laywerrobot/lib/python3.6/site-packages/pandas/plotting/_style.py
2020-08-27 21:55:39 +02:00

183 lines
6.4 KiB
Python

# being a bit too dynamic
# pylint: disable=E1101
from __future__ import division
import warnings
from contextlib import contextmanager
import re
import numpy as np
from pandas.core.dtypes.common import is_list_like
from pandas.compat import lrange, lmap
import pandas.compat as compat
from pandas.plotting._compat import _mpl_ge_2_0_0
def _get_standard_colors(num_colors=None, colormap=None, color_type='default',
color=None):
import matplotlib.pyplot as plt
if color is None and colormap is not None:
if isinstance(colormap, compat.string_types):
import matplotlib.cm as cm
cmap = colormap
colormap = cm.get_cmap(colormap)
if colormap is None:
raise ValueError("Colormap {0} is not recognized".format(cmap))
colors = lmap(colormap, np.linspace(0, 1, num=num_colors))
elif color is not None:
if colormap is not None:
warnings.warn("'color' and 'colormap' cannot be used "
"simultaneously. Using 'color'")
colors = list(color) if is_list_like(color) else color
else:
if color_type == 'default':
# need to call list() on the result to copy so we don't
# modify the global rcParams below
try:
colors = [c['color']
for c in list(plt.rcParams['axes.prop_cycle'])]
except KeyError:
colors = list(plt.rcParams.get('axes.color_cycle',
list('bgrcmyk')))
if isinstance(colors, compat.string_types):
colors = list(colors)
elif color_type == 'random':
import pandas.core.common as com
def random_color(column):
""" Returns a random color represented as a list of length 3"""
# GH17525 use common._random_state to avoid resetting the seed
rs = com._random_state(column)
return rs.rand(3).tolist()
colors = lmap(random_color, lrange(num_colors))
else:
raise ValueError("color_type must be either 'default' or 'random'")
if isinstance(colors, compat.string_types):
import matplotlib.colors
conv = matplotlib.colors.ColorConverter()
def _maybe_valid_colors(colors):
try:
[conv.to_rgba(c) for c in colors]
return True
except ValueError:
return False
# check whether the string can be convertible to single color
maybe_single_color = _maybe_valid_colors([colors])
# check whether each character can be convertible to colors
maybe_color_cycle = _maybe_valid_colors(list(colors))
if maybe_single_color and maybe_color_cycle and len(colors) > 1:
# Special case for single str 'CN' match and convert to hex
# for supporting matplotlib < 2.0.0
if re.match(r'\AC[0-9]\Z', colors) and _mpl_ge_2_0_0():
hex_color = [c['color']
for c in list(plt.rcParams['axes.prop_cycle'])]
colors = [hex_color[int(colors[1])]]
else:
# this may no longer be required
msg = ("'{0}' can be parsed as both single color and "
"color cycle. Specify each color using a list "
"like ['{0}'] or {1}")
raise ValueError(msg.format(colors, list(colors)))
elif maybe_single_color:
colors = [colors]
else:
# ``colors`` is regarded as color cycle.
# mpl will raise error any of them is invalid
pass
if len(colors) != num_colors:
try:
multiple = num_colors // len(colors) - 1
except ZeroDivisionError:
raise ValueError("Invalid color argument: ''")
mod = num_colors % len(colors)
colors += multiple * colors
colors += colors[:mod]
return colors
class _Options(dict):
"""
Stores pandas plotting options.
Allows for parameter aliasing so you can just use parameter names that are
the same as the plot function parameters, but is stored in a canonical
format that makes it easy to breakdown into groups later
"""
# alias so the names are same as plotting method parameter names
_ALIASES = {'x_compat': 'xaxis.compat'}
_DEFAULT_KEYS = ['xaxis.compat']
def __init__(self, deprecated=False):
self._deprecated = deprecated
# self['xaxis.compat'] = False
super(_Options, self).__setitem__('xaxis.compat', False)
def _warn_if_deprecated(self):
if self._deprecated:
warnings.warn("'pandas.plot_params' is deprecated. Use "
"'pandas.plotting.plot_params' instead",
FutureWarning, stacklevel=3)
def __getitem__(self, key):
self._warn_if_deprecated()
key = self._get_canonical_key(key)
if key not in self:
raise ValueError(
'{key} is not a valid pandas plotting option'.format(key=key))
return super(_Options, self).__getitem__(key)
def __setitem__(self, key, value):
self._warn_if_deprecated()
key = self._get_canonical_key(key)
return super(_Options, self).__setitem__(key, value)
def __delitem__(self, key):
key = self._get_canonical_key(key)
if key in self._DEFAULT_KEYS:
raise ValueError(
'Cannot remove default parameter {key}'.format(key=key))
return super(_Options, self).__delitem__(key)
def __contains__(self, key):
key = self._get_canonical_key(key)
return super(_Options, self).__contains__(key)
def reset(self):
"""
Reset the option store to its initial state
Returns
-------
None
"""
self._warn_if_deprecated()
self.__init__()
def _get_canonical_key(self, key):
return self._ALIASES.get(key, key)
@contextmanager
def use(self, key, value):
"""
Temporarily set a parameter value using the with statement.
Aliasing allowed.
"""
self._warn_if_deprecated()
old_value = self[key]
try:
self[key] = value
yield self
finally:
self[key] = old_value
plot_params = _Options()