Graphics.Rendering.Plot.Render.Plot.Axis:renderAxisTick from plot-0.2.3.4, B

Average Accuracy: 74.4% → 92.3%

Time: 16.0s

Precision: binary64

Cost: 3533.00

Math

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

↓

\[\begin{array}{l} t_1 := \left(x + y\right) + \frac{y \cdot \left(t - z\right)}{a - t}\\ \mathbf{if}\;t_1 \leq -\infty:\\ \;\;\;\;x - \frac{y}{t} \cdot \left(a - z\right)\\ \mathbf{elif}\;t_1 \leq -1 \cdot 10^{-237} \lor \neg \left(t_1 \leq 0\right):\\ \;\;\;\;x + \left(y - \frac{y}{\frac{a - t}{z - t}}\right)\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y \cdot \left(z - a\right)}{t}\\ \end{array} \]

FPCore

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

↓

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ (+ x y) (/ (* y (- t z)) (- a t)))))
   (if (<= t_1 (- INFINITY))
     (- x (* (/ y t) (- a z)))
     (if (or (<= t_1 -1e-237) (not (<= t_1 0.0)))
       (+ x (- y (/ y (/ (- a t) (- z t)))))
       (+ x (/ (* y (- z a)) t))))))

C

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

↓

double code(double x, double y, double z, double t, double a) {
	double t_1 = (x + y) + ((y * (t - z)) / (a - t));
	double tmp;
	if (t_1 <= -((double) INFINITY)) {
		tmp = x - ((y / t) * (a - z));
	} else if ((t_1 <= -1e-237) || !(t_1 <= 0.0)) {
		tmp = x + (y - (y / ((a - t) / (z - t))));
	} else {
		tmp = x + ((y * (z - a)) / t);
	}
	return tmp;
}

Java

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

↓

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = (x + y) + ((y * (t - z)) / (a - t));
	double tmp;
	if (t_1 <= -Double.POSITIVE_INFINITY) {
		tmp = x - ((y / t) * (a - z));
	} else if ((t_1 <= -1e-237) || !(t_1 <= 0.0)) {
		tmp = x + (y - (y / ((a - t) / (z - t))));
	} else {
		tmp = x + ((y * (z - a)) / t);
	}
	return tmp;
}

Python

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

↓

def code(x, y, z, t, a):
	t_1 = (x + y) + ((y * (t - z)) / (a - t))
	tmp = 0
	if t_1 <= -math.inf:
		tmp = x - ((y / t) * (a - z))
	elif (t_1 <= -1e-237) or not (t_1 <= 0.0):
		tmp = x + (y - (y / ((a - t) / (z - t))))
	else:
		tmp = x + ((y * (z - a)) / t)
	return tmp

Julia

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

↓

function code(x, y, z, t, a)
	t_1 = Float64(Float64(x + y) + Float64(Float64(y * Float64(t - z)) / Float64(a - t)))
	tmp = 0.0
	if (t_1 <= Float64(-Inf))
		tmp = Float64(x - Float64(Float64(y / t) * Float64(a - z)));
	elseif ((t_1 <= -1e-237) || !(t_1 <= 0.0))
		tmp = Float64(x + Float64(y - Float64(y / Float64(Float64(a - t) / Float64(z - t)))));
	else
		tmp = Float64(x + Float64(Float64(y * Float64(z - a)) / t));
	end
	return tmp
end

MATLAB

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

↓

function tmp_2 = code(x, y, z, t, a)
	t_1 = (x + y) + ((y * (t - z)) / (a - t));
	tmp = 0.0;
	if (t_1 <= -Inf)
		tmp = x - ((y / t) * (a - z));
	elseif ((t_1 <= -1e-237) || ~((t_1 <= 0.0)))
		tmp = x + (y - (y / ((a - t) / (z - t))));
	else
		tmp = x + ((y * (z - a)) / t);
	end
	tmp_2 = tmp;
end

Wolfram

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

↓

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(N[(x + y), $MachinePrecision] + N[(N[(y * N[(t - z), $MachinePrecision]), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, (-Infinity)], N[(x - N[(N[(y / t), $MachinePrecision] * N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[t$95$1, -1e-237], N[Not[LessEqual[t$95$1, 0.0]], $MachinePrecision]], N[(x + N[(y - N[(y / N[(N[(a - t), $MachinePrecision] / N[(z - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(N[(y * N[(z - a), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision]]]]

