Numeric.Signal:interpolate from hsignal-0.2.7.1

Percentage Accurate: 80.1% → 94.8%

Time: 20.3s

Precision: binary64

Cost: 4944

Math

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

↓

\[\begin{array}{l} t_1 := \frac{t}{\frac{a - z}{y - z}} + x \cdot \left(1 - \frac{y - z}{a - z}\right)\\ t_2 := x - \left(y - z\right) \cdot \frac{x - t}{a - z}\\ \mathbf{if}\;t_2 \leq -5 \cdot 10^{+288}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t_2 \leq -1 \cdot 10^{-306}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t_2 \leq 0:\\ \;\;\;\;t - \frac{a - y}{\frac{z}{x}}\\ \mathbf{elif}\;t_2 \leq 4 \cdot 10^{+242}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

FPCore

(FPCore (x y z t a) :precision binary64 (+ x (* (- y z) (/ (- t x) (- a z)))))

↓

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ (/ t (/ (- a z) (- y z))) (* x (- 1.0 (/ (- y z) (- a z))))))
        (t_2 (- x (* (- y z) (/ (- x t) (- a z))))))
   (if (<= t_2 -5e+288)
     t_2
     (if (<= t_2 -1e-306)
       t_1
       (if (<= t_2 0.0)
         (- t (/ (- a y) (/ z x)))
         (if (<= t_2 4e+242) t_1 t_2))))))

C

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 t_1 = (t / ((a - z) / (y - z))) + (x * (1.0 - ((y - z) / (a - z))));
	double t_2 = x - ((y - z) * ((x - t) / (a - z)));
	double tmp;
	if (t_2 <= -5e+288) {
		tmp = t_2;
	} else if (t_2 <= -1e-306) {
		tmp = t_1;
	} else if (t_2 <= 0.0) {
		tmp = t - ((a - y) / (z / x));
	} else if (t_2 <= 4e+242) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    code = x + ((y - z) * ((t - x) / (a - z)))
end function

↓

real(8) function code(x, y, z, t, a)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = (t / ((a - z) / (y - z))) + (x * (1.0d0 - ((y - z) / (a - z))))
    t_2 = x - ((y - z) * ((x - t) / (a - z)))
    if (t_2 <= (-5d+288)) then
        tmp = t_2
    else if (t_2 <= (-1d-306)) then
        tmp = t_1
    else if (t_2 <= 0.0d0) then
        tmp = t - ((a - y) / (z / x))
    else if (t_2 <= 4d+242) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	return x + ((y - z) * ((t - x) / (a - z)));
}

↓

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = (t / ((a - z) / (y - z))) + (x * (1.0 - ((y - z) / (a - z))));
	double t_2 = x - ((y - z) * ((x - t) / (a - z)));
	double tmp;
	if (t_2 <= -5e+288) {
		tmp = t_2;
	} else if (t_2 <= -1e-306) {
		tmp = t_1;
	} else if (t_2 <= 0.0) {
		tmp = t - ((a - y) / (z / x));
	} else if (t_2 <= 4e+242) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	return x + ((y - z) * ((t - x) / (a - z)))

↓

def code(x, y, z, t, a):
	t_1 = (t / ((a - z) / (y - z))) + (x * (1.0 - ((y - z) / (a - z))))
	t_2 = x - ((y - z) * ((x - t) / (a - z)))
	tmp = 0
	if t_2 <= -5e+288:
		tmp = t_2
	elif t_2 <= -1e-306:
		tmp = t_1
	elif t_2 <= 0.0:
		tmp = t - ((a - y) / (z / x))
	elif t_2 <= 4e+242:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a)
	return Float64(x + Float64(Float64(y - z) * Float64(Float64(t - x) / Float64(a - z))))
end

