def testT(self, df, dtype):
key = random.PRNGKey(0)
rand = lambda key, df: random.t(key, df, (10000, ), dtype)
crand = api.jit(rand)
uncompiled_samples = rand(key, df)
compiled_samples = crand(key, df)
for samples in [uncompiled_samples, compiled_samples]:
self._CheckKolmogorovSmirnovCDF(samples, scipy.stats.t(df).cdf)
def standard_t(df, size=None):
return JaxArray(jr.t(DEFAULT.split_key(), df=df, shape=_size2shape(size)))
def sample(self, rng_key, sample_shape=()):
shape = sample_shape + self.batch_shape + self.event_shape
return random.t(rng_key, self.df, shape)
