Update app.py

app.py

@@ -393,7 +393,7 @@ with tab5:
     st.header("Decode Binary Labels to String")
 
     # Utility: Track source volumes and update if exceeds limit
-    def track_and_replace_source(source_list, robot_script, volume_limit=170):
+    def track_and_replace_source(source_list, robot_script, volume_limit=180):
         source_volumes = {}
         adjusted_sources = []
 
@@ -407,7 +407,6 @@ with tab5:
             source_volumes[src] += vol
 
             if source_volumes[src] > volume_limit:
-                # Convert A->E, B->F, ..., by shifting ASCII code +4
                 row_letter = src[0]
                 col_number = src[1:]
                 new_row_letter = chr(ord(row_letter) + 4)
@@ -434,7 +433,6 @@ with tab5:
         for row_idx, sample in df_robot.iterrows():
             for col in mutation_headers:
                 if col in sample and int(sample[col]) == 1:
-                    # Check current D well volume
                     current_d_well = f"D{current_d_index}"
                     if current_d_well not in d_source_volumes:
                         d_source_volumes[current_d_well] = 0
@@ -458,13 +456,21 @@ with tab5:
 
         return d_source_script, d_source_volumes
 
+    def generate_source_wells(n):
+        wells = []
+        rows = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
+        for i in range(n):
+            row = rows[i // 12]  # cycle through A, B, C...
+            col = (i % 12) + 1    # 1 to 12
+            wells.append(f"{row}{col}")
+        return wells
+
     # ========== 32-BIT DECODING ==========
     st.subheader("32-bit Binary per Row")
     st.write("Upload CSV with 32 columns (0 or 1), no headers, from EF Binary format or enter manually below.")
 
     binary32_file = st.file_uploader("Upload 32-bit Binary CSV", type=["csv"], key="binary_32")
 
-    # === Optional fields ===
     st.subheader("Optional Metadata (Optional)")
     barcode_id_input = st.text_input("Barcode ID (applied to all rows, optional)", value="")
     labware_source_input = st.text_input("Labware for Source (optional, default = 1)", value="1")
@@ -502,10 +508,7 @@ with tab5:
         st.write(decoded_asc)
         st.download_button("Download Concatenated Output", decoded_asc, "decoded_32bit_string_ascending.txt", key="download_txt_tab5_32_asc")
 
-        # === Robot Preparation Script from 32-bit Binary ===
         st.subheader("Robot Preparation Script from 32-bit Binary")
-        robot_template_32 = pd.read_csv("/home/user/app/Robot2.csv", skiprows=3)
-        robot_template_32.columns = ['Labware', 'Source', 'Labware_2', 'Destination', 'Volume', 'Tool', 'Name']
 
         df_32_robot = df_32.copy()
         df_32_robot.insert(0, 'Sample', range(1, len(df_32_robot)+1))
@@ -513,10 +516,7 @@ with tab5:
         df_32_robot['volume donors (µl)'] = 64 / df_32_robot['# donors']
 
         robot_script_32 = []
-        source_wells_32 = robot_template_32['Source'].unique().tolist()
-        if len(source_wells_32) < df_32.shape[1]:
-            source_wells_32 += [f"Fake{i}" for i in range(df_32.shape[1] - len(source_wells_32))]
-        source_wells_32 = source_wells_32[:df_32.shape[1]]
+        source_wells_32 = generate_source_wells(df_32.shape[1])
 
         for i, col in enumerate(df_32.columns):
             for row_idx, sample in df_32_robot.iterrows():
@@ -534,17 +534,15 @@ with tab5:
 
         robot_script_32, source_volumes_32 = track_and_replace_source(source_wells_32, robot_script_32)
 
-        # Add fixed 16ul D sources
         d_script, d_volumes = generate_fixed_d_source_instructions(df_32_robot)
         full_robot_script = robot_script_32 + d_script
 
         robot_script_32_df = pd.DataFrame(full_robot_script)
         robot_script_32_df.insert(0, 'Barcode ID', barcode_id_input)
-        robot_script_32_df.insert(1, 'Labware_1', labware_source_input)
-        robot_script_32_df.insert(3, 'Labware_2', labware_dest_input)
+        robot_script_32_df.insert(1, 'Labware_Source', labware_source_input)
+        robot_script_32_df.insert(3, 'Labware_Destination', labware_dest_input)
         robot_script_32_df['Name'] = name_input
-        robot_script_32_df = robot_script_32_df[['Barcode ID', 'Labware_1', 'Source', 'Labware_2', 'Destination', 'Volume', 'Tool', 'Name']]
-        robot_script_32_df.columns = ['Barcode ID', 'Labware', 'Source', 'Labware', 'Destination', 'Volume', 'Tool', 'Name']
+        robot_script_32_df = robot_script_32_df[['Barcode ID', 'Labware_Source', 'Source', 'Labware_Destination', 'Destination', 'Volume', 'Tool', 'Name']]
 
         st.dataframe(robot_script_32_df)
         st.download_button("Download Robot Script (32-bit)", robot_script_32_df.to_csv(index=False), "robot_script_32bit.csv", key="download_robot_32")