
(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 5 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 1 t)
(FPCore (t_s t_m l k_m)
:precision binary64
(*
t_s
(if (<= k_m 1.5)
(/ 2.0 (pow (* (/ k_m (/ l (sin k_m))) (sqrt (/ t_m (cos k_m)))) 2.0))
(*
2.0
(* (pow (/ l k_m) 2.0) (/ (cos k_m) (* t_m (pow (sin k_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) {
double tmp;
if (k_m <= 1.5) {
tmp = 2.0 / pow(((k_m / (l / sin(k_m))) * sqrt((t_m / cos(k_m)))), 2.0);
} else {
tmp = 2.0 * (pow((l / k_m), 2.0) * (cos(k_m) / (t_m * pow(sin(k_m), 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 <= 1.5d0) then
tmp = 2.0d0 / (((k_m / (l / sin(k_m))) * sqrt((t_m / cos(k_m)))) ** 2.0d0)
else
tmp = 2.0d0 * (((l / k_m) ** 2.0d0) * (cos(k_m) / (t_m * (sin(k_m) ** 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 <= 1.5) {
tmp = 2.0 / Math.pow(((k_m / (l / Math.sin(k_m))) * Math.sqrt((t_m / Math.cos(k_m)))), 2.0);
} else {
tmp = 2.0 * (Math.pow((l / k_m), 2.0) * (Math.cos(k_m) / (t_m * Math.pow(Math.sin(k_m), 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 <= 1.5: tmp = 2.0 / math.pow(((k_m / (l / math.sin(k_m))) * math.sqrt((t_m / math.cos(k_m)))), 2.0) else: tmp = 2.0 * (math.pow((l / k_m), 2.0) * (math.cos(k_m) / (t_m * math.pow(math.sin(k_m), 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 <= 1.5) tmp = Float64(2.0 / (Float64(Float64(k_m / Float64(l / sin(k_m))) * sqrt(Float64(t_m / cos(k_m)))) ^ 2.0)); else tmp = Float64(2.0 * Float64((Float64(l / k_m) ^ 2.0) * Float64(cos(k_m) / Float64(t_m * (sin(k_m) ^ 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 <= 1.5) tmp = 2.0 / (((k_m / (l / sin(k_m))) * sqrt((t_m / cos(k_m)))) ^ 2.0); else tmp = 2.0 * (((l / k_m) ^ 2.0) * (cos(k_m) / (t_m * (sin(k_m) ^ 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, 1.5], N[(2.0 / N[Power[N[(N[(k$95$m / N[(l / N[Sin[k$95$m], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[(t$95$m / N[Cos[k$95$m], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision], N[(2.0 * N[(N[Power[N[(l / k$95$m), $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[k$95$m], $MachinePrecision] / N[(t$95$m * N[Power[N[Sin[k$95$m], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $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 1.5:\\
\;\;\;\;\frac{2}{{\left(\frac{k_m}{\frac{\ell}{\sin k_m}} \cdot \sqrt{\frac{t_m}{\cos k_m}}\right)}^{2}}\\
\mathbf{else}:\\
\;\;\;\;2 \cdot \left({\left(\frac{\ell}{k_m}\right)}^{2} \cdot \frac{\cos k_m}{t_m \cdot {\sin k_m}^{2}}\right)\\
\end{array}
\end{array}
if k < 1.5Initial program 37.4%
Applied egg-rr22.6%
unpow222.6%
pow-sqr22.6%
associate-*l/23.1%
associate-*r/23.6%
associate-*r/24.1%
metadata-eval24.1%
Simplified24.1%
Taylor expanded in k around inf 34.0%
sqrt-pow138.6%
associate-/l*39.1%
metadata-eval39.1%
Applied egg-rr39.1%
if 1.5 < k Initial program 38.7%
associate-/r*38.7%
*-commutative38.7%
associate-*l*38.6%
associate-*l/38.6%
+-commutative38.6%
unpow238.6%
