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

Average Error: 0.1 → 0.2

Time: 5.3s

Precision: binary64

Cost: 704

Math

\[1 - x \cdot \left(0.253 + x \cdot 0.12\right) \]

↓

\[1 - \left(0.12 \cdot \left(x \cdot x\right) - x \cdot -0.253\right) \]

FPCore

(FPCore (x) :precision binary64 (- 1.0 (* x (+ 0.253 (* x 0.12)))))

↓

(FPCore (x) :precision binary64 (- 1.0 (- (* 0.12 (* x x)) (* x -0.253))))

C

double code(double x) {
	return 1.0 - (x * (0.253 + (x * 0.12)));
}

↓

double code(double x) {
	return 1.0 - ((0.12 * (x * x)) - (x * -0.253));
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = 1.0d0 - (x * (0.253d0 + (x * 0.12d0)))
end function

↓

real(8) function code(x)
    real(8), intent (in) :: x
    code = 1.0d0 - ((0.12d0 * (x * x)) - (x * (-0.253d0)))
end function

Java

public static double code(double x) {
	return 1.0 - (x * (0.253 + (x * 0.12)));
}

↓

public static double code(double x) {
	return 1.0 - ((0.12 * (x * x)) - (x * -0.253));
}

Python

def code(x):
	return 1.0 - (x * (0.253 + (x * 0.12)))

↓

def code(x):
	return 1.0 - ((0.12 * (x * x)) - (x * -0.253))

Julia

function code(x)
	return Float64(1.0 - Float64(x * Float64(0.253 + Float64(x * 0.12))))
end

↓

function code(x)
	return Float64(1.0 - Float64(Float64(0.12 * Float64(x * x)) - Float64(x * -0.253)))
end

MATLAB

function tmp = code(x)
	tmp = 1.0 - (x * (0.253 + (x * 0.12)));
end

↓

function tmp = code(x)
	tmp = 1.0 - ((0.12 * (x * x)) - (x * -0.253));
end

Wolfram

code[x_] := N[(1.0 - N[(x * N[(0.253 + N[(x * 0.12), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[x_] := N[(1.0 - N[(N[(0.12 * N[(x * x), $MachinePrecision]), $MachinePrecision] - N[(x * -0.253), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 0.1

   \[1 - x \cdot \left(0.253 + x \cdot 0.12\right) \]

2. Applied egg-rr 0.1

   \[\leadsto 1 - \color{blue}{\left(x \cdot \left(x \cdot 0.12\right) - x \cdot -0.253\right)} \]

3. Applied egg-rr 0.1

   \[\leadsto 1 - \left(\color{blue}{\left(x \cdot \left(x \cdot 0.12\right) + 0\right)} - x \cdot -0.253\right) \]

4. Simplified 0.2

   \[\leadsto 1 - \left(\color{blue}{0.12 \cdot \left(x \cdot x\right)} - x \cdot -0.253\right) \]
   Proof

   [Start] 0.1	\[ 1 - \left(\left(x \cdot \left(x \cdot 0.12\right) + 0\right) - x \cdot -0.253\right) \]
   rational_best_oopsla_all_46_json_45_simplify-85 [=>] 0.1	\[ 1 - \left(\color{blue}{x \cdot \left(x \cdot 0.12\right)} - x \cdot -0.253\right) \]
   rational_best_oopsla_all_46_json_45_simplify-74 [=>] 0.1	\[ 1 - \left(x \cdot \color{blue}{\left(0.12 \cdot x\right)} - x \cdot -0.253\right) \]
   rational_best_oopsla_all_46_json_45_simplify-7 [=>] 0.2	\[ 1 - \left(\color{blue}{0.12 \cdot \left(x \cdot x\right)} - x \cdot -0.253\right) \]

5. Final simplification 0.2

   \[\leadsto 1 - \left(0.12 \cdot \left(x \cdot x\right) - x \cdot -0.253\right) \]

Alternatives

Alternative 1
Error	0.1
Cost	576

\[1 - x \cdot \left(0.253 + x \cdot 0.12\right) \]

Alternative 2
Error	20.7
Cost	320

\[1 - x \cdot 0.253 \]

Alternative 3
Error	21.7
Cost	64

\[1 \]

Reproduce

herbie shell --seed 2023090 
(FPCore (x)
  :name "Numeric.SpecFunctions:invIncompleteGamma from math-functions-0.1.5.2, A"
  :precision binary64
  (- 1.0 (* x (+ 0.253 (* x 0.12)))))