/usr/lib/python2.7/dist-packages/seaborn/rcmod.py is in python-seaborn 0.4.0-3.
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import numpy as np
import matplotlib as mpl
from . import palettes
_style_keys = (
"axes.facecolor",
"axes.edgecolor",
"axes.grid",
"axes.axisbelow",
"axes.linewidth",
"axes.labelcolor",
"grid.color",
"grid.linestyle",
"text.color",
"xtick.color",
"ytick.color",
"xtick.direction",
"ytick.direction",
"xtick.major.size",
"ytick.major.size",
"xtick.minor.size",
"ytick.minor.size",
"legend.frameon",
"legend.numpoints",
"legend.scatterpoints",
"lines.solid_capstyle",
"image.cmap",
"font.family",
"pdf.fonttype",
"font.sans-serif",
)
_context_keys = (
"figure.figsize",
"axes.labelsize",
"axes.titlesize",
"xtick.labelsize",
"ytick.labelsize",
"legend.fontsize",
"grid.linewidth",
"lines.linewidth",
"patch.linewidth",
"lines.markersize",
"lines.markeredgewidth",
"xtick.major.width",
"ytick.major.width",
"xtick.minor.width",
"ytick.minor.width",
"xtick.major.pad",
"ytick.major.pad"
)
def set(context="notebook", style="darkgrid", palette="deep",
font="sans-serif", font_scale=1, rc=None):
"""Set aesthetic parameters in one step.
Each set of parameters can be set directly or temporarily, see the
referenced functions below for more information.
Parameters
----------
context : string or dict
Plotting context parameters, see :func:`plotting_context`
style : string or dict
Axes style parameters, see :func:`axes_style`
palette : string or sequence
Color palette, see :func:`color_palette`
font : string
Font family, see matplotlib font manager.
font_scale : float, optional
Separate scaling factor to independently scale the size of the
font elements.
rc : dict or None
Dictionary of rc parameter mappings to override the above.
"""
set_context(context, font_scale)
set_style(style, rc={"font.family": font})
set_palette(palette)
if rc is not None:
mpl.rcParams.update(rc)
def reset_defaults():
"""Restore all RC params to default settings."""
mpl.rcParams.update(mpl.rcParamsDefault)
def reset_orig():
"""Restore all RC params to original settings (respects custom rc)."""
mpl.rcParams.update(mpl.rcParamsOrig)
class _AxesStyle(dict):
"""Light wrapper on a dict to set style temporarily."""
def __enter__(self):
"""Open the context."""
rc = mpl.rcParams
self._orig_style = {k: rc[k] for k in _style_keys}
set_style(self)
return self
def __exit__(self, *args):
"""Close the context."""
set_style(self._orig_style)
class _PlottingContext(dict):
"""Light wrapper on a dict to set context temporarily."""
def __enter__(self):
"""Open the context."""
rc = mpl.rcParams
self._orig_context = {k: rc[k] for k in _context_keys}
set_context(self)
return self
def __exit__(self, *args):
"""Close the context."""
set_context(self._orig_context)
def axes_style(style=None, rc=None):
"""Return a parameter dict for the aesthetic style of the plots.
This affects things like the color of the axes, whether a grid is
enabled by default, and other aesthetic elements.
This function returns an object that can be used in a ``with`` statement
to temporarily change the style parameters.
Parameters
----------
style : dict, None, or one of {darkgrid, whitegrid, dark, white, ticks}
A dictionary of parameters or the name of a preconfigured set.
rc : dict, optional
Parameter mappings to override the values in the preset seaborn
style dictionaries. This only updates parameters that are
considered part of the style definition.
