Random Sampling

The following table lists both implemented and not implemented methods. If you have need of an operation that is listed as not implemented, feel free to open an issue on the GitHub repository, or give a thumbs up to already created issues. Contributions are also welcome!

The following table is structured as follows: The first column contains the method name. The second column contains link to a description of corresponding numpy method. The third column is a flag for whether or not there is an implementation in Xorbits for the method in the left column. Y stands for yes, N stands for no, P standsfor partial (meaning some parameters may not be supported yet), and D stands for default to numpy.

Sample random data

xorbits.numpy.random	numpy.random	Implemented? (Y/N/P/D)	Notes for Current implementation
rand	rand	Y
randn	randn	Y
randint	randint	Y
random_integers	random_integers	Y
random_sample	random_sample	Y
random	random	Y
ranf	ranf	Y
sample	sample	Y
choice	choice	Y
bytes	bytes	Y

Distributions

xorbits.numpy.random	numpy.random	Implemented? (Y/N/P/D)	Notes for Current implementation
beta	beta	Y
binomial	binomial	Y
chisquare	chisquare	Y
dirichlet	dirichlet	Y
exponential	exponential	Y
f	f	Y
gamma	gamma	Y
geometric	geometric	Y
gumbel	gumbel	Y
hypergeometric	hypergeometric	Y
laplace	laplace	Y
lognormal	lognormal	Y
logseries	logseries	Y
multinomial	multinomial	Y
multivariate_normal	multivariate_normal	Y
negative_binomial	negative_binomial	Y
noncentral_chisquare	noncentral_chisquare	Y
noncentral_f	noncentral_f	Y
normal	normal	Y
pareto	pareto	Y
poisson	poisson	Y
power	power	Y
rayleigh	rayleigh	Y
standard_cauchy	standard_cauchy	Y
standard_exponential	standard_exponential	Y
standard_gamma	standard_gamma	Y
standard_normal	standard_normal	Y
standard_t	standard_t	Y
triangular	triangular	Y
uniform	uniform	Y
vonmises	vonmises	Y
wald	wald	Y
weibull	weibull	Y
zipf	zipf	Y

Random number generator

xorbits.numpy.random	numpy.random	Implemented? (Y/N/P/D)	Notes for Current implementation
seed	seed	Y
RandomState	RandomState	Y	RandomState ensures backward compatibility with NumPy 1.16, reproducing identical sequences. It is frozen with no further updates and should only be used for consistency with older versions.