↓

function code(x, y, z, t, a)
	t_1 = Float64(Float64(t / Float64(Float64(a - z) / Float64(y - z))) + Float64(x * Float64(1.0 - Float64(Float64(y - z) / Float64(a - z)))))
	t_2 = Float64(x - Float64(Float64(y - z) * Float64(Float64(x - t) / Float64(a - z))))
	tmp = 0.0
	if (t_2 <= -5e+288)
		tmp = t_2;
	elseif (t_2 <= -1e-306)
		tmp = t_1;
	elseif (t_2 <= 0.0)
		tmp = Float64(t - Float64(Float64(a - y) / Float64(z / x)));
	elseif (t_2 <= 4e+242)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp = code(x, y, z, t, a)
	tmp = x + ((y - z) * ((t - x) / (a - z)));
end

↓

function tmp_2 = code(x, y, z, t, a)
	t_1 = (t / ((a - z) / (y - z))) + (x * (1.0 - ((y - z) / (a - z))));
	t_2 = x - ((y - z) * ((x - t) / (a - z)));
	tmp = 0.0;
	if (t_2 <= -5e+288)
		tmp = t_2;
	elseif (t_2 <= -1e-306)
		tmp = t_1;
	elseif (t_2 <= 0.0)
		tmp = t - ((a - y) / (z / x));
	elseif (t_2 <= 4e+242)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := N[(x + N[(N[(y - z), $MachinePrecision] * N[(N[(t - x), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(N[(t / N[(N[(a - z), $MachinePrecision] / N[(y - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(1.0 - N[(N[(y - z), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x - N[(N[(y - z), $MachinePrecision] * N[(N[(x - t), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$2, -5e+288], t$95$2, If[LessEqual[t$95$2, -1e-306], t$95$1, If[LessEqual[t$95$2, 0.0], N[(t - N[(N[(a - y), $MachinePrecision] / N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$2, 4e+242], t$95$1, t$95$2]]]]]]

Derivation

1. Split input into 3 regimes

2. if (+.f64 x (*.f64 (-.f64 y z) (/.f64 (-.f64 t x) (-.f64 a z)))) < -5.0000000000000003e288 or 4.0000000000000002e242 < (+.f64 x (*.f64 (-.f64 y z) (/.f64 (-.f64 t x) (-.f64 a z))))

   1. Initial program 88.8%

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

   if -5.0000000000000003e288 < (+.f64 x (*.f64 (-.f64 y z) (/.f64 (-.f64 t x) (-.f64 a z)))) < -1.00000000000000003e-306 or 0.0 < (+.f64 x (*.f64 (-.f64 y z) (/.f64 (-.f64 t x) (-.f64 a z)))) < 4.0000000000000002e242

   1. Initial program 90.5%

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

   2. Taylor expanded in x around -inf 83.8%

      \[\leadsto \color{blue}{\frac{t \cdot \left(y - z\right)}{a - z} + -1 \cdot \left(\left(\frac{y}{a - z} - \left(\frac{z}{a - z} + 1\right)\right) \cdot x\right)} \]

   3. Simplified 97.9%

      \[\leadsto \color{blue}{\frac{t}{\frac{a - z}{y - z}} - x \cdot \left(\frac{y - z}{a - z} + -1\right)} \]
      Step-by-step derivation

