
(FPCore (z)
:precision binary64
(let* ((t_0 (- (- 1.0 z) 1.0)) (t_1 (+ t_0 7.0)) (t_2 (+ t_1 0.5)))
(*
(/ PI (sin (* PI z)))
(*
(* (* (sqrt (* PI 2.0)) (pow t_2 (+ t_0 0.5))) (exp (- t_2)))
(+
(+
(+
(+
(+
(+
(+
(+ 0.9999999999998099 (/ 676.5203681218851 (+ t_0 1.0)))
(/ -1259.1392167224028 (+ t_0 2.0)))
(/ 771.3234287776531 (+ t_0 3.0)))
(/ -176.6150291621406 (+ t_0 4.0)))
(/ 12.507343278686905 (+ t_0 5.0)))
(/ -0.13857109526572012 (+ t_0 6.0)))
(/ 9.984369578019572e-6 t_1))
(/ 1.5056327351493116e-7 (+ t_0 8.0)))))))
double code(double z) {
double t_0 = (1.0 - z) - 1.0;
double t_1 = t_0 + 7.0;
double t_2 = t_1 + 0.5;
return (((double) M_PI) / sin((((double) M_PI) * z))) * (((sqrt((((double) M_PI) * 2.0)) * pow(t_2, (t_0 + 0.5))) * exp(-t_2)) * ((((((((0.9999999999998099 + (676.5203681218851 / (t_0 + 1.0))) + (-1259.1392167224028 / (t_0 + 2.0))) + (771.3234287776531 / (t_0 + 3.0))) + (-176.6150291621406 / (t_0 + 4.0))) + (12.507343278686905 / (t_0 + 5.0))) + (-0.13857109526572012 / (t_0 + 6.0))) + (9.984369578019572e-6 / t_1)) + (1.5056327351493116e-7 / (t_0 + 8.0))));
}
public static double code(double z) {
double t_0 = (1.0 - z) - 1.0;
double t_1 = t_0 + 7.0;
double t_2 = t_1 + 0.5;
return (Math.PI / Math.sin((Math.PI * z))) * (((Math.sqrt((Math.PI * 2.0)) * Math.pow(t_2, (t_0 + 0.5))) * Math.exp(-t_2)) * ((((((((0.9999999999998099 + (676.5203681218851 / (t_0 + 1.0))) + (-1259.1392167224028 / (t_0 + 2.0))) + (771.3234287776531 / (t_0 + 3.0))) + (-176.6150291621406 / (t_0 + 4.0))) + (12.507343278686905 / (t_0 + 5.0))) + (-0.13857109526572012 / (t_0 + 6.0))) + (9.984369578019572e-6 / t_1)) + (1.5056327351493116e-7 / (t_0 + 8.0))));
}
def code(z): t_0 = (1.0 - z) - 1.0 t_1 = t_0 + 7.0 t_2 = t_1 + 0.5 return (math.pi / math.sin((math.pi * z))) * (((math.sqrt((math.pi * 2.0)) * math.pow(t_2, (t_0 + 0.5))) * math.exp(-t_2)) * ((((((((0.9999999999998099 + (676.5203681218851 / (t_0 + 1.0))) + (-1259.1392167224028 / (t_0 + 2.0))) + (771.3234287776531 / (t_0 + 3.0))) + (-176.6150291621406 / (t_0 + 4.0))) + (12.507343278686905 / (t_0 + 5.0))) + (-0.13857109526572012 / (t_0 + 6.0))) + (9.984369578019572e-6 / t_1)) + (1.5056327351493116e-7 / (t_0 + 8.0))))
function code(z) t_0 = Float64(Float64(1.0 - z) - 1.0) t_1 = Float64(t_0 + 7.0) t_2 = Float64(t_1 + 0.5) return Float64(Float64(pi / sin(Float64(pi * z))) * Float64(Float64(Float64(sqrt(Float64(pi * 2.0)) * (t_2 ^ Float64(t_0 + 0.5))) * exp(Float64(-t_2))) * Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(0.9999999999998099 + Float64(676.5203681218851 / Float64(t_0 + 1.0))) + Float64(-1259.1392167224028 / Float64(t_0 + 2.0))) + Float64(771.3234287776531 / Float64(t_0 + 3.0))) + Float64(-176.6150291621406 / Float64(t_0 + 4.0))) + Float64(12.507343278686905 / Float64(t_0 + 5.0))) + Float64(-0.13857109526572012 / Float64(t_0 + 6.0))) + Float64(9.984369578019572e-6 / t_1)) + Float64(1.5056327351493116e-7 / Float64(t_0 + 8.0))))) end
