
(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 14 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 (* t_0 0.5)))
(/
(- 1.0 (/ (fma t_0 -0.5 0.5) (fma 0.5 t_0 0.5)))
(+ 1.0 (/ (- 0.5 t_1) (+ 0.5 t_1))))))
double code(double x) {
double t_0 = cos((x + x));
double t_1 = t_0 * 0.5;
return (1.0 - (fma(t_0, -0.5, 0.5) / fma(0.5, t_0, 0.5))) / (1.0 + ((0.5 - t_1) / (0.5 + t_1)));
}
function code(x) t_0 = cos(Float64(x + x)) t_1 = Float64(t_0 * 0.5) 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(0.5 - t_1) / Float64(0.5 + t_1)))) end
code[x_] := Block[{t$95$0 = N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * 0.5), $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[(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 + x\right)\\
t_1 := t\_0 \cdot 0.5\\
\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{0.5 - t\_1}{0.5 + t\_1}}
\end{array}
\end{array}
Initial program 99.5%
tan-quotN/A
tan-quotN/A
frac-timesN/A
/-lowering-/.f64N/A
sqr-sin-aN/A
--lowering--.f64N/A
cos-2N/A
cos-sumN/A
*-lowering-*.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
sqr-cos-aN/A
+-lowering-+.f64N/A
cos-2N/A
cos-sumN/A
*-lowering-*.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f6498.9
Applied egg-rr98.9%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
count-2N/A
sqr-cos-aN/A
count-2N/A
/-lowering-/.f64N/A
sub-negN/A
+-commutativeN/A
*-commutativeN/A
distribute-rgt-neg-inN/A
accelerator-lowering-fma.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
metadata-evalN/A
+-commutativeN/A
accelerator-lowering-fma.f64N/A
Applied egg-rr99.6%
Final simplification99.6%
(FPCore (x)
:precision binary64
(let* ((t_0 (* (tan x) (tan x))) (t_1 (cos (+ x x))))
(if (<= (/ (- 1.0 t_0) (+ 1.0 t_0)) 0.23)
(- 1.0 (* (fma t_1 -0.5 0.5) (/ 1.0 (fma 0.5 t_1 0.5))))
(/ (- (- 1.0 (* t_1 -0.5)) 0.5) (fma (tan x) (tan x) 1.0)))))
double code(double x) {
double t_0 = tan(x) * tan(x);
double t_1 = cos((x + x));
double tmp;
if (((1.0 - t_0) / (1.0 + t_0)) <= 0.23) {
tmp = 1.0 - (fma(t_1, -0.5, 0.5) * (1.0 / fma(0.5, t_1, 0.5)));
} else {
tmp = ((1.0 - (t_1 * -0.5)) - 0.5) / fma(tan(x), tan(x), 1.0);
}
return tmp;
}
function code(x) t_0 = Float64(tan(x) * tan(x)) t_1 = cos(Float64(x + x)) tmp = 0.0 if (Float64(Float64(1.0 - t_0) / Float64(1.0 + t_0)) <= 0.23) tmp = Float64(1.0 - Float64(fma(t_1, -0.5, 0.5) * Float64(1.0 / fma(0.5, t_1, 0.5)))); else tmp = Float64(Float64(Float64(1.0 - Float64(t_1 * -0.5)) - 0.5) / fma(tan(x), tan(x), 1.0)); end return tmp end
code[x_] := Block[{t$95$0 = N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(N[(1.0 - t$95$0), $MachinePrecision] / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision], 0.23], N[(1.0 - N[(N[(t$95$1 * -0.5 + 0.5), $MachinePrecision] * N[(1.0 / N[(0.5 * t$95$1 + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(1.0 - N[(t$95$1 * -0.5), $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision] / N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \tan x \cdot \tan x\\
t_1 := \cos \left(x + x\right)\\
\mathbf{if}\;\frac{1 - t\_0}{1 + t\_0} \leq 0.23:\\
\;\;\;\;1 - \mathsf{fma}\left(t\_1, -0.5, 0.5\right) \cdot \frac{1}{\mathsf{fma}\left(0.5, t\_1, 0.5\right)}\\
\mathbf{else}:\\
\;\;\;\;\frac{\left(1 - t\_1 \cdot -0.5\right) - 0.5}{\mathsf{fma}\left(\tan x, \tan x, 1\right)}\\
\end{array}
\end{array}
if (/.f64 (-.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x))) (+.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x)))) < 0.23000000000000001Initial program 98.9%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6498.9
Applied egg-rr98.9%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
count-2N/A
sqr-cos-aN/A
count-2N/A
div-invN/A
*-lowering-*.f64N/A
sub-negN/A
+-commutativeN/A
*-commutativeN/A
