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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="MLab.html">MLab</a><br>
<a href="matplotlib._image.html">matplotlib._image</a><br>
</td><td width="25%" valign=top><a href="matplotlib.cm.html">matplotlib.cm</a><br>
<a href="math.html">math</a><br>
</td><td width="25%" valign=top><a href="matplotlib.mlab.html">matplotlib.mlab</a><br>
<a href="sys.html">sys</a><br>
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<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
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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#Subplot">Subplot</a>
</font></dt></dl>
</dd>
</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 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>)</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></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></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)<br>
<br>
Make a bar plot with rectangles at<br>
left, left+width, 0, height<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>
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-cla"><strong>cla</strong></a>(self)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="Axes-clear"><strong>clear</strong></a>(self)</dt></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 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. See the docs for psd and csd for information<br>
about the function arguments NFFT, detrend, windowm noverlap, as<br>
well as the methods used to compute Pxy, Pxx and Pyy.<br>
<br>
Returns the tuple Cxy, freqs<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-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>The cross spectral density Pxy by Welches average periodogram<br>
method. The vectors x and y are divided into NFFT length<br>
segments. Each segment is detrended by function detrend and<br>
windowed by function window. noverlap gives the length of the<br>
overlap between segments. The product of the direct FFTs of x and<br>
y are averaged over each segment to compute Pxy, with a scaling to<br>
correct for power loss due to windowing. Fs is the sampling<br>
frequency.<br>
<br>
NFFT must be a power of 2<br>
<br>
detrend and window are functions, unlike in matlab where they are<br>
vectors. For detrending you can use detrend_none, detrend_mean,<br>
detrend_linear or a custom function. For windowing, you can use<br>
window_none, window_hanning, or a custom function<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-draw"><strong>draw</strong></a>(self, renderer, *args, **kwargs)</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">='k'</font>, capsize<font color="#909090">=3</font>)</dt><dd><tt>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>
a rank-0, Nx1 Numpy array - symmetric errorbars +/- value<br>
an N-element list or tuple - symmetric errorbars +/- value<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>
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.<br>
<br>
capsize is the size of the error bar caps in points</tt></dd></dl>
<dl><dt><a name="Axes-fill"><strong>fill</strong></a>(self, *args, **kwargs)</dt><dd><tt>Emulate matlab's fill command. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional<br>
color format string. For example, all of the following are<br>
legal, assuming a is the Axis instance:<br>
<br>
a.<a href="#Axes-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
a.<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>
a.<a href="#Axes-fill">fill</a>(x1, y1, 'g', x2, y2, 'r') <br>
<br>
Returns a list of patches that were added.</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></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></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></dl>
<dl><dt><a name="Axes-get_position"><strong>get_position</strong></a>(self)</dt><dd><tt>Return the axes position</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_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_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)</dt><dd><tt>Set the axes grids on or off; b is a boolean</tt></dd></dl>
<dl><dt><a name="Axes-has_data"><strong>has_data</strong></a>(self)</dt></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>)</dt><dd><tt>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>
if noplot is True, just compute the histogram and return the<br>
number of observations and the bins as an (n, bins) tuple.<br>
<br>
If noplot is False, compute the histogram and plot it, returning<br>
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)</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>plot horizontal lines at each y from xmin to xmax. xmin or<br>
xmax can be scalars or len(x) numpy arrays. If they are<br>
scalars, then the respective values are constant, else the<br>
widths of the lines are 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>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>, origin<font color="#909090">=None</font>)</dt><dd><tt>Display the image in array X to current axes. X must be a<br>
float array<br>
<br>
If X is MxN, assume luminance (grayscale)<br>
If X is MxNx3, assume RGB<br>
