
(FPCore (a b) :precision binary64 (* (* (/ PI 2.0) (/ 1.0 (- (* b b) (* a a)))) (- (/ 1.0 a) (/ 1.0 b))))
double code(double a, double b) {
return ((((double) M_PI) / 2.0) * (1.0 / ((b * b) - (a * a)))) * ((1.0 / a) - (1.0 / b));
}
public static double code(double a, double b) {
return ((Math.PI / 2.0) * (1.0 / ((b * b) - (a * a)))) * ((1.0 / a) - (1.0 / b));
}
def code(a, b): return ((math.pi / 2.0) * (1.0 / ((b * b) - (a * a)))) * ((1.0 / a) - (1.0 / b))
function code(a, b) return Float64(Float64(Float64(pi / 2.0) * Float64(1.0 / Float64(Float64(b * b) - Float64(a * a)))) * Float64(Float64(1.0 / a) - Float64(1.0 / b))) end
function tmp = code(a, b) tmp = ((pi / 2.0) * (1.0 / ((b * b) - (a * a)))) * ((1.0 / a) - (1.0 / b)); end
code[a_, b_] := N[(N[(N[(Pi / 2.0), $MachinePrecision] * N[(1.0 / N[(N[(b * b), $MachinePrecision] - N[(a * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 / a), $MachinePrecision] - N[(1.0 / b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\frac{\pi}{2} \cdot \frac{1}{b \cdot b - a \cdot a}\right) \cdot \left(\frac{1}{a} - \frac{1}{b}\right)
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 3 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (a b) :precision binary64 (* (* (/ PI 2.0) (/ 1.0 (- (* b b) (* a a)))) (- (/ 1.0 a) (/ 1.0 b))))
double code(double a, double b) {
return ((((double) M_PI) / 2.0) * (1.0 / ((b * b) - (a * a)))) * ((1.0 / a) - (1.0 / b));
}
public static double code(double a, double b) {
return ((Math.PI / 2.0) * (1.0 / ((b * b) - (a * a)))) * ((1.0 / a) - (1.0 / b));
}
def code(a, b): return ((math.pi / 2.0) * (1.0 / ((b * b) - (a * a)))) * ((1.0 / a) - (1.0 / b))
function code(a, b) return Float64(Float64(Float64(pi / 2.0) * Float64(1.0 / Float64(Float64(b * b) - Float64(a * a)))) * Float64(Float64(1.0 / a) - Float64(1.0 / b))) end
function tmp = code(a, b) tmp = ((pi / 2.0) * (1.0 / ((b * b) - (a * a)))) * ((1.0 / a) - (1.0 / b)); end
code[a_, b_] := N[(N[(N[(Pi / 2.0), $MachinePrecision] * N[(1.0 / N[(N[(b * b), $MachinePrecision] - N[(a * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 / a), $MachinePrecision] - N[(1.0 / b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\frac{\pi}{2} \cdot \frac{1}{b \cdot b - a \cdot a}\right) \cdot \left(\frac{1}{a} - \frac{1}{b}\right)
\end{array}
(FPCore (a b) :precision binary64 (/ (* 0.5 (/ PI (* a b))) (+ a b)))
double code(double a, double b) {
return (0.5 * (((double) M_PI) / (a * b))) / (a + b);
}
public static double code(double a, double b) {
return (0.5 * (Math.PI / (a * b))) / (a + b);
}
def code(a, b): return (0.5 * (math.pi / (a * b))) / (a + b)
function code(a, b) return Float64(Float64(0.5 * Float64(pi / Float64(a * b))) / Float64(a + b)) end
function tmp = code(a, b) tmp = (0.5 * (pi / (a * b))) / (a + b); end
code[a_, b_] := N[(N[(0.5 * N[(Pi / N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(a + b), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{0.5 \cdot \frac{\pi}{a \cdot b}}{a + b}
\end{array}
Initial program 75.8%
*-commutative75.8%
associate-*r*75.8%
associate-*r/75.9%
associate-*r*75.9%
*-rgt-identity75.9%
sub-neg75.9%
distribute-neg-frac75.9%
metadata-eval75.9%
Simplified75.9%
*-commutative75.9%
difference-of-squares86.8%
times-frac99.7%
div-inv99.7%
metadata-eval99.7%
add-sqr-sqrt48.6%
