Graphics.Rendering.Chart.Drawing:drawTextsR from Chart-1.5.3

Average Accuracy: 100.0% → 100.0%

Time: 2.3s

Precision: binary64

Cost: 576

Math

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

↓

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

FPCore

(FPCore (x y z) :precision binary64 (+ (* x y) (* (- x 1.0) z)))

↓

(FPCore (x y z) :precision binary64 (+ (* x y) (* (+ x -1.0) z)))

C

double code(double x, double y, double z) {
	return (x * y) + ((x - 1.0) * z);
}

↓

double code(double x, double y, double z) {
	return (x * y) + ((x + -1.0) * z);
}

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) + ((x - 1.0d0) * 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 * y) + ((x + (-1.0d0)) * z)
end function

Java

public static double code(double x, double y, double z) {
	return (x * y) + ((x - 1.0) * z);
}

↓

public static double code(double x, double y, double z) {
	return (x * y) + ((x + -1.0) * z);
}

Python

def code(x, y, z):
	return (x * y) + ((x - 1.0) * z)

↓

def code(x, y, z):
	return (x * y) + ((x + -1.0) * z)

Julia

function code(x, y, z)
	return Float64(Float64(x * y) + Float64(Float64(x - 1.0) * z))
end

↓

function code(x, y, z)
	return Float64(Float64(x * y) + Float64(Float64(x + -1.0) * z))
end

MATLAB

function tmp = code(x, y, z)
	tmp = (x * y) + ((x - 1.0) * z);
end

↓

function tmp = code(x, y, z)
	tmp = (x * y) + ((x + -1.0) * z);
end

Wolfram

code[x_, y_, z_] := N[(N[(x * y), $MachinePrecision] + N[(N[(x - 1.0), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]

↓

code[x_, y_, z_] := N[(N[(x * y), $MachinePrecision] + N[(N[(x + -1.0), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 100.0%

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

2. Final simplification 100.0%

   \[\leadsto x \cdot y + \left(x + -1\right) \cdot z \]

Alternatives

Alternative 1
Accuracy	89.1%
Cost	585

\[\begin{array}{l} \mathbf{if}\;y \leq -5.5 \cdot 10^{-108} \lor \neg \left(y \leq 1.3 \cdot 10^{-121}\right):\\ \;\;\;\;x \cdot y - z\\ \mathbf{else}:\\ \;\;\;\;\left(x + -1\right) \cdot z\\ \end{array} \]

Alternative 2
Accuracy	100.0%
Cost	448

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

Alternative 3
Accuracy	63.8%
Cost	320

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

Alternative 4
Accuracy	45.5%
Cost	128

\[-z \]

Reproduce

herbie shell --seed 2023135 
(FPCore (x y z)
  :name "Graphics.Rendering.Chart.Drawing:drawTextsR from Chart-1.5.3"
  :precision binary64
  (+ (* x y) (* (- x 1.0) z)))