
(FPCore (v t) :precision binary64 (/ (- 1.0 (* 5.0 (* v v))) (* (* (* PI t) (sqrt (* 2.0 (- 1.0 (* 3.0 (* v v)))))) (- 1.0 (* v v)))))
double code(double v, double t) {
return (1.0 - (5.0 * (v * v))) / (((((double) M_PI) * t) * sqrt((2.0 * (1.0 - (3.0 * (v * v)))))) * (1.0 - (v * v)));
}
public static double code(double v, double t) {
return (1.0 - (5.0 * (v * v))) / (((Math.PI * t) * Math.sqrt((2.0 * (1.0 - (3.0 * (v * v)))))) * (1.0 - (v * v)));
}
def code(v, t): return (1.0 - (5.0 * (v * v))) / (((math.pi * t) * math.sqrt((2.0 * (1.0 - (3.0 * (v * v)))))) * (1.0 - (v * v)))
function code(v, t) return Float64(Float64(1.0 - Float64(5.0 * Float64(v * v))) / Float64(Float64(Float64(pi * t) * sqrt(Float64(2.0 * Float64(1.0 - Float64(3.0 * Float64(v * v)))))) * Float64(1.0 - Float64(v * v)))) end
function tmp = code(v, t) tmp = (1.0 - (5.0 * (v * v))) / (((pi * t) * sqrt((2.0 * (1.0 - (3.0 * (v * v)))))) * (1.0 - (v * v))); end
code[v_, t_] := N[(N[(1.0 - N[(5.0 * N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(Pi * t), $MachinePrecision] * N[Sqrt[N[(2.0 * N[(1.0 - N[(3.0 * N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\pi \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 10 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (v t) :precision binary64 (/ (- 1.0 (* 5.0 (* v v))) (* (* (* PI t) (sqrt (* 2.0 (- 1.0 (* 3.0 (* v v)))))) (- 1.0 (* v v)))))
double code(double v, double t) {
return (1.0 - (5.0 * (v * v))) / (((((double) M_PI) * t) * sqrt((2.0 * (1.0 - (3.0 * (v * v)))))) * (1.0 - (v * v)));
}
public static double code(double v, double t) {
return (1.0 - (5.0 * (v * v))) / (((Math.PI * t) * Math.sqrt((2.0 * (1.0 - (3.0 * (v * v)))))) * (1.0 - (v * v)));
}
def code(v, t): return (1.0 - (5.0 * (v * v))) / (((math.pi * t) * math.sqrt((2.0 * (1.0 - (3.0 * (v * v)))))) * (1.0 - (v * v)))
function code(v, t) return Float64(Float64(1.0 - Float64(5.0 * Float64(v * v))) / Float64(Float64(Float64(pi * t) * sqrt(Float64(2.0 * Float64(1.0 - Float64(3.0 * Float64(v * v)))))) * Float64(1.0 - Float64(v * v)))) end
function tmp = code(v, t) tmp = (1.0 - (5.0 * (v * v))) / (((pi * t) * sqrt((2.0 * (1.0 - (3.0 * (v * v)))))) * (1.0 - (v * v))); end
code[v_, t_] := N[(N[(1.0 - N[(5.0 * N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(Pi * t), $MachinePrecision] * N[Sqrt[N[(2.0 * N[(1.0 - N[(3.0 * N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\pi \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}
\end{array}
(FPCore (v t) :precision binary64 (/ (/ (+ 1.0 (* v (* v -5.0))) (* (sqrt (- 2.0 (* (* v v) 6.0))) (* (- 1.0 (* v v)) PI))) t))
double code(double v, double t) {
return ((1.0 + (v * (v * -5.0))) / (sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * ((double) M_PI)))) / t;
}
public static double code(double v, double t) {
return ((1.0 + (v * (v * -5.0))) / (Math.sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * Math.PI))) / t;
}
def code(v, t): return ((1.0 + (v * (v * -5.0))) / (math.sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * math.pi))) / t
function code(v, t) return Float64(Float64(Float64(1.0 + Float64(v * Float64(v * -5.0))) / Float64(sqrt(Float64(2.0 - Float64(Float64(v * v) * 6.0))) * Float64(Float64(1.0 - Float64(v * v)) * pi))) / t) end
function tmp = code(v, t) tmp = ((1.0 + (v * (v * -5.0))) / (sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * pi))) / t; end