If X is MxNx4, assume RGBA<br>
<br>
A matplotlib.image.AxesImage instance is returned<br>
<br>
<br>
The following kwargs are allowed: if any of them are None, the<br>
corresponding image.* rc param value is used<br>
<br>
* cmap is a cm colormap instance, eg cm.jet. <br>
<br>
* aspect is one of: free or preserve<br>
<br>
* interpolation is one of: bicubic bilinear blackman100<br>
blackman256 blackman64 nearest sinc144 sinc256 sinc64 spline16<br>
or spline36<br>
<br>
* norm is a matplotlib.colors.Norm instance; default is<br>
normalization. This scales luminance -> 0-1<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.</tt></dd></dl>
<dl><dt><a name="Axes-in_axes"><strong>in_axes</strong></a>(self, xwin, ywin)</dt></dl>
<dl><dt><a name="Axes-legend"><strong>legend</strong></a>(self, *args, **kwargs)</dt><dd><tt>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<br>
specifying 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. You can set the label of a line by<br>
doing <a href="#Axes-plot">plot</a>(x, y, label='my data') or<br>
line.set_label('my data')<br>
<br>
<a href="#Axes-legend">legend</a>( LABELS )<br>
>>> <a href="#Axes-legend">legend</a>( ('label1', 'label2', 'label3') ) <br>
<br>
Make a legend for Line2D instances lines1, line2, line3<br>
<a href="#Axes-legend">legend</a>( LINES, LABELS )<br>
>>> <a href="#Axes-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3') )<br>
<br>
Make a legend at LOC<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),<br>
('label1', 'label2', 'label3'),<br>
loc=2)<br>
<br>
The LOC location codes are<br>
<br>
The location codes are<br>
<br>
'best' : 0, (currently not supported, defaults to upper right)<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</tt></dd></dl>
<dl><dt><a name="Axes-loglog"><strong>loglog</strong></a>(self, *args, **kwargs)</dt><dd><tt>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</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><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<br>
using rectangle patches using a colormap jet. Colormaps are<br>
avalible 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>
normalization functions are derived from<br>
matplotlib.colors.Norm<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<br>
square. Default 'faceteted'<br>
e.g., <br>
<a href="#Axes-pcolor">pcolor</a>(C, shading='flat') <br>
<a href="#Axes-pcolor">pcolor</a>(X, Y, C, shading='faceted')<br>
<br>
returns a list of patch objects<br>
<br>
Note, the behavior of meshgrid in matlab is a bit<br>
counterintuitive for 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 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-pcolor_classic"><strong>pcolor_classic</strong></a>(self, *args, **kwargs)</dt><dd><tt><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<br>
using rectangle patches using a colormap jet. Colormaps are<br>
avalible 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>
normalization functions are derived from<br>
matplotlib.colors.Norm<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<br>
square. Default 'faceteted'<br>
e.g., <br>
<a href="#Axes-pcolor">pcolor</a>(C, shading='flat') <br>
<a href="#Axes-pcolor">pcolor</a>(X, Y, C, shading='faceted')<br>
<br>
returns a list of patch objects<br>
<br>
Note, the behavior of meshgrid in matlab is a bit<br>
counterintuitive for 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 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-plot"><strong>plot</strong></a>(self, *args, **kwargs)</dt><dd><tt>Emulate matlab's plot command. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional<br>
format string. For example, all of the following are legal,<br>
assuming a is the Axis instance:<br>
<br>
a.<a href="#Axes-plot">plot</a>(x,y) # plot Numeric arrays y vs x<br>
a.<a href="#Axes-plot">plot</a>(x,y, 'bo') # plot Numeric arrays y vs x with blue circles<br>
a.<a href="#Axes-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
a.<a href="#Axes-plot">plot</a>(y, 'r+') # ditto with red plusses<br>
<br>
An arbitrary number of x, y, fmt groups can be specified, as in <br>
a.<a href="#Axes-plot">plot</a>(x1, y1, 'g^', x2, y2, 'l-') <br>
<br>
Returns a list of lines that were added</tt></dd></dl>
<dl><dt><a name="Axes-plot_date"><strong>plot_date</strong></a>(self, d, y, converter, fmt<font color="#909090">='bo'</font>, **kwargs)</dt><dd><tt><a href="#Axes-plot_date">plot_date</a>(d, y, converter, fmt='bo', **kwargs)<br>
<br>
d is a sequence of dates; converter is a dates.DateConverter<br>
instance that converts your dates to seconds since the epoch for<br>
plotting. y are the y values at those dates. fmt is a plot<br>
format string. kwargs are passed on to plot. See plot for more<br>
information.<br>
<br>
pass converter = None if your dates are already in epoch format</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>The power spectral density by Welches average periodogram method.<br>
The vector x is divided into NFFT length segments. Each segment<br>
is 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<br>
the sampling frequency.<br>
<br>
-- NFFT must be a power of 2<br>
<br>
-- detrend and window are functions, unlike in matlab where they<br>
