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* Allow function/functor passed to py::vectorize to return void

* Stealing @sizmailov's test and fixing unused argument warning

* Add missing std::move()

RVO doesn't work here because function return type is different from
actual returned type

* remove extra EOL

* docs: add a few details

* chore: pre-commit autoupdate

* Remove array_iterator, array_begin, and array_end (in detail namespace)
Co-authored-by: Sergei Izmailov <sergei.a.izmailov@gmail.com>
Co-authored-by: Henry Schreiner <henryschreineriii@gmail.com>

* tests: refactor and cleanup

* refactor: more consistent

* tests: vendor six

* tests: more xfails, nicer system

* tests: simplify to info

* tests: suggestions from @YannickJadoul and @bstaletic

* tests: restore some pypy tests that now pass

* tests: rename info to env

* tests: strict False/True

* tests: drop explicit strict=True again

* tests: reduce minimum PyTest to 3.1

This udpates all the remaining tests to the new test suite code and
comment styles started in #898.  For the most part, the test coverage
here is unchanged, with a few minor exceptions as noted below.

- test_constants_and_functions: this adds more overload tests with
  overloads with different number of arguments for more comprehensive
  overload_cast testing.  The test style conversion broke the overload
  tests under MSVC 2015, prompting the additional tests while looking
  for a workaround.

- test_eigen: this dropped the unused functions `get_cm_corners` and
  `get_cm_corners_const`--these same tests were duplicates of the same
  things provided (and used) via ReturnTester methods.

- test_opaque_types: this test had a hidden dependence on ExampleMandA
  which is now fixed by using the global UserType which suffices for the
  relevant test.

- test_methods_and_attributes: this required some additions to UserType
  to make it usable as a replacement for the test's previous SimpleType:
  UserType gained a value mutator, and the `value` property is not
  mutable (it was previously readonly).  Some overload tests were also
  added to better test overload_cast (as described above).

- test_numpy_array: removed the untemplated mutate_data/mutate_data_t:
  the templated versions with an empty parameter pack expand to the same
  thing.

- test_stl: this was already mostly in the new style; this just tweaks
  things a bit, localizing a class, and adding some missing
  `// test_whatever` comments.

- test_virtual_functions: like `test_stl`, this was mostly in the new
  test style already, but needed some `// test_whatever` comments.
  This commit also moves the inherited virtual example code to the end
  of the file, after the main set of tests (since it is less important
  than the other tests, and rather length); it also got renamed to
  `test_inherited_virtuals` (from `test_inheriting_repeat`) because it
  tests both inherited virtual approaches, not just the repeat approach.

This extends py::vectorize to automatically pass through
non-vectorizable arguments.  This removes the need for the documented
"explicitly exclude an argument" workaround.

Vectorization now applies to arithmetic, std::complex, and POD types,
passed as plain value or by const lvalue reference (previously only
pass-by-value types were supported).  Non-const lvalue references and
any other types are passed through as-is.

Functions with rvalue reference arguments (whether vectorizable or not)
are explicitly prohibited: an rvalue reference is inherently not
something that can be passed multiple times and is thus unsuitable to
being in a vectorized function.

The vectorize returned value is also now more sensitive to inputs:
previously it would return by value when all inputs are of size 1; this
is now amended to having all inputs of size 1 *and* 0 dimensions.  Thus
if you pass in, for example, [[1]], you get back a 1x1, 2D array, while
previously you got back just the resulting single value.

Vectorization of member function specializations is now also supported
via `py::vectorize(&Class::method)`; this required passthrough support
for the initial object pointer on the wrapping function pointer.

This extends the trivial handling to support trivial handling for
Fortran-order arrays (i.e. column major): if inputs aren't all
C-contiguous, but *are* all F-contiguous, the resulting array will be
F-contiguous and we can do trivial processing.

For anything else (e.g. C-contiguous, or inputs requiring non-trivial
processing), the result is in (numpy-default) C-contiguous layout.

The only part of the vectorize code that actually needs c-contiguous is
the "trivial" broadcast; for non-trivial arguments, the code already
uses strides properly (and so handles C-style, F-style, neither, slices,
etc.)

This commit rewrites `broadcast` to additionally check for C-contiguous
storage, then takes off the `c_style` flag for the arguments, which
will keep the functionality more or less the same, except for no longer
requiring an array copy for non-c-contiguous input arrays.

Additionally, if we're given a singleton slice (e.g. a[0::4, 0::4] for a
4x4 or smaller array), we no longer fail triviality because the trivial
code path never actually uses the strides on a singleton.

* Add value_type member alias to py::array_t (resolve #632)

* Use numpy scalar name in py::array_t function signatures (e.g. float32/64 instead of just float)

test_eigen.py and test_numpy_*.py have the same
@pytest.requires_eigen_and_numpy or @pytest.requires_numpy on every
single test; this changes them to use pytest's global `pytestmark = ...`
instead to disable the entire module when numpy and/or eigen aren't
available.

The C++ part of the test code is modified to achieve this. As a result,
this kind of test:

```python
with capture:
    kw_func1(5, y=10)
assert capture == "kw_func(x=5, y=10)"
```

can be replaced with a simple:

`assert kw_func1(5, y=10) == "x=5, y=10"`

Use simple asserts and pytest's powerful introspection to make testing
simpler. This merges the old .py/.ref file pairs into simple .py files
where the expected values are right next to the code being tested.

This commit does not touch the C++ part of the code and replicates the
Python tests exactly like the old .ref-file-based approach.