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@header@
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="heading">
<tr bgcolor="#7799ee">
<td valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"> <br><big><big><strong><a href="matplotlib.html"><font color="#ffffff">matplotlib</font></a>.image</strong></big></big></font></td
><td align=right valign=bottom
><font color="#ffffff" face="helvetica, arial"><a href=".">index</a><br><a href="file:/home/jdhunter/dev/lib64/python2.5/site-packages/matplotlib/image.py">/home/jdhunter/dev/lib64/python2.5/site-packages/matplotlib/image.py</a></font></td></tr></table>
<p><tt>The image module supports basic image loading, rescaling and display<br>
operations.</tt></p>
<p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#aa55cc">
<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._image.html">matplotlib._image</a><br>
<a href="matplotlib._png.html">matplotlib._png</a><br>
<a href="matplotlib.cm.html">matplotlib.cm</a><br>
</td><td width="25%" valign=top><a href="numpy.ma.html">numpy.ma</a><br>
<a href="matplotlib.artist.html">matplotlib.artist</a><br>
<a href="matplotlib.colors.html">matplotlib.colors</a><br>
</td><td width="25%" valign=top><a href="numpy.html">numpy</a><br>
<a href="os.html">os</a><br>
<a href="warnings.html">warnings</a><br>
</td><td width="25%" valign=top></td></tr></table></td></tr></table><p>
<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.artist.html#Artist">matplotlib.artist.Artist</a>(<a href="__builtin__.html#object">__builtin__.object</a>)
</font></dt><dd>
<dl>
<dt><font face="helvetica, arial"><a href="matplotlib.image.html#AxesImage">AxesImage</a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>, <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>)
</font></dt><dd>
<dl>
<dt><font face="helvetica, arial"><a href="matplotlib.image.html#NonUniformImage">NonUniformImage</a>
</font></dt></dl>
</dd>
<dt><font face="helvetica, arial"><a href="matplotlib.image.html#FigureImage">FigureImage</a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>, <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>)
</font></dt><dt><font face="helvetica, arial"><a href="matplotlib.image.html#PcolorImage">PcolorImage</a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>, <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>)
</font></dt></dl>
</dd>
<dt><font face="helvetica, arial"><a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>
</font></dt><dd>
<dl>
<dt><font face="helvetica, arial"><a href="matplotlib.image.html#AxesImage">AxesImage</a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>, <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>)
</font></dt><dd>
<dl>
<dt><font face="helvetica, arial"><a href="matplotlib.image.html#NonUniformImage">NonUniformImage</a>
</font></dt></dl>
</dd>
<dt><font face="helvetica, arial"><a href="matplotlib.image.html#FigureImage">FigureImage</a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>, <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>)
</font></dt><dt><font face="helvetica, arial"><a href="matplotlib.image.html#PcolorImage">PcolorImage</a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>, <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>)
</font></dt></dl>
</dd>
</dl>
<p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="AxesImage">class <strong>AxesImage</strong></a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>, <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>)</font></td></tr>
<tr><td bgcolor="#ffc8d8"><tt> </tt></td><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="matplotlib.image.html#AxesImage">AxesImage</a></dd>
<dd><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a></dd>
<dd><a href="__builtin__.html#object">__builtin__.object</a></dd>
<dd><a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="AxesImage-__init__"><strong>__init__</strong></a>(self, ax, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, interpolation<font color="#909090">=None</font>, origin<font color="#909090">=None</font>, extent<font color="#909090">=None</font>, filternorm<font color="#909090">=1</font>, filterrad<font color="#909090">=4.0</font>, resample<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>interpolation and cmap default to their rc settings<br>
<br>
cmap is a colors.Colormap instance<br>
norm is a colors.Normalize instance to map luminance to 0-1<br>
<br>
extent is data axes (left, right, bottom, top) for making image plots<br>
registered with data plots. Default is to label the pixel<br>
centers with the zero-based row and column indices.<br>
<br>
Additional kwargs are matplotlib.artist properties</tt></dd></dl>
<dl><dt><a name="AxesImage-__str__"><strong>__str__</strong></a>(self)</dt></dl>
<dl><dt><a name="AxesImage-changed"><strong>changed</strong></a>(self)</dt><dd><tt>Call this whenever the mappable is changed so observers can<br>
update state</tt></dd></dl>
<dl><dt><a name="AxesImage-contains"><strong>contains</strong></a>(self, mouseevent)</dt><dd><tt>Test whether the mouse event occured within the image.</tt></dd></dl>
<dl><dt><a name="AxesImage-draw"><strong>draw</strong></a>(self, renderer, *args, **kwargs)</dt></dl>
<dl><dt><a name="AxesImage-get_extent"><strong>get_extent</strong></a>(self)</dt><dd><tt>get the image extent: left, right, bottom, top</tt></dd></dl>
<dl><dt><a name="AxesImage-get_filternorm"><strong>get_filternorm</strong></a>(self)</dt><dd><tt>return the filternorm setting</tt></dd></dl>
<dl><dt><a name="AxesImage-get_filterrad"><strong>get_filterrad</strong></a>(self)</dt><dd><tt>return the filterrad setting</tt></dd></dl>
<dl><dt><a name="AxesImage-get_interpolation"><strong>get_interpolation</strong></a>(self)</dt></dl>
<dl><dt><a name="AxesImage-get_size"><strong>get_size</strong></a>(self)</dt><dd><tt>Get the numrows, numcols of the input image</tt></dd></dl>
<dl><dt><a name="AxesImage-make_image"><strong>make_image</strong></a>(self, magnification<font color="#909090">=1.0</font>)</dt></dl>
<dl><dt><a name="AxesImage-set_alpha"><strong>set_alpha</strong></a>(self, alpha)</dt><dd><tt>Set the alpha value used for blending - not supported on<br>
all backends<br>
<br>
ACCEPTS: float</tt></dd></dl>
<dl><dt><a name="AxesImage-set_array"><strong>set_array</strong></a>(self, A)</dt><dd><tt>retained for backwards compatibility - use set_data instead<br>
<br>
ACCEPTS: numpy array A or PIL Image</tt></dd></dl>
<dl><dt><a name="AxesImage-set_data"><strong>set_data</strong></a>(self, A, shape<font color="#909090">=None</font>)</dt><dd><tt>Set the image array<br>
<br>
ACCEPTS: numpy/PIL Image A</tt></dd></dl>
<dl><dt><a name="AxesImage-set_extent"><strong>set_extent</strong></a>(self, extent)</dt><dd><tt>extent is data axes (left, right, bottom, top) for making image plots</tt></dd></dl>
<dl><dt><a name="AxesImage-set_filternorm"><strong>set_filternorm</strong></a>(self, filternorm)</dt><dd><tt>Set whether the resize filter norms the weights -- see<br>
help for imshow<br>
<br>
ACCEPTS: 0 or 1</tt></dd></dl>
<dl><dt><a name="AxesImage-set_filterrad"><strong>set_filterrad</strong></a>(self, filterrad)</dt><dd><tt>Set the resize filter radius only applicable to some<br>
interpolation schemes -- see help for imshow<br>
<br>
ACCEPTS: positive float</tt></dd></dl>
<dl><dt><a name="AxesImage-set_interpolation"><strong>set_interpolation</strong></a>(self, s)</dt><dd><tt>Set the interpolation method the image uses when resizing.<br>
<br>
ACCEPTS: ['bicubic' | 'bilinear' | 'blackman100' | 'blackman256' | 'blackman64', 'nearest' | 'sinc144' | 'sinc256' | 'sinc64' | 'spline16' | 'spline36']</tt></dd></dl>
<dl><dt><a name="AxesImage-set_resample"><strong>set_resample</strong></a>(self, v)</dt></dl>
<dl><dt><a name="AxesImage-write_png"><strong>write_png</strong></a>(self, fname, noscale<font color="#909090">=False</font>)</dt><dd><tt>Write the image to png file with fname</tt></dd></dl>
<hr>
Data and other attributes defined here:<br>
