diff options
Diffstat (limited to 'numpy/doc/structured_arrays.py')
| -rw-r--r-- | numpy/doc/structured_arrays.py | 40 |
1 files changed, 13 insertions, 27 deletions
diff --git a/numpy/doc/structured_arrays.py b/numpy/doc/structured_arrays.py index 73bf3b317..fe17c133e 100644 --- a/numpy/doc/structured_arrays.py +++ b/numpy/doc/structured_arrays.py @@ -258,6 +258,19 @@ appropriate :ref:`view`: :: >>> recordarr = arr.view(dtype=dtype((np.record, arr.dtype)), ... type=np.recarray) +For convenience, viewing an ndarray as type `np.recarray` will automatically +convert to `np.record` datatype, so the dtype can be left out of the view: :: + + >>> recordarr = arr.view(np.recarray) + >>> recordarr.dtype + dtype((numpy.record, [('foo', '<i4'), ('bar', '<f4'), ('baz', 'S10')])) + +To get back to a plain ndarray both the dtype and type must be reset. The +following view does so, taking into account the unusual case that the +recordarr was not a structured type: :: + + >>> arr2 = recordarr.view(recordarr.dtype.fields or recordarr.dtype, np.ndarray) + Record array fields accessed by index or by attribute are returned as a record array if the field has a structured type but as a plain ndarray otherwise. :: @@ -272,33 +285,6 @@ Note that if a field has the same name as an ndarray attribute, the ndarray attribute takes precedence. Such fields will be inaccessible by attribute but may still be accessed by index. -Partial Attribute Access ------------------------- - -The differences between record arrays and plain structured arrays induce a -small performance penalty. It is possible to apply one or the other view -independently if desired. To allow field access by attribute only on the array -object it is sufficient to view an array as a recarray: :: - - >>> recarr = arr.view(np.recarray) - -This type of view is commonly used, for example in np.npyio and -np.recfunctions. Note that unlike full record arrays the individual elements of -such a view do not have field attributes:: - - >>> recarr[0].foo - AttributeError: 'numpy.void' object has no attribute 'foo' - -To use the np.record dtype only, convert the dtype using the (base_class, -dtype) form described in numpy.dtype. This type of view is rarely used. :: - - >>> arr_records = arr.view(dtype((np.record, arr.dtype))) - -In documentation, the term 'structured array' will refer to objects of type -np.ndarray with structured dtype, 'record array' will refer to structured -arrays subclassed as np.recarray and whose dtype is of type np.record, and -'recarray' will refer to arrays subclassed as np.recarray but whose dtype is -not of type np.record. """ from __future__ import division, absolute_import, print_function |