b912ae50a0ca1766eceb062973e2952997285fac,Python/phate/phate.py,PHATE,von_neumann_entropy,#PHATE#Any#,456

Before Change

            raise NotFittedError("This PHATE instance is not fitted yet. Call "
                                 ""fit" with appropriate arguments before "
                                 "using this method.")
        is_sparse = sparse.issparse(self.gs_ker)
        diff_aff = np.power(self.gs_ker.sum(axis=0), 1 / 2)
        if is_sparse:
            diff_aff = sparse.diags(np.array(diff_aff)[0])
        else:
            diff_aff = np.diagflat(diff_aff)
        diff_aff = diff_aff @ self.gs_ker @ diff_aff
        diff_aff = (diff_aff + diff_aff.T) / 2

        if is_sparse:

After Change

            raise NotFittedError("This PHATE instance is not fitted yet. Call "
                                 ""fit" with appropriate arguments before "
                                 "using this method.")
        if self.landmark_transitions is not None:
            // landmark operator is doing diffusion twice
            t_max = np.floor(t_max / 2).astype(np.int16)
        _, eigenvalues, _ = svd(self.diff_op)
        entropy = []
        eigenvalues_t = np.copy(eigenvalues)
        for _ in range(t_max):

Instances