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Cleanup unnecessary prim/fun signatures and checks (redundant as of C++11) #1702

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Cleanup unnecessary prim/fun signatures and checks (redundant as of C++11) #1702

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e9903fb
clean up unnecessary signatures and checks
rok-cesnovar Feb 12, 2020
6176aea
add some checks back and fix #1704
rok-cesnovar Feb 12, 2020
338185c
[Jenkins] auto-formatting by clang-format version 5.0.0-3~16.04.1 (ta…
stan-buildbot Feb 12, 2020
652bed1
cleanup gp_matern code if we are touching it anyways
rok-cesnovar Feb 12, 2020
97eb3c2
[Jenkins] auto-formatting by clang-format version 5.0.0-3~16.04.1 (ta…
stan-buildbot Feb 12, 2020
aa5f0ef
fix ambiguity
rok-cesnovar Feb 12, 2020
5e32563
[Jenkins] auto-formatting by clang-format version 5.0.0-3~16.04.1 (ta…
stan-buildbot Feb 12, 2020
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16 changes: 2 additions & 14 deletions stan/math/prim/fun/acosh.hpp
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Expand Up @@ -23,10 +23,6 @@ inline double acosh(double x) {
return x;
} else {
check_greater_or_equal("acosh", "x", x, 1.0);
#ifdef _WIN32
if (is_inf(x))
return x;
#endif
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This worked fine on my Windows box, but will let Jenkins give the final verdict. Will just revert back if Jenkins flags this.

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Is this what made the test fail on Jenkins?

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Yep, will remove once I update the PR. Was hoping it could go away :)

return std::acosh(x);
}
}
Expand All @@ -39,16 +35,8 @@ inline double acosh(double x) {
* @throw std::domain_error If argument is less than 1.
*/
inline double acosh(int x) {
if (is_nan(x)) {
return x;
} else {
check_greater_or_equal("acosh", "x", x, 1);
#ifdef _WIN32
if (is_inf(x))
return x;
#endif
return std::acosh(x);
}
check_greater_or_equal("acosh", "x", x, 1);
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I think is_nan for integer inputs is redundant, isnt it?

return std::acosh(x);
}

/**
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20 changes: 1 addition & 19 deletions stan/math/prim/fun/asinh.hpp
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Expand Up @@ -7,25 +7,6 @@
namespace stan {
namespace math {

/**
* Return the inverse hyperbolic sine of the specified value.
* Returns infinity for infinity argument and -infinity for
* -infinity argument.
* Returns nan for nan argument.
*
* @param[in] x Argument.
* @return Inverse hyperbolic sine of the argument.
*/
inline double asinh(double x) { return std::asinh(x); }

/**
* Integer version of asinh.
*
* @param[in] x Argument.
* @return Inverse hyperbolic sine of the argument.
*/
inline double asinh(int x) { return std::asinh(x); }

/**
* Structure to wrap asinh() so it can be vectorized.
*
Expand All @@ -36,6 +17,7 @@ inline double asinh(int x) { return std::asinh(x); }
struct asinh_fun {
template <typename T>
static inline T fun(const T& x) {
using std::asinh;
return asinh(x);
}
};
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8 changes: 2 additions & 6 deletions stan/math/prim/fun/atanh.hpp
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Expand Up @@ -36,12 +36,8 @@ inline double atanh(double x) {
* @throw std::domain_error If argument is less than 1.
*/
inline double atanh(int x) {
if (is_nan(x)) {
return x;
} else {
check_bounded("atanh", "x", x, -1, 1);
return std::atanh(x);
}
check_bounded("atanh", "x", x, -1, 1);
return std::atanh(x);
}

/**
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19 changes: 1 addition & 18 deletions stan/math/prim/fun/cbrt.hpp
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Expand Up @@ -7,24 +7,6 @@
namespace stan {
namespace math {

/**
* Return the cube root of the specified value
*
* @param[in] x Argument.
* @return Cube root of the argument.
* @throw std::domain_error If argument is negative.
*/
inline double cbrt(double x) { return std::cbrt(x); }

/**
* Integer version of cbrt.
*
* @param[in] x Argument.
* @return Cube root of the argument.
* @throw std::domain_error If argument is less than 1.
*/
inline double cbrt(int x) { return std::cbrt(x); }

