Curve intersection, scale width based on ribbon orientation

Percentage Accurate: 97.1% → 99.4%
Time: 4.8s
Alternatives: 13
Speedup: 19.0×

Specification

?
\[\left(\left(\left(0 \leq normAngle \land normAngle \leq \frac{\pi}{2}\right) \land \left(-1 \leq n0\_i \land n0\_i \leq 1\right)\right) \land \left(-1 \leq n1\_i \land n1\_i \leq 1\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq u \land u \leq 1\right)\]
\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{1}{\sin normAngle}\\ \left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot t\_0\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot t\_0\right) \cdot n1\_i \end{array} \end{array} \]
(FPCore (normAngle u n0_i n1_i)
 :precision binary32
 (let* ((t_0 (/ 1.0 (sin normAngle))))
   (+
    (* (* (sin (* (- 1.0 u) normAngle)) t_0) n0_i)
    (* (* (sin (* u normAngle)) t_0) n1_i))))
float code(float normAngle, float u, float n0_i, float n1_i) {
	float t_0 = 1.0f / sinf(normAngle);
	return ((sinf(((1.0f - u) * normAngle)) * t_0) * n0_i) + ((sinf((u * normAngle)) * t_0) * n1_i);
}
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(4) function code(normangle, u, n0_i, n1_i)
use fmin_fmax_functions
    real(4), intent (in) :: normangle
    real(4), intent (in) :: u
    real(4), intent (in) :: n0_i
    real(4), intent (in) :: n1_i
    real(4) :: t_0
    t_0 = 1.0e0 / sin(normangle)
    code = ((sin(((1.0e0 - u) * normangle)) * t_0) * n0_i) + ((sin((u * normangle)) * t_0) * n1_i)
end function
function code(normAngle, u, n0_i, n1_i)
	t_0 = Float32(Float32(1.0) / sin(normAngle))
	return Float32(Float32(Float32(sin(Float32(Float32(Float32(1.0) - u) * normAngle)) * t_0) * n0_i) + Float32(Float32(sin(Float32(u * normAngle)) * t_0) * n1_i))
end
function tmp = code(normAngle, u, n0_i, n1_i)
	t_0 = single(1.0) / sin(normAngle);
	tmp = ((sin(((single(1.0) - u) * normAngle)) * t_0) * n0_i) + ((sin((u * normAngle)) * t_0) * n1_i);
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \frac{1}{\sin normAngle}\\
\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot t\_0\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot t\_0\right) \cdot n1\_i
\end{array}
\end{array}

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 13 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 97.1% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{1}{\sin normAngle}\\ \left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot t\_0\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot t\_0\right) \cdot n1\_i \end{array} \end{array} \]
(FPCore (normAngle u n0_i n1_i)
 :precision binary32
 (let* ((t_0 (/ 1.0 (sin normAngle))))
   (+
    (* (* (sin (* (- 1.0 u) normAngle)) t_0) n0_i)
    (* (* (sin (* u normAngle)) t_0) n1_i))))
float code(float normAngle, float u, float n0_i, float n1_i) {
	float t_0 = 1.0f / sinf(normAngle);
	return ((sinf(((1.0f - u) * normAngle)) * t_0) * n0_i) + ((sinf((u * normAngle)) * t_0) * n1_i);
}
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(4) function code(normangle, u, n0_i, n1_i)
use fmin_fmax_functions
    real(4), intent (in) :: normangle
    real(4), intent (in) :: u
    real(4), intent (in) :: n0_i
    real(4), intent (in) :: n1_i
    real(4) :: t_0
    t_0 = 1.0e0 / sin(normangle)
    code = ((sin(((1.0e0 - u) * normangle)) * t_0) * n0_i) + ((sin((u * normangle)) * t_0) * n1_i)
end function
function code(normAngle, u, n0_i, n1_i)
	t_0 = Float32(Float32(1.0) / sin(normAngle))
	return Float32(Float32(Float32(sin(Float32(Float32(Float32(1.0) - u) * normAngle)) * t_0) * n0_i) + Float32(Float32(sin(Float32(u * normAngle)) * t_0) * n1_i))
end
function tmp = code(normAngle, u, n0_i, n1_i)
	t_0 = single(1.0) / sin(normAngle);
	tmp = ((sin(((single(1.0) - u) * normAngle)) * t_0) * n0_i) + ((sin((u * normAngle)) * t_0) * n1_i);
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \frac{1}{\sin normAngle}\\
\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot t\_0\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot t\_0\right) \cdot n1\_i
\end{array}
\end{array}

Alternative 1: 99.4% accurate, 2.8× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\sin normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \end{array} \]
(FPCore (normAngle u n0_i n1_i)
 :precision binary32
 (fma
  (fma
   (/ normAngle (sin normAngle))
   n1_i
   (- (* 0.3333333333333333 (* (* normAngle normAngle) n0_i)) n0_i))
  u
  n0_i))
float code(float normAngle, float u, float n0_i, float n1_i) {
	return fmaf(fmaf((normAngle / sinf(normAngle)), n1_i, ((0.3333333333333333f * ((normAngle * normAngle) * n0_i)) - n0_i)), u, n0_i);
}
function code(normAngle, u, n0_i, n1_i)
	return fma(fma(Float32(normAngle / sin(normAngle)), n1_i, Float32(Float32(Float32(0.3333333333333333) * Float32(Float32(normAngle * normAngle) * n0_i)) - n0_i)), u, n0_i)
end
\begin{array}{l}

\\
\mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\sin normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right)
\end{array}
Derivation
  1. Initial program 97.1%

    \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
  2. Taylor expanded in u around 0

    \[\leadsto \color{blue}{n0\_i + u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right)} \]
  3. Step-by-step derivation
    1. +-commutativeN/A

      \[\leadsto u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) + \color{blue}{n0\_i} \]
    2. *-commutativeN/A

      \[\leadsto \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) \cdot u + n0\_i \]
    3. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}, \color{blue}{u}, n0\_i\right) \]
  4. Applied rewrites94.8%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, -\frac{\left(n0\_i \cdot normAngle\right) \cdot \cos normAngle}{\sin normAngle}\right), u, n0\_i\right)} \]
  5. Taylor expanded in normAngle around 0

    \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
  6. Step-by-step derivation
    1. lower--.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
    2. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
    3. pow2N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
    4. lift-*.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
    5. lower--.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
    6. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
    7. lower-*.f3299.4

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
  7. Applied rewrites99.4%

    \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
  8. Step-by-step derivation
    1. Applied rewrites99.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\sin normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right)} \]
    2. Add Preprocessing

    Alternative 2: 99.3% accurate, 3.0× speedup?

    \[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(\mathsf{fma}\left(-0.0001984126984126984, normAngle \cdot normAngle, 0.008333333333333333\right) \cdot \left(normAngle \cdot normAngle\right) - 0.16666666666666666, normAngle \cdot normAngle, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \end{array} \]
    (FPCore (normAngle u n0_i n1_i)
     :precision binary32
     (fma
      (fma
       (/
        normAngle
        (*
         (fma
          (-
           (*
            (fma
             -0.0001984126984126984
             (* normAngle normAngle)
             0.008333333333333333)
            (* normAngle normAngle))
           0.16666666666666666)
          (* normAngle normAngle)
          1.0)
         normAngle))
       n1_i
       (- (* 0.3333333333333333 (* (* normAngle normAngle) n0_i)) n0_i))
      u
      n0_i))
    float code(float normAngle, float u, float n0_i, float n1_i) {
    	return fmaf(fmaf((normAngle / (fmaf(((fmaf(-0.0001984126984126984f, (normAngle * normAngle), 0.008333333333333333f) * (normAngle * normAngle)) - 0.16666666666666666f), (normAngle * normAngle), 1.0f) * normAngle)), n1_i, ((0.3333333333333333f * ((normAngle * normAngle) * n0_i)) - n0_i)), u, n0_i);
    }
    
    function code(normAngle, u, n0_i, n1_i)
    	return fma(fma(Float32(normAngle / Float32(fma(Float32(Float32(fma(Float32(-0.0001984126984126984), Float32(normAngle * normAngle), Float32(0.008333333333333333)) * Float32(normAngle * normAngle)) - Float32(0.16666666666666666)), Float32(normAngle * normAngle), Float32(1.0)) * normAngle)), n1_i, Float32(Float32(Float32(0.3333333333333333) * Float32(Float32(normAngle * normAngle) * n0_i)) - n0_i)), u, n0_i)
    end
    
    \begin{array}{l}
    
    \\
    \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(\mathsf{fma}\left(-0.0001984126984126984, normAngle \cdot normAngle, 0.008333333333333333\right) \cdot \left(normAngle \cdot normAngle\right) - 0.16666666666666666, normAngle \cdot normAngle, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right)
    \end{array}
    
    Derivation
    1. Initial program 97.1%

      \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
    2. Taylor expanded in u around 0

      \[\leadsto \color{blue}{n0\_i + u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right)} \]
    3. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) + \color{blue}{n0\_i} \]
      2. *-commutativeN/A

        \[\leadsto \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) \cdot u + n0\_i \]
      3. lower-fma.f32N/A

        \[\leadsto \mathsf{fma}\left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}, \color{blue}{u}, n0\_i\right) \]
    4. Applied rewrites94.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, -\frac{\left(n0\_i \cdot normAngle\right) \cdot \cos normAngle}{\sin normAngle}\right), u, n0\_i\right)} \]
    5. Taylor expanded in normAngle around 0

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
    6. Step-by-step derivation
      1. lower--.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      2. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      3. pow2N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      4. lift-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      5. lower--.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      6. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      7. lower-*.f3299.4

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
    7. Applied rewrites99.4%

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
    8. Step-by-step derivation
      1. Applied rewrites99.4%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\sin normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right)} \]
      2. Taylor expanded in normAngle around 0

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{normAngle \cdot \left(1 + {normAngle}^{2} \cdot \left({normAngle}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {normAngle}^{2}\right) - \frac{1}{6}\right)\right)}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      3. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\left(1 + {normAngle}^{2} \cdot \left({normAngle}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {normAngle}^{2}\right) - \frac{1}{6}\right)\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        2. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\left(1 + {normAngle}^{2} \cdot \left({normAngle}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {normAngle}^{2}\right) - \frac{1}{6}\right)\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      4. Applied rewrites99.3%

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(\mathsf{fma}\left(-0.0001984126984126984, normAngle \cdot normAngle, 0.008333333333333333\right) \cdot \left(normAngle \cdot normAngle\right) - 0.16666666666666666, normAngle \cdot normAngle, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      5. Add Preprocessing

      Alternative 3: 99.3% accurate, 3.5× speedup?

      \[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.00205026455026455, 0.019444444444444445\right), normAngle \cdot normAngle, 0.16666666666666666\right) \cdot normAngle, normAngle, 1\right), n1\_i, \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) \cdot 0.3333333333333333 - n0\_i\right), u, n0\_i\right) \end{array} \]
      (FPCore (normAngle u n0_i n1_i)
       :precision binary32
       (fma
        (fma
         (fma
          (*
           (fma
            (fma (* normAngle normAngle) 0.00205026455026455 0.019444444444444445)
            (* normAngle normAngle)
            0.16666666666666666)
           normAngle)
          normAngle
          1.0)
         n1_i
         (- (* (* (* normAngle normAngle) n0_i) 0.3333333333333333) n0_i))
        u
        n0_i))
      float code(float normAngle, float u, float n0_i, float n1_i) {
      	return fmaf(fmaf(fmaf((fmaf(fmaf((normAngle * normAngle), 0.00205026455026455f, 0.019444444444444445f), (normAngle * normAngle), 0.16666666666666666f) * normAngle), normAngle, 1.0f), n1_i, ((((normAngle * normAngle) * n0_i) * 0.3333333333333333f) - n0_i)), u, n0_i);
      }
      
      function code(normAngle, u, n0_i, n1_i)
      	return fma(fma(fma(Float32(fma(fma(Float32(normAngle * normAngle), Float32(0.00205026455026455), Float32(0.019444444444444445)), Float32(normAngle * normAngle), Float32(0.16666666666666666)) * normAngle), normAngle, Float32(1.0)), n1_i, Float32(Float32(Float32(Float32(normAngle * normAngle) * n0_i) * Float32(0.3333333333333333)) - n0_i)), u, n0_i)
      end
      
      \begin{array}{l}
      
      \\
      \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.00205026455026455, 0.019444444444444445\right), normAngle \cdot normAngle, 0.16666666666666666\right) \cdot normAngle, normAngle, 1\right), n1\_i, \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) \cdot 0.3333333333333333 - n0\_i\right), u, n0\_i\right)
      \end{array}
      
      Derivation
      1. Initial program 97.1%

        \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
      2. Taylor expanded in u around 0

        \[\leadsto \color{blue}{n0\_i + u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right)} \]
      3. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) + \color{blue}{n0\_i} \]
        2. *-commutativeN/A

          \[\leadsto \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) \cdot u + n0\_i \]
        3. lower-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}, \color{blue}{u}, n0\_i\right) \]
      4. Applied rewrites94.8%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, -\frac{\left(n0\_i \cdot normAngle\right) \cdot \cos normAngle}{\sin normAngle}\right), u, n0\_i\right)} \]
      5. Taylor expanded in normAngle around 0

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      6. Step-by-step derivation
        1. lower--.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        2. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        3. pow2N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        4. lift-*.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        5. lower--.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        6. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        7. lower-*.f3299.4

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      7. Applied rewrites99.4%

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      8. Taylor expanded in normAngle around 0

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, 1 + {normAngle}^{2} \cdot \left(\frac{1}{6} + {normAngle}^{2} \cdot \left(\frac{7}{360} + \frac{31}{15120} \cdot {normAngle}^{2}\right)\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      9. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, {normAngle}^{2} \cdot \left(\frac{1}{6} + {normAngle}^{2} \cdot \left(\frac{7}{360} + \frac{31}{15120} \cdot {normAngle}^{2}\right)\right) + 1, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        2. *-commutativeN/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \left(\frac{1}{6} + {normAngle}^{2} \cdot \left(\frac{7}{360} + \frac{31}{15120} \cdot {normAngle}^{2}\right)\right) \cdot {normAngle}^{2} + 1, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        3. lower-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\frac{1}{6} + {normAngle}^{2} \cdot \left(\frac{7}{360} + \frac{31}{15120} \cdot {normAngle}^{2}\right), {normAngle}^{2}, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        4. +-commutativeN/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left({normAngle}^{2} \cdot \left(\frac{7}{360} + \frac{31}{15120} \cdot {normAngle}^{2}\right) + \frac{1}{6}, {normAngle}^{2}, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        5. *-commutativeN/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\left(\frac{7}{360} + \frac{31}{15120} \cdot {normAngle}^{2}\right) \cdot {normAngle}^{2} + \frac{1}{6}, {normAngle}^{2}, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        6. lower-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\mathsf{fma}\left(\frac{7}{360} + \frac{31}{15120} \cdot {normAngle}^{2}, {normAngle}^{2}, \frac{1}{6}\right), {normAngle}^{2}, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        7. +-commutativeN/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\mathsf{fma}\left(\frac{31}{15120} \cdot {normAngle}^{2} + \frac{7}{360}, {normAngle}^{2}, \frac{1}{6}\right), {normAngle}^{2}, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        8. lower-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{31}{15120}, {normAngle}^{2}, \frac{7}{360}\right), {normAngle}^{2}, \frac{1}{6}\right), {normAngle}^{2}, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        9. pow2N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{31}{15120}, normAngle \cdot normAngle, \frac{7}{360}\right), {normAngle}^{2}, \frac{1}{6}\right), {normAngle}^{2}, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        10. lift-*.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{31}{15120}, normAngle \cdot normAngle, \frac{7}{360}\right), {normAngle}^{2}, \frac{1}{6}\right), {normAngle}^{2}, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        11. pow2N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{31}{15120}, normAngle \cdot normAngle, \frac{7}{360}\right), normAngle \cdot normAngle, \frac{1}{6}\right), {normAngle}^{2}, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        12. lift-*.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{31}{15120}, normAngle \cdot normAngle, \frac{7}{360}\right), normAngle \cdot normAngle, \frac{1}{6}\right), {normAngle}^{2}, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        13. pow2N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{31}{15120}, normAngle \cdot normAngle, \frac{7}{360}\right), normAngle \cdot normAngle, \frac{1}{6}\right), normAngle \cdot normAngle, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        14. lift-*.f3299.3

