Update app.py

app.py

@@ -18,6 +18,7 @@ feature_columns = model_package['feature_columns']
 aa_list = model_package['aa_list']
 dipeptides = model_package['dipeptides']
 hydrophobicity_scale = model_package['hydrophobicity_scale']
+eisenberg_scale = model_package['eisenberg_scale']
 aa_mass = model_package['aa_mass']
 aa_charge = model_package['aa_charge']
 aa_boman = model_package['aa_boman']
@@ -52,7 +53,7 @@ def extract_features_app(seq: str) -> pd.DataFrame:
         aromatic = np.mean([(dp[0] in 'FWY') + (dp[1] in 'FWY') for dp in dipeptides_seq]) / 2.0
         pI = np.mean([h(dp, {aa: 7 + (int(aa in 'KRH') - int(aa in 'DE')) for aa in aa_list}) for dp in dipeptides_seq])
         instability = np.mean([((dp[0] in 'DEKR') + (dp[1] in 'DEKR')) / 2.0 for dp in dipeptides_seq])
-        hydro_moment = np.sqrt(np.mean([(h(dp, hydrophobicity_scale))**2 for dp in dipeptides_seq]))
+        hydro_moment = np.sqrt(np.mean([(h(dp, eisenberg_scale))**2 for dp in dipeptides_seq]))
         aliphatic = np.mean([h(dp, aa_aliphatic) for dp in dipeptides_seq])
         boman = np.mean([h(dp, aa_boman) for dp in dipeptides_seq])
         flexibility = np.mean([h(dp, aa_flexibility) for dp in dipeptides_seq])