      [Start] 83.8%	\[ \frac{t \cdot \left(y - z\right)}{a - z} + -1 \cdot \left(\left(\frac{y}{a - z} - \left(\frac{z}{a - z} + 1\right)\right) \cdot x\right) \]
      mul-1-neg [=>] 83.8%	\[ \frac{t \cdot \left(y - z\right)}{a - z} + \color{blue}{\left(-\left(\frac{y}{a - z} - \left(\frac{z}{a - z} + 1\right)\right) \cdot x\right)} \]
      unsub-neg [=>] 83.8%	\[ \color{blue}{\frac{t \cdot \left(y - z\right)}{a - z} - \left(\frac{y}{a - z} - \left(\frac{z}{a - z} + 1\right)\right) \cdot x} \]
      associate-/l* [=>] 97.9%	\[ \color{blue}{\frac{t}{\frac{a - z}{y - z}}} - \left(\frac{y}{a - z} - \left(\frac{z}{a - z} + 1\right)\right) \cdot x \]
      *-commutative [=>] 97.9%	\[ \frac{t}{\frac{a - z}{y - z}} - \color{blue}{x \cdot \left(\frac{y}{a - z} - \left(\frac{z}{a - z} + 1\right)\right)} \]
      associate--r+ [=>] 97.9%	\[ \frac{t}{\frac{a - z}{y - z}} - x \cdot \color{blue}{\left(\left(\frac{y}{a - z} - \frac{z}{a - z}\right) - 1\right)} \]
      div-sub [<=] 97.9%	\[ \frac{t}{\frac{a - z}{y - z}} - x \cdot \left(\color{blue}{\frac{y - z}{a - z}} - 1\right) \]
      sub-neg [=>] 97.9%	\[ \frac{t}{\frac{a - z}{y - z}} - x \cdot \color{blue}{\left(\frac{y - z}{a - z} + \left(-1\right)\right)} \]
      metadata-eval [=>] 97.9%	\[ \frac{t}{\frac{a - z}{y - z}} - x \cdot \left(\frac{y - z}{a - z} + \color{blue}{-1}\right) \]

   if -1.00000000000000003e-306 < (+.f64 x (*.f64 (-.f64 y z) (/.f64 (-.f64 t x) (-.f64 a z)))) < 0.0

   1. Initial program 3.2%

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

   2. Simplified 3.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(y - z, \frac{t - x}{a - z}, x\right)} \]
      Step-by-step derivation

      [Start] 3.2%	\[ x + \left(y - z\right) \cdot \frac{t - x}{a - z} \]
      +-commutative [=>] 3.2%	\[ \color{blue}{\left(y - z\right) \cdot \frac{t - x}{a - z} + x} \]
      fma-def [=>] 3.0%	\[ \color{blue}{\mathsf{fma}\left(y - z, \frac{t - x}{a - z}, x\right)} \]

   3. Taylor expanded in z around inf 77.8%

      \[\leadsto \color{blue}{-1 \cdot \frac{y \cdot \left(t - x\right)}{z} + \left(t + \frac{a \cdot \left(t - x\right)}{z}\right)} \]

   4. Taylor expanded in t around -inf 77.8%

      \[\leadsto \color{blue}{\frac{y \cdot x}{z} + \left(-1 \cdot \frac{a \cdot x}{z} + -1 \cdot \left(t \cdot \left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) - 1\right)\right)\right)} \]

   5. Simplified 99.7%

      \[\leadsto \color{blue}{\frac{y - a}{\frac{z}{x}} - t \cdot \left(\frac{y - a}{z} + -1\right)} \]
      Step-by-step derivation

