
(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 8 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
(pow
(cbrt (hypot 1.0 (* (* 2.0 (/ l Om)) (hypot (sin ky) (sin kx)))))
3.0))))))
double code(double l, double Om, double kx, double ky) {
return sqrt((0.5 + (0.5 * (1.0 / pow(cbrt(hypot(1.0, ((2.0 * (l / Om)) * hypot(sin(ky), sin(kx))))), 3.0)))));
}
public static double code(double l, double Om, double kx, double ky) {
return Math.sqrt((0.5 + (0.5 * (1.0 / Math.pow(Math.cbrt(Math.hypot(1.0, ((2.0 * (l / Om)) * Math.hypot(Math.sin(ky), Math.sin(kx))))), 3.0)))));
}
function code(l, Om, kx, ky) return sqrt(Float64(0.5 + Float64(0.5 * Float64(1.0 / (cbrt(hypot(1.0, Float64(Float64(2.0 * Float64(l / Om)) * hypot(sin(ky), sin(kx))))) ^ 3.0))))) end
code[l_, Om_, kx_, ky_] := N[Sqrt[N[(0.5 + N[(0.5 * N[(1.0 / N[Power[N[Power[N[Sqrt[1.0 ^ 2 + N[(N[(2.0 * N[(l / Om), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[Sin[ky], $MachinePrecision] ^ 2 + N[Sin[kx], $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision], 1/3], $MachinePrecision], 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0.5 + 0.5 \cdot \frac{1}{{\left(\sqrt[3]{\mathsf{hypot}\left(1, \left(2 \cdot \frac{\ell}{Om}\right) \cdot \mathsf{hypot}\left(\sin ky, \sin kx\right)\right)}\right)}^{3}}}
\end{array}
Initial program 96.8%
Simplified96.8%
add-cube-cbrt96.8%
pow396.8%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (l Om kx ky)
:precision binary64
(sqrt
(+
0.5
(*
0.5
(/ 1.0 (hypot 1.0 (* (* 2.0 (/ l Om)) (hypot (sin ky) (sin kx)))))))))
double code(double l, double Om, double kx, double ky) {
return sqrt((0.5 + (0.5 * (1.0 / hypot(1.0, ((2.0 * (l / Om)) * hypot(sin(ky), sin(kx))))))));
}
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, ((2.0 * (l / Om)) * Math.hypot(Math.sin(ky), Math.sin(kx))))))));
}
def code(l, Om, kx, ky): return math.sqrt((0.5 + (0.5 * (1.0 / math.hypot(1.0, ((2.0 * (l / Om)) * math.hypot(math.sin(ky), math.sin(kx))))))))
function code(l, Om, kx, ky) return sqrt(Float64(0.5 + Float64(0.5 * Float64(1.0 / hypot(1.0, Float64(Float64(2.0 * Float64(l / Om)) * hypot(sin(ky), sin(kx)))))))) end
function tmp = code(l, Om, kx, ky) tmp = sqrt((0.5 + (0.5 * (1.0 / hypot(1.0, ((2.0 * (l / Om)) * hypot(sin(ky), sin(kx)))))))); end
code[l_, Om_, kx_, ky_] := N[Sqrt[N[(0.5 + N[(0.5 * N[(1.0 / N[Sqrt[1.0 ^ 2 + N[(N[(2.0 * N[(l / Om), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[Sin[ky], $MachinePrecision] ^ 2 + N[Sin[kx], $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0.5 + 0.5 \cdot \frac{1}{\mathsf{hypot}\left(1, \left(2 \cdot \frac{\ell}{Om}\right) \cdot \mathsf{hypot}\left(\sin ky, \sin kx\right)\right)}}
\end{array}
Initial program 96.8%
Simplified96.8%
add-sqr-sqrt96.8%
hypot-1-def96.8%
sqrt-prod96.8%
sqrt-pow197.4%
metadata-eval97.4%
pow197.4%
div-inv97.4%
clear-num97.4%
+-commutative97.4%
unpow297.4%
unpow297.4%
hypot-def100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (l Om kx ky) :precision binary64 (sqrt (+ 0.5 (* 0.5 (log (exp (/ 1.0 (hypot 1.0 (* (/ l Om) (* 2.0 (sin ky)))))))))))
double code(double l, double Om, double kx, double ky) {
return sqrt((0.5 + (0.5 * log(exp((1.0 / hypot(1.0, ((l / Om) * (2.0 * sin(ky))))))))));
}
public static double code(double l, double Om, double kx, double ky) {
