Average Error: 0.1 → 0.0
Time: 2.6s
Precision: binary64
\[\frac{4 \cdot \left(\left(x - y\right) - z \cdot 0.5\right)}{z} \]
\[4 \cdot \frac{x}{z} - \mathsf{fma}\left(\frac{y}{z}, 4, 2\right) \]
(FPCore (x y z) :precision binary64 (/ (* 4.0 (- (- x y) (* z 0.5))) z))
(FPCore (x y z) :precision binary64 (- (* 4.0 (/ x z)) (fma (/ y z) 4.0 2.0)))
double code(double x, double y, double z) {
	return (4.0 * ((x - y) - (z * 0.5))) / z;
}
double code(double x, double y, double z) {
	return (4.0 * (x / z)) - fma((y / z), 4.0, 2.0);
}
function code(x, y, z)
	return Float64(Float64(4.0 * Float64(Float64(x - y) - Float64(z * 0.5))) / z)
end
function code(x, y, z)
	return Float64(Float64(4.0 * Float64(x / z)) - fma(Float64(y / z), 4.0, 2.0))
end
code[x_, y_, z_] := N[(N[(4.0 * N[(N[(x - y), $MachinePrecision] - N[(z * 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / z), $MachinePrecision]
code[x_, y_, z_] := N[(N[(4.0 * N[(x / z), $MachinePrecision]), $MachinePrecision] - N[(N[(y / z), $MachinePrecision] * 4.0 + 2.0), $MachinePrecision]), $MachinePrecision]
\frac{4 \cdot \left(\left(x - y\right) - z \cdot 0.5\right)}{z}
4 \cdot \frac{x}{z} - \mathsf{fma}\left(\frac{y}{z}, 4, 2\right)

Error

Bits error versus x

Bits error versus y

Bits error versus z

Target

Original0.1
Target0.0
Herbie0.0
\[4 \cdot \frac{x}{z} - \left(2 + 4 \cdot \frac{y}{z}\right) \]

Derivation

  1. Initial program 0.1

    \[\frac{4 \cdot \left(\left(x - y\right) - z \cdot 0.5\right)}{z} \]
  2. Taylor expanded in x around 0 0.0

    \[\leadsto \color{blue}{4 \cdot \frac{x}{z} - \left(2 + 4 \cdot \frac{y}{z}\right)} \]
  3. Applied egg-rr0.0

    \[\leadsto 4 \cdot \frac{x}{z} - \color{blue}{\mathsf{fma}\left(\frac{y}{z}, 4, 2\right)} \]
  4. Final simplification0.0

    \[\leadsto 4 \cdot \frac{x}{z} - \mathsf{fma}\left(\frac{y}{z}, 4, 2\right) \]

Reproduce

herbie shell --seed 2022166 
(FPCore (x y z)
  :name "Data.Array.Repa.Algorithms.ColorRamp:rampColorHotToCold from repa-algorithms-3.4.0.1, B"
  :precision binary64

  :herbie-target
  (- (* 4.0 (/ x z)) (+ 2.0 (* 4.0 (/ y z))))

  (/ (* 4.0 (- (- x y) (* z 0.5))) z))