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added random seed #3

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merged 7 commits into from
Aug 7, 2024
Merged

added random seed #3

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c48dc92
rearranged data files
anushka255 Aug 6, 2024
48c4344
removing hashlib from dependencies
anushka255 Aug 6, 2024
6327f83
added test data and checking hashsum
anushka255 Aug 6, 2024
b53c7be
minor update
anushka255 Aug 6, 2024
c4ade35
Merge branch 'main' into aa/seed
anushka255 Aug 6, 2024
aed7d3c
added random seed
anushka255 Aug 6, 2024
b93ba16
added todo
anushka255 Aug 7, 2024
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30 changes: 15 additions & 15 deletions tests/data/output/H_center.csv
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508 changes: 254 additions & 254 deletions tests/data/output/W_center.csv
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310 changes: 155 additions & 155 deletions tests/data/output/center_slice2_pairwise.csv
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364 changes: 182 additions & 182 deletions tests/data/output/center_slice3_pairwise.csv
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362 changes: 181 additions & 181 deletions tests/data/output/center_slice4_pairwise.csv
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27 changes: 12 additions & 15 deletions tests/test_paste.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,10 @@
output_dir = test_dir / "data/output"


def assert_checksum_equals(generated_file, oracle):
def assert_checksum_equals(temp_dir, filename):
generated_file = temp_dir / filename
oracle = output_dir / filename

assert (
hashlib.md5(
"".join(open(generated_file, "r").readlines()).encode("utf8")
Expand All @@ -32,16 +35,12 @@ def test_pairwise_alignment(slices):
b_distribution=slices[1].obsm["weights"],
G_init=None,
)
outcome_df = pd.DataFrame(
pd.DataFrame(
outcome, index=slices[0].obs.index, columns=slices[1].obs.index
)
outcome_df.to_csv(temp_dir / "slices_1_2_pairwise.csv")
assert_checksum_equals(
temp_dir / "slices_1_2_pairwise.csv", output_dir / "slices_1_2_pairwise.csv"
)
).to_csv(temp_dir / "slices_1_2_pairwise.csv")
assert_checksum_equals(temp_dir, "slices_1_2_pairwise.csv")


# TODO: possibly some randomness to the code that needs to be dealt with
def test_center_alignment(slices):
temp_dir = Path(tempfile.mkdtemp())

Expand All @@ -52,6 +51,7 @@ def test_center_alignment(slices):
lmbda=n_slices * [1.0 / n_slices],
alpha=0.1,
n_components=15,
random_seed=0,
threshold=0.001,
dissimilarity="kl",
distributions=[slices[i].obsm["weights"] for i in range(len(slices))],
Expand All @@ -63,15 +63,12 @@ def test_center_alignment(slices):
temp_dir / "H_center.csv"
)

# assert_checksum_equals(temp_dir / "W_center.csv", output_dir / "W_center.csv")
#
# assert_checksum_equals(temp_dir / "H_center.csv", output_dir / "H_center.csv")
# TODO: The following computations seem to be architecture dependent (need to look into as for how)
# assert_checksum_equals(temp_dir, "W_center.csv")
# assert_checksum_equals(temp_dir, "H_center.csv")

for i, pi in enumerate(pairwise_info):
pd.DataFrame(
pi, index=center_slice.obs.index, columns=slices[i].obs.index
).to_csv(temp_dir / f"center_slice{i+1}_pairwise.csv")
# assert_checksum_equals(
# temp_dir / f"center_slice{i}_pairwise.csv",
# output_dir / f"center_slice{i}_pairwise.csv",
# )
assert_checksum_equals(temp_dir, f"center_slice{i+1}_pairwise.csv")