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<font color="#ffffff" face="helvetica, arial"> <br><big><big><strong><a href="matplotlib.html"><font color="#ffffff">matplotlib</font></a>.pylab</strong></big></big></font></td
><td align=right valign=bottom
><font color="#ffffff" face="helvetica, arial"><a href=".">index</a><br><a href="file:/usr/local/lib/python2.3/site-packages/matplotlib/pylab.py">/usr/local/lib/python2.3/site-packages/matplotlib/pylab.py</a></font></td></tr></table>
<p><tt>This is a matlab(TM) style interface to matplotlib.<br>
<br>
The following plotting commands are provided; some of these do not<br>
exist in matlab(TM) but have proven themselves to be useful nonetheless.<br>
The majority of them, however, have matlab analogs<br>
<br>
_Plotting commands<br>
<br>
axes - Create a new axes<br>
axhline - draw a horizontal line across axes<br>
axvline - draw a vertical line across axes<br>
axhspan - draw a horizontal bar across axes<br>
axvspan - draw a vertical bar across axes <br>
axis - Set or return the current axis limits<br>
bar - make a bar chart<br>
barh - a horizontal bar chart <br>
cla - clear current axes<br>
clf - clear a figure window<br>
clim - adjust the color limits of the current image<br>
close - close a figure window<br>
colorbar - add a colorbar to the current figure<br>
cohere - make a plot of coherence<br>
contour - make a contour plot<br>
csd - make a plot of cross spectral density <br>
delaxes - delete an axes from the current figure<br>
draw - Force a redraw of the current figure<br>
errorbar - make an errorbar graph<br>
figlegend - make legend on the figure rather than the axes<br>
figimage - make a figure image<br>
figtext - add text in figure coords<br>
figure - create or change active figure<br>
fill - make filled polygons<br>
gca - return the current axes<br>
gcf - return the current figure<br>
gci - get the current image, or None<br>
get - get a handle graphics property<br>
grid - set whether gridding is on<br>
hist - make a histogram<br>
hold - set the axes hold state<br>
ioff - turn interaction mode off<br>
ion - turn interaction mode on<br>
isinteractive - return True if interaction mode is on<br>
imread - load image file into array<br>
imshow - plot image data<br>
ishold - return the hold state of the current axes<br>
legend - make an axes legend<br>
loglog - a log log plot<br>
pcolor - make a pseudocolor plot<br>
pie - make a pie chart<br>
plot - make a line plot<br>
pie - pie charts<br>
polar - make a polar plot on a PolarAxes<br>
psd - make a plot of power spectral density<br>
rc - control the default params<br>
rgrids - customize the radial grids and labels for polar <br>
savefig - save the current figure<br>
scatter - make a scatter plot<br>
set - set a handle graphics property<br>
semilogx - log x axis<br>
semilogy - log y axis<br>
show - show the figures<br>
specgram - a spectrogram plot<br>
spy - plot sparsity pattern using markers<br>
spy2 - plot sparsity pattern using image<br>
stem - make a stem plot<br>
subplot - make a subplot (numrows, numcols, axesnum)<br>
table - add a table to the plot<br>
text - add some text at location x,y to the current axes<br>
thetagrids - customize the radial theta grids and labels for polar <br>
title - add a title to the current axes<br>
xlim - set/get the xlimits<br>
ylim - set/get the ylimits<br>
xticks - set/get the xticks<br>
yticks - set/get the yticks<br>
xlabel - add an xlabel to the current axes<br>
ylabel - add a ylabel to the current axes<br>
<br>
autumn - set the default colormap to autumn<br>
bone - set the default colormap to bone <br>
cool - set the default colormap to cool <br>
copper - set the default colormap to copper<br>
flag - set the default colormap to flag <br>
gray - set the default colormap to gray <br>
hot - set the default colormap to hot <br>
hsv - set the default colormap to hsv <br>
jet - set the default colormap to jet <br>
pink - set the default colormap to pink <br>
prism - set the default colormap to prism <br>
spring - set the default colormap to spring<br>
summer - set the default colormap to summer<br>
winter - set the default colormap to winter<br>
<br>
_Event handling<br>
<br>
connect - register an event handler<br>
disconnect - remove a connected event handler<br>
<br>
_Matrix commands<br>
<br>
cumprod - the cumulative product along a dimension<br>
cumsum - the cumulative sum along a dimension<br>
detrend - remove the mean or besdt fit line from an array<br>
diag - the k-th diagonal of matrix <br>
diff - the n-th differnce of an array<br>
eig - the eigenvalues and eigen vectors of v<br>
eye - a matrix where the k-th diagonal is ones, else zero <br>
find - return the indices where a condition is nonzero <br>
fliplr - flip the rows of a matrix up/down<br>
flipud - flip the columns of a matrix left/right<br>
linspace - a linear spaced vector of N values from min to max inclusive<br>
meshgrid - repeat x and y to make regular matrices<br>
ones - an array of ones<br>
rand - an array from the uniform distribution [0,1]<br>
randn - an array from the normal distribution<br>
rot90 - rotate matrix k*90 degress counterclockwise<br>
squeeze - squeeze an array removing any dimensions of length 1<br>
tri - a triangular matrix<br>
tril - a lower triangular matrix<br>
triu - an upper triangular matrix<br>
vander - the Vandermonde matrix of vector x<br>
svd - singular value decomposition<br>
zeros - a matrix of zeros<br>
<br>
_Probability<br>
<br>
levypdf - The levy probability density function from the char. func.<br>
normpdf - The Gaussian probability density function<br>
rand - random numbers from the uniform distribution<br>
randn - random numbers from the normal distribution<br>
<br>
_Statistics<br>
<br>
corrcoef - correlation coefficient<br>
cov - covariance matrix<br>
max - the maximum along dimension m<br>
mean - the mean along dimension m<br>
median - the median along dimension m<br>
min - the minimum along dimension m<br>
norm - the norm of vector x<br>
prod - the product along dimension m<br>
ptp - the max-min along dimension m<br>
std - the standard deviation along dimension m<br>
sum - the sum along dimension m<br>
<br>
_Time series analysis<br>
<br>
bartlett - M-point Bartlett window<br>
blackman - M-point Blackman window<br>
cohere - the coherence using average periodiogram<br>
csd - the cross spectral density using average periodiogram<br>
fft - the fast Fourier transform of vector x<br>
hamming - M-point Hamming window<br>
hanning - M-point Hanning window<br>
hist - compute the histogram of x<br>
kaiser - M length Kaiser window<br>
psd - the power spectral density using average periodiogram<br>
sinc - the sinc function of array x<br>
<br>
_Dates<br>
<br>
date2num - convert python datetimes to numeric representation<br>
drange - create an array of numbers for date plots<br>
num2date - convert numeric type (float days since 0001) to datetime<br>
<br>
_Other<br>
<br>
angle - the angle of a complex array<br>
load - load ASCII data into array<br>
polyfit - fit x, y to an n-th order polynomial<br>
polyval - evaluate an n-th order polynomial<br>
roots - the roots of the polynomial coefficients in p<br>
save - save an array to an ASCII file<br>
trapz - trapezoidal integration<br>
<br>
__end<br>
<br>
Credits: The plotting commands were provided by<br>
John D. Hunter <jdhunter@ace.bsd.uhicago.edu><br>
<br>
Most of the other commands are from Numeric, MLab and FFT, with the<br>
exception of those in mlab.py provided by matplotlib.</tt></p>
<p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#aa55cc">
<td colspan=3 valign=bottom> <br>
<font color="#fffff" face="helvetica, arial"><big><strong>Modules</strong></big></font></td></tr>
<tr><td bgcolor="#aa55cc"><tt> </tt></td><td> </td>
<td width="100%"><table width="100%" summary="list"><tr><td width="25%" valign=top><a href="LinearAlgebra.html">LinearAlgebra</a><br>
<a href="MLab.html">MLab</a><br>
<a href="Numeric.html">Numeric</a><br>
<a href="RandomArray.html">RandomArray</a><br>
<a href="matplotlib._pylab_helpers.html">matplotlib._pylab_helpers</a><br>
<a href="matplotlib.cm.html">matplotlib.cm</a><br>
</td><td width="25%" valign=top><a href="copy.html">copy</a><br>
<a href="copy_reg.html">copy_reg</a><br>
<a href="matplotlib.image.html">matplotlib.image</a><br>
<a href="math.html">math</a><br>
<a href="matplotlib.html">matplotlib</a><br>
<a href="matplotlib.mlab.html">matplotlib.mlab</a><br>
</td><td width="25%" valign=top><a href="multiarray.html">multiarray</a><br>
<a href="matplotlib.numerix.html">matplotlib.numerix</a><br>
<a href="operator.html">operator</a><br>
<a href="os.html">os</a><br>
<a href="pickle.html">pickle</a><br>
<a href="random.html">random</a><br>
</td><td width="25%" valign=top><a href="re.html">re</a><br>
<a href="string.html">string</a><br>
<a href="sys.html">sys</a><br>
<a href="time.html">time</a><br>
<a href="types.html">types</a><br>
</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="-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="-arrayrange"><strong>arrayrange</strong></a> = arange(...)</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="-autumn"><strong>autumn</strong></a>()</dt><dd><tt>set the default colormap to autumn and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-axes"><strong>axes</strong></a>(*args, **kwargs)</dt><dd><tt>Add an axes at positon rect specified by::<br>
<br>
<a href="#-axes">axes</a>() by itself creates a default full <a href="#-subplot">subplot</a>(111) window axis<br>
<br>
<a href="#-axes">axes</a>(rect, axisbg='w') where rect=[left, bottom, width, height] in<br>
normalized (0,1) units. axisbg is the background color for the<br>
axis, default white<br>
<br>
<a href="#-axes">axes</a>(h) where h is an axes instance makes h the<br>
current axis An Axes instance is returned</tt></dd></dl>
<dl><dt><a name="-axhline"><strong>axhline</strong></a>(*args, **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="#-axhline">axhline</a>(linewidth=4, color='r')<br>
<br>
# draw a default hline at y=1 that spans the xrange<br>
<a href="#-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="#-axhline">axhline</a>(y=.5, xmin=0.25, xmax=0.75)<br>
<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-axhspan"><strong>axhspan</strong></a>(*args, **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="#-axhspan">axhspan</a>(0.25, 0.75, facecolor=0.5, alpha=0.5)<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-axis"><strong>axis</strong></a>(*v)</dt><dd><tt>Set/Get the axis properties::<br>
<br>
<a href="#-axis">axis</a>() returns the current axis as a length a length 4 vector<br>
<br>
<a href="#-axis">axis</a>(v) where v = [xmin, xmax, ymin, ymax] sets the min and max of the x<br>
and y axis limits<br>
<br>
<a href="#-axis">axis</a>('off') turns off the axis lines and labels<br>
<br>
<a href="#-axis">axis</a>('equal') sets the xlim width and ylim height to be to be<br>
identical. The longer of the two intervals is chosen</tt></dd></dl>
<dl><dt><a name="-axvline"><strong>axvline</strong></a>(*args, **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="#-axvline">axvline</a>(linewidth=4, color='r')<br>
<br>
# draw a default vline at x=1 that spans the yrange<br>
l = <a href="#-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="#-axvline">axvline</a>(x=.5, ymin=0.25, ymax=0.75)<br>
<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-axvspan"><strong>axvspan</strong></a>(*args, **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="#-axvspan">axvspan</a>(1.25, 1.55, facecolor='g', alpha=0.5)<br>
<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-bar"><strong>bar</strong></a>(*args, **kwargs)</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<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-barh"><strong>barh</strong></a>(*args, **kwargs)</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<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-bone"><strong>bone</strong></a>()</dt><dd><tt>set the default colormap to bone and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-choose"><strong>choose</strong></a>(...)</dt><dd><tt><a href="#-choose">choose</a>(a, (b1,b2,...))</tt></dd></dl>
<dl><dt><a name="-cla"><strong>cla</strong></a>(*args, **kwargs)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="-clf"><strong>clf</strong></a>()</dt><dd><tt>Clear the current figure</tt></dd></dl>
<dl><dt><a name="-clim"><strong>clim</strong></a>(vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>)</dt><dd><tt>Set the color limits of the current image<br>
<br>
To apply clim to all axes images do<br>
<br>
<a href="#-clim">clim</a>(0, 0.5)<br>
<br>
If either vmin or vmax is None, the image min/max respectively<br>
will be used for color scaling.<br>
<br>
If you want to set the clim of multiple images,<br>
use, for example for im in <a href="#-gca">gca</a>().get_images(): im.set_clim(0,<br>
0.05)</tt></dd></dl>
<dl><dt><a name="-close"><strong>close</strong></a>(*args)</dt><dd><tt>Close a figure window<br>
<br>
<a href="#-close">close</a>() by itself closes the current figure<br>
<br>
<a href="#-close">close</a>(num) closes figure number num<br>
<br>
<a href="#-close">close</a>(h) where h is a figure handle(instance) closes that figure<br>
<br>
<a href="#-close">close</a>('all') closes all the figure windows</tt></dd></dl>
<dl><dt><a name="-cohere"><strong>cohere</strong></a>(*args, **kwargs)</dt><dd><tt>COHERE(x, y, NFFT=256, Fs=2, detrend=mlab.detrend_none,<br>
window=mlab.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)<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-colorbar"><strong>colorbar</strong></a>(tickfmt<font color="#909090">='%1.1f'</font>)</dt><dd><tt>Create a colorbar for current mappable image (see gci)<br>
