
(FPCore (x) :precision binary64 (let* ((t_0 (* (tan x) (tan x)))) (/ (- 1.0 t_0) (+ 1.0 t_0))))
double code(double x) {
double t_0 = tan(x) * tan(x);
return (1.0 - t_0) / (1.0 + t_0);
}
real(8) function code(x)
real(8), intent (in) :: x
real(8) :: t_0
t_0 = tan(x) * tan(x)
code = (1.0d0 - t_0) / (1.0d0 + t_0)
end function
public static double code(double x) {
double t_0 = Math.tan(x) * Math.tan(x);
return (1.0 - t_0) / (1.0 + t_0);
}
def code(x): t_0 = math.tan(x) * math.tan(x) return (1.0 - t_0) / (1.0 + t_0)
function code(x) t_0 = Float64(tan(x) * tan(x)) return Float64(Float64(1.0 - t_0) / Float64(1.0 + t_0)) end
function tmp = code(x) t_0 = tan(x) * tan(x); tmp = (1.0 - t_0) / (1.0 + t_0); end
code[x_] := Block[{t$95$0 = N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision]), $MachinePrecision]}, N[(N[(1.0 - t$95$0), $MachinePrecision] / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \tan x \cdot \tan x\\
\frac{1 - t\_0}{1 + t\_0}
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 6 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (x) :precision binary64 (let* ((t_0 (* (tan x) (tan x)))) (/ (- 1.0 t_0) (+ 1.0 t_0))))
double code(double x) {
double t_0 = tan(x) * tan(x);
return (1.0 - t_0) / (1.0 + t_0);
}
real(8) function code(x)
real(8), intent (in) :: x
real(8) :: t_0
t_0 = tan(x) * tan(x)
code = (1.0d0 - t_0) / (1.0d0 + t_0)
end function
public static double code(double x) {
double t_0 = Math.tan(x) * Math.tan(x);
return (1.0 - t_0) / (1.0 + t_0);
}
def code(x): t_0 = math.tan(x) * math.tan(x) return (1.0 - t_0) / (1.0 + t_0)
function code(x) t_0 = Float64(tan(x) * tan(x)) return Float64(Float64(1.0 - t_0) / Float64(1.0 + t_0)) end
function tmp = code(x) t_0 = tan(x) * tan(x); tmp = (1.0 - t_0) / (1.0 + t_0); end
code[x_] := Block[{t$95$0 = N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision]), $MachinePrecision]}, N[(N[(1.0 - t$95$0), $MachinePrecision] / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \tan x \cdot \tan x\\
\frac{1 - t\_0}{1 + t\_0}
\end{array}
\end{array}
(FPCore (x) :precision binary64 (let* ((t_0 (cos (* x -2.0))) (t_1 (- 1.0 t_0))) (/ (+ 1.0 (/ t_1 (- -1.0 t_0))) (+ 1.0 (/ t_1 (+ 1.0 t_0))))))
double code(double x) {
double t_0 = cos((x * -2.0));
double t_1 = 1.0 - t_0;
return (1.0 + (t_1 / (-1.0 - t_0))) / (1.0 + (t_1 / (1.0 + t_0)));
}
real(8) function code(x)
real(8), intent (in) :: x
real(8) :: t_0
real(8) :: t_1
t_0 = cos((x * (-2.0d0)))
t_1 = 1.0d0 - t_0
code = (1.0d0 + (t_1 / ((-1.0d0) - t_0))) / (1.0d0 + (t_1 / (1.0d0 + t_0)))
end function
public static double code(double x) {
double t_0 = Math.cos((x * -2.0));
double t_1 = 1.0 - t_0;
return (1.0 + (t_1 / (-1.0 - t_0))) / (1.0 + (t_1 / (1.0 + t_0)));
}
def code(x): t_0 = math.cos((x * -2.0)) t_1 = 1.0 - t_0 return (1.0 + (t_1 / (-1.0 - t_0))) / (1.0 + (t_1 / (1.0 + t_0)))
function code(x) t_0 = cos(Float64(x * -2.0)) t_1 = Float64(1.0 - t_0) return Float64(Float64(1.0 + Float64(t_1 / Float64(-1.0 - t_0))) / Float64(1.0 + Float64(t_1 / Float64(1.0 + t_0)))) end
function tmp = code(x) t_0 = cos((x * -2.0)); t_1 = 1.0 - t_0; tmp = (1.0 + (t_1 / (-1.0 - t_0))) / (1.0 + (t_1 / (1.0 + t_0))); end
