
(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 8 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 (- (/ (* ew (cos t)) (hypot 1.0 (* (tan t) (/ eh ew)))) (* eh (* (sin t) (sin (atan (* (tan t) (/ eh (- ew))))))))))
double code(double eh, double ew, double t) {
return fabs((((ew * cos(t)) / hypot(1.0, (tan(t) * (eh / ew)))) - (eh * (sin(t) * sin(atan((tan(t) * (eh / -ew))))))));
}
public static double code(double eh, double ew, double t) {
return Math.abs((((ew * Math.cos(t)) / Math.hypot(1.0, (Math.tan(t) * (eh / ew)))) - (eh * (Math.sin(t) * Math.sin(Math.atan((Math.tan(t) * (eh / -ew))))))));
}
def code(eh, ew, t): return math.fabs((((ew * math.cos(t)) / math.hypot(1.0, (math.tan(t) * (eh / ew)))) - (eh * (math.sin(t) * math.sin(math.atan((math.tan(t) * (eh / -ew))))))))
function code(eh, ew, t) return abs(Float64(Float64(Float64(ew * cos(t)) / hypot(1.0, Float64(tan(t) * Float64(eh / ew)))) - Float64(eh * Float64(sin(t) * sin(atan(Float64(tan(t) * Float64(eh / Float64(-ew))))))))) end
function tmp = code(eh, ew, t) tmp = abs((((ew * cos(t)) / hypot(1.0, (tan(t) * (eh / ew)))) - (eh * (sin(t) * sin(atan((tan(t) * (eh / -ew)))))))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision] / N[Sqrt[1.0 ^ 2 + N[(N[Tan[t], $MachinePrecision] * N[(eh / ew), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision] - N[(eh * N[(N[Sin[t], $MachinePrecision] * N[Sin[N[ArcTan[N[(N[Tan[t], $MachinePrecision] * N[(eh / (-ew)), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|\frac{ew \cdot \cos t}{\mathsf{hypot}\left(1, \tan t \cdot \frac{eh}{ew}\right)} - eh \cdot \left(\sin t \cdot \sin \tan^{-1} \left(\tan t \cdot \frac{eh}{-ew}\right)\right)\right|
\end{array}
Initial program 99.8%
Simplified99.8%
associate-*r*99.8%
cos-atan99.8%
un-div-inv99.8%
*-commutative99.8%
hypot-1-def99.8%
add-sqr-sqrt49.5%
sqrt-unprod94.5%
sqr-neg94.5%
sqrt-unprod50.3%
add-sqr-sqrt99.8%
Applied egg-rr99.8%
Final simplification99.8%
(FPCore (eh ew t) :precision binary64 (fabs (- (/ ew (/ (hypot 1.0 (* (tan t) (/ eh ew))) (cos t))) (* eh (* (sin t) (sin (atan (* (tan t) (/ eh (- ew))))))))))
double code(double eh, double ew, double t) {
return fabs(((ew / (hypot(1.0, (tan(t) * (eh / ew))) / cos(t))) - (eh * (sin(t) * sin(atan((tan(t) * (eh / -ew))))))));
}
public static double code(double eh, double ew, double t) {
return Math.abs(((ew / (Math.hypot(1.0, (Math.tan(t) * (eh / ew))) / Math.cos(t))) - (eh * (Math.sin(t) * Math.sin(Math.atan((Math.tan(t) * (eh / -ew))))))));
}
def code(eh, ew, t): return math.fabs(((ew / (math.hypot(1.0, (math.tan(t) * (eh / ew))) / math.cos(t))) - (eh * (math.sin(t) * math.sin(math.atan((math.tan(t) * (eh / -ew))))))))
function code(eh, ew, t) return abs(Float64(Float64(ew / Float64(hypot(1.0, Float64(tan(t) * Float64(eh / ew))) / cos(t))) - Float64(eh * Float64(sin(t) * sin(atan(Float64(tan(t) * Float64(eh / Float64(-ew))))))))) end
function tmp = code(eh, ew, t) tmp = abs(((ew / (hypot(1.0, (tan(t) * (eh / ew))) / cos(t))) - (eh * (sin(t) * sin(atan((tan(t) * (eh / -ew)))))))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(ew / N[(N[Sqrt[1.0 ^ 2 + N[(N[Tan[t], $MachinePrecision] * N[(eh / ew), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Cos[t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(eh * N[(N[Sin[t], $MachinePrecision] * N[Sin[N[ArcTan[N[(N[Tan[t], $MachinePrecision] * N[(eh / (-ew)), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|\frac{ew}{\frac{\mathsf{hypot}\left(1, \tan t \cdot \frac{eh}{ew}\right)}{\cos t}} - eh \cdot \left(\sin t \cdot \sin \tan^{-1} \left(\tan t \cdot \frac{eh}{-ew}\right)\right)\right|
\end{array}
Initial program 99.8%
Simplified99.8%
associate-*r*99.8%
cos-atan99.8%
un-div-inv99.8%
*-commutative99.8%
associate-/l*99.8%
hypot-1-def99.8%
add-sqr-sqrt49.5%
sqrt-unprod94.5%
sqr-neg94.5%
sqrt-unprod50.3%
add-sqr-sqrt99.8%
Applied egg-rr99.8%
Final simplification99.8%
(FPCore (eh ew t) :precision binary64 (fabs (- (/ (cos t) (/ (hypot 1.0 (* (tan t) (/ eh ew))) ew)) (* eh (* (sin t) (sin (atan (* (/ eh ew) (- t)))))))))
double code(double eh, double ew, double t) {
return fabs(((cos(t) / (hypot(1.0, (tan(t) * (eh / ew))) / ew)) - (eh * (sin(t) * sin(atan(((eh / ew) * -t)))))));
}
public static double code(double eh, double ew, double t) {
return Math.abs(((Math.cos(t) / (Math.hypot(1.0, (Math.tan(t) * (eh / ew))) / ew)) - (eh * (Math.sin(t) * Math.sin(Math.atan(((eh / ew) * -t)))))));
}
def code(eh, ew, t): return math.fabs(((math.cos(t) / (math.hypot(1.0, (math.tan(t) * (eh / ew))) / ew)) - (eh * (math.sin(t) * math.sin(math.atan(((eh / ew) * -t)))))))
function code(eh, ew, t) return abs(Float64(Float64(cos(t) / Float64(hypot(1.0, Float64(tan(t) * Float64(eh / ew))) / ew)) - Float64(eh * Float64(sin(t) * sin(atan(Float64(Float64(eh / ew) * Float64(-t)))))))) end
function tmp = code(eh, ew, t) tmp = abs(((cos(t) / (hypot(1.0, (tan(t) * (eh / ew))) / ew)) - (eh * (sin(t) * sin(atan(((eh / ew) * -t))))))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(N[Cos[t], $MachinePrecision] / N[(N[Sqrt[1.0 ^ 2 + N[(N[Tan[t], $MachinePrecision] * N[(eh / ew), $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / ew), $MachinePrecision]), $MachinePrecision] - N[(eh * N[(N[Sin[t], $MachinePrecision] * N[Sin[N[ArcTan[N[(N[(eh / ew), $MachinePrecision] * (-t)), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|\frac{\cos t}{\frac{\mathsf{hypot}\left(1, \tan t \cdot \frac{eh}{ew}\right)}{ew}} - eh \cdot \left(\sin t \cdot \sin \tan^{-1} \left(\frac{eh}{ew} \cdot \left(-t\right)\right)\right)\right|
\end{array}
Initial program 99.8%
Simplified99.8%
associate-*r*99.8%
cos-atan99.8%
un-div-inv99.8%
associate-/l*99.6%
hypot-1-def99.6%
