Data.HashTable.ST.Basic:computeOverhead from hashtables-1.2.0.2

Average Error: 15.46% → 0.13%

Time: 13.3s

Precision: binary64

Cost: 832

Math

\[\frac{x}{y} + \frac{2 + \left(z \cdot 2\right) \cdot \left(1 - t\right)}{t \cdot z} \]

↓

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

FPCore

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

↓

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

C

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

↓

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

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) + ((2.0d0 + ((z * 2.0d0) * (1.0d0 - t))) / (t * z))
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) + ((-2.0d0) + ((2.0d0 + (2.0d0 / z)) / t))
end function

Java

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

↓

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

Python

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

↓

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

Julia

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

↓

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

MATLAB

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

↓

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

Wolfram

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

↓

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

Target

Original	15.46%
Target	0.13%
Herbie	0.13%

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

Derivation

1. Initial program 15.46

   \[\frac{x}{y} + \frac{2 + \left(z \cdot 2\right) \cdot \left(1 - t\right)}{t \cdot z} \]

2. Simplified 0.13

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

   [Start] 15.46	\[ \frac{x}{y} + \frac{2 + \left(z \cdot 2\right) \cdot \left(1 - t\right)}{t \cdot z} \]
   +-rgt-identity [<=] 15.46	\[ \color{blue}{\left(\frac{x}{y} + 0\right)} + \frac{2 + \left(z \cdot 2\right) \cdot \left(1 - t\right)}{t \cdot z} \]
   mul0-lft [<=] 15.46	\[ \left(\frac{x}{y} + \color{blue}{0 \cdot \frac{2}{t \cdot z}}\right) + \frac{2 + \left(z \cdot 2\right) \cdot \left(1 - t\right)}{t \cdot z} \]
   associate-+r+ [<=] 15.46	\[ \color{blue}{\frac{x}{y} + \left(0 \cdot \frac{2}{t \cdot z} + \frac{2 + \left(z \cdot 2\right) \cdot \left(1 - t\right)}{t \cdot z}\right)} \]
   mul0-lft [=>] 15.46	\[ \frac{x}{y} + \left(\color{blue}{0} + \frac{2 + \left(z \cdot 2\right) \cdot \left(1 - t\right)}{t \cdot z}\right) \]
   +-lft-identity [=>] 15.46	\[ \frac{x}{y} + \color{blue}{\frac{2 + \left(z \cdot 2\right) \cdot \left(1 - t\right)}{t \cdot z}} \]
   sub-neg [=>] 15.46	\[ \frac{x}{y} + \frac{2 + \left(z \cdot 2\right) \cdot \color{blue}{\left(1 + \left(-t\right)\right)}}{t \cdot z} \]
   distribute-rgt-in [=>] 15.46	\[ \frac{x}{y} + \frac{2 + \color{blue}{\left(1 \cdot \left(z \cdot 2\right) + \left(-t\right) \cdot \left(z \cdot 2\right)\right)}}{t \cdot z} \]
   associate-+r+ [=>] 15.46	\[ \frac{x}{y} + \frac{\color{blue}{\left(2 + 1 \cdot \left(z \cdot 2\right)\right) + \left(-t\right) \cdot \left(z \cdot 2\right)}}{t \cdot z} \]
   cancel-sign-sub-inv [<=] 15.46	\[ \frac{x}{y} + \frac{\color{blue}{\left(2 + 1 \cdot \left(z \cdot 2\right)\right) - t \cdot \left(z \cdot 2\right)}}{t \cdot z} \]
   div-sub [=>] 15.44	\[ \frac{x}{y} + \color{blue}{\left(\frac{2 + 1 \cdot \left(z \cdot 2\right)}{t \cdot z} - \frac{t \cdot \left(z \cdot 2\right)}{t \cdot z}\right)} \]
   associate-*r* [=>] 15.44	\[ \frac{x}{y} + \left(\frac{2 + 1 \cdot \left(z \cdot 2\right)}{t \cdot z} - \frac{\color{blue}{\left(t \cdot z\right) \cdot 2}}{t \cdot z}\right) \]
   associate-*l/ [<=] 15.42	\[ \frac{x}{y} + \left(\frac{2 + 1 \cdot \left(z \cdot 2\right)}{t \cdot z} - \color{blue}{\frac{t \cdot z}{t \cdot z} \cdot 2}\right) \]
   *-inverses [=>] 0.22	\[ \frac{x}{y} + \left(\frac{2 + 1 \cdot \left(z \cdot 2\right)}{t \cdot z} - \color{blue}{1} \cdot 2\right) \]
   metadata-eval [=>] 0.22	\[ \frac{x}{y} + \left(\frac{2 + 1 \cdot \left(z \cdot 2\right)}{t \cdot z} - \color{blue}{2}\right) \]
   sub-neg [=>] 0.22	\[ \frac{x}{y} + \color{blue}{\left(\frac{2 + 1 \cdot \left(z \cdot 2\right)}{t \cdot z} + \left(-2\right)\right)} \]