sqr-neg38.6%
distribute-frac-neg38.6%
distribute-frac-neg38.6%
unpow238.6%
associate--l+52.0%
metadata-eval52.0%
+-rgt-identity52.0%
unpow252.0%
distribute-frac-neg52.0%
distribute-frac-neg52.0%
Simplified52.0%
Taylor expanded in k around inf 70.6%
times-frac72.3%
Simplified72.3%
associate-*r/72.3%
div-inv72.2%
pow-flip72.5%
metadata-eval72.5%
Applied egg-rr72.5%
add-sqr-sqrt72.5%
pow272.5%
sqrt-prod72.4%
unpow272.4%
sqrt-prod41.8%
add-sqr-sqrt80.7%
Applied egg-rr80.7%
Taylor expanded in l around 0 70.6%
times-frac72.3%
unpow272.3%
unpow272.3%
times-frac96.4%
*-lft-identity96.4%
associate-*l/96.3%
*-lft-identity96.3%
associate-*l/96.2%
unpow196.2%
pow-plus96.2%
associate-*l/96.4%
*-lft-identity96.4%
metadata-eval96.4%
Simplified96.4%
Final simplification52.5%
k_m = (fabs.f64 k)
t_m = (fabs.f64 t)
t_s = (copysign.f64 1 t)
(FPCore (t_s t_m l k_m)
:precision binary64
(let* ((t_2 (/ t_m (cos k_m))))
(*
t_s
(if (<= t_m 1.9e-261)
(/ 2.0 (pow (* (/ k_m (/ l (sin k_m))) (sqrt t_2)) 2.0))
(/ 2.0 (* t_2 (pow (* (sin k_m) (/ k_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 t_2 = t_m / cos(k_m);
double tmp;
if (t_m <= 1.9e-261) {
tmp = 2.0 / pow(((k_m / (l / sin(k_m))) * sqrt(t_2)), 2.0);
} else {
tmp = 2.0 / (t_2 * pow((sin(k_m) * (k_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) :: t_2
real(8) :: tmp
t_2 = t_m / cos(k_m)
if (t_m <= 1.9d-261) then
tmp = 2.0d0 / (((k_m / (l / sin(k_m))) * sqrt(t_2)) ** 2.0d0)
else
tmp = 2.0d0 / (t_2 * ((sin(k_m) * (k_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 t_2 = t_m / Math.cos(k_m);
double tmp;
if (t_m <= 1.9e-261) {
tmp = 2.0 / Math.pow(((k_m / (l / Math.sin(k_m))) * Math.sqrt(t_2)), 2.0);
} else {
tmp = 2.0 / (t_2 * Math.pow((Math.sin(k_m) * (k_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): t_2 = t_m / math.cos(k_m) tmp = 0 if t_m <= 1.9e-261: tmp = 2.0 / math.pow(((k_m / (l / math.sin(k_m))) * math.sqrt(t_2)), 2.0) else: tmp = 2.0 / (t_2 * math.pow((math.sin(k_m) * (k_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) t_2 = Float64(t_m / cos(k_m)) tmp = 0.0 if (t_m <= 1.9e-261) tmp = Float64(2.0 / (Float64(Float64(k_m / Float64(l / sin(k_m))) * sqrt(t_2)) ^ 2.0)); else tmp = Float64(2.0 / Float64(t_2 * (Float64(sin(k_m) * Float64(k_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) t_2 = t_m / cos(k_m); tmp = 0.0; if (t_m <= 1.9e-261) tmp = 2.0 / (((k_m / (l / sin(k_m))) * sqrt(t_2)) ^ 2.0); else tmp = 2.0 / (t_2 * ((sin(k_m) * (k_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_] := Block[{t$95$2 = N[(t$95$m / N[Cos[k$95$m], $MachinePrecision]), $MachinePrecision]}, N[(t$95$s * If[LessEqual[t$95$m, 1.9e-261], N[(2.0 / N[Power[N[(N[(k$95$m / N[(l / N[Sin[k$95$m], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[t$95$2], $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision], N[(2.0 / N[(t$95$2 * N[Power[N[(N[Sin[k$95$m], $MachinePrecision] * N[(k$95$m / l), $MachinePrecision]), $MachinePrecision], 2.0], $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)