add-sqr-sqrt49.5%
sqrt-unprod94.4%
sqr-neg94.4%
sqrt-unprod50.2%
add-sqr-sqrt99.6%
Applied egg-rr99.6%
Taylor expanded in t around 0 99.3%
mul-1-neg79.3%
associate-/l*79.3%
associate-/r/79.3%
distribute-rgt-neg-in79.3%
Simplified99.3%
Final simplification99.3%
(FPCore (eh ew t) :precision binary64 (fabs (- (* ew (cos t)) (* eh (* (sin t) (sin (atan (* (tan t) (/ eh (- ew))))))))))
double code(double eh, double ew, double t) {
return fabs(((ew * cos(t)) - (eh * (sin(t) * sin(atan((tan(t) * (eh / -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)) - (eh * (sin(t) * sin(atan((tan(t) * (eh / -ew))))))))
end function
public static double code(double eh, double ew, double t) {
return Math.abs(((ew * Math.cos(t)) - (eh * (Math.sin(t) * Math.sin(Math.atan((Math.tan(t) * (eh / -ew))))))));
}
def code(eh, ew, t): return math.fabs(((ew * math.cos(t)) - (eh * (math.sin(t) * math.sin(math.atan((math.tan(t) * (eh / -ew))))))))
function code(eh, ew, t) return abs(Float64(Float64(ew * cos(t)) - Float64(eh * Float64(sin(t) * sin(atan(Float64(tan(t) * Float64(eh / Float64(-ew))))))))) end
function tmp = code(eh, ew, t) tmp = abs(((ew * cos(t)) - (eh * (sin(t) * sin(atan((tan(t) * (eh / -ew)))))))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision] - N[(eh * N[(N[Sin[t], $MachinePrecision] * N[Sin[N[ArcTan[N[(N[Tan[t], $MachinePrecision] * N[(eh / (-ew)), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|ew \cdot \cos t - eh \cdot \left(\sin t \cdot \sin \tan^{-1} \left(\tan t \cdot \frac{eh}{-ew}\right)\right)\right|
\end{array}
Initial program 99.8%
Simplified99.8%
associate-*r*99.8%
cos-atan99.8%
un-div-inv99.8%
associate-/l*99.6%
hypot-1-def99.6%
add-sqr-sqrt49.5%
sqrt-unprod94.4%
sqr-neg94.4%
sqrt-unprod50.2%
add-sqr-sqrt99.6%
Applied egg-rr99.6%
Taylor expanded in eh around 0 99.1%
Final simplification99.1%
(FPCore (eh ew t) :precision binary64 (fabs (- (* ew (cos t)) (* (* eh (sin t)) (sin (atan (/ (tan t) (/ ew eh))))))))
double code(double eh, double ew, double t) {
return fabs(((ew * cos(t)) - ((eh * sin(t)) * sin(atan((tan(t) / (ew / eh)))))));
}
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)) * sin(atan((tan(t) / (ew / eh)))))))
end function
public static double code(double eh, double ew, double t) {
return Math.abs(((ew * Math.cos(t)) - ((eh * Math.sin(t)) * Math.sin(Math.atan((Math.tan(t) / (ew / eh)))))));
}
def code(eh, ew, t): return math.fabs(((ew * math.cos(t)) - ((eh * math.sin(t)) * math.sin(math.atan((math.tan(t) / (ew / eh)))))))
function code(eh, ew, t) return abs(Float64(Float64(ew * cos(t)) - Float64(Float64(eh * sin(t)) * sin(atan(Float64(tan(t) / Float64(ew / eh))))))) end
