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"""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 IPython.config.configurable import SingletonConfigurable
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from IPython.utils.traitlets import Dict, Instance, CaselessStrEnum, Bool, Int
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from IPython.utils.warn import warn
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#-----------------------------------------------------------------------------
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# Configurable for inline backend options
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#-----------------------------------------------------------------------------
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try:
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from PIL import Image
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has_pil = True
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except:
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has_pil = False
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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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def _config_changed(self, name, old, new):
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# warn on change of renamed config section
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if new.InlineBackendConfig != old.InlineBackendConfig:
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warn("InlineBackendConfig has been renamed to InlineBackend")
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super(InlineBackend, self)._config_changed(name, old, new)
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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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'savefig.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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}, config=True,
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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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)
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fmts = ['svg', 'png', 'retina']
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if has_pil:
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# If we have PIL using jpeg as inline image format can save some bytes.
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fmts.append('jpg')
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# Matplotlib's JPEG printer supports a quality option that can be tweaked.
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# We expose it only if PIL is available so the user isn't confused. But it
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# isn't guarded by "has_pil" test because core/pylabtools.py expects this
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# field OR we need to propagate the has_pil test to that module too.
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quality = Int(default_value=90, config=has_pil,
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help="Quality of compression [0-100], currently for lossy JPEG only.")
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figure_format = CaselessStrEnum(fmts, default_value='png', config=True,
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help="The image format for figures with the inline backend.")
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def _figure_format_changed(self, name, old, new):
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from IPython.core.pylabtools import select_figure_format
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if self.shell is None:
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return
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else:
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select_figure_format(self.shell, new)
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close_figures = Bool(True, config=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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""")
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shell = Instance('IPython.core.interactiveshell.InteractiveShellABC')
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