<br>
tickfmt is a format string to format the colorbar ticks<br>
<br>
return value is the colorbar axes instance</tt></dd></dl>
<dl><dt><a name="-colormaps"><strong>colormaps</strong></a>()</dt><dd><tt>matplotlib provides the following colormaps. <br>
<br>
autumn bone cool copper flag gray hot hsv jet pink prism<br>
spring summer winter<br>
<br>
You can set the colormap for an image, pcolor, scatter, etc,<br>
either as a keyword argument<br>
<br>
>>> <a href="#-imshow">imshow</a>(X, cmap=cm.hot)<br>
<br>
or post-hoc using the corresponding pylab interface function<br>
<br>
>>> <a href="#-imshow">imshow</a>(X)<br>
>>> <a href="#-hot">hot</a>()<br>
>>> <a href="#-jet">jet</a>()<br>
<br>
In interactive mode, this will update the colormap allowing you to<br>
see which one works best for your data.</tt></dd></dl>
<dl><dt><a name="-colors"><strong>colors</strong></a>()</dt><dd><tt>This is a do nothing function to provide you with help on how<br>
matplotlib handles colors.<br>
<br>
Commands which take color arguments can use several formats to<br>
specify the colors. For the basic builtin colors, you can use a<br>
single letter<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>
<br>
For a greater range of colors, you have two options. You can<br>
specify the color using an html hex string, as in<br>
<br>
color = '#eeefff'<br>
<br>
or you can pass an R,G,B tuple, where each of R,G,B are in the<br>
range [0,1].<br>
<br>
You can also use any legal html name for a color, like 'red',<br>
'burlywood' and 'chartreuse'<br>
<br>
The example below creates a subplot with a dark<br>
slate gray background<br>
<br>
<a href="#-subplot">subplot</a>(111, axisbg=(0.1843, 0.3098, 0.3098))<br>
<br>
Here is an example that creates a pale turqoise title<br>
<br>
<a href="#-title">title</a>('Is this the best color?', color='#afeeee')</tt></dd></dl>
<dl><dt><a name="-connect"><strong>connect</strong></a>(s, func)</dt><dd><tt>Connect event with string s to func. The signature of func is<br>
<br>
def func(event)<br>
<br>
where event is a MplEvent. The following events are recognized<br>
<br>
'key_press_event' <br>
'button_press_event' <br>
'button_release_event' <br>
'motion_notify_event' <br>
<br>
For the three events above, if the mouse is over the axes,<br>
the variable event.inaxes will be set to the axes it is over,<br>
and additionally, the variables event.xdata and event.ydata<br>
will be defined. This is the mouse location in data coords.<br>
See backend_bases.MplEvent.<br>
<br>
return value is a connection id that can be used with<br>
mpl_disconnect</tt></dd></dl>
<dl><dt><a name="-contour"><strong>contour</strong></a>(*args, **kwargs)</dt><dd><tt>CONTOUR(z, x = None, y = None, levels = None, colors = None)<br>
<br>
plots contour lines of an image z<br>
<br>
z is a 2D array of image values<br>
x and y are 2D arrays with coordinates of z values in the<br>
two directions. x and y do not need to be evenly spaced but must<br>
be of the same shape as z<br>
<br>
levels can be a list of level values or the number of levels to be<br>
plotted. If levels == None, a default number of 7 evenly spaced<br>
levels is plotted.<br>
<br>
colors is one of these:<br>
<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 color for lines.color in<br>
.matplotlibrc is used.<br>
<br>
linewidths is one of:<br>
<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>
<br>
<br>
reg is a 2D region number array with the same dimensions as x and<br>
y. 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>
alpha : the default transparency of contour lines<br>
<br>
fmt is a format string for adding a label to each collection.<br>
Currently this is useful for auto-legending and may be useful down<br>
the road for legend labeling<br>
<br>
origin = 'upper'|'lower'|None. If None, the rc value for image.origin<br>
will be used<br>
<br>
More information on reg and triangle arrays is in _contour.c<br>
<br>
Return value is levels, collections where levels is a list of contour<br>
levels used and collections is a list of<br>
matplotlib.collections.LineCollection instances<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-cool"><strong>cool</strong></a>()</dt><dd><tt>set the default colormap to cool and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-copper"><strong>copper</strong></a>()</dt><dd><tt>set the default colormap to copper and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-cross_correlate"><strong>cross_correlate</strong></a>(...)</dt><dd><tt><a href="#-cross_correlate">cross_correlate</a>(a,v, mode=0)</tt></dd></dl>
<dl><dt><a name="-csd"><strong>csd</strong></a>(*args, **kwargs)</dt><dd><tt>CSD(x, y, NFFT=256, Fs=2, detrend=mlab.detrend_none,<br>
window=mlab.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)<br>
<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-delaxes"><strong>delaxes</strong></a>(*args)</dt><dd><tt><a href="#-delaxes">delaxes</a>(ax) - remove ax from the current figure. If ax doesn't<br>
exist an error will be raised.<br>
<br>
<a href="#-delaxes">delaxes</a>(): delete the current axes</tt></dd></dl>
<dl><dt><a name="-disconnect"><strong>disconnect</strong></a>(cid)</dt><dd><tt>Connect s to func. return an id that can be used with disconnect<br>
Method should return None</tt></dd></dl>
<dl><dt><a name="-draw"><strong>draw</strong></a>()</dt><dd><tt>redraw the current figure</tt></dd></dl>
<dl><dt><a name="-errorbar"><strong>errorbar</strong></a>(*args, **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.<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-figimage"><strong>figimage</strong></a>(*args, **kwargs)</dt><dd><tt>FIGIMAGE(X) # add non-resampled array to figure<br>
<br>
FIGIMAGE(X, xo, yo) # with pixel offsets<br>
<br>
FIGIMAGE(X, **kwargs) # control interpolation ,scaling, etc<br>
<br>
Add a nonresampled figure to the figure from array X. xo and yo are<br>
offsets in pixels<br>
<br>
X must be a 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>
The following kwargs are allowed: <br>
<br>
* cmap is a cm colormap instance, eg cm.jet. If None, default to<br>
the rc image.cmap valuex<br>
<br>
* norm is a matplotlib.colors.normalize instance; default is<br>
normalization(). This scales luminance -> 0-1<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. Defaults to the rc image.origin value<br>
<br>
This complements the axes image which will be resampled to fit the<br>
current axes. If you want a resampled image to fill the entire<br>
figure, you can define an Axes with size [0,1,0,1].<br>
<br>
A image.FigureImage instance is returned.<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-figlegend"><strong>figlegend</strong></a>(handles, labels, loc, **kwargs)</dt><dd><tt>Place a legend in the figure. Labels are a sequence of<br>
