fix cdf normalization

Author: dweindl

petab/v1/distributions.py

@@ -64,7 +64,7 @@ def __init__(
                 self._cd_high = self._cdf_transformed_untruncated(
                     self.trunc_high
                 )
-                # normalization factor for the PDF of the transformed
+                # normalization factor for the PDF/CDF of the transformed
                 #  distribution to account for truncation
                 self._truncation_normalizer = 1 / (
                     self._cd_high - self._cd_low
@@ -172,7 +172,11 @@ def cdf(self, x):
         :param x: The value at which to evaluate the CDF.
         :return: The value of the CDF at ``x``.
         """
-        return self._cdf_transformed_untruncated(x) - self._cd_low
+        if self._trunc is None:
+            return self._cdf_transformed_untruncated(x)
+        return (
+            self._cdf_transformed_untruncated(x) - self._cd_low
+        ) * self._truncation_normalizer
 
     def _cdf_transformed_untruncated(self, x):
         """Cumulative distribution function of the transformed, but untruncated

tests/v1/test_distributions.py

@@ -1,3 +1,5 @@
+import sys
+
 import numpy as np
 import pytest
 from numpy.testing import assert_allclose
@@ -56,6 +58,21 @@ def cdf(x):
 
     assert p > 0.05, (p, distribution)
 
+    # check min/max of CDF at the bounds
+    assert np.isclose(
+        distribution.cdf(
+            distribution.trunc_low
+            if not distribution.logbase
+            else max(sys.float_info.min, distribution.trunc_low)
+        ),
+        0,
+        atol=1e-16,
+        rtol=0,
+    )
+    assert np.isclose(
+        distribution.cdf(distribution.trunc_high), 1, atol=1e-14, rtol=0
+    )
+
     # Test samples match scipy CDFs
     reference_pdf = None
     if distribution._trunc is None and distribution.logbase is False: