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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.
The text was updated successfully, but these errors were encountered:
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 toL
. Check with the product scheme and, perhaps, ndim.The text was updated successfully, but these errors were encountered: