Example from Robby

Percentage Accurate: 99.8% → 99.8%

Time: 17.7s

Alternatives: 17

Speedup: 1.1×

Specification

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\\ \left|\left(ew \cdot \sin t\right) \cdot \cos t\_1 + \left(eh \cdot \cos t\right) \cdot \sin t\_1\right| \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (atan (/ (/ eh ew) (tan t)))))
   (fabs (+ (* (* ew (sin t)) (cos t_1)) (* (* eh (cos t)) (sin t_1))))))

C

double code(double eh, double ew, double t) {
	double t_1 = atan(((eh / ew) / tan(t)));
	return fabs((((ew * sin(t)) * cos(t_1)) + ((eh * cos(t)) * sin(t_1))));
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(eh, ew, t)
use fmin_fmax_functions
    real(8), intent (in) :: eh
    real(8), intent (in) :: ew
    real(8), intent (in) :: t
    real(8) :: t_1
    t_1 = atan(((eh / ew) / tan(t)))
    code = abs((((ew * sin(t)) * cos(t_1)) + ((eh * cos(t)) * sin(t_1))))
end function

Java

public static double code(double eh, double ew, double t) {
	double t_1 = Math.atan(((eh / ew) / Math.tan(t)));
	return Math.abs((((ew * Math.sin(t)) * Math.cos(t_1)) + ((eh * Math.cos(t)) * Math.sin(t_1))));
}

Python

def code(eh, ew, t):
	t_1 = math.atan(((eh / ew) / math.tan(t)))
	return math.fabs((((ew * math.sin(t)) * math.cos(t_1)) + ((eh * math.cos(t)) * math.sin(t_1))))

Julia

function code(eh, ew, t)
	t_1 = atan(Float64(Float64(eh / ew) / tan(t)))
	return abs(Float64(Float64(Float64(ew * sin(t)) * cos(t_1)) + Float64(Float64(eh * cos(t)) * sin(t_1))))
end

MATLAB

function tmp = code(eh, ew, t)
	t_1 = atan(((eh / ew) / tan(t)));
	tmp = abs((((ew * sin(t)) * cos(t_1)) + ((eh * cos(t)) * sin(t_1))));
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[ArcTan[N[(N[(eh / ew), $MachinePrecision] / N[Tan[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[Abs[N[(N[(N[(ew * N[Sin[t], $MachinePrecision]), $MachinePrecision] * N[Cos[t$95$1], $MachinePrecision]), $MachinePrecision] + N[(N[(eh * N[Cos[t], $MachinePrecision]), $MachinePrecision] * N[Sin[t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]

Initial Program: 99.8% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\\ \left|\left(ew \cdot \sin t\right) \cdot \cos t\_1 + \left(eh \cdot \cos t\right) \cdot \sin t\_1\right| \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (atan (/ (/ eh ew) (tan t)))))
   (fabs (+ (* (* ew (sin t)) (cos t_1)) (* (* eh (cos t)) (sin t_1))))))

C

double code(double eh, double ew, double t) {
	double t_1 = atan(((eh / ew) / tan(t)));
	return fabs((((ew * sin(t)) * cos(t_1)) + ((eh * cos(t)) * sin(t_1))));
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(eh, ew, t)
use fmin_fmax_functions
    real(8), intent (in) :: eh
    real(8), intent (in) :: ew
    real(8), intent (in) :: t
    real(8) :: t_1
    t_1 = atan(((eh / ew) / tan(t)))
    code = abs((((ew * sin(t)) * cos(t_1)) + ((eh * cos(t)) * sin(t_1))))
end function

Java

public static double code(double eh, double ew, double t) {
	double t_1 = Math.atan(((eh / ew) / Math.tan(t)));
	return Math.abs((((ew * Math.sin(t)) * Math.cos(t_1)) + ((eh * Math.cos(t)) * Math.sin(t_1))));
}

Python

def code(eh, ew, t):
	t_1 = math.atan(((eh / ew) / math.tan(t)))
	return math.fabs((((ew * math.sin(t)) * math.cos(t_1)) + ((eh * math.cos(t)) * math.sin(t_1))))

Julia

function code(eh, ew, t)
	t_1 = atan(Float64(Float64(eh / ew) / tan(t)))
	return abs(Float64(Float64(Float64(ew * sin(t)) * cos(t_1)) + Float64(Float64(eh * cos(t)) * sin(t_1))))
end

MATLAB

function tmp = code(eh, ew, t)
	t_1 = atan(((eh / ew) / tan(t)));
	tmp = abs((((ew * sin(t)) * cos(t_1)) + ((eh * cos(t)) * sin(t_1))));
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[ArcTan[N[(N[(eh / ew), $MachinePrecision] / N[Tan[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[Abs[N[(N[(N[(ew * N[Sin[t], $MachinePrecision]), $MachinePrecision] * N[Cos[t$95$1], $MachinePrecision]), $MachinePrecision] + N[(N[(eh * N[Cos[t], $MachinePrecision]), $MachinePrecision] * N[Sin[t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]

Alternative 1: 99.8% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh\right| \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (fabs
  (+
   (* (* ew (sin t)) (cos (atan (/ (/ eh ew) (tan t)))))
   (* (* (tanh (asinh (/ eh (* (tan t) ew)))) (cos t)) eh))))

C

double code(double eh, double ew, double t) {
	return fabs((((ew * sin(t)) * cos(atan(((eh / ew) / tan(t))))) + ((tanh(asinh((eh / (tan(t) * ew)))) * cos(t)) * eh)));
}

Python

def code(eh, ew, t):
	return math.fabs((((ew * math.sin(t)) * math.cos(math.atan(((eh / ew) / math.tan(t))))) + ((math.tanh(math.asinh((eh / (math.tan(t) * ew)))) * math.cos(t)) * eh)))

Julia

function code(eh, ew, t)
	return abs(Float64(Float64(Float64(ew * sin(t)) * cos(atan(Float64(Float64(eh / ew) / tan(t))))) + Float64(Float64(tanh(asinh(Float64(eh / Float64(tan(t) * ew)))) * cos(t)) * eh)))
end

MATLAB

function tmp = code(eh, ew, t)
	tmp = abs((((ew * sin(t)) * cos(atan(((eh / ew) / tan(t))))) + ((tanh(asinh((eh / (tan(t) * ew)))) * cos(t)) * eh)));
end

Wolfram

code[eh_, ew_, t_] := N[Abs[N[(N[(N[(ew * N[Sin[t], $MachinePrecision]), $MachinePrecision] * N[Cos[N[ArcTan[N[(N[(eh / ew), $MachinePrecision] / N[Tan[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(N[(N[Tanh[N[ArcSinh[N[(eh / N[(N[Tan[t], $MachinePrecision] * ew), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[Cos[t], $MachinePrecision]), $MachinePrecision] * eh), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]

Derivation

1. Initial program 99.8%

   \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
2. Step-by-step derivation

   1. lift-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

   2. lift-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   3. associate-*l* N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

   4. *-commutative N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   5. lower-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

3. Applied rewrites 99.8%

   \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]
4. Add Preprocessing

Alternative 2: 99.8% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\\ \left|\mathsf{fma}\left(\tanh t\_1 \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh t\_1}\right)\right| \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (asinh (/ eh (* (tan t) ew)))))
   (fabs (fma (* (tanh t_1) eh) (cos t) (/ (* (sin t) ew) (cosh t_1))))))

C

double code(double eh, double ew, double t) {
	double t_1 = asinh((eh / (tan(t) * ew)));
	return fabs(fma((tanh(t_1) * eh), cos(t), ((sin(t) * ew) / cosh(t_1))));
}

Julia

function code(eh, ew, t)
	t_1 = asinh(Float64(eh / Float64(tan(t) * ew)))
	return abs(fma(Float64(tanh(t_1) * eh), cos(t), Float64(Float64(sin(t) * ew) / cosh(t_1))))
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[ArcSinh[N[(eh / N[(N[Tan[t], $MachinePrecision] * ew), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[Abs[N[(N[(N[Tanh[t$95$1], $MachinePrecision] * eh), $MachinePrecision] * N[Cos[t], $MachinePrecision] + N[(N[(N[Sin[t], $MachinePrecision] * ew), $MachinePrecision] / N[Cosh[t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]

Derivation

1. Initial program 99.8%

   \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
2. Step-by-step derivation

   1. lift-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

   2. lift-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   3. associate-*l* N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

   4. *-commutative N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   5. lower-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

3. Applied rewrites 99.8%

   \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

5. Applied rewrites 99.8%

   \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]
6. Add Preprocessing

Alternative 3: 92.0% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \sin t \cdot ew\\ t_2 := \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\\ t_3 := \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\\ t_4 := \tanh t\_3\\ \mathbf{if}\;\left(ew \cdot \sin t\right) \cdot \cos t\_2 + \left(eh \cdot \cos t\right) \cdot \sin t\_2 \leq -5 \cdot 10^{-229}:\\ \;\;\;\;\left|\frac{1}{1} + \frac{t\_4 \cdot \frac{eh}{\tan t}}{ew}\right| \cdot \left|t\_1\right|\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(t\_4 \cdot eh, \cos t, \frac{t\_1}{\cosh t\_3}\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (* (sin t) ew))
        (t_2 (atan (/ (/ eh ew) (tan t))))
        (t_3 (asinh (/ eh (* (tan t) ew))))
        (t_4 (tanh t_3)))
   (if (<=
        (+ (* (* ew (sin t)) (cos t_2)) (* (* eh (cos t)) (sin t_2)))
        -5e-229)
     (* (fabs (+ (/ 1.0 1.0) (/ (* t_4 (/ eh (tan t))) ew))) (fabs t_1))
     (fma (* t_4 eh) (cos t) (/ t_1 (cosh t_3))))))

