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Fixed database typo and removed unnecessary class identifier.

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Batuhan Berk Başoğlu 2020-10-14 10:10:37 -04:00
parent 00ad49a143
commit 45fb349a7d
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venv/Lib/site-packages/scipy/spatial/tests/test_hausdorff.py Normal file
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import numpy as np
from numpy.testing import (assert_almost_equal,
assert_array_equal,
assert_equal,
assert_)
import pytest
from scipy.spatial.distance import directed_hausdorff
from scipy.spatial import distance
from scipy._lib._util import check_random_state
class TestHausdorff(object):
# Test various properties of the directed Hausdorff code.
def setup_method(self):
np.random.seed(1234)
random_angles = np.random.random(100) * np.pi * 2
random_columns = np.column_stack(
(random_angles, random_angles, np.zeros(100)))
random_columns[..., 0] = np.cos(random_columns[..., 0])
random_columns[..., 1] = np.sin(random_columns[..., 1])
random_columns_2 = np.column_stack(
(random_angles, random_angles, np.zeros(100)))
random_columns_2[1:, 0] = np.cos(random_columns_2[1:, 0]) * 2.0
random_columns_2[1:, 1] = np.sin(random_columns_2[1:, 1]) * 2.0
# move one point farther out so we don't have two perfect circles
random_columns_2[0, 0] = np.cos(random_columns_2[0, 0]) * 3.3
random_columns_2[0, 1] = np.sin(random_columns_2[0, 1]) * 3.3
self.path_1 = random_columns
self.path_2 = random_columns_2
self.path_1_4d = np.insert(self.path_1, 3, 5, axis=1)
self.path_2_4d = np.insert(self.path_2, 3, 27, axis=1)
def test_symmetry(self):
# Ensure that the directed (asymmetric) Hausdorff distance is
# actually asymmetric
forward = directed_hausdorff(self.path_1, self.path_2)[0]
reverse = directed_hausdorff(self.path_2, self.path_1)[0]
assert_(forward != reverse)
def test_brute_force_comparison_forward(self):
# Ensure that the algorithm for directed_hausdorff gives the
# same result as the simple / brute force approach in the
# forward direction.
actual = directed_hausdorff(self.path_1, self.path_2)[0]
# brute force over rows:
expected = max(np.amin(distance.cdist(self.path_1, self.path_2),
axis=1))
assert_almost_equal(actual, expected, decimal=9)
def test_brute_force_comparison_reverse(self):
# Ensure that the algorithm for directed_hausdorff gives the
# same result as the simple / brute force approach in the
# reverse direction.
actual = directed_hausdorff(self.path_2, self.path_1)[0]
# brute force over columns:
expected = max(np.amin(distance.cdist(self.path_1, self.path_2),
axis=0))
assert_almost_equal(actual, expected, decimal=9)
def test_degenerate_case(self):
# The directed Hausdorff distance must be zero if both input
# data arrays match.
actual = directed_hausdorff(self.path_1, self.path_1)[0]
assert_almost_equal(actual, 0.0, decimal=9)
def test_2d_data_forward(self):
# Ensure that 2D data is handled properly for a simple case
# relative to brute force approach.
actual = directed_hausdorff(self.path_1[..., :2],
self.path_2[..., :2])[0]
expected = max(np.amin(distance.cdist(self.path_1[..., :2],
self.path_2[..., :2]),
axis=1))
assert_almost_equal(actual, expected, decimal=9)
def test_4d_data_reverse(self):
# Ensure that 4D data is handled properly for a simple case
# relative to brute force approach.
actual = directed_hausdorff(self.path_2_4d, self.path_1_4d)[0]
# brute force over columns:
expected = max(np.amin(distance.cdist(self.path_1_4d, self.path_2_4d),
axis=0))
assert_almost_equal(actual, expected, decimal=9)
def test_indices(self):
# Ensure that correct point indices are returned -- they should
# correspond to the Hausdorff pair
path_simple_1 = np.array([[-1,-12],[0,0], [1,1], [3,7], [1,2]])
path_simple_2 = np.array([[0,0], [1,1], [4,100], [10,9]])
actual = directed_hausdorff(path_simple_2, path_simple_1)[1:]
expected = (2, 3)
assert_array_equal(actual, expected)
def test_random_state(self):
# ensure that the global random state is not modified because
# the directed Hausdorff algorithm uses randomization
rs = check_random_state(None)
old_global_state = rs.get_state()
directed_hausdorff(self.path_1, self.path_2)
rs2 = check_random_state(None)
new_global_state = rs2.get_state()
assert_equal(new_global_state, old_global_state)
def test_random_state_None_int(self):
# check that seed values of None or int do not alter global
# random state
for seed in [None, 27870671]:
rs = check_random_state(None)
old_global_state = rs.get_state()
directed_hausdorff(self.path_1, self.path_2, seed)
rs2 = check_random_state(None)
new_global_state = rs2.get_state()
assert_equal(new_global_state, old_global_state)
def test_invalid_dimensions(self):
# Ensure that a ValueError is raised when the number of columns
# is not the same
np.random.seed(1234)
A = np.random.rand(3, 2)
B = np.random.rand(4, 5)
with pytest.raises(ValueError):
directed_hausdorff(A, B)
@pytest.mark.parametrize("A, B, seed, expected", [
# the two cases from gh-11332
([(0,0)],
[(0,1), (0,0)],
0,
(0.0, 0, 1)),
([(0,0)],
[(0,1), (0,0)],
1,
(0.0, 0, 1)),
# slightly more complex case
([(-5, 3), (0,0)],
[(0,1), (0,0), (-5, 3)],
77098,
# the maximum minimum distance will
# be the last one found, but a unique
# solution is not guaranteed more broadly
(0.0, 1, 1)),
])
def test_subsets(self, A, B, seed, expected):
# verify fix for gh-11332
actual = directed_hausdorff(u=A, v=B, seed=seed)
# check distance
assert_almost_equal(actual[0], expected[0], decimal=9)
# check indices
assert actual[1:] == expected[1:]