qlog (example 3.10)

Percentage Accurate: 3.8% → 100.0%

Time: 3.5s

Alternatives: 9

Speedup: 218.0×

Specification

\[\left|x\right| \leq 1\]

Math

\[\begin{array}{l} \\ \frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \end{array} \]

FPCore

(FPCore (x) :precision binary64 (/ (log (- 1.0 x)) (log (+ 1.0 x))))

C

double code(double x) {
	return log((1.0 - x)) / log((1.0 + x));
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

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

real(8) function code(x)
use fmin_fmax_functions
    real(8), intent (in) :: x
    code = log((1.0d0 - x)) / log((1.0d0 + x))
end function

Java

public static double code(double x) {
	return Math.log((1.0 - x)) / Math.log((1.0 + x));
}

Python

def code(x):
	return math.log((1.0 - x)) / math.log((1.0 + x))

Julia

function code(x)
	return Float64(log(Float64(1.0 - x)) / log(Float64(1.0 + x)))
end

MATLAB

function tmp = code(x)
	tmp = log((1.0 - x)) / log((1.0 + x));
end

Wolfram

code[x_] := N[(N[Log[N[(1.0 - x), $MachinePrecision]], $MachinePrecision] / N[Log[N[(1.0 + x), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]

Initial Program: 3.8% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \end{array} \]

FPCore

(FPCore (x) :precision binary64 (/ (log (- 1.0 x)) (log (+ 1.0 x))))

C

double code(double x) {
	return log((1.0 - x)) / log((1.0 + x));
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

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

real(8) function code(x)
use fmin_fmax_functions
    real(8), intent (in) :: x
    code = log((1.0d0 - x)) / log((1.0d0 + x))
end function

Java

public static double code(double x) {
	return Math.log((1.0 - x)) / Math.log((1.0 + x));
}

Python

def code(x):
	return math.log((1.0 - x)) / math.log((1.0 + x))

Julia

function code(x)
	return Float64(log(Float64(1.0 - x)) / log(Float64(1.0 + x)))
end

MATLAB

function tmp = code(x)
	tmp = log((1.0 - x)) / log((1.0 + x));
end

Wolfram

code[x_] := N[(N[Log[N[(1.0 - x), $MachinePrecision]], $MachinePrecision] / N[Log[N[(1.0 + x), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]

Alternative 1: 100.0% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1 \end{array} \]

FPCore

(FPCore (x) :precision binary64 (- (/ (log1p (* (- x) x)) (log1p x)) 1.0))

C

double code(double x) {
	return (log1p((-x * x)) / log1p(x)) - 1.0;
}

Java

public static double code(double x) {
	return (Math.log1p((-x * x)) / Math.log1p(x)) - 1.0;
}

Python

def code(x):
	return (math.log1p((-x * x)) / math.log1p(x)) - 1.0

Julia

function code(x)
	return Float64(Float64(log1p(Float64(Float64(-x) * x)) / log1p(x)) - 1.0)
end

Wolfram

code[x_] := N[(N[(N[Log[1 + N[((-x) * x), $MachinePrecision]], $MachinePrecision] / N[Log[1 + x], $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]

Derivation

1. Initial program 3.8%

   \[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \]
2. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(1 - x\right)}}{\log \left(1 + x\right)} \]

   2. flip-- N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   3. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 \cdot 1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   4. lower-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   5. metadata-eval N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1} - x \cdot x}{1 + x}\right)}{\log \left(1 + x\right)} \]

   6. lower--.f64 N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1 - x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   7. lower-*.f64 4.3

      \[\leadsto \frac{\log \left(\frac{1 - \color{blue}{x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   8. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   9. +-commutative N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x + 1}}\right)}{\log \left(1 + x\right)} \]

   10. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x + \color{blue}{1 \cdot 1}}\right)}{\log \left(1 + x\right)} \]

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

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right) \cdot 1}}\right)}{\log \left(1 + x\right)} \]

   12. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1} \cdot 1}\right)}{\log \left(1 + x\right)} \]

   13. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

   14. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   15. lower--.f64 N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   16. metadata-eval 4.3

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

3. Applied rewrites 4.3%

   \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]
4. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}{\log \left(1 + x\right)}} \]

   2. lift-log.f64 N/A

      \[\leadsto \frac{\color{blue}{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   3. lift-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   4. log-div N/A

      \[\leadsto \frac{\color{blue}{\log \left(1 - x \cdot x\right) - \log \left(x - -1\right)}}{\log \left(1 + x\right)} \]

   5. lift--.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x - -1\right)}}{\log \left(1 + x\right)} \]

   6. sub-negate1 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x + \left(\mathsf{neg}\left(-1\right)\right)\right)}}{\log \left(1 + x\right)} \]

   7. metadata-eval N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \left(x + \color{blue}{1}\right)}{\log \left(1 + x\right)} \]

   8. +-commutative N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(1 + x\right)}}{\log \left(1 + x\right)} \]

   9. lift-log1p.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \color{blue}{\mathsf{log1p}\left(x\right)}}{\log \left(1 + x\right)} \]

   10. lift-log.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\log \left(1 + x\right)}} \]

   11. lift-+.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\log \color{blue}{\left(1 + x\right)}} \]

   12. lift-log1p.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\mathsf{log1p}\left(x\right)}} \]

   13. div-sub N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   14. lower--.f64 N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

5. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]
6. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{\frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   2. *-inverses 100.0

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{1} \]

7. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1} \]
8. Add Preprocessing

Alternative 2: 99.8% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \frac{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.25, x \cdot x, -0.3333333333333333\right), x \cdot x, -0.5\right), x \cdot x, -1\right) \cdot \left(x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1 \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (-
  (/
   (*
    (fma
     (fma (fma -0.25 (* x x) -0.3333333333333333) (* x x) -0.5)
     (* x x)
     -1.0)
    (* x x))
   (log1p x))
  1.0))

C

double code(double x) {
	return ((fma(fma(fma(-0.25, (x * x), -0.3333333333333333), (x * x), -0.5), (x * x), -1.0) * (x * x)) / log1p(x)) - 1.0;
}

Julia

function code(x)
	return Float64(Float64(Float64(fma(fma(fma(-0.25, Float64(x * x), -0.3333333333333333), Float64(x * x), -0.5), Float64(x * x), -1.0) * Float64(x * x)) / log1p(x)) - 1.0)
end

