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Implement functions from np.random #46

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Implement functions from np.random #46

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a5cc202
add numpy.random.rand
prasunanand Feb 19, 2020
754e810
add more functions from Random module
prasunanand Feb 20, 2020
6c0068b
Lint and adding random functions
prasunanand Feb 28, 2020
ed9e827
add to __ua_function__
prasunanand Mar 3, 2020
92d3f50
Few tests passing: Import error fixed
prasunanand Mar 4, 2020
97bdc75
More tests passing
prasunanand Mar 5, 2020
36af3ec
All tests pass
prasunanand Mar 7, 2020
f24e867
Dask backend tests pass now
prasunanand Mar 11, 2020
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178 changes: 89 additions & 89 deletions unumpy/random/_multimethods.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,50 +27,50 @@ def randn(*tup):

@create_numpy(_dtype_argreplacer)
@all_of_type(ndarray)
def randint(low, high=None, size=None, dtype="l"):
def randint(low, high=None, size=None, dtype=None):
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return mark_dtype(dtype)


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def random_integers(low, high=None, size=None):
return low
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def random_sample(size=None):
return size
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def random(size=None):
return size
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def ranf(size=None):
return size
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def sample(size=None):
return size
return ()


@create_numpy(_self_argreplacer)
@all_of_type(ndarray)
def choice(a, size=None, replace=True, p=None):
return (a, size, replace, p)
return (a,)


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def bytes(length):
return length
return ()


@create_numpy(_self_argreplacer)
Expand All @@ -79,22 +79,22 @@ def shuffle(x):
return x


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def permutation(x):
return x


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def beta(a, b, size=None):
return (a, b, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def binomial(n, p, size=None):
return (n, p, size)
return ()


@create_numpy(_identity_argreplacer)
Expand All @@ -103,215 +103,215 @@ def chisquare(df, size=None):
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def dirichlet(alpha, size=None):
return (alpha, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def exponential(scale, size=None):
return (scale, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def f(dfnum, dfden, size=None):
return (dfnum, dfden, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def gamma(shape, scale=1.0, size=None):
return (shape, scale, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def geometric(p, size=None):
return (p, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def gumbel(loc=0.0, scale=1.0, size=None):
return (loc, scale, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def hypergeometric(ngood, nbad, nsample, size=None):
return (ngood, nbad, nsample, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def laplace(loc=0.0, scale=1.0, size=None):
return (loc, scale, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def logistic(loc=0.0, scale=1.0, size=None):
return (loc, scale, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def lognormal(mean=0.0, sigma=1.0, size=None):
return (mean, sigma, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def logseries(p, size=None):
return (p, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def multinomial(n, pvals, size=None):
return (n, pvals, size)
return ()


# check
@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def multivariate_normal(mean, cov, size=None, check_valid=None, tol=None):
return (mean, cov, size, check_valid, tol)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def negative_binomial(n, p, size=None):
return (n, p, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def noncentral_chisquare(df, nonc, size=None):
return (df, nonc, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def noncentral_f(dfnum, dfden, nonc, size=None):
return (dfnum, dfden, nonc, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def normal(loc=0.0, scale=1.0, size=None):
return (loc, scale, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def pareto(a, size=None):
return (a, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def poisson(lam=1.0, size=None):
return (lam, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def power(a, size=None):
return (a, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def rayleigh(scale=1.0, size=None):
return (scale, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def standard_cauchy(size=None):
return size
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def standard_exponential(size=None):
return size
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def standard_gamma(shape, size=None):
return (shape, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def standard_normal(size=None):
return size
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def standard_t(df, size=None):
return (df, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def triangular(left, mode, right, size=None):
return (left, mode, right, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def uniform(low=0.0, high=1.0, size=None):
return (low, high, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def vonmises(mu, kappa, size=None):
return (mu, kappa, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def wald(mean, scale, size=None):
return (mean, scale, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def weibull(a, size=None):
return (a, size)
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def zipf(a, size=None):
return (a, size)
return ()


# discuss: RandomState


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def seed(seed=None):
return seed
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def get_state():
return
return ()


@create_numpy(_self_argreplacer)
@create_numpy(_identity_argreplacer)
@all_of_type(ndarray)
def set_state(state):
return state
return ()