Diagrams.ThreeD.Transform:aboutX from diagrams-lib-1.3.0.3, A

Percentage Accurate: 99.8% → 99.8%

Time: 10.3s

Alternatives: 7

Speedup: N/A×

Specification

Math

\[\begin{array}{l} \\ x \cdot \cos y - z \cdot \sin y \end{array} \]

FPCore

(FPCore (x y z) :precision binary64 (- (* x (cos y)) (* z (sin y))))

C

double code(double x, double y, double z) {
	return (x * cos(y)) - (z * sin(y));
}

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(x, y, z)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = (x * cos(y)) - (z * sin(y))
end function

Java

public static double code(double x, double y, double z) {
	return (x * Math.cos(y)) - (z * Math.sin(y));
}

Python

def code(x, y, z):
	return (x * math.cos(y)) - (z * math.sin(y))

Julia

function code(x, y, z)
	return Float64(Float64(x * cos(y)) - Float64(z * sin(y)))
end

MATLAB

function tmp = code(x, y, z)
	tmp = (x * cos(y)) - (z * sin(y));
end

Wolfram

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

Initial Program: 99.8% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ x \cdot \cos y - z \cdot \sin y \end{array} \]

FPCore

(FPCore (x y z) :precision binary64 (- (* x (cos y)) (* z (sin y))))

C

double code(double x, double y, double z) {
	return (x * cos(y)) - (z * sin(y));
}

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(x, y, z)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = (x * cos(y)) - (z * sin(y))
end function

Java

public static double code(double x, double y, double z) {
	return (x * Math.cos(y)) - (z * Math.sin(y));
}

Python

def code(x, y, z):
	return (x * math.cos(y)) - (z * math.sin(y))

Julia

function code(x, y, z)
	return Float64(Float64(x * cos(y)) - Float64(z * sin(y)))
end

MATLAB

function tmp = code(x, y, z)
	tmp = (x * cos(y)) - (z * sin(y));
end

Wolfram

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

Alternative 1: 99.8% accurate, N/A× speedup

Math

\[\begin{array}{l} \\ \mathsf{fma}\left(-1 \cdot \sin y, z, \left(--1 \cdot x\right) \cdot \cos y\right) \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (fma (* -1.0 (sin y)) z (* (- (* -1.0 x)) (cos y))))

C

double code(double x, double y, double z) {
	return fma((-1.0 * sin(y)), z, (-(-1.0 * x) * cos(y)));
}

Julia

function code(x, y, z)
	return fma(Float64(-1.0 * sin(y)), z, Float64(Float64(-Float64(-1.0 * x)) * cos(y)))
end

Wolfram

code[x_, y_, z_] := N[(N[(-1.0 * N[Sin[y], $MachinePrecision]), $MachinePrecision] * z + N[((-N[(-1.0 * x), $MachinePrecision]) * N[Cos[y], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 99.8%

   \[x \cdot \cos y - z \cdot \sin y \]
2. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \color{blue}{x \cdot \cos y - z \cdot \sin y} \]

   2. lift-*.f64 N/A

      \[\leadsto \color{blue}{x \cdot \cos y} - z \cdot \sin y \]

   3. lift-cos.f64 N/A

      \[\leadsto x \cdot \color{blue}{\cos y} - z \cdot \sin y \]

   4. lift-*.f64 N/A

      \[\leadsto x \cdot \cos y - \color{blue}{z \cdot \sin y} \]

   5. lift-sin.f64 N/A

      \[\leadsto x \cdot \cos y - z \cdot \color{blue}{\sin y} \]

   6. fp-cancel-sub-sign-inv N/A

      \[\leadsto \color{blue}{x \cdot \cos y + \left(\mathsf{neg}\left(z\right)\right) \cdot \sin y} \]

   7. distribute-lft-neg-in N/A

      \[\leadsto x \cdot \cos y + \color{blue}{\left(\mathsf{neg}\left(z \cdot \sin y\right)\right)} \]

   8. mul-1-neg N/A

      \[\leadsto x \cdot \cos y + \color{blue}{-1 \cdot \left(z \cdot \sin y\right)} \]

   9. +-commutative N/A

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \sin y\right) + x \cdot \cos y} \]

   10. fp-cancel-sign-sub-inv N/A

       \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \sin y\right) - \left(\mathsf{neg}\left(x\right)\right) \cdot \cos y} \]

   11. fp-cancel-sub-sign-inv N/A

       \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \sin y\right) + \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(x\right)\right)\right)\right) \cdot \cos y} \]

   12. *-commutative N/A

       \[\leadsto -1 \cdot \color{blue}{\left(\sin y \cdot z\right)} + \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(x\right)\right)\right)\right) \cdot \cos y \]

   13. associate-*r* N/A

       \[\leadsto \color{blue}{\left(-1 \cdot \sin y\right) \cdot z} + \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(x\right)\right)\right)\right) \cdot \cos y \]

   14. lower-fma.f64 N/A

       \[\leadsto \color{blue}{\mathsf{fma}\left(-1 \cdot \sin y, z, \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(x\right)\right)\right)\right) \cdot \cos y\right)} \]

   15. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(\color{blue}{-1 \cdot \sin y}, z, \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(x\right)\right)\right)\right) \cdot \cos y\right) \]

   16. lift-sin.f64 N/A

       \[\leadsto \mathsf{fma}\left(-1 \cdot \color{blue}{\sin y}, z, \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(x\right)\right)\right)\right) \cdot \cos y\right) \]

   17. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(-1 \cdot \sin y, z, \color{blue}{\left(\mathsf{neg}\left(\left(\mathsf{neg}\left(x\right)\right)\right)\right) \cdot \cos y}\right) \]

   18. lower-neg.f64 N/A

       \[\leadsto \mathsf{fma}\left(-1 \cdot \sin y, z, \color{blue}{\left(-\left(\mathsf{neg}\left(x\right)\right)\right)} \cdot \cos y\right) \]

   19. mul-1-neg N/A

       \[\leadsto \mathsf{fma}\left(-1 \cdot \sin y, z, \left(-\color{blue}{-1 \cdot x}\right) \cdot \cos y\right) \]

   20. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(-1 \cdot \sin y, z, \left(-\color{blue}{-1 \cdot x}\right) \cdot \cos y\right) \]

   21. lift-cos.f64 99.8

       \[\leadsto \mathsf{fma}\left(-1 \cdot \sin y, z, \left(--1 \cdot x\right) \cdot \color{blue}{\cos y}\right) \]

3. Applied rewrites 99.8%

   \[\leadsto \color{blue}{\mathsf{fma}\left(-1 \cdot \sin y, z, \left(--1 \cdot x\right) \cdot \cos y\right)} \]
4. Add Preprocessing

Alternative 2: 99.8% accurate, N/A× speedup

Math

\[\begin{array}{l} \\ x \cdot \cos y - z \cdot \sin y \end{array} \]

FPCore

(FPCore (x y z) :precision binary64 (- (* x (cos y)) (* z (sin y))))

C

double code(double x, double y, double z) {
	return (x * cos(y)) - (z * sin(y));
}

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(x, y, z)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = (x * cos(y)) - (z * sin(y))
end function

Java

public static double code(double x, double y, double z) {
	return (x * Math.cos(y)) - (z * Math.sin(y));
}

Python

def code(x, y, z):
	return (x * math.cos(y)) - (z * math.sin(y))

Julia

function code(x, y, z)
	return Float64(Float64(x * cos(y)) - Float64(z * sin(y)))
end

MATLAB

function tmp = code(x, y, z)
	tmp = (x * cos(y)) - (z * sin(y));
end

Wolfram

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

Derivation

1. Initial program 99.8%

   \[x \cdot \cos y - z \cdot \sin y \]
2. Add Preprocessing

Alternative 3: 91.5% accurate, N/A× speedup

Math

\[\begin{array}{l} \\ \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (* (fma (/ (* (sin y) z) x) -1.0 (cos y)) x))

C

double code(double x, double y, double z) {
	return fma(((sin(y) * z) / x), -1.0, cos(y)) * x;
}

Julia

function code(x, y, z)
	return Float64(fma(Float64(Float64(sin(y) * z) / x), -1.0, cos(y)) * x)
end

Wolfram

code[x_, y_, z_] := N[(N[(N[(N[(N[Sin[y], $MachinePrecision] * z), $MachinePrecision] / x), $MachinePrecision] * -1.0 + N[Cos[y], $MachinePrecision]), $MachinePrecision] * x), $MachinePrecision]

Derivation

1. Initial program 99.8%

   \[x \cdot \cos y - z \cdot \sin y \]

2. Taylor expanded in x around inf

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

   1. *-commutative N/A

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

   2. lower-*.f64 N/A

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

   3. +-commutative N/A

      \[\leadsto \left(-1 \cdot \frac{z \cdot \sin y}{x} + \cos y\right) \cdot x \]

   4. *-commutative N/A

      \[\leadsto \left(\frac{z \cdot \sin y}{x} \cdot -1 + \cos y\right) \cdot x \]

   5. lower-fma.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

   6. lower-/.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

   7. *-commutative N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   8. lower-*.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   9. lift-sin.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   10. lift-cos.f64 91.5

