Merge pull request #3140 from stan-dev/std_normal-vec

Simplify vectorisation of std_normal_lpdf

Author: andrjohns

stan/math/prim/fun/dot_self.hpp

@@ -10,6 +10,11 @@
 namespace stan {
 namespace math {
 
+template <typename T, require_stan_scalar_t<T>* = nullptr>
+inline T dot_self(const T& x) {
+  return x * x;
+}
+
 inline double dot_self(const std::vector<double>& x) {
   double sum = 0.0;
   for (double i : x) {

stan/math/prim/prob/std_normal_lpdf.hpp

@@ -4,10 +4,10 @@
 #include <stan/math/prim/meta.hpp>
 #include <stan/math/prim/err.hpp>
 #include <stan/math/prim/fun/constants.hpp>
-#include <stan/math/prim/fun/scalar_seq_view.hpp>
 #include <stan/math/prim/fun/size.hpp>
 #include <stan/math/prim/fun/size_zero.hpp>
-#include <stan/math/prim/fun/value_of.hpp>
+#include <stan/math/prim/fun/dot_self.hpp>
+#include <stan/math/prim/fun/as_value_column_vector_or_scalar.hpp>
 #include <stan/math/prim/functor/partials_propagator.hpp>
 
 namespace stan {
@@ -43,22 +43,16 @@ return_type_t<T_y> std_normal_lpdf(const T_y& y) {
     return 0.0;
   }
 
-  T_partials_return logp(0.0);
+  const auto& y_val = as_value_column_vector_or_scalar(y_ref);
+  T_partials_return logp = -dot_self(y_val) / 2.0;
   auto ops_partials = make_partials_propagator(y_ref);
 
-  scalar_seq_view<T_y_ref> y_vec(y_ref);
-  size_t N = stan::math::size(y);
-
-  for (size_t n = 0; n < N; n++) {
-    const T_partials_return y_val = y_vec.val(n);
-    logp += y_val * y_val;
-    if (!is_constant_all<T_y>::value) {
-      partials<0>(ops_partials)[n] -= y_val;
-    }
+  if (!is_constant_all<T_y>::value) {
+    partials<0>(ops_partials) = -y_val;
   }
-  logp *= -0.5;
+
   if (include_summand<propto>::value) {
-    logp += NEG_LOG_SQRT_TWO_PI * N;
+    logp += NEG_LOG_SQRT_TWO_PI * math::size(y);
   }
 
   return ops_partials.build(logp);

test/unit/math/mix/prob/std_normal_test.cpp

@@ -7,4 +7,12 @@ TEST_F(AgradRev, mathMixScalFun_std_normal) {
   stan::test::expect_ad(f, -0.3);
   stan::test::expect_ad(f, 0.0);
   stan::test::expect_ad(f, 1.7);
+
+  Eigen::VectorXd x(3);
+  x << -0.3, 0.0, 1.7;
+  std::vector<double> x2{0.0, 1.7};
+
+  stan::test::expect_ad(f, x);
+  stan::test::expect_ad(f, x.transpose().eval());
+  stan::test::expect_ad(f, x2);
 }