tmp
/
pip-install-ghxuqwgs
/numpy_78e94bf2b6094bf9a1f3d92042f9bf46
/numpy
/lib
/tests
/test_shape_base.py
from __future__ import division, absolute_import, print_function | |
import numpy as np | |
from numpy.lib.shape_base import ( | |
apply_along_axis, apply_over_axes, array_split, split, hsplit, dsplit, | |
vsplit, dstack, kron, tile | |
) | |
from numpy.testing import ( | |
run_module_suite, TestCase, assert_, assert_equal, assert_array_equal, | |
assert_raises, assert_warns | |
) | |
class TestApplyAlongAxis(TestCase): | |
def test_simple(self): | |
a = np.ones((20, 10), 'd') | |
assert_array_equal( | |
apply_along_axis(len, 0, a), len(a)*np.ones(a.shape[1])) | |
def test_simple101(self, level=11): | |
a = np.ones((10, 101), 'd') | |
assert_array_equal( | |
apply_along_axis(len, 0, a), len(a)*np.ones(a.shape[1])) | |
def test_3d(self): | |
a = np.arange(27).reshape((3, 3, 3)) | |
assert_array_equal(apply_along_axis(np.sum, 0, a), | |
[[27, 30, 33], [36, 39, 42], [45, 48, 51]]) | |
class TestApplyOverAxes(TestCase): | |
def test_simple(self): | |
a = np.arange(24).reshape(2, 3, 4) | |
aoa_a = apply_over_axes(np.sum, a, [0, 2]) | |
assert_array_equal(aoa_a, np.array([[[60], [92], [124]]])) | |
class TestArraySplit(TestCase): | |
def test_integer_0_split(self): | |
a = np.arange(10) | |
assert_raises(ValueError, array_split, a, 0) | |
def test_integer_split(self): | |
a = np.arange(10) | |
res = array_split(a, 1) | |
desired = [np.arange(10)] | |
compare_results(res, desired) | |
res = array_split(a, 2) | |
desired = [np.arange(5), np.arange(5, 10)] | |
compare_results(res, desired) | |
res = array_split(a, 3) | |
desired = [np.arange(4), np.arange(4, 7), np.arange(7, 10)] | |
compare_results(res, desired) | |
res = array_split(a, 4) | |
desired = [np.arange(3), np.arange(3, 6), np.arange(6, 8), | |
np.arange(8, 10)] | |
compare_results(res, desired) | |
res = array_split(a, 5) | |
desired = [np.arange(2), np.arange(2, 4), np.arange(4, 6), | |
np.arange(6, 8), np.arange(8, 10)] | |
compare_results(res, desired) | |
res = array_split(a, 6) | |
desired = [np.arange(2), np.arange(2, 4), np.arange(4, 6), | |
np.arange(6, 8), np.arange(8, 9), np.arange(9, 10)] | |
compare_results(res, desired) | |
res = array_split(a, 7) | |
desired = [np.arange(2), np.arange(2, 4), np.arange(4, 6), | |
np.arange(6, 7), np.arange(7, 8), np.arange(8, 9), | |
np.arange(9, 10)] | |
compare_results(res, desired) | |
res = array_split(a, 8) | |
desired = [np.arange(2), np.arange(2, 4), np.arange(4, 5), | |
np.arange(5, 6), np.arange(6, 7), np.arange(7, 8), | |
np.arange(8, 9), np.arange(9, 10)] | |
compare_results(res, desired) | |
res = array_split(a, 9) | |
desired = [np.arange(2), np.arange(2, 3), np.arange(3, 4), | |
np.arange(4, 5), np.arange(5, 6), np.arange(6, 7), | |
np.arange(7, 8), np.arange(8, 9), np.arange(9, 10)] | |
compare_results(res, desired) | |
res = array_split(a, 10) | |
desired = [np.arange(1), np.arange(1, 2), np.arange(2, 3), | |
np.arange(3, 4), np.arange(4, 5), np.arange(5, 6), | |
np.arange(6, 7), np.arange(7, 8), np.arange(8, 9), | |
np.arange(9, 10)] | |
compare_results(res, desired) | |
res = array_split(a, 11) | |
desired = [np.arange(1), np.arange(1, 2), np.arange(2, 3), | |
np.arange(3, 4), np.arange(4, 5), np.arange(5, 6), | |
np.arange(6, 7), np.arange(7, 8), np.arange(8, 9), | |
np.arange(9, 10), np.array([])] | |
compare_results(res, desired) | |
def test_integer_split_2D_rows(self): | |
a = np.array([np.arange(10), np.arange(10)]) | |
res = assert_warns(FutureWarning, array_split, a, 3, axis=0) | |
# After removing the FutureWarning, the last should be zeros((0, 10)) | |
desired = [np.array([np.arange(10)]), np.array([np.arange(10)]), | |
np.array([])] | |
compare_results(res, desired) | |
assert_(a.dtype.type is res[-1].dtype.type) | |
def test_integer_split_2D_cols(self): | |
a = np.array([np.arange(10), np.arange(10)]) | |
res = array_split(a, 3, axis=-1) | |
desired = [np.array([np.arange(4), np.arange(4)]), | |
np.array([np.arange(4, 7), np.arange(4, 7)]), | |
np.array([np.arange(7, 10), np.arange(7, 10)])] | |
compare_results(res, desired) | |
def test_integer_split_2D_default(self): | |
""" This will fail if we change default axis | |
""" | |
a = np.array([np.arange(10), np.arange(10)]) | |
res = assert_warns(FutureWarning, array_split, a, 3) | |
# After removing the FutureWarning, the last should be zeros((0, 10)) | |
desired = [np.array([np.arange(10)]), np.array([np.arange(10)]), | |
np.array([])] | |
compare_results(res, desired) | |
assert_(a.dtype.type is res[-1].dtype.type) | |
# perhaps should check higher dimensions | |
def test_index_split_simple(self): | |
a = np.arange(10) | |
indices = [1, 5, 7] | |
res = array_split(a, indices, axis=-1) | |
desired = [np.arange(0, 1), np.arange(1, 5), np.arange(5, 7), | |
np.arange(7, 10)] | |
compare_results(res, desired) | |
def test_index_split_low_bound(self): | |
a = np.arange(10) | |
indices = [0, 5, 7] | |
res = array_split(a, indices, axis=-1) | |
desired = [np.array([]), np.arange(0, 5), np.arange(5, 7), | |
np.arange(7, 10)] | |
compare_results(res, desired) | |
def test_index_split_high_bound(self): | |
a = np.arange(10) | |
indices = [0, 5, 7, 10, 12] | |
res = array_split(a, indices, axis=-1) | |
desired = [np.array([]), np.arange(0, 5), np.arange(5, 7), | |
np.arange(7, 10), np.array([]), np.array([])] | |
compare_results(res, desired) | |
class TestSplit(TestCase): | |
# The split function is essentially the same as array_split, | |
# except that it test if splitting will result in an | |
# equal split. Only test for this case. | |
def test_equal_split(self): | |
a = np.arange(10) | |
res = split(a, 2) | |
desired = [np.arange(5), np.arange(5, 10)] | |
compare_results(res, desired) | |
def test_unequal_split(self): | |
a = np.arange(10) | |
assert_raises(ValueError, split, a, 3) | |
class TestDstack(TestCase): | |
def test_0D_array(self): | |
a = np.array(1) | |
b = np.array(2) | |
res = dstack([a, b]) | |
desired = np.array([[[1, 2]]]) | |
assert_array_equal(res, desired) | |
def test_1D_array(self): | |
a = np.array([1]) | |
b = np.array([2]) | |
res = dstack([a, b]) | |
desired = np.array([[[1, 2]]]) | |
assert_array_equal(res, desired) | |
def test_2D_array(self): | |
a = np.array([[1], [2]]) | |
b = np.array([[1], [2]]) | |
res = dstack([a, b]) | |
desired = np.array([[[1, 1]], [[2, 2, ]]]) | |
assert_array_equal(res, desired) | |
def test_2D_array2(self): | |
a = np.array([1, 2]) | |
b = np.array([1, 2]) | |
res = dstack([a, b]) | |
desired = np.array([[[1, 1], [2, 2]]]) | |
assert_array_equal(res, desired) | |
# array_split has more comprehensive test of splitting. | |
# only do simple test on hsplit, vsplit, and dsplit | |
class TestHsplit(TestCase): | |
"""Only testing for integer splits. | |
""" | |
def test_0D_array(self): | |
a = np.array(1) | |
try: | |
hsplit(a, 2) | |
assert_(0) | |
except ValueError: | |
pass | |
def test_1D_array(self): | |
a = np.array([1, 2, 3, 4]) | |
res = hsplit(a, 2) | |
desired = [np.array([1, 2]), np.array([3, 4])] | |
compare_results(res, desired) | |
def test_2D_array(self): | |
a = np.array([[1, 2, 3, 4], | |
[1, 2, 3, 4]]) | |
res = hsplit(a, 2) | |
desired = [np.array([[1, 2], [1, 2]]), np.array([[3, 4], [3, 4]])] | |
compare_results(res, desired) | |
class TestVsplit(TestCase): | |
"""Only testing for integer splits. | |
""" | |
def test_1D_array(self): | |