are vectors. For detrending you can use detrend_none,<br>
detrend_mean, detrend_linear or a custom function. For<br>
windowing, you can use window_none, window_hanning, or a custom<br>
function<br>
<br>
-- if length x < NFFT, it will be zero padded to NFFT<br>
<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>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="Axes-scatter"><strong>scatter</strong></a>(self, x, y, s<font color="#909090">=3</font>, c<font color="#909090">='b'</font>, marker<font color="#909090">='o'</font>, cmap<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>)</dt><dd><tt>Make a scatter plot of x versus y. s is a size in points^2 a<br>
scalar or an array of the same length as x or y. c is a color<br>
and can be a single color format string or an length(x) array<br>
of intensities which will be mapped by the<br>
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' : octogon<br>
<br>
s is a size argument in points squared.<br>
<br>
if cmap is None, default to the current rc params cmap</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>Make a scatter plot of x versus y. s is a size (in data<br>
coords) and can be either a scalar or an array of the same<br>
length as x or y. c is a color and can be a single color<br>
format string or an length(x) array of intensities which will<br>
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>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<br>
more info</tt></dd></dl>
<dl><dt><a name="Axes-semilogy"><strong>semilogy</strong></a>(self, *args, **kwargs)</dt><dd><tt>Make a semilog plot with log scaling on the y axis. The args to<br>
semilog x are the same as the args to plot. See help plot for<br>
more info</tt></dd></dl>
<dl><dt><a name="Axes-set_axis_bgcolor"><strong>set_axis_bgcolor</strong></a>(self, color)</dt></dl>
<dl><dt><a name="Axes-set_axis_off"><strong>set_axis_off</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-set_axis_on"><strong>set_axis_on</strong></a>(self)</dt></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 with boolean b</tt></dd></dl>
<dl><dt><a name="Axes-set_image_extent"><strong>set_image_extent</strong></a>(self, xmin, xmax, ymin, ymax)</dt><dd><tt>Set the data units of the image. This is useful if you want to<br>
plot other things over the image, eg, lines or scatter</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</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 the title for the xaxis<br>
<br>
See the text docstring for information of how override and the<br>
optional args work</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 the label for the xaxis<br>
<br>
See the text docstring for information of how override and the<br>
optional args work</tt></dd></dl>
<dl><dt><a name="Axes-set_xlim"><strong>set_xlim</strong></a>(self, v)</dt><dd><tt>Set the limits for the xaxis; v = [xmin, xmax]</tt></dd></dl>
<dl><dt><a name="Axes-set_xscale"><strong>set_xscale</strong></a>(self, value)</dt></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 the xtick labels with list of strings labels<br>
Return a list of axis text instances</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</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 the label for the yaxis<br>
<br>
Defaults override is<br>
<br>
override = {<br>
'fontproperties' : see FontProperties()<br>
'verticalalignment' : 'center',<br>
'horizontalalignment' : 'right',<br>
'rotation'='vertical' : }<br>
<br>
See the text doctstring for information of how override and<br>
the optional args work</tt></dd></dl>
<dl><dt><a name="Axes-set_ylim"><strong>set_ylim</strong></a>(self, v)</dt><dd><tt>Set the limits for the xaxis; v = [ymin, ymax]</tt></dd></dl>
<dl><dt><a name="Axes-set_yscale"><strong>set_yscale</strong></a>(self, value)</dt></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 the ytick labels with list of strings labels.<br>
Return a list of Text instances</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</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>)</dt><dd><tt>Compute a spectrogram of data in x. Data are split into NFFT<br>
length segements and the PSD of each section is computed. The<br>
windowing function window is applied to each segment, and the<br>
amount of overlap of each segment is specified with noverlap<br>
<br>
See help(psd) for information on the other arguments<br>
<br>
cmap is a colormap; if None use default determined by rc<br>
<br>
return value is Pxx, freqs, bins, im<br>
<br>
bins are the time points the spectrogram is calculated over<br>
freqs is an array of frequencies<br>
Pxx is a len(times) x len(freqs) array of power<br>
im is a matplotlib image</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>A stem plot plots vertical lines (using linefmt) at each x<br>
location from the baseline to y, and places a marker there using<br>
markerfmt. A 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>Create a table and add it to the axes. Returns a table<br>
instance. For finer grained control over tables, use the<br>
Table class and add it 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, text, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>Add text 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 default is<br>
