add some checks back and fix #1704

Author: rok-cesnovar

stan/math/prim/fun/acosh.hpp

@@ -19,8 +19,12 @@ namespace math {
  * @throw std::domain_error If argument is less than 1.
  */
 inline double acosh(double x) {
-  check_greater_or_equal("acosh", "x", x, 1.0);
-  return std::acosh(x);
+  if (is_nan(x)) {	  
+    return x;
+  } else {	
+    check_greater_or_equal("acosh", "x", x, 1.0);	
+    return std::acosh(x);	
+  }
 }
 
 /**

stan/math/prim/fun/atanh.hpp

@@ -20,8 +20,12 @@ namespace math {
  * @throw std::domain_error If argument is not in [-1, 1].
  */
 inline double atanh(double x) {
-  check_bounded("atanh", "x", x, -1.0, 1.0);
-  return std::atanh(x);
+  if (is_nan(x)) {
+    return x;
+  } else {	
+    check_bounded("atanh", "x", x, -1.0, 1.0);	
+    return std::atanh(x);	
+  }
 }
 
 /**

stan/math/prim/fun/exp.hpp

@@ -36,7 +36,7 @@ struct exp_fun {
  * @param[in] x container
  * @return Elementwise application of exponentiation to the argument.
  */
-template <typename T, typename = require_not_eigen_vt<std::is_arithmetic, T>>
+template <typename T, typename = require_not_eigen_vt<std::is_arithmetic, T>, typename = require_not_double_or_int_t<T>>
 inline auto exp(const T& x) {
   return apply_scalar_unary<exp_fun, T>::apply(x);
 }

stan/math/prim/fun/gp_matern32_cov.hpp

@@ -41,7 +41,6 @@ gp_matern32_cov(const std::vector<T_x> &x, const T_s &sigma,
                 const T_l &length_scale) {
   using std::exp;
   using std::pow;
-  using std::sqrt;
 
   size_t x_size = size(x);
   Eigen::Matrix<return_type_t<T_x, T_s, T_l>, Eigen::Dynamic, Eigen::Dynamic>
@@ -66,8 +65,8 @@ gp_matern32_cov(const std::vector<T_x> &x, const T_s &sigma,
   check_positive_finite(function, "length scale", length_scale);
 
   T_s sigma_sq = square(sigma);
-  T_l root_3_inv_l = sqrt(3.0) / length_scale;
-  T_l neg_root_3_inv_l = -1.0 * sqrt(3.0) / length_scale;
+  T_l root_3_inv_l = std::sqrt(3.0) / length_scale;
+  T_l neg_root_3_inv_l = -1.0 * std::sqrt(3.0) / length_scale;
 
   for (size_t i = 0; i < x_size; ++i) {
     cov(i, i) = sigma_sq;
@@ -130,8 +129,8 @@ gp_matern32_cov(const std::vector<Eigen::Matrix<T_x, -1, 1>> &x,
                    "number of length scales", l_size);
 
   T_s sigma_sq = square(sigma);
-  double root_3 = sqrt(3.0);
-  double neg_root_3 = -1.0 * sqrt(3.0);
+  double root_3 = std::sqrt(3.0);
+  double neg_root_3 = -1.0 * std::sqrt(3.0);
 
   std::vector<Eigen::Matrix<return_type_t<T_x, T_l>, -1, 1>> x_new
       = divide_columns(x, length_scale);
@@ -209,8 +208,8 @@ gp_matern32_cov(const std::vector<T_x1> &x1, const std::vector<T_x2> &x2,
   check_positive_finite(function, "length scale", length_scale);
 
   T_s sigma_sq = square(sigma);
-  T_l root_3_inv_l_sq = sqrt(3.0) / length_scale;
-  T_l neg_root_3_inv_l_sq = -1.0 * sqrt(3.0) / length_scale;
+  T_l root_3_inv_l_sq = std::sqrt(3.0) / length_scale;
+  T_l neg_root_3_inv_l_sq = -1.0 * std::sqrt(3.0) / length_scale;
 
   for (size_t i = 0; i < x1_size; ++i) {
     for (size_t j = 0; j < x2_size; ++j) {
@@ -290,8 +289,8 @@ gp_matern32_cov(const std::vector<Eigen::Matrix<T_x1, -1, 1>> &x1,
   }
 
   T_s sigma_sq = square(sigma);
-  double root_3 = sqrt(3.0);
-  double neg_root_3 = -1.0 * sqrt(3.0);
+  double root_3 = std::sqrt(3.0);
+  double neg_root_3 = -1.0 * std::sqrt(3.0);
 
   std::vector<Eigen::Matrix<return_type_t<T_x1, T_l>, -1, 1>> x1_new
       = divide_columns(x1, length_scale);

stan/math/prim/fun/gp_matern52_cov.hpp

@@ -59,9 +59,9 @@ gp_matern52_cov(const std::vector<T_x> &x, const T_s &sigma,
   check_positive_finite("gp_matern52_cov", "length scale", length_scale);
 