<dl><dt><strong>interpnames</strong> = ['bilinear', 'nearest', 'kaiser', 'quadric', 'hermite', 'blackman', 'catrom', 'gaussian', 'hanning', 'spline36', 'hamming', 'lanczos', 'bicubic', 'mitchell', 'bessel', 'sinc', 'spline16']</dl>
<dl><dt><strong>k</strong> = 'spline16'</dl>
<dl><dt><strong>v</strong> = 3</dl>
<dl><dt><strong>zorder</strong> = 1</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="AxesImage-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="AxesImage-convert_xunits"><strong>convert_xunits</strong></a>(self, x)</dt><dd><tt>for artists in an axes, if the xaxis as units support,<br>
convert *x* using xaxis unit type</tt></dd></dl>
<dl><dt><a name="AxesImage-convert_yunits"><strong>convert_yunits</strong></a>(self, y)</dt><dd><tt>for artists in an axes, if the yaxis as units support,<br>
convert *y* using yaxis unit type</tt></dd></dl>
<dl><dt><a name="AxesImage-findobj"><strong>findobj</strong></a>(self, match<font color="#909090">=None</font>)</dt><dd><tt>pyplot signature:<br>
<a href="#AxesImage-findobj">findobj</a>(o=gcf(), match=None) <br>
<br>
recursively find all :class:matplotlib.artist.<a href="matplotlib.artist.html#Artist">Artist</a> instances<br>
contained in self<br>
<br>
*match* can be<br>
<br>
- None: return all objects contained in artist (including artist)<br>
<br>
- function with signature ``boolean = match(artist)`` used to filter matches<br>
<br>
- class instance: eg Line2D. Only return artists of class type<br>
<br>
.. plot:: ../mpl_examples/pylab_examples/findobj_demo.py</tt></dd></dl>
<dl><dt><a name="AxesImage-get_alpha"><strong>get_alpha</strong></a>(self)</dt><dd><tt>Return the alpha value used for blending - not supported on all<br>
backends</tt></dd></dl>
<dl><dt><a name="AxesImage-get_animated"><strong>get_animated</strong></a>(self)</dt><dd><tt>return the artist's animated state</tt></dd></dl>
<dl><dt><a name="AxesImage-get_axes"><strong>get_axes</strong></a>(self)</dt><dd><tt>return the axes instance the artist resides in, or *None*</tt></dd></dl>
<dl><dt><a name="AxesImage-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="AxesImage-get_clip_on"><strong>get_clip_on</strong></a>(self)</dt><dd><tt>Return whether artist uses clipping</tt></dd></dl>
<dl><dt><a name="AxesImage-get_clip_path"><strong>get_clip_path</strong></a>(self)</dt><dd><tt>Return artist clip path</tt></dd></dl>
<dl><dt><a name="AxesImage-get_contains"><strong>get_contains</strong></a>(self)</dt><dd><tt>return the _contains test used by the artist, or *None* for default.</tt></dd></dl>
<dl><dt><a name="AxesImage-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>Return the :class:`~matplotlib.figure.Figure` instance the<br>
artist belongs to.</tt></dd></dl>
<dl><dt><a name="AxesImage-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="AxesImage-get_picker"><strong>get_picker</strong></a>(self)</dt><dd><tt>return the Pickeration instance used by this artist</tt></dd></dl>
<dl><dt><a name="AxesImage-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>Return the :class:`~matplotlib.transforms.Transform`<br>
instance used by this artist.</tt></dd></dl>
<dl><dt><a name="AxesImage-get_transformed_clip_path_and_affine"><strong>get_transformed_clip_path_and_affine</strong></a>(self)</dt><dd><tt>Return the clip path with the non-affine part of its<br>
transformation applied, and the remaining affine part of its<br>
transformation.</tt></dd></dl>
<dl><dt><a name="AxesImage-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="AxesImage-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="AxesImage-have_units"><strong>have_units</strong></a>(self)</dt><dd><tt>return *True* if units are set on the x or y axes</tt></dd></dl>
<dl><dt><a name="AxesImage-hitlist"><strong>hitlist</strong></a>(self, event)</dt><dd><tt>List the children of the artist which contain the mouse event</tt></dd></dl>
<dl><dt><a name="AxesImage-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="AxesImage-is_transform_set"><strong>is_transform_set</strong></a>(self)</dt><dd><tt><a href="matplotlib.artist.html#Artist">Artist</a> has transform explicity let</tt></dd></dl>
<dl><dt><a name="AxesImage-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="AxesImage-pick"><strong>pick</strong></a>(self, mouseevent)</dt><dd><tt>call signature::<br>
<br>
<a href="#AxesImage-pick">pick</a>(mouseevent)<br>
<br>
each child artist will fire a pick event if *mouseevent* is over<br>
the artist and the artist has picker set</tt></dd></dl>
<dl><dt><a name="AxesImage-pickable"><strong>pickable</strong></a>(self)</dt><dd><tt>return *True* if self is pickable</tt></dd></dl>
<dl><dt><a name="AxesImage-remove"><strong>remove</strong></a>(self)</dt><dd><tt>Remove the artist from the figure if possible. The effect<br>
will not be visible until the figure is redrawn, e.g., with<br>
:meth:`matplotlib.axes.Axes.draw_idle`. Call<br>
:meth:`matplotlib.axes.Axes.relim` to update the axes limits<br>
if desired.<br>
<br>
Note: :meth:`~matplotlib.axes.Axes.relim` will not see<br>
collections even if the collection was added to axes with<br>
*autolim* = True.<br>
<br>
Note: there is no support for removing the artist's legend entry.</tt></dd></dl>
<dl><dt><a name="AxesImage-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="AxesImage-set"><strong>set</strong></a>(self, **kwargs)</dt><dd><tt>A tkstyle set command, pass *kwargs* to set properties</tt></dd></dl>
<dl><dt><a name="AxesImage-set_animated"><strong>set_animated</strong></a>(self, b)</dt><dd><tt>set the artist's animation state<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="AxesImage-set_axes"><strong>set_axes</strong></a>(self, axes)</dt><dd><tt>set the axes instance in which the artist resides, if any<br>
<br>
ACCEPTS: an axes instance</tt></dd></dl>
<dl><dt><a name="AxesImage-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a :class:`matplotlib.transform.Bbox` instance</tt></dd></dl>
<dl><dt><a name="AxesImage-set_clip_on"><strong>set_clip_on</strong></a>(self, b)</dt><dd><tt>Set whether artist uses clipping<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="AxesImage-set_clip_path"><strong>set_clip_path</strong></a>(self, path, transform<font color="#909090">=None</font>)</dt><dd><tt>Set the artist's clip path, which may be:<br>
<br>
* a :class:`~matplotlib.patches.Patch` (or subclass) instance<br>
<br>
* a :class:`~matplotlib.path.Path` instance, in which case<br>
an optional :class:`~matplotlib.transforms.Transform`<br>
instance may be provided, which will be applied to the<br>
path before using it for clipping.<br>
<br>
* *None*, to remove the clipping path<br>
<br>
For efficiency, if the path happens to be an axis-aligned<br>
rectangle, this method will set the clipping box to the<br>
corresponding rectangle and set the clipping path to *None*.<br>
<br>
ACCEPTS: a :class:`~matplotlib.path.Path` instance and a<br>
:class:`~matplotlib.transforms.Transform` instance, a<br>
:class:`~matplotlib.patches.Patch` instance, or *None*.</tt></dd></dl>
<dl><dt><a name="AxesImage-set_contains"><strong>set_contains</strong></a>(self, picker)</dt><dd><tt>Replace the contains test used by this artist. The new picker should<br>
be a callable function which determines whether the artist is hit by the<br>
mouse event::<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
If the mouse event is over the artist, return *hit=True* and *props*<br>
is a dictionary of properties you want returned with the contains test.</tt></dd></dl>
<dl><dt><a name="AxesImage-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the :class:`~matplotlib.figure.Figure` instance the artist<br>
belongs to.<br>
<br>
ACCEPTS: a :class:`matplotlib.figure.Figure` instance</tt></dd></dl>
<dl><dt><a name="AxesImage-set_label"><strong>set_label</strong></a>(self, s)</dt><dd><tt>Set the line label to *s* for auto legend<br>
<br>
ACCEPTS: any string</tt></dd></dl>
<dl><dt><a name="AxesImage-set_lod"><strong>set_lod</strong></a>(self, on)</dt><dd><tt>Set Level of Detail on or off. If on, the artists may examine<br>
things like the pixel width of the axes and draw a subset of<br>
their contents accordingly<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="AxesImage-set_picker"><strong>set_picker</strong></a>(self, picker)</dt><dd><tt>set the epsilon for picking used by this artist<br>
<br>
*picker* can be one of the following:<br>
<br>
* *None*: picking is disabled for this artist (default)<br>
<br>
* A boolean: if *True* then picking will be enabled and the<br>
artist will fire a pick event if the mouse event is over<br>
the artist<br>
<br>
* A float: if picker is a number it is interpreted as an<br>
epsilon tolerance in points and the artist will fire<br>
off an event if it's data is within epsilon of the mouse<br>
event. For some artists like lines and patch collections,<br>
the artist may provide additional data to the pick event<br>
that is generated, e.g. the indices of the data within<br>
epsilon of the pick event<br>
<br>
* A function: if picker is callable, it is a user supplied<br>
function which determines whether the artist is hit by the<br>
mouse event::<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
to determine the hit test. if the mouse event is over the<br>
artist, return *hit=True* and props is a dictionary of<br>
properties you want added to the PickEvent attributes.<br>
<br>
ACCEPTS: [None|float|boolean|callable]</tt></dd></dl>
<dl><dt><a name="AxesImage-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>Set the :class:`~matplotlib.transforms.Transform` instance<br>
used by this artist.</tt></dd></dl>
<dl><dt><a name="AxesImage-set_visible"><strong>set_visible</strong></a>(self, b)</dt><dd><tt>set the artist's visiblity<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="AxesImage-set_zorder"><strong>set_zorder</strong></a>(self, level)</dt><dd><tt>Set the zorder for the artist<br>
<br>
ACCEPTS: any number</tt></dd></dl>
<dl><dt><a name="AxesImage-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="AxesImage-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>Copy properties from *other* to *self*.</tt></dd></dl>
<hr>
Data descriptors inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>__dict__</strong></dt>
<dd><tt>dictionary for instance variables (if defined)</tt></dd>
</dl>
<dl><dt><strong>__weakref__</strong></dt>
<dd><tt>list of weak references to the object (if defined)</tt></dd>
</dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>aname</strong> = 'Artist'</dl>
<hr>
Methods inherited from <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>:<br>
<dl><dt><a name="AxesImage-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="AxesImage-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="AxesImage-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="AxesImage-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="AxesImage-get_array"><strong>get_array</strong></a>(self)</dt><dd><tt>Return the array</tt></dd></dl>
<dl><dt><a name="AxesImage-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="AxesImage-get_cmap"><strong>get_cmap</strong></a>(self)</dt><dd><tt>return the colormap</tt></dd></dl>
<dl><dt><a name="AxesImage-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="AxesImage-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="AxesImage-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="AxesImage-set_norm"><strong>set_norm</strong></a>(self, norm)</dt><dd><tt>set the normalization instance</tt></dd></dl>
<dl><dt><a name="AxesImage-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> <p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="FigureImage">class <strong>FigureImage</strong></a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>, <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>)</font></td></tr>
<tr><td bgcolor="#ffc8d8"><tt> </tt></td><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="matplotlib.image.html#FigureImage">FigureImage</a></dd>
<dd><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a></dd>
<dd><a href="__builtin__.html#object">__builtin__.object</a></dd>
<dd><a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="FigureImage-__init__"><strong>__init__</strong></a>(self, fig, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, offsetx<font color="#909090">=0</font>, offsety<font color="#909090">=0</font>, origin<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>cmap is a colors.Colormap instance<br>
norm is a colors.Normalize instance to map luminance to 0-1<br>
<br>
kwargs are an optional list of <a href="matplotlib.artist.html#Artist">Artist</a> keyword args</tt></dd></dl>
<dl><dt><a name="FigureImage-contains"><strong>contains</strong></a>(self, mouseevent)</dt><dd><tt>Test whether the mouse event occured within the image.</tt></dd></dl>
<dl><dt><a name="FigureImage-draw"><strong>draw</strong></a>(self, renderer, *args, **kwargs)</dt></dl>
<dl><dt><a name="FigureImage-get_extent"><strong>get_extent</strong></a>(self)</dt><dd><tt>get the image extent: left, right, bottom, top</tt></dd></dl>
<dl><dt><a name="FigureImage-get_size"><strong>get_size</strong></a>(self)</dt><dd><tt>Get the numrows, numcols of the input image</tt></dd></dl>
<dl><dt><a name="FigureImage-make_image"><strong>make_image</strong></a>(self, magnification<font color="#909090">=1.0</font>)</dt></dl>
<dl><dt><a name="FigureImage-write_png"><strong>write_png</strong></a>(self, fname)</dt><dd><tt>Write the image to png file with fname</tt></dd></dl>
<hr>
Data and other attributes defined here:<br>
<dl><dt><strong>zorder</strong> = 1</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="FigureImage-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="FigureImage-convert_xunits"><strong>convert_xunits</strong></a>(self, x)</dt><dd><tt>for artists in an axes, if the xaxis as units support,<br>
convert *x* using xaxis unit type</tt></dd></dl>
<dl><dt><a name="FigureImage-convert_yunits"><strong>convert_yunits</strong></a>(self, y)</dt><dd><tt>for artists in an axes, if the yaxis as units support,<br>
convert *y* using yaxis unit type</tt></dd></dl>
<dl><dt><a name="FigureImage-findobj"><strong>findobj</strong></a>(self, match<font color="#909090">=None</font>)</dt><dd><tt>pyplot signature:<br>
<a href="#FigureImage-findobj">findobj</a>(o=gcf(), match=None) <br>
<br>
recursively find all :class:matplotlib.artist.<a href="matplotlib.artist.html#Artist">Artist</a> instances<br>
contained in self<br>
<br>
*match* can be<br>
<br>
- None: return all objects contained in artist (including artist)<br>
<br>
- function with signature ``boolean = match(artist)`` used to filter matches<br>
<br>
- class instance: eg Line2D. Only return artists of class type<br>
<br>
.. plot:: ../mpl_examples/pylab_examples/findobj_demo.py</tt></dd></dl>
<dl><dt><a name="FigureImage-get_alpha"><strong>get_alpha</strong></a>(self)</dt><dd><tt>Return the alpha value used for blending - not supported on all<br>
backends</tt></dd></dl>
<dl><dt><a name="FigureImage-get_animated"><strong>get_animated</strong></a>(self)</dt><dd><tt>return the artist's animated state</tt></dd></dl>
<dl><dt><a name="FigureImage-get_axes"><strong>get_axes</strong></a>(self)</dt><dd><tt>return the axes instance the artist resides in, or *None*</tt></dd></dl>
<dl><dt><a name="FigureImage-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="FigureImage-get_clip_on"><strong>get_clip_on</strong></a>(self)</dt><dd><tt>Return whether artist uses clipping</tt></dd></dl>
<dl><dt><a name="FigureImage-get_clip_path"><strong>get_clip_path</strong></a>(self)</dt><dd><tt>Return artist clip path</tt></dd></dl>
<dl><dt><a name="FigureImage-get_contains"><strong>get_contains</strong></a>(self)</dt><dd><tt>return the _contains test used by the artist, or *None* for default.</tt></dd></dl>
<dl><dt><a name="FigureImage-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>Return the :class:`~matplotlib.figure.Figure` instance the<br>
artist belongs to.</tt></dd></dl>
<dl><dt><a name="FigureImage-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="FigureImage-get_picker"><strong>get_picker</strong></a>(self)</dt><dd><tt>return the Pickeration instance used by this artist</tt></dd></dl>
<dl><dt><a name="FigureImage-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>Return the :class:`~matplotlib.transforms.Transform`<br>
instance used by this artist.</tt></dd></dl>
<dl><dt><a name="FigureImage-get_transformed_clip_path_and_affine"><strong>get_transformed_clip_path_and_affine</strong></a>(self)</dt><dd><tt>Return the clip path with the non-affine part of its<br>
transformation applied, and the remaining affine part of its<br>
transformation.</tt></dd></dl>
<dl><dt><a name="FigureImage-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="FigureImage-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="FigureImage-have_units"><strong>have_units</strong></a>(self)</dt><dd><tt>return *True* if units are set on the x or y axes</tt></dd></dl>
<dl><dt><a name="FigureImage-hitlist"><strong>hitlist</strong></a>(self, event)</dt><dd><tt>List the children of the artist which contain the mouse event</tt></dd></dl>
<dl><dt><a name="FigureImage-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="FigureImage-is_transform_set"><strong>is_transform_set</strong></a>(self)</dt><dd><tt><a href="matplotlib.artist.html#Artist">Artist</a> has transform explicity let</tt></dd></dl>
<dl><dt><a name="FigureImage-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="FigureImage-pick"><strong>pick</strong></a>(self, mouseevent)</dt><dd><tt>call signature::<br>
<br>
<a href="#FigureImage-pick">pick</a>(mouseevent)<br>
<br>
each child artist will fire a pick event if *mouseevent* is over<br>
the artist and the artist has picker set</tt></dd></dl>
<dl><dt><a name="FigureImage-pickable"><strong>pickable</strong></a>(self)</dt><dd><tt>return *True* if self is pickable</tt></dd></dl>
<dl><dt><a name="FigureImage-remove"><strong>remove</strong></a>(self)</dt><dd><tt>Remove the artist from the figure if possible. The effect<br>
will not be visible until the figure is redrawn, e.g., with<br>
:meth:`matplotlib.axes.Axes.draw_idle`. Call<br>
:meth:`matplotlib.axes.Axes.relim` to update the axes limits<br>
if desired.<br>
<br>
Note: :meth:`~matplotlib.axes.Axes.relim` will not see<br>
collections even if the collection was added to axes with<br>
*autolim* = True.<br>
<br>
Note: there is no support for removing the artist's legend entry.</tt></dd></dl>
<dl><dt><a name="FigureImage-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="FigureImage-set"><strong>set</strong></a>(self, **kwargs)</dt><dd><tt>A tkstyle set command, pass *kwargs* to set properties</tt></dd></dl>
<dl><dt><a name="FigureImage-set_alpha"><strong>set_alpha</strong></a>(self, alpha)</dt><dd><tt>Set the alpha value used for blending - not supported on<br>
all backends<br>
<br>
ACCEPTS: float</tt></dd></dl>
<dl><dt><a name="FigureImage-set_animated"><strong>set_animated</strong></a>(self, b)</dt><dd><tt>set the artist's animation state<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="FigureImage-set_axes"><strong>set_axes</strong></a>(self, axes)</dt><dd><tt>set the axes instance in which the artist resides, if any<br>
<br>
ACCEPTS: an axes instance</tt></dd></dl>
<dl><dt><a name="FigureImage-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a :class:`matplotlib.transform.Bbox` instance</tt></dd></dl>
<dl><dt><a name="FigureImage-set_clip_on"><strong>set_clip_on</strong></a>(self, b)</dt><dd><tt>Set whether artist uses clipping<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="FigureImage-set_clip_path"><strong>set_clip_path</strong></a>(self, path, transform<font color="#909090">=None</font>)</dt><dd><tt>Set the artist's clip path, which may be:<br>
<br>
* a :class:`~matplotlib.patches.Patch` (or subclass) instance<br>
<br>
* a :class:`~matplotlib.path.Path` instance, in which case<br>
an optional :class:`~matplotlib.transforms.Transform`<br>
instance may be provided, which will be applied to the<br>
path before using it for clipping.<br>
<br>
* *None*, to remove the clipping path<br>
<br>
For efficiency, if the path happens to be an axis-aligned<br>
rectangle, this method will set the clipping box to the<br>
corresponding rectangle and set the clipping path to *None*.<br>
<br>
ACCEPTS: a :class:`~matplotlib.path.Path` instance and a<br>
:class:`~matplotlib.transforms.Transform` instance, a<br>
:class:`~matplotlib.patches.Patch` instance, or *None*.</tt></dd></dl>
<dl><dt><a name="FigureImage-set_contains"><strong>set_contains</strong></a>(self, picker)</dt><dd><tt>Replace the contains test used by this artist. The new picker should<br>
be a callable function which determines whether the artist is hit by the<br>
mouse event::<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
If the mouse event is over the artist, return *hit=True* and *props*<br>
is a dictionary of properties you want returned with the contains test.</tt></dd></dl>
<dl><dt><a name="FigureImage-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the :class:`~matplotlib.figure.Figure` instance the artist<br>
belongs to.<br>
<br>
ACCEPTS: a :class:`matplotlib.figure.Figure` instance</tt></dd></dl>
<dl><dt><a name="FigureImage-set_label"><strong>set_label</strong></a>(self, s)</dt><dd><tt>Set the line label to *s* for auto legend<br>
<br>
ACCEPTS: any string</tt></dd></dl>
<dl><dt><a name="FigureImage-set_lod"><strong>set_lod</strong></a>(self, on)</dt><dd><tt>Set Level of Detail on or off. If on, the artists may examine<br>
things like the pixel width of the axes and draw a subset of<br>
their contents accordingly<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="FigureImage-set_picker"><strong>set_picker</strong></a>(self, picker)</dt><dd><tt>set the epsilon for picking used by this artist<br>
<br>
*picker* can be one of the following:<br>
<br>
* *None*: picking is disabled for this artist (default)<br>
<br>
* A boolean: if *True* then picking will be enabled and the<br>
artist will fire a pick event if the mouse event is over<br>
the artist<br>
<br>
* A float: if picker is a number it is interpreted as an<br>
epsilon tolerance in points and the artist will fire<br>
off an event if it's data is within epsilon of the mouse<br>
event. For some artists like lines and patch collections,<br>
the artist may provide additional data to the pick event<br>
that is generated, e.g. the indices of the data within<br>
epsilon of the pick event<br>
<br>
* A function: if picker is callable, it is a user supplied<br>
function which determines whether the artist is hit by the<br>
mouse event::<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
to determine the hit test. if the mouse event is over the<br>
artist, return *hit=True* and props is a dictionary of<br>
properties you want added to the PickEvent attributes.<br>
<br>
ACCEPTS: [None|float|boolean|callable]</tt></dd></dl>
<dl><dt><a name="FigureImage-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>Set the :class:`~matplotlib.transforms.Transform` instance<br>
used by this artist.</tt></dd></dl>
<dl><dt><a name="FigureImage-set_visible"><strong>set_visible</strong></a>(self, b)</dt><dd><tt>set the artist's visiblity<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="FigureImage-set_zorder"><strong>set_zorder</strong></a>(self, level)</dt><dd><tt>Set the zorder for the artist<br>
<br>
ACCEPTS: any number</tt></dd></dl>
<dl><dt><a name="FigureImage-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="FigureImage-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>Copy properties from *other* to *self*.</tt></dd></dl>
<hr>
Data descriptors inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>__dict__</strong></dt>
<dd><tt>dictionary for instance variables (if defined)</tt></dd>
</dl>
<dl><dt><strong>__weakref__</strong></dt>
<dd><tt>list of weak references to the object (if defined)</tt></dd>
</dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>aname</strong> = 'Artist'</dl>
<hr>
Methods inherited from <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>:<br>
