Statistics.Distribution.Beta:$centropy from math-functions-0.1.5.2

Average Accuracy: 100.0% → 100.0%

Time: 28.9s

Precision: binary64

Cost: 1344

Math

\[\left(\left(x - \left(y - 1\right) \cdot z\right) - \left(t - 1\right) \cdot a\right) + \left(\left(y + t\right) - 2\right) \cdot b \]

↓

\[\left(x + z \cdot \left(1 - y\right)\right) + \left(\left(y - \left(2 - t\right)\right) \cdot b + \left(a - t \cdot a\right)\right) \]

FPCore

(FPCore (x y z t a b)
 :precision binary64
 (+ (- (- x (* (- y 1.0) z)) (* (- t 1.0) a)) (* (- (+ y t) 2.0) b)))

↓

(FPCore (x y z t a b)
 :precision binary64
 (+ (+ x (* z (- 1.0 y))) (+ (* (- y (- 2.0 t)) b) (- a (* t a)))))

C

double code(double x, double y, double z, double t, double a, double b) {
	return ((x - ((y - 1.0) * z)) - ((t - 1.0) * a)) + (((y + t) - 2.0) * b);
}

↓

double code(double x, double y, double z, double t, double a, double b) {
	return (x + (z * (1.0 - y))) + (((y - (2.0 - t)) * b) + (a - (t * a)));
}

Fortran

real(8) function code(x, y, z, t, a, b)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    code = ((x - ((y - 1.0d0) * z)) - ((t - 1.0d0) * a)) + (((y + t) - 2.0d0) * b)
end function

↓

real(8) function code(x, y, z, t, a, b)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    code = (x + (z * (1.0d0 - y))) + (((y - (2.0d0 - t)) * b) + (a - (t * a)))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b) {
	return ((x - ((y - 1.0) * z)) - ((t - 1.0) * a)) + (((y + t) - 2.0) * b);
}

↓

public static double code(double x, double y, double z, double t, double a, double b) {
	return (x + (z * (1.0 - y))) + (((y - (2.0 - t)) * b) + (a - (t * a)));
}

Python

def code(x, y, z, t, a, b):
	return ((x - ((y - 1.0) * z)) - ((t - 1.0) * a)) + (((y + t) - 2.0) * b)

↓

def code(x, y, z, t, a, b):
	return (x + (z * (1.0 - y))) + (((y - (2.0 - t)) * b) + (a - (t * a)))

Julia

function code(x, y, z, t, a, b)
	return Float64(Float64(Float64(x - Float64(Float64(y - 1.0) * z)) - Float64(Float64(t - 1.0) * a)) + Float64(Float64(Float64(y + t) - 2.0) * b))
end

↓

function code(x, y, z, t, a, b)
	return Float64(Float64(x + Float64(z * Float64(1.0 - y))) + Float64(Float64(Float64(y - Float64(2.0 - t)) * b) + Float64(a - Float64(t * a))))
end

MATLAB

function tmp = code(x, y, z, t, a, b)
	tmp = ((x - ((y - 1.0) * z)) - ((t - 1.0) * a)) + (((y + t) - 2.0) * b);
end

↓

function tmp = code(x, y, z, t, a, b)
	tmp = (x + (z * (1.0 - y))) + (((y - (2.0 - t)) * b) + (a - (t * a)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_] := N[(N[(N[(x - N[(N[(y - 1.0), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision] - N[(N[(t - 1.0), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(y + t), $MachinePrecision] - 2.0), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]

↓

code[x_, y_, z_, t_, a_, b_] := N[(N[(x + N[(z * N[(1.0 - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(y - N[(2.0 - t), $MachinePrecision]), $MachinePrecision] * b), $MachinePrecision] + N[(a - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 100.0%

   \[\left(\left(x - \left(y - 1\right) \cdot z\right) - \left(t - 1\right) \cdot a\right) + \left(\left(y + t\right) - 2\right) \cdot b \]