<br>
If len(args) the override dictionary will be:<br>
<br>
'fontproperties' : see FontProperties<br>
'verticalalignment' : 'bottom',<br>
'horizontalalignment' : 'left'<br>
<br>
<br>
**kwargs can in turn be used to override the override, as in<br>
<br>
a.<a href="#Axes-text">text</a>(x,y,label, fontpropeties=FontProperties(size=12))<br>
<br>
will have verticalalignment=bottom and<br>
horizontalalignment=left but will have a fontsize of 12<br>
<br>
<br>
The Text defaults are<br>
'color' : 'k',<br>
'fontproperties' : see FontProperties<br>
'horizontalalignment' : 'left'<br>
'rotation' : 'horizontal',<br>
'verticalalignment' : 'bottom',<br>
'transform' : self.<strong>transData</strong>,<br>
<br>
the default transform specifies that text is in data coords,<br>
alternatively, you can specify text in axis coords (0,0 lower<br>
left and 1,1 upper right). The example below places text in<br>
the center of the axes<br>
<br>
ax = subplot(111)<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-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-vlines"><strong>vlines</strong></a>(self, x, ymin, ymax, color<font color="#909090">='k'</font>)</dt><dd><tt>Plot vertical lines at each x from ymin to ymax. ymin or ymax<br>
can be scalars or len(x) numpy arrays. If they are scalars,<br>
then the respective values are constant, else the heights of<br>
the lines are 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>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<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<br>
all backends</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_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-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-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</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</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</tt></dd></dl>
<dl><dt><a name="Axes-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the figure instance the artist belong to</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</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</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</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>
</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#Axes">Axes</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Emulate matlab's 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#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>
<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></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></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)<br>
<br>
Make a bar plot with rectangles at<br>
left, left+width, 0, height<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>
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-cla"><strong>cla</strong></a>(self)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="Subplot-clear"><strong>clear</strong></a>(self)</dt></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 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. See the docs for psd and csd for information<br>
about the function arguments NFFT, detrend, windowm noverlap, as<br>
well as the methods used to compute Pxy, Pxx and Pyy.<br>
<br>
Returns the tuple Cxy, freqs<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-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>The cross spectral density Pxy by Welches average periodogram<br>
method. The vectors x and y are divided into NFFT length<br>
segments. Each segment is detrended by function detrend and<br>
windowed by function window. noverlap gives the length of the<br>
overlap between segments. The product of the direct FFTs of x and<br>
y are averaged over each segment to compute Pxy, with a scaling to<br>
correct for power loss due to windowing. Fs is the sampling<br>
frequency.<br>
<br>
NFFT must be a power of 2<br>
<br>
detrend and window are functions, unlike in matlab where they are<br>
vectors. For detrending you can use detrend_none, detrend_mean,<br>
detrend_linear or a custom function. For windowing, you can use<br>
window_none, window_hanning, or a custom function<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-draw"><strong>draw</strong></a>(self, renderer, *args, **kwargs)</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">='k'</font>, capsize<font color="#909090">=3</font>)</dt><dd><tt>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>
a rank-0, Nx1 Numpy array - symmetric errorbars +/- value<br>
an N-element list or tuple - symmetric errorbars +/- value<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>
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.<br>
<br>
capsize is the size of the error bar caps in points</tt></dd></dl>
<dl><dt><a name="Subplot-fill"><strong>fill</strong></a>(self, *args, **kwargs)</dt><dd><tt>Emulate matlab's fill command. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional<br>
color format string. For example, all of the following are<br>
legal, assuming a is the Axis instance:<br>
<br>
