Improving Random Sampling in Python- Pamphile Roy | SciPy 2022

NumPy random number generators and SciPy distributions are widely used to get random numbers. However, challenges might arise in the following situations: (i) sampling from non-standard distributions can be slow if a custom implementation is not available and (ii) sampling in high dimensions leads to poor convergence rates. Thanks to new developments in SciPy, there is an answer to these problems with two new submodules: scipy.stats.sampling and scipy.stats.qmc.