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Add new downsample method for lines #7632

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90692fe
untested proof of concept
kbrose Dec 17, 2016
c956349
renaming to avoid name clash with reduce
kbrose Dec 17, 2016
3cb6dd0
initializing value of downsample
kbrose Dec 17, 2016
e55b107
refactoring to bring _downsample_path into Line
kbrose Dec 17, 2016
99883ed
adding test
kbrose Dec 17, 2016
624786b
adding example
kbrose Dec 17, 2016
b6c4b2c
fixing nose test for np array equality
kbrose Dec 18, 2016
86f1612
pep8 conformance
kbrose Dec 18, 2016
e6b62a1
adding property, clean up docstring
kbrose Dec 18, 2016
b11984e
simplifying loop per suggestion from @efiring
kbrose Dec 19, 2016
445a051
using property decorator, works for non-linear axes scales
kbrose Dec 19, 2016
d460c90
guarding against NaN y-values and non-monotonic x-values
kbrose Dec 19, 2016
5a9bc7a
updating test to reflect changes
kbrose Dec 20, 2016
0fd581b
adding docstring to the example
kbrose Dec 31, 2016
f9d359b
downsample docstring cleanups
kbrose Dec 31, 2016
53f5ca9
adding a whats-new description
kbrose Dec 31, 2016
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adding test
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@kbrose
kbrose committed Dec 17, 2016
commit 99883edd0c213e9828163598531dffdc1eaa11c1
33 changes: 32 additions & 1 deletion lib/matplotlib/tests/test_lines.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
import itertools
import matplotlib.lines as mlines
import nose
from nose.tools import assert_true, assert_raises
from nose.tools import assert_true, assert_raises, assert_equal
from timeit import repeat
import numpy as np
from cycler import cycler
Expand Down Expand Up @@ -191,5 +191,36 @@ def test_nan_is_sorted():
assert_true(not line._is_sorted([3, 5] + [np.nan] * 100 + [0, 2]))


@cleanup
def test_downsample_lines():
x = np.array([0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1.0])
y = np.array([2, 8, 3, 6, 1, 5, 5, 8, 7, 6, 6, 7.0])

line = mlines.Line2D(x, y, downsample=True)

fig, ax = plt.subplots()

# Adjust size of figure to ensure downsampling occurs
fig.set_dpi(1)
fig.set_size_inches([2,1])

ax.add_line(line)

tpath, _ = line._get_transformed_path().get_transformed_path_and_affine()
down_verts = line._downsample_path(tpath).vertices

expected_down_verts = np.array([
[0.0, 2.0],
[0.0, 1.0],
[0.0, 8.0],
[0.0, 5.0],
[1.0, 5.0],
[1.0, 5.0],
[1.0, 8.0],
[1.0, 7.0]
])
assert_equal(down_verts, expected_down_verts)


if __name__ == '__main__':
nose.runmodule(argv=['-s', '--with-doctest'], exit=False)