2. Simplified 100.0%

   \[\leadsto \color{blue}{\left(x - \left(y + -1\right) \cdot z\right) - \left(\left(t + -1\right) \cdot a - \left(y + \left(t - 2\right)\right) \cdot b\right)} \]
   Proof

   [Start] 100.0	\[ \left(\left(x - \left(y - 1\right) \cdot z\right) - \left(t - 1\right) \cdot a\right) + \left(\left(y + t\right) - 2\right) \cdot b \]
   associate-+l- [=>] 100.0	\[ \color{blue}{\left(x - \left(y - 1\right) \cdot z\right) - \left(\left(t - 1\right) \cdot a - \left(\left(y + t\right) - 2\right) \cdot b\right)} \]
   sub-neg [=>] 100.0	\[ \color{blue}{\left(x - \left(y - 1\right) \cdot z\right) + \left(-\left(\left(t - 1\right) \cdot a - \left(\left(y + t\right) - 2\right) \cdot b\right)\right)} \]
   neg-sub0 [=>] 100.0	\[ \left(x - \left(y - 1\right) \cdot z\right) + \color{blue}{\left(0 - \left(\left(t - 1\right) \cdot a - \left(\left(y + t\right) - 2\right) \cdot b\right)\right)} \]
   associate-+r- [=>] 100.0	\[ \color{blue}{\left(\left(x - \left(y - 1\right) \cdot z\right) + 0\right) - \left(\left(t - 1\right) \cdot a - \left(\left(y + t\right) - 2\right) \cdot b\right)} \]
   +-rgt-identity [=>] 100.0	\[ \color{blue}{\left(x - \left(y - 1\right) \cdot z\right)} - \left(\left(t - 1\right) \cdot a - \left(\left(y + t\right) - 2\right) \cdot b\right) \]
   sub-neg [=>] 100.0	\[ \left(x - \color{blue}{\left(y + \left(-1\right)\right)} \cdot z\right) - \left(\left(t - 1\right) \cdot a - \left(\left(y + t\right) - 2\right) \cdot b\right) \]
   metadata-eval [=>] 100.0	\[ \left(x - \left(y + \color{blue}{-1}\right) \cdot z\right) - \left(\left(t - 1\right) \cdot a - \left(\left(y + t\right) - 2\right) \cdot b\right) \]
   sub-neg [=>] 100.0	\[ \left(x - \left(y + -1\right) \cdot z\right) - \color{blue}{\left(\left(t - 1\right) \cdot a + \left(-\left(\left(y + t\right) - 2\right) \cdot b\right)\right)} \]
   neg-mul-1 [=>] 100.0	\[ \left(x - \left(y + -1\right) \cdot z\right) - \left(\left(t - 1\right) \cdot a + \color{blue}{-1 \cdot \left(\left(\left(y + t\right) - 2\right) \cdot b\right)}\right) \]
   metadata-eval [<=] 100.0	\[ \left(x - \left(y + -1\right) \cdot z\right) - \left(\left(t - 1\right) \cdot a + \color{blue}{\left(-1\right)} \cdot \left(\left(\left(y + t\right) - 2\right) \cdot b\right)\right) \]
   cancel-sign-sub-inv [<=] 100.0	\[ \left(x - \left(y + -1\right) \cdot z\right) - \color{blue}{\left(\left(t - 1\right) \cdot a - 1 \cdot \left(\left(\left(y + t\right) - 2\right) \cdot b\right)\right)} \]
   sub-neg [=>] 100.0	\[ \left(x - \left(y + -1\right) \cdot z\right) - \left(\color{blue}{\left(t + \left(-1\right)\right)} \cdot a - 1 \cdot \left(\left(\left(y + t\right) - 2\right) \cdot b\right)\right) \]
   metadata-eval [=>] 100.0	\[ \left(x - \left(y + -1\right) \cdot z\right) - \left(\left(t + \color{blue}{-1}\right) \cdot a - 1 \cdot \left(\left(\left(y + t\right) - 2\right) \cdot b\right)\right) \]
   *-lft-identity [=>] 100.0	\[ \left(x - \left(y + -1\right) \cdot z\right) - \left(\left(t + -1\right) \cdot a - \color{blue}{\left(\left(y + t\right) - 2\right) \cdot b}\right) \]
   associate--l+ [=>] 100.0	\[ \left(x - \left(y + -1\right) \cdot z\right) - \left(\left(t + -1\right) \cdot a - \color{blue}{\left(y + \left(t - 2\right)\right)} \cdot b\right) \]

