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from sparse.numba_backend._compressed import convert
from sparse.numba_backend._utils import assert_eq
import pytest
from numba.typed import List
import numpy as np
def make_inds(shape):
return [np.arange(1, a - 1) for a in shape]
def make_increments(shape):
inds = make_inds(shape)
shape_bins = convert.transform_shape(np.asarray(shape))
return List([inds[i] * shape_bins[i] for i in range(len(shape))])
@pytest.mark.parametrize(
"shape, expected_subsample, subsample",
[
[(5, 6, 7, 8, 9), np.array([3610, 6892, 10338]), 1000],
[(13, 12, 12, 9, 7), np.array([9899, 34441, 60635, 86703]), 10000],
[
(12, 15, 7, 14, 9),
np.array([14248, 36806, 61382, 85956, 110532, 135106]),
10000,
],
[(9, 9, 12, 7, 12), np.array([10177, 34369, 60577]), 10000],
],
)
def test_convert_to_flat(shape, expected_subsample, subsample):
inds = make_inds(shape)
dtype = inds[0].dtype
assert_eq(
convert.convert_to_flat(inds, shape, dtype)[::subsample],
expected_subsample.astype(dtype),
)
@pytest.mark.parametrize(
"shape, expected_subsample, subsample",
[
[(5, 6, 7, 8, 9), np.array([3610, 6892, 10338]), 1000],
[(13, 12, 12, 9, 7), np.array([9899, 34441, 60635, 86703]), 10000],
[
(12, 15, 7, 14, 9),
np.array([14248, 36806, 61382, 85956, 110532, 135106]),
10000,
],
[(9, 9, 12, 7, 12), np.array([10177, 34369, 60577]), 10000],
],
)
def test_compute_flat(shape, expected_subsample, subsample):
increments = make_increments(shape)
dtype = increments[0].dtype
operations = np.prod([inc.shape[0] for inc in increments[:-1]], dtype=dtype)
cols = np.tile(increments[-1], operations)
assert_eq(
convert.compute_flat(increments, cols, operations)[::subsample],
expected_subsample.astype(dtype),
)
@pytest.mark.parametrize(
"shape, expected_shape",
[
[(5, 6, 7, 8, 9), np.array([3024, 504, 72, 9, 1])],
[(13, 12, 12, 9, 7), np.array([9072, 756, 63, 7, 1])],
[(12, 15, 7, 14, 9), np.array([13230, 882, 126, 9, 1])],
[
(18, 5, 12, 14, 9, 11, 8, 14),
np.array([9313920, 1862784, 155232, 11088, 1232, 112, 14, 1]),
],
[
(11, 6, 13, 11, 17, 7, 15),
np.array([1531530, 255255, 19635, 1785, 105, 15, 1]),
],
[(9, 9, 12, 7, 12), np.array([9072, 1008, 84, 12, 1])],
],
)
def test_transform_shape(shape, expected_shape):
assert_eq(convert.transform_shape(np.asarray(shape)), expected_shape, compare_dtype=False)
|
