
(FPCore (u1 u2) :precision binary64 (+ (* (* (/ 1.0 6.0) (pow (* -2.0 (log u1)) 0.5)) (cos (* (* 2.0 PI) u2))) 0.5))
double code(double u1, double u2) {
return (((1.0 / 6.0) * pow((-2.0 * log(u1)), 0.5)) * cos(((2.0 * ((double) M_PI)) * u2))) + 0.5;
}
public static double code(double u1, double u2) {
return (((1.0 / 6.0) * Math.pow((-2.0 * Math.log(u1)), 0.5)) * Math.cos(((2.0 * Math.PI) * u2))) + 0.5;
}
def code(u1, u2): return (((1.0 / 6.0) * math.pow((-2.0 * math.log(u1)), 0.5)) * math.cos(((2.0 * math.pi) * u2))) + 0.5
function code(u1, u2) return Float64(Float64(Float64(Float64(1.0 / 6.0) * (Float64(-2.0 * log(u1)) ^ 0.5)) * cos(Float64(Float64(2.0 * pi) * u2))) + 0.5) end
function tmp = code(u1, u2) tmp = (((1.0 / 6.0) * ((-2.0 * log(u1)) ^ 0.5)) * cos(((2.0 * pi) * u2))) + 0.5; end
code[u1_, u2_] := N[(N[(N[(N[(1.0 / 6.0), $MachinePrecision] * N[Power[N[(-2.0 * N[Log[u1], $MachinePrecision]), $MachinePrecision], 0.5], $MachinePrecision]), $MachinePrecision] * N[Cos[N[(N[(2.0 * Pi), $MachinePrecision] * u2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + 0.5), $MachinePrecision]
\begin{array}{l}
\\
\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 8 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (u1 u2) :precision binary64 (+ (* (* (/ 1.0 6.0) (pow (* -2.0 (log u1)) 0.5)) (cos (* (* 2.0 PI) u2))) 0.5))
double code(double u1, double u2) {
return (((1.0 / 6.0) * pow((-2.0 * log(u1)), 0.5)) * cos(((2.0 * ((double) M_PI)) * u2))) + 0.5;
}
public static double code(double u1, double u2) {
return (((1.0 / 6.0) * Math.pow((-2.0 * Math.log(u1)), 0.5)) * Math.cos(((2.0 * Math.PI) * u2))) + 0.5;
}
def code(u1, u2): return (((1.0 / 6.0) * math.pow((-2.0 * math.log(u1)), 0.5)) * math.cos(((2.0 * math.pi) * u2))) + 0.5
function code(u1, u2) return Float64(Float64(Float64(Float64(1.0 / 6.0) * (Float64(-2.0 * log(u1)) ^ 0.5)) * cos(Float64(Float64(2.0 * pi) * u2))) + 0.5) end
function tmp = code(u1, u2) tmp = (((1.0 / 6.0) * ((-2.0 * log(u1)) ^ 0.5)) * cos(((2.0 * pi) * u2))) + 0.5; end
code[u1_, u2_] := N[(N[(N[(N[(1.0 / 6.0), $MachinePrecision] * N[Power[N[(-2.0 * N[Log[u1], $MachinePrecision]), $MachinePrecision], 0.5], $MachinePrecision]), $MachinePrecision] * N[Cos[N[(N[(2.0 * Pi), $MachinePrecision] * u2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + 0.5), $MachinePrecision]
\begin{array}{l}
\\
\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5
\end{array}
(FPCore (u1 u2) :precision binary64 (+ (* (sqrt (- 0.0 (log u1))) (* (* 0.16666666666666666 (sqrt 2.0)) (cos (* 2.0 (* u2 PI))))) 0.5))
double code(double u1, double u2) {
return (sqrt((0.0 - log(u1))) * ((0.16666666666666666 * sqrt(2.0)) * cos((2.0 * (u2 * ((double) M_PI)))))) + 0.5;
}
public static double code(double u1, double u2) {
return (Math.sqrt((0.0 - Math.log(u1))) * ((0.16666666666666666 * Math.sqrt(2.0)) * Math.cos((2.0 * (u2 * Math.PI))))) + 0.5;
}
def code(u1, u2): return (math.sqrt((0.0 - math.log(u1))) * ((0.16666666666666666 * math.sqrt(2.0)) * math.cos((2.0 * (u2 * math.pi))))) + 0.5
