Average Error: 24.6 → 10.2
Time: 6.8s
Precision: binary64
\[x + \frac{\left(y - z\right) \cdot \left(t - x\right)}{a - z} \]
\[\begin{array}{l} \mathbf{if}\;a \leq -5.662532019002217 \cdot 10^{-168}:\\ \;\;\;\;x + \frac{t - x}{\frac{a - z}{y - z}}\\ \mathbf{elif}\;a \leq 1.3731471589482035 \cdot 10^{-146}:\\ \;\;\;\;\left(\frac{x \cdot y}{z} + \left(t + \frac{a \cdot t}{z}\right)\right) - \left(\frac{t \cdot y}{z} + \frac{a \cdot x}{z}\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(t - x, \frac{y - z}{a - z}, x\right)\\ \end{array} \]
(FPCore (x y z t a) :precision binary64 (+ x (/ (* (- y z) (- t x)) (- a z))))
(FPCore (x y z t a)
 :precision binary64
 (if (<= a -5.662532019002217e-168)
   (+ x (/ (- t x) (/ (- a z) (- y z))))
   (if (<= a 1.3731471589482035e-146)
     (- (+ (/ (* x y) z) (+ t (/ (* a t) z))) (+ (/ (* t y) z) (/ (* a x) z)))
     (fma (- t x) (/ (- y z) (- a z)) x))))
double code(double x, double y, double z, double t, double a) {
	return x + (((y - z) * (t - x)) / (a - z));
}
double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -5.662532019002217e-168) {
		tmp = x + ((t - x) / ((a - z) / (y - z)));
	} else if (a <= 1.3731471589482035e-146) {
		tmp = (((x * y) / z) + (t + ((a * t) / z))) - (((t * y) / z) + ((a * x) / z));
	} else {
		tmp = fma((t - x), ((y - z) / (a - z)), x);
	}
	return tmp;
}
function code(x, y, z, t, a)
	return Float64(x + Float64(Float64(Float64(y - z) * Float64(t - x)) / Float64(a - z)))
end
function code(x, y, z, t, a)
	tmp = 0.0
	if (a <= -5.662532019002217e-168)
		tmp = Float64(x + Float64(Float64(t - x) / Float64(Float64(a - z) / Float64(y - z))));
	elseif (a <= 1.3731471589482035e-146)
		tmp = Float64(Float64(Float64(Float64(x * y) / z) + Float64(t + Float64(Float64(a * t) / z))) - Float64(Float64(Float64(t * y) / z) + Float64(Float64(a * x) / z)));
	else
		tmp = fma(Float64(t - x), Float64(Float64(y - z) / Float64(a - z)), x);
	end
	return tmp
end
code[x_, y_, z_, t_, a_] := N[(x + N[(N[(N[(y - z), $MachinePrecision] * N[(t - x), $MachinePrecision]), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_, y_, z_, t_, a_] := If[LessEqual[a, -5.662532019002217e-168], N[(x + N[(N[(t - x), $MachinePrecision] / N[(N[(a - z), $MachinePrecision] / N[(y - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.3731471589482035e-146], N[(N[(N[(N[(x * y), $MachinePrecision] / z), $MachinePrecision] + N[(t + N[(N[(a * t), $MachinePrecision] / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(t * y), $MachinePrecision] / z), $MachinePrecision] + N[(N[(a * x), $MachinePrecision] / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(t - x), $MachinePrecision] * N[(N[(y - z), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision] + x), $MachinePrecision]]]
x + \frac{\left(y - z\right) \cdot \left(t - x\right)}{a - z}
\begin{array}{l}
\mathbf{if}\;a \leq -5.662532019002217 \cdot 10^{-168}:\\
\;\;\;\;x + \frac{t - x}{\frac{a - z}{y - z}}\\

\mathbf{elif}\;a \leq 1.3731471589482035 \cdot 10^{-146}:\\
\;\;\;\;\left(\frac{x \cdot y}{z} + \left(t + \frac{a \cdot t}{z}\right)\right) - \left(\frac{t \cdot y}{z} + \frac{a \cdot x}{z}\right)\\

\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(t - x, \frac{y - z}{a - z}, x\right)\\


\end{array}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Bits error versus t

Bits error versus a

Target

Original24.6
Target12.6
Herbie10.2
\[\begin{array}{l} \mathbf{if}\;z < -1.2536131056095036 \cdot 10^{+188}:\\ \;\;\;\;t - \frac{y}{z} \cdot \left(t - x\right)\\ \mathbf{elif}\;z < 4.446702369113811 \cdot 10^{+64}:\\ \;\;\;\;x + \frac{y - z}{\frac{a - z}{t - x}}\\ \mathbf{else}:\\ \;\;\;\;t - \frac{y}{z} \cdot \left(t - x\right)\\ \end{array} \]

Derivation

  1. Split input into 3 regimes
  2. if a < -5.6625320190022166e-168

    1. Initial program 23.8

      \[x + \frac{\left(y - z\right) \cdot \left(t - x\right)}{a - z} \]
    2. Applied egg-rr10.2

      \[\leadsto x + \color{blue}{\frac{y - z}{a - z} \cdot \left(t - x\right)} \]
    3. Applied egg-rr10.2

      \[\leadsto x + \color{blue}{\frac{t - x}{\frac{a - z}{y - z}}} \]

    if -5.6625320190022166e-168 < a < 1.3731471589482035e-146

    1. Initial program 29.5

      \[x + \frac{\left(y - z\right) \cdot \left(t - x\right)}{a - z} \]
    2. Simplified25.8

      \[\leadsto \color{blue}{\mathsf{fma}\left(y - z, \frac{t - x}{a - z}, x\right)} \]
    3. Taylor expanded in z around inf 12.1

      \[\leadsto \color{blue}{\left(\frac{y \cdot x}{z} + \left(t + \frac{a \cdot t}{z}\right)\right) - \left(\frac{y \cdot t}{z} + \frac{a \cdot x}{z}\right)} \]

    if 1.3731471589482035e-146 < a

    1. Initial program 22.7

      \[x + \frac{\left(y - z\right) \cdot \left(t - x\right)}{a - z} \]
    2. Applied egg-rr9.2

      \[\leadsto x + \color{blue}{\frac{y - z}{a - z} \cdot \left(t - x\right)} \]
    3. Applied egg-rr9.2

      \[\leadsto \color{blue}{\mathsf{fma}\left(t - x, \frac{y - z}{a - z}, x\right)} \]
  3. Recombined 3 regimes into one program.
  4. Final simplification10.2

    \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -5.662532019002217 \cdot 10^{-168}:\\ \;\;\;\;x + \frac{t - x}{\frac{a - z}{y - z}}\\ \mathbf{elif}\;a \leq 1.3731471589482035 \cdot 10^{-146}:\\ \;\;\;\;\left(\frac{x \cdot y}{z} + \left(t + \frac{a \cdot t}{z}\right)\right) - \left(\frac{t \cdot y}{z} + \frac{a \cdot x}{z}\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(t - x, \frac{y - z}{a - z}, x\right)\\ \end{array} \]

Reproduce

herbie shell --seed 2022133 
(FPCore (x y z t a)
  :name "Graphics.Rendering.Chart.Axis.Types:invLinMap from Chart-1.5.3"
  :precision binary64

  :herbie-target
  (if (< z -1.2536131056095036e+188) (- t (* (/ y z) (- t x))) (if (< z 4.446702369113811e+64) (+ x (/ (- y z) (/ (- a z) (- t x)))) (- t (* (/ y z) (- t x)))))

  (+ x (/ (* (- y z) (- t x)) (- a z))))