code[v_, t_] := N[(N[(N[(1.0 + N[(v * N[(v * -5.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[Sqrt[N[(2.0 - N[(N[(v * v), $MachinePrecision] * 6.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision] * Pi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{1 + v \cdot \left(v \cdot -5\right)}{\sqrt{2 - \left(v \cdot v\right) \cdot 6} \cdot \left(\left(1 - v \cdot v\right) \cdot \pi\right)}}{t}
\end{array}
Initial program 99.3%
/-lowering-/.f64N/A
sub-negN/A
+-lowering-+.f64N/A
associate-*r*N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
metadata-evalN/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-lowering-*.f64N/A
Simplified99.3%
*-rgt-identityN/A
*-commutativeN/A
associate-*r*N/A
times-fracN/A
*-lowering-*.f64N/A
Applied egg-rr99.6%
un-div-invN/A
/-lowering-/.f64N/A
Applied egg-rr99.9%
(FPCore (v t) :precision binary64 (/ (/ (+ 1.0 (* v (* v -5.0))) PI) (* (sqrt (- 2.0 (* (* v v) 6.0))) (* (- 1.0 (* v v)) t))))
double code(double v, double t) {
return ((1.0 + (v * (v * -5.0))) / ((double) M_PI)) / (sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * t));
}
public static double code(double v, double t) {
return ((1.0 + (v * (v * -5.0))) / Math.PI) / (Math.sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * t));
}
def code(v, t): return ((1.0 + (v * (v * -5.0))) / math.pi) / (math.sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * t))
function code(v, t) return Float64(Float64(Float64(1.0 + Float64(v * Float64(v * -5.0))) / pi) / Float64(sqrt(Float64(2.0 - Float64(Float64(v * v) * 6.0))) * Float64(Float64(1.0 - Float64(v * v)) * t))) end
function tmp = code(v, t) tmp = ((1.0 + (v * (v * -5.0))) / pi) / (sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * t)); end
code[v_, t_] := N[(N[(N[(1.0 + N[(v * N[(v * -5.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / Pi), $MachinePrecision] / N[(N[Sqrt[N[(2.0 - N[(N[(v * v), $MachinePrecision] * 6.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{1 + v \cdot \left(v \cdot -5\right)}{\pi}}{\sqrt{2 - \left(v \cdot v\right) \cdot 6} \cdot \left(\left(1 - v \cdot v\right) \cdot t\right)}
\end{array}
Initial program 99.3%
/-lowering-/.f64N/A
sub-negN/A
+-lowering-+.f64N/A
associate-*r*N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
metadata-evalN/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-lowering-*.f64N/A
Simplified99.3%
associate-*l*N/A
associate-/r*N/A
/-lowering-/.f64N/A
/-lowering-/.f64N/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-commutativeN/A
associate-*l*N/A
*-lowering-*.f64N/A
Applied egg-rr99.6%
(FPCore (v t) :precision binary64 (/ (+ 1.0 (* v (* v -5.0))) (* t (* (sqrt (- 2.0 (* (* v v) 6.0))) (* (- 1.0 (* v v)) PI)))))
double code(double v, double t) {
return (1.0 + (v * (v * -5.0))) / (t * (sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * ((double) M_PI))));
}
public static double code(double v, double t) {
return (1.0 + (v * (v * -5.0))) / (t * (Math.sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * Math.PI)));
}
def code(v, t): return (1.0 + (v * (v * -5.0))) / (t * (math.sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * math.pi)))
function code(v, t) return Float64(Float64(1.0 + Float64(v * Float64(v * -5.0))) / Float64(t * Float64(sqrt(Float64(2.0 - Float64(Float64(v * v) * 6.0))) * Float64(Float64(1.0 - Float64(v * v)) * pi)))) end
function tmp = code(v, t) tmp = (1.0 + (v * (v * -5.0))) / (t * (sqrt((2.0 - ((v * v) * 6.0))) * ((1.0 - (v * v)) * pi))); end