function code(u1, u2) return Float64(Float64(sqrt(Float64(0.0 - log(u1))) * Float64(Float64(0.16666666666666666 * sqrt(2.0)) * cos(Float64(2.0 * Float64(u2 * pi))))) + 0.5) end
function tmp = code(u1, u2) tmp = (sqrt((0.0 - log(u1))) * ((0.16666666666666666 * sqrt(2.0)) * cos((2.0 * (u2 * pi))))) + 0.5; end
code[u1_, u2_] := N[(N[(N[Sqrt[N[(0.0 - N[Log[u1], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(N[(0.16666666666666666 * N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] * N[Cos[N[(2.0 * N[(u2 * Pi), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 0.5), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0 - \log u1} \cdot \left(\left(0.16666666666666666 \cdot \sqrt{2}\right) \cdot \cos \left(2 \cdot \left(u2 \cdot \pi\right)\right)\right) + 0.5
\end{array}
Initial program 99.3%
metadata-evalN/A
pow1/2N/A
*-commutativeN/A
associate-*l*N/A
pow1/2N/A
sqr-powN/A
associate-*l*N/A
*-lowering-*.f64N/A
metadata-evalN/A
metadata-evalN/A
pow-lowering-pow.f64N/A
*-lowering-*.f64N/A
log-lowering-log.f64N/A
metadata-evalN/A
*-lowering-*.f64N/A
Applied egg-rr99.1%
Taylor expanded in u1 around inf
associate-*r*N/A
*-commutativeN/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
log-recN/A
neg-sub0N/A
--lowering--.f64N/A
log-lowering-log.f64N/A
*-commutativeN/A
associate-*r*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
cos-lowering-cos.f64N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6499.6%
Simplified99.6%
sub0-negN/A
neg-lowering-neg.f64N/A
log-lowering-log.f6499.6%
Applied egg-rr99.6%
Final simplification99.6%
(FPCore (u1 u2) :precision binary64 (+ 0.5 (* (cos (* u2 (* 2.0 PI))) (* 0.16666666666666666 (pow (* (log u1) -2.0) 0.5)))))
double code(double u1, double u2) {
return 0.5 + (cos((u2 * (2.0 * ((double) M_PI)))) * (0.16666666666666666 * pow((log(u1) * -2.0), 0.5)));
}
public static double code(double u1, double u2) {
return 0.5 + (Math.cos((u2 * (2.0 * Math.PI))) * (0.16666666666666666 * Math.pow((Math.log(u1) * -2.0), 0.5)));
}
def code(u1, u2): return 0.5 + (math.cos((u2 * (2.0 * math.pi))) * (0.16666666666666666 * math.pow((math.log(u1) * -2.0), 0.5)))
function code(u1, u2) return Float64(0.5 + Float64(cos(Float64(u2 * Float64(2.0 * pi))) * Float64(0.16666666666666666 * (Float64(log(u1) * -2.0) ^ 0.5)))) end
function tmp = code(u1, u2) tmp = 0.5 + (cos((u2 * (2.0 * pi))) * (0.16666666666666666 * ((log(u1) * -2.0) ^ 0.5))); end
code[u1_, u2_] := N[(0.5 + N[(N[Cos[N[(u2 * N[(2.0 * Pi), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(0.16666666666666666 * N[Power[N[(N[Log[u1], $MachinePrecision] * -2.0), $MachinePrecision], 0.5], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.5 + \cos \left(u2 \cdot \left(2 \cdot \pi\right)\right) \cdot \left(0.16666666666666666 \cdot {\left(\log u1 \cdot -2\right)}^{0.5}\right)
\end{array}
Initial program 99.3%
metadata-eval99.3%
Applied egg-rr99.3%
Final simplification99.3%
(FPCore (u1 u2) :precision binary64 (+ 0.5 (* (* 0.16666666666666666 (sqrt (* (log u1) -2.0))) (cos (* 2.0 (* u2 PI))))))