3. Applied egg-rr 100.0%

   \[\leadsto \left(x - \left(y + -1\right) \cdot z\right) - \left(\color{blue}{\left(t \cdot a + -1 \cdot a\right)} - \left(y + \left(t - 2\right)\right) \cdot b\right) \]

4. Final simplification 100.0%

   \[\leadsto \left(x + z \cdot \left(1 - y\right)\right) + \left(\left(y - \left(2 - t\right)\right) \cdot b + \left(a - t \cdot a\right)\right) \]

Alternatives

Alternative 1
Accuracy	36.2%
Cost	2168

\[\begin{array}{l} t_1 := a \cdot \left(1 - t\right)\\ t_2 := b \cdot \left(y + -2\right)\\ \mathbf{if}\;b \leq -4.1 \cdot 10^{+158}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \leq -3.5 \cdot 10^{+121}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq -1.8 \cdot 10^{+66}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq -1250000000000:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq -4.7 \cdot 10^{-102}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq -4 \cdot 10^{-154}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq -2.8 \cdot 10^{-193}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq -1.4 \cdot 10^{-244}:\\ \;\;\;\;y \cdot \left(b - z\right)\\ \mathbf{elif}\;b \leq 1.16 \cdot 10^{-248}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 2.2 \cdot 10^{-139}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq 2 \cdot 10^{-100}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 1.35 \cdot 10^{-55}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq 4.2 \cdot 10^{+27}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 1.7 \cdot 10^{+111}:\\ \;\;\;\;\left(t + -2\right) \cdot b\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 2
Accuracy	36.3%
Cost	2168

\[\begin{array}{l} t_1 := a - t \cdot a\\ t_2 := a \cdot \left(1 - t\right)\\ t_3 := b \cdot \left(y + -2\right)\\ \mathbf{if}\;b \leq -7.3 \cdot 10^{+152}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;b \leq -1.2 \cdot 10^{+120}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq -7.8 \cdot 10^{+66}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \leq -1060000000000:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq -4.3 \cdot 10^{-104}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \leq -2.1 \cdot 10^{-154}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq -3.1 \cdot 10^{-193}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \leq -9.8 \cdot 10^{-245}:\\ \;\;\;\;y \cdot \left(b - z\right)\\ \mathbf{elif}\;b \leq 3 \cdot 10^{-250}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 5.2 \cdot 10^{-138}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq 2.3 \cdot 10^{-100}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 7 \cdot 10^{-54}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq 3.7 \cdot 10^{+27}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \leq 1.6 \cdot 10^{+111}:\\ \;\;\;\;\left(t + -2\right) \cdot b\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \]

Alternative 3
Accuracy	34.7%
Cost	2040

\[\begin{array}{l} t_1 := a \cdot \left(1 - t\right)\\ \mathbf{if}\;b \leq -1.45 \cdot 10^{+159}:\\ \;\;\;\;b \cdot -2\\ \mathbf{elif}\;b \leq -9.5 \cdot 10^{+121}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq -1.4 \cdot 10^{+68}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq -1050000000000:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq -2 \cdot 10^{-105}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq -2.05 \cdot 10^{-163}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq -3.1 \cdot 10^{-193}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq -4.4 \cdot 10^{-250}:\\ \;\;\;\;-y \cdot z\\ \mathbf{elif}\;b \leq 2 \cdot 10^{-250}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 4.7 \cdot 10^{-138}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq 3.7 \cdot 10^{-100}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 5.6 \cdot 10^{-60}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;b \leq 5800000:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 8.8 \cdot 10^{+154}:\\ \;\;\;\;x + z\\ \mathbf{else}:\\ \;\;\;\;b \cdot -2\\ \end{array} \]

