Data.Array.Repa.Algorithms.ColorRamp:rampColorHotToCold from repa-algorithms-3.4.0.1, C

Average Accuracy: 99.9% → 99.7%

Time: 7.4s

Precision: binary64

Cost: 6848

Math

\[1 + \frac{4 \cdot \left(\left(x + y \cdot 0.25\right) - z\right)}{y} \]

↓

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

FPCore

(FPCore (x y z)
 :precision binary64
 (+ 1.0 (/ (* 4.0 (- (+ x (* y 0.25)) z)) y)))

↓

(FPCore (x y z) :precision binary64 (fma (/ -4.0 y) (- z x) 2.0))

C

double code(double x, double y, double z) {
	return 1.0 + ((4.0 * ((x + (y * 0.25)) - z)) / y);
}

↓

double code(double x, double y, double z) {
	return fma((-4.0 / y), (z - x), 2.0);
}

Julia

function code(x, y, z)
	return Float64(1.0 + Float64(Float64(4.0 * Float64(Float64(x + Float64(y * 0.25)) - z)) / y))
end

↓

function code(x, y, z)
	return fma(Float64(-4.0 / y), Float64(z - x), 2.0)
end

Wolfram

code[x_, y_, z_] := N[(1.0 + N[(N[(4.0 * N[(N[(x + N[(y * 0.25), $MachinePrecision]), $MachinePrecision] - z), $MachinePrecision]), $MachinePrecision] / y), $MachinePrecision]), $MachinePrecision]

↓

code[x_, y_, z_] := N[(N[(-4.0 / y), $MachinePrecision] * N[(z - x), $MachinePrecision] + 2.0), $MachinePrecision]

Derivation

1. Initial program 99.9%

   \[1 + \frac{4 \cdot \left(\left(x + y \cdot 0.25\right) - z\right)}{y} \]

2. Simplified 99.7%

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

   [Start] 99.9	\[ 1 + \frac{4 \cdot \left(\left(x + y \cdot 0.25\right) - z\right)}{y} \]
   associate-*l/ [<=] 99.7	\[ 1 + \color{blue}{\frac{4}{y} \cdot \left(\left(x + y \cdot 0.25\right) - z\right)} \]
   +-commutative [=>] 99.7	\[ 1 + \frac{4}{y} \cdot \left(\color{blue}{\left(y \cdot 0.25 + x\right)} - z\right) \]
   associate--l+ [=>] 99.7	\[ 1 + \frac{4}{y} \cdot \color{blue}{\left(y \cdot 0.25 + \left(x - z\right)\right)} \]
   +-commutative [=>] 99.7	\[ 1 + \frac{4}{y} \cdot \color{blue}{\left(\left(x - z\right) + y \cdot 0.25\right)} \]
   distribute-lft-in [=>] 99.7	\[ 1 + \color{blue}{\left(\frac{4}{y} \cdot \left(x - z\right) + \frac{4}{y} \cdot \left(y \cdot 0.25\right)\right)} \]
   *-commutative [<=] 99.7	\[ 1 + \left(\color{blue}{\left(x - z\right) \cdot \frac{4}{y}} + \frac{4}{y} \cdot \left(y \cdot 0.25\right)\right) \]
   associate-+r+ [=>] 99.7	\[ \color{blue}{\left(1 + \left(x - z\right) \cdot \frac{4}{y}\right) + \frac{4}{y} \cdot \left(y \cdot 0.25\right)} \]
   +-commutative [<=] 99.7	\[ \color{blue}{\left(\left(x - z\right) \cdot \frac{4}{y} + 1\right)} + \frac{4}{y} \cdot \left(y \cdot 0.25\right) \]
   associate-+r+ [<=] 99.7	\[ \color{blue}{\left(x - z\right) \cdot \frac{4}{y} + \left(1 + \frac{4}{y} \cdot \left(y \cdot 0.25\right)\right)} \]
   *-commutative [=>] 99.7	\[ \color{blue}{\frac{4}{y} \cdot \left(x - z\right)} + \left(1 + \frac{4}{y} \cdot \left(y \cdot 0.25\right)\right) \]

3. Final simplification 99.7%

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

Alternatives

Alternative 1
Accuracy	52.3%
Cost	980

\[\begin{array}{l} t_0 := -4 \cdot \frac{z}{y}\\ \mathbf{if}\;y \leq -1.9 \cdot 10^{+81}:\\ \;\;\;\;2\\ \mathbf{elif}\;y \leq -1.3 \cdot 10^{+64}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y \leq -122000000000:\\ \;\;\;\;2\\ \mathbf{elif}\;y \leq -7.6 \cdot 10^{-143}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y \leq 5.8 \cdot 10^{+83}:\\ \;\;\;\;4 \cdot \frac{x}{y}\\ \mathbf{else}:\\ \;\;\;\;2\\ \end{array} \]

Alternative 2
Accuracy	52.8%
Cost	850

\[\begin{array}{l} \mathbf{if}\;z \leq -2.8 \cdot 10^{+152} \lor \neg \left(z \leq -3.8 \cdot 10^{+119} \lor \neg \left(z \leq -3.8 \cdot 10^{+92}\right) \land z \leq 1.55 \cdot 10^{+119}\right):\\ \;\;\;\;-4 \cdot \frac{z}{y}\\ \mathbf{else}:\\ \;\;\;\;2\\ \end{array} \]

Alternative 3
Accuracy	99.7%
Cost	832

\[1 + \frac{4}{\frac{y}{x + \left(y \cdot 0.25 - z\right)}} \]

Alternative 4
Accuracy	80.8%
Cost	713

\[\begin{array}{l} \mathbf{if}\;y \leq -96000000000 \lor \neg \left(y \leq 8.5 \cdot 10^{+82}\right):\\ \;\;\;\;2 + -4 \cdot \frac{z}{y}\\ \mathbf{else}:\\ \;\;\;\;-4 \cdot \frac{z - x}{y}\\ \end{array} \]

Alternative 5
Accuracy	84.9%
Cost	713

\[\begin{array}{l} \mathbf{if}\;z \leq -1.02 \cdot 10^{+91} \lor \neg \left(z \leq 1.8 \cdot 10^{+109}\right):\\ \;\;\;\;2 + -4 \cdot \frac{z}{y}\\ \mathbf{else}:\\ \;\;\;\;2 + 4 \cdot \frac{x}{y}\\ \end{array} \]

Alternative 6
Accuracy	73.6%
Cost	712

\[\begin{array}{l} \mathbf{if}\;y \leq -8.5 \cdot 10^{+80}:\\ \;\;\;\;2\\ \mathbf{elif}\;y \leq 9.2 \cdot 10^{+173}:\\ \;\;\;\;-4 \cdot \frac{z - x}{y}\\ \mathbf{else}:\\ \;\;\;\;2\\ \end{array} \]

Alternative 7
Accuracy	42.6%
Cost	64

\[2 \]

Reproduce

herbie shell --seed 2023140 
(FPCore (x y z)
  :name "Data.Array.Repa.Algorithms.ColorRamp:rampColorHotToCold from repa-algorithms-3.4.0.1, C"
  :precision binary64
  (+ 1.0 (/ (* 4.0 (- (+ x (* y 0.25)) z)) y)))