3. Final simplification 0.13

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

Alternatives

Alternative 1
Error	31.53%
Cost	2272

\[\begin{array}{l} t_1 := -2 + \frac{2}{z \cdot t}\\ t_2 := -2 + \frac{2}{t}\\ \mathbf{if}\;\frac{x}{y} \leq -4.1 \cdot 10^{+49}:\\ \;\;\;\;\frac{x}{y}\\ \mathbf{elif}\;\frac{x}{y} \leq -9.2 \cdot 10^{-235}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;\frac{x}{y} \leq -4.8 \cdot 10^{-304}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;\frac{x}{y} \leq 9.8 \cdot 10^{-256}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;\frac{x}{y} \leq 6.5 \cdot 10^{-170}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;\frac{x}{y} \leq 2.55 \cdot 10^{-116}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;\frac{x}{y} \leq 460000000:\\ \;\;\;\;t_1\\ \mathbf{elif}\;\frac{x}{y} \leq 8.6 \cdot 10^{+49}:\\ \;\;\;\;\frac{2}{t}\\ \mathbf{else}:\\ \;\;\;\;\frac{x}{y}\\ \end{array} \]

Alternative 2
Error	20.37%
Cost	1500

\[\begin{array}{l} t_1 := \frac{2}{z \cdot t}\\ t_2 := \frac{x}{y} + -2\\ t_3 := \frac{x}{y} + t_1\\ \mathbf{if}\;t \leq -4.1 \cdot 10^{+190}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -5 \cdot 10^{+105}:\\ \;\;\;\;-2 + t_1\\ \mathbf{elif}\;t \leq -1.75 \cdot 10^{+52}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-14}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq -7.5 \cdot 10^{-64}:\\ \;\;\;\;\frac{2 + \frac{2}{z}}{t}\\ \mathbf{elif}\;t \leq -1.2 \cdot 10^{-113}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{-12}:\\ \;\;\;\;t_1 + \frac{2}{t}\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 3
Error	9%
Cost	1225

\[\begin{array}{l} t_1 := \frac{2}{z \cdot t}\\ \mathbf{if}\;\frac{x}{y} \leq -1.4 \cdot 10^{+56} \lor \neg \left(\frac{x}{y} \leq 8.5 \cdot 10^{+49}\right):\\ \;\;\;\;\frac{x}{y} + t_1\\ \mathbf{else}:\\ \;\;\;\;t_1 + \left(-2 + \frac{2}{t}\right)\\ \end{array} \]

Alternative 4
Error	32.08%
Cost	1112

\[\begin{array}{l} t_1 := \frac{2}{z \cdot t}\\ t_2 := \frac{x}{y} + -2\\ t_3 := -2 + \frac{2}{t}\\ \mathbf{if}\;t \leq -2.2 \cdot 10^{+52}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -1.45 \cdot 10^{+23}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -1 \cdot 10^{-13}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -1.6 \cdot 10^{-64}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq -4.2 \cdot 10^{-155}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 1.02 \cdot 10^{-12}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 5
Error	32.13%
Cost	1112

\[\begin{array}{l} t_1 := \frac{x}{y} + -2\\ t_2 := -2 + \frac{2}{t}\\ \mathbf{if}\;t \leq -2.2 \cdot 10^{+53}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -5.2 \cdot 10^{+22}:\\ \;\;\;\;\frac{2}{z \cdot t}\\ \mathbf{elif}\;t \leq -8.5 \cdot 10^{-14}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -5.5 \cdot 10^{-65}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -2.3 \cdot 10^{-155}:\\ \;\;\;\;\frac{\frac{2}{t}}{z}\\ \mathbf{elif}\;t \leq 4.45 \cdot 10^{-13}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

