
(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 5 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 (* t_0 0.5)) (t_2 (* -0.5 t_0)))
(/
(+ 1.0 (/ (+ 0.5 t_2) (+ -0.5 t_2)))
(+ 1.0 (/ (- 0.5 t_1) (+ 0.5 t_1))))))
double code(double x) {
double t_0 = cos((x * 2.0));
double t_1 = t_0 * 0.5;
double t_2 = -0.5 * t_0;
return (1.0 + ((0.5 + t_2) / (-0.5 + t_2))) / (1.0 + ((0.5 - t_1) / (0.5 + t_1)));
}
real(8) function code(x)
real(8), intent (in) :: x
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = cos((x * 2.0d0))
t_1 = t_0 * 0.5d0
t_2 = (-0.5d0) * t_0
code = (1.0d0 + ((0.5d0 + t_2) / ((-0.5d0) + t_2))) / (1.0d0 + ((0.5d0 - t_1) / (0.5d0 + t_1)))
end function
public static double code(double x) {
double t_0 = Math.cos((x * 2.0));
double t_1 = t_0 * 0.5;
double t_2 = -0.5 * t_0;
return (1.0 + ((0.5 + t_2) / (-0.5 + t_2))) / (1.0 + ((0.5 - t_1) / (0.5 + t_1)));
}
def code(x): t_0 = math.cos((x * 2.0)) t_1 = t_0 * 0.5 t_2 = -0.5 * t_0 return (1.0 + ((0.5 + t_2) / (-0.5 + t_2))) / (1.0 + ((0.5 - t_1) / (0.5 + t_1)))
function code(x) t_0 = cos(Float64(x * 2.0)) t_1 = Float64(t_0 * 0.5) t_2 = Float64(-0.5 * t_0) return Float64(Float64(1.0 + Float64(Float64(0.5 + t_2) / Float64(-0.5 + t_2))) / Float64(1.0 + Float64(Float64(0.5 - t_1) / Float64(0.5 + t_1)))) end
function tmp = code(x) t_0 = cos((x * 2.0)); t_1 = t_0 * 0.5; t_2 = -0.5 * t_0; tmp = (1.0 + ((0.5 + t_2) / (-0.5 + t_2))) / (1.0 + ((0.5 - t_1) / (0.5 + t_1))); end
code[x_] := Block[{t$95$0 = N[Cos[N[(x * 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * 0.5), $MachinePrecision]}, Block[{t$95$2 = N[(-0.5 * t$95$0), $MachinePrecision]}, N[(N[(1.0 + N[(N[(0.5 + t$95$2), $MachinePrecision] / N[(-0.5 + t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(N[(0.5 - t$95$1), $MachinePrecision] / N[(0.5 + t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(x \cdot 2\right)\\
t_1 := t\_0 \cdot 0.5\\
t_2 := -0.5 \cdot t\_0\\
\frac{1 + \frac{0.5 + t\_2}{-0.5 + t\_2}}{1 + \frac{0.5 - t\_1}{0.5 + t\_1}}
\end{array}
\end{array}
Initial program 99.5%
flip--N/A
/-lowering-/.f64N/A
metadata-evalN/A
--lowering--.f64N/A
pow2N/A
pow2N/A
pow-prod-upN/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f64N/A
metadata-evalN/A
+-lowering-+.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.3%
Applied egg-rr99.3%
tan-quotN/A
tan-quotN/A
frac-timesN/A
/-lowering-/.f64N/A
sqr-sin-aN/A
metadata-evalN/A
--lowering--.f64N/A
metadata-evalN/A
metadata-evalN/A
*-lowering-*.f64N/A
metadata-evalN/A
cos-lowering-cos.f64N/A
*-lowering-*.f64N/A
sqr-cos-aN/A
metadata-evalN/A
+-lowering-+.f64N/A
metadata-evalN/A
metadata-evalN/A
*-lowering-*.f64N/A
metadata-evalN/A
cos-lowering-cos.f64N/A
*-lowering-*.f6499.0%
Applied egg-rr99.0%
metadata-evalN/A
metadata-evalN/A
pow-sqrN/A
flip--N/A
unpow2N/A
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
sqr-cos-aN/A
div-invN/A
cancel-sign-sub-invN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
Applied egg-rr99.5%
Applied egg-rr99.6%
Final simplification99.6%
(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 99.5%
--lowering--.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.5%
Applied egg-rr99.5%
pow2N/A
+-commutativeN/A
+-lowering-+.f64N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.5%
Applied egg-rr99.5%
Final simplification99.5%
(FPCore (x)
:precision binary64
(let* ((t_0 (cos (* x 2.0))) (t_1 (* t_0 0.5)))
(/
(+ 1.0 (* (- -0.5 (* -0.5 t_0)) (/ 1.0 (+ 0.5 t_1))))
(+ 1.0 (- 0.5 t_1)))))
double code(double x) {
double t_0 = cos((x * 2.0));
double t_1 = t_0 * 0.5;
return (1.0 + ((-0.5 - (-0.5 * t_0)) * (1.0 / (0.5 + t_1)))) / (1.0 + (0.5 - t_1));
}
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 = t_0 * 0.5d0
code = (1.0d0 + (((-0.5d0) - ((-0.5d0) * t_0)) * (1.0d0 / (0.5d0 + t_1)))) / (1.0d0 + (0.5d0 - t_1))
end function
public static double code(double x) {
double t_0 = Math.cos((x * 2.0));
double t_1 = t_0 * 0.5;
return (1.0 + ((-0.5 - (-0.5 * t_0)) * (1.0 / (0.5 + t_1)))) / (1.0 + (0.5 - t_1));
}
def code(x): t_0 = math.cos((x * 2.0)) t_1 = t_0 * 0.5 return (1.0 + ((-0.5 - (-0.5 * t_0)) * (1.0 / (0.5 + t_1)))) / (1.0 + (0.5 - t_1))
function code(x) t_0 = cos(Float64(x * 2.0)) t_1 = Float64(t_0 * 0.5) return Float64(Float64(1.0 + Float64(Float64(-0.5 - Float64(-0.5 * t_0)) * Float64(1.0 / Float64(0.5 + t_1)))) / Float64(1.0 + Float64(0.5 - t_1))) end
function tmp = code(x) t_0 = cos((x * 2.0)); t_1 = t_0 * 0.5; tmp = (1.0 + ((-0.5 - (-0.5 * t_0)) * (1.0 / (0.5 + t_1)))) / (1.0 + (0.5 - t_1)); end
code[x_] := Block[{t$95$0 = N[Cos[N[(x * 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * 0.5), $MachinePrecision]}, N[(N[(1.0 + N[(N[(-0.5 - N[(-0.5 * t$95$0), $MachinePrecision]), $MachinePrecision] * N[(1.0 / N[(0.5 + t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(0.5 - t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(x \cdot 2\right)\\
t_1 := t\_0 \cdot 0.5\\
\frac{1 + \left(-0.5 - -0.5 \cdot t\_0\right) \cdot \frac{1}{0.5 + t\_1}}{1 + \left(0.5 - t\_1\right)}
\end{array}
\end{array}
Initial program 99.5%
flip--N/A
/-lowering-/.f64N/A
metadata-evalN/A
--lowering--.f64N/A
pow2N/A
pow2N/A
pow-prod-upN/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f64N/A
metadata-evalN/A
+-lowering-+.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.3%
Applied egg-rr99.3%
tan-quotN/A
tan-quotN/A
frac-timesN/A
/-lowering-/.f64N/A
sqr-sin-aN/A
metadata-evalN/A
--lowering--.f64N/A
metadata-evalN/A
metadata-evalN/A
*-lowering-*.f64N/A
metadata-evalN/A
cos-lowering-cos.f64N/A
*-lowering-*.f64N/A
sqr-cos-aN/A
metadata-evalN/A
+-lowering-+.f64N/A
metadata-evalN/A
metadata-evalN/A
*-lowering-*.f64N/A
metadata-evalN/A
cos-lowering-cos.f64N/A
*-lowering-*.f6499.0%
Applied egg-rr99.0%
metadata-evalN/A
metadata-evalN/A
pow-sqrN/A
flip--N/A
unpow2N/A
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
sqr-cos-aN/A
div-invN/A
cancel-sign-sub-invN/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
Applied egg-rr99.5%
Taylor expanded in x around 0
Simplified65.2%
Final simplification65.2%
(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 99.5%
--lowering--.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.5%
Applied egg-rr99.5%
Taylor expanded in x around 0
Simplified63.3%
Final simplification63.3%
(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 99.5%
Applied egg-rr59.7%
herbie shell --seed 2024185
(FPCore (x)
:name "Trigonometry B"
:precision binary64
(/ (- 1.0 (* (tan x) (tan x))) (+ 1.0 (* (tan x) (tan x)))))