Montecarlo Capability

[rdoddanavar]

CPP routine that generates random sequence given seed (int) and desired distribution (string), using the <random> library: http://www.cplusplus.com/reference/random/

Multiprocessing capability w/ RNG

[rdoddanavar]

Is this going to be an issue? https://codingnest.com/generating-random-numbers-using-c-standard-library-the-problems/

[rdoddanavar]

Use python's multiprocessing module to execute runs

[rdoddanavar]

• numpy.random for rng... can return numpy arrays of arbitrary shape
• pyDOE2 for LHS capability

[rdoddanavar]

Be careful with numpy.random; make sure RNG state is properly isolated between processes (import multiprocessing as mp

[rdoddanavar]

Use new instance of numpy.random.RandomState() in each process to isolate RNG state(s)

[rdoddanavar]

Managing RNG state across processes, consequences on seeding:

• https://peteroupc.github.io/random.html#Seeding_Multiple_Processes
• https://numpy.org/doc/stable/reference/random/parallel.html
• https://stackoverflow.com/questions/59263562/impact-of-setting-random-seed-to-recreate-a-simulated-behaviour-and-choosing-t

[rdoddanavar]

Passing multiple arguments into map for Pool:

• https://stackoverflow.com/questions/5442910/how-to-use-multiprocessing-pool-map-with-multiple-arguments
• https://stackoverflow.com/questions/25553919/passing-multiple-parameters-to-pool-map-function-in-python?noredirect=1&lq=1

Good solution are those above, in tandem with functools.partial:

• https://stackoverflow.com/questions/15331726/how-does-functools-partial-do-what-it-does

[rdoddanavar]

Use Philox in numpy.random to generate independent, uncorrelated streams: https://numpy.org/doc/stable/reference/random/parallel.html#independent-streams