Commit Graph

10 Commits

Author SHA1 Message Date
Jason Rhinelander
ee2e5a5086 Make string conversion stricter (#695)
* Make string conversion stricter

The string conversion logic added in PR #624 for all std::basic_strings
was derived from the old std::wstring logic, but that was underused and
turns out to have had a bug in accepting almost anything convertible to
unicode, while the previous std::string logic was much stricter.  This
restores the previous std::string logic by only allowing actual unicode
or string types.

Fixes #685.

* Added missing 'requires numpy' decorator

(I forgot that the change to a global decorator here is in the
not-yet-merged Eigen PR)
2017-02-24 11:33:31 +01:00
Dean Moldovan
4de271027d Improve consistency of array and array_t with regard to other pytypes
* `array_t(const object &)` now throws on error
* `array_t::ensure()` is intended for casters —- old constructor is
  deprecated
* `array` and `array_t` get default constructors (empty array)
* `array` gets a converting constructor
* `py::isinstance<array_T<T>>()` checks the type (but not flags)

There is only one special thing which must remain: `array_t` gets
its own `type_caster` specialization which uses `ensure` instead
of a simple check.
2016-11-17 08:55:42 +01:00
Sylvain Corlay
5027c4f95b Switch NumPy variadic indexing to per-value arguments (#500)
* Also added unsafe version without checks
2016-11-16 17:53:37 +01:00
Wenzel Jakob
030d10e826 minor style fix 2016-10-28 01:23:42 +02:00
Wenzel Jakob
496feacfd0 pybind11: implicitly convert NumPy integer scalars
The current integer caster was unnecessarily strict and rejected
various kinds of NumPy integer types when calling C++ functions
expecting normal integers. This relaxes the current behavior.
2016-10-28 01:02:46 +02:00
Wenzel Jakob
fac7c09458 NumPy "base" feature: integrated feedback by @aldanor 2016-10-13 10:49:53 +02:00
Wenzel Jakob
369e9b3937 Permit creation of NumPy arrays with a "base" object that owns the data
This patch adds an extra base handle parameter to most ``py::array`` and
``py::array_t<>`` constructors. If specified along with a pointer to
data, the base object will be registered within NumPy, which increases
the base's reference count. This feature is useful to create shallow
copies of C++ or Python arrays while ensuring that the owners of the
underlying can't be garbage collected while referenced by NumPy.

The commit also adds a simple test function involving a ``wrap()``
function that creates shallow copies of various N-D arrays.
2016-10-13 01:03:40 +02:00
Wenzel Jakob
43f6aa6846 added numpy test (minor): check that 'strides' is respected even when creating new arrays
- This actually works with no changes, I just wasn't 100% convinced and
  decided to write a test to see if it's true.
2016-10-12 23:34:13 +02:00
Ivan Smirnov
aca6bcaea5 Add tests for array data access /index methods 2016-09-10 16:42:17 +01:00
Ivan Smirnov
91b3d681ad Expose some dtype/array attributes via NumPy C API 2016-09-10 16:24:00 +01:00