
(FPCore (eh ew t) :precision binary64 (let* ((t_1 (atan (/ (* (- eh) (tan t)) ew)))) (fabs (- (* (* ew (cos t)) (cos t_1)) (* (* eh (sin t)) (sin t_1))))))
double code(double eh, double ew, double t) {
double t_1 = atan(((-eh * tan(t)) / ew));
return fabs((((ew * cos(t)) * cos(t_1)) - ((eh * sin(t)) * sin(t_1))));
}
real(8) function code(eh, ew, t)
real(8), intent (in) :: eh
real(8), intent (in) :: ew
real(8), intent (in) :: t
real(8) :: t_1
t_1 = atan(((-eh * tan(t)) / ew))
code = abs((((ew * cos(t)) * cos(t_1)) - ((eh * sin(t)) * sin(t_1))))
end function
public static double code(double eh, double ew, double t) {
double t_1 = Math.atan(((-eh * Math.tan(t)) / ew));
return Math.abs((((ew * Math.cos(t)) * Math.cos(t_1)) - ((eh * Math.sin(t)) * Math.sin(t_1))));
}
def code(eh, ew, t): t_1 = math.atan(((-eh * math.tan(t)) / ew)) return math.fabs((((ew * math.cos(t)) * math.cos(t_1)) - ((eh * math.sin(t)) * math.sin(t_1))))
function code(eh, ew, t) t_1 = atan(Float64(Float64(Float64(-eh) * tan(t)) / ew)) return abs(Float64(Float64(Float64(ew * cos(t)) * cos(t_1)) - Float64(Float64(eh * sin(t)) * sin(t_1)))) end
function tmp = code(eh, ew, t) t_1 = atan(((-eh * tan(t)) / ew)); tmp = abs((((ew * cos(t)) * cos(t_1)) - ((eh * sin(t)) * sin(t_1)))); end
code[eh_, ew_, t_] := Block[{t$95$1 = N[ArcTan[N[(N[((-eh) * N[Tan[t], $MachinePrecision]), $MachinePrecision] / ew), $MachinePrecision]], $MachinePrecision]}, N[Abs[N[(N[(N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision] * N[Cos[t$95$1], $MachinePrecision]), $MachinePrecision] - N[(N[(eh * N[Sin[t], $MachinePrecision]), $MachinePrecision] * N[Sin[t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_1 := \tan^{-1} \left(\frac{\left(-eh\right) \cdot \tan t}{ew}\right)\\
\left|\left(ew \cdot \cos t\right) \cdot \cos t\_1 - \left(eh \cdot \sin t\right) \cdot \sin t\_1\right|
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 9 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (eh ew t) :precision binary64 (let* ((t_1 (atan (/ (* (- eh) (tan t)) ew)))) (fabs (- (* (* ew (cos t)) (cos t_1)) (* (* eh (sin t)) (sin t_1))))))
double code(double eh, double ew, double t) {
double t_1 = atan(((-eh * tan(t)) / ew));
return fabs((((ew * cos(t)) * cos(t_1)) - ((eh * sin(t)) * sin(t_1))));
}
real(8) function code(eh, ew, t)
real(8), intent (in) :: eh
real(8), intent (in) :: ew
real(8), intent (in) :: t
real(8) :: t_1
t_1 = atan(((-eh * tan(t)) / ew))
code = abs((((ew * cos(t)) * cos(t_1)) - ((eh * sin(t)) * sin(t_1))))
end function
public static double code(double eh, double ew, double t) {
double t_1 = Math.atan(((-eh * Math.tan(t)) / ew));
return Math.abs((((ew * Math.cos(t)) * Math.cos(t_1)) - ((eh * Math.sin(t)) * Math.sin(t_1))));
}
def code(eh, ew, t): t_1 = math.atan(((-eh * math.tan(t)) / ew)) return math.fabs((((ew * math.cos(t)) * math.cos(t_1)) - ((eh * math.sin(t)) * math.sin(t_1))))