       \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

4. Applied rewrites 91.5%

   \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x} \]
5. Add Preprocessing

Alternative 4: 91.3% accurate, N/A× speedup

Math

\[\begin{array}{l} \\ \left(z \cdot \mathsf{fma}\left(-1, \frac{\sin y}{x}, \frac{\cos y}{z}\right)\right) \cdot x \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (* (* z (fma -1.0 (/ (sin y) x) (/ (cos y) z))) x))

C

double code(double x, double y, double z) {
	return (z * fma(-1.0, (sin(y) / x), (cos(y) / z))) * x;
}

Julia

function code(x, y, z)
	return Float64(Float64(z * fma(-1.0, Float64(sin(y) / x), Float64(cos(y) / z))) * x)
end

Wolfram

code[x_, y_, z_] := N[(N[(z * N[(-1.0 * N[(N[Sin[y], $MachinePrecision] / x), $MachinePrecision] + N[(N[Cos[y], $MachinePrecision] / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * x), $MachinePrecision]

Derivation

1. Initial program 99.8%

   \[x \cdot \cos y - z \cdot \sin y \]

2. Taylor expanded in x around inf

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

   1. *-commutative N/A

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

   2. lower-*.f64 N/A

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

   3. +-commutative N/A

      \[\leadsto \left(-1 \cdot \frac{z \cdot \sin y}{x} + \cos y\right) \cdot x \]

   4. *-commutative N/A

      \[\leadsto \left(\frac{z \cdot \sin y}{x} \cdot -1 + \cos y\right) \cdot x \]

   5. lower-fma.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

   6. lower-/.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

   7. *-commutative N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   8. lower-*.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   9. lift-sin.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   10. lift-cos.f64 91.5

       \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

4. Applied rewrites 91.5%

   \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x} \]

5. Taylor expanded in z around inf

   \[\leadsto \left(z \cdot \left(-1 \cdot \frac{\sin y}{x} + \frac{\cos y}{z}\right)\right) \cdot x \]
6. Step-by-step derivation

   1. lower-*.f64 N/A

      \[\leadsto \left(z \cdot \left(-1 \cdot \frac{\sin y}{x} + \frac{\cos y}{z}\right)\right) \cdot x \]

   2. lower-fma.f64 N/A

      \[\leadsto \left(z \cdot \mathsf{fma}\left(-1, \frac{\sin y}{x}, \frac{\cos y}{z}\right)\right) \cdot x \]

   3. lower-/.f64 N/A

      \[\leadsto \left(z \cdot \mathsf{fma}\left(-1, \frac{\sin y}{x}, \frac{\cos y}{z}\right)\right) \cdot x \]

   4. lift-sin.f64 N/A

      \[\leadsto \left(z \cdot \mathsf{fma}\left(-1, \frac{\sin y}{x}, \frac{\cos y}{z}\right)\right) \cdot x \]

   5. lower-/.f64 N/A

      \[\leadsto \left(z \cdot \mathsf{fma}\left(-1, \frac{\sin y}{x}, \frac{\cos y}{z}\right)\right) \cdot x \]

   6. lift-cos.f64 91.3

      \[\leadsto \left(z \cdot \mathsf{fma}\left(-1, \frac{\sin y}{x}, \frac{\cos y}{z}\right)\right) \cdot x \]

7. Applied rewrites 91.3%

   \[\leadsto \left(z \cdot \mathsf{fma}\left(-1, \frac{\sin y}{x}, \frac{\cos y}{z}\right)\right) \cdot x \]
8. Add Preprocessing

Alternative 5: 76.9% accurate, N/A× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := z \cdot \sin y\\ \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{t\_0}^{2}}{x}\right)}{-1 \cdot \frac{t\_0}{x} - \cos y} \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (* z (sin y))))
   (/
    (fma -1.0 (* x (pow (cos y) 2.0)) (/ (pow t_0 2.0) x))
    (- (* -1.0 (/ t_0 x)) (cos y)))))

C

double code(double x, double y, double z) {
	double t_0 = z * sin(y);
	return fma(-1.0, (x * pow(cos(y), 2.0)), (pow(t_0, 2.0) / x)) / ((-1.0 * (t_0 / x)) - cos(y));
}

Julia

function code(x, y, z)
	t_0 = Float64(z * sin(y))
	return Float64(fma(-1.0, Float64(x * (cos(y) ^ 2.0)), Float64((t_0 ^ 2.0) / x)) / Float64(Float64(-1.0 * Float64(t_0 / x)) - cos(y)))
end

