
(FPCore (t l k) :precision binary64 (/ 2.0 (* (* (* (/ (pow t 3.0) (* l l)) (sin k)) (tan k)) (- (+ 1.0 (pow (/ k t) 2.0)) 1.0))))
double code(double t, double l, double k) {
return 2.0 / ((((pow(t, 3.0) / (l * l)) * sin(k)) * tan(k)) * ((1.0 + pow((k / t), 2.0)) - 1.0));
}
real(8) function code(t, l, k)
real(8), intent (in) :: t
real(8), intent (in) :: l
real(8), intent (in) :: k
code = 2.0d0 / (((((t ** 3.0d0) / (l * l)) * sin(k)) * tan(k)) * ((1.0d0 + ((k / t) ** 2.0d0)) - 1.0d0))
end function
public static double code(double t, double l, double k) {
return 2.0 / ((((Math.pow(t, 3.0) / (l * l)) * Math.sin(k)) * Math.tan(k)) * ((1.0 + Math.pow((k / t), 2.0)) - 1.0));
}
def code(t, l, k): return 2.0 / ((((math.pow(t, 3.0) / (l * l)) * math.sin(k)) * math.tan(k)) * ((1.0 + math.pow((k / t), 2.0)) - 1.0))
function code(t, l, k) return Float64(2.0 / Float64(Float64(Float64(Float64((t ^ 3.0) / Float64(l * l)) * sin(k)) * tan(k)) * Float64(Float64(1.0 + (Float64(k / t) ^ 2.0)) - 1.0))) end
function tmp = code(t, l, k) tmp = 2.0 / (((((t ^ 3.0) / (l * l)) * sin(k)) * tan(k)) * ((1.0 + ((k / t) ^ 2.0)) - 1.0)); end
code[t_, l_, k_] := N[(2.0 / N[(N[(N[(N[(N[Power[t, 3.0], $MachinePrecision] / N[(l * l), $MachinePrecision]), $MachinePrecision] * N[Sin[k], $MachinePrecision]), $MachinePrecision] * N[Tan[k], $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 + N[Power[N[(k / t), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{2}{\left(\left(\frac{{t}^{3}}{\ell \cdot \ell} \cdot \sin k\right) \cdot \tan k\right) \cdot \left(\left(1 + {\left(\frac{k}{t}\right)}^{2}\right) - 1\right)}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 6 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (t l k) :precision binary64 (/ 2.0 (* (* (* (/ (pow t 3.0) (* l l)) (sin k)) (tan k)) (- (+ 1.0 (pow (/ k t) 2.0)) 1.0))))
double code(double t, double l, double k) {
return 2.0 / ((((pow(t, 3.0) / (l * l)) * sin(k)) * tan(k)) * ((1.0 + pow((k / t), 2.0)) - 1.0));
}
real(8) function code(t, l, k)
real(8), intent (in) :: t
real(8), intent (in) :: l
real(8), intent (in) :: k
code = 2.0d0 / (((((t ** 3.0d0) / (l * l)) * sin(k)) * tan(k)) * ((1.0d0 + ((k / t) ** 2.0d0)) - 1.0d0))
end function
public static double code(double t, double l, double k) {
return 2.0 / ((((Math.pow(t, 3.0) / (l * l)) * Math.sin(k)) * Math.tan(k)) * ((1.0 + Math.pow((k / t), 2.0)) - 1.0));
}
def code(t, l, k): return 2.0 / ((((math.pow(t, 3.0) / (l * l)) * math.sin(k)) * math.tan(k)) * ((1.0 + math.pow((k / t), 2.0)) - 1.0))
function code(t, l, k) return Float64(2.0 / Float64(Float64(Float64(Float64((t ^ 3.0) / Float64(l * l)) * sin(k)) * tan(k)) * Float64(Float64(1.0 + (Float64(k / t) ^ 2.0)) - 1.0))) end
function tmp = code(t, l, k) tmp = 2.0 / (((((t ^ 3.0) / (l * l)) * sin(k)) * tan(k)) * ((1.0 + ((k / t) ^ 2.0)) - 1.0)); end
