8e0ca26e5571d47425fc73bb3bb118082b742d00,geomstats/geometry/spd_matrices.py,SPDMatrices,random_uniform,#SPDMatrices#Any#,54

Before Change

            Points sampled in SPD(n).
        
        n = self.n
        size = (n_samples, n, n) if n_samples != 1 else (n, n)

        mat = 2 * gs.random.rand(*size) - 1
        spd_mat = GeneralLinear.exp(Matrices.to_symmetric(mat))

After Change

    @classmethod
    @geomstats.vectorization.decorator(["else", "matrix", "matrix"])
    def inverse_differential_log(cls, tangent_vec, base_point):
        Compute the inverse of the differential of the matrix logarithm.

        Compute the inverse of the differential of the matrix
        logarithm on SPD matrices at base_point applied to
        tangent_vec.

        Parameters
        ----------
        tangent_vec : array_like, shape=[..., n, n]
            Tangent vector at base point.
        base_point : array_like, shape=[..., n, n]
            Base point.

        Returns
        -------
        inverse_differential_log : array-like, shape=[..., n, n]
            Inverse of the differential of the matrix logarithm.
        
        eigvectors, transp_eigvectors, numerator, denominator, temp_result =\
            cls.aux_differential_power(0, tangent_vec, base_point)

Instances