message: fixed error in DiagramScaler
diff: @@ -64,25 +64,25 @@ class Clamping(BaseEstimator, TransformerMixin):
  def fit(self, X, y=None):
  """
  - Fit the Clamping class on a list of list of values (this function actually does nothing but is useful when Clamping is included in a scikit-learn Pipeline).
  + Fit the Clamping class on a list of values (this function actually does nothing but is useful when Clamping is included in a scikit-learn Pipeline).
  Parameters:
  - X (list of numpy arrays of size n): input values.
  + X (numpy array of size n): input values.
  y (n x 1 array): value labels (unused).
  """
  return self
  def transform(self, X):
  """
  - Clamp each list of values individually.
  + Clamp list of values.
  Parameters:
  - X (list of numpy arrays of size n): input list of list of values.
  + X (numpy array of size n): input list of values.
  Returns:
  - Xfit (list of numpy arrays of size n): output list of list of values.
  + Xfit (numpy array of size n): output list of values.
  """
  - Xfit = [np.where(L >= self.limit, self.limit * np.ones(L.shape), L) for L in X]
  + Xfit = np.where(X >= self.limit, self.limit * np.ones(X.shape), X)
  return Xfit
  class DiagramScaler(BaseEstimator, TransformerMixin):
  @@ -132,7 +132,8 @@ class DiagramScaler(BaseEstimator, TransformerMixin):
  for i in range(len(Xfit)):
  if Xfit[i].shape[0] > 0:
  for (indices, scaler) in self.scalers:
  - Xfit[i][:,indices] = scaler.transform(Xfit[i][:,indices])
  + for I in indices:
  + Xfit[i][:,I] = np.squeeze(scaler.transform(np.reshape(Xfit[i][:,I], [-1,1])))
  return Xfit
  class Padding(BaseEstimator, TransformerMixin):
  