code[x_] := Block[{t$95$0 = N[Cos[N[(x * -2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(1.0 - t$95$0), $MachinePrecision]}, N[(N[(1.0 + N[(t$95$1 / N[(-1.0 - t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(t$95$1 / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(x \cdot -2\right)\\
t_1 := 1 - t\_0\\
\frac{1 + \frac{t\_1}{-1 - t\_0}}{1 + \frac{t\_1}{1 + t\_0}}
\end{array}
\end{array}
Initial program 99.6%
tan-quotN/A
tan-quotN/A
frac-timesN/A
lower-/.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-+.f64N/A
sqr-cos-aN/A
lower-+.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-+.f6499.0
Applied egg-rr99.0%
tan-quotN/A
lift-sin.f64N/A
tan-quotN/A
lift-sin.f64N/A
frac-timesN/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
count-2N/A
lift-+.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift--.f64N/A
sqr-cos-aN/A
count-2N/A
lift-+.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-+.f64N/A
lift-/.f6499.7
Applied egg-rr99.7%
Taylor expanded in x around inf
div-subN/A
*-commutativeN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt1-inN/A
*-commutativeN/A
associate-/r*N/A
metadata-evalN/A
*-commutativeN/A
metadata-evalN/A
distribute-lft-neg-inN/A
*-commutativeN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt1-inN/A
Simplified99.7%
Taylor expanded in x around inf
metadata-evalN/A
distribute-lft-neg-inN/A
metadata-evalN/A
*-commutativeN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt-inN/A
cos-negN/A
associate-/r*N/A
Simplified99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (let* ((t_0 (pow (tan x) 2.0))) (/ (- 1.0 t_0) (+ 1.0 t_0))))
double code(double x) {
double t_0 = pow(tan(x), 2.0);
return (1.0 - t_0) / (1.0 + t_0);
}
real(8) function code(x)
real(8), intent (in) :: x
real(8) :: t_0
t_0 = tan(x) ** 2.0d0
code = (1.0d0 - t_0) / (1.0d0 + t_0)
end function
public static double code(double x) {
double t_0 = Math.pow(Math.tan(x), 2.0);
return (1.0 - t_0) / (1.0 + t_0);
}
def code(x): t_0 = math.pow(math.tan(x), 2.0) return (1.0 - t_0) / (1.0 + t_0)
function code(x) t_0 = tan(x) ^ 2.0 return Float64(Float64(1.0 - t_0) / Float64(1.0 + t_0)) end
function tmp = code(x) t_0 = tan(x) ^ 2.0; tmp = (1.0 - t_0) / (1.0 + t_0); end
code[x_] := Block[{t$95$0 = N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(1.0 - t$95$0), $MachinePrecision] / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\tan x}^{2}\\
\frac{1 - t\_0}{1 + t\_0}
\end{array}
\end{array}
Initial program 99.6%
lift-tan.f64N/A
lift-tan.f64N/A
lift-*.f64N/A
lift--.f6499.6
lift-*.f64N/A
pow2N/A
lower-pow.f6499.6
Applied egg-rr99.6%
Applied egg-rr99.6%
Final simplification99.6%
(FPCore (x)
:precision binary64
(let* ((t_0 (cos (* x -2.0))))
(/
(+ 1.0 (/ (- 1.0 t_0) (- -1.0 t_0)))
(+ 1.0 (fma (cos (+ x x)) -0.5 0.5)))))
double code(double x) {
double t_0 = cos((x * -2.0));
return (1.0 + ((1.0 - t_0) / (-1.0 - t_0))) / (1.0 + fma(cos((x + x)), -0.5, 0.5));
}
function code(x) t_0 = cos(Float64(x * -2.0)) return Float64(Float64(1.0 + Float64(Float64(1.0 - t_0) / Float64(-1.0 - t_0))) / Float64(1.0 + fma(cos(Float64(x + x)), -0.5, 0.5))) end
code[x_] := Block[{t$95$0 = N[Cos[N[(x * -2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(1.0 + N[(N[(1.0 - t$95$0), $MachinePrecision] / N[(-1.0 - t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(x \cdot -2\right)\\
