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<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="heading">
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<font color="#ffffff" face="helvetica, arial"> <br><big><big><strong><a href="matplotlib.html"><font color="#ffffff">matplotlib</font></a>.axes</strong></big></big></font></td
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><font color="#ffffff" face="helvetica, arial"><a href=".">index</a><br><a href="file:/usr/local/lib/python2.3/site-packages/matplotlib/axes.py">/usr/local/lib/python2.3/site-packages/matplotlib/axes.py</a></font></td></tr></table>
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<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.cm.html">matplotlib.cm</a><br>
</td><td width="25%" valign=top><a href="math.html">math</a><br>
<a href="matplotlib.html">matplotlib</a><br>
</td><td width="25%" valign=top><a href="sys.html">sys</a><br>
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<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>
</font></dt><dd>
<dl>
<dt><font face="helvetica, arial"><a href="matplotlib.axes.html#Axes">Axes</a>
</font></dt><dd>
<dl>
<dt><font face="helvetica, arial"><a href="matplotlib.axes.html#PolarAxes">PolarAxes</a>
</font></dt></dl>
</dd>
</dl>
</dd>
<dt><font face="helvetica, arial"><a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>
</font></dt><dd>
<dl>
<dt><font face="helvetica, arial"><a href="matplotlib.axes.html#PolarSubplot">PolarSubplot</a>(<a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>, <a href="matplotlib.axes.html#PolarAxes">PolarAxes</a>)
</font></dt><dt><font face="helvetica, arial"><a href="matplotlib.axes.html#Subplot">Subplot</a>(<a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>, <a href="matplotlib.axes.html#Axes">Axes</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="Axes">class <strong>Axes</strong></a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Emulate matlab's (TM) axes command, creating axes with<br>
<br>
<a href="#Axes">Axes</a>(position=[left, bottom, width, height])<br>
<br>
where all the arguments are fractions in [0,1] which specify the<br>
fraction of the total figure window.<br>
<br>
axisbg is the color of the axis background<br> </tt></td></tr>
<tr><td> </td>
<td width="100%">Methods defined here:<br>
<dl><dt><a name="Axes-__init__"><strong>__init__</strong></a>(self, fig, rect, axisbg<font color="#909090">=None</font>, frameon<font color="#909090">=True</font>, sharex<font color="#909090">=None</font>, sharey<font color="#909090">=None</font>, label<font color="#909090">=''</font>)</dt></dl>
<dl><dt><a name="Axes-add_artist"><strong>add_artist</strong></a>(self, a)</dt><dd><tt>Add any artist to the axes</tt></dd></dl>
<dl><dt><a name="Axes-add_collection"><strong>add_collection</strong></a>(self, collection)</dt><dd><tt>add a Collection instance to <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Axes-add_line"><strong>add_line</strong></a>(self, l)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="Axes-add_patch"><strong>add_patch</strong></a>(self, p)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="Axes-add_table"><strong>add_table</strong></a>(self, tab)</dt><dd><tt>Add a table instance to the list of axes tables</tt></dd></dl>
<dl><dt><a name="Axes-autoscale_view"><strong>autoscale_view</strong></a>(self)</dt><dd><tt>autoscale the view limits using the data limits</tt></dd></dl>
<dl><dt><a name="Axes-axhline"><strong>axhline</strong></a>(self, y<font color="#909090">=0</font>, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHLINE(y=0, xmin=0, xmax=1, **kwargs)<br>
<br>
Axis Horizontal Line<br>
<br>
Draw a horizontal line at y from xmin to xmax. With the default<br>
values of xmin=0 and xmax=1, this line will always span the horizontal<br>
extent of the axes, regardless of the xlim settings, even if you<br>
change them, eg with the xlim command. That is, the horizontal extent<br>
is in axes coords: 0=left, 0.5=middle, 1.0=right but the y location is<br>
in data coordinates.<br>
<br>
Return value is the Line2D instance. kwargs are the same as kwargs to<br>
plot, and can be used to control the line properties. Eg<br>
<br>
# draw a thick red hline at y=0 that spans the xrange<br>
<a href="#Axes-axhline">axhline</a>(linewidth=4, color='r')<br>
<br>
# draw a default hline at y=1 that spans the xrange<br>
<a href="#Axes-axhline">axhline</a>(y=1)<br>
<br>
# draw a default hline at y=.5 that spans the the middle half of<br>
# the xrange<br>
<a href="#Axes-axhline">axhline</a>(y=.5, xmin=0.25, xmax=0.75)</tt></dd></dl>
<dl><dt><a name="Axes-axhspan"><strong>axhspan</strong></a>(self, ymin, ymax, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHSPAN(ymin, ymax, xmin=0, xmax=1, **kwargs)<br>
<br>
Axis Horizontal Span. ycoords are in data units and x<br>
coords are in axes (relative 0-1) units<br>
<br>
Draw a horizontal span (regtangle) from ymin to ymax. With the<br>
default values of xmin=0 and xmax=1, this always span the xrange,<br>
regardless of the xlim settings, even if you change them, eg with the<br>
xlim command. That is, the horizontal extent is in axes coords:<br>
0=left, 0.5=middle, 1.0=right but the y location is in data<br>
coordinates.<br>
<br>
kwargs are the kwargs to Patch, eg<br>
<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
<br>
the terms on the right are aliases<br>
<br>
Return value is the patches.Polygon instance.<br>
<br>
#draws a gray rectangle from y=0.25-0.75 that spans the horizontal<br>
#extent of the axes<br>
<a href="#Axes-axhspan">axhspan</a>(0.25, 0.75, facecolor=0.5, alpha=0.5)</tt></dd></dl>
<dl><dt><a name="Axes-axvline"><strong>axvline</strong></a>(self, x<font color="#909090">=0</font>, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVLINE(x=0, ymin=0, ymax=1, **kwargs)<br>
<br>
Axis Vertical Line<br>
<br>
Draw a vertical line at x from ymin to ymax. With the default values<br>
of ymin=0 and ymax=1, this line will always span the vertical extent<br>
of the axes, regardless of the xlim settings, even if you change them,<br>
eg with the xlim command. That is, the vertical extent is in axes<br>
coords: 0=bottom, 0.5=middle, 1.0=top but the x location is in data<br>
coordinates.<br>
<br>
Return value is the Line2D instance. kwargs are the same as<br>
kwargs to plot, and can be used to control the line properties. Eg<br>
<br>
# draw a thick red vline at x=0 that spans the yrange<br>
l = <a href="#Axes-axvline">axvline</a>(linewidth=4, color='r')<br>
<br>
# draw a default vline at x=1 that spans the yrange<br>
l = <a href="#Axes-axvline">axvline</a>(x=1)<br>
<br>
# draw a default vline at x=.5 that spans the the middle half of<br>
# the yrange<br>
<a href="#Axes-axvline">axvline</a>(x=.5, ymin=0.25, ymax=0.75)</tt></dd></dl>
<dl><dt><a name="Axes-axvspan"><strong>axvspan</strong></a>(self, xmin, xmax, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVSPAN(xmin, xmax, ymin=0, ymax=1, **kwargs)<br>
<br>
axvspan : Axis Vertical Span. xcoords are in data units and y coords<br>
are in axes (relative 0-1) units<br>
<br>
Draw a vertical span (regtangle) from xmin to xmax. With the default<br>
values of ymin=0 and ymax=1, this always span the yrange, regardless<br>
of the ylim settings, even if you change them, eg with the ylim<br>
command. That is, the vertical extent is in axes coords: 0=bottom,<br>
0.5=middle, 1.0=top but the y location is in data coordinates.<br>
<br>
kwargs are the kwargs to Patch, eg<br>
<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
<br>
the terms on the right are aliases<br>
<br>
return value is the patches.Polygon instance.<br>
<br>
# draw a vertical green translucent rectangle from x=1.25 to 1.55 that<br>
# spans the yrange of the axes<br>
<a href="#Axes-axvspan">axvspan</a>(1.25, 1.55, facecolor='g', alpha=0.5)</tt></dd></dl>
<dl><dt><a name="Axes-bar"><strong>bar</strong></a>(self, left, height, width<font color="#909090">=0.80000000000000004</font>, bottom<font color="#909090">=0</font>, color<font color="#909090">='b'</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">='k'</font>, capsize<font color="#909090">=3</font>)</dt><dd><tt>BAR(left, height, width=0.8, bottom=0,<br>
color='b', yerr=None, xerr=None, ecolor='k', capsize=3)<br>
<br>
Make a bar plot with rectangles at<br>
<br>
left, left+width, 0, height<br>
<br>
left and height are Numeric arrays.<br>
<br>
Return value is a list of Rectangle patch instances<br>
<br>
BAR(left, height, width, bottom,<br>
color, yerr, xerr, capsize, yoff)<br>
<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
<br>
color specifies the color of the bar<br>
<br>
ecolor specifies the color of any errorbar<br>
<br>
capsize determines the length in points of the error bar caps<br>
<br>
<br>
The optional arguments color, width and bottom can be either<br>
scalars or len(x) sequences<br>
<br>
This enables you to use bar as the basis for stacked bar<br>
charts, or candlestick plots</tt></dd></dl>
<dl><dt><a name="Axes-barh"><strong>barh</strong></a>(self, x, y, height<font color="#909090">=0.80000000000000004</font>, left<font color="#909090">=0</font>, color<font color="#909090">='b'</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">='k'</font>, capsize<font color="#909090">=3</font>)</dt><dd><tt>BARH(x, y, height=0.8, left=0,<br>
color='b', yerr=None, xerr=None, ecolor='k', capsize=3)<br>
<br>
BARH(x, y)<br>
<br>
The y values give the heights of the center of the bars. The<br>
x values give the length of the bars.<br>
<br>
Return value is a list of Rectangle patch instances<br>
<br>
Optional arguments<br>
<br>
height - the height (thickness) of the bar<br>
<br>
left - the x coordinate of the left side of the bar<br>
<br>
color specifies the color of the bar<br>
<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
<br>
ecolor specifies the color of any errorbar<br>
<br>
capsize determines the length in points of the error bar caps<br>
<br>
The optional arguments color, height and left can be either<br>
scalars or len(x) sequences</tt></dd></dl>
<dl><dt><a name="Axes-boxplot"><strong>boxplot</strong></a>(self, x, notch<font color="#909090">=0</font>, sym<font color="#909090">='b+'</font>, vert<font color="#909090">=1</font>, whis<font color="#909090">=1.5</font>)</dt><dd><tt><a href="#Axes-boxplot">boxplot</a>(x, notch=0, sym='+', vert=1, whis=1.5)<br>
<br>
Make a box and whisker plot for each column of x.<br>
The box extends from the lower to upper quartile values<br>
of the data, with a line at the median. The whiskers<br>
extend from the box to show the range of the data. Flier<br>
points are those past the end of the whiskers.<br>
<br>
notch = 0 (default) produces a rectangular box plot. <br>
notch = 1 will produce a notched box plot<br>
<br>
sym (default 'b+') is the default symbol for flier points.<br>
Enter an empty string ('') if you don't want to show fliers.<br>
<br>
vert = 1 (default) makes the boxes vertical.<br>
vert = 0 makes horizontal boxes. This seems goofy, but<br>
that's how Matlab did it.<br>
<br>
whis (default 1.5) defines the length of the whiskers as<br>
a function of the inner quartile range. They extend to the<br>
most extreme data point within ( whis*(75%-25%) ) data range.<br>
<br>
x is a Numeric array<br>
<br>
Returns a list of the lines added</tt></dd></dl>
<dl><dt><a name="Axes-cla"><strong>cla</strong></a>(self)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="Axes-clabel"><strong>clabel</strong></a>(self, *args, **kwargs)</dt><dd><tt>CLABEL(*args, **kwargs)<br>
<br>
Function signatures<br>
<br>
CLABEL(C) - plots contour labels,<br>
C is the output of contour or a list of contours<br>
<br>
CLABEL(C,V) - creates labels only for those contours, given in<br>
a list V<br>
<br>
CLABEL(C, **kwargs) - keyword args are explained below:<br>
<br>
<br>
<br>
* fontsize = None: as described in <a href="http://matplotlib.sf.net/fonts.html">http://matplotlib.sf.net/fonts.html</a><br>
<br>
* colors = None:<br>
<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different labels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all labels<br>
will be plotted in this color<br>
<br>
- if colors == None, the color of each label matches the color<br>
of the corresponding contour<br>
<br>
* inline = 0: controls whether the underlying contour is removed<br>
(inline = 1) or not<br>
<br>
* fmt = '%1.3f': a format string for the label</tt></dd></dl>
<dl><dt><a name="Axes-clear"><strong>clear</strong></a>(self)</dt><dd><tt>clear the axes</tt></dd></dl>
<dl><dt><a name="Axes-cohere"><strong>cohere</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>COHERE(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
cohere the coherence between x and y. Coherence is the normalized<br>
cross spectral density<br>
<br>
Cxy = |Pxy|^2/(Pxx*Pyy)<br>
<br>
The return value is (Cxy, f), where f are the frequencies of the<br>
coherence vector.<br>
<br>
See the PSD help for a description of the optional parameters.<br>
<br>
Returns the tuple Cxy, freqs<br>
<br>
Refs: Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="Axes-connect"><strong>connect</strong></a>(self, s, func)</dt><dd><tt>Register observers to be notified when certain events occur. Register<br>
with callback functions with the following signatures. The function<br>
has the following signature<br>
<br>
func(ax) # where ax is the instance making the callback.<br>
<br>
The following events can be connected to:<br>
<br>
'xlim_changed','ylim_changed'<br>
<br>
The connection id is is returned - you can use this with<br>
disconnect to disconnect from the axes event</tt></dd></dl>
<dl><dt><a name="Axes-contour"><strong>contour</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Axes-contour">contour</a>(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#Axes-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#Axes-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#Axes-contour">contour</a>(Z,N) and <a href="#Axes-contour">contour</a>(X,Y,Z,N) - draw N contour lines overriding<br>
the automatic value<br>
<br>
<a href="#Axes-contour">contour</a>(Z,V) and <a href="#Axes-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in V (array, list, tuple)<br>
<br>
<a href="#Axes-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
[L,C] = <a href="#Axes-contour">contour</a>(...) returns a list of levels and a silent_list of LineCollections<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None: one of these:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the default colormap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified.<br>
<br>
* badmask = None: array with dimensions of Z, and with values<br>
of zero at locations corresponding to valid data, and one<br>
at locations where the value of Z should be ignored.<br>
This is experimental. It presently works for edge regions<br>
for line and filled contours, but for interior regions it<br>
works correctly only for line contours. The badmask kwarg<br>
may go away in the future, to be replaced by the use of<br>
NaN value in Z and/or the use of a masked array in Z.<br>
<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
.matplotlibrc is used<br>
<br>
* fmt = '1.3f': a format string for adding a label to each collection.<br>
Useful for auto-legending.</tt></dd></dl>
<dl><dt><a name="Axes-contourf"><strong>contourf</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Axes-contourf">contourf</a>(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#Axes-contourf">contourf</a>(Z) - make a filled contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#Axes-contourf">contourf</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#Axes-contourf">contourf</a>(Z,N) and <a href="#Axes-contourf">contourf</a>(X,Y,Z,N) - make a filled contour plot<br>
corresponding to N contour levels<br>
<br>
<a href="#Axes-contourf">contourf</a>(Z,V) and <a href="#Axes-contourf">contourf</a>(X,Y,Z,V) - fill len(V) regions,<br>
between the levels specified in sequence V, and a final region<br>
for values of Z greater than the last element in V<br>
<br>
<a href="#Axes-contourf">contourf</a>(Z, **kwargs) - Use keyword args to control colors,<br>
origin, cmap ... see below<br>
<br>
[L,C] = <a href="#Axes-contourf">contourf</a>(...) returns a list of levels and a silent_list<br>
of PolyCollections<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None: one of these:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the default colormap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* badmask = None: array with dimensions of Z, and with values<br>
of zero at locations corresponding to valid data, and one<br>
at locations where the value of Z should be ignored.<br>
This is experimental. It presently works for edge regions<br>
for line and filled contours, but for interior regions it<br>
works correctly only for line contours. The badmask kwarg<br>
may go away in the future, to be replaced by the use of<br>
NaN value in Z and/or the use of a masked array in Z.<br>
<br>
reg is a 1D region number array with of imax*(jmax+1)+1 size<br>
The values of reg should be positive region numbers, and zero fro<br>
zones wich do not exist.<br>
<br>
triangle - triangulation array - must be the same shape as reg<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges (because the contouring engine yields<br>
simply connected regions with branch cuts.) To draw the edges,<br>
add line contours with calls to contour.</tt></dd></dl>
<dl><dt><a name="Axes-csd"><strong>csd</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>CSD(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
The cross spectral density Pxy by Welches average periodogram method.<br>
The vectors x and y are divided into NFFT length segments. Each<br>
segment is detrended by function detrend and windowed by function<br>
window. The product of the direct FFTs of x and y are averaged over<br>
each segment to compute Pxy, with a scaling to correct for power loss<br>
due to windowing.<br>
<br>
See the PSD help for a description of the optional parameters.<br>
<br>
Returns the tuple Pxy, freqs. Pxy is the cross spectrum (complex<br>
valued), and 10*log10(|Pxy|) is plotted<br>
<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="Axes-disconnect"><strong>disconnect</strong></a>(self, cid)</dt><dd><tt>disconnect from the <a href="#Axes">Axes</a> event.</tt></dd></dl>
<dl><dt><a name="Axes-draw"><strong>draw</strong></a>(self, renderer)</dt><dd><tt>Draw everything (plot lines, axes, labels)</tt></dd></dl>
<dl><dt><a name="Axes-errorbar"><strong>errorbar</strong></a>(self, x, y, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, fmt<font color="#909090">='b-'</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, barsabove<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>ERRORBAR(x, y, yerr=None, xerr=None,<br>
fmt='b-', ecolor=None, capsize=3, barsabove=False)<br>
<br>
Plot x versus y with error deltas in yerr and xerr.<br>
Vertical errorbars are plotted if yerr is not None<br>
Horizontal errorbars are plotted if xerr is not None<br>
<br>
xerr and yerr may be any of:<br>
<br>
a rank-0, Nx1 Numpy array - symmetric errorbars +/- value<br>
<br>
an N-element list or tuple - symmetric errorbars +/- value<br>
<br>
a rank-1, Nx2 Numpy array - asymmetric errorbars -column1/+column2<br>
<br>
Alternatively, x, y, xerr, and yerr can all be scalars, which<br>
plots a single error bar at x, y.<br>
<br>
fmt is the plot format symbol for y. if fmt is None, just<br>
plot the errorbars with no line symbols. This can be useful<br>
for creating a bar plot with errorbars<br>
<br>
ecolor is a matplotlib color arg which gives the color the<br>
errorbar lines; if None, use the marker color.<br>
<br>
capsize is the size of the error bar caps in points<br>
<br>
barsabove, if True, will plot the errorbars above the plot symbols<br>
- default is below<br>
<br>
kwargs are passed on to the plot command for the markers<br>
<br>
Return value is a length 2 tuple. The first element is a list of<br>
y symbol lines. The second element is a list of error bar lines.</tt></dd></dl>
<dl><dt><a name="Axes-fill"><strong>fill</strong></a>(self, *args, **kwargs)</dt><dd><tt>FILL(*args, **kwargs)<br>
<br>
plot filled polygons. *args is a variable length argument, allowing<br>
for multiple x,y pairs with an optional color format string; see plot<br>
for details on the argument parsing. For example, all of the<br>
following are legal, assuming a is the Axis instance:<br>
<br>
ax.<a href="#Axes-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
ax.<a href="#Axes-fill">fill</a>(x,y, 'b' ) # plot polygon with vertices at x,y in blue<br>
<br>
An arbitrary number of x, y, color groups can be specified, as in<br>
ax.<a href="#Axes-fill">fill</a>(x1, y1, 'g', x2, y2, 'r')<br>
<br>
Return value is a list of patches that were added<br>
<br>
The same color strings that plot supports are supported by the fill<br>
format string.<br>
<br>
The kwargs that are can be used to set line properties (any<br>
property that has a set_* method). You can use this to set edge<br>
color, face color, etc.</tt></dd></dl>
<dl><dt><a name="Axes-format_coord"><strong>format_coord</strong></a>(self, x, y)</dt><dd><tt>return a format string formatting the x, y coord</tt></dd></dl>
<dl><dt><a name="Axes-format_xdata"><strong>format_xdata</strong></a>(self, x)</dt><dd><tt>Return x string formatted. This function will use the attribute<br>
self.<strong>fmt_xdata</strong> if it is callable, else will fall back on the xaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="Axes-format_ydata"><strong>format_ydata</strong></a>(self, y)</dt><dd><tt>Return y string formatted. This function will use the attribute<br>
self.<strong>fmt_ydata</strong> if it is callable, else will fall back on the yaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="Axes-get_axis_bgcolor"><strong>get_axis_bgcolor</strong></a>(self)</dt><dd><tt>Return the axis background color</tt></dd></dl>
<dl><dt><a name="Axes-get_child_artists"><strong>get_child_artists</strong></a>(self)</dt><dd><tt>Return a list of artists the axes contains. Deprecated</tt></dd></dl>
<dl><dt><a name="Axes-get_cursor_props"><strong>get_cursor_props</strong></a>(self)</dt><dd><tt>return the cursor props as a linewidth, color tuple where<br>
linewidth is a float and color is an RGBA tuple</tt></dd></dl>
<dl><dt><a name="Axes-get_frame"><strong>get_frame</strong></a>(self)</dt><dd><tt>Return the axes Rectangle frame</tt></dd></dl>
<dl><dt><a name="Axes-get_images"><strong>get_images</strong></a>(self)</dt><dd><tt>return a list of <a href="#Axes">Axes</a> images contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Axes-get_legend"><strong>get_legend</strong></a>(self)</dt><dd><tt>Return the Legend instance, or None if no legend is defined</tt></dd></dl>
<dl><dt><a name="Axes-get_lines"><strong>get_lines</strong></a>(self)</dt><dd><tt>Return a list of lines contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Axes-get_position"><strong>get_position</strong></a>(self)</dt><dd><tt>Return the axes rectangle left, bottom, width, height</tt></dd></dl>
<dl><dt><a name="Axes-get_xaxis"><strong>get_xaxis</strong></a>(self)</dt><dd><tt>Return the XAxis instance</tt></dd></dl>
<dl><dt><a name="Axes-get_xgridlines"><strong>get_xgridlines</strong></a>(self)</dt><dd><tt>Get the x grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Axes-get_xlim"><strong>get_xlim</strong></a>(self)</dt><dd><tt>Get the x axis range [xmin, xmax]</tt></dd></dl>
<dl><dt><a name="Axes-get_xscale"><strong>get_xscale</strong></a>(self)</dt><dd><tt>return the xaxis scale string: log or linear</tt></dd></dl>
<dl><dt><a name="Axes-get_xticklabels"><strong>get_xticklabels</strong></a>(self)</dt><dd><tt>Get the xtick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="Axes-get_xticklines"><strong>get_xticklines</strong></a>(self)</dt><dd><tt>Get the xtick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Axes-get_xticks"><strong>get_xticks</strong></a>(self)</dt><dd><tt>Return the x ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="Axes-get_yaxis"><strong>get_yaxis</strong></a>(self)</dt><dd><tt>Return the YAxis instance</tt></dd></dl>
<dl><dt><a name="Axes-get_ygridlines"><strong>get_ygridlines</strong></a>(self)</dt><dd><tt>Get the y grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Axes-get_ylim"><strong>get_ylim</strong></a>(self)</dt><dd><tt>Get the y axis range [ymin, ymax]</tt></dd></dl>
<dl><dt><a name="Axes-get_yscale"><strong>get_yscale</strong></a>(self)</dt><dd><tt>return the yaxis scale string: log or linear</tt></dd></dl>
<dl><dt><a name="Axes-get_yticklabels"><strong>get_yticklabels</strong></a>(self)</dt><dd><tt>Get the ytick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="Axes-get_yticklines"><strong>get_yticklines</strong></a>(self)</dt><dd><tt>Get the ytick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Axes-get_yticks"><strong>get_yticks</strong></a>(self)</dt><dd><tt>Return the y ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="Axes-grid"><strong>grid</strong></a>(self, b<font color="#909090">=None</font>)</dt><dd><tt>Set the axes grids on or off; b is a boolean<br>
if b is None, toggle the grid state</tt></dd></dl>
<dl><dt><a name="Axes-has_data"><strong>has_data</strong></a>(self)</dt><dd><tt>return true if any artists have been added to axes</tt></dd></dl>
<dl><dt><a name="Axes-hist"><strong>hist</strong></a>(self, x, bins<font color="#909090">=10</font>, normed<font color="#909090">=0</font>, bottom<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>HIST(x, bins=10, normed=0, bottom=0)<br>
<br>
Compute the histogram of x. bins is either an integer number of<br>
bins or a sequence giving the bins. x are the data to be binned.<br>
<br>
The return values is (n, bins, patches)<br>
<br>
If normed is true, the first element of the return tuple will be the<br>
counts normalized to form a probability distribtion, ie,<br>
n/(len(x)*dbin)<br>
<br>
kwargs are used to update the properties of the hist bars</tt></dd></dl>
<dl><dt><a name="Axes-hlines"><strong>hlines</strong></a>(self, y, xmin, xmax, fmt<font color="#909090">='k-'</font>)</dt><dd><tt>HLINES(y, xmin, xmax, fmt='k-')<br>
<br>
plot horizontal lines at each y from xmin to xmax. xmin or xmax can<br>
be scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the widths of the lines are<br>
determined by xmin and xmax<br>
<br>
Returns a list of line instances that were added</tt></dd></dl>
<dl><dt><a name="Axes-hold"><strong>hold</strong></a>(self, b<font color="#909090">=None</font>)</dt><dd><tt>HOLD(b=None)<br>
<br>
Set the hold state. If hold is None (default), toggle the<br>
hold state. Else set the hold state to boolean value b.<br>
<br>
Eg<br>
<a href="#Axes-hold">hold</a>() # toggle hold<br>
<a href="#Axes-hold">hold</a>(True) # hold is on<br>
<a href="#Axes-hold">hold</a>(False) # hold is off</tt></dd></dl>
<dl><dt><a name="Axes-imshow"><strong>imshow</strong></a>(self, X, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, aspect<font color="#909090">=None</font>, interpolation<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, origin<font color="#909090">=None</font>, extent<font color="#909090">=None</font>)</dt><dd><tt>IMSHOW(X, cmap=None, norm=None, aspect=None, interpolation=None,<br>
alpha=1.0, vmin=None, vmax=None, origin=None, extent=None)<br>
<br>
IMSHOW(X) - plot image X to current axes, resampling to scale to axes<br>
size (X may be numarray/Numeric array or PIL image)<br>
<br>
IMSHOW(X, **kwargs) - Use keyword args to control image scaling,<br>
colormapping etc. See below for details<br>
<br>
<br>
Display the image in X to current axes. X may be a float array or a<br>
PIL image. If X is a float array, X can have the following shapes<br>
<br>
MxN : luminance (grayscale)<br>
<br>
MxNx3 : RGB<br>
<br>
MxNx4 : RGBA<br>
<br>
A matplotlib.image.AxesImage instance is returned<br>
<br>
The following kwargs are allowed:<br>
<br>
* cmap is a cm colormap instance, eg cm.jet. If None, default to rc<br>
image.cmap value (Ignored when X has RGB(A) information)<br>
<br>
* aspect is one of: free or preserve. if None, default to rc<br>
image.aspect value<br>
<br>
* interpolation is one of: bicubic bilinear blackman100 blackman256<br>
blackman64 nearest sinc144 sinc256 sinc64 spline16 or spline36.<br>
If None, default to rc image.interpolation<br>
<br>
* norm is a matplotlib.colors.normalize instance; default is<br>
normalization(). This scales luminance -> 0-1 (Ignored when X is<br>
PIL image).<br>
<br>
* vmin and vmax are used to scale a luminance image to 0-1. If<br>
either is None, the min and max of the luminance values will be<br>
used. Note if you pass a norm instance, the settings for vmin and<br>
vmax will be ignored.<br>
<br>
* alpha = 1.0 : the alpha blending value<br>
<br>
* origin is either upper or lower, which indicates where the [0,0]<br>
index of the array is in the upper left or lower left corner of<br>
the axes. If None, default to rc image.origin<br>
<br>
* extent is a data xmin, xmax, ymin, ymax for making image plots<br>
registered with data plots. Default is the image dimensions<br>
in pixels</tt></dd></dl>
<dl><dt><a name="Axes-in_axes"><strong>in_axes</strong></a>(self, xwin, ywin)</dt><dd><tt>return True is the point xwin, ywin (display coords) are in the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Axes-ishold"><strong>ishold</strong></a>(self)</dt><dd><tt>return the HOLD status of the axes</tt></dd></dl>
<dl><dt><a name="Axes-legend"><strong>legend</strong></a>(self, *args, **kwargs)</dt><dd><tt>LEGEND(*args, **kwargs)<br>
<br>
Place a legend on the current axes at location loc. Labels are a<br>
sequence of strings and loc can be a string or an integer specifying<br>
the legend location<br>
<br>
USAGE:<br>
<br>
Make a legend with existing lines<br>
<br>
>>> <a href="#Axes-legend">legend</a>()<br>
<br>
legend by itself will try and build a legend using the label<br>
property of the lines/patches/collections. You can set the label of<br>
a line by doing <a href="#Axes-plot">plot</a>(x, y, label='my data') or line.<a href="#Axes-set_label">set_label</a>('my<br>
data')<br>
<br>
# automatically generate the legend from labels<br>
<a href="#Axes-legend">legend</a>( ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend for a list of lines and labels<br>
<a href="#Axes-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend at a given location, using a location argument<br>
# <a href="#Axes-legend">legend</a>( LABELS, LOC ) or<br>
# <a href="#Axes-legend">legend</a>( LINES, LABELS, LOC )<br>
<a href="#Axes-legend">legend</a>( ('label1', 'label2', 'label3'), loc='upper left')<br>