code[t_, l_, k_] := N[(2.0 / N[(N[(N[(N[(N[Power[t, 3.0], $MachinePrecision] / N[(l * l), $MachinePrecision]), $MachinePrecision] * N[Sin[k], $MachinePrecision]), $MachinePrecision] * N[Tan[k], $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 + N[Power[N[(k / t), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{2}{\left(\left(\frac{{t}^{3}}{\ell \cdot \ell} \cdot \sin k\right) \cdot \tan k\right) \cdot \left(\left(1 + {\left(\frac{k}{t}\right)}^{2}\right) - 1\right)}
\end{array}
k_m = (fabs.f64 k)
t\_m = (fabs.f64 t)
t\_s = (copysign.f64 #s(literal 1 binary64) t)
(FPCore (t_s t_m l k_m)
:precision binary64
(*
t_s
(if (<= k_m 1.7e-35)
(/ 2.0 (pow (* (* k_m (/ k_m l)) (sqrt t_m)) 2.0))
(/ (/ 2.0 (pow (* k_m (/ (sin k_m) l)) 2.0)) (/ t_m (cos k_m))))))k_m = fabs(k);
t\_m = fabs(t);
t\_s = copysign(1.0, t);
double code(double t_s, double t_m, double l, double k_m) {
double tmp;
if (k_m <= 1.7e-35) {
tmp = 2.0 / pow(((k_m * (k_m / l)) * sqrt(t_m)), 2.0);
} else {
tmp = (2.0 / pow((k_m * (sin(k_m) / l)), 2.0)) / (t_m / cos(k_m));
}
return t_s * tmp;
}
k_m = abs(k)
t\_m = abs(t)
t\_s = copysign(1.0d0, t)
real(8) function code(t_s, t_m, l, k_m)
real(8), intent (in) :: t_s
real(8), intent (in) :: t_m
real(8), intent (in) :: l
real(8), intent (in) :: k_m
real(8) :: tmp
if (k_m <= 1.7d-35) then
tmp = 2.0d0 / (((k_m * (k_m / l)) * sqrt(t_m)) ** 2.0d0)
else
tmp = (2.0d0 / ((k_m * (sin(k_m) / l)) ** 2.0d0)) / (t_m / cos(k_m))
end if
code = t_s * tmp
end function
k_m = Math.abs(k);
t\_m = Math.abs(t);
t\_s = Math.copySign(1.0, t);
public static double code(double t_s, double t_m, double l, double k_m) {
double tmp;
if (k_m <= 1.7e-35) {
tmp = 2.0 / Math.pow(((k_m * (k_m / l)) * Math.sqrt(t_m)), 2.0);
} else {
tmp = (2.0 / Math.pow((k_m * (Math.sin(k_m) / l)), 2.0)) / (t_m / Math.cos(k_m));
}
return t_s * tmp;
}
k_m = math.fabs(k) t\_m = math.fabs(t) t\_s = math.copysign(1.0, t) def code(t_s, t_m, l, k_m): tmp = 0 if k_m <= 1.7e-35: tmp = 2.0 / math.pow(((k_m * (k_m / l)) * math.sqrt(t_m)), 2.0) else: tmp = (2.0 / math.pow((k_m * (math.sin(k_m) / l)), 2.0)) / (t_m / math.cos(k_m)) return t_s * tmp
k_m = abs(k) t\_m = abs(t) t\_s = copysign(1.0, t) function code(t_s, t_m, l, k_m) tmp = 0.0 if (k_m <= 1.7e-35) tmp = Float64(2.0 / (Float64(Float64(k_m * Float64(k_m / l)) * sqrt(t_m)) ^ 2.0)); else tmp = Float64(Float64(2.0 / (Float64(k_m * Float64(sin(k_m) / l)) ^ 2.0)) / Float64(t_m / cos(k_m))); end return Float64(t_s * tmp) end
k_m = abs(k); t\_m = abs(t); t\_s = sign(t) * abs(1.0); function tmp_2 = code(t_s, t_m, l, k_m) tmp = 0.0; if (k_m <= 1.7e-35) tmp = 2.0 / (((k_m * (k_m / l)) * sqrt(t_m)) ^ 2.0); else tmp = (2.0 / ((k_m * (sin(k_m) / l)) ^ 2.0)) / (t_m / cos(k_m)); end tmp_2 = t_s * tmp; end
k_m = N[Abs[k], $MachinePrecision]
t\_m = N[Abs[t], $MachinePrecision]
t\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[t]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[t$95$s_, t$95$m_, l_, k$95$m_] := N[(t$95$s * If[LessEqual[k$95$m, 1.7e-35], N[(2.0 / N[Power[N[(N[(k$95$m * N[(k$95$m / l), $MachinePrecision]), $MachinePrecision] * N[Sqrt[t$95$m], $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision], N[(N[(2.0 / N[Power[N[(k$95$m * N[(N[Sin[k$95$m], $MachinePrecision] / l), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] / N[(t$95$m / N[Cos[k$95$m], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]), $MachinePrecision]
\begin{array}{l}
k_m = \left|k\right|
\\
t\_m = \left|t\right|
\\
t\_s = \mathsf{copysign}\left(1, t\right)
\\
t\_s \cdot \begin{array}{l}
\mathbf{if}\;k\_m \leq 1.7 \cdot 10^{-35}:\\
\;\;\;\;\frac{2}{{\left(\left(k\_m \cdot \frac{k\_m}{\ell}\right) \cdot \sqrt{t\_m}\right)}^{2}}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{2}{{\left(k\_m \cdot \frac{\sin k\_m}{\ell}\right)}^{2}}}{\frac{t\_m}{\cos k\_m}}\\
\end{array}
\end{array}
if k < 1.7000000000000001e-35Initial program 41.0%
*-commutative41.0%
associate-/r*41.0%
Simplified46.8%
+-rgt-identity46.8%
associate-/l/46.8%
div-inv46.8%
+-rgt-identity46.8%
metadata-eval46.8%
metadata-eval46.8%
associate-+l+41.0%
sub-neg41.0%
+-commutative41.0%
add-sqr-sqrt20.8%
Applied egg-rr34.2%
associate-*r/34.2%
metadata-eval34.2%
*-commutative34.2%
associate-*l*34.3%
Simplified34.3%
Taylor expanded in k around 0 40.3%
unpow240.3%
add-sqr-sqrt21.3%
times-frac21.7%
Applied egg-rr21.7%
unpow221.7%
Simplified21.7%
unpow221.7%
frac-times21.3%
add-sqr-sqrt40.3%
associate-*r/41.2%
*-commutative41.2%
Applied egg-rr41.2%
if 1.7000000000000001e-35 < k Initial program 29.5%
*-commutative29.5%
associate-/r*29.5%
Simplified47.0%
+-rgt-identity47.0%
associate-/l/47.1%
div-inv47.1%
+-rgt-identity47.1%
metadata-eval47.1%
metadata-eval47.1%
associate-+l+29.5%
sub-neg29.5%
+-commutative29.5%
add-sqr-sqrt11.7%
Applied egg-rr27.9%
associate-*r/27.9%
metadata-eval27.9%
*-commutative27.9%
associate-*l*28.0%
Simplified28.0%
Taylor expanded in k around inf 47.0%
associate-*l/45.3%
associate-/l*47.1%
Simplified47.1%
add-sqr-sqrt47.0%
sqrt-div47.1%
sqrt-pow136.8%
metadata-eval36.8%
pow136.8%
sqrt-div36.7%
sqrt-pow146.9%
metadata-eval46.9%
pow146.9%
Applied egg-rr46.9%
unpow246.9%
associate-*r/45.2%
associate-*l/46.8%
associate-/l*46.9%
Simplified46.9%
unpow246.9%
associate-/r*47.0%
associate-/r*46.9%
frac-times43.7%
add-sqr-sqrt95.1%
Applied egg-rr95.1%
associate-*l/95.1%
associate-*r/94.9%
rem-square-sqrt95.2%
associate-/l/95.3%
unpow295.3%
Simplified95.3%
Final simplification53.2%
k_m = (fabs.f64 k)
t\_m = (fabs.f64 t)
t\_s = (copysign.f64 #s(literal 1 binary64) t)
(FPCore (t_s t_m l k_m)
:precision binary64
(*
t_s
(if (<= k_m 0.04)
(/ 2.0 (pow (* (* k_m (/ k_m l)) (sqrt t_m)) 2.0))
(/ 2.0 (pow (* (* k_m (sin k_m)) (/ (sqrt t_m) l)) 2.0)))))k_m = fabs(k);
