M/Ph?&ddlZddlmZdZddZdS)NawPassing `None` as the seed currently return the NumPy singleton RandomState (np.random.mtrand._rand). After release 0.13 this will change to using the default generator provided by NumPy (np.random.default_rng()). If you need reproducible draws, you should pass a seeded np.random.Generator, e.g., import numpy as np seed = 32839283923801 rng = np.random.default_rng(seed)" cttdr!t|tjjr|St|t jjr|St|t jjr|S|t j |Sddl }| ttt jjjS)a Turn `seed` into a random number generator. Parameters ---------- seed : {None, int, array_like[ints], `numpy.random.Generator`, `numpy.random.RandomState`, `scipy.stats.qmc.QMCEngine`}, optional If `seed` is None fresh, unpredictable entropy will be pulled from the OS and `numpy.random.Generator` is used. If `seed` is an int or ``array_like[ints]``, a new ``Generator`` instance is used, seeded with `seed`. If `seed` is already a ``Generator``, ``RandomState`` or `scipy.stats.qmc.QMCEngine` instance then that instance is used. `scipy.stats.qmc.QMCEngine` requires SciPy >=1.7. It also means that the generator only have the method ``random``. Returns ------- seed : {`numpy.random.Generator`, `numpy.random.RandomState`, `scipy.stats.qmc.QMCEngine`} Random number generator. qmcNr)hasattrstats isinstancer QMCEnginenprandom RandomState Generator default_rngwarningswarn _future_warn FutureWarningmtrand_rand)seedrs Z/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/statsmodels/tools/rng_qrng.pycheck_random_staters6ue & tUY0 1 1 & D")/ 0 0 & D")- . .& y$$T*** lM222y%%)N)numpyr scipy.statsrrrrrrsH  '&'&'&'&'&'&r