<a href="#Axes-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3'), loc=2)<br>
<br>
The location codes are<br>
<br>
'best' : 0, <br>
'upper right' : 1, (default)<br>
'upper left' : 2,<br>
'lower left' : 3,<br>
'lower right' : 4,<br>
'right' : 5,<br>
'center left' : 6,<br>
'center right' : 7,<br>
'lower center' : 8,<br>
'upper center' : 9,<br>
'center' : 10,<br>
<br>
If none of these are suitable, loc can be a 2-tuple giving x,y<br>
in axes coords, ie,<br>
<br>
loc = 0, 1 is left top<br>
loc = 0.5, 0.5 is center, center<br>
<br>
and so on. The following kwargs are supported<br>
<br>
numpoints = 4 # the number of points in the legend line<br>
prop = FontProperties('smaller') # the font properties<br>
pad = 0.2 # the fractional whitespace inside the legend border<br>
<br>
# The kwarg dimensions are in axes coords<br>
labelsep = 0.005 # the vertical space between the legend entries<br>
handlelen = 0.05 # the length of the legend lines<br>
handletextsep = 0.02 # the space between the legend line and legend text<br>
axespad = 0.02 # the border between the axes and legend edge<br>
shadow = False # if True, draw a shadow behind legend</tt></dd></dl>
<dl><dt><a name="Axes-loglog"><strong>loglog</strong></a>(self, *args, **kwargs)</dt><dd><tt>LOGLOG(*args, **kwargs)<br>
<br>
Make a loglog plot with log scaling on the a and y axis. The args<br>
to semilog x are the same as the args to plot. See help plot for<br>
more info.<br>
<br>
Optional keyword args supported are any of the kwargs<br>
supported by plot or set_xscale or set_yscale. Notable, for<br>
log scaling:<br>
<br>
* basex: base of the x logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot<br>
<br>
* basey: base of the y logarithm<br>
<br>
* subsy: the location of the minor yticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="Axes-panx"><strong>panx</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan right, minus pan left)</tt></dd></dl>
<dl><dt><a name="Axes-pany"><strong>pany</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan up, minus pan down)</tt></dd></dl>
<dl><dt><a name="Axes-pcolor"><strong>pcolor</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLOR(*args, **kwargs)<br>
<br>
Function signatures<br>
<br>
PCOLOR(C) - make a pseudocolor plot of matrix C<br>
<br>
PCOLOR(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
<br>
PCOLOR(C, **kwargs) - Use keywork args to control colormapping and<br>
scaling; see below<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
<br>
* norm = normalize() : matplotlib.colors.normalize is used to scale<br>
luminance data to 0,1.<br>
<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. If you pass a norm<br>
instance, vmin and vmax will be None<br>
<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edge colors are same as<br>
face colors<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
<br>
Grid Orientation<br>
<br>
The behavior of meshgrid in matlab(TM) is a bit counterintuitive for<br>
x and y arrays. For example,<br>
<br>
x = <a href="#-arange">arange</a>(7)<br>
y = <a href="#-arange">arange</a>(5)<br>
X, Y = meshgrid(x,y)<br>
<br>
Z = rand( len(x), len(y))<br>
<a href="#Axes-pcolor">pcolor</a>(X, Y, Z)<br>
<br>
will fail in matlab and pylab. You will probably be<br>
happy with<br>
<br>
<a href="#Axes-pcolor">pcolor</a>(X, Y, transpose(Z))<br>
<br>
Likewise, for nonsquare Z,<br>
<br>
<a href="#Axes-pcolor">pcolor</a>(transpose(Z))<br>
<br>
will make the x and y axes in the plot agree with the numrows and<br>
numcols of Z</tt></dd></dl>
<dl><dt><a name="Axes-pcolor_classic"><strong>pcolor_classic</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLOR_CLASSIC(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#Axes-pcolor">pcolor</a>(C) - make a pseudocolor plot of matrix C<br>
<br>
<a href="#Axes-pcolor">pcolor</a>(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
<br>
<a href="#Axes-pcolor">pcolor</a>(C, cmap=cm.jet) - make a pseudocolor plot of matrix C using<br>
rectangle patches using a colormap jet. Colormaps are avalible<br>
in matplotlib.cm. You must pass this as a kwarg.<br>
<br>
<a href="#Axes-pcolor">pcolor</a>(C, norm=normalize()) - the normalization function used<br>
` to scale your color data to 0-1. must be passed as a kwarg.<br>
<br>
<a href="#Axes-pcolor">pcolor</a>(C, alpha=0.5) - set the alpha of the pseudocolor plot.<br>
Must be used as a kwarg<br>
<br>
Shading:<br>
<br>
The optional keyword arg shading ('flat' or 'faceted') will<br>
determine whether a black grid is drawn around each pcolor square.<br>
Default 'faceteted' e.g., <a href="#Axes-pcolor">pcolor</a>(C, shading='flat') <a href="#Axes-pcolor">pcolor</a>(X, Y,<br>
C, shading='faceted')<br>
<br>
Return value is a list of patch objects.<br>
<br>
Grid orientation<br>
<br>
The behavior of meshgrid in matlab(TM) is a bit counterintuitive for x<br>
and y arrays. For example,<br>
<br>
x = <a href="#-arange">arange</a>(7)<br>
y = <a href="#-arange">arange</a>(5)<br>
X, Y = meshgrid(x,y)<br>
<br>
Z = rand( len(x), len(y))<br>
<a href="#Axes-pcolor">pcolor</a>(X, Y, Z)<br>
<br>
will fail in matlab and matplotlib. You will probably be<br>
happy with<br>
<br>
<a href="#Axes-pcolor">pcolor</a>(X, Y, transpose(Z))<br>
<br>
Likewise, for nonsquare Z,<br>
<br>
<a href="#Axes-pcolor">pcolor</a>(transpose(Z))<br>
<br>
will make the x and y axes in the plot agree with the numrows<br>
and numcols of Z</tt></dd></dl>
<dl><dt><a name="Axes-pick"><strong>pick</strong></a>(self, x, y, trans<font color="#909090">=None</font>)</dt><dd><tt>Return the artist under point that is closest to the x, y. if trans<br>
is None, x, and y are in window coords, 0,0 = lower left. Otherwise,<br>
trans is a matplotlib transform that specifies the coordinate system<br>
of x, y.<br>
<br>
Note this algorithm calculates distance to the vertices of the<br>
polygon, so if you want to pick a patch, click on the edge!</tt></dd></dl>
<dl><dt><a name="Axes-pie"><strong>pie</strong></a>(self, x, explode<font color="#909090">=None</font>, labels<font color="#909090">=None</font>, colors<font color="#909090">=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w')</font>, autopct<font color="#909090">=None</font>, shadow<font color="#909090">=False</font>)</dt><dd><tt>Make a pie chart of array x. The fractional area of each wedge is<br>
given by x/sum(x). If sum(x)<=1, then the values of x give the<br>
fractional area directly and the array will not be normalized.<br>
<br>
- explode, if not None, is a len(x) array which specifies the<br>
fraction of the radius to offset that wedge.<br>
<br>
- colors is a sequence of matplotlib color args that the pie chart<br>
will cycle.<br>
<br>
- labels, if not None, is a len(x) list of labels.<br>
<br>
- autopct, if not None, is a string or function used to label the<br>
wedges with their numeric value. The label will be placed inside<br>
the wedge. If it is a format string, the label will be fmt%pct.<br>
If it is a function, it will be called<br>
<br>
- shadow, if True, will draw a shadow beneath the pie.<br>
<br>
The pie chart will probably look best if the figure and axes are<br>
square. Eg,<br>
<br>
figure(figsize=(8,8))<br>
ax = axes([0.1, 0.1, 0.8, 0.8])<br>
<br>
Return value:<br>
<br>
If autopct is None, return a list of (patches, texts), where patches<br>
is a sequence of matplotlib.patches.Wedge instances and texts is a<br>
list of the label Text instnaces<br>
<br>
If autopct is not None, return (patches, texts, autotexts), where<br>
patches and texts are as above, and autotexts is a list of text<br>
instances for the numeric labels</tt></dd></dl>
<dl><dt><a name="Axes-plot"><strong>plot</strong></a>(self, *args, **kwargs)</dt><dd><tt>PLOT(*args, **kwargs)<br>
<br>
Plot lines and/or markers to the <a href="#Axes">Axes</a>. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional format<br>
string. For example, each of the following is legal<br>
<br>
<a href="#Axes-plot">plot</a>(x,y) # plot x and y using the default line style and color<br>
<a href="#Axes-plot">plot</a>(x,y, 'bo') # plot x and y using blue circle markers<br>
<a href="#Axes-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
<a href="#Axes-plot">plot</a>(y, 'r+') # ditto, but with red plusses<br>
<br>
An arbitrary number of x, y, fmt groups can be specified, as in<br>
<br>
a.<a href="#Axes-plot">plot</a>(x1, y1, 'g^', x2, y2, 'g-')<br>
<br>
Return value is a list of lines that were added.<br>
<br>
The following line styles are supported:<br>
<br>
- : solid line<br>
-- : dashed line<br>
-. : dash-dot line<br>
: : dotted line<br>
. : points<br>
, : pixels<br>
o : circle symbols<br>
^ : triangle up symbols<br>
v : triangle down symbols<br>
< : triangle left symbols<br>
> : triangle right symbols<br>
s : square symbols<br>
+ : plus symbols<br>
x : cross symbols<br>
D : diamond symbols<br>
d : thin diamond symbols<br>
1 : tripod down symbols<br>
2 : tripod up symbols<br>
3 : tripod left symbols<br>
4 : tripod right symbols<br>
h : hexagon symbols<br>
H : rotated hexagon symbols<br>
p : pentagon symbols<br>
| : vertical line symbols<br>
_ : horizontal line symbols<br>
steps : use gnuplot style 'steps' # kwarg only<br>
<br>
The following color strings are supported<br>
<br>
b : blue<br>
g : green<br>
r : red<br>
c : cyan<br>
m : magenta<br>
y : yellow<br>
k : black<br>
w : white<br>
<br>
Line styles and colors are combined in a single format string, as in<br>
'bo' for blue circles.<br>
<br>
The **kwargs can be used to set line properties (any property that has<br>
a set_* method). You can use this to set a line label (for auto<br>
legends), linewidth, anitialising, marker face color, etc. Here is an<br>
example:<br>
<br>
<a href="#Axes-plot">plot</a>([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)<br>
<a href="#Axes-plot">plot</a>([1,2,3], [1,4,9], 'rs', label='line 2')<br>
axis([0, 4, 0, 10])<br>
<a href="#Axes-legend">legend</a>()<br>
<br>
If you make multiple lines with one plot command, the kwargs apply<br>
to all those lines, eg<br>
<br>
<a href="#Axes-plot">plot</a>(x1, y1, x2, y2, antialising=False)<br>
<br>
Neither line will be antialiased.</tt></dd></dl>
<dl><dt><a name="Axes-plot_date"><strong>plot_date</strong></a>(self, d, y, fmt<font color="#909090">='bo'</font>, tz<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>PLOT_DATE(d, y, converter, fmt='bo', tz=None, **kwargs)<br>
<br>
d is a sequence of dates represented as float days since<br>
0001-01-01 UTC and y are the y values at those dates. fmt is<br>
a plot format string. kwargs are passed on to plot. See plot<br>
for more information.<br>
<br>
See matplotlib.dates for helper functions date2num, num2date<br>
and drange for help on creating the required floating point dates<br>
<br>
tz is the timezone - defaults to rc value</tt></dd></dl>
<dl><dt><a name="Axes-psd"><strong>psd</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>PSD(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
The power spectral density by Welches average periodogram method. The<br>
vector x is divided into NFFT length segments. Each segment is<br>
detrended by function detrend and windowed by function window.<br>
noperlap gives the length of the overlap between segments. The<br>
absolute(fft(segment))**2 of each segment are averaged to compute Pxx,<br>
with a scaling to correct for power loss due to windowing. Fs is the<br>
sampling frequency.<br>
<br>
NFFT is the length of the fft segment; must be a power of 2<br>
<br>
Fs is the sampling frequency.<br>
<br>
detrend - the function applied to each segment before fft-ing,<br>
designed to remove the mean or linear trend. Unlike in matlab,<br>
where the detrend parameter is a vector, in matplotlib is it a<br>
function. The mlab module defines detrend_none, detrend_mean,<br>
detrend_linear, but you can use a custom function as well.<br>
<br>
window - the function used to window the segments. window is a<br>
function, unlike in matlab(TM) where it is a vector. mlab defines<br>
window_none, window_hanning, but you can use a custom function<br>
as well.<br>
<br>
noverlap gives the length of the overlap between segments.<br>
<br>
Returns the tuple Pxx, freqs<br>
<br>
For plotting, the power is plotted as 10*log10(pxx)) for decibels,<br>
though pxx itself is returned<br>
<br>
Refs:<br>
<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="Axes-quiver"><strong>quiver</strong></a>(self, U, V, *args, **kwargs)</dt><dd><tt>QUIVER( X, Y, U, V )<br>
QUIVER( U, V )<br>
QUIVER( X, Y, U, V, S)<br>
QUIVER( U, V, S )<br>
QUIVER( ..., color=None, width=1.0, cmap=None,norm=None )<br>
<br>
Make a vector plot (U, V) with arrows on a grid (X, Y)<br>
<br>
The optional arguments color and width are used to specify the color and width<br>
of the arrow. color can be an array of colors in which case the arrows can be<br>
colored according to another dataset.<br>
<br>
If cm is specied and color is None, the colormap is used to give a color<br>
according to the vector's length.<br>
<br>
If color is a scalar field, the colormap is used to map the scalar to a color<br>
If a colormap is specified and color is an array of color triplets, then the<br>
colormap is ignored<br>
<br>
width is a scalar that controls the width of the arrows<br>
<br>
if S is specified it is used to scale the vectors. Use S=0 to disable automatic<br>
scaling.<br>
If S!=0, vectors are scaled to fit within the grid and then are multiplied by S.</tt></dd></dl>
<dl><dt><a name="Axes-scatter"><strong>scatter</strong></a>(self, x, y, s<font color="#909090">=20</font>, c<font color="#909090">='b'</font>, marker<font color="#909090">='o'</font>, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, **kwargs)</dt><dd><tt>SCATTER(x, y, s=20, c='b', marker='o', cmap=None, norm=None,<br>
vmin=None, vmax=None, alpha=1.0)<br>
<br>
Supported function signatures:<br>
<br>
SCATTER(x, y) - make a scatter plot of x vs y<br>
<br>
SCATTER(x, y, s) - make a scatter plot of x vs y with size in area<br>
given by s<br>
<br>
SCATTER(x, y, s, c) - make a scatter plot of x vs y with size in area<br>
given by s and colors given by c<br>
<br>
SCATTER(x, y, s, c, **kwargs) - control colormapping and scaling<br>
with keyword args; see below<br>
<br>
Make a scatter plot of x versus y. s is a size in points^2 a scalar<br>
or an array of the same length as x or y. c is a color and can be a<br>
single color format string or an length(x) array of intensities which<br>
will be mapped by the matplotlib.colors.colormap instance cmap<br>
<br>
The marker can be one of<br>
<br>
's' : square<br>
'o' : circle<br>
'^' : triangle up<br>
'>' : triangle right<br>
'v' : triangle down<br>
'<' : triangle left<br>
'd' : diamond<br>
'p' : pentagram<br>
'h' : hexagon<br>
'8' : octagon<br>
<br>
s is a size argument in points squared.<br>
<br>
Other keyword args; the color mapping and normalization arguments will<br>
on be used if c is an array of floats<br>
<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to rc image.cmap<br>
<br>
* norm = normalize() : matplotlib.colors.normalize is used to<br>
scale luminance data to 0,1.<br>
<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. Note if you pass a norm<br>
instance, your settings for vmin and vmax will be ignored<br>
<br>
* alpha =1.0 : the alpha value for the patches</tt></dd></dl>
<dl><dt><a name="Axes-scatter_classic"><strong>scatter_classic</strong></a>(self, x, y, s<font color="#909090">=None</font>, c<font color="#909090">='b'</font>)</dt><dd><tt>SCATTER_CLASSIC(x, y, s=None, c='b')<br>
<br>
Make a scatter plot of x versus y. s is a size (in data coords) and<br>
can be either a scalar or an array of the same length as x or y. c is<br>
a color and can be a single color format string or an length(x) array<br>
of intensities which will be mapped by the colormap jet.<br>
<br>
If size is None a default size will be used</tt></dd></dl>
<dl><dt><a name="Axes-semilogx"><strong>semilogx</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGX(*args, **kwargs)<br>
<br>
Make a semilog plot with log scaling on the x axis. The args to<br>
semilog x are the same as the args to plot. See help plot for more<br>
info.<br>
<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_xscale. Notable, for log scaling:<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="Axes-semilogy"><strong>semilogy</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGY(*args, **kwargs):<br>
<br>
Make a semilog plot with log scaling on the y axis. The args to<br>
semilogy are the same as the args to plot. See help plot for more<br>
info.<br>
<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_yscale. Notable, for log scaling:<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="Axes-set_axis_bgcolor"><strong>set_axis_bgcolor</strong></a>(self, color)</dt><dd><tt>set the axes background color<br>
<br>
ACCEPTS: any matplotlib color - see help(colors)</tt></dd></dl>
<dl><dt><a name="Axes-set_axis_off"><strong>set_axis_off</strong></a>(self)</dt><dd><tt>turn off the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="Axes-set_axis_on"><strong>set_axis_on</strong></a>(self)</dt><dd><tt>turn on the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="Axes-set_cursor_props"><strong>set_cursor_props</strong></a>(self, *args)</dt><dd><tt>Set the cursor property as<br>
ax.<a href="#Axes-set_cursor_props">set_cursor_props</a>(linewidth, color) OR<br>
ax.<a href="#Axes-set_cursor_props">set_cursor_props</a>((linewidth, color))<br>
<br>
ACCEPTS: a (float, color) tuple</tt></dd></dl>
<dl><dt><a name="Axes-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the <a href="#Axes">Axes</a> figure<br>
<br>
ACCEPTS: a Figure instance</tt></dd></dl>
<dl><dt><a name="Axes-set_frame_on"><strong>set_frame_on</strong></a>(self, b)</dt><dd><tt>Set whether the axes rectangle patch is drawn<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="Axes-set_position"><strong>set_position</strong></a>(self, pos)</dt><dd><tt>Set the axes position with pos = [left, bottom, width, height]<br>
in relative 0,1 coords<br>
<br>
ACCEPTS: len(4) sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-set_title"><strong>set_title</strong></a>(self, label, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_TITLE(label, fontdict=None, **kwargs):<br>
<br>
Set the title for the xaxis. See the text docstring for information<br>
of how override and the optional args work<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Axes-set_xlabel"><strong>set_xlabel</strong></a>(self, xlabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XLABEL(xlabel, fontdict=None, **kwargs)<br>
<br>
Set the label for the xaxis. See the text docstring for information<br>
of how override and the optional args work.<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Axes-set_xlim"><strong>set_xlim</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Axes-set_xlim">set_xlim</a>(self, *args, **kwargs):<br>
<br>
Set the limits for the xaxis; v = [xmin, xmax]<br>
<br>
<a href="#Axes-set_xlim">set_xlim</a>((valmin, valmax))<br>
<a href="#Axes-set_xlim">set_xlim</a>(valmin, valmax)<br>
<a href="#Axes-set_xlim">set_xlim</a>(xmin=1) # xmax unchanged<br>
<a href="#Axes-set_xlim">set_xlim</a>(xmax=1) # xmin unchanged<br>
<br>
Valid kwargs:<br>
<br>
xmin : the min of the xlim<br>
xmax : the max of the xlim <br>
emit : notify observers of lim change<br>
<br>
<br>
Returns the current xlimits as a length 2 tuple<br>
<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-set_xscale"><strong>set_xscale</strong></a>(self, value, basex<font color="#909090">=10</font>, subsx<font color="#909090">=None</font>)</dt><dd><tt>SET_XSCALE(value, basex=10, subsx=None)<br>
<br>
Set the xscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Axes-set_xticklabels"><strong>set_xticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XTICKLABELS(labels, fontdict=None, **kwargs)<br>
<br>
Set the xtick labels with list of strings labels Return a list of axis<br>
text instances<br>
<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="Axes-set_xticks"><strong>set_xticks</strong></a>(self, ticks)</dt><dd><tt>Set the x ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-set_ylabel"><strong>set_ylabel</strong></a>(self, ylabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YLABEL(ylabel, fontdict=None, **kwargs)<br>
<br>
Set the label for the yaxis<br>
<br>
See the text doctstring for information of how override and<br>
the optional args work<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Axes-set_ylim"><strong>set_ylim</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Axes-set_ylim">set_ylim</a>(self, *args, **kwargs):<br>
<br>
Set the limits for the yaxis; v = [ymin, ymax]<br>
<br>
<a href="#Axes-set_ylim">set_ylim</a>((valmin, valmax))<br>
<a href="#Axes-set_ylim">set_ylim</a>(valmin, valmax)<br>
<a href="#Axes-set_ylim">set_ylim</a>(ymin=1) # ymax unchanged<br>
<a href="#Axes-set_ylim">set_ylim</a>(ymax=1) # ymin unchanged<br>
<br>
Valid kwargs:<br>
<br>
ymin : the min of the ylim<br>
ymax : the max of the ylim <br>
emit : notify observers of lim change<br>
<br>
<br>
Returns the current ylimits as a length 2 tuple<br>
<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-set_yscale"><strong>set_yscale</strong></a>(self, value, basey<font color="#909090">=10</font>, subsy<font color="#909090">=None</font>)</dt><dd><tt>SET_YSCALE(value, basey=10, subsy=None)<br>
<br>
Set the yscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: the location of the minor ticks; None are the default<br>
is to autosub<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Axes-set_yticklabels"><strong>set_yticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YTICKLABELS(labels, fontdict=None, **kwargs)<br>
<br>
Set the ytick labels with list of strings labels. Return a list of<br>
Text instances<br>
<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="Axes-set_yticks"><strong>set_yticks</strong></a>(self, ticks)</dt><dd><tt>Set the y ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-specgram"><strong>specgram</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=128</font>, cmap<font color="#909090">=None</font>, xextent<font color="#909090">=None</font>)</dt><dd><tt>SPECGRAM(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=128,<br>
cmap=None, xextent=None)<br>
<br>
Compute a spectrogram of data in x. Data are split into NFFT length<br>
segements and the PSD of each section is computed. The windowing<br>
function window is applied to each segment, and the amount of overlap<br>
of each segment is specified with noverlap.<br>
<br>
* cmap is a colormap; if None use default determined by rc<br>
<br>
* xextent is the image extent in the xaxes xextent=xmin, xmax -<br>
default 0, max(bins), 0, max(freqs) where bins is the return<br>
value from matplotlib.matplotlib.mlab.specgram<br>
<br>
* See help(psd) for information on the other keyword arguments.<br>
<br>
Return value is (Pxx, freqs, bins, im), where<br>
<br>
bins are the time points the spectrogram is calculated over<br>
<br>
freqs is an array of frequencies<br>
<br>
Pxx is a len(times) x len(freqs) array of power<br>
<br>
im is a matplotlib.image.AxesImage.</tt></dd></dl>
<dl><dt><a name="Axes-spy"><strong>spy</strong></a>(self, Z, marker<font color="#909090">='s'</font>, markersize<font color="#909090">=10</font>, **kwargs)</dt><dd><tt>SPY(Z, **kwrags) plots the sparsity pattern of the matrix S<br>
using plot markers.<br>
<br>
kwargs give the marker properties - see help(plot) for more<br>
information on marker properties<br>
<br>
The line handles are returned</tt></dd></dl>
<dl><dt><a name="Axes-spy2"><strong>spy2</strong></a>(self, Z)</dt><dd><tt>SPY2(Z) plots the sparsity pattern of the matrix S as an image<br>
<br>
The image instance is returned</tt></dd></dl>
<dl><dt><a name="Axes-stem"><strong>stem</strong></a>(self, x, y, linefmt<font color="#909090">='b-'</font>, markerfmt<font color="#909090">='bo'</font>, basefmt<font color="#909090">='r-'</font>)</dt><dd><tt>STEM(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')<br>
<br>
A stem plot plots vertical lines (using linefmt) at each x location<br>
from the baseline to y, and places a marker there using markerfmt. A<br>
horizontal line at 0 is is plotted using basefmt<br>
<br>
Return value is (markerline, stemlines, baseline) .<br>
<br>
See<br>
<a href="http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html">http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html</a><br>
for details and examples/stem_plot.py for a demo.</tt></dd></dl>
<dl><dt><a name="Axes-table"><strong>table</strong></a>(self, cellText<font color="#909090">=None</font>, cellColours<font color="#909090">=None</font>, cellLoc<font color="#909090">='right'</font>, colWidths<font color="#909090">=None</font>, rowLabels<font color="#909090">=None</font>, rowColours<font color="#909090">=None</font>, rowLoc<font color="#909090">='left'</font>, colLabels<font color="#909090">=None</font>, colColours<font color="#909090">=None</font>, colLoc<font color="#909090">='center'</font>, loc<font color="#909090">='bottom'</font>, bbox<font color="#909090">=None</font>)</dt><dd><tt>TABLE(cellText=None, cellColours=None,<br>
cellLoc='right', colWidths=None,<br>
rowLabels=None, rowColours=None, rowLoc='left',<br>
colLabels=None, colColours=None, colLoc='center',<br>
loc='bottom', bbox=None):<br>
<br>
Add a table to the current axes. Returns a table instance. For<br>
finer grained control over tables, use the Table class and add it<br>
to the axes with add_table.<br>
<br>
Thanks to John Gill for providing the class and table.</tt></dd></dl>
<dl><dt><a name="Axes-text"><strong>text</strong></a>(self, x, y, s, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>TEXT(x, y, s, fontdict=None, **kwargs)<br>
<br>
Add text in string s to axis at location x,y (data coords)<br>
<br>
fontdict is a dictionary to override the default text properties.<br>
If fontdict is None, the defaults are determined by your rc<br>
parameters.<br>
<br>
Individual keyword arguemnts can be used to override any given<br>
parameter<br>
<br>
<a href="#Axes-text">text</a>(x, y, s, fontsize=12)<br>
<br>
The default transform specifies that text is in data coords,<br>
alternatively, you can specify text in axis coords (0,0 lower left and<br>
1,1 upper right). The example below places text in the center of the<br>
axes<br>
<br>
<a href="#Axes-text">text</a>(0.5, 0.5,'matplotlib',<br>
horizontalalignment='center',<br>
verticalalignment='center',<br>
transform = ax.transAxes,<br>
)</tt></dd></dl>
<dl><dt><a name="Axes-toggle_log_lineary"><strong>toggle_log_lineary</strong></a>(self)</dt><dd><tt>toggle between log and linear on the y axis</tt></dd></dl>
<dl><dt><a name="Axes-update_datalim"><strong>update_datalim</strong></a>(self, xys)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="Axes-update_datalim_numerix"><strong>update_datalim_numerix</strong></a>(self, x, y)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="Axes-vlines"><strong>vlines</strong></a>(self, x, ymin, ymax, color<font color="#909090">='k'</font>)</dt><dd><tt>VLINES(x, ymin, ymax, color='k')<br>
<br>
Plot vertical lines at each x from ymin to ymax. ymin or ymax can be<br>
scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the heights of the lines are<br>
determined by ymin and ymax<br>
<br>
Returns a list of lines that were added</tt></dd></dl>
<dl><dt><a name="Axes-zoomx"><strong>zoomx</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<dl><dt><a name="Axes-zoomy"><strong>zoomy</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<hr>
Data and other attributes defined here:<br>
<dl><dt><strong>scaled</strong> = {0: 'linear', 1: 'log'}</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="Axes-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="Axes-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="Axes-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="Axes-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="Axes-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>return the figure instance</tt></dd></dl>
<dl><dt><a name="Axes-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>return the Transformation instance used by this artist</tt></dd></dl>
<dl><dt><a name="Axes-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="Axes-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-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="Axes-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="Axes-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="Axes-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="Axes-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a matplotlib.transform.Bbox instance</tt></dd></dl>
<dl><dt><a name="Axes-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="Axes-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="Axes-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="Axes-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>set the Transformation instance used by this artist<br>
<br>
ACCEPTS: a matplotlib.transform transformation instance</tt></dd></dl>
<dl><dt><a name="Axes-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="Axes-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="Axes-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="Axes-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>copy properties from other to self</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>
</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="PolarAxes">class <strong>PolarAxes</strong></a>(<a href="matplotlib.axes.html#Axes">Axes</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Make a <a href="#PolarAxes">PolarAxes</a>. The rectangular bounding box of the axes is given by<br>
<br>
<br>
<a href="#PolarAxes">PolarAxes</a>(position=[left, bottom, width, height])<br>
<br>
where all the arguments are fractions in [0,1] which specify the<br>
fraction of the total figure window.<br>
<br>
axisbg is the color of the axis background<br>
<br>
Attributes:<br>
thetagridlines : a list of Line2D for the theta grids<br>
rgridlines : a list of Line2D for the radial grids<br>
thetagridlabels : a list of Text for the theta grid labels<br>
rgridlabels : a list of Text for the theta grid labels<br> </tt></td></tr>
<tr><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="matplotlib.axes.html#PolarAxes">PolarAxes</a></dd>
<dd><a href="matplotlib.axes.html#Axes">Axes</a></dd>
<dd><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="PolarAxes-__init__"><strong>__init__</strong></a>(self, *args, **kwarg)</dt></dl>
<dl><dt><a name="PolarAxes-autoscale_view"><strong>autoscale_view</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-cla"><strong>cla</strong></a>(self)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-draw"><strong>draw</strong></a>(self, renderer)</dt></dl>
<dl><dt><a name="PolarAxes-format_coord"><strong>format_coord</strong></a>(self, theta, r)</dt><dd><tt>return a format string formatting the coordinate</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_rmax"><strong>get_rmax</strong></a>(self)</dt><dd><tt>get the maximum radius in the view limits dimension</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xscale"><strong>get_xscale</strong></a>(self)</dt><dd><tt>return the xaxis scale string</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_yscale"><strong>get_yscale</strong></a>(self)</dt><dd><tt>return the yaxis scale string</tt></dd></dl>
<dl><dt><a name="PolarAxes-grid"><strong>grid</strong></a>(self, b)</dt><dd><tt>Set the axes grids on or off; b is a boolean</tt></dd></dl>
<dl><dt><a name="PolarAxes-has_data"><strong>has_data</strong></a>(self)</dt><dd><tt>return true if any artists have been added to axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_rgrids"><strong>set_rgrids</strong></a>(self, radii, labels<font color="#909090">=None</font>, angle<font color="#909090">=22.5</font>, **kwargs)</dt><dd><tt>set the radial locations and labels of the r grids<br>
<br>
The labels will appear at radial distances radii at angle<br>
<br>
labels, if not None, is a len(radii) list of strings of the<br>
labels to use at each angle.<br>
<br>
if labels is None, the self.<strong>rformatter</strong> will be used<br>
<br>
Return value is a list of lines, labels where the lines are<br>
matplotlib.Line2D instances and the labels are matplotlib.Text<br>
instances<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_thetagrids"><strong>set_thetagrids</strong></a>(self, angles, labels<font color="#909090">=None</font>, fmt<font color="#909090">='%d'</font>, frac<font color="#909090">=1.1000000000000001</font>, **kwargs)</dt><dd><tt>set the angles at which to place the theta grids (these<br>
gridlines are equal along the theta dimension). angles is in<br>
degrees<br>
<br>
labels, if not None, is a len(angles) list of strings of the<br>
labels to use at each angle.<br>
<br>
if labels is None, the labels with be fmt%angle<br>
<br>
frac is the fraction of the polar axes radius at which to<br>
place the label (1 is the edge).Eg 1.05 isd outside the axes<br>
and 0.95 is inside the axes<br>
<br>
kwargs are optional text properties for the labels<br>
<br>
Return value is a list of lines, labels where the lines are<br>
matplotlib.Line2D instances and the labels are matplotlib.Text<br>
instances<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_xlabel"><strong>set_xlabel</strong></a>(self, xlabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>xlabel not implemented</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_xlim"><strong>set_xlim</strong></a>(self, v, emit<font color="#909090">=True</font>)</dt><dd><tt>SET_XLIM(v, emit=True)<br>
<br>
A do nothing impl until we can figure out how to handle interaction<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_ylabel"><strong>set_ylabel</strong></a>(self, ylabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>ylabel not implemented</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_ylim"><strong>set_ylim</strong></a>(self, v, emit<font color="#909090">=True</font>)</dt><dd><tt>SET_YLIM(v, emit=True)<br>
<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-toggle_log_lineary"><strong>toggle_log_lineary</strong></a>(self)</dt><dd><tt>toggle between log and linear axes ignored for polar</tt></dd></dl>
<hr>
Data and other attributes defined here:<br>
<dl><dt><strong>RESOLUTION</strong> = 200</dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><a name="PolarAxes-add_artist"><strong>add_artist</strong></a>(self, a)</dt><dd><tt>Add any artist to the axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-add_collection"><strong>add_collection</strong></a>(self, collection)</dt><dd><tt>add a Collection instance to <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarAxes-add_line"><strong>add_line</strong></a>(self, l)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="PolarAxes-add_patch"><strong>add_patch</strong></a>(self, p)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="PolarAxes-add_table"><strong>add_table</strong></a>(self, tab)</dt><dd><tt>Add a table instance to the list of axes tables</tt></dd></dl>
<dl><dt><a name="PolarAxes-axhline"><strong>axhline</strong></a>(self, y<font color="#909090">=0</font>, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHLINE(y=0, xmin=0, xmax=1, **kwargs)<br>
<br>
Axis Horizontal Line<br>
<br>
Draw a horizontal line at y from xmin to xmax. With the default<br>
values of xmin=0 and xmax=1, this line will always span the horizontal<br>
extent of the axes, regardless of the xlim settings, even if you<br>
change them, eg with the xlim command. That is, the horizontal extent<br>
is in axes coords: 0=left, 0.5=middle, 1.0=right but the y location is<br>
in data coordinates.<br>
<br>
Return value is the Line2D instance. kwargs are the same as kwargs to<br>
plot, and can be used to control the line properties. Eg<br>
<br>
# draw a thick red hline at y=0 that spans the xrange<br>
<a href="#PolarAxes-axhline">axhline</a>(linewidth=4, color='r')<br>
<br>
# draw a default hline at y=1 that spans the xrange<br>
<a href="#PolarAxes-axhline">axhline</a>(y=1)<br>
<br>
# draw a default hline at y=.5 that spans the the middle half of<br>
# the xrange<br>
<a href="#PolarAxes-axhline">axhline</a>(y=.5, xmin=0.25, xmax=0.75)</tt></dd></dl>
<dl><dt><a name="PolarAxes-axhspan"><strong>axhspan</strong></a>(self, ymin, ymax, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHSPAN(ymin, ymax, xmin=0, xmax=1, **kwargs)<br>
<br>
Axis Horizontal Span. ycoords are in data units and x<br>
coords are in axes (relative 0-1) units<br>
<br>
Draw a horizontal span (regtangle) from ymin to ymax. With the<br>
default values of xmin=0 and xmax=1, this always span the xrange,<br>
regardless of the xlim settings, even if you change them, eg with the<br>
xlim command. That is, the horizontal extent is in axes coords:<br>
0=left, 0.5=middle, 1.0=right but the y location is in data<br>
coordinates.<br>
<br>
kwargs are the kwargs to Patch, eg<br>
<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
<br>
the terms on the right are aliases<br>
<br>
Return value is the patches.Polygon instance.<br>
<br>
#draws a gray rectangle from y=0.25-0.75 that spans the horizontal<br>
#extent of the axes<br>
<a href="#PolarAxes-axhspan">axhspan</a>(0.25, 0.75, facecolor=0.5, alpha=0.5)</tt></dd></dl>
<dl><dt><a name="PolarAxes-axvline"><strong>axvline</strong></a>(self, x<font color="#909090">=0</font>, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVLINE(x=0, ymin=0, ymax=1, **kwargs)<br>
<br>
Axis Vertical Line<br>
<br>
Draw a vertical line at x from ymin to ymax. With the default values<br>
of ymin=0 and ymax=1, this line will always span the vertical extent<br>
of the axes, regardless of the xlim settings, even if you change them,<br>
eg with the xlim command. That is, the vertical extent is in axes<br>
coords: 0=bottom, 0.5=middle, 1.0=top but the x location is in data<br>
coordinates.<br>
<br>
Return value is the Line2D instance. kwargs are the same as<br>
kwargs to plot, and can be used to control the line properties. Eg<br>
<br>
# draw a thick red vline at x=0 that spans the yrange<br>
l = <a href="#PolarAxes-axvline">axvline</a>(linewidth=4, color='r')<br>
<br>
# draw a default vline at x=1 that spans the yrange<br>
l = <a href="#PolarAxes-axvline">axvline</a>(x=1)<br>
<br>
# draw a default vline at x=.5 that spans the the middle half of<br>
# the yrange<br>
<a href="#PolarAxes-axvline">axvline</a>(x=.5, ymin=0.25, ymax=0.75)</tt></dd></dl>
<dl><dt><a name="PolarAxes-axvspan"><strong>axvspan</strong></a>(self, xmin, xmax, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVSPAN(xmin, xmax, ymin=0, ymax=1, **kwargs)<br>
<br>
axvspan : Axis Vertical Span. xcoords are in data units and y coords<br>
are in axes (relative 0-1) units<br>
<br>
Draw a vertical span (regtangle) from xmin to xmax. With the default<br>
values of ymin=0 and ymax=1, this always span the yrange, regardless<br>
of the ylim settings, even if you change them, eg with the ylim<br>
command. That is, the vertical extent is in axes coords: 0=bottom,<br>
0.5=middle, 1.0=top but the y location is in data coordinates.<br>
<br>
kwargs are the kwargs to Patch, eg<br>
<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
<br>
the terms on the right are aliases<br>
<br>
return value is the patches.Polygon instance.<br>
<br>
# draw a vertical green translucent rectangle from x=1.25 to 1.55 that<br>
# spans the yrange of the axes<br>
<a href="#PolarAxes-axvspan">axvspan</a>(1.25, 1.55, facecolor='g', alpha=0.5)</tt></dd></dl>
<dl><dt><a name="PolarAxes-bar"><strong>bar</strong></a>(self, left, height, width<font color="#909090">=0.80000000000000004</font>, bottom<font color="#909090">=0</font>, color<font color="#909090">='b'</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">='k'</font>, capsize<font color="#909090">=3</font>)</dt><dd><tt>BAR(left, height, width=0.8, bottom=0,<br>
color='b', yerr=None, xerr=None, ecolor='k', capsize=3)<br>
<br>
Make a bar plot with rectangles at<br>
<br>
left, left+width, 0, height<br>
<br>
left and height are Numeric arrays.<br>
<br>
Return value is a list of Rectangle patch instances<br>
<br>
BAR(left, height, width, bottom,<br>
color, yerr, xerr, capsize, yoff)<br>
<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
<br>
color specifies the color of the bar<br>
<br>
ecolor specifies the color of any errorbar<br>
<br>
capsize determines the length in points of the error bar caps<br>
<br>
<br>
The optional arguments color, width and bottom can be either<br>
scalars or len(x) sequences<br>
<br>
This enables you to use bar as the basis for stacked bar<br>
charts, or candlestick plots</tt></dd></dl>
<dl><dt><a name="PolarAxes-barh"><strong>barh</strong></a>(self, x, y, height<font color="#909090">=0.80000000000000004</font>, left<font color="#909090">=0</font>, color<font color="#909090">='b'</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">='k'</font>, capsize<font color="#909090">=3</font>)</dt><dd><tt>BARH(x, y, height=0.8, left=0,<br>
color='b', yerr=None, xerr=None, ecolor='k', capsize=3)<br>
<br>
BARH(x, y)<br>
<br>
The y values give the heights of the center of the bars. The<br>
x values give the length of the bars.<br>
<br>
Return value is a list of Rectangle patch instances<br>
<br>
Optional arguments<br>
<br>
height - the height (thickness) of the bar<br>
<br>
left - the x coordinate of the left side of the bar<br>
<br>
color specifies the color of the bar<br>
<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
<br>
ecolor specifies the color of any errorbar<br>
<br>
capsize determines the length in points of the error bar caps<br>
<br>
The optional arguments color, height and left can be either<br>
scalars or len(x) sequences</tt></dd></dl>
<dl><dt><a name="PolarAxes-boxplot"><strong>boxplot</strong></a>(self, x, notch<font color="#909090">=0</font>, sym<font color="#909090">='b+'</font>, vert<font color="#909090">=1</font>, whis<font color="#909090">=1.5</font>)</dt><dd><tt><a href="#PolarAxes-boxplot">boxplot</a>(x, notch=0, sym='+', vert=1, whis=1.5)<br>
<br>
Make a box and whisker plot for each column of x.<br>
The box extends from the lower to upper quartile values<br>
of the data, with a line at the median. The whiskers<br>
extend from the box to show the range of the data. Flier<br>
points are those past the end of the whiskers.<br>
<br>
notch = 0 (default) produces a rectangular box plot. <br>
notch = 1 will produce a notched box plot<br>
<br>
sym (default 'b+') is the default symbol for flier points.<br>
Enter an empty string ('') if you don't want to show fliers.<br>
<br>
vert = 1 (default) makes the boxes vertical.<br>
vert = 0 makes horizontal boxes. This seems goofy, but<br>
that's how Matlab did it.<br>
<br>
whis (default 1.5) defines the length of the whiskers as<br>
a function of the inner quartile range. They extend to the<br>
most extreme data point within ( whis*(75%-25%) ) data range.<br>
<br>
x is a Numeric array<br>
<br>
Returns a list of the lines added</tt></dd></dl>
<dl><dt><a name="PolarAxes-clabel"><strong>clabel</strong></a>(self, *args, **kwargs)</dt><dd><tt>CLABEL(*args, **kwargs)<br>
<br>
Function signatures<br>
<br>
CLABEL(C) - plots contour labels,<br>
C is the output of contour or a list of contours<br>
<br>
CLABEL(C,V) - creates labels only for those contours, given in<br>
a list V<br>
<br>
CLABEL(C, **kwargs) - keyword args are explained below:<br>
<br>
<br>
<br>
* fontsize = None: as described in <a href="http://matplotlib.sf.net/fonts.html">http://matplotlib.sf.net/fonts.html</a><br>
<br>
* colors = None:<br>
<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different labels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all labels<br>
will be plotted in this color<br>
<br>
- if colors == None, the color of each label matches the color<br>
of the corresponding contour<br>
<br>
* inline = 0: controls whether the underlying contour is removed<br>
(inline = 1) or not<br>
<br>
* fmt = '%1.3f': a format string for the label</tt></dd></dl>
<dl><dt><a name="PolarAxes-clear"><strong>clear</strong></a>(self)</dt><dd><tt>clear the axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-cohere"><strong>cohere</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>COHERE(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
cohere the coherence between x and y. Coherence is the normalized<br>
cross spectral density<br>
<br>
Cxy = |Pxy|^2/(Pxx*Pyy)<br>
<br>
The return value is (Cxy, f), where f are the frequencies of the<br>
coherence vector.<br>
<br>
See the PSD help for a description of the optional parameters.<br>
<br>
Returns the tuple Cxy, freqs<br>
<br>
Refs: Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="PolarAxes-connect"><strong>connect</strong></a>(self, s, func)</dt><dd><tt>Register observers to be notified when certain events occur. Register<br>
with callback functions with the following signatures. The function<br>
has the following signature<br>
<br>
func(ax) # where ax is the instance making the callback.<br>
<br>
The following events can be connected to:<br>
<br>
'xlim_changed','ylim_changed'<br>
<br>
The connection id is is returned - you can use this with<br>
disconnect to disconnect from the axes event</tt></dd></dl>
<dl><dt><a name="PolarAxes-contour"><strong>contour</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#PolarAxes-contour">contour</a>(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#PolarAxes-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z,N) and <a href="#PolarAxes-contour">contour</a>(X,Y,Z,N) - draw N contour lines overriding<br>
the automatic value<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z,V) and <a href="#PolarAxes-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in V (array, list, tuple)<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
[L,C] = <a href="#PolarAxes-contour">contour</a>(...) returns a list of levels and a silent_list of LineCollections<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None: one of these:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the default colormap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified.<br>
<br>
* badmask = None: array with dimensions of Z, and with values<br>
of zero at locations corresponding to valid data, and one<br>
at locations where the value of Z should be ignored.<br>
This is experimental. It presently works for edge regions<br>
for line and filled contours, but for interior regions it<br>
works correctly only for line contours. The badmask kwarg<br>
may go away in the future, to be replaced by the use of<br>
NaN value in Z and/or the use of a masked array in Z.<br>
<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
.matplotlibrc is used<br>
<br>
* fmt = '1.3f': a format string for adding a label to each collection.<br>
Useful for auto-legending.</tt></dd></dl>
<dl><dt><a name="PolarAxes-contourf"><strong>contourf</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#PolarAxes-contourf">contourf</a>(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#PolarAxes-contourf">contourf</a>(Z) - make a filled contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#PolarAxes-contourf">contourf</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#PolarAxes-contourf">contourf</a>(Z,N) and <a href="#PolarAxes-contourf">contourf</a>(X,Y,Z,N) - make a filled contour plot<br>
corresponding to N contour levels<br>
<br>
<a href="#PolarAxes-contourf">contourf</a>(Z,V) and <a href="#PolarAxes-contourf">contourf</a>(X,Y,Z,V) - fill len(V) regions,<br>
between the levels specified in sequence V, and a final region<br>
for values of Z greater than the last element in V<br>
<br>
<a href="#PolarAxes-contourf">contourf</a>(Z, **kwargs) - Use keyword args to control colors,<br>
origin, cmap ... see below<br>
<br>
[L,C] = <a href="#PolarAxes-contourf">contourf</a>(...) returns a list of levels and a silent_list<br>
of PolyCollections<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None: one of these:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the default colormap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* badmask = None: array with dimensions of Z, and with values<br>
of zero at locations corresponding to valid data, and one<br>
at locations where the value of Z should be ignored.<br>
This is experimental. It presently works for edge regions<br>
for line and filled contours, but for interior regions it<br>
works correctly only for line contours. The badmask kwarg<br>
may go away in the future, to be replaced by the use of<br>
NaN value in Z and/or the use of a masked array in Z.<br>
<br>
reg is a 1D region number array with of imax*(jmax+1)+1 size<br>
The values of reg should be positive region numbers, and zero fro<br>
zones wich do not exist.<br>
<br>
triangle - triangulation array - must be the same shape as reg<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges (because the contouring engine yields<br>
simply connected regions with branch cuts.) To draw the edges,<br>
add line contours with calls to contour.</tt></dd></dl>
<dl><dt><a name="PolarAxes-csd"><strong>csd</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>CSD(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
The cross spectral density Pxy by Welches average periodogram method.<br>
The vectors x and y are divided into NFFT length segments. Each<br>
segment is detrended by function detrend and windowed by function<br>
window. The product of the direct FFTs of x and y are averaged over<br>
each segment to compute Pxy, with a scaling to correct for power loss<br>
due to windowing.<br>
<br>
See the PSD help for a description of the optional parameters.<br>
<br>
Returns the tuple Pxy, freqs. Pxy is the cross spectrum (complex<br>
valued), and 10*log10(|Pxy|) is plotted<br>
<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="PolarAxes-disconnect"><strong>disconnect</strong></a>(self, cid)</dt><dd><tt>disconnect from the <a href="#Axes">Axes</a> event.</tt></dd></dl>
<dl><dt><a name="PolarAxes-errorbar"><strong>errorbar</strong></a>(self, x, y, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, fmt<font color="#909090">='b-'</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, barsabove<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>ERRORBAR(x, y, yerr=None, xerr=None,<br>
fmt='b-', ecolor=None, capsize=3, barsabove=False)<br>
<br>
Plot x versus y with error deltas in yerr and xerr.<br>
Vertical errorbars are plotted if yerr is not None<br>
Horizontal errorbars are plotted if xerr is not None<br>
<br>
xerr and yerr may be any of:<br>
<br>
a rank-0, Nx1 Numpy array - symmetric errorbars +/- value<br>
<br>
an N-element list or tuple - symmetric errorbars +/- value<br>
<br>
a rank-1, Nx2 Numpy array - asymmetric errorbars -column1/+column2<br>
<br>
Alternatively, x, y, xerr, and yerr can all be scalars, which<br>
plots a single error bar at x, y.<br>
<br>
fmt is the plot format symbol for y. if fmt is None, just<br>
plot the errorbars with no line symbols. This can be useful<br>
for creating a bar plot with errorbars<br>
<br>
ecolor is a matplotlib color arg which gives the color the<br>
errorbar lines; if None, use the marker color.<br>
<br>
capsize is the size of the error bar caps in points<br>
<br>
barsabove, if True, will plot the errorbars above the plot symbols<br>
- default is below<br>
<br>
kwargs are passed on to the plot command for the markers<br>
<br>
Return value is a length 2 tuple. The first element is a list of<br>
y symbol lines. The second element is a list of error bar lines.</tt></dd></dl>
<dl><dt><a name="PolarAxes-fill"><strong>fill</strong></a>(self, *args, **kwargs)</dt><dd><tt>FILL(*args, **kwargs)<br>
<br>
plot filled polygons. *args is a variable length argument, allowing<br>
for multiple x,y pairs with an optional color format string; see plot<br>
for details on the argument parsing. For example, all of the<br>
following are legal, assuming a is the Axis instance:<br>
<br>
ax.<a href="#PolarAxes-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
ax.<a href="#PolarAxes-fill">fill</a>(x,y, 'b' ) # plot polygon with vertices at x,y in blue<br>
<br>
An arbitrary number of x, y, color groups can be specified, as in<br>
ax.<a href="#PolarAxes-fill">fill</a>(x1, y1, 'g', x2, y2, 'r')<br>
<br>
Return value is a list of patches that were added<br>
<br>
The same color strings that plot supports are supported by the fill<br>
format string.<br>
<br>
The kwargs that are can be used to set line properties (any<br>
property that has a set_* method). You can use this to set edge<br>
color, face color, etc.</tt></dd></dl>
<dl><dt><a name="PolarAxes-format_xdata"><strong>format_xdata</strong></a>(self, x)</dt><dd><tt>Return x string formatted. This function will use the attribute<br>
self.<strong>fmt_xdata</strong> if it is callable, else will fall back on the xaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="PolarAxes-format_ydata"><strong>format_ydata</strong></a>(self, y)</dt><dd><tt>Return y string formatted. This function will use the attribute<br>
self.<strong>fmt_ydata</strong> if it is callable, else will fall back on the yaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_axis_bgcolor"><strong>get_axis_bgcolor</strong></a>(self)</dt><dd><tt>Return the axis background color</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_child_artists"><strong>get_child_artists</strong></a>(self)</dt><dd><tt>Return a list of artists the axes contains. Deprecated</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_cursor_props"><strong>get_cursor_props</strong></a>(self)</dt><dd><tt>return the cursor props as a linewidth, color tuple where<br>
linewidth is a float and color is an RGBA tuple</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_frame"><strong>get_frame</strong></a>(self)</dt><dd><tt>Return the axes Rectangle frame</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_images"><strong>get_images</strong></a>(self)</dt><dd><tt>return a list of <a href="#Axes">Axes</a> images contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarAxes-get_legend"><strong>get_legend</strong></a>(self)</dt><dd><tt>Return the Legend instance, or None if no legend is defined</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_lines"><strong>get_lines</strong></a>(self)</dt><dd><tt>Return a list of lines contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarAxes-get_position"><strong>get_position</strong></a>(self)</dt><dd><tt>Return the axes rectangle left, bottom, width, height</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xaxis"><strong>get_xaxis</strong></a>(self)</dt><dd><tt>Return the XAxis instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xgridlines"><strong>get_xgridlines</strong></a>(self)</dt><dd><tt>Get the x grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xlim"><strong>get_xlim</strong></a>(self)</dt><dd><tt>Get the x axis range [xmin, xmax]</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xticklabels"><strong>get_xticklabels</strong></a>(self)</dt><dd><tt>Get the xtick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xticklines"><strong>get_xticklines</strong></a>(self)</dt><dd><tt>Get the xtick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xticks"><strong>get_xticks</strong></a>(self)</dt><dd><tt>Return the x ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_yaxis"><strong>get_yaxis</strong></a>(self)</dt><dd><tt>Return the YAxis instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_ygridlines"><strong>get_ygridlines</strong></a>(self)</dt><dd><tt>Get the y grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_ylim"><strong>get_ylim</strong></a>(self)</dt><dd><tt>Get the y axis range [ymin, ymax]</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_yticklabels"><strong>get_yticklabels</strong></a>(self)</dt><dd><tt>Get the ytick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_yticklines"><strong>get_yticklines</strong></a>(self)</dt><dd><tt>Get the ytick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_yticks"><strong>get_yticks</strong></a>(self)</dt><dd><tt>Return the y ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="PolarAxes-hist"><strong>hist</strong></a>(self, x, bins<font color="#909090">=10</font>, normed<font color="#909090">=0</font>, bottom<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>HIST(x, bins=10, normed=0, bottom=0)<br>
<br>
Compute the histogram of x. bins is either an integer number of<br>
bins or a sequence giving the bins. x are the data to be binned.<br>
<br>
The return values is (n, bins, patches)<br>
<br>
If normed is true, the first element of the return tuple will be the<br>
counts normalized to form a probability distribtion, ie,<br>
n/(len(x)*dbin)<br>
<br>
kwargs are used to update the properties of the hist bars</tt></dd></dl>
<dl><dt><a name="PolarAxes-hlines"><strong>hlines</strong></a>(self, y, xmin, xmax, fmt<font color="#909090">='k-'</font>)</dt><dd><tt>HLINES(y, xmin, xmax, fmt='k-')<br>
<br>
plot horizontal lines at each y from xmin to xmax. xmin or xmax can<br>
be scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the widths of the lines are<br>
determined by xmin and xmax<br>
<br>
Returns a list of line instances that were added</tt></dd></dl>
<dl><dt><a name="PolarAxes-hold"><strong>hold</strong></a>(self, b<font color="#909090">=None</font>)</dt><dd><tt>HOLD(b=None)<br>
<br>
Set the hold state. If hold is None (default), toggle the<br>
hold state. Else set the hold state to boolean value b.<br>
<br>
Eg<br>
<a href="#PolarAxes-hold">hold</a>() # toggle hold<br>
<a href="#PolarAxes-hold">hold</a>(True) # hold is on<br>
<a href="#PolarAxes-hold">hold</a>(False) # hold is off</tt></dd></dl>
<dl><dt><a name="PolarAxes-imshow"><strong>imshow</strong></a>(self, X, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, aspect<font color="#909090">=None</font>, interpolation<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, origin<font color="#909090">=None</font>, extent<font color="#909090">=None</font>)</dt><dd><tt>IMSHOW(X, cmap=None, norm=None, aspect=None, interpolation=None,<br>
alpha=1.0, vmin=None, vmax=None, origin=None, extent=None)<br>
<br>
IMSHOW(X) - plot image X to current axes, resampling to scale to axes<br>
size (X may be numarray/Numeric array or PIL image)<br>
<br>
IMSHOW(X, **kwargs) - Use keyword args to control image scaling,<br>
colormapping etc. See below for details<br>
<br>
<br>
Display the image in X to current axes. X may be a float array or a<br>
PIL image. If X is a float array, X can have the following shapes<br>
<br>
MxN : luminance (grayscale)<br>
<br>
MxNx3 : RGB<br>
<br>
MxNx4 : RGBA<br>
<br>
A matplotlib.image.AxesImage instance is returned<br>
<br>
The following kwargs are allowed:<br>
<br>
* cmap is a cm colormap instance, eg cm.jet. If None, default to rc<br>
image.cmap value (Ignored when X has RGB(A) information)<br>
<br>
* aspect is one of: free or preserve. if None, default to rc<br>
image.aspect value<br>
<br>
* interpolation is one of: bicubic bilinear blackman100 blackman256<br>
blackman64 nearest sinc144 sinc256 sinc64 spline16 or spline36.<br>
If None, default to rc image.interpolation<br>
<br>
* norm is a matplotlib.colors.normalize instance; default is<br>
normalization(). This scales luminance -> 0-1 (Ignored when X is<br>
PIL image).<br>
<br>
* vmin and vmax are used to scale a luminance image to 0-1. If<br>
either is None, the min and max of the luminance values will be<br>
used. Note if you pass a norm instance, the settings for vmin and<br>
vmax will be ignored.<br>
<br>
* alpha = 1.0 : the alpha blending value<br>
<br>
* origin is either upper or lower, which indicates where the [0,0]<br>
index of the array is in the upper left or lower left corner of<br>
the axes. If None, default to rc image.origin<br>
<br>
* extent is a data xmin, xmax, ymin, ymax for making image plots<br>
registered with data plots. Default is the image dimensions<br>
in pixels</tt></dd></dl>
<dl><dt><a name="PolarAxes-in_axes"><strong>in_axes</strong></a>(self, xwin, ywin)</dt><dd><tt>return True is the point xwin, ywin (display coords) are in the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarAxes-ishold"><strong>ishold</strong></a>(self)</dt><dd><tt>return the HOLD status of the axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-legend"><strong>legend</strong></a>(self, *args, **kwargs)</dt><dd><tt>LEGEND(*args, **kwargs)<br>
<br>
Place a legend on the current axes at location loc. Labels are a<br>
sequence of strings and loc can be a string or an integer specifying<br>
the legend location<br>
<br>
USAGE:<br>
<br>
Make a legend with existing lines<br>
<br>
>>> <a href="#PolarAxes-legend">legend</a>()<br>
<br>
legend by itself will try and build a legend using the label<br>
property of the lines/patches/collections. You can set the label of<br>
a line by doing <a href="#PolarAxes-plot">plot</a>(x, y, label='my data') or line.<a href="#PolarAxes-set_label">set_label</a>('my<br>
data')<br>
<br>