t\_m = fabs(t);
t\_s = copysign(1.0, t);
double code(double t_s, double t_m, double l, double k_m) {
double tmp;
if (k_m <= 0.04) {
tmp = 2.0 / pow(((k_m * (k_m / l)) * sqrt(t_m)), 2.0);
} else {
tmp = 2.0 / pow(((k_m * sin(k_m)) * (sqrt(t_m) / l)), 2.0);
}
return t_s * tmp;
}
k_m = abs(k)
t\_m = abs(t)
t\_s = copysign(1.0d0, t)
real(8) function code(t_s, t_m, l, k_m)
real(8), intent (in) :: t_s
real(8), intent (in) :: t_m
real(8), intent (in) :: l
real(8), intent (in) :: k_m
real(8) :: tmp
if (k_m <= 0.04d0) then
tmp = 2.0d0 / (((k_m * (k_m / l)) * sqrt(t_m)) ** 2.0d0)
else
tmp = 2.0d0 / (((k_m * sin(k_m)) * (sqrt(t_m) / l)) ** 2.0d0)
end if
code = t_s * tmp
end function
k_m = Math.abs(k);
t\_m = Math.abs(t);
t\_s = Math.copySign(1.0, t);
public static double code(double t_s, double t_m, double l, double k_m) {
double tmp;
if (k_m <= 0.04) {
tmp = 2.0 / Math.pow(((k_m * (k_m / l)) * Math.sqrt(t_m)), 2.0);
} else {
tmp = 2.0 / Math.pow(((k_m * Math.sin(k_m)) * (Math.sqrt(t_m) / l)), 2.0);
}
return t_s * tmp;
}
k_m = math.fabs(k) t\_m = math.fabs(t) t\_s = math.copysign(1.0, t) def code(t_s, t_m, l, k_m): tmp = 0 if k_m <= 0.04: tmp = 2.0 / math.pow(((k_m * (k_m / l)) * math.sqrt(t_m)), 2.0) else: tmp = 2.0 / math.pow(((k_m * math.sin(k_m)) * (math.sqrt(t_m) / l)), 2.0) return t_s * tmp
k_m = abs(k) t\_m = abs(t) t\_s = copysign(1.0, t) function code(t_s, t_m, l, k_m) tmp = 0.0 if (k_m <= 0.04) tmp = Float64(2.0 / (Float64(Float64(k_m * Float64(k_m / l)) * sqrt(t_m)) ^ 2.0)); else tmp = Float64(2.0 / (Float64(Float64(k_m * sin(k_m)) * Float64(sqrt(t_m) / l)) ^ 2.0)); end return Float64(t_s * tmp) end
k_m = abs(k); t\_m = abs(t); t\_s = sign(t) * abs(1.0); function tmp_2 = code(t_s, t_m, l, k_m) tmp = 0.0; if (k_m <= 0.04) tmp = 2.0 / (((k_m * (k_m / l)) * sqrt(t_m)) ^ 2.0); else tmp = 2.0 / (((k_m * sin(k_m)) * (sqrt(t_m) / l)) ^ 2.0); end tmp_2 = t_s * tmp; end
k_m = N[Abs[k], $MachinePrecision]
t\_m = N[Abs[t], $MachinePrecision]
t\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[t]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[t$95$s_, t$95$m_, l_, k$95$m_] := N[(t$95$s * If[LessEqual[k$95$m, 0.04], N[(2.0 / N[Power[N[(N[(k$95$m * N[(k$95$m / l), $MachinePrecision]), $MachinePrecision] * N[Sqrt[t$95$m], $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision], N[(2.0 / N[Power[N[(N[(k$95$m * N[Sin[k$95$m], $MachinePrecision]), $MachinePrecision] * N[(N[Sqrt[t$95$m], $MachinePrecision] / l), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]]), $MachinePrecision]
\begin{array}{l}
k_m = \left|k\right|
\\
t\_m = \left|t\right|
\\
t\_s = \mathsf{copysign}\left(1, t\right)
\\
t\_s \cdot \begin{array}{l}
\mathbf{if}\;k\_m \leq 0.04:\\
\;\;\;\;\frac{2}{{\left(\left(k\_m \cdot \frac{k\_m}{\ell}\right) \cdot \sqrt{t\_m}\right)}^{2}}\\
\mathbf{else}:\\