/**
* Structure to wrap cbrt() so it can be vectorized.
*
Expand All @@ -35,6 +17,7 @@ inline double cbrt(int x) { return std::cbrt(x); }
struct cbrt_fun {
template <typename T>
static inline T fun(const T& x) {
using std::cbrt;
return cbrt(x);
}
};
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22 changes: 1 addition & 21 deletions stan/math/prim/fun/erf.hpp
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Expand Up @@ -7,27 +7,6 @@
namespace stan {
namespace math {

/**
* Return the error function of the specified value.
*
* \f[
* \mbox{erf}(x) = \frac{2}{\sqrt{\pi}} \int_0^x e^{-t^2} dt
* \f]
*
* @param[in] x Argument.
* @return Error function of the argument.
*/
inline double erf(double x) { return std::erf(x); }

/**
* Return the error function of the specified argument. This
* version is required to disambiguate <code>erf(int)</code>.
*
* @param[in] x Argument.
* @return Error function of the argument.
*/
inline double erf(int x) { return std::erf(x); }

/**
* Structure to wrap erf() so it can be vectorized.
*
Expand All @@ -38,6 +17,7 @@ inline double erf(int x) { return std::erf(x); }
struct erf_fun {
template <typename T>
static inline T fun(const T& x) {
using std::erf;
return erf(x);
}
};
Expand Down
22 changes: 1 addition & 21 deletions stan/math/prim/fun/erfc.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -7,27 +7,6 @@
namespace stan {
namespace math {

/**
* Return the complementary error function of the specified value.
*
* \f[
* \mbox{erfc}(x) = 1 - \frac{2}{\sqrt{\pi}} \int_0^x e^{-t^2} dt
* \f]
*
* @param[in] x Argument.
* @return Complementary error function of the argument.
*/
inline double erfc(double x) { return std::erfc(x); }

/**
* Return the error function of the specified argument. This
* version is required to disambiguate <code>erfc(int)</code>.
*
* @param[in] x Argument.
* @return Complementary error function value of the argument.
*/
inline double erfc(int x) { return std::erfc(x); }

/**
* Structure to wrap erfc() so that it can be vectorized.
*
Expand All @@ -38,6 +17,7 @@ inline double erfc(int x) { return std::erfc(x); }
struct erfc_fun {
template <typename T>
static inline T fun(const T& x) {
using std::erfc;
return erfc(x);
}
};
Expand Down
9 changes: 0 additions & 9 deletions stan/math/prim/fun/exp.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -8,15 +8,6 @@
namespace stan {
namespace math {

/**
* Return the natural exponential of the specified argument. This
* version is required to disambiguate <code>exp(int)</code>.
*
* @param[in] x Argument.
* @return Natural exponential of argument.
*/
inline double exp(int x) { return std::exp(x); }

/**
* Structure to wrap <code>exp()</code> so that it can be
* vectorized.
Expand Down
19 changes: 1 addition & 18 deletions stan/math/prim/fun/expm1.hpp
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Expand Up @@ -7,24 +7,6 @@
namespace stan {
namespace math {

/**
* Return the natural exponentiation of x minus one.
* Returns infinity for infinity argument and -infinity for
* -infinity argument.
*
* @param[in] x Argument.
* @return Natural exponentiation of argument minus one.
*/
inline double expm1(double x) { return std::expm1(x); }

/**
* Integer version of expm1.
*
* @param[in] x Argument.
* @return Natural exponentiation of argument minus one.
*/
inline double expm1(int x) { return std::expm1(x); }

/**
* Structure to wrap expm1() so that it can be vectorized.
*
Expand All @@ -35,6 +17,7 @@ inline double expm1(int x) { return std::expm1(x); }
struct expm1_fun {
template <typename T>
static inline T fun(const T& x) {
using std::expm1;
return expm1(x);
}
};
Expand Down
23 changes: 9 additions & 14 deletions stan/math/prim/fun/gp_matern32_cov.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -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>
Expand All @@ -66,15 +65,14 @@ 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;

for (size_t i = 0; i < x_size; ++i) {
cov(i, i) = sigma_sq;
for (size_t j = i + 1; j < x_size; ++j) {
return_type_t<T_x> dist = distance(x[i], x[j]);
cov(i, j) = sigma_sq * (1.0 + root_3_inv_l * dist)
* exp(neg_root_3_inv_l * dist);
cov(i, j)
= sigma_sq * (1.0 + root_3_inv_l * dist) * exp(-root_3_inv_l * dist);
cov(j, i) = cov(i, j);
}
}
Expand Down Expand Up @@ -130,16 +128,15 @@ 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);

