<strong>Pastel2</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c5f0><br>
<strong>Pastel2_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1f38><br>
<strong>PiYG</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c638><br>
<strong>PiYG_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364bd8><br>
<strong>PuBu</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c6c8><br>
<strong>PuBuGn</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c710><br>
<strong>PuBuGn_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5e18><br>
<strong>PuBu_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134bbd8><br>
<strong>PuOr</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c758><br>
<strong>PuOr_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5998><br>
<strong>PuRd</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c7a0><br>
<strong>PuRd_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5ab8><br>
<strong>Purples</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c7e8><br>
<strong>Purples_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1cf8><br>
<strong>RdBu</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c830><br>
<strong>RdBu_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134b878><br>
<strong>RdGy</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c878><br>
<strong>RdGy_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5758><br>
<strong>RdPu</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c8c0><br>
<strong>RdPu_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1098><br>
<strong>RdYlBu</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c908><br>
<strong>RdYlBu_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1758><br>
<strong>RdYlGn</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c950><br>
<strong>RdYlGn_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134b1b8><br>
<strong>Reds</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c998><br>
<strong>Reds_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364e18><br>
<strong>Set1</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132c9e0><br>
<strong>Set1_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134bab8><br>
<strong>Set2</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132ca28><br>
<strong>Set2_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134b2d8><br>
<strong>Set3</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132ca70><br>
<strong>Set3_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134bcf8><br>
<strong>Spectral</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cab8><br>
<strong>Spectral_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cf38><br>
<strong>YlGn</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cb00><br>
<strong>YlGnBu</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cb48><br>
<strong>YlGnBu_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1638><br>
<strong>YlGn_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5518><br>
<strong>YlOrBr</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cb90><br>
<strong>YlOrBr_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364cf8><br>
<strong>YlOrRd</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cbd8><br>
<strong>YlOrRd_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5878><br>
<strong>autumn</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270998><br>
<strong>autumn_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134b998><br>
<strong>binary</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270a28><br>
<strong>binary_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364098><br>
<strong>bone</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x12709e0><br>
<strong>bone_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x141e098><br>
<strong>cmapdat_r</strong> = {'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)]}<br>
<strong>cmapname</strong> = 'bone'<br>
<strong>cmapname_r</strong> = 'bone_r'<br>
<strong>cmapnames</strong> = ['Spectral', 'copper', 'RdYlGn', 'Set2', 'summer', 'spring', 'Accent', 'OrRd', 'RdBu', 'autumn', 'Set1', 'PuBu', 'Set3', 'gist_rainbow', 'pink', 'binary', 'winter', 'jet', 'BuPu', 'Dark2', ...]<br>
<strong>cool</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270a70><br>
<strong>cool_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1e18><br>
<strong>copper</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270ab8><br>
<strong>copper_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134b098><br>
<strong>datad</strong> = {'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, 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0.74901962280273438), (0.875, 0.87843137979507446, 0.87843137979507446), (1.0, 0.9686274528503418, 0.9686274528503418)]}, ...}<br>
<strong>flag</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270b00><br>
<strong>flag_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1998><br>
<strong>gist_earth</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cc20><br>
<strong>gist_earth_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5f38><br>
<strong>gist_gray</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cc68><br>
<strong>gist_gray_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5bd8><br>
<strong>gist_heat</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132ccb0><br>
<strong>gist_heat_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1518><br>
<strong>gist_ncar</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132ccf8><br>
<strong>gist_ncar_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a12d8><br>
<strong>gist_rainbow</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cd40><br>
<strong>gist_rainbow_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134be18><br>
<strong>gist_stern</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cd88><br>
<strong>gist_stern_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c52d8><br>
<strong>gist_yarg</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x132cdd0><br>
<strong>gist_yarg_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364878><br>
<strong>gray</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270b48><br>
<strong>gray_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13c5098><br>
<strong>hot</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270b90><br>
<strong>hot_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364ab8><br>
<strong>hsv</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270bd8><br>
<strong>hsv_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13a1ab8><br>
<strong>jet</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270c20><br>
<strong>jet_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13642d8><br>
<strong>pink</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270c68><br>
<strong>pink_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134bf38><br>
<strong>prism</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270cb0><br>
<strong>prism_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364638><br>
<strong>spectral</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270dd0><br>
<strong>spectral_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1364f38><br>
<strong>spring</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270cf8><br>
<strong>spring_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134b518><br>
<strong>summer</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270d40><br>
<strong>summer_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x134b3f8><br>
<strong>winter</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x1270d88><br>
<strong>winter_r</strong> = <matplotlib.colors.LinearSegmentedColormap instance at 0x13641b8></td></tr></table>
@footer@