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.00205026455026455, normAngle \cdot normAngle, 0.019444444444444445\right), normAngle \cdot normAngle, 0.16666666666666666\right), normAngle \cdot normAngle, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      10. Applied rewrites99.3%

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.00205026455026455, normAngle \cdot normAngle, 0.019444444444444445\right), normAngle \cdot normAngle, 0.16666666666666666\right), normAngle \cdot normAngle, 1\right), \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      11. Applied rewrites99.3%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.00205026455026455, 0.019444444444444445\right), normAngle \cdot normAngle, 0.16666666666666666\right) \cdot normAngle, normAngle, 1\right), n1\_i, \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) \cdot 0.3333333333333333 - n0\_i\right), u, n0\_i\right)} \]
      12. Add Preprocessing

      Alternative 4: 99.3% accurate, 3.5× speedup?

      \[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(0.008333333333333333 \cdot \left(normAngle \cdot normAngle\right) - 0.16666666666666666, normAngle \cdot normAngle, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \end{array} \]
      (FPCore (normAngle u n0_i n1_i)
       :precision binary32
       (fma
        (fma
         (/
          normAngle
          (*
           (fma
            (- (* 0.008333333333333333 (* normAngle normAngle)) 0.16666666666666666)
            (* normAngle normAngle)
            1.0)
           normAngle))
         n1_i
         (- (* 0.3333333333333333 (* (* normAngle normAngle) n0_i)) n0_i))
        u
        n0_i))
      float code(float normAngle, float u, float n0_i, float n1_i) {
      	return fmaf(fmaf((normAngle / (fmaf(((0.008333333333333333f * (normAngle * normAngle)) - 0.16666666666666666f), (normAngle * normAngle), 1.0f) * normAngle)), n1_i, ((0.3333333333333333f * ((normAngle * normAngle) * n0_i)) - n0_i)), u, n0_i);
      }
      
      function code(normAngle, u, n0_i, n1_i)
      	return fma(fma(Float32(normAngle / Float32(fma(Float32(Float32(Float32(0.008333333333333333) * Float32(normAngle * normAngle)) - Float32(0.16666666666666666)), Float32(normAngle * normAngle), Float32(1.0)) * normAngle)), n1_i, Float32(Float32(Float32(0.3333333333333333) * Float32(Float32(normAngle * normAngle) * n0_i)) - n0_i)), u, n0_i)
      end
      
      \begin{array}{l}
      
      \\
      \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(0.008333333333333333 \cdot \left(normAngle \cdot normAngle\right) - 0.16666666666666666, normAngle \cdot normAngle, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right)
      \end{array}
      
      Derivation
      1. Initial program 97.1%

        \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
      2. Taylor expanded in u around 0

        \[\leadsto \color{blue}{n0\_i + u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right)} \]
      3. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) + \color{blue}{n0\_i} \]
        2. *-commutativeN/A

          \[\leadsto \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) \cdot u + n0\_i \]
        3. lower-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}, \color{blue}{u}, n0\_i\right) \]
      4. Applied rewrites94.8%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, -\frac{\left(n0\_i \cdot normAngle\right) \cdot \cos normAngle}{\sin normAngle}\right), u, n0\_i\right)} \]
      5. Taylor expanded in normAngle around 0

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      6. Step-by-step derivation
        1. lower--.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        2. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        3. pow2N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        4. lift-*.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        5. lower--.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        6. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        7. lower-*.f3299.4

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      7. Applied rewrites99.4%

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
      8. Step-by-step derivation
        1. Applied rewrites99.4%

          \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\sin normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right)} \]
        2. Taylor expanded in normAngle around 0

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{normAngle \cdot \left(1 + {normAngle}^{2} \cdot \left(\frac{1}{120} \cdot {normAngle}^{2} - \frac{1}{6}\right)\right)}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        3. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\left(1 + {normAngle}^{2} \cdot \left(\frac{1}{120} \cdot {normAngle}^{2} - \frac{1}{6}\right)\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          2. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\left(1 + {normAngle}^{2} \cdot \left(\frac{1}{120} \cdot {normAngle}^{2} - \frac{1}{6}\right)\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          3. +-commutativeN/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\left({normAngle}^{2} \cdot \left(\frac{1}{120} \cdot {normAngle}^{2} - \frac{1}{6}\right) + 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          4. *-commutativeN/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\left(\left(\frac{1}{120} \cdot {normAngle}^{2} - \frac{1}{6}\right) \cdot {normAngle}^{2} + 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          5. lower-fma.f32N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(\frac{1}{120} \cdot {normAngle}^{2} - \frac{1}{6}, {normAngle}^{2}, 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          6. lower--.f32N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(\frac{1}{120} \cdot {normAngle}^{2} - \frac{1}{6}, {normAngle}^{2}, 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          7. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(\frac{1}{120} \cdot {normAngle}^{2} - \frac{1}{6}, {normAngle}^{2}, 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          8. pow2N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(\frac{1}{120} \cdot \left(normAngle \cdot normAngle\right) - \frac{1}{6}, {normAngle}^{2}, 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          9. lift-*.f32N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(\frac{1}{120} \cdot \left(normAngle \cdot normAngle\right) - \frac{1}{6}, {normAngle}^{2}, 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          10. pow2N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(\frac{1}{120} \cdot \left(normAngle \cdot normAngle\right) - \frac{1}{6}, normAngle \cdot normAngle, 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          11. lift-*.f3299.3

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(0.008333333333333333 \cdot \left(normAngle \cdot normAngle\right) - 0.16666666666666666, normAngle \cdot normAngle, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        4. Applied rewrites99.3%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(0.008333333333333333 \cdot \left(normAngle \cdot normAngle\right) - 0.16666666666666666, normAngle \cdot normAngle, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        5. Add Preprocessing

        Alternative 5: 99.2% accurate, 4.2× speedup?

        \[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.019444444444444445, 0.16666666666666666\right), normAngle \cdot normAngle, 1\right), n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \end{array} \]
        (FPCore (normAngle u n0_i n1_i)
         :precision binary32
         (fma
          (fma
           (fma
            (fma (* normAngle normAngle) 0.019444444444444445 0.16666666666666666)
            (* normAngle normAngle)
            1.0)
           n1_i
           (- (* 0.3333333333333333 (* (* normAngle normAngle) n0_i)) n0_i))
          u
          n0_i))
        float code(float normAngle, float u, float n0_i, float n1_i) {
        	return fmaf(fmaf(fmaf(fmaf((normAngle * normAngle), 0.019444444444444445f, 0.16666666666666666f), (normAngle * normAngle), 1.0f), n1_i, ((0.3333333333333333f * ((normAngle * normAngle) * n0_i)) - n0_i)), u, n0_i);
        }
        
        function code(normAngle, u, n0_i, n1_i)
        	return fma(fma(fma(fma(Float32(normAngle * normAngle), Float32(0.019444444444444445), Float32(0.16666666666666666)), Float32(normAngle * normAngle), Float32(1.0)), n1_i, Float32(Float32(Float32(0.3333333333333333) * Float32(Float32(normAngle * normAngle) * n0_i)) - n0_i)), u, n0_i)
        end
        
        \begin{array}{l}
        
        \\
        \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.019444444444444445, 0.16666666666666666\right), normAngle \cdot normAngle, 1\right), n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right)
        \end{array}
        
        Derivation
        1. Initial program 97.1%

          \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
        2. Taylor expanded in u around 0

          \[\leadsto \color{blue}{n0\_i + u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right)} \]
        3. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) + \color{blue}{n0\_i} \]
          2. *-commutativeN/A

            \[\leadsto \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) \cdot u + n0\_i \]
          3. lower-fma.f32N/A

            \[\leadsto \mathsf{fma}\left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}, \color{blue}{u}, n0\_i\right) \]
        4. Applied rewrites94.8%

          \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, -\frac{\left(n0\_i \cdot normAngle\right) \cdot \cos normAngle}{\sin normAngle}\right), u, n0\_i\right)} \]
        5. Taylor expanded in normAngle around 0

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        6. Step-by-step derivation
          1. lower--.f32N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          2. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          3. pow2N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          4. lift-*.f32N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          5. lower--.f32N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          6. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          7. lower-*.f3299.4

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        7. Applied rewrites99.4%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
        8. Step-by-step derivation
          1. Applied rewrites99.4%

            \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\sin normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right)} \]
          2. Taylor expanded in normAngle around 0

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(1 + {normAngle}^{2} \cdot \left(\frac{1}{6} + \frac{7}{360} \cdot {normAngle}^{2}\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          3. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left({normAngle}^{2} \cdot \left(\frac{1}{6} + \frac{7}{360} \cdot {normAngle}^{2}\right) + 1, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            2. *-commutativeN/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\left(\frac{1}{6} + \frac{7}{360} \cdot {normAngle}^{2}\right) \cdot {normAngle}^{2} + 1, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            3. fp-cancel-sign-sub-invN/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\left(\frac{1}{6} - \left(\mathsf{neg}\left(\frac{7}{360}\right)\right) \cdot {normAngle}^{2}\right) \cdot {normAngle}^{2} + 1, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            4. metadata-evalN/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\left(\frac{1}{6} - \frac{-7}{360} \cdot {normAngle}^{2}\right) \cdot {normAngle}^{2} + 1, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            5. pow2N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\left(\frac{1}{6} - \frac{-7}{360} \cdot \left(normAngle \cdot normAngle\right)\right) \cdot {normAngle}^{2} + 1, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            6. lower-fma.f32N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{6} - \frac{-7}{360} \cdot \left(normAngle \cdot normAngle\right), {normAngle}^{2}, 1\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            7. pow2N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{6} - \frac{-7}{360} \cdot {normAngle}^{2}, {normAngle}^{2}, 1\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            8. fp-cancel-sub-sign-invN/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{6} + \left(\mathsf{neg}\left(\frac{-7}{360}\right)\right) \cdot {normAngle}^{2}, {normAngle}^{2}, 1\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            9. metadata-evalN/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{6} + \frac{7}{360} \cdot {normAngle}^{2}, {normAngle}^{2}, 1\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            10. +-commutativeN/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{7}{360} \cdot {normAngle}^{2} + \frac{1}{6}, {normAngle}^{2}, 1\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            11. *-commutativeN/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left({normAngle}^{2} \cdot \frac{7}{360} + \frac{1}{6}, {normAngle}^{2}, 1\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            12. lower-fma.f32N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left({normAngle}^{2}, \frac{7}{360}, \frac{1}{6}\right), {normAngle}^{2}, 1\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            13. pow2N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(normAngle \cdot normAngle, \frac{7}{360}, \frac{1}{6}\right), {normAngle}^{2}, 1\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            14. lift-*.f32N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(normAngle \cdot normAngle, \frac{7}{360}, \frac{1}{6}\right), {normAngle}^{2}, 1\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            15. pow2N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(normAngle \cdot normAngle, \frac{7}{360}, \frac{1}{6}\right), normAngle \cdot normAngle, 1\right), n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            16. lift-*.f3299.2

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.019444444444444445, 0.16666666666666666\right), normAngle \cdot normAngle, 1\right), n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          4. Applied rewrites99.2%

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.019444444444444445, 0.16666666666666666\right), normAngle \cdot normAngle, 1\right), n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          5. Add Preprocessing

          Alternative 6: 99.0% accurate, 4.4× speedup?

          \[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(normAngle \cdot normAngle, -0.16666666666666666, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \end{array} \]
          (FPCore (normAngle u n0_i n1_i)
           :precision binary32
           (fma
            (fma
             (/
              normAngle
              (* (fma (* normAngle normAngle) -0.16666666666666666 1.0) normAngle))
             n1_i
             (- (* 0.3333333333333333 (* (* normAngle normAngle) n0_i)) n0_i))
            u
            n0_i))
          float code(float normAngle, float u, float n0_i, float n1_i) {
          	return fmaf(fmaf((normAngle / (fmaf((normAngle * normAngle), -0.16666666666666666f, 1.0f) * normAngle)), n1_i, ((0.3333333333333333f * ((normAngle * normAngle) * n0_i)) - n0_i)), u, n0_i);
          }
          
          function code(normAngle, u, n0_i, n1_i)
          	return fma(fma(Float32(normAngle / Float32(fma(Float32(normAngle * normAngle), Float32(-0.16666666666666666), Float32(1.0)) * normAngle)), n1_i, Float32(Float32(Float32(0.3333333333333333) * Float32(Float32(normAngle * normAngle) * n0_i)) - n0_i)), u, n0_i)
          end
          
          \begin{array}{l}
          
          \\
          \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(normAngle \cdot normAngle, -0.16666666666666666, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right)
          \end{array}
          
          Derivation
          1. Initial program 97.1%

            \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
          2. Taylor expanded in u around 0

            \[\leadsto \color{blue}{n0\_i + u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right)} \]
          3. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) + \color{blue}{n0\_i} \]
            2. *-commutativeN/A

              \[\leadsto \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) \cdot u + n0\_i \]
            3. lower-fma.f32N/A

              \[\leadsto \mathsf{fma}\left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}, \color{blue}{u}, n0\_i\right) \]
          4. Applied rewrites94.8%

            \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, -\frac{\left(n0\_i \cdot normAngle\right) \cdot \cos normAngle}{\sin normAngle}\right), u, n0\_i\right)} \]
          5. Taylor expanded in normAngle around 0

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          6. Step-by-step derivation
            1. lower--.f32N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            2. lower-*.f32N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            3. pow2N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            4. lift-*.f32N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            5. lower--.f32N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            6. lower-*.f32N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            7. lower-*.f3299.4

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          7. Applied rewrites99.4%

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
          8. Step-by-step derivation
            1. Applied rewrites99.4%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\sin normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right)} \]
            2. Taylor expanded in normAngle around 0

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{normAngle \cdot \left(1 + \frac{-1}{6} \cdot {normAngle}^{2}\right)}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            3. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\left(1 + \frac{-1}{6} \cdot {normAngle}^{2}\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              2. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\left(1 + \frac{-1}{6} \cdot {normAngle}^{2}\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              3. +-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\left(\frac{-1}{6} \cdot {normAngle}^{2} + 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              4. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\left({normAngle}^{2} \cdot \frac{-1}{6} + 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              5. lower-fma.f32N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left({normAngle}^{2}, \frac{-1}{6}, 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              6. pow2N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(normAngle \cdot normAngle, \frac{-1}{6}, 1\right) \cdot normAngle}, n1\_i, \frac{1}{3} \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              7. lift-*.f3299.0

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(normAngle \cdot normAngle, -0.16666666666666666, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            4. Applied rewrites99.0%

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{normAngle}{\mathsf{fma}\left(normAngle \cdot normAngle, -0.16666666666666666, 1\right) \cdot normAngle}, n1\_i, 0.3333333333333333 \cdot \left(\left(normAngle \cdot normAngle\right) \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            5. Add Preprocessing

