Cython API for random

Typed versions of many of the Generator and BitGenerator methods as well as the classes themselves can be accessed directly from Cython via

cimport numpy.random

C API for random

Access to various distributions is available via Cython or C-wrapper libraries like CFFI. All the functions accept a bitgen_t as their first argument.

bitgen_t

The bitgen_t holds the current state of the BitGenerator and pointers to functions that return standard C types while advancing the state.

struct bitgen:
    void *state
    npy_uint64 (*next_uint64)(void *st) nogil
    uint32_t (*next_uint32)(void *st) nogil
    double (*next_double)(void *st) nogil
    npy_uint64 (*next_raw)(void *st) nogil

ctypedef bitgen bitgen_t

See Extending for examples of using these functions.

The functions are named with the following conventions:

• “standard” refers to the reference values for any parameters. For instance “standard_uniform” means a uniform distribution on the interval 0.0 to 1.0

• “fill” functions will fill the provided out with cnt values.

• The functions without “standard” in their name require additional parameters to describe the distributions.

• zig in the name are based on a ziggurat lookup algorithm is used instead of calculating the log, which is significantly faster. The non-ziggurat variants are used in corner cases and for legacy compatibility.

double random_standard_uniform(bitgen_t *bitgen_state)

void random_standard_uniform_fill(bitgen_t* bitgen_state, npy_intp cnt, double *out)

double random_standard_exponential(bitgen_t *bitgen_state)

void random_standard_exponential_fill(bitgen_t *bitgen_state, npy_intp cnt, double *out)

double random_standard_normal(bitgen_t* bitgen_state)

void random_standard_normal_fill(bitgen_t *bitgen_state, npy_intp count, double *out)

void random_standard_normal_fill_f(bitgen_t *bitgen_state, npy_intp count, float *out)

double random_standard_gamma(bitgen_t *bitgen_state, double shape)

float random_standard_uniform_f(bitgen_t *bitgen_state)

void random_standard_uniform_fill_f(bitgen_t* bitgen_state, npy_intp cnt, float *out)

float random_standard_exponential_f(bitgen_t *bitgen_state)

void random_standard_exponential_fill_f(bitgen_t *bitgen_state, npy_intp cnt, float *out)

float random_standard_normal_f(bitgen_t* bitgen_state)

float random_standard_gamma_f(bitgen_t *bitgen_state, float shape)

double random_normal(bitgen_t *bitgen_state, double loc, double scale)

double random_gamma(bitgen_t *bitgen_state, double shape, double scale)

float random_gamma_f(bitgen_t *bitgen_state, float shape, float scale)

double random_exponential(bitgen_t *bitgen_state, double scale)

double random_uniform(bitgen_t *bitgen_state, double lower, double range)

double random_beta(bitgen_t *bitgen_state, double a, double b)

double random_chisquare(bitgen_t *bitgen_state, double df)

double random_f(bitgen_t *bitgen_state, double dfnum, double dfden)

double random_standard_cauchy(bitgen_t *bitgen_state)

double random_pareto(bitgen_t *bitgen_state, double a)

double random_weibull(bitgen_t *bitgen_state, double a)

double random_power(bitgen_t *bitgen_state, double a)

double random_laplace(bitgen_t *bitgen_state, double loc, double scale)

double random_gumbel(bitgen_t *bitgen_state, double loc, double scale)

double random_logistic(bitgen_t *bitgen_state, double loc, double scale)

double random_lognormal(bitgen_t *bitgen_state, double mean, double sigma)

double random_rayleigh(bitgen_t *bitgen_state, double mode)

double random_standard_t(bitgen_t *bitgen_state, double df)

double random_noncentral_chisquare(bitgen_t *bitgen_state, double df, double nonc)

double random_noncentral_f(bitgen_t *bitgen_state, double dfnum, double dfden, double nonc)

double random_wald(bitgen_t *bitgen_state, double mean, double scale)

double random_vonmises(bitgen_t *bitgen_state, double mu, double kappa)

double random_triangular(bitgen_t *bitgen_state, double left, double mode, double right)

npy_int64 random_poisson(bitgen_t *bitgen_state, double lam)

npy_int64 random_negative_binomial(bitgen_t *bitgen_state, double n, double p)

binomial_t

typedef struct s_binomial_t {
  int has_binomial; /* !=0: following parameters initialized for binomial */
  double psave;
  RAND_INT_TYPE nsave;
  double r;
  double q;
  double fm;
  RAND_INT_TYPE m;
  double p1;
  double xm;
  double xl;
  double xr;
  double c;
  double laml;
  double lamr;
  double p2;
  double p3;
  double p4;
} binomial_t;

npy_int64 random_binomial(bitgen_t *bitgen_state, double p, npy_int64 n, binomial_t *binomial)

npy_int64 random_logseries(bitgen_t *bitgen_state, double p)

npy_int64 random_geometric_search(bitgen_t *bitgen_state, double p)

npy_int64 random_geometric_inversion(bitgen_t *bitgen_state, double p)

npy_int64 random_geometric(bitgen_t *bitgen_state, double p)

npy_int64 random_zipf(bitgen_t *bitgen_state, double a)

npy_int64 random_hypergeometric(bitgen_t *bitgen_state, npy_int64 good, npy_int64 bad, npy_int64 sample)

npy_uint64 random_interval(bitgen_t *bitgen_state, npy_uint64 max)

void random_multinomial(bitgen_t *bitgen_state, npy_int64 n, npy_int64 *mnix, double *pix, npy_intp d, binomial_t *binomial)

int random_multivariate_hypergeometric_count(bitgen_t *bitgen_state, npy_int64 total, size_t num_colors, npy_int64 *colors, npy_int64 nsample, size_t num_variates, npy_int64 *variates)

void random_multivariate_hypergeometric_marginals(bitgen_t *bitgen_state, npy_int64 total, size_t num_colors, npy_int64 *colors, npy_int64 nsample, size_t num_variates, npy_int64 *variates)

Generate a single integer

npy_int64 random_positive_int64(bitgen_t *bitgen_state)

npy_int32 random_positive_int32(bitgen_t *bitgen_state)

npy_int64 random_positive_int(bitgen_t *bitgen_state)

npy_uint64 random_uint(bitgen_t *bitgen_state)

Generate random uint64 numbers in closed interval [off, off + rng].

npy_uint64 random_bounded_uint64(bitgen_t *bitgen_state, npy_uint64 off, npy_uint64 rng, npy_uint64 mask, bint use_masked)