Diagrams.TwoD.Ellipse:ellipse from diagrams-lib-1.3.0.3

Average Accuracy: 100.0% → 100.0%

Time: 1.3s

Precision: binary64

Cost: 6720

Math

\[\sqrt{1 - x \cdot x} \]

↓

\[\sqrt{1 - x \cdot x} \]

FPCore

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

↓

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

C

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

↓

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

Fortran

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

↓

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

Java

public static double code(double x) {
	return Math.sqrt((1.0 - (x * x)));
}

↓

public static double code(double x) {
	return Math.sqrt((1.0 - (x * x)));
}

Python

def code(x):
	return math.sqrt((1.0 - (x * x)))

↓

def code(x):
	return math.sqrt((1.0 - (x * x)))

Julia

function code(x)
	return sqrt(Float64(1.0 - Float64(x * x)))
end

↓

function code(x)
	return sqrt(Float64(1.0 - Float64(x * x)))
end

MATLAB

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

↓

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

Wolfram

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

↓

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

Derivation

1. Initial program 100.0%

   \[\sqrt{1 - x \cdot x} \]

2. Final simplification 100.0%

   \[\leadsto \sqrt{1 - x \cdot x} \]

Alternatives

Alternative 1
Accuracy	99.5%
Cost	448

\[1 + \left(x \cdot x\right) \cdot -0.5 \]

Alternative 2
Accuracy	98.9%
Cost	64

\[1 \]

Reproduce

herbie shell --seed 2023129 
(FPCore (x)
  :name "Diagrams.TwoD.Ellipse:ellipse from diagrams-lib-1.3.0.3"
  :precision binary64
  (sqrt (- 1.0 (* x x))))