class_docstr: Wrapped Gaussian Process.
  
  The implementation is based on the algorithm 4 of [1]_.
  
  Parameters
  ----------
  space : Manifold
      Equipped manifold.
  prior : callable
      Associate to each input a manifold valued point.
  
  References
  ----------
  .. [1] Mallasto, A. and Feragen, A. Wrapped gaussian process
      regression on riemannian manifolds. In 2018 IEEE/CVF
      Conference on Computer Vision and Pattern Recognition
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docstr: Fit Wrapped Gaussian process regression model.
  
  The Wrapped Gaussian process is fit through the following steps:
  
  - Compute the tangent dataset using the prior
  - Fit a Gaussian process regression on the tangent dataset
  - Store the resulting euclidean Gaussian process
  
  Parameters
  ----------
  X : array-like, shape=[n_samples,]
      Training input samples.
  y : array-like, shape[n_samples, {dim, [n,n]}]
      Training target values.
  
  Returns
  -------
  self : object
      Returns self.
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code: def fit(self, X, y):
      """Fit Wrapped Gaussian process regression model.
  
      The Wrapped Gaussian process is fit through the following steps:
  
      - Compute the tangent dataset using the prior
      - Fit a Gaussian process regression on the tangent dataset
      - Store the resulting euclidean Gaussian process
  
      Parameters
      ----------
      X : array-like, shape=[n_samples,]
          Training input samples.
      y : array-like, shape[n_samples, {dim, [n,n]}]
          Training target values.
  
      Returns
      -------
      self : object
          Returns self.
      """
      self.tangent_y_train_ = tangent_y = self._get_tangent_targets(
          X, y
      )
      tangent_y = gs.reshape(tangent_y, (y.shape[0], -1))
  
      self.euclidean_gpr.fit(X, tangent_y)
  
      return self
  
file_path: geomstats/geomstats/learning/wrapped_gaussian_process.py
imports: from sklearn.base import BaseEstimator, MultiOutputMixin, RegressorMixin
  from sklearn.gaussian_process import GaussianProcessRegressor
  import geomstats.backend
label_desc: Use image node_id 4 for calling the WrappedGaussianProcess obj's underlying member method code with example usage: obj.fit(X, y) and returns: self