Diagrams.TwoD.Segment:bezierClip from diagrams-lib-1.3.0.3

Average Accuracy: 100.0% → 100.0%

Time: 2.7s

Precision: binary64

Cost: 576

Math

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

↓

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

FPCore

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

↓

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

C

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

↓

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

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

Java

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

↓

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

Python

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

↓

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

Julia

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

↓

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

MATLAB

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

↓

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

Wolfram

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

↓

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

Target

Original	100.0%
Target	100.0%
Herbie	100.0%

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

Derivation

1. Initial program 100.0%

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

2. Final simplification 100.0%

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

Alternatives

Alternative 1
Accuracy	60.3%
Cost	1444

\[\begin{array}{l} t_0 := y \cdot \left(-z\right)\\ \mathbf{if}\;y \leq -2.45 \cdot 10^{+96}:\\ \;\;\;\;x \cdot y\\ \mathbf{elif}\;y \leq -7.8 \cdot 10^{+70}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y \leq -5.1 \cdot 10^{-15}:\\ \;\;\;\;x \cdot y\\ \mathbf{elif}\;y \leq -6.2 \cdot 10^{-159}:\\ \;\;\;\;z\\ \mathbf{elif}\;y \leq -1.76 \cdot 10^{-171}:\\ \;\;\;\;x \cdot y\\ \mathbf{elif}\;y \leq 1.8 \cdot 10^{-169}:\\ \;\;\;\;z\\ \mathbf{elif}\;y \leq 1.7 \cdot 10^{-134}:\\ \;\;\;\;x \cdot y\\ \mathbf{elif}\;y \leq 8.4 \cdot 10^{-75}:\\ \;\;\;\;z\\ \mathbf{elif}\;y \leq 1.16 \cdot 10^{+70}:\\ \;\;\;\;x \cdot y\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]

Alternative 2
Accuracy	78.2%
Cost	1112

\[\begin{array}{l} t_0 := y \cdot \left(x - z\right)\\ \mathbf{if}\;y \leq -7 \cdot 10^{-15}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y \leq -6.2 \cdot 10^{-159}:\\ \;\;\;\;z\\ \mathbf{elif}\;y \leq -1.76 \cdot 10^{-171}:\\ \;\;\;\;x \cdot y\\ \mathbf{elif}\;y \leq 1.8 \cdot 10^{-169}:\\ \;\;\;\;z\\ \mathbf{elif}\;y \leq 2.2 \cdot 10^{-134}:\\ \;\;\;\;x \cdot y\\ \mathbf{elif}\;y \leq 1.06 \cdot 10^{-74}:\\ \;\;\;\;z\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]

Alternative 3
Accuracy	98.7%
Cost	585

\[\begin{array}{l} \mathbf{if}\;y \leq -180 \lor \neg \left(y \leq 1\right):\\ \;\;\;\;y \cdot \left(x - z\right)\\ \mathbf{else}:\\ \;\;\;\;z + x \cdot y\\ \end{array} \]

Alternative 4
Accuracy	60.1%
Cost	456

\[\begin{array}{l} \mathbf{if}\;z \leq -2.6 \cdot 10^{+30}:\\ \;\;\;\;z\\ \mathbf{elif}\;z \leq 2.4 \cdot 10^{-90}:\\ \;\;\;\;x \cdot y\\ \mathbf{else}:\\ \;\;\;\;z\\ \end{array} \]

Alternative 5
Accuracy	45.3%
Cost	64

\[z \]

Reproduce

herbie shell --seed 2023122 
(FPCore (x y z)
  :name "Diagrams.TwoD.Segment:bezierClip from diagrams-lib-1.3.0.3"
  :precision binary64

  :herbie-target
  (- z (* (- z x) y))

  (+ (* x y) (* z (- 1.0 y))))