strings, handles is a sequence of line or patch instances, and<br>
loc can be a string r an integer specifying the legend<br>
location<br>
<br>
USAGE: <br>
<a href="#-legend">legend</a>( (line1, line2, line3),<br>
('label1', 'label2', 'label3'),<br>
'upper right')<br>
<br>
See help(legend) for information about the location codes<br>
<br>
A matplotlib.legend.Legend instance is returned</tt></dd></dl>
<dl><dt><a name="-figtext"><strong>figtext</strong></a>(*args, **kwargs)</dt><dd><tt>Add text to figure at location x,y (relative 0-1 coords) See<br>
the help for Axis text for the meaning of the other arguments</tt></dd></dl>
<dl><dt><a name="-figure"><strong>figure</strong></a>(num<font color="#909090">=1</font>, figsize<font color="#909090">=None</font>, dpi<font color="#909090">=None</font>, facecolor<font color="#909090">=None</font>, edgecolor<font color="#909090">=None</font>, frameon<font color="#909090">=True</font>)</dt><dd><tt><a href="#-figure">figure</a>(num = 1, figsize=(8, 6), dpi=80, facecolor='w', edgecolor='k')<br>
<br>
<br>
Create a new figure and return a handle to it<br>
<br>
If <a href="#-figure">figure</a>(num) already exists, make it active and return the<br>
handle to it.<br>
<br>
<a href="#-figure">figure</a>(1)<br>
<br>
figsize - width in height x inches; defaults to rc figure.figsize<br>
dpi - resolution; defaults to rc figure.dpi<br>
facecolor - the background color; defaults to rc figure.facecolor<br>
edgecolor - the border color; defaults to rc figure.edgecolor<br>
<br>
rcParams gives the default values from the .matplotlibrc file</tt></dd></dl>
<dl><dt><a name="-fill"><strong>fill</strong></a>(*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="#-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
ax.<a href="#-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="#-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.<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-flag"><strong>flag</strong></a>()</dt><dd><tt>set the default colormap to flag and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-fromstring"><strong>fromstring</strong></a>(...)</dt><dd><tt><a href="#-fromstring">fromstring</a>(string, typecode='l', count=-1) returns a new 1d array initialized from the raw binary data in string. If count is positive, the new array will have count elements, otherwise it's size is determined by the size of string.</tt></dd></dl>
<dl><dt><a name="-gca"><strong>gca</strong></a>(**kwargs)</dt><dd><tt>Return the current axis instance. This can be used to control<br>
axis properties either using set or the Axes methods.<br>
<br>
Example:<br>
<br>
<a href="#-plot">plot</a>(t,s)<br>
<a href="#-set">set</a>(<a href="#-gca">gca</a>(), 'xlim', [0,10]) # set the x axis limits<br>
<br>
or<br>
<br>
<a href="#-plot">plot</a>(t,s)<br>
a = <a href="#-gca">gca</a>()<br>
a.set_xlim([0,10]) # does the same</tt></dd></dl>
<dl><dt><a name="-gcf"><strong>gcf</strong></a>()</dt><dd><tt>Return a handle to the current figure</tt></dd></dl>
<dl><dt><a name="-gci"><strong>gci</strong></a>()</dt><dd><tt>get the current ScalarMappable instance (image or patch<br>
collection), or None if no images or patch collecitons have been<br>
defined. The commands imshow and figimage create images<br>
instances, and the commands pcolor and scatter create patch<br>
collection instances</tt></dd></dl>
<dl><dt><a name="-get"><strong>get</strong></a>(o, *args)</dt><dd><tt>Return the value of handle property s<br>
<br>
h is an instance of a class, eg a Line2D or an Axes or Text.<br>
if s is 'somename', this function returns<br>
<br>
o.get_somename()<br>
<br>
get can be used to query all the gettable properties with <a href="#-get">get</a>(o)<br>
Many properties have aliases for shorter typing, eg 'lw' is an<br>
alias for 'linewidth'. In the output, aliases and full property<br>
names will be listed as<br>
<br>
property or alias = value<br>
<br>
eg<br>
<br>
linewidth or lw = 2</tt></dd></dl>
<dl><dt><a name="-get_current_fig_manager"><strong>get_current_fig_manager</strong></a>()</dt></dl>
<dl><dt><a name="-get_plot_commands"><strong>get_plot_commands</strong></a>()</dt></dl>
<dl><dt><a name="-gray"><strong>gray</strong></a>()</dt><dd><tt>set the default colormap to gray and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-grid"><strong>grid</strong></a>(*args, **kwargs)</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="-hist"><strong>hist</strong></a>(*args, **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>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-hlines"><strong>hlines</strong></a>(*args, **kwargs)</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<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-hold"><strong>hold</strong></a>(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="#-hold">hold</a>() # toggle hold<br>
<a href="#-hold">hold</a>(True) # hold is on<br>
<a href="#-hold">hold</a>(False) # hold is off</tt></dd></dl>
<dl><dt><a name="-hot"><strong>hot</strong></a>()</dt><dd><tt>set the default colormap to hot and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-hsv"><strong>hsv</strong></a>()</dt><dd><tt>set the default colormap to hsv and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-imread"><strong>imread</strong></a>(*args, **kwargs)</dt><dd><tt>return image file in fname as numerix array<br>
<br>
Return value is a MxNx4 array of 0-1 normalized floats</tt></dd></dl>
<dl><dt><a name="-imshow"><strong>imshow</strong></a>(*args, **kwargs)</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<br>
<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-ioff"><strong>ioff</strong></a>()</dt><dd><tt>turn interactive mode off</tt></dd></dl>
<dl><dt><a name="-ion"><strong>ion</strong></a>()</dt><dd><tt>turn interactive mode on</tt></dd></dl>
<dl><dt><a name="-ishold"><strong>ishold</strong></a>()</dt><dd><tt>Return the hold status of the current axes</tt></dd></dl>
<dl><dt><a name="-isinteractive"><strong>isinteractive</strong></a>()</dt><dd><tt>Return the interactive status</tt></dd></dl>
<dl><dt><a name="-jet"><strong>jet</strong></a>()</dt><dd><tt>set the default colormap to jet and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-legend"><strong>legend</strong></a>(*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="#-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="#-plot">plot</a>(x, y, label='my data') or line.set_label('my<br>
data')<br>
<br>
# automatically generate the legend from labels<br>
<a href="#-legend">legend</a>( ('label1', 'label2', 'label3') ) <br>
<br>
# Make a legend for a list of lines and labels<br>
<a href="#-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="#-legend">legend</a>( LABELS, LOC ) or<br>
