Average Error: 0.1 → 0.1
Time: 6.0s
Precision: binary64
\[x \cdot \cos y + z \cdot \sin y \]
↓
\[\mathsf{fma}\left(\cos y, x, z \cdot \sin y\right) \]
(FPCore (x y z) :precision binary64 (+ (* x (cos y)) (* z (sin y))))
↓
(FPCore (x y z) :precision binary64 (fma (cos y) x (* z (sin y))))
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(cos(y), x, (z * sin(y)));
}

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

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[(N[Cos[y], $MachinePrecision] * x + N[(z * N[Sin[y], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

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

Error

Bits error versus x

Bits error versus y

Bits error versus z

Derivation

  1. Initial program 0.1

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

  2. Simplified0.1

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

  3. Applied egg-rr0.3

    \[\leadsto \mathsf{fma}\left(x, \color{blue}{e^{\mathsf{log1p}\left(\cos y\right)} - 1}, z \cdot \sin y\right) \]

  4. Applied egg-rr0.4

    \[\leadsto \mathsf{fma}\left(x, \color{blue}{\log \left(\sqrt{e^{\cos y}}\right) + \log \left(\sqrt{e^{\cos y}}\right)}, z \cdot \sin y\right) \]

  5. Applied egg-rr0.1

    \[\leadsto \color{blue}{{\left(\mathsf{fma}\left(\cos y, x, z \cdot \sin y\right)\right)}^{1}} \]

  6. Final simplification0.1

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

Reproduce

herbie shell --seed 2022134 
(FPCore (x y z)
  :name "Diagrams.ThreeD.Transform:aboutY from diagrams-lib-1.3.0.3"
  :precision binary64
  (+ (* x (cos y)) (* z (sin y))))