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"""A matplotlib backend for publishing figures via display_data"""
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# Copyright (c) IPython Development Team.
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# Distributed under the terms of the Modified BSD License.
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from __future__ import print_function
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import matplotlib
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from matplotlib.backends.backend_agg import new_figure_manager, FigureCanvasAgg # analysis: ignore
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from matplotlib._pylab_helpers import Gcf
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from IPython.core.getipython import get_ipython
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from IPython.core.display import display
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from .config import InlineBackend
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def show(close=None):
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"""Show all figures as SVG/PNG payloads sent to the IPython clients.
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Parameters
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----------
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close : bool, optional
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If true, a ``plt.close('all')`` call is automatically issued after
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sending all the figures. If this is set, the figures will entirely
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removed from the internal list of figures.
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"""
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if close is None:
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close = InlineBackend.instance().close_figures
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try:
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for figure_manager in Gcf.get_all_fig_managers():
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display(figure_manager.canvas.figure)
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finally:
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show._to_draw = []
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# only call close('all') if any to close
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# close triggers gc.collect, which can be slow
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if close and Gcf.get_all_fig_managers():
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matplotlib.pyplot.close('all')
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# This flag will be reset by draw_if_interactive when called
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show._draw_called = False
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# list of figures to draw when flush_figures is called
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show._to_draw = []
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def draw_if_interactive():
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"""
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Is called after every pylab drawing command
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"""
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# signal that the current active figure should be sent at the end of
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# execution. Also sets the _draw_called flag, signaling that there will be
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# something to send. At the end of the code execution, a separate call to
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# flush_figures() will act upon these values
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manager = Gcf.get_active()
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if manager is None:
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return
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fig = manager.canvas.figure
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# Hack: matplotlib FigureManager objects in interacive backends (at least
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# in some of them) monkeypatch the figure object and add a .show() method
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# to it. This applies the same monkeypatch in order to support user code
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# that might expect `.show()` to be part of the official API of figure
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# objects.
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# For further reference:
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# https://github.com/ipython/ipython/issues/1612
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# https://github.com/matplotlib/matplotlib/issues/835
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if not hasattr(fig, 'show'):
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# Queue up `fig` for display
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fig.show = lambda *a: display(fig)
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# If matplotlib was manually set to non-interactive mode, this function
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# should be a no-op (otherwise we'll generate duplicate plots, since a user
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# who set ioff() manually expects to make separate draw/show calls).
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if not matplotlib.is_interactive():
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return
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# ensure current figure will be drawn, and each subsequent call
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# of draw_if_interactive() moves the active figure to ensure it is
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# drawn last
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try:
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show._to_draw.remove(fig)
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except ValueError:
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# ensure it only appears in the draw list once
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pass
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# Queue up the figure for drawing in next show() call
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show._to_draw.append(fig)
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show._draw_called = True
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def flush_figures():
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"""Send all figures that changed
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This is meant to be called automatically and will call show() if, during
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prior code execution, there had been any calls to draw_if_interactive.
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This function is meant to be used as a post_execute callback in IPython,
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so user-caused errors are handled with showtraceback() instead of being
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allowed to raise. If this function is not called from within IPython,
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then these exceptions will raise.
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"""
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if not show._draw_called:
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return
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if InlineBackend.instance().close_figures:
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# ignore the tracking, just draw and close all figures
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try:
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return show(True)
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except Exception as e:
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# safely show traceback if in IPython, else raise
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ip = get_ipython()
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if ip is None:
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raise e
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else:
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ip.showtraceback()
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return
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try:
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# exclude any figures that were closed:
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active = set([fm.canvas.figure for fm in Gcf.get_all_fig_managers()])
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for fig in [ fig for fig in show._to_draw if fig in active ]:
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try:
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display(fig)
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except Exception as e:
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# safely show traceback if in IPython, else raise
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ip = get_ipython()
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if ip is None:
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raise e
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else:
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ip.showtraceback()
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return
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finally:
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# clear flags for next round
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show._to_draw = []
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show._draw_called = False
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# Changes to matplotlib in version 1.2 requires a mpl backend to supply a default
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# figurecanvas. This is set here to a Agg canvas
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# See https://github.com/matplotlib/matplotlib/pull/1125
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FigureCanvas = FigureCanvasAgg
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