Average Error: 33.2 → 0.4
Time: 5.3s
Precision: binary64
\[\frac{x \cdot x}{y \cdot y} + \frac{z \cdot z}{t \cdot t} \]
\[\frac{\frac{x}{y}}{\frac{y}{x}} + {\left(\frac{z}{t}\right)}^{2} \]
(FPCore (x y z t)
 :precision binary64
 (+ (/ (* x x) (* y y)) (/ (* z z) (* t t))))
(FPCore (x y z t)
 :precision binary64
 (+ (/ (/ x y) (/ y x)) (pow (/ z t) 2.0)))
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) / (y / x)) + pow((z / t), 2.0);
}
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) / (y / x)) + ((z / t) ** 2.0d0)
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) / (y / x)) + Math.pow((z / t), 2.0);
}
def code(x, y, z, t):
	return ((x * x) / (y * y)) + ((z * z) / (t * t))
def code(x, y, z, t):
	return ((x / y) / (y / x)) + math.pow((z / t), 2.0)
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(y / x)) + (Float64(z / t) ^ 2.0))
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) / (y / x)) + ((z / t) ^ 2.0);
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[(y / x), $MachinePrecision]), $MachinePrecision] + N[Power[N[(z / t), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]
\frac{x \cdot x}{y \cdot y} + \frac{z \cdot z}{t \cdot t}
\frac{\frac{x}{y}}{\frac{y}{x}} + {\left(\frac{z}{t}\right)}^{2}

Error

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original33.2
Target0.4
Herbie0.4
\[{\left(\frac{x}{y}\right)}^{2} + {\left(\frac{z}{t}\right)}^{2} \]

Derivation

  1. Initial program 33.2

    \[\frac{x \cdot x}{y \cdot y} + \frac{z \cdot z}{t \cdot t} \]
  2. Simplified13.4

    \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{z}{t}, \frac{z}{t}, x \cdot \frac{x}{y \cdot y}\right)} \]
  3. Applied egg-rr0.4

    \[\leadsto \color{blue}{{\left(\frac{x}{y}\right)}^{2} + {\left(\frac{z}{t}\right)}^{2}} \]
  4. Applied egg-rr0.4

    \[\leadsto \color{blue}{\frac{\frac{x}{y}}{\frac{y}{x}}} + {\left(\frac{z}{t}\right)}^{2} \]
  5. Final simplification0.4

    \[\leadsto \frac{\frac{x}{y}}{\frac{y}{x}} + {\left(\frac{z}{t}\right)}^{2} \]

Reproduce

herbie shell --seed 2022210 
(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))))