d65cddeddda46bb20f82b1e233cd5305ace7b1c7,chaospy/descriptives/conditional.py,,E_cond,#Any#Any#Any#,10

Before Change

    if len(freeze.shape) == 1:
        out = _E_cond(poly, freeze, dist, cache, **kws)
    else:
        out = polynomials.concatenate([
            _E_cond(poly, freeze_, dist, cache, **kws)[numpy.newaxis]
            for freeze_ in freeze
        ])
    if out.isconstant():
        out = out.tonumpy()
    return out

After Change

    unfrozen = poly(**{
        ("q%d" % idx): 1 for idx, keep in enumerate(freeze) if keep})
    frozen = poly(**{
        ("q%d" % idx): 1 for idx, keep in enumerate(freeze) if not keep})

    // if no unfrozen, poly will return numpy.ndarray instead of numpoly.ndpoly
    if not isinstance(unfrozen, polynomials.ndpoly):
        return polynomials.sum(frozen, 0)

    // Remove frozen coefficients, such that poly == sum(frozen*unfrozen) holds
    for key in unfrozen.keys:
        unfrozen[key] = unfrozen[key] != 0

    return polynomials.sum(frozen*E(unfrozen, dist), 0)

Instances