# automatically generate the legend from labels<br>
<a href="#PolarAxes-legend">legend</a>( ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend for a list of lines and labels<br>
<a href="#PolarAxes-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend at a given location, using a location argument<br>
# <a href="#PolarAxes-legend">legend</a>( LABELS, LOC ) or<br>
# <a href="#PolarAxes-legend">legend</a>( LINES, LABELS, LOC )<br>
<a href="#PolarAxes-legend">legend</a>( ('label1', 'label2', 'label3'), loc='upper left')<br>
<a href="#PolarAxes-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3'), loc=2)<br>
<br>
The location codes are<br>
<br>
'best' : 0, <br>
'upper right' : 1, (default)<br>
'upper left' : 2,<br>
'lower left' : 3,<br>
'lower right' : 4,<br>
'right' : 5,<br>
'center left' : 6,<br>
'center right' : 7,<br>
'lower center' : 8,<br>
'upper center' : 9,<br>
'center' : 10,<br>
<br>
If none of these are suitable, loc can be a 2-tuple giving x,y<br>
in axes coords, ie,<br>
<br>
loc = 0, 1 is left top<br>
loc = 0.5, 0.5 is center, center<br>
<br>
and so on. The following kwargs are supported<br>
<br>
numpoints = 4 # the number of points in the legend line<br>
prop = FontProperties('smaller') # the font properties<br>
pad = 0.2 # the fractional whitespace inside the legend border<br>
<br>
# The kwarg dimensions are in axes coords<br>
labelsep = 0.005 # the vertical space between the legend entries<br>
handlelen = 0.05 # the length of the legend lines<br>
handletextsep = 0.02 # the space between the legend line and legend text<br>
axespad = 0.02 # the border between the axes and legend edge<br>
shadow = False # if True, draw a shadow behind legend</tt></dd></dl>
<dl><dt><a name="PolarAxes-loglog"><strong>loglog</strong></a>(self, *args, **kwargs)</dt><dd><tt>LOGLOG(*args, **kwargs)<br>
<br>
Make a loglog plot with log scaling on the a and y axis. The args<br>
to semilog x are the same as the args to plot. See help plot for<br>
more info.<br>
<br>
Optional keyword args supported are any of the kwargs<br>
supported by plot or set_xscale or set_yscale. Notable, for<br>
log scaling:<br>
<br>
* basex: base of the x logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot<br>
<br>
* basey: base of the y logarithm<br>
<br>
* subsy: the location of the minor yticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="PolarAxes-panx"><strong>panx</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan right, minus pan left)</tt></dd></dl>
<dl><dt><a name="PolarAxes-pany"><strong>pany</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan up, minus pan down)</tt></dd></dl>
<dl><dt><a name="PolarAxes-pcolor"><strong>pcolor</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLOR(*args, **kwargs)<br>
<br>
Function signatures<br>
<br>
PCOLOR(C) - make a pseudocolor plot of matrix C<br>
<br>
PCOLOR(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
<br>
PCOLOR(C, **kwargs) - Use keywork args to control colormapping and<br>
scaling; see below<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
<br>
* norm = normalize() : matplotlib.colors.normalize is used to scale<br>
luminance data to 0,1.<br>
<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. If you pass a norm<br>
instance, vmin and vmax will be None<br>
<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edge colors are same as<br>
face colors<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
<br>
Grid Orientation<br>
<br>
The behavior of meshgrid in matlab(TM) is a bit counterintuitive for<br>
x and y arrays. For example,<br>
<br>
x = <a href="#-arange">arange</a>(7)<br>
y = <a href="#-arange">arange</a>(5)<br>
X, Y = meshgrid(x,y)<br>
<br>
Z = rand( len(x), len(y))<br>
<a href="#PolarAxes-pcolor">pcolor</a>(X, Y, Z)<br>
<br>
will fail in matlab and pylab. You will probably be<br>
happy with<br>
<br>
<a href="#PolarAxes-pcolor">pcolor</a>(X, Y, transpose(Z))<br>
<br>
Likewise, for nonsquare Z,<br>
<br>
<a href="#PolarAxes-pcolor">pcolor</a>(transpose(Z))<br>
<br>
will make the x and y axes in the plot agree with the numrows and<br>
numcols of Z</tt></dd></dl>
<dl><dt><a name="PolarAxes-pcolor_classic"><strong>pcolor_classic</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLOR_CLASSIC(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#PolarAxes-pcolor">pcolor</a>(C) - make a pseudocolor plot of matrix C<br>
<br>
<a href="#PolarAxes-pcolor">pcolor</a>(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
<br>
<a href="#PolarAxes-pcolor">pcolor</a>(C, cmap=cm.jet) - make a pseudocolor plot of matrix C using<br>
rectangle patches using a colormap jet. Colormaps are avalible<br>
in matplotlib.cm. You must pass this as a kwarg.<br>
<br>
<a href="#PolarAxes-pcolor">pcolor</a>(C, norm=normalize()) - the normalization function used<br>
` to scale your color data to 0-1. must be passed as a kwarg.<br>
<br>
<a href="#PolarAxes-pcolor">pcolor</a>(C, alpha=0.5) - set the alpha of the pseudocolor plot.<br>
Must be used as a kwarg<br>
<br>
Shading:<br>
<br>
The optional keyword arg shading ('flat' or 'faceted') will<br>
determine whether a black grid is drawn around each pcolor square.<br>
Default 'faceteted' e.g., <a href="#PolarAxes-pcolor">pcolor</a>(C, shading='flat') <a href="#PolarAxes-pcolor">pcolor</a>(X, Y,<br>
C, shading='faceted')<br>
<br>
Return value is a list of patch objects.<br>
<br>
Grid orientation<br>
<br>
The behavior of meshgrid in matlab(TM) is a bit counterintuitive for x<br>
and y arrays. For example,<br>
<br>
x = <a href="#-arange">arange</a>(7)<br>
y = <a href="#-arange">arange</a>(5)<br>
X, Y = meshgrid(x,y)<br>
<br>
Z = rand( len(x), len(y))<br>
<a href="#PolarAxes-pcolor">pcolor</a>(X, Y, Z)<br>
<br>
will fail in matlab and matplotlib. You will probably be<br>
happy with<br>
<br>
<a href="#PolarAxes-pcolor">pcolor</a>(X, Y, transpose(Z))<br>
<br>
Likewise, for nonsquare Z,<br>
<br>
<a href="#PolarAxes-pcolor">pcolor</a>(transpose(Z))<br>
<br>
will make the x and y axes in the plot agree with the numrows<br>
and numcols of Z</tt></dd></dl>
<dl><dt><a name="PolarAxes-pick"><strong>pick</strong></a>(self, x, y, trans<font color="#909090">=None</font>)</dt><dd><tt>Return the artist under point that is closest to the x, y. if trans<br>
is None, x, and y are in window coords, 0,0 = lower left. Otherwise,<br>
trans is a matplotlib transform that specifies the coordinate system<br>
of x, y.<br>
<br>
Note this algorithm calculates distance to the vertices of the<br>
polygon, so if you want to pick a patch, click on the edge!</tt></dd></dl>
<dl><dt><a name="PolarAxes-pie"><strong>pie</strong></a>(self, x, explode<font color="#909090">=None</font>, labels<font color="#909090">=None</font>, colors<font color="#909090">=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w')</font>, autopct<font color="#909090">=None</font>, shadow<font color="#909090">=False</font>)</dt><dd><tt>Make a pie chart of array x. The fractional area of each wedge is<br>
given by x/sum(x). If sum(x)<=1, then the values of x give the<br>
fractional area directly and the array will not be normalized.<br>
<br>
- explode, if not None, is a len(x) array which specifies the<br>
fraction of the radius to offset that wedge.<br>
<br>
- colors is a sequence of matplotlib color args that the pie chart<br>
will cycle.<br>
<br>
- labels, if not None, is a len(x) list of labels.<br>
<br>
- autopct, if not None, is a string or function used to label the<br>
wedges with their numeric value. The label will be placed inside<br>
the wedge. If it is a format string, the label will be fmt%pct.<br>
If it is a function, it will be called<br>
<br>
- shadow, if True, will draw a shadow beneath the pie.<br>
<br>
The pie chart will probably look best if the figure and axes are<br>
square. Eg,<br>
<br>
figure(figsize=(8,8))<br>
ax = axes([0.1, 0.1, 0.8, 0.8])<br>
<br>
Return value:<br>
<br>
If autopct is None, return a list of (patches, texts), where patches<br>
is a sequence of matplotlib.patches.Wedge instances and texts is a<br>
list of the label Text instnaces<br>
<br>
If autopct is not None, return (patches, texts, autotexts), where<br>
patches and texts are as above, and autotexts is a list of text<br>
instances for the numeric labels</tt></dd></dl>
<dl><dt><a name="PolarAxes-plot"><strong>plot</strong></a>(self, *args, **kwargs)</dt><dd><tt>PLOT(*args, **kwargs)<br>
<br>
Plot lines and/or markers to the <a href="#Axes">Axes</a>. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional format<br>
string. For example, each of the following is legal<br>
<br>
<a href="#PolarAxes-plot">plot</a>(x,y) # plot x and y using the default line style and color<br>
<a href="#PolarAxes-plot">plot</a>(x,y, 'bo') # plot x and y using blue circle markers<br>
<a href="#PolarAxes-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
<a href="#PolarAxes-plot">plot</a>(y, 'r+') # ditto, but with red plusses<br>
<br>
An arbitrary number of x, y, fmt groups can be specified, as in<br>
<br>
a.<a href="#PolarAxes-plot">plot</a>(x1, y1, 'g^', x2, y2, 'g-')<br>
<br>
Return value is a list of lines that were added.<br>
<br>
The following line styles are supported:<br>
<br>
- : solid line<br>
-- : dashed line<br>
-. : dash-dot line<br>
: : dotted line<br>
. : points<br>
, : pixels<br>
o : circle symbols<br>
^ : triangle up symbols<br>
v : triangle down symbols<br>
< : triangle left symbols<br>
> : triangle right symbols<br>
s : square symbols<br>
+ : plus symbols<br>
x : cross symbols<br>
D : diamond symbols<br>
d : thin diamond symbols<br>
1 : tripod down symbols<br>
2 : tripod up symbols<br>
3 : tripod left symbols<br>
4 : tripod right symbols<br>
h : hexagon symbols<br>
H : rotated hexagon symbols<br>
p : pentagon symbols<br>
| : vertical line symbols<br>
_ : horizontal line symbols<br>
steps : use gnuplot style 'steps' # kwarg only<br>
<br>
The following color strings are supported<br>
<br>
b : blue<br>
g : green<br>
r : red<br>
c : cyan<br>
m : magenta<br>
y : yellow<br>
k : black<br>
w : white<br>
<br>
Line styles and colors are combined in a single format string, as in<br>
'bo' for blue circles.<br>
<br>
The **kwargs can be used to set line properties (any property that has<br>
a set_* method). You can use this to set a line label (for auto<br>
legends), linewidth, anitialising, marker face color, etc. Here is an<br>
example:<br>
<br>
<a href="#PolarAxes-plot">plot</a>([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)<br>
<a href="#PolarAxes-plot">plot</a>([1,2,3], [1,4,9], 'rs', label='line 2')<br>
axis([0, 4, 0, 10])<br>
<a href="#PolarAxes-legend">legend</a>()<br>
<br>
If you make multiple lines with one plot command, the kwargs apply<br>
to all those lines, eg<br>
<br>
<a href="#PolarAxes-plot">plot</a>(x1, y1, x2, y2, antialising=False)<br>
<br>
Neither line will be antialiased.</tt></dd></dl>
<dl><dt><a name="PolarAxes-plot_date"><strong>plot_date</strong></a>(self, d, y, fmt<font color="#909090">='bo'</font>, tz<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>PLOT_DATE(d, y, converter, fmt='bo', tz=None, **kwargs)<br>
<br>
d is a sequence of dates represented as float days since<br>
0001-01-01 UTC and y are the y values at those dates. fmt is<br>
a plot format string. kwargs are passed on to plot. See plot<br>
for more information.<br>
<br>
See matplotlib.dates for helper functions date2num, num2date<br>
and drange for help on creating the required floating point dates<br>
<br>
tz is the timezone - defaults to rc value</tt></dd></dl>
<dl><dt><a name="PolarAxes-psd"><strong>psd</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>PSD(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
The power spectral density by Welches average periodogram method. The<br>
vector x is divided into NFFT length segments. Each segment is<br>
detrended by function detrend and windowed by function window.<br>
noperlap gives the length of the overlap between segments. The<br>
absolute(fft(segment))**2 of each segment are averaged to compute Pxx,<br>
with a scaling to correct for power loss due to windowing. Fs is the<br>
sampling frequency.<br>
<br>
NFFT is the length of the fft segment; must be a power of 2<br>
<br>
Fs is the sampling frequency.<br>
<br>
detrend - the function applied to each segment before fft-ing,<br>
designed to remove the mean or linear trend. Unlike in matlab,<br>
where the detrend parameter is a vector, in matplotlib is it a<br>
function. The mlab module defines detrend_none, detrend_mean,<br>
detrend_linear, but you can use a custom function as well.<br>
<br>
window - the function used to window the segments. window is a<br>
function, unlike in matlab(TM) where it is a vector. mlab defines<br>
window_none, window_hanning, but you can use a custom function<br>
as well.<br>
<br>
noverlap gives the length of the overlap between segments.<br>
<br>
Returns the tuple Pxx, freqs<br>
<br>
For plotting, the power is plotted as 10*log10(pxx)) for decibels,<br>
though pxx itself is returned<br>
<br>
Refs:<br>
<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="PolarAxes-quiver"><strong>quiver</strong></a>(self, U, V, *args, **kwargs)</dt><dd><tt>QUIVER( X, Y, U, V )<br>
QUIVER( U, V )<br>
QUIVER( X, Y, U, V, S)<br>
QUIVER( U, V, S )<br>
QUIVER( ..., color=None, width=1.0, cmap=None,norm=None )<br>
<br>
Make a vector plot (U, V) with arrows on a grid (X, Y)<br>
<br>
The optional arguments color and width are used to specify the color and width<br>
of the arrow. color can be an array of colors in which case the arrows can be<br>
colored according to another dataset.<br>
<br>
If cm is specied and color is None, the colormap is used to give a color<br>
according to the vector's length.<br>
<br>
If color is a scalar field, the colormap is used to map the scalar to a color<br>
If a colormap is specified and color is an array of color triplets, then the<br>
colormap is ignored<br>
<br>
width is a scalar that controls the width of the arrows<br>
<br>
if S is specified it is used to scale the vectors. Use S=0 to disable automatic<br>
scaling.<br>
If S!=0, vectors are scaled to fit within the grid and then are multiplied by S.</tt></dd></dl>
<dl><dt><a name="PolarAxes-scatter"><strong>scatter</strong></a>(self, x, y, s<font color="#909090">=20</font>, c<font color="#909090">='b'</font>, marker<font color="#909090">='o'</font>, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, **kwargs)</dt><dd><tt>SCATTER(x, y, s=20, c='b', marker='o', cmap=None, norm=None,<br>
vmin=None, vmax=None, alpha=1.0)<br>
<br>
Supported function signatures:<br>
<br>
SCATTER(x, y) - make a scatter plot of x vs y<br>
<br>
SCATTER(x, y, s) - make a scatter plot of x vs y with size in area<br>
given by s<br>
<br>
SCATTER(x, y, s, c) - make a scatter plot of x vs y with size in area<br>
given by s and colors given by c<br>
<br>
SCATTER(x, y, s, c, **kwargs) - control colormapping and scaling<br>
with keyword args; see below<br>
<br>
Make a scatter plot of x versus y. s is a size in points^2 a scalar<br>
or an array of the same length as x or y. c is a color and can be a<br>
single color format string or an length(x) array of intensities which<br>
will be mapped by the matplotlib.colors.colormap instance cmap<br>
<br>
The marker can be one of<br>
<br>
's' : square<br>
'o' : circle<br>
'^' : triangle up<br>
'>' : triangle right<br>
'v' : triangle down<br>
'<' : triangle left<br>
'd' : diamond<br>
'p' : pentagram<br>
'h' : hexagon<br>
'8' : octagon<br>
<br>
s is a size argument in points squared.<br>
<br>
Other keyword args; the color mapping and normalization arguments will<br>
on be used if c is an array of floats<br>
<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to rc image.cmap<br>
<br>
* norm = normalize() : matplotlib.colors.normalize is used to<br>
scale luminance data to 0,1.<br>
<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. Note if you pass a norm<br>
instance, your settings for vmin and vmax will be ignored<br>
<br>
* alpha =1.0 : the alpha value for the patches</tt></dd></dl>
<dl><dt><a name="PolarAxes-scatter_classic"><strong>scatter_classic</strong></a>(self, x, y, s<font color="#909090">=None</font>, c<font color="#909090">='b'</font>)</dt><dd><tt>SCATTER_CLASSIC(x, y, s=None, c='b')<br>
<br>
Make a scatter plot of x versus y. s is a size (in data coords) and<br>
can be either a scalar or an array of the same length as x or y. c is<br>
a color and can be a single color format string or an length(x) array<br>
of intensities which will be mapped by the colormap jet.<br>
<br>
If size is None a default size will be used</tt></dd></dl>
<dl><dt><a name="PolarAxes-semilogx"><strong>semilogx</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGX(*args, **kwargs)<br>
<br>
Make a semilog plot with log scaling on the x axis. The args to<br>
semilog x are the same as the args to plot. See help plot for more<br>
info.<br>
<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_xscale. Notable, for log scaling:<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="PolarAxes-semilogy"><strong>semilogy</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGY(*args, **kwargs):<br>
<br>
Make a semilog plot with log scaling on the y axis. The args to<br>
semilogy are the same as the args to plot. See help plot for more<br>
info.<br>
<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_yscale. Notable, for log scaling:<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_axis_bgcolor"><strong>set_axis_bgcolor</strong></a>(self, color)</dt><dd><tt>set the axes background color<br>
<br>
ACCEPTS: any matplotlib color - see help(colors)</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_axis_off"><strong>set_axis_off</strong></a>(self)</dt><dd><tt>turn off the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_axis_on"><strong>set_axis_on</strong></a>(self)</dt><dd><tt>turn on the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_cursor_props"><strong>set_cursor_props</strong></a>(self, *args)</dt><dd><tt>Set the cursor property as<br>
ax.<a href="#PolarAxes-set_cursor_props">set_cursor_props</a>(linewidth, color) OR<br>
ax.<a href="#PolarAxes-set_cursor_props">set_cursor_props</a>((linewidth, color))<br>
<br>
ACCEPTS: a (float, color) tuple</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the <a href="#Axes">Axes</a> figure<br>
<br>
ACCEPTS: a Figure instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_frame_on"><strong>set_frame_on</strong></a>(self, b)</dt><dd><tt>Set whether the axes rectangle patch is drawn<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_position"><strong>set_position</strong></a>(self, pos)</dt><dd><tt>Set the axes position with pos = [left, bottom, width, height]<br>
in relative 0,1 coords<br>
<br>
ACCEPTS: len(4) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_title"><strong>set_title</strong></a>(self, label, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_TITLE(label, fontdict=None, **kwargs):<br>
<br>
Set the title for the xaxis. See the text docstring for information<br>
of how override and the optional args work<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_xscale"><strong>set_xscale</strong></a>(self, value, basex<font color="#909090">=10</font>, subsx<font color="#909090">=None</font>)</dt><dd><tt>SET_XSCALE(value, basex=10, subsx=None)<br>
<br>
Set the xscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_xticklabels"><strong>set_xticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XTICKLABELS(labels, fontdict=None, **kwargs)<br>
<br>
Set the xtick labels with list of strings labels Return a list of axis<br>
text instances<br>
<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_xticks"><strong>set_xticks</strong></a>(self, ticks)</dt><dd><tt>Set the x ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_yscale"><strong>set_yscale</strong></a>(self, value, basey<font color="#909090">=10</font>, subsy<font color="#909090">=None</font>)</dt><dd><tt>SET_YSCALE(value, basey=10, subsy=None)<br>
<br>
Set the yscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: the location of the minor ticks; None are the default<br>
is to autosub<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_yticklabels"><strong>set_yticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YTICKLABELS(labels, fontdict=None, **kwargs)<br>
<br>
Set the ytick labels with list of strings labels. Return a list of<br>
Text instances<br>
<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_yticks"><strong>set_yticks</strong></a>(self, ticks)</dt><dd><tt>Set the y ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-specgram"><strong>specgram</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=128</font>, cmap<font color="#909090">=None</font>, xextent<font color="#909090">=None</font>)</dt><dd><tt>SPECGRAM(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=128,<br>
cmap=None, xextent=None)<br>
<br>
Compute a spectrogram of data in x. Data are split into NFFT length<br>
segements and the PSD of each section is computed. The windowing<br>
function window is applied to each segment, and the amount of overlap<br>
of each segment is specified with noverlap.<br>
<br>
* cmap is a colormap; if None use default determined by rc<br>
<br>
* xextent is the image extent in the xaxes xextent=xmin, xmax -<br>
default 0, max(bins), 0, max(freqs) where bins is the return<br>
value from matplotlib.matplotlib.mlab.specgram<br>
<br>
* See help(psd) for information on the other keyword arguments.<br>
<br>
Return value is (Pxx, freqs, bins, im), where<br>
<br>
bins are the time points the spectrogram is calculated over<br>
<br>
freqs is an array of frequencies<br>
<br>
Pxx is a len(times) x len(freqs) array of power<br>
<br>
im is a matplotlib.image.AxesImage.</tt></dd></dl>
<dl><dt><a name="PolarAxes-spy"><strong>spy</strong></a>(self, Z, marker<font color="#909090">='s'</font>, markersize<font color="#909090">=10</font>, **kwargs)</dt><dd><tt>SPY(Z, **kwrags) plots the sparsity pattern of the matrix S<br>
using plot markers.<br>
<br>
kwargs give the marker properties - see help(plot) for more<br>
information on marker properties<br>
<br>
The line handles are returned</tt></dd></dl>
<dl><dt><a name="PolarAxes-spy2"><strong>spy2</strong></a>(self, Z)</dt><dd><tt>SPY2(Z) plots the sparsity pattern of the matrix S as an image<br>
<br>
The image instance is returned</tt></dd></dl>
<dl><dt><a name="PolarAxes-stem"><strong>stem</strong></a>(self, x, y, linefmt<font color="#909090">='b-'</font>, markerfmt<font color="#909090">='bo'</font>, basefmt<font color="#909090">='r-'</font>)</dt><dd><tt>STEM(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')<br>
<br>
A stem plot plots vertical lines (using linefmt) at each x location<br>
from the baseline to y, and places a marker there using markerfmt. A<br>
horizontal line at 0 is is plotted using basefmt<br>
<br>
Return value is (markerline, stemlines, baseline) .<br>
<br>
See<br>
<a href="http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html">http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html</a><br>
for details and examples/stem_plot.py for a demo.</tt></dd></dl>
<dl><dt><a name="PolarAxes-table"><strong>table</strong></a>(self, cellText<font color="#909090">=None</font>, cellColours<font color="#909090">=None</font>, cellLoc<font color="#909090">='right'</font>, colWidths<font color="#909090">=None</font>, rowLabels<font color="#909090">=None</font>, rowColours<font color="#909090">=None</font>, rowLoc<font color="#909090">='left'</font>, colLabels<font color="#909090">=None</font>, colColours<font color="#909090">=None</font>, colLoc<font color="#909090">='center'</font>, loc<font color="#909090">='bottom'</font>, bbox<font color="#909090">=None</font>)</dt><dd><tt>TABLE(cellText=None, cellColours=None,<br>
cellLoc='right', colWidths=None,<br>
rowLabels=None, rowColours=None, rowLoc='left',<br>
colLabels=None, colColours=None, colLoc='center',<br>
loc='bottom', bbox=None):<br>
<br>
Add a table to the current axes. Returns a table instance. For<br>
finer grained control over tables, use the Table class and add it<br>
to the axes with add_table.<br>
<br>
Thanks to John Gill for providing the class and table.</tt></dd></dl>
<dl><dt><a name="PolarAxes-text"><strong>text</strong></a>(self, x, y, s, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>TEXT(x, y, s, fontdict=None, **kwargs)<br>
<br>
Add text in string s to axis at location x,y (data coords)<br>
<br>
fontdict is a dictionary to override the default text properties.<br>
If fontdict is None, the defaults are determined by your rc<br>
parameters.<br>
<br>
Individual keyword arguemnts can be used to override any given<br>
parameter<br>
<br>
<a href="#PolarAxes-text">text</a>(x, y, s, fontsize=12)<br>
<br>
The default transform specifies that text is in data coords,<br>
alternatively, you can specify text in axis coords (0,0 lower left and<br>
1,1 upper right). The example below places text in the center of the<br>
axes<br>
<br>
<a href="#PolarAxes-text">text</a>(0.5, 0.5,'matplotlib',<br>
horizontalalignment='center',<br>
verticalalignment='center',<br>
transform = ax.transAxes,<br>
)</tt></dd></dl>
<dl><dt><a name="PolarAxes-update_datalim"><strong>update_datalim</strong></a>(self, xys)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="PolarAxes-update_datalim_numerix"><strong>update_datalim_numerix</strong></a>(self, x, y)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="PolarAxes-vlines"><strong>vlines</strong></a>(self, x, ymin, ymax, color<font color="#909090">='k'</font>)</dt><dd><tt>VLINES(x, ymin, ymax, color='k')<br>
<br>
Plot vertical lines at each x from ymin to ymax. ymin or ymax can be<br>
scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the heights of the lines are<br>
determined by ymin and ymax<br>
<br>
Returns a list of lines that were added</tt></dd></dl>
<dl><dt><a name="PolarAxes-zoomx"><strong>zoomx</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<dl><dt><a name="PolarAxes-zoomy"><strong>zoomy</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><strong>scaled</strong> = {0: 'linear', 1: 'log'}</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="PolarAxes-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="PolarAxes-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="PolarAxes-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="PolarAxes-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="PolarAxes-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>return the figure instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>return the Transformation instance used by this artist</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-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="PolarAxes-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="PolarAxes-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="PolarAxes-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="PolarAxes-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a matplotlib.transform.Bbox instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-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="PolarAxes-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="PolarAxes-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="PolarAxes-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>set the Transformation instance used by this artist<br>
<br>
ACCEPTS: a matplotlib.transform transformation instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-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="PolarAxes-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="PolarAxes-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="PolarAxes-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>copy properties from other to self</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>
</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="PolarSubplot">class <strong>PolarSubplot</strong></a>(<a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>, <a href="matplotlib.axes.html#PolarAxes">PolarAxes</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Create a polar subplot with<br>
<br>
<a href="#PolarSubplot">PolarSubplot</a>(numRows, numCols, plotNum)<br>
<br>
where plotNum=1 is the first plot number and increasing plotNums<br>
fill rows first. max(plotNum)==numRows*numCols<br>
<br>
You can leave out the commas if numRows<=numCols<=plotNum<10, as<br>
in<br>
<br>
<a href="#Subplot">Subplot</a>(211) # 2 rows, 1 column, first (upper) plot<br> </tt></td></tr>
<tr><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="matplotlib.axes.html#PolarSubplot">PolarSubplot</a></dd>
<dd><a href="matplotlib.axes.html#SubplotBase">SubplotBase</a></dd>
<dd><a href="matplotlib.axes.html#PolarAxes">PolarAxes</a></dd>
<dd><a href="matplotlib.axes.html#Axes">Axes</a></dd>
<dd><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="PolarSubplot-__init__"><strong>__init__</strong></a>(self, fig, *args, **kwargs)</dt></dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>:<br>
<dl><dt><a name="PolarSubplot-is_first_col"><strong>is_first_col</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-is_first_row"><strong>is_first_row</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-is_last_col"><strong>is_last_col</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-is_last_row"><strong>is_last_row</strong></a>(self)</dt></dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#PolarAxes">PolarAxes</a>:<br>
<dl><dt><a name="PolarSubplot-autoscale_view"><strong>autoscale_view</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-cla"><strong>cla</strong></a>(self)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-draw"><strong>draw</strong></a>(self, renderer)</dt></dl>
<dl><dt><a name="PolarSubplot-format_coord"><strong>format_coord</strong></a>(self, theta, r)</dt><dd><tt>return a format string formatting the coordinate</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_rmax"><strong>get_rmax</strong></a>(self)</dt><dd><tt>get the maximum radius in the view limits dimension</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xscale"><strong>get_xscale</strong></a>(self)</dt><dd><tt>return the xaxis scale string</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_yscale"><strong>get_yscale</strong></a>(self)</dt><dd><tt>return the yaxis scale string</tt></dd></dl>
<dl><dt><a name="PolarSubplot-grid"><strong>grid</strong></a>(self, b)</dt><dd><tt>Set the axes grids on or off; b is a boolean</tt></dd></dl>
<dl><dt><a name="PolarSubplot-has_data"><strong>has_data</strong></a>(self)</dt><dd><tt>return true if any artists have been added to axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_rgrids"><strong>set_rgrids</strong></a>(self, radii, labels<font color="#909090">=None</font>, angle<font color="#909090">=22.5</font>, **kwargs)</dt><dd><tt>set the radial locations and labels of the r grids<br>
