Data.Colour.RGB:hslsv from colour-2.3.3, B

?

Percentage Accurate: 99.4% → 99.8%
Time: 22.8s
Precision: binary64
Cost: 7104

?

\[\frac{60 \cdot \left(x - y\right)}{z - t} + a \cdot 120 \]
\[\mathsf{fma}\left(a, 120, \frac{x - y}{\left(z - t\right) \cdot 0.016666666666666666}\right) \]
(FPCore (x y z t a)
 :precision binary64
 (+ (/ (* 60.0 (- x y)) (- z t)) (* a 120.0)))
(FPCore (x y z t a)
 :precision binary64
 (fma a 120.0 (/ (- x y) (* (- z t) 0.016666666666666666))))
double code(double x, double y, double z, double t, double a) {
	return ((60.0 * (x - y)) / (z - t)) + (a * 120.0);
}
double code(double x, double y, double z, double t, double a) {
	return fma(a, 120.0, ((x - y) / ((z - t) * 0.016666666666666666)));
}
function code(x, y, z, t, a)
	return Float64(Float64(Float64(60.0 * Float64(x - y)) / Float64(z - t)) + Float64(a * 120.0))
end
function code(x, y, z, t, a)
	return fma(a, 120.0, Float64(Float64(x - y) / Float64(Float64(z - t) * 0.016666666666666666)))
end
code[x_, y_, z_, t_, a_] := N[(N[(N[(60.0 * N[(x - y), $MachinePrecision]), $MachinePrecision] / N[(z - t), $MachinePrecision]), $MachinePrecision] + N[(a * 120.0), $MachinePrecision]), $MachinePrecision]
code[x_, y_, z_, t_, a_] := N[(a * 120.0 + N[(N[(x - y), $MachinePrecision] / N[(N[(z - t), $MachinePrecision] * 0.016666666666666666), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{60 \cdot \left(x - y\right)}{z - t} + a \cdot 120
\mathsf{fma}\left(a, 120, \frac{x - y}{\left(z - t\right) \cdot 0.016666666666666666}\right)

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Herbie found 24 alternatives:

AlternativeAccuracySpeedup

Accuracy vs Speed

The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Bogosity?

Bogosity

Target

Original99.4%
Target99.8%
Herbie99.8%
\[\frac{60}{\frac{z - t}{x - y}} + a \cdot 120 \]

Derivation?

  1. Initial program 98.9%

    \[\frac{60 \cdot \left(x - y\right)}{z - t} + a \cdot 120 \]
  2. Simplified99.8%

    \[\leadsto \color{blue}{\mathsf{fma}\left(a, 120, \frac{60}{z - t} \cdot \left(x - y\right)\right)} \]
    Step-by-step derivation

    [Start]98.9%

    \[ \frac{60 \cdot \left(x - y\right)}{z - t} + a \cdot 120 \]

    +-commutative [=>]98.9%

    \[ \color{blue}{a \cdot 120 + \frac{60 \cdot \left(x - y\right)}{z - t}} \]

    fma-def [=>]99.0%

    \[ \color{blue}{\mathsf{fma}\left(a, 120, \frac{60 \cdot \left(x - y\right)}{z - t}\right)} \]

    associate-*l/ [<=]99.8%

    \[ \mathsf{fma}\left(a, 120, \color{blue}{\frac{60}{z - t} \cdot \left(x - y\right)}\right) \]
  3. Applied egg-rr99.8%

    \[\leadsto \mathsf{fma}\left(a, 120, \color{blue}{\frac{x - y}{\left(z - t\right) \cdot 0.016666666666666666}}\right) \]
    Step-by-step derivation

    [Start]99.8%

    \[ \mathsf{fma}\left(a, 120, \frac{60}{z - t} \cdot \left(x - y\right)\right) \]

    *-commutative [=>]99.8%

    \[ \mathsf{fma}\left(a, 120, \color{blue}{\left(x - y\right) \cdot \frac{60}{z - t}}\right) \]

    clear-num [=>]99.7%

    \[ \mathsf{fma}\left(a, 120, \left(x - y\right) \cdot \color{blue}{\frac{1}{\frac{z - t}{60}}}\right) \]

    un-div-inv [=>]99.8%

    \[ \mathsf{fma}\left(a, 120, \color{blue}{\frac{x - y}{\frac{z - t}{60}}}\right) \]

    div-inv [=>]99.8%

    \[ \mathsf{fma}\left(a, 120, \frac{x - y}{\color{blue}{\left(z - t\right) \cdot \frac{1}{60}}}\right) \]

    metadata-eval [=>]99.8%

    \[ \mathsf{fma}\left(a, 120, \frac{x - y}{\left(z - t\right) \cdot \color{blue}{0.016666666666666666}}\right) \]
  4. Final simplification99.8%

    \[\leadsto \mathsf{fma}\left(a, 120, \frac{x - y}{\left(z - t\right) \cdot 0.016666666666666666}\right) \]

Alternatives

Alternative 1
Accuracy99.8%
Cost7104
\[\mathsf{fma}\left(a, 120, \frac{x - y}{\left(z - t\right) \cdot 0.016666666666666666}\right) \]
Alternative 2
Accuracy99.8%
Cost7104
\[\mathsf{fma}\left(a, 120, \left(x - y\right) \cdot \frac{60}{z - t}\right) \]
Alternative 3
Accuracy57.9%
Cost1504
\[\begin{array}{l} t_1 := \left(x - y\right) \cdot \frac{-60}{t}\\ t_2 := 60 \cdot \frac{x}{z - t}\\ t_3 := -60 \cdot \frac{y}{z - t}\\ \mathbf{if}\;a \leq -2.95 \cdot 10^{+23}:\\ \;\;\;\;a \cdot 120\\ \mathbf{elif}\;a \leq -1.3 \cdot 10^{-10}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -1.9 \cdot 10^{-156}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -5.4 \cdot 10^{-275}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -2.1 \cdot 10^{-290}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.7 \cdot 10^{-186}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 9.6 \cdot 10^{-111}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq 2.6 \cdot 10^{-86}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 4
Accuracy57.9%
Cost1504
\[\begin{array}{l} t_1 := \left(x - y\right) \cdot \frac{-60}{t}\\ t_2 := 60 \cdot \frac{x}{z - t}\\ t_3 := -60 \cdot \frac{y}{z - t}\\ \mathbf{if}\;a \leq -2.8 \cdot 10^{+23}:\\ \;\;\;\;a \cdot 120\\ \mathbf{elif}\;a \leq -1.4 \cdot 10^{-10}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -1.65 \cdot 10^{-156}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -5.8 \cdot 10^{-274}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -1.1 \cdot 10^{-286}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.2 \cdot 10^{-186}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.8 \cdot 10^{-104}:\\ \;\;\;\;\frac{-60}{\frac{z - t}{y}}\\ \mathbf{elif}\;a \leq 1.95 \cdot 10^{-85}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 5
Accuracy57.3%
Cost1504
\[\begin{array}{l} t_1 := \left(x - y\right) \cdot \frac{-60}{t}\\ t_2 := -60 \cdot \frac{y}{z - t}\\ \mathbf{if}\;a \leq -2.55 \cdot 10^{+23}:\\ \;\;\;\;a \cdot 120\\ \mathbf{elif}\;a \leq -1.5 \cdot 10^{-10}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -2.6 \cdot 10^{-157}:\\ \;\;\;\;\frac{60}{\frac{z - t}{x}}\\ \mathbf{elif}\;a \leq -1.6 \cdot 10^{-238}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.5 \cdot 10^{-275}:\\ \;\;\;\;60 \cdot \frac{y}{t}\\ \mathbf{elif}\;a \leq 1.65 \cdot 10^{-186}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 3 \cdot 10^{-109}:\\ \;\;\;\;\frac{-60}{\frac{z - t}{y}}\\ \mathbf{elif}\;a \leq 1.8 \cdot 10^{-87}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 6
