
(FPCore (f) :precision binary64 (let* ((t_0 (* (/ PI 4.0) f)) (t_1 (exp t_0)) (t_2 (exp (- t_0)))) (- (* (/ 1.0 (/ PI 4.0)) (log (/ (+ t_1 t_2) (- t_1 t_2)))))))
double code(double f) {
double t_0 = (((double) M_PI) / 4.0) * f;
double t_1 = exp(t_0);
double t_2 = exp(-t_0);
return -((1.0 / (((double) M_PI) / 4.0)) * log(((t_1 + t_2) / (t_1 - t_2))));
}
public static double code(double f) {
double t_0 = (Math.PI / 4.0) * f;
double t_1 = Math.exp(t_0);
double t_2 = Math.exp(-t_0);
return -((1.0 / (Math.PI / 4.0)) * Math.log(((t_1 + t_2) / (t_1 - t_2))));
}
def code(f): t_0 = (math.pi / 4.0) * f t_1 = math.exp(t_0) t_2 = math.exp(-t_0) return -((1.0 / (math.pi / 4.0)) * math.log(((t_1 + t_2) / (t_1 - t_2))))
function code(f) t_0 = Float64(Float64(pi / 4.0) * f) t_1 = exp(t_0) t_2 = exp(Float64(-t_0)) return Float64(-Float64(Float64(1.0 / Float64(pi / 4.0)) * log(Float64(Float64(t_1 + t_2) / Float64(t_1 - t_2))))) end
function tmp = code(f) t_0 = (pi / 4.0) * f; t_1 = exp(t_0); t_2 = exp(-t_0); tmp = -((1.0 / (pi / 4.0)) * log(((t_1 + t_2) / (t_1 - t_2)))); end
code[f_] := Block[{t$95$0 = N[(N[(Pi / 4.0), $MachinePrecision] * f), $MachinePrecision]}, Block[{t$95$1 = N[Exp[t$95$0], $MachinePrecision]}, Block[{t$95$2 = N[Exp[(-t$95$0)], $MachinePrecision]}, (-N[(N[(1.0 / N[(Pi / 4.0), $MachinePrecision]), $MachinePrecision] * N[Log[N[(N[(t$95$1 + t$95$2), $MachinePrecision] / N[(t$95$1 - t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision])]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{\pi}{4} \cdot f\\
t_1 := e^{t\_0}\\
t_2 := e^{-t\_0}\\
-\frac{1}{\frac{\pi}{4}} \cdot \log \left(\frac{t\_1 + t\_2}{t\_1 - t\_2}\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 8 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (f) :precision binary64 (let* ((t_0 (* (/ PI 4.0) f)) (t_1 (exp t_0)) (t_2 (exp (- t_0)))) (- (* (/ 1.0 (/ PI 4.0)) (log (/ (+ t_1 t_2) (- t_1 t_2)))))))
double code(double f) {
double t_0 = (((double) M_PI) / 4.0) * f;
double t_1 = exp(t_0);
double t_2 = exp(-t_0);
return -((1.0 / (((double) M_PI) / 4.0)) * log(((t_1 + t_2) / (t_1 - t_2))));
}
public static double code(double f) {
double t_0 = (Math.PI / 4.0) * f;
double t_1 = Math.exp(t_0);
double t_2 = Math.exp(-t_0);
return -((1.0 / (Math.PI / 4.0)) * Math.log(((t_1 + t_2) / (t_1 - t_2))));
}
def code(f): t_0 = (math.pi / 4.0) * f t_1 = math.exp(t_0) t_2 = math.exp(-t_0) return -((1.0 / (math.pi / 4.0)) * math.log(((t_1 + t_2) / (t_1 - t_2))))
function code(f) t_0 = Float64(Float64(pi / 4.0) * f) t_1 = exp(t_0) t_2 = exp(Float64(-t_0)) return Float64(-Float64(Float64(1.0 / Float64(pi / 4.0)) * log(Float64(Float64(t_1 + t_2) / Float64(t_1 - t_2))))) end
function tmp = code(f) t_0 = (pi / 4.0) * f; t_1 = exp(t_0); t_2 = exp(-t_0); tmp = -((1.0 / (pi / 4.0)) * log(((t_1 + t_2) / (t_1 - t_2)))); end