C

double code(double eh, double ew, double t) {
	double t_1 = sin(t) * ew;
	double t_2 = atan(((eh / ew) / tan(t)));
	double t_3 = asinh((eh / (tan(t) * ew)));
	double t_4 = tanh(t_3);
	double tmp;
	if ((((ew * sin(t)) * cos(t_2)) + ((eh * cos(t)) * sin(t_2))) <= -5e-229) {
		tmp = fabs(((1.0 / 1.0) + ((t_4 * (eh / tan(t))) / ew))) * fabs(t_1);
	} else {
		tmp = fma((t_4 * eh), cos(t), (t_1 / cosh(t_3)));
	}
	return tmp;
}

Julia

function code(eh, ew, t)
	t_1 = Float64(sin(t) * ew)
	t_2 = atan(Float64(Float64(eh / ew) / tan(t)))
	t_3 = asinh(Float64(eh / Float64(tan(t) * ew)))
	t_4 = tanh(t_3)
	tmp = 0.0
	if (Float64(Float64(Float64(ew * sin(t)) * cos(t_2)) + Float64(Float64(eh * cos(t)) * sin(t_2))) <= -5e-229)
		tmp = Float64(abs(Float64(Float64(1.0 / 1.0) + Float64(Float64(t_4 * Float64(eh / tan(t))) / ew))) * abs(t_1));
	else
		tmp = fma(Float64(t_4 * eh), cos(t), Float64(t_1 / cosh(t_3)));
	end
	return tmp
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[(N[Sin[t], $MachinePrecision] * ew), $MachinePrecision]}, Block[{t$95$2 = N[ArcTan[N[(N[(eh / ew), $MachinePrecision] / N[Tan[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[ArcSinh[N[(eh / N[(N[Tan[t], $MachinePrecision] * ew), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Tanh[t$95$3], $MachinePrecision]}, If[LessEqual[N[(N[(N[(ew * N[Sin[t], $MachinePrecision]), $MachinePrecision] * N[Cos[t$95$2], $MachinePrecision]), $MachinePrecision] + N[(N[(eh * N[Cos[t], $MachinePrecision]), $MachinePrecision] * N[Sin[t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], -5e-229], N[(N[Abs[N[(N[(1.0 / 1.0), $MachinePrecision] + N[(N[(t$95$4 * N[(eh / N[Tan[t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / ew), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Abs[t$95$1], $MachinePrecision]), $MachinePrecision], N[(N[(t$95$4 * eh), $MachinePrecision] * N[Cos[t], $MachinePrecision] + N[(t$95$1 / N[Cosh[t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 2 regimes

2. if (+.f64 (*.f64 (*.f64 ew (sin.f64 t)) (cos.f64 (atan.f64 (/.f64 (/.f64 eh ew) (tan.f64 t))))) (*.f64 (*.f64 eh (cos.f64 t)) (sin.f64 (atan.f64 (/.f64 (/.f64 eh ew) (tan.f64 t)))))) < -5.00000000000000016e-229

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   3. Applied rewrites 76.1%

      \[\leadsto \color{blue}{\left|\frac{1}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right|} \]

   4. Taylor expanded in eh around 0

      \[\leadsto \left|\frac{1}{\color{blue}{1}} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right| \]
   5. Step-by-step derivation

   6. Applied rewrites 74.7%

      \[\leadsto \left|\frac{1}{\color{blue}{1}} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right| \]
   7. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\frac{1}{1} + \color{blue}{\frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}}\right| \cdot \left|\sin t \cdot ew\right| \]

      2. lift-/.f64 N/A

         \[\leadsto \left|\frac{1}{1} + \color{blue}{\frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew}} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right| \]

      3. associate-*l/ N/A

         \[\leadsto \left|\frac{1}{1} + \color{blue}{\frac{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh\right) \cdot \frac{1}{\tan t}}{ew}}\right| \cdot \left|\sin t \cdot ew\right| \]

      4. lower-/.f64 N/A

         \[\leadsto \left|\frac{1}{1} + \color{blue}{\frac{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh\right) \cdot \frac{1}{\tan t}}{ew}}\right| \cdot \left|\sin t \cdot ew\right| \]

   8. Applied rewrites 70.7%

      \[\leadsto \left|\frac{1}{1} + \color{blue}{\frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \frac{eh}{\tan t}}{ew}}\right| \cdot \left|\sin t \cdot ew\right| \]

   if -5.00000000000000016e-229 < (+.f64 (*.f64 (*.f64 ew (sin.f64 t)) (cos.f64 (atan.f64 (/.f64 (/.f64 eh ew) (tan.f64 t))))) (*.f64 (*.f64 eh (cos.f64 t)) (sin.f64 (atan.f64 (/.f64 (/.f64 eh ew) (tan.f64 t))))))

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-fabs.f64 N/A

         \[\leadsto \color{blue}{\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right|} \]

      2. rem-sqrt-square-rev N/A

         \[\leadsto \color{blue}{\sqrt{\left(\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot \left(\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}} \]

      3. sqrt-prod N/A

         \[\leadsto \color{blue}{\sqrt{\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)} \cdot \sqrt{\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}} \]

      4. rem-square-sqrt 50.3

         \[\leadsto \color{blue}{\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)} \]

      5. lift-+.f64 N/A

         \[\leadsto \color{blue}{\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)} \]

      6. +-commutative N/A

         \[\leadsto \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)} \]

   3. Applied rewrites 50.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 4: 92.0% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{eh}{ew \cdot t}\\ t_2 := \frac{eh}{\tan t \cdot ew}\\ \mathbf{if}\;eh \leq 62000000000:\\ \;\;\;\;\left|\mathsf{fma}\left(\tanh \sinh^{-1} t\_1 \cdot \cos t, eh, \frac{\sin t \cdot ew}{\sqrt{\mathsf{fma}\left(t\_1, t\_1, 1\right)}}\right)\right|\\ \mathbf{else}:\\ \;\;\;\;\left|\left(\left({t\_2}^{-2} - -1\right) \cdot \tanh \sinh^{-1} t\_2\right) \cdot \left(\cos t \cdot eh\right)\right|\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (/ eh (* ew t))) (t_2 (/ eh (* (tan t) ew))))
   (if (<= eh 62000000000.0)
     (fabs
      (fma
       (* (tanh (asinh t_1)) (cos t))
       eh
       (/ (* (sin t) ew) (sqrt (fma t_1 t_1 1.0)))))
     (fabs
      (* (* (- (pow t_2 -2.0) -1.0) (tanh (asinh t_2))) (* (cos t) eh))))))

C

double code(double eh, double ew, double t) {
	double t_1 = eh / (ew * t);
	double t_2 = eh / (tan(t) * ew);
	double tmp;
	if (eh <= 62000000000.0) {
		tmp = fabs(fma((tanh(asinh(t_1)) * cos(t)), eh, ((sin(t) * ew) / sqrt(fma(t_1, t_1, 1.0)))));
	} else {
		tmp = fabs((((pow(t_2, -2.0) - -1.0) * tanh(asinh(t_2))) * (cos(t) * eh)));
	}
	return tmp;
}

Julia

function code(eh, ew, t)
	t_1 = Float64(eh / Float64(ew * t))
	t_2 = Float64(eh / Float64(tan(t) * ew))
	tmp = 0.0
	if (eh <= 62000000000.0)
		tmp = abs(fma(Float64(tanh(asinh(t_1)) * cos(t)), eh, Float64(Float64(sin(t) * ew) / sqrt(fma(t_1, t_1, 1.0)))));
	else
		tmp = abs(Float64(Float64(Float64((t_2 ^ -2.0) - -1.0) * tanh(asinh(t_2))) * Float64(cos(t) * eh)));
	end
	return tmp
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[(eh / N[(ew * t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(eh / N[(N[Tan[t], $MachinePrecision] * ew), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[eh, 62000000000.0], N[Abs[N[(N[(N[Tanh[N[ArcSinh[t$95$1], $MachinePrecision]], $MachinePrecision] * N[Cos[t], $MachinePrecision]), $MachinePrecision] * eh + N[(N[(N[Sin[t], $MachinePrecision] * ew), $MachinePrecision] / N[Sqrt[N[(t$95$1 * t$95$1 + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[Abs[N[(N[(N[(N[Power[t$95$2, -2.0], $MachinePrecision] - -1.0), $MachinePrecision] * N[Tanh[N[ArcSinh[t$95$2], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[Cos[t], $MachinePrecision] * eh), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]]]

Derivation

1. Split input into 2 regimes

2. if eh < 6.2e10

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]
   7. Step-by-step derivation

   8. Applied rewrites 89.8%

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]

   9. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
   10. Step-by-step derivation

   11. Applied rewrites 89.9%

       \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
   12. Step-by-step derivation

       1. lift-fma.f64 N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh\right) \cdot \cos t + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}}\right| \]

       2. lift-*.f64 N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh\right)} \cdot \cos t + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       3. associate-*l* N/A

          \[\leadsto \left|\color{blue}{\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \left(eh \cdot \cos t\right)} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       4. *-commutative N/A

          \[\leadsto \left|\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \color{blue}{\left(\cos t \cdot eh\right)} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       5. associate-*r* N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \cos t\right) \cdot eh} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       6. lower-fma.f64 N/A

          \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \cos t, eh, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)}\right| \]

   13. Applied rewrites 89.9%

       \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{ew \cdot t}\right) \cdot \cos t, eh, \frac{\sin t \cdot ew}{\sqrt{\mathsf{fma}\left(\frac{eh}{ew \cdot t}, \frac{eh}{ew \cdot t}, 1\right)}}\right)}\right| \]

   if 6.2e10 < eh

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 76.4%

      \[\leadsto \left|\color{blue}{\left(\frac{1}{{\left(\frac{eh}{\tan t \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right)}\right| \]
   6. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\color{blue}{\left(\frac{1}{{\left(\frac{eh}{\tan t \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(\frac{1}{{\left(\frac{eh}{\tan t \cdot ew}\right)}^{2}} + 1\right) \cdot \color{blue}{\left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right)}\right| \]

