`); SciPySciPy Installing User Guide API reference Building from source Development Release notes GitHubGitHub TwitterTwitter Installing User Guide API reference Building from source Development Release notes GitHubGitHub TwitterTwitterSection Navigationscipyscipy.clusterscipy.constantsscipy.datasetsscipy.differentiatescipy.fftscipy.fftpackscipy.integratescipy.interpolatescipy.ioscipy.linalgscipy.ndimagescipy.odrscipy.optimizescipy.signalscipy.sparsescipy.spatialscipy.specialscipy..." />`); SciPySciPy Installing User Guide API reference Building from source Development Release notes GitHubGitHub TwitterTwitter Installing User Guide API reference Building from source Development Release notes GitHubGitHub TwitterTwitterSection Navigationscipyscipy.clusterscipy.constantsscipy.datasetsscipy.differentiatescipy.fftscipy.fftpackscipy.integratescipy.interpolatescipy.ioscipy.linalgscipy.ndimagescipy.odrscipy.optimizescipy.signalscipy.sparsescipy.spatialscipy.specialscipy..." /> set_random_state — SciPy v1.15.3 Manual
scipy.stats.sampling.NumericalInverseHermite.

set_random_state#

NumericalInverseHermite.set_random_state(random_state=None)#

Set the underlying uniform random number generator.

Parameters:
random_state{None, int, numpy.random.Generator,

A NumPy random number generator or seed for the underlying NumPy random number generator used to generate the stream of uniform random numbers. If random_state is None (or np.random), the numpy.random.RandomState singleton is used. If random_state is an int, a new RandomState instance is used, seeded with random_state. If random_state is already a Generator or RandomState instance then that instance is used.