message: Fix barycenter sphinx warnings
diff: @@ -18,8 +18,7 @@ from gudhi.wasserstein import wasserstein_distance
  def _mean(x, m):
  '''
  :param x: a list of 2D-points, off diagonal, x_0... x_{k-1}
  - :param m: total amount of points taken into account,
  - that is we have (m-k) copies of diagonal
  + :param m: total amount of points taken into account, that is we have (m-k) copies of diagonal
  :returns: the weighted mean of x with (m-k) copies of the diagonal
  '''
  k = len(x)
  @@ -33,34 +32,28 @@ def _mean(x, m):
  def lagrangian_barycenter(pdiagset, init=None, verbose=False):
  '''
  - :param pdiagset: a list of ``numpy.array`` of shape `(n x 2)`
  - (`n` can variate), encoding a set of
  - persistence diagrams with only finite coordinates.
  + :param pdiagset: a list of ``numpy.array`` of shape `(n x 2)` (`n` can variate), encoding a set of persistence
  + diagrams with only finite coordinates.
  :param init: The initial value for barycenter estimate.
  If ``None``, init is made on a random diagram from the dataset.
  - Otherwise, it can be an ``int``
  - (then initialization is made on ``pdiagset[init]``)
  - or a `(n x 2)` ``numpy.array`` enconding
  - a persistence diagram with `n` points.
  + Otherwise, it can be an ``int`` (then initialization is made on ``pdiagset[init]``)
  + or a `(n x 2)` ``numpy.array`` enconding a persistence diagram with `n` points.
  :type init: ``int``, or (n x 2) ``np.array``
  - :param verbose: if ``True``, returns additional information about the
  - barycenter.
  + :param verbose: if ``True``, returns additional information about the barycenter.
  :type verbose: boolean
  - :returns: If not verbose (default), a ``numpy.array`` encoding
  - the barycenter estimate of pdiagset
  + :returns: If not verbose (default), a ``numpy.array`` encoding the barycenter estimate of pdiagset
  (local minimum of the energy function).
  If ``pdiagset`` is empty, returns ``None``.
  - If verbose, returns a couple ``(Y, log)``
  - where ``Y`` is the barycenter estimate,
  + If verbose, returns a couple ``(Y, log)`` where ``Y`` is the barycenter estimate,
  and ``log`` is a ``dict`` that contains additional informations:
  - `"groupings"`, a list of list of pairs ``(i,j)``.
  - Namely, ``G[k] = [...(i, j)...]``, where ``(i,j)`` indicates
  - that ``pdiagset[k][i]`` is matched to ``Y[j]``
  - if ``i = -1`` or ``j = -1``, it means they
  - represent the diagonal.
  +
  + Namely, ``G[k] = [...(i, j)...]``, where ``(i,j)`` indicates that ``pdiagset[k][i]`` is matched to ``Y[j]``
  + if ``i = -1`` or ``j = -1``, it means they represent the diagonal.
  - `"energy"`, ``float`` representing the Frechet energy value obtained.
  +
  It is the mean of squared distances of observations to the output.
  - `"nb_iter"`, ``int`` number of iterations performed before convergence of the algorithm.
  