std::vector<Eigen::Matrix<return_type_t<T_x, T_l>, -1, 1>> x_new
= divide_columns(x, length_scale);

for (size_t i = 0; i < x_size; ++i) {
for (size_t j = i; j < x_size; ++j) {
return_type_t<T_x, T_l> dist = distance(x_new[i], x_new[j]);
cov(i, j) = sigma_sq * (1.0 + root_3 * dist) * exp(neg_root_3 * dist);
cov(i, j) = sigma_sq * (1.0 + root_3 * dist) * exp(-root_3 * dist);
cov(j, i) = cov(i, j);
}
}
Expand Down Expand Up @@ -209,14 +206,13 @@ 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;

for (size_t i = 0; i < x1_size; ++i) {
for (size_t j = 0; j < x2_size; ++j) {
return_type_t<T_x1, T_x2> dist = distance(x1[i], x2[j]);
cov(i, j) = sigma_sq * (1.0 + root_3_inv_l_sq * dist)
* exp(neg_root_3_inv_l_sq * dist);
* exp(-root_3_inv_l_sq * dist);
}
}
return cov;
Expand Down Expand Up @@ -290,8 +286,7 @@ 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);

std::vector<Eigen::Matrix<return_type_t<T_x1, T_l>, -1, 1>> x1_new
= divide_columns(x1, length_scale);
Expand All @@ -301,7 +296,7 @@ gp_matern32_cov(const std::vector<Eigen::Matrix<T_x1, -1, 1>> &x1,
for (size_t i = 0; i < x1_size; ++i) {
for (size_t j = 0; j < x2_size; ++j) {
return_type_t<T_x1, T_x2, T_l> dist = distance(x1_new[i], x2_new[j]);
cov(i, j) = sigma_sq * (1.0 + root_3 * dist) * exp(neg_root_3 * dist);
cov(i, j) = sigma_sq * (1.0 + root_3 * dist) * exp(-root_3 * dist);
}
}
return cov;
Expand Down
19 changes: 8 additions & 11 deletions stan/math/prim/fun/gp_matern52_cov.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -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;
Expand Down Expand Up @@ -125,9 +125,8 @@ 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;

std::vector<Eigen::Matrix<return_type_t<T_x, T_l>, -1, 1>> x_new
= divide_columns(x, length_scale);
Expand All @@ -139,7 +138,7 @@ gp_matern52_cov(const std::vector<Eigen::Matrix<T_x, Eigen::Dynamic, 1>> &x,
= squared_distance(x_new[i], x_new[j]);
return_type_t<T_x, T_l> dist = sqrt(sq_distance);
cov(i, j) = sigma_sq * (1.0 + root_5 * dist + five_thirds * sq_distance)
* exp(neg_root_5 * dist);
* exp(-root_5 * dist);
cov(j, i) = cov(i, j);
}
}
Expand Down Expand Up @@ -196,17 +195,16 @@ 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;

for (size_t i = 0; i < x1_size; ++i) {
for (size_t j = 0; j < x2_size; ++j) {
return_type_t<T_x1, T_x2> sq_distance = squared_distance(x1[i], x2[j]);
return_type_t<T_x1, T_x2> dist = sqrt(sq_distance);
cov(i, j) = sigma_sq
* (1.0 + root_5_inv_l * dist + inv_l_sq_5_3 * sq_distance)
* exp(neg_root_5_inv_l * dist);
* exp(-root_5_inv_l * dist);
}
}
return cov;
Expand Down Expand Up @@ -273,9 +271,8 @@ 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;

std::vector<Eigen::Matrix<return_type_t<T_x1, T_l>, -1, 1>> x1_new
= divide_columns(x1, length_scale);
Expand All @@ -288,7 +285,7 @@ gp_matern52_cov(const std::vector<Eigen::Matrix<T_x1, Eigen::Dynamic, 1>> &x1,
= squared_distance(x1_new[i], x2_new[j]);
return_type_t<T_x1, T_x2, T_l> dist = sqrt(sq_distance);
cov(i, j) = sigma_sq * (1.0 + root_5 * dist + five_thirds * sq_distance)
* exp(neg_root_5 * dist);
* exp(-root_5 * dist);
}
}
return cov;
Expand Down
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