code: def ppf(self, u):
          
          N, du = u.shape
          if du < self.dim:
              z = np.zeros((N, self.dim))
              z[:, :du] = stats.norm.ppf(u)
          else:
              z = stats.norm.ppf(u)
          return self.linear_transform(z)
docs: Note: if dim(u) < self.dim, the remaining columns are filled with 0
          Useful in case the distribution is partly degenerate