Wolfram

code[x_, y_, z_] := Block[{t$95$0 = N[(z * N[Sin[y], $MachinePrecision]), $MachinePrecision]}, N[(N[(-1.0 * N[(x * N[Power[N[Cos[y], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(N[Power[t$95$0, 2.0], $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision] / N[(N[(-1.0 * N[(t$95$0 / x), $MachinePrecision]), $MachinePrecision] - N[Cos[y], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Initial program 99.8%

   \[x \cdot \cos y - z \cdot \sin y \]

2. Taylor expanded in x around inf

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

   1. *-commutative N/A

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

   2. lower-*.f64 N/A

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

   3. +-commutative N/A

      \[\leadsto \left(-1 \cdot \frac{z \cdot \sin y}{x} + \cos y\right) \cdot x \]

   4. *-commutative N/A

      \[\leadsto \left(\frac{z \cdot \sin y}{x} \cdot -1 + \cos y\right) \cdot x \]

   5. lower-fma.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

   6. lower-/.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

   7. *-commutative N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   8. lower-*.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   9. lift-sin.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   10. lift-cos.f64 91.5

       \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

4. Applied rewrites 91.5%

   \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x} \]
5. Step-by-step derivation

   1. lift-cos.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   2. lift-fma.f64 N/A

      \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

   3. lift-/.f64 N/A

      \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

   4. lift-*.f64 N/A

      \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

   5. lift-sin.f64 N/A

      \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

   6. flip-+ N/A

      \[\leadsto \frac{\left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \left(\frac{\sin y \cdot z}{x} \cdot -1\right) - \cos y \cdot \cos y}{\frac{\sin y \cdot z}{x} \cdot -1 - \cos y} \cdot x \]

   7. lower-/.f64 N/A

      \[\leadsto \frac{\left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \left(\frac{\sin y \cdot z}{x} \cdot -1\right) - \cos y \cdot \cos y}{\frac{\sin y \cdot z}{x} \cdot -1 - \cos y} \cdot x \]

6. Applied rewrites 78.9%

   \[\leadsto \frac{\left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \left(\frac{\sin y \cdot z}{x} \cdot -1\right) - {\cos y}^{2}}{\frac{\sin y \cdot z}{x} \cdot -1 - \cos y} \cdot x \]

7. Taylor expanded in y around inf

   \[\leadsto \frac{x \cdot \left(\frac{{z}^{2} \cdot {\sin y}^{2}}{{x}^{2}} - {\cos y}^{2}\right)}{\color{blue}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y}} \]
8. Step-by-step derivation

   1. lower-/.f64 N/A

      \[\leadsto \frac{x \cdot \left(\frac{{z}^{2} \cdot {\sin y}^{2}}{{x}^{2}} - {\cos y}^{2}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \color{blue}{\cos y}} \]

9. Applied rewrites 62.2%

   \[\leadsto \frac{x \cdot \left(\frac{{\left(z \cdot \sin y\right)}^{2}}{x \cdot x} - {\cos y}^{2}\right)}{\color{blue}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y}} \]

10. Taylor expanded in z around 0

    \[\leadsto \frac{-1 \cdot \left(x \cdot {\cos y}^{2}\right) + \frac{{z}^{2} \cdot {\sin y}^{2}}{x}}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos \color{blue}{y}} \]
11. Step-by-step derivation

    1. lower-fma.f64 N/A

       \[\leadsto \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{z}^{2} \cdot {\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

    2. lower-*.f64 N/A

       \[\leadsto \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{z}^{2} \cdot {\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

    3. lift-pow.f64 N/A

       \[\leadsto \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{z}^{2} \cdot {\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

    4. lift-cos.f64 N/A

       \[\leadsto \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{z}^{2} \cdot {\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

    5. lower-/.f64 N/A

       \[\leadsto \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{z}^{2} \cdot {\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

    6. unpow-prod-down N/A

       \[\leadsto \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{\left(z \cdot \sin y\right)}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

    7. lift-sin.f64 N/A

       \[\leadsto \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{\left(z \cdot \sin y\right)}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

    8. lift-*.f64 N/A

       \[\leadsto \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{\left(z \cdot \sin y\right)}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

    9. lift-pow.f64 76.9

       \[\leadsto \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{\left(z \cdot \sin y\right)}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

12. Applied rewrites 76.9%

    \[\leadsto \frac{\mathsf{fma}\left(-1, x \cdot {\cos y}^{2}, \frac{{\left(z \cdot \sin y\right)}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos \color{blue}{y}} \]
13. Add Preprocessing

