
(FPCore (l Om kx ky)
:precision binary64
(sqrt
(*
(/ 1.0 2.0)
(+
1.0
(/
1.0
(sqrt
(+
1.0
(*
(pow (/ (* 2.0 l) Om) 2.0)
(+ (pow (sin kx) 2.0) (pow (sin ky) 2.0))))))))))
double code(double l, double Om, double kx, double ky) {
return sqrt(((1.0 / 2.0) * (1.0 + (1.0 / sqrt((1.0 + (pow(((2.0 * l) / Om), 2.0) * (pow(sin(kx), 2.0) + pow(sin(ky), 2.0)))))))));
}
real(8) function code(l, om, kx, ky)
real(8), intent (in) :: l
real(8), intent (in) :: om
real(8), intent (in) :: kx
real(8), intent (in) :: ky
code = sqrt(((1.0d0 / 2.0d0) * (1.0d0 + (1.0d0 / sqrt((1.0d0 + ((((2.0d0 * l) / om) ** 2.0d0) * ((sin(kx) ** 2.0d0) + (sin(ky) ** 2.0d0)))))))))
end function
public static double code(double l, double Om, double kx, double ky) {
return Math.sqrt(((1.0 / 2.0) * (1.0 + (1.0 / Math.sqrt((1.0 + (Math.pow(((2.0 * l) / Om), 2.0) * (Math.pow(Math.sin(kx), 2.0) + Math.pow(Math.sin(ky), 2.0)))))))));
}
def code(l, Om, kx, ky): return math.sqrt(((1.0 / 2.0) * (1.0 + (1.0 / math.sqrt((1.0 + (math.pow(((2.0 * l) / Om), 2.0) * (math.pow(math.sin(kx), 2.0) + math.pow(math.sin(ky), 2.0)))))))))
function code(l, Om, kx, ky) return sqrt(Float64(Float64(1.0 / 2.0) * Float64(1.0 + Float64(1.0 / sqrt(Float64(1.0 + Float64((Float64(Float64(2.0 * l) / Om) ^ 2.0) * Float64((sin(kx) ^ 2.0) + (sin(ky) ^ 2.0))))))))) end
function tmp = code(l, Om, kx, ky) tmp = sqrt(((1.0 / 2.0) * (1.0 + (1.0 / sqrt((1.0 + ((((2.0 * l) / Om) ^ 2.0) * ((sin(kx) ^ 2.0) + (sin(ky) ^ 2.0))))))))); end
code[l_, Om_, kx_, ky_] := N[Sqrt[N[(N[(1.0 / 2.0), $MachinePrecision] * N[(1.0 + N[(1.0 / N[Sqrt[N[(1.0 + N[(N[Power[N[(N[(2.0 * l), $MachinePrecision] / Om), $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Power[N[Sin[kx], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[ky], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{2} \cdot \left(1 + \frac{1}{\sqrt{1 + {\left(\frac{2 \cdot \ell}{Om}\right)}^{2} \cdot \left({\sin kx}^{2} + {\sin ky}^{2}\right)}}\right)}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 5 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (l Om kx ky)
:precision binary64
(sqrt
(*
(/ 1.0 2.0)
(+
1.0
(/
1.0
(sqrt
(+
1.0
(*
(pow (/ (* 2.0 l) Om) 2.0)
(+ (pow (sin kx) 2.0) (pow (sin ky) 2.0))))))))))
double code(double l, double Om, double kx, double ky) {
return sqrt(((1.0 / 2.0) * (1.0 + (1.0 / sqrt((1.0 + (pow(((2.0 * l) / Om), 2.0) * (pow(sin(kx), 2.0) + pow(sin(ky), 2.0)))))))));
}
real(8) function code(l, om, kx, ky)
real(8), intent (in) :: l
real(8), intent (in) :: om
real(8), intent (in) :: kx
real(8), intent (in) :: ky
code = sqrt(((1.0d0 / 2.0d0) * (1.0d0 + (1.0d0 / sqrt((1.0d0 + ((((2.0d0 * l) / om) ** 2.0d0) * ((sin(kx) ** 2.0d0) + (sin(ky) ** 2.0d0)))))))))
