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. | +--------------------------+------------------+------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ .. _`GitHub repository`: https://github.com/xorbitsai/xorbits/issues .. _`rand`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.rand.html .. _`randn`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.randn.html .. _`randint`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.randint.html .. _`random_integers`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.random_integers.html .. _`random_sample`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.random_sample.html .. _`random`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.random.html .. _`ranf`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.ranf.html .. _`sample`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.sample.html .. _`choice`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.choice.html .. _`bytes`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.bytes.html .. _`beta`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.beta.html .. _`binomial`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.binomial.html .. _`chisquare`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.chisquare.html .. _`dirichlet`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.dirichlet.html .. _`exponential`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.exponential.html .. _`f`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.f.html .. _`gamma`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.gamma.html .. _`geometric`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.geometric.html .. _`gumbel`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.gumbel.html .. _`hypergeometric`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.hypergeometric.html .. _`laplace`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.laplace.html .. _`lognormal`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.lognormal.html .. _`logseries`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.logseries.html .. _`multinomial`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.multinomial.html .. _`multivariate_normal`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.multivariate_normal.html .. _`negative_binomial`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.negative_binomial.html .. _`noncentral_chisquare`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.noncentral_chisquare.html .. _`noncentral_f`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.noncentral_f.html .. _`normal`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.normal.html .. _`pareto`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.pareto.html .. _`poisson`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.poisson.html .. _`power`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.power.html .. _`rayleigh`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.rayleigh.html .. _`standard_cauchy`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.standard_cauchy.html .. _`standard_exponential`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.standard_exponential.html .. _`standard_gamma`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.standard_gamma.html .. _`standard_normal`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.standard_normal.html .. _`standard_t`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.standard_t.html .. _`triangular`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.triangular.html .. _`uniform`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.uniform.html .. _`vonmises`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.vonmises.html .. _`wald`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.wald.html .. _`weibull`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.weibull.html .. _`zipf`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.zipf.html .. _`seed`: https://numpy.org/doc/stable/reference/random/generated/numpy.random.seed.html .. _`RandomState`: https://numpy.org/doc/stable/reference/random/legacy.html#numpy.random.RandomState