Alternative 4
Accuracy	40.9%
Cost	1904

\[\begin{array}{l} t_1 := x - y \cdot z\\ t_2 := b \cdot \left(-2 + \left(y + t\right)\right)\\ t_3 := a \cdot \left(1 - t\right)\\ t_4 := z - y \cdot z\\ \mathbf{if}\;a \leq -1.45 \cdot 10^{+74}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -1.1 \cdot 10^{+18}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -3200000000000:\\ \;\;\;\;t \cdot \left(b - a\right)\\ \mathbf{elif}\;a \leq -2.1 \cdot 10^{-220}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq 2.1 \cdot 10^{-266}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 8 \cdot 10^{-263}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq 5.4 \cdot 10^{-191}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 9.2 \cdot 10^{-138}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.4 \cdot 10^{-31}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{-7}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;a \leq 2.4 \cdot 10^{+99}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq 5.6 \cdot 10^{+138}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;a - t \cdot a\\ \end{array} \]

Alternative 5
Accuracy	22.6%
Cost	1776

\[\begin{array}{l} \mathbf{if}\;t \leq -1.05 \cdot 10^{+127}:\\ \;\;\;\;t \cdot b\\ \mathbf{elif}\;t \leq -1.12 \cdot 10^{+26}:\\ \;\;\;\;z\\ \mathbf{elif}\;t \leq -1.5 \cdot 10^{-176}:\\ \;\;\;\;a\\ \mathbf{elif}\;t \leq -1.25 \cdot 10^{-249}:\\ \;\;\;\;b \cdot -2\\ \mathbf{elif}\;t \leq -4.1 \cdot 10^{-265}:\\ \;\;\;\;a\\ \mathbf{elif}\;t \leq -1.18 \cdot 10^{-266}:\\ \;\;\;\;b \cdot -2\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-293}:\\ \;\;\;\;x\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{-275}:\\ \;\;\;\;a\\ \mathbf{elif}\;t \leq 7.5 \cdot 10^{-233}:\\ \;\;\;\;z\\ \mathbf{elif}\;t \leq 3.9 \cdot 10^{-225}:\\ \;\;\;\;x\\ \mathbf{elif}\;t \leq 1.3 \cdot 10^{-10}:\\ \;\;\;\;a\\ \mathbf{elif}\;t \leq 9.5 \cdot 10^{+176}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;t \cdot b\\ \end{array} \]

Alternative 6
Accuracy	40.5%
Cost	1640

\[\begin{array}{l} t_1 := x - y \cdot z\\ t_2 := a \cdot \left(1 - t\right)\\ t_3 := z - y \cdot z\\ \mathbf{if}\;a \leq -1.1 \cdot 10^{+75}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.48 \cdot 10^{+19}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -150000000:\\ \;\;\;\;t \cdot \left(b - a\right)\\ \mathbf{elif}\;a \leq -3.8 \cdot 10^{-294}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq 1.5 \cdot 10^{-308}:\\ \;\;\;\;\left(t + -2\right) \cdot b\\ \mathbf{elif}\;a \leq 5.5 \cdot 10^{-265}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{-32}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 8.5 \cdot 10^{-7}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;a \leq 5.7 \cdot 10^{+97}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.38 \cdot 10^{+138}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;a - t \cdot a\\ \end{array} \]