<br>
The labels will appear at radial distances radii at angle<br>
<br>
labels, if not None, is a len(radii) list of strings of the<br>
labels to use at each angle.<br>
<br>
if labels is None, the self.<strong>rformatter</strong> will be used<br>
<br>
Return value is a list of lines, labels where the lines are<br>
matplotlib.Line2D instances and the labels are matplotlib.Text<br>
instances<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_thetagrids"><strong>set_thetagrids</strong></a>(self, angles, labels<font color="#909090">=None</font>, fmt<font color="#909090">='%d'</font>, frac<font color="#909090">=1.1000000000000001</font>, **kwargs)</dt><dd><tt>set the angles at which to place the theta grids (these<br>
gridlines are equal along the theta dimension). angles is in<br>
degrees<br>
<br>
labels, if not None, is a len(angles) list of strings of the<br>
labels to use at each angle.<br>
<br>
if labels is None, the labels with be fmt%angle<br>
<br>
frac is the fraction of the polar axes radius at which to<br>
place the label (1 is the edge).Eg 1.05 isd outside the axes<br>
and 0.95 is inside the axes<br>
<br>
kwargs are optional text properties for the labels<br>
<br>
Return value is a list of lines, labels where the lines are<br>
matplotlib.Line2D instances and the labels are matplotlib.Text<br>
instances<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_xlabel"><strong>set_xlabel</strong></a>(self, xlabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>xlabel not implemented</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_xlim"><strong>set_xlim</strong></a>(self, v, emit<font color="#909090">=True</font>)</dt><dd><tt>SET_XLIM(v, emit=True)<br>
<br>
A do nothing impl until we can figure out how to handle interaction<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_ylabel"><strong>set_ylabel</strong></a>(self, ylabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>ylabel not implemented</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_ylim"><strong>set_ylim</strong></a>(self, v, emit<font color="#909090">=True</font>)</dt><dd><tt>SET_YLIM(v, emit=True)<br>
<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-toggle_log_lineary"><strong>toggle_log_lineary</strong></a>(self)</dt><dd><tt>toggle between log and linear axes ignored for polar</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.axes.html#PolarAxes">PolarAxes</a>:<br>
<dl><dt><strong>RESOLUTION</strong> = 200</dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><a name="PolarSubplot-add_artist"><strong>add_artist</strong></a>(self, a)</dt><dd><tt>Add any artist to the axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-add_collection"><strong>add_collection</strong></a>(self, collection)</dt><dd><tt>add a Collection instance to <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarSubplot-add_line"><strong>add_line</strong></a>(self, l)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="PolarSubplot-add_patch"><strong>add_patch</strong></a>(self, p)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="PolarSubplot-add_table"><strong>add_table</strong></a>(self, tab)</dt><dd><tt>Add a table instance to the list of axes tables</tt></dd></dl>
<dl><dt><a name="PolarSubplot-axhline"><strong>axhline</strong></a>(self, y<font color="#909090">=0</font>, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHLINE(y=0, xmin=0, xmax=1, **kwargs)<br>
<br>
Axis Horizontal Line<br>
<br>
Draw a horizontal line at y from xmin to xmax. With the default<br>
values of xmin=0 and xmax=1, this line will always span the horizontal<br>
extent of the axes, regardless of the xlim settings, even if you<br>
change them, eg with the xlim command. That is, the horizontal extent<br>
is in axes coords: 0=left, 0.5=middle, 1.0=right but the y location is<br>
in data coordinates.<br>
<br>
Return value is the Line2D instance. kwargs are the same as kwargs to<br>
plot, and can be used to control the line properties. Eg<br>
<br>
# draw a thick red hline at y=0 that spans the xrange<br>
<a href="#PolarSubplot-axhline">axhline</a>(linewidth=4, color='r')<br>
<br>
# draw a default hline at y=1 that spans the xrange<br>
<a href="#PolarSubplot-axhline">axhline</a>(y=1)<br>
<br>
# draw a default hline at y=.5 that spans the the middle half of<br>
# the xrange<br>
<a href="#PolarSubplot-axhline">axhline</a>(y=.5, xmin=0.25, xmax=0.75)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-axhspan"><strong>axhspan</strong></a>(self, ymin, ymax, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHSPAN(ymin, ymax, xmin=0, xmax=1, **kwargs)<br>
<br>
Axis Horizontal Span. ycoords are in data units and x<br>
coords are in axes (relative 0-1) units<br>
<br>
Draw a horizontal span (regtangle) from ymin to ymax. With the<br>
default values of xmin=0 and xmax=1, this always span the xrange,<br>
regardless of the xlim settings, even if you change them, eg with the<br>
xlim command. That is, the horizontal extent is in axes coords:<br>
0=left, 0.5=middle, 1.0=right but the y location is in data<br>
coordinates.<br>
<br>
kwargs are the kwargs to Patch, eg<br>
<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
<br>
the terms on the right are aliases<br>
<br>
Return value is the patches.Polygon instance.<br>
<br>
#draws a gray rectangle from y=0.25-0.75 that spans the horizontal<br>
#extent of the axes<br>
<a href="#PolarSubplot-axhspan">axhspan</a>(0.25, 0.75, facecolor=0.5, alpha=0.5)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-axvline"><strong>axvline</strong></a>(self, x<font color="#909090">=0</font>, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVLINE(x=0, ymin=0, ymax=1, **kwargs)<br>
<br>
Axis Vertical Line<br>
<br>
Draw a vertical line at x from ymin to ymax. With the default values<br>
of ymin=0 and ymax=1, this line will always span the vertical extent<br>
of the axes, regardless of the xlim settings, even if you change them,<br>
eg with the xlim command. That is, the vertical extent is in axes<br>
coords: 0=bottom, 0.5=middle, 1.0=top but the x location is in data<br>
coordinates.<br>
<br>
Return value is the Line2D instance. kwargs are the same as<br>
kwargs to plot, and can be used to control the line properties. Eg<br>
<br>
# draw a thick red vline at x=0 that spans the yrange<br>
l = <a href="#PolarSubplot-axvline">axvline</a>(linewidth=4, color='r')<br>
<br>
# draw a default vline at x=1 that spans the yrange<br>
l = <a href="#PolarSubplot-axvline">axvline</a>(x=1)<br>
<br>
# draw a default vline at x=.5 that spans the the middle half of<br>
# the yrange<br>
<a href="#PolarSubplot-axvline">axvline</a>(x=.5, ymin=0.25, ymax=0.75)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-axvspan"><strong>axvspan</strong></a>(self, xmin, xmax, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVSPAN(xmin, xmax, ymin=0, ymax=1, **kwargs)<br>
<br>
axvspan : Axis Vertical Span. xcoords are in data units and y coords<br>
are in axes (relative 0-1) units<br>
<br>
Draw a vertical span (regtangle) from xmin to xmax. With the default<br>
values of ymin=0 and ymax=1, this always span the yrange, regardless<br>
of the ylim settings, even if you change them, eg with the ylim<br>
command. That is, the vertical extent is in axes coords: 0=bottom,<br>
0.5=middle, 1.0=top but the y location is in data coordinates.<br>
<br>
kwargs are the kwargs to Patch, eg<br>
<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
<br>
the terms on the right are aliases<br>
<br>
return value is the patches.Polygon instance.<br>
<br>
# draw a vertical green translucent rectangle from x=1.25 to 1.55 that<br>
# spans the yrange of the axes<br>
<a href="#PolarSubplot-axvspan">axvspan</a>(1.25, 1.55, facecolor='g', alpha=0.5)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-bar"><strong>bar</strong></a>(self, left, height, width<font color="#909090">=0.80000000000000004</font>, bottom<font color="#909090">=0</font>, color<font color="#909090">='b'</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">='k'</font>, capsize<font color="#909090">=3</font>)</dt><dd><tt>BAR(left, height, width=0.8, bottom=0,<br>
color='b', yerr=None, xerr=None, ecolor='k', capsize=3)<br>
<br>
Make a bar plot with rectangles at<br>
<br>
left, left+width, 0, height<br>
<br>
left and height are Numeric arrays.<br>
<br>
Return value is a list of Rectangle patch instances<br>
<br>
BAR(left, height, width, bottom,<br>
color, yerr, xerr, capsize, yoff)<br>
<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
<br>
color specifies the color of the bar<br>
<br>
ecolor specifies the color of any errorbar<br>
<br>
capsize determines the length in points of the error bar caps<br>
<br>
<br>
The optional arguments color, width and bottom can be either<br>
scalars or len(x) sequences<br>
<br>
This enables you to use bar as the basis for stacked bar<br>
charts, or candlestick plots</tt></dd></dl>
<dl><dt><a name="PolarSubplot-barh"><strong>barh</strong></a>(self, x, y, height<font color="#909090">=0.80000000000000004</font>, left<font color="#909090">=0</font>, color<font color="#909090">='b'</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">='k'</font>, capsize<font color="#909090">=3</font>)</dt><dd><tt>BARH(x, y, height=0.8, left=0,<br>
color='b', yerr=None, xerr=None, ecolor='k', capsize=3)<br>
<br>
BARH(x, y)<br>
<br>
The y values give the heights of the center of the bars. The<br>
x values give the length of the bars.<br>
<br>
Return value is a list of Rectangle patch instances<br>
<br>
Optional arguments<br>
<br>
height - the height (thickness) of the bar<br>
<br>
left - the x coordinate of the left side of the bar<br>
<br>
color specifies the color of the bar<br>
<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
<br>
ecolor specifies the color of any errorbar<br>
<br>
capsize determines the length in points of the error bar caps<br>
<br>
The optional arguments color, height and left can be either<br>
scalars or len(x) sequences</tt></dd></dl>
<dl><dt><a name="PolarSubplot-boxplot"><strong>boxplot</strong></a>(self, x, notch<font color="#909090">=0</font>, sym<font color="#909090">='b+'</font>, vert<font color="#909090">=1</font>, whis<font color="#909090">=1.5</font>)</dt><dd><tt><a href="#PolarSubplot-boxplot">boxplot</a>(x, notch=0, sym='+', vert=1, whis=1.5)<br>
<br>
Make a box and whisker plot for each column of x.<br>
The box extends from the lower to upper quartile values<br>
of the data, with a line at the median. The whiskers<br>
extend from the box to show the range of the data. Flier<br>
points are those past the end of the whiskers.<br>
<br>
notch = 0 (default) produces a rectangular box plot. <br>
notch = 1 will produce a notched box plot<br>
<br>
sym (default 'b+') is the default symbol for flier points.<br>
Enter an empty string ('') if you don't want to show fliers.<br>
<br>
vert = 1 (default) makes the boxes vertical.<br>
vert = 0 makes horizontal boxes. This seems goofy, but<br>
that's how Matlab did it.<br>
<br>
whis (default 1.5) defines the length of the whiskers as<br>
a function of the inner quartile range. They extend to the<br>
most extreme data point within ( whis*(75%-25%) ) data range.<br>
<br>
x is a Numeric array<br>
<br>
Returns a list of the lines added</tt></dd></dl>
<dl><dt><a name="PolarSubplot-clabel"><strong>clabel</strong></a>(self, *args, **kwargs)</dt><dd><tt>CLABEL(*args, **kwargs)<br>
<br>
Function signatures<br>
<br>
CLABEL(C) - plots contour labels,<br>
C is the output of contour or a list of contours<br>
<br>
CLABEL(C,V) - creates labels only for those contours, given in<br>
a list V<br>
<br>
CLABEL(C, **kwargs) - keyword args are explained below:<br>
<br>
<br>
<br>
* fontsize = None: as described in <a href="http://matplotlib.sf.net/fonts.html">http://matplotlib.sf.net/fonts.html</a><br>
<br>
* colors = None:<br>
<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different labels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all labels<br>
will be plotted in this color<br>
<br>
- if colors == None, the color of each label matches the color<br>
of the corresponding contour<br>
<br>
* inline = 0: controls whether the underlying contour is removed<br>
(inline = 1) or not<br>
<br>
* fmt = '%1.3f': a format string for the label</tt></dd></dl>
<dl><dt><a name="PolarSubplot-clear"><strong>clear</strong></a>(self)</dt><dd><tt>clear the axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-cohere"><strong>cohere</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>COHERE(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
cohere the coherence between x and y. Coherence is the normalized<br>
cross spectral density<br>
<br>
Cxy = |Pxy|^2/(Pxx*Pyy)<br>
<br>
The return value is (Cxy, f), where f are the frequencies of the<br>
coherence vector.<br>
<br>
See the PSD help for a description of the optional parameters.<br>
<br>
Returns the tuple Cxy, freqs<br>
<br>
Refs: Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-connect"><strong>connect</strong></a>(self, s, func)</dt><dd><tt>Register observers to be notified when certain events occur. Register<br>
with callback functions with the following signatures. The function<br>
has the following signature<br>
<br>
func(ax) # where ax is the instance making the callback.<br>
<br>
The following events can be connected to:<br>
<br>
'xlim_changed','ylim_changed'<br>
<br>
The connection id is is returned - you can use this with<br>
disconnect to disconnect from the axes event</tt></dd></dl>
<dl><dt><a name="PolarSubplot-contour"><strong>contour</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#PolarSubplot-contour">contour</a>(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z,N) and <a href="#PolarSubplot-contour">contour</a>(X,Y,Z,N) - draw N contour lines overriding<br>
the automatic value<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z,V) and <a href="#PolarSubplot-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in V (array, list, tuple)<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
[L,C] = <a href="#PolarSubplot-contour">contour</a>(...) returns a list of levels and a silent_list of LineCollections<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None: one of these:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the default colormap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified.<br>
<br>
* badmask = None: array with dimensions of Z, and with values<br>
of zero at locations corresponding to valid data, and one<br>
at locations where the value of Z should be ignored.<br>
This is experimental. It presently works for edge regions<br>
for line and filled contours, but for interior regions it<br>
works correctly only for line contours. The badmask kwarg<br>
may go away in the future, to be replaced by the use of<br>
NaN value in Z and/or the use of a masked array in Z.<br>
<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
.matplotlibrc is used<br>
<br>
* fmt = '1.3f': a format string for adding a label to each collection.<br>
Useful for auto-legending.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-contourf"><strong>contourf</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#PolarSubplot-contourf">contourf</a>(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#PolarSubplot-contourf">contourf</a>(Z) - make a filled contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#PolarSubplot-contourf">contourf</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#PolarSubplot-contourf">contourf</a>(Z,N) and <a href="#PolarSubplot-contourf">contourf</a>(X,Y,Z,N) - make a filled contour plot<br>
corresponding to N contour levels<br>
<br>
<a href="#PolarSubplot-contourf">contourf</a>(Z,V) and <a href="#PolarSubplot-contourf">contourf</a>(X,Y,Z,V) - fill len(V) regions,<br>
between the levels specified in sequence V, and a final region<br>
for values of Z greater than the last element in V<br>
<br>
<a href="#PolarSubplot-contourf">contourf</a>(Z, **kwargs) - Use keyword args to control colors,<br>
origin, cmap ... see below<br>
<br>
[L,C] = <a href="#PolarSubplot-contourf">contourf</a>(...) returns a list of levels and a silent_list<br>
of PolyCollections<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None: one of these:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the default colormap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* badmask = None: array with dimensions of Z, and with values<br>
of zero at locations corresponding to valid data, and one<br>
at locations where the value of Z should be ignored.<br>
This is experimental. It presently works for edge regions<br>
for line and filled contours, but for interior regions it<br>
works correctly only for line contours. The badmask kwarg<br>
may go away in the future, to be replaced by the use of<br>
NaN value in Z and/or the use of a masked array in Z.<br>
<br>
reg is a 1D region number array with of imax*(jmax+1)+1 size<br>
The values of reg should be positive region numbers, and zero fro<br>
zones wich do not exist.<br>
<br>
triangle - triangulation array - must be the same shape as reg<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges (because the contouring engine yields<br>
simply connected regions with branch cuts.) To draw the edges,<br>
add line contours with calls to contour.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-csd"><strong>csd</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>CSD(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
The cross spectral density Pxy by Welches average periodogram method.<br>
The vectors x and y are divided into NFFT length segments. Each<br>
segment is detrended by function detrend and windowed by function<br>
window. The product of the direct FFTs of x and y are averaged over<br>
each segment to compute Pxy, with a scaling to correct for power loss<br>
due to windowing.<br>
<br>
See the PSD help for a description of the optional parameters.<br>
<br>
Returns the tuple Pxy, freqs. Pxy is the cross spectrum (complex<br>
valued), and 10*log10(|Pxy|) is plotted<br>
<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-disconnect"><strong>disconnect</strong></a>(self, cid)</dt><dd><tt>disconnect from the <a href="#Axes">Axes</a> event.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-errorbar"><strong>errorbar</strong></a>(self, x, y, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, fmt<font color="#909090">='b-'</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, barsabove<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>ERRORBAR(x, y, yerr=None, xerr=None,<br>
fmt='b-', ecolor=None, capsize=3, barsabove=False)<br>
<br>
Plot x versus y with error deltas in yerr and xerr.<br>
Vertical errorbars are plotted if yerr is not None<br>
Horizontal errorbars are plotted if xerr is not None<br>
<br>
xerr and yerr may be any of:<br>
<br>
a rank-0, Nx1 Numpy array - symmetric errorbars +/- value<br>
<br>
an N-element list or tuple - symmetric errorbars +/- value<br>
<br>
a rank-1, Nx2 Numpy array - asymmetric errorbars -column1/+column2<br>
<br>
Alternatively, x, y, xerr, and yerr can all be scalars, which<br>
plots a single error bar at x, y.<br>
<br>
fmt is the plot format symbol for y. if fmt is None, just<br>
plot the errorbars with no line symbols. This can be useful<br>
for creating a bar plot with errorbars<br>
<br>
ecolor is a matplotlib color arg which gives the color the<br>
errorbar lines; if None, use the marker color.<br>
<br>
capsize is the size of the error bar caps in points<br>
<br>
barsabove, if True, will plot the errorbars above the plot symbols<br>
- default is below<br>
<br>
kwargs are passed on to the plot command for the markers<br>
<br>
Return value is a length 2 tuple. The first element is a list of<br>
y symbol lines. The second element is a list of error bar lines.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-fill"><strong>fill</strong></a>(self, *args, **kwargs)</dt><dd><tt>FILL(*args, **kwargs)<br>
<br>
plot filled polygons. *args is a variable length argument, allowing<br>
for multiple x,y pairs with an optional color format string; see plot<br>
for details on the argument parsing. For example, all of the<br>
following are legal, assuming a is the Axis instance:<br>
<br>
ax.<a href="#PolarSubplot-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
ax.<a href="#PolarSubplot-fill">fill</a>(x,y, 'b' ) # plot polygon with vertices at x,y in blue<br>
<br>
An arbitrary number of x, y, color groups can be specified, as in<br>
ax.<a href="#PolarSubplot-fill">fill</a>(x1, y1, 'g', x2, y2, 'r')<br>
<br>
Return value is a list of patches that were added<br>
<br>
The same color strings that plot supports are supported by the fill<br>
format string.<br>
<br>
The kwargs that are can be used to set line properties (any<br>
property that has a set_* method). You can use this to set edge<br>
color, face color, etc.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-format_xdata"><strong>format_xdata</strong></a>(self, x)</dt><dd><tt>Return x string formatted. This function will use the attribute<br>
self.<strong>fmt_xdata</strong> if it is callable, else will fall back on the xaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="PolarSubplot-format_ydata"><strong>format_ydata</strong></a>(self, y)</dt><dd><tt>Return y string formatted. This function will use the attribute<br>
self.<strong>fmt_ydata</strong> if it is callable, else will fall back on the yaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_axis_bgcolor"><strong>get_axis_bgcolor</strong></a>(self)</dt><dd><tt>Return the axis background color</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_child_artists"><strong>get_child_artists</strong></a>(self)</dt><dd><tt>Return a list of artists the axes contains. Deprecated</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_cursor_props"><strong>get_cursor_props</strong></a>(self)</dt><dd><tt>return the cursor props as a linewidth, color tuple where<br>
linewidth is a float and color is an RGBA tuple</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_frame"><strong>get_frame</strong></a>(self)</dt><dd><tt>Return the axes Rectangle frame</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_images"><strong>get_images</strong></a>(self)</dt><dd><tt>return a list of <a href="#Axes">Axes</a> images contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_legend"><strong>get_legend</strong></a>(self)</dt><dd><tt>Return the Legend instance, or None if no legend is defined</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_lines"><strong>get_lines</strong></a>(self)</dt><dd><tt>Return a list of lines contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_position"><strong>get_position</strong></a>(self)</dt><dd><tt>Return the axes rectangle left, bottom, width, height</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xaxis"><strong>get_xaxis</strong></a>(self)</dt><dd><tt>Return the XAxis instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xgridlines"><strong>get_xgridlines</strong></a>(self)</dt><dd><tt>Get the x grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xlim"><strong>get_xlim</strong></a>(self)</dt><dd><tt>Get the x axis range [xmin, xmax]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xticklabels"><strong>get_xticklabels</strong></a>(self)</dt><dd><tt>Get the xtick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xticklines"><strong>get_xticklines</strong></a>(self)</dt><dd><tt>Get the xtick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xticks"><strong>get_xticks</strong></a>(self)</dt><dd><tt>Return the x ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_yaxis"><strong>get_yaxis</strong></a>(self)</dt><dd><tt>Return the YAxis instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_ygridlines"><strong>get_ygridlines</strong></a>(self)</dt><dd><tt>Get the y grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_ylim"><strong>get_ylim</strong></a>(self)</dt><dd><tt>Get the y axis range [ymin, ymax]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_yticklabels"><strong>get_yticklabels</strong></a>(self)</dt><dd><tt>Get the ytick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_yticklines"><strong>get_yticklines</strong></a>(self)</dt><dd><tt>Get the ytick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_yticks"><strong>get_yticks</strong></a>(self)</dt><dd><tt>Return the y ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="PolarSubplot-hist"><strong>hist</strong></a>(self, x, bins<font color="#909090">=10</font>, normed<font color="#909090">=0</font>, bottom<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>HIST(x, bins=10, normed=0, bottom=0)<br>
<br>
Compute the histogram of x. bins is either an integer number of<br>
bins or a sequence giving the bins. x are the data to be binned.<br>
<br>
The return values is (n, bins, patches)<br>
<br>
If normed is true, the first element of the return tuple will be the<br>
counts normalized to form a probability distribtion, ie,<br>
n/(len(x)*dbin)<br>
<br>
kwargs are used to update the properties of the hist bars</tt></dd></dl>
<dl><dt><a name="PolarSubplot-hlines"><strong>hlines</strong></a>(self, y, xmin, xmax, fmt<font color="#909090">='k-'</font>)</dt><dd><tt>HLINES(y, xmin, xmax, fmt='k-')<br>
<br>
plot horizontal lines at each y from xmin to xmax. xmin or xmax can<br>
be scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the widths of the lines are<br>
determined by xmin and xmax<br>
<br>
Returns a list of line instances that were added</tt></dd></dl>
<dl><dt><a name="PolarSubplot-hold"><strong>hold</strong></a>(self, b<font color="#909090">=None</font>)</dt><dd><tt>HOLD(b=None)<br>
<br>
Set the hold state. If hold is None (default), toggle the<br>
hold state. Else set the hold state to boolean value b.<br>
<br>
Eg<br>
<a href="#PolarSubplot-hold">hold</a>() # toggle hold<br>
<a href="#PolarSubplot-hold">hold</a>(True) # hold is on<br>
<a href="#PolarSubplot-hold">hold</a>(False) # hold is off</tt></dd></dl>
<dl><dt><a name="PolarSubplot-imshow"><strong>imshow</strong></a>(self, X, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, aspect<font color="#909090">=None</font>, interpolation<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, origin<font color="#909090">=None</font>, extent<font color="#909090">=None</font>)</dt><dd><tt>IMSHOW(X, cmap=None, norm=None, aspect=None, interpolation=None,<br>
alpha=1.0, vmin=None, vmax=None, origin=None, extent=None)<br>
<br>
IMSHOW(X) - plot image X to current axes, resampling to scale to axes<br>
size (X may be numarray/Numeric array or PIL image)<br>
<br>
IMSHOW(X, **kwargs) - Use keyword args to control image scaling,<br>
colormapping etc. See below for details<br>
<br>
<br>
Display the image in X to current axes. X may be a float array or a<br>
PIL image. If X is a float array, X can have the following shapes<br>
<br>
MxN : luminance (grayscale)<br>
<br>
MxNx3 : RGB<br>
<br>
MxNx4 : RGBA<br>
<br>
A matplotlib.image.AxesImage instance is returned<br>
<br>
The following kwargs are allowed:<br>
<br>
* cmap is a cm colormap instance, eg cm.jet. If None, default to rc<br>
image.cmap value (Ignored when X has RGB(A) information)<br>
<br>
* aspect is one of: free or preserve. if None, default to rc<br>
image.aspect value<br>
<br>
* interpolation is one of: bicubic bilinear blackman100 blackman256<br>
blackman64 nearest sinc144 sinc256 sinc64 spline16 or spline36.<br>
If None, default to rc image.interpolation<br>
<br>
* norm is a matplotlib.colors.normalize instance; default is<br>
normalization(). This scales luminance -> 0-1 (Ignored when X is<br>
PIL image).<br>
<br>
* vmin and vmax are used to scale a luminance image to 0-1. If<br>
either is None, the min and max of the luminance values will be<br>
used. Note if you pass a norm instance, the settings for vmin and<br>
vmax will be ignored.<br>
<br>
* alpha = 1.0 : the alpha blending value<br>
<br>
* origin is either upper or lower, which indicates where the [0,0]<br>
index of the array is in the upper left or lower left corner of<br>
the axes. If None, default to rc image.origin<br>
<br>
* extent is a data xmin, xmax, ymin, ymax for making image plots<br>
registered with data plots. Default is the image dimensions<br>
in pixels</tt></dd></dl>
<dl><dt><a name="PolarSubplot-in_axes"><strong>in_axes</strong></a>(self, xwin, ywin)</dt><dd><tt>return True is the point xwin, ywin (display coords) are in the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarSubplot-ishold"><strong>ishold</strong></a>(self)</dt><dd><tt>return the HOLD status of the axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-legend"><strong>legend</strong></a>(self, *args, **kwargs)</dt><dd><tt>LEGEND(*args, **kwargs)<br>
<br>
Place a legend on the current axes at location loc. Labels are a<br>
sequence of strings and loc can be a string or an integer specifying<br>
the legend location<br>
<br>
USAGE:<br>
<br>
Make a legend with existing lines<br>
<br>
>>> <a href="#PolarSubplot-legend">legend</a>()<br>
<br>
legend by itself will try and build a legend using the label<br>
property of the lines/patches/collections. You can set the label of<br>
a line by doing <a href="#PolarSubplot-plot">plot</a>(x, y, label='my data') or line.<a href="#PolarSubplot-set_label">set_label</a>('my<br>
data')<br>
<br>
# automatically generate the legend from labels<br>
<a href="#PolarSubplot-legend">legend</a>( ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend for a list of lines and labels<br>
<a href="#PolarSubplot-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend at a given location, using a location argument<br>
# <a href="#PolarSubplot-legend">legend</a>( LABELS, LOC ) or<br>
# <a href="#PolarSubplot-legend">legend</a>( LINES, LABELS, LOC )<br>
<a href="#PolarSubplot-legend">legend</a>( ('label1', 'label2', 'label3'), loc='upper left')<br>
<a href="#PolarSubplot-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3'), loc=2)<br>
<br>
The location codes are<br>
<br>
'best' : 0, <br>
'upper right' : 1, (default)<br>
'upper left' : 2,<br>
'lower left' : 3,<br>
'lower right' : 4,<br>
'right' : 5,<br>
'center left' : 6,<br>
'center right' : 7,<br>
'lower center' : 8,<br>
'upper center' : 9,<br>
'center' : 10,<br>
<br>
If none of these are suitable, loc can be a 2-tuple giving x,y<br>
in axes coords, ie,<br>
<br>
loc = 0, 1 is left top<br>
loc = 0.5, 0.5 is center, center<br>
<br>
and so on. The following kwargs are supported<br>
<br>
numpoints = 4 # the number of points in the legend line<br>