return Math.sqrt((0.5 + (0.5 * Math.log(Math.exp((1.0 / Math.hypot(1.0, ((l / Om) * (2.0 * Math.sin(ky))))))))));
}
def code(l, Om, kx, ky): return math.sqrt((0.5 + (0.5 * math.log(math.exp((1.0 / math.hypot(1.0, ((l / Om) * (2.0 * math.sin(ky))))))))))
function code(l, Om, kx, ky) return sqrt(Float64(0.5 + Float64(0.5 * log(exp(Float64(1.0 / hypot(1.0, Float64(Float64(l / Om) * Float64(2.0 * sin(ky)))))))))) end
function tmp = code(l, Om, kx, ky) tmp = sqrt((0.5 + (0.5 * log(exp((1.0 / hypot(1.0, ((l / Om) * (2.0 * sin(ky)))))))))); end
code[l_, Om_, kx_, ky_] := N[Sqrt[N[(0.5 + N[(0.5 * N[Log[N[Exp[N[(1.0 / N[Sqrt[1.0 ^ 2 + N[(N[(l / Om), $MachinePrecision] * N[(2.0 * N[Sin[ky], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0.5 + 0.5 \cdot \log \left(e^{\frac{1}{\mathsf{hypot}\left(1, \frac{\ell}{Om} \cdot \left(2 \cdot \sin ky\right)\right)}}\right)}
\end{array}
Initial program 96.8%
Simplified96.8%
Taylor expanded in kx around 0 72.5%
associate-/l*72.1%
associate-/r/72.3%
metadata-eval72.3%
unpow272.3%
unpow272.3%
times-frac84.2%
unpow284.2%
swap-sqr91.9%
swap-sqr91.9%
associate-*l*91.9%
associate-*l*91.9%
unpow291.9%
associate-*l*91.9%
Simplified91.9%
add-log-exp91.9%
unpow291.9%
hypot-1-def91.9%
*-commutative91.9%
associate-*r*91.9%
Applied egg-rr91.9%
Final simplification91.9%
(FPCore (l Om kx ky) :precision binary64 (sqrt (+ 0.5 (* 0.5 (pow (sqrt (hypot 1.0 (* 2.0 (* (/ l Om) (sin ky))))) -2.0)))))
double code(double l, double Om, double kx, double ky) {
return sqrt((0.5 + (0.5 * pow(sqrt(hypot(1.0, (2.0 * ((l / Om) * sin(ky))))), -2.0))));
}
public static double code(double l, double Om, double kx, double ky) {
return Math.sqrt((0.5 + (0.5 * Math.pow(Math.sqrt(Math.hypot(1.0, (2.0 * ((l / Om) * Math.sin(ky))))), -2.0))));
}
def code(l, Om, kx, ky): return math.sqrt((0.5 + (0.5 * math.pow(math.sqrt(math.hypot(1.0, (2.0 * ((l / Om) * math.sin(ky))))), -2.0))))
function code(l, Om, kx, ky) return sqrt(Float64(0.5 + Float64(0.5 * (sqrt(hypot(1.0, Float64(2.0 * Float64(Float64(l / Om) * sin(ky))))) ^ -2.0)))) end
function tmp = code(l, Om, kx, ky) tmp = sqrt((0.5 + (0.5 * (sqrt(hypot(1.0, (2.0 * ((l / Om) * sin(ky))))) ^ -2.0)))); end
code[l_, Om_, kx_, ky_] := N[Sqrt[N[(0.5 + N[(0.5 * N[Power[N[Sqrt[N[Sqrt[1.0 ^ 2 + N[(2.0 * N[(N[(l / Om), $MachinePrecision] * N[Sin[ky], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]], $MachinePrecision], -2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0.5 + 0.5 \cdot {\left(\sqrt{\mathsf{hypot}\left(1, 2 \cdot \left(\frac{\ell}{Om} \cdot \sin ky\right)\right)}\right)}^{-2}}
\end{array}
Initial program 96.8%
Simplified96.8%
Taylor expanded in kx around 0 72.5%
associate-/l*72.1%
associate-/r/72.3%
metadata-eval72.3%
unpow272.3%
unpow272.3%
times-frac84.2%
unpow284.2%
swap-sqr91.9%
swap-sqr91.9%
associate-*l*91.9%
associate-*l*91.9%
unpow291.9%
associate-*l*91.9%
Simplified91.9%
inv-pow91.9%
add-sqr-sqrt91.9%
unpow-prod-down91.9%
unpow291.9%
hypot-1-def91.9%
*-commutative91.9%
associate-*r*91.9%
Applied egg-rr91.9%
pow-sqr91.9%
associate-*l*91.9%
metadata-eval91.9%
Simplified91.9%
Final simplification91.9%
(FPCore (l Om kx ky) :precision binary64 (if (<= l 5.4e+239) (sqrt (+ 0.5 (* 0.5 (/ 1.0 (hypot 1.0 (* 2.0 (/ (* l (sin kx)) Om))))))) (sqrt 0.5)))
double code(double l, double Om, double kx, double ky) {
double tmp;
if (l <= 5.4e+239) {
tmp = sqrt((0.5 + (0.5 * (1.0 / hypot(1.0, (2.0 * ((l * sin(kx)) / Om)))))));
} else {
tmp = sqrt(0.5);
}
return tmp;
}
public static double code(double l, double Om, double kx, double ky) {
double tmp;
if (l <= 5.4e+239) {
tmp = Math.sqrt((0.5 + (0.5 * (1.0 / Math.hypot(1.0, (2.0 * ((l * Math.sin(kx)) / Om)))))));
} else {
tmp = Math.sqrt(0.5);
}
return tmp;
}
def code(l, Om, kx, ky): tmp = 0 if l <= 5.4e+239: tmp = math.sqrt((0.5 + (0.5 * (1.0 / math.hypot(1.0, (2.0 * ((l * math.sin(kx)) / Om))))))) else: tmp = math.sqrt(0.5) return tmp
function code(l, Om, kx, ky) tmp = 0.0 if (l <= 5.4e+239) tmp = sqrt(Float64(0.5 + Float64(0.5 * Float64(1.0 / hypot(1.0, Float64(2.0 * Float64(Float64(l * sin(kx)) / Om))))))); else tmp = sqrt(0.5); end return tmp end
function tmp_2 = code(l, Om, kx, ky) tmp = 0.0; if (l <= 5.4e+239) tmp = sqrt((0.5 + (0.5 * (1.0 / hypot(1.0, (2.0 * ((l * sin(kx)) / Om))))))); else tmp = sqrt(0.5); end tmp_2 = tmp; end
code[l_, Om_, kx_, ky_] := If[LessEqual[l, 5.4e+239], N[Sqrt[N[(0.5 + N[(0.5 * N[(1.0 / N[Sqrt[1.0 ^ 2 + N[(2.0 * N[(N[(l * N[Sin[kx], $MachinePrecision]), $MachinePrecision] / Om), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[Sqrt[0.5], $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;\ell \leq 5.4 \cdot 10^{+239}:\\
\;\;\;\;\sqrt{0.5 + 0.5 \cdot \frac{1}{\mathsf{hypot}\left(1, 2 \cdot \frac{\ell \cdot \sin kx}{Om}\right)}}\\
\mathbf{else}:\\
\;\;\;\;\sqrt{0.5}\\
\end{array}
\end{array}
if l < 5.3999999999999997e239Initial program 97.4%
Simplified97.4%
add-sqr-sqrt97.4%
hypot-1-def97.4%
sqrt-prod97.4%
sqrt-pow198.1%
metadata-eval98.1%
pow198.1%
div-inv98.1%
clear-num98.1%
+-commutative98.1%
unpow298.1%
unpow298.1%
hypot-def100.0%
Applied egg-rr100.0%
Taylor expanded in ky around 0 93.5%
if 5.3999999999999997e239 < l Initial program 87.5%
Simplified87.5%
Taylor expanded in Om around 0 81.3%
+-commutative81.3%
unpow281.3%
unpow281.3%
hypot-def93.8%
hypot-def81.3%
unpow281.3%
unpow281.3%
+-commutative81.3%
unpow281.3%
unpow281.3%
hypot-def93.8%
Simplified93.8%
Taylor expanded in l around inf 94.8%
Final simplification93.6%
(FPCore (l Om kx ky) :precision binary64 (sqrt (+ 0.5 (* 0.5 (/ 1.0 (hypot 1.0 (* (/ l Om) (* 2.0 (sin ky)))))))))
double code(double l, double Om, double kx, double ky) {
return sqrt((0.5 + (0.5 * (1.0 / hypot(1.0, ((l / Om) * (2.0 * sin(ky))))))));
}
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, ((l / Om) * (2.0 * Math.sin(ky))))))));
}
def code(l, Om, kx, ky): return math.sqrt((0.5 + (0.5 * (1.0 / math.hypot(1.0, ((l / Om) * (2.0 * math.sin(ky))))))))
function code(l, Om, kx, ky) return sqrt(Float64(0.5 + Float64(0.5 * Float64(1.0 / hypot(1.0, Float64(Float64(l / Om) * Float64(2.0 * sin(ky)))))))) end
function tmp = code(l, Om, kx, ky) tmp = sqrt((0.5 + (0.5 * (1.0 / hypot(1.0, ((l / Om) * (2.0 * sin(ky)))))))); end
code[l_, Om_, kx_, ky_] := N[Sqrt[N[(0.5 + N[(0.5 * N[(1.0 / N[Sqrt[1.0 ^ 2 + N[(N[(l / Om), $MachinePrecision] * N[(2.0 * N[Sin[ky], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0.5 + 0.5 \cdot \frac{1}{\mathsf{hypot}\left(1, \frac{\ell}{Om} \cdot \left(2 \cdot \sin ky\right)\right)}}
\end{array}
Initial program 96.8%
Simplified96.8%
Taylor expanded in kx around 0 72.5%
associate-/l*72.1%
associate-/r/72.3%
metadata-eval72.3%
unpow272.3%
unpow272.3%
times-frac84.2%
unpow284.2%
swap-sqr91.9%
swap-sqr91.9%
associate-*l*91.9%
associate-*l*91.9%
unpow291.9%
associate-*l*91.9%
Simplified91.9%
unpow291.9%
hypot-1-def91.9%
*-commutative91.9%
associate-*r*91.9%
Applied egg-rr91.9%
Final simplification91.9%
(FPCore (l Om kx ky) :precision binary64 (if (<= Om 1e-7) (sqrt 0.5) 1.0))
double code(double l, double Om, double kx, double ky) {
double tmp;
if (Om <= 1e-7) {
tmp = sqrt(0.5);
} else {
tmp = 1.0;
}
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 (om <= 1d-7) then
tmp = sqrt(0.5d0)
else
tmp = 1.0d0
end if
code = tmp
end function
public static double code(double l, double Om, double kx, double ky) {
double tmp;
if (Om <= 1e-7) {
tmp = Math.sqrt(0.5);
} else {
tmp = 1.0;
}
return tmp;
}
def code(l, Om, kx, ky): tmp = 0 if Om <= 1e-7: tmp = math.sqrt(0.5) else: tmp = 1.0 return tmp
function code(l, Om, kx, ky) tmp = 0.0 if (Om <= 1e-7) tmp = sqrt(0.5); else tmp = 1.0; end return tmp end
function tmp_2 = code(l, Om, kx, ky) tmp = 0.0; if (Om <= 1e-7) tmp = sqrt(0.5); else tmp = 1.0; end tmp_2 = tmp; end
code[l_, Om_, kx_, ky_] := If[LessEqual[Om, 1e-7], N[Sqrt[0.5], $MachinePrecision], 1.0]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;Om \leq 10^{-7}:\\
\;\;\;\;\sqrt{0.5}\\
\mathbf{else}:\\
\;\;\;\;1\\
\end{array}
\end{array}
if Om < 9.9999999999999995e-8Initial program 95.5%
Simplified95.5%
Taylor expanded in Om around 0 58.6%
+-commutative58.6%
unpow258.6%
unpow258.6%
hypot-def62.1%
hypot-def58.6%
unpow258.6%
unpow258.6%
+-commutative58.6%
unpow258.6%
unpow258.6%
hypot-def62.1%
Simplified62.1%
Taylor expanded in l around inf 67.7%
if 9.9999999999999995e-8 < Om Initial program 100.0%
Simplified100.0%
Taylor expanded in kx around 0 77.5%
associate-/l*76.1%
associate-/r/77.5%
metadata-eval77.5%
unpow277.5%
unpow277.5%
times-frac90.3%
unpow290.3%
swap-sqr91.1%
swap-sqr91.1%
associate-*l*91.1%
associate-*l*91.1%
unpow291.1%
associate-*l*91.1%
Simplified91.1%
add-log-exp91.1%
unpow291.1%
hypot-1-def91.1%
*-commutative91.1%
associate-*r*91.1%
Applied egg-rr91.1%
Taylor expanded in ky around 0 78.9%
Final simplification70.9%
(FPCore (l Om kx ky) :precision binary64 (sqrt 0.5))
double code(double l, double Om, double kx, double ky) {
return sqrt(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)
end function
public static double code(double l, double Om, double kx, double ky) {
return Math.sqrt(0.5);
}
def code(l, Om, kx, ky): return math.sqrt(0.5)
function code(l, Om, kx, ky) return sqrt(0.5) end
function tmp = code(l, Om, kx, ky) tmp = sqrt(0.5); end
code[l_, Om_, kx_, ky_] := N[Sqrt[0.5], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0.5}
\end{array}
Initial program 96.8%
Simplified96.8%
Taylor expanded in Om around 0 49.7%
+-commutative49.7%
unpow249.7%
unpow249.7%
hypot-def52.3%
hypot-def49.7%
unpow249.7%
unpow249.7%
+-commutative49.7%
unpow249.7%
unpow249.7%
hypot-def52.3%
Simplified52.3%
Taylor expanded in l around inf 59.7%
Final simplification59.7%
herbie shell --seed 2023292
(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))))))))))