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only do numpy contiguous C/Fortran array conversion when explicitly requested
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@ -902,16 +902,30 @@ type of Python object satisfying the buffer protocol).
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In many situations, we want to define a function which only accepts a NumPy
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array of a certain data type. This is possible via the ``py::array_t<T>``
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template. For instance, the following function requires the argument to be a
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dense array of doubles in C-style ordering.
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NumPy array containing double precision values.
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.. code-block:: cpp
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void f(py::array_t<double> array);
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When it is invoked with a different type (e.g. an integer), the binding code
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will attempt to cast the input into a NumPy array of the requested type. Note
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that this feature requires the :file:``pybind11/numpy.h`` header to be
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included.
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When it is invoked with a different type (e.g. an integer or a list of
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integers), the binding code will attempt to cast the input into a NumPy array
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of the requested type. Note that this feature requires the
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:file:``pybind11/numpy.h`` header to be included.
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Data in NumPy arrays is not guaranteed to packed in a dense manner;
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furthermore, entries can be separated by arbitrary column and row strides.
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Sometimes, it can be useful to require a function to only accept dense arrays
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using either the C (row-major) or Fortran (column-major) ordering. This can be
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accomplished via a second template argument with values ``py::array::c_style``
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or ``py::array::f_style``.
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.. code-block:: cpp
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void f(py::array_t<double, py::array::c_style> array);
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As before, the implementation will attempt to convert non-conforming arguments
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into an array satisfying the specified requirements.
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Vectorizing functions
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=====================
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@ -77,6 +77,11 @@ public:
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PYBIND11_OBJECT_DEFAULT(array, buffer, lookup_api().PyArray_Check_)
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enum {
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c_style = API::NPY_C_CONTIGUOUS_,
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f_style = API::NPY_F_CONTIGUOUS_
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};
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template <typename Type> array(size_t size, const Type *ptr) {
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API& api = lookup_api();
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PyObject *descr = api.PyArray_DescrFromType_(npy_format_descriptor<Type>::value);
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@ -120,7 +125,7 @@ protected:
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}
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};
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template <typename T> class array_t : public array {
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template <typename T, int ExtraFlags = 0> class array_t : public array {
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public:
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PYBIND11_OBJECT_CVT(array_t, array, is_non_null, m_ptr = ensure(m_ptr));
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array_t() : array() { }
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@ -131,8 +136,9 @@ public:
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API &api = lookup_api();
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PyObject *descr = api.PyArray_DescrFromType_(npy_format_descriptor<T>::value);
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PyObject *result = api.PyArray_FromAny_(
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ptr, descr, 0, 0, API::NPY_C_CONTIGUOUS_ | API::NPY_ENSURE_ARRAY_
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| API::NPY_ARRAY_FORCECAST_, nullptr);
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ptr, descr, 0, 0,
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API::NPY_ENSURE_ARRAY_ | API::NPY_ARRAY_FORCECAST_ | ExtraFlags,
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nullptr);
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Py_DECREF(ptr);
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return result;
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}
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