prop = FontProperties('smaller') # the font properties<br>
pad = 0.2 # the fractional whitespace inside the legend border<br>
<br>
# The kwarg dimensions are in axes coords<br>
labelsep = 0.005 # the vertical space between the legend entries<br>
handlelen = 0.05 # the length of the legend lines<br>
handletextsep = 0.02 # the space between the legend line and legend text<br>
axespad = 0.02 # the border between the axes and legend edge<br>
shadow = False # if True, draw a shadow behind legend</tt></dd></dl>
<dl><dt><a name="PolarSubplot-loglog"><strong>loglog</strong></a>(self, *args, **kwargs)</dt><dd><tt>LOGLOG(*args, **kwargs)<br>
<br>
Make a loglog plot with log scaling on the a and y axis. The args<br>
to semilog x are the same as the args to plot. See help plot for<br>
more info.<br>
<br>
Optional keyword args supported are any of the kwargs<br>
supported by plot or set_xscale or set_yscale. Notable, for<br>
log scaling:<br>
<br>
* basex: base of the x logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot<br>
<br>
* basey: base of the y logarithm<br>
<br>
* subsy: the location of the minor yticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="PolarSubplot-panx"><strong>panx</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan right, minus pan left)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pany"><strong>pany</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan up, minus pan down)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pcolor"><strong>pcolor</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLOR(*args, **kwargs)<br>
<br>
Function signatures<br>
<br>
PCOLOR(C) - make a pseudocolor plot of matrix C<br>
<br>
PCOLOR(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
<br>
PCOLOR(C, **kwargs) - Use keywork args to control colormapping and<br>
scaling; see below<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
<br>
* norm = normalize() : matplotlib.colors.normalize is used to scale<br>
luminance data to 0,1.<br>
<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. If you pass a norm<br>
instance, vmin and vmax will be None<br>
<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edge colors are same as<br>
face colors<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
<br>
Grid Orientation<br>
<br>
The behavior of meshgrid in matlab(TM) is a bit counterintuitive for<br>
x and y arrays. For example,<br>
<br>
x = <a href="#-arange">arange</a>(7)<br>
y = <a href="#-arange">arange</a>(5)<br>
X, Y = meshgrid(x,y)<br>
<br>
Z = rand( len(x), len(y))<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(X, Y, Z)<br>
<br>
will fail in matlab and pylab. You will probably be<br>
happy with<br>
<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(X, Y, transpose(Z))<br>
<br>
Likewise, for nonsquare Z,<br>
<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(transpose(Z))<br>
<br>
will make the x and y axes in the plot agree with the numrows and<br>
numcols of Z</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pcolor_classic"><strong>pcolor_classic</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLOR_CLASSIC(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(C) - make a pseudocolor plot of matrix C<br>
<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(C, cmap=cm.jet) - make a pseudocolor plot of matrix C using<br>
rectangle patches using a colormap jet. Colormaps are avalible<br>
in matplotlib.cm. You must pass this as a kwarg.<br>
<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(C, norm=normalize()) - the normalization function used<br>
` to scale your color data to 0-1. must be passed as a kwarg.<br>
<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(C, alpha=0.5) - set the alpha of the pseudocolor plot.<br>
Must be used as a kwarg<br>
<br>
Shading:<br>
<br>
The optional keyword arg shading ('flat' or 'faceted') will<br>
determine whether a black grid is drawn around each pcolor square.<br>
Default 'faceteted' e.g., <a href="#PolarSubplot-pcolor">pcolor</a>(C, shading='flat') <a href="#PolarSubplot-pcolor">pcolor</a>(X, Y,<br>
C, shading='faceted')<br>
<br>
Return value is a list of patch objects.<br>
<br>
Grid orientation<br>
<br>
The behavior of meshgrid in matlab(TM) is a bit counterintuitive for x<br>
and y arrays. For example,<br>
<br>
x = <a href="#-arange">arange</a>(7)<br>
y = <a href="#-arange">arange</a>(5)<br>
X, Y = meshgrid(x,y)<br>
<br>
Z = rand( len(x), len(y))<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(X, Y, Z)<br>
<br>
will fail in matlab and matplotlib. You will probably be<br>
happy with<br>
<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(X, Y, transpose(Z))<br>
<br>
Likewise, for nonsquare Z,<br>
<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(transpose(Z))<br>
<br>
will make the x and y axes in the plot agree with the numrows<br>
and numcols of Z</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pick"><strong>pick</strong></a>(self, x, y, trans<font color="#909090">=None</font>)</dt><dd><tt>Return the artist under point that is closest to the x, y. if trans<br>
is None, x, and y are in window coords, 0,0 = lower left. Otherwise,<br>
trans is a matplotlib transform that specifies the coordinate system<br>
of x, y.<br>
<br>
Note this algorithm calculates distance to the vertices of the<br>
polygon, so if you want to pick a patch, click on the edge!</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pie"><strong>pie</strong></a>(self, x, explode<font color="#909090">=None</font>, labels<font color="#909090">=None</font>, colors<font color="#909090">=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w')</font>, autopct<font color="#909090">=None</font>, shadow<font color="#909090">=False</font>)</dt><dd><tt>Make a pie chart of array x. The fractional area of each wedge is<br>
given by x/sum(x). If sum(x)<=1, then the values of x give the<br>
fractional area directly and the array will not be normalized.<br>
<br>
- explode, if not None, is a len(x) array which specifies the<br>
fraction of the radius to offset that wedge.<br>
<br>
- colors is a sequence of matplotlib color args that the pie chart<br>
will cycle.<br>
<br>
- labels, if not None, is a len(x) list of labels.<br>
<br>
- autopct, if not None, is a string or function used to label the<br>
wedges with their numeric value. The label will be placed inside<br>
the wedge. If it is a format string, the label will be fmt%pct.<br>
If it is a function, it will be called<br>
<br>
- shadow, if True, will draw a shadow beneath the pie.<br>
<br>
The pie chart will probably look best if the figure and axes are<br>
square. Eg,<br>
<br>
figure(figsize=(8,8))<br>
ax = axes([0.1, 0.1, 0.8, 0.8])<br>
<br>
Return value:<br>
<br>
If autopct is None, return a list of (patches, texts), where patches<br>
is a sequence of matplotlib.patches.Wedge instances and texts is a<br>
list of the label Text instnaces<br>
<br>
If autopct is not None, return (patches, texts, autotexts), where<br>
patches and texts are as above, and autotexts is a list of text<br>
instances for the numeric labels</tt></dd></dl>
<dl><dt><a name="PolarSubplot-plot"><strong>plot</strong></a>(self, *args, **kwargs)</dt><dd><tt>PLOT(*args, **kwargs)<br>
<br>
Plot lines and/or markers to the <a href="#Axes">Axes</a>. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional format<br>
string. For example, each of the following is legal<br>
<br>
<a href="#PolarSubplot-plot">plot</a>(x,y) # plot x and y using the default line style and color<br>
<a href="#PolarSubplot-plot">plot</a>(x,y, 'bo') # plot x and y using blue circle markers<br>
<a href="#PolarSubplot-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
<a href="#PolarSubplot-plot">plot</a>(y, 'r+') # ditto, but with red plusses<br>
<br>
An arbitrary number of x, y, fmt groups can be specified, as in<br>
<br>
a.<a href="#PolarSubplot-plot">plot</a>(x1, y1, 'g^', x2, y2, 'g-')<br>
<br>
Return value is a list of lines that were added.<br>
<br>
The following line styles are supported:<br>
<br>
- : solid line<br>
-- : dashed line<br>
-. : dash-dot line<br>
: : dotted line<br>
. : points<br>
, : pixels<br>
o : circle symbols<br>
^ : triangle up symbols<br>
v : triangle down symbols<br>
< : triangle left symbols<br>
> : triangle right symbols<br>
s : square symbols<br>
+ : plus symbols<br>
x : cross symbols<br>
D : diamond symbols<br>
d : thin diamond symbols<br>
1 : tripod down symbols<br>
2 : tripod up symbols<br>
3 : tripod left symbols<br>
4 : tripod right symbols<br>
h : hexagon symbols<br>
H : rotated hexagon symbols<br>
p : pentagon symbols<br>
| : vertical line symbols<br>
_ : horizontal line symbols<br>
steps : use gnuplot style 'steps' # kwarg only<br>
<br>
The following color strings are supported<br>
<br>
b : blue<br>
g : green<br>
r : red<br>
c : cyan<br>
m : magenta<br>
y : yellow<br>
k : black<br>
w : white<br>
<br>
Line styles and colors are combined in a single format string, as in<br>
'bo' for blue circles.<br>
<br>
The **kwargs can be used to set line properties (any property that has<br>
a set_* method). You can use this to set a line label (for auto<br>
legends), linewidth, anitialising, marker face color, etc. Here is an<br>
example:<br>
<br>
<a href="#PolarSubplot-plot">plot</a>([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)<br>
<a href="#PolarSubplot-plot">plot</a>([1,2,3], [1,4,9], 'rs', label='line 2')<br>
axis([0, 4, 0, 10])<br>
<a href="#PolarSubplot-legend">legend</a>()<br>
<br>
If you make multiple lines with one plot command, the kwargs apply<br>
to all those lines, eg<br>
<br>
<a href="#PolarSubplot-plot">plot</a>(x1, y1, x2, y2, antialising=False)<br>
<br>
Neither line will be antialiased.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-plot_date"><strong>plot_date</strong></a>(self, d, y, fmt<font color="#909090">='bo'</font>, tz<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>PLOT_DATE(d, y, converter, fmt='bo', tz=None, **kwargs)<br>
<br>
d is a sequence of dates represented as float days since<br>
0001-01-01 UTC and y are the y values at those dates. fmt is<br>
a plot format string. kwargs are passed on to plot. See plot<br>
for more information.<br>
<br>
See matplotlib.dates for helper functions date2num, num2date<br>
and drange for help on creating the required floating point dates<br>
<br>
tz is the timezone - defaults to rc value</tt></dd></dl>
<dl><dt><a name="PolarSubplot-psd"><strong>psd</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>PSD(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
The power spectral density by Welches average periodogram method. The<br>
vector x is divided into NFFT length segments. Each segment is<br>
detrended by function detrend and windowed by function window.<br>
noperlap gives the length of the overlap between segments. The<br>
absolute(fft(segment))**2 of each segment are averaged to compute Pxx,<br>
with a scaling to correct for power loss due to windowing. Fs is the<br>
sampling frequency.<br>
<br>
NFFT is the length of the fft segment; must be a power of 2<br>
<br>
Fs is the sampling frequency.<br>
<br>
detrend - the function applied to each segment before fft-ing,<br>
designed to remove the mean or linear trend. Unlike in matlab,<br>
where the detrend parameter is a vector, in matplotlib is it a<br>
function. The mlab module defines detrend_none, detrend_mean,<br>
detrend_linear, but you can use a custom function as well.<br>
<br>
window - the function used to window the segments. window is a<br>
function, unlike in matlab(TM) where it is a vector. mlab defines<br>
window_none, window_hanning, but you can use a custom function<br>
as well.<br>
<br>
noverlap gives the length of the overlap between segments.<br>
<br>
Returns the tuple Pxx, freqs<br>
<br>
For plotting, the power is plotted as 10*log10(pxx)) for decibels,<br>
though pxx itself is returned<br>
<br>
Refs:<br>
<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-quiver"><strong>quiver</strong></a>(self, U, V, *args, **kwargs)</dt><dd><tt>QUIVER( X, Y, U, V )<br>
QUIVER( U, V )<br>
QUIVER( X, Y, U, V, S)<br>
QUIVER( U, V, S )<br>
QUIVER( ..., color=None, width=1.0, cmap=None,norm=None )<br>
<br>
Make a vector plot (U, V) with arrows on a grid (X, Y)<br>
<br>
The optional arguments color and width are used to specify the color and width<br>
of the arrow. color can be an array of colors in which case the arrows can be<br>
colored according to another dataset.<br>
<br>
If cm is specied and color is None, the colormap is used to give a color<br>
according to the vector's length.<br>
<br>
If color is a scalar field, the colormap is used to map the scalar to a color<br>
If a colormap is specified and color is an array of color triplets, then the<br>
colormap is ignored<br>
<br>
width is a scalar that controls the width of the arrows<br>
<br>
if S is specified it is used to scale the vectors. Use S=0 to disable automatic<br>
scaling.<br>
If S!=0, vectors are scaled to fit within the grid and then are multiplied by S.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-scatter"><strong>scatter</strong></a>(self, x, y, s<font color="#909090">=20</font>, c<font color="#909090">='b'</font>, marker<font color="#909090">='o'</font>, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, **kwargs)</dt><dd><tt>SCATTER(x, y, s=20, c='b', marker='o', cmap=None, norm=None,<br>
vmin=None, vmax=None, alpha=1.0)<br>
<br>
Supported function signatures:<br>
<br>
SCATTER(x, y) - make a scatter plot of x vs y<br>
<br>
SCATTER(x, y, s) - make a scatter plot of x vs y with size in area<br>
given by s<br>
<br>
SCATTER(x, y, s, c) - make a scatter plot of x vs y with size in area<br>
given by s and colors given by c<br>
<br>
SCATTER(x, y, s, c, **kwargs) - control colormapping and scaling<br>
with keyword args; see below<br>
<br>
Make a scatter plot of x versus y. s is a size in points^2 a scalar<br>
or an array of the same length as x or y. c is a color and can be a<br>
single color format string or an length(x) array of intensities which<br>
will be mapped by the matplotlib.colors.colormap instance cmap<br>
<br>
The marker can be one of<br>
<br>
's' : square<br>
'o' : circle<br>
'^' : triangle up<br>
'>' : triangle right<br>
'v' : triangle down<br>
'<' : triangle left<br>
'd' : diamond<br>
'p' : pentagram<br>
'h' : hexagon<br>
'8' : octagon<br>
<br>
s is a size argument in points squared.<br>
<br>
Other keyword args; the color mapping and normalization arguments will<br>
on be used if c is an array of floats<br>
<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to rc image.cmap<br>
<br>
* norm = normalize() : matplotlib.colors.normalize is used to<br>
scale luminance data to 0,1.<br>
<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. Note if you pass a norm<br>
instance, your settings for vmin and vmax will be ignored<br>
<br>
* alpha =1.0 : the alpha value for the patches</tt></dd></dl>
<dl><dt><a name="PolarSubplot-scatter_classic"><strong>scatter_classic</strong></a>(self, x, y, s<font color="#909090">=None</font>, c<font color="#909090">='b'</font>)</dt><dd><tt>SCATTER_CLASSIC(x, y, s=None, c='b')<br>
<br>
Make a scatter plot of x versus y. s is a size (in data coords) and<br>
can be either a scalar or an array of the same length as x or y. c is<br>
a color and can be a single color format string or an length(x) array<br>
of intensities which will be mapped by the colormap jet.<br>
<br>
If size is None a default size will be used</tt></dd></dl>
<dl><dt><a name="PolarSubplot-semilogx"><strong>semilogx</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGX(*args, **kwargs)<br>
<br>
Make a semilog plot with log scaling on the x axis. The args to<br>
semilog x are the same as the args to plot. See help plot for more<br>
info.<br>
<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_xscale. Notable, for log scaling:<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="PolarSubplot-semilogy"><strong>semilogy</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGY(*args, **kwargs):<br>
<br>
Make a semilog plot with log scaling on the y axis. The args to<br>
semilogy are the same as the args to plot. See help plot for more<br>
info.<br>
<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_yscale. Notable, for log scaling:<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_axis_bgcolor"><strong>set_axis_bgcolor</strong></a>(self, color)</dt><dd><tt>set the axes background color<br>
<br>
ACCEPTS: any matplotlib color - see help(colors)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_axis_off"><strong>set_axis_off</strong></a>(self)</dt><dd><tt>turn off the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_axis_on"><strong>set_axis_on</strong></a>(self)</dt><dd><tt>turn on the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_cursor_props"><strong>set_cursor_props</strong></a>(self, *args)</dt><dd><tt>Set the cursor property as<br>
ax.<a href="#PolarSubplot-set_cursor_props">set_cursor_props</a>(linewidth, color) OR<br>
ax.<a href="#PolarSubplot-set_cursor_props">set_cursor_props</a>((linewidth, color))<br>
<br>
ACCEPTS: a (float, color) tuple</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the <a href="#Axes">Axes</a> figure<br>
<br>
ACCEPTS: a Figure instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_frame_on"><strong>set_frame_on</strong></a>(self, b)</dt><dd><tt>Set whether the axes rectangle patch is drawn<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_position"><strong>set_position</strong></a>(self, pos)</dt><dd><tt>Set the axes position with pos = [left, bottom, width, height]<br>
in relative 0,1 coords<br>
<br>
ACCEPTS: len(4) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_title"><strong>set_title</strong></a>(self, label, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_TITLE(label, fontdict=None, **kwargs):<br>
<br>
Set the title for the xaxis. See the text docstring for information<br>
of how override and the optional args work<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_xscale"><strong>set_xscale</strong></a>(self, value, basex<font color="#909090">=10</font>, subsx<font color="#909090">=None</font>)</dt><dd><tt>SET_XSCALE(value, basex=10, subsx=None)<br>
<br>
Set the xscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_xticklabels"><strong>set_xticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XTICKLABELS(labels, fontdict=None, **kwargs)<br>
<br>
Set the xtick labels with list of strings labels Return a list of axis<br>
text instances<br>
<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_xticks"><strong>set_xticks</strong></a>(self, ticks)</dt><dd><tt>Set the x ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_yscale"><strong>set_yscale</strong></a>(self, value, basey<font color="#909090">=10</font>, subsy<font color="#909090">=None</font>)</dt><dd><tt>SET_YSCALE(value, basey=10, subsy=None)<br>
<br>
Set the yscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: the location of the minor ticks; None are the default<br>
is to autosub<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_yticklabels"><strong>set_yticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YTICKLABELS(labels, fontdict=None, **kwargs)<br>
<br>
Set the ytick labels with list of strings labels. Return a list of<br>
Text instances<br>
<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_yticks"><strong>set_yticks</strong></a>(self, ticks)</dt><dd><tt>Set the y ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-specgram"><strong>specgram</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=128</font>, cmap<font color="#909090">=None</font>, xextent<font color="#909090">=None</font>)</dt><dd><tt>SPECGRAM(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=128,<br>
cmap=None, xextent=None)<br>
<br>
Compute a spectrogram of data in x. Data are split into NFFT length<br>
segements and the PSD of each section is computed. The windowing<br>
function window is applied to each segment, and the amount of overlap<br>
of each segment is specified with noverlap.<br>
<br>
* cmap is a colormap; if None use default determined by rc<br>
<br>
* xextent is the image extent in the xaxes xextent=xmin, xmax -<br>
default 0, max(bins), 0, max(freqs) where bins is the return<br>
value from matplotlib.matplotlib.mlab.specgram<br>
<br>
* See help(psd) for information on the other keyword arguments.<br>
<br>
Return value is (Pxx, freqs, bins, im), where<br>
<br>
bins are the time points the spectrogram is calculated over<br>
<br>
freqs is an array of frequencies<br>
<br>
Pxx is a len(times) x len(freqs) array of power<br>
<br>
im is a matplotlib.image.AxesImage.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-spy"><strong>spy</strong></a>(self, Z, marker<font color="#909090">='s'</font>, markersize<font color="#909090">=10</font>, **kwargs)</dt><dd><tt>SPY(Z, **kwrags) plots the sparsity pattern of the matrix S<br>
using plot markers.<br>
<br>
kwargs give the marker properties - see help(plot) for more<br>
information on marker properties<br>
<br>
The line handles are returned</tt></dd></dl>
<dl><dt><a name="PolarSubplot-spy2"><strong>spy2</strong></a>(self, Z)</dt><dd><tt>SPY2(Z) plots the sparsity pattern of the matrix S as an image<br>
<br>
The image instance is returned</tt></dd></dl>
<dl><dt><a name="PolarSubplot-stem"><strong>stem</strong></a>(self, x, y, linefmt<font color="#909090">='b-'</font>, markerfmt<font color="#909090">='bo'</font>, basefmt<font color="#909090">='r-'</font>)</dt><dd><tt>STEM(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')<br>
<br>
A stem plot plots vertical lines (using linefmt) at each x location<br>
from the baseline to y, and places a marker there using markerfmt. A<br>
horizontal line at 0 is is plotted using basefmt<br>
<br>
Return value is (markerline, stemlines, baseline) .<br>
<br>
See<br>
<a href="http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html">http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html</a><br>
for details and examples/stem_plot.py for a demo.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-table"><strong>table</strong></a>(self, cellText<font color="#909090">=None</font>, cellColours<font color="#909090">=None</font>, cellLoc<font color="#909090">='right'</font>, colWidths<font color="#909090">=None</font>, rowLabels<font color="#909090">=None</font>, rowColours<font color="#909090">=None</font>, rowLoc<font color="#909090">='left'</font>, colLabels<font color="#909090">=None</font>, colColours<font color="#909090">=None</font>, colLoc<font color="#909090">='center'</font>, loc<font color="#909090">='bottom'</font>, bbox<font color="#909090">=None</font>)</dt><dd><tt>TABLE(cellText=None, cellColours=None,<br>
cellLoc='right', colWidths=None,<br>
rowLabels=None, rowColours=None, rowLoc='left',<br>
colLabels=None, colColours=None, colLoc='center',<br>
loc='bottom', bbox=None):<br>
<br>
Add a table to the current axes. Returns a table instance. For<br>
finer grained control over tables, use the Table class and add it<br>
to the axes with add_table.<br>
<br>
Thanks to John Gill for providing the class and table.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-text"><strong>text</strong></a>(self, x, y, s, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>TEXT(x, y, s, fontdict=None, **kwargs)<br>
<br>
Add text in string s to axis at location x,y (data coords)<br>
<br>
fontdict is a dictionary to override the default text properties.<br>
If fontdict is None, the defaults are determined by your rc<br>
parameters.<br>
<br>
Individual keyword arguemnts can be used to override any given<br>
parameter<br>
<br>
<a href="#PolarSubplot-text">text</a>(x, y, s, fontsize=12)<br>
<br>
The default transform specifies that text is in data coords,<br>
alternatively, you can specify text in axis coords (0,0 lower left and<br>
1,1 upper right). The example below places text in the center of the<br>
axes<br>
<br>
<a href="#PolarSubplot-text">text</a>(0.5, 0.5,'matplotlib',<br>
horizontalalignment='center',<br>
verticalalignment='center',<br>
transform = ax.transAxes,<br>
)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-update_datalim"><strong>update_datalim</strong></a>(self, xys)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="PolarSubplot-update_datalim_numerix"><strong>update_datalim_numerix</strong></a>(self, x, y)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="PolarSubplot-vlines"><strong>vlines</strong></a>(self, x, ymin, ymax, color<font color="#909090">='k'</font>)</dt><dd><tt>VLINES(x, ymin, ymax, color='k')<br>
<br>
Plot vertical lines at each x from ymin to ymax. ymin or ymax can be<br>
scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the heights of the lines are<br>
determined by ymin and ymax<br>
<br>
Returns a list of lines that were added</tt></dd></dl>
<dl><dt><a name="PolarSubplot-zoomx"><strong>zoomx</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-zoomy"><strong>zoomy</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><strong>scaled</strong> = {0: 'linear', 1: 'log'}</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="PolarSubplot-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="PolarSubplot-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="PolarSubplot-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="PolarSubplot-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="PolarSubplot-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>return the figure instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>return the Transformation instance used by this artist</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-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="PolarSubplot-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="PolarSubplot-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="PolarSubplot-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="PolarSubplot-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a matplotlib.transform.Bbox instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-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="PolarSubplot-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="PolarSubplot-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="PolarSubplot-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>set the Transformation instance used by this artist<br>
<br>
ACCEPTS: a matplotlib.transform transformation instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-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="PolarSubplot-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="PolarSubplot-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="PolarSubplot-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>copy properties from other to self</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>
</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="Subplot">class <strong>Subplot</strong></a>(<a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>, <a href="matplotlib.axes.html#Axes">Axes</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Emulate matlab's(TM) subplot command, creating axes with<br>
<br>
<a href="#Subplot">Subplot</a>(numRows, numCols, plotNum)<br>
<br>
where plotNum=1 is the first plot number and increasing plotNums<br>
fill rows first. max(plotNum)==numRows*numCols<br>
<br>
You can leave out the commas if numRows<=numCols<=plotNum<10, as<br>
in<br>
<br>
<a href="#Subplot">Subplot</a>(211) # 2 rows, 1 column, first (upper) plot<br> </tt></td></tr>
<tr><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="matplotlib.axes.html#Subplot">Subplot</a></dd>
<dd><a href="matplotlib.axes.html#SubplotBase">SubplotBase</a></dd>
<dd><a href="matplotlib.axes.html#Axes">Axes</a></dd>
<dd><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="Subplot-__init__"><strong>__init__</strong></a>(self, fig, *args, **kwargs)</dt></dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>:<br>
<dl><dt><a name="Subplot-is_first_col"><strong>is_first_col</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-is_first_row"><strong>is_first_row</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-is_last_col"><strong>is_last_col</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-is_last_row"><strong>is_last_row</strong></a>(self)</dt></dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><a name="Subplot-add_artist"><strong>add_artist</strong></a>(self, a)</dt><dd><tt>Add any artist to the axes</tt></dd></dl>
<dl><dt><a name="Subplot-add_collection"><strong>add_collection</strong></a>(self, collection)</dt><dd><tt>add a Collection instance to <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Subplot-add_line"><strong>add_line</strong></a>(self, l)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="Subplot-add_patch"><strong>add_patch</strong></a>(self, p)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="Subplot-add_table"><strong>add_table</strong></a>(self, tab)</dt><dd><tt>Add a table instance to the list of axes tables</tt></dd></dl>
<dl><dt><a name="Subplot-autoscale_view"><strong>autoscale_view</strong></a>(self)</dt><dd><tt>autoscale the view limits using the data limits</tt></dd></dl>
<dl><dt><a name="Subplot-axhline"><strong>axhline</strong></a>(self, y<font color="#909090">=0</font>, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHLINE(y=0, xmin=0, xmax=1, **kwargs)<br>
<br>
Axis Horizontal Line<br>
<br>
Draw a horizontal line at y from xmin to xmax. With the default<br>
values of xmin=0 and xmax=1, this line will always span the horizontal<br>
extent of the axes, regardless of the xlim settings, even if you<br>
change them, eg with the xlim command. That is, the horizontal extent<br>
is in axes coords: 0=left, 0.5=middle, 1.0=right but the y location is<br>
in data coordinates.<br>
<br>
Return value is the Line2D instance. kwargs are the same as kwargs to<br>
plot, and can be used to control the line properties. Eg<br>
<br>
# draw a thick red hline at y=0 that spans the xrange<br>
<a href="#Subplot-axhline">axhline</a>(linewidth=4, color='r')<br>
<br>
# draw a default hline at y=1 that spans the xrange<br>
<a href="#Subplot-axhline">axhline</a>(y=1)<br>
<br>
# draw a default hline at y=.5 that spans the the middle half of<br>
# the xrange<br>
<a href="#Subplot-axhline">axhline</a>(y=.5, xmin=0.25, xmax=0.75)</tt></dd></dl>
<dl><dt><a name="Subplot-axhspan"><strong>axhspan</strong></a>(self, ymin, ymax, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHSPAN(ymin, ymax, xmin=0, xmax=1, **kwargs)<br>
<br>
Axis Horizontal Span. ycoords are in data units and x<br>
coords are in axes (relative 0-1) units<br>
<br>