function code(eh, ew, t) t_1 = atan(Float64(Float64(Float64(-eh) * tan(t)) / ew)) return abs(Float64(Float64(Float64(ew * cos(t)) * cos(t_1)) - Float64(Float64(eh * sin(t)) * sin(t_1)))) end
function tmp = code(eh, ew, t) t_1 = atan(((-eh * tan(t)) / ew)); tmp = abs((((ew * cos(t)) * cos(t_1)) - ((eh * sin(t)) * sin(t_1)))); end
code[eh_, ew_, t_] := Block[{t$95$1 = N[ArcTan[N[(N[((-eh) * N[Tan[t], $MachinePrecision]), $MachinePrecision] / ew), $MachinePrecision]], $MachinePrecision]}, N[Abs[N[(N[(N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision] * N[Cos[t$95$1], $MachinePrecision]), $MachinePrecision] - N[(N[(eh * N[Sin[t], $MachinePrecision]), $MachinePrecision] * N[Sin[t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_1 := \tan^{-1} \left(\frac{\left(-eh\right) \cdot \tan t}{ew}\right)\\
\left|\left(ew \cdot \cos t\right) \cdot \cos t\_1 - \left(eh \cdot \sin t\right) \cdot \sin t\_1\right|
\end{array}
\end{array}
(FPCore (eh ew t) :precision binary64 (fabs (fma ew (* (cos t) (/ -1.0 (hypot 1.0 (/ eh (/ ew (tan t)))))) (* eh (* (sin t) (sin (atan (* eh (/ (tan t) (- ew))))))))))
double code(double eh, double ew, double t) {
return fabs(fma(ew, (cos(t) * (-1.0 / hypot(1.0, (eh / (ew / tan(t)))))), (eh * (sin(t) * sin(atan((eh * (tan(t) / -ew))))))));
}
function code(eh, ew, t) return abs(fma(ew, Float64(cos(t) * Float64(-1.0 / hypot(1.0, Float64(eh / Float64(ew / tan(t)))))), Float64(eh * Float64(sin(t) * sin(atan(Float64(eh * Float64(tan(t) / Float64(-ew))))))))) end
code[eh_, ew_, t_] := N[Abs[N[(ew * N[(N[Cos[t], $MachinePrecision] * N[(-1.0 / N[Sqrt[1.0 ^ 2 + N[(eh / N[(ew / N[Tan[t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(eh * N[(N[Sin[t], $MachinePrecision] * N[Sin[N[ArcTan[N[(eh * N[(N[Tan[t], $MachinePrecision] / (-ew)), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|\mathsf{fma}\left(ew, \cos t \cdot \frac{-1}{\mathsf{hypot}\left(1, \frac{eh}{\frac{ew}{\tan t}}\right)}, eh \cdot \left(\sin t \cdot \sin \tan^{-1} \left(eh \cdot \frac{\tan t}{-ew}\right)\right)\right)\right|
\end{array}
Initial program 99.8%
fabs-sub99.8%
sub-neg99.8%
+-commutative99.8%
associate-*l*99.8%
distribute-rgt-neg-in99.8%
fma-define99.8%
Simplified99.8%
cos-atan99.8%
hypot-1-def99.8%
associate-*r/99.8%
*-commutative99.8%
associate-/l*99.8%
add-sqr-sqrt50.3%
sqrt-unprod93.6%
sqr-neg93.6%
sqrt-unprod49.5%
add-sqr-sqrt99.8%
Applied egg-rr99.8%
*-commutative99.8%
associate-/r/99.8%
Simplified99.8%
Final simplification99.8%
(FPCore (eh ew t) :precision binary64 (fabs (- (* (/ 1.0 (hypot 1.0 (/ eh (/ ew (tan t))))) (* ew (cos t))) (* eh (* (sin t) (sin (atan (* eh (/ (tan t) (- ew))))))))))
double code(double eh, double ew, double t) {
return fabs((((1.0 / hypot(1.0, (eh / (ew / tan(t))))) * (ew * cos(t))) - (eh * (sin(t) * sin(atan((eh * (tan(t) / -ew))))))));
}
public static double code(double eh, double ew, double t) {
return Math.abs((((1.0 / Math.hypot(1.0, (eh / (ew / Math.tan(t))))) * (ew * Math.cos(t))) - (eh * (Math.sin(t) * Math.sin(Math.atan((eh * (Math.tan(t) / -ew))))))));
}
def code(eh, ew, t): return math.fabs((((1.0 / math.hypot(1.0, (eh / (ew / math.tan(t))))) * (ew * math.cos(t))) - (eh * (math.sin(t) * math.sin(math.atan((eh * (math.tan(t) / -ew))))))))
function code(eh, ew, t) return abs(Float64(Float64(Float64(1.0 / hypot(1.0, Float64(eh / Float64(ew / tan(t))))) * Float64(ew * cos(t))) - Float64(eh * Float64(sin(t) * sin(atan(Float64(eh * Float64(tan(t) / Float64(-ew))))))))) end
function tmp = code(eh, ew, t) tmp = abs((((1.0 / hypot(1.0, (eh / (ew / tan(t))))) * (ew * cos(t))) - (eh * (sin(t) * sin(atan((eh * (tan(t) / -ew)))))))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(N[(1.0 / N[Sqrt[1.0 ^ 2 + N[(eh / N[(ew / N[Tan[t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision] * N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(eh * N[(N[Sin[t], $MachinePrecision] * N[Sin[N[ArcTan[N[(eh * N[(N[Tan[t], $MachinePrecision] / (-ew)), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|\frac{1}{\mathsf{hypot}\left(1, \frac{eh}{\frac{ew}{\tan t}}\right)} \cdot \left(ew \cdot \cos t\right) - eh \cdot \left(\sin t \cdot \sin \tan^{-1} \left(eh \cdot \frac{\tan t}{-ew}\right)\right)\right|
\end{array}
Initial program 99.8%
sub-neg99.8%
associate-*l*99.8%
distribute-rgt-neg-in99.8%
cancel-sign-sub99.8%
associate-/l*99.8%
Simplified99.8%
cos-atan99.8%
hypot-1-def99.8%
associate-*r/99.8%
*-commutative99.8%
associate-/l*99.8%
add-sqr-sqrt50.3%
sqrt-unprod93.6%
sqr-neg93.6%
sqrt-unprod49.5%
add-sqr-sqrt99.8%
Applied egg-rr99.8%
*-commutative99.8%
associate-/r/99.8%
Simplified99.8%
Final simplification99.8%
(FPCore (eh ew t) :precision binary64 (fabs (- (* (* ew (cos t)) (cos (atan (/ (* eh (tan t)) (- ew))))) (* (* eh (sin t)) (sin (atan (/ (* eh (- t)) ew)))))))
double code(double eh, double ew, double t) {
return fabs((((ew * cos(t)) * cos(atan(((eh * tan(t)) / -ew)))) - ((eh * sin(t)) * sin(atan(((eh * -t) / ew))))));
}
real(8) function code(eh, ew, t)
real(8), intent (in) :: eh
real(8), intent (in) :: ew
real(8), intent (in) :: t
code = abs((((ew * cos(t)) * cos(atan(((eh * tan(t)) / -ew)))) - ((eh * sin(t)) * sin(atan(((eh * -t) / ew))))))
end function
public static double code(double eh, double ew, double t) {
return Math.abs((((ew * Math.cos(t)) * Math.cos(Math.atan(((eh * Math.tan(t)) / -ew)))) - ((eh * Math.sin(t)) * Math.sin(Math.atan(((eh * -t) / ew))))));
}
def code(eh, ew, t): return math.fabs((((ew * math.cos(t)) * math.cos(math.atan(((eh * math.tan(t)) / -ew)))) - ((eh * math.sin(t)) * math.sin(math.atan(((eh * -t) / ew))))))
function code(eh, ew, t) return abs(Float64(Float64(Float64(ew * cos(t)) * cos(atan(Float64(Float64(eh * tan(t)) / Float64(-ew))))) - Float64(Float64(eh * sin(t)) * sin(atan(Float64(Float64(eh * Float64(-t)) / ew)))))) end