code[v_, t_] := N[(N[(1.0 + N[(v * N[(v * -5.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(t * N[(N[Sqrt[N[(2.0 - N[(N[(v * v), $MachinePrecision] * 6.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision] * Pi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1 + v \cdot \left(v \cdot -5\right)}{t \cdot \left(\sqrt{2 - \left(v \cdot v\right) \cdot 6} \cdot \left(\left(1 - v \cdot v\right) \cdot \pi\right)\right)}
\end{array}
Initial program 99.3%
/-lowering-/.f64N/A
sub-negN/A
+-lowering-+.f64N/A
associate-*r*N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
metadata-evalN/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-lowering-*.f64N/A
Simplified99.3%
associate-*l*N/A
*-commutativeN/A
associate-*r*N/A
*-lowering-*.f64N/A
Applied egg-rr99.5%
Final simplification99.5%
(FPCore (v t) :precision binary64 (/ (+ 1.0 (* v (* v -5.0))) (* (* PI t) (* (sqrt (- 2.0 (* (* v v) 6.0))) (- 1.0 (* v v))))))
double code(double v, double t) {
return (1.0 + (v * (v * -5.0))) / ((((double) M_PI) * t) * (sqrt((2.0 - ((v * v) * 6.0))) * (1.0 - (v * v))));
}
public static double code(double v, double t) {
return (1.0 + (v * (v * -5.0))) / ((Math.PI * t) * (Math.sqrt((2.0 - ((v * v) * 6.0))) * (1.0 - (v * v))));
}
def code(v, t): return (1.0 + (v * (v * -5.0))) / ((math.pi * t) * (math.sqrt((2.0 - ((v * v) * 6.0))) * (1.0 - (v * v))))
function code(v, t) return Float64(Float64(1.0 + Float64(v * Float64(v * -5.0))) / Float64(Float64(pi * t) * Float64(sqrt(Float64(2.0 - Float64(Float64(v * v) * 6.0))) * Float64(1.0 - Float64(v * v))))) end
function tmp = code(v, t) tmp = (1.0 + (v * (v * -5.0))) / ((pi * t) * (sqrt((2.0 - ((v * v) * 6.0))) * (1.0 - (v * v)))); end
code[v_, t_] := N[(N[(1.0 + N[(v * N[(v * -5.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(Pi * t), $MachinePrecision] * N[(N[Sqrt[N[(2.0 - N[(N[(v * v), $MachinePrecision] * 6.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1 + v \cdot \left(v \cdot -5\right)}{\left(\pi \cdot t\right) \cdot \left(\sqrt{2 - \left(v \cdot v\right) \cdot 6} \cdot \left(1 - v \cdot v\right)\right)}
\end{array}
Initial program 99.3%
/-lowering-/.f64N/A
sub-negN/A
+-lowering-+.f64N/A
associate-*r*N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
metadata-evalN/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-lowering-*.f64N/A
Simplified99.3%
(FPCore (v t) :precision binary64 (/ (* (+ 1.0 (* (* v v) -4.0)) (/ (/ 1.0 PI) (sqrt 2.0))) t))
double code(double v, double t) {
return ((1.0 + ((v * v) * -4.0)) * ((1.0 / ((double) M_PI)) / sqrt(2.0))) / t;
}
public static double code(double v, double t) {
return ((1.0 + ((v * v) * -4.0)) * ((1.0 / Math.PI) / Math.sqrt(2.0))) / t;
}
def code(v, t): return ((1.0 + ((v * v) * -4.0)) * ((1.0 / math.pi) / math.sqrt(2.0))) / t
function code(v, t) return Float64(Float64(Float64(1.0 + Float64(Float64(v * v) * -4.0)) * Float64(Float64(1.0 / pi) / sqrt(2.0))) / t) end
function tmp = code(v, t) tmp = ((1.0 + ((v * v) * -4.0)) * ((1.0 / pi) / sqrt(2.0))) / t; end
code[v_, t_] := N[(N[(N[(1.0 + N[(N[(v * v), $MachinePrecision] * -4.0), $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 / Pi), $MachinePrecision] / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]
\begin{array}{l}
\\
\frac{\left(1 + \left(v \cdot v\right) \cdot -4\right) \cdot \frac{\frac{1}{\pi}}{\sqrt{2}}}{t}
\end{array}
Initial program 99.3%
/-lowering-/.f64N/A
sub-negN/A
+-lowering-+.f64N/A