<dl><dt><a name="FigureImage-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="FigureImage-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="FigureImage-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="FigureImage-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="FigureImage-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="FigureImage-get_array"><strong>get_array</strong></a>(self)</dt><dd><tt>Return the array</tt></dd></dl>
<dl><dt><a name="FigureImage-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="FigureImage-get_cmap"><strong>get_cmap</strong></a>(self)</dt><dd><tt>return the colormap</tt></dd></dl>
<dl><dt><a name="FigureImage-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="FigureImage-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="FigureImage-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="FigureImage-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="FigureImage-set_norm"><strong>set_norm</strong></a>(self, norm)</dt><dd><tt>set the normalization instance</tt></dd></dl>
<dl><dt><a name="FigureImage-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> <p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="NonUniformImage">class <strong>NonUniformImage</strong></a>(<a href="matplotlib.image.html#AxesImage">AxesImage</a>)</font></td></tr>
<tr><td bgcolor="#ffc8d8"><tt> </tt></td><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="matplotlib.image.html#NonUniformImage">NonUniformImage</a></dd>
<dd><a href="matplotlib.image.html#AxesImage">AxesImage</a></dd>
<dd><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a></dd>
<dd><a href="__builtin__.html#object">__builtin__.object</a></dd>
<dd><a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="NonUniformImage-__init__"><strong>__init__</strong></a>(self, ax, **kwargs)</dt></dl>
<dl><dt><a name="NonUniformImage-get_extent"><strong>get_extent</strong></a>(self)</dt></dl>
<dl><dt><a name="NonUniformImage-make_image"><strong>make_image</strong></a>(self, magnification<font color="#909090">=1.0</font>)</dt></dl>
<dl><dt><a name="NonUniformImage-set_array"><strong>set_array</strong></a>(self, *args)</dt></dl>
<dl><dt><a name="NonUniformImage-set_cmap"><strong>set_cmap</strong></a>(self, cmap)</dt></dl>
<dl><dt><a name="NonUniformImage-set_data"><strong>set_data</strong></a>(self, x, y, A)</dt></dl>
<dl><dt><a name="NonUniformImage-set_filternorm"><strong>set_filternorm</strong></a>(self, s)</dt></dl>
<dl><dt><a name="NonUniformImage-set_filterrad"><strong>set_filterrad</strong></a>(self, s)</dt></dl>
<dl><dt><a name="NonUniformImage-set_interpolation"><strong>set_interpolation</strong></a>(self, s)</dt></dl>
<dl><dt><a name="NonUniformImage-set_norm"><strong>set_norm</strong></a>(self, norm)</dt></dl>
<hr>
Methods inherited from <a href="matplotlib.image.html#AxesImage">AxesImage</a>:<br>
<dl><dt><a name="NonUniformImage-__str__"><strong>__str__</strong></a>(self)</dt></dl>
<dl><dt><a name="NonUniformImage-changed"><strong>changed</strong></a>(self)</dt><dd><tt>Call this whenever the mappable is changed so observers can<br>
update state</tt></dd></dl>
<dl><dt><a name="NonUniformImage-contains"><strong>contains</strong></a>(self, mouseevent)</dt><dd><tt>Test whether the mouse event occured within the image.</tt></dd></dl>
<dl><dt><a name="NonUniformImage-draw"><strong>draw</strong></a>(self, renderer, *args, **kwargs)</dt></dl>
<dl><dt><a name="NonUniformImage-get_filternorm"><strong>get_filternorm</strong></a>(self)</dt><dd><tt>return the filternorm setting</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_filterrad"><strong>get_filterrad</strong></a>(self)</dt><dd><tt>return the filterrad setting</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_interpolation"><strong>get_interpolation</strong></a>(self)</dt></dl>
<dl><dt><a name="NonUniformImage-get_size"><strong>get_size</strong></a>(self)</dt><dd><tt>Get the numrows, numcols of the input image</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_alpha"><strong>set_alpha</strong></a>(self, alpha)</dt><dd><tt>Set the alpha value used for blending - not supported on<br>
all backends<br>
<br>
ACCEPTS: float</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_extent"><strong>set_extent</strong></a>(self, extent)</dt><dd><tt>extent is data axes (left, right, bottom, top) for making image plots</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_resample"><strong>set_resample</strong></a>(self, v)</dt></dl>
<dl><dt><a name="NonUniformImage-write_png"><strong>write_png</strong></a>(self, fname, noscale<font color="#909090">=False</font>)</dt><dd><tt>Write the image to png file with fname</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.image.html#AxesImage">AxesImage</a>:<br>
<dl><dt><strong>interpnames</strong> = ['bilinear', 'nearest', 'kaiser', 'quadric', 'hermite', 'blackman', 'catrom', 'gaussian', 'hanning', 'spline36', 'hamming', 'lanczos', 'bicubic', 'mitchell', 'bessel', 'sinc', 'spline16']</dl>
<dl><dt><strong>k</strong> = 'spline16'</dl>
<dl><dt><strong>v</strong> = 3</dl>
<dl><dt><strong>zorder</strong> = 1</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="NonUniformImage-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="NonUniformImage-convert_xunits"><strong>convert_xunits</strong></a>(self, x)</dt><dd><tt>for artists in an axes, if the xaxis as units support,<br>
convert *x* using xaxis unit type</tt></dd></dl>
<dl><dt><a name="NonUniformImage-convert_yunits"><strong>convert_yunits</strong></a>(self, y)</dt><dd><tt>for artists in an axes, if the yaxis as units support,<br>
convert *y* using yaxis unit type</tt></dd></dl>
<dl><dt><a name="NonUniformImage-findobj"><strong>findobj</strong></a>(self, match<font color="#909090">=None</font>)</dt><dd><tt>pyplot signature:<br>
<a href="#NonUniformImage-findobj">findobj</a>(o=gcf(), match=None) <br>
<br>
recursively find all :class:matplotlib.artist.<a href="matplotlib.artist.html#Artist">Artist</a> instances<br>
contained in self<br>
<br>
*match* can be<br>
<br>
- None: return all objects contained in artist (including artist)<br>
<br>
- function with signature ``boolean = match(artist)`` used to filter matches<br>
<br>
- class instance: eg Line2D. Only return artists of class type<br>
<br>
.. plot:: ../mpl_examples/pylab_examples/findobj_demo.py</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_alpha"><strong>get_alpha</strong></a>(self)</dt><dd><tt>Return the alpha value used for blending - not supported on all<br>
backends</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_animated"><strong>get_animated</strong></a>(self)</dt><dd><tt>return the artist's animated state</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_axes"><strong>get_axes</strong></a>(self)</dt><dd><tt>return the axes instance the artist resides in, or *None*</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_clip_on"><strong>get_clip_on</strong></a>(self)</dt><dd><tt>Return whether artist uses clipping</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_clip_path"><strong>get_clip_path</strong></a>(self)</dt><dd><tt>Return artist clip path</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_contains"><strong>get_contains</strong></a>(self)</dt><dd><tt>return the _contains test used by the artist, or *None* for default.</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>Return the :class:`~matplotlib.figure.Figure` instance the<br>
artist belongs to.</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="NonUniformImage-get_picker"><strong>get_picker</strong></a>(self)</dt><dd><tt>return the Pickeration instance used by this artist</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>Return the :class:`~matplotlib.transforms.Transform`<br>
instance used by this artist.</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_transformed_clip_path_and_affine"><strong>get_transformed_clip_path_and_affine</strong></a>(self)</dt><dd><tt>Return the clip path with the non-affine part of its<br>
transformation applied, and the remaining affine part of its<br>
