upstream/ipython Files · docs/examples/tests/pylab_figshow.py

Merge pull request from dopplershift/pylab-switch...

Merge pull request from dopplershift/pylab-switch Enable switching %pylab mode between inline and a single gui mode in a single notebook. With this merge, `%pylab` can be called interactively to toggle inline/GUI (matplotlib floating windows) mode. After initializing `%pylab inline`, now one can call `%pylab` without arguments to activate the default GUI or ask for a specific one as usual. IPython will detect if a different GUI is requested if one was already activated and will refuse to do so (to prevent multiple event loops from running concurrently, which often leads to problems).

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      """Manual test for figure.show() in the inline matplotlib backend.

      This script should be loaded for interactive use (via %load) into a qtconsole

      or notebook initialized with the pylab inline backend.  

      Expected behavior: only *one* copy of the figure is shown.

      For further details:

      https://github.com/ipython/ipython/issues/1612

      https://github.com/matplotlib/matplotlib/issues/835

      """

      import numpy as np

      import matplotlib.pyplot as plt

      plt.ioff()                                                                      

      x = np.random.uniform(-5, 5, size=(100))

      y = np.random.uniform(-5, 5, size=(100))

      f = plt.figure()

      plt.scatter(x, y)

      plt.plot(y)

      f.show()

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				"""Manual test for figure.show() in the inline matplotlib backend.

				This script should be loaded for interactive use (via %load) into a qtconsole
				or notebook initialized with the pylab inline backend.

				Expected behavior: only one copy of the figure is shown.


				For further details:
				https://github.com/ipython/ipython/issues/1612
				https://github.com/matplotlib/matplotlib/issues/835
				"""

				import numpy as np
				import matplotlib.pyplot as plt

				plt.ioff()
				x = np.random.uniform(-5, 5, size=(100))
				y = np.random.uniform(-5, 5, size=(100))
				f = plt.figure()
				plt.scatter(x, y)
				plt.plot(y)
				f.show()