\;\;\;\;\frac{2}{{\left(\left(k\_m \cdot \sin k\_m\right) \cdot \frac{\sqrt{t\_m}}{\ell}\right)}^{2}}\\
\end{array}
\end{array}
if k < 0.0400000000000000008Initial program 40.2%
*-commutative40.2%
associate-/r*40.2%
Simplified45.9%
+-rgt-identity45.9%
associate-/l/45.9%
div-inv45.9%
+-rgt-identity45.9%
metadata-eval45.9%
metadata-eval45.9%
associate-+l+40.2%
sub-neg40.2%
+-commutative40.2%
add-sqr-sqrt20.4%
Applied egg-rr33.6%
associate-*r/33.6%
metadata-eval33.6%
*-commutative33.6%
associate-*l*33.6%
Simplified33.6%
Taylor expanded in k around 0 40.4%
unpow240.4%
add-sqr-sqrt20.9%
times-frac21.3%
Applied egg-rr21.3%
unpow221.3%
Simplified21.3%
unpow221.3%
frac-times20.9%
add-sqr-sqrt40.4%
associate-*r/41.4%
*-commutative41.4%
Applied egg-rr41.4%
if 0.0400000000000000008 < k Initial program 31.7%
*-commutative31.7%
associate-/r*31.7%
Simplified50.5%
+-rgt-identity50.5%
associate-/l/50.6%
div-inv50.6%
+-rgt-identity50.6%
metadata-eval50.6%
metadata-eval50.6%
associate-+l+31.7%
sub-neg31.7%
+-commutative31.7%
add-sqr-sqrt12.6%
Applied egg-rr29.8%
associate-*r/29.8%
metadata-eval29.8%
*-commutative29.8%
associate-*l*29.9%
Simplified29.9%
Taylor expanded in k around inf 46.8%
associate-*l/45.0%
associate-/l*46.9%
Simplified46.9%
Taylor expanded in k around 0 36.3%
associate-*l/36.3%
*-lft-identity36.3%
Simplified36.3%
Final simplification40.3%
k_m = (fabs.f64 k) t\_m = (fabs.f64 t) t\_s = (copysign.f64 #s(literal 1 binary64) t) (FPCore (t_s t_m l k_m) :precision binary64 (* t_s (/ 2.0 (pow (* (* k_m (/ k_m l)) (sqrt t_m)) 2.0))))
k_m = fabs(k);
t\_m = fabs(t);
t\_s = copysign(1.0, t);
double code(double t_s, double t_m, double l, double k_m) {
return t_s * (2.0 / pow(((k_m * (k_m / l)) * sqrt(t_m)), 2.0));
}
k_m = abs(k)
t\_m = abs(t)
t\_s = copysign(1.0d0, t)
real(8) function code(t_s, t_m, l, k_m)
real(8), intent (in) :: t_s
real(8), intent (in) :: t_m
real(8), intent (in) :: l
real(8), intent (in) :: k_m
code = t_s * (2.0d0 / (((k_m * (k_m / l)) * sqrt(t_m)) ** 2.0d0))
end function
k_m = Math.abs(k);
t\_m = Math.abs(t);
t\_s = Math.copySign(1.0, t);
public static double code(double t_s, double t_m, double l, double k_m) {
return t_s * (2.0 / Math.pow(((k_m * (k_m / l)) * Math.sqrt(t_m)), 2.0));
}
k_m = math.fabs(k) t\_m = math.fabs(t) t\_s = math.copysign(1.0, t) def code(t_s, t_m, l, k_m): return t_s * (2.0 / math.pow(((k_m * (k_m / l)) * math.sqrt(t_m)), 2.0))
k_m = abs(k) t\_m = abs(t) t\_s = copysign(1.0, t) function code(t_s, t_m, l, k_m) return Float64(t_s * Float64(2.0 / (Float64(Float64(k_m * Float64(k_m / l)) * sqrt(t_m)) ^ 2.0))) end
k_m = abs(k); t\_m = abs(t); t\_s = sign(t) * abs(1.0); function tmp = code(t_s, t_m, l, k_m) tmp = t_s * (2.0 / (((k_m * (k_m / l)) * sqrt(t_m)) ^ 2.0)); end
k_m = N[Abs[k], $MachinePrecision]
t\_m = N[Abs[t], $MachinePrecision]
t\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[t]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[t$95$s_, t$95$m_, l_, k$95$m_] := N[(t$95$s * N[(2.0 / N[Power[N[(N[(k$95$m * N[(k$95$m / l), $MachinePrecision]), $MachinePrecision] * N[Sqrt[t$95$m], $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
k_m = \left|k\right|
\\
t\_m = \left|t\right|
\\
t\_s = \mathsf{copysign}\left(1, t\right)
\\
t\_s \cdot \frac{2}{{\left(\left(k\_m \cdot \frac{k\_m}{\ell}\right) \cdot \sqrt{t\_m}\right)}^{2}}
\end{array}
Initial program 38.4%
*-commutative38.4%
associate-/r*38.4%
Simplified46.8%
+-rgt-identity46.8%
associate-/l/46.9%
div-inv46.9%
+-rgt-identity46.9%
metadata-eval46.9%
metadata-eval46.9%
associate-+l+38.4%
sub-neg38.4%
+-commutative38.4%
add-sqr-sqrt18.8%
Applied egg-rr32.8%
associate-*r/32.8%
metadata-eval32.8%
*-commutative32.8%
associate-*l*32.9%
Simplified32.9%
Taylor expanded in k around 0 39.2%
unpow239.2%
add-sqr-sqrt20.1%
times-frac20.5%
Applied egg-rr20.5%
unpow220.5%
Simplified20.5%
unpow220.5%
frac-times20.1%
add-sqr-sqrt39.2%
associate-*r/39.9%
*-commutative39.9%
Applied egg-rr39.9%
Final simplification39.9%
k_m = (fabs.f64 k) t\_m = (fabs.f64 t) t\_s = (copysign.f64 #s(literal 1 binary64) t) (FPCore (t_s t_m l k_m) :precision binary64 (* t_s (/ (/ 2.0 t_m) (pow (/ k_m (sqrt l)) 4.0))))
k_m = fabs(k);
t\_m = fabs(t);
t\_s = copysign(1.0, t);
double code(double t_s, double t_m, double l, double k_m) {
return t_s * ((2.0 / t_m) / pow((k_m / sqrt(l)), 4.0));
}
k_m = abs(k)
t\_m = abs(t)
t\_s = copysign(1.0d0, t)
real(8) function code(t_s, t_m, l, k_m)
real(8), intent (in) :: t_s
real(8), intent (in) :: t_m
real(8), intent (in) :: l
real(8), intent (in) :: k_m
code = t_s * ((2.0d0 / t_m) / ((k_m / sqrt(l)) ** 4.0d0))
end function
k_m = Math.abs(k);
t\_m = Math.abs(t);
t\_s = Math.copySign(1.0, t);
public static double code(double t_s, double t_m, double l, double k_m) {
return t_s * ((2.0 / t_m) / Math.pow((k_m / Math.sqrt(l)), 4.0));
}
k_m = math.fabs(k) t\_m = math.fabs(t) t\_s = math.copysign(1.0, t) def code(t_s, t_m, l, k_m): return t_s * ((2.0 / t_m) / math.pow((k_m / math.sqrt(l)), 4.0))
k_m = abs(k) t\_m = abs(t) t\_s = copysign(1.0, t) function code(t_s, t_m, l, k_m) return Float64(t_s * Float64(Float64(2.0 / t_m) / (Float64(k_m / sqrt(l)) ^ 4.0))) end
k_m = abs(k); t\_m = abs(t); t\_s = sign(t) * abs(1.0); function tmp = code(t_s, t_m, l, k_m) tmp = t_s * ((2.0 / t_m) / ((k_m / sqrt(l)) ^ 4.0)); end
k_m = N[Abs[k], $MachinePrecision]
t\_m = N[Abs[t], $MachinePrecision]
t\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[t]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[t$95$s_, t$95$m_, l_, k$95$m_] := N[(t$95$s * N[(N[(2.0 / t$95$m), $MachinePrecision] / N[Power[N[(k$95$m / N[Sqrt[l], $MachinePrecision]), $MachinePrecision], 4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
k_m = \left|k\right|
\\
t\_m = \left|t\right|
\\