Alternative 6: 63.0% accurate, N/A× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := {\cos y}^{2}\\ t_1 := z \cdot \sin y\\ t_2 := \frac{x \cdot \mathsf{fma}\left(-1, \frac{{t\_1}^{3}}{{x}^{3}}, {\cos y}^{3}\right)}{\left(\frac{{t\_1}^{2}}{x \cdot x} + t\_0\right) - -1 \cdot \frac{z \cdot \left(\cos y \cdot \sin y\right)}{x}}\\ \mathbf{if}\;x \leq -3.6 \cdot 10^{-108}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;x \leq 3 \cdot 10^{-119}:\\ \;\;\;\;\frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot t\_0}{z \cdot z}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{t\_1}{x} - \cos y}\\ \mathbf{else}:\\ \;\;\;\;t\_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (pow (cos y) 2.0))
        (t_1 (* z (sin y)))
        (t_2
         (/
          (* x (fma -1.0 (/ (pow t_1 3.0) (pow x 3.0)) (pow (cos y) 3.0)))
          (-
           (+ (/ (pow t_1 2.0) (* x x)) t_0)
           (* -1.0 (/ (* z (* (cos y) (sin y))) x))))))
   (if (<= x -3.6e-108)
     t_2
     (if (<= x 3e-119)
       (/
        (* (* z z) (fma -1.0 (/ (* x t_0) (* z z)) (/ (pow (sin y) 2.0) x)))
        (- (* -1.0 (/ t_1 x)) (cos y)))
       t_2))))

C

double code(double x, double y, double z) {
	double t_0 = pow(cos(y), 2.0);
	double t_1 = z * sin(y);
	double t_2 = (x * fma(-1.0, (pow(t_1, 3.0) / pow(x, 3.0)), pow(cos(y), 3.0))) / (((pow(t_1, 2.0) / (x * x)) + t_0) - (-1.0 * ((z * (cos(y) * sin(y))) / x)));
	double tmp;
	if (x <= -3.6e-108) {
		tmp = t_2;
	} else if (x <= 3e-119) {
		tmp = ((z * z) * fma(-1.0, ((x * t_0) / (z * z)), (pow(sin(y), 2.0) / x))) / ((-1.0 * (t_1 / x)) - cos(y));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Julia

function code(x, y, z)
	t_0 = cos(y) ^ 2.0
	t_1 = Float64(z * sin(y))
	t_2 = Float64(Float64(x * fma(-1.0, Float64((t_1 ^ 3.0) / (x ^ 3.0)), (cos(y) ^ 3.0))) / Float64(Float64(Float64((t_1 ^ 2.0) / Float64(x * x)) + t_0) - Float64(-1.0 * Float64(Float64(z * Float64(cos(y) * sin(y))) / x))))
	tmp = 0.0
	if (x <= -3.6e-108)
		tmp = t_2;
	elseif (x <= 3e-119)
		tmp = Float64(Float64(Float64(z * z) * fma(-1.0, Float64(Float64(x * t_0) / Float64(z * z)), Float64((sin(y) ^ 2.0) / x))) / Float64(Float64(-1.0 * Float64(t_1 / x)) - cos(y)));
	else
		tmp = t_2;
	end
	return tmp
end

Wolfram

code[x_, y_, z_] := Block[{t$95$0 = N[Power[N[Cos[y], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(z * N[Sin[y], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * N[(-1.0 * N[(N[Power[t$95$1, 3.0], $MachinePrecision] / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Cos[y], $MachinePrecision], 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(N[Power[t$95$1, 2.0], $MachinePrecision] / N[(x * x), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision] - N[(-1.0 * N[(N[(z * N[(N[Cos[y], $MachinePrecision] * N[Sin[y], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -3.6e-108], t$95$2, If[LessEqual[x, 3e-119], N[(N[(N[(z * z), $MachinePrecision] * N[(-1.0 * N[(N[(x * t$95$0), $MachinePrecision] / N[(z * z), $MachinePrecision]), $MachinePrecision] + N[(N[Power[N[Sin[y], $MachinePrecision], 2.0], $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(-1.0 * N[(t$95$1 / x), $MachinePrecision]), $MachinePrecision] - N[Cos[y], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]

Derivation

1. Split input into 2 regimes

2. if x < -3.6000000000000001e-108 or 3.0000000000000002e-119 < x

   1. Initial program 99.8%

      \[x \cdot \cos y - z \cdot \sin y \]

   2. Taylor expanded in x around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. +-commutative N/A

         \[\leadsto \left(-1 \cdot \frac{z \cdot \sin y}{x} + \cos y\right) \cdot x \]

      4. *-commutative N/A

         \[\leadsto \left(\frac{z \cdot \sin y}{x} \cdot -1 + \cos y\right) \cdot x \]

      5. lower-fma.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

      6. lower-/.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

      7. *-commutative N/A

         \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

      8. lower-*.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

      9. lift-sin.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

      10. lift-cos.f64 98.6

          \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   4. Applied rewrites 98.6%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x} \]
   5. Step-by-step derivation

