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Refactor color parsing of Axes.scatter
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@anntzer
anntzer authored Nov 4, 2018
2 parents 2f796c4 + 1b68e69 commit ac0525e
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259 changes: 151 additions & 108 deletions lib/matplotlib/axes/_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
import itertools
import logging
import math
import operator
from numbers import Number
import warnings

Expand Down Expand Up @@ -4012,6 +4013,150 @@ def dopatch(xs, ys, **kwargs):
return dict(whiskers=whiskers, caps=caps, boxes=boxes,
medians=medians, fliers=fliers, means=means)

def _parse_scatter_color_args(self, c, edgecolors, kwargs, xshape, yshape):
"""
Helper function to process color related arguments of `.Axes.scatter`.
Argument precedence for facecolors:
- c (if not None)
- kwargs['facecolors']
- kwargs['facecolor']
- kwargs['color'] (==kwcolor)
- 'b' if in classic mode else next color from color cycle
Argument precedence for edgecolors:
- edgecolors (is an explicit kw argument in scatter())
- kwargs['edgecolor']
- kwargs['color'] (==kwcolor)
- 'face' if not in classic mode else None
Arguments
---------
c : color or sequence or sequence of color or None
See argument description of `.Axes.scatter`.
edgecolors : color or sequence of color or {'face', 'none'} or None
See argument description of `.Axes.scatter`.
kwargs : dict
Additional kwargs. If these keys exist, we pop and process them:
'facecolors', 'facecolor', 'edgecolor', 'color'
Note: The dict is modified by this function.
xshape, yshape : tuple of int
The shape of the x and y arrays passed to `.Axes.scatter`.
Returns
-------
c
The input *c* if it was not *None*, else some color specification
derived from the other inputs or defaults.
colors : array(N, 4) or None
The facecolors as RGBA values or *None* if a colormap is used.
edgecolors
The edgecolor specification.
"""
xsize = functools.reduce(operator.mul, xshape, 1)
ysize = functools.reduce(operator.mul, yshape, 1)

facecolors = kwargs.pop('facecolors', None)
facecolors = kwargs.pop('facecolor', facecolors)
edgecolors = kwargs.pop('edgecolor', edgecolors)

kwcolor = kwargs.pop('color', None)

if kwcolor is not None and c is not None:
raise ValueError("Supply a 'c' argument or a 'color'"
" kwarg but not both; they differ but"
" their functionalities overlap.")

if kwcolor is not None:
try:
mcolors.to_rgba_array(kwcolor)
except ValueError:
raise ValueError("'color' kwarg must be an mpl color"
" spec or sequence of color specs.\n"
"For a sequence of values to be color-mapped,"
" use the 'c' argument instead.")
if edgecolors is None:
edgecolors = kwcolor
if facecolors is None:
facecolors = kwcolor

if edgecolors is None and not rcParams['_internal.classic_mode']:
edgecolors = 'face'

c_was_none = c is None
if c is None:
c = (facecolors if facecolors is not None
else "b" if rcParams['_internal.classic_mode']
else self._get_patches_for_fill.get_next_color())

# After this block, c_array will be None unless
# c is an array for mapping. The potential ambiguity
# with a sequence of 3 or 4 numbers is resolved in
# favor of mapping, not rgb or rgba.
# Convenience vars to track shape mismatch *and* conversion failures.
valid_shape = True # will be put to the test!
n_elem = -1 # used only for (some) exceptions

if (c_was_none or
kwcolor is not None or
isinstance(c, str) or
(isinstance(c, collections.abc.Iterable) and
len(c) > 0 and
isinstance(cbook.safe_first_element(c), str))):
c_array = None
else:
try: # First, does 'c' look suitable for value-mapping?
c_array = np.asanyarray(c, dtype=float)
n_elem = c_array.shape[0]
if c_array.shape in [xshape, yshape]:
c = np.ma.ravel(c_array)
else:
if c_array.shape in ((3,), (4,)):
_log.warning(
"'c' argument looks like a single numeric RGB or "
"RGBA sequence, which should be avoided as value-"
"mapping will have precedence in case its length "
"matches with 'x' & 'y'. Please use a 2-D array "
"with a single row if you really want to specify "
"the same RGB or RGBA value for all points.")
# Wrong size; it must not be intended for mapping.
valid_shape = False
c_array = None
except ValueError:
# Failed to make a floating-point array; c must be color specs.
c_array = None
if c_array is None:
try: # Then is 'c' acceptable as PathCollection facecolors?
colors = mcolors.to_rgba_array(c)
n_elem = colors.shape[0]
if colors.shape[0] not in (0, 1, xsize, ysize):
# NB: remember that a single color is also acceptable.
# Besides *colors* will be an empty array if c == 'none'.
valid_shape = False
raise ValueError
except ValueError:
if not valid_shape: # but at least one conversion succeeded.
raise ValueError(
"'c' argument has {nc} elements, which is not "
"acceptable for use with 'x' with size {xs}, "
"'y' with size {ys}."
.format(nc=n_elem, xs=xsize, ys=ysize)
)
else:
# Both the mapping *and* the RGBA conversion failed: pretty
# severe failure => one may appreciate a verbose feedback.
raise ValueError(
"'c' argument must be a mpl color, a sequence of mpl "
"colors or a sequence of numbers, not {}."
.format(c) # note: could be long depending on c
)
else:
colors = None # use cmap, norm after collection is created
return c, colors, edgecolors

