Version 2.0 was commit: 5b8b5c21ec18c878a93be2fca95f9c9dafd58ac6
Short version:
Made it work without point/weighted_point implicit conversions
and made it more generic by reworking the inheritance of adaptors and providing
appropriate constructors
Long version:
-- Reworked P3_construct_point_3 and P3_construct_weighted_point_3 to inherit
a base Construct_point_3 and initialize it properly at construction.
-- Renamed Traits_with_offset / Regular_traits_with_offset adaptors. These
classes now inherit the base functor and the constructors allow to initialize
that base from an existing functor (meaning that we don't default constructor
functors anymore). This also means that we can use the base operator() of the
functors and can thus use all possible inputs (with or without offsets).
-- Static filters now probably inherit the correct *_filtered_traits_base_3.
-- All traits classes now have constructor to be able to initialize traits
from a given domain and a given base kernel (rather than default construct)
-- Fixed Del/regular_remove_traits inherting the wrong classes
-- Filtered traits have exact and approximate traits rather than exact and
approximate domains with default constructed traits
One problem is left:
Filtered traits members are initialized with a default constructed base kernel.
Ideally, it should use Cartesian_converter(Base::kernel()), but this does not
exist...
BEFORE:
A template mecanism allows to determine wether the kernel offers filtered, or
even statistically filtered operations. The highest level is chosen and includes
the sub-levels. For example, if the kernel offers filtered but _not_ statistically
filtered operations, using the traits class `Periodic_3_triangulation_traits_3`
is equivalent to using the class `Periodic_3_triangulation_filtered_traits_3`,
which inherits the operations of `Periodic_3_triangulation_traits_3` (implemented
in `Periodic_3_triangulation_traits_base_3`) and overwrites some of them.
A similar mecanism is done for Delaunay and regular traits; e.g. if the kernel
offers statistically filtered traits, then using `Periodic_3_Delaunay_triangulation_traits_3`
is similar to using `Periodic_3_Delaunay_triangulation_statistically_filtered_traits_3`,
which inherits from `Periodic_3_Delaunay_triangulation_filtered_traits_3`, which itself
inherits from `Periodic_3_Delaunay_triangulation_traits_3`.
PROBLEM:
The base class of Delaunay and regular traits, respectively
`Periodic_3_Delaunay_triangulation_traits_base_3` and
`Periodic_3_regular_triangulation_traits_base_3` inherit the class
`Periodic_3_triangulation_traits_base_3`. Thus, if the kernel is filtered
or statistically filtered, then the filtered operations that should
"belong" at the level of triangulation traits (for example, orientation_3)
must be duplicated in the Delaunay and regular traits file otherwise
they are not filtered.
AFTER:
With this commit, the Delaunay and regular bases traits inherit
from `Periodic_3_triangulation_traits_3` (no "_base"). This means
that the base class will also select its highest possible level of
filtration and there is no need to duplicate code 3 times anymore.
-- A real kernel is now passed to the traits and not some kind of Regular_traits
thus removing the need for Weighted_converter_3 (and similar changes)
-- Updated function objects names
Andreas Fabri
Sébastien Loriot
Mael Rouxel-Labbé
Laurent Rineau
Sébastien Loriot
Manuel Caroli