
(FPCore (x) :precision binary64 (* 2.0 (atan (sqrt (/ (- 1.0 x) (+ 1.0 x))))))
double code(double x) {
return 2.0 * atan(sqrt(((1.0 - x) / (1.0 + x))));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan(sqrt(((1.0d0 - x) / (1.0d0 + x))))
end function
public static double code(double x) {
return 2.0 * Math.atan(Math.sqrt(((1.0 - x) / (1.0 + x))));
}
def code(x): return 2.0 * math.atan(math.sqrt(((1.0 - x) / (1.0 + x))))
function code(x) return Float64(2.0 * atan(sqrt(Float64(Float64(1.0 - x) / Float64(1.0 + x))))) end
function tmp = code(x) tmp = 2.0 * atan(sqrt(((1.0 - x) / (1.0 + x)))); end
code[x_] := N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(1.0 - x), $MachinePrecision] / N[(1.0 + x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} \left(\sqrt{\frac{1 - x}{1 + x}}\right)
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 10 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (x) :precision binary64 (* 2.0 (atan (sqrt (/ (- 1.0 x) (+ 1.0 x))))))
double code(double x) {
return 2.0 * atan(sqrt(((1.0 - x) / (1.0 + x))));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan(sqrt(((1.0d0 - x) / (1.0d0 + x))))
end function
public static double code(double x) {
return 2.0 * Math.atan(Math.sqrt(((1.0 - x) / (1.0 + x))));
}
def code(x): return 2.0 * math.atan(math.sqrt(((1.0 - x) / (1.0 + x))))
function code(x) return Float64(2.0 * atan(sqrt(Float64(Float64(1.0 - x) / Float64(1.0 + x))))) end
function tmp = code(x) tmp = 2.0 * atan(sqrt(((1.0 - x) / (1.0 + x)))); end
code[x_] := N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(1.0 - x), $MachinePrecision] / N[(1.0 + x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} \left(\sqrt{\frac{1 - x}{1 + x}}\right)
\end{array}
(FPCore (x) :precision binary64 (* 2.0 (atan (sqrt (/ (- 1.0 x) (+ 1.0 x))))))
double code(double x) {
return 2.0 * atan(sqrt(((1.0 - x) / (1.0 + x))));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan(sqrt(((1.0d0 - x) / (1.0d0 + x))))
end function
public static double code(double x) {
return 2.0 * Math.atan(Math.sqrt(((1.0 - x) / (1.0 + x))));
}
def code(x): return 2.0 * math.atan(math.sqrt(((1.0 - x) / (1.0 + x))))
function code(x) return Float64(2.0 * atan(sqrt(Float64(Float64(1.0 - x) / Float64(1.0 + x))))) end
function tmp = code(x) tmp = 2.0 * atan(sqrt(((1.0 - x) / (1.0 + x)))); end
code[x_] := N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(1.0 - x), $MachinePrecision] / N[(1.0 + x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} \left(\sqrt{\frac{1 - x}{1 + x}}\right)
\end{array}
Initial program 100.0%
(FPCore (x)
:precision binary64
(let* ((t_0 (+ -1.0 (* x (+ 0.5 (* x -0.5))))))
(*
2.0
(atan
(*
(+
-1.0
(*
t_0
(/
(* (* x x) (+ -1.0 (* -0.125 (* x (* x x)))))
(+ 1.0 (* (* x 0.5) (- (* x 0.5) -1.0))))))
(/ 1.0 (+ -1.0 (* x t_0))))))))
double code(double x) {
double t_0 = -1.0 + (x * (0.5 + (x * -0.5)));
return 2.0 * atan(((-1.0 + (t_0 * (((x * x) * (-1.0 + (-0.125 * (x * (x * x))))) / (1.0 + ((x * 0.5) * ((x * 0.5) - -1.0)))))) * (1.0 / (-1.0 + (x * t_0)))));
}
real(8) function code(x)
real(8), intent (in) :: x
real(8) :: t_0
t_0 = (-1.0d0) + (x * (0.5d0 + (x * (-0.5d0))))
code = 2.0d0 * atan((((-1.0d0) + (t_0 * (((x * x) * ((-1.0d0) + ((-0.125d0) * (x * (x * x))))) / (1.0d0 + ((x * 0.5d0) * ((x * 0.5d0) - (-1.0d0))))))) * (1.0d0 / ((-1.0d0) + (x * t_0)))))
end function
public static double code(double x) {