            Alternative 7: 99.0% accurate, 6.6× speedup?

            \[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.3333333333333333, n0\_i, 0.16666666666666666 \cdot n1\_i\right), normAngle \cdot normAngle, n1\_i\right) - n0\_i, u, n0\_i\right) \end{array} \]
            (FPCore (normAngle u n0_i n1_i)
             :precision binary32
             (fma
              (-
               (fma
                (fma 0.3333333333333333 n0_i (* 0.16666666666666666 n1_i))
                (* normAngle normAngle)
                n1_i)
               n0_i)
              u
              n0_i))
            float code(float normAngle, float u, float n0_i, float n1_i) {
            	return fmaf((fmaf(fmaf(0.3333333333333333f, n0_i, (0.16666666666666666f * n1_i)), (normAngle * normAngle), n1_i) - n0_i), u, n0_i);
            }
            
            function code(normAngle, u, n0_i, n1_i)
            	return fma(Float32(fma(fma(Float32(0.3333333333333333), n0_i, Float32(Float32(0.16666666666666666) * n1_i)), Float32(normAngle * normAngle), n1_i) - n0_i), u, n0_i)
            end
            
            \begin{array}{l}
            
            \\
            \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.3333333333333333, n0\_i, 0.16666666666666666 \cdot n1\_i\right), normAngle \cdot normAngle, n1\_i\right) - n0\_i, u, n0\_i\right)
            \end{array}
            
            Derivation
            1. Initial program 97.1%

              \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
            2. Taylor expanded in u around 0

              \[\leadsto \color{blue}{n0\_i + u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right)} \]
            3. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) + \color{blue}{n0\_i} \]
              2. *-commutativeN/A

                \[\leadsto \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) \cdot u + n0\_i \]
              3. lower-fma.f32N/A

                \[\leadsto \mathsf{fma}\left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}, \color{blue}{u}, n0\_i\right) \]
            4. Applied rewrites94.8%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, -\frac{\left(n0\_i \cdot normAngle\right) \cdot \cos normAngle}{\sin normAngle}\right), u, n0\_i\right)} \]
            5. Taylor expanded in normAngle around 0

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            6. Step-by-step derivation
              1. lower--.f32N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              2. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              3. pow2N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              4. lift-*.f32N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              5. lower--.f32N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              6. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
              7. lower-*.f3299.4

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            7. Applied rewrites99.4%

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, \left(normAngle \cdot normAngle\right) \cdot \left(-0.16666666666666666 \cdot n0\_i - -0.5 \cdot n0\_i\right) - n0\_i\right), u, n0\_i\right) \]
            8. Taylor expanded in normAngle around 0

              \[\leadsto \mathsf{fma}\left(\left(n1\_i + {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \left(\frac{-1}{2} \cdot n0\_i + \frac{-1}{6} \cdot n1\_i\right)\right)\right) - n0\_i, u, n0\_i\right) \]
            9. Step-by-step derivation
              1. lower--.f32N/A

                \[\leadsto \mathsf{fma}\left(\left(n1\_i + {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \left(\frac{-1}{2} \cdot n0\_i + \frac{-1}{6} \cdot n1\_i\right)\right)\right) - n0\_i, u, n0\_i\right) \]
              2. +-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left({normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot n0\_i - \left(\frac{-1}{2} \cdot n0\_i + \frac{-1}{6} \cdot n1\_i\right)\right) + n1\_i\right) - n0\_i, u, n0\_i\right) \]
              3. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\left(\frac{-1}{6} \cdot n0\_i - \left(\frac{-1}{2} \cdot n0\_i + \frac{-1}{6} \cdot n1\_i\right)\right) \cdot {normAngle}^{2} + n1\_i\right) - n0\_i, u, n0\_i\right) \]
              4. lower-fma.f32N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{6} \cdot n0\_i - \left(\frac{-1}{2} \cdot n0\_i + \frac{-1}{6} \cdot n1\_i\right), {normAngle}^{2}, n1\_i\right) - n0\_i, u, n0\_i\right) \]
              5. associate--r+N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\left(\frac{-1}{6} \cdot n0\_i - \frac{-1}{2} \cdot n0\_i\right) - \frac{-1}{6} \cdot n1\_i, {normAngle}^{2}, n1\_i\right) - n0\_i, u, n0\_i\right) \]
              6. distribute-rgt-out--N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n0\_i \cdot \left(\frac{-1}{6} - \frac{-1}{2}\right) - \frac{-1}{6} \cdot n1\_i, {normAngle}^{2}, n1\_i\right) - n0\_i, u, n0\_i\right) \]
              7. metadata-evalN/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(n0\_i \cdot \frac{1}{3} - \frac{-1}{6} \cdot n1\_i, {normAngle}^{2}, n1\_i\right) - n0\_i, u, n0\_i\right) \]
              8. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{3} \cdot n0\_i - \frac{-1}{6} \cdot n1\_i, {normAngle}^{2}, n1\_i\right) - n0\_i, u, n0\_i\right) \]
              9. fp-cancel-sub-sign-invN/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{3} \cdot n0\_i + \left(\mathsf{neg}\left(\frac{-1}{6}\right)\right) \cdot n1\_i, {normAngle}^{2}, n1\_i\right) - n0\_i, u, n0\_i\right) \]
              10. metadata-evalN/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{3} \cdot n0\_i + \frac{1}{6} \cdot n1\_i, {normAngle}^{2}, n1\_i\right) - n0\_i, u, n0\_i\right) \]
              11. lower-fma.f32N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{3}, n0\_i, \frac{1}{6} \cdot n1\_i\right), {normAngle}^{2}, n1\_i\right) - n0\_i, u, n0\_i\right) \]
              12. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{3}, n0\_i, \frac{1}{6} \cdot n1\_i\right), {normAngle}^{2}, n1\_i\right) - n0\_i, u, n0\_i\right) \]
              13. pow2N/A

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{3}, n0\_i, \frac{1}{6} \cdot n1\_i\right), normAngle \cdot normAngle, n1\_i\right) - n0\_i, u, n0\_i\right) \]
              14. lift-*.f3299.0

                \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.3333333333333333, n0\_i, 0.16666666666666666 \cdot n1\_i\right), normAngle \cdot normAngle, n1\_i\right) - n0\_i, u, n0\_i\right) \]
            10. Applied rewrites99.0%

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.3333333333333333, n0\_i, 0.16666666666666666 \cdot n1\_i\right), normAngle \cdot normAngle, n1\_i\right) - n0\_i, u, n0\_i\right) \]
            11. Add Preprocessing

            Alternative 8: 98.5% accurate, 7.2× speedup?

            \[\begin{array}{l} \\ \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.16666666666666666, 1\right) \cdot n1\_i\right)\right) \end{array} \]
            (FPCore (normAngle u n0_i n1_i)
             :precision binary32
             (fma
              (- 1.0 u)
              n0_i
              (* u (* (fma (* normAngle normAngle) 0.16666666666666666 1.0) n1_i))))
            float code(float normAngle, float u, float n0_i, float n1_i) {
            	return fmaf((1.0f - u), n0_i, (u * (fmaf((normAngle * normAngle), 0.16666666666666666f, 1.0f) * n1_i)));
            }
            
            function code(normAngle, u, n0_i, n1_i)
            	return fma(Float32(Float32(1.0) - u), n0_i, Float32(u * Float32(fma(Float32(normAngle * normAngle), Float32(0.16666666666666666), Float32(1.0)) * n1_i)))
            end
            
            \begin{array}{l}
            
            \\
            \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.16666666666666666, 1\right) \cdot n1\_i\right)\right)
            \end{array}
            
