It seems .jumped() when applied to PCG64 bitgenerator advances the state by different amounts when using numpy and randomgen's implementation. This is true even when numpy_seed parameter is set to True. Looking at numpy documentation and randomgen code it seems that numpy has a more sophisticated jump mechanism where it advances the state based on a value derived from the golden ratio to reduce correlation between streams, while randomgen jumps by multiples of 2^64. Now is this deviation from numpy's jump implementation intentional? Or is it possible to make randomgen's behavior the same as that of numpy's?
It seems .jumped() when applied to PCG64 bitgenerator advances the state by different amounts when using numpy and randomgen's implementation. This is true even when numpy_seed parameter is set to True. Looking at numpy documentation and randomgen code it seems that numpy has a more sophisticated jump mechanism where it advances the state based on a value derived from the golden ratio to reduce correlation between streams, while randomgen jumps by multiples of 2^64. Now is this deviation from numpy's jump implementation intentional? Or is it possible to make randomgen's behavior the same as that of numpy's?