a.<a href="#Subplot-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
a.<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>
a.<a href="#Subplot-fill">fill</a>(x1, y1, 'g', x2, y2, 'r') <br>
<br>
Returns a list of patches that were added.</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></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></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></dl>
<dl><dt><a name="Subplot-get_position"><strong>get_position</strong></a>(self)</dt><dd><tt>Return the axes position</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_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_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)</dt><dd><tt>Set the axes grids on or off; b is a boolean</tt></dd></dl>
<dl><dt><a name="Subplot-has_data"><strong>has_data</strong></a>(self)</dt></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>)</dt><dd><tt>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>
if noplot is True, just compute the histogram and return the<br>
number of observations and the bins as an (n, bins) tuple.<br>
<br>
If noplot is False, compute the histogram and plot it, returning<br>
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)</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>plot horizontal lines at each y from xmin to xmax. xmin or<br>
xmax can be scalars or len(x) numpy arrays. If they are<br>
scalars, then the respective values are constant, else the<br>
widths of the lines are 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>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>, origin<font color="#909090">=None</font>)</dt><dd><tt>Display the image in array X to current axes. X must be a<br>
float array<br>
<br>
If X is MxN, assume luminance (grayscale)<br>
If X is MxNx3, assume RGB<br>
If X is MxNx4, assume RGBA<br>
<br>
A matplotlib.image.AxesImage instance is returned<br>
<br>
<br>
The following kwargs are allowed: if any of them are None, the<br>
corresponding image.* rc param value is used<br>
<br>
* cmap is a cm colormap instance, eg cm.jet. <br>
<br>
* aspect is one of: free or preserve<br>
<br>
* interpolation is one of: bicubic bilinear blackman100<br>
blackman256 blackman64 nearest sinc144 sinc256 sinc64 spline16<br>
or spline36<br>
<br>
* norm is a matplotlib.colors.Norm instance; default is<br>
normalization. This scales luminance -> 0-1<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.</tt></dd></dl>
<dl><dt><a name="Subplot-in_axes"><strong>in_axes</strong></a>(self, xwin, ywin)</dt></dl>
<dl><dt><a name="Subplot-legend"><strong>legend</strong></a>(self, *args, **kwargs)</dt><dd><tt>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<br>
specifying 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. You can set the label of a line by<br>
doing <a href="#Subplot-plot">plot</a>(x, y, label='my data') or<br>
line.set_label('my data')<br>
<br>
<a href="#Subplot-legend">legend</a>( LABELS )<br>
>>> <a href="#Subplot-legend">legend</a>( ('label1', 'label2', 'label3') ) <br>
<br>
Make a legend for Line2D instances lines1, line2, line3<br>
<a href="#Subplot-legend">legend</a>( LINES, LABELS )<br>
>>> <a href="#Subplot-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3') )<br>
<br>
Make a legend at LOC<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),<br>
('label1', 'label2', 'label3'),<br>
loc=2)<br>
<br>
The LOC location codes are<br>
<br>
The location codes are<br>
<br>
'best' : 0, (currently not supported, defaults to upper right)<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</tt></dd></dl>
<dl><dt><a name="Subplot-loglog"><strong>loglog</strong></a>(self, *args, **kwargs)</dt><dd><tt>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</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><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<br>
using rectangle patches using a colormap jet. Colormaps are<br>
avalible 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>
normalization functions are derived from<br>
matplotlib.colors.Norm<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<br>
square. Default 'faceteted'<br>
e.g., <br>
<a href="#Subplot-pcolor">pcolor</a>(C, shading='flat') <br>
<a href="#Subplot-pcolor">pcolor</a>(X, Y, C, shading='faceted')<br>
<br>
returns a list of patch objects<br>
<br>
Note, the behavior of meshgrid in matlab is a bit<br>
counterintuitive for 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 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-pcolor_classic"><strong>pcolor_classic</strong></a>(self, *args, **kwargs)</dt><dd><tt><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<br>
using rectangle patches using a colormap jet. Colormaps are<br>
avalible 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>
normalization functions are derived from<br>
matplotlib.colors.Norm<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<br>
square. Default 'faceteted'<br>
e.g., <br>
<a href="#Subplot-pcolor">pcolor</a>(C, shading='flat') <br>
<a href="#Subplot-pcolor">pcolor</a>(X, Y, C, shading='faceted')<br>
<br>
returns a list of patch objects<br>
<br>
Note, the behavior of meshgrid in matlab is a bit<br>
