Update app.py

app.py

@@ -392,12 +392,87 @@ def get_well_position(sample_index):
 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):
+        source_volumes = {}
+        adjusted_sources = []
+
+        for entry in robot_script:
+            src = entry['Source']
+            vol = entry['Volume']
+
+            if src not in source_volumes:
+                source_volumes[src] = 0
+
+            source_volumes[src] += vol
+
+            if source_volumes[src] > volume_limit:
+                row_letter = src[0]
+                col_number = src[1:]
+                new_row_letter = chr(ord(row_letter) + 4)
+                new_src = f"{new_row_letter}{col_number}"
+                entry['Source'] = new_src
+
+                if new_src not in source_volumes:
+                    source_volumes[new_src] = 0
+                source_volumes[new_src] += vol
+                source_volumes[src] -= vol
+
+            adjusted_sources.append(entry)
+
+        return adjusted_sources, source_volumes
+
+    # Utility: Generate fixed-volume D source to all sample wells
+    def generate_fixed_d_source_instructions_to_all_samples(n_samples, fixed_volume=16, volume_limit=170):
+        d_source_volumes = {}
+        d_source_script = []
+        current_d_index = 1
+
+        for i in range(n_samples):
+            dest = get_well_position(i + 1)
+            current_d_well = f"D{current_d_index}"
+
+            if current_d_well not in d_source_volumes:
+                d_source_volumes[current_d_well] = 0
+
+            if d_source_volumes[current_d_well] + fixed_volume > volume_limit:
+                current_d_index += 1
+                current_d_well = f"D{current_d_index}"
+                d_source_volumes[current_d_well] = 0
+
+            d_source_volumes[current_d_well] += fixed_volume
+            tool = 'TS_10' if fixed_volume < 10 else 'TS_50'
+
+            d_source_script.append({
+                'Source': current_d_well,
+                'Destination': dest,
+                'Volume': fixed_volume,
+                'Tool': tool
+            })
+
+        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")
 
+    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")
+    labware_dest_input = st.text_input("Labware for Destination (optional, default = 1)", value="1")
+    name_input = st.text_input("Name field (optional, default = blank)", value="")
+
     if binary32_file:
         df_32 = pd.read_csv(binary32_file, header=None)
         df_32.columns = [str(h) for h in mutation_site_headers_actual_3614]
@@ -429,10 +504,7 @@ 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))
@@ -440,23 +512,45 @@ 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])
+        used_destinations = set()
 
         for i, col in enumerate(df_32.columns):
             for row_idx, sample in df_32_robot.iterrows():
                 if int(sample[col]) == 1:
                     source = source_wells_32[i]
                     dest = get_well_position(int(sample['Sample']))
+                    used_destinations.add(dest)
                     vol = round(sample['volume donors (µl)'], 2)
-                    robot_script_32.append({'Source': source, 'Destination': dest, 'Volume': vol})
+                    tool = 'TS_10' if vol < 10 else 'TS_50'
+                    robot_script_32.append({
+                        'Source': source,
+                        'Destination': dest,
+                        'Volume': vol,
+                        'Tool': tool
+                    })
+
+        robot_script_32, source_volumes_32 = track_and_replace_source(source_wells_32, robot_script_32)
+
+        d_script, d_volumes = generate_fixed_d_source_instructions_to_all_samples(len(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_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_Source', 'Source', 'Labware_Destination', 'Destination', 'Volume', 'Tool', 'Name']]
 
-        robot_script_32_df = pd.DataFrame(robot_script_32)
         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")
 
+        st.subheader("Total Volume Used Per Source")
+        combined_volumes = {**source_volumes_32, **d_volumes}
+        source_volume_df = pd.DataFrame(list(combined_volumes.items()), columns=['Source', 'Total Volume (µl)'])
+        st.dataframe(source_volume_df)
+        st.download_button("Download Source Volumes", source_volume_df.to_csv(index=False), "source_total_volumes.csv", key="download_volume_32")
+
     st.markdown("---")
 
     # ========== 31-BIT DECODING ==========