end function
public static double code(double l, double Om, double kx, double ky) {
return Math.sqrt(((1.0 / 2.0) * (1.0 + (1.0 / Math.sqrt((1.0 + (Math.pow(((2.0 * l) / Om), 2.0) * (Math.pow(Math.sin(kx), 2.0) + Math.pow(Math.sin(ky), 2.0)))))))));
}
def code(l, Om, kx, ky): return math.sqrt(((1.0 / 2.0) * (1.0 + (1.0 / math.sqrt((1.0 + (math.pow(((2.0 * l) / Om), 2.0) * (math.pow(math.sin(kx), 2.0) + math.pow(math.sin(ky), 2.0)))))))))
function code(l, Om, kx, ky) return sqrt(Float64(Float64(1.0 / 2.0) * Float64(1.0 + Float64(1.0 / sqrt(Float64(1.0 + Float64((Float64(Float64(2.0 * l) / Om) ^ 2.0) * Float64((sin(kx) ^ 2.0) + (sin(ky) ^ 2.0))))))))) end
function tmp = code(l, Om, kx, ky) tmp = sqrt(((1.0 / 2.0) * (1.0 + (1.0 / sqrt((1.0 + ((((2.0 * l) / Om) ^ 2.0) * ((sin(kx) ^ 2.0) + (sin(ky) ^ 2.0))))))))); end
code[l_, Om_, kx_, ky_] := N[Sqrt[N[(N[(1.0 / 2.0), $MachinePrecision] * N[(1.0 + N[(1.0 / N[Sqrt[N[(1.0 + N[(N[Power[N[(N[(2.0 * l), $MachinePrecision] / Om), $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Power[N[Sin[kx], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[ky], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{2} \cdot \left(1 + \frac{1}{\sqrt{1 + {\left(\frac{2 \cdot \ell}{Om}\right)}^{2} \cdot \left({\sin kx}^{2} + {\sin ky}^{2}\right)}}\right)}
\end{array}
(FPCore (l Om kx ky)
:precision binary64
(sqrt
(+
0.5
(*
0.5
(/ 1.0 (hypot 1.0 (* (hypot (sin kx) (sin ky)) (* (/ 2.0 Om) l))))))))
double code(double l, double Om, double kx, double ky) {
return sqrt((0.5 + (0.5 * (1.0 / hypot(1.0, (hypot(sin(kx), sin(ky)) * ((2.0 / Om) * l)))))));
}
public static double code(double l, double Om, double kx, double ky) {
return Math.sqrt((0.5 + (0.5 * (1.0 / Math.hypot(1.0, (Math.hypot(Math.sin(kx), Math.sin(ky)) * ((2.0 / Om) * l)))))));
}
def code(l, Om, kx, ky): return math.sqrt((0.5 + (0.5 * (1.0 / math.hypot(1.0, (math.hypot(math.sin(kx), math.sin(ky)) * ((2.0 / Om) * l)))))))
function code(l, Om, kx, ky) return sqrt(Float64(0.5 + Float64(0.5 * Float64(1.0 / hypot(1.0, Float64(hypot(sin(kx), sin(ky)) * Float64(Float64(2.0 / Om) * l))))))) end
function tmp = code(l, Om, kx, ky) tmp = sqrt((0.5 + (0.5 * (1.0 / hypot(1.0, (hypot(sin(kx), sin(ky)) * ((2.0 / Om) * l))))))); end
code[l_, Om_, kx_, ky_] := N[Sqrt[N[(0.5 + N[(0.5 * N[(1.0 / N[Sqrt[1.0 ^ 2 + N[(N[Sqrt[N[Sin[kx], $MachinePrecision] ^ 2 + N[Sin[ky], $MachinePrecision] ^ 2], $MachinePrecision] * N[(N[(2.0 / Om), $MachinePrecision] * l), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0.5 + 0.5 \cdot \frac{1}{\mathsf{hypot}\left(1, \mathsf{hypot}\left(\sin kx, \sin ky\right) \cdot \left(\frac{2}{Om} \cdot \ell\right)\right)}}