      1. lift-cos.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

      2. lift-fma.f64 N/A

         \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

      3. lift-/.f64 N/A

         \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

      4. lift-*.f64 N/A

         \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

      5. lift-sin.f64 N/A

         \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

      6. flip3-+ N/A

         \[\leadsto \frac{{\left(\frac{\sin y \cdot z}{x} \cdot -1\right)}^{3} + {\cos y}^{3}}{\left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \left(\frac{\sin y \cdot z}{x} \cdot -1\right) + \left(\cos y \cdot \cos y - \left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \cos y\right)} \cdot x \]

      7. lower-/.f64 N/A

         \[\leadsto \frac{{\left(\frac{\sin y \cdot z}{x} \cdot -1\right)}^{3} + {\cos y}^{3}}{\left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \left(\frac{\sin y \cdot z}{x} \cdot -1\right) + \left(\cos y \cdot \cos y - \left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \cos y\right)} \cdot x \]

   6. Applied rewrites 87.1%

      \[\leadsto \frac{{\left(\frac{\sin y \cdot z}{x} \cdot -1\right)}^{3} + {\cos y}^{3}}{\mathsf{fma}\left(\frac{\sin y \cdot z}{x} \cdot -1, \frac{\sin y \cdot z}{x} \cdot -1, {\cos y}^{2} - \left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \cos y\right)} \cdot x \]

   7. Taylor expanded in y around inf

      \[\leadsto \frac{x \cdot \left(-1 \cdot \frac{{z}^{3} \cdot {\sin y}^{3}}{{x}^{3}} + {\cos y}^{3}\right)}{\color{blue}{\left(\frac{{z}^{2} \cdot {\sin y}^{2}}{{x}^{2}} + {\cos y}^{2}\right) - -1 \cdot \frac{z \cdot \left(\cos y \cdot \sin y\right)}{x}}} \]
   8. Step-by-step derivation

      1. lower-/.f64 N/A

         \[\leadsto \frac{x \cdot \left(-1 \cdot \frac{{z}^{3} \cdot {\sin y}^{3}}{{x}^{3}} + {\cos y}^{3}\right)}{\left(\frac{{z}^{2} \cdot {\sin y}^{2}}{{x}^{2}} + {\cos y}^{2}\right) - \color{blue}{-1 \cdot \frac{z \cdot \left(\cos y \cdot \sin y\right)}{x}}} \]

   9. Applied rewrites 75.9%

      \[\leadsto \frac{x \cdot \mathsf{fma}\left(-1, \frac{{\left(z \cdot \sin y\right)}^{3}}{{x}^{3}}, {\cos y}^{3}\right)}{\color{blue}{\left(\frac{{\left(z \cdot \sin y\right)}^{2}}{x \cdot x} + {\cos y}^{2}\right) - -1 \cdot \frac{z \cdot \left(\cos y \cdot \sin y\right)}{x}}} \]

   if -3.6000000000000001e-108 < x < 3.0000000000000002e-119

   1. Initial program 99.8%

      \[x \cdot \cos y - z \cdot \sin y \]

   2. Taylor expanded in x around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. +-commutative N/A

         \[\leadsto \left(-1 \cdot \frac{z \cdot \sin y}{x} + \cos y\right) \cdot x \]

      4. *-commutative N/A

         \[\leadsto \left(\frac{z \cdot \sin y}{x} \cdot -1 + \cos y\right) \cdot x \]

      5. lower-fma.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

      6. lower-/.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

      7. *-commutative N/A

         \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

      8. lower-*.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

      9. lift-sin.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

      10. lift-cos.f64 76.0

          \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   4. Applied rewrites 76.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x} \]
   5. Step-by-step derivation

      1. lift-cos.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

      2. lift-fma.f64 N/A

         \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

      3. lift-/.f64 N/A

         \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

      4. lift-*.f64 N/A

         \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

      5. lift-sin.f64 N/A

         \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

      6. flip-+ N/A

         \[\leadsto \frac{\left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \left(\frac{\sin y \cdot z}{x} \cdot -1\right) - \cos y \cdot \cos y}{\frac{\sin y \cdot z}{x} \cdot -1 - \cos y} \cdot x \]

      7. lower-/.f64 N/A

         \[\leadsto \frac{\left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \left(\frac{\sin y \cdot z}{x} \cdot -1\right) - \cos y \cdot \cos y}{\frac{\sin y \cdot z}{x} \cdot -1 - \cos y} \cdot x \]

