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[tests] refactor tests

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This commit is contained in:
Jan Petykiewicz 2026-04-18 00:52:04 -07:00
commit 8cdcd08ba0
25 changed files with 649 additions and 616 deletions
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19
meanas/test/test_fdmath_operators.py
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@ -1,14 +1,15 @@
import numpy
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from ..fdmath import operators, unvec, vec
from ._test_builders import real_ramp
from .utils import assert_close
SHAPE = (2, 3, 2)
SCALAR_FIELD = numpy.arange(numpy.prod(SHAPE), dtype=float).reshape(SHAPE, order='C')
VECTOR_LEFT = (numpy.arange(3 * numpy.prod(SHAPE), dtype=float).reshape((3, *SHAPE), order='C') + 0.5)
VECTOR_RIGHT = (2.0 + numpy.arange(3 * numpy.prod(SHAPE), dtype=float).reshape((3, *SHAPE), order='C') / 3.0)
SCALAR_FIELD = real_ramp(SHAPE)
VECTOR_LEFT = real_ramp((3, *SHAPE), offset=0.5)
VECTOR_RIGHT = real_ramp((3, *SHAPE), scale=1 / 3, offset=2.0)
def _apply_scalar_matrix(op: operators.sparse.spmatrix) -> numpy.ndarray:
@ -26,7 +27,7 @@ def _mirrored_indices(size: int, shift_distance: int) -> numpy.ndarray:
def test_shift_circ_matches_numpy_roll(axis: int, shift_distance: int) -> None:
matrix_result = _apply_scalar_matrix(operators.shift_circ(axis, SHAPE, shift_distance))
expected = numpy.roll(SCALAR_FIELD, -shift_distance, axis=axis)
assert_array_equal(matrix_result, expected)
assert_close(matrix_result, expected)
@pytest.mark.parametrize(('axis', 'shift_distance'), [(0, 1), (1, -1), (2, 1)])
@ -35,7 +36,7 @@ def test_shift_with_mirror_matches_explicit_mirrored_indices(axis: int, shift_di
indices = [numpy.arange(length) for length in SHAPE]
indices[axis] = _mirrored_indices(SHAPE[axis], shift_distance)
expected = SCALAR_FIELD[numpy.ix_(*indices)]
assert_array_equal(matrix_result, expected)
assert_close(matrix_result, expected)
@pytest.mark.parametrize(
@ -69,19 +70,19 @@ def test_vec_cross_matches_pointwise_cross_product() -> None:
expected[0] = VECTOR_LEFT[1] * VECTOR_RIGHT[2] - VECTOR_LEFT[2] * VECTOR_RIGHT[1]
expected[1] = VECTOR_LEFT[2] * VECTOR_RIGHT[0] - VECTOR_LEFT[0] * VECTOR_RIGHT[2]
expected[2] = VECTOR_LEFT[0] * VECTOR_RIGHT[1] - VECTOR_LEFT[1] * VECTOR_RIGHT[0]
assert_allclose(matrix_result, expected)
assert_close(matrix_result, expected)
def test_avg_forward_matches_half_sum_with_forward_neighbor() -> None:
matrix_result = _apply_scalar_matrix(operators.avg_forward(1, SHAPE))
expected = 0.5 * (SCALAR_FIELD + numpy.roll(SCALAR_FIELD, -1, axis=1))
assert_allclose(matrix_result, expected)
assert_close(matrix_result, expected)
def test_avg_back_matches_half_sum_with_backward_neighbor() -> None:
matrix_result = _apply_scalar_matrix(operators.avg_back(1, SHAPE))
expected = 0.5 * (SCALAR_FIELD + numpy.roll(SCALAR_FIELD, 1, axis=1))
assert_allclose(matrix_result, expected)
assert_close(matrix_result, expected)
def test_avg_forward_rejects_invalid_shape() -> None: