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d5efa2c
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1 Parent(s): 848033d

Update app.py

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  1. app.py +12 -6
app.py CHANGED
@@ -10,15 +10,21 @@ scaler = MinMaxScaler()
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  def extract_features(sequence):
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  """Calculate AAC, Dipeptide Composition, and normalize features."""
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- # Calculate Amino Acid Composition (AAC)
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- aac = AAComposition.CalculateAADipeptideComposition(sequence)
 
 
 
 
 
 
 
 
 
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-
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- # Normalize with pre-trained scaler (avoid fitting new data)
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- normalized_features = scaler.fit_transform([aac])
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-
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  return normalized_features
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  def predict(sequence):
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  """Predict AMP vs Non-AMP"""
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  features = extract_features(sequence)
 
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  def extract_features(sequence):
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  """Calculate AAC, Dipeptide Composition, and normalize features."""
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+ # Calculate Amino Acid Composition (AAC) and convert to array
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+ aac = np.array(list(propy.AAComposition.CalculateAAC(sequence).values()))
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+
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+ # Calculate Dipeptide Composition and convert to array
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+ dipeptide_comp = np.array(list(propy.AAComposition.CalculateAADipeptideComposition(sequence).values()))
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+
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+ # Combine both features (AAC and Dipeptide Composition)
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+ features = np.concatenate((aac, dipeptide_comp))
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+
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+ # Normalize using the pre-trained scaler (Ensure the scaler is loaded correctly)
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+ normalized_features = scaler.transform([features]) # Don't use fit_transform(), only transform()
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  return normalized_features
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+
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  def predict(sequence):
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  """Predict AMP vs Non-AMP"""
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  features = extract_features(sequence)