      3. *-commutative N/A

         \[\leadsto \left|\left(\frac{1}{{\left(\frac{eh}{\tan t \cdot ew}\right)}^{2}} + 1\right) \cdot \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \left(\cos t \cdot eh\right)\right)}\right| \]

      4. associate-*r* N/A

         \[\leadsto \left|\color{blue}{\left(\left(\frac{1}{{\left(\frac{eh}{\tan t \cdot ew}\right)}^{2}} + 1\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right) \cdot \left(\cos t \cdot eh\right)}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\color{blue}{\left(\left(\frac{1}{{\left(\frac{eh}{\tan t \cdot ew}\right)}^{2}} + 1\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right) \cdot \left(\cos t \cdot eh\right)}\right| \]

   7. Applied rewrites 79.3%

      \[\leadsto \left|\color{blue}{\left(\left({\left(\frac{eh}{\tan t \cdot ew}\right)}^{-2} - -1\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right) \cdot \left(\cos t \cdot eh\right)}\right| \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 5: 92.0% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{eh}{ew \cdot t}\\ t_2 := \frac{eh}{\tan t \cdot ew}\\ \mathbf{if}\;t \leq 2.4 \cdot 10^{+58}:\\ \;\;\;\;\left|\mathsf{fma}\left(\tanh \sinh^{-1} t\_1 \cdot \cos t, eh, \frac{\sin t \cdot ew}{\sqrt{\mathsf{fma}\left(t\_1, t\_1, 1\right)}}\right)\right|\\ \mathbf{else}:\\ \;\;\;\;\left|\sin t\right| \cdot \left(\left|ew\right| \cdot \left|\mathsf{fma}\left(\tanh \sinh^{-1} t\_2, t\_2, \frac{1}{1}\right)\right|\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (/ eh (* ew t))) (t_2 (/ eh (* (tan t) ew))))
   (if (<= t 2.4e+58)
     (fabs
      (fma
       (* (tanh (asinh t_1)) (cos t))
       eh
       (/ (* (sin t) ew) (sqrt (fma t_1 t_1 1.0)))))
     (*
      (fabs (sin t))
      (* (fabs ew) (fabs (fma (tanh (asinh t_2)) t_2 (/ 1.0 1.0))))))))

C

double code(double eh, double ew, double t) {
	double t_1 = eh / (ew * t);
	double t_2 = eh / (tan(t) * ew);
	double tmp;
	if (t <= 2.4e+58) {
		tmp = fabs(fma((tanh(asinh(t_1)) * cos(t)), eh, ((sin(t) * ew) / sqrt(fma(t_1, t_1, 1.0)))));
	} else {
		tmp = fabs(sin(t)) * (fabs(ew) * fabs(fma(tanh(asinh(t_2)), t_2, (1.0 / 1.0))));
	}
	return tmp;
}

Julia

function code(eh, ew, t)
	t_1 = Float64(eh / Float64(ew * t))
	t_2 = Float64(eh / Float64(tan(t) * ew))
	tmp = 0.0
	if (t <= 2.4e+58)
		tmp = abs(fma(Float64(tanh(asinh(t_1)) * cos(t)), eh, Float64(Float64(sin(t) * ew) / sqrt(fma(t_1, t_1, 1.0)))));
	else
		tmp = Float64(abs(sin(t)) * Float64(abs(ew) * abs(fma(tanh(asinh(t_2)), t_2, Float64(1.0 / 1.0)))));
	end
	return tmp
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[(eh / N[(ew * t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(eh / N[(N[Tan[t], $MachinePrecision] * ew), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, 2.4e+58], N[Abs[N[(N[(N[Tanh[N[ArcSinh[t$95$1], $MachinePrecision]], $MachinePrecision] * N[Cos[t], $MachinePrecision]), $MachinePrecision] * eh + N[(N[(N[Sin[t], $MachinePrecision] * ew), $MachinePrecision] / N[Sqrt[N[(t$95$1 * t$95$1 + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[(N[Abs[N[Sin[t], $MachinePrecision]], $MachinePrecision] * N[(N[Abs[ew], $MachinePrecision] * N[Abs[N[(N[Tanh[N[ArcSinh[t$95$2], $MachinePrecision]], $MachinePrecision] * t$95$2 + N[(1.0 / 1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 2 regimes

2. if t < 2.4e58

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]
   7. Step-by-step derivation

   8. Applied rewrites 89.8%

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]

   9. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
   10. Step-by-step derivation

   11. Applied rewrites 89.9%

       \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
   12. Step-by-step derivation

       1. lift-fma.f64 N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh\right) \cdot \cos t + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}}\right| \]

       2. lift-*.f64 N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh\right)} \cdot \cos t + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       3. associate-*l* N/A

          \[\leadsto \left|\color{blue}{\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \left(eh \cdot \cos t\right)} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       4. *-commutative N/A

          \[\leadsto \left|\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \color{blue}{\left(\cos t \cdot eh\right)} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       5. associate-*r* N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \cos t\right) \cdot eh} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       6. lower-fma.f64 N/A

          \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \cos t, eh, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)}\right| \]

   13. Applied rewrites 89.9%

       \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{ew \cdot t}\right) \cdot \cos t, eh, \frac{\sin t \cdot ew}{\sqrt{\mathsf{fma}\left(\frac{eh}{ew \cdot t}, \frac{eh}{ew \cdot t}, 1\right)}}\right)}\right| \]

   if 2.4e58 < t

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   3. Applied rewrites 76.1%

      \[\leadsto \color{blue}{\left|\frac{1}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right|} \]

   4. Taylor expanded in eh around 0

      \[\leadsto \left|\frac{1}{\color{blue}{1}} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right| \]
   5. Step-by-step derivation

   6. Applied rewrites 74.7%

      \[\leadsto \left|\frac{1}{\color{blue}{1}} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right| \]

   8. Applied rewrites 70.9%

      \[\leadsto \color{blue}{\left|\sin t\right| \cdot \left(\left|ew\right| \cdot \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right), \frac{eh}{\tan t \cdot ew}, \frac{1}{1}\right)\right|\right)} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 6: 91.9% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \sin t \cdot ew\\ t_2 := \frac{eh}{ew \cdot t}\\ t_3 := \frac{eh}{\tan t \cdot ew}\\ \mathbf{if}\;t \leq 2.4 \cdot 10^{+58}:\\ \;\;\;\;\left|\mathsf{fma}\left(\tanh \sinh^{-1} t\_2 \cdot \cos t, eh, \frac{t\_1}{\sqrt{\mathsf{fma}\left(t\_2, t\_2, 1\right)}}\right)\right|\\ \mathbf{else}:\\ \;\;\;\;\left|\mathsf{fma}\left(\tanh \sinh^{-1} t\_3, t\_3, \frac{1}{1}\right) \cdot t\_1\right|\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (* (sin t) ew)) (t_2 (/ eh (* ew t))) (t_3 (/ eh (* (tan t) ew))))
   (if (<= t 2.4e+58)
     (fabs
      (fma (* (tanh (asinh t_2)) (cos t)) eh (/ t_1 (sqrt (fma t_2 t_2 1.0)))))
     (fabs (* (fma (tanh (asinh t_3)) t_3 (/ 1.0 1.0)) t_1)))))

C

double code(double eh, double ew, double t) {
	double t_1 = sin(t) * ew;
	double t_2 = eh / (ew * t);
	double t_3 = eh / (tan(t) * ew);
	double tmp;
	if (t <= 2.4e+58) {
		tmp = fabs(fma((tanh(asinh(t_2)) * cos(t)), eh, (t_1 / sqrt(fma(t_2, t_2, 1.0)))));
	} else {
		tmp = fabs((fma(tanh(asinh(t_3)), t_3, (1.0 / 1.0)) * t_1));
	}
	return tmp;
}

Julia

function code(eh, ew, t)
	t_1 = Float64(sin(t) * ew)
	t_2 = Float64(eh / Float64(ew * t))
	t_3 = Float64(eh / Float64(tan(t) * ew))
	tmp = 0.0
	if (t <= 2.4e+58)
		tmp = abs(fma(Float64(tanh(asinh(t_2)) * cos(t)), eh, Float64(t_1 / sqrt(fma(t_2, t_2, 1.0)))));
	else
		tmp = abs(Float64(fma(tanh(asinh(t_3)), t_3, Float64(1.0 / 1.0)) * t_1));
	end
	return tmp
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[(N[Sin[t], $MachinePrecision] * ew), $MachinePrecision]}, Block[{t$95$2 = N[(eh / N[(ew * t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(eh / N[(N[Tan[t], $MachinePrecision] * ew), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, 2.4e+58], N[Abs[N[(N[(N[Tanh[N[ArcSinh[t$95$2], $MachinePrecision]], $MachinePrecision] * N[Cos[t], $MachinePrecision]), $MachinePrecision] * eh + N[(t$95$1 / N[Sqrt[N[(t$95$2 * t$95$2 + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[Abs[N[(N[(N[Tanh[N[ArcSinh[t$95$3], $MachinePrecision]], $MachinePrecision] * t$95$3 + N[(1.0 / 1.0), $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]], $MachinePrecision]]]]]

Derivation

1. Split input into 2 regimes

2. if t < 2.4e58

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]
   7. Step-by-step derivation

   8. Applied rewrites 89.8%

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]

   9. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
   10. Step-by-step derivation

   11. Applied rewrites 89.9%

       \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
   12. Step-by-step derivation

       1. lift-fma.f64 N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh\right) \cdot \cos t + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}}\right| \]

       2. lift-*.f64 N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh\right)} \cdot \cos t + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       3. associate-*l* N/A

          \[\leadsto \left|\color{blue}{\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \left(eh \cdot \cos t\right)} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       4. *-commutative N/A

          \[\leadsto \left|\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \color{blue}{\left(\cos t \cdot eh\right)} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       5. associate-*r* N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \cos t\right) \cdot eh} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       6. lower-fma.f64 N/A

