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Fix containment test with nonlinear transforms. #7844

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Merged
merged 2 commits into from
Mar 19, 2017
Merged

Fix containment test with nonlinear transforms. #7844

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15eb7e7
Fix containment test with nonlinear transforms.
anntzer Jan 16, 2017
76173e1
Test path containment w/ nonlin. transforms; group containment tests.
anntzer Jan 28, 2017
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16 changes: 10 additions & 6 deletions lib/matplotlib/path.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,9 +22,8 @@

import numpy as np

from matplotlib import _path
from matplotlib.cbook import simple_linear_interpolation, maxdict
from matplotlib import rcParams
from . import _path, rcParams
from .cbook import simple_linear_interpolation, maxdict


class Path(object):
Expand Down Expand Up @@ -493,9 +492,14 @@ def contains_point(self, point, transform=None, radius=0.0):
"""
if transform is not None:
transform = transform.frozen()
result = _path.point_in_path(point[0], point[1], radius, self,
transform)
return result
# `point_in_path` does not handle nonlinear transforms, so we
# transform the path ourselves. If `transform` is affine, letting
# `point_in_path` handle the transform avoids allocating an extra
# buffer.
if transform and not transform.is_affine:
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Is there a reason not to just do the transformation here even if it is an affine transformation? (thus removing the if block)

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I guess you may save the creation of a large temporary (if the c++ code does the transform one point at a time), which would be relevant for very large paths.

To be honest I don't know but decided not to take any risks.

self = transform.transform_path(self)
transform = None
return _path.point_in_path(point[0], point[1], radius, self, transform)

def contains_points(self, points, transform=None, radius=0.0):
"""
Expand Down
30 changes: 21 additions & 9 deletions lib/matplotlib/tests/test_path.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,6 +45,27 @@ def test_contains_points_negative_radius():
assert np.all(result == expected)


def test_point_in_path_nan():
box = np.array([[0, 0], [1, 0], [1, 1], [0, 1], [0, 0]])
p = Path(box)
test = np.array([[np.nan, 0.5]])
contains = p.contains_points(test)
assert len(contains) == 1
assert not contains[0]


def test_nonlinear_containment():
fig, ax = plt.subplots()
ax.set(xscale="log", ylim=(0, 1))
polygon = ax.axvspan(1, 10)
assert polygon.get_path().contains_point(
ax.transData.transform_point((5, .5)), ax.transData)
assert not polygon.get_path().contains_point(
ax.transData.transform_point((.5, .5)), ax.transData)
assert not polygon.get_path().contains_point(
ax.transData.transform_point((50, .5)), ax.transData)


@image_comparison(baseline_images=['path_clipping'],
extensions=['svg'], remove_text=True)
def test_path_clipping():
Expand All @@ -66,15 +87,6 @@ def test_path_clipping():
xy, facecolor='none', edgecolor='red', closed=True))


def test_point_in_path_nan():
box = np.array([[0, 0], [1, 0], [1, 1], [0, 1], [0, 0]])
p = Path(box)
test = np.array([[np.nan, 0.5]])
contains = p.contains_points(test)
assert len(contains) == 1
assert not contains[0]


@image_comparison(baseline_images=['semi_log_with_zero'], extensions=['png'])
def test_log_transform_with_zero():
x = np.arange(-10, 10)
Expand Down