Optimisation.CirclePacking:place from circle-packing-0.1.0.4, B

Average Accuracy: 99.9% → 99.9%

Time: 10.1s

Precision: binary64

Cost: 576

Math

\[\frac{\left(x + y\right) - z}{t \cdot 2} \]

↓

\[\frac{\left(x + y\right) - z}{t \cdot 2} \]

FPCore

(FPCore (x y z t) :precision binary64 (/ (- (+ x y) z) (* t 2.0)))

↓

(FPCore (x y z t) :precision binary64 (/ (- (+ x y) z) (* t 2.0)))

C

double code(double x, double y, double z, double t) {
	return ((x + y) - z) / (t * 2.0);
}

↓

double code(double x, double y, double z, double t) {
	return ((x + y) - z) / (t * 2.0);
}

Fortran

real(8) function code(x, y, z, t)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    code = ((x + y) - z) / (t * 2.0d0)
end function

↓

real(8) function code(x, y, z, t)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    code = ((x + y) - z) / (t * 2.0d0)
end function

Java

public static double code(double x, double y, double z, double t) {
	return ((x + y) - z) / (t * 2.0);
}

↓

public static double code(double x, double y, double z, double t) {
	return ((x + y) - z) / (t * 2.0);
}

Python

def code(x, y, z, t):
	return ((x + y) - z) / (t * 2.0)

↓

def code(x, y, z, t):
	return ((x + y) - z) / (t * 2.0)

Julia

function code(x, y, z, t)
	return Float64(Float64(Float64(x + y) - z) / Float64(t * 2.0))
end

↓

function code(x, y, z, t)
	return Float64(Float64(Float64(x + y) - z) / Float64(t * 2.0))
end

MATLAB

function tmp = code(x, y, z, t)
	tmp = ((x + y) - z) / (t * 2.0);
end

↓

function tmp = code(x, y, z, t)
	tmp = ((x + y) - z) / (t * 2.0);
end

Wolfram

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

↓

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

Derivation

1. Initial program 99.9%

   \[\frac{\left(x + y\right) - z}{t \cdot 2} \]

2. Final simplification 99.9%

   \[\leadsto \frac{\left(x + y\right) - z}{t \cdot 2} \]

Alternatives

Alternative 1
Accuracy	43.5%
Cost	848

\[\begin{array}{l} t_1 := \frac{x}{\frac{t}{0.5}}\\ t_2 := \frac{-0.5}{\frac{t}{z}}\\ \mathbf{if}\;x \leq -1.25 \cdot 10^{+75}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq -2.3 \cdot 10^{+43}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;x \leq -9.2 \cdot 10^{-57}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq -5.8 \cdot 10^{-259}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;\frac{y}{\frac{t}{0.5}}\\ \end{array} \]

Alternative 2
Accuracy	43.5%
Cost	848

\[\begin{array}{l} t_1 := \frac{x}{\frac{t}{0.5}}\\ t_2 := \frac{z \cdot -0.5}{t}\\ \mathbf{if}\;x \leq -7.1 \cdot 10^{+74}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq -9.5 \cdot 10^{+40}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;x \leq -1.25 \cdot 10^{-59}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq -1.12 \cdot 10^{-261}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;\frac{y}{\frac{t}{0.5}}\\ \end{array} \]

Alternative 3
Accuracy	74.6%
Cost	708

\[\begin{array}{l} \mathbf{if}\;y \leq 9 \cdot 10^{-119}:\\ \;\;\;\;\frac{-0.5 \cdot \left(z - x\right)}{t}\\ \mathbf{else}:\\ \;\;\;\;0.5 \cdot \left(\frac{y}{t} - \frac{z}{t}\right)\\ \end{array} \]

Alternative 4
Accuracy	52.5%
Cost	585

\[\begin{array}{l} \mathbf{if}\;z \leq -4.6 \cdot 10^{+83} \lor \neg \left(z \leq 8 \cdot 10^{+33}\right):\\ \;\;\;\;\frac{-0.5}{\frac{t}{z}}\\ \mathbf{else}:\\ \;\;\;\;x \cdot \frac{0.5}{t}\\ \end{array} \]

Alternative 5
Accuracy	52.6%
Cost	585

\[\begin{array}{l} \mathbf{if}\;z \leq -7 \cdot 10^{+83} \lor \neg \left(z \leq 2.35 \cdot 10^{+33}\right):\\ \;\;\;\;\frac{-0.5}{\frac{t}{z}}\\ \mathbf{else}:\\ \;\;\;\;\frac{x}{\frac{t}{0.5}}\\ \end{array} \]

Alternative 6
Accuracy	73.3%
Cost	580

\[\begin{array}{l} \mathbf{if}\;y \leq 1.05 \cdot 10^{+61}:\\ \;\;\;\;\frac{-0.5}{t} \cdot \left(z - x\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{y}{\frac{t}{0.5}}\\ \end{array} \]

Alternative 7
Accuracy	74.3%
Cost	580

\[\begin{array}{l} \mathbf{if}\;y \leq 9.2 \cdot 10^{-119}:\\ \;\;\;\;\frac{-0.5}{t} \cdot \left(z - x\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.5}{t} \cdot \left(z - y\right)\\ \end{array} \]

Alternative 8
Accuracy	74.3%
Cost	580

\[\begin{array}{l} \mathbf{if}\;y \leq 9.2 \cdot 10^{-119}:\\ \;\;\;\;\frac{-0.5}{t} \cdot \left(z - x\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.5}{\frac{t}{z - y}}\\ \end{array} \]

Alternative 9
Accuracy	74.5%
Cost	580

\[\begin{array}{l} \mathbf{if}\;y \leq 9.2 \cdot 10^{-119}:\\ \;\;\;\;\frac{-0.5 \cdot \left(z - x\right)}{t}\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.5}{\frac{t}{z - y}}\\ \end{array} \]

Alternative 10
Accuracy	99.6%
Cost	576

\[\left(z - \left(x + y\right)\right) \cdot \frac{-0.5}{t} \]

Alternative 11
Accuracy	36.5%
Cost	320

\[x \cdot \frac{0.5}{t} \]

Reproduce

herbie shell --seed 2023138 
(FPCore (x y z t)
  :name "Optimisation.CirclePacking:place from circle-packing-0.1.0.4, B"
  :precision binary64
  (/ (- (+ x y) z) (* t 2.0)))