Accuracy57.2%
Cost1504
\[\begin{array}{l} t_1 := \left(x - y\right) \cdot \frac{-60}{t}\\ t_2 := -60 \cdot \frac{y}{z - t}\\ \mathbf{if}\;a \leq -7.2 \cdot 10^{+24}:\\ \;\;\;\;a \cdot 120\\ \mathbf{elif}\;a \leq -5 \cdot 10^{-9}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1 \cdot 10^{-156}:\\ \;\;\;\;\frac{60}{\frac{z - t}{x}}\\ \mathbf{elif}\;a \leq -1.6 \cdot 10^{-238}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.5 \cdot 10^{-275}:\\ \;\;\;\;60 \cdot \frac{y}{t}\\ \mathbf{elif}\;a \leq 7.8 \cdot 10^{-187}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.2 \cdot 10^{-114}:\\ \;\;\;\;\frac{y \cdot -60}{z - t}\\ \mathbf{elif}\;a \leq 8.8 \cdot 10^{-86}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 7
Accuracy57.5%
Cost1372
\[\begin{array}{l} t_1 := \left(x - y\right) \cdot \frac{-60}{t}\\ \mathbf{if}\;a \leq -2.2 \cdot 10^{+23}:\\ \;\;\;\;a \cdot 120\\ \mathbf{elif}\;a \leq -1.4 \cdot 10^{-10}:\\ \;\;\;\;-60 \cdot \frac{y}{z - t}\\ \mathbf{elif}\;a \leq -2.55 \cdot 10^{-157}:\\ \;\;\;\;\frac{60}{\frac{z - t}{x}}\\ \mathbf{elif}\;a \leq -6.7 \cdot 10^{-214}:\\ \;\;\;\;\frac{\left(x - y\right) \cdot 60}{z}\\ \mathbf{elif}\;a \leq 7.5 \cdot 10^{-187}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 2.1 \cdot 10^{-114}:\\ \;\;\;\;\frac{y \cdot -60}{z - t}\\ \mathbf{elif}\;a \leq 1.4 \cdot 10^{-88}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 8
Accuracy57.7%
Cost1240
\[\begin{array}{l} t_1 := 60 \cdot \frac{x}{z - t}\\ t_2 := -60 \cdot \frac{y}{z - t}\\ \mathbf{if}\;a \leq -2.2 \cdot 10^{+23}:\\ \;\;\;\;a \cdot 120\\ \mathbf{elif}\;a \leq -1.4 \cdot 10^{-10}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -2.6 \cdot 10^{-156}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 6.6 \cdot 10^{-260}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.8 \cdot 10^{-186}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 3.05 \cdot 10^{-62}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 9
Accuracy81.6%
Cost1233
\[\begin{array}{l} t_1 := x \cdot \frac{60}{z - t} + a \cdot 120\\ \mathbf{if}\;z \leq -2.45 \cdot 10^{+201}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -3.9 \cdot 10^{+112}:\\ \;\;\;\;a \cdot 120 + \frac{-60}{\frac{z}{y}}\\ \mathbf{elif}\;z \leq -1.8 \cdot 10^{-47} \lor \neg \left(z \leq 2 \cdot 10^{-8}\right):\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120 + -60 \cdot \frac{x - y}{t}\\ \end{array} \]
Alternative 10
Accuracy78.6%
Cost1232
\[\begin{array}{l} t_1 := a \cdot 120 + \frac{-60}{\frac{z}{y}}\\ t_2 := a \cdot 120 + \frac{60}{\frac{z}{x}}\\ \mathbf{if}\;z \leq -2.1 \cdot 10^{+198}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -5.8 \cdot 10^{+92}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -1 \cdot 10^{+45}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 2:\\ \;\;\;\;a \cdot 120 + -60 \cdot \frac{x - y}{t}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]
Alternative 11
Accuracy85.3%
Cost1100
\[\begin{array}{l} t_1 := \left(x - y\right) \cdot \frac{60}{z} + a \cdot 120\\ \mathbf{if}\;z \leq -1.85 \cdot 10^{+85}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -2.2 \cdot 10^{-47}:\\ \;\;\;\;x \cdot \frac{60}{z - t} + a \cdot 120\\ \mathbf{elif}\;z \leq 1.3:\\ \;\;\;\;a \cdot 120 + -60 \cdot \frac{x - y}{t}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]
