don't trust convexity with affine transforms
In theory, a convex shape transformed by an affine matrix should still
be convex. However, due to numerical nastiness of floats, when we try
to determine if something is convex, we can get different answers pre
and post a transformation (think of two line segments nearly colinear).
Convex paths take a faster scan converter, but it is only well behaved
if the path is, in fact, convex. Thus we have to be conservative about
which paths we mark as convex.
This bug found a case where a "convex" path, after going through a transform,
became (according to our measure) non-convex. The bug was that we *thought*
that once convex always convex, but in reality it was not. The fix (hack) is
to notice when we transform by an affine matrix (we're still assuming/hoping
that scaling and translate keep things convex (1)...) and mark the convexity
as "unknown", forcing us to re-compute it.
This will slow down these paths, since it costs something to compute convexity.
Hopefully non-scale-translate transforms are rare, so we won't notice the
speed loss too much.
(1) This is not proven. If we find scaling/translation to break our notion of
convexity, we'll need to get more aggressive/clever to find a fix.
Commit-Queue: Mike Reed <email@example.com>
Reviewed-by: Cary Clark <firstname.lastname@example.org>
Reviewed-by: Jim Van Verth <email@example.com>
2 files changed