function tmp = code(z) t_0 = (1.0 - z) - 1.0; t_1 = t_0 + 7.0; t_2 = t_1 + 0.5; tmp = (pi / sin((pi * z))) * (((sqrt((pi * 2.0)) * (t_2 ^ (t_0 + 0.5))) * exp(-t_2)) * ((((((((0.9999999999998099 + (676.5203681218851 / (t_0 + 1.0))) + (-1259.1392167224028 / (t_0 + 2.0))) + (771.3234287776531 / (t_0 + 3.0))) + (-176.6150291621406 / (t_0 + 4.0))) + (12.507343278686905 / (t_0 + 5.0))) + (-0.13857109526572012 / (t_0 + 6.0))) + (9.984369578019572e-6 / t_1)) + (1.5056327351493116e-7 / (t_0 + 8.0)))); end
code[z_] := Block[{t$95$0 = N[(N[(1.0 - z), $MachinePrecision] - 1.0), $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 + 7.0), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 + 0.5), $MachinePrecision]}, N[(N[(Pi / N[Sin[N[(Pi * z), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(N[Sqrt[N[(Pi * 2.0), $MachinePrecision]], $MachinePrecision] * N[Power[t$95$2, N[(t$95$0 + 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Exp[(-t$95$2)], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(N[(N[(N[(N[(N[(0.9999999999998099 + N[(676.5203681218851 / N[(t$95$0 + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-1259.1392167224028 / N[(t$95$0 + 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(771.3234287776531 / N[(t$95$0 + 3.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-176.6150291621406 / N[(t$95$0 + 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(12.507343278686905 / N[(t$95$0 + 5.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-0.13857109526572012 / N[(t$95$0 + 6.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(9.984369578019572e-6 / t$95$1), $MachinePrecision]), $MachinePrecision] + N[(1.5056327351493116e-7 / N[(t$95$0 + 8.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \left(1 - z\right) - 1\\
t_1 := t\_0 + 7\\
t_2 := t\_1 + 0.5\\
\frac{\pi}{\sin \left(\pi \cdot z\right)} \cdot \left(\left(\left(\sqrt{\pi \cdot 2} \cdot {t\_2}^{\left(t\_0 + 0.5\right)}\right) \cdot e^{-t\_2}\right) \cdot \left(\left(\left(\left(\left(\left(\left(\left(0.9999999999998099 + \frac{676.5203681218851}{t\_0 + 1}\right) + \frac{-1259.1392167224028}{t\_0 + 2}\right) + \frac{771.3234287776531}{t\_0 + 3}\right) + \frac{-176.6150291621406}{t\_0 + 4}\right) + \frac{12.507343278686905}{t\_0 + 5}\right) + \frac{-0.13857109526572012}{t\_0 + 6}\right) + \frac{9.984369578019572 \cdot 10^{-6}}{t\_1}\right) + \frac{1.5056327351493116 \cdot 10^{-7}}{t\_0 + 8}\right)\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 9 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (z)
:precision binary64
(let* ((t_0 (- (- 1.0 z) 1.0)) (t_1 (+ t_0 7.0)) (t_2 (+ t_1 0.5)))
(*
(/ PI (sin (* PI z)))
(*
(* (* (sqrt (* PI 2.0)) (pow t_2 (+ t_0 0.5))) (exp (- t_2)))
(+
(+
(+
(+
(+
(+
(+
(+ 0.9999999999998099 (/ 676.5203681218851 (+ t_0 1.0)))
(/ -1259.1392167224028 (+ t_0 2.0)))
(/ 771.3234287776531 (+ t_0 3.0)))
(/ -176.6150291621406 (+ t_0 4.0)))
(/ 12.507343278686905 (+ t_0 5.0)))
(/ -0.13857109526572012 (+ t_0 6.0)))
(/ 9.984369578019572e-6 t_1))
(/ 1.5056327351493116e-7 (+ t_0 8.0)))))))
double code(double z) {
double t_0 = (1.0 - z) - 1.0;
double t_1 = t_0 + 7.0;
double t_2 = t_1 + 0.5;
return (((double) M_PI) / sin((((double) M_PI) * z))) * (((sqrt((((double) M_PI) * 2.0)) * pow(t_2, (t_0 + 0.5))) * exp(-t_2)) * ((((((((0.9999999999998099 + (676.5203681218851 / (t_0 + 1.0))) + (-1259.1392167224028 / (t_0 + 2.0))) + (771.3234287776531 / (t_0 + 3.0))) + (-176.6150291621406 / (t_0 + 4.0))) + (12.507343278686905 / (t_0 + 5.0))) + (-0.13857109526572012 / (t_0 + 6.0))) + (9.984369578019572e-6 / t_1)) + (1.5056327351493116e-7 / (t_0 + 8.0))));
}
public static double code(double z) {
double t_0 = (1.0 - z) - 1.0;
double t_1 = t_0 + 7.0;
double t_2 = t_1 + 0.5;
return (Math.PI / Math.sin((Math.PI * z))) * (((Math.sqrt((Math.PI * 2.0)) * Math.pow(t_2, (t_0 + 0.5))) * Math.exp(-t_2)) * ((((((((0.9999999999998099 + (676.5203681218851 / (t_0 + 1.0))) + (-1259.1392167224028 / (t_0 + 2.0))) + (771.3234287776531 / (t_0 + 3.0))) + (-176.6150291621406 / (t_0 + 4.0))) + (12.507343278686905 / (t_0 + 5.0))) + (-0.13857109526572012 / (t_0 + 6.0))) + (9.984369578019572e-6 / t_1)) + (1.5056327351493116e-7 / (t_0 + 8.0))));
}
def code(z): t_0 = (1.0 - z) - 1.0 t_1 = t_0 + 7.0 t_2 = t_1 + 0.5 return (math.pi / math.sin((math.pi * z))) * (((math.sqrt((math.pi * 2.0)) * math.pow(t_2, (t_0 + 0.5))) * math.exp(-t_2)) * ((((((((0.9999999999998099 + (676.5203681218851 / (t_0 + 1.0))) + (-1259.1392167224028 / (t_0 + 2.0))) + (771.3234287776531 / (t_0 + 3.0))) + (-176.6150291621406 / (t_0 + 4.0))) + (12.507343278686905 / (t_0 + 5.0))) + (-0.13857109526572012 / (t_0 + 6.0))) + (9.984369578019572e-6 / t_1)) + (1.5056327351493116e-7 / (t_0 + 8.0))))
function code(z) t_0 = Float64(Float64(1.0 - z) - 1.0) t_1 = Float64(t_0 + 7.0) t_2 = Float64(t_1 + 0.5) return Float64(Float64(pi / sin(Float64(pi * z))) * Float64(Float64(Float64(sqrt(Float64(pi * 2.0)) * (t_2 ^ Float64(t_0 + 0.5))) * exp(Float64(-t_2))) * Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(0.9999999999998099 + Float64(676.5203681218851 / Float64(t_0 + 1.0))) + Float64(-1259.1392167224028 / Float64(t_0 + 2.0))) + Float64(771.3234287776531 / Float64(t_0 + 3.0))) + Float64(-176.6150291621406 / Float64(t_0 + 4.0))) + Float64(12.507343278686905 / Float64(t_0 + 5.0))) + Float64(-0.13857109526572012 / Float64(t_0 + 6.0))) + Float64(9.984369578019572e-6 / t_1)) + Float64(1.5056327351493116e-7 / Float64(t_0 + 8.0))))) end
function tmp = code(z) t_0 = (1.0 - z) - 1.0; t_1 = t_0 + 7.0; t_2 = t_1 + 0.5; tmp = (pi / sin((pi * z))) * (((sqrt((pi * 2.0)) * (t_2 ^ (t_0 + 0.5))) * exp(-t_2)) * ((((((((0.9999999999998099 + (676.5203681218851 / (t_0 + 1.0))) + (-1259.1392167224028 / (t_0 + 2.0))) + (771.3234287776531 / (t_0 + 3.0))) + (-176.6150291621406 / (t_0 + 4.0))) + (12.507343278686905 / (t_0 + 5.0))) + (-0.13857109526572012 / (t_0 + 6.0))) + (9.984369578019572e-6 / t_1)) + (1.5056327351493116e-7 / (t_0 + 8.0)))); end
