Diagrams.Solve.Tridiagonal:solveCyclicTriDiagonal from diagrams-solve-0.1, A

Average Accuracy: 90.3% → 98.2%

Time: 3.3s

Precision: binary64

Cost: 1360

\[ \begin{array}{c}[x, y] = \mathsf{sort}([x, y])\\ \end{array} \]

Math

\[\frac{x \cdot y}{z} \]

↓

\[\begin{array}{l} t_0 := x \cdot \frac{y}{z}\\ t_1 := \frac{x \cdot y}{z}\\ \mathbf{if}\;x \cdot y \leq -5 \cdot 10^{+300}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;x \cdot y \leq -2 \cdot 10^{-80}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \cdot y \leq 5 \cdot 10^{-142}:\\ \;\;\;\;\frac{y}{\frac{z}{x}}\\ \mathbf{elif}\;x \cdot y \leq 4 \cdot 10^{+162}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]

FPCore

(FPCore (x y z) :precision binary64 (/ (* x y) z))

↓

(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (* x (/ y z))) (t_1 (/ (* x y) z)))
   (if (<= (* x y) -5e+300)
     t_0
     (if (<= (* x y) -2e-80)
       t_1
       (if (<= (* x y) 5e-142)
         (/ y (/ z x))
         (if (<= (* x y) 4e+162) t_1 t_0))))))

C

double code(double x, double y, double z) {
	return (x * y) / z;
}

↓

double code(double x, double y, double z) {
	double t_0 = x * (y / z);
	double t_1 = (x * y) / z;
	double tmp;
	if ((x * y) <= -5e+300) {
		tmp = t_0;
	} else if ((x * y) <= -2e-80) {
		tmp = t_1;
	} else if ((x * y) <= 5e-142) {
		tmp = y / (z / x);
	} else if ((x * y) <= 4e+162) {
		tmp = t_1;
	} else {
		tmp = t_0;
	}
	return tmp;
}

Fortran

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

↓

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: t_0
    real(8) :: t_1
    real(8) :: tmp
    t_0 = x * (y / z)
    t_1 = (x * y) / z
    if ((x * y) <= (-5d+300)) then
        tmp = t_0
    else if ((x * y) <= (-2d-80)) then
        tmp = t_1
    else if ((x * y) <= 5d-142) then
        tmp = y / (z / x)
    else if ((x * y) <= 4d+162) then
        tmp = t_1
    else
        tmp = t_0
    end if
    code = tmp
end function

Java

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

↓

public static double code(double x, double y, double z) {
	double t_0 = x * (y / z);
	double t_1 = (x * y) / z;
	double tmp;
	if ((x * y) <= -5e+300) {
		tmp = t_0;
	} else if ((x * y) <= -2e-80) {
		tmp = t_1;
	} else if ((x * y) <= 5e-142) {
		tmp = y / (z / x);
	} else if ((x * y) <= 4e+162) {
		tmp = t_1;
	} else {
		tmp = t_0;
	}
	return tmp;
}

Python

def code(x, y, z):
	return (x * y) / z

↓

def code(x, y, z):
	t_0 = x * (y / z)
	t_1 = (x * y) / z
	tmp = 0
	if (x * y) <= -5e+300:
		tmp = t_0
	elif (x * y) <= -2e-80:
		tmp = t_1
	elif (x * y) <= 5e-142:
		tmp = y / (z / x)
	elif (x * y) <= 4e+162:
		tmp = t_1
	else:
		tmp = t_0
	return tmp

Julia

function code(x, y, z)
	return Float64(Float64(x * y) / z)
end

↓

function code(x, y, z)
	t_0 = Float64(x * Float64(y / z))
	t_1 = Float64(Float64(x * y) / z)
	tmp = 0.0
	if (Float64(x * y) <= -5e+300)
		tmp = t_0;
	elseif (Float64(x * y) <= -2e-80)
		tmp = t_1;
	elseif (Float64(x * y) <= 5e-142)
		tmp = Float64(y / Float64(z / x));
	elseif (Float64(x * y) <= 4e+162)
		tmp = t_1;
	else
		tmp = t_0;
	end
	return tmp
end

MATLAB

function tmp = code(x, y, z)
	tmp = (x * y) / z;
end

↓

function tmp_2 = code(x, y, z)
	t_0 = x * (y / z);
	t_1 = (x * y) / z;
	tmp = 0.0;
	if ((x * y) <= -5e+300)
		tmp = t_0;
	elseif ((x * y) <= -2e-80)
		tmp = t_1;
	elseif ((x * y) <= 5e-142)
		tmp = y / (z / x);
	elseif ((x * y) <= 4e+162)
		tmp = t_1;
	else
		tmp = t_0;
	end
	tmp_2 = tmp;
end

