It was already pretty badly intrusive, but it also appears to make MSVC
segfault. Rather than investigating and fixing it, it's easier to just
remove it.
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.
Example signatures (old => new):
foo(int) => foo(arg0: int)
bar(Object, int) => bar(self: Object, arg0: int)
The change makes the signatures uniform for named and unnamed arguments
and it helps static analysis tools reconstruct function signatures from
docstrings.
This also tweaks the signature whitespace style to better conform to
PEP 8 for annotations and default arguments:
" : " => ": "
" = " => "="
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.
Some Eigen objects, such as those returned by matrix.diagonal() and
matrix.block() have non-standard stride values because they are
basically just maps onto the underlying matrix without copying it (for
example, the primary diagonal of a 3x3 matrix is a vector-like object
with .src equal to the full matrix data, but with stride 4). Returning
such an object from a pybind11 method breaks, however, because pybind11
assumes vectors have stride 1, and that matrices have strides equal to
the number of rows/columns or 1 (depending on whether the matrix is
stored column-major or row-major).
This commit fixes the issue by making pybind11 use Eigen's stride
methods when copying the data.
PR #309 broke scoped enums, which failed to compile because the added:
value == value2
comparison isn't valid for a scoped enum (they aren't implicitly
convertible to the underlying type). This commit fixes it by
explicitly converting the enum value to its underlying type before
doing the comparison.
It also adds a scoped enum example to the constants-and-functions
example that triggers the problem fixed in this commit.
Eigen::Ref is a common way to pass eigen dense types without needing a
template, e.g. the single definition `void
func(Eigen::Ref<Eigen::MatrixXd> x)` can be called with any double
matrix-like object.
The current pybind11 eigen support fails with internal errors if
attempting to bind a function with an Eigen::Ref<...> argument because
Eigen::Ref<...> satisfies the "is_eigen_dense" requirement, but can't
compile if actually used: Eigen::Ref<...> itself is not default
constructible, and so the argument std::tuple containing an
Eigen::Ref<...> isn't constructible, which results in compilation
failure.
This commit adds support for Eigen::Ref<...> by giving it its own
type_caster implementation which consists of an internal type_caster of
the referenced type, load/cast methods that dispatch to the internal
type_caster, and a unique_ptr to an Eigen::Ref<> instance that gets
set during load().
There is, of course, no performance advantage for pybind11-using code of
using Eigen::Ref<...>--we are allocating a matrix of the derived type
when loading it--but this has the advantage of allowing pybind11 to bind
transparently to C++ methods taking Eigen::Refs.
This renames example files from `exampleN` to `example-description`.
Specifically, the following renaming is applied:
example1 -> example-methods-and-attributes
example2 -> example-python-types
example3 -> example-operator-overloading
example4 -> example-constants-and-functions
example5 -> example-callbacks (*)
example6 -> example-sequence-and-iterators
example7 -> example-buffers
example8 -> example-custom-ref-counting
example9 -> example-modules
example10 -> example-numpy-vectorize
example11 -> example-arg-keywords-and-defaults
example12 -> example-virtual-functions
example13 -> example-keep-alive
example14 -> example-opaque-types
example15 -> example-pickling
example16 -> example-inheritance
example17 -> example-stl-binders
example18 -> example-eval
example19 -> example-custom-exceptions
* the inheritance parts of example5 are moved into example-inheritance
(previously example16), and the remainder is left as example-callbacks.
This commit also renames the internal variables ("Example1",
"Example2", "Example4", etc.) into non-numeric names ("ExampleMandA",
"ExamplePythonTypes", "ExampleWithEnum", etc.) to correspond to the
file renaming.
The order of tests is preserved, but this can easily be changed if
there is some more natural ordering by updating the list in
examples/CMakeLists.txt.
This changes the exception error message of a bad-arguments error to
suppress the constructor argument when the failure is a constructor.
This changes both the "Invoked with: " output to omit the object
instances, and rewrites the constructor signature to make it look
like a constructor (changing the first argument to the object name, and
removing the ' -> NoneType' return type.
This allows (and changes the current examples) to exit with status 99 to
skip a test instead of outputting a special string ("NumPy missing").
This also fixes the eigen test, which currently fails when eigen
headers are available but NumPy is not, to skip instead of failing when
NumPy isn't available.
Add and declare to Python functions
double_mat_cm() --- compute 2* a column-major matrix
double_mat_rm() --- compute 2* a row-major matrix
to 'eigen.cpp' tests / example.
Passing a non-contiguous one-dimensional numpy array gives incorrect
results, so three of these tests fail. The only one passing is the
simple case where the numpy array is contiguous and we are building a
column-major vector. Subsequent commit will fix the three failing
cases.
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.
args was derived from list, but cpp_function::dispatcher sends a tuple to it->impl (line #346 and #392 in pybind11.h). As a result args::size() and args::operator[] don't work at all. On my mac args::size() returns -1. Making args a subclass of tuple fixes it.
