Add truncated normal distribution support (#3761)

tests/cpp_unit_tests/test_distribution.cpp

@@ -92,3 +92,103 @@ TEST_CASE("Test construction of SpatialBox with parameters")
   REQUIRE(box.upper_right() == openmc::Position {30, 15, 5});
   REQUIRE_FALSE(box.only_fissionable());
 }
+
+TEST_CASE("Test Normal distribution")
+{
+  // Test untruncated normal distribution
+  openmc::Normal normal_unbounded(0.0, 1.0);
+
+  // Check PDF at mean (should be 1/sqrt(2*pi) ≈ 0.3989)
+  REQUIRE_THAT(
+    normal_unbounded.evaluate(0.0), Catch::Matchers::WithinRel(0.3989, 0.001));
+
+  // Check that it's not truncated
+  REQUIRE_FALSE(normal_unbounded.is_truncated());
+
+  // Check accessors
+  REQUIRE(normal_unbounded.mean_value() == 0.0);
+  REQUIRE(normal_unbounded.std_dev() == 1.0);
+  REQUIRE(normal_unbounded.lower() == -openmc::INFTY);
+  REQUIRE(normal_unbounded.upper() == openmc::INFTY);
+}
+
+TEST_CASE("Test truncated Normal distribution")
+{
+  // Create a truncated normal: mean=0, std=1, bounds=[-1, 1]
+  openmc::Normal normal_truncated(0.0, 1.0, -1.0, 1.0);
+
+  // Check that it's truncated
+  REQUIRE(normal_truncated.is_truncated());
+
+  // Check accessors
+  REQUIRE(normal_truncated.lower() == -1.0);
+  REQUIRE(normal_truncated.upper() == 1.0);
+
+  // PDF should be zero outside bounds
+  REQUIRE(normal_truncated.evaluate(-2.0) == 0.0);
+  REQUIRE(normal_truncated.evaluate(2.0) == 0.0);
+
+  // PDF inside bounds should be higher than untruncated (due to
+  // renormalization)
+  openmc::Normal normal_unbounded(0.0, 1.0);
+  REQUIRE(normal_truncated.evaluate(0.0) > normal_unbounded.evaluate(0.0));
+
+  // The truncated PDF at mean should be approximately 0.3989 / 0.6827 ≈ 0.584
+  // (0.6827 is the probability mass of N(0,1) in [-1,1])
+  REQUIRE_THAT(
+    normal_truncated.evaluate(0.0), Catch::Matchers::WithinRel(0.584, 0.01));
+}
+
+TEST_CASE("Test truncated Normal sampling")
+{
+  constexpr int n_samples = 10000;
+  openmc::Normal normal_truncated(0.0, 1.0, -1.0, 1.0);
+  uint64_t seed = openmc::init_seed(0, 0);
+
+  // Sample and verify all samples are within bounds
+  for (int i = 0; i < n_samples; ++i) {
+    auto [x, w] = normal_truncated.sample(&seed);
+    REQUIRE(x >= -1.0);
+    REQUIRE(x <= 1.0);
+    REQUIRE(w == 1.0); // Unbiased sampling should have weight 1
+  }
+}
+
+TEST_CASE("Test one-sided truncated Normal")
+{
+  // Test lower-bounded only (positive half-normal)
+  openmc::Normal lower_bounded(0.0, 1.0, 0.0, openmc::INFTY);
+  REQUIRE(lower_bounded.is_truncated());
+  REQUIRE(lower_bounded.evaluate(-1.0) == 0.0);
+  REQUIRE(lower_bounded.evaluate(1.0) > 0.0);
+
+  // PDF at 0 should be approximately 2 * 0.3989 ≈ 0.798 (half-normal)
+  REQUIRE_THAT(
+    lower_bounded.evaluate(0.0), Catch::Matchers::WithinRel(0.798, 0.01));
+
+  // Test upper-bounded only
+  openmc::Normal upper_bounded(0.0, 1.0, -openmc::INFTY, 0.0);
+  REQUIRE(upper_bounded.is_truncated());
+  REQUIRE(upper_bounded.evaluate(1.0) == 0.0);
+  REQUIRE(upper_bounded.evaluate(-1.0) > 0.0);
+}
+
+TEST_CASE("Test Normal XML constructor with truncation")
+{
+  // XML doc node for truncated Normal
+  pugi::xml_document doc;
+  pugi::xml_node energy = doc.append_child("energy");
+  energy.append_child("type")
+    .append_child(pugi::node_pcdata)
+    .set_value("normal");
+  energy.append_child("parameters")
+    .append_child(pugi::node_pcdata)
+    .set_value("1.0e6 1.0e5 0.8e6 1.2e6");
+
+  openmc::Normal dist(energy);
+  REQUIRE(dist.mean_value() == 1.0e6);
+  REQUIRE(dist.std_dev() == 1.0e5);
+  REQUIRE(dist.lower() == 0.8e6);
+  REQUIRE(dist.upper() == 1.2e6);
+  REQUIRE(dist.is_truncated());
+}