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.
GCC-6 adds a -Wplacement-new warning that warns for placement-new into a
space that is too small, which is sometimes being triggered here (e.g.
example5 always generates the warning under g++-6). It's a false
warning, however: the line immediately before just checked the size, and
so this line is never going to actually be reached in the cases where
the GCC warning is being triggered.
This localizes the warning disabling just to this one spot as there are
other placement-new uses in pybind11 where this warning could warn about
legitimate future problems.
This commit adds an additional _ template function for compile-time
selection between two description strings. This in turn allows the
elimination of needing two name() methods in type_caster<arithmetic
types> and type_caster<eigen types>, which allows them to start using
PYBIND11_TYPE_CASTER instead, simplifying their code by eliminating all
the code that they are duplicating from the macro.
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.
In eigen.h, type_caster<Type>::load(): For the 'ndim == 1' case, use
the 'InnerStride' type because there is only an inner stride for a
vector. Choose between (n_elts x 1) or (1 x n_elts) according to
whether we're constructing a Vector or a RowVector.
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.
