8000 Merge pull request #8963 from dstansby/pylab-moves · choldgraf/matplotlib@a0a959f · GitHub
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Merge pull request matplotlib#8963 from dstansby/pylab-moves
Some more pylab moves
2 parents e477912 + be8dc79 commit a0a959f

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‎doc/users/prev_whats_new/whats_new_0.98.4.rst

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@@ -79,7 +79,7 @@ psd amplitude scaling
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Ryan May did a lot of work to rationalize the amplitude scaling of
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:func:`~matplotlib.pyplot.psd` and friends. See
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:ref:`sphx_glr_gallery_pylab_examples_psd_demo.py`.
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:ref:`sphx_glr_gallery_lines_bars_and_markers_psd_demo.py`.
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The changes should increase MATLAB
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compatibility and increase scaling options.
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@@ -298,6 +298,3 @@ Here are the 0.98.4 notes from the CHANGELOG::
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Added support for arbitrary rasterization resolutions to the SVG
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backend. - MW
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‎doc/users/prev_whats_new/whats_new_0.99.rst

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@@ -65,7 +65,7 @@ that denote the data limits -- in various arbitrary locations. No
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longer are your axis lines constrained to be a simple rectangle around
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the figure -- you can turn on or off left, bottom, right and top, as
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well as "detach" the spine to offset it away from the data. See
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:ref:`sphx_glr_gallery_pylab_examples_spine_placement_demo.py` and
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:ref:`sphx_glr_gallery_ticks_and_spines_spine_placement_demo.py` and
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:class:`matplotlib.spines.Spine`.
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.. figure:: ../../gallery/pyplots/images/sphx_glr_whats_new_99_spines_001.png
@@ -74,7 +74,3 @@ well as "detach" the spine to offset it away from the data. See
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:scale: 50
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Whats New 99 Spines
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‎doc/users/prev_whats_new/whats_new_1.3.rst

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@@ -154,8 +154,8 @@ Till Stensitzki added non-zero baselines to
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:func:`~matplotlib.pyplot.stackplot`. They may be symmetric or
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weighted.
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.. figure:: ../../gallery/pylab_examples/images/sphx_glr_stackplot_demo_001.png
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:target: ../../gallery/pylab_examples/stackplot_demo.html
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.. figure:: ../../gallery/lines_bars_and_markers/images/sphx_glr_stackplot_demo_001.png
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:target: ../../gallery/lines_bars_and_markers/stackplot_demo.html
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:align: center
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:scale: 50
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‎examples/pylab_examples/coords_demo.py renamed to ‎examples/event_handling/coords_demo.py

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@@ -12,7 +12,7 @@
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import numpy as np
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t = np.arange(0.0, 1.0, 0.01)
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s = np.sin(2*np.pi*t)
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s = np.sin(2 * np.pi * t)
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fig, ax = plt.subplots()
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ax.plot(t, s)
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@@ -33,6 +33,7 @@ def on_click(event):
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if event.inaxes is not None:
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print('data coords %f %f' % (event.xdata, event.ydata))
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binding_id = plt.connect('motion_notify_event', on_move)
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plt.connect('button_press_event', on_click)
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‎examples/pylab_examples/barb_demo.py renamed to ‎examples/images_contours_and_fields/barb_demo.py

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‎examples/pylab_examples/custom_cmap.py renamed to ‎examples/images_contours_and_fields/custom_cmap.py

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# Make some illustrative fake data:
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x = np.arange(0, np.pi, 0.1)
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y = np.arange(0, 2*np.pi, 0.1)
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y = np.arange(0, 2 * np.pi, 0.1)
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X, Y = np.meshgrid(x, y)
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Z = np.cos(X) * np.sin(Y) * 10
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#
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# Draw a line with low zorder so it will be behind the image.
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axs[1, 1].plot([0, 10*np.pi], [0, 20*np.pi], color='c', lw=20, zorder=-1)
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axs[1, 1].plot([0, 10 * np.pi], [0, 20 * np.pi], color='c', lw=20, zorder=-1)
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im4 = axs[1, 1].imshow(Z, interpolation='nearest')
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fig.colorbar(im4, ax=axs[1, 1])
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#
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fig.suptitle('Custom Blue-Red colormaps', fontsize=16)
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fig.subplots_adjust(top=0.9)
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plt.show()

‎examples/pylab_examples/matshow.py renamed to ‎examples/images_contours_and_fields/matshow.py

File renamed without changes.

