sampling#

Sample distributions, either from real world data or from uniform distributions.

Functions

`check_dist`	Check whether counts match the expected distribution.
`check_normal`	Alias to check_dist(dist='normal')
`check_poisson`	Alias to check_dist(dist='poisson')
`check_truncated_poisson`	test if data fits in truncated poisson distribution between upperbound and lowerbound using kstest :type testdata: :param testdata: data to be tested :type testdata: array :type mu: :param mu: expected mean for the poisson distribution :type mu: float :type lowerbound: :param lowerbound: lowerbound for truncation :type lowerbound: float :type upperbound: :param upperbound: upperbound for truncation :type upperbound: float
`fast_choice`	Choose an option -- quickly -- from the provided weights.
`resample_age`	Resample age from single year age distribution.
`sample_from_range`	Sample from a distribution from min_val to max_val, inclusive.
`sample_single_arr`	Sample from a distribution.
`sample_single_dict`	Sample from a distribution.
`set_seed`	Reset the random seed -- complicated because of Numba.
`statistic_test`	Perform statistical checks for expected and actual data based on the null hypothesis that expected and actual distributions are identical.