Alternative 12
Accuracy74.1%
Cost1096
\[\begin{array}{l} \mathbf{if}\;a \cdot 120 \leq -1 \cdot 10^{+35}:\\ \;\;\;\;a \cdot 120 + x \cdot \frac{-60}{t}\\ \mathbf{elif}\;a \cdot 120 \leq 10^{+21}:\\ \;\;\;\;60 \cdot \frac{x - y}{z - t}\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 13
Accuracy73.6%
Cost1096
\[\begin{array}{l} \mathbf{if}\;a \cdot 120 \leq -1 \cdot 10^{+35}:\\ \;\;\;\;a \cdot 120 + x \cdot \frac{-60}{t}\\ \mathbf{elif}\;a \cdot 120 \leq 50000000000000:\\ \;\;\;\;60 \cdot \frac{x - y}{z - t}\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120 + \frac{60}{\frac{t}{y}}\\ \end{array} \]
Alternative 14
Accuracy58.1%
Cost977
\[\begin{array}{l} \mathbf{if}\;a \leq -2.95 \cdot 10^{+23}:\\ \;\;\;\;a \cdot 120\\ \mathbf{elif}\;a \leq -7.5 \cdot 10^{-9} \lor \neg \left(a \leq -1.06 \cdot 10^{-94}\right) \land a \leq 5.5 \cdot 10^{-83}:\\ \;\;\;\;-60 \cdot \frac{y}{z - t}\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 15
Accuracy89.4%
Cost969
\[\begin{array}{l} \mathbf{if}\;x \leq -4.4 \cdot 10^{+64} \lor \neg \left(x \leq 5.1 \cdot 10^{+33}\right):\\ \;\;\;\;x \cdot \frac{60}{z - t} + a \cdot 120\\ \mathbf{else}:\\ \;\;\;\;\frac{-60}{\frac{z - t}{y}} + a \cdot 120\\ \end{array} \]
Alternative 16
Accuracy89.4%
Cost969
\[\begin{array}{l} \mathbf{if}\;x \leq -2.8 \cdot 10^{+64} \lor \neg \left(x \leq 1.05 \cdot 10^{+33}\right):\\ \;\;\;\;\frac{60}{\frac{z - t}{x}} + a \cdot 120\\ \mathbf{else}:\\ \;\;\;\;\frac{-60}{\frac{z - t}{y}} + a \cdot 120\\ \end{array} \]
Alternative 17
Accuracy89.1%
Cost969
\[\begin{array}{l} \mathbf{if}\;x \leq -3.9 \cdot 10^{+65} \lor \neg \left(x \leq 400000\right):\\ \;\;\;\;\frac{60}{\frac{z - t}{x}} + a \cdot 120\\ \mathbf{else}:\\ \;\;\;\;\frac{y \cdot -60}{z - t} + a \cdot 120\\ \end{array} \]
Alternative 18
Accuracy74.9%
Cost840
\[\begin{array}{l} \mathbf{if}\;a \leq -3.3 \cdot 10^{+44}:\\ \;\;\;\;a \cdot 120\\ \mathbf{elif}\;a \leq 1.9 \cdot 10^{+19}:\\ \;\;\;\;60 \cdot \frac{x - y}{z - t}\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 19
Accuracy74.0%
Cost840
\[\begin{array}{l} \mathbf{if}\;a \leq -4.05 \cdot 10^{+24}:\\ \;\;\;\;a \cdot 120 + -60 \cdot \frac{x}{t}\\ \mathbf{elif}\;a \leq 1.52 \cdot 10^{+19}:\\ \;\;\;\;60 \cdot \frac{x - y}{z - t}\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 20
Accuracy99.8%
Cost832
\[\left(x - y\right) \cdot \frac{60}{z - t} + a \cdot 120 \]
Alternative 21
Accuracy99.8%
Cost832
\[\frac{60}{\frac{z - t}{x - y}} + a \cdot 120 \]
Alternative 22
Accuracy99.8%
Cost832
\[\frac{x - y}{\left(z - t\right) \cdot 0.016666666666666666} + a \cdot 120 \]
Alternative 23
Accuracy53.0%
Cost584
\[\begin{array}{l} \mathbf{if}\;a \leq -1.95 \cdot 10^{-193}:\\ \;\;\;\;a \cdot 120\\ \mathbf{elif}\;a \leq 2.1 \cdot 10^{-86}:\\ \;\;\;\;60 \cdot \frac{y}{t}\\ \mathbf{else}:\\ \;\;\;\;a \cdot 120\\ \end{array} \]
Alternative 24
Accuracy51.0%
Cost192
\[a \cdot 120 \]

Reproduce?

herbie shell --seed 2023271 
(FPCore (x y z t a)
  :name "Data.Colour.RGB:hslsv from colour-2.3.3, B"
  :precision binary64

  :herbie-target
  (+ (/ 60.0 (/ (- z t) (- x y))) (* a 120.0))

  (+ (/ (* 60.0 (- x y)) (- z t)) (* a 120.0)))