      [Start] 77.8%	\[ \frac{y \cdot x}{z} + \left(-1 \cdot \frac{a \cdot x}{z} + -1 \cdot \left(t \cdot \left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) - 1\right)\right)\right) \]
      associate-+r+ [=>] 77.8%	\[ \color{blue}{\left(\frac{y \cdot x}{z} + -1 \cdot \frac{a \cdot x}{z}\right) + -1 \cdot \left(t \cdot \left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) - 1\right)\right)} \]
      mul-1-neg [=>] 77.8%	\[ \left(\frac{y \cdot x}{z} + -1 \cdot \frac{a \cdot x}{z}\right) + \color{blue}{\left(-t \cdot \left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) - 1\right)\right)} \]
      unsub-neg [=>] 77.8%	\[ \color{blue}{\left(\frac{y \cdot x}{z} + -1 \cdot \frac{a \cdot x}{z}\right) - t \cdot \left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) - 1\right)} \]
      mul-1-neg [=>] 77.8%	\[ \left(\frac{y \cdot x}{z} + \color{blue}{\left(-\frac{a \cdot x}{z}\right)}\right) - t \cdot \left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) - 1\right) \]
      unsub-neg [=>] 77.8%	\[ \color{blue}{\left(\frac{y \cdot x}{z} - \frac{a \cdot x}{z}\right)} - t \cdot \left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) - 1\right) \]
      associate-/l* [=>] 90.1%	\[ \left(\color{blue}{\frac{y}{\frac{z}{x}}} - \frac{a \cdot x}{z}\right) - t \cdot \left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) - 1\right) \]
      associate-/l* [=>] 99.7%	\[ \left(\frac{y}{\frac{z}{x}} - \color{blue}{\frac{a}{\frac{z}{x}}}\right) - t \cdot \left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) - 1\right) \]
      div-sub [<=] 99.7%	\[ \color{blue}{\frac{y - a}{\frac{z}{x}}} - t \cdot \left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) - 1\right) \]
      sub-neg [=>] 99.7%	\[ \frac{y - a}{\frac{z}{x}} - t \cdot \color{blue}{\left(\left(-1 \cdot \frac{a}{z} + \frac{y}{z}\right) + \left(-1\right)\right)} \]
      +-commutative [=>] 99.7%	\[ \frac{y - a}{\frac{z}{x}} - t \cdot \left(\color{blue}{\left(\frac{y}{z} + -1 \cdot \frac{a}{z}\right)} + \left(-1\right)\right) \]
      mul-1-neg [=>] 99.7%	\[ \frac{y - a}{\frac{z}{x}} - t \cdot \left(\left(\frac{y}{z} + \color{blue}{\left(-\frac{a}{z}\right)}\right) + \left(-1\right)\right) \]
      sub-neg [<=] 99.7%	\[ \frac{y - a}{\frac{z}{x}} - t \cdot \left(\color{blue}{\left(\frac{y}{z} - \frac{a}{z}\right)} + \left(-1\right)\right) \]
      div-sub [<=] 99.7%	\[ \frac{y - a}{\frac{z}{x}} - t \cdot \left(\color{blue}{\frac{y - a}{z}} + \left(-1\right)\right) \]
      metadata-eval [=>] 99.7%	\[ \frac{y - a}{\frac{z}{x}} - t \cdot \left(\frac{y - a}{z} + \color{blue}{-1}\right) \]

   6. Taylor expanded in z around inf 99.7%

      \[\leadsto \frac{y - a}{\frac{z}{x}} - \color{blue}{-1 \cdot t} \]

   7. Simplified 99.7%

      \[\leadsto \frac{y - a}{\frac{z}{x}} - \color{blue}{\left(-t\right)} \]
      Step-by-step derivation

      [Start] 99.7%	\[ \frac{y - a}{\frac{z}{x}} - -1 \cdot t \]
      neg-mul-1 [<=] 99.7%	\[ \frac{y - a}{\frac{z}{x}} - \color{blue}{\left(-t\right)} \]

3. Recombined 3 regimes into one program.

4. Final simplification 96.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x - \left(y - z\right) \cdot \frac{x - t}{a - z} \leq -5 \cdot 10^{+288}:\\ \;\;\;\;x - \left(y - z\right) \cdot \frac{x - t}{a - z}\\ \mathbf{elif}\;x - \left(y - z\right) \cdot \frac{x - t}{a - z} \leq -1 \cdot 10^{-306}:\\ \;\;\;\;\frac{t}{\frac{a - z}{y - z}} + x \cdot \left(1 - \frac{y - z}{a - z}\right)\\ \mathbf{elif}\;x - \left(y - z\right) \cdot \frac{x - t}{a - z} \leq 0:\\ \;\;\;\;t - \frac{a - y}{\frac{z}{x}}\\ \mathbf{elif}\;x - \left(y - z\right) \cdot \frac{x - t}{a - z} \leq 4 \cdot 10^{+242}:\\ \;\;\;\;\frac{t}{\frac{a - z}{y - z}} + x \cdot \left(1 - \frac{y - z}{a - z}\right)\\ \mathbf{else}:\\ \;\;\;\;x - \left(y - z\right) \cdot \frac{x - t}{a - z}\\ \end{array} \]

