Add Uniform

distributions/uniform.py

@@ -0,0 +1,84 @@
+import pytensor.tensor as pt
+
+from distributions.helper import ppf_bounds_cont
+
+
+def mean(lower, upper):
+    return (upper + lower) / 2
+
+
+def mode(lower, upper):
+    shape = pt.broadcast_arrays(lower, upper)[0]
+    return pt.full_like(shape, pt.nan)
+
+
+def median(lower, upper):
+    return mean(lower, upper)
+
+
+def var(lower, upper):
+    return (upper - lower) ** 2 / 12
+
+
+def std(lower, upper):
+    return pt.sqrt(var(lower, upper))
+
+
+def skewness(lower, upper):
+    shape = pt.broadcast_arrays(lower, upper)[0]
+    return pt.zeros_like(shape)
+
+
+def kurtosis(lower, upper):
+    shape = pt.broadcast_arrays(lower, upper)[0]
+    return pt.full_like(shape, -6 / 5)
+
+
+def entropy(lower, upper):
+    return pt.log(upper - lower)
+
+
+def cdf(x, lower, upper):
+    return pt.switch(
+        pt.lt(x, lower),
+        pt.zeros_like(x),
+        pt.switch(pt.gt(x, upper), pt.ones_like(x), (x - lower) / (upper - lower)),
+    )
+
+
+def pdf(x, lower, upper):
+    return pt.exp(logpdf(x, lower, upper))
+
+
+def ppf(q, lower, upper):
+    x_vals = lower + q * (upper - lower)
+    return ppf_bounds_cont(x_vals, q, lower, upper)
+
+
+def sf(x, lower, upper):
+    return 1 - cdf(x, lower, upper)
+
+
+def isf(x, lower, upper):
+    return ppf(1 - x, lower, upper)
+
+
+def rvs(lower, upper, size=None, random_state=None):
+    return pt.random.uniform(lower, upper, size=size, rng=random_state)
+
+
+def logcdf(x, lower, upper):
+    return pt.switch(
+        pt.lt(x, lower),
+        -pt.inf,
+        pt.switch(pt.gt(x, upper), 0, pt.log((x - lower) / (upper - lower))),
+    )
+
+
+def logpdf(x, lower, upper):
+    log_height = -pt.log(upper - lower)
+    return pt.switch(pt.or_(pt.lt(x, lower), pt.gt(x, upper)), -pt.inf, log_height)
+
+
+def logsf(x, lower, upper):
+    return pt.log(sf(x, lower, upper))

tests/test_uniform.py

@@ -0,0 +1,32 @@
+"""Test Uniform distribution against scipy implementation."""
+
+import pytest
+from scipy import stats
+
+from distributions import uniform as Uniform
+from tests.helper_scipy import make_params, run_distribution_tests
+
+
+@pytest.mark.parametrize(
+    "params, sp_params",
+    [
+        ([0.0, 1.0], {"loc": 0.0, "scale": 1.0}),
+        ([-5.0, 5.0], {"loc": -5.0, "scale": 10.0}),
+        ([10.0, 20.0], {"loc": 10.0, "scale": 10.0}),
+        ([-100.0, -50.0], {"loc": -100.0, "scale": 50.0}),
+        ([0.0, 1e-6], {"loc": 0.0, "scale": 1e-6}),
+    ],
+)
+def test_uniform_vs_scipy(params, sp_params):
+    """Test Uniform distribution against scipy."""
+    p_params = make_params(*params)
+    support = (params[0], params[1])
+
+    run_distribution_tests(
+        p_dist=Uniform,
+        sp_dist=stats.uniform,
+        p_params=p_params,
+        sp_params=sp_params,
+        support=support,
+        name="uniform",
+    )