code[z_] := Block[{t$95$0 = N[(N[(1.0 - z), $MachinePrecision] - 1.0), $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 + 7.0), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 + 0.5), $MachinePrecision]}, N[(N[(Pi / N[Sin[N[(Pi * z), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(N[Sqrt[N[(Pi * 2.0), $MachinePrecision]], $MachinePrecision] * N[Power[t$95$2, N[(t$95$0 + 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Exp[(-t$95$2)], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(N[(N[(N[(N[(N[(0.9999999999998099 + N[(676.5203681218851 / N[(t$95$0 + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-1259.1392167224028 / N[(t$95$0 + 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(771.3234287776531 / N[(t$95$0 + 3.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-176.6150291621406 / N[(t$95$0 + 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(12.507343278686905 / N[(t$95$0 + 5.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-0.13857109526572012 / N[(t$95$0 + 6.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(9.984369578019572e-6 / t$95$1), $MachinePrecision]), $MachinePrecision] + N[(1.5056327351493116e-7 / N[(t$95$0 + 8.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \left(1 - z\right) - 1\\
t_1 := t\_0 + 7\\
t_2 := t\_1 + 0.5\\
\frac{\pi}{\sin \left(\pi \cdot z\right)} \cdot \left(\left(\left(\sqrt{\pi \cdot 2} \cdot {t\_2}^{\left(t\_0 + 0.5\right)}\right) \cdot e^{-t\_2}\right) \cdot \left(\left(\left(\left(\left(\left(\left(\left(0.9999999999998099 + \frac{676.5203681218851}{t\_0 + 1}\right) + \frac{-1259.1392167224028}{t\_0 + 2}\right) + \frac{771.3234287776531}{t\_0 + 3}\right) + \frac{-176.6150291621406}{t\_0 + 4}\right) + \frac{12.507343278686905}{t\_0 + 5}\right) + \frac{-0.13857109526572012}{t\_0 + 6}\right) + \frac{9.984369578019572 \cdot 10^{-6}}{t\_1}\right) + \frac{1.5056327351493116 \cdot 10^{-7}}{t\_0 + 8}\right)\right)
\end{array}
\end{array}
(FPCore (z)
:precision binary64
(let* ((t_0 (+ 1.0 (+ z -1.0))) (t_1 (+ (- 1.0 z) -1.0)))
(*
(/ PI (sin (* PI z)))
(*
(* (sqrt (* PI 2.0)) (exp (fma (- 0.5 z) (log (- 7.5 z)) (- z 7.5))))
(+
(+
(+
(-
(/ 12.507343278686905 (- 5.0 z))
(+
(/ -176.6150291621406 (- t_0 4.0))
(+
(-
(+
(/ -1259.1392167224028 (- z 2.0))
(/ 676.5203681218851 (+ z -1.0)))
0.9999999999998099)
(/ 771.3234287776531 (- t_0 3.0)))))
(/ -0.13857109526572012 (+ t_1 6.0)))
(/ 9.984369578019572e-6 (+ t_1 7.0)))
(/ 1.5056327351493116e-7 (- 8.0 t_0)))))))
double code(double z) {
double t_0 = 1.0 + (z + -1.0);
double t_1 = (1.0 - z) + -1.0;
