(FPCore (x y z t) :precision binary64 (/ (- (+ x y) z) (* t 2.0)))
(FPCore (x y z t) :precision binary64 (fma 1.0 (* 0.5 (+ (/ x t) (/ y t))) (* (/ z t) -0.5)))
double code(double x, double y, double z, double t) {
return ((x + y) - z) / (t * 2.0);
}
double code(double x, double y, double z, double t) {
return fma(1.0, (0.5 * ((x / t) + (y / t))), ((z / t) * -0.5));
}
function code(x, y, z, t) return Float64(Float64(Float64(x + y) - z) / Float64(t * 2.0)) end
function code(x, y, z, t) return fma(1.0, Float64(0.5 * Float64(Float64(x / t) + Float64(y / t))), Float64(Float64(z / t) * -0.5)) end
code[x_, y_, z_, t_] := N[(N[(N[(x + y), $MachinePrecision] - z), $MachinePrecision] / N[(t * 2.0), $MachinePrecision]), $MachinePrecision]
code[x_, y_, z_, t_] := N[(1.0 * N[(0.5 * N[(N[(x / t), $MachinePrecision] + N[(y / t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(z / t), $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision]
\frac{\left(x + y\right) - z}{t \cdot 2}
\mathsf{fma}\left(1, 0.5 \cdot \left(\frac{x}{t} + \frac{y}{t}\right), \frac{z}{t} \cdot -0.5\right)



Bits error versus x



Bits error versus y



Bits error versus z



Bits error versus t
Initial program 0.1
Taylor expanded in x around 0 0.0
Applied egg-rr0.0
Final simplification0.0
herbie shell --seed 2022150
(FPCore (x y z t)
:name "Optimisation.CirclePacking:place from circle-packing-0.1.0.4, B"
:precision binary64
(/ (- (+ x y) z) (* t 2.0)))