Target

Original	74.4%
Target	86.9%
Herbie	92.3%

\[\begin{array}{l} \mathbf{if}\;\left(x + y\right) - \frac{\left(z - t\right) \cdot y}{a - t} < -1.3664970889390727 \cdot 10^{-7}:\\ \;\;\;\;\left(y + x\right) - \left(\left(z - t\right) \cdot \frac{1}{a - t}\right) \cdot y\\ \mathbf{elif}\;\left(x + y\right) - \frac{\left(z - t\right) \cdot y}{a - t} < 1.4754293444577233 \cdot 10^{-239}:\\ \;\;\;\;\frac{y \cdot \left(a - z\right) - x \cdot t}{a - t}\\ \mathbf{else}:\\ \;\;\;\;\left(y + x\right) - \left(\left(z - t\right) \cdot \frac{1}{a - t}\right) \cdot y\\ \end{array} \]

Derivation

1. Split input into 3 regimes

2. if (-.f64 (+.f64 x y) (/.f64 (*.f64 (-.f64 z t) y) (-.f64 a t))) < -inf.0

   1. Initial program 0.0%

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

   2. Simplified 70.1%

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

      [Start] 0.0	\[ \left(x + y\right) - \frac{\left(z - t\right) \cdot y}{a - t} \]
      associate--l+ [=>] 0.0	\[ \color{blue}{x + \left(y - \frac{\left(z - t\right) \cdot y}{a - t}\right)} \]
      sub-neg [=>] 0.0	\[ x + \color{blue}{\left(y + \left(-\frac{\left(z - t\right) \cdot y}{a - t}\right)\right)} \]
      +-commutative [=>] 0.0	\[ x + \color{blue}{\left(\left(-\frac{\left(z - t\right) \cdot y}{a - t}\right) + y\right)} \]
      neg-mul-1 [=>] 0.0	\[ x + \left(\color{blue}{-1 \cdot \frac{\left(z - t\right) \cdot y}{a - t}} + y\right) \]
      associate-*l/ [<=] 70.1	\[ x + \left(-1 \cdot \color{blue}{\left(\frac{z - t}{a - t} \cdot y\right)} + y\right) \]
      associate-*r* [=>] 70.1	\[ x + \left(\color{blue}{\left(-1 \cdot \frac{z - t}{a - t}\right) \cdot y} + y\right) \]
      fma-def [=>] 70.1	\[ x + \color{blue}{\mathsf{fma}\left(-1 \cdot \frac{z - t}{a - t}, y, y\right)} \]
      mul-1-neg [=>] 70.1	\[ x + \mathsf{fma}\left(\color{blue}{-\frac{z - t}{a - t}}, y, y\right) \]
      neg-sub0 [=>] 70.1	\[ x + \mathsf{fma}\left(\color{blue}{0 - \frac{z - t}{a - t}}, y, y\right) \]
      div-sub [=>] 70.2	\[ x + \mathsf{fma}\left(0 - \color{blue}{\left(\frac{z}{a - t} - \frac{t}{a - t}\right)}, y, y\right) \]
      associate--r- [=>] 70.2	\[ x + \mathsf{fma}\left(\color{blue}{\left(0 - \frac{z}{a - t}\right) + \frac{t}{a - t}}, y, y\right) \]
      neg-sub0 [<=] 70.2	\[ x + \mathsf{fma}\left(\color{blue}{\left(-\frac{z}{a - t}\right)} + \frac{t}{a - t}, y, y\right) \]
      +-commutative [=>] 70.2	\[ x + \mathsf{fma}\left(\color{blue}{\frac{t}{a - t} + \left(-\frac{z}{a - t}\right)}, y, y\right) \]
      sub-neg [<=] 70.2	\[ x + \mathsf{fma}\left(\color{blue}{\frac{t}{a - t} - \frac{z}{a - t}}, y, y\right) \]
      div-sub [<=] 70.1	\[ x + \mathsf{fma}\left(\color{blue}{\frac{t - z}{a - t}}, y, y\right) \]

   3. Taylor expanded in y around 0 83.2%

      \[\leadsto \color{blue}{y \cdot \left(\left(1 + \frac{t}{a - t}\right) - \frac{z}{a - t}\right) + x} \]

   4. Taylor expanded in t around inf 39.0%

      \[\leadsto \color{blue}{-1 \cdot \frac{\left(-1 \cdot z + a\right) \cdot y}{t} + x} \]

