fix for correlation_demo template

2 files changed, 44 insertions, 32 deletions

diff --git a/wqflask/wqflask/correlation/correlation_gn3_api.py b/wqflask/wqflask/correlation/correlation_gn3_api.py
index 75bd5561..ba606b92 100644
--- a/wqflask/wqflask/correlation/correlation_gn3_api.py
+++ b/wqflask/wqflask/correlation/correlation_gn3_api.py
@@ -9,9 +9,10 @@ from base.trait import create_trait
 from base.trait import retrieve_sample_data
 # gn3 lib
 from gn3.computations.correlations import compute_all_sample_correlation
-from gn3.computations.correlations import benchmark_compute_all_sample
 from gn3.computations.correlations import map_shared_keys_to_values
 from gn3.computations.correlations import compute_all_tissue_correlation
+from gn3.computations.correlations import compute_all_lit_correlation
+from gn3.db_utils import database_connector
 
 GN3_CORRELATION_API = "http://127.0.0.1:8202/api/correlation"
 
@@ -36,10 +37,6 @@ def process_samples(start_vars, sample_names, excluded_samples=None):
 def create_target_this_trait(start_vars):
     """this function creates the required trait and target dataset for correlation"""
 
-    print("creating the dataset and trait")
-    import time
-
-    initial_time = time.time()
 
     this_dataset = data_set.create_dataset(dataset_name=start_vars['dataset'])
     target_dataset = data_set.create_dataset(
@@ -48,17 +45,10 @@ def create_target_this_trait(start_vars):
     this_trait = create_trait(dataset=this_dataset,
                               name=start_vars['trait_id'])
 
-    
     # target_dataset.get_trait_data(list(self.sample_data.keys()))
 
     # this_trait = retrieve_sample_data(this_trait, this_dataset)
-    print(f"Starting to creat the target dataset ")
-    dataset_start_time = time.time()
     sample_data = ()
-
-    
-
-    time_taken = time.time() - initial_time
     return (this_dataset, this_trait, target_dataset, sample_data)
 
 
@@ -77,6 +67,7 @@ def compute_correlation(start_vars, method="pearson"):
     corr_input_data = {}
 
     if corr_type == "sample":
+        initial_time = time.time()
         # corr_input_data = {
         #     "target_dataset": target_dataset.trait_data,
         #     "target_samplelist": target_dataset.samplelist,
@@ -85,50 +76,44 @@ def compute_correlation(start_vars, method="pearson"):
         #         "trait_id": start_vars["trait_id"]
         #     }
         # }
-
-        sample_data = process_samples(start_vars, this_dataset.group.samplelist)
+        sample_data = process_samples(
+            start_vars, this_dataset.group.samplelist)
         target_dataset.get_trait_data(list(sample_data.keys()))
         this_trait = retrieve_sample_data(this_trait, this_dataset)
 
-
+        print("Creating dataset and trait took",time.time()-initial_time)
 
         this_trait_data = {
             "trait_sample_data": sample_data,
             "trait_id": start_vars["trait_id"]
         }
-
         initial_time = time.time()
-        print("Calling sample correlation")
         results = map_shared_keys_to_values(
             target_dataset.samplelist, target_dataset.trait_data)
         correlation_results = compute_all_sample_correlation(corr_method=method,
                                                              this_trait=this_trait_data,
                                                              target_dataset=results)
 
-        print("Time taken is>>>>",time.time()-initial_time)
+        print("doing sample correlation took",time.time()-initial_time)
 
         # requests_url = f"{GN3_CORRELATION_API}/sample_x/{method}"
         return correlation_results
 
     elif corr_type == "tissue":
         trait_symbol_dict = this_dataset.retrieve_genes("Symbol")
-        time_to_retrieve = time.time()
         primary_tissue_data, target_tissue_data = get_tissue_correlation_input(
             this_trait, trait_symbol_dict)
-        print("Time taken to retrieve this is",time.time()-time_to_retrieve)
 
         corr_input_data = {
             "primary_tissue": primary_tissue_data,
             "target_tissues_dict": target_tissue_data
         }
-        print("Calling tissue correlation")
         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)
 
-        time_taken = time.time()
-        print("Time taken is ??????",time_taken-initial_time)
 
         # requests_url = f"{GN3_CORRELATION_API}/tissue_corr/{method}"
         return correlation_results
@@ -137,15 +122,23 @@ def compute_correlation(start_vars, method="pearson"):
         (this_trait_geneid, geneid_dict, species) = do_lit_correlation(
             this_trait, this_dataset, target_dataset)
 
-        requests_url = f"{GN3_CORRELATION_API}/lit_corr/{species}/{this_trait_geneid}"
-        corr_input_data = geneid_dict
+        conn, _cursor_object = database_connector()
+        initial_time = time.time()
+        with conn:
 
-    print("Sending this request")
-    corr_results = requests.post(requests_url, json=corr_input_data)
+            lit_corr_results = compute_all_lit_correlation(
+                conn=conn, trait_lists=list(geneid_dict.items()),
+                species=species, gene_id=this_trait_geneid)
 
-    data = corr_results.json()
+        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)
 
-    return data
+    # data = corr_results.json()
+
+    # return data
 
 
 def do_lit_correlation(this_trait, this_dataset, target_dataset):
@@ -164,11 +157,11 @@ def get_tissue_correlation_input(this_trait, trait_symbol_dict):
     """Gets tissue expression values for the primary trait and target tissues values"""
     primary_trait_tissue_vals_dict = correlation_functions.get_trait_symbol_and_tissue_values(
         symbol_list=[this_trait.symbol])
-
     if this_trait.symbol.lower() in primary_trait_tissue_vals_dict:
         primary_trait_tissue_values = primary_trait_tissue_vals_dict[this_trait.symbol.lower(
         )]
 
+        time_to_to_fetch_all = time.time()
         corr_result_tissue_vals_dict = correlation_functions.get_trait_symbol_and_tissue_values(
             symbol_list=list(trait_symbol_dict.values()))
         primary_tissue_data = {
diff --git a/wqflask/wqflask/templates/demo_correlation_page.html b/wqflask/wqflask/templates/demo_correlation_page.html
index d2979f9d..67e3c57c 100644
--- a/wqflask/wqflask/templates/demo_correlation_page.html
+++ b/wqflask/wqflask/templates/demo_correlation_page.html
@@ -22,9 +22,28 @@
    {% for key,value in corr_result.items()%}
       <div class="container-content">
       <div><p>{{key}}</p></div>
-      {%for o_key,o_value in value.items()%}
+      <!-- 'p_value': 5.909407416079734e-11, 'num_overlap': 67 -->
+      {% if "corr_coeffient" in  value %}
+      <div><p>{{value["corr_coeffient"]}}</p></div>
+      {%elif "tissue_corr" in value %}
+      <div><p>{{value["tissue_corr"]}}</p></div>
+      {%elif "lit_corr" in value %}
+      {{value["lit_corr"]}}
+      {% endif %}
+      {%if "tissue_number" in value %}
+      <div>{{value["tissue_number"]}}</div>
+      {%elif "num_overlap" in value %}
+      <div><p>{{value["num_overlap"]}}</p></div>
+      {% endif %}
+      <div><p>{{value["p_value"]}}</p></div>
+
+
+
+<!--       {{value["num_overlap"]}}
+      {{value["p_value"]}} -->
+<!--       {%for o_key,o_value in value.items()%}
      <div><p>{{o_value}}</p></div>
-      {%endfor%}
+      {%endfor%} -->
    {% endfor %}
 </div>
    {% endfor %}