code[f_] := Block[{t$95$0 = N[(N[(Pi / 4.0), $MachinePrecision] * f), $MachinePrecision]}, Block[{t$95$1 = N[Exp[t$95$0], $MachinePrecision]}, Block[{t$95$2 = N[Exp[(-t$95$0)], $MachinePrecision]}, (-N[(N[(1.0 / N[(Pi / 4.0), $MachinePrecision]), $MachinePrecision] * N[Log[N[(N[(t$95$1 + t$95$2), $MachinePrecision] / N[(t$95$1 - t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision])]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{\pi}{4} \cdot f\\
t_1 := e^{t\_0}\\
t_2 := e^{-t\_0}\\
-\frac{1}{\frac{\pi}{4}} \cdot \log \left(\frac{t\_1 + t\_2}{t\_1 - t\_2}\right)
\end{array}
\end{array}
(FPCore (f) :precision binary64 (/ (/ (log (/ 1.0 (tanh (/ (* PI f) 4.0)))) -0.25) PI))
double code(double f) {
return (log((1.0 / tanh(((((double) M_PI) * f) / 4.0)))) / -0.25) / ((double) M_PI);
}
public static double code(double f) {
return (Math.log((1.0 / Math.tanh(((Math.PI * f) / 4.0)))) / -0.25) / Math.PI;
}
def code(f): return (math.log((1.0 / math.tanh(((math.pi * f) / 4.0)))) / -0.25) / math.pi
function code(f) return Float64(Float64(log(Float64(1.0 / tanh(Float64(Float64(pi * f) / 4.0)))) / -0.25) / pi) end
function tmp = code(f) tmp = (log((1.0 / tanh(((pi * f) / 4.0)))) / -0.25) / pi; end
code[f_] := N[(N[(N[Log[N[(1.0 / N[Tanh[N[(N[(Pi * f), $MachinePrecision] / 4.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / -0.25), $MachinePrecision] / Pi), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{\log \left(\frac{1}{\tanh \left(\frac{\pi \cdot f}{4}\right)}\right)}{-0.25}}{\pi}
\end{array}
Initial program 5.1%
distribute-lft-neg-inN/A
distribute-neg-frac2N/A
associate-*l/N/A
*-lft-identityN/A
/-lowering-/.f64N/A
Simplified5.1%
clear-numN/A
associate-/r/N/A
associate-/r*N/A
/-lowering-/.f64N/A
Applied egg-rr99.5%
associate-/r/N/A
associate-*l/N/A
/-lowering-/.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6499.5%
Applied egg-rr99.5%
(FPCore (f) :precision binary64 (/ (/ (log (/ 1.0 (tanh (/ PI (/ 4.0 f))))) -0.25) PI))
double code(double f) {
return (log((1.0 / tanh((((double) M_PI) / (4.0 / f))))) / -0.25) / ((double) M_PI);
}
public static double code(double f) {
return (Math.log((1.0 / Math.tanh((Math.PI / (4.0 / f))))) / -0.25) / Math.PI;
}
def code(f): return (math.log((1.0 / math.tanh((math.pi / (4.0 / f))))) / -0.25) / math.pi
function code(f) return Float64(Float64(log(Float64(1.0 / tanh(Float64(pi / Float64(4.0 / f))))) / -0.25) / pi) end
function tmp = code(f) tmp = (log((1.0 / tanh((pi / (4.0 / f))))) / -0.25) / pi; end
code[f_] := N[(N[(N[Log[N[(1.0 / N[Tanh[N[(Pi / N[(4.0 / f), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / -0.25), $MachinePrecision] / Pi), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{\log \left(\frac{1}{\tanh \left(\frac{\pi}{\frac{4}{f}}\right)}\right)}{-0.25}}{\pi}
\end{array}
Initial program 5.1%
distribute-lft-neg-inN/A
distribute-neg-frac2N/A
associate-*l/N/A
*-lft-identityN/A
/-lowering-/.f64N/A
Simplified5.1%
clear-numN/A
associate-/r/N/A
associate-/r*N/A
/-lowering-/.f64N/A
Applied egg-rr99.5%
(FPCore (f) :precision binary64 (/ (/ (log (tanh (/ (* PI f) 4.0))) 0.25) PI))
double code(double f) {
return (log(tanh(((((double) M_PI) * f) / 4.0))) / 0.25) / ((double) M_PI);
