Diagrams.ThreeD.Transform:aboutY from diagrams-lib-1.3.0.3

Average Accuracy: 99.8% → 99.8%

Time: 11.6s

Precision: binary64

Cost: 19520

Math

\[x \cdot \cos y + z \cdot \sin y \]

↓

\[\mathsf{fma}\left(x, \cos y, z \cdot \sin y\right) \]

FPCore

(FPCore (x y z) :precision binary64 (+ (* x (cos y)) (* z (sin y))))

↓

(FPCore (x y z) :precision binary64 (fma x (cos y) (* z (sin y))))

C

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

↓

double code(double x, double y, double z) {
	return fma(x, cos(y), (z * sin(y)));
}

Julia

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

↓

function code(x, y, z)
	return fma(x, cos(y), Float64(z * sin(y)))
end

Wolfram

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

↓

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

Derivation

1. Initial program 99.8%

   \[x \cdot \cos y + z \cdot \sin y \]

2. Simplified 99.8%

   \[\leadsto \color{blue}{\mathsf{fma}\left(x, \cos y, z \cdot \sin y\right)} \]
   Proof

   [Start] 99.8	\[ x \cdot \cos y + z \cdot \sin y \]
   fma-def [=>] 99.8	\[ \color{blue}{\mathsf{fma}\left(x, \cos y, z \cdot \sin y\right)} \]

3. Final simplification 99.8%

   \[\leadsto \mathsf{fma}\left(x, \cos y, z \cdot \sin y\right) \]

Alternatives

Alternative 1
Accuracy	85.8%
Cost	13257

\[\begin{array}{l} \mathbf{if}\;x \leq -6.5 \cdot 10^{+64} \lor \neg \left(x \leq 3 \cdot 10^{+113}\right):\\ \;\;\;\;x \cdot \cos y\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\sin y, z, x\right)\\ \end{array} \]

Alternative 2
Accuracy	99.8%
Cost	13248

\[z \cdot \sin y + x \cdot \cos y \]

Alternative 3
Accuracy	74.5%
Cost	7253

\[\begin{array}{l} t_0 := z \cdot \sin y\\ t_1 := x \cdot \cos y\\ \mathbf{if}\;y \leq -7.8 \cdot 10^{+103}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y \leq -0.0105:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 4.3 \cdot 10^{-13}:\\ \;\;\;\;x + y \cdot z\\ \mathbf{elif}\;y \leq 1.75 \cdot 10^{+49} \lor \neg \left(y \leq 1.2 \cdot 10^{+145}\right):\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

Alternative 4
Accuracy	74.6%
Cost	7253

\[\begin{array}{l} t_0 := z \cdot \sin y\\ t_1 := x \cdot \cos y\\ \mathbf{if}\;y \leq -6.6 \cdot 10^{+102}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y \leq -0.00185:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 4.3 \cdot 10^{-13}:\\ \;\;\;\;\mathsf{fma}\left(z, y, x\right)\\ \mathbf{elif}\;y \leq 2.05 \cdot 10^{+46} \lor \neg \left(y \leq 3.7 \cdot 10^{+146}\right):\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

Alternative 5
Accuracy	85.8%
Cost	6985

\[\begin{array}{l} \mathbf{if}\;z \leq -2.2 \cdot 10^{-106} \lor \neg \left(z \leq 2.95 \cdot 10^{-67}\right):\\ \;\;\;\;x + z \cdot \sin y\\ \mathbf{else}:\\ \;\;\;\;x \cdot \cos y\\ \end{array} \]

Alternative 6
Accuracy	74.2%
Cost	6857

\[\begin{array}{l} \mathbf{if}\;y \leq -0.0036 \lor \neg \left(y \leq 4.3 \cdot 10^{-13}\right):\\ \;\;\;\;z \cdot \sin y\\ \mathbf{else}:\\ \;\;\;\;x + y \cdot z\\ \end{array} \]

Alternative 7
Accuracy	41.6%
Cost	456

\[\begin{array}{l} \mathbf{if}\;x \leq -6.5 \cdot 10^{-167}:\\ \;\;\;\;x\\ \mathbf{elif}\;x \leq 6 \cdot 10^{-150}:\\ \;\;\;\;y \cdot z\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 8
Accuracy	51.6%
Cost	320

\[x + y \cdot z \]

Alternative 9
Accuracy	39.1%
Cost	64

\[x \]

Reproduce

herbie shell --seed 2023138 
(FPCore (x y z)
  :name "Diagrams.ThreeD.Transform:aboutY from diagrams-lib-1.3.0.3"
  :precision binary64
  (+ (* x (cos y)) (* z (sin y))))