Wolfram

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

↓

code[x_, y_, z_] := Block[{t$95$0 = N[(x * N[(y / z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(x * y), $MachinePrecision] / z), $MachinePrecision]}, If[LessEqual[N[(x * y), $MachinePrecision], -5e+300], t$95$0, If[LessEqual[N[(x * y), $MachinePrecision], -2e-80], t$95$1, If[LessEqual[N[(x * y), $MachinePrecision], 5e-142], N[(y / N[(z / x), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(x * y), $MachinePrecision], 4e+162], t$95$1, t$95$0]]]]]]

Target

Original	90.3%
Target	90.3%
Herbie	98.2%

\[\begin{array}{l} \mathbf{if}\;z < -4.262230790519429 \cdot 10^{-138}:\\ \;\;\;\;\frac{x \cdot y}{z}\\ \mathbf{elif}\;z < 1.7042130660650472 \cdot 10^{-164}:\\ \;\;\;\;\frac{x}{\frac{z}{y}}\\ \mathbf{else}:\\ \;\;\;\;\frac{x}{z} \cdot y\\ \end{array} \]

Derivation

1. Split input into 3 regimes

2. if (*.f64 x y) < -5.00000000000000026e300 or 3.9999999999999998e162 < (*.f64 x y)

   1. Initial program 52.4%

      \[\frac{x \cdot y}{z} \]

   2. Simplified 97.1%

      \[\leadsto \color{blue}{x \cdot \frac{y}{z}} \]
      Proof

      [Start] 52.4	\[ \frac{x \cdot y}{z} \]
      associate-*r/ [<=] 97.1	\[ \color{blue}{x \cdot \frac{y}{z}} \]

   if -5.00000000000000026e300 < (*.f64 x y) < -1.99999999999999992e-80 or 5.0000000000000002e-142 < (*.f64 x y) < 3.9999999999999998e162

   1. Initial program 99.6%

      \[\frac{x \cdot y}{z} \]

   if -1.99999999999999992e-80 < (*.f64 x y) < 5.0000000000000002e-142

   1. Initial program 88.9%

      \[\frac{x \cdot y}{z} \]

   2. Simplified 97.0%

      \[\leadsto \color{blue}{\frac{x}{z} \cdot y} \]
      Proof

      [Start] 88.9	\[ \frac{x \cdot y}{z} \]
      associate-*l/ [<=] 97.0	\[ \color{blue}{\frac{x}{z} \cdot y} \]

   3. Applied egg-rr 96.9%

      \[\leadsto \color{blue}{\frac{y}{\frac{z}{x}}} \]
3. Recombined 3 regimes into one program.

4. Final simplification 98.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \cdot y \leq -5 \cdot 10^{+300}:\\ \;\;\;\;x \cdot \frac{y}{z}\\ \mathbf{elif}\;x \cdot y \leq -2 \cdot 10^{-80}:\\ \;\;\;\;\frac{x \cdot y}{z}\\ \mathbf{elif}\;x \cdot y \leq 5 \cdot 10^{-142}:\\ \;\;\;\;\frac{y}{\frac{z}{x}}\\ \mathbf{elif}\;x \cdot y \leq 4 \cdot 10^{+162}:\\ \;\;\;\;\frac{x \cdot y}{z}\\ \mathbf{else}:\\ \;\;\;\;x \cdot \frac{y}{z}\\ \end{array} \]

Alternatives

Alternative 1
Accuracy	90.3%
Cost	585

\[\begin{array}{l} \mathbf{if}\;z \leq -5.5 \cdot 10^{-100} \lor \neg \left(z \leq 3.25 \cdot 10^{-254}\right):\\ \;\;\;\;y \cdot \frac{x}{z}\\ \mathbf{else}:\\ \;\;\;\;x \cdot \frac{y}{z}\\ \end{array} \]

Alternative 2
Accuracy	90.4%
Cost	585

\[\begin{array}{l} \mathbf{if}\;z \leq -3.4 \cdot 10^{-97} \lor \neg \left(z \leq 2.5 \cdot 10^{-242}\right):\\ \;\;\;\;y \cdot \frac{x}{z}\\ \mathbf{else}:\\ \;\;\;\;\frac{x}{\frac{z}{y}}\\ \end{array} \]

Alternative 3
Accuracy	90.4%
Cost	584

\[\begin{array}{l} \mathbf{if}\;z \leq -2.1 \cdot 10^{-99}:\\ \;\;\;\;y \cdot \frac{x}{z}\\ \mathbf{elif}\;z \leq 6.8 \cdot 10^{-259}:\\ \;\;\;\;\frac{x}{\frac{z}{y}}\\ \mathbf{else}:\\ \;\;\;\;\frac{y}{\frac{z}{x}}\\ \end{array} \]

Alternative 4
Accuracy	90.4%
Cost	320

\[x \cdot \frac{y}{z} \]

Reproduce

herbie shell --seed 2023129 
(FPCore (x y z)
  :name "Diagrams.Solve.Tridiagonal:solveCyclicTriDiagonal from diagrams-solve-0.1, A"
  :precision binary64

  :herbie-target
  (if (< z -4.262230790519429e-138) (/ (* x y) z) (if (< z 1.7042130660650472e-164) (/ x (/ z y)) (* (/ x z) y)))

  (/ (* x y) z))