   5. Simplified 72.0%

      \[\leadsto \color{blue}{x - \frac{y}{t} \cdot \left(a - z\right)} \]
      Proof

      [Start] 39.0	\[ -1 \cdot \frac{\left(-1 \cdot z + a\right) \cdot y}{t} + x \]
      +-commutative [=>] 39.0	\[ \color{blue}{x + -1 \cdot \frac{\left(-1 \cdot z + a\right) \cdot y}{t}} \]
      mul-1-neg [=>] 39.0	\[ x + \color{blue}{\left(-\frac{\left(-1 \cdot z + a\right) \cdot y}{t}\right)} \]
      *-commutative [=>] 39.0	\[ x + \left(-\frac{\color{blue}{y \cdot \left(-1 \cdot z + a\right)}}{t}\right) \]
      +-commutative [=>] 39.0	\[ x + \left(-\frac{y \cdot \color{blue}{\left(a + -1 \cdot z\right)}}{t}\right) \]
      mul-1-neg [=>] 39.0	\[ x + \left(-\frac{y \cdot \left(a + \color{blue}{\left(-z\right)}\right)}{t}\right) \]
      sub-neg [<=] 39.0	\[ x + \left(-\frac{y \cdot \color{blue}{\left(a - z\right)}}{t}\right) \]
      unsub-neg [=>] 39.0	\[ \color{blue}{x - \frac{y \cdot \left(a - z\right)}{t}} \]
      associate-/l* [=>] 70.0	\[ x - \color{blue}{\frac{y}{\frac{t}{a - z}}} \]
      associate-/r/ [=>] 72.0	\[ x - \color{blue}{\frac{y}{t} \cdot \left(a - z\right)} \]

   if -inf.0 < (-.f64 (+.f64 x y) (/.f64 (*.f64 (-.f64 z t) y) (-.f64 a t))) < -9.9999999999999999e-238 or 0.0 < (-.f64 (+.f64 x y) (/.f64 (*.f64 (-.f64 z t) y) (-.f64 a t)))

   1. Initial program 87.9%

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

   2. Simplified 93.8%

      \[\leadsto \color{blue}{x + \left(y - \frac{y}{\frac{a - t}{z - t}}\right)} \]
      Proof

      [Start] 87.9	\[ \left(x + y\right) - \frac{\left(z - t\right) \cdot y}{a - t} \]
      +-rgt-identity [<=] 87.9	\[ \color{blue}{\left(\left(x + y\right) + 0\right)} - \frac{\left(z - t\right) \cdot y}{a - t} \]
      associate-+l+ [=>] 87.9	\[ \color{blue}{\left(x + \left(y + 0\right)\right)} - \frac{\left(z - t\right) \cdot y}{a - t} \]
      associate-+r- [<=] 88.2	\[ \color{blue}{x + \left(\left(y + 0\right) - \frac{\left(z - t\right) \cdot y}{a - t}\right)} \]
      +-rgt-identity [=>] 88.2	\[ x + \left(\color{blue}{y} - \frac{\left(z - t\right) \cdot y}{a - t}\right) \]
      *-commutative [=>] 88.2	\[ x + \left(y - \frac{\color{blue}{y \cdot \left(z - t\right)}}{a - t}\right) \]
      associate-/l* [=>] 93.8	\[ x + \left(y - \color{blue}{\frac{y}{\frac{a - t}{z - t}}}\right) \]

   if -9.9999999999999999e-238 < (-.f64 (+.f64 x y) (/.f64 (*.f64 (-.f64 z t) y) (-.f64 a t))) < 0.0

   1. Initial program 10.7%

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

   2. Simplified 48.8%

      \[\leadsto \color{blue}{x + \left(y - \frac{y}{\frac{a - t}{z - t}}\right)} \]
      Proof

      [Start] 10.7	\[ \left(x + y\right) - \frac{\left(z - t\right) \cdot y}{a - t} \]
      +-rgt-identity [<=] 10.7	\[ \color{blue}{\left(\left(x + y\right) + 0\right)} - \frac{\left(z - t\right) \cdot y}{a - t} \]
      associate-+l+ [=>] 10.7	\[ \color{blue}{\left(x + \left(y + 0\right)\right)} - \frac{\left(z - t\right) \cdot y}{a - t} \]
      associate-+r- [<=] 48.2	\[ \color{blue}{x + \left(\left(y + 0\right) - \frac{\left(z - t\right) \cdot y}{a - t}\right)} \]
      +-rgt-identity [=>] 48.2	\[ x + \left(\color{blue}{y} - \frac{\left(z - t\right) \cdot y}{a - t}\right) \]
      *-commutative [=>] 48.2	\[ x + \left(y - \frac{\color{blue}{y \cdot \left(z - t\right)}}{a - t}\right) \]
      associate-/l* [=>] 48.8	\[ x + \left(y - \color{blue}{\frac{y}{\frac{a - t}{z - t}}}\right) \]