   6. Applied rewrites 51.8%

      \[\leadsto \frac{\left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \left(\frac{\sin y \cdot z}{x} \cdot -1\right) - {\cos y}^{2}}{\frac{\sin y \cdot z}{x} \cdot -1 - \cos y} \cdot x \]

   7. Taylor expanded in y around inf

      \[\leadsto \frac{x \cdot \left(\frac{{z}^{2} \cdot {\sin y}^{2}}{{x}^{2}} - {\cos y}^{2}\right)}{\color{blue}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y}} \]
   8. Step-by-step derivation

      1. lower-/.f64 N/A

         \[\leadsto \frac{x \cdot \left(\frac{{z}^{2} \cdot {\sin y}^{2}}{{x}^{2}} - {\cos y}^{2}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \color{blue}{\cos y}} \]

   9. Applied rewrites 15.1%

      \[\leadsto \frac{x \cdot \left(\frac{{\left(z \cdot \sin y\right)}^{2}}{x \cdot x} - {\cos y}^{2}\right)}{\color{blue}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y}} \]

   10. Taylor expanded in z around inf

       \[\leadsto \frac{{z}^{2} \cdot \left(-1 \cdot \frac{x \cdot {\cos y}^{2}}{{z}^{2}} + \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos \color{blue}{y}} \]
   11. Step-by-step derivation

       1. lower-*.f64 N/A

          \[\leadsto \frac{{z}^{2} \cdot \left(-1 \cdot \frac{x \cdot {\cos y}^{2}}{{z}^{2}} + \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       2. unpow2 N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot \left(-1 \cdot \frac{x \cdot {\cos y}^{2}}{{z}^{2}} + \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       3. lower-*.f64 N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot \left(-1 \cdot \frac{x \cdot {\cos y}^{2}}{{z}^{2}} + \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       4. lower-fma.f64 N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{{z}^{2}}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       5. lower-/.f64 N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{{z}^{2}}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       6. lower-*.f64 N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{{z}^{2}}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       7. lift-pow.f64 N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{{z}^{2}}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       8. lift-cos.f64 N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{{z}^{2}}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       9. unpow2 N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{z \cdot z}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       10. lower-*.f64 N/A

           \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{z \cdot z}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       11. lower-/.f64 N/A

           \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{z \cdot z}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       12. lower-pow.f64 N/A

           \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{z \cdot z}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

       13. lift-sin.f64 35.0

           \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{z \cdot z}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos y} \]

   12. Applied rewrites 35.0%

       \[\leadsto \frac{\left(z \cdot z\right) \cdot \mathsf{fma}\left(-1, \frac{x \cdot {\cos y}^{2}}{z \cdot z}, \frac{{\sin y}^{2}}{x}\right)}{-1 \cdot \frac{z \cdot \sin y}{x} - \cos \color{blue}{y}} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 7: 52.0% accurate, N/A× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := z \cdot \sin y\\ \frac{x \cdot \mathsf{fma}\left(-1, \frac{{t\_0}^{3}}{{x}^{3}}, {\cos y}^{3}\right)}{\left(\frac{{t\_0}^{2}}{x \cdot x} + {\cos y}^{2}\right) - -1 \cdot \frac{z \cdot \left(\cos y \cdot \sin y\right)}{x}} \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (* z (sin y))))
   (/
    (* x (fma -1.0 (/ (pow t_0 3.0) (pow x 3.0)) (pow (cos y) 3.0)))
    (-
     (+ (/ (pow t_0 2.0) (* x x)) (pow (cos y) 2.0))
     (* -1.0 (/ (* z (* (cos y) (sin y))) x))))))

C

double code(double x, double y, double z) {
	double t_0 = z * sin(y);
	return (x * fma(-1.0, (pow(t_0, 3.0) / pow(x, 3.0)), pow(cos(y), 3.0))) / (((pow(t_0, 2.0) / (x * x)) + pow(cos(y), 2.0)) - (-1.0 * ((z * (cos(y) * sin(y))) / x)));
}

Julia

function code(x, y, z)
	t_0 = Float64(z * sin(y))
	return Float64(Float64(x * fma(-1.0, Float64((t_0 ^ 3.0) / (x ^ 3.0)), (cos(y) ^ 3.0))) / Float64(Float64(Float64((t_0 ^ 2.0) / Float64(x * x)) + (cos(y) ^ 2.0)) - Float64(-1.0 * Float64(Float64(z * Float64(cos(y) * sin(y))) / x))))
end