double t_0 = -1.0 + (x * (0.5 + (x * -0.5)));
return 2.0 * Math.atan(((-1.0 + (t_0 * (((x * x) * (-1.0 + (-0.125 * (x * (x * x))))) / (1.0 + ((x * 0.5) * ((x * 0.5) - -1.0)))))) * (1.0 / (-1.0 + (x * t_0)))));
}
def code(x): t_0 = -1.0 + (x * (0.5 + (x * -0.5))) return 2.0 * math.atan(((-1.0 + (t_0 * (((x * x) * (-1.0 + (-0.125 * (x * (x * x))))) / (1.0 + ((x * 0.5) * ((x * 0.5) - -1.0)))))) * (1.0 / (-1.0 + (x * t_0)))))
function code(x) t_0 = Float64(-1.0 + Float64(x * Float64(0.5 + Float64(x * -0.5)))) return Float64(2.0 * atan(Float64(Float64(-1.0 + Float64(t_0 * Float64(Float64(Float64(x * x) * Float64(-1.0 + Float64(-0.125 * Float64(x * Float64(x * x))))) / Float64(1.0 + Float64(Float64(x * 0.5) * Float64(Float64(x * 0.5) - -1.0)))))) * Float64(1.0 / Float64(-1.0 + Float64(x * t_0)))))) end
function tmp = code(x) t_0 = -1.0 + (x * (0.5 + (x * -0.5))); tmp = 2.0 * atan(((-1.0 + (t_0 * (((x * x) * (-1.0 + (-0.125 * (x * (x * x))))) / (1.0 + ((x * 0.5) * ((x * 0.5) - -1.0)))))) * (1.0 / (-1.0 + (x * t_0))))); end
code[x_] := Block[{t$95$0 = N[(-1.0 + N[(x * N[(0.5 + N[(x * -0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(2.0 * N[ArcTan[N[(N[(-1.0 + N[(t$95$0 * N[(N[(N[(x * x), $MachinePrecision] * N[(-1.0 + N[(-0.125 * N[(x * N[(x * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(N[(x * 0.5), $MachinePrecision] * N[(N[(x * 0.5), $MachinePrecision] - -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(1.0 / N[(-1.0 + N[(x * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := -1 + x \cdot \left(0.5 + x \cdot -0.5\right)\\
2 \cdot \tan^{-1} \left(\left(-1 + t\_0 \cdot \frac{\left(x \cdot x\right) \cdot \left(-1 + -0.125 \cdot \left(x \cdot \left(x \cdot x\right)\right)\right)}{1 + \left(x \cdot 0.5\right) \cdot \left(x \cdot 0.5 - -1\right)}\right) \cdot \frac{1}{-1 + x \cdot t\_0}\right)
\end{array}
\end{array}
Initial program 100.0%
Taylor expanded in x around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
*-commutativeN/A
distribute-lft-neg-inN/A
mul-1-negN/A
distribute-rgt1-inN/A
+-commutativeN/A
*-lowering-*.f64N/A
mul-1-negN/A
sub-negN/A
--lowering--.f6499.2%
Simplified99.2%
+-commutativeN/A
flip-+N/A
div-invN/A
*-lowering-*.f64N/A
Applied egg-rr99.2%
Taylor expanded in x around 0
unpow2N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f6499.3%
Simplified99.3%
associate-*r*N/A
flip3-+N/A
associate-*r/N/A
/-lowering-/.f64N/A
Applied egg-rr99.3%
Final simplification99.3%
(FPCore (x)
:precision binary64
(*
2.0
(atan
(*
(/ 1.0 (+ -1.0 (* x (+ -1.0 (* x (+ 0.5 (* x -0.5)))))))
(+ -1.0 (* (* x x) (+ 1.0 (* x (+ -1.0 (* x 0.75))))))))))
double code(double x) {
return 2.0 * atan(((1.0 / (-1.0 + (x * (-1.0 + (x * (0.5 + (x * -0.5))))))) * (-1.0 + ((x * x) * (1.0 + (x * (-1.0 + (x * 0.75))))))));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan(((1.0d0 / ((-1.0d0) + (x * ((-1.0d0) + (x * (0.5d0 + (x * (-0.5d0)))))))) * ((-1.0d0) + ((x * x) * (1.0d0 + (x * ((-1.0d0) + (x * 0.75d0))))))))
end function
public static double code(double x) {
return 2.0 * Math.atan(((1.0 / (-1.0 + (x * (-1.0 + (x * (0.5 + (x * -0.5))))))) * (-1.0 + ((x * x) * (1.0 + (x * (-1.0 + (x * 0.75))))))));
}
def code(x): return 2.0 * math.atan(((1.0 / (-1.0 + (x * (-1.0 + (x * (0.5 + (x * -0.5))))))) * (-1.0 + ((x * x) * (1.0 + (x * (-1.0 + (x * 0.75))))))))
