Numeric.SpecFunctions:invIncompleteBetaWorker from math-functions-0.1.5.2, D

Average Error: 0.0 → 0.0

Time: 7.8s

Precision: binary64

Cost: 1216

Math

\[x - \frac{2.30753 + x \cdot 0.27061}{1 + \left(0.99229 + x \cdot 0.04481\right) \cdot x} \]

↓

\[x - \frac{2.30753 + x \cdot 0.27061}{1 + \left(x \cdot \left(x \cdot 0.04481\right) + x \cdot 0.99229\right)} \]

FPCore

(FPCore (x)
 :precision binary64
 (- x (/ (+ 2.30753 (* x 0.27061)) (+ 1.0 (* (+ 0.99229 (* x 0.04481)) x)))))

↓

(FPCore (x)
 :precision binary64
 (-
  x
  (/ (+ 2.30753 (* x 0.27061)) (+ 1.0 (+ (* x (* x 0.04481)) (* x 0.99229))))))

C

double code(double x) {
	return x - ((2.30753 + (x * 0.27061)) / (1.0 + ((0.99229 + (x * 0.04481)) * x)));
}

↓

double code(double x) {
	return x - ((2.30753 + (x * 0.27061)) / (1.0 + ((x * (x * 0.04481)) + (x * 0.99229))));
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = x - ((2.30753d0 + (x * 0.27061d0)) / (1.0d0 + ((0.99229d0 + (x * 0.04481d0)) * x)))
end function

↓

real(8) function code(x)
    real(8), intent (in) :: x
    code = x - ((2.30753d0 + (x * 0.27061d0)) / (1.0d0 + ((x * (x * 0.04481d0)) + (x * 0.99229d0))))
end function

Java

public static double code(double x) {
	return x - ((2.30753 + (x * 0.27061)) / (1.0 + ((0.99229 + (x * 0.04481)) * x)));
}

↓

public static double code(double x) {
	return x - ((2.30753 + (x * 0.27061)) / (1.0 + ((x * (x * 0.04481)) + (x * 0.99229))));
}

Python

def code(x):
	return x - ((2.30753 + (x * 0.27061)) / (1.0 + ((0.99229 + (x * 0.04481)) * x)))

↓

def code(x):
	return x - ((2.30753 + (x * 0.27061)) / (1.0 + ((x * (x * 0.04481)) + (x * 0.99229))))

Julia

function code(x)
	return Float64(x - Float64(Float64(2.30753 + Float64(x * 0.27061)) / Float64(1.0 + Float64(Float64(0.99229 + Float64(x * 0.04481)) * x))))
end

↓

function code(x)
	return Float64(x - Float64(Float64(2.30753 + Float64(x * 0.27061)) / Float64(1.0 + Float64(Float64(x * Float64(x * 0.04481)) + Float64(x * 0.99229)))))
end

MATLAB

function tmp = code(x)
	tmp = x - ((2.30753 + (x * 0.27061)) / (1.0 + ((0.99229 + (x * 0.04481)) * x)));
end

↓

function tmp = code(x)
	tmp = x - ((2.30753 + (x * 0.27061)) / (1.0 + ((x * (x * 0.04481)) + (x * 0.99229))));
end

Wolfram

code[x_] := N[(x - N[(N[(2.30753 + N[(x * 0.27061), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(N[(0.99229 + N[(x * 0.04481), $MachinePrecision]), $MachinePrecision] * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[x_] := N[(x - N[(N[(2.30753 + N[(x * 0.27061), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(N[(x * N[(x * 0.04481), $MachinePrecision]), $MachinePrecision] + N[(x * 0.99229), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 0.0

   \[x - \frac{2.30753 + x \cdot 0.27061}{1 + \left(0.99229 + x \cdot 0.04481\right) \cdot x} \]

2. Applied egg-rr 0.0

   \[\leadsto x - \frac{2.30753 + x \cdot 0.27061}{1 + \color{blue}{\left(\left(x \cdot 0.04481\right) \cdot x + 0.99229 \cdot x\right)}} \]

3. Final simplification 0.0

   \[\leadsto x - \frac{2.30753 + x \cdot 0.27061}{1 + \left(x \cdot \left(x \cdot 0.04481\right) + x \cdot 0.99229\right)} \]

Alternatives

Alternative 1
Error	0.0
Cost	1088

\[x + \frac{-2.30753 + x \cdot -0.27061}{1 + x \cdot \left(x \cdot 0.04481 + 0.99229\right)} \]

Alternative 2
Error	0.9
Cost	832

\[x + \frac{-2.30753 + x \cdot -0.27061}{1 + x \cdot 0.99229} \]

Alternative 3
Error	1.0
Cost	328

\[\begin{array}{l} \mathbf{if}\;x \leq -3.6:\\ \;\;\;\;x\\ \mathbf{elif}\;x \leq 1.15:\\ \;\;\;\;-2.30753\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 4
Error	1.3
Cost	192

\[x + -2.30753 \]

Alternative 5
Error	31.6
Cost	64

\[-2.30753 \]

Reproduce

herbie shell --seed 2022364 
(FPCore (x)
  :name "Numeric.SpecFunctions:invIncompleteBetaWorker from math-functions-0.1.5.2, D"
  :precision binary64
  (- x (/ (+ 2.30753 (* x 0.27061)) (+ 1.0 (* (+ 0.99229 (* x 0.04481)) x)))))