Alternatives

Alternative 1
Accuracy	94.8%
Cost	4944

\[\begin{array}{l} t_1 := \frac{t}{\frac{a - z}{y - z}} + x \cdot \left(1 - \frac{y - z}{a - z}\right)\\ t_2 := x - \left(y - z\right) \cdot \frac{x - t}{a - z}\\ \mathbf{if}\;t_2 \leq -5 \cdot 10^{+288}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t_2 \leq -1 \cdot 10^{-306}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t_2 \leq 0:\\ \;\;\;\;t - \frac{a - y}{\frac{z}{x}}\\ \mathbf{elif}\;t_2 \leq 4 \cdot 10^{+242}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 2
Accuracy	96.1%
Cost	9804

\[\begin{array}{l} t_1 := \frac{y - z}{a - z}\\ t_2 := \mathsf{fma}\left(t - x, t_1, x\right)\\ t_3 := x - \left(y - z\right) \cdot \frac{x - t}{a - z}\\ \mathbf{if}\;t_3 \leq -1 \cdot 10^{-306}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t_3 \leq 0:\\ \;\;\;\;t - \frac{a - y}{\frac{z}{x}}\\ \mathbf{elif}\;t_3 \leq 4 \cdot 10^{+242}:\\ \;\;\;\;\frac{t}{\frac{a - z}{y - z}} + x \cdot \left(1 - t_1\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 3
Accuracy	91.1%
Cost	2633

\[\begin{array}{l} t_1 := x - \left(y - z\right) \cdot \frac{x - t}{a - z}\\ \mathbf{if}\;t_1 \leq -1 \cdot 10^{-306} \lor \neg \left(t_1 \leq 10^{-239}\right):\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t - \frac{a - y}{\frac{z}{x}}\\ \end{array} \]

Alternative 4
Accuracy	43.0%
Cost	1372

\[\begin{array}{l} t_1 := \frac{y}{z} \cdot \left(x - t\right)\\ \mathbf{if}\;a \leq -7.6 \cdot 10^{+101}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -2.55 \cdot 10^{-80}:\\ \;\;\;\;\frac{y}{\frac{a}{t - x}}\\ \mathbf{elif}\;a \leq -1.9 \cdot 10^{-190}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -3.4 \cdot 10^{-250}:\\ \;\;\;\;t\\ \mathbf{elif}\;a \leq 9.5 \cdot 10^{-99}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 7 \cdot 10^{-81}:\\ \;\;\;\;t\\ \mathbf{elif}\;a \leq 0.0021:\\ \;\;\;\;\frac{y \cdot \left(t - x\right)}{a}\\ \mathbf{elif}\;a \leq 7.8 \cdot 10^{+83}:\\ \;\;\;\;t\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 5
Accuracy	53.7%
Cost	1368

\[\begin{array}{l} t_1 := y \cdot \frac{t - x}{a - z}\\ t_2 := t \cdot \frac{y - z}{a - z}\\ \mathbf{if}\;a \leq -2.2 \cdot 10^{+188}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -1.15 \cdot 10^{+51}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.12 \cdot 10^{-181}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -3.2 \cdot 10^{-277}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.4 \cdot 10^{-98}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.36 \cdot 10^{+84}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 6
Accuracy	60.3%
Cost	1368

\[\begin{array}{l} t_1 := t \cdot \frac{y - z}{a - z}\\ t_2 := x - \frac{t}{a} \cdot \left(z - y\right)\\ t_3 := y \cdot \frac{t - x}{a - z}\\ \mathbf{if}\;a \leq -2.2 \cdot 10^{+188}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -7.1 \cdot 10^{+50}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.8 \cdot 10^{-181}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -5.5 \cdot 10^{-278}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.2 \cdot 10^{-98}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq 5.6 \cdot 10^{+83}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 7
Accuracy	72.3%
Cost	1360

\[\begin{array}{l} \mathbf{if}\;a \leq -1.25 \cdot 10^{+124}:\\ \;\;\;\;x - \frac{t - x}{a} \cdot \left(z - y\right)\\ \mathbf{elif}\;a \leq -1.15 \cdot 10^{+51}:\\ \;\;\;\;t \cdot \frac{y - z}{a - z}\\ \mathbf{elif}\;a \leq -2.4 \cdot 10^{-25}:\\ \;\;\;\;y \cdot \frac{t - x}{a - z}\\ \mathbf{elif}\;a \leq 2.2 \cdot 10^{+43}:\\ \;\;\;\;t + \frac{\left(t - x\right) \cdot \left(a - y\right)}{z}\\ \mathbf{else}:\\ \;\;\;\;x + \left(y - z\right) \cdot \left(\left(t - x\right) \cdot \frac{1}{a}\right)\\ \end{array} \]

Alternative 8
Accuracy	46.2%
Cost	1304

\[\begin{array}{l} t_1 := \frac{t}{\frac{-z}{y - z}}\\ \mathbf{if}\;a \leq -8.2 \cdot 10^{+124}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -4 \cdot 10^{+29}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.4 \cdot 10^{-86}:\\ \;\;\;\;\frac{x \cdot \left(-y\right)}{a - z}\\ \mathbf{elif}\;a \leq -7 \cdot 10^{-279}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.05 \cdot 10^{-106}:\\ \;\;\;\;\frac{y}{z} \cdot \left(x - t\right)\\ \mathbf{elif}\;a \leq 1.25 \cdot 10^{+84}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 9
Accuracy	38.1%
Cost	1240

\[\begin{array}{l} t_1 := x \cdot \frac{y - a}{z}\\ \mathbf{if}\;a \leq -1.25 \cdot 10^{+124}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -4.8 \cdot 10^{+28}:\\ \;\;\;\;t\\ \mathbf{elif}\;a \leq -0.029:\\ \;\;\;\;\frac{x \cdot \left(-y\right)}{a}\\ \mathbf{elif}\;a \leq -2.45 \cdot 10^{-129}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -2.7 \cdot 10^{-272}:\\ \;\;\;\;t\\ \mathbf{elif}\;a \leq 6.2 \cdot 10^{-111}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.2 \cdot 10^{+84}:\\ \;\;\;\;t\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 10
Accuracy	38.9%
Cost	1240

\[\begin{array}{l} \mathbf{if}\;a \leq -1.3 \cdot 10^{+102}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -1.4 \cdot 10^{-34}:\\ \;\;\;\;\frac{y}{\frac{a}{t - x}}\\ \mathbf{elif}\;a \leq -1.9 \cdot 10^{-133}:\\ \;\;\;\;\frac{y - a}{\frac{z}{x}}\\ \mathbf{elif}\;a \leq -3.7 \cdot 10^{-152}:\\ \;\;\;\;\frac{y}{\frac{a - z}{t}}\\ \mathbf{elif}\;a \leq -5.8 \cdot 10^{-276}:\\ \;\;\;\;t\\ \mathbf{elif}\;a \leq 4.8 \cdot 10^{-107}:\\ \;\;\;\;x \cdot \frac{y - a}{z}\\ \mathbf{elif}\;a \leq 5.6 \cdot 10^{+83}:\\ \;\;\;\;t\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 11
Accuracy	72.3%
Cost	1232

\[\begin{array}{l} t_1 := x - \frac{t - x}{a} \cdot \left(z - y\right)\\ \mathbf{if}\;a \leq -1.5 \cdot 10^{+124}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -9 \cdot 10^{+49}:\\ \;\;\;\;t \cdot \frac{y - z}{a - z}\\ \mathbf{elif}\;a \leq -1.45 \cdot 10^{-27}:\\ \;\;\;\;y \cdot \frac{t - x}{a - z}\\ \mathbf{elif}\;a \leq 2.2 \cdot 10^{+43}:\\ \;\;\;\;t + \frac{\left(t - x\right) \cdot \left(a - y\right)}{z}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

