>
> >>> I don't know the best way to be "smart" about fixing this such as how
> >>> much of the asymptote to include, etc.
> >> Yeah, I was thinking about this, because what you would really want to
> >> do is have an algorithm which would automatically check if the 'bend'
> >> was too great compared to the rest of the function and then NOT plot
> >> the line connecting those points.  But would that slow plotting down
> >> too much (since you'd have to compare *all* the bends to each other,
> >> not just to max_bend like in adaptive refinement, as I understand
> >> it)?  Not to mention trying to decide what "too great compared" means.
>
> > It might be easier to detect a root in 1/f(x) (or some kind of  
> > heuristic given a sign change between f(a) and f(b), is a root of f
> > (x) or 1/f(x) more likely).

Thanks for your thoughts, Jason.

>
> Another thing: does the adaptive plotting code handle asymptotes
> intelligently?  That is, when it picks one point on either side of an
> asymptote, it seems like it would try to recursively subdivide unless it
> knows there is an asymptote there or can somehow guess there is an
> asymptote.
>


Not currently, that's for sure, but combined with Robert's idea it
might be a good starting point, given this snippet of the result of
the xdata:
sage: P=plot(tan,-5,5); list=P[0].xdata;len(list)
1201
sage: list
<snip>
-4.7260837325003902,
 -4.7260666712822843,
 -4.7260496100641793,
 -4.7260325488460744,
 -4.7260154876279685,
 -4.7259984264098627,
 -4.7259813651917577,
<snip>
 -0.10341837811481863,
 -0.03500403414505103,
 -0.010279622543906589,
 0.069496699401952633,
 0.10646492301295057,
 0.13438881092313087,
 0.20201941119890751,

Interesting that Mma includes the "asymptotes", but that they really
look like asymptotes given that it intelligently chooses the ymin and
ymax.  That could be another way to go.

- kcrisman
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