# <a href="#-legend">legend</a>( LINES, LABELS, LOC )<br>
<a href="#-legend">legend</a>( ('label1', 'label2', 'label3'), loc='upper left')<br>
<a href="#-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3'), loc=2)<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. 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="-load"><strong>load</strong></a>(fname)</dt><dd><tt>Load ASCII data from fname into an array and return the array.<br>
<br>
The data must be regular, same number of values in every row<br>
<br>
fname can be a filename or a file handle<br>
<br>
matfile data is not currently supported, but see<br>
Nigel Wade's matfile <a href="ftp://ion.le.ac.uk/matfile/matfile.tar.gz">ftp://ion.le.ac.uk/matfile/matfile.tar.gz</a><br>
<br>
Example usage:<br>
<br>
x,y = <a href="#-load">load</a>('test.dat') # data in two columns<br>
<br>
X = <a href="#-load">load</a>('test.dat') # a matrix of data<br>
<br>
x = <a href="#-load">load</a>('test.dat') # a single column of data</tt></dd></dl>
<dl><dt><a name="-loglog"><strong>loglog</strong></a>(*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 range(2,basex)<br>
<br>
* basey: base of the y logarithm<br>
<br>
* subsy: the location of the minor yticks; None defaults to range(2,basey) <br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-over"><strong>over</strong></a>(func, *args, **kwargs)</dt><dd><tt>Call func(*args, **kwargs) with <a href="#-hold">hold</a>(True) and then restore the hold state</tt></dd></dl>
<dl><dt><a name="-pcolor"><strong>pcolor</strong></a>(*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="#-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="#-pcolor">pcolor</a>(X, Y, transpose(Z))<br>
<br>
Likewise, for nonsquare Z,<br>
<br>
<a href="#-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<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-pcolor_classic"><strong>pcolor_classic</strong></a>(*args, **kwargs)</dt><dd><tt>PCOLOR_CLASSIC(self, *args, **kwargs)<br>
<br>
Function signatures<br>
<br>
<a href="#-pcolor">pcolor</a>(C) - make a pseudocolor plot of matrix C<br>
<br>
<a href="#-pcolor">pcolor</a>(X, Y, C) - a pseudo color plot of C on the matrices X and Y <br>
<br>
<a href="#-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="#-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="#-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="#-pcolor">pcolor</a>(C, shading='flat') <a href="#-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="#-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="#-pcolor">pcolor</a>(X, Y, transpose(Z))<br>
<br>
Likewise, for nonsquare Z,<br>
<br>
<a href="#-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<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-pie"><strong>pie</strong></a>(*args, **kwargs)</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>
<a href="#-figure">figure</a>(figsize=(8,8))<br>
ax = <a href="#-axes">axes</a>([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<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-pink"><strong>pink</strong></a>()</dt><dd><tt>set the default colormap to pink and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-plot"><strong>plot</strong></a>(*args, **kwargs)</dt><dd><tt>PLOT(*args, **kwargs) <br>
<br>
Plot lines and/or markers to the Axes. *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="#-plot">plot</a>(x,y) # plot x and y using the default line style and color<br>
<a href="#-plot">plot</a>(x,y, 'bo') # plot x and y using blue circle markers<br>
<a href="#-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
<a href="#-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="#-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="#-plot">plot</a>([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)<br>
<a href="#-plot">plot</a>([1,2,3], [1,4,9], 'rs', label='line 2')<br>
<a href="#-axis">axis</a>([0, 4, 0, 10])<br>
<a href="#-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="#-plot">plot</a>(x1, y1, x2, y2, antialising=False)<br>
<br>
Neither line will be antialiased.<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-plot_date"><strong>plot_date</strong></a>(*args, **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<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-plotting"><strong>plotting</strong></a>()</dt><dd><tt>Plotting commands<br>
axes - Create a new axes<br>
axis - Set or return the current axis limits<br>
bar - make a bar chart<br>
cla - clear current axes<br>
clf - clear a figure window<br>
close - close a figure window<br>
colorbar - add a colorbar to the current figure<br>
cohere - make a plot of coherence<br>
contour - make a contour plot<br>
csd - make a plot of cross spectral density<br>
draw - force a redraw of the current figure<br>
errorbar - make an errorbar graph<br>
figlegend - add a legend to the figure<br>
figimage - add an image to the figure, w/o resampling<br>
figtext - add text in figure coords<br>
figure - create or change active figure<br>
fill - make filled polygons<br>
gca - return the current axes<br>
gcf - return the current figure<br>
gci - get the current image, or None<br>
get - get a handle graphics property<br>
hist - make a histogram<br>
hold - set the hold state on current axes<br>
legend - add a legend to the axes<br>
loglog - a log log plot<br>
imread - load image file into array<br>
imshow - plot image data<br>
pcolor - make a pseudocolor plot<br>
plot - make a line plot<br>
psd - make a plot of power spectral density<br>
rc - control the default params<br>
savefig - save the current figure<br>
scatter - make a scatter plot<br>
set - set a handle graphics property<br>
semilogx - log x axis<br>
semilogy - log y axis<br>
show - show the figures<br>
specgram - a spectrogram plot<br>
stem - make a stem plot<br>
subplot - make a subplot (numrows, numcols, axesnum)<br>
table - add a table to the axes<br>
text - add some text at location x,y to the current axes<br>
title - add a title to the current axes<br>
xlabel - add an xlabel to the current axes<br>
ylabel - add a ylabel to the current axes<br>
<br>
autumn - set the default colormap to autumn<br>
bone - set the default colormap to bone <br>
cool - set the default colormap to cool <br>
copper - set the default colormap to copper<br>
flag - set the default colormap to flag <br>
gray - set the default colormap to gray <br>
hot - set the default colormap to hot <br>
hsv - set the default colormap to hsv <br>
jet - set the default colormap to jet <br>
pink - set the default colormap to pink <br>
prism - set the default colormap to prism <br>
spring - set the default colormap to spring<br>
summer - set the default colormap to summer<br>
winter - set the default colormap to winter</tt></dd></dl>
<dl><dt><a name="-polar"><strong>polar</strong></a>(*args, **kwargs)</dt><dd><tt>POLAR(theta, r)<br>
