
(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 9 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 x))) (t_1 (cos (* x -2.0))))
(/
(- 1.0 (/ (fma t_0 -0.5 0.5) (fma 0.5 t_0 0.5)))
(+ 1.0 (/ (- 1.0 t_1) (+ 1.0 t_1))))))
double code(double x) {
double t_0 = cos((x + x));
double t_1 = cos((x * -2.0));
return (1.0 - (fma(t_0, -0.5, 0.5) / fma(0.5, t_0, 0.5))) / (1.0 + ((1.0 - t_1) / (1.0 + t_1)));
}
function code(x) t_0 = cos(Float64(x + x)) t_1 = cos(Float64(x * -2.0)) return Float64(Float64(1.0 - Float64(fma(t_0, -0.5, 0.5) / fma(0.5, t_0, 0.5))) / Float64(1.0 + Float64(Float64(1.0 - t_1) / Float64(1.0 + t_1)))) end
code[x_] := Block[{t$95$0 = N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(x * -2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(1.0 - N[(N[(t$95$0 * -0.5 + 0.5), $MachinePrecision] / N[(0.5 * t$95$0 + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(N[(1.0 - t$95$1), $MachinePrecision] / N[(1.0 + t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(x + x\right)\\
t_1 := \cos \left(x \cdot -2\right)\\
\frac{1 - \frac{\mathsf{fma}\left(t\_0, -0.5, 0.5\right)}{\mathsf{fma}\left(0.5, t\_0, 0.5\right)}}{1 + \frac{1 - t\_1}{1 + t\_1}}
\end{array}
\end{array}
Initial program 99.5%
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-+.f6499.2
Applied egg-rr99.2%
Taylor expanded in x around inf
*-commutativeN/A
metadata-evalN/A
distribute-lft-neg-inN/A
cancel-sign-sub-invN/A
distribute-rgt1-inN/A
*-commutativeN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt1-inN/A
times-fracN/A
metadata-evalN/A
*-rgt-identityN/A
lower-/.f64N/A
Simplified99.2%
tan-quotN/A
lift-cos.f64N/A
tan-quotN/A
lift-cos.f64N/A
frac-timesN/A
pow2N/A
metadata-evalN/A
lower-/.f64N/A
sqr-sin-aN/A
count-2N/A
lift-+.f64N/A
lift-cos.f64N/A
cancel-sign-sub-invN/A
metadata-evalN/A
*-commutativeN/A
+-commutativeN/A
lift-fma.f64N/A
metadata-evalN/A
pow2N/A
lift-cos.f64N/A
lift-cos.f64N/A
sqr-cos-aN/A
Applied egg-rr99.6%
(FPCore (x) :precision binary64 (/ (fma (tan x) (- (tan x)) 1.0) (fma (tan x) (tan x) 1.0)))
double code(double x) {
return fma(tan(x), -tan(x), 1.0) / fma(tan(x), tan(x), 1.0);
}
function code(x) return Float64(fma(tan(x), Float64(-tan(x)), 1.0) / fma(tan(x), tan(x), 1.0)) end
code[x_] := N[(N[(N[Tan[x], $MachinePrecision] * (-N[Tan[x], $MachinePrecision]) + 1.0), $MachinePrecision] / N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\mathsf{fma}\left(\tan x, -\tan x, 1\right)}{\mathsf{fma}\left(\tan x, \tan x, 1\right)}
\end{array}
Initial program 99.5%
lift-tan.f64N/A
lift-tan.f64N/A
lift-*.f64N/A
+-commutativeN/A
lift-*.f64N/A
lower-fma.f6499.5
Applied egg-rr99.5%
lift-tan.f64N/A
lift-tan.f64N/A
cancel-sign-sub-invN/A
lift-neg.f64N/A
lift-tan.f64N/A
tan-quotN/A
lift-sin.f64N/A
lift-cos.f64N/A
div-invN/A
lift-/.f64N/A
associate-*l*N/A
*-commutativeN/A
lift-*.f64N/A
+-commutativeN/A
Applied egg-rr99.6%
(FPCore (x) :precision binary64 (/ (- 1.0 (pow (tan x) 2.0)) (fma (tan x) (tan x) 1.0)))
double code(double x) {
return (1.0 - pow(tan(x), 2.0)) / fma(tan(x), tan(x), 1.0);
}
function code(x) return Float64(Float64(1.0 - (tan(x) ^ 2.0)) / fma(tan(x), tan(x), 1.0)) end
code[x_] := N[(N[(1.0 - N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] / N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1 - {\tan x}^{2}}{\mathsf{fma}\left(\tan x, \tan x, 1\right)}
\end{array}
Initial program 99.5%
lift-tan.f64N/A
lift-tan.f64N/A
lift-*.f64N/A
+-commutativeN/A
lift-*.f64N/A
lower-fma.f6499.5
Applied egg-rr99.5%
lift-tan.f64N/A
lift-tan.f64N/A
pow2N/A
lower-pow.f6499.5
Applied egg-rr99.5%
(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 99.5%
tan-quotN/A
tan-quotN/A
clear-numN/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
lower-pow.f6499.4
Applied egg-rr99.4%
lift-tan.f64N/A
inv-powN/A
pow-powN/A
metadata-evalN/A
lift-pow.f6499.5
Applied egg-rr99.5%
(FPCore (x) :precision binary64 (/ 1.0 (/ (fma (cos (+ x x)) -0.5 1.5) (- 1.0 (pow (tan x) 2.0)))))
double code(double x) {
return 1.0 / (fma(cos((x + x)), -0.5, 1.5) / (1.0 - pow(tan(x), 2.0)));
}
function code(x) return Float64(1.0 / Float64(fma(cos(Float64(x + x)), -0.5, 1.5) / Float64(1.0 - (tan(x) ^ 2.0)))) end
code[x_] := N[(1.0 / N[(N[(N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision] * -0.5 + 1.5), $MachinePrecision] / N[(1.0 - N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\frac{\mathsf{fma}\left(\cos \left(x + x\right), -0.5, 1.5\right)}{1 - {\tan x}^{2}}}
\end{array}
Initial program 99.5%
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-+.f6499.2
Applied egg-rr99.2%
tan-quotN/A
lift-sin.f64N/A
lift-cos.f64N/A
tan-quotN/A
lift-sin.f64N/A
lift-cos.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
lift-cos.f64N/A
lift-cos.f64N/A
sqr-cos-aN/A
count-2N/A
lift-+.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-+.f64N/A
Applied egg-rr99.6%
Taylor expanded in x around 0
Simplified64.9%
Applied egg-rr64.9%
(FPCore (x) :precision binary64 (/ (- 1.0 (pow (tan x) 2.0)) (fma (cos (+ x x)) -0.5 1.5)))
double code(double x) {
return (1.0 - pow(tan(x), 2.0)) / fma(cos((x + x)), -0.5, 1.5);
}
function code(x) return Float64(Float64(1.0 - (tan(x) ^ 2.0)) / fma(cos(Float64(x + x)), -0.5, 1.5)) end
code[x_] := N[(N[(1.0 - N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] / N[(N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision] * -0.5 + 1.5), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1 - {\tan x}^{2}}{\mathsf{fma}\left(\cos \left(x + x\right), -0.5, 1.5\right)}
\end{array}
Initial program 99.5%
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-+.f6499.2
Applied egg-rr99.2%
tan-quotN/A
lift-sin.f64N/A
lift-cos.f64N/A
tan-quotN/A
lift-sin.f64N/A
lift-cos.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
lift-cos.f64N/A
lift-cos.f64N/A
sqr-cos-aN/A
count-2N/A
lift-+.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-+.f64N/A
Applied egg-rr99.6%
Taylor expanded in x around 0
Simplified64.9%
Applied egg-rr64.9%
(FPCore (x) :precision binary64 (/ 1.0 (fma (tan x) (tan x) 1.0)))
double code(double x) {
return 1.0 / fma(tan(x), tan(x), 1.0);
}
function code(x) return Float64(1.0 / fma(tan(x), tan(x), 1.0)) end
code[x_] := N[(1.0 / N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\mathsf{fma}\left(\tan x, \tan x, 1\right)}
\end{array}
Initial program 99.5%
lift-tan.f64N/A
lift-tan.f64N/A
lift-*.f64N/A
+-commutativeN/A
lift-*.f64N/A
lower-fma.f6499.5
Applied egg-rr99.5%
Taylor expanded in x around 0
Simplified59.9%
(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 99.5%
Taylor expanded in x around 0
Simplified62.9%
Final simplification62.9%
(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-rr59.5%
herbie shell --seed 2024215
(FPCore (x)
:name "Trigonometry B"
:precision binary64
(/ (- 1.0 (* (tan x) (tan x))) (+ 1.0 (* (tan x) (tan x)))))