}
public static double code(double f) {
return (Math.log(Math.tanh(((Math.PI * f) / 4.0))) / 0.25) / Math.PI;
}
def code(f): return (math.log(math.tanh(((math.pi * f) / 4.0))) / 0.25) / math.pi
function code(f) return Float64(Float64(log(tanh(Float64(Float64(pi * f) / 4.0))) / 0.25) / pi) end
function tmp = code(f) tmp = (log(tanh(((pi * f) / 4.0))) / 0.25) / pi; end
code[f_] := N[(N[(N[Log[N[Tanh[N[(N[(Pi * f), $MachinePrecision] / 4.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] / 0.25), $MachinePrecision] / Pi), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{\log \tanh \left(\frac{\pi \cdot f}{4}\right)}{0.25}}{\pi}
\end{array}
Initial program 5.1%
distribute-lft-neg-inN/A
distribute-neg-frac2N/A
associate-*l/N/A
*-lft-identityN/A
/-lowering-/.f64N/A
Simplified5.1%
clear-numN/A
associate-/r/N/A
associate-/r*N/A
/-lowering-/.f64N/A
Applied egg-rr99.5%
associate-/r/N/A
associate-*l/N/A
/-lowering-/.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6499.5%
Applied egg-rr99.5%
/-lowering-/.f64N/A
frac-2negN/A
log-recN/A
remove-double-negN/A
/-lowering-/.f64N/A
log-lowering-log.f64N/A
tanh-lowering-tanh.f64N/A
/-lowering-/.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
metadata-evalN/A
PI-lowering-PI.f6499.5%
Applied egg-rr99.5%
(FPCore (f) :precision binary64 (* (/ 4.0 PI) (log (tanh (/ PI (/ 4.0 f))))))
double code(double f) {
return (4.0 / ((double) M_PI)) * log(tanh((((double) M_PI) / (4.0 / f))));
}
public static double code(double f) {
return (4.0 / Math.PI) * Math.log(Math.tanh((Math.PI / (4.0 / f))));
}
def code(f): return (4.0 / math.pi) * math.log(math.tanh((math.pi / (4.0 / f))))
function code(f) return Float64(Float64(4.0 / pi) * log(tanh(Float64(pi / Float64(4.0 / f))))) end
function tmp = code(f) tmp = (4.0 / pi) * log(tanh((pi / (4.0 / f)))); end
code[f_] := N[(N[(4.0 / Pi), $MachinePrecision] * N[Log[N[Tanh[N[(Pi / N[(4.0 / f), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{4}{\pi} \cdot \log \tanh \left(\frac{\pi}{\frac{4}{f}}\right)
\end{array}
Initial program 5.1%
distribute-lft-neg-inN/A
distribute-neg-frac2N/A
associate-*l/N/A
*-lft-identityN/A
/-lowering-/.f64N/A
Simplified5.1%
clear-numN/A
frac-2negN/A
associate-/r/N/A
distribute-frac-neg2N/A
clear-numN/A
*-lowering-*.f64N/A
Applied egg-rr99.4%
(FPCore (f)
:precision binary64
(/
(/
(log
(/
(+
(/ 4.0 PI)
(*
(* f f)
(/ (* (* -16.0 (* PI (* PI PI))) -0.005208333333333333) (* PI PI))))
f))
-0.25)
PI))
double code(double f) {
return (log((((4.0 / ((double) M_PI)) + ((f * f) * (((-16.0 * (((double) M_PI) * (((double) M_PI) * ((double) M_PI)))) * -0.005208333333333333) / (((double) M_PI) * ((double) M_PI))))) / f)) / -0.25) / ((double) M_PI);
}
public static double code(double f) {
return (Math.log((((4.0 / Math.PI) + ((f * f) * (((-16.0 * (Math.PI * (Math.PI * Math.PI))) * -0.005208333333333333) / (Math.PI * Math.PI)))) / f)) / -0.25) / Math.PI;
}