Examples
--------
>>> st = axes_style("whitegrid")
>>> set_style("ticks", {"xtick.major.size": 8, "ytick.major.size": 8})
>>> import matplotlib.pyplot as plt
>>> with axes_style("white"):
... f, ax = plt.subplots()
... ax.plot(x, y) # doctest: +SKIP
See Also
--------
set_style : set the matplotlib parameters for a seaborn theme
plotting_context : return a parameter dict to to scale plot elements
color_palette : define the color palette for a plot
"""
if style is None:
style_dict = {k: mpl.rcParams[k] for k in _style_keys}
elif isinstance(style, dict):
style_dict = style
else:
styles = ["white", "dark", "whitegrid", "darkgrid", "ticks"]
if style not in styles:
raise ValueError("style must be one of %s" % ", ".join(styles))
# Define colors here
dark_gray = ".15"
light_gray = ".8"
# Common parameters
style_dict = {
"text.color": dark_gray,
"axes.labelcolor": dark_gray,
"legend.frameon": False,
"legend.numpoints": 1,
"legend.scatterpoints": 1,
"xtick.direction": "out",
"ytick.direction": "out",
"xtick.color": dark_gray,
"ytick.color": dark_gray,
"axes.axisbelow": True,
"image.cmap": "Greys",
"font.family": ["sans-serif"],
"font.sans-serif": ["Arial", "Liberation Sans",
"Bitstream Vera Sans", "sans-serif"],
"grid.linestyle": "-",
"lines.solid_capstyle": "round",
"pdf.fonttype": 42,
}
# Set grid on or off
if "grid" in style:
style_dict.update({
"axes.grid": True,
})
else:
style_dict.update({
"axes.grid": False,
})
# Set the color of the background, spines, and grids
if style.startswith("dark"):
style_dict.update({
"axes.facecolor": "#EAEAF2",
"axes.edgecolor": "white",
"axes.linewidth": 0,
"grid.color": "white",
})
elif style == "whitegrid":
style_dict.update({
"axes.facecolor": "white",
"axes.edgecolor": light_gray,
"axes.linewidth": 1,
"grid.color": light_gray,
})
elif style in ["white", "ticks"]:
style_dict.update({
"axes.facecolor": "white",
"axes.edgecolor": dark_gray,
"axes.linewidth": 1.25,
"grid.color": light_gray,
})
# Show or hide the axes ticks
if style == "ticks":
style_dict.update({
"xtick.major.size": 6,
"ytick.major.size": 6,
"xtick.minor.size": 3,
"ytick.minor.size": 3,
})
else:
style_dict.update({
"xtick.major.size": 0,
"ytick.major.size": 0,
"xtick.minor.size": 0,
"ytick.minor.size": 0,
})
# Override these settings with the provided rc dictionary
if rc is not None:
rc = {k: v for k, v in rc.items() if k in _style_keys}
style_dict.update(rc)
# Wrap in an _AxesStyle object so this can be used in a with statement
style_object = _AxesStyle(style_dict)
return style_object
def set_style(style=None, rc=None):
"""Set the aesthetic style of the plots.
This affects things like the color of the axes, whether a grid is
enabled by default, and other aesthetic elements.
Parameters
----------
style : dict, None, or one of {darkgrid, whitegrid, dark, white, ticks}
A dictionary of parameters or the name of a preconfigured set.
rc : dict, optional
Parameter mappings to override the values in the preset seaborn
style dictionaries. This only updates parameters that are
considered part of the style definition.
Examples
--------
>>> set_style("whitegrid")
>>> set_style("ticks", {"xtick.major.size": 8, "ytick.major.size": 8})
See Also
--------
axes_style : return a dict of parameters or use in a ``with`` statement
to temporarily set the style.
set_context : set parameters to scale plot elements
set_palette : set the default color palette for figures
"""
style_object = axes_style(style, rc)
mpl.rcParams.update(style_object)
def plotting_context(context=None, font_scale=1, rc=None):
"""Return a parameter dict to scale elements of the figure.
This affects things like the size of the labels, lines, and other
elements of the plot, but not the overall style. The base context
is "notebook", and the other contexts are "paper", "talk", and "poster",
which are version of the notebook parameters scaled by .8, 1.3, and 1.6,
respectively.
This function returns an object that can be used in a ``with`` statement
to temporarily change the context parameters.
Parameters
----------
context : dict, None, or one of {paper, notebook, talk, poster}
A dictionary of parameters or the name of a preconfigured set.
font_scale : float, optional
Separate scaling factor to independently scale the size of the
font elements.
rc : dict, optional
Parameter mappings to override the values in the preset seaborn
context dictionaries. This only updates parameters that are
considered part of the context definition.