counterintuitive for 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 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-plot"><strong>plot</strong></a>(self, *args, **kwargs)</dt><dd><tt>Emulate matlab's plot command. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional<br>
format string. For example, all of the following are legal,<br>
assuming a is the Axis instance:<br>
<br>
a.<a href="#Subplot-plot">plot</a>(x,y) # plot Numeric arrays y vs x<br>
a.<a href="#Subplot-plot">plot</a>(x,y, 'bo') # plot Numeric arrays y vs x with blue circles<br>
a.<a href="#Subplot-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
a.<a href="#Subplot-plot">plot</a>(y, 'r+') # ditto with red plusses<br>
<br>
An arbitrary number of x, y, fmt groups can be specified, as in <br>
a.<a href="#Subplot-plot">plot</a>(x1, y1, 'g^', x2, y2, 'l-') <br>
<br>
Returns a list of lines that were added</tt></dd></dl>
<dl><dt><a name="Subplot-plot_date"><strong>plot_date</strong></a>(self, d, y, converter, fmt<font color="#909090">='bo'</font>, **kwargs)</dt><dd><tt><a href="#Subplot-plot_date">plot_date</a>(d, y, converter, fmt='bo', **kwargs)<br>
<br>
d is a sequence of dates; converter is a dates.DateConverter<br>
instance that converts your dates to seconds since the epoch for<br>
plotting. y are the y values at those dates. fmt is a plot<br>
format string. kwargs are passed on to plot. See plot for more<br>
information.<br>
<br>
pass converter = None if your dates are already in epoch format</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>The power spectral density by Welches average periodogram method.<br>
The vector x is divided into NFFT length segments. Each segment<br>
is 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<br>
the sampling frequency.<br>
<br>
-- NFFT must be a power of 2<br>
<br>
-- detrend and window are functions, unlike in matlab where they<br>
are vectors. For detrending you can use detrend_none,<br>
detrend_mean, detrend_linear or a custom function. For<br>
windowing, you can use window_none, window_hanning, or a custom<br>
function<br>
<br>
-- if length x < NFFT, it will be zero padded to NFFT<br>
<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>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)</tt></dd></dl>
<dl><dt><a name="Subplot-scatter"><strong>scatter</strong></a>(self, x, y, s<font color="#909090">=3</font>, c<font color="#909090">='b'</font>, marker<font color="#909090">='o'</font>, cmap<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>)</dt><dd><tt>Make a scatter plot of x versus y. s is a size in points^2 a<br>
scalar or an array of the same length as x or y. c is a color<br>
and can be a single color format string or an length(x) array<br>
of intensities which will be mapped by the<br>
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' : octogon<br>
<br>
s is a size argument in points squared.<br>
<br>
if cmap is None, default to the current rc params cmap</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>Make a scatter plot of x versus y. s is a size (in data<br>
coords) and can be either a scalar or an array of the same<br>
length as x or y. c is a color and can be a single color<br>
format string or an length(x) array of intensities which will<br>
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>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<br>
more info</tt></dd></dl>
<dl><dt><a name="Subplot-semilogy"><strong>semilogy</strong></a>(self, *args, **kwargs)</dt><dd><tt>Make a semilog plot with log scaling on the y axis. The args to<br>
semilog x are the same as the args to plot. See help plot for<br>
more info</tt></dd></dl>
<dl><dt><a name="Subplot-set_axis_bgcolor"><strong>set_axis_bgcolor</strong></a>(self, color)</dt></dl>
<dl><dt><a name="Subplot-set_axis_off"><strong>set_axis_off</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-set_axis_on"><strong>set_axis_on</strong></a>(self)</dt></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 with boolean b</tt></dd></dl>
<dl><dt><a name="Subplot-set_image_extent"><strong>set_image_extent</strong></a>(self, xmin, xmax, ymin, ymax)</dt><dd><tt>Set the data units of the image. This is useful if you want to<br>
plot other things over the image, eg, lines or scatter</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</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 the title for the xaxis<br>
<br>
See the text docstring for information of how override and the<br>
optional args work</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 the label for the xaxis<br>
<br>
See the text docstring for information of how override and the<br>
optional args work</tt></dd></dl>
<dl><dt><a name="Subplot-set_xlim"><strong>set_xlim</strong></a>(self, v)</dt><dd><tt>Set the limits for the xaxis; v = [xmin, xmax]</tt></dd></dl>
<dl><dt><a name="Subplot-set_xscale"><strong>set_xscale</strong></a>(self, value)</dt></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 the xtick labels with list of strings labels<br>
Return a list of axis text instances</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</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 the label for the yaxis<br>
<br>