transformation.</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="NonUniformImage-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="NonUniformImage-have_units"><strong>have_units</strong></a>(self)</dt><dd><tt>return *True* if units are set on the x or y axes</tt></dd></dl>
<dl><dt><a name="NonUniformImage-hitlist"><strong>hitlist</strong></a>(self, event)</dt><dd><tt>List the children of the artist which contain the mouse event</tt></dd></dl>
<dl><dt><a name="NonUniformImage-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="NonUniformImage-is_transform_set"><strong>is_transform_set</strong></a>(self)</dt><dd><tt><a href="matplotlib.artist.html#Artist">Artist</a> has transform explicity let</tt></dd></dl>
<dl><dt><a name="NonUniformImage-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="NonUniformImage-pick"><strong>pick</strong></a>(self, mouseevent)</dt><dd><tt>call signature::<br>
<br>
<a href="#NonUniformImage-pick">pick</a>(mouseevent)<br>
<br>
each child artist will fire a pick event if *mouseevent* is over<br>
the artist and the artist has picker set</tt></dd></dl>
<dl><dt><a name="NonUniformImage-pickable"><strong>pickable</strong></a>(self)</dt><dd><tt>return *True* if self is pickable</tt></dd></dl>
<dl><dt><a name="NonUniformImage-remove"><strong>remove</strong></a>(self)</dt><dd><tt>Remove the artist from the figure if possible. The effect<br>
will not be visible until the figure is redrawn, e.g., with<br>
:meth:`matplotlib.axes.Axes.draw_idle`. Call<br>
:meth:`matplotlib.axes.Axes.relim` to update the axes limits<br>
if desired.<br>
<br>
Note: :meth:`~matplotlib.axes.Axes.relim` will not see<br>
collections even if the collection was added to axes with<br>
*autolim* = True.<br>
<br>
Note: there is no support for removing the artist's legend entry.</tt></dd></dl>
<dl><dt><a name="NonUniformImage-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="NonUniformImage-set"><strong>set</strong></a>(self, **kwargs)</dt><dd><tt>A tkstyle set command, pass *kwargs* to set properties</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_animated"><strong>set_animated</strong></a>(self, b)</dt><dd><tt>set the artist's animation state<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_axes"><strong>set_axes</strong></a>(self, axes)</dt><dd><tt>set the axes instance in which the artist resides, if any<br>
<br>
ACCEPTS: an axes instance</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a :class:`matplotlib.transform.Bbox` instance</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_clip_on"><strong>set_clip_on</strong></a>(self, b)</dt><dd><tt>Set whether artist uses clipping<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_clip_path"><strong>set_clip_path</strong></a>(self, path, transform<font color="#909090">=None</font>)</dt><dd><tt>Set the artist's clip path, which may be:<br>
<br>
* a :class:`~matplotlib.patches.Patch` (or subclass) instance<br>
<br>
* a :class:`~matplotlib.path.Path` instance, in which case<br>
an optional :class:`~matplotlib.transforms.Transform`<br>
instance may be provided, which will be applied to the<br>
path before using it for clipping.<br>
<br>
* *None*, to remove the clipping path<br>
<br>
For efficiency, if the path happens to be an axis-aligned<br>
rectangle, this method will set the clipping box to the<br>
corresponding rectangle and set the clipping path to *None*.<br>
<br>
ACCEPTS: a :class:`~matplotlib.path.Path` instance and a<br>
:class:`~matplotlib.transforms.Transform` instance, a<br>
:class:`~matplotlib.patches.Patch` instance, or *None*.</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_contains"><strong>set_contains</strong></a>(self, picker)</dt><dd><tt>Replace the contains test used by this artist. The new picker should<br>
be a callable function which determines whether the artist is hit by the<br>
mouse event::<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
If the mouse event is over the artist, return *hit=True* and *props*<br>
is a dictionary of properties you want returned with the contains test.</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the :class:`~matplotlib.figure.Figure` instance the artist<br>
belongs to.<br>
<br>
ACCEPTS: a :class:`matplotlib.figure.Figure` instance</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_label"><strong>set_label</strong></a>(self, s)</dt><dd><tt>Set the line label to *s* for auto legend<br>
<br>
ACCEPTS: any string</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_lod"><strong>set_lod</strong></a>(self, on)</dt><dd><tt>Set Level of Detail on or off. If on, the artists may examine<br>
things like the pixel width of the axes and draw a subset of<br>
their contents accordingly<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_picker"><strong>set_picker</strong></a>(self, picker)</dt><dd><tt>set the epsilon for picking used by this artist<br>
<br>
*picker* can be one of the following:<br>
<br>
* *None*: picking is disabled for this artist (default)<br>
<br>
* A boolean: if *True* then picking will be enabled and the<br>
artist will fire a pick event if the mouse event is over<br>
the artist<br>
<br>
* A float: if picker is a number it is interpreted as an<br>
epsilon tolerance in points and the artist will fire<br>
off an event if it's data is within epsilon of the mouse<br>
event. For some artists like lines and patch collections,<br>
the artist may provide additional data to the pick event<br>
that is generated, e.g. the indices of the data within<br>
epsilon of the pick event<br>
<br>
* A function: if picker is callable, it is a user supplied<br>
function which determines whether the artist is hit by the<br>
mouse event::<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
to determine the hit test. if the mouse event is over the<br>
artist, return *hit=True* and props is a dictionary of<br>
properties you want added to the PickEvent attributes.<br>
<br>
ACCEPTS: [None|float|boolean|callable]</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>Set the :class:`~matplotlib.transforms.Transform` instance<br>
used by this artist.</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_visible"><strong>set_visible</strong></a>(self, b)</dt><dd><tt>set the artist's visiblity<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="NonUniformImage-set_zorder"><strong>set_zorder</strong></a>(self, level)</dt><dd><tt>Set the zorder for the artist<br>
<br>
ACCEPTS: any number</tt></dd></dl>
<dl><dt><a name="NonUniformImage-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="NonUniformImage-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>Copy properties from *other* to *self*.</tt></dd></dl>
<hr>
Data descriptors inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>__dict__</strong></dt>
<dd><tt>dictionary for instance variables (if defined)</tt></dd>
</dl>
<dl><dt><strong>__weakref__</strong></dt>
<dd><tt>list of weak references to the object (if defined)</tt></dd>
</dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>aname</strong> = 'Artist'</dl>
<hr>
Methods inherited from <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>:<br>
<dl><dt><a name="NonUniformImage-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="NonUniformImage-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="NonUniformImage-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="NonUniformImage-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="NonUniformImage-get_array"><strong>get_array</strong></a>(self)</dt><dd><tt>Return the array</tt></dd></dl>
<dl><dt><a name="NonUniformImage-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="NonUniformImage-get_cmap"><strong>get_cmap</strong></a>(self)</dt><dd><tt>return the colormap</tt></dd></dl>
<dl><dt><a name="NonUniformImage-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="NonUniformImage-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="NonUniformImage-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> <p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="PcolorImage">class <strong>PcolorImage</strong></a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>, <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Make a pcolor-style plot with an irregular rectangular grid.<br>
