diff options
| -rw-r--r-- | wqflask/base/mrna_assay_tissue_data.py | 25 | ||||
| -rw-r--r-- | wqflask/wqflask/correlation/correlation_gn3_api.py | 60 |
2 files changed, 8 insertions, 77 deletions
diff --git a/wqflask/base/mrna_assay_tissue_data.py b/wqflask/base/mrna_assay_tissue_data.py index 0220d73b..5a64afb2 100644 --- a/wqflask/base/mrna_assay_tissue_data.py +++ b/wqflask/base/mrna_assay_tissue_data.py @@ -52,33 +52,9 @@ class MrnaAssayTissueData(object): # lower_symbols[gene_symbol.lower()] = True if gene_symbol != None: lower_symbols[gene_symbol.lower()] = True - - import time - # initial_time = time.time() - # conn,cursor = database_connector() - # cursor.execute(query) - # for result in cursor.fetchall(): - # symbol = result[0] - # self.data[symbol].gene_id = result[1] - # self.data[symbol].data_id = result[2] - # self.data[symbol].chr = result[3] - # self.data[symbol].mb = result[4] - # self.data[symbol].description = result[5] - # self.data[symbol].probe_target_description = result[6] - - - # print("my loop takes>>>>",time.time()-initial_time) - # conn.close() - # r - - # takes 5 seconds - initial_time = time.time() results = list(g.db.execute(query).fetchall()) for result in results: symbol = result[0] - # if symbol is not None - # exists = lower_symbols.get(symbol.lower()) - # if symbol.lower() in lower_symbols: if symbol is not None and lower_symbols.get(symbol.lower()): symbol = symbol.lower() @@ -89,7 +65,6 @@ class MrnaAssayTissueData(object): self.data[symbol].mb = result.Mb self.data[symbol].description = result.description self.data[symbol].probe_target_description = result.Probe_Target_Description - print("time taken in the loop is",time.time()-initial_time) ########################################################################### #Input: cursor, symbolList (list), dataIdDict(Dict) diff --git a/wqflask/wqflask/correlation/correlation_gn3_api.py b/wqflask/wqflask/correlation/correlation_gn3_api.py index c945f699..3c21a850 100644 --- a/wqflask/wqflask/correlation/correlation_gn3_api.py +++ b/wqflask/wqflask/correlation/correlation_gn3_api.py @@ -63,9 +63,6 @@ def sample_for_trait_lists(corr_results, target_dataset, this_trait, this_datase "trait_sample_data": sample_data, "trait_id": start_vars["trait_id"] } - # trait_lists = dict([(list(corr_result)[0],True) for corr_result in corr_results]) - # target_dataset.trait_data =list(filter(lambda dict_obj: dict_obj.keys()[ - # 0] in corr_results_traits, target_dataset_data)) results = map_shared_keys_to_values( target_dataset.samplelist, target_dataset.trait_data) correlation_results = compute_all_sample_correlation(corr_method="pearson", @@ -77,33 +74,15 @@ def sample_for_trait_lists(corr_results, target_dataset, this_trait, this_datase def tissue_for_trait_lists(corr_results, this_dataset, target_dataset, this_trait): - # # print(corr_results[0])-- - # [{"awsdsd_at": {'corr_coeffient': 0.49714692782257336, 'p_value': 1.872077762359228e-05, 'num_overlap': 67}}] - - print("creating trait_lists") - # corr_results = corr_results[0::] trait_lists = dict([(list(corr_result)[0], True) for corr_result in corr_results]) - print("finished creating trait_list") - traits_symbol_dict = this_dataset.retrieve_genes("Symbol") - print("Retrieved symbol dict") - print("creating dict here>>>>>>>>>") - import time - init_time = time.time() traits_symbol_dict = dict({trait_name: symbol for ( trait_name, symbol) in traits_symbol_dict.items() if trait_lists.get(trait_name)}) - print("time taken to create this max dict is>>>>", time.time()-init_time) - print("finished creatinf the dict") - print("Fetching tissue datas") primary_tissue_data, target_tissue_data = get_tissue_correlation_input( this_trait, traits_symbol_dict) - print("finihsed>>>>>>>>>>>>>>>>>>") - print("Calling experimental_compute_all_tissue_correlation") corr_results = experimental_compute_all_tissue_correlation( primary_tissue_dict=primary_tissue_data, target_tissues_data=target_tissue_data, corr_method="pearson") - # print('finished calling this tissue reuslts',corr_results) - return corr_results @@ -123,22 +102,14 @@ def compute_correlation(start_vars, method="pearson"): corr_input_data = {} if corr_type == "sample": - import time - initial_time = time.time() - # corr_input_data = { - # "target_dataset": target_dataset.trait_data, - # "target_samplelist": target_dataset.samplelist, - # "trait_data": { - # "trait_sample_data": sample_data, - # "trait_id": start_vars["trait_id"] - # } - # } + sample_data = process_samples( start_vars, this_dataset.group.samplelist) + initial_time = time.time() target_dataset.get_trait_data(list(sample_data.keys())) this_trait = retrieve_sample_data(this_trait, this_dataset) + print("Creating target dataset and trait took", time.time()-initial_time) - print("Creating dataset and trait took", time.time()-initial_time) this_trait_data = { "trait_sample_data": sample_data, @@ -151,15 +122,9 @@ def compute_correlation(start_vars, method="pearson"): this_trait=this_trait_data, target_dataset=results) - print("computedd>>>>>>>>>>>>>") - print("doing sample correlation took", time.time()-initial_time) - - other_results_time = time.time() - other_results = tissue_for_trait_lists( - correlation_results, this_dataset, target_dataset, this_trait) - print(">>>time taken for this is", time.time()-other_results_time) - + # other_results = tissue_for_trait_lists( + # correlation_results, this_dataset, target_dataset, this_trait) # requests_url = f"{GN3_CORRELATION_API}/sample_x/{method}" return correlation_results @@ -177,17 +142,9 @@ def compute_correlation(start_vars, method="pearson"): target_tissues_data=corr_input_data[ "target_tissues_dict"], corr_method=method) - print("correlation y took", time.time()-initial_time) - # initial_time = time.time() - # correlation_results = compute_all_tissue_correlation(primary_tissue_dict=corr_input_data["primary_tissue"], - # target_tissues_data=corr_input_data["target_tissues_dict"], - # corr_method=method) - # print("time taken for compute tissue is", time.time()-initial_time) - - # requests_url = f"{GN3_CORRELATION_API}/tissue_corr/{method}" - - sample_results = sample_for_trait_lists( - correlation_results, target_dataset, this_trait, this_dataset, start_vars) + print("computing tissue took >>>>", time.time()-initial_time) + # sample_results = sample_for_trait_lists( + # correlation_results, target_dataset, this_trait, this_dataset, start_vars) return correlation_results elif corr_type == "lit": @@ -203,7 +160,6 @@ def compute_correlation(start_vars, method="pearson"): species=species, gene_id=this_trait_geneid) return lit_corr_results - print("the time taken is", time.time()-initial_time) # requests_url = f"{GN3_CORRELATION_API}/lit_corr/{species}/{this_trait_geneid}" # corr_input_data = geneid_dict # corr_results = requests.post(requests_url, json=corr_input_data) |