Unverified Commit db594182 authored by René Fritze's avatar René Fritze Committed by GitHub
Browse files

Merge pull request #1473 from pymor/fix_issue_1472

[tests] tighten vecarray COW + add regression test case
parents 08ca794d f8c97dda
Pipeline #106780 failed with stages
in 21 seconds
......@@ -6,11 +6,12 @@ from numbers import Number
import pytest
import numpy as np
from hypothesis import assume, settings
from hypothesis import assume, settings, example
from hypothesis import strategies as hyst
from pymor.algorithms.basic import almost_equal
from pymor.vectorarrays.interface import VectorSpace
from pymor.vectorarrays.numpy import NumpyVectorArray, NumpyVectorSpace
from pymor.tools import floatcmp
from pymor.tools.floatcmp import float_cmp
from pymortests.pickling import assert_picklable_without_dumps_function
......@@ -129,6 +130,8 @@ def test_full(vector_array):
@pyst.given_vector_arrays(realizations=hyst.integers(min_value=0, max_value=30),
low=hyst.floats(allow_infinity=False, allow_nan=False),
high=hyst.floats(allow_infinity=False, allow_nan=False))
@example(vector_array=NumpyVectorArray([], NumpyVectorSpace(1)), realizations=2,
low=-5e-324, high=0.0)
def test_random_uniform(vector_array, realizations, low, high):
# avoid Overflow in np.random.RandomState.uniform
......@@ -149,11 +152,11 @@ def test_random_uniform(vector_array, realizations, low, high):
assert v.space == vector_array.space
assert len(v) == c
if min(v.dim, c) > 0:
assert np.all(v.sup_norm() < max(abs(low), abs(high)))
assert np.all(v.sup_norm() <= max(abs(low), abs(high)))
x = v.to_numpy()
assert x.shape == (c, v.dim)
assert np.all(x < high)
assert np.all(x <= high)
assert np.all(x >= low)
except NotImplementedError:
......@@ -267,6 +270,7 @@ def test_copy(vectors_and_indices):
@example(vectors_and_indices=(NumpyVectorArray(np.array([[2.22044605e-16]]), NumpyVectorSpace(1)), [0]))
def test_COW(vectors_and_indices):
v, ind = vectors_and_indices
for deep in (True, False):
......@@ -279,10 +283,8 @@ def test_COW(vectors_and_indices):
assert c.space == v.space
if len(c) > 0 and not np.all(c.norm() == 0):
c *= 2
if ind is None:
assert not np.all(almost_equal(c, v))
assert not np.all(almost_equal(c, v[ind]))
vi = v[ind] if ind else v
assert not np.all(almost_equal(c, vi, atol=0, rtol=0))
assert np.allclose(c.to_numpy(), 2*indexed(v.to_numpy(), ind))
except NotImplementedError:
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