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Handle MOVETO's, CLOSEPOLY's and empty paths in Path.interpolated#29919

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Merged
timhoffm merged 3 commits intomatplotlib:mainfromrcomer:geo-contour
Apr 18, 2025
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29 changes: 25 additions & 4 deletionslib/matplotlib/path.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -667,14 +667,35 @@ def intersects_bbox(self, bbox, filled=True):

def interpolated(self, steps):
"""
Return a new pathresampled to length N x *steps*.
Return a new pathwith each segment divided into *steps* parts.

Codes other than `LINETO` are not handled correctly.
Codes other than `LINETO`, `MOVETO`, and `CLOSEPOLY` are not handled correctly.

Parameters
----------
steps : int
The number of segments in the new path for each in the original.

Returns
-------
Path
The interpolated path.
"""
if steps == 1:
if steps == 1 or len(self) == 0:
return self

vertices = simple_linear_interpolation(self.vertices, steps)
if self.codes is not None and self.MOVETO in self.codes[1:]:
return self.make_compound_path(
*(p.interpolated(steps) for p in self._iter_connected_components()))

if self.codes is not None and self.CLOSEPOLY in self.codes and not np.all(
self.vertices[self.codes == self.CLOSEPOLY] == self.vertices[0]):
vertices = self.vertices.copy()
vertices[self.codes == self.CLOSEPOLY] = vertices[0]
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@timhoffmtimhoffmApr 17, 2025•
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I think this patch is not sufficient if you have a path with mixtures of CLOSEPOLY AND MOVETO. The MOVETO creates a new separate separate component with a starting point that is generally different fromvertices[0].

Maybe a variation of_iter_connected_components is the way to go?

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@rcomerrcomerApr 17, 2025•
edited
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But if we got to here, we have no internalMOVETO's because we already split on them and called the function again on the subpath. I think this case is covered by the newtest_interpolated_moveto_closepoly.

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Yes, you are right.

else:
vertices = self.vertices

vertices = simple_linear_interpolation(vertices, steps)
codes = self.codes
if codes is not None:
new_codes = np.full((len(codes) - 1) * steps + 1, Path.LINETO,
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81 changes: 81 additions & 0 deletionslib/matplotlib/tests/test_path.py
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Expand Up@@ -541,3 +541,84 @@ def test_cleanup_closepoly():
cleaned = p.cleaned(remove_nans=True)
assert len(cleaned) == 1
assert cleaned.codes[0] == Path.STOP


def test_interpolated_moveto():
# Initial path has two subpaths with two LINETOs each
vertices = np.array([[0, 0],
[0, 1],
[1, 2],
[4, 4],
[4, 5],
[5, 5]])
codes = [Path.MOVETO, Path.LINETO, Path.LINETO] * 2

path = Path(vertices, codes)
result = path.interpolated(3)

# Result should have two subpaths with six LINETOs each
expected_subpath_codes = [Path.MOVETO] + [Path.LINETO] * 6
np.testing.assert_array_equal(result.codes, expected_subpath_codes * 2)


def test_interpolated_closepoly():
codes = [Path.MOVETO] + [Path.LINETO]*2 + [Path.CLOSEPOLY]
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Test a compound path with multiple closepolys by doubling this again similar to your above test to make sure the implementation handles multiple MOVETOs and CLOSEPOLYS together?

vertices = [(4, 3), (5, 4), (5, 3), (0, 0)]

path = Path(vertices, codes)
result = path.interpolated(2)

expected_vertices = np.array([[4, 3],
[4.5, 3.5],
[5, 4],
[5, 3.5],
[5, 3],
[4.5, 3],
[4, 3]])
expected_codes = [Path.MOVETO] + [Path.LINETO]*5 + [Path.CLOSEPOLY]

np.testing.assert_allclose(result.vertices, expected_vertices)
np.testing.assert_array_equal(result.codes, expected_codes)

# Usually closepoly is the last vertex but does not have to be.
codes += [Path.LINETO]
vertices += [(2, 1)]

path = Path(vertices, codes)
result = path.interpolated(2)

extra_expected_vertices = np.array([[3, 2],
[2, 1]])
expected_vertices = np.concatenate([expected_vertices, extra_expected_vertices])

expected_codes += [Path.LINETO] * 2

np.testing.assert_allclose(result.vertices, expected_vertices)
np.testing.assert_array_equal(result.codes, expected_codes)


def test_interpolated_moveto_closepoly():
# Initial path has two closed subpaths
codes = ([Path.MOVETO] + [Path.LINETO]*2 + [Path.CLOSEPOLY]) * 2
vertices = [(4, 3), (5, 4), (5, 3), (0, 0), (8, 6), (10, 8), (10, 6), (0, 0)]

path = Path(vertices, codes)
result = path.interpolated(2)

expected_vertices1 = np.array([[4, 3],
[4.5, 3.5],
[5, 4],
[5, 3.5],
[5, 3],
[4.5, 3],
[4, 3]])
expected_vertices = np.concatenate([expected_vertices1, expected_vertices1 * 2])
expected_codes = ([Path.MOVETO] + [Path.LINETO]*5 + [Path.CLOSEPOLY]) * 2

np.testing.assert_allclose(result.vertices, expected_vertices)
np.testing.assert_array_equal(result.codes, expected_codes)


def test_interpolated_empty_path():
path = Path(np.zeros((0, 2)))
assert path.interpolated(42) is path
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