t\_s = \mathsf{copysign}\left(1, t\right)
\\
t\_s \cdot \frac{\frac{2}{t\_m}}{{\left(\frac{k\_m}{\sqrt{\ell}}\right)}^{4}}
\end{array}
Initial program 38.4%
*-commutative38.4%
associate-/r*38.4%
Simplified46.8%
+-rgt-identity46.8%
associate-/l/46.9%
div-inv46.9%
+-rgt-identity46.9%
metadata-eval46.9%
metadata-eval46.9%
associate-+l+38.4%
sub-neg38.4%
+-commutative38.4%
add-sqr-sqrt18.8%
Applied egg-rr32.8%
associate-*r/32.8%
metadata-eval32.8%
*-commutative32.8%
associate-*l*32.9%
Simplified32.9%
Taylor expanded in k around 0 39.2%
unpow239.2%
*-un-lft-identity39.2%
metadata-eval39.2%
times-frac39.9%
metadata-eval39.9%
Applied egg-rr39.9%
*-un-lft-identity39.9%
add-sqr-sqrt39.9%
pow239.9%
Applied egg-rr37.1%
*-lft-identity37.1%
associate-/r*37.5%
Simplified37.5%
k_m = (fabs.f64 k) t\_m = (fabs.f64 t) t\_s = (copysign.f64 #s(literal 1 binary64) t) (FPCore (t_s t_m l k_m) :precision binary64 (* t_s (/ 2.0 (* t_m (pow (/ k_m (sqrt l)) 4.0)))))
k_m = fabs(k);
t\_m = fabs(t);
t\_s = copysign(1.0, t);
double code(double t_s, double t_m, double l, double k_m) {
return t_s * (2.0 / (t_m * pow((k_m / sqrt(l)), 4.0)));
}
k_m = abs(k)
t\_m = abs(t)
t\_s = copysign(1.0d0, t)
real(8) function code(t_s, t_m, l, k_m)
real(8), intent (in) :: t_s
real(8), intent (in) :: t_m
real(8), intent (in) :: l
real(8), intent (in) :: k_m
code = t_s * (2.0d0 / (t_m * ((k_m / sqrt(l)) ** 4.0d0)))
end function
k_m = Math.abs(k);
t\_m = Math.abs(t);
t\_s = Math.copySign(1.0, t);
public static double code(double t_s, double t_m, double l, double k_m) {
return t_s * (2.0 / (t_m * Math.pow((k_m / Math.sqrt(l)), 4.0)));
}
k_m = math.fabs(k) t\_m = math.fabs(t) t\_s = math.copysign(1.0, t) def code(t_s, t_m, l, k_m): return t_s * (2.0 / (t_m * math.pow((k_m / math.sqrt(l)), 4.0)))
k_m = abs(k) t\_m = abs(t) t\_s = copysign(1.0, t) function code(t_s, t_m, l, k_m) return Float64(t_s * Float64(2.0 / Float64(t_m * (Float64(k_m / sqrt(l)) ^ 4.0)))) end
k_m = abs(k); t\_m = abs(t); t\_s = sign(t) * abs(1.0); function tmp = code(t_s, t_m, l, k_m) tmp = t_s * (2.0 / (t_m * ((k_m / sqrt(l)) ^ 4.0))); end
k_m = N[Abs[k], $MachinePrecision]
t\_m = N[Abs[t], $MachinePrecision]
t\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[t]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[t$95$s_, t$95$m_, l_, k$95$m_] := N[(t$95$s * N[(2.0 / N[(t$95$m * N[Power[N[(k$95$m / N[Sqrt[l], $MachinePrecision]), $MachinePrecision], 4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
k_m = \left|k\right|
\\
t\_m = \left|t\right|
\\
t\_s = \mathsf{copysign}\left(1, t\right)
\\
t\_s \cdot \frac{2}{t\_m \cdot {\left(\frac{k\_m}{\sqrt{\ell}}\right)}^{4}}
\end{array}
Initial program 38.4%
*-commutative38.4%
associate-/r*38.4%
Simplified46.8%
+-rgt-identity46.8%
associate-/l/46.9%
div-inv46.9%
+-rgt-identity46.9%
metadata-eval46.9%
metadata-eval46.9%
associate-+l+38.4%
