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-rw-r--r--wqflask/wqflask/correlation_matrix/show_corr_matrix.py29
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