associate-*r*N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
metadata-evalN/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-lowering-*.f64N/A
Simplified99.3%
*-rgt-identityN/A
*-commutativeN/A
associate-*r*N/A
times-fracN/A
*-lowering-*.f64N/A
Applied egg-rr99.6%
un-div-invN/A
/-lowering-/.f64N/A
Applied egg-rr99.9%
Taylor expanded in v around 0
sqrt-lowering-sqrt.f6499.2%
Simplified99.2%
Taylor expanded in v around 0
*-commutativeN/A
associate-*l/N/A
associate-*r/N/A
metadata-evalN/A
distribute-neg-fracN/A
metadata-evalN/A
associate-*r/N/A
distribute-lft-neg-inN/A
metadata-evalN/A
associate-*r*N/A
*-commutativeN/A
distribute-lft1-inN/A
*-lowering-*.f64N/A
Simplified99.2%
Final simplification99.2%
(FPCore (v t) :precision binary64 (/ (/ (/ 1.0 PI) (sqrt 2.0)) t))
double code(double v, double t) {
return ((1.0 / ((double) M_PI)) / sqrt(2.0)) / t;
}
public static double code(double v, double t) {
return ((1.0 / Math.PI) / Math.sqrt(2.0)) / t;
}
def code(v, t): return ((1.0 / math.pi) / math.sqrt(2.0)) / t
function code(v, t) return Float64(Float64(Float64(1.0 / pi) / sqrt(2.0)) / t) end
function tmp = code(v, t) tmp = ((1.0 / pi) / sqrt(2.0)) / t; end
code[v_, t_] := N[(N[(N[(1.0 / Pi), $MachinePrecision] / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{\frac{1}{\pi}}{\sqrt{2}}}{t}
\end{array}
Initial program 99.3%
/-lowering-/.f64N/A
sub-negN/A
+-lowering-+.f64N/A
associate-*r*N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
metadata-evalN/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-lowering-*.f64N/A
Simplified99.3%
*-rgt-identityN/A
*-commutativeN/A
associate-*r*N/A
times-fracN/A
*-lowering-*.f64N/A
Applied egg-rr99.6%
un-div-invN/A
/-lowering-/.f64N/A
Applied egg-rr99.9%
Taylor expanded in v around 0
sqrt-lowering-sqrt.f6499.2%
Simplified99.2%
Taylor expanded in v around 0
associate-/r*N/A
/-lowering-/.f64N/A
/-lowering-/.f64N/A
PI-lowering-PI.f64N/A
sqrt-lowering-sqrt.f6499.1%
Simplified99.1%
(FPCore (v t) :precision binary64 (/ (/ 1.0 t) (/ PI (sqrt 0.5))))
double code(double v, double t) {
return (1.0 / t) / (((double) M_PI) / sqrt(0.5));
}
public static double code(double v, double t) {
return (1.0 / t) / (Math.PI / Math.sqrt(0.5));
}
def code(v, t): return (1.0 / t) / (math.pi / math.sqrt(0.5))
function code(v, t) return Float64(Float64(1.0 / t) / Float64(pi / sqrt(0.5))) end
function tmp = code(v, t) tmp = (1.0 / t) / (pi / sqrt(0.5)); end
code[v_, t_] := N[(N[(1.0 / t), $MachinePrecision] / N[(Pi / N[Sqrt[0.5], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{1}{t}}{\frac{\pi}{\sqrt{0.5}}}
\end{array}
Initial program 99.3%
/-lowering-/.f64N/A
sub-negN/A
+-lowering-+.f64N/A
associate-*r*N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
metadata-evalN/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-lowering-*.f64N/A
Simplified99.3%
Taylor expanded in v around 0
/-lowering-/.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6498.3%
Simplified98.3%
associate-/r*N/A
/-lowering-/.f64N/A
/-lowering-/.f64N/A
sqrt-lowering-sqrt.f64N/A
PI-lowering-PI.f6498.2%
Applied egg-rr98.2%
clear-numN/A
div-invN/A
associate-/r*N/A
clear-numN/A
/-lowering-/.f64N/A
/-lowering-/.f64N/A
/-lowering-/.f64N/A
PI-lowering-PI.f64N/A
sqrt-lowering-sqrt.f6498.8%
Applied egg-rr98.8%
(FPCore (v t) :precision binary64 (/ 1.0 (* t (/ PI (sqrt 0.5)))))
double code(double v, double t) {
return 1.0 / (t * (((double) M_PI) / sqrt(0.5)));
}