function code(x) return Float64(2.0 * atan(Float64(Float64(1.0 / Float64(-1.0 + Float64(x * Float64(-1.0 + Float64(x * Float64(0.5 + Float64(x * -0.5))))))) * Float64(-1.0 + Float64(Float64(x * x) * Float64(1.0 + Float64(x * Float64(-1.0 + Float64(x * 0.75))))))))) end
function tmp = code(x) tmp = 2.0 * atan(((1.0 / (-1.0 + (x * (-1.0 + (x * (0.5 + (x * -0.5))))))) * (-1.0 + ((x * x) * (1.0 + (x * (-1.0 + (x * 0.75)))))))); end
code[x_] := N[(2.0 * N[ArcTan[N[(N[(1.0 / N[(-1.0 + N[(x * N[(-1.0 + N[(x * N[(0.5 + N[(x * -0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(-1.0 + N[(N[(x * x), $MachinePrecision] * N[(1.0 + N[(x * N[(-1.0 + N[(x * 0.75), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} \left(\frac{1}{-1 + x \cdot \left(-1 + x \cdot \left(0.5 + x \cdot -0.5\right)\right)} \cdot \left(-1 + \left(x \cdot x\right) \cdot \left(1 + x \cdot \left(-1 + x \cdot 0.75\right)\right)\right)\right)
\end{array}
Initial program 100.0%
Taylor expanded in x around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
*-commutativeN/A
distribute-lft-neg-inN/A
mul-1-negN/A
distribute-rgt1-inN/A
+-commutativeN/A
*-lowering-*.f64N/A
mul-1-negN/A
sub-negN/A
--lowering--.f6499.2%
Simplified99.2%
+-commutativeN/A
flip-+N/A
div-invN/A
*-lowering-*.f64N/A
Applied egg-rr99.2%
Taylor expanded in x around 0
unpow2N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f6499.3%
Simplified99.3%
Taylor expanded in x around 0
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-commutativeN/A
*-lowering-*.f6499.3%
Simplified99.3%
Final simplification99.3%
(FPCore (x) :precision binary64 (* 2.0 (atan (+ (/ 1.0 (+ 1.0 x)) (* x (* x (- (* x (- (* x (+ x -1.0)) -0.5)) 0.5)))))))
double code(double x) {
return 2.0 * atan(((1.0 / (1.0 + x)) + (x * (x * ((x * ((x * (x + -1.0)) - -0.5)) - 0.5)))));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan(((1.0d0 / (1.0d0 + x)) + (x * (x * ((x * ((x * (x + (-1.0d0))) - (-0.5d0))) - 0.5d0)))))
end function
public static double code(double x) {
return 2.0 * Math.atan(((1.0 / (1.0 + x)) + (x * (x * ((x * ((x * (x + -1.0)) - -0.5)) - 0.5)))));
}
def code(x): return 2.0 * math.atan(((1.0 / (1.0 + x)) + (x * (x * ((x * ((x * (x + -1.0)) - -0.5)) - 0.5)))))
function code(x) return Float64(2.0 * atan(Float64(Float64(1.0 / Float64(1.0 + x)) + Float64(x * Float64(x * Float64(Float64(x * Float64(Float64(x * Float64(x + -1.0)) - -0.5)) - 0.5)))))) end
function tmp = code(x) tmp = 2.0 * atan(((1.0 / (1.0 + x)) + (x * (x * ((x * ((x * (x + -1.0)) - -0.5)) - 0.5))))); end
code[x_] := N[(2.0 * N[ArcTan[N[(N[(1.0 / N[(1.0 + x), $MachinePrecision]), $MachinePrecision] + N[(x * N[(x * N[(N[(x * N[(N[(x * N[(x + -1.0), $MachinePrecision]), $MachinePrecision] - -0.5), $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} \left(\frac{1}{1 + x} + x \cdot \left(x \cdot \left(x \cdot \left(x \cdot \left(x + -1\right) - -0.5\right) - 0.5\right)\right)\right)
\end{array}
Initial program 100.0%
Taylor expanded in x around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
*-commutativeN/A
distribute-lft-neg-inN/A
mul-1-negN/A
distribute-rgt1-inN/A
+-commutativeN/A
*-lowering-*.f64N/A
mul-1-negN/A
sub-negN/A
--lowering--.f6499.2%
Simplified99.2%
distribute-rgt-inN/A
associate-+r+N/A
neg-mul-1N/A
sub-negN/A
flip--N/A
metadata-evalN/A
div-subN/A
associate-+l-N/A
--lowering--.f64N/A
*-lft-identityN/A
metadata-evalN/A
cancel-sign-sub-invN/A
/-lowering-/.f64N/A