Alternative 6
Error	9.16%
Cost	1097

\[\begin{array}{l} \mathbf{if}\;\frac{x}{y} \leq -1.15 \cdot 10^{+60} \lor \neg \left(\frac{x}{y} \leq 8.5 \cdot 10^{+49}\right):\\ \;\;\;\;\frac{x}{y} + \frac{2}{z \cdot t}\\ \mathbf{else}:\\ \;\;\;\;-2 + \frac{2 + \frac{2}{z}}{t}\\ \end{array} \]

Alternative 7
Error	20.83%
Cost	972

\[\begin{array}{l} t_1 := \frac{2}{z \cdot t}\\ t_2 := \frac{x}{y} + -2\\ \mathbf{if}\;t \leq -4.1 \cdot 10^{+190}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -1.25 \cdot 10^{-11}:\\ \;\;\;\;-2 + t_1\\ \mathbf{elif}\;t \leq 3.2 \cdot 10^{-12}:\\ \;\;\;\;t_1 + \frac{2}{t}\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 8
Error	31.66%
Cost	850

\[\begin{array}{l} \mathbf{if}\;t \leq -9.2 \cdot 10^{-14} \lor \neg \left(t \leq -9.8 \cdot 10^{-64}\right) \land \left(t \leq -6.2 \cdot 10^{-114} \lor \neg \left(t \leq 1.85 \cdot 10^{-12}\right)\right):\\ \;\;\;\;\frac{x}{y} + -2\\ \mathbf{else}:\\ \;\;\;\;-2 + \frac{2}{t}\\ \end{array} \]

Alternative 9
Error	20.8%
Cost	844

\[\begin{array}{l} t_1 := \frac{x}{y} + -2\\ \mathbf{if}\;t \leq -4.1 \cdot 10^{+190}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -1.25 \cdot 10^{-11}:\\ \;\;\;\;-2 + \frac{2}{z \cdot t}\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{-12}:\\ \;\;\;\;\frac{2 + \frac{2}{z}}{t}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

Alternative 10
Error	32.11%
Cost	840

\[\begin{array}{l} \mathbf{if}\;\frac{x}{y} \leq -1.6 \cdot 10^{+41}:\\ \;\;\;\;\frac{x}{y}\\ \mathbf{elif}\;\frac{x}{y} \leq 8.5 \cdot 10^{+49}:\\ \;\;\;\;-2 + \frac{2}{t}\\ \mathbf{else}:\\ \;\;\;\;\frac{x}{y}\\ \end{array} \]

Alternative 11
Error	55.85%
Cost	712

\[\begin{array}{l} \mathbf{if}\;\frac{x}{y} \leq -1.6 \cdot 10^{+41}:\\ \;\;\;\;\frac{x}{y}\\ \mathbf{elif}\;\frac{x}{y} \leq 8.5 \cdot 10^{+49}:\\ \;\;\;\;\frac{2}{t}\\ \mathbf{else}:\\ \;\;\;\;\frac{x}{y}\\ \end{array} \]

Alternative 12
Error	76.16%
Cost	192

\[\frac{2}{t} \]

Reproduce

herbie shell --seed 2023088 
(FPCore (x y z t)
  :name "Data.HashTable.ST.Basic:computeOverhead from hashtables-1.2.0.2"
  :precision binary64

  :herbie-target
  (- (/ (+ (/ 2.0 z) 2.0) t) (- 2.0 (/ x y)))

  (+ (/ x y) (/ (+ 2.0 (* (* z 2.0) (- 1.0 t))) (* t z))))