Wolfram

code[x_] := N[(N[(N[(N[(N[(N[(-0.25 * N[(x * x), $MachinePrecision] + -0.3333333333333333), $MachinePrecision] * N[(x * x), $MachinePrecision] + -0.5), $MachinePrecision] * N[(x * x), $MachinePrecision] + -1.0), $MachinePrecision] * N[(x * x), $MachinePrecision]), $MachinePrecision] / N[Log[1 + x], $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]

Derivation

1. Initial program 3.8%

   \[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \]
2. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(1 - x\right)}}{\log \left(1 + x\right)} \]

   2. flip-- N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   3. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 \cdot 1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   4. lower-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   5. metadata-eval N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1} - x \cdot x}{1 + x}\right)}{\log \left(1 + x\right)} \]

   6. lower--.f64 N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1 - x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   7. lower-*.f64 4.3

      \[\leadsto \frac{\log \left(\frac{1 - \color{blue}{x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   8. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   9. +-commutative N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x + 1}}\right)}{\log \left(1 + x\right)} \]

   10. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x + \color{blue}{1 \cdot 1}}\right)}{\log \left(1 + x\right)} \]

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

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right) \cdot 1}}\right)}{\log \left(1 + x\right)} \]

   12. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1} \cdot 1}\right)}{\log \left(1 + x\right)} \]

   13. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

   14. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   15. lower--.f64 N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   16. metadata-eval 4.3

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

3. Applied rewrites 4.3%

   \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]
4. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}{\log \left(1 + x\right)}} \]

   2. lift-log.f64 N/A

      \[\leadsto \frac{\color{blue}{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   3. lift-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   4. log-div N/A

      \[\leadsto \frac{\color{blue}{\log \left(1 - x \cdot x\right) - \log \left(x - -1\right)}}{\log \left(1 + x\right)} \]

   5. lift--.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x - -1\right)}}{\log \left(1 + x\right)} \]

   6. sub-negate1 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x + \left(\mathsf{neg}\left(-1\right)\right)\right)}}{\log \left(1 + x\right)} \]

   7. metadata-eval N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \left(x + \color{blue}{1}\right)}{\log \left(1 + x\right)} \]

   8. +-commutative N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(1 + x\right)}}{\log \left(1 + x\right)} \]

   9. lift-log1p.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \color{blue}{\mathsf{log1p}\left(x\right)}}{\log \left(1 + x\right)} \]

   10. lift-log.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\log \left(1 + x\right)}} \]

   11. lift-+.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\log \color{blue}{\left(1 + x\right)}} \]

   12. lift-log1p.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\mathsf{log1p}\left(x\right)}} \]

   13. div-sub N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   14. lower--.f64 N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

5. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]
6. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{\frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   2. *-inverses 100.0

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{1} \]

7. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1} \]

8. Taylor expanded in x around 0

   \[\leadsto \frac{\color{blue}{{x}^{2} \cdot \left({x}^{2} \cdot \left({x}^{2} \cdot \left(\frac{-1}{4} \cdot {x}^{2} - \frac{1}{3}\right) - \frac{1}{2}\right) - 1\right)}}{\mathsf{log1p}\left(x\right)} - 1 \]
9. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \frac{\left({x}^{2} \cdot \left({x}^{2} \cdot \left(\frac{-1}{4} \cdot {x}^{2} - \frac{1}{3}\right) - \frac{1}{2}\right) - 1\right) \cdot \color{blue}{{x}^{2}}}{\mathsf{log1p}\left(x\right)} - 1 \]

   2. lower-*.f64 N/A

      \[\leadsto \frac{\left({x}^{2} \cdot \left({x}^{2} \cdot \left(\frac{-1}{4} \cdot {x}^{2} - \frac{1}{3}\right) - \frac{1}{2}\right) - 1\right) \cdot \color{blue}{{x}^{2}}}{\mathsf{log1p}\left(x\right)} - 1 \]

10. Applied rewrites 99.8%

    \[\leadsto \frac{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.25, x \cdot x, -0.3333333333333333\right), x \cdot x, -0.5\right), x \cdot x, -1\right) \cdot \left(x \cdot x\right)}}{\mathsf{log1p}\left(x\right)} - 1 \]
11. Add Preprocessing

Alternative 3: 99.8% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \frac{\mathsf{fma}\left(\mathsf{fma}\left(-0.3333333333333333, x \cdot x, -0.5\right), x \cdot x, -1\right) \cdot \left(x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1 \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (-
  (/
   (* (fma (fma -0.3333333333333333 (* x x) -0.5) (* x x) -1.0) (* x x))
   (log1p x))
  1.0))

C

double code(double x) {
	return ((fma(fma(-0.3333333333333333, (x * x), -0.5), (x * x), -1.0) * (x * x)) / log1p(x)) - 1.0;
}

Julia

function code(x)
	return Float64(Float64(Float64(fma(fma(-0.3333333333333333, Float64(x * x), -0.5), Float64(x * x), -1.0) * Float64(x * x)) / log1p(x)) - 1.0)
end

Wolfram

code[x_] := N[(N[(N[(N[(N[(-0.3333333333333333 * N[(x * x), $MachinePrecision] + -0.5), $MachinePrecision] * N[(x * x), $MachinePrecision] + -1.0), $MachinePrecision] * N[(x * x), $MachinePrecision]), $MachinePrecision] / N[Log[1 + x], $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]

Derivation

1. Initial program 3.8%

   \[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \]
2. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(1 - x\right)}}{\log \left(1 + x\right)} \]

   2. flip-- N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   3. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 \cdot 1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   4. lower-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   5. metadata-eval N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1} - x \cdot x}{1 + x}\right)}{\log \left(1 + x\right)} \]

   6. lower--.f64 N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1 - x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   7. lower-*.f64 4.3

      \[\leadsto \frac{\log \left(\frac{1 - \color{blue}{x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   8. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   9. +-commutative N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x + 1}}\right)}{\log \left(1 + x\right)} \]

   10. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x + \color{blue}{1 \cdot 1}}\right)}{\log \left(1 + x\right)} \]

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

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right) \cdot 1}}\right)}{\log \left(1 + x\right)} \]

   12. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1} \cdot 1}\right)}{\log \left(1 + x\right)} \]

   13. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

   14. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   15. lower--.f64 N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   16. metadata-eval 4.3

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

3. Applied rewrites 4.3%

   \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]
4. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}{\log \left(1 + x\right)}} \]

   2. lift-log.f64 N/A

      \[\leadsto \frac{\color{blue}{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   3. lift-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   4. log-div N/A

      \[\leadsto \frac{\color{blue}{\log \left(1 - x \cdot x\right) - \log \left(x - -1\right)}}{\log \left(1 + x\right)} \]

   5. lift--.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x - -1\right)}}{\log \left(1 + x\right)} \]

   6. sub-negate1 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x + \left(\mathsf{neg}\left(-1\right)\right)\right)}}{\log \left(1 + x\right)} \]

   7. metadata-eval N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \left(x + \color{blue}{1}\right)}{\log \left(1 + x\right)} \]

   8. +-commutative N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(1 + x\right)}}{\log \left(1 + x\right)} \]

   9. lift-log1p.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \color{blue}{\mathsf{log1p}\left(x\right)}}{\log \left(1 + x\right)} \]

   10. lift-log.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\log \left(1 + x\right)}} \]

   11. lift-+.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\log \color{blue}{\left(1 + x\right)}} \]

   12. lift-log1p.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\mathsf{log1p}\left(x\right)}} \]

   13. div-sub N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   14. lower--.f64 N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

5. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]
6. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{\frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   2. *-inverses 100.0

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{1} \]

7. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1} \]

8. Taylor expanded in x around 0

   \[\leadsto \frac{\color{blue}{{x}^{2} \cdot \left({x}^{2} \cdot \left(\frac{-1}{3} \cdot {x}^{2} - \frac{1}{2}\right) - 1\right)}}{\mathsf{log1p}\left(x\right)} - 1 \]
9. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \frac{\left({x}^{2} \cdot \left(\frac{-1}{3} \cdot {x}^{2} - \frac{1}{2}\right) - 1\right) \cdot \color{blue}{{x}^{2}}}{\mathsf{log1p}\left(x\right)} - 1 \]

   2. lower-*.f64 N/A

      \[\leadsto \frac{\left({x}^{2} \cdot \left(\frac{-1}{3} \cdot {x}^{2} - \frac{1}{2}\right) - 1\right) \cdot \color{blue}{{x}^{2}}}{\mathsf{log1p}\left(x\right)} - 1 \]

   3. sub-negate1 N/A

      \[\leadsto \frac{\left({x}^{2} \cdot \left(\frac{-1}{3} \cdot {x}^{2} - \frac{1}{2}\right) + \left(\mathsf{neg}\left(1\right)\right)\right) \cdot {\color{blue}{x}}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   4. *-commutative N/A

      \[\leadsto \frac{\left(\left(\frac{-1}{3} \cdot {x}^{2} - \frac{1}{2}\right) \cdot {x}^{2} + \left(\mathsf{neg}\left(1\right)\right)\right) \cdot {x}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   5. metadata-eval N/A

      \[\leadsto \frac{\left(\left(\frac{-1}{3} \cdot {x}^{2} - \frac{1}{2}\right) \cdot {x}^{2} + -1\right) \cdot {x}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   6. lower-fma.f64 N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{-1}{3} \cdot {x}^{2} - \frac{1}{2}, {x}^{2}, -1\right) \cdot {\color{blue}{x}}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   7. sub-negate1 N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{-1}{3} \cdot {x}^{2} + \left(\mathsf{neg}\left(\frac{1}{2}\right)\right), {x}^{2}, -1\right) \cdot {x}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   8. metadata-eval N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{-1}{3} \cdot {x}^{2} + \frac{-1}{2}, {x}^{2}, -1\right) \cdot {x}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   9. lower-fma.f64 N/A

      \[\leadsto \frac{\mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, {x}^{2}, \frac{-1}{2}\right), {x}^{2}, -1\right) \cdot {x}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   10. unpow2 N/A

       \[\leadsto \frac{\mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, x \cdot x, \frac{-1}{2}\right), {x}^{2}, -1\right) \cdot {x}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   11. lower-*.f64 N/A

       \[\leadsto \frac{\mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, x \cdot x, \frac{-1}{2}\right), {x}^{2}, -1\right) \cdot {x}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   12. unpow2 N/A

       \[\leadsto \frac{\mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, x \cdot x, \frac{-1}{2}\right), x \cdot x, -1\right) \cdot {x}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   13. lower-*.f64 N/A

       \[\leadsto \frac{\mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, x \cdot x, \frac{-1}{2}\right), x \cdot x, -1\right) \cdot {x}^{2}}{\mathsf{log1p}\left(x\right)} - 1 \]

   14. unpow2 N/A

       \[\leadsto \frac{\mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, x \cdot x, \frac{-1}{2}\right), x \cdot x, -1\right) \cdot \left(x \cdot \color{blue}{x}\right)}{\mathsf{log1p}\left(x\right)} - 1 \]

   15. lower-*.f64 99.8

       \[\leadsto \frac{\mathsf{fma}\left(\mathsf{fma}\left(-0.3333333333333333, x \cdot x, -0.5\right), x \cdot x, -1\right) \cdot \left(x \cdot \color{blue}{x}\right)}{\mathsf{log1p}\left(x\right)} - 1 \]

10. Applied rewrites 99.8%

    \[\leadsto \frac{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(-0.3333333333333333, x \cdot x, -0.5\right), x \cdot x, -1\right) \cdot \left(x \cdot x\right)}}{\mathsf{log1p}\left(x\right)} - 1 \]
11. Add Preprocessing

Alternative 4: 99.7% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.25, x, 0.3333333333333333\right), x, -0.5\right), x, 1\right) \cdot x} - 1 \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (-
  (/
   (log1p (* (- x) x))
   (* (fma (fma (fma -0.25 x 0.3333333333333333) x -0.5) x 1.0) x))
  1.0))

C

double code(double x) {
	return (log1p((-x * x)) / (fma(fma(fma(-0.25, x, 0.3333333333333333), x, -0.5), x, 1.0) * x)) - 1.0;
}

Julia

function code(x)
	return Float64(Float64(log1p(Float64(Float64(-x) * x)) / Float64(fma(fma(fma(-0.25, x, 0.3333333333333333), x, -0.5), x, 1.0) * x)) - 1.0)
end

Wolfram

code[x_] := N[(N[(N[Log[1 + N[((-x) * x), $MachinePrecision]], $MachinePrecision] / N[(N[(N[(N[(-0.25 * x + 0.3333333333333333), $MachinePrecision] * x + -0.5), $MachinePrecision] * x + 1.0), $MachinePrecision] * x), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]

Derivation

1. Initial program 3.8%

   \[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \]
2. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(1 - x\right)}}{\log \left(1 + x\right)} \]

   2. flip-- N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   3. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 \cdot 1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   4. lower-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   5. metadata-eval N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1} - x \cdot x}{1 + x}\right)}{\log \left(1 + x\right)} \]

   6. lower--.f64 N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1 - x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   7. lower-*.f64 4.3

      \[\leadsto \frac{\log \left(\frac{1 - \color{blue}{x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   8. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   9. +-commutative N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x + 1}}\right)}{\log \left(1 + x\right)} \]

   10. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x + \color{blue}{1 \cdot 1}}\right)}{\log \left(1 + x\right)} \]

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

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right) \cdot 1}}\right)}{\log \left(1 + x\right)} \]

   12. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1} \cdot 1}\right)}{\log \left(1 + x\right)} \]

   13. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

   14. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   15. lower--.f64 N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   16. metadata-eval 4.3

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

3. Applied rewrites 4.3%

   \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]
4. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}{\log \left(1 + x\right)}} \]

   2. lift-log.f64 N/A

      \[\leadsto \frac{\color{blue}{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   3. lift-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   4. log-div N/A

      \[\leadsto \frac{\color{blue}{\log \left(1 - x \cdot x\right) - \log \left(x - -1\right)}}{\log \left(1 + x\right)} \]

   5. lift--.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x - -1\right)}}{\log \left(1 + x\right)} \]

   6. sub-negate1 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x + \left(\mathsf{neg}\left(-1\right)\right)\right)}}{\log \left(1 + x\right)} \]

   7. metadata-eval N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \left(x + \color{blue}{1}\right)}{\log \left(1 + x\right)} \]

   8. +-commutative N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(1 + x\right)}}{\log \left(1 + x\right)} \]

   9. lift-log1p.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \color{blue}{\mathsf{log1p}\left(x\right)}}{\log \left(1 + x\right)} \]

   10. lift-log.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\log \left(1 + x\right)}} \]

   11. lift-+.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\log \color{blue}{\left(1 + x\right)}} \]

   12. lift-log1p.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\mathsf{log1p}\left(x\right)}} \]

   13. div-sub N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   14. lower--.f64 N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

5. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]
6. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{\frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   2. *-inverses 100.0

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{1} \]

7. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1} \]

8. Taylor expanded in x around 0

   \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\color{blue}{x \cdot \left(1 + x \cdot \left(x \cdot \left(\frac{1}{3} + \frac{-1}{4} \cdot x\right) - \frac{1}{2}\right)\right)}} - 1 \]
9. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\left(1 + x \cdot \left(x \cdot \left(\frac{1}{3} + \frac{-1}{4} \cdot x\right) - \frac{1}{2}\right)\right) \cdot \color{blue}{x}} - 1 \]

   2. lower-*.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\left(1 + x \cdot \left(x \cdot \left(\frac{1}{3} + \frac{-1}{4} \cdot x\right) - \frac{1}{2}\right)\right) \cdot \color{blue}{x}} - 1 \]

   3. +-commutative N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\left(x \cdot \left(x \cdot \left(\frac{1}{3} + \frac{-1}{4} \cdot x\right) - \frac{1}{2}\right) + 1\right) \cdot x} - 1 \]

   4. *-commutative N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\left(\left(x \cdot \left(\frac{1}{3} + \frac{-1}{4} \cdot x\right) - \frac{1}{2}\right) \cdot x + 1\right) \cdot x} - 1 \]

   5. lower-fma.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{fma}\left(x \cdot \left(\frac{1}{3} + \frac{-1}{4} \cdot x\right) - \frac{1}{2}, x, 1\right) \cdot x} - 1 \]

   6. sub-negate1 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{fma}\left(x \cdot \left(\frac{1}{3} + \frac{-1}{4} \cdot x\right) + \left(\mathsf{neg}\left(\frac{1}{2}\right)\right), x, 1\right) \cdot x} - 1 \]

   7. *-commutative N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{fma}\left(\left(\frac{1}{3} + \frac{-1}{4} \cdot x\right) \cdot x + \left(\mathsf{neg}\left(\frac{1}{2}\right)\right), x, 1\right) \cdot x} - 1 \]

   8. metadata-eval N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{fma}\left(\left(\frac{1}{3} + \frac{-1}{4} \cdot x\right) \cdot x + \frac{-1}{2}, x, 1\right) \cdot x} - 1 \]

   9. lower-fma.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{3} + \frac{-1}{4} \cdot x, x, \frac{-1}{2}\right), x, 1\right) \cdot x} - 1 \]

   10. +-commutative N/A

       \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{4} \cdot x + \frac{1}{3}, x, \frac{-1}{2}\right), x, 1\right) \cdot x} - 1 \]

   11. lower-fma.f64 99.7

       \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.25, x, 0.3333333333333333\right), x, -0.5\right), x, 1\right) \cdot x} - 1 \]

10. Applied rewrites 99.7%

    \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.25, x, 0.3333333333333333\right), x, -0.5\right), x, 1\right) \cdot x}} - 1 \]
11. Add Preprocessing

Alternative 5: 99.6% accurate, 8.1× speedup

Math

\[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.2916666666666667, x, -0.4166666666666667\right), x, -0.5\right), x, -1\right) \cdot x - 1 \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (-
  (*
   (fma (fma (fma -0.2916666666666667 x -0.4166666666666667) x -0.5) x -1.0)
   x)
  1.0))

C

double code(double x) {
	return (fma(fma(fma(-0.2916666666666667, x, -0.4166666666666667), x, -0.5), x, -1.0) * x) - 1.0;
}

Julia

function code(x)
	return Float64(Float64(fma(fma(fma(-0.2916666666666667, x, -0.4166666666666667), x, -0.5), x, -1.0) * x) - 1.0)
end

Wolfram

code[x_] := N[(N[(N[(N[(N[(-0.2916666666666667 * x + -0.4166666666666667), $MachinePrecision] * x + -0.5), $MachinePrecision] * x + -1.0), $MachinePrecision] * x), $MachinePrecision] - 1.0), $MachinePrecision]

Derivation

1. Initial program 3.8%

   \[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \]
2. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(1 - x\right)}}{\log \left(1 + x\right)} \]

   2. flip-- N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   3. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 \cdot 1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   4. lower-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   5. metadata-eval N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1} - x \cdot x}{1 + x}\right)}{\log \left(1 + x\right)} \]

   6. lower--.f64 N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1 - x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   7. lower-*.f64 4.3

      \[\leadsto \frac{\log \left(\frac{1 - \color{blue}{x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   8. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   9. +-commutative N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x + 1}}\right)}{\log \left(1 + x\right)} \]

   10. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x + \color{blue}{1 \cdot 1}}\right)}{\log \left(1 + x\right)} \]

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

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right) \cdot 1}}\right)}{\log \left(1 + x\right)} \]

   12. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1} \cdot 1}\right)}{\log \left(1 + x\right)} \]

   13. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

   14. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   15. lower--.f64 N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   16. metadata-eval 4.3

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

3. Applied rewrites 4.3%

   \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]
4. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}{\log \left(1 + x\right)}} \]

   2. lift-log.f64 N/A

      \[\leadsto \frac{\color{blue}{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   3. lift-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   4. log-div N/A

      \[\leadsto \frac{\color{blue}{\log \left(1 - x \cdot x\right) - \log \left(x - -1\right)}}{\log \left(1 + x\right)} \]

   5. lift--.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x - -1\right)}}{\log \left(1 + x\right)} \]

   6. sub-negate1 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x + \left(\mathsf{neg}\left(-1\right)\right)\right)}}{\log \left(1 + x\right)} \]

   7. metadata-eval N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \left(x + \color{blue}{1}\right)}{\log \left(1 + x\right)} \]

   8. +-commutative N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(1 + x\right)}}{\log \left(1 + x\right)} \]

   9. lift-log1p.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \color{blue}{\mathsf{log1p}\left(x\right)}}{\log \left(1 + x\right)} \]

   10. lift-log.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\log \left(1 + x\right)}} \]

   11. lift-+.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\log \color{blue}{\left(1 + x\right)}} \]

   12. lift-log1p.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\mathsf{log1p}\left(x\right)}} \]

   13. div-sub N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   14. lower--.f64 N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

5. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]
6. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{\frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   2. *-inverses 100.0

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{1} \]

7. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1} \]

8. Taylor expanded in x around 0

   \[\leadsto \color{blue}{x \cdot \left(x \cdot \left(x \cdot \left(\frac{-7}{24} \cdot x - \frac{5}{12}\right) - \frac{1}{2}\right) - 1\right)} - 1 \]
9. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \left(x \cdot \left(x \cdot \left(\frac{-7}{24} \cdot x - \frac{5}{12}\right) - \frac{1}{2}\right) - 1\right) \cdot \color{blue}{x} - 1 \]

   2. lower-*.f64 N/A

      \[\leadsto \left(x \cdot \left(x \cdot \left(\frac{-7}{24} \cdot x - \frac{5}{12}\right) - \frac{1}{2}\right) - 1\right) \cdot \color{blue}{x} - 1 \]

   3. sub-negate1 N/A

      \[\leadsto \left(x \cdot \left(x \cdot \left(\frac{-7}{24} \cdot x - \frac{5}{12}\right) - \frac{1}{2}\right) + \left(\mathsf{neg}\left(1\right)\right)\right) \cdot x - 1 \]

   4. *-commutative N/A

      \[\leadsto \left(\left(x \cdot \left(\frac{-7}{24} \cdot x - \frac{5}{12}\right) - \frac{1}{2}\right) \cdot x + \left(\mathsf{neg}\left(1\right)\right)\right) \cdot x - 1 \]

   5. metadata-eval N/A

      \[\leadsto \left(\left(x \cdot \left(\frac{-7}{24} \cdot x - \frac{5}{12}\right) - \frac{1}{2}\right) \cdot x + -1\right) \cdot x - 1 \]

   6. lower-fma.f64 N/A

      \[\leadsto \mathsf{fma}\left(x \cdot \left(\frac{-7}{24} \cdot x - \frac{5}{12}\right) - \frac{1}{2}, x, -1\right) \cdot x - 1 \]

   7. sub-negate1 N/A

      \[\leadsto \mathsf{fma}\left(x \cdot \left(\frac{-7}{24} \cdot x - \frac{5}{12}\right) + \left(\mathsf{neg}\left(\frac{1}{2}\right)\right), x, -1\right) \cdot x - 1 \]

   8. *-commutative N/A

      \[\leadsto \mathsf{fma}\left(\left(\frac{-7}{24} \cdot x - \frac{5}{12}\right) \cdot x + \left(\mathsf{neg}\left(\frac{1}{2}\right)\right), x, -1\right) \cdot x - 1 \]

   9. metadata-eval N/A

      \[\leadsto \mathsf{fma}\left(\left(\frac{-7}{24} \cdot x - \frac{5}{12}\right) \cdot x + \frac{-1}{2}, x, -1\right) \cdot x - 1 \]

   10. lower-fma.f64 N/A

       \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-7}{24} \cdot x - \frac{5}{12}, x, \frac{-1}{2}\right), x, -1\right) \cdot x - 1 \]

   11. sub-negate1 N/A

       \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-7}{24} \cdot x + \left(\mathsf{neg}\left(\frac{5}{12}\right)\right), x, \frac{-1}{2}\right), x, -1\right) \cdot x - 1 \]

   12. metadata-eval N/A

       \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-7}{24} \cdot x + \frac{-5}{12}, x, \frac{-1}{2}\right), x, -1\right) \cdot x - 1 \]

   13. lower-fma.f64 99.6

       \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.2916666666666667, x, -0.4166666666666667\right), x, -0.5\right), x, -1\right) \cdot x - 1 \]

10. Applied rewrites 99.6%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.2916666666666667, x, -0.4166666666666667\right), x, -0.5\right), x, -1\right) \cdot x} - 1 \]
11. Add Preprocessing

Alternative 6: 99.5% accurate, 11.5× speedup

Math

\[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.4166666666666667, x, -0.5\right), x, -1\right), x, -1\right) \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (fma (fma (fma -0.4166666666666667 x -0.5) x -1.0) x -1.0))

C

double code(double x) {
	return fma(fma(fma(-0.4166666666666667, x, -0.5), x, -1.0), x, -1.0);
}

Julia

function code(x)
	return fma(fma(fma(-0.4166666666666667, x, -0.5), x, -1.0), x, -1.0)
end

Wolfram

code[x_] := N[(N[(N[(-0.4166666666666667 * x + -0.5), $MachinePrecision] * x + -1.0), $MachinePrecision] * x + -1.0), $MachinePrecision]

Derivation

1. Initial program 3.8%

   \[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \]
2. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(1 - x\right)}}{\log \left(1 + x\right)} \]

   2. flip-- N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   3. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 \cdot 1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   4. lower-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   5. metadata-eval N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1} - x \cdot x}{1 + x}\right)}{\log \left(1 + x\right)} \]

   6. lower--.f64 N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1 - x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   7. lower-*.f64 4.3

      \[\leadsto \frac{\log \left(\frac{1 - \color{blue}{x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   8. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   9. +-commutative N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x + 1}}\right)}{\log \left(1 + x\right)} \]

   10. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x + \color{blue}{1 \cdot 1}}\right)}{\log \left(1 + x\right)} \]

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

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right) \cdot 1}}\right)}{\log \left(1 + x\right)} \]

   12. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1} \cdot 1}\right)}{\log \left(1 + x\right)} \]

   13. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

   14. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   15. lower--.f64 N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   16. metadata-eval 4.3

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

3. Applied rewrites 4.3%

   \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]
4. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}{\log \left(1 + x\right)}} \]

   2. lift-log.f64 N/A

      \[\leadsto \frac{\color{blue}{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   3. lift-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   4. log-div N/A

      \[\leadsto \frac{\color{blue}{\log \left(1 - x \cdot x\right) - \log \left(x - -1\right)}}{\log \left(1 + x\right)} \]

   5. lift--.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x - -1\right)}}{\log \left(1 + x\right)} \]

   6. sub-negate1 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x + \left(\mathsf{neg}\left(-1\right)\right)\right)}}{\log \left(1 + x\right)} \]

   7. metadata-eval N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \left(x + \color{blue}{1}\right)}{\log \left(1 + x\right)} \]

   8. +-commutative N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(1 + x\right)}}{\log \left(1 + x\right)} \]

   9. lift-log1p.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \color{blue}{\mathsf{log1p}\left(x\right)}}{\log \left(1 + x\right)} \]

   10. lift-log.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\log \left(1 + x\right)}} \]

   11. lift-+.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\log \color{blue}{\left(1 + x\right)}} \]

   12. lift-log1p.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\mathsf{log1p}\left(x\right)}} \]

   13. div-sub N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   14. lower--.f64 N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

5. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]
6. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{\frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   2. *-inverses 100.0

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{1} \]

7. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1} \]

8. Taylor expanded in x around 0

   \[\leadsto \color{blue}{x \cdot \left(x \cdot \left(\frac{-5}{12} \cdot x - \frac{1}{2}\right) - 1\right) - 1} \]
9. Step-by-step derivation

   1. sub-negate1 N/A

      \[\leadsto x \cdot \left(x \cdot \left(\frac{-5}{12} \cdot x - \frac{1}{2}\right) - 1\right) + \color{blue}{\left(\mathsf{neg}\left(1\right)\right)} \]

   2. *-commutative N/A

      \[\leadsto \left(x \cdot \left(\frac{-5}{12} \cdot x - \frac{1}{2}\right) - 1\right) \cdot x + \left(\mathsf{neg}\left(\color{blue}{1}\right)\right) \]

   3. metadata-eval N/A

      \[\leadsto \left(x \cdot \left(\frac{-5}{12} \cdot x - \frac{1}{2}\right) - 1\right) \cdot x + -1 \]

   4. lower-fma.f64 N/A

      \[\leadsto \mathsf{fma}\left(x \cdot \left(\frac{-5}{12} \cdot x - \frac{1}{2}\right) - 1, \color{blue}{x}, -1\right) \]

   5. sub-negate1 N/A

      \[\leadsto \mathsf{fma}\left(x \cdot \left(\frac{-5}{12} \cdot x - \frac{1}{2}\right) + \left(\mathsf{neg}\left(1\right)\right), x, -1\right) \]

   6. *-commutative N/A

      \[\leadsto \mathsf{fma}\left(\left(\frac{-5}{12} \cdot x - \frac{1}{2}\right) \cdot x + \left(\mathsf{neg}\left(1\right)\right), x, -1\right) \]

   7. metadata-eval N/A

      \[\leadsto \mathsf{fma}\left(\left(\frac{-5}{12} \cdot x - \frac{1}{2}\right) \cdot x + -1, x, -1\right) \]

   8. lower-fma.f64 N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-5}{12} \cdot x - \frac{1}{2}, x, -1\right), x, -1\right) \]

   9. sub-negate1 N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-5}{12} \cdot x + \left(\mathsf{neg}\left(\frac{1}{2}\right)\right), x, -1\right), x, -1\right) \]

   10. metadata-eval N/A

       \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-5}{12} \cdot x + \frac{-1}{2}, x, -1\right), x, -1\right) \]

   11. lower-fma.f64 99.5

       \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.4166666666666667, x, -0.5\right), x, -1\right), x, -1\right) \]

10. Applied rewrites 99.5%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-0.4166666666666667, x, -0.5\right), x, -1\right), x, -1\right)} \]
11. Add Preprocessing

Alternative 7: 99.4% accurate, 16.8× speedup

Math

\[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(-0.5, x, -1\right), x, -1\right) \end{array} \]

FPCore

(FPCore (x) :precision binary64 (fma (fma -0.5 x -1.0) x -1.0))

C

double code(double x) {
	return fma(fma(-0.5, x, -1.0), x, -1.0);
}

Julia

function code(x)
	return fma(fma(-0.5, x, -1.0), x, -1.0)
end

Wolfram

code[x_] := N[(N[(-0.5 * x + -1.0), $MachinePrecision] * x + -1.0), $MachinePrecision]

Derivation

1. Initial program 3.8%

   \[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \]
2. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(1 - x\right)}}{\log \left(1 + x\right)} \]

   2. flip-- N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   3. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 \cdot 1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   4. lower-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   5. metadata-eval N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1} - x \cdot x}{1 + x}\right)}{\log \left(1 + x\right)} \]

   6. lower--.f64 N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1 - x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   7. lower-*.f64 4.3

      \[\leadsto \frac{\log \left(\frac{1 - \color{blue}{x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   8. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   9. +-commutative N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x + 1}}\right)}{\log \left(1 + x\right)} \]

   10. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x + \color{blue}{1 \cdot 1}}\right)}{\log \left(1 + x\right)} \]

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

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right) \cdot 1}}\right)}{\log \left(1 + x\right)} \]

   12. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1} \cdot 1}\right)}{\log \left(1 + x\right)} \]

   13. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

   14. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   15. lower--.f64 N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   16. metadata-eval 4.3

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

3. Applied rewrites 4.3%

   \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]
4. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}{\log \left(1 + x\right)}} \]

   2. lift-log.f64 N/A

      \[\leadsto \frac{\color{blue}{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   3. lift-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   4. log-div N/A

      \[\leadsto \frac{\color{blue}{\log \left(1 - x \cdot x\right) - \log \left(x - -1\right)}}{\log \left(1 + x\right)} \]

   5. lift--.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x - -1\right)}}{\log \left(1 + x\right)} \]

   6. sub-negate1 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x + \left(\mathsf{neg}\left(-1\right)\right)\right)}}{\log \left(1 + x\right)} \]

   7. metadata-eval N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \left(x + \color{blue}{1}\right)}{\log \left(1 + x\right)} \]

   8. +-commutative N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(1 + x\right)}}{\log \left(1 + x\right)} \]

   9. lift-log1p.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \color{blue}{\mathsf{log1p}\left(x\right)}}{\log \left(1 + x\right)} \]

   10. lift-log.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\log \left(1 + x\right)}} \]

   11. lift-+.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\log \color{blue}{\left(1 + x\right)}} \]

   12. lift-log1p.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\mathsf{log1p}\left(x\right)}} \]

   13. div-sub N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   14. lower--.f64 N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

5. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]
6. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{\frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   2. *-inverses 100.0

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{1} \]

7. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1} \]

8. Taylor expanded in x around 0

   \[\leadsto \color{blue}{x \cdot \left(\frac{-1}{2} \cdot x - 1\right) - 1} \]
9. Step-by-step derivation

   1. sub-negate1 N/A

      \[\leadsto x \cdot \left(\frac{-1}{2} \cdot x - 1\right) + \color{blue}{\left(\mathsf{neg}\left(1\right)\right)} \]

   2. *-commutative N/A

      \[\leadsto \left(\frac{-1}{2} \cdot x - 1\right) \cdot x + \left(\mathsf{neg}\left(\color{blue}{1}\right)\right) \]

   3. metadata-eval N/A

      \[\leadsto \left(\frac{-1}{2} \cdot x - 1\right) \cdot x + -1 \]

   4. lower-fma.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{-1}{2} \cdot x - 1, \color{blue}{x}, -1\right) \]

   5. sub-negate1 N/A

      \[\leadsto \mathsf{fma}\left(\frac{-1}{2} \cdot x + \left(\mathsf{neg}\left(1\right)\right), x, -1\right) \]

   6. metadata-eval N/A

      \[\leadsto \mathsf{fma}\left(\frac{-1}{2} \cdot x + -1, x, -1\right) \]

   7. lower-fma.f64 99.4

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(-0.5, x, -1\right), x, -1\right) \]

10. Applied rewrites 99.4%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(-0.5, x, -1\right), x, -1\right)} \]
11. Add Preprocessing

Alternative 8: 99.0% accurate, 36.3× speedup

Math

\[\begin{array}{l} \\ \left(-x\right) - 1 \end{array} \]

FPCore

(FPCore (x) :precision binary64 (- (- x) 1.0))

C

double code(double x) {
	return -x - 1.0;
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

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

real(8) function code(x)
use fmin_fmax_functions
    real(8), intent (in) :: x
    code = -x - 1.0d0
end function

Java

public static double code(double x) {
	return -x - 1.0;
}

Python

def code(x):
	return -x - 1.0

Julia

function code(x)
	return Float64(Float64(-x) - 1.0)
end

MATLAB

function tmp = code(x)
	tmp = -x - 1.0;
end

Wolfram

code[x_] := N[((-x) - 1.0), $MachinePrecision]

Derivation

1. Initial program 3.8%

   \[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \]
2. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(1 - x\right)}}{\log \left(1 + x\right)} \]

   2. flip-- N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   3. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 \cdot 1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   4. lower-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   5. metadata-eval N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1} - x \cdot x}{1 + x}\right)}{\log \left(1 + x\right)} \]

   6. lower--.f64 N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1 - x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   7. lower-*.f64 4.3

      \[\leadsto \frac{\log \left(\frac{1 - \color{blue}{x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   8. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   9. +-commutative N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x + 1}}\right)}{\log \left(1 + x\right)} \]

   10. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x + \color{blue}{1 \cdot 1}}\right)}{\log \left(1 + x\right)} \]

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

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right) \cdot 1}}\right)}{\log \left(1 + x\right)} \]

   12. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1} \cdot 1}\right)}{\log \left(1 + x\right)} \]

   13. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

   14. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   15. lower--.f64 N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   16. metadata-eval 4.3

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

3. Applied rewrites 4.3%

   \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]
4. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}{\log \left(1 + x\right)}} \]

   2. lift-log.f64 N/A

      \[\leadsto \frac{\color{blue}{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   3. lift-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   4. log-div N/A

      \[\leadsto \frac{\color{blue}{\log \left(1 - x \cdot x\right) - \log \left(x - -1\right)}}{\log \left(1 + x\right)} \]

   5. lift--.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x - -1\right)}}{\log \left(1 + x\right)} \]

   6. sub-negate1 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x + \left(\mathsf{neg}\left(-1\right)\right)\right)}}{\log \left(1 + x\right)} \]

   7. metadata-eval N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \left(x + \color{blue}{1}\right)}{\log \left(1 + x\right)} \]

   8. +-commutative N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(1 + x\right)}}{\log \left(1 + x\right)} \]

   9. lift-log1p.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \color{blue}{\mathsf{log1p}\left(x\right)}}{\log \left(1 + x\right)} \]

   10. lift-log.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\log \left(1 + x\right)}} \]

   11. lift-+.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\log \color{blue}{\left(1 + x\right)}} \]

   12. lift-log1p.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\mathsf{log1p}\left(x\right)}} \]

   13. div-sub N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   14. lower--.f64 N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

5. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]
6. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{\frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   2. *-inverses 100.0

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{1} \]

7. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1} \]