Examples
--------
>>> c = plotting_context("poster")
>>> c = plotting_context("notebook", font_scale=1.5)
>>> c = plotting_context("talk", rc={"lines.linewidth": 2})
>>> import matplotlib.pyplot as plt
>>> with plotting_context("paper"):
... f, ax = plt.subplots()
... ax.plot(x, y) # doctest: +SKIP
See Also
--------
set_context : set the matplotlib parameters to scale plot elements
axes_style : return a dict of parameters defining a figure style
color_palette : define the color palette for a plot
"""
if context is None:
context_dict = {k: mpl.rcParams[k] for k in _context_keys}
elif isinstance(context, dict):
context_dict = context
else:
contexts = ["paper", "notebook", "talk", "poster"]
if context not in contexts:
raise ValueError("context must be in %s" % ", ".join(contexts))
# Set up dictionary of default parameters
base_context = {
"figure.figsize": np.array([8, 5.5]),
"axes.labelsize": 11,
"axes.titlesize": 12,
"xtick.labelsize": 10,
"ytick.labelsize": 10,
"legend.fontsize": 10,
"grid.linewidth": 1,
"lines.linewidth": 1.75,
"patch.linewidth": .3,
"lines.markersize": 7,
"lines.markeredgewidth": 0,
"xtick.major.width": 1,
"ytick.major.width": 1,
"xtick.minor.width": .5,
"ytick.minor.width": .5,
"xtick.major.pad": 7,
"ytick.major.pad": 7,
}
# Scale all the parameters by the same factor depending on the context
scaling = dict(paper=.8, notebook=1, talk=1.3, poster=1.6)[context]
context_dict = {k: v * scaling for k, v in base_context.items()}
# Now independently scale the fonts
font_keys = ["axes.labelsize", "axes.titlesize", "legend.fontsize",
"xtick.labelsize", "ytick.labelsize"]
font_dict = {k: context_dict[k] * font_scale for k in font_keys}
context_dict.update(font_dict)
# Override these settings with the provided rc dictionary
if rc is not None:
rc = {k: v for k, v in rc.items() if k in _context_keys}
context_dict.update(rc)
# Wrap in a _PlottingContext object so this can be used in a with statement
context_object = _PlottingContext(context_dict)
return context_object
def set_context(context=None, font_scale=1, rc=None):
"""Set the plotting context parameters.
This affects things like the size of the labels, lines, and other
elements of the plot, but not the overall style. The base context
is "notebook", and the other contexts are "paper", "talk", and "poster",
which are version of the notebook parameters scaled by .8, 1.3, and 1.6,
respectively.
Parameters
----------
context : dict, None, or one of {paper, notebook, talk, poster}
A dictionary of parameters or the name of a preconfigured set.
font_scale : float, optional
Separate scaling factor to independently scale the size of the
font elements.
rc : dict, optional
Parameter mappings to override the values in the preset seaborn
context dictionaries. This only updates parameters that are
considered part of the context definition.
Examples
--------
>>> set_context("paper")
>>> set_context("talk", font_scale=1.4)
>>> set_context("talk", rc={"lines.linewidth": 2})
See Also
--------
plotting_context : return a dictionary of rc parameters, or use in
a ``with`` statement to temporarily set the context.
set_style : set the default parameters for figure style
set_palette : set the default color palette for figures
"""
context_object = plotting_context(context, font_scale, rc)
mpl.rcParams.update(context_object)
def set_palette(name, n_colors=6, desat=None):
"""Set the matplotlib color cycle using a seaborn palette.
Parameters
----------
name : hls | husl | matplotlib colormap | seaborn color palette
Palette definition. Should be something that :func:`color_palette`
can process.
n_colors : int
Number of colors in the cycle.
desat : float
Factor to desaturate each color by.
Examples
--------
>>> set_palette("Reds")
>>> set_palette("Set1", 8, .75)
See Also
--------
color_palette : build a color palette or set the color cycle temporarily
in a ``with`` statement.
set_context : set parameters to scale plot elements
set_style : set the default parameters for figure style
"""
colors = palettes.color_palette(name, n_colors, desat)
mpl.rcParams["axes.color_cycle"] = list(colors)
mpl.rcParams["patch.facecolor"] = colors[0]
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