return (((double) M_PI) / sin((((double) M_PI) * z))) * ((sqrt((((double) M_PI) * 2.0)) * exp(fma((0.5 - z), log((7.5 - z)), (z - 7.5)))) * (((((12.507343278686905 / (5.0 - z)) - ((-176.6150291621406 / (t_0 - 4.0)) + ((((-1259.1392167224028 / (z - 2.0)) + (676.5203681218851 / (z + -1.0))) - 0.9999999999998099) + (771.3234287776531 / (t_0 - 3.0))))) + (-0.13857109526572012 / (t_1 + 6.0))) + (9.984369578019572e-6 / (t_1 + 7.0))) + (1.5056327351493116e-7 / (8.0 - t_0))));
}
function code(z) t_0 = Float64(1.0 + Float64(z + -1.0)) t_1 = Float64(Float64(1.0 - z) + -1.0) return Float64(Float64(pi / sin(Float64(pi * z))) * Float64(Float64(sqrt(Float64(pi * 2.0)) * exp(fma(Float64(0.5 - z), log(Float64(7.5 - z)), Float64(z - 7.5)))) * Float64(Float64(Float64(Float64(Float64(12.507343278686905 / Float64(5.0 - z)) - Float64(Float64(-176.6150291621406 / Float64(t_0 - 4.0)) + Float64(Float64(Float64(Float64(-1259.1392167224028 / Float64(z - 2.0)) + Float64(676.5203681218851 / Float64(z + -1.0))) - 0.9999999999998099) + Float64(771.3234287776531 / Float64(t_0 - 3.0))))) + Float64(-0.13857109526572012 / Float64(t_1 + 6.0))) + Float64(9.984369578019572e-6 / Float64(t_1 + 7.0))) + Float64(1.5056327351493116e-7 / Float64(8.0 - t_0))))) end
code[z_] := Block[{t$95$0 = N[(1.0 + N[(z + -1.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(1.0 - z), $MachinePrecision] + -1.0), $MachinePrecision]}, N[(N[(Pi / N[Sin[N[(Pi * z), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[Sqrt[N[(Pi * 2.0), $MachinePrecision]], $MachinePrecision] * N[Exp[N[(N[(0.5 - z), $MachinePrecision] * N[Log[N[(7.5 - z), $MachinePrecision]], $MachinePrecision] + N[(z - 7.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(N[(N[(12.507343278686905 / N[(5.0 - z), $MachinePrecision]), $MachinePrecision] - N[(N[(-176.6150291621406 / N[(t$95$0 - 4.0), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(N[(-1259.1392167224028 / N[(z - 2.0), $MachinePrecision]), $MachinePrecision] + N[(676.5203681218851 / N[(z + -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 0.9999999999998099), $MachinePrecision] + N[(771.3234287776531 / N[(t$95$0 - 3.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-0.13857109526572012 / N[(t$95$1 + 6.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(9.984369578019572e-6 / N[(t$95$1 + 7.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(1.5056327351493116e-7 / N[(8.0 - t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := 1 + \left(z + -1\right)\\
t_1 := \left(1 - z\right) + -1\\
\frac{\pi}{\sin \left(\pi \cdot z\right)} \cdot \left(\left(\sqrt{\pi \cdot 2} \cdot e^{\mathsf{fma}\left(0.5 - z, \log \left(7.5 - z\right), z - 7.5\right)}\right) \cdot \left(\left(\left(\left(\frac{12.507343278686905}{5 - z} - \left(\frac{-176.6150291621406}{t\_0 - 4} + \left(\left(\left(\frac{-1259.1392167224028}{z - 2} + \frac{676.5203681218851}{z + -1}\right) - 0.9999999999998099\right) + \frac{771.3234287776531}{t\_0 - 3}\right)\right)\right) + \frac{-0.13857109526572012}{t\_1 + 6}\right) + \frac{9.984369578019572 \cdot 10^{-6}}{t\_1 + 7}\right) + \frac{1.5056327351493116 \cdot 10^{-7}}{8 - t\_0}\right)\right)
\end{array}
\end{array}
Initial program 96.2%
lift-+.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate-+l+N/A
lift-/.f64N/A
div-invN/A
*-commutativeN/A
lower-fma.f64N/A
lift-+.f64N/A
lift--.f64N/A
associate-+l-N/A
metadata-evalN/A
--rgt-identityN/A
lower-/.f64N/A
lower-+.f6496.2
lift-+.f64N/A
lift--.f64N/A
sub-negN/A
associate-+l+N/A
Applied rewrites96.2%
Applied rewrites97.5%
Applied rewrites99.3%
Taylor expanded in z around 0
mul-1-negN/A
unsub-negN/A
lower--.f6499.3
Applied rewrites99.3%
Final simplification99.3%
(FPCore (z)
:precision binary64
(let* ((t_0 (+ (- 1.0 z) -1.0)) (t_1 (+ 1.0 (+ z -1.0))))
(*
(/ PI (sin (* PI z)))
(*
(* (sqrt (* PI 2.0)) (exp (fma (- 0.5 z) (log (- 7.5 z)) (- z 7.5))))
(+
(/ 1.5056327351493116e-7 (- 8.0 t_1))
(+
(/ 9.984369578019572e-6 (+ t_0 7.0))
(+
(/ -0.13857109526572012 (+ t_0 6.0))
(-
(/ 12.507343278686905 (+ t_0 5.0))
(+
(/ -176.6150291621406 (- t_1 4.0))
(-
(-
(+
(/ -1259.1392167224028 (- z 2.0))
(/ 676.5203681218851 (+ z -1.0)))
0.9999999999998099)
(/ 771.3234287776531 (- 3.0 z))))))))))))
double code(double z) {
double t_0 = (1.0 - z) + -1.0;
double t_1 = 1.0 + (z + -1.0);
return (((double) M_PI) / sin((((double) M_PI) * z))) * ((sqrt((((double) M_PI) * 2.0)) * exp(fma((0.5 - z), log((7.5 - z)), (z - 7.5)))) * ((1.5056327351493116e-7 / (8.0 - t_1)) + ((9.984369578019572e-6 / (t_0 + 7.0)) + ((-0.13857109526572012 / (t_0 + 6.0)) + ((12.507343278686905 / (t_0 + 5.0)) - ((-176.6150291621406 / (t_1 - 4.0)) + ((((-1259.1392167224028 / (z - 2.0)) + (676.5203681218851 / (z + -1.0))) - 0.9999999999998099) - (771.3234287776531 / (3.0 - z)))))))));
}
function code(z) t_0 = Float64(Float64(1.0 - z) + -1.0) t_1 = Float64(1.0 + Float64(z + -1.0)) return Float64(Float64(pi / sin(Float64(pi * z))) * Float64(Float64(sqrt(Float64(pi * 2.0)) * exp(fma(Float64(0.5 - z), log(Float64(7.5 - z)), Float64(z - 7.5)))) * Float64(Float64(1.5056327351493116e-7 / Float64(8.0 - t_1)) + Float64(Float64(9.984369578019572e-6 / Float64(t_0 + 7.0)) + Float64(Float64(-0.13857109526572012 / Float64(t_0 + 6.0)) + Float64(Float64(12.507343278686905 / Float64(t_0 + 5.0)) - Float64(Float64(-176.6150291621406 / Float64(t_1 - 4.0)) + Float64(Float64(Float64(Float64(-1259.1392167224028 / Float64(z - 2.0)) + Float64(676.5203681218851 / Float64(z + -1.0))) - 0.9999999999998099) - Float64(771.3234287776531 / Float64(3.0 - z)))))))))) end
code[z_] := Block[{t$95$0 = N[(N[(1.0 - z), $MachinePrecision] + -1.0), $MachinePrecision]}, Block[{t$95$1 = N[(1.0 + N[(z + -1.0), $MachinePrecision]), $MachinePrecision]}, N[(N[(Pi / N[Sin[N[(Pi * z), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[Sqrt[N[(Pi * 2.0), $MachinePrecision]], $MachinePrecision] * N[Exp[N[(N[(0.5 - z), $MachinePrecision] * N[Log[N[(7.5 - z), $MachinePrecision]], $MachinePrecision] + N[(z - 7.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(1.5056327351493116e-7 / N[(8.0 - t$95$1), $MachinePrecision]), $MachinePrecision] + N[(N[(9.984369578019572e-6 / N[(t$95$0 + 7.0), $MachinePrecision]), $MachinePrecision] + N[(N[(-0.13857109526572012 / N[(t$95$0 + 6.0), $MachinePrecision]), $MachinePrecision] + N[(N[(12.507343278686905 / N[(t$95$0 + 5.0), $MachinePrecision]), $MachinePrecision] - N[(N[(-176.6150291621406 / N[(t$95$1 - 4.0), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(N[(-1259.1392167224028 / N[(z - 2.0), $MachinePrecision]), $MachinePrecision] + N[(676.5203681218851 / N[(z + -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 0.9999999999998099), $MachinePrecision] - N[(771.3234287776531 / N[(3.0 - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \left(1 - z\right) + -1\\
t_1 := 1 + \left(z + -1\right)\\
\frac{\pi}{\sin \left(\pi \cdot z\right)} \cdot \left(\left(\sqrt{\pi \cdot 2} \cdot e^{\mathsf{fma}\left(0.5 - z, \log \left(7.5 - z\right), z - 7.5\right)}\right) \cdot \left(\frac{1.5056327351493116 \cdot 10^{-7}}{8 - t\_1} + \left(\frac{9.984369578019572 \cdot 10^{-6}}{t\_0 + 7} + \left(\frac{-0.13857109526572012}{t\_0 + 6} + \left(\frac{12.507343278686905}{t\_0 + 5} - \left(\frac{-176.6150291621406}{t\_1 - 4} + \left(\left(\left(\frac{-1259.1392167224028}{z - 2} + \frac{676.5203681218851}{z + -1}\right) - 0.9999999999998099\right) - \frac{771.3234287776531}{3 - z}\right)\right)\right)\right)\right)\right)\right)
\end{array}
\end{array}
Initial program 96.5%
lift-+.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate-+l+N/A
lift-/.f64N/A
div-invN/A
*-commutativeN/A
lower-fma.f64N/A
lift-+.f64N/A
lift--.f64N/A
associate-+l-N/A
metadata-evalN/A
--rgt-identityN/A
lower-/.f64N/A
lower-+.f6496.5
lift-+.f64N/A
lift--.f64N/A
sub-negN/A
associate-+l+N/A
Applied rewrites96.5%
Applied rewrites97.5%
Applied rewrites99.2%
Taylor expanded in z around 0
mul-1-negN/A
unsub-negN/A
lower--.f6499.3
Applied rewrites99.3%
Final simplification99.3%
herbie shell --seed 2024225
(FPCore (z)
:name "Jmat.Real.gamma, branch z less than 0.5"
:precision binary64
:pre (<= z 0.5)
(* (/ PI (sin (* PI z))) (* (* (* (sqrt (* PI 2.0)) (pow (+ (+ (- (- 1.0 z) 1.0) 7.0) 0.5) (+ (- (- 1.0 z) 1.0) 0.5))) (exp (- (+ (+ (- (- 1.0 z) 1.0) 7.0) 0.5)))) (+ (+ (+ (+ (+ (+ (+ (+ 0.9999999999998099 (/ 676.5203681218851 (+ (- (- 1.0 z) 1.0) 1.0))) (/ -1259.1392167224028 (+ (- (- 1.0 z) 1.0) 2.0))) (/ 771.3234287776531 (+ (- (- 1.0 z) 1.0) 3.0))) (/ -176.6150291621406 (+ (- (- 1.0 z) 1.0) 4.0))) (/ 12.507343278686905 (+ (- (- 1.0 z) 1.0) 5.0))) (/ -0.13857109526572012 (+ (- (- 1.0 z) 1.0) 6.0))) (/ 9.984369578019572e-6 (+ (- (- 1.0 z) 1.0) 7.0))) (/ 1.5056327351493116e-7 (+ (- (- 1.0 z) 1.0) 8.0))))))