Draw a horizontal span (regtangle) from ymin to ymax. With the<br>
default values of xmin=0 and xmax=1, this always span the xrange,<br>
regardless of the xlim settings, even if you change them, eg with the<br>
xlim command. That is, the horizontal extent is in axes coords:<br>
0=left, 0.5=middle, 1.0=right but the y location is in data<br>
coordinates.<br>
<br>
kwargs are the kwargs to Patch, eg<br>
<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
<br>
the terms on the right are aliases<br>
<br>
Return value is the patches.Polygon instance.<br>
<br>
#draws a gray rectangle from y=0.25-0.75 that spans the horizontal<br>
#extent of the axes<br>
<a href="#Subplot-axhspan">axhspan</a>(0.25, 0.75, facecolor=0.5, alpha=0.5)</tt></dd></dl>
<dl><dt><a name="Subplot-axvline"><strong>axvline</strong></a>(self, x<font color="#909090">=0</font>, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVLINE(x=0, ymin=0, ymax=1, **kwargs)<br>
<br>
Axis Vertical Line<br>
<br>
Draw a vertical line at x from ymin to ymax. With the default values<br>
of ymin=0 and ymax=1, this line will always span the vertical extent<br>
of the axes, regardless of the xlim settings, even if you change them,<br>
eg with the xlim command. That is, the vertical extent is in axes<br>
coords: 0=bottom, 0.5=middle, 1.0=top but the x location is in data<br>
coordinates.<br>
<br>
Return value is the Line2D instance. kwargs are the same as<br>
kwargs to plot, and can be used to control the line properties. Eg<br>
<br>
# draw a thick red vline at x=0 that spans the yrange<br>
l = <a href="#Subplot-axvline">axvline</a>(linewidth=4, color='r')<br>
<br>
# draw a default vline at x=1 that spans the yrange<br>
l = <a href="#Subplot-axvline">axvline</a>(x=1)<br>
<br>
# draw a default vline at x=.5 that spans the the middle half of<br>
# the yrange<br>
<a href="#Subplot-axvline">axvline</a>(x=.5, ymin=0.25, ymax=0.75)</tt></dd></dl>
<dl><dt><a name="Subplot-axvspan"><strong>axvspan</strong></a>(self, xmin, xmax, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVSPAN(xmin, xmax, ymin=0, ymax=1, **kwargs)<br>
<br>
axvspan : Axis Vertical Span. xcoords are in data units and y coords<br>
are in axes (relative 0-1) units<br>
<br>
Draw a vertical span (regtangle) from xmin to xmax. With the default<br>
values of ymin=0 and ymax=1, this always span the yrange, regardless<br>
of the ylim settings, even if you change them, eg with the ylim<br>
command. That is, the vertical extent is in axes coords: 0=bottom,<br>
0.5=middle, 1.0=top but the y location is in data coordinates.<br>
<br>
kwargs are the kwargs to Patch, eg<br>
<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
<br>
the terms on the right are aliases<br>
<br>
return value is the patches.Polygon instance.<br>
<br>
# draw a vertical green translucent rectangle from x=1.25 to 1.55 that<br>
# spans the yrange of the axes<br>
<a href="#Subplot-axvspan">axvspan</a>(1.25, 1.55, facecolor='g', alpha=0.5)</tt></dd></dl>
<dl><dt><a name="Subplot-bar"><strong>bar</strong></a>(self, left, height, width<font color="#909090">=0.80000000000000004</font>, bottom<font color="#909090">=0</font>, color<font color="#909090">='b'</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">='k'</font>, capsize<font color="#909090">=3</font>)</dt><dd><tt>BAR(left, height, width=0.8, bottom=0,<br>
color='b', yerr=None, xerr=None, ecolor='k', capsize=3)<br>
<br>
Make a bar plot with rectangles at<br>
<br>
left, left+width, 0, height<br>
<br>
left and height are Numeric arrays.<br>
<br>
Return value is a list of Rectangle patch instances<br>
<br>
BAR(left, height, width, bottom,<br>
color, yerr, xerr, capsize, yoff)<br>
<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
<br>
color specifies the color of the bar<br>
<br>
ecolor specifies the color of any errorbar<br>
<br>
capsize determines the length in points of the error bar caps<br>
<br>
<br>
The optional arguments color, width and bottom can be either<br>
scalars or len(x) sequences<br>
<br>
This enables you to use bar as the basis for stacked bar<br>
charts, or candlestick plots</tt></dd></dl>
<dl><dt><a name="Subplot-barh"><strong>barh</strong></a>(self, x, y, height<font color="#909090">=0.80000000000000004</font>, left<font color="#909090">=0</font>, color<font color="#909090">='b'</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">='k'</font>, capsize<font color="#909090">=3</font>)</dt><dd><tt>BARH(x, y, height=0.8, left=0,<br>
color='b', yerr=None, xerr=None, ecolor='k', capsize=3)<br>
<br>
BARH(x, y)<br>
<br>
The y values give the heights of the center of the bars. The<br>
x values give the length of the bars.<br>
<br>
Return value is a list of Rectangle patch instances<br>
<br>
Optional arguments<br>
<br>
height - the height (thickness) of the bar<br>
<br>
left - the x coordinate of the left side of the bar<br>
<br>
color specifies the color of the bar<br>
<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
<br>
ecolor specifies the color of any errorbar<br>
<br>
capsize determines the length in points of the error bar caps<br>
<br>
The optional arguments color, height and left can be either<br>
scalars or len(x) sequences</tt></dd></dl>
<dl><dt><a name="Subplot-boxplot"><strong>boxplot</strong></a>(self, x, notch<font color="#909090">=0</font>, sym<font color="#909090">='b+'</font>, vert<font color="#909090">=1</font>, whis<font color="#909090">=1.5</font>)</dt><dd><tt><a href="#Subplot-boxplot">boxplot</a>(x, notch=0, sym='+', vert=1, whis=1.5)<br>
<br>
Make a box and whisker plot for each column of x.<br>
The box extends from the lower to upper quartile values<br>
of the data, with a line at the median. The whiskers<br>
extend from the box to show the range of the data. Flier<br>
points are those past the end of the whiskers.<br>
<br>
notch = 0 (default) produces a rectangular box plot. <br>
notch = 1 will produce a notched box plot<br>
<br>
sym (default 'b+') is the default symbol for flier points.<br>
Enter an empty string ('') if you don't want to show fliers.<br>
<br>
vert = 1 (default) makes the boxes vertical.<br>
vert = 0 makes horizontal boxes. This seems goofy, but<br>
that's how Matlab did it.<br>
<br>
whis (default 1.5) defines the length of the whiskers as<br>
a function of the inner quartile range. They extend to the<br>
most extreme data point within ( whis*(75%-25%) ) data range.<br>
<br>
x is a Numeric array<br>
<br>
Returns a list of the lines added</tt></dd></dl>
<dl><dt><a name="Subplot-cla"><strong>cla</strong></a>(self)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="Subplot-clabel"><strong>clabel</strong></a>(self, *args, **kwargs)</dt><dd><tt>CLABEL(*args, **kwargs)<br>
<br>
Function signatures<br>
<br>
CLABEL(C) - plots contour labels,<br>
C is the output of contour or a list of contours<br>
<br>
CLABEL(C,V) - creates labels only for those contours, given in<br>
a list V<br>
<br>
CLABEL(C, **kwargs) - keyword args are explained below:<br>
<br>
<br>
<br>
* fontsize = None: as described in <a href="http://matplotlib.sf.net/fonts.html">http://matplotlib.sf.net/fonts.html</a><br>
<br>
* colors = None:<br>
<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different labels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all labels<br>
will be plotted in this color<br>
<br>
- if colors == None, the color of each label matches the color<br>
of the corresponding contour<br>
<br>
* inline = 0: controls whether the underlying contour is removed<br>
(inline = 1) or not<br>
<br>
* fmt = '%1.3f': a format string for the label</tt></dd></dl>
<dl><dt><a name="Subplot-clear"><strong>clear</strong></a>(self)</dt><dd><tt>clear the axes</tt></dd></dl>
<dl><dt><a name="Subplot-cohere"><strong>cohere</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>COHERE(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
cohere the coherence between x and y. Coherence is the normalized<br>
cross spectral density<br>
<br>
Cxy = |Pxy|^2/(Pxx*Pyy)<br>
<br>
The return value is (Cxy, f), where f are the frequencies of the<br>
coherence vector.<br>
<br>
See the PSD help for a description of the optional parameters.<br>
<br>
Returns the tuple Cxy, freqs<br>
<br>
Refs: Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="Subplot-connect"><strong>connect</strong></a>(self, s, func)</dt><dd><tt>Register observers to be notified when certain events occur. Register<br>
with callback functions with the following signatures. The function<br>
has the following signature<br>
<br>
func(ax) # where ax is the instance making the callback.<br>
<br>
The following events can be connected to:<br>
<br>
'xlim_changed','ylim_changed'<br>
<br>
The connection id is is returned - you can use this with<br>
disconnect to disconnect from the axes event</tt></dd></dl>
<dl><dt><a name="Subplot-contour"><strong>contour</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Subplot-contour">contour</a>(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#Subplot-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#Subplot-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#Subplot-contour">contour</a>(Z,N) and <a href="#Subplot-contour">contour</a>(X,Y,Z,N) - draw N contour lines overriding<br>
the automatic value<br>
<br>
<a href="#Subplot-contour">contour</a>(Z,V) and <a href="#Subplot-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in V (array, list, tuple)<br>
<br>
<a href="#Subplot-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
[L,C] = <a href="#Subplot-contour">contour</a>(...) returns a list of levels and a silent_list of LineCollections<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None: one of these:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the default colormap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified.<br>
<br>
* badmask = None: array with dimensions of Z, and with values<br>
of zero at locations corresponding to valid data, and one<br>
at locations where the value of Z should be ignored.<br>
This is experimental. It presently works for edge regions<br>
for line and filled contours, but for interior regions it<br>
works correctly only for line contours. The badmask kwarg<br>
may go away in the future, to be replaced by the use of<br>
NaN value in Z and/or the use of a masked array in Z.<br>
<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
.matplotlibrc is used<br>
<br>
* fmt = '1.3f': a format string for adding a label to each collection.<br>
Useful for auto-legending.</tt></dd></dl>
<dl><dt><a name="Subplot-contourf"><strong>contourf</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Subplot-contourf">contourf</a>(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#Subplot-contourf">contourf</a>(Z) - make a filled contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#Subplot-contourf">contourf</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#Subplot-contourf">contourf</a>(Z,N) and <a href="#Subplot-contourf">contourf</a>(X,Y,Z,N) - make a filled contour plot<br>
corresponding to N contour levels<br>
<br>
<a href="#Subplot-contourf">contourf</a>(Z,V) and <a href="#Subplot-contourf">contourf</a>(X,Y,Z,V) - fill len(V) regions,<br>
between the levels specified in sequence V, and a final region<br>
for values of Z greater than the last element in V<br>
<br>
<a href="#Subplot-contourf">contourf</a>(Z, **kwargs) - Use keyword args to control colors,<br>
origin, cmap ... see below<br>
<br>
[L,C] = <a href="#Subplot-contourf">contourf</a>(...) returns a list of levels and a silent_list<br>
of PolyCollections<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None: one of these:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the default colormap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* badmask = None: array with dimensions of Z, and with values<br>
of zero at locations corresponding to valid data, and one<br>
at locations where the value of Z should be ignored.<br>
This is experimental. It presently works for edge regions<br>
for line and filled contours, but for interior regions it<br>
works correctly only for line contours. The badmask kwarg<br>
may go away in the future, to be replaced by the use of<br>
NaN value in Z and/or the use of a masked array in Z.<br>
<br>
reg is a 1D region number array with of imax*(jmax+1)+1 size<br>
The values of reg should be positive region numbers, and zero fro<br>
zones wich do not exist.<br>
<br>
triangle - triangulation array - must be the same shape as reg<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges (because the contouring engine yields<br>
simply connected regions with branch cuts.) To draw the edges,<br>
add line contours with calls to contour.</tt></dd></dl>
<dl><dt><a name="Subplot-csd"><strong>csd</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>CSD(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
The cross spectral density Pxy by Welches average periodogram method.<br>
The vectors x and y are divided into NFFT length segments. Each<br>
segment is detrended by function detrend and windowed by function<br>
window. The product of the direct FFTs of x and y are averaged over<br>
each segment to compute Pxy, with a scaling to correct for power loss<br>
due to windowing.<br>
<br>
See the PSD help for a description of the optional parameters.<br>
<br>
Returns the tuple Pxy, freqs. Pxy is the cross spectrum (complex<br>
valued), and 10*log10(|Pxy|) is plotted<br>
<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="Subplot-disconnect"><strong>disconnect</strong></a>(self, cid)</dt><dd><tt>disconnect from the <a href="#Axes">Axes</a> event.</tt></dd></dl>
<dl><dt><a name="Subplot-draw"><strong>draw</strong></a>(self, renderer)</dt><dd><tt>Draw everything (plot lines, axes, labels)</tt></dd></dl>
<dl><dt><a name="Subplot-errorbar"><strong>errorbar</strong></a>(self, x, y, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, fmt<font color="#909090">='b-'</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, barsabove<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>ERRORBAR(x, y, yerr=None, xerr=None,<br>
fmt='b-', ecolor=None, capsize=3, barsabove=False)<br>
<br>
Plot x versus y with error deltas in yerr and xerr.<br>
Vertical errorbars are plotted if yerr is not None<br>
Horizontal errorbars are plotted if xerr is not None<br>
<br>
xerr and yerr may be any of:<br>
<br>
a rank-0, Nx1 Numpy array - symmetric errorbars +/- value<br>
<br>
an N-element list or tuple - symmetric errorbars +/- value<br>
<br>
a rank-1, Nx2 Numpy array - asymmetric errorbars -column1/+column2<br>
<br>
Alternatively, x, y, xerr, and yerr can all be scalars, which<br>
plots a single error bar at x, y.<br>
<br>
fmt is the plot format symbol for y. if fmt is None, just<br>
plot the errorbars with no line symbols. This can be useful<br>
for creating a bar plot with errorbars<br>
<br>
ecolor is a matplotlib color arg which gives the color the<br>
errorbar lines; if None, use the marker color.<br>
<br>
capsize is the size of the error bar caps in points<br>
<br>
barsabove, if True, will plot the errorbars above the plot symbols<br>
- default is below<br>
<br>
kwargs are passed on to the plot command for the markers<br>
<br>
Return value is a length 2 tuple. The first element is a list of<br>
y symbol lines. The second element is a list of error bar lines.</tt></dd></dl>
<dl><dt><a name="Subplot-fill"><strong>fill</strong></a>(self, *args, **kwargs)</dt><dd><tt>FILL(*args, **kwargs)<br>
<br>
plot filled polygons. *args is a variable length argument, allowing<br>
for multiple x,y pairs with an optional color format string; see plot<br>
for details on the argument parsing. For example, all of the<br>
following are legal, assuming a is the Axis instance:<br>
<br>
ax.<a href="#Subplot-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
ax.<a href="#Subplot-fill">fill</a>(x,y, 'b' ) # plot polygon with vertices at x,y in blue<br>
<br>
An arbitrary number of x, y, color groups can be specified, as in<br>
ax.<a href="#Subplot-fill">fill</a>(x1, y1, 'g', x2, y2, 'r')<br>
<br>
Return value is a list of patches that were added<br>
<br>
The same color strings that plot supports are supported by the fill<br>
format string.<br>
<br>
The kwargs that are can be used to set line properties (any<br>
property that has a set_* method). You can use this to set edge<br>
color, face color, etc.</tt></dd></dl>
<dl><dt><a name="Subplot-format_coord"><strong>format_coord</strong></a>(self, x, y)</dt><dd><tt>return a format string formatting the x, y coord</tt></dd></dl>
<dl><dt><a name="Subplot-format_xdata"><strong>format_xdata</strong></a>(self, x)</dt><dd><tt>Return x string formatted. This function will use the attribute<br>
self.<strong>fmt_xdata</strong> if it is callable, else will fall back on the xaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="Subplot-format_ydata"><strong>format_ydata</strong></a>(self, y)</dt><dd><tt>Return y string formatted. This function will use the attribute<br>
self.<strong>fmt_ydata</strong> if it is callable, else will fall back on the yaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="Subplot-get_axis_bgcolor"><strong>get_axis_bgcolor</strong></a>(self)</dt><dd><tt>Return the axis background color</tt></dd></dl>
<dl><dt><a name="Subplot-get_child_artists"><strong>get_child_artists</strong></a>(self)</dt><dd><tt>Return a list of artists the axes contains. Deprecated</tt></dd></dl>
<dl><dt><a name="Subplot-get_cursor_props"><strong>get_cursor_props</strong></a>(self)</dt><dd><tt>return the cursor props as a linewidth, color tuple where<br>
linewidth is a float and color is an RGBA tuple</tt></dd></dl>
<dl><dt><a name="Subplot-get_frame"><strong>get_frame</strong></a>(self)</dt><dd><tt>Return the axes Rectangle frame</tt></dd></dl>
<dl><dt><a name="Subplot-get_images"><strong>get_images</strong></a>(self)</dt><dd><tt>return a list of <a href="#Axes">Axes</a> images contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Subplot-get_legend"><strong>get_legend</strong></a>(self)</dt><dd><tt>Return the Legend instance, or None if no legend is defined</tt></dd></dl>
<dl><dt><a name="Subplot-get_lines"><strong>get_lines</strong></a>(self)</dt><dd><tt>Return a list of lines contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Subplot-get_position"><strong>get_position</strong></a>(self)</dt><dd><tt>Return the axes rectangle left, bottom, width, height</tt></dd></dl>
<dl><dt><a name="Subplot-get_xaxis"><strong>get_xaxis</strong></a>(self)</dt><dd><tt>Return the XAxis instance</tt></dd></dl>
<dl><dt><a name="Subplot-get_xgridlines"><strong>get_xgridlines</strong></a>(self)</dt><dd><tt>Get the x grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_xlim"><strong>get_xlim</strong></a>(self)</dt><dd><tt>Get the x axis range [xmin, xmax]</tt></dd></dl>
<dl><dt><a name="Subplot-get_xscale"><strong>get_xscale</strong></a>(self)</dt><dd><tt>return the xaxis scale string: log or linear</tt></dd></dl>
<dl><dt><a name="Subplot-get_xticklabels"><strong>get_xticklabels</strong></a>(self)</dt><dd><tt>Get the xtick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_xticklines"><strong>get_xticklines</strong></a>(self)</dt><dd><tt>Get the xtick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_xticks"><strong>get_xticks</strong></a>(self)</dt><dd><tt>Return the x ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="Subplot-get_yaxis"><strong>get_yaxis</strong></a>(self)</dt><dd><tt>Return the YAxis instance</tt></dd></dl>
<dl><dt><a name="Subplot-get_ygridlines"><strong>get_ygridlines</strong></a>(self)</dt><dd><tt>Get the y grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_ylim"><strong>get_ylim</strong></a>(self)</dt><dd><tt>Get the y axis range [ymin, ymax]</tt></dd></dl>
<dl><dt><a name="Subplot-get_yscale"><strong>get_yscale</strong></a>(self)</dt><dd><tt>return the yaxis scale string: log or linear</tt></dd></dl>
<dl><dt><a name="Subplot-get_yticklabels"><strong>get_yticklabels</strong></a>(self)</dt><dd><tt>Get the ytick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_yticklines"><strong>get_yticklines</strong></a>(self)</dt><dd><tt>Get the ytick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_yticks"><strong>get_yticks</strong></a>(self)</dt><dd><tt>Return the y ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="Subplot-grid"><strong>grid</strong></a>(self, b<font color="#909090">=None</font>)</dt><dd><tt>Set the axes grids on or off; b is a boolean<br>
if b is None, toggle the grid state</tt></dd></dl>
<dl><dt><a name="Subplot-has_data"><strong>has_data</strong></a>(self)</dt><dd><tt>return true if any artists have been added to axes</tt></dd></dl>
<dl><dt><a name="Subplot-hist"><strong>hist</strong></a>(self, x, bins<font color="#909090">=10</font>, normed<font color="#909090">=0</font>, bottom<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>HIST(x, bins=10, normed=0, bottom=0)<br>
<br>
Compute the histogram of x. bins is either an integer number of<br>
bins or a sequence giving the bins. x are the data to be binned.<br>
<br>
The return values is (n, bins, patches)<br>
<br>
If normed is true, the first element of the return tuple will be the<br>
counts normalized to form a probability distribtion, ie,<br>
n/(len(x)*dbin)<br>
<br>
kwargs are used to update the properties of the hist bars</tt></dd></dl>
<dl><dt><a name="Subplot-hlines"><strong>hlines</strong></a>(self, y, xmin, xmax, fmt<font color="#909090">='k-'</font>)</dt><dd><tt>HLINES(y, xmin, xmax, fmt='k-')<br>
<br>
plot horizontal lines at each y from xmin to xmax. xmin or xmax can<br>
be scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the widths of the lines are<br>
determined by xmin and xmax<br>
<br>
Returns a list of line instances that were added</tt></dd></dl>
<dl><dt><a name="Subplot-hold"><strong>hold</strong></a>(self, b<font color="#909090">=None</font>)</dt><dd><tt>HOLD(b=None)<br>
<br>
Set the hold state. If hold is None (default), toggle the<br>
hold state. Else set the hold state to boolean value b.<br>
<br>
Eg<br>
<a href="#Subplot-hold">hold</a>() # toggle hold<br>
<a href="#Subplot-hold">hold</a>(True) # hold is on<br>
<a href="#Subplot-hold">hold</a>(False) # hold is off</tt></dd></dl>
<dl><dt><a name="Subplot-imshow"><strong>imshow</strong></a>(self, X, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, aspect<font color="#909090">=None</font>, interpolation<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, origin<font color="#909090">=None</font>, extent<font color="#909090">=None</font>)</dt><dd><tt>IMSHOW(X, cmap=None, norm=None, aspect=None, interpolation=None,<br>
alpha=1.0, vmin=None, vmax=None, origin=None, extent=None)<br>
<br>
IMSHOW(X) - plot image X to current axes, resampling to scale to axes<br>
size (X may be numarray/Numeric array or PIL image)<br>
<br>
IMSHOW(X, **kwargs) - Use keyword args to control image scaling,<br>
colormapping etc. See below for details<br>
<br>
<br>
Display the image in X to current axes. X may be a float array or a<br>
PIL image. If X is a float array, X can have the following shapes<br>
<br>
MxN : luminance (grayscale)<br>
<br>
MxNx3 : RGB<br>
<br>
MxNx4 : RGBA<br>
<br>
A matplotlib.image.AxesImage instance is returned<br>
<br>
The following kwargs are allowed:<br>
<br>
* cmap is a cm colormap instance, eg cm.jet. If None, default to rc<br>
image.cmap value (Ignored when X has RGB(A) information)<br>
<br>
* aspect is one of: free or preserve. if None, default to rc<br>
image.aspect value<br>
<br>
* interpolation is one of: bicubic bilinear blackman100 blackman256<br>
blackman64 nearest sinc144 sinc256 sinc64 spline16 or spline36.<br>
If None, default to rc image.interpolation<br>
<br>
* norm is a matplotlib.colors.normalize instance; default is<br>
normalization(). This scales luminance -> 0-1 (Ignored when X is<br>
PIL image).<br>
<br>
* vmin and vmax are used to scale a luminance image to 0-1. If<br>
either is None, the min and max of the luminance values will be<br>
used. Note if you pass a norm instance, the settings for vmin and<br>
vmax will be ignored.<br>
<br>
* alpha = 1.0 : the alpha blending value<br>
<br>
* origin is either upper or lower, which indicates where the [0,0]<br>
index of the array is in the upper left or lower left corner of<br>
the axes. If None, default to rc image.origin<br>
<br>
* extent is a data xmin, xmax, ymin, ymax for making image plots<br>
registered with data plots. Default is the image dimensions<br>
in pixels</tt></dd></dl>
<dl><dt><a name="Subplot-in_axes"><strong>in_axes</strong></a>(self, xwin, ywin)</dt><dd><tt>return True is the point xwin, ywin (display coords) are in the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Subplot-ishold"><strong>ishold</strong></a>(self)</dt><dd><tt>return the HOLD status of the axes</tt></dd></dl>
<dl><dt><a name="Subplot-legend"><strong>legend</strong></a>(self, *args, **kwargs)</dt><dd><tt>LEGEND(*args, **kwargs)<br>
<br>
Place a legend on the current axes at location loc. Labels are a<br>
sequence of strings and loc can be a string or an integer specifying<br>
the legend location<br>
<br>
USAGE:<br>
<br>
Make a legend with existing lines<br>
<br>
>>> <a href="#Subplot-legend">legend</a>()<br>
<br>
legend by itself will try and build a legend using the label<br>
property of the lines/patches/collections. You can set the label of<br>
a line by doing <a href="#Subplot-plot">plot</a>(x, y, label='my data') or line.<a href="#Subplot-set_label">set_label</a>('my<br>
data')<br>
<br>
# automatically generate the legend from labels<br>
<a href="#Subplot-legend">legend</a>( ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend for a list of lines and labels<br>
<a href="#Subplot-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend at a given location, using a location argument<br>
# <a href="#Subplot-legend">legend</a>( LABELS, LOC ) or<br>
# <a href="#Subplot-legend">legend</a>( LINES, LABELS, LOC )<br>
<a href="#Subplot-legend">legend</a>( ('label1', 'label2', 'label3'), loc='upper left')<br>
<a href="#Subplot-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3'), loc=2)<br>
<br>
The location codes are<br>
<br>
'best' : 0, <br>
'upper right' : 1, (default)<br>
'upper left' : 2,<br>
'lower left' : 3,<br>
'lower right' : 4,<br>
'right' : 5,<br>
'center left' : 6,<br>
'center right' : 7,<br>
'lower center' : 8,<br>
'upper center' : 9,<br>
'center' : 10,<br>
<br>
If none of these are suitable, loc can be a 2-tuple giving x,y<br>
in axes coords, ie,<br>
<br>
loc = 0, 1 is left top<br>
loc = 0.5, 0.5 is center, center<br>
<br>
and so on. The following kwargs are supported<br>
<br>
numpoints = 4 # the number of points in the legend line<br>
prop = FontProperties('smaller') # the font properties<br>
pad = 0.2 # the fractional whitespace inside the legend border<br>
<br>
# The kwarg dimensions are in axes coords<br>
labelsep = 0.005 # the vertical space between the legend entries<br>
handlelen = 0.05 # the length of the legend lines<br>
handletextsep = 0.02 # the space between the legend line and legend text<br>
axespad = 0.02 # the border between the axes and legend edge<br>
shadow = False # if True, draw a shadow behind legend</tt></dd></dl>
<dl><dt><a name="Subplot-loglog"><strong>loglog</strong></a>(self, *args, **kwargs)</dt><dd><tt>LOGLOG(*args, **kwargs)<br>
<br>
Make a loglog plot with log scaling on the a and y axis. The args<br>
to semilog x are the same as the args to plot. See help plot for<br>
more info.<br>
<br>
Optional keyword args supported are any of the kwargs<br>
supported by plot or set_xscale or set_yscale. Notable, for<br>
log scaling:<br>
<br>
* basex: base of the x logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot<br>
<br>
* basey: base of the y logarithm<br>
<br>
* subsy: the location of the minor yticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="Subplot-panx"><strong>panx</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan right, minus pan left)</tt></dd></dl>
<dl><dt><a name="Subplot-pany"><strong>pany</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan up, minus pan down)</tt></dd></dl>
<dl><dt><a name="Subplot-pcolor"><strong>pcolor</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLOR(*args, **kwargs)<br>
<br>
Function signatures<br>
<br>
PCOLOR(C) - make a pseudocolor plot of matrix C<br>
<br>
PCOLOR(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
<br>
PCOLOR(C, **kwargs) - Use keywork args to control colormapping and<br>
scaling; see below<br>
<br>
Optional keywork args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
<br>
* norm = normalize() : matplotlib.colors.normalize is used to scale<br>
luminance data to 0,1.<br>
<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. If you pass a norm<br>
instance, vmin and vmax will be None<br>
<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edge colors are same as<br>
face colors<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
<br>
Grid Orientation<br>
<br>
The behavior of meshgrid in matlab(TM) is a bit counterintuitive for<br>
x and y arrays. For example,<br>
<br>
x = <a href="#-arange">arange</a>(7)<br>
y = <a href="#-arange">arange</a>(5)<br>
X, Y = meshgrid(x,y)<br>
<br>
Z = rand( len(x), len(y))<br>
<a href="#Subplot-pcolor">pcolor</a>(X, Y, Z)<br>
<br>
will fail in matlab and pylab. You will probably be<br>
happy with<br>
<br>
<a href="#Subplot-pcolor">pcolor</a>(X, Y, transpose(Z))<br>
<br>
Likewise, for nonsquare Z,<br>
<br>
<a href="#Subplot-pcolor">pcolor</a>(transpose(Z))<br>
<br>
will make the x and y axes in the plot agree with the numrows and<br>
numcols of Z</tt></dd></dl>
<dl><dt><a name="Subplot-pcolor_classic"><strong>pcolor_classic</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLOR_CLASSIC(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#Subplot-pcolor">pcolor</a>(C) - make a pseudocolor plot of matrix C<br>
<br>
<a href="#Subplot-pcolor">pcolor</a>(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
<br>
<a href="#Subplot-pcolor">pcolor</a>(C, cmap=cm.jet) - make a pseudocolor plot of matrix C using<br>
rectangle patches using a colormap jet. Colormaps are avalible<br>
in matplotlib.cm. You must pass this as a kwarg.<br>
<br>
<a href="#Subplot-pcolor">pcolor</a>(C, norm=normalize()) - the normalization function used<br>
` to scale your color data to 0-1. must be passed as a kwarg.<br>
<br>
<a href="#Subplot-pcolor">pcolor</a>(C, alpha=0.5) - set the alpha of the pseudocolor plot.<br>
Must be used as a kwarg<br>
<br>
Shading:<br>
<br>
The optional keyword arg shading ('flat' or 'faceted') will<br>
determine whether a black grid is drawn around each pcolor square.<br>