‎examples/pylab_examples/specgram_demo.py renamed to ‎examples/images_contours_and_fields/specgram_demo.py

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dt = 0.0005
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t = np.arange(0.0, 20.0, dt)
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s1 = np.sin(2*np.pi*100*t)
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s2 = 2*np.sin(2*np.pi*400*t)
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s1 = np.sin(2 * np.pi * 100 * t)
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s2 = 2 * np.sin(2 * np.pi * 400 * t)
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# create a transient "chirp"
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mask = np.where(np.logical_and(t > 10, t < 12), 1.0, 0.0)
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s2 = s2 * mask
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# add some noise into the mix
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nse = 0.01*np.random.random(size=len(t))
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nse = 0.01 * np.random.random(size=len(t))
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x = s1 + s2 + nse # the signal
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NFFT = 1024 # the length of the windowing segments
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Fs = int(1.0/dt) # the sampling frequency
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Fs = int(1.0 / dt) # the sampling frequency
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# Pxx is the segments x freqs array of instantaneous power, freqs is
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# the frequency vector, bins are the centers of the time bins in which

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

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"""
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========
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Csd Demo
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CSD Demo
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========
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Compute the cross spectral density of two signals
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nse1 = np.random.randn(len(t)) # white noise 1
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nse2 = np.random.randn(len(t)) # white noise 2
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r = np.exp(-t/0.05)
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r = np.exp(-t / 0.05)
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cnse1 = np.convolve(nse1, r, mode='same')*dt # colored noise 1
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cnse2 = np.convolve(nse2, r, mode='same')*dt # colored noise 2
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cnse1 = np.convolve(nse1, r, mode='same') * dt # colored noise 1
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cnse2 = np.convolve(nse2, r, mode='same') * dt # colored noise 2
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# two signals with a coherent part and a random part
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s1 = 0.01*np.sin(2*np.pi*10*t) + cnse1
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s2 = 0.01*np.sin(2*np.pi*10*t) + cnse2
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s1 = 0.01 * np.sin(2 * np.pi * 10 * t) + cnse1
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s2 = 0.01 * np.sin(2 * np.pi * 10 * t) + cnse2
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ax1.plot(t, s1, t, s2)
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ax1.set_xlim(0, 5)
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ax1.set_xlabel('time')
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ax1.set_ylabel('s1 and s2')
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ax1.grid(True)
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cxy, f = ax2.csd(s1, s2, 256, 1./dt)
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cxy, f = ax2.csd(s1, s2, 256, 1. / dt)
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ax2.set_ylabel('CSD (db)')
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plt.show()

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

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fig = plt.figure(0)
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x = np.arange(10.0)
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y = np.sin(np.arange(10.0)/20.0*np.pi)
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y = np.sin(np.arange(10.0) / 20.0 * np.pi)
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plt.errorbar(x, y, yerr=0.1)
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y = np.sin(np.arange(10.0)/20.0*np.pi) + 1
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y = np.sin(np.arange(10.0) / 20.0 * np.pi) + 1
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plt.errorbar(x, y, yerr=0.1, uplims=True)
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y = np.sin(np.arange(10.0)/20.0*np.pi) + 2
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upperlimits = np.array([1, 0]*5)
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lowerlimits = np.array([0, 1]*5)
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y = np.sin(np.arange(10.0) / 20.0 * np.pi) + 2
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upperlimits = np.array([1, 0] * 5)
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lowerlimits = np.array([0, 1] * 5)
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plt.errorbar(x, y, yerr=0.1, uplims=upperlimits, lolims=lowerlimits)
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plt.xlim(-1, 10)
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###############################################################################
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fig = plt.figure(1)
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x = np.arange(10.0)/10.0
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x = np.arange(10.0) / 10.0
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y = (x + 0.1)**2
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plt.errorbar(x, y, xerr=0.1, xlolims=True)

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