8. Taylor expanded in x around 0

   \[\leadsto \color{blue}{-1 \cdot x} - 1 \]
9. Step-by-step derivation

   1. mul-1-neg N/A

      \[\leadsto \left(\mathsf{neg}\left(x\right)\right) - 1 \]

   2. lift-neg.f64 99.0

      \[\leadsto \left(-x\right) - 1 \]

10. Applied rewrites 99.0%

    \[\leadsto \color{blue}{\left(-x\right)} - 1 \]
11. Add Preprocessing

Alternative 9: 98.1% accurate, 218.0× speedup

Math

\[\begin{array}{l} \\ -1 \end{array} \]

FPCore

(FPCore (x) :precision binary64 -1.0)

C

double code(double x) {
	return -1.0;
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

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

real(8) function code(x)
use fmin_fmax_functions
    real(8), intent (in) :: x
    code = -1.0d0
end function

Java

public static double code(double x) {
	return -1.0;
}

Python

def code(x):
	return -1.0

Julia

function code(x)
	return -1.0
end

MATLAB

function tmp = code(x)
	tmp = -1.0;
end

Wolfram

code[x_] := -1.0

Derivation

1. Initial program 3.8%

   \[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)} \]
2. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(1 - x\right)}}{\log \left(1 + x\right)} \]

   2. flip-- N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   3. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 \cdot 1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   4. lower-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 \cdot 1 - x \cdot x}{1 + x}\right)}}{\log \left(1 + x\right)} \]

   5. metadata-eval N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1} - x \cdot x}{1 + x}\right)}{\log \left(1 + x\right)} \]

   6. lower--.f64 N/A

      \[\leadsto \frac{\log \left(\frac{\color{blue}{1 - x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   7. lower-*.f64 4.3

      \[\leadsto \frac{\log \left(\frac{1 - \color{blue}{x \cdot x}}{1 + x}\right)}{\log \left(1 + x\right)} \]

   8. lift-+.f64 N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{1 + x}}\right)}{\log \left(1 + x\right)} \]

   9. +-commutative N/A

      \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x + 1}}\right)}{\log \left(1 + x\right)} \]

   10. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x + \color{blue}{1 \cdot 1}}\right)}{\log \left(1 + x\right)} \]

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

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right) \cdot 1}}\right)}{\log \left(1 + x\right)} \]

   12. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1} \cdot 1}\right)}{\log \left(1 + x\right)} \]

   13. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

   14. metadata-eval N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   15. lower--.f64 N/A

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{\color{blue}{x - \left(\mathsf{neg}\left(1\right)\right)}}\right)}{\log \left(1 + x\right)} \]

   16. metadata-eval 4.3

       \[\leadsto \frac{\log \left(\frac{1 - x \cdot x}{x - \color{blue}{-1}}\right)}{\log \left(1 + x\right)} \]

3. Applied rewrites 4.3%

   \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]
4. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}{\log \left(1 + x\right)}} \]

   2. lift-log.f64 N/A

      \[\leadsto \frac{\color{blue}{\log \left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   3. lift-/.f64 N/A

      \[\leadsto \frac{\log \color{blue}{\left(\frac{1 - x \cdot x}{x - -1}\right)}}{\log \left(1 + x\right)} \]

   4. log-div N/A

      \[\leadsto \frac{\color{blue}{\log \left(1 - x \cdot x\right) - \log \left(x - -1\right)}}{\log \left(1 + x\right)} \]

   5. lift--.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x - -1\right)}}{\log \left(1 + x\right)} \]

   6. sub-negate1 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(x + \left(\mathsf{neg}\left(-1\right)\right)\right)}}{\log \left(1 + x\right)} \]

   7. metadata-eval N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \left(x + \color{blue}{1}\right)}{\log \left(1 + x\right)} \]

   8. +-commutative N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \log \color{blue}{\left(1 + x\right)}}{\log \left(1 + x\right)} \]

   9. lift-log1p.f64 N/A

      \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \color{blue}{\mathsf{log1p}\left(x\right)}}{\log \left(1 + x\right)} \]

   10. lift-log.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\log \left(1 + x\right)}} \]

   11. lift-+.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\log \color{blue}{\left(1 + x\right)}} \]

   12. lift-log1p.f64 N/A

       \[\leadsto \frac{\log \left(1 - x \cdot x\right) - \mathsf{log1p}\left(x\right)}{\color{blue}{\mathsf{log1p}\left(x\right)}} \]

   13. div-sub N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   14. lower--.f64 N/A

       \[\leadsto \color{blue}{\frac{\log \left(1 - x \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

5. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]
6. Step-by-step derivation

   1. lift-/.f64 N/A

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{\frac{\mathsf{log1p}\left(x\right)}{\mathsf{log1p}\left(x\right)}} \]

   2. *-inverses 100.0

      \[\leadsto \frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - \color{blue}{1} \]

7. Applied rewrites 100.0%

   \[\leadsto \color{blue}{\frac{\mathsf{log1p}\left(\left(-x\right) \cdot x\right)}{\mathsf{log1p}\left(x\right)} - 1} \]

8. Taylor expanded in x around 0

   \[\leadsto \color{blue}{-1} \]
9. Step-by-step derivation

10. Applied rewrites 98.1%

    \[\leadsto \color{blue}{-1} \]
11. Add Preprocessing

Developer Target 1: 100.0% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \frac{\mathsf{log1p}\left(-x\right)}{\mathsf{log1p}\left(x\right)} \end{array} \]

FPCore

(FPCore (x) :precision binary64 (/ (log1p (- x)) (log1p x)))

C

double code(double x) {
	return log1p(-x) / log1p(x);
}

Java

public static double code(double x) {
	return Math.log1p(-x) / Math.log1p(x);
}

Python

def code(x):
	return math.log1p(-x) / math.log1p(x)

Julia

function code(x)
	return Float64(log1p(Float64(-x)) / log1p(x))
end

Wolfram

code[x_] := N[(N[Log[1 + (-x)], $MachinePrecision] / N[Log[1 + x], $MachinePrecision]), $MachinePrecision]

Reproduce

herbie shell --seed 2025107 
(FPCore (x)
  :name "qlog (example 3.10)"
  :precision binary64
  :pre (<= (fabs x) 1.0)

  :alt
  (! :herbie-platform default (/ (log1p (- x)) (log1p x)))

  (/ (log (- 1.0 x)) (log (+ 1.0 x))))