function tmp = code(eh, ew, t) tmp = abs((((ew * cos(t)) * cos(atan(((eh * tan(t)) / -ew)))) - ((eh * sin(t)) * sin(atan(((eh * -t) / ew)))))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision] * N[Cos[N[ArcTan[N[(N[(eh * N[Tan[t], $MachinePrecision]), $MachinePrecision] / (-ew)), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[(eh * N[Sin[t], $MachinePrecision]), $MachinePrecision] * N[Sin[N[ArcTan[N[(N[(eh * (-t)), $MachinePrecision] / ew), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|\left(ew \cdot \cos t\right) \cdot \cos \tan^{-1} \left(\frac{eh \cdot \tan t}{-ew}\right) - \left(eh \cdot \sin t\right) \cdot \sin \tan^{-1} \left(\frac{eh \cdot \left(-t\right)}{ew}\right)\right|
\end{array}
Initial program 99.8%
Taylor expanded in t around 0 99.1%
associate-*r*99.1%
mul-1-neg99.1%
Simplified99.1%
Final simplification99.1%
(FPCore (eh ew t) :precision binary64 (fabs (+ (* eh (sin t)) (* (* ew (cos t)) (cos (atan (* eh (/ (tan t) (- ew)))))))))
double code(double eh, double ew, double t) {
return fabs(((eh * sin(t)) + ((ew * cos(t)) * cos(atan((eh * (tan(t) / -ew)))))));
}
real(8) function code(eh, ew, t)
real(8), intent (in) :: eh
real(8), intent (in) :: ew
real(8), intent (in) :: t
code = abs(((eh * sin(t)) + ((ew * cos(t)) * cos(atan((eh * (tan(t) / -ew)))))))
end function
public static double code(double eh, double ew, double t) {
return Math.abs(((eh * Math.sin(t)) + ((ew * Math.cos(t)) * Math.cos(Math.atan((eh * (Math.tan(t) / -ew)))))));
}
def code(eh, ew, t): return math.fabs(((eh * math.sin(t)) + ((ew * math.cos(t)) * math.cos(math.atan((eh * (math.tan(t) / -ew)))))))
function code(eh, ew, t) return abs(Float64(Float64(eh * sin(t)) + Float64(Float64(ew * cos(t)) * cos(atan(Float64(eh * Float64(tan(t) / Float64(-ew)))))))) end
function tmp = code(eh, ew, t) tmp = abs(((eh * sin(t)) + ((ew * cos(t)) * cos(atan((eh * (tan(t) / -ew))))))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(eh * N[Sin[t], $MachinePrecision]), $MachinePrecision] + N[(N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision] * N[Cos[N[ArcTan[N[(eh * N[(N[Tan[t], $MachinePrecision] / (-ew)), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|eh \cdot \sin t + \left(ew \cdot \cos t\right) \cdot \cos \tan^{-1} \left(eh \cdot \frac{\tan t}{-ew}\right)\right|
\end{array}
Initial program 99.8%
sub-neg99.8%
associate-*l*99.8%
distribute-rgt-neg-in99.8%
cancel-sign-sub99.8%
associate-/l*99.8%
Simplified99.8%
associate-*r*99.8%
sin-atan76.5%
associate-*r/74.0%
associate-*r/74.0%
*-commutative74.0%
associate-/l*72.1%
add-sqr-sqrt37.2%
sqrt-unprod61.1%
sqr-neg61.1%
sqrt-unprod34.7%
add-sqr-sqrt71.0%
hypot-1-def75.2%
associate-*r/75.2%
Applied egg-rr75.2%
associate-*l*75.1%
*-commutative75.1%
associate-/r/75.2%
*-commutative75.2%
associate-/r/78.3%
Simplified78.3%
Taylor expanded in eh around -inf 98.6%