Alternative 7
Accuracy	55.9%
Cost	1632

\[\begin{array}{l} t_1 := x + b \cdot \left(-2 + \left(y + t\right)\right)\\ t_2 := a \cdot \left(1 - t\right)\\ t_3 := x + \left(z - y \cdot z\right)\\ \mathbf{if}\;a \leq -1.85 \cdot 10^{+194}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -2.5 \cdot 10^{+137}:\\ \;\;\;\;x - \left(2 \cdot b - z\right)\\ \mathbf{elif}\;a \leq -6.5 \cdot 10^{+74}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.85 \cdot 10^{-216}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq 1.2 \cdot 10^{-137}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 0.0046:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq 1.2 \cdot 10^{+99}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 6.8 \cdot 10^{+137}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a - t \cdot a\\ \end{array} \]

Alternative 8
Accuracy	58.3%
Cost	1632

\[\begin{array}{l} t_1 := a \cdot \left(1 - t\right)\\ t_2 := x + \left(z - y \cdot z\right)\\ \mathbf{if}\;a \leq -1.25 \cdot 10^{+195}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -2.8 \cdot 10^{+137}:\\ \;\;\;\;x - \left(2 \cdot b - z\right)\\ \mathbf{elif}\;a \leq -1.9 \cdot 10^{+75}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.02 \cdot 10^{-160}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{-160}:\\ \;\;\;\;x + \left(z - b \cdot \left(2 - t\right)\right)\\ \mathbf{elif}\;a \leq 0.00072:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 6.8 \cdot 10^{+95}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 5.5 \cdot 10^{+142}:\\ \;\;\;\;x + b \cdot \left(-2 + \left(y + t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a - t \cdot a\\ \end{array} \]

Alternative 9
Accuracy	42.6%
Cost	1508

\[\begin{array}{l} t_1 := x - y \cdot z\\ t_2 := a \cdot \left(1 - t\right)\\ \mathbf{if}\;a \leq -2.9 \cdot 10^{+73}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -6.8 \cdot 10^{-40}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -3.4 \cdot 10^{-66}:\\ \;\;\;\;t \cdot \left(b - a\right)\\ \mathbf{elif}\;a \leq -4.5 \cdot 10^{-278}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;a \leq 6.2 \cdot 10^{-161}:\\ \;\;\;\;\left(t + -2\right) \cdot b\\ \mathbf{elif}\;a \leq 4.4 \cdot 10^{-33}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{-7}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;a \leq 2.75 \cdot 10^{+99}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 7.6 \cdot 10^{+137}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;a - t \cdot a\\ \end{array} \]

Alternative 10
Accuracy	54.8%
Cost	1504

\[\begin{array}{l} t_1 := a \cdot \left(1 - t\right)\\ t_2 := x - \left(2 \cdot b - z\right)\\ t_3 := y \cdot \left(b - z\right)\\ \mathbf{if}\;y \leq -7.8 \cdot 10^{+132}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y \leq -1.4 \cdot 10^{+22}:\\ \;\;\;\;x - y \cdot z\\ \mathbf{elif}\;y \leq -1.76 \cdot 10^{-15}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq -1.6 \cdot 10^{-66}:\\ \;\;\;\;x + \left(z + t \cdot b\right)\\ \mathbf{elif}\;y \leq -1.45 \cdot 10^{-86}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq -2.6 \cdot 10^{-174}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq -3.2 \cdot 10^{-191}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 6.7:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \]

Alternative 11
Accuracy	86.2%
Cost	1488

\[\begin{array}{l} t_1 := z \cdot \left(1 - y\right)\\ t_2 := x + b \cdot \left(-2 + \left(y + t\right)\right)\\ t_3 := a \cdot \left(1 - t\right)\\ t_4 := x + \left(t_3 + t_1\right)\\ \mathbf{if}\;a \leq -8.2 \cdot 10^{+145}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq -1.05 \cdot 10^{+18}:\\ \;\;\;\;t_2 + t_3\\ \mathbf{elif}\;a \leq -9.8 \cdot 10^{-60}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq 1.75 \cdot 10^{-69}:\\ \;\;\;\;t_2 + t_1\\ \mathbf{else}:\\ \;\;\;\;\left(x + t_1\right) + \left(a - t \cdot a\right)\\ \end{array} \]

