For higher-dimensional polynomials, the fitting data structure for each level would be a numpy.array of shape (n, n, ...), but only the lower (or upper) triangle of (n,n) is used. Perhaps even more fitting would be to address the entries in "barycentric" coordinates, such that the indices sum up to L. Check with the product scheme and, perhaps, ndim.
For higher-dimensional polynomials, the fitting data structure for each level would be a
numpy.arrayof shape(n, n, ...), but only the lower (or upper) triangle of(n,n)is used. Perhaps even more fitting would be to address the entries in "barycentric" coordinates, such that the indices sum up toL. Check with the product scheme and, perhaps, ndim.