def code(f): return (math.log((((4.0 / math.pi) + ((f * f) * (((-16.0 * (math.pi * (math.pi * math.pi))) * -0.005208333333333333) / (math.pi * math.pi)))) / f)) / -0.25) / math.pi
function code(f) return Float64(Float64(log(Float64(Float64(Float64(4.0 / pi) + Float64(Float64(f * f) * Float64(Float64(Float64(-16.0 * Float64(pi * Float64(pi * pi))) * -0.005208333333333333) / Float64(pi * pi)))) / f)) / -0.25) / pi) end
function tmp = code(f) tmp = (log((((4.0 / pi) + ((f * f) * (((-16.0 * (pi * (pi * pi))) * -0.005208333333333333) / (pi * pi)))) / f)) / -0.25) / pi; end
code[f_] := N[(N[(N[Log[N[(N[(N[(4.0 / Pi), $MachinePrecision] + N[(N[(f * f), $MachinePrecision] * N[(N[(N[(-16.0 * N[(Pi * N[(Pi * Pi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * -0.005208333333333333), $MachinePrecision] / N[(Pi * Pi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / f), $MachinePrecision]], $MachinePrecision] / -0.25), $MachinePrecision] / Pi), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{\log \left(\frac{\frac{4}{\pi} + \left(f \cdot f\right) \cdot \frac{\left(-16 \cdot \left(\pi \cdot \left(\pi \cdot \pi\right)\right)\right) \cdot -0.005208333333333333}{\pi \cdot \pi}}{f}\right)}{-0.25}}{\pi}
\end{array}
Initial program 5.1%
distribute-lft-neg-inN/A
distribute-neg-frac2N/A
associate-*l/N/A
*-lft-identityN/A
/-lowering-/.f64N/A
Simplified5.1%
clear-numN/A
associate-/r/N/A
associate-/r*N/A
/-lowering-/.f64N/A
Applied egg-rr99.5%
Taylor expanded in f around 0
Simplified96.7%
Taylor expanded in f around 0
/-lowering-/.f64N/A
Simplified96.7%
(FPCore (f) :precision binary64 (/ (log (/ (/ 4.0 PI) f)) (/ PI -4.0)))
double code(double f) {
return log(((4.0 / ((double) M_PI)) / f)) / (((double) M_PI) / -4.0);
}
public static double code(double f) {
return Math.log(((4.0 / Math.PI) / f)) / (Math.PI / -4.0);
}
def code(f): return math.log(((4.0 / math.pi) / f)) / (math.pi / -4.0)
function code(f) return Float64(log(Float64(Float64(4.0 / pi) / f)) / Float64(pi / -4.0)) end
function tmp = code(f) tmp = log(((4.0 / pi) / f)) / (pi / -4.0); end
code[f_] := N[(N[Log[N[(N[(4.0 / Pi), $MachinePrecision] / f), $MachinePrecision]], $MachinePrecision] / N[(Pi / -4.0), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\log \left(\frac{\frac{4}{\pi}}{f}\right)}{\frac{\pi}{-4}}
\end{array}
Initial program 5.1%
distribute-lft-neg-inN/A
distribute-neg-frac2N/A
associate-*l/N/A
*-lft-identityN/A
/-lowering-/.f64N/A
Simplified5.1%
Taylor expanded in f around 0
*-commutativeN/A
associate-/r*N/A
metadata-evalN/A
associate-*r/N/A
/-lowering-/.f64N/A
associate-*r/N/A
metadata-evalN/A
/-lowering-/.f64N/A
distribute-rgt-out--N/A
metadata-evalN/A
*-lowering-*.f64N/A
PI-lowering-PI.f6496.4%
Simplified96.4%
/-lowering-/.f64N/A
*-commutativeN/A
associate-/r*N/A
metadata-evalN/A
/-lowering-/.f64N/A
PI-lowering-PI.f6496.4%
Applied egg-rr96.4%
(FPCore (f) :precision binary64 (/ -4.0 (/ PI (log (/ 4.0 (* PI f))))))
double code(double f) {
return -4.0 / (((double) M_PI) / log((4.0 / (((double) M_PI) * f))));
}
public static double code(double f) {
