`scipy.stats._mgc:_perm_test`

Signature

   def     _perm_test (    x    ,    y    ,    stat    ,    reps    =  1000   ,    workers    =  -1   ,    random_state    =  None     )

Helper function that calculates the p-value. See below for uses.

x, y : ndarray: x and y have shapes (n, p) and (n, q).
stat : float: The sample test statistic.
reps : int, optional: The number of replications used to estimate the null when using the permutation test. The default is 1000 replications.
workers : int or map-like callable, optional: If workers is an int the population is subdivided into workers sections and evaluated in parallel (uses multiprocessing.Pool <multiprocessing>). Supply -1 to use all cores available to the Process. Alternatively supply a map-like callable, such as multiprocessing.Pool.map for evaluating the population in parallel. This evaluation is carried out as workers(func, iterable). Requires that func be pickleable.
random_state : {None, int, `numpy.random.Generator`,: numpy.random.RandomState}, optional
If seed is None (or np.random), the numpy.random.RandomState singleton is used. If seed is an int, a new RandomState instance is used, seeded with seed. If seed is already a Generator or RandomState instance then that instance is used.