   3. Taylor expanded in t around inf 96.1%

      \[\leadsto x + \color{blue}{\frac{-1 \cdot \left(a \cdot y\right) - -1 \cdot \left(y \cdot z\right)}{t}} \]

   4. Simplified 96.1%

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

      [Start] 96.1	\[ x + \frac{-1 \cdot \left(a \cdot y\right) - -1 \cdot \left(y \cdot z\right)}{t} \]
      *-commutative [<=] 96.1	\[ x + \frac{-1 \cdot \color{blue}{\left(y \cdot a\right)} - -1 \cdot \left(y \cdot z\right)}{t} \]
      distribute-lft-out-- [=>] 96.1	\[ x + \frac{\color{blue}{-1 \cdot \left(y \cdot a - y \cdot z\right)}}{t} \]
      distribute-lft-out-- [=>] 96.1	\[ x + \frac{-1 \cdot \color{blue}{\left(y \cdot \left(a - z\right)\right)}}{t} \]
      associate-*r* [=>] 96.1	\[ x + \frac{\color{blue}{\left(-1 \cdot y\right) \cdot \left(a - z\right)}}{t} \]
      neg-mul-1 [<=] 96.1	\[ x + \frac{\color{blue}{\left(-y\right)} \cdot \left(a - z\right)}{t} \]

3. Recombined 3 regimes into one program.

4. Final simplification 92.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(x + y\right) + \frac{y \cdot \left(t - z\right)}{a - t} \leq -\infty:\\ \;\;\;\;x - \frac{y}{t} \cdot \left(a - z\right)\\ \mathbf{elif}\;\left(x + y\right) + \frac{y \cdot \left(t - z\right)}{a - t} \leq -1 \cdot 10^{-237} \lor \neg \left(\left(x + y\right) + \frac{y \cdot \left(t - z\right)}{a - t} \leq 0\right):\\ \;\;\;\;x + \left(y - \frac{y}{\frac{a - t}{z - t}}\right)\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y \cdot \left(z - a\right)}{t}\\ \end{array} \]

Alternatives

Alternative 1
Accuracy	81.1%
Cost	1237.00

\[\begin{array}{l} t_1 := \left(x + y\right) - \frac{y}{\frac{a}{z}}\\ \mathbf{if}\;a \leq -1.65 \cdot 10^{+96}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -3.8 \cdot 10^{-31}:\\ \;\;\;\;x + \frac{y}{\frac{t - a}{z}}\\ \mathbf{elif}\;a \leq 2.9 \cdot 10^{-103}:\\ \;\;\;\;x + \frac{y \cdot \left(z - a\right)}{t}\\ \mathbf{elif}\;a \leq 1.4 \cdot 10^{-56} \lor \neg \left(a \leq 3.6 \cdot 10^{+53}\right):\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x - \frac{y}{\frac{t}{a - z}}\\ \end{array} \]

Alternative 2
Accuracy	80.0%
Cost	1236.00

\[\begin{array}{l} t_1 := x + \frac{y}{\frac{t - a}{z}}\\ \mathbf{if}\;a \leq -1.95 \cdot 10^{+96}:\\ \;\;\;\;x + y\\ \mathbf{elif}\;a \leq -6.8 \cdot 10^{-32}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.8 \cdot 10^{-120}:\\ \;\;\;\;x - \frac{y \cdot a}{t}\\ \mathbf{elif}\;a \leq 8.5 \cdot 10^{-55}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 7.9 \cdot 10^{+52}:\\ \;\;\;\;x - \frac{y}{\frac{t}{a - z}}\\ \mathbf{else}:\\ \;\;\;\;x + y\\ \end{array} \]

Alternative 3
Accuracy	87.7%
Cost	1232.00

\[\begin{array}{l} t_1 := \left(x + y\right) - \frac{z}{\frac{a - t}{y}}\\ t_2 := x - \frac{y}{t} \cdot \left(a - z\right)\\ \mathbf{if}\;t \leq -52000000:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 3.1 \cdot 10^{+36}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 1.2 \cdot 10^{+59}:\\ \;\;\;\;x - \frac{y}{\frac{t}{a - z}}\\ \mathbf{elif}\;t \leq 7.9 \cdot 10^{+90}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 4
Accuracy	93.1%
Cost	1220.00

\[\begin{array}{l} \mathbf{if}\;t \leq -1 \cdot 10^{+195}:\\ \;\;\;\;x - \frac{y}{t} \cdot \left(a - z\right)\\ \mathbf{else}:\\ \;\;\;\;x + y \cdot \left(\left(1 + \frac{t}{a - t}\right) - \frac{z}{a - t}\right)\\ \end{array} \]

