Update ASCARIS.py

ASCARIS.py

@@ -16,7 +16,7 @@ import gzip
 showWarningOnDirectExecution = False
 
 def convert_df(df):
-   return df.to_csv(index=False).encode('utf-8')
+   return df.to_csv(index=False, sep= '\t').encode('utf-8')
 
 
 if 'visibility' not in st.session_state:
@@ -35,7 +35,6 @@ st.write('')
 
 with st.form('mform', clear_on_submit=False):
     source = st.selectbox('Select the protein structure resource (1: PDB-SwissModel-Modbase, 2: AlphaFold)',[1,2])
-    #source = 1
     impute = st.selectbox('Missing value imputation (mostly for the cases where the corresponding annotation does not exist in the protein)',[True, False])
     input_data = st.text_input('Enter SAV data points (format: "UniProt/Swiss-Prot human protein accession" – "wild type a.a." – "position on the sequence" – "mutated a.a.").   Example: P04217-E-20-A or O43556-I-40-A,P57737-W-372-A')
             
@@ -43,25 +42,13 @@ with st.form('mform', clear_on_submit=False):
 
     parser = argparse.ArgumentParser(description='ASCARIS')
     
-    #parser.add_argument('-s', '--source_option',
-    #                    help='Selection of input structure data.\n 1: PDB Structures (default), 2: AlphaFold Structures',
-    #                    default=1)
-    #parser.add_argument('-i', '--input_datapoint',
-    #                    help='Input file or query datapoint\n Option 1: Comma-separated list of identifiers (UniProt ID-wt residue-position-mutated residue (e.g. Q9Y4W6-N-432-T or P41180-E-604-K, Q9Y4W6-N-432-T)) \n Option 2: Enter comma-separated file path')
-    #
-    #parser.add_argument('-impute', '--imputation_state', default='True',
-    #                    help='Whether resulting feature vector should be imputed or not. Default True.')
-    
-    #args = parser.parse_args()
     
     input_set = input_data
-    ###mode = 1
     impute = impute
     submitted = st.form_submit_button(label="Submit", help=None, on_click=None, args=None, kwargs=None, type="secondary", disabled=False, use_container_width=False)
     print('*****************************************')
     print('Feature vector generation is in progress. \nPlease check log file for updates..')
     print('*****************************************')
-    #mode = int(mode)
     mode = int(source)
     
 selected_df = pd.DataFrame()