Alternative 12
Accuracy	100.0%
Cost	1472

\[\left(x + z \cdot \left(1 - y\right)\right) + \left(\left(y \cdot b + \left(t + -2\right) \cdot b\right) + a \cdot \left(1 - t\right)\right) \]

Alternative 13
Accuracy	52.5%
Cost	1376

\[\begin{array}{l} t_1 := a \cdot \left(1 - t\right)\\ t_2 := x + \left(z - y \cdot z\right)\\ \mathbf{if}\;a \leq -1.85 \cdot 10^{+194}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -2.8 \cdot 10^{+137}:\\ \;\;\;\;x - \left(2 \cdot b - z\right)\\ \mathbf{elif}\;a \leq -3.5 \cdot 10^{+75}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 3.45 \cdot 10^{-236}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 8.5 \cdot 10^{-161}:\\ \;\;\;\;b \cdot \left(-2 + \left(y + t\right)\right)\\ \mathbf{elif}\;a \leq 0.003:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 2.6 \cdot 10^{+99}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 6.8 \cdot 10^{+137}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;a - t \cdot a\\ \end{array} \]

Alternative 14
Accuracy	88.3%
Cost	1352

\[\begin{array}{l} t_1 := a \cdot \left(1 - t\right)\\ t_2 := x + b \cdot \left(-2 + \left(y + t\right)\right)\\ t_3 := z \cdot \left(1 - y\right)\\ \mathbf{if}\;b \leq -1.6 \cdot 10^{+165}:\\ \;\;\;\;t_2 + t_1\\ \mathbf{elif}\;b \leq 4 \cdot 10^{+27}:\\ \;\;\;\;\left(x + t_3\right) + \left(y \cdot b + t_1\right)\\ \mathbf{else}:\\ \;\;\;\;t_2 + t_3\\ \end{array} \]

Alternative 15
Accuracy	100.0%
Cost	1344

\[\left(\left(x + z \cdot \left(1 - y\right)\right) + a \cdot \left(1 - t\right)\right) - b \cdot \left(2 - \left(y + t\right)\right) \]

Alternative 16
Accuracy	32.2%
Cost	1312

\[\begin{array}{l} t_1 := a \cdot \left(-t\right)\\ \mathbf{if}\;t \leq -5.2 \cdot 10^{-18}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -1.05 \cdot 10^{-137}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;t \leq -1.7 \cdot 10^{-176}:\\ \;\;\;\;a\\ \mathbf{elif}\;t \leq -2.1 \cdot 10^{-249}:\\ \;\;\;\;b \cdot -2\\ \mathbf{elif}\;t \leq -2.45 \cdot 10^{-275}:\\ \;\;\;\;a\\ \mathbf{elif}\;t \leq 7.8 \cdot 10^{-213}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;t \leq 1.6 \cdot 10^{-136}:\\ \;\;\;\;a\\ \mathbf{elif}\;t \leq 3.3 \cdot 10^{+186}:\\ \;\;\;\;x + z\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

Alternative 17
Accuracy	55.9%
Cost	1240

\[\begin{array}{l} t_1 := a \cdot \left(1 - t\right)\\ t_2 := y \cdot \left(b - z\right)\\ t_3 := x - \left(2 \cdot b - z\right)\\ \mathbf{if}\;y \leq -9 \cdot 10^{+132}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq -1.35 \cdot 10^{+22}:\\ \;\;\;\;x - y \cdot z\\ \mathbf{elif}\;y \leq -6.9 \cdot 10^{-15}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq -1.75 \cdot 10^{-174}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y \leq -2.1 \cdot 10^{-190}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 12.5:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 18
Accuracy	86.3%
Cost	1224

