diff options
Diffstat (limited to 'numpy/doc/structured_arrays.py')
| -rw-r--r-- | numpy/doc/structured_arrays.py | 15 |
1 files changed, 8 insertions, 7 deletions
diff --git a/numpy/doc/structured_arrays.py b/numpy/doc/structured_arrays.py index da3a74bd6..c3605b49a 100644 --- a/numpy/doc/structured_arrays.py +++ b/numpy/doc/structured_arrays.py @@ -57,7 +57,7 @@ A structured datatype can be thought of as a sequence of bytes of a certain length (the structure's :term:`itemsize`) which is interpreted as a collection of fields. Each field has a name, a datatype, and a byte offset within the structure. The datatype of a field may be any numpy datatype including other -structured datatypes, and it may also be a :term:`sub-array` which behaves like +structured datatypes, and it may also be a :term:`subarray` which behaves like an ndarray of a specified shape. The offsets of the fields are arbitrary, and fields may even overlap. These offsets are usually determined automatically by numpy, but can also be specified. @@ -231,7 +231,7 @@ each field's offset is a multiple of its size and that the itemsize is a multiple of the largest field size, and raise an exception if not. If the offsets of the fields and itemsize of a structured array satisfy the -alignment conditions, the array will have the ``ALIGNED`` :ref:`flag +alignment conditions, the array will have the ``ALIGNED`` :attr:`flag <numpy.ndarray.flags>` set. A convenience function :func:`numpy.lib.recfunctions.repack_fields` converts an @@ -266,7 +266,7 @@ providing a 3-element tuple ``(datatype, offset, title)`` instead of the usual >>> np.dtype({'name': ('i4', 0, 'my title')}) dtype([(('my title', 'name'), '<i4')]) -The ``dtype.fields`` dictionary will contain :term:`titles` as keys, if any +The ``dtype.fields`` dictionary will contain title as keys, if any titles are used. This means effectively that a field with a title will be represented twice in the fields dictionary. The tuple values for these fields will also have a third element, the field title. Because of this, and because @@ -431,8 +431,9 @@ array, as follows:: Assignment to the view modifies the original array. The view's fields will be in the order they were indexed. Note that unlike for single-field indexing, the -view's dtype has the same itemsize as the original array, and has fields at the -same offsets as in the original array, and unindexed fields are merely missing. +dtype of the view has the same itemsize as the original array, and has fields +at the same offsets as in the original array, and unindexed fields are merely +missing. .. warning:: In Numpy 1.15, indexing an array with a multi-field index returned a copy of @@ -453,7 +454,7 @@ same offsets as in the original array, and unindexed fields are merely missing. Numpy 1.12, and similar code has raised ``FutureWarning`` since 1.7. In 1.16 a number of functions have been introduced in the - :module:`numpy.lib.recfunctions` module to help users account for this + :mod:`numpy.lib.recfunctions` module to help users account for this change. These are :func:`numpy.lib.recfunctions.repack_fields`. :func:`numpy.lib.recfunctions.structured_to_unstructured`, @@ -610,7 +611,7 @@ creating record arrays, see :ref:`record array creation routines <routines.array-creation.rec>`. A record array representation of a structured array can be obtained using the -appropriate :ref:`view`:: +appropriate `view <numpy-ndarray-view>`_:: >>> arr = np.array([(1, 2., 'Hello'), (2, 3., "World")], ... dtype=[('foo', 'i4'),('bar', 'f4'), ('baz', 'a10')]) |