double code(double u1, double u2) {
return 0.5 + ((0.16666666666666666 * sqrt((log(u1) * -2.0))) * cos((2.0 * (u2 * ((double) M_PI)))));
}
public static double code(double u1, double u2) {
return 0.5 + ((0.16666666666666666 * Math.sqrt((Math.log(u1) * -2.0))) * Math.cos((2.0 * (u2 * Math.PI))));
}
def code(u1, u2): return 0.5 + ((0.16666666666666666 * math.sqrt((math.log(u1) * -2.0))) * math.cos((2.0 * (u2 * math.pi))))
function code(u1, u2) return Float64(0.5 + Float64(Float64(0.16666666666666666 * sqrt(Float64(log(u1) * -2.0))) * cos(Float64(2.0 * Float64(u2 * pi))))) end
function tmp = code(u1, u2) tmp = 0.5 + ((0.16666666666666666 * sqrt((log(u1) * -2.0))) * cos((2.0 * (u2 * pi)))); end
code[u1_, u2_] := N[(0.5 + N[(N[(0.16666666666666666 * N[Sqrt[N[(N[Log[u1], $MachinePrecision] * -2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Cos[N[(2.0 * N[(u2 * Pi), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.5 + \left(0.16666666666666666 \cdot \sqrt{\log u1 \cdot -2}\right) \cdot \cos \left(2 \cdot \left(u2 \cdot \pi\right)\right)
\end{array}
Initial program 99.3%
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
metadata-evalN/A
unpow1/2N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f64N/A
log-lowering-log.f64N/A
cos-lowering-cos.f64N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6499.3%
Simplified99.3%
Final simplification99.3%
(FPCore (u1 u2)
:precision binary64
(let* ((t_0 (* PI (* PI -2.0))))
(+
0.5
(/
(*
(- 1.0 (* (* (* u2 u2) (* u2 u2)) (* t_0 t_0)))
(* 0.16666666666666666 (pow (* (log u1) -2.0) 0.5)))
(- 1.0 (* u2 (* u2 t_0)))))))
double code(double u1, double u2) {
double t_0 = ((double) M_PI) * (((double) M_PI) * -2.0);
return 0.5 + (((1.0 - (((u2 * u2) * (u2 * u2)) * (t_0 * t_0))) * (0.16666666666666666 * pow((log(u1) * -2.0), 0.5))) / (1.0 - (u2 * (u2 * t_0))));
}
public static double code(double u1, double u2) {
double t_0 = Math.PI * (Math.PI * -2.0);
return 0.5 + (((1.0 - (((u2 * u2) * (u2 * u2)) * (t_0 * t_0))) * (0.16666666666666666 * Math.pow((Math.log(u1) * -2.0), 0.5))) / (1.0 - (u2 * (u2 * t_0))));
}
def code(u1, u2): t_0 = math.pi * (math.pi * -2.0) return 0.5 + (((1.0 - (((u2 * u2) * (u2 * u2)) * (t_0 * t_0))) * (0.16666666666666666 * math.pow((math.log(u1) * -2.0), 0.5))) / (1.0 - (u2 * (u2 * t_0))))
function code(u1, u2) t_0 = Float64(pi * Float64(pi * -2.0)) return Float64(0.5 + Float64(Float64(Float64(1.0 - Float64(Float64(Float64(u2 * u2) * Float64(u2 * u2)) * Float64(t_0 * t_0))) * Float64(0.16666666666666666 * (Float64(log(u1) * -2.0) ^ 0.5))) / Float64(1.0 - Float64(u2 * Float64(u2 * t_0))))) end
function tmp = code(u1, u2) t_0 = pi * (pi * -2.0); tmp = 0.5 + (((1.0 - (((u2 * u2) * (u2 * u2)) * (t_0 * t_0))) * (0.16666666666666666 * ((log(u1) * -2.0) ^ 0.5))) / (1.0 - (u2 * (u2 * t_0)))); end