public static double code(double v, double t) {
return 1.0 / (t * (Math.PI / Math.sqrt(0.5)));
}
def code(v, t): return 1.0 / (t * (math.pi / math.sqrt(0.5)))
function code(v, t) return Float64(1.0 / Float64(t * Float64(pi / sqrt(0.5)))) end
function tmp = code(v, t) tmp = 1.0 / (t * (pi / sqrt(0.5))); end
code[v_, t_] := N[(1.0 / N[(t * N[(Pi / N[Sqrt[0.5], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{t \cdot \frac{\pi}{\sqrt{0.5}}}
\end{array}
Initial program 99.3%
/-lowering-/.f64N/A
sub-negN/A
+-lowering-+.f64N/A
associate-*r*N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
metadata-evalN/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-lowering-*.f64N/A
Simplified99.3%
Taylor expanded in v around 0
/-lowering-/.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6498.3%
Simplified98.3%
clear-numN/A
/-lowering-/.f64N/A
associate-/l*N/A
*-lowering-*.f64N/A
/-lowering-/.f64N/A
PI-lowering-PI.f64N/A
sqrt-lowering-sqrt.f6498.8%
Applied egg-rr98.8%
(FPCore (v t) :precision binary64 (* (sqrt 0.5) (/ 1.0 (* PI t))))
double code(double v, double t) {
return sqrt(0.5) * (1.0 / (((double) M_PI) * t));
}
public static double code(double v, double t) {
return Math.sqrt(0.5) * (1.0 / (Math.PI * t));
}
def code(v, t): return math.sqrt(0.5) * (1.0 / (math.pi * t))
function code(v, t) return Float64(sqrt(0.5) * Float64(1.0 / Float64(pi * t))) end
function tmp = code(v, t) tmp = sqrt(0.5) * (1.0 / (pi * t)); end
code[v_, t_] := N[(N[Sqrt[0.5], $MachinePrecision] * N[(1.0 / N[(Pi * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{0.5} \cdot \frac{1}{\pi \cdot t}
\end{array}
Initial program 99.3%
/-lowering-/.f64N/A
sub-negN/A
+-lowering-+.f64N/A
associate-*r*N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
metadata-evalN/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-lowering-*.f64N/A
Simplified99.3%
Taylor expanded in v around 0
/-lowering-/.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6498.3%
Simplified98.3%
clear-numN/A
*-commutativeN/A
associate-/r/N/A
*-lowering-*.f64N/A
/-lowering-/.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
sqrt-lowering-sqrt.f6498.4%
Applied egg-rr98.4%
Final simplification98.4%
(FPCore (v t) :precision binary64 (/ (sqrt 0.5) (* PI t)))
double code(double v, double t) {
return sqrt(0.5) / (((double) M_PI) * t);
}
public static double code(double v, double t) {
return Math.sqrt(0.5) / (Math.PI * t);
}
def code(v, t): return math.sqrt(0.5) / (math.pi * t)
function code(v, t) return Float64(sqrt(0.5) / Float64(pi * t)) end
function tmp = code(v, t) tmp = sqrt(0.5) / (pi * t); end
code[v_, t_] := N[(N[Sqrt[0.5], $MachinePrecision] / N[(Pi * t), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\sqrt{0.5}}{\pi \cdot t}
\end{array}
Initial program 99.3%
/-lowering-/.f64N/A
sub-negN/A
+-lowering-+.f64N/A
associate-*r*N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
*-commutativeN/A
distribute-rgt-neg-inN/A
*-lowering-*.f64N/A
metadata-evalN/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f64N/A
*-lowering-*.f64N/A
Simplified99.3%
Taylor expanded in v around 0
/-lowering-/.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f64N/A
PI-lowering-PI.f6498.3%
Simplified98.3%
Final simplification98.3%
herbie shell --seed 2024152
(FPCore (v t)
:name "Falkner and Boettcher, Equation (20:1,3)"
:precision binary64
(/ (- 1.0 (* 5.0 (* v v))) (* (* (* PI t) (sqrt (* 2.0 (- 1.0 (* 3.0 (* v v)))))) (- 1.0 (* v v)))))