diff options
| -rw-r--r-- | wqflask/wqflask/correlation/pre_computes.py | 37 |
1 files changed, 23 insertions, 14 deletions
diff --git a/wqflask/wqflask/correlation/pre_computes.py b/wqflask/wqflask/correlation/pre_computes.py index 241b0730..77592a3a 100644 --- a/wqflask/wqflask/correlation/pre_computes.py +++ b/wqflask/wqflask/correlation/pre_computes.py @@ -9,7 +9,7 @@ from base.webqtlConfig import TMPDIR def fetch_all_cached_metadata(dataset_name): """in a gvein dataset fetch all the traits metadata""" - file_name = f"{dataset_name}_metadata.json" + file_name = generate_file_name(dataset_name, suffix="metadata") file_path = os.path.join(TMPDIR, file_name) @@ -33,11 +33,11 @@ def cache_new_traits_metadata(dataset_metadata: dict, new_traits_metadata, file_ json.dump(dataset_metadata, file_handler) -def generate_file_name(*args, prefix=""): +def generate_file_name(*args, suffix="", file_ext="json"): """given a list of args generate a unique filename""" - string_unicode = f"{*args,}{prefix}".encode() - return hashlib.md5(string_unicode).hexdigest() + string_unicode = f"{*args,}".encode() + return f"{hashlib.md5(string_unicode).hexdigest()}_{suffix}.{file_ext}" def generate_filename(base_dataset_name, target_dataset_name, base_timestamp, target_dataset_timestamp): @@ -65,11 +65,12 @@ def cache_compute_results(base_dataset_type, target_dataset_timestamp = base_timestamp - file_name = generate_filename( + file_name = generate_file_name( base_dataset_name, target_dataset_name, - base_timestamp, target_dataset_timestamp) + base_timestamp, target_dataset_timestamp, + suffix="corr_precomputes") - file_path = os.path.join(TMPDIR, f"{file_name}.json") + file_path = os.path.join(TMPDIR, file_name) try: with open(file_path, "r+") as json_file_handler: @@ -91,16 +92,20 @@ def cache_compute_results(base_dataset_type, json.dump(data, file_handler) -def fetch_precompute_results(base_dataset_name, target_dataset_name, dataset_type, trait_name): +def fetch_precompute_results(base_dataset_name, + target_dataset_name, + dataset_type, + trait_name): """function to check for precomputed results""" base_timestamp = target_dataset_timestamp = query_table_timestamp( dataset_type) - file_name = generate_filename( + file_name = generate_file_name( base_dataset_name, target_dataset_name, - base_timestamp, target_dataset_timestamp) + base_timestamp, target_dataset_timestamp, + suffix="corr_precomputes") - file_path = os.path.join(TMPDIR, f"{file_name}.json") + file_path = os.path.join(TMPDIR, file_name) try: with open(file_path, "r+") as json_handler: @@ -112,7 +117,9 @@ def fetch_precompute_results(base_dataset_name, target_dataset_name, dataset_typ pass -def pre_compute_dataset_vs_dataset(base_dataset, target_dataset, corr_method): +def pre_compute_dataset_vs_dataset(base_dataset, + target_dataset, + corr_method): """compute sample correlation between dataset vs dataset wn:heavy function should be invoked less frequently input:datasets_data(two dicts),corr_method @@ -131,8 +138,10 @@ def pre_compute_dataset_vs_dataset(base_dataset, target_dataset, corr_method): "trait_id": primary_trait_name } - trait_correlation_result = fast_compute_all_sample_correlation( - corr_method=corr_method, this_trait=this_trait_data, target_dataset=target_traits_data) + trait_correlation_result = compute_all_sample_correlation( + corr_method=corr_method, + this_trait=this_trait_data, + target_dataset=target_traits_data) dataset_correlation_results[primary_trait_name] = trait_correlation_result |