diff options
Diffstat (limited to 'gn3/computations/partial_correlations.py')
| -rw-r--r-- | gn3/computations/partial_correlations.py | 41 |
1 files changed, 23 insertions, 18 deletions
diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index 6eee299..8674910 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -16,7 +16,6 @@ import pandas import pingouin from scipy.stats import pearsonr, spearmanr -from gn3.settings import TEXTDIR from gn3.chancy import random_string from gn3.function_helpers import compose from gn3.data_helpers import parse_csv_line @@ -99,7 +98,7 @@ def fix_samples( primary_samples, tuple(primary_trait_data["data"][sample]["value"] for sample in primary_samples), - control_vals_vars[0], + (control_vals_vars[0],), tuple(primary_trait_data["data"][sample]["variance"] for sample in primary_samples), control_vals_vars[1]) @@ -209,7 +208,7 @@ def good_dataset_samples_indexes( samples_from_file.index(good) for good in set(samples).intersection(set(samples_from_file)))) -def partial_correlations_fast(# pylint: disable=[R0913, R0914] +def partial_correlations_fast(# pylint: disable=[R0913, R0914, too-many-positional-arguments] samples, primary_vals, control_vals, database_filename, fetched_correlations, method: str, correlation_type: str) -> Generator: """ @@ -334,7 +333,7 @@ def compute_partial( This implementation reworks the child function `compute_partial` which will then be used in the place of `determinPartialsByR`. """ - with Pool(processes=(cpu_count() - 1)) as pool: + with Pool(processes=cpu_count() - 1) as pool: return ( result for result in ( pool.starmap( @@ -345,7 +344,7 @@ def compute_partial( for target in targets))) if result is not None) -def partial_correlations_normal(# pylint: disable=R0913 +def partial_correlations_normal(# pylint: disable=[R0913, too-many-positional-arguments] primary_vals, control_vals, input_trait_gene_id, trait_database, data_start_pos: int, db_type: str, method: str) -> Generator: """ @@ -381,7 +380,7 @@ def partial_correlations_normal(# pylint: disable=R0913 return all_correlations -def partial_corrs(# pylint: disable=[R0913] +def partial_corrs(# pylint: disable=[R0913, too-many-positional-arguments] conn, samples, primary_vals, control_vals, return_number, species, input_trait_geneid, input_trait_symbol, tissue_probeset_freeze_id, method, dataset, database_filename): @@ -667,10 +666,15 @@ def check_for_common_errors(# pylint: disable=[R0914] return non_error_result -def partial_correlations_with_target_db(# pylint: disable=[R0913, R0914, R0911] - conn: Any, primary_trait_name: str, - control_trait_names: Tuple[str, ...], method: str, - criteria: int, target_db_name: str) -> dict: +def partial_correlations_with_target_db(# pylint: disable=[R0913, R0914, R0911 too-many-positional-arguments] + conn: Any, + primary_trait_name: str, + control_trait_names: Tuple[str, ...], + method: str, + criteria: int, + target_db_name: str, + textdir: str +) -> dict: """ This is the 'ochestration' function for the partial-correlation feature. @@ -755,7 +759,7 @@ def partial_correlations_with_target_db(# pylint: disable=[R0913, R0914, R0911] threshold, conn) - database_filename = get_filename(conn, target_db_name, TEXTDIR) + database_filename = get_filename(conn, target_db_name, textdir) all_correlations = partial_corrs( conn, check_res["common_primary_control_samples"], check_res["fixed_primary_values"], check_res["fixed_control_values"], @@ -837,7 +841,7 @@ def partial_correlations_with_target_traits( return check_res target_traits = { - trait["name"]: trait + trait["trait_name"]: trait for trait in traits_info(conn, threshold, target_trait_names)} target_traits_data = traits_data(conn, tuple(target_traits.values())) @@ -854,12 +858,13 @@ def partial_correlations_with_target_traits( __merge( target_traits[target_name], compute_trait_info( - check_res["primary_values"], check_res["fixed_control_values"], - (export_trait_data( - target_data, - samplelist=check_res["common_primary_control_samples"]), - target_name), - method)) + check_res["primary_values"], + check_res["fixed_control_values"], + (export_trait_data( + target_data, + samplelist=check_res["common_primary_control_samples"]), + target_name), + method)) for target_name, target_data in target_traits_data.items()) return { |