\\
\begin{array}{l}
t_2 := \frac{t_m}{\cos k_m}\\
t_s \cdot \begin{array}{l}
\mathbf{if}\;t_m \leq 1.9 \cdot 10^{-261}:\\
\;\;\;\;\frac{2}{{\left(\frac{k_m}{\frac{\ell}{\sin k_m}} \cdot \sqrt{t_2}\right)}^{2}}\\
\mathbf{else}:\\
\;\;\;\;\frac{2}{t_2 \cdot {\left(\sin k_m \cdot \frac{k_m}{\ell}\right)}^{2}}\\
\end{array}
\end{array}
\end{array}
if t < 1.9e-261Initial program 37.2%
Applied egg-rr1.4%
unpow21.4%
pow-sqr1.4%
associate-*l/1.4%
associate-*r/1.4%
associate-*r/1.4%
metadata-eval1.4%
Simplified1.4%
Taylor expanded in k around inf 21.0%
sqrt-pow124.5%
associate-/l*24.5%
metadata-eval24.5%
Applied egg-rr24.5%
if 1.9e-261 < t Initial program 38.4%
Applied egg-rr48.5%
unpow248.5%
pow-sqr48.5%
associate-*l/50.4%
associate-*r/51.4%
associate-*r/52.3%
metadata-eval52.3%
Simplified52.3%
Taylor expanded in k around inf 56.2%
expm1-log1p-u55.9%
expm1-udef52.2%
sqrt-pow155.5%
*-commutative55.5%
metadata-eval55.5%
unpow-prod-down55.5%
pow255.5%
add-sqr-sqrt55.5%
associate-/l*55.5%
Applied egg-rr55.5%
expm1-def71.7%
expm1-log1p96.0%
associate-/r/96.0%
Simplified96.0%
Final simplification53.0%
k_m = (fabs.f64 k) t_m = (fabs.f64 t) t_s = (copysign.f64 1 t) (FPCore (t_s t_m l k_m) :precision binary64 (* t_s (/ 2.0 (* (/ t_m (cos k_m)) (pow (* (sin k_m) (/ k_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) {
return t_s * (2.0 / ((t_m / cos(k_m)) * pow((sin(k_m) * (k_m / l)), 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 / ((t_m / cos(k_m)) * ((sin(k_m) * (k_m / l)) ** 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 / ((t_m / Math.cos(k_m)) * Math.pow((Math.sin(k_m) * (k_m / l)), 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 / ((t_m / math.cos(k_m)) * math.pow((math.sin(k_m) * (k_m / l)), 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(t_m / cos(k_m)) * (Float64(sin(k_m) * Float64(k_m / l)) ^ 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 / ((t_m / cos(k_m)) * ((sin(k_m) * (k_m / l)) ^ 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[(N[(t$95$m / N[Cos[k$95$m], $MachinePrecision]), $MachinePrecision] * N[Power[N[(N[Sin[k$95$m], $MachinePrecision] * N[(k$95$m / l), $MachinePrecision]), $MachinePrecision], 2.0], $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}{\frac{t_m}{\cos k_m} \cdot {\left(\sin k_m \cdot \frac{k_m}{\ell}\right)}^{2}}
\end{array}
Initial program 37.7%
Applied egg-rr20.1%
unpow220.1%
pow-sqr20.1%
associate-*l/20.9%
associate-*r/21.3%
associate-*r/21.7%
metadata-eval21.7%
Simplified21.7%
Taylor expanded in k around inf 35.0%
expm1-log1p-u34.7%
expm1-udef31.4%
sqrt-pow134.6%
*-commutative34.6%
metadata-eval34.6%
unpow-prod-down33.3%
pow233.3%
add-sqr-sqrt33.7%
associate-/l*33.7%
Applied egg-rr33.7%
expm1-def71.2%
expm1-log1p94.9%
associate-/r/94.9%
Simplified94.9%
Final simplification94.9%