Alternative 5
Accuracy	81.5%
Cost	1104.00

\[\begin{array}{l} t_1 := x + \frac{y}{\frac{t - a}{z}}\\ \mathbf{if}\;a \leq -1.75 \cdot 10^{+96}:\\ \;\;\;\;x + y\\ \mathbf{elif}\;a \leq -1.65 \cdot 10^{-28}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -2.2 \cdot 10^{-123}:\\ \;\;\;\;x - \frac{y \cdot a}{t}\\ \mathbf{elif}\;a \leq 1.18 \cdot 10^{+89}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x + y\\ \end{array} \]

Alternative 6
Accuracy	82.1%
Cost	1104.00

\[\begin{array}{l} t_1 := x - \frac{y}{t} \cdot \left(a - z\right)\\ \mathbf{if}\;t \leq -400000:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{+34}:\\ \;\;\;\;\left(x + y\right) - \frac{y}{\frac{a}{z}}\\ \mathbf{elif}\;t \leq 4.3 \cdot 10^{+57}:\\ \;\;\;\;x - \frac{y}{\frac{t}{a - z}}\\ \mathbf{elif}\;t \leq 5.5 \cdot 10^{+77}:\\ \;\;\;\;x + y\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

Alternative 7
Accuracy	68.0%
Cost	720.00

\[\begin{array}{l} \mathbf{if}\;a \leq -2.1 \cdot 10^{-88}:\\ \;\;\;\;x + y\\ \mathbf{elif}\;a \leq -6.6 \cdot 10^{-259}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -3.3 \cdot 10^{-301}:\\ \;\;\;\;y \cdot \frac{z}{t}\\ \mathbf{elif}\;a \leq 2.5 \cdot 10^{-110}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;x + y\\ \end{array} \]

Alternative 8
Accuracy	76.1%
Cost	712.00

\[\begin{array}{l} \mathbf{if}\;a \leq -1.6 \cdot 10^{+74}:\\ \;\;\;\;x + y\\ \mathbf{elif}\;a \leq 9.5 \cdot 10^{-103}:\\ \;\;\;\;x + \frac{y}{t} \cdot z\\ \mathbf{else}:\\ \;\;\;\;x + y\\ \end{array} \]

Alternative 9
Accuracy	76.4%
Cost	712.00

\[\begin{array}{l} \mathbf{if}\;a \leq -1.35 \cdot 10^{+75}:\\ \;\;\;\;x + y\\ \mathbf{elif}\;a \leq 5.2 \cdot 10^{-103}:\\ \;\;\;\;x + \frac{y}{\frac{t}{z}}\\ \mathbf{else}:\\ \;\;\;\;x + y\\ \end{array} \]

Alternative 10
Accuracy	55.8%
Cost	592.00

\[\begin{array}{l} \mathbf{if}\;x \leq -2 \cdot 10^{-108}:\\ \;\;\;\;x\\ \mathbf{elif}\;x \leq -1.6 \cdot 10^{-215}:\\ \;\;\;\;y\\ \mathbf{elif}\;x \leq -1.5 \cdot 10^{-291}:\\ \;\;\;\;x\\ \mathbf{elif}\;x \leq 4.1 \cdot 10^{-87}:\\ \;\;\;\;y\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 11
Accuracy	67.7%
Cost	456.00

\[\begin{array}{l} \mathbf{if}\;t \leq -1.75 \cdot 10^{+70}:\\ \;\;\;\;x\\ \mathbf{elif}\;t \leq 7 \cdot 10^{+194}:\\ \;\;\;\;x + y\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 12
Accuracy	54.7%
Cost	64.00

\[x \]

Reproduce

herbie shell --seed 2023096 
(FPCore (x y z t a)
  :name "Graphics.Rendering.Plot.Render.Plot.Axis:renderAxisTick from plot-0.2.3.4, B"
  :precision binary64

  :herbie-target
  (if (< (- (+ x y) (/ (* (- z t) y) (- a t))) -1.3664970889390727e-7) (- (+ y x) (* (* (- z t) (/ 1.0 (- a t))) y)) (if (< (- (+ x y) (/ (* (- z t) y) (- a t))) 1.4754293444577233e-239) (/ (- (* y (- a z)) (* x t)) (- a t)) (- (+ y x) (* (* (- z t) (/ 1.0 (- a t))) y))))

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