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author | Alexander Kabui | 2021-12-15 09:50:24 +0300 |
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committer | Alexander Kabui | 2021-12-15 09:50:24 +0300 |
commit | 6d87fc08c130937c3f35fb9bbf6d2c68bc825e97 (patch) | |
tree | d2cad5339142db3c01f87c5e30151b6a2f160b05 /gn3/computations | |
parent | 4f8042a67cab94384bb30e73ec5139fdd3a4c8b5 (diff) | |
download | genenetwork3-6d87fc08c130937c3f35fb9bbf6d2c68bc825e97.tar.gz |
init mp calculate 1
Diffstat (limited to 'gn3/computations')
-rw-r--r-- | gn3/computations/correlations.py | 23 |
1 files changed, 23 insertions, 0 deletions
diff --git a/gn3/computations/correlations.py b/gn3/computations/correlations.py index d38946e..24e9871 100644 --- a/gn3/computations/correlations.py +++ b/gn3/computations/correlations.py @@ -422,3 +422,26 @@ def fast_compute_tissue_correlation(primary_tissue_dict: dict, return sorted( tissues_results, key=lambda trait_name: -abs(list(trait_name.values())[0]["tissue_corr"])) + + +def _mp_calculate(x_val, dataset, n_jobs, chunk_size): + """corr mp reimplementation + credit:https://github.com/bukson/nancorrmp + """ + + def _compute_correlation_2(x_val, y_val, trait_name): + """function to compute correlation""" + + return (trait_name, scipy.stats.pearsonr(x_val, y_val)) + + arguments = ((x_val, y_val, trait_name) for (trait_name, y_val) in dataset) + + processes = n_jobs if n_jobs > 0 else None + + worker_function = _compute_correlation_2 + + with multiprocessing.pool(processes=processes) as pool: + results = list(pool.imap_unordered( + worker_function, arguments, chunksize=chunks)) + + return results |