def parse_samples(self, t):
        """
        Parse a list of samples to make sure that it has the correct
        dimensions.

        :param t: ``(nsamples,)`` or ``(nsamples, ndim)``
            The list of samples. If 1-D, this is assumed to be a list of
            one-dimensional samples otherwise, the size of the second
            dimension is assumed to be the dimension of the input space.

        Raises:
            ValueError: If the input dimension doesn't match the dimension of
                the kernel.

        """
        t = np.atleast_1d(t)
        # Deal with one-dimensional data.
        if len(t.shape) == 1:
            t = np.atleast_2d(t).T

        # Double check the dimensions against the kernel.
        if len(t.shape) != 2 or (self.kernel is not None and
                                 t.shape[1] != self.kernel.ndim):
            raise ValueError("Dimension mismatch")

        return t
Parse a list of samples to make sure that it has the correct
        dimensions.

        :param t: ``(nsamples,)`` or ``(nsamples, ndim)``
            The list of samples. If 1-D, this is assumed to be a list of
            one-dimensional samples otherwise, the size of the second
            dimension is assumed to be the dimension of the input space.

        Raises:
            ValueError: If the input dimension doesn't match the dimension of
                the kernel.