\end{array}
Initial program 99.2%
Simplified99.2%
*-un-lft-identity99.2%
add-sqr-sqrt99.2%
hypot-1-def99.2%
sqrt-prod99.2%
sqrt-pow199.6%
metadata-eval99.6%
pow199.6%
clear-num99.6%
un-div-inv99.6%
unpow299.6%
unpow299.6%
hypot-define100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
*-commutative100.0%
associate-/r/100.0%
Simplified100.0%
(FPCore (l Om kx ky) :precision binary64 (sqrt (+ 0.5 (* 0.5 (pow (+ 1.0 (* (pow (* (sin ky) (/ l Om)) 2.0) 4.0)) -0.5)))))
double code(double l, double Om, double kx, double ky) {
return sqrt((0.5 + (0.5 * pow((1.0 + (pow((sin(ky) * (l / Om)), 2.0) * 4.0)), -0.5))));
}
real(8) function code(l, om, kx, ky)
real(8), intent (in) :: l
real(8), intent (in) :: om
real(8), intent (in) :: kx
real(8), intent (in) :: ky
code = sqrt((0.5d0 + (0.5d0 * ((1.0d0 + (((sin(ky) * (l / om)) ** 2.0d0) * 4.0d0)) ** (-0.5d0)))))
end function
public static double code(double l, double Om, double kx, double ky) {
return Math.sqrt((0.5 + (0.5 * Math.pow((1.0 + (Math.pow((Math.sin(ky) * (l / Om)), 2.0) * 4.0)), -0.5))));
}
def code(l, Om, kx, ky): return math.sqrt((0.5 + (0.5 * math.pow((1.0 + (math.pow((math.sin(ky) * (l / Om)), 2.0) * 4.0)), -0.5))))
function code(l, Om, kx, ky) return sqrt(Float64(0.5 + Float64(0.5 * (Float64(1.0 + Float64((Float64(sin(ky) * Float64(l / Om)) ^ 2.0) * 4.0)) ^ -0.5)))) end
function tmp = code(l, Om, kx, ky) tmp = sqrt((0.5 + (0.5 * ((1.0 + (((sin(ky) * (l / Om)) ^ 2.0) * 4.0)) ^ -0.5)))); end
code[l_, Om_, kx_, ky_] := N[Sqrt[N[(0.5 + N[(0.5 * N[Power[N[(1.0 + N[(N[Power[N[(N[Sin[ky], $MachinePrecision] * N[(l / Om), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] * 4.0), $MachinePrecision]), $MachinePrecision], -0.5], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0.5 + 0.5 \cdot {\left(1 + {\left(\sin ky \cdot \frac{\ell}{Om}\right)}^{2} \cdot 4\right)}^{-0.5}}
\end{array}
Initial program 99.2%
Simplified99.2%
Taylor expanded in kx around 0 78.3%
+-commutative78.3%
fma-define78.3%
*-commutative78.3%
associate-/l*78.6%
unpow278.6%
unpow278.6%
times-frac91.5%
unpow291.5%
Simplified91.5%
fma-undefine91.5%
pow-prod-down95.5%
clear-num95.5%
un-div-inv95.5%
Applied egg-rr95.5%
sqrt-div95.5%
metadata-eval95.5%
+-commutative95.5%
add-sqr-sqrt95.5%
hypot-1-def95.5%
*-commutative95.5%
sqrt-prod95.5%
sqrt-pow195.5%
metadata-eval95.5%
pow195.5%
div-inv95.5%
clear-num95.5%
metadata-eval95.5%
Applied egg-rr95.5%
inv-pow95.5%
hypot-undefine95.5%
sqrt-pow295.5%
metadata-eval95.5%
swap-sqr95.5%
pow295.5%
metadata-eval95.5%
metadata-eval95.5%
Applied egg-rr95.5%
