def check_uniform(low, high):
rng = check_random_state(1)
p_carl = Uniform(low=low, high=high)
p_scipy = st.uniform(loc=low, scale=high - low)
X = 3 * rng.rand(50, 1) - 1
assert_array_almost_equal(p_carl.pdf(X),
p_scipy.pdf(X.ravel()))
assert_array_almost_equal(p_carl.cdf(X),
p_scipy.cdf(X.ravel()))
assert_array_almost_equal(-np.log(p_carl.pdf(X)),
p_carl.nnlf(X))
def test_rvs():
p = Uniform(low=-10, high=10, random_state=0)
samples = p.rvs(100)
assert_equal(samples.shape, (100, 1))
assert np.all(samples < 10)
assert np.all(samples > -10)
q = Uniform(low=-10, high=10, random_state=0)
samples2 = q.rvs(100)
assert_array_equal(samples, samples2)
q = Uniform(low=-10, high=10, random_state=1)
samples2 = q.rvs(100)
assert np.all(samples != samples2)
def check_uniform(low, high):
rng = check_random_state(1)
p_carl = Uniform(low=low, high=high)
p_scipy = st.uniform(loc=low, scale=high - low)
X = 3 * rng.rand(50, 1) - 1
assert_array_almost_equal(p_carl.pdf(X), p_scipy.pdf(X.ravel()))
assert_array_almost_equal(p_carl.cdf(X), p_scipy.cdf(X.ravel()))
assert_array_almost_equal(-np.log(p_carl.pdf(X)), p_carl.nnlf(X))
def test_rvs():
p = Uniform(low=-10, high=10, random_state=0)
samples = p.rvs(100)
assert_equal(samples.shape, (100, 1))
assert np.all(samples < 10)
assert np.all(samples > -10)
q = Uniform(low=-10, high=10, random_state=0)
samples2 = q.rvs(100)
assert_array_equal(samples, samples2)
q = Uniform(low=-10, high=10, random_state=1)
samples2 = q.rvs(100)
assert np.all(samples != samples2)
