+ i RRt^RIHt^RIHt^RIHt^RIHtRRlt RRlt R #) z-Astroid hooks for numpy.random.mtrand module.)nodes)register_module_extenderparseAstroidManagerc8V^8dQhR\P/#)return)rModule)formats"I/usr/lib/python3/dist-packages/astroid/brain/brain_numpy_random_mtrand.py __annotate__rs4 4 u||4 c\R4#)a def beta(a, b, size=None): return uninferable def binomial(n, p, size=None): return uninferable def bytes(length): return uninferable def chisquare(df, size=None): return uninferable def choice(a, size=None, replace=True, p=None): return uninferable def dirichlet(alpha, size=None): return uninferable def exponential(scale=1.0, size=None): return uninferable def f(dfnum, dfden, size=None): return uninferable def gamma(shape, scale=1.0, size=None): return uninferable def geometric(p, size=None): return uninferable def get_state(): return uninferable def gumbel(loc=0.0, scale=1.0, size=None): return uninferable def hypergeometric(ngood, nbad, nsample, size=None): return uninferable def laplace(loc=0.0, scale=1.0, size=None): return uninferable def logistic(loc=0.0, scale=1.0, size=None): return uninferable def lognormal(mean=0.0, sigma=1.0, size=None): return uninferable def logseries(p, size=None): return uninferable def multinomial(n, pvals, size=None): return uninferable def multivariate_normal(mean, cov, size=None): return uninferable def negative_binomial(n, p, size=None): return uninferable def noncentral_chisquare(df, nonc, size=None): return uninferable def noncentral_f(dfnum, dfden, nonc, size=None): return uninferable def normal(loc=0.0, scale=1.0, size=None): return uninferable def pareto(a, size=None): return uninferable def permutation(x): return uninferable def poisson(lam=1.0, size=None): return uninferable def power(a, size=None): return uninferable def rand(*args): return uninferable def randint(low, high=None, size=None, dtype='l'): import numpy return numpy.ndarray((1,1)) def randn(*args): return uninferable def random(size=None): return uninferable def random_integers(low, high=None, size=None): return uninferable def random_sample(size=None): return uninferable def rayleigh(scale=1.0, size=None): return uninferable def seed(seed=None): return uninferable def set_state(state): return uninferable def shuffle(x): return uninferable def standard_cauchy(size=None): return uninferable def standard_exponential(size=None): return uninferable def standard_gamma(shape, size=None): return uninferable def standard_normal(size=None): return uninferable def standard_t(df, size=None): return uninferable def triangular(left, mode, right, size=None): return uninferable def uniform(low=0.0, high=1.0, size=None): return uninferable def vonmises(mu, kappa, size=None): return uninferable def wald(mean, scale, size=None): return uninferable def weibull(a, size=None): return uninferable def zipf(a, size=None): return uninferable rrr numpy_random_mtrand_transformrs 33 3 rc(V^8dQhR\RR/#)r managerr Nr)r s"r rrEsnrc(\VR\4R#)znumpy.random.mtrandN)rr)rs&r registerrEs&(ErN) __doc__astroidrastroid.brain.helpersrastroid.builderrastroid.managerrrrrrr rs! 4:!*4 nr