(FPCore (l Om kx ky) :precision binary64 (sqrt (+ 0.5 (/ 0.5 (hypot 1.0 (* (sin ky) (/ (* 2.0 l) Om)))))))
double code(double l, double Om, double kx, double ky) {
return sqrt((0.5 + (0.5 / hypot(1.0, (sin(ky) * ((2.0 * l) / Om))))));
}
public static double code(double l, double Om, double kx, double ky) {
return Math.sqrt((0.5 + (0.5 / Math.hypot(1.0, (Math.sin(ky) * ((2.0 * l) / Om))))));
}
def code(l, Om, kx, ky): return math.sqrt((0.5 + (0.5 / math.hypot(1.0, (math.sin(ky) * ((2.0 * l) / Om))))))
function code(l, Om, kx, ky) return sqrt(Float64(0.5 + Float64(0.5 / hypot(1.0, Float64(sin(ky) * Float64(Float64(2.0 * l) / Om)))))) end
function tmp = code(l, Om, kx, ky) tmp = sqrt((0.5 + (0.5 / hypot(1.0, (sin(ky) * ((2.0 * l) / Om)))))); end
code[l_, Om_, kx_, ky_] := N[Sqrt[N[(0.5 + N[(0.5 / N[Sqrt[1.0 ^ 2 + N[(N[Sin[ky], $MachinePrecision] * N[(N[(2.0 * l), $MachinePrecision] / Om), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0.5 + \frac{0.5}{\mathsf{hypot}\left(1, \sin ky \cdot \frac{2 \cdot \ell}{Om}\right)}}
\end{array}
Initial program 99.2%
Simplified99.2%
Taylor expanded in kx around 0 78.3%
+-commutative78.3%
fma-define78.3%
*-commutative78.3%
associate-/l*78.6%
unpow278.6%
unpow278.6%
times-frac91.5%
unpow291.5%
Simplified91.5%
fma-undefine91.5%
pow-prod-down95.5%
clear-num95.5%
un-div-inv95.5%
Applied egg-rr95.5%
sqrt-div95.5%
metadata-eval95.5%
+-commutative95.5%
add-sqr-sqrt95.5%
hypot-1-def95.5%
*-commutative95.5%
sqrt-prod95.5%
sqrt-pow195.5%
metadata-eval95.5%
pow195.5%
div-inv95.5%
clear-num95.5%
metadata-eval95.5%
Applied egg-rr95.5%
*-un-lft-identity95.5%
un-div-inv95.5%
associate-*l*95.5%
Applied egg-rr95.5%
*-lft-identity95.5%
*-commutative95.5%
associate-*r/95.5%
Simplified95.5%
(FPCore (l Om kx ky) :precision binary64 (if (<= l 1.2e-70) 1.0 (sqrt 0.5)))
double code(double l, double Om, double kx, double ky) {
double tmp;
if (l <= 1.2e-70) {
tmp = 1.0;
} else {
tmp = sqrt(0.5);
}
return tmp;
}
real(8) function code(l, om, kx, ky)
real(8), intent (in) :: l
real(8), intent (in) :: om
real(8), intent (in) :: kx
real(8), intent (in) :: ky
real(8) :: tmp
if (l <= 1.2d-70) then
tmp = 1.0d0
else
tmp = sqrt(0.5d0)
end if
code = tmp
end function
public static double code(double l, double Om, double kx, double ky) {
double tmp;
if (l <= 1.2e-70) {
tmp = 1.0;
} else {
tmp = Math.sqrt(0.5);
}
return tmp;
}
def code(l, Om, kx, ky): tmp = 0 if l <= 1.2e-70: tmp = 1.0 else: tmp = math.sqrt(0.5) return tmp
function code(l, Om, kx, ky) tmp = 0.0 if (l <= 1.2e-70) tmp = 1.0; else tmp = sqrt(0.5); end return tmp end
function tmp_2 = code(l, Om, kx, ky) tmp = 0.0; if (l <= 1.2e-70) tmp = 1.0; else tmp = sqrt(0.5); end tmp_2 = tmp; end