          \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \cos t, eh, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)}\right| \]

   13. Applied rewrites 89.9%

       \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{ew \cdot t}\right) \cdot \cos t, eh, \frac{\sin t \cdot ew}{\sqrt{\mathsf{fma}\left(\frac{eh}{ew \cdot t}, \frac{eh}{ew \cdot t}, 1\right)}}\right)}\right| \]

   if 2.4e58 < t

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   3. Applied rewrites 76.1%

      \[\leadsto \color{blue}{\left|\frac{1}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right|} \]

   4. Taylor expanded in eh around 0

      \[\leadsto \left|\frac{1}{\color{blue}{1}} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right| \]
   5. Step-by-step derivation

   6. Applied rewrites 74.7%

      \[\leadsto \left|\frac{1}{\color{blue}{1}} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right| \]

   8. Applied rewrites 74.7%

      \[\leadsto \color{blue}{\left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right), \frac{eh}{\tan t \cdot ew}, \frac{1}{1}\right) \cdot \left(\sin t \cdot ew\right)\right|} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 7: 89.9% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \sin t \cdot ew\\ t_2 := \frac{eh}{ew \cdot t}\\ \mathbf{if}\;t \leq 2.4 \cdot 10^{+58}:\\ \;\;\;\;\left|\mathsf{fma}\left(\tanh \sinh^{-1} t\_2 \cdot \cos t, eh, \frac{t\_1}{\sqrt{\mathsf{fma}\left(t\_2, t\_2, 1\right)}}\right)\right|\\ \mathbf{else}:\\ \;\;\;\;\left|\frac{1}{1} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \frac{eh}{\tan t}}{ew}\right| \cdot \left|t\_1\right|\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (* (sin t) ew)) (t_2 (/ eh (* ew t))))
   (if (<= t 2.4e+58)
     (fabs
      (fma (* (tanh (asinh t_2)) (cos t)) eh (/ t_1 (sqrt (fma t_2 t_2 1.0)))))
     (*
      (fabs
       (+
        (/ 1.0 1.0)
        (/ (* (tanh (asinh (/ eh (* (tan t) ew)))) (/ eh (tan t))) ew)))
      (fabs t_1)))))

C

double code(double eh, double ew, double t) {
	double t_1 = sin(t) * ew;
	double t_2 = eh / (ew * t);
	double tmp;
	if (t <= 2.4e+58) {
		tmp = fabs(fma((tanh(asinh(t_2)) * cos(t)), eh, (t_1 / sqrt(fma(t_2, t_2, 1.0)))));
	} else {
		tmp = fabs(((1.0 / 1.0) + ((tanh(asinh((eh / (tan(t) * ew)))) * (eh / tan(t))) / ew))) * fabs(t_1);
	}
	return tmp;
}

Julia

function code(eh, ew, t)
	t_1 = Float64(sin(t) * ew)
	t_2 = Float64(eh / Float64(ew * t))
	tmp = 0.0
	if (t <= 2.4e+58)
		tmp = abs(fma(Float64(tanh(asinh(t_2)) * cos(t)), eh, Float64(t_1 / sqrt(fma(t_2, t_2, 1.0)))));
	else
		tmp = Float64(abs(Float64(Float64(1.0 / 1.0) + Float64(Float64(tanh(asinh(Float64(eh / Float64(tan(t) * ew)))) * Float64(eh / tan(t))) / ew))) * abs(t_1));
	end
	return tmp
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[(N[Sin[t], $MachinePrecision] * ew), $MachinePrecision]}, Block[{t$95$2 = N[(eh / N[(ew * t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, 2.4e+58], N[Abs[N[(N[(N[Tanh[N[ArcSinh[t$95$2], $MachinePrecision]], $MachinePrecision] * N[Cos[t], $MachinePrecision]), $MachinePrecision] * eh + N[(t$95$1 / N[Sqrt[N[(t$95$2 * t$95$2 + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[(N[Abs[N[(N[(1.0 / 1.0), $MachinePrecision] + N[(N[(N[Tanh[N[ArcSinh[N[(eh / N[(N[Tan[t], $MachinePrecision] * ew), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(eh / N[Tan[t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / ew), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Abs[t$95$1], $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 2 regimes

2. if t < 2.4e58

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]
   7. Step-by-step derivation

   8. Applied rewrites 89.8%

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]

   9. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
   10. Step-by-step derivation

   11. Applied rewrites 89.9%

       \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
   12. Step-by-step derivation

       1. lift-fma.f64 N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh\right) \cdot \cos t + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}}\right| \]

       2. lift-*.f64 N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh\right)} \cdot \cos t + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       3. associate-*l* N/A

          \[\leadsto \left|\color{blue}{\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \left(eh \cdot \cos t\right)} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       4. *-commutative N/A

          \[\leadsto \left|\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \color{blue}{\left(\cos t \cdot eh\right)} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       5. associate-*r* N/A

          \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \cos t\right) \cdot eh} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

       6. lower-fma.f64 N/A

          \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \cos t, eh, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)}\right| \]

   13. Applied rewrites 89.9%

       \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{ew \cdot t}\right) \cdot \cos t, eh, \frac{\sin t \cdot ew}{\sqrt{\mathsf{fma}\left(\frac{eh}{ew \cdot t}, \frac{eh}{ew \cdot t}, 1\right)}}\right)}\right| \]

   if 2.4e58 < t

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   3. Applied rewrites 76.1%

      \[\leadsto \color{blue}{\left|\frac{1}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right|} \]

   4. Taylor expanded in eh around 0

      \[\leadsto \left|\frac{1}{\color{blue}{1}} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right| \]
   5. Step-by-step derivation

   6. Applied rewrites 74.7%

      \[\leadsto \left|\frac{1}{\color{blue}{1}} + \frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right| \]
   7. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\frac{1}{1} + \color{blue}{\frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew} \cdot \frac{1}{\tan t}}\right| \cdot \left|\sin t \cdot ew\right| \]

      2. lift-/.f64 N/A

         \[\leadsto \left|\frac{1}{1} + \color{blue}{\frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh}{ew}} \cdot \frac{1}{\tan t}\right| \cdot \left|\sin t \cdot ew\right| \]

      3. associate-*l/ N/A

         \[\leadsto \left|\frac{1}{1} + \color{blue}{\frac{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh\right) \cdot \frac{1}{\tan t}}{ew}}\right| \cdot \left|\sin t \cdot ew\right| \]

      4. lower-/.f64 N/A

         \[\leadsto \left|\frac{1}{1} + \color{blue}{\frac{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh\right) \cdot \frac{1}{\tan t}}{ew}}\right| \cdot \left|\sin t \cdot ew\right| \]

   8. Applied rewrites 70.7%

      \[\leadsto \left|\frac{1}{1} + \color{blue}{\frac{\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \frac{eh}{\tan t}}{ew}}\right| \cdot \left|\sin t \cdot ew\right| \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 8: 84.6% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{eh}{ew \cdot t}\\ \left|\mathsf{fma}\left(\tanh \sinh^{-1} t\_1 \cdot \cos t, eh, \frac{\sin t \cdot ew}{\sqrt{\mathsf{fma}\left(t\_1, t\_1, 1\right)}}\right)\right| \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (/ eh (* ew t))))
   (fabs
    (fma
     (* (tanh (asinh t_1)) (cos t))
     eh
     (/ (* (sin t) ew) (sqrt (fma t_1 t_1 1.0)))))))

C

double code(double eh, double ew, double t) {
	double t_1 = eh / (ew * t);
	return fabs(fma((tanh(asinh(t_1)) * cos(t)), eh, ((sin(t) * ew) / sqrt(fma(t_1, t_1, 1.0)))));
}

Julia

function code(eh, ew, t)
	t_1 = Float64(eh / Float64(ew * t))
	return abs(fma(Float64(tanh(asinh(t_1)) * cos(t)), eh, Float64(Float64(sin(t) * ew) / sqrt(fma(t_1, t_1, 1.0)))))
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[(eh / N[(ew * t), $MachinePrecision]), $MachinePrecision]}, N[Abs[N[(N[(N[Tanh[N[ArcSinh[t$95$1], $MachinePrecision]], $MachinePrecision] * N[Cos[t], $MachinePrecision]), $MachinePrecision] * eh + N[(N[(N[Sin[t], $MachinePrecision] * ew), $MachinePrecision] / N[Sqrt[N[(t$95$1 * t$95$1 + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]

Derivation

1. Initial program 99.8%

   \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
2. Step-by-step derivation

   1. lift-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

   2. lift-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   3. associate-*l* N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

   4. *-commutative N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   5. lower-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

3. Applied rewrites 99.8%

   \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

5. Applied rewrites 99.8%

   \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

6. Taylor expanded in t around 0

   \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]
7. Step-by-step derivation

8. Applied rewrites 89.8%

   \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]

9. Taylor expanded in t around 0

   \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
10. Step-by-step derivation

11. Applied rewrites 89.9%

    \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
12. Step-by-step derivation

    1. lift-fma.f64 N/A

       \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh\right) \cdot \cos t + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}}\right| \]

    2. lift-*.f64 N/A

       \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh\right)} \cdot \cos t + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

    3. associate-*l* N/A

       \[\leadsto \left|\color{blue}{\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \left(eh \cdot \cos t\right)} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

    4. *-commutative N/A

       \[\leadsto \left|\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \color{blue}{\left(\cos t \cdot eh\right)} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

    5. associate-*r* N/A

       \[\leadsto \left|\color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \cos t\right) \cdot eh} + \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right| \]

    6. lower-fma.f64 N/A

       \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot \cos t, eh, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)}\right| \]

13. Applied rewrites 89.9%

    \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{ew \cdot t}\right) \cdot \cos t, eh, \frac{\sin t \cdot ew}{\sqrt{\mathsf{fma}\left(\frac{eh}{ew \cdot t}, \frac{eh}{ew \cdot t}, 1\right)}}\right)}\right| \]
14. Add Preprocessing

Alternative 9: 68.8% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{eh}{t \cdot ew}\\ t_2 := \sinh^{-1} t\_1\\ t_3 := \tanh t\_2\\ \mathbf{if}\;t \leq 1.4 \cdot 10^{+55}:\\ \;\;\;\;\left|\mathsf{fma}\left(t\_3 \cdot eh, 1 + -0.5 \cdot {t}^{2}, \frac{\sin t \cdot ew}{\cosh t\_2}\right)\right|\\ \mathbf{elif}\;t \leq 2.25 \cdot 10^{+69}:\\ \;\;\;\;\left|\left(\frac{1}{{t\_1}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot t\_3\right)\right|\\ \mathbf{else}:\\ \;\;\;\;\left|ew \cdot \sin t\right|\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (/ eh (* t ew))) (t_2 (asinh t_1)) (t_3 (tanh t_2)))
   (if (<= t 1.4e+55)
     (fabs
      (fma
       (* t_3 eh)
       (+ 1.0 (* -0.5 (pow t 2.0)))
       (/ (* (sin t) ew) (cosh t_2))))
     (if (<= t 2.25e+69)
       (fabs (* (+ (/ 1.0 (pow t_1 2.0)) 1.0) (* (* (cos t) eh) t_3)))
       (fabs (* ew (sin t)))))))

C

double code(double eh, double ew, double t) {
	double t_1 = eh / (t * ew);
	double t_2 = asinh(t_1);
	double t_3 = tanh(t_2);
	double tmp;
	if (t <= 1.4e+55) {
		tmp = fabs(fma((t_3 * eh), (1.0 + (-0.5 * pow(t, 2.0))), ((sin(t) * ew) / cosh(t_2))));
	} else if (t <= 2.25e+69) {
		tmp = fabs((((1.0 / pow(t_1, 2.0)) + 1.0) * ((cos(t) * eh) * t_3)));
	} else {
		tmp = fabs((ew * sin(t)));
	}
	return tmp;
}

Julia

function code(eh, ew, t)
	t_1 = Float64(eh / Float64(t * ew))
	t_2 = asinh(t_1)
	t_3 = tanh(t_2)
	tmp = 0.0
	if (t <= 1.4e+55)
		tmp = abs(fma(Float64(t_3 * eh), Float64(1.0 + Float64(-0.5 * (t ^ 2.0))), Float64(Float64(sin(t) * ew) / cosh(t_2))));
	elseif (t <= 2.25e+69)
		tmp = abs(Float64(Float64(Float64(1.0 / (t_1 ^ 2.0)) + 1.0) * Float64(Float64(cos(t) * eh) * t_3)));
	else
		tmp = abs(Float64(ew * sin(t)));
	end
	return tmp
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[(eh / N[(t * ew), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[ArcSinh[t$95$1], $MachinePrecision]}, Block[{t$95$3 = N[Tanh[t$95$2], $MachinePrecision]}, If[LessEqual[t, 1.4e+55], N[Abs[N[(N[(t$95$3 * eh), $MachinePrecision] * N[(1.0 + N[(-0.5 * N[Power[t, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[Sin[t], $MachinePrecision] * ew), $MachinePrecision] / N[Cosh[t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], If[LessEqual[t, 2.25e+69], N[Abs[N[(N[(N[(1.0 / N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision] * N[(N[(N[Cos[t], $MachinePrecision] * eh), $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[Abs[N[(ew * N[Sin[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]]]]]

Derivation

1. Split input into 3 regimes

2. if t < 1.4e55

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]
   7. Step-by-step derivation

   8. Applied rewrites 89.8%

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]

   9. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
   10. Step-by-step derivation

   11. Applied rewrites 89.9%

       \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]

   12. Taylor expanded in t around 0

       \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \color{blue}{1 + \frac{-1}{2} \cdot {t}^{2}}, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]
   13. Step-by-step derivation

       1. lower-+.f64 N/A

          \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, 1 + \color{blue}{\frac{-1}{2} \cdot {t}^{2}}, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]

       2. lower-*.f64 N/A

          \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, 1 + \frac{-1}{2} \cdot \color{blue}{{t}^{2}}, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]

       3. lower-pow.f64 61.9

          \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, 1 + -0.5 \cdot {t}^{\color{blue}{2}}, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]

   14. Applied rewrites 61.9%

       \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \color{blue}{1 + -0.5 \cdot {t}^{2}}, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]

   if 1.4e55 < t < 2.25e69

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 76.4%

      \[\leadsto \left|\color{blue}{\left(\frac{1}{{\left(\frac{eh}{\tan t \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right)}\right| \]

   6. Taylor expanded in t around 0

      \[\leadsto \left|\left(\frac{1}{{\left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right)\right| \]
   7. Step-by-step derivation

   8. Applied rewrites 57.7%

      \[\leadsto \left|\left(\frac{1}{{\left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right)\right| \]

   9. Taylor expanded in t around 0

      \[\leadsto \left|\left(\frac{1}{{\left(\frac{eh}{t \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)\right)\right| \]
   10. Step-by-step derivation

   11. Applied rewrites 57.3%

       \[\leadsto \left|\left(\frac{1}{{\left(\frac{eh}{t \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)\right)\right| \]

   if 2.25e69 < t

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in eh around 0

      \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]
   7. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto \left|ew \cdot \color{blue}{\sin t}\right| \]

      2. lower-sin.f64 41.9

         \[\leadsto \left|ew \cdot \sin t\right| \]

   8. Applied rewrites 41.9%

      \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 10: 66.7% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)\\ \mathbf{if}\;t \leq 2700000000000:\\ \;\;\;\;\left|\mathsf{fma}\left(\tanh t\_1 \cdot eh, \cos t, \frac{\left(t \cdot \left(1 + -0.16666666666666666 \cdot {t}^{2}\right)\right) \cdot ew}{\cosh t\_1}\right)\right|\\ \mathbf{else}:\\ \;\;\;\;\left|ew \cdot \sin t\right|\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (asinh (/ eh (* t ew)))))
   (if (<= t 2700000000000.0)
     (fabs
      (fma
       (* (tanh t_1) eh)
       (cos t)
       (/
        (* (* t (+ 1.0 (* -0.16666666666666666 (pow t 2.0)))) ew)
        (cosh t_1))))
     (fabs (* ew (sin t))))))

C

double code(double eh, double ew, double t) {
	double t_1 = asinh((eh / (t * ew)));
	double tmp;
	if (t <= 2700000000000.0) {
		tmp = fabs(fma((tanh(t_1) * eh), cos(t), (((t * (1.0 + (-0.16666666666666666 * pow(t, 2.0)))) * ew) / cosh(t_1))));
	} else {
		tmp = fabs((ew * sin(t)));
	}
	return tmp;
}

Julia

function code(eh, ew, t)
	t_1 = asinh(Float64(eh / Float64(t * ew)))
	tmp = 0.0
	if (t <= 2700000000000.0)
		tmp = abs(fma(Float64(tanh(t_1) * eh), cos(t), Float64(Float64(Float64(t * Float64(1.0 + Float64(-0.16666666666666666 * (t ^ 2.0)))) * ew) / cosh(t_1))));
	else
		tmp = abs(Float64(ew * sin(t)));
	end
	return tmp
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[ArcSinh[N[(eh / N[(t * ew), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t, 2700000000000.0], N[Abs[N[(N[(N[Tanh[t$95$1], $MachinePrecision] * eh), $MachinePrecision] * N[Cos[t], $MachinePrecision] + N[(N[(N[(t * N[(1.0 + N[(-0.16666666666666666 * N[Power[t, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * ew), $MachinePrecision] / N[Cosh[t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[Abs[N[(ew * N[Sin[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if t < 2.7e12

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]
   7. Step-by-step derivation

   8. Applied rewrites 89.8%

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)\right| \]

   9. Taylor expanded in t around 0

      \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]
   10. Step-by-step derivation

   11. Applied rewrites 89.9%

       \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}\right)\right| \]

   12. Taylor expanded in t around 0

       \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\color{blue}{\left(t \cdot \left(1 + \frac{-1}{6} \cdot {t}^{2}\right)\right)} \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]
   13. Step-by-step derivation

       1. lower-*.f64 N/A

          \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\left(t \cdot \color{blue}{\left(1 + \frac{-1}{6} \cdot {t}^{2}\right)}\right) \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]

       2. lower-+.f64 N/A

          \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\left(t \cdot \left(1 + \color{blue}{\frac{-1}{6} \cdot {t}^{2}}\right)\right) \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]

       3. lower-*.f64 N/A

          \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\left(t \cdot \left(1 + \frac{-1}{6} \cdot \color{blue}{{t}^{2}}\right)\right) \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]

       4. lower-pow.f64 57.3

          \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\left(t \cdot \left(1 + -0.16666666666666666 \cdot {t}^{\color{blue}{2}}\right)\right) \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]

   14. Applied rewrites 57.3%

       \[\leadsto \left|\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right) \cdot eh, \cos t, \frac{\color{blue}{\left(t \cdot \left(1 + -0.16666666666666666 \cdot {t}^{2}\right)\right)} \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{t \cdot ew}\right)}\right)\right| \]

   if 2.7e12 < t

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in eh around 0

      \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]
   7. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto \left|ew \cdot \color{blue}{\sin t}\right| \]

      2. lower-sin.f64 41.9

         \[\leadsto \left|ew \cdot \sin t\right| \]