mul-1-neg98.6%
*-commutative98.6%
distribute-rgt-neg-in98.6%
Simplified98.6%
Final simplification98.6%
(FPCore (eh ew t) :precision binary64 (fabs (+ (* (/ 1.0 (hypot 1.0 (/ eh (/ ew (tan t))))) (* ew (cos t))) (* eh (sin t)))))
double code(double eh, double ew, double t) {
return fabs((((1.0 / hypot(1.0, (eh / (ew / tan(t))))) * (ew * cos(t))) + (eh * sin(t))));
}
public static double code(double eh, double ew, double t) {
return Math.abs((((1.0 / Math.hypot(1.0, (eh / (ew / Math.tan(t))))) * (ew * Math.cos(t))) + (eh * Math.sin(t))));
}
def code(eh, ew, t): return math.fabs((((1.0 / math.hypot(1.0, (eh / (ew / math.tan(t))))) * (ew * math.cos(t))) + (eh * math.sin(t))))
function code(eh, ew, t) return abs(Float64(Float64(Float64(1.0 / hypot(1.0, Float64(eh / Float64(ew / tan(t))))) * Float64(ew * cos(t))) + Float64(eh * sin(t)))) end
function tmp = code(eh, ew, t) tmp = abs((((1.0 / hypot(1.0, (eh / (ew / tan(t))))) * (ew * cos(t))) + (eh * sin(t)))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(N[(1.0 / N[Sqrt[1.0 ^ 2 + N[(eh / N[(ew / N[Tan[t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision] * N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(eh * N[Sin[t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|\frac{1}{\mathsf{hypot}\left(1, \frac{eh}{\frac{ew}{\tan t}}\right)} \cdot \left(ew \cdot \cos t\right) + eh \cdot \sin t\right|
\end{array}
Initial program 99.8%
sub-neg99.8%
associate-*l*99.8%
distribute-rgt-neg-in99.8%
cancel-sign-sub99.8%
associate-/l*99.8%
Simplified99.8%
associate-*r*99.8%
sin-atan76.5%
associate-*r/74.0%
associate-*r/74.0%
*-commutative74.0%
associate-/l*72.1%
add-sqr-sqrt37.2%
sqrt-unprod61.1%
sqr-neg61.1%
sqrt-unprod34.7%
add-sqr-sqrt71.0%
hypot-1-def75.2%
associate-*r/75.2%
Applied egg-rr75.2%
associate-*l*75.1%
*-commutative75.1%
associate-/r/75.2%
*-commutative75.2%
associate-/r/78.3%
Simplified78.3%
Taylor expanded in eh around -inf 98.6%
mul-1-neg98.6%
*-commutative98.6%
distribute-rgt-neg-in98.6%
Simplified98.6%
cos-atan99.8%
hypot-1-def99.8%
associate-*r/99.8%
*-commutative99.8%
associate-/l*99.8%
add-sqr-sqrt50.3%
sqrt-unprod93.6%
sqr-neg93.6%
sqrt-unprod49.5%
add-sqr-sqrt99.8%
Applied egg-rr98.6%
*-commutative99.8%
associate-/r/99.8%
Simplified98.6%
Final simplification98.6%
(FPCore (eh ew t) :precision binary64 (fabs (* ew (cos (atan (* eh (/ t ew)))))))
double code(double eh, double ew, double t) {
return fabs((ew * cos(atan((eh * (t / ew))))));
}
real(8) function code(eh, ew, t)
real(8), intent (in) :: eh
real(8), intent (in) :: ew
real(8), intent (in) :: t
code = abs((ew * cos(atan((eh * (t / ew))))))
end function
public static double code(double eh, double ew, double t) {
return Math.abs((ew * Math.cos(Math.atan((eh * (t / ew))))));
}
def code(eh, ew, t): return math.fabs((ew * math.cos(math.atan((eh * (t / ew))))))
function code(eh, ew, t) return abs(Float64(ew * cos(atan(Float64(eh * Float64(t / ew)))))) end