Default 'faceteted' e.g., <a href="#Subplot-pcolor">pcolor</a>(C, shading='flat') <a href="#Subplot-pcolor">pcolor</a>(X, Y,<br>
C, shading='faceted')<br>
<br>
Return value is a list of patch objects.<br>
<br>
Grid orientation<br>
<br>
The behavior of meshgrid in matlab(TM) is a bit counterintuitive for x<br>
and y arrays. For example,<br>
<br>
x = <a href="#-arange">arange</a>(7)<br>
y = <a href="#-arange">arange</a>(5)<br>
X, Y = meshgrid(x,y)<br>
<br>
Z = rand( len(x), len(y))<br>
<a href="#Subplot-pcolor">pcolor</a>(X, Y, Z)<br>
<br>
will fail in matlab and matplotlib. You will probably be<br>
happy with<br>
<br>
<a href="#Subplot-pcolor">pcolor</a>(X, Y, transpose(Z))<br>
<br>
Likewise, for nonsquare Z,<br>
<br>
<a href="#Subplot-pcolor">pcolor</a>(transpose(Z))<br>
<br>
will make the x and y axes in the plot agree with the numrows<br>
and numcols of Z</tt></dd></dl>
<dl><dt><a name="Subplot-pick"><strong>pick</strong></a>(self, x, y, trans<font color="#909090">=None</font>)</dt><dd><tt>Return the artist under point that is closest to the x, y. if trans<br>
is None, x, and y are in window coords, 0,0 = lower left. Otherwise,<br>
trans is a matplotlib transform that specifies the coordinate system<br>
of x, y.<br>
<br>
Note this algorithm calculates distance to the vertices of the<br>
polygon, so if you want to pick a patch, click on the edge!</tt></dd></dl>
<dl><dt><a name="Subplot-pie"><strong>pie</strong></a>(self, x, explode<font color="#909090">=None</font>, labels<font color="#909090">=None</font>, colors<font color="#909090">=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w')</font>, autopct<font color="#909090">=None</font>, shadow<font color="#909090">=False</font>)</dt><dd><tt>Make a pie chart of array x. The fractional area of each wedge is<br>
given by x/sum(x). If sum(x)<=1, then the values of x give the<br>
fractional area directly and the array will not be normalized.<br>
<br>
- explode, if not None, is a len(x) array which specifies the<br>
fraction of the radius to offset that wedge.<br>
<br>
- colors is a sequence of matplotlib color args that the pie chart<br>
will cycle.<br>
<br>
- labels, if not None, is a len(x) list of labels.<br>
<br>
- autopct, if not None, is a string or function used to label the<br>
wedges with their numeric value. The label will be placed inside<br>
the wedge. If it is a format string, the label will be fmt%pct.<br>
If it is a function, it will be called<br>
<br>
- shadow, if True, will draw a shadow beneath the pie.<br>
<br>
The pie chart will probably look best if the figure and axes are<br>
square. Eg,<br>
<br>
figure(figsize=(8,8))<br>
ax = axes([0.1, 0.1, 0.8, 0.8])<br>
<br>
Return value:<br>
<br>
If autopct is None, return a list of (patches, texts), where patches<br>
is a sequence of matplotlib.patches.Wedge instances and texts is a<br>
list of the label Text instnaces<br>
<br>
If autopct is not None, return (patches, texts, autotexts), where<br>
patches and texts are as above, and autotexts is a list of text<br>
instances for the numeric labels</tt></dd></dl>
<dl><dt><a name="Subplot-plot"><strong>plot</strong></a>(self, *args, **kwargs)</dt><dd><tt>PLOT(*args, **kwargs)<br>
<br>
Plot lines and/or markers to the <a href="#Axes">Axes</a>. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional format<br>
string. For example, each of the following is legal<br>
<br>
<a href="#Subplot-plot">plot</a>(x,y) # plot x and y using the default line style and color<br>
<a href="#Subplot-plot">plot</a>(x,y, 'bo') # plot x and y using blue circle markers<br>
<a href="#Subplot-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
<a href="#Subplot-plot">plot</a>(y, 'r+') # ditto, but with red plusses<br>
<br>
An arbitrary number of x, y, fmt groups can be specified, as in<br>
<br>
a.<a href="#Subplot-plot">plot</a>(x1, y1, 'g^', x2, y2, 'g-')<br>
<br>
Return value is a list of lines that were added.<br>
<br>
The following line styles are supported:<br>
<br>
- : solid line<br>
-- : dashed line<br>
-. : dash-dot line<br>
: : dotted line<br>
. : points<br>
, : pixels<br>
o : circle symbols<br>
^ : triangle up symbols<br>
v : triangle down symbols<br>
< : triangle left symbols<br>
> : triangle right symbols<br>
s : square symbols<br>
+ : plus symbols<br>
x : cross symbols<br>
D : diamond symbols<br>
d : thin diamond symbols<br>
1 : tripod down symbols<br>
2 : tripod up symbols<br>
3 : tripod left symbols<br>
4 : tripod right symbols<br>
h : hexagon symbols<br>
H : rotated hexagon symbols<br>
p : pentagon symbols<br>
| : vertical line symbols<br>
_ : horizontal line symbols<br>
steps : use gnuplot style 'steps' # kwarg only<br>
<br>
The following color strings are supported<br>
<br>
b : blue<br>
g : green<br>
r : red<br>
c : cyan<br>
m : magenta<br>
y : yellow<br>
k : black<br>
w : white<br>
<br>
Line styles and colors are combined in a single format string, as in<br>
'bo' for blue circles.<br>
<br>
The **kwargs can be used to set line properties (any property that has<br>
a set_* method). You can use this to set a line label (for auto<br>
legends), linewidth, anitialising, marker face color, etc. Here is an<br>
example:<br>
<br>
<a href="#Subplot-plot">plot</a>([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)<br>
<a href="#Subplot-plot">plot</a>([1,2,3], [1,4,9], 'rs', label='line 2')<br>
axis([0, 4, 0, 10])<br>
<a href="#Subplot-legend">legend</a>()<br>
<br>
If you make multiple lines with one plot command, the kwargs apply<br>
to all those lines, eg<br>
<br>
<a href="#Subplot-plot">plot</a>(x1, y1, x2, y2, antialising=False)<br>
<br>
Neither line will be antialiased.</tt></dd></dl>
<dl><dt><a name="Subplot-plot_date"><strong>plot_date</strong></a>(self, d, y, fmt<font color="#909090">='bo'</font>, tz<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>PLOT_DATE(d, y, converter, fmt='bo', tz=None, **kwargs)<br>
<br>
d is a sequence of dates represented as float days since<br>
0001-01-01 UTC and y are the y values at those dates. fmt is<br>
a plot format string. kwargs are passed on to plot. See plot<br>
for more information.<br>
<br>
See matplotlib.dates for helper functions date2num, num2date<br>
and drange for help on creating the required floating point dates<br>
<br>
tz is the timezone - defaults to rc value</tt></dd></dl>
<dl><dt><a name="Subplot-psd"><strong>psd</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=0</font>)</dt><dd><tt>PSD(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0)<br>
<br>
The power spectral density by Welches average periodogram method. The<br>
vector x is divided into NFFT length segments. Each segment is<br>
detrended by function detrend and windowed by function window.<br>
noperlap gives the length of the overlap between segments. The<br>
absolute(fft(segment))**2 of each segment are averaged to compute Pxx,<br>
with a scaling to correct for power loss due to windowing. Fs is the<br>
sampling frequency.<br>
<br>
NFFT is the length of the fft segment; must be a power of 2<br>
<br>
Fs is the sampling frequency.<br>
<br>
detrend - the function applied to each segment before fft-ing,<br>
designed to remove the mean or linear trend. Unlike in matlab,<br>
where the detrend parameter is a vector, in matplotlib is it a<br>
function. The mlab module defines detrend_none, detrend_mean,<br>
detrend_linear, but you can use a custom function as well.<br>
<br>
window - the function used to window the segments. window is a<br>
function, unlike in matlab(TM) where it is a vector. mlab defines<br>
window_none, window_hanning, but you can use a custom function<br>
as well.<br>
<br>
noverlap gives the length of the overlap between segments.<br>
<br>
Returns the tuple Pxx, freqs<br>
<br>
For plotting, the power is plotted as 10*log10(pxx)) for decibels,<br>
though pxx itself is returned<br>
<br>
Refs:<br>
<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="Subplot-quiver"><strong>quiver</strong></a>(self, U, V, *args, **kwargs)</dt><dd><tt>QUIVER( X, Y, U, V )<br>
QUIVER( U, V )<br>
QUIVER( X, Y, U, V, S)<br>
QUIVER( U, V, S )<br>
QUIVER( ..., color=None, width=1.0, cmap=None,norm=None )<br>
<br>
Make a vector plot (U, V) with arrows on a grid (X, Y)<br>
<br>
The optional arguments color and width are used to specify the color and width<br>
of the arrow. color can be an array of colors in which case the arrows can be<br>
colored according to another dataset.<br>
<br>
If cm is specied and color is None, the colormap is used to give a color<br>
according to the vector's length.<br>
<br>
If color is a scalar field, the colormap is used to map the scalar to a color<br>
If a colormap is specified and color is an array of color triplets, then the<br>
colormap is ignored<br>
<br>
width is a scalar that controls the width of the arrows<br>
<br>
if S is specified it is used to scale the vectors. Use S=0 to disable automatic<br>
scaling.<br>
If S!=0, vectors are scaled to fit within the grid and then are multiplied by S.</tt></dd></dl>
<dl><dt><a name="Subplot-scatter"><strong>scatter</strong></a>(self, x, y, s<font color="#909090">=20</font>, c<font color="#909090">='b'</font>, marker<font color="#909090">='o'</font>, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, **kwargs)</dt><dd><tt>SCATTER(x, y, s=20, c='b', marker='o', cmap=None, norm=None,<br>
vmin=None, vmax=None, alpha=1.0)<br>
<br>
Supported function signatures:<br>
<br>
SCATTER(x, y) - make a scatter plot of x vs y<br>
<br>
SCATTER(x, y, s) - make a scatter plot of x vs y with size in area<br>
given by s<br>
<br>
SCATTER(x, y, s, c) - make a scatter plot of x vs y with size in area<br>
given by s and colors given by c<br>
<br>
SCATTER(x, y, s, c, **kwargs) - control colormapping and scaling<br>
with keyword args; see below<br>
<br>
Make a scatter plot of x versus y. s is a size in points^2 a scalar<br>
or an array of the same length as x or y. c is a color and can be a<br>
single color format string or an length(x) array of intensities which<br>
will be mapped by the matplotlib.colors.colormap instance cmap<br>
<br>
The marker can be one of<br>
<br>
's' : square<br>
'o' : circle<br>
'^' : triangle up<br>
'>' : triangle right<br>
'v' : triangle down<br>
'<' : triangle left<br>
'd' : diamond<br>
'p' : pentagram<br>
'h' : hexagon<br>
'8' : octagon<br>
<br>
s is a size argument in points squared.<br>
<br>
Other keyword args; the color mapping and normalization arguments will<br>
on be used if c is an array of floats<br>
<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to rc image.cmap<br>
<br>
* norm = normalize() : matplotlib.colors.normalize is used to<br>
scale luminance data to 0,1.<br>
<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. Note if you pass a norm<br>
instance, your settings for vmin and vmax will be ignored<br>
<br>
* alpha =1.0 : the alpha value for the patches</tt></dd></dl>
<dl><dt><a name="Subplot-scatter_classic"><strong>scatter_classic</strong></a>(self, x, y, s<font color="#909090">=None</font>, c<font color="#909090">='b'</font>)</dt><dd><tt>SCATTER_CLASSIC(x, y, s=None, c='b')<br>
<br>
Make a scatter plot of x versus y. s is a size (in data coords) and<br>
can be either a scalar or an array of the same length as x or y. c is<br>
a color and can be a single color format string or an length(x) array<br>
of intensities which will be mapped by the colormap jet.<br>
<br>
If size is None a default size will be used</tt></dd></dl>
<dl><dt><a name="Subplot-semilogx"><strong>semilogx</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGX(*args, **kwargs)<br>
<br>
Make a semilog plot with log scaling on the x axis. The args to<br>
semilog x are the same as the args to plot. See help plot for more<br>
info.<br>
<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_xscale. Notable, for log scaling:<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="Subplot-semilogy"><strong>semilogy</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGY(*args, **kwargs):<br>
<br>
Make a semilog plot with log scaling on the y axis. The args to<br>
semilogy are the same as the args to plot. See help plot for more<br>
info.<br>
<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_yscale. Notable, for log scaling:<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot</tt></dd></dl>
<dl><dt><a name="Subplot-set_axis_bgcolor"><strong>set_axis_bgcolor</strong></a>(self, color)</dt><dd><tt>set the axes background color<br>
<br>
ACCEPTS: any matplotlib color - see help(colors)</tt></dd></dl>
<dl><dt><a name="Subplot-set_axis_off"><strong>set_axis_off</strong></a>(self)</dt><dd><tt>turn off the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="Subplot-set_axis_on"><strong>set_axis_on</strong></a>(self)</dt><dd><tt>turn on the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="Subplot-set_cursor_props"><strong>set_cursor_props</strong></a>(self, *args)</dt><dd><tt>Set the cursor property as<br>
ax.<a href="#Subplot-set_cursor_props">set_cursor_props</a>(linewidth, color) OR<br>
ax.<a href="#Subplot-set_cursor_props">set_cursor_props</a>((linewidth, color))<br>
<br>
ACCEPTS: a (float, color) tuple</tt></dd></dl>
<dl><dt><a name="Subplot-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the <a href="#Axes">Axes</a> figure<br>
<br>
ACCEPTS: a Figure instance</tt></dd></dl>
<dl><dt><a name="Subplot-set_frame_on"><strong>set_frame_on</strong></a>(self, b)</dt><dd><tt>Set whether the axes rectangle patch is drawn<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="Subplot-set_position"><strong>set_position</strong></a>(self, pos)</dt><dd><tt>Set the axes position with pos = [left, bottom, width, height]<br>
in relative 0,1 coords<br>
<br>
ACCEPTS: len(4) sequence of floats</tt></dd></dl>
<dl><dt><a name="Subplot-set_title"><strong>set_title</strong></a>(self, label, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_TITLE(label, fontdict=None, **kwargs):<br>
<br>
Set the title for the xaxis. See the text docstring for information<br>
of how override and the optional args work<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Subplot-set_xlabel"><strong>set_xlabel</strong></a>(self, xlabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XLABEL(xlabel, fontdict=None, **kwargs)<br>
<br>
Set the label for the xaxis. See the text docstring for information<br>
of how override and the optional args work.<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Subplot-set_xlim"><strong>set_xlim</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Subplot-set_xlim">set_xlim</a>(self, *args, **kwargs):<br>
<br>
Set the limits for the xaxis; v = [xmin, xmax]<br>
<br>
<a href="#Subplot-set_xlim">set_xlim</a>((valmin, valmax))<br>
<a href="#Subplot-set_xlim">set_xlim</a>(valmin, valmax)<br>
<a href="#Subplot-set_xlim">set_xlim</a>(xmin=1) # xmax unchanged<br>
<a href="#Subplot-set_xlim">set_xlim</a>(xmax=1) # xmin unchanged<br>
<br>
Valid kwargs:<br>
<br>
xmin : the min of the xlim<br>
xmax : the max of the xlim <br>
emit : notify observers of lim change<br>
<br>
<br>
Returns the current xlimits as a length 2 tuple<br>
<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="Subplot-set_xscale"><strong>set_xscale</strong></a>(self, value, basex<font color="#909090">=10</font>, subsx<font color="#909090">=None</font>)</dt><dd><tt>SET_XSCALE(value, basex=10, subsx=None)<br>
<br>
Set the xscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: the location of the minor ticks; None defaults to autosubs,<br>
which depend on the number of decades in the plot<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Subplot-set_xticklabels"><strong>set_xticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XTICKLABELS(labels, fontdict=None, **kwargs)<br>
<br>
Set the xtick labels with list of strings labels Return a list of axis<br>
text instances<br>
<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="Subplot-set_xticks"><strong>set_xticks</strong></a>(self, ticks)</dt><dd><tt>Set the x ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="Subplot-set_ylabel"><strong>set_ylabel</strong></a>(self, ylabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YLABEL(ylabel, fontdict=None, **kwargs)<br>
<br>
Set the label for the yaxis<br>
<br>
See the text doctstring for information of how override and<br>
the optional args work<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Subplot-set_ylim"><strong>set_ylim</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Subplot-set_ylim">set_ylim</a>(self, *args, **kwargs):<br>
<br>
Set the limits for the yaxis; v = [ymin, ymax]<br>
<br>
<a href="#Subplot-set_ylim">set_ylim</a>((valmin, valmax))<br>
<a href="#Subplot-set_ylim">set_ylim</a>(valmin, valmax)<br>
<a href="#Subplot-set_ylim">set_ylim</a>(ymin=1) # ymax unchanged<br>
<a href="#Subplot-set_ylim">set_ylim</a>(ymax=1) # ymin unchanged<br>
<br>
Valid kwargs:<br>
<br>
ymin : the min of the ylim<br>
ymax : the max of the ylim <br>
emit : notify observers of lim change<br>
<br>
<br>
Returns the current ylimits as a length 2 tuple<br>
<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="Subplot-set_yscale"><strong>set_yscale</strong></a>(self, value, basey<font color="#909090">=10</font>, subsy<font color="#909090">=None</font>)</dt><dd><tt>SET_YSCALE(value, basey=10, subsy=None)<br>
<br>
Set the yscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: the location of the minor ticks; None are the default<br>
is to autosub<br>
<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Subplot-set_yticklabels"><strong>set_yticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YTICKLABELS(labels, fontdict=None, **kwargs)<br>
<br>
Set the ytick labels with list of strings labels. Return a list of<br>
Text instances<br>
<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="Subplot-set_yticks"><strong>set_yticks</strong></a>(self, ticks)</dt><dd><tt>Set the y ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="Subplot-specgram"><strong>specgram</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none></font>, window<font color="#909090">=<function window_hanning></font>, noverlap<font color="#909090">=128</font>, cmap<font color="#909090">=None</font>, xextent<font color="#909090">=None</font>)</dt><dd><tt>SPECGRAM(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=128,<br>
cmap=None, xextent=None)<br>
<br>
Compute a spectrogram of data in x. Data are split into NFFT length<br>
segements and the PSD of each section is computed. The windowing<br>
function window is applied to each segment, and the amount of overlap<br>
of each segment is specified with noverlap.<br>
<br>
* cmap is a colormap; if None use default determined by rc<br>
<br>
* xextent is the image extent in the xaxes xextent=xmin, xmax -<br>
default 0, max(bins), 0, max(freqs) where bins is the return<br>
value from matplotlib.matplotlib.mlab.specgram<br>
<br>
* See help(psd) for information on the other keyword arguments.<br>
<br>
Return value is (Pxx, freqs, bins, im), where<br>
<br>
bins are the time points the spectrogram is calculated over<br>
<br>
freqs is an array of frequencies<br>
<br>
Pxx is a len(times) x len(freqs) array of power<br>
<br>
im is a matplotlib.image.AxesImage.</tt></dd></dl>
<dl><dt><a name="Subplot-spy"><strong>spy</strong></a>(self, Z, marker<font color="#909090">='s'</font>, markersize<font color="#909090">=10</font>, **kwargs)</dt><dd><tt>SPY(Z, **kwrags) plots the sparsity pattern of the matrix S<br>
using plot markers.<br>
<br>
kwargs give the marker properties - see help(plot) for more<br>
information on marker properties<br>
<br>
The line handles are returned</tt></dd></dl>
<dl><dt><a name="Subplot-spy2"><strong>spy2</strong></a>(self, Z)</dt><dd><tt>SPY2(Z) plots the sparsity pattern of the matrix S as an image<br>
<br>
The image instance is returned</tt></dd></dl>
<dl><dt><a name="Subplot-stem"><strong>stem</strong></a>(self, x, y, linefmt<font color="#909090">='b-'</font>, markerfmt<font color="#909090">='bo'</font>, basefmt<font color="#909090">='r-'</font>)</dt><dd><tt>STEM(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')<br>
<br>
A stem plot plots vertical lines (using linefmt) at each x location<br>
from the baseline to y, and places a marker there using markerfmt. A<br>
horizontal line at 0 is is plotted using basefmt<br>
<br>
Return value is (markerline, stemlines, baseline) .<br>
<br>
See<br>
<a href="http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html">http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html</a><br>
for details and examples/stem_plot.py for a demo.</tt></dd></dl>
<dl><dt><a name="Subplot-table"><strong>table</strong></a>(self, cellText<font color="#909090">=None</font>, cellColours<font color="#909090">=None</font>, cellLoc<font color="#909090">='right'</font>, colWidths<font color="#909090">=None</font>, rowLabels<font color="#909090">=None</font>, rowColours<font color="#909090">=None</font>, rowLoc<font color="#909090">='left'</font>, colLabels<font color="#909090">=None</font>, colColours<font color="#909090">=None</font>, colLoc<font color="#909090">='center'</font>, loc<font color="#909090">='bottom'</font>, bbox<font color="#909090">=None</font>)</dt><dd><tt>TABLE(cellText=None, cellColours=None,<br>
cellLoc='right', colWidths=None,<br>
rowLabels=None, rowColours=None, rowLoc='left',<br>
colLabels=None, colColours=None, colLoc='center',<br>
loc='bottom', bbox=None):<br>
<br>
Add a table to the current axes. Returns a table instance. For<br>
finer grained control over tables, use the Table class and add it<br>
to the axes with add_table.<br>
<br>
Thanks to John Gill for providing the class and table.</tt></dd></dl>
<dl><dt><a name="Subplot-text"><strong>text</strong></a>(self, x, y, s, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>TEXT(x, y, s, fontdict=None, **kwargs)<br>
<br>
Add text in string s to axis at location x,y (data coords)<br>
<br>
fontdict is a dictionary to override the default text properties.<br>
If fontdict is None, the defaults are determined by your rc<br>
parameters.<br>
<br>
Individual keyword arguemnts can be used to override any given<br>
parameter<br>
<br>
<a href="#Subplot-text">text</a>(x, y, s, fontsize=12)<br>
<br>
The default transform specifies that text is in data coords,<br>
alternatively, you can specify text in axis coords (0,0 lower left and<br>
1,1 upper right). The example below places text in the center of the<br>
axes<br>
<br>
<a href="#Subplot-text">text</a>(0.5, 0.5,'matplotlib',<br>
horizontalalignment='center',<br>
verticalalignment='center',<br>
transform = ax.transAxes,<br>
)</tt></dd></dl>
<dl><dt><a name="Subplot-toggle_log_lineary"><strong>toggle_log_lineary</strong></a>(self)</dt><dd><tt>toggle between log and linear on the y axis</tt></dd></dl>
<dl><dt><a name="Subplot-update_datalim"><strong>update_datalim</strong></a>(self, xys)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="Subplot-update_datalim_numerix"><strong>update_datalim_numerix</strong></a>(self, x, y)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="Subplot-vlines"><strong>vlines</strong></a>(self, x, ymin, ymax, color<font color="#909090">='k'</font>)</dt><dd><tt>VLINES(x, ymin, ymax, color='k')<br>
<br>
Plot vertical lines at each x from ymin to ymax. ymin or ymax can be<br>
scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the heights of the lines are<br>
determined by ymin and ymax<br>
<br>
Returns a list of lines that were added</tt></dd></dl>
<dl><dt><a name="Subplot-zoomx"><strong>zoomx</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<dl><dt><a name="Subplot-zoomy"><strong>zoomy</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><strong>scaled</strong> = {0: 'linear', 1: 'log'}</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="Subplot-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="Subplot-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="Subplot-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="Subplot-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="Subplot-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>return the figure instance</tt></dd></dl>
<dl><dt><a name="Subplot-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>return the Transformation instance used by this artist</tt></dd></dl>
<dl><dt><a name="Subplot-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="Subplot-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-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="Subplot-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="Subplot-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="Subplot-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="Subplot-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a matplotlib.transform.Bbox instance</tt></dd></dl>
<dl><dt><a name="Subplot-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="Subplot-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="Subplot-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="Subplot-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>set the Transformation instance used by this artist<br>
<br>
ACCEPTS: a matplotlib.transform transformation instance</tt></dd></dl>
<dl><dt><a name="Subplot-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="Subplot-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="Subplot-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="Subplot-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>copy properties from other to self</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>
</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="SubplotBase">class <strong>SubplotBase</strong></a></font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Emulate matlab's(TM) subplot command, creating axes with<br>
<br>
<a href="#Subplot">Subplot</a>(numRows, numCols, plotNum)<br>
<br>
where plotNum=1 is the first plot number and increasing plotNums<br>
fill rows first. max(plotNum)==numRows*numCols<br>
<br>
You can leave out the commas if numRows<=numCols<=plotNum<10, as<br>
in<br>
<br>
<a href="#Subplot">Subplot</a>(211) # 2 rows, 1 column, first (upper) plot<br> </tt></td></tr>
<tr><td> </td>
<td width="100%">Methods defined here:<br>
<dl><dt><a name="SubplotBase-__init__"><strong>__init__</strong></a>(self, *args)</dt></dl>
<dl><dt><a name="SubplotBase-is_first_col"><strong>is_first_col</strong></a>(self)</dt></dl>
<dl><dt><a name="SubplotBase-is_first_row"><strong>is_first_row</strong></a>(self)</dt></dl>
<dl><dt><a name="SubplotBase-is_last_col"><strong>is_last_col</strong></a>(self)</dt></dl>
<dl><dt><a name="SubplotBase-is_last_row"><strong>is_last_row</strong></a>(self)</dt></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="-Affine"><strong>Affine</strong></a>(...)</dt><dd><tt><a href="#-Affine">Affine</a>(a,b,c,d,tx,ty)</tt></dd></dl>
<dl><dt><a name="-Bbox"><strong>Bbox</strong></a>(...)</dt><dd><tt><a href="#-Bbox">Bbox</a>(ll, ur)</tt></dd></dl>
<dl><dt><a name="-Func"><strong>Func</strong></a>(...)</dt><dd><tt><a href="#-Func">Func</a>(typecode)</tt></dd></dl>
<dl><dt><a name="-FuncXY"><strong>FuncXY</strong></a>(...)</dt><dd><tt><a href="#-FuncXY">FuncXY</a>(funcx, funcy)</tt></dd></dl>
<dl><dt><a name="-Interval"><strong>Interval</strong></a>(...)</dt><dd><tt><a href="#-Interval">Interval</a>(val1, val2)</tt></dd></dl>
<dl><dt><a name="-NonseparableTransformation"><strong>NonseparableTransformation</strong></a>(...)</dt><dd><tt><a href="#-NonseparableTransformation">NonseparableTransformation</a>(box1, box2, funcxy))</tt></dd></dl>
<dl><dt><a name="-Point"><strong>Point</strong></a>(...)</dt><dd><tt><a href="#-Point">Point</a>(x, y)</tt></dd></dl>
<dl><dt><a name="-Value"><strong>Value</strong></a>(...)</dt><dd><tt><a href="#-Value">Value</a>(x)</tt></dd></dl>
<dl><dt><a name="-arange"><strong>arange</strong></a>(...)</dt><dd><tt><a href="#-arange">arange</a>(start, stop=None, step=1, typecode=None)<br>
<br>
Just like range() except it returns an array whose type can be<br>
specified by the keyword argument typecode.</tt></dd></dl>
<dl><dt><a name="-array"><strong>array</strong></a>(...)</dt><dd><tt><a href="#-array">array</a>(sequence, typecode=None, copy=1, savespace=0) will return a new array formed from the given (potentially nested) sequence with type given by typecode. If no typecode is given, then the type will be determined as the minimum type required to hold the objects in sequence. If copy is zero and sequence is already an array, a reference will be returned. If savespace is nonzero, the new array will maintain its precision in operations.</tt></dd></dl>
<dl><dt><a name="-makeValue"><strong>makeValue</strong></a>(v)</dt></dl>
<dl><dt><a name="-zeros"><strong>zeros</strong></a>(...)</dt><dd><tt><a href="#-zeros">zeros</a>((d1,...,dn),typecode='l',savespace=0) will return a new array of shape (d1,...,dn) and type typecode with all it's entries initialized to zero. If savespace is nonzero the array will be a spacesaver array.</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>Float</strong> = 'd'<br>
<strong>Float32</strong> = 'f'<br>
<strong>Float64</strong> = 'd'<br>
<strong>IDENTITY</strong> = 0<br>
<strong>Int</strong> = 'l'<br>
<strong>Int16</strong> = 's'<br>
<strong>Int32</strong> = 'i'<br>
<strong>LOG10</strong> = 1<br>
<strong>POLAR</strong> = 0<br>
<strong>SEC_PER_DAY</strong> = 86400<br>
<strong>SEC_PER_HOUR</strong> = 3600<br>
<strong>SEC_PER_MIN</strong> = 60<br>
<strong>SEC_PER_WEEK</strong> = 604800<br>
<strong>absolute</strong> = <ufunc 'absolute'><br>
<strong>ceil</strong> = <ufunc 'ceil'><br>
<strong>colorConverter</strong> = <matplotlib.colors.ColorConverter instance><br>
<strong>divide</strong> = <ufunc 'divide'><br>
<strong>division</strong> = _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)<br>
<strong>generators</strong> = _Feature((2, 2, 0, 'alpha', 1), (2, 3, 0, 'final', 0), 4096)<br>
<strong>lineMarkers</strong> = {0: 1, 1: 1, 2: 1, 3: 1, '+': 1, ',': 1, '.': 1, '1': 1, '2': 1, '3': 1, ...}<br>
<strong>lineStyles</strong> = {'-': 1, '--': 1, '-.': 1, ':': 1, 'None': 1, 'steps': 1}<br>
<strong>log</strong> = <ufunc 'log'><br>
<strong>log10</strong> = <ufunc 'log10'><br>
<strong>maximum</strong> = <ufunc 'maximum'><br>
<strong>minimum</strong> = <ufunc 'minimum'><br>
<strong>rcParams</strong> = {'axes.edgecolor': 'black', 'axes.facecolor': 'white', 'axes.grid': False, 'axes.hold': True, 'axes.labelcolor': 'black', 'axes.labelsize': 12.0, 'axes.linewidth': 1.0, 'axes.titlesize': 14.0, 'backend': 'WXAgg', 'datapath': '/usr/local/share/matplotlib', ...}<br>
<strong>sqrt</strong> = <ufunc 'sqrt'><br>
<strong>which</strong> = ('numeric', 'rc')</td></tr></table>
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