110 lines
4.4 KiB
Python
110 lines
4.4 KiB
Python
"""Configurable for configuring the IPython inline backend
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This module does not import anything from matplotlib.
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"""
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#-----------------------------------------------------------------------------
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# Copyright (C) 2011 The IPython Development Team
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#
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# Distributed under the terms of the BSD License. The full license is in
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# the file COPYING, distributed as part of this software.
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#-----------------------------------------------------------------------------
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#-----------------------------------------------------------------------------
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# Imports
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#-----------------------------------------------------------------------------
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from traitlets.config.configurable import SingletonConfigurable
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from traitlets import (
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Dict, Instance, Set, Bool, TraitError, Unicode
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)
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#-----------------------------------------------------------------------------
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# Configurable for inline backend options
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#-----------------------------------------------------------------------------
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def pil_available():
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"""Test if PIL/Pillow is available"""
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out = False
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try:
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from PIL import Image
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out = True
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except:
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pass
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return out
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# inherit from InlineBackendConfig for deprecation purposes
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class InlineBackendConfig(SingletonConfigurable):
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pass
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class InlineBackend(InlineBackendConfig):
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"""An object to store configuration of the inline backend."""
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# The typical default figure size is too large for inline use,
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# so we shrink the figure size to 6x4, and tweak fonts to
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# make that fit.
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rc = Dict({'figure.figsize': (6.0,4.0),
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# play nicely with white background in the Qt and notebook frontend
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'figure.facecolor': (1,1,1,0),
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'figure.edgecolor': (1,1,1,0),
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# 12pt labels get cutoff on 6x4 logplots, so use 10pt.
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'font.size': 10,
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# 72 dpi matches SVG/qtconsole
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# this only affects PNG export, as SVG has no dpi setting
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'figure.dpi': 72,
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# 10pt still needs a little more room on the xlabel:
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'figure.subplot.bottom' : .125
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},
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help="""Subset of matplotlib rcParams that should be different for the
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inline backend."""
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).tag(config=True)
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figure_formats = Set({'png'},
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help="""A set of figure formats to enable: 'png',
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'retina', 'jpeg', 'svg', 'pdf'.""").tag(config=True)
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def _update_figure_formatters(self):
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if self.shell is not None:
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from IPython.core.pylabtools import select_figure_formats
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select_figure_formats(self.shell, self.figure_formats, **self.print_figure_kwargs)
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def _figure_formats_changed(self, name, old, new):
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if 'jpg' in new or 'jpeg' in new:
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if not pil_available():
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raise TraitError("Requires PIL/Pillow for JPG figures")
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self._update_figure_formatters()
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figure_format = Unicode(help="""The figure format to enable (deprecated
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use `figure_formats` instead)""").tag(config=True)
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def _figure_format_changed(self, name, old, new):
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if new:
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self.figure_formats = {new}
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print_figure_kwargs = Dict({'bbox_inches' : 'tight'},
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help="""Extra kwargs to be passed to fig.canvas.print_figure.
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Logical examples include: bbox_inches, quality (for jpeg figures), etc.
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"""
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).tag(config=True)
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_print_figure_kwargs_changed = _update_figure_formatters
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close_figures = Bool(True,
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help="""Close all figures at the end of each cell.
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When True, ensures that each cell starts with no active figures, but it
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also means that one must keep track of references in order to edit or
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redraw figures in subsequent cells. This mode is ideal for the notebook,
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where residual plots from other cells might be surprising.
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When False, one must call figure() to create new figures. This means
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that gcf() and getfigs() can reference figures created in other cells,
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and the active figure can continue to be edited with pylab/pyplot
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methods that reference the current active figure. This mode facilitates
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iterative editing of figures, and behaves most consistently with
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other matplotlib backends, but figure barriers between cells must
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be explicit.
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""").tag(config=True)
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shell = Instance('IPython.core.interactiveshell.InteractiveShellABC',
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allow_none=True)
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