   8. Applied rewrites 41.9%

      \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 11: 56.3% accurate, 2.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{eh}{t \cdot ew}\\ \mathbf{if}\;eh \leq 6 \cdot 10^{-170}:\\ \;\;\;\;\left|ew \cdot \sin t\right|\\ \mathbf{else}:\\ \;\;\;\;\left|\left(\frac{1}{{t\_1}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} t\_1\right)\right|\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (let* ((t_1 (/ eh (* t ew))))
   (if (<= eh 6e-170)
     (fabs (* ew (sin t)))
     (fabs
      (*
       (+ (/ 1.0 (pow t_1 2.0)) 1.0)
       (* (* (cos t) eh) (tanh (asinh t_1))))))))

C

double code(double eh, double ew, double t) {
	double t_1 = eh / (t * ew);
	double tmp;
	if (eh <= 6e-170) {
		tmp = fabs((ew * sin(t)));
	} else {
		tmp = fabs((((1.0 / pow(t_1, 2.0)) + 1.0) * ((cos(t) * eh) * tanh(asinh(t_1)))));
	}
	return tmp;
}

Python

def code(eh, ew, t):
	t_1 = eh / (t * ew)
	tmp = 0
	if eh <= 6e-170:
		tmp = math.fabs((ew * math.sin(t)))
	else:
		tmp = math.fabs((((1.0 / math.pow(t_1, 2.0)) + 1.0) * ((math.cos(t) * eh) * math.tanh(math.asinh(t_1)))))
	return tmp

Julia

function code(eh, ew, t)
	t_1 = Float64(eh / Float64(t * ew))
	tmp = 0.0
	if (eh <= 6e-170)
		tmp = abs(Float64(ew * sin(t)));
	else
		tmp = abs(Float64(Float64(Float64(1.0 / (t_1 ^ 2.0)) + 1.0) * Float64(Float64(cos(t) * eh) * tanh(asinh(t_1)))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(eh, ew, t)
	t_1 = eh / (t * ew);
	tmp = 0.0;
	if (eh <= 6e-170)
		tmp = abs((ew * sin(t)));
	else
		tmp = abs((((1.0 / (t_1 ^ 2.0)) + 1.0) * ((cos(t) * eh) * tanh(asinh(t_1)))));
	end
	tmp_2 = tmp;
end

Wolfram

code[eh_, ew_, t_] := Block[{t$95$1 = N[(eh / N[(t * ew), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[eh, 6e-170], N[Abs[N[(ew * N[Sin[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[Abs[N[(N[(N[(1.0 / N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision] * N[(N[(N[Cos[t], $MachinePrecision] * eh), $MachinePrecision] * N[Tanh[N[ArcSinh[t$95$1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if eh < 6.00000000000000027e-170

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in eh around 0

      \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]
   7. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto \left|ew \cdot \color{blue}{\sin t}\right| \]

      2. lower-sin.f64 41.9

         \[\leadsto \left|ew \cdot \sin t\right| \]

   8. Applied rewrites 41.9%

      \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]

   if 6.00000000000000027e-170 < eh

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 76.4%

      \[\leadsto \left|\color{blue}{\left(\frac{1}{{\left(\frac{eh}{\tan t \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right)}\right| \]

   6. Taylor expanded in t around 0

      \[\leadsto \left|\left(\frac{1}{{\left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right)\right| \]
   7. Step-by-step derivation

   8. Applied rewrites 57.7%

      \[\leadsto \left|\left(\frac{1}{{\left(\frac{eh}{\color{blue}{t} \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)\right)\right| \]

   9. Taylor expanded in t around 0

      \[\leadsto \left|\left(\frac{1}{{\left(\frac{eh}{t \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)\right)\right| \]
   10. Step-by-step derivation

   11. Applied rewrites 57.3%

       \[\leadsto \left|\left(\frac{1}{{\left(\frac{eh}{t \cdot ew}\right)}^{2}} + 1\right) \cdot \left(\left(\cos t \cdot eh\right) \cdot \tanh \sinh^{-1} \left(\frac{eh}{\color{blue}{t} \cdot ew}\right)\right)\right| \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 12: 50.6% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;eh \leq 6.4 \cdot 10^{-62}:\\ \;\;\;\;\left|ew \cdot \sin t\right|\\ \mathbf{else}:\\ \;\;\;\;\left|\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh\right|\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (if (<= eh 6.4e-62)
   (fabs (* ew (sin t)))
   (fabs (* (tanh (asinh (/ eh (* (tan t) ew)))) eh))))

C

double code(double eh, double ew, double t) {
	double tmp;
	if (eh <= 6.4e-62) {
		tmp = fabs((ew * sin(t)));
	} else {
		tmp = fabs((tanh(asinh((eh / (tan(t) * ew)))) * eh));
	}
	return tmp;
}

Python

def code(eh, ew, t):
	tmp = 0
	if eh <= 6.4e-62:
		tmp = math.fabs((ew * math.sin(t)))
	else:
		tmp = math.fabs((math.tanh(math.asinh((eh / (math.tan(t) * ew)))) * eh))
	return tmp

Julia

function code(eh, ew, t)
	tmp = 0.0
	if (eh <= 6.4e-62)
		tmp = abs(Float64(ew * sin(t)));
	else
		tmp = abs(Float64(tanh(asinh(Float64(eh / Float64(tan(t) * ew)))) * eh));
	end
	return tmp
end

MATLAB

function tmp_2 = code(eh, ew, t)
	tmp = 0.0;
	if (eh <= 6.4e-62)
		tmp = abs((ew * sin(t)));
	else
		tmp = abs((tanh(asinh((eh / (tan(t) * ew)))) * eh));
	end
	tmp_2 = tmp;
end

Wolfram

code[eh_, ew_, t_] := If[LessEqual[eh, 6.4e-62], N[Abs[N[(ew * N[Sin[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[Abs[N[(N[Tanh[N[ArcSinh[N[(eh / N[(N[Tan[t], $MachinePrecision] * ew), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * eh), $MachinePrecision]], $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if eh < 6.40000000000000043e-62

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in eh around 0

      \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]
   7. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto \left|ew \cdot \color{blue}{\sin t}\right| \]

      2. lower-sin.f64 41.9

         \[\leadsto \left|ew \cdot \sin t\right| \]

   8. Applied rewrites 41.9%

      \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]

   if 6.40000000000000043e-62 < eh

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   2. Taylor expanded in t around 0

      \[\leadsto \left|\color{blue}{eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)}\right| \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto \left|eh \cdot \color{blue}{\sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)}\right| \]

      2. lower-sin.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      3. lower-atan.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      4. lower-/.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      6. lower-cos.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      7. lower-*.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      8. lower-sin.f64 41.5

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

   4. Applied rewrites 41.5%

      \[\leadsto \left|\color{blue}{eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)}\right| \]
   5. Step-by-step derivation

      1. lift-sin.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      2. lift-atan.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      3. sin-atan N/A

         \[\leadsto \left|eh \cdot \frac{\frac{eh \cdot \cos t}{ew \cdot \sin t}}{\color{blue}{\sqrt{1 + \frac{eh \cdot \cos t}{ew \cdot \sin t} \cdot \frac{eh \cdot \cos t}{ew \cdot \sin t}}}}\right| \]

      4. tanh-asinh-rev N/A

         \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      5. lift-/.f64 N/A

         \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      6. mult-flip N/A

         \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(\left(eh \cdot \cos t\right) \cdot \frac{1}{ew \cdot \sin t}\right)\right| \]

      7. lift-*.f64 N/A

         \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(\left(eh \cdot \cos t\right) \cdot \frac{1}{ew \cdot \sin t}\right)\right| \]

      8. associate-*l* N/A

         \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \left(\cos t \cdot \frac{1}{ew \cdot \sin t}\right)\right)\right| \]

      9. lift-*.f64 N/A

         \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \left(\cos t \cdot \frac{1}{ew \cdot \sin t}\right)\right)\right| \]

      10. *-commutative N/A

          \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \left(\cos t \cdot \frac{1}{\sin t \cdot ew}\right)\right)\right| \]

      11. lift-*.f64 N/A

          \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \left(\cos t \cdot \frac{1}{\sin t \cdot ew}\right)\right)\right| \]

      12. mult-flip N/A

          \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \frac{\cos t}{\sin t \cdot ew}\right)\right| \]

      13. div-flip N/A

          \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \frac{1}{\frac{\sin t \cdot ew}{\cos t}}\right)\right| \]

      14. lift-*.f64 N/A

          \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \frac{1}{\frac{\sin t \cdot ew}{\cos t}}\right)\right| \]

      15. associate-*l/ N/A

          \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \frac{1}{\frac{\sin t}{\cos t} \cdot ew}\right)\right| \]

      16. lift-sin.f64 N/A

          \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \frac{1}{\frac{\sin t}{\cos t} \cdot ew}\right)\right| \]

      17. lift-cos.f64 N/A

          \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \frac{1}{\frac{\sin t}{\cos t} \cdot ew}\right)\right| \]

      18. tan-quot N/A

          \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \frac{1}{\tan t \cdot ew}\right)\right| \]

      19. lift-tan.f64 N/A

          \[\leadsto \left|eh \cdot \tanh \sinh^{-1} \left(eh \cdot \frac{1}{\tan t \cdot ew}\right)\right| \]

   6. Applied rewrites 41.5%

      \[\leadsto \left|\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \color{blue}{eh}\right| \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 13: 50.0% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;eh \leq 6.4 \cdot 10^{-62}:\\ \;\;\;\;\left|ew \cdot \sin t\right|\\ \mathbf{else}:\\ \;\;\;\;\left|\tanh \sinh^{-1} \left(\cos t \cdot \frac{eh}{t \cdot ew}\right) \cdot eh\right|\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (if (<= eh 6.4e-62)
   (fabs (* ew (sin t)))
   (fabs (* (tanh (asinh (* (cos t) (/ eh (* t ew))))) eh))))

C

double code(double eh, double ew, double t) {
	double tmp;
	if (eh <= 6.4e-62) {
		tmp = fabs((ew * sin(t)));
	} else {
		tmp = fabs((tanh(asinh((cos(t) * (eh / (t * ew))))) * eh));
	}
	return tmp;
}