cancel-sign-sub-invN/A
metadata-evalN/A
*-lft-identityN/A
+-lowering-+.f64N/A
--lowering--.f64N/A
Applied egg-rr99.2%
Taylor expanded in x around 0
unpow2N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
mul-1-negN/A
sub-negN/A
--lowering--.f6499.2%
Simplified99.2%
Final simplification99.2%
(FPCore (x) :precision binary64 (* 2.0 (atan (- 1.0 (* x (- (* x (* 0.5 (+ x -1.0))) -1.0))))))
double code(double x) {
return 2.0 * atan((1.0 - (x * ((x * (0.5 * (x + -1.0))) - -1.0))));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan((1.0d0 - (x * ((x * (0.5d0 * (x + (-1.0d0)))) - (-1.0d0)))))
end function
public static double code(double x) {
return 2.0 * Math.atan((1.0 - (x * ((x * (0.5 * (x + -1.0))) - -1.0))));
}
def code(x): return 2.0 * math.atan((1.0 - (x * ((x * (0.5 * (x + -1.0))) - -1.0))))
function code(x) return Float64(2.0 * atan(Float64(1.0 - Float64(x * Float64(Float64(x * Float64(0.5 * Float64(x + -1.0))) - -1.0))))) end
function tmp = code(x) tmp = 2.0 * atan((1.0 - (x * ((x * (0.5 * (x + -1.0))) - -1.0)))); end
code[x_] := N[(2.0 * N[ArcTan[N[(1.0 - N[(x * N[(N[(x * N[(0.5 * N[(x + -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} \left(1 - x \cdot \left(x \cdot \left(0.5 \cdot \left(x + -1\right)\right) - -1\right)\right)
\end{array}
Initial program 100.0%
Taylor expanded in x around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
*-commutativeN/A
distribute-lft-neg-inN/A
mul-1-negN/A
distribute-rgt1-inN/A
+-commutativeN/A
*-lowering-*.f64N/A
mul-1-negN/A
sub-negN/A
--lowering--.f6499.2%
Simplified99.2%
Final simplification99.2%
(FPCore (x) :precision binary64 (* 2.0 (atan (* (- 1.0 x) (+ 1.0 (* x (* x 0.5)))))))
double code(double x) {
return 2.0 * atan(((1.0 - x) * (1.0 + (x * (x * 0.5)))));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan(((1.0d0 - x) * (1.0d0 + (x * (x * 0.5d0)))))
end function
public static double code(double x) {
return 2.0 * Math.atan(((1.0 - x) * (1.0 + (x * (x * 0.5)))));
}
def code(x): return 2.0 * math.atan(((1.0 - x) * (1.0 + (x * (x * 0.5)))))
function code(x) return Float64(2.0 * atan(Float64(Float64(1.0 - x) * Float64(1.0 + Float64(x * Float64(x * 0.5)))))) end
function tmp = code(x) tmp = 2.0 * atan(((1.0 - x) * (1.0 + (x * (x * 0.5))))); end
code[x_] := N[(2.0 * N[ArcTan[N[(N[(1.0 - x), $MachinePrecision] * N[(1.0 + N[(x * N[(x * 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} \left(\left(1 - x\right) \cdot \left(1 + x \cdot \left(x \cdot 0.5\right)\right)\right)
\end{array}
Initial program 100.0%
Taylor expanded in x around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
*-commutativeN/A
distribute-lft-neg-inN/A
mul-1-negN/A
distribute-rgt1-inN/A
+-commutativeN/A
*-lowering-*.f64N/A
mul-1-negN/A
sub-negN/A
--lowering--.f6499.2%
Simplified99.2%
Taylor expanded in x around 0
*-lowering-*.f64N/A
atan-lowering-atan.f64N/A
+-commutativeN/A
distribute-lft-out--N/A
*-rgt-identityN/A
unsub-negN/A
associate-+l+N/A
*-commutativeN/A
associate-*l*N/A
associate-*r*N/A
unpow2N/A
*-commutativeN/A
+-commutativeN/A
sub-negN/A
associate-*l*N/A
*-commutativeN/A
distribute-lft1-inN/A
+-commutativeN/A
Simplified99.2%
Final simplification99.2%
(FPCore (x) :precision binary64 (* 2.0 (atan (+ (- 1.0 x) (* x (* x 0.5))))))
double code(double x) {
return 2.0 * atan(((1.0 - x) + (x * (x * 0.5))));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan(((1.0d0 - x) + (x * (x * 0.5d0))))
