Numeric.Integration.TanhSinh:everywhere from integration-0.2.1

Average Accuracy: 91.9% → 99.9%

Time: 8.0s

Precision: binary64

Cost: 713

Math

\[x \cdot \left(1 + y \cdot y\right) \]

↓

\[\begin{array}{l} \mathbf{if}\;y \leq -2 \cdot 10^{+124} \lor \neg \left(y \leq 2.35 \cdot 10^{+145}\right):\\ \;\;\;\;y \cdot \left(y \cdot x\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(1 + y \cdot y\right)\\ \end{array} \]

FPCore

(FPCore (x y) :precision binary64 (* x (+ 1.0 (* y y))))

↓

(FPCore (x y)
 :precision binary64
 (if (or (<= y -2e+124) (not (<= y 2.35e+145)))
   (* y (* y x))
   (* x (+ 1.0 (* y y)))))

C

double code(double x, double y) {
	return x * (1.0 + (y * y));
}

↓

double code(double x, double y) {
	double tmp;
	if ((y <= -2e+124) || !(y <= 2.35e+145)) {
		tmp = y * (y * x);
	} else {
		tmp = x * (1.0 + (y * y));
	}
	return tmp;
}

Fortran

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = x * (1.0d0 + (y * y))
end function

↓

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8) :: tmp
    if ((y <= (-2d+124)) .or. (.not. (y <= 2.35d+145))) then
        tmp = y * (y * x)
    else
        tmp = x * (1.0d0 + (y * y))
    end if
    code = tmp
end function

Java

public static double code(double x, double y) {
	return x * (1.0 + (y * y));
}

↓

public static double code(double x, double y) {
	double tmp;
	if ((y <= -2e+124) || !(y <= 2.35e+145)) {
		tmp = y * (y * x);
	} else {
		tmp = x * (1.0 + (y * y));
	}
	return tmp;
}

Python

def code(x, y):
	return x * (1.0 + (y * y))

↓

def code(x, y):
	tmp = 0
	if (y <= -2e+124) or not (y <= 2.35e+145):
		tmp = y * (y * x)
	else:
		tmp = x * (1.0 + (y * y))
	return tmp

Julia

function code(x, y)
	return Float64(x * Float64(1.0 + Float64(y * y)))
end

↓

function code(x, y)
	tmp = 0.0
	if ((y <= -2e+124) || !(y <= 2.35e+145))
		tmp = Float64(y * Float64(y * x));
	else
		tmp = Float64(x * Float64(1.0 + Float64(y * y)));
	end
	return tmp
end

MATLAB

function tmp = code(x, y)
	tmp = x * (1.0 + (y * y));
end

↓

function tmp_2 = code(x, y)
	tmp = 0.0;
	if ((y <= -2e+124) || ~((y <= 2.35e+145)))
		tmp = y * (y * x);
	else
		tmp = x * (1.0 + (y * y));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_] := N[(x * N[(1.0 + N[(y * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[x_, y_] := If[Or[LessEqual[y, -2e+124], N[Not[LessEqual[y, 2.35e+145]], $MachinePrecision]], N[(y * N[(y * x), $MachinePrecision]), $MachinePrecision], N[(x * N[(1.0 + N[(y * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Target

Original	91.9%
Target	99.9%
Herbie	99.9%

\[x + \left(x \cdot y\right) \cdot y \]

Derivation

1. Split input into 2 regimes

2. if y < -1.9999999999999999e124 or 2.3500000000000001e145 < y

   1. Initial program 22.4%

      \[x \cdot \left(1 + y \cdot y\right) \]

   2. Taylor expanded in y around inf 22.4%

      \[\leadsto \color{blue}{{y}^{2} \cdot x} \]

   3. Simplified 99.6%

      \[\leadsto \color{blue}{y \cdot \left(y \cdot x\right)} \]
      Proof

      [Start] 22.4	\[ {y}^{2} \cdot x \]
      unpow2 [=>] 22.4	\[ \color{blue}{\left(y \cdot y\right)} \cdot x \]
      associate-*r* [<=] 99.6	\[ \color{blue}{y \cdot \left(y \cdot x\right)} \]

   if -1.9999999999999999e124 < y < 2.3500000000000001e145

   1. Initial program 99.9%

      \[x \cdot \left(1 + y \cdot y\right) \]
3. Recombined 2 regimes into one program.

4. Final simplification 99.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -2 \cdot 10^{+124} \lor \neg \left(y \leq 2.35 \cdot 10^{+145}\right):\\ \;\;\;\;y \cdot \left(y \cdot x\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(1 + y \cdot y\right)\\ \end{array} \]

Alternatives

Alternative 1
Accuracy	98.4%
Cost	580

\[\begin{array}{l} \mathbf{if}\;y \cdot y \leq 1:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(y \cdot x\right)\\ \end{array} \]

Alternative 2
Accuracy	99.9%
Cost	448

\[x + y \cdot \left(y \cdot x\right) \]

Alternative 3
Accuracy	67.5%
Cost	64

\[x \]

Reproduce

herbie shell --seed 2023151 
(FPCore (x y)
  :name "Numeric.Integration.TanhSinh:everywhere from integration-0.2.1"
  :precision binary64

  :herbie-target
  (+ x (* (* x y) y))

  (* x (+ 1.0 (* y y))))