code[u1_, u2_] := Block[{t$95$0 = N[(Pi * N[(Pi * -2.0), $MachinePrecision]), $MachinePrecision]}, N[(0.5 + N[(N[(N[(1.0 - N[(N[(N[(u2 * u2), $MachinePrecision] * N[(u2 * u2), $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(0.16666666666666666 * N[Power[N[(N[Log[u1], $MachinePrecision] * -2.0), $MachinePrecision], 0.5], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 - N[(u2 * N[(u2 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \pi \cdot \left(\pi \cdot -2\right)\\
0.5 + \frac{\left(1 - \left(\left(u2 \cdot u2\right) \cdot \left(u2 \cdot u2\right)\right) \cdot \left(t\_0 \cdot t\_0\right)\right) \cdot \left(0.16666666666666666 \cdot {\left(\log u1 \cdot -2\right)}^{0.5}\right)}{1 - u2 \cdot \left(u2 \cdot t\_0\right)}
\end{array}
\end{array}
Initial program 99.3%
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
metadata-evalN/A
unpow1/2N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f64N/A
log-lowering-log.f64N/A
cos-lowering-cos.f64N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6499.3%
Simplified99.3%
pow1/2N/A
pow-to-expN/A
exp-lowering-exp.f64N/A
*-commutativeN/A
*-lowering-*.f64N/A
log-lowering-log.f64N/A
*-lowering-*.f64N/A
log-lowering-log.f6499.0%
Applied egg-rr99.0%
Taylor expanded in u2 around 0
rem-square-sqrtN/A
unpow2N/A
*-commutativeN/A
associate-*r*N/A
unpow2N/A
rem-square-sqrtN/A
+-lowering-+.f64N/A
*-commutativeN/A
unpow2N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
*-commutativeN/A
rem-square-sqrtN/A
unpow2N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
PI-lowering-PI.f64N/A
unpow2N/A
rem-square-sqrt98.1%
Simplified98.1%
Applied egg-rr98.4%
(FPCore (u1 u2) :precision binary64 (+ 0.5 (* (* 0.16666666666666666 (sqrt (* (log u1) -2.0))) (+ 1.0 (* u2 (* u2 (* -2.0 (* PI PI))))))))
double code(double u1, double u2) {
return 0.5 + ((0.16666666666666666 * sqrt((log(u1) * -2.0))) * (1.0 + (u2 * (u2 * (-2.0 * (((double) M_PI) * ((double) M_PI)))))));
}
public static double code(double u1, double u2) {
return 0.5 + ((0.16666666666666666 * Math.sqrt((Math.log(u1) * -2.0))) * (1.0 + (u2 * (u2 * (-2.0 * (Math.PI * Math.PI))))));
}
def code(u1, u2): return 0.5 + ((0.16666666666666666 * math.sqrt((math.log(u1) * -2.0))) * (1.0 + (u2 * (u2 * (-2.0 * (math.pi * math.pi))))))
function code(u1, u2) return Float64(0.5 + Float64(Float64(0.16666666666666666 * sqrt(Float64(log(u1) * -2.0))) * Float64(1.0 + Float64(u2 * Float64(u2 * Float64(-2.0 * Float64(pi * pi))))))) end
function tmp = code(u1, u2) tmp = 0.5 + ((0.16666666666666666 * sqrt((log(u1) * -2.0))) * (1.0 + (u2 * (u2 * (-2.0 * (pi * pi)))))); end
code[u1_, u2_] := N[(0.5 + N[(N[(0.16666666666666666 * N[Sqrt[N[(N[Log[u1], $MachinePrecision] * -2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 + N[(u2 * N[(u2 * N[(-2.0 * N[(Pi * Pi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.5 + \left(0.16666666666666666 \cdot \sqrt{\log u1 \cdot -2}\right) \cdot \left(1 + u2 \cdot \left(u2 \cdot \left(-2 \cdot \left(\pi \cdot \pi\right)\right)\right)\right)
\end{array}
Initial program 99.3%
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
metadata-evalN/A
unpow1/2N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f64N/A
log-lowering-log.f64N/A
