FRP.Yampa.Vector3:vector3Rho from Yampa-0.10.2

Percentage Accurate: 44.6% → 99.2%

Time: 2.9s

Precision: binary64

Cost: 6528

• Unsound rule application detected in e-graph. Results may not be sound.

\[ \begin{array}{c}[x, y, z] = \mathsf{sort}([x, y, z])\\ \end{array} \]

Math

\[\sqrt{\left(x \cdot x + y \cdot y\right) + z \cdot z} \]

↓

\[\mathsf{hypot}\left(z, x\right) \]

FPCore

(FPCore (x y z) :precision binary64 (sqrt (+ (+ (* x x) (* y y)) (* z z))))

↓

(FPCore (x y z) :precision binary64 (hypot z x))

C

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

↓

double code(double x, double y, double z) {
	return hypot(z, x);
}

Java

public static double code(double x, double y, double z) {
	return Math.sqrt((((x * x) + (y * y)) + (z * z)));
}

↓

public static double code(double x, double y, double z) {
	return Math.hypot(z, x);
}

Python

def code(x, y, z):
	return math.sqrt((((x * x) + (y * y)) + (z * z)))

↓

def code(x, y, z):
	return math.hypot(z, x)

Julia

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

↓

function code(x, y, z)
	return hypot(z, x)
end

MATLAB

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

↓

function tmp = code(x, y, z)
	tmp = hypot(z, x);
end

Wolfram

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

↓

code[x_, y_, z_] := N[Sqrt[z ^ 2 + x ^ 2], $MachinePrecision]

Target

Original	44.6%
Target	69.9%
Herbie	99.2%

\[\begin{array}{l} \mathbf{if}\;z < -6.396479394109776 \cdot 10^{+136}:\\ \;\;\;\;-z\\ \mathbf{elif}\;z < 7.320293694404182 \cdot 10^{+117}:\\ \;\;\;\;\sqrt{\left(z \cdot z + x \cdot x\right) + y \cdot y}\\ \mathbf{else}:\\ \;\;\;\;z\\ \end{array} \]

Derivation

1. Initial program 49.9%

   \[\sqrt{\left(x \cdot x + y \cdot y\right) + z \cdot z} \]

2. Taylor expanded in y around 0 37.3%

   \[\leadsto \color{blue}{\sqrt{{z}^{2} + {x}^{2}}} \]

3. Simplified 70.1%

   \[\leadsto \color{blue}{\mathsf{hypot}\left(z, x\right)} \]
   Step-by-step derivation

   [Start] 37.3	\[ \sqrt{{z}^{2} + {x}^{2}} \]
   unpow2 [=>] 37.3	\[ \sqrt{\color{blue}{z \cdot z} + {x}^{2}} \]
   unpow2 [=>] 37.3	\[ \sqrt{z \cdot z + \color{blue}{x \cdot x}} \]
   hypot-def [=>] 70.1	\[ \color{blue}{\mathsf{hypot}\left(z, x\right)} \]

4. Final simplification 70.1%

   \[\leadsto \mathsf{hypot}\left(z, x\right) \]

Alternatives

Alternative 1
Accuracy	79.0%
Cost	7188

\[\begin{array}{l} \mathbf{if}\;x \leq -1.86 \cdot 10^{+133}:\\ \;\;\;\;\mathsf{hypot}\left(y, x\right)\\ \mathbf{elif}\;x \leq -1.8 \cdot 10^{+115}:\\ \;\;\;\;z\\ \mathbf{elif}\;x \leq -5.4 \cdot 10^{+45}:\\ \;\;\;\;\mathsf{hypot}\left(y, x\right)\\ \mathbf{elif}\;x \leq -1.1 \cdot 10^{+25}:\\ \;\;\;\;z\\ \mathbf{elif}\;x \leq -2.15 \cdot 10^{-42}:\\ \;\;\;\;\mathsf{hypot}\left(y, x\right)\\ \mathbf{else}:\\ \;\;\;\;z\\ \end{array} \]

Alternative 2
Accuracy	76.9%
Cost	788

\[\begin{array}{l} \mathbf{if}\;x \leq -1.85 \cdot 10^{+133}:\\ \;\;\;\;-x\\ \mathbf{elif}\;x \leq -2.65 \cdot 10^{+115}:\\ \;\;\;\;z\\ \mathbf{elif}\;x \leq -2.6 \cdot 10^{+99}:\\ \;\;\;\;-x\\ \mathbf{elif}\;x \leq -9.6 \cdot 10^{+24}:\\ \;\;\;\;z\\ \mathbf{elif}\;x \leq -3 \cdot 10^{-38}:\\ \;\;\;\;-x\\ \mathbf{else}:\\ \;\;\;\;z\\ \end{array} \]

Alternative 3
Accuracy	49.8%
Cost	64

\[z \]

Reproduce

herbie shell --seed 2023160 
(FPCore (x y z)
  :name "FRP.Yampa.Vector3:vector3Rho from Yampa-0.10.2"
  :precision binary64

  :herbie-target
  (if (< z -6.396479394109776e+136) (- z) (if (< z 7.320293694404182e+117) (sqrt (+ (+ (* z z) (* x x)) (* y y))) z))

  (sqrt (+ (+ (* x x) (* y y)) (* z z))))