As discussed in #320.
The adds a documentation block that mentions that the trampoline classes
must provide overrides for both the classes' own virtual methods *and*
any inherited virtual methods. It also provides a templated solution to
avoiding method duplication.
The example includes a third method (only mentioned in the "see also"
section of the documentation addition), using multiple inheritance.
While this approach works, and avoids code generation in deep
hierarchies, it is intrusive by requiring that the wrapped classes use
virtual inheritance, which itself is more instrusive if any of the
virtual base classes need anything other than default constructors. As
per the discussion in #320, it is kept as an example, but not suggested
in the documentation.
Functions returning specialized Eigen matrices like Eigen::DiagonalMatrix and
Eigen::SelfAdjointView--which inherit from EigenBase but not
DenseBase--isn't currently allowed; such classes are explicitly copyable
into a Matrix (by definition), and so we can support functions that
return them by copying the value into a Matrix then casting that
resulting dense Matrix into a numpy.ndarray. This commit does exactly
that.
Sergey Lyskov pointed out that the trampoline mechanism used to override
virtual methods from within Python caused unnecessary overheads when
instantiating the original (i.e. non-extended) class.
This commit removes this inefficiency, but some syntax changes were
needed to achieve this. Projects using this features will need to make a
few changes:
In particular, the example below shows the old syntax to instantiate a
class with a trampoline:
class_<TrampolineClass>("MyClass")
.alias<MyClass>()
....
This is what should be used now:
class_<MyClass, std::unique_ptr<MyClass, TrampolineClass>("MyClass")
....
Importantly, the trampoline class is now specified as the *third*
argument to the class_ template, and the alias<..>() call is gone. The
second argument with the unique pointer is simply the default holder
type used by pybind11.