code[l_, Om_, kx_, ky_] := If[LessEqual[l, 1.2e-70], 1.0, N[Sqrt[0.5], $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;\ell \leq 1.2 \cdot 10^{-70}:\\
\;\;\;\;1\\
\mathbf{else}:\\
\;\;\;\;\sqrt{0.5}\\
\end{array}
\end{array}
if l < 1.2000000000000001e-70Initial program 100.0%
Simplified100.0%
Taylor expanded in kx around 0 76.0%
+-commutative76.0%
fma-define76.0%
*-commutative76.0%
associate-/l*76.5%
unpow276.5%
unpow276.5%
times-frac92.3%
unpow292.3%
Simplified92.3%
fma-undefine92.3%
pow-prod-down96.2%
clear-num96.2%
un-div-inv96.2%
Applied egg-rr96.2%
sqrt-div96.2%
metadata-eval96.2%
+-commutative96.2%
add-sqr-sqrt96.2%
hypot-1-def96.2%
*-commutative96.2%
sqrt-prod96.2%
sqrt-pow196.2%
metadata-eval96.2%
pow196.2%
div-inv96.2%
clear-num96.2%
metadata-eval96.2%
Applied egg-rr96.2%
Taylor expanded in ky around 0 71.1%
if 1.2000000000000001e-70 < l Initial program 97.8%
Simplified97.8%
*-un-lft-identity97.8%
add-sqr-sqrt97.8%
hypot-1-def97.8%
sqrt-prod97.8%
sqrt-pow198.9%
metadata-eval98.9%
pow198.9%
clear-num98.9%
un-div-inv98.9%
unpow298.9%
unpow298.9%
hypot-define100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
*-commutative100.0%
associate-/r/100.0%
Simplified100.0%
Taylor expanded in Om around 0 74.4%
(FPCore (l Om kx ky) :precision binary64 1.0)
double code(double l, double Om, double kx, double ky) {
return 1.0;
}
real(8) function code(l, om, kx, ky)
real(8), intent (in) :: l
real(8), intent (in) :: om
real(8), intent (in) :: kx
real(8), intent (in) :: ky
code = 1.0d0
end function
public static double code(double l, double Om, double kx, double ky) {
return 1.0;
}
def code(l, Om, kx, ky): return 1.0
function code(l, Om, kx, ky) return 1.0 end
function tmp = code(l, Om, kx, ky) tmp = 1.0; end
code[l_, Om_, kx_, ky_] := 1.0
\begin{array}{l}
\\
1
\end{array}
Initial program 99.2%
Simplified99.2%
Taylor expanded in kx around 0 78.3%
+-commutative78.3%
fma-define78.3%
*-commutative78.3%
associate-/l*78.6%
unpow278.6%
unpow278.6%
times-frac91.5%
unpow291.5%
Simplified91.5%
fma-undefine91.5%
pow-prod-down95.5%
clear-num95.5%
un-div-inv95.5%
Applied egg-rr95.5%
sqrt-div95.5%
metadata-eval95.5%
+-commutative95.5%
add-sqr-sqrt95.5%
hypot-1-def95.5%
*-commutative95.5%
sqrt-prod95.5%
sqrt-pow195.5%
metadata-eval95.5%
pow195.5%
div-inv95.5%
clear-num95.5%
metadata-eval95.5%
Applied egg-rr95.5%
Taylor expanded in ky around 0 61.7%
herbie shell --seed 2024136
(FPCore (l Om kx ky)
:name "Toniolo and Linder, Equation (3a)"
:precision binary64
(sqrt (* (/ 1.0 2.0) (+ 1.0 (/ 1.0 (sqrt (+ 1.0 (* (pow (/ (* 2.0 l) Om) 2.0) (+ (pow (sin kx) 2.0) (pow (sin ky) 2.0))))))))))