function tmp = code(eh, ew, t) tmp = abs((ew * cos(atan((eh * (t / ew)))))); end
code[eh_, ew_, t_] := N[Abs[N[(ew * N[Cos[N[ArcTan[N[(eh * N[(t / ew), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|ew \cdot \cos \tan^{-1} \left(eh \cdot \frac{t}{ew}\right)\right|
\end{array}
Initial program 99.8%
sub-neg99.8%
associate-*l*99.8%
distribute-rgt-neg-in99.8%
cancel-sign-sub99.8%
associate-/l*99.8%
Simplified99.8%
sin-mult60.9%
associate-*r/60.9%
Applied egg-rr59.0%
+-inverses59.0%
associate-/l*59.0%
metadata-eval59.0%
mul0-rgt59.0%
Simplified59.0%
Taylor expanded in t around 0 40.7%
Taylor expanded in t around 0 39.4%
associate-*r/39.4%
associate-*r*39.4%
mul-1-neg39.4%
Simplified39.4%
associate-/l*39.4%
*-commutative39.4%
add-sqr-sqrt19.5%
sqrt-unprod34.7%
sqr-neg34.7%
sqrt-unprod19.9%
add-sqr-sqrt39.4%
Applied egg-rr39.4%
Final simplification39.4%
(FPCore (eh ew t) :precision binary64 (fabs (+ (* ew (cos t)) (* eh (sin t)))))
double code(double eh, double ew, double t) {
return fabs(((ew * cos(t)) + (eh * sin(t))));
}
real(8) function code(eh, ew, t)
real(8), intent (in) :: eh
real(8), intent (in) :: ew
real(8), intent (in) :: t
code = abs(((ew * cos(t)) + (eh * sin(t))))
end function
public static double code(double eh, double ew, double t) {
return Math.abs(((ew * Math.cos(t)) + (eh * Math.sin(t))));
}
def code(eh, ew, t): return math.fabs(((ew * math.cos(t)) + (eh * math.sin(t))))
function code(eh, ew, t) return abs(Float64(Float64(ew * cos(t)) + Float64(eh * sin(t)))) end
function tmp = code(eh, ew, t) tmp = abs(((ew * cos(t)) + (eh * sin(t)))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision] + N[(eh * N[Sin[t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|ew \cdot \cos t + eh \cdot \sin t\right|
\end{array}
Initial program 99.8%
sub-neg99.8%
associate-*l*99.8%
distribute-rgt-neg-in99.8%
cancel-sign-sub99.8%
associate-/l*99.8%
Simplified99.8%
associate-*r*99.8%
sin-atan76.5%
associate-*r/74.0%
associate-*r/74.0%
*-commutative74.0%
associate-/l*72.1%
add-sqr-sqrt37.2%
sqrt-unprod61.1%
sqr-neg61.1%
sqrt-unprod34.7%
add-sqr-sqrt71.0%
hypot-1-def75.2%
associate-*r/75.2%
Applied egg-rr75.2%
associate-*l*75.1%
*-commutative75.1%
associate-/r/75.2%
*-commutative75.2%
associate-/r/78.3%
Simplified78.3%
Taylor expanded in eh around -inf 98.6%
mul-1-neg98.6%
*-commutative98.6%
distribute-rgt-neg-in98.6%
Simplified98.6%
cos-atan99.8%
hypot-1-def99.8%
associate-*r/99.8%
*-commutative99.8%
associate-/l*99.8%
add-sqr-sqrt50.3%
sqrt-unprod93.6%
sqr-neg93.6%
sqrt-unprod49.5%
add-sqr-sqrt99.8%
Applied egg-rr98.6%
*-commutative99.8%
associate-/r/99.8%
Simplified98.6%
Taylor expanded in eh around 0 97.8%
Final simplification97.8%
(FPCore (eh ew t) :precision binary64 (fabs (* ew (/ 1.0 (hypot 1.0 (* eh (/ t ew)))))))
double code(double eh, double ew, double t) {
