
(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 (+ t_0 -1.0))) (/ (+ 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 = t_0 + -1.0;
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 = t_0 + (-1.0d0)
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 = t_0 + -1.0;
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 = t_0 + -1.0 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(t_0 + -1.0) 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 = t_0 + -1.0; 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[(t$95$0 + -1.0), $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 := t\_0 + -1\\
\frac{1 + \frac{t\_1}{1 + t\_0}}{1 + \frac{t\_1}{-1 - t\_0}}
\end{array}
\end{array}
Initial program 99.6%
pow2N/A
tan-quotN/A
clear-numN/A
inv-powN/A
pow-powN/A
metadata-evalN/A
pow-lowering-pow.f64N/A
clear-numN/A
tan-quotN/A
/-lowering-/.f64N/A
tan-lowering-tan.f6499.4%
Applied egg-rr99.4%
inv-powN/A
pow-powN/A
metadata-evalN/A
pow2N/A
tan-quotN/A
tan-quotN/A
frac-timesN/A
pow2N/A
/-lowering-/.f64N/A
pow2N/A
sqr-sin-aN/A
--lowering--.f64N/A
cos-2N/A
cos-sumN/A
*-lowering-*.f64N/A
cos-sumN/A
cos-2N/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
Applied egg-rr98.8%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sin-multN/A
sqr-cos-aN/A
associate-/l/N/A
metadata-evalN/A
div-invN/A
/-lowering-/.f64N/A
Applied egg-rr99.6%
Taylor expanded in x around inf
Simplified99.6%
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 99.6%
/-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.f6499.6%
Applied egg-rr99.6%
(FPCore (x) :precision binary64 (let* ((t_0 (cos (* x 2.0))) (t_1 (* t_0 0.5))) (/ (+ 1.0 (/ (- t_1 0.5) (+ 0.5 t_1))) (+ 1.0 (/ (- 1.0 t_0) 2.0)))))
double code(double x) {
double t_0 = cos((x * 2.0));
double t_1 = t_0 * 0.5;
return (1.0 + ((t_1 - 0.5) / (0.5 + t_1))) / (1.0 + ((1.0 - t_0) / 2.0));
}
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 = t_0 * 0.5d0
code = (1.0d0 + ((t_1 - 0.5d0) / (0.5d0 + t_1))) / (1.0d0 + ((1.0d0 - t_0) / 2.0d0))
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 + ((t_1 - 0.5) / (0.5 + t_1))) / (1.0 + ((1.0 - t_0) / 2.0));
}
def code(x): t_0 = math.cos((x * 2.0)) t_1 = t_0 * 0.5 return (1.0 + ((t_1 - 0.5) / (0.5 + t_1))) / (1.0 + ((1.0 - t_0) / 2.0))
function code(x) t_0 = cos(Float64(x * 2.0)) t_1 = Float64(t_0 * 0.5) return Float64(Float64(1.0 + Float64(Float64(t_1 - 0.5) / Float64(0.5 + t_1))) / Float64(1.0 + Float64(Float64(1.0 - t_0) / 2.0))) end
function tmp = code(x) t_0 = cos((x * 2.0)); t_1 = t_0 * 0.5; tmp = (1.0 + ((t_1 - 0.5) / (0.5 + t_1))) / (1.0 + ((1.0 - t_0) / 2.0)); 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[(t$95$1 - 0.5), $MachinePrecision] / N[(0.5 + t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(N[(1.0 - t$95$0), $MachinePrecision] / 2.0), $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 + \frac{t\_1 - 0.5}{0.5 + t\_1}}{1 + \frac{1 - t\_0}{2}}
\end{array}
\end{array}
Initial program 99.6%
pow2N/A
tan-quotN/A
clear-numN/A
inv-powN/A
pow-powN/A
metadata-evalN/A
pow-lowering-pow.f64N/A
clear-numN/A
tan-quotN/A
/-lowering-/.f64N/A
tan-lowering-tan.f6499.4%
Applied egg-rr99.4%
inv-powN/A
pow-powN/A
metadata-evalN/A
pow2N/A
tan-quotN/A
tan-quotN/A
frac-timesN/A
pow2N/A
/-lowering-/.f64N/A
pow2N/A
sqr-sin-aN/A
--lowering--.f64N/A
cos-2N/A
cos-sumN/A
*-lowering-*.f64N/A
cos-sumN/A
cos-2N/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
Applied egg-rr98.8%
tan-quotN/A
tan-quotN/A
frac-timesN/A
sin-multN/A
sqr-cos-aN/A
associate-/l/N/A
metadata-evalN/A
div-invN/A
/-lowering-/.f64N/A
Applied egg-rr99.6%
Taylor expanded in x around 0
Simplified59.4%
Final simplification59.4%
(FPCore (x) :precision binary64 (/ 1.0 (- (pow (tan x) 2.0) -1.0)))
double code(double x) {
return 1.0 / (pow(tan(x), 2.0) - -1.0);
}
real(8) function code(x)
real(8), intent (in) :: x
code = 1.0d0 / ((tan(x) ** 2.0d0) - (-1.0d0))
end function
public static double code(double x) {
return 1.0 / (Math.pow(Math.tan(x), 2.0) - -1.0);
}
def code(x): return 1.0 / (math.pow(math.tan(x), 2.0) - -1.0)
function code(x) return Float64(1.0 / Float64((tan(x) ^ 2.0) - -1.0)) end
function tmp = code(x) tmp = 1.0 / ((tan(x) ^ 2.0) - -1.0); end
code[x_] := N[(1.0 / N[(N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision] - -1.0), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{{\tan x}^{2} - -1}
\end{array}
Initial program 99.6%
sub-negN/A
+-commutativeN/A
distribute-lft-neg-inN/A
fma-defineN/A
fma-lowering-fma.f64N/A
neg-sub0N/A
--lowering--.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.6%
Applied egg-rr99.6%
+-commutativeN/A
fma-defineN/A
metadata-evalN/A
fmm-defN/A
--lowering--.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.6%
Applied egg-rr99.6%
Taylor expanded in x around 0
Simplified53.5%
(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 99.6%
sub-negN/A
+-commutativeN/A
distribute-lft-neg-inN/A
fma-defineN/A
fma-lowering-fma.f64N/A
neg-sub0N/A
--lowering--.f64N/A
tan-lowering-tan.f64N/A
tan-lowering-tan.f6499.6%
Applied egg-rr99.6%
+-commutativeN/A
fma-defineN/A
metadata-evalN/A
fmm-defN/A
--lowering--.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.6%
Applied egg-rr99.6%
+-commutativeN/A
sub0-negN/A
cancel-sign-sub-invN/A
--lowering--.f64N/A
pow2N/A
pow-lowering-pow.f64N/A
tan-lowering-tan.f6499.6%
Applied egg-rr99.6%
Taylor expanded in x around 0
Simplified57.6%
Final simplification57.6%
(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%
Taylor expanded in x around 0
Simplified53.2%
herbie shell --seed 2024164
(FPCore (x)
:name "Trigonometry B"
:precision binary64
(/ (- 1.0 (* (tan x) (tan x))) (+ 1.0 (* (tan x) (tan x)))))