            Derivation
            1. Initial program 97.1%

              \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
            2. Taylor expanded in normAngle around 0

              \[\leadsto \color{blue}{n0\_i \cdot \left(1 - u\right) + \left(n1\_i \cdot u + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right)} \]
            3. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \left(1 - u\right) \cdot n0\_i + \left(\color{blue}{n1\_i \cdot u} + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right) \]
              2. lower-fma.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, \color{blue}{n0\_i}, n1\_i \cdot u + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right) \]
              3. lift--.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, n1\_i \cdot u + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right) \]
              4. +-commutativeN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right) + n1\_i \cdot u\right) \]
            4. Applied rewrites98.9%

              \[\leadsto \color{blue}{\mathsf{fma}\left(1 - u, n0\_i, \mathsf{fma}\left(-0.16666666666666666 \cdot \mathsf{fma}\left(\left(\left(1 - u\right) \cdot \left(1 - u\right)\right) \cdot \left(1 - u\right), n0\_i, \left(\left(u \cdot u\right) \cdot u\right) \cdot n1\_i\right) - -0.16666666666666666 \cdot \mathsf{fma}\left(1 - u, n0\_i, n1\_i \cdot u\right), normAngle \cdot normAngle, n1\_i \cdot u\right)\right)} \]
            5. Taylor expanded in u around 0

              \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
            6. Step-by-step derivation
              1. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              2. lower-+.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              3. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              4. pow2N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              5. lift-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              6. lower--.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              7. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              8. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              9. fp-cancel-sign-sub-invN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i - \left(\mathsf{neg}\left(-1\right)\right) \cdot n0\_i\right)\right)\right)\right) \]
              10. lower--.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i - \left(\mathsf{neg}\left(-1\right)\right) \cdot n0\_i\right)\right)\right)\right) \]
              11. metadata-evalN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i - 1 \cdot n0\_i\right)\right)\right)\right) \]
              12. lower-*.f3298.7

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(0.5 \cdot n0\_i - -0.16666666666666666 \cdot \left(n1\_i - 1 \cdot n0\_i\right)\right)\right)\right) \]
            7. Applied rewrites98.7%

              \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(0.5 \cdot n0\_i - -0.16666666666666666 \cdot \left(n1\_i - 1 \cdot n0\_i\right)\right)\right)\right) \]
            8. Taylor expanded in n1_i around inf

              \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i \cdot \left(1 + \frac{1}{6} \cdot {normAngle}^{2}\right)\right)\right) \]
            9. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(\left(1 + \frac{1}{6} \cdot {normAngle}^{2}\right) \cdot n1\_i\right)\right) \]
              2. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(\left(1 + \frac{1}{6} \cdot {normAngle}^{2}\right) \cdot n1\_i\right)\right) \]
              3. +-commutativeN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(\left(\frac{1}{6} \cdot {normAngle}^{2} + 1\right) \cdot n1\_i\right)\right) \]
              4. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(\left({normAngle}^{2} \cdot \frac{1}{6} + 1\right) \cdot n1\_i\right)\right) \]
              5. lower-fma.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(\mathsf{fma}\left({normAngle}^{2}, \frac{1}{6}, 1\right) \cdot n1\_i\right)\right) \]
              6. pow2N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(\mathsf{fma}\left(normAngle \cdot normAngle, \frac{1}{6}, 1\right) \cdot n1\_i\right)\right) \]
              7. lift-*.f3298.5

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.16666666666666666, 1\right) \cdot n1\_i\right)\right) \]
            10. Applied rewrites98.5%

              \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.16666666666666666, 1\right) \cdot n1\_i\right)\right) \]
            11. Add Preprocessing

            Alternative 9: 98.5% accurate, 7.2× speedup?

            \[\begin{array}{l} \\ \mathsf{fma}\left(1 - u, n0\_i, \left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.16666666666666666, 1\right) \cdot u\right) \cdot n1\_i\right) \end{array} \]
            (FPCore (normAngle u n0_i n1_i)
             :precision binary32
             (fma
              (- 1.0 u)
              n0_i
              (* (* (fma (* normAngle normAngle) 0.16666666666666666 1.0) u) n1_i)))
            float code(float normAngle, float u, float n0_i, float n1_i) {
            	return fmaf((1.0f - u), n0_i, ((fmaf((normAngle * normAngle), 0.16666666666666666f, 1.0f) * u) * n1_i));
            }
            
            function code(normAngle, u, n0_i, n1_i)
            	return fma(Float32(Float32(1.0) - u), n0_i, Float32(Float32(fma(Float32(normAngle * normAngle), Float32(0.16666666666666666), Float32(1.0)) * u) * n1_i))
            end
            
            \begin{array}{l}
            
            \\
            \mathsf{fma}\left(1 - u, n0\_i, \left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.16666666666666666, 1\right) \cdot u\right) \cdot n1\_i\right)
            \end{array}
            
            Derivation
            1. Initial program 97.1%

              \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
            2. Taylor expanded in normAngle around 0

              \[\leadsto \color{blue}{n0\_i \cdot \left(1 - u\right) + \left(n1\_i \cdot u + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right)} \]
            3. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \left(1 - u\right) \cdot n0\_i + \left(\color{blue}{n1\_i \cdot u} + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right) \]
              2. lower-fma.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, \color{blue}{n0\_i}, n1\_i \cdot u + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right) \]
              3. lift--.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, n1\_i \cdot u + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right) \]
              4. +-commutativeN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right) + n1\_i \cdot u\right) \]
            4. Applied rewrites98.9%

              \[\leadsto \color{blue}{\mathsf{fma}\left(1 - u, n0\_i, \mathsf{fma}\left(-0.16666666666666666 \cdot \mathsf{fma}\left(\left(\left(1 - u\right) \cdot \left(1 - u\right)\right) \cdot \left(1 - u\right), n0\_i, \left(\left(u \cdot u\right) \cdot u\right) \cdot n1\_i\right) - -0.16666666666666666 \cdot \mathsf{fma}\left(1 - u, n0\_i, n1\_i \cdot u\right), normAngle \cdot normAngle, n1\_i \cdot u\right)\right)} \]
            5. Taylor expanded in u around 0

              \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
            6. Step-by-step derivation
              1. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              2. lower-+.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              3. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              4. pow2N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              5. lift-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              6. lower--.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              7. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              8. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
              9. fp-cancel-sign-sub-invN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i - \left(\mathsf{neg}\left(-1\right)\right) \cdot n0\_i\right)\right)\right)\right) \]
              10. lower--.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i - \left(\mathsf{neg}\left(-1\right)\right) \cdot n0\_i\right)\right)\right)\right) \]
              11. metadata-evalN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i - 1 \cdot n0\_i\right)\right)\right)\right) \]
              12. lower-*.f3298.7

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(0.5 \cdot n0\_i - -0.16666666666666666 \cdot \left(n1\_i - 1 \cdot n0\_i\right)\right)\right)\right) \]
            7. Applied rewrites98.7%

              \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(0.5 \cdot n0\_i - -0.16666666666666666 \cdot \left(n1\_i - 1 \cdot n0\_i\right)\right)\right)\right) \]
            8. Taylor expanded in n1_i around inf

              \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, n1\_i \cdot \left(u \cdot \left(1 + \frac{1}{6} \cdot {normAngle}^{2}\right)\right)\right) \]
            9. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, \left(u \cdot \left(1 + \frac{1}{6} \cdot {normAngle}^{2}\right)\right) \cdot n1\_i\right) \]
              2. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, \left(u \cdot \left(1 + \frac{1}{6} \cdot {normAngle}^{2}\right)\right) \cdot n1\_i\right) \]
              3. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, \left(\left(1 + \frac{1}{6} \cdot {normAngle}^{2}\right) \cdot u\right) \cdot n1\_i\right) \]
              4. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, \left(\left(1 + \frac{1}{6} \cdot {normAngle}^{2}\right) \cdot u\right) \cdot n1\_i\right) \]
              5. +-commutativeN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, \left(\left(\frac{1}{6} \cdot {normAngle}^{2} + 1\right) \cdot u\right) \cdot n1\_i\right) \]
              6. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, \left(\left({normAngle}^{2} \cdot \frac{1}{6} + 1\right) \cdot u\right) \cdot n1\_i\right) \]
              7. lower-fma.f32N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, \left(\mathsf{fma}\left({normAngle}^{2}, \frac{1}{6}, 1\right) \cdot u\right) \cdot n1\_i\right) \]
              8. pow2N/A

