Diagrams.Solve.Polynomial:quadForm from diagrams-solve-0.1, C

Average Error: 0.0 → 0.0

Time: 1.1s

Precision: binary64

Cost: 320

Math

\[\frac{x}{y \cdot 2} \]

↓

\[\frac{x}{y} \cdot 0.5 \]

FPCore

(FPCore (x y) :precision binary64 (/ x (* y 2.0)))

↓

(FPCore (x y) :precision binary64 (* (/ x y) 0.5))

C

double code(double x, double y) {
	return x / (y * 2.0);
}

↓

double code(double x, double y) {
	return (x / y) * 0.5;
}

Fortran

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

↓

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (x / y) * 0.5d0
end function

Java

public static double code(double x, double y) {
	return x / (y * 2.0);
}

↓

public static double code(double x, double y) {
	return (x / y) * 0.5;
}

Python

def code(x, y):
	return x / (y * 2.0)

↓

def code(x, y):
	return (x / y) * 0.5

Julia

function code(x, y)
	return Float64(x / Float64(y * 2.0))
end

↓

function code(x, y)
	return Float64(Float64(x / y) * 0.5)
end

MATLAB

function tmp = code(x, y)
	tmp = x / (y * 2.0);
end

↓

function tmp = code(x, y)
	tmp = (x / y) * 0.5;
end

Wolfram

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

↓

code[x_, y_] := N[(N[(x / y), $MachinePrecision] * 0.5), $MachinePrecision]

Derivation

1. Initial program 0.0

   \[\frac{x}{y \cdot 2} \]

2. Applied egg-rr 0.0

   \[\leadsto \color{blue}{\frac{x}{y} \cdot 0.5} \]

3. Final simplification 0.0

   \[\leadsto \frac{x}{y} \cdot 0.5 \]

Reproduce

herbie shell --seed 2023046 
(FPCore (x y)
  :name "Diagrams.Solve.Polynomial:quadForm from diagrams-solve-0.1, C"
  :precision binary64
  (/ x (* y 2.0)))