# HG changeset patch
# User luca_milaz
# Date 1728804064 0
# Node ID 547942aa1a93db97e78722ae11a470c480bd0d85
# Parent  d4162562c8f5ec17bbd29b27bb92e766d4f7f245
Uploaded

diff -r d4162562c8f5 -r 547942aa1a93 COBRAxy/ras_to_bounds.py
--- a/COBRAxy/ras_to_bounds.py	Sun Oct 13 07:20:51 2024 +0000
+++ b/COBRAxy/ras_to_bounds.py	Sun Oct 13 07:21:04 2024 +0000
@@ -58,11 +58,6 @@
                         required = True,
                         type=utils.Bool("using_RAS"),
                         help = 'ras selector')
-    
-    parser.add_argument('-c', '--classes',
-                    type = str,
-                    required = False,
-                    help = 'input classes')
 
     parser.add_argument('-cc', '--cell_class',
                     type = str,
@@ -218,10 +213,9 @@
 
     if(ARGS.ras_selector == True):
         ras_file_list = ARGS.input_ras.split(",")
-        if(len(ras_file_list)>1):
-            ras_class_names = [cls.strip() for cls in ARGS.classes.split(',')]
-        else:
-            ras_class_names = ["placeHolder"]
+        ras_class_names = []
+        for file in ras_file_list:
+            ras_class_names.append(file.split(".")[0])
         ras_list = []
         class_assignments = pd.DataFrame(columns=["Patient_ID", "Class"])
         for ras_matrix, ras_class_name in zip(ras_file_list, ras_class_names):
@@ -232,7 +226,7 @@
             ras = ras.astype(float)
             ras_list.append(ras)
             for patient_id in ras.index:
-                class_assignments = pd.concat([class_assignments, pd.DataFrame({"Patient_ID": ras.index, "Class": ras_class_name})])
+                class_assignments = pd.concat([class_assignments, pd.DataFrame({"Patient_ID": patient_id, "Class": ras_class_name})])
         
         
         # Concatenate all ras DataFrames into a single DataFrame