diff options
| -rw-r--r-- | wqflask/wqflask/correlation_matrix/show_corr_matrix.py | 29 |
1 files changed, 15 insertions, 14 deletions
diff --git a/wqflask/wqflask/correlation_matrix/show_corr_matrix.py b/wqflask/wqflask/correlation_matrix/show_corr_matrix.py index 499a4e13..9b4cb2eb 100644 --- a/wqflask/wqflask/correlation_matrix/show_corr_matrix.py +++ b/wqflask/wqflask/correlation_matrix/show_corr_matrix.py @@ -33,12 +33,11 @@ from utility import corr_result_helpers from utility.redis_tools import get_redis_conn -from gn3.computations.principal_component_analysis import compute_pca +from gn3.computations.pca import compute_pca -from gn3.computations.principal_component_analysis import process_factor_loadings_tdata -from gn3.computations.principal_component_analysis import generate_pca_traits_vals -from gn3.computations.principal_component_analysis import generate_pca_temp_dataset -from gn3.computations.principal_component_analysis import cache_pca_dataset +from gn3.computations.pca import process_factor_loadings_tdata +from gn3.computations.pca import generate_pca_temp_traits +from gn3.computations.pca import cache_pca_dataset Redis = get_redis_conn() THIRTY_DAYS = 60 * 60 * 24 * 30 @@ -168,12 +167,12 @@ class CorrelationMatrix: self.pca_works = "False" try: - if self.do_PCA == True: + if self.do_PCA: self.pca_works = "True" self.pca_trait_ids = [] pca = self.calculate_pca() self.loadings_array = process_factor_loadings_tdata( - self.loadings, len(self.trait_list)) + factor_loadings=self.loadings, traits_num=len(self.trait_list)) else: self.pca_works = "False" except: @@ -198,15 +197,17 @@ class CorrelationMatrix: dataset_name="Temp", dataset_type="Temp", group_name=this_group_name) temp_dataset.group.get_samplelist() - pca_dataset = generate_pca_temp_dataset(species=temp_dataset.group.species, group=this_group_name, - traits_data=self.trait_data_array, corr_array=self.pca_corr_results, - dataset_samples=temp_dataset.group.all_samples_ordered(), - shared_samples=self.shared_samples_list, - create_time=datetime.datetime.now().strftime("%m%d%H%M%S")) + pca_temp_traits = generate_pca_temp_traits(species=temp_dataset.group.species, group=this_group_name, + traits_data=self.trait_data_array, corr_array=self.pca_corr_results, + dataset_samples=temp_dataset.group.all_samples_ordered(), + shared_samples=self.shared_samples_list, + create_time=datetime.datetime.now().strftime("%m%d%H%M%S")) - cache_pca_dataset(Redis, THIRTY_DAYS, pca_dataset) + + cache_pca_dataset(redis_conn=get_redis_conn( + ), exp_days=60 * 60 * 24 * 30, pca_trait_dict=pca_temp_traits) - self.pca_trait_ids = list(pca_dataset.keys()) + self.pca_trait_ids = list(pca_temp_traits.keys()) return pca |