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# C API for random

Access to various distributions below is available via Cython or C-wrapper libraries like CFFI. All the functions accept a `bitgen_t` as their first argument. To access these from Cython or C, you must link with the `npyrandom` static library which is part of the NumPy distribution, located in `numpy/random/lib`. Note that you must also link with `npymath`, see Linking against the core math library in an extension.

type 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.

- Functions with `inv` in their name are based on the slower inverse method instead of a ziggurat lookup algorithm, 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)

void random_standard_exponential_inv_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)

void random_standard_exponential_inv_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)

type 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, bool use_masked)