Update code/alphafold_featureVector.py

code/alphafold_featureVector.py

@@ -195,6 +195,8 @@ 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']
@@ -251,6 +253,8 @@ 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])
@@ -272,6 +276,8 @@ 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'])