\[\begin{array}{l} t_1 := z \cdot \left(1 - y\right)\\ \mathbf{if}\;a \leq -2.3 \cdot 10^{-60}:\\ \;\;\;\;x + \left(a \cdot \left(1 - t\right) + t_1\right)\\ \mathbf{elif}\;a \leq 9.4 \cdot 10^{-69}:\\ \;\;\;\;\left(x + b \cdot \left(-2 + \left(y + t\right)\right)\right) + t_1\\ \mathbf{else}:\\ \;\;\;\;\left(x + t_1\right) + \left(a - t \cdot a\right)\\ \end{array} \]

Alternative 19
Accuracy	43.8%
Cost	1113

\[\begin{array}{l} t_1 := a \cdot \left(1 - t\right)\\ \mathbf{if}\;a \leq -8 \cdot 10^{+32}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -4.3 \cdot 10^{-278}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;a \leq 6.6 \cdot 10^{-161}:\\ \;\;\;\;\left(t + -2\right) \cdot b\\ \mathbf{elif}\;a \leq 8.5 \cdot 10^{-7}:\\ \;\;\;\;x + z\\ \mathbf{elif}\;a \leq 3.3 \cdot 10^{+98} \lor \neg \left(a \leq 6.8 \cdot 10^{+137}\right):\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 20
Accuracy	80.0%
Cost	1097

\[\begin{array}{l} \mathbf{if}\;b \leq -1.05 \cdot 10^{+172} \lor \neg \left(b \leq 1.55 \cdot 10^{+43}\right):\\ \;\;\;\;x + b \cdot \left(-2 + \left(y + t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;x + \left(a \cdot \left(1 - t\right) + z \cdot \left(1 - y\right)\right)\\ \end{array} \]

Alternative 21
Accuracy	80.1%
Cost	1097

\[\begin{array}{l} \mathbf{if}\;b \leq -1.05 \cdot 10^{+172} \lor \neg \left(b \leq 8.4 \cdot 10^{+43}\right):\\ \;\;\;\;x + b \cdot \left(-2 + \left(y + t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(x + z \cdot \left(1 - y\right)\right) + \left(a - t \cdot a\right)\\ \end{array} \]

Alternative 22
Accuracy	27.5%
Cost	724

\[\begin{array}{l} \mathbf{if}\;a \leq -2.1 \cdot 10^{+33}:\\ \;\;\;\;a\\ \mathbf{elif}\;a \leq 1.92 \cdot 10^{-264}:\\ \;\;\;\;z\\ \mathbf{elif}\;a \leq 2.8 \cdot 10^{-43}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq 35000000000000:\\ \;\;\;\;z\\ \mathbf{elif}\;a \leq 1.85 \cdot 10^{+138}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;a\\ \end{array} \]

Alternative 23
Accuracy	44.4%
Cost	456

\[\begin{array}{l} \mathbf{if}\;a \leq -1.85 \cdot 10^{+194}:\\ \;\;\;\;a\\ \mathbf{elif}\;a \leq 1.65 \cdot 10^{+145}:\\ \;\;\;\;x + z\\ \mathbf{else}:\\ \;\;\;\;a\\ \end{array} \]

Alternative 24
Accuracy	31.1%
Cost	328

\[\begin{array}{l} \mathbf{if}\;x \leq -2.45 \cdot 10^{+123}:\\ \;\;\;\;x\\ \mathbf{elif}\;x \leq 6.8 \cdot 10^{+93}:\\ \;\;\;\;a\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 25
Accuracy	15.9%
Cost	64

\[a \]

Reproduce

herbie shell --seed 2023141 
(FPCore (x y z t a b)
  :name "Statistics.Distribution.Beta:$centropy from math-functions-0.1.5.2"
  :precision binary64
  (+ (- (- x (* (- y 1.0) z)) (* (- t 1.0) a)) (* (- (+ y t) 2.0) b)))