message: update default param for representation.metrics
diff: @@ -328,22 +328,28 @@ class PersistenceFisherDistance(BaseEstimator, TransformerMixin):
  """
  return _persistence_fisher_distance(diag1, diag2, bandwidth=self.bandwidth, kernel_approx=self.kernel_approx)
  +
  class WassersteinDistance(BaseEstimator, TransformerMixin):
  """
  This is a class for computing the Wasserstein distance matrix from a list of persistence diagrams.
  """
  - def __init__(self, order=2, internal_p=2, mode="pot", delta=0.01):
  + def __init__(self, order=1, internal_p=np.inf, mode="hera", delta=0.01):
  """
  Constructor for the WassersteinDistance class.
  Parameters:
  - order (int): exponent for Wasserstein, default value is 2., see :func:`gudhi.wasserstein.wasserstein_distance`.
  - internal_p (int): ground metric on the (upper-half) plane (i.e. norm l_p in R^2), default value is 2 (euclidean norm), see :func:`gudhi.wasserstein.wasserstein_distance`.
  - mode (str): method for computing Wasserstein distance. Either "pot" or "hera".
  + order (int): exponent for Wasserstein, default value is 1., see :func:`gudhi.wasserstein.wasserstein_distance`.
  + internal_p (int): ground metric on the (upper-half) plane (i.e. norm l_p in R^2), default value is `np.inf`, see :func:`gudhi.wasserstein.wasserstein_distance`.
  + mode (str): method for computing Wasserstein distance. Either "pot" or "hera". Default set to "hera".
  delta (float): relative error 1+delta. Used only if mode == "hera".
  """
  self.order, self.internal_p, self.mode = order, internal_p, mode
  - self.metric = "pot_wasserstein" if mode == "pot" else "hera_wasserstein"
  + if mode == "pot":
  + self.metric = "pot_wasserstein"
  + elif mode == "hera":
  + self.metric = "hera_wasserstein"
  + else:
  + raise NameError("Unknown mode. Current available values for mode are 'hera' and 'pot'")
  self.delta = delta
  def fit(self, X, y=None):
  