Defaults override is<br>
<br>
override = {<br>
'fontproperties' : see FontProperties()<br>
'verticalalignment' : 'center',<br>
'horizontalalignment' : 'right',<br>
'rotation'='vertical' : }<br>
<br>
See the text doctstring for information of how override and<br>
the optional args work</tt></dd></dl>
<dl><dt><a name="Subplot-set_ylim"><strong>set_ylim</strong></a>(self, v)</dt><dd><tt>Set the limits for the xaxis; v = [ymin, ymax]</tt></dd></dl>
<dl><dt><a name="Subplot-set_yscale"><strong>set_yscale</strong></a>(self, value)</dt></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 the ytick labels with list of strings labels.<br>
Return a list of Text instances</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</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>)</dt><dd><tt>Compute a spectrogram of data in x. Data are split into NFFT<br>
length segements and the PSD of each section is computed. The<br>
windowing function window is applied to each segment, and the<br>
amount of overlap of each segment is specified with noverlap<br>
<br>
See help(psd) for information on the other arguments<br>
<br>
cmap is a colormap; if None use default determined by rc<br>
<br>
return value is Pxx, freqs, bins, im<br>
<br>
bins are the time points the spectrogram is calculated over<br>
freqs is an array of frequencies<br>
Pxx is a len(times) x len(freqs) array of power<br>
im is a matplotlib image</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>A stem plot plots vertical lines (using linefmt) at each x<br>
location from the baseline to y, and places a marker there using<br>
markerfmt. A 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>Create a table and add it to the axes. Returns a table<br>
instance. For finer grained control over tables, use the<br>
Table class and add it 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, text, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>Add text 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 default is<br>
<br>
If len(args) the override dictionary will be:<br>
<br>
'fontproperties' : see FontProperties<br>
'verticalalignment' : 'bottom',<br>
'horizontalalignment' : 'left'<br>
<br>
<br>
**kwargs can in turn be used to override the override, as in<br>
<br>
a.<a href="#Subplot-text">text</a>(x,y,label, fontpropeties=FontProperties(size=12))<br>
<br>
will have verticalalignment=bottom and<br>
horizontalalignment=left but will have a fontsize of 12<br>
<br>
<br>
The Text defaults are<br>
'color' : 'k',<br>
'fontproperties' : see FontProperties<br>
'horizontalalignment' : 'left'<br>
'rotation' : 'horizontal',<br>
'verticalalignment' : 'bottom',<br>
'transform' : self.<strong>transData</strong>,<br>
<br>
the default transform specifies that text is in data coords,<br>
alternatively, you can specify text in axis coords (0,0 lower<br>
left and 1,1 upper right). The example below places text in<br>
the center of the axes<br>
<br>
ax = subplot(111)<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-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-vlines"><strong>vlines</strong></a>(self, x, ymin, ymax, color<font color="#909090">='k'</font>)</dt><dd><tt>Plot vertical lines at each x from ymin to ymax. ymin or ymax<br>
can be scalars or len(x) numpy arrays. If they are scalars,<br>
then the respective values are constant, else the heights of<br>
the lines are 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>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<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<br>
all backends</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_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-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-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</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</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</tt></dd></dl>
<dl><dt><a name="Subplot-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the figure instance the artist belong to</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</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</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</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>
</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="-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>
</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>False</strong> = False<br>
<strong>Float</strong> = 'd'<br>
<strong>IDENTITY</strong> = 0<br>
<strong>LOG10</strong> = 1<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>True</strong> = True<br>
<strong>absolute</strong> = <ufunc 'absolute'><br>
<strong>colorConverter</strong> = <matplotlib.colors.ColorConverter instance><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}<br>
<strong>log10</strong> = <ufunc 'log10'><br>
<strong>rcParams</strong> = {'axes.edgecolor': 'k', 'axes.facecolor': 'w', 'axes.grid': False, 'axes.hold': True, 'axes.labelcolor': 'k', 'axes.labelsize': 12.0, 'axes.linewidth': 1.0, 'axes.titlesize': 14.0, 'backend': 'GTKAgg', 'datapath': '/usr/local/share/matplotlib', ...}</td></tr></table>
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