sqrt-unprod67.3%
frac-times67.3%
metadata-eval67.3%
metadata-eval67.3%
frac-times67.3%
sqrt-unprod29.6%
add-sqr-sqrt61.0%
Applied egg-rr61.0%
associate-*l/61.0%
*-commutative61.0%
+-commutative61.0%
+-commutative61.0%
Simplified61.0%
Taylor expanded in b around inf 99.7%
Final simplification99.7%
(FPCore (a b) :precision binary64 (* 0.5 (/ PI (* (* a b) (+ a b)))))
double code(double a, double b) {
return 0.5 * (((double) M_PI) / ((a * b) * (a + b)));
}
public static double code(double a, double b) {
return 0.5 * (Math.PI / ((a * b) * (a + b)));
}
def code(a, b): return 0.5 * (math.pi / ((a * b) * (a + b)))
function code(a, b) return Float64(0.5 * Float64(pi / Float64(Float64(a * b) * Float64(a + b)))) end
function tmp = code(a, b) tmp = 0.5 * (pi / ((a * b) * (a + b))); end
code[a_, b_] := N[(0.5 * N[(Pi / N[(N[(a * b), $MachinePrecision] * N[(a + b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.5 \cdot \frac{\pi}{\left(a \cdot b\right) \cdot \left(a + b\right)}
\end{array}
Initial program 75.8%
*-commutative75.8%
associate-*r*75.8%
associate-*r/75.9%
associate-*r*75.9%
*-rgt-identity75.9%
sub-neg75.9%
distribute-neg-frac75.9%
metadata-eval75.9%
Simplified75.9%
*-commutative75.9%
difference-of-squares86.8%
times-frac99.7%
div-inv99.7%
metadata-eval99.7%
add-sqr-sqrt48.6%
sqrt-unprod67.3%
frac-times67.3%
metadata-eval67.3%
metadata-eval67.3%
frac-times67.3%
sqrt-unprod29.6%
add-sqr-sqrt61.0%
Applied egg-rr61.0%
associate-*l/61.0%
*-commutative61.0%
+-commutative61.0%
+-commutative61.0%
Simplified61.0%
Taylor expanded in b around inf 99.7%
associate-/l*99.7%
Applied egg-rr99.7%
associate-/l/98.6%
*-commutative98.6%
Simplified98.6%
Final simplification98.6%
(FPCore (a b) :precision binary64 (* (/ PI (+ a b)) (/ 0.5 (* a b))))
double code(double a, double b) {
return (((double) M_PI) / (a + b)) * (0.5 / (a * b));
}
public static double code(double a, double b) {
return (Math.PI / (a + b)) * (0.5 / (a * b));
}
def code(a, b): return (math.pi / (a + b)) * (0.5 / (a * b))
function code(a, b) return Float64(Float64(pi / Float64(a + b)) * Float64(0.5 / Float64(a * b))) end
function tmp = code(a, b) tmp = (pi / (a + b)) * (0.5 / (a * b)); end
code[a_, b_] := N[(N[(Pi / N[(a + b), $MachinePrecision]), $MachinePrecision] * N[(0.5 / N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\pi}{a + b} \cdot \frac{0.5}{a \cdot b}
\end{array}
Initial program 75.8%
*-commutative75.8%
associate-*r*75.8%
associate-*r/75.9%
associate-*r*75.9%
*-rgt-identity75.9%
sub-neg75.9%
distribute-neg-frac75.9%
metadata-eval75.9%
Simplified75.9%
*-commutative75.9%
difference-of-squares86.8%
times-frac99.7%
div-inv99.7%
metadata-eval99.7%
add-sqr-sqrt48.6%
sqrt-unprod67.3%
frac-times67.3%
metadata-eval67.3%
metadata-eval67.3%
frac-times67.3%
sqrt-unprod29.6%
add-sqr-sqrt61.0%
Applied egg-rr61.0%
associate-*l/61.0%
*-commutative61.0%
+-commutative61.0%
+-commutative61.0%
Simplified61.0%
Taylor expanded in b around inf 99.7%
associate-/r*99.6%
Simplified99.6%
associate-/r*99.7%
un-div-inv99.7%
associate-/r*98.6%
*-commutative98.6%
*-commutative98.6%
times-frac99.7%
Applied egg-rr99.7%
Final simplification99.7%
herbie shell --seed 2024066
(FPCore (a b)
:name "NMSE Section 6.1 mentioned, B"
:precision binary64
(* (* (/ PI 2.0) (/ 1.0 (- (* b b) (* a a)))) (- (/ 1.0 a) (/ 1.0 b))))