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Class EArray

tables/earray.py:27–293  ·  view source on GitHub ↗

r"""This class represents extendable, homogeneous datasets in an HDF5 file. The main difference between an EArray and a CArray (see :ref:`CArrayClassDescr`), from which it inherits, is that the former can be enlarged along one of its dimensions, the *enlargeable dimension*. That me

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25
26
27class EArray(CArray):
28 r"""This class represents extendable, homogeneous datasets in an HDF5 file.
29
30 The main difference between an EArray and a CArray (see
31 :ref:`CArrayClassDescr`), from which it inherits, is that the former
32 can be enlarged along one of its dimensions, the *enlargeable
33 dimension*. That means that the :attr:`Leaf.extdim` attribute (see
34 :class:`Leaf`) of any EArray instance will always be non-negative.
35 Multiple enlargeable dimensions might be supported in the future.
36
37 New rows can be added to the end of an enlargeable array by using the
38 :meth:`EArray.append` method.
39
40 Parameters
41 ----------
42 parentnode
43 The parent :class:`Group` object.
44
45 .. versionchanged:: 3.0
46 Renamed from *parentNode* to *parentnode*.
47
48 name : str
49 The name of this node in its parent group.
50
51 atom
52 An `Atom` instance representing the *type* and *shape*
53 of the atomic objects to be saved.
54
55 shape
56 The shape of the new array. One (and only one) of
57 the shape dimensions *must* be 0. The dimension being 0
58 means that the resulting `EArray` object can be extended
59 along it. Multiple enlargeable dimensions are not supported
60 right now.
61
62 title
63 A description for this node (it sets the ``TITLE``
64 HDF5 attribute on disk).
65
66 filters
67 An instance of the `Filters` class that provides information
68 about the desired I/O filters to be applied during the life
69 of this object.
70
71 expectedrows
72 A user estimate about the number of row elements that will
73 be added to the growable dimension in the `EArray` node.
74 If not provided, the default value is ``EXPECTED_ROWS_EARRAY``
75 (see ``tables/parameters.py``). If you plan to create either
76 a much smaller or a much bigger `EArray` try providing a guess;
77 this will optimize the HDF5 B-Tree creation and management
78 process time and the amount of memory used.
79
80 chunkshape
81 The shape of the data chunk to be read or written in a single
82 HDF5 I/O operation. Filters are applied to those chunks of data.
83 The dimensionality of `chunkshape` must be the same as that of
84 `shape` (beware: no dimension should be 0 this time!).

Callers 4

_g_copy_with_statsMethod · 0.85
_g_post_init_hookMethod · 0.85
create_tempMethod · 0.85
create_earrayMethod · 0.85

Calls

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