\frac{1 + \frac{1 - t\_0}{-1 - t\_0}}{1 + \mathsf{fma}\left(\cos \left(x + x\right), -0.5, 0.5\right)}
\end{array}
\end{array}
Initial program 99.6%
tan-quotN/A
tan-quotN/A
frac-timesN/A
lower-/.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-+.f64N/A
sqr-cos-aN/A
lower-+.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-+.f6499.0
Applied egg-rr99.0%
tan-quotN/A
lift-sin.f64N/A
tan-quotN/A
lift-sin.f64N/A
frac-timesN/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
count-2N/A
lift-+.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift--.f64N/A
sqr-cos-aN/A
count-2N/A
lift-+.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-+.f64N/A
lift-/.f6499.7
Applied egg-rr99.7%
Taylor expanded in x around inf
div-subN/A
*-commutativeN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt1-inN/A
*-commutativeN/A
associate-/r*N/A
metadata-evalN/A
*-commutativeN/A
metadata-evalN/A
distribute-lft-neg-inN/A
*-commutativeN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt1-inN/A
Simplified99.7%
Taylor expanded in x around 0
Simplified58.4%
Final simplification58.4%
(FPCore (x) :precision binary64 (/ 1.0 (+ 1.0 (pow (tan x) 2.0))))
double code(double x) {
return 1.0 / (1.0 + pow(tan(x), 2.0));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 1.0d0 / (1.0d0 + (tan(x) ** 2.0d0))
end function
public static double code(double x) {
return 1.0 / (1.0 + Math.pow(Math.tan(x), 2.0));
}
def code(x): return 1.0 / (1.0 + math.pow(math.tan(x), 2.0))
function code(x) return Float64(1.0 / Float64(1.0 + (tan(x) ^ 2.0))) end
function tmp = code(x) tmp = 1.0 / (1.0 + (tan(x) ^ 2.0)); end
code[x_] := N[(1.0 / N[(1.0 + N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{1 + {\tan x}^{2}}
\end{array}
Initial program 99.6%
tan-quotN/A
clear-numN/A
tan-quotN/A
clear-numN/A
inv-powN/A
inv-powN/A
pow-prod-upN/A
lower-pow.f64N/A
clear-numN/A
tan-quotN/A
lift-tan.f64N/A
lower-/.f64N/A
metadata-eval99.4
Applied egg-rr99.4%
lift-tan.f64N/A
lift-tan.f64N/A
pow2N/A
lift-pow.f6499.4
Applied egg-rr99.4%
Taylor expanded in x around 0
Simplified52.6%
(FPCore (x) :precision binary64 (- 1.0 (* (tan x) (tan x))))
double code(double x) {
return 1.0 - (tan(x) * tan(x));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 1.0d0 - (tan(x) * tan(x))
end function
public static double code(double x) {
return 1.0 - (Math.tan(x) * Math.tan(x));
}
def code(x): return 1.0 - (math.tan(x) * math.tan(x))
function code(x) return Float64(1.0 - Float64(tan(x) * tan(x))) end
function tmp = code(x) tmp = 1.0 - (tan(x) * tan(x)); end
code[x_] := N[(1.0 - N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
1 - \tan x \cdot \tan x
\end{array}
Initial program 99.6%
Taylor expanded in x around 0
Simplified56.8%
Final simplification56.8%
(FPCore (x) :precision binary64 1.0)
double code(double x) {
return 1.0;
}
real(8) function code(x)
real(8), intent (in) :: x
code = 1.0d0
end function
public static double code(double x) {
return 1.0;
}
def code(x): return 1.0
function code(x) return 1.0 end
function tmp = code(x) tmp = 1.0; end
code[x_] := 1.0
\begin{array}{l}
\\
1
\end{array}
Initial program 99.6%
Applied egg-rr52.3%
herbie shell --seed 2024208
(FPCore (x)
:name "Trigonometry B"
:precision binary64
(/ (- 1.0 (* (tan x) (tan x))) (+ 1.0 (* (tan x) (tan x)))))