<br>
Make a polar plot. Multiple theta, r arguments are supported,<br>
with format strings, as in plot.</tt></dd></dl>
<dl><dt><a name="-prism"><strong>prism</strong></a>()</dt><dd><tt>set the default colormap to prism and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-psd"><strong>psd</strong></a>(*args, **kwargs)</dt><dd><tt>PSD(x, NFFT=256, Fs=2, detrend=mlab.detrend_none,<br>
window=mlab.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)<br>
<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-raise_msg_to_str"><strong>raise_msg_to_str</strong></a>(msg)</dt><dd><tt>msg is a return arg from a raise. Join with new lines</tt></dd></dl>
<dl><dt><a name="-rc"><strong>rc</strong></a>(*args, **kwargs)</dt><dd><tt>Set the current rc params. Group is the grouping for the rc, eg<br>
for lines.linewidth the group is 'lines', for axes.facecolor, the<br>
group is 'axes', and so on. kwargs is a list of attribute<br>
name/value pairs, eg<br>
<br>
<a href="#-rc">rc</a>('lines', linewidth=2, color='r')<br>
<br>
sets the current rc params and is equivalent to<br>
<br>
rcParams['lines.linewidth'] = 2<br>
rcParams['lines.color'] = 'r'<br>
<br>
The following aliases are available to save typing for interactive<br>
users<br>
'lw' : 'linewidth'<br>
'ls' : 'linestyle' <br>
'c' : 'color'<br>
'fc' : 'facecolor'<br>
'ec' : 'edgecolor'<br>
'mfc' : 'markerfacecolor'<br>
'mec' : 'markeredgecolor'<br>
'mew' : 'markeredgewidth'<br>
'aa' : 'antialiased' <br>
'l' : 'lines'<br>
'a' : 'axes'<br>
'f' : 'figure'<br>
'p' : 'patches'<br>
'g' : 'grid'<br>
<br>
Thus you could abbreviate the above rc command as<br>
<br>
<a href="#-rc">rc</a>('l', lw=2, c='r')<br>
<br>
<br>
Note you can use python's kwargs dictionary facility to store<br>
dictionaries of default parameters. Eg, you can customize the<br>
font rc as follows<br>
<br>
font = {'family' : 'monospace',<br>
'weight' : 'bold',<br>
'size' : 'larger',<br>
}<br>
<br>
<a href="#-rc">rc</a>('font', **font) # pass in the font dict as kwargs<br>
<br>
This enables you to easily switch between several configurations.<br>
Use rcdefaults to restore the default rc params after changes.</tt></dd></dl>
<dl><dt><a name="-rcdefaults"><strong>rcdefaults</strong></a>()</dt><dd><tt>Restore the default rc params - the ones that were created at<br>
matplotlib load time</tt></dd></dl>
<dl><dt><a name="-reshape"><strong>reshape</strong></a>(...)</dt><dd><tt><a href="#-reshape">reshape</a>(a, (d1, d2, ..., dn)). Change the shape of a to be an n-dimensional array with dimensions given by d1...dn. Note: the size specified for the new array must be exactly equal to the size of the old one or an error will occur.</tt></dd></dl>
<dl><dt><a name="-rgrids"><strong>rgrids</strong></a>(*args, **kwargs)</dt><dd><tt>Set/Get the radial locations of the gridlines and ticklabels<br>
<br>
With no args, simply return lines, labels where lines is an<br>
array of radial gridlines (Line2D instances) and labels is an<br>
array of tick labels (Text instances).<br>
<br>
lines, labels = <a href="#-rgrids">rgrids</a>() <br>
<br>
With arguments, the syntax is<br>
<br>
lines, labels = RGRIDS(radii, labels=None, angle=22.5, **kwargs)<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. Note that on input the labels argument is a list of<br>
strings, and on output it is a list of Text instances<br>
<br>
Examples<br>
# set the locations of the radial gridlines and labels<br>
lines, labels = <a href="#-rgrids">rgrids</a>( (0.25, 0.5, 1.0) )<br>
<br>
# set the locations and labels of the radial gridlines and labels<br>
lines, labels = <a href="#-rgrids">rgrids</a>( (0.25, 0.5, 1.0), ('Tom', 'Dick', 'Harry' )</tt></dd></dl>
<dl><dt><a name="-save"><strong>save</strong></a>(fname, X, fmt<font color="#909090">='%1.4f'</font>)</dt><dd><tt>Save the data in X to file fname using fmt string to convert the<br>
data to strings<br>
<br>
fname can be a filename or a file handle <br>
<br>
Example usage:<br>
<br>
<a href="#-save">save</a>('test.out', X) # X is an array<br>
<a href="#-save">save</a>('test1.out', (x,y,z)) # x,y,z equal sized 1D arrays<br>
<a href="#-save">save</a>('test2.out', x) # x is 1D<br>
<a href="#-save">save</a>('test3.out', x, fmt='%1.4e') # use exponential notation</tt></dd></dl>
<dl><dt><a name="-savefig"><strong>savefig</strong></a>(*args, **kwargs)</dt><dd><tt>SAVEFIG(fname, dpi=150, facecolor='w', edgecolor='w',<br>
orientation='portrait'):<br>
<br>
Save the current figure to filename fname. dpi is the resolution<br>
in dots per inch.<br>
<br>
Output file types currently supported are jpeg and png and will be<br>
deduced by the extension to fname<br>
<br>
facecolor and edgecolor are the colors os the figure rectangle<br>
<br>
orientation is either 'landscape' or 'portrait' - not supported on<br>
all backends; currently only on postscript output.</tt></dd></dl>
<dl><dt><a name="-scatter"><strong>scatter</strong></a>(*args, **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 <br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-scatter_classic"><strong>scatter_classic</strong></a>(*args, **kwargs)</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<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-searchsorted"><strong>searchsorted</strong></a> = binarysearch(...)</dt><dd><tt>binarysearch(a,v)</tt></dd></dl>
<dl><dt><a name="-semilogx"><strong>semilogx</strong></a>(*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<br>
range(2,basex)<br>
<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-semilogy"><strong>semilogy</strong></a>(*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<br>
range(2,basey)<br>
<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-set"><strong>set</strong></a>(h, *args, **kwargs)</dt><dd><tt>matlab(TM) and pylab allow you to use set and get to set and get<br>
object properties, as well as to do introspection on the object<br>
For example, to set the linestyle of a line to be dashed, you can do<br>
<br>
>>> line, = <a href="#-plot">plot</a>([1,2,3])<br>
>>> <a href="#-set">set</a>(line, linestyle='--')<br>
<br>
If you want to know the valid types of arguments, you can provide the<br>
name of the property you want to set without a value<br>
<br>
>>> <a href="#-set">set</a>(line, 'linestyle')<br>
linestyle: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' ]<br>
<br>
If you want to see all the properties that can be set, and their<br>
possible values, you can do<br>
<br>
<br>
>>> <a href="#-set">set</a>(line)<br>
... long output listing omitted'<br>
<br>
set operates on a single instance or a list of instances. If you are<br>
in quey mode introspecting the possible values, only the first<br>
instance in the sequnce is used. When actually setting values, all<br>
the instances will be set. Eg, suppose you have a list of two lines,<br>
the following will make both lines thicker and red<br>
<br>
>>> x = <a href="#-arange">arange</a>(0,1.0,0.01)<br>
>>> y1 = sin(2*pi*x)<br>
>>> y2 = sin(4*pi*x)<br>
>>> lines = <a href="#-plot">plot</a>(x, y1, x, y2)<br>
>>> <a href="#-set">set</a>(lines, linewidth=2, color='r')<br>
<br>
Set works with the matlab(TM) style string/value pairs or with python<br>
kwargs. For example, the following are equivalent<br>
<br>
>>> <a href="#-set">set</a>(lines, 'linewidth', 2, 'color', r') # matlab style<br>
>>> <a href="#-set">set</a>(lines, linewidth=2, color='r') # python style</tt></dd></dl>
<dl><dt><a name="-specgram"><strong>specgram</strong></a>(*args, **kwargs)</dt><dd><tt>SPECGRAM(x, NFFT=256, Fs=2, detrend=mlab.detrend_none,<br>
window=mlab.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.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.<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-spring"><strong>spring</strong></a>()</dt><dd><tt>set the default colormap to spring and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-spy"><strong>spy</strong></a>(*args, **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<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-spy2"><strong>spy2</strong></a>(*args, **kwargs)</dt><dd><tt>SPY2(Z) plots the sparsity pattern of the matrix S as an image<br>
<br>
The image instance is returned<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-stem"><strong>stem</strong></a>(*args, **kwargs)</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.<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-subplot"><strong>subplot</strong></a>(*args, **kwargs)</dt><dd><tt>Create a 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>
<br>
<a href="#-subplot">subplot</a>(111) is the default axis<br>
<br>
The background color of the subplot can be specified via keyword<br>
argument 'axisbg', which takes a color string or gdk.Color as value, as in<br>
<br>
<a href="#-subplot">subplot</a>(211, axisbg='y')</tt></dd></dl>
<dl><dt><a name="-summer"><strong>summer</strong></a>()</dt><dd><tt>set the default colormap to summer and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-table"><strong>table</strong></a>(*args, **kwargs)</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="-take"><strong>take</strong></a>(...)</dt><dd><tt><a href="#-take">take</a>(a, indices, axis=0). Selects the elements in indices from array a along the given axis.</tt></dd></dl>
<dl><dt><a name="-text"><strong>text</strong></a>(*args, **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="#-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="#-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="-thetagrids"><strong>thetagrids</strong></a>(*args, **kwargs)</dt><dd><tt>Set/Get the theta locations of the gridlines and ticklabels<br>
<br>
If no arguments are passed, return lines, labels where lines is an<br>
array of radial gridlines (Line2D instances) and labels is an<br>
array of tick labels (Text instances).<br>
<br>
lines, labels = <a href="#-thetagrids">thetagrids</a>() <br>
<br>
Otherwise the syntax is<br>
<br>
lines, labels = THETAGRIDS(angles, labels=None, fmt='%d', frac = 1.1)<br>
<br>
set the angles at which to place the theta grids (these gridlines<br>
are equal along the theta dimension). angles is in 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 place<br>
the label (1 is the edge).Eg 1.05 isd outside the axes and 0.95<br>
is inside the axes<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. Note that on input the labels argument is a list of<br>
strings, and on output it is a list of Text instances<br>
<br>
Examples:<br>
<br>
# set the locations of the radial gridlines and labels<br>
lines, labels = <a href="#-thetagrids">thetagrids</a>( range(45,360,90) )<br>
<br>
# set the locations and labels of the radial gridlines and labels<br>
lines, labels = <a href="#-thetagrids">thetagrids</a>( range(45,360,90), ('NE', 'NW', 'SW','SE') )</tt></dd></dl>
<dl><dt><a name="-title"><strong>title</strong></a>(s, *args, **kwargs)</dt><dd><tt>Set the title of the current axis to s<br>
<br>
Default font override is:<br>
override = {<br>
'fontsize' : 'medium',<br>
'verticalalignment' : 'bottom',<br>
'horizontalalignment' : 'center'<br>
}<br>
<br>
See the text docstring for information of how override and the<br>
optional args work</tt></dd></dl>
<dl><dt><a name="-vlines"><strong>vlines</strong></a>(*args, **kwargs)</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<br>
<br>
Addition kwargs: hold = [True|False] overrides default hold state</tt></dd></dl>
<dl><dt><a name="-winter"><strong>winter</strong></a>()</dt><dd><tt>set the default colormap to winter and apply to current image if any. See help(colormaps) for more information</tt></dd></dl>
<dl><dt><a name="-xlabel"><strong>xlabel</strong></a>(s, *args, **kwargs)</dt><dd><tt>Set the x axis label of the current axis to s<br>
<br>
Default override is<br>
<br>
override = {<br>
'fontsize' : 'small',<br>
'verticalalignment' : 'top',<br>
'horizontalalignment' : 'center'<br>
}<br>
<br>
See the text docstring for information of how override and<br>
the optional args work</tt></dd></dl>
<dl><dt><a name="-xlim"><strong>xlim</strong></a>(*args, **kwargs)</dt><dd><tt>Set/Get the xlimits of the current axes<br>
<br>
xmin, xmax = <a href="#-xlim">xlim</a>() : return the current xlim<br>
<a href="#-xlim">xlim</a>( (xmin, xmax) ) : set the xlim to xmin, xmax<br>
<a href="#-xlim">xlim</a>( xmin, xmax ) : set the xlim to xmin, xmax</tt></dd></dl>
<dl><dt><a name="-xticks"><strong>xticks</strong></a>(*args, **kwargs)</dt><dd><tt>Set/Get the xlimits of the current ticklocs, labels<br>
<br>
# return locs, labels where locs is an array of tick locations and<br>
# labels is an array of tick labels.<br>
locs, labels = <a href="#-xticks">xticks</a>() <br>
<br>
# set the locations of the xticks<br>
<a href="#-xticks">xticks</a>( <a href="#-arange">arange</a>(6) )<br>
<br>
# set the locations and labels of the xticks<br>
<a href="#-xticks">xticks</a>( <a href="#-arange">arange</a>(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )<br>
<br>
The keyword args, if any, are text properties; see text for more<br>
information on text properties.</tt></dd></dl>
<dl><dt><a name="-ylabel"><strong>ylabel</strong></a>(s, *args, **kwargs)</dt><dd><tt>Set the y axis label of the current axis to s<br>
<br>
Defaults override is<br>
<br>
override = {<br>
'fontsize' : 'small',<br>
'verticalalignment' : 'center',<br>
'horizontalalignment' : 'right',<br>
'rotation'='vertical' : }<br>
<br>
See the text docstring for information of how override and the<br>
optional args work</tt></dd></dl>
<dl><dt><a name="-ylim"><strong>ylim</strong></a>(*args, **kwargs)</dt><dd><tt>Set/Get the ylimits of the current axes<br>
<br>
ymin, ymax = <a href="#-ylim">ylim</a>() : return the current ylim<br>
