Average Error: 62.0 → 51.5
Time: 2.3s
Precision: binary64
\[lo < -1 \cdot 10^{+308} \land hi > 10^{+308}\]
\[\frac{x - lo}{hi - lo} \]
\[\left(\frac{{\left(\sqrt[3]{hi}\right)}^{2}}{lo} \cdot \frac{\sqrt[3]{hi}}{lo}\right) \cdot \left(hi - x\right) \]
(FPCore (lo hi x) :precision binary64 (/ (- x lo) (- hi lo)))
(FPCore (lo hi x)
 :precision binary64
 (* (* (/ (pow (cbrt hi) 2.0) lo) (/ (cbrt hi) lo)) (- hi x)))
double code(double lo, double hi, double x) {
	return (x - lo) / (hi - lo);
}
double code(double lo, double hi, double x) {
	return ((pow(cbrt(hi), 2.0) / lo) * (cbrt(hi) / lo)) * (hi - x);
}
public static double code(double lo, double hi, double x) {
	return (x - lo) / (hi - lo);
}
public static double code(double lo, double hi, double x) {
	return ((Math.pow(Math.cbrt(hi), 2.0) / lo) * (Math.cbrt(hi) / lo)) * (hi - x);
}
function code(lo, hi, x)
	return Float64(Float64(x - lo) / Float64(hi - lo))
end
function code(lo, hi, x)
	return Float64(Float64(Float64((cbrt(hi) ^ 2.0) / lo) * Float64(cbrt(hi) / lo)) * Float64(hi - x))
end
code[lo_, hi_, x_] := N[(N[(x - lo), $MachinePrecision] / N[(hi - lo), $MachinePrecision]), $MachinePrecision]
code[lo_, hi_, x_] := N[(N[(N[(N[Power[N[Power[hi, 1/3], $MachinePrecision], 2.0], $MachinePrecision] / lo), $MachinePrecision] * N[(N[Power[hi, 1/3], $MachinePrecision] / lo), $MachinePrecision]), $MachinePrecision] * N[(hi - x), $MachinePrecision]), $MachinePrecision]
\frac{x - lo}{hi - lo}
\left(\frac{{\left(\sqrt[3]{hi}\right)}^{2}}{lo} \cdot \frac{\sqrt[3]{hi}}{lo}\right) \cdot \left(hi - x\right)

Error

Bits error versus lo

Bits error versus hi

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 62.0

    \[\frac{x - lo}{hi - lo} \]
  2. Taylor expanded in lo around inf 64.0

    \[\leadsto \color{blue}{\left(1 + \left(\frac{hi}{lo} + \frac{{hi}^{2}}{{lo}^{2}}\right)\right) - \left(\frac{hi \cdot x}{{lo}^{2}} + \frac{x}{lo}\right)} \]
  3. Simplified51.9

    \[\leadsto \color{blue}{\frac{hi}{lo} + \left(1 + \left(\frac{hi}{lo} \cdot \left(\frac{hi}{lo} - \frac{x}{lo}\right) - \frac{x}{lo}\right)\right)} \]
  4. Taylor expanded in lo around 0 64.0

    \[\leadsto \color{blue}{\frac{{hi}^{2} - hi \cdot x}{{lo}^{2}}} \]
  5. Simplified51.5

    \[\leadsto \color{blue}{\frac{\frac{hi}{lo}}{lo} \cdot \left(hi - x\right)} \]
  6. Applied egg-rr51.5

    \[\leadsto \color{blue}{\left(\frac{{\left(\sqrt[3]{hi}\right)}^{2}}{lo} \cdot \frac{\sqrt[3]{hi}}{lo}\right)} \cdot \left(hi - x\right) \]
  7. Final simplification51.5

    \[\leadsto \left(\frac{{\left(\sqrt[3]{hi}\right)}^{2}}{lo} \cdot \frac{\sqrt[3]{hi}}{lo}\right) \cdot \left(hi - x\right) \]

Reproduce

herbie shell --seed 2022151 
(FPCore (lo hi x)
  :name "(/ (- x lo) (- hi lo))"
  :precision binary64
  :pre (and (< lo -1e+308) (> hi 1e+308))
  (/ (- x lo) (- hi lo)))