   T_s sigma_sq = square(sigma);
-  T_l root_5_inv_l = sqrt(5.0) / length_scale;
+  T_l root_5_inv_l = std::sqrt(5.0) / length_scale;
   T_l inv_l_sq_5_3 = 5.0 / (3.0 * square(length_scale));
-  T_l neg_root_5_inv_l = -sqrt(5.0) / length_scale;
+  T_l neg_root_5_inv_l = -std::sqrt(5.0) / length_scale;
 
   for (size_t i = 0; i < x_size; ++i) {
     cov(i, i) = sigma_sq;
@@ -125,7 +125,7 @@ gp_matern52_cov(const std::vector<Eigen::Matrix<T_x, Eigen::Dynamic, 1>> &x,
                    "number of length scales", l_size);
 
   T_s sigma_sq = square(sigma);
-  double root_5 = sqrt(5.0);
+  double root_5 = std::sqrt(5.0);
   double five_thirds = 5.0 / 3.0;
   double neg_root_5 = -root_5;
 
@@ -196,9 +196,9 @@ gp_matern52_cov(const std::vector<T_x1> &x1, const std::vector<T_x2> &x2,
   check_positive_finite("gp_matern52_cov", "length scale", length_scale);
 
   T_s sigma_sq = square(sigma);
-  T_l root_5_inv_l = sqrt(5.0) / length_scale;
+  T_l root_5_inv_l = std::sqrt(5.0) / length_scale;
   T_l inv_l_sq_5_3 = 5.0 / (3.0 * square(length_scale));
-  T_l neg_root_5_inv_l = -sqrt(5.0) / length_scale;
+  T_l neg_root_5_inv_l = -std::sqrt(5.0) / length_scale;
 
   for (size_t i = 0; i < x1_size; ++i) {
     for (size_t j = 0; j < x2_size; ++j) {
@@ -273,7 +273,7 @@ gp_matern52_cov(const std::vector<Eigen::Matrix<T_x1, Eigen::Dynamic, 1>> &x1,
                    "number of length scales", l_size);
 
   T_s sigma_sq = square(sigma);
-  double root_5 = sqrt(5.0);
+  double root_5 = std::sqrt(5.0);
   double five_thirds = 5.0 / 3.0;
   double neg_root_5 = -root_5;
 

stan/math/prim/fun/lbeta.hpp

@@ -12,6 +12,7 @@
 #include <stan/math/prim/fun/log_sum_exp.hpp>
 #include <stan/math/prim/fun/log1m.hpp>
 #include <stan/math/prim/fun/multiply_log.hpp>
+#include <cmath>
 
 namespace stan {
 namespace math {
@@ -64,6 +65,7 @@ namespace math {
  */
 template <typename T1, typename T2>
 return_type_t<T1, T2> lbeta(const T1 a, const T2 b) {
+  using std::log;
   using T_ret = return_type_t<T1, T2>;
 
   if (is_any_nan(a, b)) {

stan/math/prim/fun/lgamma_stirling.hpp

@@ -23,6 +23,7 @@ namespace math {
  */
 template <typename T>
 return_type_t<T> lgamma_stirling(const T x) {
+  using std::log;
   return HALF_LOG_TWO_PI + (x - 0.5) * log(x) - x;
 }
 

stan/math/prim/fun/log.hpp

@@ -36,7 +36,7 @@ struct log_fun {
  * @param[in] x container
  * @return Elementwise application of natural log to the argument.
  */
-template <typename T, typename = require_not_eigen_vt<std::is_arithmetic, T>>
+template <typename T, typename = require_not_eigen_vt<std::is_arithmetic, T>, typename = require_not_double_or_int_t<T>>
 inline auto log(const T& x) {
   return apply_scalar_unary<log_fun, T>::apply(x);
 }

stan/math/prim/fun/log1p.hpp

@@ -27,8 +27,12 @@ namespace math {
  * @throw std::domain_error If argument is less than -1.
  */
 inline double log1p(double x) {
-  check_greater_or_equal("log1p", "x", x, -1.0);
-  return std::log1p(x);
+  if (is_nan(x)) {
+    return x;
+  } else {
+    check_greater_or_equal("log1p", "x", x, -1.0);
+    return std::log1p(x);
+  }
 }
 
 /**

stan/math/prim/fun/sqrt.hpp

@@ -30,7 +30,7 @@ struct sqrt_fun {
  * @param x container
  * @return Square root of each value in x.
  */
-template <typename T, typename = require_not_eigen_vt<std::is_arithmetic, T>>
+template <typename T, typename = require_not_eigen_vt<std::is_arithmetic, T>, typename = require_not_double_or_int_t<T>>
 inline auto sqrt(const T& x) {
   return apply_scalar_unary<sqrt_fun, T>::apply(x);
 }