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Make Dask chunking tests independent of Dask version #568

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Oct 3, 2022
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Make Dask chunking tests independent of Dask version #568

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68 changes: 43 additions & 25 deletions kikuchipy/signals/util/tests/test_dask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,8 +15,6 @@
# You should have received a copy of the GNU General Public License
# along with kikuchipy. If not, see <http://www.gnu.org/licenses/>.

import sys

import dask.array as da
import numpy as np
import pytest
Expand All @@ -37,51 +35,71 @@ def test_get_chunking_no_parameters(self):

def test_chunk_shape(self):
s = LazyEBSD(da.zeros((32, 32, 256, 256), dtype=np.uint16))
chunks = get_chunking(s, chunk_shape=16)
assert chunks == ((16, 16), (16, 16), (256,), (256,))
assert get_chunking(s, chunk_shape=16) == da.core.normalize_chunks(
chunks={0: 16, 1: 16, 2: -1, 3: -1},
limit=30e6,
shape=s.data.shape,
dtype=s.data.dtype,
)

@pytest.mark.skipif(sys.version_info < (3, 8), reason="Requires Python >= 3.8")
def test_chunk_bytes(self):
s = LazyEBSD(da.zeros((32, 32, 256, 256), dtype=np.uint16))
chunks = get_chunking(s, chunk_bytes=15e6)
assert chunks == ((10, 10, 10, 2), (10, 10, 10, 2), (256,), (256,))
assert get_chunking(s, chunk_bytes=15e6) == da.core.normalize_chunks(
chunks={0: "auto", 1: "auto", 2: -1, 3: -1},
limit=15e6,
shape=s.data.shape,
dtype=s.data.dtype,
)

@pytest.mark.skipif(sys.version_info < (3, 8), reason="Requires Python >= 3.8")
def test_get_chunking_dtype(self):
s = LazyEBSD(da.zeros((32, 32, 256, 256), dtype=np.uint8))
chunks0 = get_chunking(s, dtype=np.float32)
chunks1 = get_chunking(s)
assert chunks0 == ((10, 10, 10, 2), (10, 10, 10, 2), (256,), (256,))
assert chunks1 == ((21, 11), (21, 11), (256,), (256,))
assert get_chunking(s) == da.core.normalize_chunks(
chunks={0: "auto", 1: "auto", 2: -1, 3: -1},
limit=30e6,
shape=s.data.shape,
dtype=s.data.dtype,
)
assert get_chunking(s, dtype=np.float32) == da.core.normalize_chunks(
chunks={0: "auto", 1: "auto", 2: -1, 3: -1},
limit=30e6,
shape=s.data.shape,
dtype=np.dtype("float32"),
)

@pytest.mark.skipif(sys.version_info < (3, 8), reason="Requires Python >= 3.8")
@pytest.mark.parametrize(
"shape, nav_dim, sig_dim, dtype, desired_chunks",
"shape, nav_dim, sig_dim, dtype",
[
(
(32, 32, 256, 256),
2,
2,
np.uint16,
((15, 15, 2), (15, 15, 2), (256,), (256,)),
np.dtype("uint16"),
),
((32, 32, 256, 256), 2, 2, np.uint8, ((21, 11), (21, 11), (256,), (256,))),
((32, 32, 256, 256), 2, 2, np.dtype("uint8")),
],
)
def test_get_chunking_no_signal(
self, shape, nav_dim, sig_dim, dtype, desired_chunks
):
def test_get_chunking_no_signal(self, shape, nav_dim, sig_dim, dtype):
chunks = get_chunking(
data_shape=shape, nav_dim=nav_dim, sig_dim=sig_dim, dtype=dtype
)
assert chunks == desired_chunks
assert chunks == da.core.normalize_chunks(
chunks={0: "auto", 1: "auto", 2: -1, 3: -1},
limit=30e6,
shape=shape,
dtype=dtype,
)

def test_get_dask_array(self):
s = EBSD((255 * np.random.rand(10, 10, 120, 120)).astype(np.uint8))
dask_array = get_dask_array(s, chunk_shape=8)
assert dask_array.chunksize == (8, 8, 120, 120)
assert dask_array.chunks == da.core.normalize_chunks(
chunks={0: 8, 1: 8, 2: -1, 3: -1},
limit=30e6,
shape=s.data.shape,
dtype=s.data.dtype,
)

# Make data lazy
# Make data lazy (chunk size is kept)
s.data = dask_array.rechunk((5, 5, 120, 120))
dask_array = get_dask_array(s)
assert dask_array.chunksize == (5, 5, 120, 120)
Expand All @@ -91,8 +109,8 @@ def test_chunk_bytes_indirectly(self):
array_out0 = get_dask_array(s)
array_out1 = get_dask_array(s, chunk_bytes="25KiB")
array_out2 = get_dask_array(s, chunk_bytes=30e3)
assert array_out0.chunksize != array_out1.chunksize
assert array_out1.chunksize == array_out2.chunksize
assert array_out0.chunks != array_out1.chunks
assert array_out1.chunks == array_out2.chunks

def test_rechunk_learning_results(self):
data = da.from_array(np.random.rand(10, 100, 100, 5).astype(np.float32))
Expand Down