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ran a spell-checker on some files
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examples/pylab_examples/agg_buffer_to_array.py

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ax.set_title('a simple figure')
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fig.canvas.draw()
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# grab rhe pixel buffer and dumpy it into a numpy array
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# grab the pixel buffer and dump it into a numpy array
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buf = fig.canvas.buffer_rgba()
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l, b, w, h = fig.bbox.bounds
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X = np.frombuffer(buf, np.uint8)

examples/pylab_examples/anchored_artists.py

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pad=0.1, borderpad=0.1, sep=2, prop=None, frameon=True):
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"""
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Draw a horizontal bar with the size in data coordinate of the give axes.
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A label will be drawn underneath (center-alinged).
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A label will be drawn underneath (center-aligned).
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pad, borderpad in fraction of the legend font size (or prop)
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sep in points.

examples/pylab_examples/annotation_demo.py

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if 1:
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# You can also use polar notation on a catesian axes. Here the
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# You can also use polar notation on a cartesian axes. Here the
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# native coordinate system ('data') is cartesian, so you need to
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# specify the xycoords and textcoords as 'polar' if you want to
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# use (theta, radius)

examples/pylab_examples/axhspan_demo.py

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# draw a default vline at x=1 that spans the yrange
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l = plt.axvline(x=1)
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# draw a thick blue vline at x=0 that spans the the upper quadrant of
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# draw a thick blue vline at x=0 that spans the upper quadrant of
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# the yrange
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l = plt.axvline(x=0, ymin=0.75, linewidth=4, color='b')
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examples/pylab_examples/boxplot_demo2.py

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medianY.append(med.get_ydata()[j])
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plt.plot(medianX, medianY, 'k')
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medians[i] = medianY[0]
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# Finally, overplot the sample averages, with horixzontal alignment
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# Finally, overplot the sample averages, with horizontal alignment
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# in the center of each box
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plt.plot([np.average(med.get_xdata())], [np.average(data[i])],
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color='w', marker='*', markeredgecolor='k')

examples/pylab_examples/centered_ticklabels.py

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# sometimes it is nice to have ticklabels centered. mpl currently
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# associates a label with a tick, and the label can be aligned
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# 'center', 'feft', or 'right' using the horizontal alignment property:
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# 'center', 'left', or 'right' using the horizontal alignment property:
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#
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#
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# for label in ax.xaxis.get_xticklabels():
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# label.set_horizntal_alignment('right')
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# label.set_horizontalalignment('right')
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#
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#
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# but this doesn't help center the label between ticks. One solution

examples/pylab_examples/custom_figure_class.py

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"""
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You can pass a custom Figure constructor to figure if youy want to derive from the default Figure. This simple example creates a figure with a figure title
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You can pass a custom Figure constructor to figure if you want to derive from the default Figure. This simple example creates a figure with a figure title
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"""
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from matplotlib.pyplot import figure, show
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from matplotlib.figure import Figure

examples/pylab_examples/custom_ticker1.py

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#!/usr/bin/env python
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"""
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The new ticker code was designed to explicity support user customized
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The new ticker code was designed to explicitly support user customized
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ticking. The documentation
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http://matplotlib.sourceforge.net/matplotlib.ticker.html details this
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process. That code defines a lot of preset tickers but was primarily

examples/pylab_examples/customize_rc.py

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rc('xtick.major', size=5, pad=7)
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rc('xtick', labelsize=15)
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# using aliases for color, linestyle and linewith; gray, solid, thick
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# using aliases for color, linestyle and linewidth; gray, solid, thick
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rc('grid', c='0.5', ls='-', lw=5)
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rc('lines', lw=2, color='g')
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subplot(312)

examples/pylab_examples/date_demo_convert.py

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ax.plot_date(dates, y*y)
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# this is superfluous, since the autoscaler should get it right, but
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# use date2num and num2date to to convert between dates and floats if
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# use date2num and num2date to convert between dates and floats if
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# you want; both date2num and num2date convert an instance or sequence
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ax.set_xlim( dates[0], dates[-1] )
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examples/pylab_examples/demo_agg_filter.py

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def drop_shadow_line(ax):
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# copyed from examples/misc/svg_filter_line.py
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# copied from examples/misc/svg_filter_line.py
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# draw lines
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l1, = ax.plot([0.1, 0.5, 0.9], [0.1, 0.9, 0.5], "bo-",

examples/pylab_examples/fancybox_demo.py

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def test2(ax):
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# bbox=round has two optional argument. pad and rounding_size.
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# They can be set during the initiallization.
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# They can be set during the initialization.
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p_fancy = FancyBboxPatch((bb.xmin, bb.ymin),
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abs(bb.width), abs(bb.height),
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boxstyle="round,pad=0.1",

examples/pylab_examples/finance_work2.py

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fig = plt.figure(facecolor='white')
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axescolor = '#f6f6f6' # the axies background color
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axescolor = '#f6f6f6' # the axes background color
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ax1 = fig.add_axes(rect1, axisbg=axescolor) #left, bottom, width, height
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ax2 = fig.add_axes(rect2, axisbg=axescolor, sharex=ax1)

examples/pylab_examples/ganged_plots.py

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#!/usr/bin/env python
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"""
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To create plots that share a common axes (visually) you can set the
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hspace bewtween the subplots close to zero (do not use zero itself).
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hspace between the subplots close to zero (do not use zero itself).
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Normally you'll want to turn off the tick labels on all but one of the
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axes.
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examples/pylab_examples/major_minor_demo1.py

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some base. The FormatStrFormatter uses a string format string (eg
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'%d' or '%1.2f' or '%1.1f cm' ) to format the tick
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The pylab interface grid command chnages the grid settings of the
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The pylab interface grid command changes the grid settings of the
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major ticks of the y and y axis together. If you want to control the
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grid of the minor ticks for a given axis, use for example
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examples/pylab_examples/mathtext_demo.py

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#!/usr/bin/env python
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"""
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Use matplotlib's internal LaTex parser and layout engine. For true
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Use matplotlib's internal LaTeX parser and layout engine. For true
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latex rendering, see the text.usetex option
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"""
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import numpy as np

examples/pylab_examples/polar_demo.py

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# PolarAxes) -- other axes plotting functions may work on PolarAxes
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# but haven't been tested and may need tweaking.
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#
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# you can get get a PolarSubplot instance by doing, for example
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# you can get a PolarSubplot instance by doing, for example
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#
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# subplot(211, polar=True)
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#

examples/pylab_examples/psd_demo2.py

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ax2.psd(y, NFFT=len(t), pad_to=len(t)*4, Fs=fs)
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plt.title('zero padding')
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#Plot the PSD with different block sizes, Zero pad to the length of the orignal
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#Plot the PSD with different block sizes, Zero pad to the length of the original
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#data sequence.
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ax3 = fig.add_subplot(2, 3, 5, sharex=ax2, sharey=ax2)
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ax3.psd(y, NFFT=len(t), pad_to=len(t), Fs=fs)

examples/pylab_examples/pythonic_matplotlib.py

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#!/usr/bin/env python
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"""
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Some people prefer to write more pythonic, object oriented, code
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rather than use the pylab interface to matplotlib. This example show
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rather than use the pylab interface to matplotlib. This example shows
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you how.
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Unless you are an application developer, I recommend using part of the

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