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, \left(\mathsf{fma}\left(normAngle \cdot normAngle, \frac{1}{6}, 1\right) \cdot u\right) \cdot n1\_i\right) \]
              9. lift-*.f3298.5

                \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, \left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.16666666666666666, 1\right) \cdot u\right) \cdot n1\_i\right) \]
            10. Applied rewrites98.5%

              \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, \left(\mathsf{fma}\left(normAngle \cdot normAngle, 0.16666666666666666, 1\right) \cdot u\right) \cdot n1\_i\right) \]
            11. Add Preprocessing

            Alternative 10: 98.2% accurate, 19.0× speedup?

            \[\begin{array}{l} \\ \mathsf{fma}\left(n1\_i - n0\_i, u, n0\_i\right) \end{array} \]
            (FPCore (normAngle u n0_i n1_i) :precision binary32 (fma (- n1_i n0_i) u n0_i))
            float code(float normAngle, float u, float n0_i, float n1_i) {
            	return fmaf((n1_i - n0_i), u, n0_i);
            }
            
            function code(normAngle, u, n0_i, n1_i)
            	return fma(Float32(n1_i - n0_i), u, n0_i)
            end
            
            \begin{array}{l}
            
            \\
            \mathsf{fma}\left(n1\_i - n0\_i, u, n0\_i\right)
            \end{array}
            
            Derivation
            1. Initial program 97.1%

              \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
            2. Taylor expanded in u around 0

              \[\leadsto \color{blue}{n0\_i + u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right)} \]
            3. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) + \color{blue}{n0\_i} \]
              2. *-commutativeN/A

                \[\leadsto \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) \cdot u + n0\_i \]
              3. lower-fma.f32N/A

                \[\leadsto \mathsf{fma}\left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}, \color{blue}{u}, n0\_i\right) \]
            4. Applied rewrites94.8%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, -\frac{\left(n0\_i \cdot normAngle\right) \cdot \cos normAngle}{\sin normAngle}\right), u, n0\_i\right)} \]
            5. Taylor expanded in normAngle around 0

              \[\leadsto \mathsf{fma}\left(n1\_i - n0\_i, u, n0\_i\right) \]
            6. Step-by-step derivation
              1. lower--.f3298.2

                \[\leadsto \mathsf{fma}\left(n1\_i - n0\_i, u, n0\_i\right) \]
            7. Applied rewrites98.2%

              \[\leadsto \mathsf{fma}\left(n1\_i - n0\_i, u, n0\_i\right) \]
            8. Add Preprocessing

            Alternative 11: 81.9% accurate, 26.9× speedup?

            \[\begin{array}{l} \\ \mathsf{fma}\left(n1\_i, u, n0\_i\right) \end{array} \]
            (FPCore (normAngle u n0_i n1_i) :precision binary32 (fma n1_i u n0_i))
            float code(float normAngle, float u, float n0_i, float n1_i) {
            	return fmaf(n1_i, u, n0_i);
            }
            
            function code(normAngle, u, n0_i, n1_i)
            	return fma(n1_i, u, n0_i)
            end
            
            \begin{array}{l}
            
            \\
            \mathsf{fma}\left(n1\_i, u, n0\_i\right)
            \end{array}
            
            Derivation
            1. Initial program 97.1%

              \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
            2. Taylor expanded in u around 0

              \[\leadsto \color{blue}{n0\_i + u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right)} \]
            3. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto u \cdot \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) + \color{blue}{n0\_i} \]
              2. *-commutativeN/A

                \[\leadsto \left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}\right) \cdot u + n0\_i \]
              3. lower-fma.f32N/A

                \[\leadsto \mathsf{fma}\left(-1 \cdot \frac{n0\_i \cdot \left(normAngle \cdot \cos normAngle\right)}{\sin normAngle} + \frac{n1\_i \cdot normAngle}{\sin normAngle}, \color{blue}{u}, n0\_i\right) \]
            4. Applied rewrites94.8%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(n1\_i, \frac{normAngle}{\sin normAngle}, -\frac{\left(n0\_i \cdot normAngle\right) \cdot \cos normAngle}{\sin normAngle}\right), u, n0\_i\right)} \]
            5. Taylor expanded in n0_i around 0

              \[\leadsto \mathsf{fma}\left(\frac{n1\_i \cdot normAngle}{\sin normAngle}, u, n0\_i\right) \]
            6. Step-by-step derivation
              1. lower-/.f32N/A

                \[\leadsto \mathsf{fma}\left(\frac{n1\_i \cdot normAngle}{\sin normAngle}, u, n0\_i\right) \]
              2. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(\frac{n1\_i \cdot normAngle}{\sin normAngle}, u, n0\_i\right) \]
              3. lift-sin.f3275.7

                \[\leadsto \mathsf{fma}\left(\frac{n1\_i \cdot normAngle}{\sin normAngle}, u, n0\_i\right) \]
            7. Applied rewrites75.7%

              \[\leadsto \mathsf{fma}\left(\frac{n1\_i \cdot normAngle}{\sin normAngle}, u, n0\_i\right) \]
            8. Taylor expanded in normAngle around 0

              \[\leadsto \mathsf{fma}\left(n1\_i, u, n0\_i\right) \]
            9. Step-by-step derivation
              1. Applied rewrites81.9%

                \[\leadsto \mathsf{fma}\left(n1\_i, u, n0\_i\right) \]
              2. Add Preprocessing

              Alternative 12: 60.5% accurate, 14.0× speedup?

              \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;n1\_i \leq -1.0000000036274937 \cdot 10^{-15}:\\ \;\;\;\;u \cdot n1\_i\\ \mathbf{elif}\;n1\_i \leq 4.999999980020986 \cdot 10^{-13}:\\ \;\;\;\;n0\_i\\ \mathbf{else}:\\ \;\;\;\;u \cdot n1\_i\\ \end{array} \end{array} \]
              (FPCore (normAngle u n0_i n1_i)
               :precision binary32
               (if (<= n1_i -1.0000000036274937e-15)
                 (* u n1_i)
                 (if (<= n1_i 4.999999980020986e-13) n0_i (* u n1_i))))
              float code(float normAngle, float u, float n0_i, float n1_i) {
              	float tmp;
              	if (n1_i <= -1.0000000036274937e-15f) {
              		tmp = u * n1_i;
              	} else if (n1_i <= 4.999999980020986e-13f) {
              		tmp = n0_i;
              	} else {
              		tmp = u * n1_i;
              	}
              	return tmp;
              }
              
              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(4) function code(normangle, u, n0_i, n1_i)
              use fmin_fmax_functions
                  real(4), intent (in) :: normangle
                  real(4), intent (in) :: u
                  real(4), intent (in) :: n0_i
                  real(4), intent (in) :: n1_i
                  real(4) :: tmp
                  if (n1_i <= (-1.0000000036274937e-15)) then
                      tmp = u * n1_i
                  else if (n1_i <= 4.999999980020986e-13) then
                      tmp = n0_i
                  else
                      tmp = u * n1_i
                  end if
                  code = tmp
              end function
              
              function code(normAngle, u, n0_i, n1_i)
              	tmp = Float32(0.0)
              	if (n1_i <= Float32(-1.0000000036274937e-15))
              		tmp = Float32(u * n1_i);
              	elseif (n1_i <= Float32(4.999999980020986e-13))
              		tmp = n0_i;
              	else
              		tmp = Float32(u * n1_i);
              	end
              	return tmp
              end
              
              function tmp_2 = code(normAngle, u, n0_i, n1_i)
              	tmp = single(0.0);
              	if (n1_i <= single(-1.0000000036274937e-15))
              		tmp = u * n1_i;
              	elseif (n1_i <= single(4.999999980020986e-13))
              		tmp = n0_i;
              	else
              		tmp = u * n1_i;
              	end
              	tmp_2 = tmp;
              end
              
              \begin{array}{l}
              
              \\
              \begin{array}{l}
              \mathbf{if}\;n1\_i \leq -1.0000000036274937 \cdot 10^{-15}:\\
              \;\;\;\;u \cdot n1\_i\\
              