end function
public static double code(double x) {
return 2.0 * Math.atan(((1.0 - x) + (x * (x * 0.5))));
}
def code(x): return 2.0 * math.atan(((1.0 - x) + (x * (x * 0.5))))
function code(x) return Float64(2.0 * atan(Float64(Float64(1.0 - x) + Float64(x * Float64(x * 0.5))))) end
function tmp = code(x) tmp = 2.0 * atan(((1.0 - x) + (x * (x * 0.5)))); end
code[x_] := N[(2.0 * N[ArcTan[N[(N[(1.0 - x), $MachinePrecision] + N[(x * N[(x * 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} \left(\left(1 - x\right) + x \cdot \left(x \cdot 0.5\right)\right)
\end{array}
Initial program 100.0%
Taylor expanded in x around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-commutativeN/A
*-lowering-*.f6499.1%
Simplified99.1%
distribute-lft-inN/A
associate-+r+N/A
*-commutativeN/A
neg-mul-1N/A
sub-negN/A
+-lowering-+.f64N/A
--lowering--.f64N/A
*-lowering-*.f64N/A
*-lowering-*.f6499.1%
Applied egg-rr99.1%
(FPCore (x) :precision binary64 (* 2.0 (atan (+ 1.0 (* x (+ -1.0 (* x 0.5)))))))
double code(double x) {
return 2.0 * atan((1.0 + (x * (-1.0 + (x * 0.5)))));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan((1.0d0 + (x * ((-1.0d0) + (x * 0.5d0)))))
end function
public static double code(double x) {
return 2.0 * Math.atan((1.0 + (x * (-1.0 + (x * 0.5)))));
}
def code(x): return 2.0 * math.atan((1.0 + (x * (-1.0 + (x * 0.5)))))
function code(x) return Float64(2.0 * atan(Float64(1.0 + Float64(x * Float64(-1.0 + Float64(x * 0.5)))))) end
function tmp = code(x) tmp = 2.0 * atan((1.0 + (x * (-1.0 + (x * 0.5))))); end
code[x_] := N[(2.0 * N[ArcTan[N[(1.0 + N[(x * N[(-1.0 + N[(x * 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} \left(1 + x \cdot \left(-1 + x \cdot 0.5\right)\right)
\end{array}
Initial program 100.0%
Taylor expanded in x around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
sub-negN/A
metadata-evalN/A
+-commutativeN/A
+-lowering-+.f64N/A
*-commutativeN/A
*-lowering-*.f6499.1%
Simplified99.1%
(FPCore (x) :precision binary64 (* 2.0 (atan (- 1.0 x))))
double code(double x) {
return 2.0 * atan((1.0 - x));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan((1.0d0 - x))
end function
public static double code(double x) {
return 2.0 * Math.atan((1.0 - x));
}
def code(x): return 2.0 * math.atan((1.0 - x))
function code(x) return Float64(2.0 * atan(Float64(1.0 - x))) end
function tmp = code(x) tmp = 2.0 * atan((1.0 - x)); end
code[x_] := N[(2.0 * N[ArcTan[N[(1.0 - x), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} \left(1 - x\right)
\end{array}
Initial program 100.0%
Taylor expanded in x around 0
mul-1-negN/A
sub-negN/A
--lowering--.f6498.7%
Simplified98.7%
(FPCore (x) :precision binary64 (* 2.0 (atan 1.0)))
double code(double x) {
return 2.0 * atan(1.0);
}
real(8) function code(x)
real(8), intent (in) :: x
code = 2.0d0 * atan(1.0d0)
end function
public static double code(double x) {
return 2.0 * Math.atan(1.0);
}
def code(x): return 2.0 * math.atan(1.0)
function code(x) return Float64(2.0 * atan(1.0)) end
function tmp = code(x) tmp = 2.0 * atan(1.0); end
code[x_] := N[(2.0 * N[ArcTan[1.0], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \tan^{-1} 1
\end{array}
Initial program 100.0%
Taylor expanded in x around 0
Simplified97.9%
herbie shell --seed 2024156
(FPCore (x)
:name "arccos"
:precision binary64
(* 2.0 (atan (sqrt (/ (- 1.0 x) (+ 1.0 x))))))