<a href="#-ylim">ylim</a>( (ymin, ymax) ) : set the ylim to ymin, ymax<br>
<a href="#-ylim">ylim</a>( ymin, ymax ) : set the ylim to ymin, ymax</tt></dd></dl>
<dl><dt><a name="-yticks"><strong>yticks</strong></a>(*args, **kwargs)</dt><dd><tt>Set/Get the ylimits of the current ticklocs, labels<br>
<br>
# return locs, labels where locs is an array of tick locations and<br>
# labels is an array of tick labels.<br>
locs, labels = <a href="#-yticks">yticks</a>() <br>
<br>
# set the locations of the yticks<br>
<a href="#-yticks">yticks</a>( <a href="#-arange">arange</a>(6) )<br>
<br>
# set the locations and labels of the yticks<br>
<a href="#-yticks">yticks</a>( <a href="#-arange">arange</a>(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )<br>
<br>
The keyword args, if any, are text properties; see text for more<br>
information on text properties.</tt></dd></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>Character</strong> = 'c'<br>
<strong>Complex</strong> = 'D'<br>
<strong>Complex0</strong> = 'F'<br>
<strong>Complex16</strong> = 'F'<br>
<strong>Complex32</strong> = 'F'<br>
<strong>Complex64</strong> = 'D'<br>
<strong>Complex8</strong> = 'F'<br>
<strong>DAILY</strong> = 3<br>
<strong>FR</strong> = FR<br>
<strong>FRIDAY</strong> = FR<br>
<strong>Float</strong> = 'd'<br>
<strong>Float0</strong> = 'f'<br>
<strong>Float16</strong> = 'f'<br>
<strong>Float32</strong> = 'f'<br>
<strong>Float64</strong> = 'd'<br>
<strong>Float8</strong> = 'f'<br>
<strong>HOURLY</strong> = 4<br>
<strong>HOURS_PER_DAY</strong> = 24.0<br>
<strong>Infinity</strong> = inf<br>
<strong>Int</strong> = 'l'<br>
<strong>Int0</strong> = '1'<br>
<strong>Int16</strong> = 's'<br>
<strong>Int32</strong> = 'i'<br>
<strong>Int8</strong> = '1'<br>
<strong>LittleEndian</strong> = True<br>
<strong>MINUTELY</strong> = 5<br>
<strong>MINUTES_PER_DAY</strong> = 1440.0<br>
<strong>MO</strong> = MO<br>
<strong>MONDAY</strong> = MO<br>
<strong>MONTHLY</strong> = 1<br>
<strong>MUSECONDS_PER_DAY</strong> = 86400000000.0<br>
<strong>NewAxis</strong> = None<br>
<strong>PyObject</strong> = 'O'<br>
<strong>SA</strong> = SA<br>
<strong>SATURDAY</strong> = SA<br>
<strong>SECONDLY</strong> = 6<br>
<strong>SECONDS_PER_DAY</strong> = 86400.0<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>SU</strong> = SU<br>
<strong>SUNDAY</strong> = SU<br>
<strong>TH</strong> = TH<br>
<strong>THURSDAY</strong> = TH<br>
<strong>TU</strong> = TU<br>
<strong>TUESDAY</strong> = TU<br>
<strong>UInt</strong> = 'u'<br>
<strong>UInt16</strong> = 'w'<br>
<strong>UInt32</strong> = 'u'<br>
<strong>UInt8</strong> = 'b'<br>
<strong>UnsignedInt16</strong> = 'w'<br>
<strong>UnsignedInt32</strong> = 'u'<br>
<strong>UnsignedInt8</strong> = 'b'<br>
<strong>UnsignedInteger</strong> = 'u'<br>
<strong>WE</strong> = WE<br>
<strong>WEDNESDAY</strong> = WE<br>
<strong>WEEKDAYS</strong> = (MO, TU, WE, TH, FR, SA, SU)<br>
<strong>WEEKLY</strong> = 2<br>
<strong>YEARLY</strong> = 0<br>
<strong>absolute</strong> = <ufunc 'absolute'><br>
<strong>add</strong> = <ufunc 'add'><br>
<strong>arccos</strong> = <ufunc 'arccos'><br>
<strong>arccosh</strong> = <ufunc 'arccosh'><br>
<strong>arcsin</strong> = <ufunc 'arcsin'><br>
<strong>arcsinh</strong> = <ufunc 'arcsinh'><br>
<strong>arctan</strong> = <ufunc 'arctan'><br>
<strong>arctan2</strong> = <ufunc 'arctan2'><br>
<strong>arctanh</strong> = <ufunc 'arctanh'><br>
<strong>bitwise_and</strong> = <ufunc 'bitwise_and'><br>
<strong>bitwise_or</strong> = <ufunc 'bitwise_or'><br>
<strong>bitwise_xor</strong> = <ufunc 'bitwise_xor'><br>
<strong>ceil</strong> = <ufunc 'ceil'><br>
<strong>conjugate</strong> = <ufunc 'conjugate'><br>
<strong>cos</strong> = <ufunc 'cos'><br>
<strong>cosh</strong> = <ufunc 'cosh'><br>
<strong>divide</strong> = <ufunc 'divide'><br>
<strong>divide_safe</strong> = <ufunc 'divide_safe'><br>
<strong>division</strong> = _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)<br>
<strong>e</strong> = 2.7182818284590451<br>
<strong>equal</strong> = <ufunc 'equal'><br>
<strong>exp</strong> = <ufunc 'exp'><br>
<strong>exp_safe_MAX</strong> = 1.7976931348623157e+308<br>
<strong>exp_safe_MIN</strong> = -708.39641853226408<br>
<strong>fabs</strong> = <ufunc 'fabs'><br>
<strong>floor</strong> = <ufunc 'floor'><br>
<strong>floor_divide</strong> = <ufunc 'floor_divide'><br>
<strong>fmod</strong> = <ufunc 'fmod'><br>
<strong>greater</strong> = <ufunc 'greater'><br>
<strong>greater_equal</strong> = <ufunc 'greater_equal'><br>
<strong>hypot</strong> = <ufunc 'hypot'><br>
<strong>inf</strong> = inf<br>
<strong>infty</strong> = inf<br>
<strong>invert</strong> = <ufunc 'invert'><br>
<strong>left_shift</strong> = <ufunc 'left_shift'><br>
<strong>less</strong> = <ufunc 'less'><br>
<strong>less_equal</strong> = <ufunc 'less_equal'><br>
<strong>log</strong> = <ufunc 'log'><br>
<strong>log10</strong> = <ufunc 'log10'><br>
<strong>logical_and</strong> = <ufunc 'logical_and'><br>
<strong>logical_not</strong> = <ufunc 'logical_not'><br>
<strong>logical_or</strong> = <ufunc 'logical_or'><br>
<strong>logical_xor</strong> = <ufunc 'logical_xor'><br>
<strong>maximum</strong> = <ufunc 'maximum'><br>
<strong>minimum</strong> = <ufunc 'minimum'><br>
<strong>multiply</strong> = <ufunc 'multiply'><br>
<strong>negative</strong> = <ufunc 'negative'><br>
<strong>not_equal</strong> = <ufunc 'not_equal'><br>
<strong>nx</strong> = <matplotlib.nc_imports._TypeNamespace instance><br>
<strong>pi</strong> = 3.1415926535897931<br>
<strong>power</strong> = <ufunc 'power'><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': 'TkAgg', 'datapath': '/usr/local/share/matplotlib', ...}<br>
<strong>rcParamsDefault</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': 'TkAgg', 'datapath': '/usr/local/share/matplotlib', ...}<br>
<strong>readme</strong> = '<font color="#c040c0">\n</font>MLab2.py, release 1<font color="#c040c0">\n\n</font>Created on February 2003 b...<font color="#c040c0">\n</font>Look at: http://pdilib.sf.net for new releases.<font color="#c040c0">\n</font>'<br>
<strong>remainder</strong> = <ufunc 'remainder'><br>
<strong>right_shift</strong> = <ufunc 'right_shift'><br>
<strong>sin</strong> = <ufunc 'sin'><br>
<strong>sinh</strong> = <ufunc 'sinh'><br>
<strong>sqrt</strong> = <ufunc 'sqrt'><br>
<strong>subtract</strong> = <ufunc 'subtract'><br>
<strong>tan</strong> = <ufunc 'tan'><br>
<strong>tanh</strong> = <ufunc 'tanh'><br>
<strong>true_divide</strong> = <ufunc 'true_divide'><br>
<strong>typecodes</strong> = {'Character': 'c', 'Complex': 'FD', 'Float': 'fd', 'Integer': '1sil', 'UnsignedInteger': 'bwu'}<br>
<strong>verbose</strong> = <matplotlib.Verbose instance><br>
<strong>version</strong> = 'Numeric 23.1'<br>
<strong>which</strong> = ('numeric', 'rc')</td></tr></table>
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