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

Average Error: 5.9 → 0.6

Time: 2.4s

Precision: binary64

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

Math

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

↓

\[\begin{array}{l} t_0 := \frac{y}{\frac{z}{x}}\\ t_1 := \frac{x \cdot y}{z}\\ \mathbf{if}\;x \cdot y \leq -1 \cdot 10^{+131}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;x \cdot y \leq -2 \cdot 10^{-242}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \cdot y \leq 10^{-200}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;x \cdot y \leq 2 \cdot 10^{+225}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;y \cdot \frac{x}{z}\\ \end{array} \]

FPCore

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

↓

(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (/ y (/ z x))) (t_1 (/ (* x y) z)))
   (if (<= (* x y) -1e+131)
     t_0
     (if (<= (* x y) -2e-242)
       t_1
       (if (<= (* x y) 1e-200)
         t_0
         (if (<= (* x y) 2e+225) t_1 (* y (/ x z))))))))

C

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

↓

double code(double x, double y, double z) {
	double t_0 = y / (z / x);
	double t_1 = (x * y) / z;
	double tmp;
	if ((x * y) <= -1e+131) {
		tmp = t_0;
	} else if ((x * y) <= -2e-242) {
		tmp = t_1;
	} else if ((x * y) <= 1e-200) {
		tmp = t_0;
	} else if ((x * y) <= 2e+225) {
		tmp = t_1;
	} else {
		tmp = y * (x / z);
	}
	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 = y / (z / x)
    t_1 = (x * y) / z
    if ((x * y) <= (-1d+131)) then
        tmp = t_0
    else if ((x * y) <= (-2d-242)) then
        tmp = t_1
    else if ((x * y) <= 1d-200) then
        tmp = t_0
    else if ((x * y) <= 2d+225) then
        tmp = t_1
    else
        tmp = y * (x / z)
    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 = y / (z / x);
	double t_1 = (x * y) / z;
	double tmp;
	if ((x * y) <= -1e+131) {
		tmp = t_0;
	} else if ((x * y) <= -2e-242) {
		tmp = t_1;
	} else if ((x * y) <= 1e-200) {
		tmp = t_0;
	} else if ((x * y) <= 2e+225) {
		tmp = t_1;
	} else {
		tmp = y * (x / z);
	}
	return tmp;
}

Python

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

↓

def code(x, y, z):
	t_0 = y / (z / x)
	t_1 = (x * y) / z
	tmp = 0
	if (x * y) <= -1e+131:
		tmp = t_0
	elif (x * y) <= -2e-242:
		tmp = t_1
	elif (x * y) <= 1e-200:
		tmp = t_0
	elif (x * y) <= 2e+225:
		tmp = t_1
	else:
		tmp = y * (x / z)
	return tmp

Julia

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

↓

function code(x, y, z)
	t_0 = Float64(y / Float64(z / x))
	t_1 = Float64(Float64(x * y) / z)
	tmp = 0.0
	if (Float64(x * y) <= -1e+131)
		tmp = t_0;
	elseif (Float64(x * y) <= -2e-242)
		tmp = t_1;
	elseif (Float64(x * y) <= 1e-200)
		tmp = t_0;
	elseif (Float64(x * y) <= 2e+225)
		tmp = t_1;
	else
		tmp = Float64(y * Float64(x / z));
	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 = y / (z / x);
	t_1 = (x * y) / z;
	tmp = 0.0;
	if ((x * y) <= -1e+131)
		tmp = t_0;
	elseif ((x * y) <= -2e-242)
		tmp = t_1;
	elseif ((x * y) <= 1e-200)
		tmp = t_0;
	elseif ((x * y) <= 2e+225)
		tmp = t_1;
	else
		tmp = y * (x / z);
	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[(y / N[(z / x), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(x * y), $MachinePrecision] / z), $MachinePrecision]}, If[LessEqual[N[(x * y), $MachinePrecision], -1e+131], t$95$0, If[LessEqual[N[(x * y), $MachinePrecision], -2e-242], t$95$1, If[LessEqual[N[(x * y), $MachinePrecision], 1e-200], t$95$0, If[LessEqual[N[(x * y), $MachinePrecision], 2e+225], t$95$1, N[(y * N[(x / z), $MachinePrecision]), $MachinePrecision]]]]]]]

Target

Original	5.9
Target	6.1
Herbie	0.6

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

Derivation

1. Split input into 3 regimes

2. if (*.f64 x y) < -9.9999999999999991e130 or -2e-242 < (*.f64 x y) < 9.9999999999999998e-201

   1. Initial program 12.4

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

   2. Simplified 1.2

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

   if -9.9999999999999991e130 < (*.f64 x y) < -2e-242 or 9.9999999999999998e-201 < (*.f64 x y) < 1.99999999999999986e225

   1. Initial program 0.2

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

   if 1.99999999999999986e225 < (*.f64 x y)

   1. Initial program 30.2

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

   2. Simplified 1.4

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

   3. Applied egg-rr 1.1

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

4. Final simplification 0.6

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \cdot y \leq -1 \cdot 10^{+131}:\\ \;\;\;\;\frac{y}{\frac{z}{x}}\\ \mathbf{elif}\;x \cdot y \leq -2 \cdot 10^{-242}:\\ \;\;\;\;\frac{x \cdot y}{z}\\ \mathbf{elif}\;x \cdot y \leq 10^{-200}:\\ \;\;\;\;\frac{y}{\frac{z}{x}}\\ \mathbf{elif}\;x \cdot y \leq 2 \cdot 10^{+225}:\\ \;\;\;\;\frac{x \cdot y}{z}\\ \mathbf{else}:\\ \;\;\;\;y \cdot \frac{x}{z}\\ \end{array} \]

Reproduce

herbie shell --seed 2022203 
(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))