def test_DiscreteRV():
p = S(1) / 2
x = Symbol('x', integer=True, positive=True)
pdf = p * (1 - p)**(x - 1) # pdf of Geometric Distribution
D = DiscreteRV(x, pdf, set=S.Naturals)
assert E(D) == E(Geometric('G', S(1) / 2)) == 2
assert P(D > 3) == S(1) / 8
assert D.pspace.domain.set == S.Naturals
raises(ValueError, lambda: DiscreteRV(x, x, FiniteSet(*range(4))))
def test_DiscreteRV():
p = S(1)/2
x = Symbol('x', integer=True, positive=True)
pdf = p*(1 - p)**(x - 1) # pdf of Geometric Distribution
D = DiscreteRV(x, pdf, set=S.Naturals, check=True)
assert E(D) == E(Geometric('G', S(1)/2)) == 2
assert P(D > 3) == S(1)/8
assert D.pspace.domain.set == S.Naturals
raises(ValueError, lambda: DiscreteRV(x, x, FiniteSet(*range(4)), check=True))
# purposeful invalid pmf but it should not raise since check=False
# see test_drv_types.test_ContinuousRV for explanation
X = DiscreteRV(x, 1/x, S.Naturals)
assert P(X < 2) == 1
assert E(X) == oo
def test_sample_scipy():
p = S(2) / 3
x = Symbol('x', integer=True, positive=True)
pdf = p * (1 - p)**(x - 1) # pdf of Geometric Distribution
distribs_scipy = [
DiscreteRV(x, pdf, set=S.Naturals),
Geometric('G', 0.5),
Logarithmic('L', 0.5),
NegativeBinomial('N', 5, 0.4),
Poisson('P', 1),
Skellam('S', 1, 1),
YuleSimon('Y', 1),
Zeta('Z', 2)
]
size = 3
numsamples = 5
scipy = import_module('scipy')
if not scipy:
skip('Scipy is not installed. Abort tests for _sample_scipy.')
else:
with ignore_warnings(
UserWarning
): ### TODO: Restore tests once warnings are removed
z_sample = list(
sample(Zeta("G", 7), size=size, numsamples=numsamples))
assert len(z_sample) == numsamples
for X in distribs_scipy:
samps = next(sample(X, size=size, library='scipy'))
samps2 = next(sample(X, size=(2, 2), library='scipy'))
for sam in samps:
assert sam in X.pspace.domain.set
for i in range(2):
for j in range(2):
assert samps2[i][j] in X.pspace.domain.set