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

Average Error: 0.0 → 0.0

Time: 1.3s

Precision: binary64

Cost: 448

Math

\[x - \left(y \cdot 4\right) \cdot z \]

↓

\[x + z \cdot \left(y \cdot -4\right) \]

FPCore

(FPCore (x y z) :precision binary64 (- x (* (* y 4.0) z)))

↓

(FPCore (x y z) :precision binary64 (+ x (* z (* y -4.0))))

C

double code(double x, double y, double z) {
	return x - ((y * 4.0) * z);
}

↓

double code(double x, double y, double z) {
	return x + (z * (y * -4.0));
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = x - ((y * 4.0d0) * z)
end function

↓

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = x + (z * (y * (-4.0d0)))
end function

Java

public static double code(double x, double y, double z) {
	return x - ((y * 4.0) * z);
}

↓

public static double code(double x, double y, double z) {
	return x + (z * (y * -4.0));
}

Python

def code(x, y, z):
	return x - ((y * 4.0) * z)

↓

def code(x, y, z):
	return x + (z * (y * -4.0))

Julia

function code(x, y, z)
	return Float64(x - Float64(Float64(y * 4.0) * z))
end

↓

function code(x, y, z)
	return Float64(x + Float64(z * Float64(y * -4.0)))
end

MATLAB

function tmp = code(x, y, z)
	tmp = x - ((y * 4.0) * z);
end

↓

function tmp = code(x, y, z)
	tmp = x + (z * (y * -4.0));
end

Wolfram

code[x_, y_, z_] := N[(x - N[(N[(y * 4.0), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]

↓

code[x_, y_, z_] := N[(x + N[(z * N[(y * -4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 0.0

   \[x - \left(y \cdot 4\right) \cdot z \]

2. Final simplification 0.0

   \[\leadsto x + z \cdot \left(y \cdot -4\right) \]

Reproduce

herbie shell --seed 2022329 
(FPCore (x y z)
  :name "Diagrams.Solve.Polynomial:quadForm from diagrams-solve-0.1, A"
  :precision binary64
  (- x (* (* y 4.0) z)))