distribute-rgt-neg-inN/A
accelerator-lowering-fma.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
metadata-evalN/A
/-lowering-/.f64N/A
Applied egg-rr96.9%
Taylor expanded in x around 0
Simplified16.7%
if 0.23000000000000001 < (/.f64 (-.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x))) (+.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x)))) Initial program 99.7%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.7
Applied egg-rr99.7%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
count-2N/A
sqr-cos-aN/A
count-2N/A
div-invN/A
*-lowering-*.f64N/A
sub-negN/A
+-commutativeN/A
*-commutativeN/A
distribute-rgt-neg-inN/A
accelerator-lowering-fma.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
metadata-evalN/A
/-lowering-/.f64N/A
Applied egg-rr99.7%
Taylor expanded in x around 0
Simplified73.9%
*-rgt-identityN/A
associate--r+N/A
--lowering--.f64N/A
--lowering--.f64N/A
*-lowering-*.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f6473.9
Applied egg-rr73.9%
Final simplification57.3%
(FPCore (x)
:precision binary64
(let* ((t_0 (* (tan x) (tan x))) (t_1 (cos (+ x x))))
(if (<= (/ (- 1.0 t_0) (+ 1.0 t_0)) 0.23)
(- 1.0 (* (fma t_1 -0.5 0.5) (/ 1.0 (fma 0.5 t_1 0.5))))
(* (/ 1.0 (+ 1.0 (pow (tan x) 2.0))) (- 0.5 (* t_1 -0.5))))))
double code(double x) {
double t_0 = tan(x) * tan(x);
double t_1 = cos((x + x));
double tmp;
if (((1.0 - t_0) / (1.0 + t_0)) <= 0.23) {
tmp = 1.0 - (fma(t_1, -0.5, 0.5) * (1.0 / fma(0.5, t_1, 0.5)));
} else {
tmp = (1.0 / (1.0 + pow(tan(x), 2.0))) * (0.5 - (t_1 * -0.5));
}
return tmp;
}
function code(x) t_0 = Float64(tan(x) * tan(x)) t_1 = cos(Float64(x + x)) tmp = 0.0 if (Float64(Float64(1.0 - t_0) / Float64(1.0 + t_0)) <= 0.23) tmp = Float64(1.0 - Float64(fma(t_1, -0.5, 0.5) * Float64(1.0 / fma(0.5, t_1, 0.5)))); else tmp = Float64(Float64(1.0 / Float64(1.0 + (tan(x) ^ 2.0))) * Float64(0.5 - Float64(t_1 * -0.5))); end return tmp end
code[x_] := Block[{t$95$0 = N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(N[(1.0 - t$95$0), $MachinePrecision] / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision], 0.23], N[(1.0 - N[(N[(t$95$1 * -0.5 + 0.5), $MachinePrecision] * N[(1.0 / N[(0.5 * t$95$1 + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(1.0 / N[(1.0 + N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(0.5 - N[(t$95$1 * -0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \tan x \cdot \tan x\\
t_1 := \cos \left(x + x\right)\\
\mathbf{if}\;\frac{1 - t\_0}{1 + t\_0} \leq 0.23:\\
\;\;\;\;1 - \mathsf{fma}\left(t\_1, -0.5, 0.5\right) \cdot \frac{1}{\mathsf{fma}\left(0.5, t\_1, 0.5\right)}\\
\mathbf{else}:\\
\;\;\;\;\frac{1}{1 + {\tan x}^{2}} \cdot \left(0.5 - t\_1 \cdot -0.5\right)\\
\end{array}
\end{array}
if (/.f64 (-.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x))) (+.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x)))) < 0.23000000000000001Initial program 98.9%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6498.9
Applied egg-rr98.9%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
count-2N/A
sqr-cos-aN/A
count-2N/A
div-invN/A
*-lowering-*.f64N/A
sub-negN/A
+-commutativeN/A
*-commutativeN/A
distribute-rgt-neg-inN/A
accelerator-lowering-fma.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
metadata-evalN/A
/-lowering-/.f64N/A
Applied egg-rr96.9%
Taylor expanded in x around 0
Simplified16.7%
if 0.23000000000000001 < (/.f64 (-.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x))) (+.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x)))) Initial program 99.7%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.7
Applied egg-rr99.7%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
count-2N/A
sqr-cos-aN/A
count-2N/A
div-invN/A
*-lowering-*.f64N/A
sub-negN/A