sub-neg38.4%
+-commutative38.4%
add-sqr-sqrt18.8%
Applied egg-rr32.8%
associate-*r/32.8%
metadata-eval32.8%
*-commutative32.8%
associate-*l*32.9%
Simplified32.9%
Taylor expanded in k around 0 39.2%
unpow239.2%
*-un-lft-identity39.2%
metadata-eval39.2%
times-frac39.9%
metadata-eval39.9%
Applied egg-rr39.9%
unpow-prod-down37.9%
frac-times37.9%
*-un-lft-identity37.9%
add-sqr-sqrt19.2%
frac-times19.2%
unpow219.2%
pow219.2%
add-sqr-sqrt37.1%
pow-pow37.1%
metadata-eval37.1%
Applied egg-rr37.1%
Final simplification37.1%
k_m = (fabs.f64 k) t\_m = (fabs.f64 t) t\_s = (copysign.f64 #s(literal 1 binary64) t) (FPCore (t_s t_m l k_m) :precision binary64 (* t_s (* (* (/ 2.0 t_m) (pow k_m -4.0)) (* l l))))
k_m = fabs(k);
t\_m = fabs(t);
t\_s = copysign(1.0, t);
double code(double t_s, double t_m, double l, double k_m) {
return t_s * (((2.0 / t_m) * pow(k_m, -4.0)) * (l * l));
}
k_m = abs(k)
t\_m = abs(t)
t\_s = copysign(1.0d0, t)
real(8) function code(t_s, t_m, l, k_m)
real(8), intent (in) :: t_s
real(8), intent (in) :: t_m
real(8), intent (in) :: l
real(8), intent (in) :: k_m
code = t_s * (((2.0d0 / t_m) * (k_m ** (-4.0d0))) * (l * l))
end function
k_m = Math.abs(k);
t\_m = Math.abs(t);
t\_s = Math.copySign(1.0, t);
public static double code(double t_s, double t_m, double l, double k_m) {
return t_s * (((2.0 / t_m) * Math.pow(k_m, -4.0)) * (l * l));
}
k_m = math.fabs(k) t\_m = math.fabs(t) t\_s = math.copysign(1.0, t) def code(t_s, t_m, l, k_m): return t_s * (((2.0 / t_m) * math.pow(k_m, -4.0)) * (l * l))
k_m = abs(k) t\_m = abs(t) t\_s = copysign(1.0, t) function code(t_s, t_m, l, k_m) return Float64(t_s * Float64(Float64(Float64(2.0 / t_m) * (k_m ^ -4.0)) * Float64(l * l))) end
k_m = abs(k); t\_m = abs(t); t\_s = sign(t) * abs(1.0); function tmp = code(t_s, t_m, l, k_m) tmp = t_s * (((2.0 / t_m) * (k_m ^ -4.0)) * (l * l)); end
k_m = N[Abs[k], $MachinePrecision]
t\_m = N[Abs[t], $MachinePrecision]
t\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[t]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[t$95$s_, t$95$m_, l_, k$95$m_] := N[(t$95$s * N[(N[(N[(2.0 / t$95$m), $MachinePrecision] * N[Power[k$95$m, -4.0], $MachinePrecision]), $MachinePrecision] * N[(l * l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
k_m = \left|k\right|
\\
t\_m = \left|t\right|
\\
t\_s = \mathsf{copysign}\left(1, t\right)
\\
t\_s \cdot \left(\left(\frac{2}{t\_m} \cdot {k\_m}^{-4}\right) \cdot \left(\ell \cdot \ell\right)\right)
\end{array}
Initial program 38.4%
Simplified46.4%
Taylor expanded in k around 0 66.4%
*-commutative66.4%
associate-/r*66.4%
Simplified66.4%
div-inv66.4%
pow-flip66.4%
metadata-eval66.4%
Applied egg-rr66.4%
herbie shell --seed 2024103
(FPCore (t l k)
:name "Toniolo and Linder, Equation (10-)"
:precision binary64
(/ 2.0 (* (* (* (/ (pow t 3.0) (* l l)) (sin k)) (tan k)) (- (+ 1.0 (pow (/ k t) 2.0)) 1.0))))