seed([seed])
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split_key()
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default_rng([seed_or_key, clone])
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- rtype
RandomState
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rand(*dn[, key])
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randint(low[, high, size, dtype, key])
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random_integers(low[, high, size, key])
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randn(*dn[, key])
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random([size, key])
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random_sample([size, key])
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ranf([size, key])
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sample([size, key])
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choice(a[, size, replace, p, key])
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permutation(x[, axis, independent, key])
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shuffle(x[, axis, key])
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beta(a, b[, size, key])
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exponential([scale, size, key])
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gamma(shape[, scale, size, key])
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gumbel([loc, scale, size, key])
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laplace([loc, scale, size, key])
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logistic([loc, scale, size, key])
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normal([loc, scale, size, key])
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pareto(a[, size, key])
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poisson([lam, size, key])
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standard_cauchy([size, key])
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standard_exponential([size, key])
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standard_gamma(shape[, size, key])
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standard_normal([size, key])
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standard_t(df[, size, key])
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uniform([low, high, size, key])
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truncated_normal(lower, upper[, size, ...])
|
Sample truncated standard normal random values with given shape and dtype. |
bernoulli([p, size, key])
|
Sample Bernoulli random values with given shape and mean. |
lognormal([mean, sigma, size, key])
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binomial(n, p[, size, key])
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chisquare(df[, size, key])
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dirichlet(alpha[, size, key])
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geometric(p[, size, key])
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f(dfnum, dfden[, size, key])
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hypergeometric(ngood, nbad, nsample[, size, key])
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logseries(p[, size, key])
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multinomial(n, pvals[, size, key])
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multivariate_normal(mean, cov[, size, ...])
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negative_binomial(n, p[, size, key])
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noncentral_chisquare(df, nonc[, size, key])
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noncentral_f(dfnum, dfden, nonc[, size, key])
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power(a[, size, key])
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rayleigh([scale, size, key])
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triangular([size, key])
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vonmises(mu, kappa[, size, key])
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wald(mean, scale[, size, key])
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weibull(a[, size, key])
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weibull_min(a[, scale, size, key])
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zipf(a[, size, key])
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maxwell([size, key])
|
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t(df[, size, key])
|
Sample Student’s t random values. |
orthogonal(n[, size, key])
|
Sample uniformly from the orthogonal group O(n). |
loggamma(a[, size, key])
|
Sample log-gamma random values. |
categorical(logits[, axis, size, key])
|
|
RandomState([seed_or_key, seed])
|
RandomState that track the random generator state. |
Generator
|
alias of brainpy._src.math.random.RandomState |
DEFAULT
|
RandomState that track the random generator state. |