<br>
This uses a variation of the original irregular image code,<br>
and it is used by pcolorfast for the corresponding grid type.<br> </tt></td></tr>
<tr><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="matplotlib.image.html#PcolorImage">PcolorImage</a></dd>
<dd><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a></dd>
<dd><a href="__builtin__.html#object">__builtin__.object</a></dd>
<dd><a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="PcolorImage-__init__"><strong>__init__</strong></a>(self, ax, x<font color="#909090">=None</font>, y<font color="#909090">=None</font>, A<font color="#909090">=None</font>, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>cmap defaults to its rc setting<br>
<br>
cmap is a colors.Colormap instance<br>
norm is a colors.Normalize instance to map luminance to 0-1<br>
<br>
Additional kwargs are matplotlib.artist properties</tt></dd></dl>
<dl><dt><a name="PcolorImage-draw"><strong>draw</strong></a>(self, renderer, *args, **kwargs)</dt></dl>
<dl><dt><a name="PcolorImage-make_image"><strong>make_image</strong></a>(self, magnification<font color="#909090">=1.0</font>)</dt></dl>
<dl><dt><a name="PcolorImage-set_alpha"><strong>set_alpha</strong></a>(self, alpha)</dt><dd><tt>Set the alpha value used for blending - not supported on<br>
all backends<br>
<br>
ACCEPTS: float</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_array"><strong>set_array</strong></a>(self, *args)</dt></dl>
<dl><dt><a name="PcolorImage-set_data"><strong>set_data</strong></a>(self, x, y, A)</dt></dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="PcolorImage-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="PcolorImage-contains"><strong>contains</strong></a>(self, mouseevent)</dt><dd><tt>Test whether the artist contains the mouse event.<br>
<br>
Returns the truth value and a dictionary of artist specific details of<br>
selection, such as which points are contained in the pick radius. See<br>
individual artists for details.</tt></dd></dl>
<dl><dt><a name="PcolorImage-convert_xunits"><strong>convert_xunits</strong></a>(self, x)</dt><dd><tt>for artists in an axes, if the xaxis as units support,<br>
convert *x* using xaxis unit type</tt></dd></dl>
<dl><dt><a name="PcolorImage-convert_yunits"><strong>convert_yunits</strong></a>(self, y)</dt><dd><tt>for artists in an axes, if the yaxis as units support,<br>
convert *y* using yaxis unit type</tt></dd></dl>
<dl><dt><a name="PcolorImage-findobj"><strong>findobj</strong></a>(self, match<font color="#909090">=None</font>)</dt><dd><tt>pyplot signature:<br>
<a href="#PcolorImage-findobj">findobj</a>(o=gcf(), match=None) <br>
<br>
recursively find all :class:matplotlib.artist.<a href="matplotlib.artist.html#Artist">Artist</a> instances<br>
contained in self<br>
<br>
*match* can be<br>
<br>
- None: return all objects contained in artist (including artist)<br>
<br>
- function with signature ``boolean = match(artist)`` used to filter matches<br>
<br>
- class instance: eg Line2D. Only return artists of class type<br>
<br>
.. plot:: ../mpl_examples/pylab_examples/findobj_demo.py</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_alpha"><strong>get_alpha</strong></a>(self)</dt><dd><tt>Return the alpha value used for blending - not supported on all<br>
backends</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_animated"><strong>get_animated</strong></a>(self)</dt><dd><tt>return the artist's animated state</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_axes"><strong>get_axes</strong></a>(self)</dt><dd><tt>return the axes instance the artist resides in, or *None*</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_clip_on"><strong>get_clip_on</strong></a>(self)</dt><dd><tt>Return whether artist uses clipping</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_clip_path"><strong>get_clip_path</strong></a>(self)</dt><dd><tt>Return artist clip path</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_contains"><strong>get_contains</strong></a>(self)</dt><dd><tt>return the _contains test used by the artist, or *None* for default.</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>Return the :class:`~matplotlib.figure.Figure` instance the<br>
artist belongs to.</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="PcolorImage-get_picker"><strong>get_picker</strong></a>(self)</dt><dd><tt>return the Pickeration instance used by this artist</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>Return the :class:`~matplotlib.transforms.Transform`<br>
instance used by this artist.</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_transformed_clip_path_and_affine"><strong>get_transformed_clip_path_and_affine</strong></a>(self)</dt><dd><tt>Return the clip path with the non-affine part of its<br>
transformation applied, and the remaining affine part of its<br>
transformation.</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="PcolorImage-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="PcolorImage-have_units"><strong>have_units</strong></a>(self)</dt><dd><tt>return *True* if units are set on the x or y axes</tt></dd></dl>
<dl><dt><a name="PcolorImage-hitlist"><strong>hitlist</strong></a>(self, event)</dt><dd><tt>List the children of the artist which contain the mouse event</tt></dd></dl>
<dl><dt><a name="PcolorImage-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="PcolorImage-is_transform_set"><strong>is_transform_set</strong></a>(self)</dt><dd><tt><a href="matplotlib.artist.html#Artist">Artist</a> has transform explicity let</tt></dd></dl>
<dl><dt><a name="PcolorImage-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="PcolorImage-pick"><strong>pick</strong></a>(self, mouseevent)</dt><dd><tt>call signature::<br>
<br>
<a href="#PcolorImage-pick">pick</a>(mouseevent)<br>
<br>
each child artist will fire a pick event if *mouseevent* is over<br>
the artist and the artist has picker set</tt></dd></dl>
<dl><dt><a name="PcolorImage-pickable"><strong>pickable</strong></a>(self)</dt><dd><tt>return *True* if self is pickable</tt></dd></dl>
<dl><dt><a name="PcolorImage-remove"><strong>remove</strong></a>(self)</dt><dd><tt>Remove the artist from the figure if possible. The effect<br>
will not be visible until the figure is redrawn, e.g., with<br>
:meth:`matplotlib.axes.Axes.draw_idle`. Call<br>
:meth:`matplotlib.axes.Axes.relim` to update the axes limits<br>
if desired.<br>
<br>
Note: :meth:`~matplotlib.axes.Axes.relim` will not see<br>
collections even if the collection was added to axes with<br>
*autolim* = True.<br>
<br>
Note: there is no support for removing the artist's legend entry.</tt></dd></dl>
<dl><dt><a name="PcolorImage-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="PcolorImage-set"><strong>set</strong></a>(self, **kwargs)</dt><dd><tt>A tkstyle set command, pass *kwargs* to set properties</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_animated"><strong>set_animated</strong></a>(self, b)</dt><dd><tt>set the artist's animation state<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_axes"><strong>set_axes</strong></a>(self, axes)</dt><dd><tt>set the axes instance in which the artist resides, if any<br>
<br>
ACCEPTS: an axes instance</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a :class:`matplotlib.transform.Bbox` instance</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_clip_on"><strong>set_clip_on</strong></a>(self, b)</dt><dd><tt>Set whether artist uses clipping<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_clip_path"><strong>set_clip_path</strong></a>(self, path, transform<font color="#909090">=None</font>)</dt><dd><tt>Set the artist's clip path, which may be:<br>
<br>
* a :class:`~matplotlib.patches.Patch` (or subclass) instance<br>
<br>
* a :class:`~matplotlib.path.Path` instance, in which case<br>