              \mathbf{elif}\;n1\_i \leq 4.999999980020986 \cdot 10^{-13}:\\
              \;\;\;\;n0\_i\\
              
              \mathbf{else}:\\
              \;\;\;\;u \cdot n1\_i\\
              
              
              \end{array}
              \end{array}
              
              Derivation
              1. Split input into 2 regimes
              2. if n1_i < -1e-15 or 4.99999998e-13 < n1_i

                1. Initial program 95.9%

                  \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
                2. Taylor expanded in normAngle around 0

                  \[\leadsto \color{blue}{n0\_i \cdot \left(1 - u\right) + \left(n1\_i \cdot u + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right)} \]
                3. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto \left(1 - u\right) \cdot n0\_i + \left(\color{blue}{n1\_i \cdot u} + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right) \]
                  2. lower-fma.f32N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, \color{blue}{n0\_i}, n1\_i \cdot u + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right) \]
                  3. lift--.f32N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, n1\_i \cdot u + {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right)\right) \]
                  4. +-commutativeN/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, {normAngle}^{2} \cdot \left(\left(\frac{-1}{6} \cdot \left(n0\_i \cdot {\left(1 - u\right)}^{3}\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot {u}^{3}\right)\right) - \left(\frac{-1}{6} \cdot \left(n0\_i \cdot \left(1 - u\right)\right) + \frac{-1}{6} \cdot \left(n1\_i \cdot u\right)\right)\right) + n1\_i \cdot u\right) \]
                4. Applied rewrites98.6%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(1 - u, n0\_i, \mathsf{fma}\left(-0.16666666666666666 \cdot \mathsf{fma}\left(\left(\left(1 - u\right) \cdot \left(1 - u\right)\right) \cdot \left(1 - u\right), n0\_i, \left(\left(u \cdot u\right) \cdot u\right) \cdot n1\_i\right) - -0.16666666666666666 \cdot \mathsf{fma}\left(1 - u, n0\_i, n1\_i \cdot u\right), normAngle \cdot normAngle, n1\_i \cdot u\right)\right)} \]
                5. Taylor expanded in u around 0

                  \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
                6. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
                  2. lower-+.f32N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
                  3. lower-*.f32N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + {normAngle}^{2} \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
                  4. pow2N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
                  5. lift-*.f32N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
                  6. lower--.f32N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
                  7. lower-*.f32N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
                  8. lower-*.f32N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i + -1 \cdot n0\_i\right)\right)\right)\right) \]
                  9. fp-cancel-sign-sub-invN/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i - \left(\mathsf{neg}\left(-1\right)\right) \cdot n0\_i\right)\right)\right)\right) \]
                  10. lower--.f32N/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i - \left(\mathsf{neg}\left(-1\right)\right) \cdot n0\_i\right)\right)\right)\right) \]
                  11. metadata-evalN/A

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(\frac{1}{2} \cdot n0\_i - \frac{-1}{6} \cdot \left(n1\_i - 1 \cdot n0\_i\right)\right)\right)\right) \]
                  12. lower-*.f3298.5

                    \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(0.5 \cdot n0\_i - -0.16666666666666666 \cdot \left(n1\_i - 1 \cdot n0\_i\right)\right)\right)\right) \]
                7. Applied rewrites98.5%

                  \[\leadsto \mathsf{fma}\left(1 - u, n0\_i, u \cdot \left(n1\_i + \left(normAngle \cdot normAngle\right) \cdot \left(0.5 \cdot n0\_i - -0.16666666666666666 \cdot \left(n1\_i - 1 \cdot n0\_i\right)\right)\right)\right) \]
                8. Taylor expanded in n1_i around inf

                  \[\leadsto n1\_i \cdot \color{blue}{\left(u + {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot {u}^{3} - \frac{-1}{6} \cdot u\right)\right)} \]
                9. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto \left(u + {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot {u}^{3} - \frac{-1}{6} \cdot u\right)\right) \cdot n1\_i \]
                  2. lower-*.f32N/A

                    \[\leadsto \left(u + {normAngle}^{2} \cdot \left(\frac{-1}{6} \cdot {u}^{3} - \frac{-1}{6} \cdot u\right)\right) \cdot n1\_i \]
                10. Applied rewrites65.6%

                  \[\leadsto \mathsf{fma}\left(-0.16666666666666666 \cdot \left(\left(u \cdot u\right) \cdot u - u\right), normAngle \cdot normAngle, u\right) \cdot \color{blue}{n1\_i} \]
                11. Taylor expanded in normAngle around 0

                  \[\leadsto u \cdot n1\_i \]
                12. Step-by-step derivation
                  1. Applied rewrites64.7%

                    \[\leadsto u \cdot n1\_i \]

                  if -1e-15 < n1_i < 4.99999998e-13

                  1. Initial program 97.8%

                    \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
                  2. Taylor expanded in u around 0

                    \[\leadsto \color{blue}{n0\_i} \]
                  3. Step-by-step derivation
                    1. Applied rewrites58.2%

                      \[\leadsto \color{blue}{n0\_i} \]
                  4. Recombined 2 regimes into one program.
                  5. Add Preprocessing

                  Alternative 13: 46.7% accurate, 161.4× speedup?

                  \[\begin{array}{l} \\ n0\_i \end{array} \]
                  (FPCore (normAngle u n0_i n1_i) :precision binary32 n0_i)
                  float code(float normAngle, float u, float n0_i, float n1_i) {
                  	return n0_i;
                  }
                  
                  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(4) function code(normangle, u, n0_i, n1_i)
                  use fmin_fmax_functions
                      real(4), intent (in) :: normangle
                      real(4), intent (in) :: u
                      real(4), intent (in) :: n0_i
                      real(4), intent (in) :: n1_i
                      code = n0_i
                  end function
                  
                  function code(normAngle, u, n0_i, n1_i)
                  	return n0_i
                  end
                  
                  function tmp = code(normAngle, u, n0_i, n1_i)
                  	tmp = n0_i;
                  end
                  
                  \begin{array}{l}
                  
                  \\
                  n0\_i
                  \end{array}
                  
                  Derivation
                  1. Initial program 97.1%

                    \[\left(\sin \left(\left(1 - u\right) \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n0\_i + \left(\sin \left(u \cdot normAngle\right) \cdot \frac{1}{\sin normAngle}\right) \cdot n1\_i \]
                  2. Taylor expanded in u around 0

                    \[\leadsto \color{blue}{n0\_i} \]
                  3. Step-by-step derivation
                    1. Applied rewrites46.7%

                      \[\leadsto \color{blue}{n0\_i} \]
                    2. Add Preprocessing

                    Reproduce

                    ?
                    herbie shell --seed 2025106 
                    (FPCore (normAngle u n0_i n1_i)
                      :name "Curve intersection, scale width based on ribbon orientation"
                      :precision binary32
                      :pre (and (and (and (and (<= 0.0 normAngle) (<= normAngle (/ PI 2.0))) (and (<= -1.0 n0_i) (<= n0_i 1.0))) (and (<= -1.0 n1_i) (<= n1_i 1.0))) (and (<= 2.328306437e-10 u) (<= u 1.0)))
                      (+ (* (* (sin (* (- 1.0 u) normAngle)) (/ 1.0 (sin normAngle))) n0_i) (* (* (sin (* u normAngle)) (/ 1.0 (sin normAngle))) n1_i)))