@_preprocess_data(replace_names=["x", "y", "s", "linewidths",
"edgecolors", "c", "facecolor",
"facecolors", "color"],
Expand Down Expand Up @@ -4125,129 +4270,27 @@ def scatter(self, x, y, s=None, c=None, marker=None, cmap=None, norm=None,
"""
# Process **kwargs to handle aliases, conflicts with explicit kwargs:
facecolors = None
edgecolors = kwargs.pop('edgecolor', edgecolors)
fc = kwargs.pop('facecolors', None)
fc = kwargs.pop('facecolor', fc)
if fc is not None:
facecolors = fc
co = kwargs.pop('color', None)
if co is not None:
try:
mcolors.to_rgba_array(co)
except ValueError:
raise ValueError("'color' kwarg must be an mpl color"
" spec or sequence of color specs.\n"
"For a sequence of values to be color-mapped,"
" use the 'c' argument instead.")
if edgecolors is None:
edgecolors = co
if facecolors is None:
facecolors = co
if c is not None:
raise ValueError("Supply a 'c' argument or a 'color'"
" kwarg but not both; they differ but"
" their functionalities overlap.")
if c is None:
if facecolors is not None:
c = facecolors
else:
if rcParams['_internal.classic_mode']:
c = 'b' # The original default
else:
c = self._get_patches_for_fill.get_next_color()
c_none = True
else:
c_none = False

if edgecolors is None and not rcParams['_internal.classic_mode']:
edgecolors = 'face'

self._process_unit_info(xdata=x, ydata=y, kwargs=kwargs)
x = self.convert_xunits(x)
y = self.convert_yunits(y)

# np.ma.ravel yields an ndarray, not a masked array,
# unless its argument is a masked array.
xy_shape = (np.shape(x), np.shape(y))
xshape, yshape = np.shape(x), np.shape(y)
x = np.ma.ravel(x)
y = np.ma.ravel(y)
if x.size != y.size:
raise ValueError("x and y must be the same size")

if s is None:
if rcParams['_internal.classic_mode']:
s = 20
else:
s = rcParams['lines.markersize'] ** 2.0

s = (20 if rcParams['_internal.classic_mode'] else
rcParams['lines.markersize'] ** 2.0)
s = np.ma.ravel(s) # This doesn't have to match x, y in size.

# After this block, c_array will be None unless
# c is an array for mapping. The potential ambiguity
# with a sequence of 3 or 4 numbers is resolved in
# favor of mapping, not rgb or rgba.

# Convenience vars to track shape mismatch *and* conversion failures.
valid_shape = True # will be put to the test!
n_elem = -1 # used only for (some) exceptions

if (c_none or
co is not None or
isinstance(c, str) or
(isinstance(c, collections.Iterable) and
len(c) > 0 and
isinstance(cbook.safe_first_element(c), str))):
c_array = None
else:
try: # First, does 'c' look suitable for value-mapping?
c_array = np.asanyarray(c, dtype=float)
n_elem = c_array.shape[0]
if c_array.shape in xy_shape:
c = np.ma.ravel(c_array)
else:
if c_array.shape in ((3,), (4,)):
_log.warning(
"'c' argument looks like a single numeric RGB or "
"RGBA sequence, which should be avoided as value-"
"mapping will have precedence in case its length "
"matches with 'x' & 'y'. Please use a 2-D array "
"with a single row if you really want to specify "
"the same RGB or RGBA value for all points.")
# Wrong size; it must not be intended for mapping.
valid_shape = False
c_array = None
except ValueError:
# Failed to make a floating-point array; c must be color specs.
c_array = None