cos-lowering-cos.f64N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6499.3%
Simplified99.3%
pow1/2N/A
pow-to-expN/A
exp-lowering-exp.f64N/A
*-commutativeN/A
*-lowering-*.f64N/A
log-lowering-log.f64N/A
*-lowering-*.f64N/A
log-lowering-log.f6499.0%
Applied egg-rr99.0%
Taylor expanded in u2 around 0
rem-square-sqrtN/A
unpow2N/A
*-commutativeN/A
associate-*r*N/A
unpow2N/A
rem-square-sqrtN/A
+-lowering-+.f64N/A
*-commutativeN/A
unpow2N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
*-commutativeN/A
rem-square-sqrtN/A
unpow2N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
PI-lowering-PI.f64N/A
unpow2N/A
rem-square-sqrt98.1%
Simplified98.1%
*-commutativeN/A
*-commutativeN/A
pow-to-expN/A
unpow1/2N/A
rem-square-sqrtN/A
unpow1/2N/A
metadata-evalN/A
pow-powN/A
unpow1/2N/A
metadata-evalN/A
pow-powN/A
sqrt-lowering-sqrt.f64N/A
pow-powN/A
metadata-evalN/A
unpow1/2N/A
pow-powN/A
metadata-evalN/A
unpow1/2N/A
Applied egg-rr98.4%
Final simplification98.4%
(FPCore (u1 u2) :precision binary64 (+ 0.5 (* 0.16666666666666666 (sqrt (/ -2.0 (/ 1.0 (log u1)))))))
double code(double u1, double u2) {
return 0.5 + (0.16666666666666666 * sqrt((-2.0 / (1.0 / log(u1)))));
}
real(8) function code(u1, u2)
real(8), intent (in) :: u1
real(8), intent (in) :: u2
code = 0.5d0 + (0.16666666666666666d0 * sqrt(((-2.0d0) / (1.0d0 / log(u1)))))
end function
public static double code(double u1, double u2) {
return 0.5 + (0.16666666666666666 * Math.sqrt((-2.0 / (1.0 / Math.log(u1)))));
}
def code(u1, u2): return 0.5 + (0.16666666666666666 * math.sqrt((-2.0 / (1.0 / math.log(u1)))))
function code(u1, u2) return Float64(0.5 + Float64(0.16666666666666666 * sqrt(Float64(-2.0 / Float64(1.0 / log(u1)))))) end
function tmp = code(u1, u2) tmp = 0.5 + (0.16666666666666666 * sqrt((-2.0 / (1.0 / log(u1))))); end
code[u1_, u2_] := N[(0.5 + N[(0.16666666666666666 * N[Sqrt[N[(-2.0 / N[(1.0 / N[Log[u1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.5 + 0.16666666666666666 \cdot \sqrt{\frac{-2}{\frac{1}{\log u1}}}
\end{array}
Initial program 99.3%
Taylor expanded in u2 around 0
*-commutativeN/A
associate-*l*N/A
*-commutativeN/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
log-lowering-log.f64N/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f640.0%
Simplified0.0%
associate-*r*N/A
*-commutativeN/A
associate-*l*N/A
sqrt-prodN/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f64N/A
log-lowering-log.f6498.1%
Applied egg-rr98.1%
Applied egg-rr98.1%
clear-numN/A
un-div-invN/A
/-lowering-/.f64N/A
clear-numN/A
div-invN/A
sqrt-pow1N/A
metadata-evalN/A
inv-powN/A
pow-prod-upN/A
metadata-evalN/A
unpow1N/A
/-lowering-/.f64N/A
log-lowering-log.f6498.2%
Applied egg-rr98.2%
Final simplification98.2%
(FPCore (u1 u2) :precision binary64 (+ 0.5 (* 0.16666666666666666 (pow (* (log u1) -2.0) 0.5))))
double code(double u1, double u2) {
return 0.5 + (0.16666666666666666 * pow((log(u1) * -2.0), 0.5));
}
real(8) function code(u1, u2)
real(8), intent (in) :: u1
real(8), intent (in) :: u2