function tmp = code(eh, ew, t) tmp = abs(((ew * cos(t)) - ((eh * sin(t)) * sin(atan((tan(t) / (ew / eh))))))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision] - N[(N[(eh * N[Sin[t], $MachinePrecision]), $MachinePrecision] * N[Sin[N[ArcTan[N[(N[Tan[t], $MachinePrecision] / N[(ew / eh), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|ew \cdot \cos t - \left(eh \cdot \sin t\right) \cdot \sin \tan^{-1} \left(\frac{\tan t}{\frac{ew}{eh}}\right)\right|
\end{array}
Initial program 99.8%
Simplified99.8%
associate-*r*99.8%
cos-atan99.8%
un-div-inv99.8%
associate-/l*99.6%
hypot-1-def99.6%
add-sqr-sqrt49.5%
sqrt-unprod94.4%
sqr-neg94.4%
sqrt-unprod50.2%
add-sqr-sqrt99.6%
Applied egg-rr99.6%
Taylor expanded in eh around 0 99.1%
expm1-log1p-u88.2%
expm1-udef77.8%
associate-*r*77.8%
*-commutative77.8%
add-sqr-sqrt40.3%
sqrt-unprod79.9%
sqr-neg79.9%
sqrt-unprod38.9%
add-sqr-sqrt72.9%
Applied egg-rr72.9%
expm1-def83.4%
expm1-log1p99.1%
*-commutative99.1%
associate-*r/99.1%
associate-/l*99.1%
Simplified99.1%
Final simplification99.1%
(FPCore (eh ew t) :precision binary64 (fabs (- (* ew (cos t)) (* eh (* (sin t) (sin (atan (* (/ eh ew) (- t)))))))))
double code(double eh, double ew, double t) {
return fabs(((ew * cos(t)) - (eh * (sin(t) * sin(atan(((eh / ew) * -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) * sin(atan(((eh / ew) * -t)))))))
end function
public static double code(double eh, double ew, double t) {
return Math.abs(((ew * Math.cos(t)) - (eh * (Math.sin(t) * Math.sin(Math.atan(((eh / ew) * -t)))))));
}
def code(eh, ew, t): return math.fabs(((ew * math.cos(t)) - (eh * (math.sin(t) * math.sin(math.atan(((eh / ew) * -t)))))))
function code(eh, ew, t) return abs(Float64(Float64(ew * cos(t)) - Float64(eh * Float64(sin(t) * sin(atan(Float64(Float64(eh / ew) * Float64(-t)))))))) end
function tmp = code(eh, ew, t) tmp = abs(((ew * cos(t)) - (eh * (sin(t) * sin(atan(((eh / ew) * -t))))))); end
code[eh_, ew_, t_] := N[Abs[N[(N[(ew * N[Cos[t], $MachinePrecision]), $MachinePrecision] - N[(eh * N[(N[Sin[t], $MachinePrecision] * N[Sin[N[ArcTan[N[(N[(eh / ew), $MachinePrecision] * (-t)), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|ew \cdot \cos t - eh \cdot \left(\sin t \cdot \sin \tan^{-1} \left(\frac{eh}{ew} \cdot \left(-t\right)\right)\right)\right|
\end{array}
Initial program 99.8%
Simplified99.8%
associate-*r*99.8%
cos-atan99.8%
un-div-inv99.8%
associate-/l*99.6%
hypot-1-def99.6%
add-sqr-sqrt49.5%
sqrt-unprod94.4%
sqr-neg94.4%
sqrt-unprod50.2%
add-sqr-sqrt99.6%
Applied egg-rr99.6%
Taylor expanded in eh around 0 99.1%
Taylor expanded in t around 0 98.9%
mul-1-neg79.3%
associate-/l*79.3%
associate-/r/79.3%
distribute-rgt-neg-in79.3%
Simplified98.9%
Final simplification98.9%
(FPCore (eh ew t) :precision binary64 (fabs (- ew (* eh (* (sin t) (sin (atan (* (tan t) (/ eh (- ew))))))))))
double code(double eh, double ew, double t) {
return fabs((ew - (eh * (sin(t) * sin(atan((tan(t) * (eh / -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 - (eh * (sin(t) * sin(atan((tan(t) * (eh / -ew))))))))