if c_array is None:
try: # Then is 'c' acceptable as PathCollection facecolors?
colors = mcolors.to_rgba_array(c)
n_elem = colors.shape[0]
if colors.shape[0] not in (0, 1, x.size, y.size):
# NB: remember that a single color is also acceptable.
# Besides *colors* will be an empty array if c == 'none'.
valid_shape = False
raise ValueError
except ValueError:
if not valid_shape: # but at least one conversion succeeded.
raise ValueError(
"'c' argument has {nc} elements, which is not "
"acceptable for use with 'x' with size {xs}, "
"'y' with size {ys}."
.format(nc=n_elem, xs=x.size, ys=y.size)
)
# Both the mapping *and* the RGBA conversion failed: pretty
# severe failure => one may appreciate a verbose feedback.
raise ValueError(
"'c' argument must either be valid as mpl color(s) "
"or as numbers to be mapped to colors. "
"Here c = {}." # <- beware, could be long depending on c.
.format(c)
)
else:
colors = None # use cmap, norm after collection is created
c, colors, edgecolors = \
self._parse_scatter_color_args(c, edgecolors, kwargs,
xshape, yshape)

# `delete_masked_points` only modifies arguments of the same length as
# `x`.
Expand Down
62 changes: 61 additions & 1 deletion lib/matplotlib/tests/test_axes.py
View file
Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
from collections import namedtuple
from itertools import product
from distutils.version import LooseVersion
import io
Expand Down Expand Up @@ -1795,7 +1796,7 @@ def test_scatter_c(self, c_case, re_key):
# Additional checking of *c* (introduced in #11383).
REGEXP = {
"shape": "^'c' argument has [0-9]+ elements", # shape mismatch
"conversion": "^'c' argument must either be valid", # bad vals
"conversion": "^'c' argument must be a mpl color", # bad vals
}
x = y = [0, 1, 2, 3]
fig, ax = plt.subplots()
Expand All @@ -1807,6 +1808,65 @@ def test_scatter_c(self, c_case, re_key):
ax.scatter(x, y, c=c_case, edgecolors="black")


def _params(c=None, xshape=(2,), yshape=(2,), **kwargs):
edgecolors = kwargs.pop('edgecolors', None)
return (c, edgecolors, kwargs if kwargs is not None else {},
xshape, yshape)
_result = namedtuple('_result', 'c, colors')


@pytest.mark.parametrize('params, expected_result',
[(_params(),
_result(c='b', colors=np.array([[0, 0, 1, 1]]))),
(_params(c='r'),
_result(c='r', colors=np.array([[1, 0, 0, 1]]))),
(_params(c='r', colors='b'),
_result(c='r', colors=np.array([[1, 0, 0, 1]]))),
# color
(_params(color='b'),
_result(c='b', colors=np.array([[0, 0, 1, 1]]))),
(_params(color=['b', 'g']),
_result(c=['b', 'g'], colors=np.array([[0, 0, 1, 1], [0, .5, 0, 1]]))),
])
def test_parse_scatter_color_args(params, expected_result):
from matplotlib.axes import Axes
dummyself = 'UNUSED' # self is only used in one case, which we do not
# test. Therefore we can get away without costly
# creating an Axes instance.
c, colors, _edgecolors = Axes._parse_scatter_color_args(dummyself, *params)
assert c == expected_result.c
assert_allclose(colors, expected_result.colors)

del _params
del _result


@pytest.mark.parametrize('kwargs, expected_edgecolors',
[(dict(), None),
(dict(c='b'), None),
(dict(edgecolors='r'), 'r'),
(dict(edgecolors=['r', 'g']), ['r', 'g']),
(dict(edgecolor='r'), 'r'),
(dict(edgecolors='face'), 'face'),
(dict(edgecolors='none'), 'none'),
(dict(edgecolor='r', edgecolors='g'), 'r'),
(dict(c='b', edgecolor='r', edgecolors='g'), 'r'),
(dict(color='r'), 'r'),
(dict(color='r', edgecolor='g'), 'g'),
])
def test_parse_scatter_color_args_edgecolors(kwargs, expected_edgecolors):
from matplotlib.axes import Axes
dummyself = 'UNUSED' # self is only used in one case, which we do not
# test. Therefore we can get away without costly
# creating an Axes instance.
c = kwargs.pop('c', None)
edgecolors = kwargs.pop('edgecolors', None)
_, _, result_edgecolors = \
Axes._parse_scatter_color_args(dummyself, c, edgecolors, kwargs,
xshape=(2,), yshape=(2,))
assert result_edgecolors == expected_edgecolors


def test_as_mpl_axes_api():
# tests the _as_mpl_axes api
from matplotlib.projections.polar import PolarAxes
Expand Down

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