?

Average Accuracy: 99.9% → 99.9%
Time: 8.9s
Precision: binary64
Cost: 576

?

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

Error?

Try it out?

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation?

  1. Initial program 99.9%

    \[\frac{\left(x + y\right) - z}{t \cdot 2} \]
  2. Final simplification99.9%

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

Alternatives

Alternative 1
Accuracy44.9%
Cost1112
\[\begin{array}{l} t_1 := z \cdot \frac{-0.5}{t}\\ t_2 := y \cdot \frac{0.5}{t}\\ t_3 := \frac{x}{\frac{t}{0.5}}\\ \mathbf{if}\;y \leq 10^{-245}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y \leq 1.6 \cdot 10^{-37}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 27:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq 2 \cdot 10^{+35}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{+48}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 5 \cdot 10^{+56}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]
Alternative 2
Accuracy44.9%
Cost1112
\[\begin{array}{l} t_1 := z \cdot \frac{-0.5}{t}\\ t_2 := \frac{y}{\frac{t}{0.5}}\\ t_3 := \frac{x}{\frac{t}{0.5}}\\ \mathbf{if}\;y \leq 2.25 \cdot 10^{-243}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y \leq 4.9 \cdot 10^{-37}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 0.102:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq 8.8 \cdot 10^{+33}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y \leq 2.25 \cdot 10^{+48}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 1.12 \cdot 10^{+57}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]
Alternative 3
Accuracy45.0%
Cost1112
\[\begin{array}{l} t_1 := \frac{y}{\frac{t}{0.5}}\\ t_2 := \frac{x}{\frac{t}{0.5}}\\ \mathbf{if}\;y \leq 1.3 \cdot 10^{-243}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq 8 \cdot 10^{-37}:\\ \;\;\;\;\frac{z \cdot -0.5}{t}\\ \mathbf{elif}\;y \leq 0.85:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 1.35 \cdot 10^{+32}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq 2.22 \cdot 10^{+48}:\\ \;\;\;\;z \cdot \frac{-0.5}{t}\\ \mathbf{elif}\;y \leq 1.05 \cdot 10^{+55}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]
Alternative 4
Accuracy75.2%
Cost845
\[\begin{array}{l} \mathbf{if}\;y \leq 1.5 \cdot 10^{-58} \lor \neg \left(y \leq 39\right) \land y \leq 5.5 \cdot 10^{+55}:\\ \;\;\;\;\frac{-0.5}{t} \cdot \left(z - x\right)\\ \mathbf{else}:\\ \;\;\;\;0.5 \cdot \frac{y - z}{t}\\ \end{array} \]
Alternative 5
Accuracy75.5%
Cost845
\[\begin{array}{l} \mathbf{if}\;y \leq 1.5 \cdot 10^{-58} \lor \neg \left(y \leq 0.46\right) \land y \leq 1.6 \cdot 10^{+55}:\\ \;\;\;\;\frac{-0.5 \cdot \left(z - x\right)}{t}\\ \mathbf{else}:\\ \;\;\;\;0.5 \cdot \frac{y - z}{t}\\ \end{array} \]
Alternative 6
Accuracy73.8%
Cost580
\[\begin{array}{l} \mathbf{if}\;x \leq -1.9 \cdot 10^{+107}:\\ \;\;\;\;\frac{x}{\frac{t}{0.5}}\\ \mathbf{else}:\\ \;\;\;\;0.5 \cdot \frac{y - z}{t}\\ \end{array} \]
Alternative 7
Accuracy99.6%
Cost576
\[\left(z - \left(x + y\right)\right) \cdot \frac{-0.5}{t} \]
Alternative 8
Accuracy43.8%
Cost452
\[\begin{array}{l} \mathbf{if}\;y \leq 7.5 \cdot 10^{-37}:\\ \;\;\;\;z \cdot \frac{-0.5}{t}\\ \mathbf{else}:\\ \;\;\;\;y \cdot \frac{0.5}{t}\\ \end{array} \]
Alternative 9
Accuracy36.3%
Cost320
\[y \cdot \frac{0.5}{t} \]

Error

Reproduce?

herbie shell --seed 2023137 
(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)))