end function
public static double code(double eh, double ew, double t) {
return Math.abs((ew - (eh * (Math.sin(t) * Math.sin(Math.atan((Math.tan(t) * (eh / -ew))))))));
}
def code(eh, ew, t): return math.fabs((ew - (eh * (math.sin(t) * math.sin(math.atan((math.tan(t) * (eh / -ew))))))))
function code(eh, ew, t) return abs(Float64(ew - Float64(eh * Float64(sin(t) * sin(atan(Float64(tan(t) * Float64(eh / Float64(-ew))))))))) end
function tmp = code(eh, ew, t) tmp = abs((ew - (eh * (sin(t) * sin(atan((tan(t) * (eh / -ew)))))))); end
code[eh_, ew_, t_] := N[Abs[N[(ew - N[(eh * N[(N[Sin[t], $MachinePrecision] * N[Sin[N[ArcTan[N[(N[Tan[t], $MachinePrecision] * N[(eh / (-ew)), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|ew - eh \cdot \left(\sin t \cdot \sin \tan^{-1} \left(\tan t \cdot \frac{eh}{-ew}\right)\right)\right|
\end{array}
Initial program 99.8%
Simplified99.8%
associate-*r*99.8%
cos-atan99.8%
un-div-inv99.8%
associate-/l*99.6%
hypot-1-def99.6%
add-sqr-sqrt49.5%
sqrt-unprod94.4%
sqr-neg94.4%
sqrt-unprod50.2%
add-sqr-sqrt99.6%
Applied egg-rr99.6%
Taylor expanded in eh around 0 99.1%
Taylor expanded in t around 0 79.3%
Final simplification79.3%
(FPCore (eh ew t) :precision binary64 (fabs (- ew (* eh (* (sin t) (sin (atan (* (/ eh ew) (- t)))))))))
double code(double eh, double ew, double t) {
return fabs((ew - (eh * (sin(t) * sin(atan(((eh / ew) * -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 - (eh * (sin(t) * sin(atan(((eh / ew) * -t)))))))
end function
public static double code(double eh, double ew, double t) {
return Math.abs((ew - (eh * (Math.sin(t) * Math.sin(Math.atan(((eh / ew) * -t)))))));
}
def code(eh, ew, t): return math.fabs((ew - (eh * (math.sin(t) * math.sin(math.atan(((eh / ew) * -t)))))))
function code(eh, ew, t) return abs(Float64(ew - Float64(eh * Float64(sin(t) * sin(atan(Float64(Float64(eh / ew) * Float64(-t)))))))) end
function tmp = code(eh, ew, t) tmp = abs((ew - (eh * (sin(t) * sin(atan(((eh / ew) * -t))))))); end
code[eh_, ew_, t_] := N[Abs[N[(ew - N[(eh * N[(N[Sin[t], $MachinePrecision] * N[Sin[N[ArcTan[N[(N[(eh / ew), $MachinePrecision] * (-t)), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\left|ew - eh \cdot \left(\sin t \cdot \sin \tan^{-1} \left(\frac{eh}{ew} \cdot \left(-t\right)\right)\right)\right|
\end{array}
Initial program 99.8%
Simplified99.8%
associate-*r*99.8%
cos-atan99.8%
un-div-inv99.8%
associate-/l*99.6%
hypot-1-def99.6%
add-sqr-sqrt49.5%
sqrt-unprod94.4%
sqr-neg94.4%
sqrt-unprod50.2%
add-sqr-sqrt99.6%
Applied egg-rr99.6%
Taylor expanded in eh around 0 99.1%
Taylor expanded in t around 0 79.3%
Taylor expanded in t around 0 79.3%
mul-1-neg79.3%
associate-/l*79.3%
associate-/r/79.3%
distribute-rgt-neg-in79.3%
Simplified79.3%
Final simplification79.3%
herbie shell --seed 2023336
(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)))))))