Average Error: 62.0 → 51.9
Time: 2.9s
Precision: binary64
\[lo < -1 \cdot 10^{+308} \land hi > 10^{+308}\]
\[\frac{x - lo}{hi - lo} \]
↓
\[\frac{x}{hi} + \left(\mathsf{fma}\left(\frac{x}{hi}, \frac{lo}{hi} \cdot \frac{lo}{hi}, \frac{lo}{hi} \cdot \left(-1 - \frac{lo}{hi}\right)\right) - {\left(\frac{lo}{hi}\right)}^{3}\right) \]
(FPCore (lo hi x) :precision binary64 (/ (- x lo) (- hi lo)))
↓
(FPCore (lo hi x)
 :precision binary64
 (+
  (/ x hi)
  (-
   (fma (/ x hi) (* (/ lo hi) (/ lo hi)) (* (/ lo hi) (- -1.0 (/ lo hi))))
   (pow (/ lo hi) 3.0))))
double code(double lo, double hi, double x) {
	return (x - lo) / (hi - lo);
}
↓
double code(double lo, double hi, double x) {
	return (x / hi) + (fma((x / hi), ((lo / hi) * (lo / hi)), ((lo / hi) * (-1.0 - (lo / hi)))) - pow((lo / hi), 3.0));
}

function code(lo, hi, x)
	return Float64(Float64(x - lo) / Float64(hi - lo))
end
↓
function code(lo, hi, x)
	return Float64(Float64(x / hi) + Float64(fma(Float64(x / hi), Float64(Float64(lo / hi) * Float64(lo / hi)), Float64(Float64(lo / hi) * Float64(-1.0 - Float64(lo / hi)))) - (Float64(lo / hi) ^ 3.0)))
end

code[lo_, hi_, x_] := N[(N[(x - lo), $MachinePrecision] / N[(hi - lo), $MachinePrecision]), $MachinePrecision]
↓
code[lo_, hi_, x_] := N[(N[(x / hi), $MachinePrecision] + N[(N[(N[(x / hi), $MachinePrecision] * N[(N[(lo / hi), $MachinePrecision] * N[(lo / hi), $MachinePrecision]), $MachinePrecision] + N[(N[(lo / hi), $MachinePrecision] * N[(-1.0 - N[(lo / hi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[(lo / hi), $MachinePrecision], 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

\frac{x - lo}{hi - lo}
↓
\frac{x}{hi} + \left(\mathsf{fma}\left(\frac{x}{hi}, \frac{lo}{hi} \cdot \frac{lo}{hi}, \frac{lo}{hi} \cdot \left(-1 - \frac{lo}{hi}\right)\right) - {\left(\frac{lo}{hi}\right)}^{3}\right)

Error

Bits error versus lo

Bits error versus hi

Bits error versus x

Derivation

  1. Initial program 62.0

    \[\frac{x - lo}{hi - lo} \]

  2. Taylor expanded in hi around inf 64.0

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

  3. Simplified51.9

    \[\leadsto \color{blue}{\frac{x}{hi} + \left(\mathsf{fma}\left(\frac{x}{hi}, \left(\frac{lo}{hi} + 1\right) \cdot \frac{lo}{hi}, \frac{lo}{hi} \cdot \left(-1 - \frac{lo}{hi}\right)\right) - {\left(\frac{lo}{hi}\right)}^{3}\right)} \]

  4. Taylor expanded in lo around inf 51.9

    \[\leadsto \frac{x}{hi} + \left(\mathsf{fma}\left(\frac{x}{hi}, \color{blue}{\frac{lo}{hi}} \cdot \frac{lo}{hi}, \frac{lo}{hi} \cdot \left(-1 - \frac{lo}{hi}\right)\right) - {\left(\frac{lo}{hi}\right)}^{3}\right) \]

  5. Final simplification51.9

    \[\leadsto \frac{x}{hi} + \left(\mathsf{fma}\left(\frac{x}{hi}, \frac{lo}{hi} \cdot \frac{lo}{hi}, \frac{lo}{hi} \cdot \left(-1 - \frac{lo}{hi}\right)\right) - {\left(\frac{lo}{hi}\right)}^{3}\right) \]

Reproduce

herbie shell --seed 2022137 
(FPCore (lo hi x)
  :name "(/ (- x lo) (- hi lo))"
  :precision binary64
  :pre (and (< lo -1e+308) (> hi 1e+308))
  (/ (- x lo) (- hi lo)))