return fabs((ew * (1.0 / hypot(1.0, (eh * (t / ew))))));
}
public static double code(double eh, double ew, double t) {
return Math.abs((ew * (1.0 / Math.hypot(1.0, (eh * (t / ew))))));
}
def code(eh, ew, t): return math.fabs((ew * (1.0 / math.hypot(1.0, (eh * (t / ew))))))
function code(eh, ew, t) return abs(Float64(ew * Float64(1.0 / hypot(1.0, Float64(eh * Float64(t / ew)))))) end
function tmp = code(eh, ew, t) tmp = abs((ew * (1.0 / hypot(1.0, (eh * (t / ew)))))); end
code[eh_, ew_, t_] := N[Abs[N[(ew * N[(1.0 / N[Sqrt[1.0 ^ 2 + N[(eh * N[(t / ew), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|ew \cdot \frac{1}{\mathsf{hypot}\left(1, eh \cdot \frac{t}{ew}\right)}\right|
\end{array}
Initial program 99.8%
sub-neg99.8%
associate-*l*99.8%
distribute-rgt-neg-in99.8%
cancel-sign-sub99.8%
associate-/l*99.8%
Simplified99.8%
sin-mult60.9%
associate-*r/60.9%
Applied egg-rr59.0%
+-inverses59.0%
associate-/l*59.0%
metadata-eval59.0%
mul0-rgt59.0%
Simplified59.0%
Taylor expanded in t around 0 40.7%
Taylor expanded in t around 0 39.4%
associate-*r/39.4%
associate-*r*39.4%
mul-1-neg39.4%
Simplified39.4%
cos-atan38.5%
hypot-1-def38.5%
associate-/l*38.6%
add-sqr-sqrt19.1%
sqrt-unprod33.6%
sqr-neg33.6%
sqrt-unprod19.5%
add-sqr-sqrt38.6%
Applied egg-rr38.6%
Final simplification38.6%
(FPCore (eh ew t) :precision binary64 (fabs (/ ew (hypot 1.0 (* t (/ eh ew))))))
double code(double eh, double ew, double t) {
return fabs((ew / hypot(1.0, (t * (eh / ew)))));
}
public static double code(double eh, double ew, double t) {
return Math.abs((ew / Math.hypot(1.0, (t * (eh / ew)))));
}
def code(eh, ew, t): return math.fabs((ew / math.hypot(1.0, (t * (eh / ew)))))
function code(eh, ew, t) return abs(Float64(ew / hypot(1.0, Float64(t * Float64(eh / ew))))) end
function tmp = code(eh, ew, t) tmp = abs((ew / hypot(1.0, (t * (eh / ew))))); end
code[eh_, ew_, t_] := N[Abs[N[(ew / N[Sqrt[1.0 ^ 2 + N[(t * N[(eh / ew), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|\frac{ew}{\mathsf{hypot}\left(1, t \cdot \frac{eh}{ew}\right)}\right|
\end{array}
Initial program 99.8%
sub-neg99.8%
associate-*l*99.8%
distribute-rgt-neg-in99.8%
cancel-sign-sub99.8%
associate-/l*99.8%
Simplified99.8%
sin-mult60.9%
associate-*r/60.9%
Applied egg-rr59.0%
+-inverses59.0%
associate-/l*59.0%
metadata-eval59.0%
mul0-rgt59.0%
Simplified59.0%
Taylor expanded in t around 0 40.7%
Taylor expanded in t around 0 39.4%
associate-*r/39.4%
associate-*r*39.4%
mul-1-neg39.4%
Simplified39.4%
cos-atan38.5%
un-div-inv38.5%
hypot-1-def38.5%
*-commutative38.5%
associate-/l*38.6%
add-sqr-sqrt19.1%
sqrt-unprod33.9%
sqr-neg33.9%
sqrt-unprod19.5%
add-sqr-sqrt38.6%
Applied egg-rr38.6%
Final simplification38.6%
herbie shell --seed 2024077
(FPCore (eh ew t)
:name "Example 2 from Robby"
:precision binary64
(fabs (- (* (* ew (cos t)) (cos (atan (/ (* (- eh) (tan t)) ew)))) (* (* eh (sin t)) (sin (atan (/ (* (- eh) (tan t)) ew)))))))