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author | Alexander Kabui | 2021-08-20 09:04:12 +0300 |
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committer | GitHub | 2021-08-20 09:04:12 +0300 |
commit | c9ee473ff7797f6bbd7507eb55c772a3a646acee (patch) | |
tree | d14302938081ce61637ae84cda2077aaf0db9733 | |
parent | f8be3a85567cc17d50a01382eb10cb3b05436214 (diff) | |
download | genenetwork3-c9ee473ff7797f6bbd7507eb55c772a3a646acee.tar.gz |
Minor correlation fixes (#36)
* fix key error for (*tissue_cor) tissue correlation
* update tests for tissue correlation
* rename speed_compute to fast_compute
* pep8 formatting
-rw-r--r-- | gn3/computations/correlations.py | 15 | ||||
-rw-r--r-- | tests/unit/computations/test_correlation.py | 8 |
2 files changed, 11 insertions, 12 deletions
diff --git a/gn3/computations/correlations.py b/gn3/computations/correlations.py index 8d76c09..bb13ff1 100644 --- a/gn3/computations/correlations.py +++ b/gn3/computations/correlations.py @@ -124,9 +124,9 @@ def filter_shared_sample_keys(this_samplelist, return (this_vals, target_vals) -def speed_compute_all_sample_correlation(this_trait, - target_dataset, - corr_method="pearson") -> List: +def fast_compute_all_sample_correlation(this_trait, + target_dataset, + corr_method="pearson") -> List: """Given a trait data sample-list and target__datasets compute all sample correlation this functions uses multiprocessing if not use the normal fun @@ -362,8 +362,7 @@ def compute_tissue_correlation(primary_tissue_dict: dict, target_tissues_values=target_tissue_vals, trait_id=trait_id, corr_method=corr_method) - tissue_result_dict = {trait_id: tissue_result} - tissues_results.append(tissue_result_dict) + tissues_results.append(tissue_result) return sorted( tissues_results, key=lambda trait_name: -abs(list(trait_name.values())[0]["tissue_corr"])) @@ -386,9 +385,9 @@ def process_trait_symbol_dict(trait_symbol_dict, symbol_tissue_vals_dict) -> Lis return traits_tissue_vals -def speed_compute_tissue_correlation(primary_tissue_dict: dict, - target_tissues_data: dict, - corr_method: str): +def fast_compute_tissue_correlation(primary_tissue_dict: dict, + target_tissues_data: dict, + corr_method: str): """Experimental function that uses multiprocessing for computing tissue correlation diff --git a/tests/unit/computations/test_correlation.py b/tests/unit/computations/test_correlation.py index f2d65bd..fc52ec1 100644 --- a/tests/unit/computations/test_correlation.py +++ b/tests/unit/computations/test_correlation.py @@ -406,10 +406,10 @@ class TestCorrelation(TestCase): target_tissue_data = {"trait_symbol_dict": target_trait_symbol, "symbol_tissue_vals_dict": target_symbol_tissue_vals} - mock_tissue_corr.side_effect = [{"tissue_corr": -0.5, "tissue_p_val": 0.9, - "tissue_number": 3}, - {"tissue_corr": 1.11, "tissue_p_val": 0.2, - "tissue_number": 3}] + mock_tissue_corr.side_effect = [{"1418702_a_at": {"tissue_corr": -0.5, "tissue_p_val": 0.9, + "tissue_number": 3}}, + {"1412_at": {"tissue_corr": 1.11, "tissue_p_val": 0.2, + "tissue_number": 3}}] expected_results = [{"1412_at": {"tissue_corr": 1.11, "tissue_p_val": 0.2, "tissue_number": 3}}, |