k_m = (fabs.f64 k) t_m = (fabs.f64 t) t_s = (copysign.f64 1 t) (FPCore (t_s t_m l k_m) :precision binary64 (* t_s (* (/ 2.0 t_m) (pow (* l (sqrt (pow k_m -4.0))) 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 / t_m) * pow((l * sqrt(pow(k_m, -4.0))), 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 / t_m) * ((l * sqrt((k_m ** (-4.0d0)))) ** 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 / t_m) * Math.pow((l * Math.sqrt(Math.pow(k_m, -4.0))), 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 / t_m) * math.pow((l * math.sqrt(math.pow(k_m, -4.0))), 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(Float64(2.0 / t_m) * (Float64(l * sqrt((k_m ^ -4.0))) ^ 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 / t_m) * ((l * sqrt((k_m ^ -4.0))) ^ 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[(N[(2.0 / t$95$m), $MachinePrecision] * N[Power[N[(l * N[Sqrt[N[Power[k$95$m, -4.0], $MachinePrecision]], $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 \left(\frac{2}{t_m} \cdot {\left(\ell \cdot \sqrt{{k_m}^{-4}}\right)}^{2}\right)
\end{array}
Initial program 37.7%
+-commutative37.7%
associate--l+46.8%
metadata-eval46.8%
+-rgt-identity46.8%
unpow246.8%
div-inv46.7%
associate-*r*46.7%
Applied egg-rr46.7%
Taylor expanded in k around 0 62.5%
*-commutative62.5%
associate-/l*62.2%
Simplified62.2%
Taylor expanded in t around 0 62.5%
associate-*r/62.5%
*-commutative62.5%
times-frac62.3%
Simplified62.3%
add-sqr-sqrt62.2%
pow262.2%
div-inv62.2%
sqrt-prod62.2%
unpow262.2%
sqrt-prod37.5%
add-sqr-sqrt69.0%
pow-flip69.0%
metadata-eval69.0%
Applied egg-rr69.0%
Final simplification69.0%
k_m = (fabs.f64 k) t_m = (fabs.f64 t) t_s = (copysign.f64 1 t) (FPCore (t_s t_m l k_m) :precision binary64 (* t_s (* 2.0 (/ (pow l 2.0) (* t_m (pow k_m 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 * (pow(l, 2.0) / (t_m * pow(k_m, 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 * ((l ** 2.0d0) / (t_m * (k_m ** 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 * (Math.pow(l, 2.0) / (t_m * Math.pow(k_m, 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 * (math.pow(l, 2.0) / (t_m * math.pow(k_m, 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((l ^ 2.0) / Float64(t_m * (k_m ^ 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 * ((l ^ 2.0) / (t_m * (k_m ^ 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[(N[Power[l, 2.0], $MachinePrecision] / N[(t$95$m * N[Power[k$95$m, 4.0], $MachinePrecision]), $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 \left(2 \cdot \frac{{\ell}^{2}}{t_m \cdot {k_m}^{4}}\right)
\end{array}
Initial program 37.7%
associate-/r*37.7%
*-commutative37.7%
associate-*l*37.7%
associate-*l/38.1%
+-commutative38.1%
unpow238.1%
sqr-neg38.1%
distribute-frac-neg38.1%
distribute-frac-neg38.1%
unpow238.1%
associate--l+47.1%
metadata-eval47.1%
+-rgt-identity47.1%
unpow247.1%
distribute-frac-neg47.1%
distribute-frac-neg47.1%
Simplified47.1%
Taylor expanded in k around 0 62.5%
Final simplification62.5%
herbie shell --seed 2023334
(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))))