| 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576777879808182838485868788899091 |
- import pytest
- import numpy as np
- from numpy.testing import assert_, assert_array_equal, assert_allclose
- try:
- import matplotlib
- matplotlib.rcParams['backend'] = 'Agg'
- import matplotlib.pyplot as plt
- has_matplotlib = True
- except Exception:
- has_matplotlib = False
- from scipy.spatial import \
- delaunay_plot_2d, voronoi_plot_2d, convex_hull_plot_2d, \
- Delaunay, Voronoi, ConvexHull
- @pytest.mark.skipif(not has_matplotlib, reason="Matplotlib not available")
- class TestPlotting:
- points = [(0,0), (0,1), (1,0), (1,1)]
- def test_delaunay(self):
- # Smoke test
- fig = plt.figure()
- obj = Delaunay(self.points)
- s_before = obj.simplices.copy()
- r = delaunay_plot_2d(obj, ax=fig.gca())
- assert_array_equal(obj.simplices, s_before) # shouldn't modify
- assert_(r is fig)
- delaunay_plot_2d(obj, ax=fig.gca())
- def test_voronoi(self):
- # Smoke test
- fig = plt.figure()
- obj = Voronoi(self.points)
- r = voronoi_plot_2d(obj, ax=fig.gca())
- assert_(r is fig)
- voronoi_plot_2d(obj)
- voronoi_plot_2d(obj, show_vertices=False)
- def test_convex_hull(self):
- # Smoke test
- fig = plt.figure()
- tri = ConvexHull(self.points)
- r = convex_hull_plot_2d(tri, ax=fig.gca())
- assert_(r is fig)
- convex_hull_plot_2d(tri)
- def test_gh_19653(self):
- # aspect ratio sensitivity of voronoi_plot_2d
- # infinite Voronoi edges
- points = np.array([[245.059986986012, 10.971011721360075],
- [320.49044143557785, 10.970258360366753],
- [239.79023081978914, 13.108487516946218],
- [263.38325791238833, 12.93241352743668],
- [219.53334398353175, 13.346107628161008]])
- vor = Voronoi(points)
- fig = voronoi_plot_2d(vor)
- ax = fig.gca()
- infinite_segments = ax.collections[1].get_segments()
- expected_segments = np.array([[[282.77256, -254.76904],
- [282.729714, -4544.744698]],
- [[282.77256014, -254.76904029],
- [430.08561382, 4032.67658742]],
- [[229.26733285, -20.39957514],
- [-168.17167404, -4291.92545966]],
- [[289.93433364, 5151.40412217],
- [330.40553385, 9441.18887532]]])
- assert_allclose(infinite_segments, expected_segments)
- def test_gh_19653_smaller_aspect(self):
- # reasonable behavior for less extreme aspect
- # ratio
- points = np.array([[24.059986986012, 10.971011721360075],
- [32.49044143557785, 10.970258360366753],
- [23.79023081978914, 13.108487516946218],
- [26.38325791238833, 12.93241352743668],
- [21.53334398353175, 13.346107628161008]])
- vor = Voronoi(points)
- fig = voronoi_plot_2d(vor)
- ax = fig.gca()
- infinite_segments = ax.collections[1].get_segments()
- expected_segments = np.array([[[28.274979, 8.335027],
- [28.270463, -42.19763338]],
- [[28.27497869, 8.33502697],
- [43.73223829, 56.44555501]],
- [[22.51805823, 11.8621754],
- [-12.09266506, -24.95694485]],
- [[29.53092448, 78.46952378],
- [33.82572726, 128.81934455]]])
- assert_allclose(infinite_segments, expected_segments)
|