code = 0.5d0 + (0.16666666666666666d0 * ((log(u1) * (-2.0d0)) ** 0.5d0))
end function
public static double code(double u1, double u2) {
return 0.5 + (0.16666666666666666 * Math.pow((Math.log(u1) * -2.0), 0.5));
}
def code(u1, u2): return 0.5 + (0.16666666666666666 * math.pow((math.log(u1) * -2.0), 0.5))
function code(u1, u2) return Float64(0.5 + Float64(0.16666666666666666 * (Float64(log(u1) * -2.0) ^ 0.5))) end
function tmp = code(u1, u2) tmp = 0.5 + (0.16666666666666666 * ((log(u1) * -2.0) ^ 0.5)); end
code[u1_, u2_] := N[(0.5 + N[(0.16666666666666666 * N[Power[N[(N[Log[u1], $MachinePrecision] * -2.0), $MachinePrecision], 0.5], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.5 + 0.16666666666666666 \cdot {\left(\log u1 \cdot -2\right)}^{0.5}
\end{array}
Initial program 99.3%
Taylor expanded in u2 around 0
*-commutativeN/A
associate-*l*N/A
*-commutativeN/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
log-lowering-log.f64N/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f640.0%
Simplified0.0%
associate-*r*N/A
*-commutativeN/A
associate-*l*N/A
sqrt-prodN/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f64N/A
log-lowering-log.f6498.1%
Applied egg-rr98.1%
pow1/2N/A
rem-square-sqrtN/A
pow-lowering-pow.f64N/A
rem-square-sqrtN/A
*-commutativeN/A
*-lowering-*.f64N/A
log-lowering-log.f6498.1%
Applied egg-rr98.1%
Final simplification98.1%
(FPCore (u1 u2) :precision binary64 (+ 0.5 (* 0.16666666666666666 (sqrt (* (log u1) -2.0)))))
double code(double u1, double u2) {
return 0.5 + (0.16666666666666666 * sqrt((log(u1) * -2.0)));
}
real(8) function code(u1, u2)
real(8), intent (in) :: u1
real(8), intent (in) :: u2
code = 0.5d0 + (0.16666666666666666d0 * sqrt((log(u1) * (-2.0d0))))
end function
public static double code(double u1, double u2) {
return 0.5 + (0.16666666666666666 * Math.sqrt((Math.log(u1) * -2.0)));
}
def code(u1, u2): return 0.5 + (0.16666666666666666 * math.sqrt((math.log(u1) * -2.0)))
function code(u1, u2) return Float64(0.5 + Float64(0.16666666666666666 * sqrt(Float64(log(u1) * -2.0)))) end
function tmp = code(u1, u2) tmp = 0.5 + (0.16666666666666666 * sqrt((log(u1) * -2.0))); end
code[u1_, u2_] := N[(0.5 + N[(0.16666666666666666 * N[Sqrt[N[(N[Log[u1], $MachinePrecision] * -2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.5 + 0.16666666666666666 \cdot \sqrt{\log u1 \cdot -2}
\end{array}
Initial program 99.3%
Taylor expanded in u2 around 0
*-commutativeN/A
associate-*l*N/A
*-commutativeN/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
log-lowering-log.f64N/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f640.0%
Simplified0.0%
associate-*r*N/A
*-commutativeN/A
associate-*l*N/A
sqrt-prodN/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f64N/A
log-lowering-log.f6498.1%
Applied egg-rr98.1%
Final simplification98.1%
herbie shell --seed 2024141
(FPCore (u1 u2)
:name "normal distribution"
:precision binary64
:pre (and (and (<= 0.0 u1) (<= u1 1.0)) (and (<= 0.0 u2) (<= u2 1.0)))
(+ (* (* (/ 1.0 6.0) (pow (* -2.0 (log u1)) 0.5)) (cos (* (* 2.0 PI) u2))) 0.5))