
(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 4 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 (* 2.0 x))) (t_1 (+ 0.5 (* -0.5 t_0))))
(/
(- 1.0 (/ t_1 (+ 0.5 (* 0.5 t_0))))
(+ 1.0 (/ (/ t_1 (+ 1.0 t_0)) 0.5)))))
double code(double x) {
double t_0 = cos((2.0 * x));
double t_1 = 0.5 + (-0.5 * t_0);
return (1.0 - (t_1 / (0.5 + (0.5 * t_0)))) / (1.0 + ((t_1 / (1.0 + t_0)) / 0.5));
}
real(8) function code(x)
real(8), intent (in) :: x
real(8) :: t_0
real(8) :: t_1
t_0 = cos((2.0d0 * x))
t_1 = 0.5d0 + ((-0.5d0) * t_0)
code = (1.0d0 - (t_1 / (0.5d0 + (0.5d0 * t_0)))) / (1.0d0 + ((t_1 / (1.0d0 + t_0)) / 0.5d0))
end function
public static double code(double x) {
double t_0 = Math.cos((2.0 * x));
double t_1 = 0.5 + (-0.5 * t_0);
return (1.0 - (t_1 / (0.5 + (0.5 * t_0)))) / (1.0 + ((t_1 / (1.0 + t_0)) / 0.5));
}
def code(x): t_0 = math.cos((2.0 * x)) t_1 = 0.5 + (-0.5 * t_0) return (1.0 - (t_1 / (0.5 + (0.5 * t_0)))) / (1.0 + ((t_1 / (1.0 + t_0)) / 0.5))
function code(x) t_0 = cos(Float64(2.0 * x)) t_1 = Float64(0.5 + Float64(-0.5 * t_0)) return Float64(Float64(1.0 - Float64(t_1 / Float64(0.5 + Float64(0.5 * t_0)))) / Float64(1.0 + Float64(Float64(t_1 / Float64(1.0 + t_0)) / 0.5))) end
function tmp = code(x) t_0 = cos((2.0 * x)); t_1 = 0.5 + (-0.5 * t_0); tmp = (1.0 - (t_1 / (0.5 + (0.5 * t_0)))) / (1.0 + ((t_1 / (1.0 + t_0)) / 0.5)); end
code[x_] := Block[{t$95$0 = N[Cos[N[(2.0 * x), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(0.5 + N[(-0.5 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(N[(1.0 - N[(t$95$1 / N[(0.5 + N[(0.5 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(N[(t$95$1 / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision] / 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(2 \cdot x\right)\\
t_1 := 0.5 + -0.5 \cdot t\_0\\
\frac{1 - \frac{t\_1}{0.5 + 0.5 \cdot t\_0}}{1 + \frac{\frac{t\_1}{1 + t\_0}}{0.5}}
\end{array}
\end{array}
Initial program 99.4%
/-lowering-/.f64N/A
--lowering--.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f64N/A
+-lowering-+.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.4%
Applied egg-rr99.4%
tan-quotN/A
/-lowering-/.f64N/A
sin-lowering-sin.f64N/A
cos-lowering-cos.f6499.3%
Applied egg-rr99.3%
metadata-evalN/A
pow-flipN/A
tan-quotN/A
div-invN/A
unpow-prod-downN/A
associate-/r*N/A
pow-flipN/A
metadata-evalN/A
/-lowering-/.f64N/A
pow2N/A
sqr-sin-aN/A
cos-2N/A
cos-sumN/A
cancel-sign-sub-invN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
metadata-evalN/A
cos-sumN/A
cos-2N/A
cos-lowering-cos.f64N/A
*-lowering-*.f64N/A
Applied egg-rr98.6%
tan-quotN/A
unpow2N/A
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
sqr-cos-aN/A
cancel-sign-sub-invN/A
metadata-evalN/A
*-commutativeN/A
distribute-rgt1-inN/A
associate-/r*N/A
/-lowering-/.f64N/A
Applied egg-rr99.5%
Final simplification99.5%
(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 99.4%
/-lowering-/.f64N/A
--lowering--.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f64N/A
+-lowering-+.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.4%
Applied egg-rr99.4%
(FPCore (x) :precision binary64 (- 1.0 (pow (tan x) 2.0)))
double code(double x) {
return 1.0 - pow(tan(x), 2.0);
}
real(8) function code(x)
real(8), intent (in) :: x
code = 1.0d0 - (tan(x) ** 2.0d0)
end function
public static double code(double x) {
return 1.0 - Math.pow(Math.tan(x), 2.0);
}
def code(x): return 1.0 - math.pow(math.tan(x), 2.0)
function code(x) return Float64(1.0 - (tan(x) ^ 2.0)) end
function tmp = code(x) tmp = 1.0 - (tan(x) ^ 2.0); end
code[x_] := N[(1.0 - N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
1 - {\tan x}^{2}
\end{array}
Initial program 99.4%
/-lowering-/.f64N/A
--lowering--.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f64N/A
+-lowering-+.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.4%
Applied egg-rr99.4%
Taylor expanded in x around 0
Simplified49.8%
Final simplification49.8%
(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 99.4%
Taylor expanded in x around 0
Simplified44.2%
herbie shell --seed 2024159
(FPCore (x)
:name "Trigonometry B"
:precision binary64
(/ (- 1.0 (* (tan x) (tan x))) (+ 1.0 (* (tan x) (tan x)))))