Alternative 12
Accuracy	36.9%
Cost	1112

\[\begin{array}{l} \mathbf{if}\;a \leq -2.5 \cdot 10^{+124}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -3.8 \cdot 10^{+27}:\\ \;\;\;\;t\\ \mathbf{elif}\;a \leq -0.048:\\ \;\;\;\;\frac{x \cdot \left(-y\right)}{a}\\ \mathbf{elif}\;a \leq -3.9 \cdot 10^{-128}:\\ \;\;\;\;\frac{x \cdot y}{z}\\ \mathbf{elif}\;a \leq -5 \cdot 10^{-272}:\\ \;\;\;\;t\\ \mathbf{elif}\;a \leq 7.8 \cdot 10^{-128}:\\ \;\;\;\;x \cdot \frac{y}{z}\\ \mathbf{elif}\;a \leq 5.5 \cdot 10^{+83}:\\ \;\;\;\;t\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 13
Accuracy	37.9%
Cost	1108

\[\begin{array}{l} \mathbf{if}\;a \leq -4.6 \cdot 10^{+99}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -4 \cdot 10^{+54}:\\ \;\;\;\;\frac{t}{\frac{a}{y - z}}\\ \mathbf{elif}\;a \leq -2.3 \cdot 10^{-86}:\\ \;\;\;\;\frac{-y}{\frac{a}{x}}\\ \mathbf{elif}\;a \leq -8 \cdot 10^{-274}:\\ \;\;\;\;t\\ \mathbf{elif}\;a \leq 2.5 \cdot 10^{-103}:\\ \;\;\;\;x \cdot \frac{y - a}{z}\\ \mathbf{elif}\;a \leq 8.5 \cdot 10^{+83}:\\ \;\;\;\;t\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 14
Accuracy	55.0%
Cost	1104

\[\begin{array}{l} t_1 := t \cdot \frac{y - z}{a - z}\\ \mathbf{if}\;a \leq -2.2 \cdot 10^{+188}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -2.9 \cdot 10^{+30}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -2.65 \cdot 10^{-86}:\\ \;\;\;\;\frac{x \cdot \left(-y\right)}{a - z}\\ \mathbf{elif}\;a \leq 1.36 \cdot 10^{+84}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 15
Accuracy	47.7%
Cost	1040

\[\begin{array}{l} t_1 := \frac{t}{\frac{-z}{y - z}}\\ \mathbf{if}\;a \leq -4.8 \cdot 10^{+124}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -1.45 \cdot 10^{-279}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 6.2 \cdot 10^{-113}:\\ \;\;\;\;\frac{y}{z} \cdot \left(x - t\right)\\ \mathbf{elif}\;a \leq 5.5 \cdot 10^{+83}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 16
Accuracy	65.5%
Cost	972

\[\begin{array}{l} t_1 := t \cdot \frac{y - z}{a - z}\\ \mathbf{if}\;z \leq -6.7 \cdot 10^{-12}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 1.6 \cdot 10^{-123}:\\ \;\;\;\;x + \frac{y}{\frac{a}{t - x}}\\ \mathbf{elif}\;z \leq 1.82 \cdot 10^{+31}:\\ \;\;\;\;y \cdot \frac{t - x}{a - z}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