Python

def code(eh, ew, t):
	tmp = 0
	if eh <= 6.4e-62:
		tmp = math.fabs((ew * math.sin(t)))
	else:
		tmp = math.fabs((math.tanh(math.asinh((math.cos(t) * (eh / (t * ew))))) * eh))
	return tmp

Julia

function code(eh, ew, t)
	tmp = 0.0
	if (eh <= 6.4e-62)
		tmp = abs(Float64(ew * sin(t)));
	else
		tmp = abs(Float64(tanh(asinh(Float64(cos(t) * Float64(eh / Float64(t * ew))))) * eh));
	end
	return tmp
end

MATLAB

function tmp_2 = code(eh, ew, t)
	tmp = 0.0;
	if (eh <= 6.4e-62)
		tmp = abs((ew * sin(t)));
	else
		tmp = abs((tanh(asinh((cos(t) * (eh / (t * ew))))) * eh));
	end
	tmp_2 = tmp;
end

Wolfram

code[eh_, ew_, t_] := If[LessEqual[eh, 6.4e-62], N[Abs[N[(ew * N[Sin[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[Abs[N[(N[Tanh[N[ArcSinh[N[(N[Cos[t], $MachinePrecision] * N[(eh / N[(t * ew), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * eh), $MachinePrecision]], $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if eh < 6.40000000000000043e-62

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

      2. lift-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

      3. associate-*l* N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

      4. *-commutative N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   3. Applied rewrites 99.8%

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

   5. Applied rewrites 99.8%

      \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

   6. Taylor expanded in eh around 0

      \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]
   7. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto \left|ew \cdot \color{blue}{\sin t}\right| \]

      2. lower-sin.f64 41.9

         \[\leadsto \left|ew \cdot \sin t\right| \]

   8. Applied rewrites 41.9%

      \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]

   if 6.40000000000000043e-62 < eh

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   2. Taylor expanded in t around 0

      \[\leadsto \left|\color{blue}{eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)}\right| \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto \left|eh \cdot \color{blue}{\sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)}\right| \]

      2. lower-sin.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      3. lower-atan.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      4. lower-/.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      5. lower-*.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      6. lower-cos.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      7. lower-*.f64 N/A

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

      8. lower-sin.f64 41.5

         \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)\right| \]

   4. Applied rewrites 41.5%

      \[\leadsto \left|\color{blue}{eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot \sin t}\right)}\right| \]

   5. Taylor expanded in t around 0

      \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot t}\right)\right| \]
   6. Step-by-step derivation

   7. Applied rewrites 39.7%

      \[\leadsto \left|eh \cdot \sin \tan^{-1} \left(\frac{eh \cdot \cos t}{ew \cdot t}\right)\right| \]

   9. Applied rewrites 39.7%

      \[\leadsto \left|\color{blue}{\tanh \sinh^{-1} \left(\cos t \cdot \frac{eh}{t \cdot ew}\right) \cdot eh}\right| \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 14: 41.9% accurate, 6.7× speedup

Math

\[\begin{array}{l} \\ \left|ew \cdot \sin t\right| \end{array} \]

FPCore

(FPCore (eh ew t) :precision binary64 (fabs (* ew (sin t))))

C

double code(double eh, double ew, double t) {
	return fabs((ew * sin(t)));
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(eh, ew, t)
use fmin_fmax_functions
    real(8), intent (in) :: eh
    real(8), intent (in) :: ew
    real(8), intent (in) :: t
    code = abs((ew * sin(t)))
end function

Java

public static double code(double eh, double ew, double t) {
	return Math.abs((ew * Math.sin(t)));
}

Python

def code(eh, ew, t):
	return math.fabs((ew * math.sin(t)))

Julia

function code(eh, ew, t)
	return abs(Float64(ew * sin(t)))
end

MATLAB

function tmp = code(eh, ew, t)
	tmp = abs((ew * sin(t)));
end

Wolfram

code[eh_, ew_, t_] := N[Abs[N[(ew * N[Sin[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]

Derivation

1. Initial program 99.8%

   \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]
2. Step-by-step derivation

   1. lift-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)}\right| \]

   2. lift-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(eh \cdot \cos t\right)} \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   3. associate-*l* N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{eh \cdot \left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right)}\right| \]

   4. *-commutative N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

   5. lower-*.f64 N/A

      \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\cos t \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right) \cdot eh}\right| \]

3. Applied rewrites 99.8%

   \[\leadsto \left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \color{blue}{\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot \cos t\right) \cdot eh}\right| \]

5. Applied rewrites 99.8%

   \[\leadsto \left|\color{blue}{\mathsf{fma}\left(\tanh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right) \cdot eh, \cos t, \frac{\sin t \cdot ew}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}\right)}\right| \]

6. Taylor expanded in eh around 0

   \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]
7. Step-by-step derivation

   1. lower-*.f64 N/A

      \[\leadsto \left|ew \cdot \color{blue}{\sin t}\right| \]

   2. lower-sin.f64 41.9

      \[\leadsto \left|ew \cdot \sin t\right| \]

8. Applied rewrites 41.9%

   \[\leadsto \left|\color{blue}{ew \cdot \sin t}\right| \]
9. Add Preprocessing

Alternative 15: 21.8% accurate, 6.9× speedup

Math

\[\begin{array}{l} \\ \sin t \cdot ew \end{array} \]

FPCore

(FPCore (eh ew t) :precision binary64 (* (sin t) ew))

C

double code(double eh, double ew, double t) {
	return sin(t) * ew;
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(eh, ew, t)
use fmin_fmax_functions
    real(8), intent (in) :: eh
    real(8), intent (in) :: ew
    real(8), intent (in) :: t
    code = sin(t) * ew
end function

Java

public static double code(double eh, double ew, double t) {
	return Math.sin(t) * ew;
}

Python

def code(eh, ew, t):
	return math.sin(t) * ew

Julia

function code(eh, ew, t)
	return Float64(sin(t) * ew)
end

MATLAB

function tmp = code(eh, ew, t)
	tmp = sin(t) * ew;
end

Wolfram

code[eh_, ew_, t_] := N[(N[Sin[t], $MachinePrecision] * ew), $MachinePrecision]

Derivation

1. Initial program 99.8%

   \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

3. Applied rewrites 31.6%

   \[\leadsto \color{blue}{\frac{1}{\frac{1}{\frac{\mathsf{fma}\left(\cos t \cdot eh, \frac{eh}{\tan t \cdot ew}, \sin t \cdot ew\right)}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}}}} \]

4. Taylor expanded in eh around 0

   \[\leadsto \color{blue}{ew \cdot \sin t} \]
5. Step-by-step derivation

   1. lower-*.f64 N/A

      \[\leadsto ew \cdot \color{blue}{\sin t} \]

   2. lower-sin.f64 21.8

      \[\leadsto ew \cdot \sin t \]

6. Applied rewrites 21.8%

   \[\leadsto \color{blue}{ew \cdot \sin t} \]
7. Step-by-step derivation

   1. lift-*.f64 N/A

      \[\leadsto ew \cdot \color{blue}{\sin t} \]

   2. *-commutative N/A

      \[\leadsto \sin t \cdot \color{blue}{ew} \]

   3. lift-*.f64 21.8

      \[\leadsto \sin t \cdot \color{blue}{ew} \]

8. Applied rewrites 21.8%

   \[\leadsto \color{blue}{\sin t \cdot ew} \]
9. Add Preprocessing

Alternative 16: 9.7% accurate, 6.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq 0.64:\\ \;\;\;\;ew \cdot \left(t \cdot \mathsf{fma}\left(-0.16666666666666666 \cdot t, t, 1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\frac{1}{\frac{\frac{{eh}^{2}}{ew \cdot t}}{1}}}\\ \end{array} \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (if (<= t 0.64)
   (* ew (* t (fma (* -0.16666666666666666 t) t 1.0)))
   (/ 1.0 (/ 1.0 (/ (/ (pow eh 2.0) (* ew t)) 1.0)))))

C

double code(double eh, double ew, double t) {
	double tmp;
	if (t <= 0.64) {
		tmp = ew * (t * fma((-0.16666666666666666 * t), t, 1.0));
	} else {
		tmp = 1.0 / (1.0 / ((pow(eh, 2.0) / (ew * t)) / 1.0));
	}
	return tmp;
}

Julia

function code(eh, ew, t)
	tmp = 0.0
	if (t <= 0.64)
		tmp = Float64(ew * Float64(t * fma(Float64(-0.16666666666666666 * t), t, 1.0)));
	else
		tmp = Float64(1.0 / Float64(1.0 / Float64(Float64((eh ^ 2.0) / Float64(ew * t)) / 1.0)));
	end
	return tmp
end

Wolfram

code[eh_, ew_, t_] := If[LessEqual[t, 0.64], N[(ew * N[(t * N[(N[(-0.16666666666666666 * t), $MachinePrecision] * t + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(1.0 / N[(1.0 / N[(N[(N[Power[eh, 2.0], $MachinePrecision] / N[(ew * t), $MachinePrecision]), $MachinePrecision] / 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if t < 0.640000000000000013

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   3. Applied rewrites 31.6%

      \[\leadsto \color{blue}{\frac{1}{\frac{1}{\frac{\mathsf{fma}\left(\cos t \cdot eh, \frac{eh}{\tan t \cdot ew}, \sin t \cdot ew\right)}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}}}} \]

   4. Taylor expanded in eh around 0

      \[\leadsto \color{blue}{ew \cdot \sin t} \]
   5. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto ew \cdot \color{blue}{\sin t} \]

      2. lower-sin.f64 21.8

         \[\leadsto ew \cdot \sin t \]

   6. Applied rewrites 21.8%

      \[\leadsto \color{blue}{ew \cdot \sin t} \]