+-commutativeN/A
*-commutativeN/A
distribute-rgt-neg-inN/A
accelerator-lowering-fma.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
metadata-evalN/A
/-lowering-/.f64N/A
Applied egg-rr99.7%
Taylor expanded in x around 0
Simplified73.9%
clear-numN/A
associate-/r/N/A
*-lowering-*.f64N/A
/-lowering-/.f64N/A
+-commutativeN/A
+-lowering-+.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f64N/A
*-rgt-identityN/A
+-commutativeN/A
associate--r+N/A
metadata-evalN/A
--lowering--.f64N/A
*-lowering-*.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f6473.9
Applied egg-rr73.9%
Final simplification57.3%
(FPCore (x)
:precision binary64
(let* ((t_0 (* (tan x) (tan x))) (t_1 (cos (+ x x))))
(if (<= (/ (- 1.0 t_0) (+ 1.0 t_0)) 0.23)
(- 1.0 (* (fma t_1 -0.5 0.5) (/ 1.0 (fma 0.5 t_1 0.5))))
(/ (- 0.5 (* t_1 -0.5)) (+ 1.0 (pow (tan x) 2.0))))))
double code(double x) {
double t_0 = tan(x) * tan(x);
double t_1 = cos((x + x));
double tmp;
if (((1.0 - t_0) / (1.0 + t_0)) <= 0.23) {
tmp = 1.0 - (fma(t_1, -0.5, 0.5) * (1.0 / fma(0.5, t_1, 0.5)));
} else {
tmp = (0.5 - (t_1 * -0.5)) / (1.0 + pow(tan(x), 2.0));
}
return tmp;
}
function code(x) t_0 = Float64(tan(x) * tan(x)) t_1 = cos(Float64(x + x)) tmp = 0.0 if (Float64(Float64(1.0 - t_0) / Float64(1.0 + t_0)) <= 0.23) tmp = Float64(1.0 - Float64(fma(t_1, -0.5, 0.5) * Float64(1.0 / fma(0.5, t_1, 0.5)))); else tmp = Float64(Float64(0.5 - Float64(t_1 * -0.5)) / Float64(1.0 + (tan(x) ^ 2.0))); end return tmp end
code[x_] := Block[{t$95$0 = N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(N[(1.0 - t$95$0), $MachinePrecision] / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision], 0.23], N[(1.0 - N[(N[(t$95$1 * -0.5 + 0.5), $MachinePrecision] * N[(1.0 / N[(0.5 * t$95$1 + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(0.5 - N[(t$95$1 * -0.5), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \tan x \cdot \tan x\\
t_1 := \cos \left(x + x\right)\\
\mathbf{if}\;\frac{1 - t\_0}{1 + t\_0} \leq 0.23:\\
\;\;\;\;1 - \mathsf{fma}\left(t\_1, -0.5, 0.5\right) \cdot \frac{1}{\mathsf{fma}\left(0.5, t\_1, 0.5\right)}\\
\mathbf{else}:\\
\;\;\;\;\frac{0.5 - t\_1 \cdot -0.5}{1 + {\tan x}^{2}}\\
\end{array}
\end{array}
if (/.f64 (-.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x))) (+.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x)))) < 0.23000000000000001Initial program 98.9%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6498.9
Applied egg-rr98.9%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
count-2N/A
sqr-cos-aN/A
count-2N/A
div-invN/A
*-lowering-*.f64N/A
sub-negN/A
+-commutativeN/A
*-commutativeN/A
distribute-rgt-neg-inN/A
accelerator-lowering-fma.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
metadata-evalN/A
/-lowering-/.f64N/A
Applied egg-rr96.9%
Taylor expanded in x around 0
Simplified16.7%
if 0.23000000000000001 < (/.f64 (-.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x))) (+.f64 #s(literal 1 binary64) (*.f64 (tan.f64 x) (tan.f64 x)))) Initial program 99.7%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.7
Applied egg-rr99.7%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
count-2N/A
sqr-cos-aN/A
count-2N/A
div-invN/A
*-lowering-*.f64N/A
sub-negN/A
+-commutativeN/A
*-commutativeN/A
distribute-rgt-neg-inN/A
accelerator-lowering-fma.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
metadata-evalN/A
/-lowering-/.f64N/A
Applied egg-rr99.7%
Taylor expanded in x around 0
Simplified73.9%
/-lowering-/.f64N/A
*-rgt-identityN/A
+-commutativeN/A
associate--r+N/A
metadata-evalN/A
--lowering--.f64N/A
*-lowering-*.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
+-commutativeN/A
+-lowering-+.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6473.9
Applied egg-rr73.9%
Final simplification57.3%
(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%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.5
Applied egg-rr99.5%
cancel-sign-sub-invN/A
tan-quotN/A
div-invN/A
associate-*l*N/A
*-commutativeN/A
+-commutativeN/A
*-commutativeN/A
associate-*l*N/A
div-invN/A
tan-quotN/A
*-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
neg-lowering-neg.f64N/A
tan-lowering-tan.f6499.5
Applied egg-rr99.5%
(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%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.5
Applied egg-rr99.5%
--lowering--.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.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%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.5
Applied egg-rr99.5%
/-lowering-/.f64N/A
--lowering--.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f64N/A
+-commutativeN/A
+-lowering-+.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.5
Applied egg-rr99.5%
(FPCore (x)
:precision binary64
(let* ((t_0 (cos (+ x x))))
(/
(- 1.0 (/ (fma t_0 -0.5 0.5) (fma 0.5 t_0 0.5)))
(+ 1.0 (- 0.5 (* t_0 0.5))))))
double code(double x) {
double t_0 = cos((x + x));
return (1.0 - (fma(t_0, -0.5, 0.5) / fma(0.5, t_0, 0.5))) / (1.0 + (0.5 - (t_0 * 0.5)));
}
function code(x) t_0 = cos(Float64(x + x)) return Float64(Float64(1.0 - Float64(fma(t_0, -0.5, 0.5) / fma(0.5, t_0, 0.5))) / Float64(1.0 + Float64(0.5 - Float64(t_0 * 0.5)))) end
code[x_] := Block[{t$95$0 = N[Cos[N[(x + x), $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[(0.5 - N[(t$95$0 * 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(x + x\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 + \left(0.5 - t\_0 \cdot 0.5\right)}
\end{array}
\end{array}
Initial program 99.5%
tan-quotN/A
tan-quotN/A
frac-timesN/A
/-lowering-/.f64N/A
sqr-sin-aN/A
--lowering--.f64N/A
cos-2N/A
cos-sumN/A
*-lowering-*.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
sqr-cos-aN/A
+-lowering-+.f64N/A
cos-2N/A
cos-sumN/A
*-lowering-*.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f6498.9
Applied egg-rr98.9%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
count-2N/A
sqr-cos-aN/A
count-2N/A
/-lowering-/.f64N/A
sub-negN/A
+-commutativeN/A
*-commutativeN/A
distribute-rgt-neg-inN/A
accelerator-lowering-fma.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
metadata-evalN/A
+-commutativeN/A
accelerator-lowering-fma.f64N/A
Applied egg-rr99.6%
Taylor expanded in x around 0
Simplified57.8%
Final simplification57.8%
(FPCore (x) :precision binary64 (/ (- 1.0 (* (tan x) (tan x))) (+ 1.0 (- 0.5 (* (cos (+ x x)) 0.5)))))
double code(double x) {
return (1.0 - (tan(x) * tan(x))) / (1.0 + (0.5 - (cos((x + x)) * 0.5)));
}
real(8) function code(x)
real(8), intent (in) :: x
code = (1.0d0 - (tan(x) * tan(x))) / (1.0d0 + (0.5d0 - (cos((x + x)) * 0.5d0)))
end function
public static double code(double x) {
return (1.0 - (Math.tan(x) * Math.tan(x))) / (1.0 + (0.5 - (Math.cos((x + x)) * 0.5)));
}
def code(x): return (1.0 - (math.tan(x) * math.tan(x))) / (1.0 + (0.5 - (math.cos((x + x)) * 0.5)))
function code(x) return Float64(Float64(1.0 - Float64(tan(x) * tan(x))) / Float64(1.0 + Float64(0.5 - Float64(cos(Float64(x + x)) * 0.5)))) end
function tmp = code(x) tmp = (1.0 - (tan(x) * tan(x))) / (1.0 + (0.5 - (cos((x + x)) * 0.5))); end
code[x_] := N[(N[(1.0 - N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(0.5 - N[(N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision] * 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1 - \tan x \cdot \tan x}{1 + \left(0.5 - \cos \left(x + x\right) \cdot 0.5\right)}
\end{array}
Initial program 99.5%
tan-quotN/A
tan-quotN/A
frac-timesN/A
/-lowering-/.f64N/A
sqr-sin-aN/A
--lowering--.f64N/A
cos-2N/A
cos-sumN/A
*-lowering-*.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
sqr-cos-aN/A
+-lowering-+.f64N/A
cos-2N/A
cos-sumN/A
*-lowering-*.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f6498.9
Applied egg-rr98.9%
Taylor expanded in x around 0
Simplified57.8%
Final simplification57.8%
(FPCore (x) :precision binary64 (let* ((t_0 (cos (+ x x)))) (- 1.0 (* (fma t_0 -0.5 0.5) (/ 1.0 (fma 0.5 t_0 0.5))))))
double code(double x) {
double t_0 = cos((x + x));
return 1.0 - (fma(t_0, -0.5, 0.5) * (1.0 / fma(0.5, t_0, 0.5)));
}
function code(x) t_0 = cos(Float64(x + x)) return Float64(1.0 - Float64(fma(t_0, -0.5, 0.5) * Float64(1.0 / fma(0.5, t_0, 0.5)))) end
code[x_] := Block[{t$95$0 = N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision]}, N[(1.0 - N[(N[(t$95$0 * -0.5 + 0.5), $MachinePrecision] * N[(1.0 / N[(0.5 * t$95$0 + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(x + x\right)\\
1 - \mathsf{fma}\left(t\_0, -0.5, 0.5\right) \cdot \frac{1}{\mathsf{fma}\left(0.5, t\_0, 0.5\right)}
\end{array}
\end{array}
Initial program 99.5%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.5
Applied egg-rr99.5%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
count-2N/A
sqr-cos-aN/A
count-2N/A
div-invN/A
*-lowering-*.f64N/A
sub-negN/A
+-commutativeN/A
*-commutativeN/A
distribute-rgt-neg-inN/A
accelerator-lowering-fma.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
metadata-evalN/A
/-lowering-/.f64N/A
Applied egg-rr98.9%
Taylor expanded in x around 0
Simplified55.4%
Final simplification55.4%
(FPCore (x) :precision binary64 (/ 1.0 (/ 1.0 (- 1.0 (pow (tan x) 2.0)))))
double code(double x) {
return 1.0 / (1.0 / (1.0 - pow(tan(x), 2.0)));
}
real(8) function code(x)
real(8), intent (in) :: x
code = 1.0d0 / (1.0d0 / (1.0d0 - (tan(x) ** 2.0d0)))
end function
public static double code(double x) {
return 1.0 / (1.0 / (1.0 - Math.pow(Math.tan(x), 2.0)));
}
def code(x): return 1.0 / (1.0 / (1.0 - math.pow(math.tan(x), 2.0)))
function code(x) return Float64(1.0 / Float64(1.0 / Float64(1.0 - (tan(x) ^ 2.0)))) end
function tmp = code(x) tmp = 1.0 / (1.0 / (1.0 - (tan(x) ^ 2.0))); end
code[x_] := N[(1.0 / N[(1.0 / N[(1.0 - N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\frac{1}{1 - {\tan x}^{2}}}
\end{array}
Initial program 99.5%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.5
Applied egg-rr99.5%
clear-numN/A
/-lowering-/.f64N/A
/-lowering-/.f64N/A
+-commutativeN/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
Simplified55.4%
(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
Simplified55.4%
Final simplification55.4%
(FPCore (x) :precision binary64 (- 1.0 (fma (cos (+ x x)) -0.5 0.5)))
double code(double x) {
return 1.0 - fma(cos((x + x)), -0.5, 0.5);
}
function code(x) return Float64(1.0 - fma(cos(Float64(x + x)), -0.5, 0.5)) end
code[x_] := N[(1.0 - N[(N[Cos[N[(x + x), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
1 - \mathsf{fma}\left(\cos \left(x + x\right), -0.5, 0.5\right)
\end{array}
Initial program 99.5%
+-commutativeN/A
accelerator-lowering-fma.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.5
Applied egg-rr99.5%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sqr-sin-aN/A
count-2N/A
sqr-cos-aN/A
count-2N/A
div-invN/A
*-lowering-*.f64N/A
sub-negN/A
+-commutativeN/A
*-commutativeN/A
distribute-rgt-neg-inN/A
accelerator-lowering-fma.f64N/A
cos-lowering-cos.f64N/A
+-lowering-+.f64N/A
metadata-evalN/A
/-lowering-/.f64N/A
Applied egg-rr98.9%
Taylor expanded in x around 0
Simplified53.4%
Taylor expanded in x around 0
Simplified51.3%
Final simplification51.3%
(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-rr50.9%
herbie shell --seed 2024199
(FPCore (x)
:name "Trigonometry B"
:precision binary64
(/ (- 1.0 (* (tan x) (tan x))) (+ 1.0 (* (tan x) (tan x)))))