Alternative 17
Accuracy	65.5%
Cost	972

\[\begin{array}{l} \mathbf{if}\;z \leq -4.2 \cdot 10^{-12}:\\ \;\;\;\;t \cdot \frac{y - z}{a - z}\\ \mathbf{elif}\;z \leq 1.6 \cdot 10^{-123}:\\ \;\;\;\;x + \frac{y}{\frac{a}{t - x}}\\ \mathbf{elif}\;z \leq 1.55 \cdot 10^{+30}:\\ \;\;\;\;y \cdot \frac{t - x}{a - z}\\ \mathbf{else}:\\ \;\;\;\;\frac{t}{\frac{a - z}{y - z}}\\ \end{array} \]

Alternative 18
Accuracy	66.6%
Cost	972

\[\begin{array}{l} \mathbf{if}\;z \leq -6.7 \cdot 10^{-12}:\\ \;\;\;\;t \cdot \frac{y - z}{a - z}\\ \mathbf{elif}\;z \leq 2.3 \cdot 10^{-123}:\\ \;\;\;\;x + \frac{y}{\frac{a}{t - x}}\\ \mathbf{elif}\;z \leq 1.1 \cdot 10^{+41}:\\ \;\;\;\;y \cdot \frac{t - x}{a - z}\\ \mathbf{else}:\\ \;\;\;\;t - \frac{a - y}{\frac{z}{x}}\\ \end{array} \]

Alternative 19
Accuracy	67.5%
Cost	972

\[\begin{array}{l} \mathbf{if}\;z \leq -2.9 \cdot 10^{-12}:\\ \;\;\;\;t \cdot \frac{y - z}{a - z}\\ \mathbf{elif}\;z \leq 2.3 \cdot 10^{-123}:\\ \;\;\;\;x - \frac{t - x}{a} \cdot \left(z - y\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{+39}:\\ \;\;\;\;y \cdot \frac{t - x}{a - z}\\ \mathbf{else}:\\ \;\;\;\;t - \frac{a - y}{\frac{z}{x}}\\ \end{array} \]

Alternative 20
Accuracy	38.9%
Cost	844

\[\begin{array}{l} \mathbf{if}\;a \leq -5.6 \cdot 10^{+101}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -6.5 \cdot 10^{-40}:\\ \;\;\;\;\frac{y}{\frac{a}{t - x}}\\ \mathbf{elif}\;a \leq 1.6 \cdot 10^{-108}:\\ \;\;\;\;x \cdot \frac{y - a}{z}\\ \mathbf{elif}\;a \leq 5.8 \cdot 10^{+83}:\\ \;\;\;\;t\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 21
Accuracy	37.9%
Cost	716

\[\begin{array}{l} \mathbf{if}\;a \leq -1.25 \cdot 10^{+124}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -1.6 \cdot 10^{-279}:\\ \;\;\;\;t\\ \mathbf{elif}\;a \leq 8 \cdot 10^{-129}:\\ \;\;\;\;y \cdot \frac{x}{z}\\ \mathbf{elif}\;a \leq 5.6 \cdot 10^{+83}:\\ \;\;\;\;t\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 22
Accuracy	38.1%
Cost	716

\[\begin{array}{l} \mathbf{if}\;a \leq -1.25 \cdot 10^{+124}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -1.35 \cdot 10^{-275}:\\ \;\;\;\;t\\ \mathbf{elif}\;a \leq 4.5 \cdot 10^{-125}:\\ \;\;\;\;x \cdot \frac{y}{z}\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{+84}:\\ \;\;\;\;t\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 23
Accuracy	39.2%
Cost	328

\[\begin{array}{l} \mathbf{if}\;a \leq -2.3 \cdot 10^{+124}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq 5.8 \cdot 10^{+83}:\\ \;\;\;\;t\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 24
Accuracy	25.7%
Cost	64

\[t \]

Reproduce

herbie shell --seed 2023165 
(FPCore (x y z t a)
  :name "Numeric.Signal:interpolate   from hsignal-0.2.7.1"
  :precision binary64
  (+ x (* (- y z) (/ (- t x) (- a z)))))