return -4.0 / (Math.PI / Math.log((4.0 / (Math.PI * f))));
}
def code(f): return -4.0 / (math.pi / math.log((4.0 / (math.pi * f))))
function code(f) return Float64(-4.0 / Float64(pi / log(Float64(4.0 / Float64(pi * f))))) end
function tmp = code(f) tmp = -4.0 / (pi / log((4.0 / (pi * f)))); end
code[f_] := N[(-4.0 / N[(Pi / N[Log[N[(4.0 / N[(Pi * f), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{-4}{\frac{\pi}{\log \left(\frac{4}{\pi \cdot f}\right)}}
\end{array}
Initial program 5.1%
distribute-lft-neg-inN/A
distribute-neg-frac2N/A
associate-*l/N/A
*-lft-identityN/A
/-lowering-/.f64N/A
Simplified5.1%
clear-numN/A
associate-/r/N/A
associate-/r*N/A
/-lowering-/.f64N/A
Applied egg-rr99.5%
associate-/r/N/A
associate-*l/N/A
/-lowering-/.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6499.5%
Applied egg-rr99.5%
Taylor expanded in f around 0
*-commutativeN/A
associate-/r*N/A
metadata-evalN/A
associate-*r/N/A
/-lowering-/.f64N/A
associate-*r/N/A
metadata-evalN/A
/-lowering-/.f64N/A
PI-lowering-PI.f6496.4%
Simplified96.4%
div-invN/A
clear-numN/A
associate-/r*N/A
*-commutativeN/A
div-invN/A
associate-/r*N/A
metadata-evalN/A
frac-timesN/A
metadata-evalN/A
div-invN/A
/-lowering-/.f64N/A
/-lowering-/.f64N/A
PI-lowering-PI.f64N/A
log-lowering-log.f64N/A
/-lowering-/.f64N/A
Applied egg-rr96.4%
(FPCore (f) :precision binary64 (* (/ -4.0 PI) (log (/ (/ 4.0 f) PI))))
double code(double f) {
return (-4.0 / ((double) M_PI)) * log(((4.0 / f) / ((double) M_PI)));
}
public static double code(double f) {
return (-4.0 / Math.PI) * Math.log(((4.0 / f) / Math.PI));
}
def code(f): return (-4.0 / math.pi) * math.log(((4.0 / f) / math.pi))
function code(f) return Float64(Float64(-4.0 / pi) * log(Float64(Float64(4.0 / f) / pi))) end
function tmp = code(f) tmp = (-4.0 / pi) * log(((4.0 / f) / pi)); end
code[f_] := N[(N[(-4.0 / Pi), $MachinePrecision] * N[Log[N[(N[(4.0 / f), $MachinePrecision] / Pi), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{-4}{\pi} \cdot \log \left(\frac{\frac{4}{f}}{\pi}\right)
\end{array}
Initial program 5.1%
distribute-lft-neg-inN/A
distribute-neg-frac2N/A
associate-*l/N/A
*-lft-identityN/A
/-lowering-/.f64N/A
Simplified5.1%
Taylor expanded in f around 0
*-commutativeN/A
associate-/r*N/A
metadata-evalN/A
associate-*r/N/A
/-lowering-/.f64N/A
associate-*r/N/A
metadata-evalN/A
/-lowering-/.f64N/A
distribute-rgt-out--N/A
metadata-evalN/A
*-lowering-*.f64N/A
PI-lowering-PI.f6496.4%
Simplified96.4%
diff-logN/A
clear-numN/A
associate-/r/N/A
clear-numN/A
*-lowering-*.f64N/A
/-lowering-/.f64N/A
PI-lowering-PI.f64N/A
diff-logN/A
div-invN/A
clear-numN/A
frac-timesN/A
metadata-evalN/A
associate-/l*N/A
metadata-evalN/A
metadata-evalN/A
div-invN/A
associate-/r/N/A
clear-numN/A
Applied egg-rr96.4%
herbie shell --seed 2024138
(FPCore (f)
:name "VandenBroeck and Keller, Equation (20)"
:precision binary64
(- (* (/ 1.0 (/ PI 4.0)) (log (/ (+ (exp (* (/ PI 4.0) f)) (exp (- (* (/ PI 4.0) f)))) (- (exp (* (/ PI 4.0) f)) (exp (- (* (/ PI 4.0) f)))))))))