Stephan Hoyer <sho...@gmail.com> wrote: > I have recently encountered several use cases for randomly generate random > number seeds: > > 1. When writing a library of stochastic functions that take a seed as an > input argument, and some of these functions call multiple other such > stochastic functions. Dask is one such example [1]. > > 2. When a library needs to produce results that are reproducible after > calling numpy.random.seed, but that do not want to use the functions in > numpy.random directly. This came up recently in a pandas pull request [2], > because we want to allow using RandomState objects as an alternative to > global state in numpy.random. A major advantage of this approach is that it > provides an obvious alternative to reusing the private numpy.random._mtrand > [3].
What about making numpy.random a finite state machine, and keeping a stack of RandomState seeds? That is, something similar to what OpenGL does for its matrices? Then we get two functions, numpy.random.push_seed and numpy.random.pop_seed. Sturla _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