Wolfram

code[x_, y_, z_] := Block[{t$95$0 = N[(z * N[Sin[y], $MachinePrecision]), $MachinePrecision]}, N[(N[(x * N[(-1.0 * N[(N[Power[t$95$0, 3.0], $MachinePrecision] / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Cos[y], $MachinePrecision], 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(N[Power[t$95$0, 2.0], $MachinePrecision] / N[(x * x), $MachinePrecision]), $MachinePrecision] + N[Power[N[Cos[y], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(-1.0 * N[(N[(z * N[(N[Cos[y], $MachinePrecision] * N[Sin[y], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Initial program 99.8%

   \[x \cdot \cos y - z \cdot \sin y \]

2. Taylor expanded in x around inf

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

   1. *-commutative N/A

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

   2. lower-*.f64 N/A

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

   3. +-commutative N/A

      \[\leadsto \left(-1 \cdot \frac{z \cdot \sin y}{x} + \cos y\right) \cdot x \]

   4. *-commutative N/A

      \[\leadsto \left(\frac{z \cdot \sin y}{x} \cdot -1 + \cos y\right) \cdot x \]

   5. lower-fma.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

   6. lower-/.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{z \cdot \sin y}{x}, -1, \cos y\right) \cdot x \]

   7. *-commutative N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   8. lower-*.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   9. lift-sin.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   10. lift-cos.f64 91.5

       \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

4. Applied rewrites 91.5%

   \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x} \]
5. Step-by-step derivation

   1. lift-cos.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\sin y \cdot z}{x}, -1, \cos y\right) \cdot x \]

   2. lift-fma.f64 N/A

      \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

   3. lift-/.f64 N/A

      \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

   4. lift-*.f64 N/A

      \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

   5. lift-sin.f64 N/A

      \[\leadsto \left(\frac{\sin y \cdot z}{x} \cdot -1 + \cos y\right) \cdot x \]

   6. flip3-+ N/A

      \[\leadsto \frac{{\left(\frac{\sin y \cdot z}{x} \cdot -1\right)}^{3} + {\cos y}^{3}}{\left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \left(\frac{\sin y \cdot z}{x} \cdot -1\right) + \left(\cos y \cdot \cos y - \left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \cos y\right)} \cdot x \]

   7. lower-/.f64 N/A

      \[\leadsto \frac{{\left(\frac{\sin y \cdot z}{x} \cdot -1\right)}^{3} + {\cos y}^{3}}{\left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \left(\frac{\sin y \cdot z}{x} \cdot -1\right) + \left(\cos y \cdot \cos y - \left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \cos y\right)} \cdot x \]

6. Applied rewrites 73.5%

   \[\leadsto \frac{{\left(\frac{\sin y \cdot z}{x} \cdot -1\right)}^{3} + {\cos y}^{3}}{\mathsf{fma}\left(\frac{\sin y \cdot z}{x} \cdot -1, \frac{\sin y \cdot z}{x} \cdot -1, {\cos y}^{2} - \left(\frac{\sin y \cdot z}{x} \cdot -1\right) \cdot \cos y\right)} \cdot x \]

7. Taylor expanded in y around inf

   \[\leadsto \frac{x \cdot \left(-1 \cdot \frac{{z}^{3} \cdot {\sin y}^{3}}{{x}^{3}} + {\cos y}^{3}\right)}{\color{blue}{\left(\frac{{z}^{2} \cdot {\sin y}^{2}}{{x}^{2}} + {\cos y}^{2}\right) - -1 \cdot \frac{z \cdot \left(\cos y \cdot \sin y\right)}{x}}} \]
8. Step-by-step derivation

   1. lower-/.f64 N/A

      \[\leadsto \frac{x \cdot \left(-1 \cdot \frac{{z}^{3} \cdot {\sin y}^{3}}{{x}^{3}} + {\cos y}^{3}\right)}{\left(\frac{{z}^{2} \cdot {\sin y}^{2}}{{x}^{2}} + {\cos y}^{2}\right) - \color{blue}{-1 \cdot \frac{z \cdot \left(\cos y \cdot \sin y\right)}{x}}} \]

9. Applied rewrites 52.0%

   \[\leadsto \frac{x \cdot \mathsf{fma}\left(-1, \frac{{\left(z \cdot \sin y\right)}^{3}}{{x}^{3}}, {\cos y}^{3}\right)}{\color{blue}{\left(\frac{{\left(z \cdot \sin y\right)}^{2}}{x \cdot x} + {\cos y}^{2}\right) - -1 \cdot \frac{z \cdot \left(\cos y \cdot \sin y\right)}{x}}} \]
10. Add Preprocessing

Reproduce

herbie shell --seed 2025093 
(FPCore (x y z)
  :name "Diagrams.ThreeD.Transform:aboutX from diagrams-lib-1.3.0.3, A"
  :precision binary64
  (- (* x (cos y)) (* z (sin y))))