| Alternative 1 | |
|---|---|
| Error | 29.6 |
| Cost | 960 |
\[x \cdot \frac{x}{y \cdot y} + \frac{z \cdot z}{t \cdot t}
\]
(FPCore (x y z t) :precision binary64 (+ (/ (* x x) (* y y)) (/ (* z z) (* t t))))
(FPCore (x y z t) :precision binary64 (+ (* (/ x y) (/ x y)) (* (/ z t) (/ z t))))
double code(double x, double y, double z, double t) {
return ((x * x) / (y * y)) + ((z * z) / (t * t));
}
double code(double x, double y, double z, double t) {
return ((x / y) * (x / y)) + ((z / t) * (z / t));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = ((x * x) / (y * y)) + ((z * z) / (t * t))
end function
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = ((x / y) * (x / y)) + ((z / t) * (z / t))
end function
public static double code(double x, double y, double z, double t) {
return ((x * x) / (y * y)) + ((z * z) / (t * t));
}
public static double code(double x, double y, double z, double t) {
return ((x / y) * (x / y)) + ((z / t) * (z / t));
}
def code(x, y, z, t): return ((x * x) / (y * y)) + ((z * z) / (t * t))
def code(x, y, z, t): return ((x / y) * (x / y)) + ((z / t) * (z / t))
function code(x, y, z, t) return Float64(Float64(Float64(x * x) / Float64(y * y)) + Float64(Float64(z * z) / Float64(t * t))) end
function code(x, y, z, t) return Float64(Float64(Float64(x / y) * Float64(x / y)) + Float64(Float64(z / t) * Float64(z / t))) end
function tmp = code(x, y, z, t) tmp = ((x * x) / (y * y)) + ((z * z) / (t * t)); end
function tmp = code(x, y, z, t) tmp = ((x / y) * (x / y)) + ((z / t) * (z / t)); end
code[x_, y_, z_, t_] := N[(N[(N[(x * x), $MachinePrecision] / N[(y * y), $MachinePrecision]), $MachinePrecision] + N[(N[(z * z), $MachinePrecision] / N[(t * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_, y_, z_, t_] := N[(N[(N[(x / y), $MachinePrecision] * N[(x / y), $MachinePrecision]), $MachinePrecision] + N[(N[(z / t), $MachinePrecision] * N[(z / t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{x \cdot x}{y \cdot y} + \frac{z \cdot z}{t \cdot t}
\frac{x}{y} \cdot \frac{x}{y} + \frac{z}{t} \cdot \frac{z}{t}
Results
| Original | 33.7 |
|---|---|
| Target | 0.4 |
| Herbie | 0.4 |
Initial program 33.7
Simplified0.4
[Start]33.7 | \[ \frac{x \cdot x}{y \cdot y} + \frac{z \cdot z}{t \cdot t}
\] |
|---|---|
rational.json-simplify-46 [=>]29.6 | \[ \color{blue}{\frac{\frac{x \cdot x}{y}}{y}} + \frac{z \cdot z}{t \cdot t}
\] |
rational.json-simplify-49 [=>]22.4 | \[ \frac{\color{blue}{x \cdot \frac{x}{y}}}{y} + \frac{z \cdot z}{t \cdot t}
\] |
rational.json-simplify-49 [=>]19.2 | \[ \color{blue}{\frac{x}{y} \cdot \frac{x}{y}} + \frac{z \cdot z}{t \cdot t}
\] |
rational.json-simplify-46 [=>]13.6 | \[ \frac{x}{y} \cdot \frac{x}{y} + \color{blue}{\frac{\frac{z \cdot z}{t}}{t}}
\] |
rational.json-simplify-49 [=>]4.6 | \[ \frac{x}{y} \cdot \frac{x}{y} + \frac{\color{blue}{z \cdot \frac{z}{t}}}{t}
\] |
rational.json-simplify-49 [=>]0.4 | \[ \frac{x}{y} \cdot \frac{x}{y} + \color{blue}{\frac{z}{t} \cdot \frac{z}{t}}
\] |
Final simplification0.4
| Alternative 1 | |
|---|---|
| Error | 29.6 |
| Cost | 960 |
| Alternative 2 | |
|---|---|
| Error | 16.6 |
| Cost | 960 |
| Alternative 3 | |
|---|---|
| Error | 7.8 |
| Cost | 960 |
| Alternative 4 | |
|---|---|
| Error | 7.8 |
| Cost | 960 |
| Alternative 5 | |
|---|---|
| Error | 4.1 |
| Cost | 960 |
herbie shell --seed 2023064
(FPCore (x y z t)
:name "Graphics.Rasterific.Svg.PathConverter:arcToSegments from rasterific-svg-0.2.3.1"
:precision binary64
:herbie-target
(+ (pow (/ x y) 2.0) (pow (/ z t) 2.0))
(+ (/ (* x x) (* y y)) (/ (* z z) (* t t))))