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NelleVNelleV
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Merge pull request #8813 from dstansby/pylab-moves
Move and clean some pylab examples
2 parents e41fca5 + 94bdcbe commit 0d1d968

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‎doc/faq/howto_faq.rst‎

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@@ -191,7 +191,7 @@ specify the location explicitly::
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ax = fig.add_axes([left, bottom, width, height])
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where all values are in fractional (0 to 1) coordinates. See
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:ref:`sphx_glr_gallery_pylab_examples_axes_demo.py` for an example of placing axes manually.
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:ref:`sphx_glr_gallery_subplots_axes_and_figures_axes_demo.py` for an example of placing axes manually.
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.. _howto-auto-adjust:
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.. htmlonly::
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See :ref:`sphx_glr_gallery_pylab_examples_axis_equal_demo.py` for a
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See :ref:`sphx_glr_gallery_subplots_axes_and_figures_axis_equal_demo.py` for a
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complete example.
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.. _howto-twoscale:
@@ -755,4 +755,3 @@ reference page <http://dx.doi.org/10.1109/MCSE.2007.55>`_)::
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development, interactive scripting, and publication-quality image
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generation across user interfaces and operating systems.},
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Bdsk-Url-1 = {http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS&DestLinkType=FullRecord;KeyUT=000245668100019}}
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examples/pylab_examples/arctest.py renamed to examples/lines_bars_and_markers/arctest.py

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def f(t):
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'a damped exponential'
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'A damped exponential'
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s1 = np.cos(2 * np.pi * t)
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e1 = np.exp(-t)
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return s1 * e1
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t1 = np.arange(0.0, 5.0, .2)
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t1 = np.arange(0.0, 5.0, .2)
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l = plt.plot(t1, f(t1), 'ro')
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plt.setp(l, 'markersize', 30)
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plt.setp(l, 'markerfacecolor', 'b')
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plt.setp(l, 'markerfacecolor', 'C0')
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plt.show()

examples/pylab_examples/bar_stacked.py renamed to examples/lines_bars_and_markers/bar_stacked.py

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ind = np.arange(N) # the x locations for the groups
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width = 0.35 # the width of the bars: can also be len(x) sequence
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p1 = plt.bar(ind, menMeans, width, color='#d62728', yerr=menStd)
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p1 = plt.bar(ind, menMeans, width, yerr=menStd)
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p2 = plt.bar(ind, womenMeans, width,
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bottom=menMeans, yerr=womenStd)
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‎examples/pylab_examples/axhspan_demo.py‎

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This file was deleted.

‎examples/recipes/fill_between_alpha.py‎

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# vertical spans of an axes -- for that matplotlib has some helper
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# functions :meth:`~matplotlib.axes.Axes.axhspan` and
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# :meth:`~matplotlib.axes.Axes.axvspan` and example
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# :ref:`sphx_glr_gallery_pylab_examples_axhspan_demo.py`.
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# :ref:`sphx_glr_gallery_subplots_axes_and_figures_axhspan_demo.py`.

examples/pylab_examples/anscombe.py renamed to examples/specialty_plots/anscombe.py

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def fit(x):
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return 3 + 0.5*x
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return 3 + 0.5 * x
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xfit = np.array([np.min(x), np.max(x)])
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plt.subplot(222)
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plt.plot(x, y2, 'ks', xfit, fit(xfit), 'r-', lw=2)
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plt.axis([2, 20, 2, 14])
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plt.setp(plt.gca(), xticklabels=[], yticks=(4, 8, 12), yticklabels=[], xticks=(0, 10, 20))
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plt.setp(plt.gca(), xticks=(0, 10, 20), xticklabels=[],
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yticks=(4, 8, 12), yticklabels=[], )
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plt.text(3, 12, 'II', fontsize=20)
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plt.subplot(223)
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# verify the stats
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pairs = (x, y1), (x, y2), (x, y3), (x4, y4)
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for x, y in pairs:
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print('mean=%1.2f, std=%1.2f, r=%1.2f' % (np.mean(y), np.std(y), np.corrcoef(x, y)[0][1]))
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print('mean=%1.2f, std=%1.2f, r=%1.2f' % (np.mean(y), np.std(y),
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np.corrcoef(x, y)[0][1]))
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plt.show()

examples/pylab_examples/axes_demo.py renamed to examples/subplots_axes_and_figures/axes_demo.py

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# create some data to use for the plot
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dt = 0.001
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t = np.arange(0.0, 10.0, dt)
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r = np.exp(-t[:1000]/0.05) # impulse response
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r = np.exp(-t[:1000] / 0.05) # impulse response
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x = np.random.randn(len(t))
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s = np.convolve(x, r)[:len(x)]*dt # colored noise
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s = np.convolve(x, r)[:len(x)] * dt # colored noise
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# the main axes is subplot(111) by default
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plt.plot(t, s)
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plt.title('Gaussian colored noise')
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# this is an inset axes over the main axes
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a = plt.axes([.65, .6, .2, .2], facecolor='y')
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a = plt.axes([.65, .6, .2, .2], facecolor='k')
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n, bins, patches = plt.hist(s, 400, normed=1)
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plt.title('Probability')
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plt.xticks([])
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plt.yticks([])
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# this is another inset axes over the main axes
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a = plt.axes([0.2, 0.6, .2, .2], facecolor='y')
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a = plt.axes([0.2, 0.6, .2, .2], facecolor='k')
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plt.plot(t[:len(r)], r)
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plt.title('Impulse response')
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plt.xlim(0, 0.2)

examples/pylab_examples/axes_props.py renamed to examples/subplots_axes_and_figures/axes_props.py

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examples/pylab_examples/axes_zoom_effect.py renamed to examples/subplots_axes_and_figures/axes_zoom_effect.py

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@@ -16,7 +16,7 @@ def connect_bbox(bbox1, bbox2,
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prop_lines, prop_patches=None):
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if prop_patches is None:
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prop_patches = prop_lines.copy()
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prop_patches["alpha"] = prop_patches.get("alpha", 1)*0.2
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prop_patches["alpha"] = prop_patches.get("alpha", 1) * 0.2
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c1 = BboxConnector(bbox1, bbox2, loc1=loc1a, loc2=loc2a, **prop_lines)
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c1.set_clip_on(False)

‎examples/subplots_axes_and_figures/axhspan_demo.py‎

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"""
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============
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axhspan Demo
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============
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Create lines or rectangles that span the axes in either the horizontal or
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vertical direction.
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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t = np.arange(-1, 2, .01)
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s = np.sin(2 * np.pi * t)
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plt.plot(t, s)
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# Draw a thick red hline at y=0 that spans the xrange
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plt.axhline(linewidth=8, color='#d62728')
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# Draw a default hline at y=1 that spans the xrange
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plt.axhline(y=1)
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# Draw a default vline at x=1 that spans the yrange
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plt.axvline(x=1)
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# Draw a thick blue vline at x=0 that spans the upper quadrant of the yrange
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plt.axvline(x=0, ymin=0.75, linewidth=8, color='#1f77b4')
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# Draw a default hline at y=.5 that spans the middle half of the axes
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plt.axhline(y=.5, xmin=0.25, xmax=0.75)
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plt.axhspan(0.25, 0.75, facecolor='0.5', alpha=0.5)
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plt.axvspan(1.25, 1.55, facecolor='#2ca02c', alpha=0.5)
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plt.axis([-1, 2, -1, 2])
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plt.show()

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