Update code/alphafold_featureVector.py

code/alphafold_featureVector.py

@@ -195,8 +195,7 @@ def alphafold(input_set, mode, impute):
             model_count[k] = int(v / 2)  # two types of files for each file.
         data_updated = pd.DataFrame(columns = data.columns)
         new_ind =0
-        st.write('DATA')
-        st.write(data)
+
         for i in data.index:
             uniprotID = data.at[i, 'uniprotID']
             datapoint = data.at[i, 'datapoint']
@@ -253,8 +252,7 @@ def alphafold(input_set, mode, impute):
                     data_updated.at[new_ind, 'distance'] = domainDistanceModels(domStart, domEnd, coordinates, varPos)
                 for col in UNIPROT_ANNOTATION_COLS[0:30]:
                     allDist = []
-                    st.write('FOR EACH COL')
-                    st.write(col, data.at[i, col])
+
                     if (data.at[i, col] != np.NaN) & (data.at[i, col] != 'hit') & (data.at[i, col] != '[]') & (
                             data.at[i, col] != []):
                         annots_list = ast.literal_eval(data.at[i, col])
@@ -276,8 +274,7 @@ def alphafold(input_set, mode, impute):
                                     data_updated.at[new_ind, col] = np.NaN
 
                 new_ind +=1
-        st.write('data_updated')
-        st.write(data_updated)
+
         data_updated = selectMaxAnnot(data_updated)
         data_updated = data_updated.sort_values(['hitTotal', 'annotTotal'], ascending = [False, True])
         data_updated = data_updated.drop_duplicates(['datapoint'])
@@ -466,4 +463,4 @@ def alphafold(input_set, mode, impute):
             minutes, seconds = divmod(rem, 60)
             print("Time passed: {:0>2}:{:0>2}:{:05.2f}".format(int(hours), int(minutes), seconds))
 
-        return data
+        return final_data