an optional :class:`~matplotlib.transforms.Transform`<br>
instance may be provided, which will be applied to the<br>
path before using it for clipping.<br>
<br>
* *None*, to remove the clipping path<br>
<br>
For efficiency, if the path happens to be an axis-aligned<br>
rectangle, this method will set the clipping box to the<br>
corresponding rectangle and set the clipping path to *None*.<br>
<br>
ACCEPTS: a :class:`~matplotlib.path.Path` instance and a<br>
:class:`~matplotlib.transforms.Transform` instance, a<br>
:class:`~matplotlib.patches.Patch` instance, or *None*.</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_contains"><strong>set_contains</strong></a>(self, picker)</dt><dd><tt>Replace the contains test used by this artist. The new picker should<br>
be a callable function which determines whether the artist is hit by the<br>
mouse event::<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
If the mouse event is over the artist, return *hit=True* and *props*<br>
is a dictionary of properties you want returned with the contains test.</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the :class:`~matplotlib.figure.Figure` instance the artist<br>
belongs to.<br>
<br>
ACCEPTS: a :class:`matplotlib.figure.Figure` instance</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_label"><strong>set_label</strong></a>(self, s)</dt><dd><tt>Set the line label to *s* for auto legend<br>
<br>
ACCEPTS: any string</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_lod"><strong>set_lod</strong></a>(self, on)</dt><dd><tt>Set Level of Detail on or off. If on, the artists may examine<br>
things like the pixel width of the axes and draw a subset of<br>
their contents accordingly<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_picker"><strong>set_picker</strong></a>(self, picker)</dt><dd><tt>set the epsilon for picking used by this artist<br>
<br>
*picker* can be one of the following:<br>
<br>
* *None*: picking is disabled for this artist (default)<br>
<br>
* A boolean: if *True* then picking will be enabled and the<br>
artist will fire a pick event if the mouse event is over<br>
the artist<br>
<br>
* A float: if picker is a number it is interpreted as an<br>
epsilon tolerance in points and the artist will fire<br>
off an event if it's data is within epsilon of the mouse<br>
event. For some artists like lines and patch collections,<br>
the artist may provide additional data to the pick event<br>
that is generated, e.g. the indices of the data within<br>
epsilon of the pick event<br>
<br>
* A function: if picker is callable, it is a user supplied<br>
function which determines whether the artist is hit by the<br>
mouse event::<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
to determine the hit test. if the mouse event is over the<br>
artist, return *hit=True* and props is a dictionary of<br>
properties you want added to the PickEvent attributes.<br>
<br>
ACCEPTS: [None|float|boolean|callable]</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>Set the :class:`~matplotlib.transforms.Transform` instance<br>
used by this artist.</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_visible"><strong>set_visible</strong></a>(self, b)</dt><dd><tt>set the artist's visiblity<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PcolorImage-set_zorder"><strong>set_zorder</strong></a>(self, level)</dt><dd><tt>Set the zorder for the artist<br>
<br>
ACCEPTS: any number</tt></dd></dl>
<dl><dt><a name="PcolorImage-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="PcolorImage-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>Copy properties from *other* to *self*.</tt></dd></dl>
<hr>
Data descriptors inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>__dict__</strong></dt>
<dd><tt>dictionary for instance variables (if defined)</tt></dd>
</dl>
<dl><dt><strong>__weakref__</strong></dt>
<dd><tt>list of weak references to the object (if defined)</tt></dd>
</dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>aname</strong> = 'Artist'</dl>
<dl><dt><strong>zorder</strong> = 0</dl>
<hr>
Methods inherited from <a href="matplotlib.cm.html#ScalarMappable">matplotlib.cm.ScalarMappable</a>:<br>
<dl><dt><a name="PcolorImage-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="PcolorImage-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="PcolorImage-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="PcolorImage-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="PcolorImage-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="PcolorImage-get_array"><strong>get_array</strong></a>(self)</dt><dd><tt>Return the array</tt></dd></dl>
<dl><dt><a name="PcolorImage-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="PcolorImage-get_cmap"><strong>get_cmap</strong></a>(self)</dt><dd><tt>return the colormap</tt></dd></dl>
<dl><dt><a name="PcolorImage-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="PcolorImage-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="PcolorImage-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="PcolorImage-set_norm"><strong>set_norm</strong></a>(self, norm)</dt><dd><tt>set the normalization instance</tt></dd></dl>
<dl><dt><a name="PcolorImage-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>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<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="-from_images"><strong>from_images</strong></a>(...)</dt><dd><tt>from_images</tt></dd></dl>
<dl><dt><a name="-fromarray"><strong>fromarray</strong></a>(...)</dt><dd><tt>fromarray</tt></dd></dl>
<dl><dt><a name="-fromarray2"><strong>fromarray2</strong></a>(...)</dt><dd><tt>fromarray2</tt></dd></dl>
<dl><dt><a name="-frombuffer"><strong>frombuffer</strong></a>(...)</dt><dd><tt>frombuffer</tt></dd></dl>
<dl><dt><a name="-frombyte"><strong>frombyte</strong></a>(...)</dt><dd><tt>frombyte</tt></dd></dl>
<dl><dt><a name="-imread"><strong>imread</strong></a>(fname)</dt><dd><tt>Return image file in *fname* as :class:`numpy.array`.<br>
<br>
Return value is a :class:`numpy.array`. For grayscale images, the<br>
return array is MxN. For RGB images, the return value is MxNx3.<br>
For RGBA images the return value is MxNx4.<br>
<br>
matplotlib can only read PNGs natively, but if `PIL<br>
<<a href="http://www.pythonware.com/products/pil/>`_">http://www.pythonware.com/products/pil/>`_</a> is installed, it will<br>
use it to load the image and return an array (if possible) which<br>
can be used with :func:`~matplotlib.pyplot.imshow`.<br>
<br>
TODO: support RGB and grayscale return values in _image.readpng</tt></dd></dl>
<dl><dt><a name="-pcolor"><strong>pcolor</strong></a>(...)</dt><dd><tt>pcolor</tt></dd></dl>
<dl><dt><a name="-pcolor2"><strong>pcolor2</strong></a>(...)</dt><dd><tt>pcolor2</tt></dd></dl>
<dl><dt><a name="-pil_to_array"><strong>pil_to_array</strong></a>(pilImage)</dt><dd><tt>load a PIL image and return it as a numpy array of uint8. For<br>
grayscale images, the return array is MxN. For RGB images, the<br>
return value is MxNx3. For RGBA images the return value is MxNx4</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>ASPECT_FREE</strong> = 1<br>
<strong>ASPECT_PRESERVE</strong> = 0<br>
<strong>BESSEL</strong> = 12<br>
<strong>BICUBIC</strong> = 2<br>
<strong>BILINEAR</strong> = 1<br>
<strong>BLACKMAN</strong> = 16<br>
<strong>CATROM</strong> = 10<br>
<strong>GAUSSIAN</strong> = 11<br>
<strong>HAMMING</strong> = 6<br>
<strong>HANNING</strong> = 5<br>
<strong>HERMITE</strong> = 7<br>
<strong>KAISER</strong> = 8<br>
<strong>LANCZOS</strong> = 15<br>
<strong>MITCHELL</strong> = 13<br>
<strong>NEAREST</strong> = 0<br>
<strong>QUADRIC</strong> = 9<br>
<strong>SINC</strong> = 14<br>
<strong>SPLINE16</strong> = 3<br>
<strong>SPLINE36</strong> = 4<br>
<strong>division</strong> = _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)<br>
<strong>rcParams</strong> = {'figure.subplot.right': 0.90000000000000002, 'm...persize': 'letter', 'svg.embed_char_paths': True}</td></tr></table>
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