def fit(self, X, y=None, input_type='data'):
        X = self._validate_input(X, input_type)
        self.fit_geometry(X, input_type)
        random_state = check_random_state(self.random_state)
        self.embedding_ = spectral_embedding(self.geom_,
                                             n_components = self.n_components,
                                             eigen_solver = self.eigen_solver,
                                             random_state = random_state,
                                             eigen_tol = self.eigen_tol,
                                             drop_first = self.drop_first,
                                             diffusion_maps = self.diffusion_maps)
        self.affinity_matrix_ = self.geom_.affinity_matrix
        self.laplacian_matrix_ = self.geom_.laplacian_matrix
        self.laplacian_matrix_type_ = self.geom_.laplacian_method
        return self
Fit the model from data in X.
dataset/ETHPy150Open mmp2/megaman/megaman/embedding/spectral_embedding.py/SpectralEmbedding.fit