--- a/COBRAxy/flux_to_map.py	Mon Jan 13 10:01:40 2025 +0000
+++ b/COBRAxy/flux_to_map.py	Mon Jan 13 15:16:18 2025 +0000
@@ -842,24 +842,37 @@
     if missing_reactions:
         sys.exit(f'Execution aborted: Missing required reactions {missing_reactions} in {datasetName}\n')
 
+
     # Calculate new rows using safe division
     lact_glc = np.divide(
-        dataset.loc['EX_lac__L_e'], -dataset.loc['EX_glc__D_e'], 
-        out=np.zeros_like(dataset.loc['EX_lac__L_e']), where=dataset.loc['EX_glc__D_e'] != 0
+        np.clip(dataset.loc['EX_lac__L_e'].to_numpy(), a_min=0, a_max=None),
+        np.clip(dataset.loc['EX_glc__D_e'].to_numpy(), a_min=None, a_max=0),
+        out=np.full_like(dataset.loc['EX_lac__L_e'].to_numpy(), np.nan),  # Prepara un array con NaN come output di default
+        where=dataset.loc['EX_glc__D_e'].to_numpy() != 0  # Condizione per evitare la divisione per zero
     )
     lact_gln = np.divide(
-        dataset.loc['EX_lac__L_e'], -dataset.loc['EX_gln__L_e'], 
-        out=np.zeros_like(dataset.loc['EX_lac__L_e']), where=dataset.loc['EX_gln__L_e'] != 0
+        np.clip(dataset.loc['EX_lac__L_e'].to_numpy(), a_min=0, a_max=None),
+        np.clip(dataset.loc['EX_gln__L_e'].to_numpy(), a_min=None, a_max=0),
+        out=np.full_like(dataset.loc['EX_lac__L_e'].to_numpy(), np.nan), 
+        where=dataset.loc['EX_gln__L_e'].to_numpy() != 0
+    )
+    lact_o2 = np.divide(
+        np.clip(dataset.loc['EX_lac__L_e'].to_numpy(), a_min=0, a_max=None),
+        np.clip(dataset.loc['EX_o2_e'].to_numpy(), a_min=None, a_max=0),
+        out=np.full_like(dataset.loc['EX_lac__L_e'].to_numpy(), np.nan), 
+        where=dataset.loc['EX_o2_e'].to_numpy() != 0
     )
     glu_gln = np.divide(
-        dataset.loc['EX_glu__L_e'], -dataset.loc['EX_gln__L_e'], 
-        out=np.zeros_like(dataset.loc['EX_glu__L_e']), where=dataset.loc['EX_gln__L_e'] != 0
+        dataset.loc['EX_glu__L_e'].to_numpy(),
+        np.clip(dataset.loc['EX_gln__L_e'].to_numpy(), a_min=None, a_max=0), 
+        out=np.full_like(dataset.loc['EX_lac__L_e'].to_numpy(), np.nan),
+        where=dataset.loc['EX_gln__L_e'].to_numpy() != 0
     )
 
     # Create a DataFrame for the new rows
     new_rows = pd.DataFrame({
-        dataset.index.name: ['LactGlc', 'LactGln', 'GluGln'],
-        **{col: [lact_glc[i], lact_gln[i], glu_gln[i]] for i, col in enumerate(dataset.columns)}
+        dataset.index.name: ['LactGlc', 'LactGln','LactO2', 'GluGln'],
+        **{col: [lact_glc[i], lact_gln[i],lact_o2[i], glu_gln[i]] for i, col in enumerate(dataset.columns)}
     })
 
     # Reset the index of the original dataset and append new rows