a = np.array([1, 2, 3, 4]) | |
try: | |
vsplit(a, 2) | |
assert_(0) | |
except ValueError: | |
pass | |
def test_2D_array(self): | |
a = np.array([[1, 2, 3, 4], | |
[1, 2, 3, 4]]) | |
res = vsplit(a, 2) | |
desired = [np.array([[1, 2, 3, 4]]), np.array([[1, 2, 3, 4]])] | |
compare_results(res, desired) | |
class TestDsplit(TestCase): | |
# Only testing for integer splits. | |
def test_2D_array(self): | |
a = np.array([[1, 2, 3, 4], | |
[1, 2, 3, 4]]) | |
try: | |
dsplit(a, 2) | |
assert_(0) | |
except ValueError: | |
pass | |
def test_3D_array(self): | |
a = np.array([[[1, 2, 3, 4], | |
[1, 2, 3, 4]], | |
[[1, 2, 3, 4], | |
[1, 2, 3, 4]]]) | |
res = dsplit(a, 2) | |
desired = [np.array([[[1, 2], [1, 2]], [[1, 2], [1, 2]]]), | |
np.array([[[3, 4], [3, 4]], [[3, 4], [3, 4]]])] | |
compare_results(res, desired) | |
class TestSqueeze(TestCase): | |
def test_basic(self): | |
from numpy.random import rand | |
a = rand(20, 10, 10, 1, 1) | |
b = rand(20, 1, 10, 1, 20) | |
c = rand(1, 1, 20, 10) | |
assert_array_equal(np.squeeze(a), np.reshape(a, (20, 10, 10))) | |
assert_array_equal(np.squeeze(b), np.reshape(b, (20, 10, 20))) | |
assert_array_equal(np.squeeze(c), np.reshape(c, (20, 10))) | |
# Squeezing to 0-dim should still give an ndarray | |
a = [[[1.5]]] | |
res = np.squeeze(a) | |
assert_equal(res, 1.5) | |
assert_equal(res.ndim, 0) | |
assert_equal(type(res), np.ndarray) | |
class TestKron(TestCase): | |
def test_return_type(self): | |
a = np.ones([2, 2]) | |
m = np.asmatrix(a) | |
assert_equal(type(kron(a, a)), np.ndarray) | |
assert_equal(type(kron(m, m)), np.matrix) | |
assert_equal(type(kron(a, m)), np.matrix) | |
assert_equal(type(kron(m, a)), np.matrix) | |
class myarray(np.ndarray): | |
__array_priority__ = 0.0 | |
ma = myarray(a.shape, a.dtype, a.data) | |
assert_equal(type(kron(a, a)), np.ndarray) | |
assert_equal(type(kron(ma, ma)), myarray) | |
assert_equal(type(kron(a, ma)), np.ndarray) | |
assert_equal(type(kron(ma, a)), myarray) | |
class TestTile(TestCase): | |
def test_basic(self): | |
a = np.array([0, 1, 2]) | |
b = [[1, 2], [3, 4]] | |
assert_equal(tile(a, 2), [0, 1, 2, 0, 1, 2]) | |
assert_equal(tile(a, (2, 2)), [[0, 1, 2, 0, 1, 2], [0, 1, 2, 0, 1, 2]]) | |
assert_equal(tile(a, (1, 2)), [[0, 1, 2, 0, 1, 2]]) | |
assert_equal(tile(b, 2), [[1, 2, 1, 2], [3, 4, 3, 4]]) | |
assert_equal(tile(b, (2, 1)), [[1, 2], [3, 4], [1, 2], [3, 4]]) | |
assert_equal(tile(b, (2, 2)), [[1, 2, 1, 2], [3, 4, 3, 4], | |
[1, 2, 1, 2], [3, 4, 3, 4]]) | |
def test_empty(self): | |
a = np.array([[[]]]) | |
d = tile(a, (3, 2, 5)).shape | |
assert_equal(d, (3, 2, 0)) | |
def test_kroncompare(self): | |
from numpy.random import randint | |
reps = [(2,), (1, 2), (2, 1), (2, 2), (2, 3, 2), (3, 2)] | |
shape = [(3,), (2, 3), (3, 4, 3), (3, 2, 3), (4, 3, 2, 4), (2, 2)] | |
for s in shape: | |
b = randint(0, 10, size=s) | |
for r in reps: | |
a = np.ones(r, b.dtype) | |
large = tile(b, r) | |
klarge = kron(a, b) | |
assert_equal(large, klarge) | |
class TestMayShareMemory(TestCase): | |
def test_basic(self): | |
d = np.ones((50, 60)) | |
d2 = np.ones((30, 60, 6)) | |
self.assertTrue(np.may_share_memory(d, d)) | |
self.assertTrue(np.may_share_memory(d, d[::-1])) | |
self.assertTrue(np.may_share_memory(d, d[::2])) | |
self.assertTrue(np.may_share_memory(d, d[1:, ::-1])) | |
self.assertFalse(np.may_share_memory(d[::-1], d2)) | |
self.assertFalse(np.may_share_memory(d[::2], d2)) | |
self.assertFalse(np.may_share_memory(d[1:, ::-1], d2)) | |
self.assertTrue(np.may_share_memory(d2[1:, ::-1], d2)) | |
# Utility | |
def compare_results(res, desired): | |
for i in range(len(desired)): | |
assert_array_equal(res[i], desired[i]) | |
if __name__ == "__main__": | |
run_module_suite() | |