   7. Taylor expanded in t around 0

      \[\leadsto ew \cdot \left(t \cdot \color{blue}{\left(1 + \frac{-1}{6} \cdot {t}^{2}\right)}\right) \]
   8. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto ew \cdot \left(t \cdot \left(1 + \color{blue}{\frac{-1}{6} \cdot {t}^{2}}\right)\right) \]

      2. lower-+.f64 N/A

         \[\leadsto ew \cdot \left(t \cdot \left(1 + \frac{-1}{6} \cdot \color{blue}{{t}^{2}}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto ew \cdot \left(t \cdot \left(1 + \frac{-1}{6} \cdot {t}^{\color{blue}{2}}\right)\right) \]

      4. lower-pow.f64 9.7

         \[\leadsto ew \cdot \left(t \cdot \left(1 + -0.16666666666666666 \cdot {t}^{2}\right)\right) \]

   9. Applied rewrites 9.7%

      \[\leadsto ew \cdot \left(t \cdot \color{blue}{\left(1 + -0.16666666666666666 \cdot {t}^{2}\right)}\right) \]
   10. Step-by-step derivation

       1. lift-+.f64 N/A

          \[\leadsto ew \cdot \left(t \cdot \left(1 + \frac{-1}{6} \cdot \color{blue}{{t}^{2}}\right)\right) \]

       2. +-commutative N/A

          \[\leadsto ew \cdot \left(t \cdot \left(\frac{-1}{6} \cdot {t}^{2} + 1\right)\right) \]

       3. lift-*.f64 N/A

          \[\leadsto ew \cdot \left(t \cdot \left(\frac{-1}{6} \cdot {t}^{2} + 1\right)\right) \]

       4. lift-pow.f64 N/A

          \[\leadsto ew \cdot \left(t \cdot \left(\frac{-1}{6} \cdot {t}^{2} + 1\right)\right) \]

       5. unpow2 N/A

          \[\leadsto ew \cdot \left(t \cdot \left(\frac{-1}{6} \cdot \left(t \cdot t\right) + 1\right)\right) \]

       6. associate-*r* N/A

          \[\leadsto ew \cdot \left(t \cdot \left(\left(\frac{-1}{6} \cdot t\right) \cdot t + 1\right)\right) \]

       7. lower-fma.f64 N/A

          \[\leadsto ew \cdot \left(t \cdot \mathsf{fma}\left(\frac{-1}{6} \cdot t, t, 1\right)\right) \]

       8. lower-*.f64 9.7

          \[\leadsto ew \cdot \left(t \cdot \mathsf{fma}\left(-0.16666666666666666 \cdot t, t, 1\right)\right) \]

   11. Applied rewrites 9.7%

       \[\leadsto ew \cdot \left(t \cdot \mathsf{fma}\left(-0.16666666666666666 \cdot t, t, 1\right)\right) \]

   if 0.640000000000000013 < t

   1. Initial program 99.8%

      \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

   3. Applied rewrites 31.6%

      \[\leadsto \color{blue}{\frac{1}{\frac{1}{\frac{\mathsf{fma}\left(\cos t \cdot eh, \frac{eh}{\tan t \cdot ew}, \sin t \cdot ew\right)}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}}}} \]

   4. Taylor expanded in eh around 0

      \[\leadsto \frac{1}{\frac{1}{\frac{\mathsf{fma}\left(\cos t \cdot eh, \frac{eh}{\tan t \cdot ew}, \sin t \cdot ew\right)}{\color{blue}{1}}}} \]
   5. Step-by-step derivation

   6. Applied rewrites 21.8%

      \[\leadsto \frac{1}{\frac{1}{\frac{\mathsf{fma}\left(\cos t \cdot eh, \frac{eh}{\tan t \cdot ew}, \sin t \cdot ew\right)}{\color{blue}{1}}}} \]

   7. Taylor expanded in t around 0

      \[\leadsto \frac{1}{\frac{1}{\frac{\color{blue}{\frac{{eh}^{2}}{ew \cdot t}}}{1}}} \]
   8. Step-by-step derivation

      1. lower-/.f64 N/A

         \[\leadsto \frac{1}{\frac{1}{\frac{\frac{{eh}^{2}}{\color{blue}{ew \cdot t}}}{1}}} \]

      2. lower-pow.f64 N/A

         \[\leadsto \frac{1}{\frac{1}{\frac{\frac{{eh}^{2}}{\color{blue}{ew} \cdot t}}{1}}} \]

      3. lower-*.f64 3.2

         \[\leadsto \frac{1}{\frac{1}{\frac{\frac{{eh}^{2}}{ew \cdot \color{blue}{t}}}{1}}} \]

   9. Applied rewrites 3.2%

      \[\leadsto \frac{1}{\frac{1}{\frac{\color{blue}{\frac{{eh}^{2}}{ew \cdot t}}}{1}}} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 17: 9.7% accurate, 16.6× speedup

Math

\[\begin{array}{l} \\ ew \cdot \left(t \cdot \mathsf{fma}\left(-0.16666666666666666 \cdot t, t, 1\right)\right) \end{array} \]

FPCore

(FPCore (eh ew t)
 :precision binary64
 (* ew (* t (fma (* -0.16666666666666666 t) t 1.0))))

C

double code(double eh, double ew, double t) {
	return ew * (t * fma((-0.16666666666666666 * t), t, 1.0));
}

Julia

function code(eh, ew, t)
	return Float64(ew * Float64(t * fma(Float64(-0.16666666666666666 * t), t, 1.0)))
end

Wolfram

code[eh_, ew_, t_] := N[(ew * N[(t * N[(N[(-0.16666666666666666 * t), $MachinePrecision] * t + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 99.8%

   \[\left|\left(ew \cdot \sin t\right) \cdot \cos \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right) + \left(eh \cdot \cos t\right) \cdot \sin \tan^{-1} \left(\frac{\frac{eh}{ew}}{\tan t}\right)\right| \]

3. Applied rewrites 31.6%

   \[\leadsto \color{blue}{\frac{1}{\frac{1}{\frac{\mathsf{fma}\left(\cos t \cdot eh, \frac{eh}{\tan t \cdot ew}, \sin t \cdot ew\right)}{\cosh \sinh^{-1} \left(\frac{eh}{\tan t \cdot ew}\right)}}}} \]

4. Taylor expanded in eh around 0

   \[\leadsto \color{blue}{ew \cdot \sin t} \]
5. Step-by-step derivation

   1. lower-*.f64 N/A

      \[\leadsto ew \cdot \color{blue}{\sin t} \]

   2. lower-sin.f64 21.8

      \[\leadsto ew \cdot \sin t \]

6. Applied rewrites 21.8%

   \[\leadsto \color{blue}{ew \cdot \sin t} \]

7. Taylor expanded in t around 0

   \[\leadsto ew \cdot \left(t \cdot \color{blue}{\left(1 + \frac{-1}{6} \cdot {t}^{2}\right)}\right) \]
8. Step-by-step derivation

   1. lower-*.f64 N/A

      \[\leadsto ew \cdot \left(t \cdot \left(1 + \color{blue}{\frac{-1}{6} \cdot {t}^{2}}\right)\right) \]

   2. lower-+.f64 N/A

      \[\leadsto ew \cdot \left(t \cdot \left(1 + \frac{-1}{6} \cdot \color{blue}{{t}^{2}}\right)\right) \]

   3. lower-*.f64 N/A

      \[\leadsto ew \cdot \left(t \cdot \left(1 + \frac{-1}{6} \cdot {t}^{\color{blue}{2}}\right)\right) \]

   4. lower-pow.f64 9.7

      \[\leadsto ew \cdot \left(t \cdot \left(1 + -0.16666666666666666 \cdot {t}^{2}\right)\right) \]

9. Applied rewrites 9.7%

   \[\leadsto ew \cdot \left(t \cdot \color{blue}{\left(1 + -0.16666666666666666 \cdot {t}^{2}\right)}\right) \]
10. Step-by-step derivation

    1. lift-+.f64 N/A

       \[\leadsto ew \cdot \left(t \cdot \left(1 + \frac{-1}{6} \cdot \color{blue}{{t}^{2}}\right)\right) \]

    2. +-commutative N/A

       \[\leadsto ew \cdot \left(t \cdot \left(\frac{-1}{6} \cdot {t}^{2} + 1\right)\right) \]

    3. lift-*.f64 N/A

       \[\leadsto ew \cdot \left(t \cdot \left(\frac{-1}{6} \cdot {t}^{2} + 1\right)\right) \]

    4. lift-pow.f64 N/A

       \[\leadsto ew \cdot \left(t \cdot \left(\frac{-1}{6} \cdot {t}^{2} + 1\right)\right) \]

    5. unpow2 N/A

       \[\leadsto ew \cdot \left(t \cdot \left(\frac{-1}{6} \cdot \left(t \cdot t\right) + 1\right)\right) \]

    6. associate-*r* N/A

       \[\leadsto ew \cdot \left(t \cdot \left(\left(\frac{-1}{6} \cdot t\right) \cdot t + 1\right)\right) \]

    7. lower-fma.f64 N/A

       \[\leadsto ew \cdot \left(t \cdot \mathsf{fma}\left(\frac{-1}{6} \cdot t, t, 1\right)\right) \]

    8. lower-*.f64 9.7

       \[\leadsto ew \cdot \left(t \cdot \mathsf{fma}\left(-0.16666666666666666 \cdot t, t, 1\right)\right) \]

11. Applied rewrites 9.7%

    \[\leadsto ew \cdot \left(t \cdot \mathsf{fma}\left(-0.16666666666666666 \cdot t, t, 1\right)\right) \]
12. Add Preprocessing

Reproduce

herbie shell --seed 2025156 
(FPCore (eh ew t)
  :name "Example from Robby"
  :precision binary64
  (fabs (+ (* (* ew (sin t)) (cos (atan (/ (/ eh ew) (tan t))))) (* (* eh (cos t)) (sin (atan (/ (/ eh ew) (tan t))))))))