Numeric.SpecFunctions:log1p from math-functions-0.1.5.2, A

Average Error: 0.1 → 0.1

Time: 13.4s

Precision: binary64

Cost: 576

Math

\[x \cdot \left(1 - x \cdot y\right) \]

↓

\[x \cdot \left(-1 - \left(x \cdot y + -2\right)\right) \]

FPCore

(FPCore (x y) :precision binary64 (* x (- 1.0 (* x y))))

↓

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

C

double code(double x, double y) {
	return x * (1.0 - (x * y));
}

↓

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

Fortran

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = x * (1.0d0 - (x * y))
end function

↓

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

Java

public static double code(double x, double y) {
	return x * (1.0 - (x * y));
}

↓

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

Python

def code(x, y):
	return x * (1.0 - (x * y))

↓

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

Julia

function code(x, y)
	return Float64(x * Float64(1.0 - Float64(x * y)))
end

↓

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

MATLAB

function tmp = code(x, y)
	tmp = x * (1.0 - (x * y));
end

↓

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

Wolfram

code[x_, y_] := N[(x * N[(1.0 - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

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

Derivation

1. Initial program 0.1

   \[x \cdot \left(1 - x \cdot y\right) \]

2. Applied egg-rr 0.1

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

3. Applied egg-rr 0.1

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

4. Final simplification 0.1

   \[\leadsto x \cdot \left(-1 - \left(x \cdot y + -2\right)\right) \]

Alternatives

Alternative 1
Error	15.4
Cost	912

\[\begin{array}{l} t_0 := x \cdot \left(y \cdot \left(-x\right)\right)\\ \mathbf{if}\;y \leq -2.5 \cdot 10^{+234}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y \leq -1.25 \cdot 10^{+143}:\\ \;\;\;\;x\\ \mathbf{elif}\;y \leq -8.5 \cdot 10^{+90}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y \leq 2.2 \cdot 10^{+80}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]

Alternative 2
Error	0.1
Cost	448

\[x \cdot \left(1 - x \cdot y\right) \]

Alternative 3
Error	21.1
Cost	64

\[x \]

Reproduce

herbie shell --seed 2023074 
(FPCore (x y)
  :name "Numeric.SpecFunctions:log1p from math-functions-0.1.5.2, A"
  :precision binary64
  (* x (- 1.0 (* x y))))