Update app.py

app.py

@@ -394,17 +394,21 @@ with tab5:
 
     # ========== 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.")
-    binary32_file = st.file_uploader("Upload 32-bit Binary CSV", type=["csv"], key="binary_32")
-
+    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")
 
-    
     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]  # assume ascending
+    else:
+        df_32 = st.data_editor(
+            pd.DataFrame(columns=[str(h) for h in mutation_site_headers_actual_3614]),
+            num_rows="dynamic",
+            key="manual_32_input"
+        )
 
-        # Reordered: 4402 → 3244, 4882 → 4455
+    if not df_32.empty:
         reordered_df_32 = df_32[[str(h) for h in mutation_site_headers_3614 if str(h) in df_32.columns]]
         st.subheader("Binary Labels (Reordered 4402→3244, 4882→4455)")
         st.dataframe(reordered_df_32.style.applymap(lambda v: "background-color: lightgreen" if v == 1 else "background-color: lightcoral"))
@@ -414,7 +418,6 @@ with tab5:
         st.subheader("Decoded String (Reordered 4402→3244, 4882→4455)")
         st.write(decoded_reordered)
 
-        # Ascending: 3244 → 4882
         df_ascending = df_32[[str(h) for h in mutation_site_headers_actual_3614 if str(h) in df_32.columns]]
         st.subheader("Binary Labels (Ascending 3244→4882)")
         st.dataframe(df_ascending.style.applymap(lambda v: "background-color: lightgreen" if v == 1 else "background-color: lightcoral"))
@@ -431,7 +434,7 @@ with tab5:
 
         df_32_robot = df_32.copy()
         df_32_robot.insert(0, 'Sample', range(1, len(df_32_robot)+1))
-        df_32_robot['# donors'] = df_32_robot.iloc[:, 1:].sum(axis=1)
+        df_32_robot['# donors'] = df_32_robot.iloc[:, 1:].astype(int).sum(axis=1)
         df_32_robot['volume donors (µl)'] = 32 / df_32_robot['# donors']
 
         robot_script_32 = []
@@ -442,9 +445,9 @@ with tab5:
 
         for i, col in enumerate(df_32.columns):
             for row_idx, sample in df_32_robot.iterrows():
-                if sample[col] == 1:
+                if int(sample[col]) == 1:
                     source = source_wells_32[i]
-                    dest = f"A{sample['Sample']}"
+                    dest = get_well_position(int(sample['Sample']))
                     vol = round(sample['volume donors (µl)'], 2)
                     robot_script_32.append({'Source': source, 'Destination': dest, 'Volume': vol})
 
@@ -452,12 +455,11 @@ with tab5:
         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.markdown("---")
 
     # ========== 31-BIT DECODING ==========
     st.subheader("31-bit Binary Grouped per Row")
-    st.write("Upload CSV with 31 columns (no headers), each row = one 6-bit ASCII character group.")
+    st.write("Upload CSV with 31 columns (no headers), each row = one 6-bit ASCII character group or enter manually below.")
 
     binary31_file = st.file_uploader("Upload 31-bit Group CSV", type=["csv"], key="binary_31")
 
@@ -470,33 +472,28 @@ with tab5:
             num_rows="dynamic",
             key="manual_31_input"
         )
-        
-    if not df_31.empty:
 
-        # Reordered: 4402 → 3244, 4882 → 4455
+    if not df_31.empty:
         reordered_df_31 = df_31[[str(h) for h in mutation_site_headers if str(h) in df_31.columns]]
         st.subheader("Binary Labels (Reordered 4402→3244, 4882→4455)")
         st.dataframe(reordered_df_31.style.applymap(lambda v: "background-color: lightgreen" if v == 1 else "background-color: lightcoral"))
         st.download_button("Download Reordered CSV", reordered_df_31.to_csv(index=False), "decoded_binary_31_reordered.csv", key="download_csv_tab5_31_reordered")
 
-        # Flattened decoding for reordered
         decoded_flat_reordered = binary_labels_to_string(reordered_df_31.values.flatten().astype(int).tolist())
         st.subheader("Decoded String (Flattened 31-bit Reordered)")
         st.write(decoded_flat_reordered)
         st.download_button("Download Concatenated Output", decoded_flat_reordered, "decoded_31bit_string_reordered.txt", key="download_csv_tab5_31")
 
-        # Ascending: 3244 → 4882
         df_31_asc = df_31[[str(h) for h in mutation_site_headers_actual if str(h) in df_31.columns]]
         st.subheader("Binary Labels (Ascending 3244→4882)")
         st.dataframe(df_31_asc.style.applymap(lambda v: "background-color: lightgreen" if v == 1 else "background-color: lightcoral"))
         st.download_button("Download Ascending CSV", df_31_asc.to_csv(index=False), "decoded_binary_31_ascending.csv", key="download_csv_tab5_31_ascend")
 
-        # Flattened decoding for ascending
         decoded_flat_asc = binary_labels_to_string(df_31_asc.values.flatten().astype(int).tolist())
         st.subheader("Decoded String (Flattened 31-bit Ascending)")
         st.write(decoded_flat_asc)
         st.download_button("Download Concatenated Output", decoded_flat_asc, "decoded_31bit_string_ascending.txt", key="download_csv_tab5_31_asc")
-        
+
         # === Robot Preparation Script from 31-bit Binary ===
         st.subheader("Robot Preparation Script from 31-bit Binary")
         robot_template_31 = pd.read_csv("/home/user/app/Robot2.csv", skiprows=3)
@@ -504,7 +501,7 @@ with tab5:
 
         df_31_robot = df_31.copy()
         df_31_robot.insert(0, 'Sample', range(1, len(df_31_robot)+1))
-        df_31_robot['# donors'] = df_31_robot.iloc[:, 1:].sum(axis=1)
+        df_31_robot['# donors'] = df_31_robot.iloc[:, 1:].astype(int).sum(axis=1)
         df_31_robot['volume donors (µl)'] = 64 / df_31_robot['# donors']
 
         robot_script_31 = []
@@ -515,7 +512,7 @@ with tab5:
 
         for i, col in enumerate(df_31.columns):
             for row_idx, sample in df_31_robot.iterrows():
-                if sample[col] == 1:
+                if int(sample[col]) == 1:
                     source = source_wells_31[i]
                     dest = get_well_position(int(sample['Sample']))
                     vol = round(sample['volume donors (µl)'], 2)
@@ -523,4 +520,4 @@ with tab5:
 
         robot_script_31_df = pd.DataFrame(robot_script_31)
         st.dataframe(robot_script_31_df)
-        st.download_button("Download Robot Script (31-bit)", robot_script_31_df.to_csv(index=False), "robot_script_31bit.csv", key="download_robot_31")
+        st.download_button("Download Robot Script (31-bit)", robot_script_31_df.to_csv(index=False), "robot_script_31bit.csv", key="download_robot_31")