Module H5S

Low-level interface to the “H5S” family of data-space functions.

Functional API

h5py.h5s.create(INT class_code) → SpaceID

Create a new HDF5 dataspace object, of the given class. Legal values are SCALAR and SIMPLE.

h5py.h5s.create_simple(TUPLE dims_tpl, TUPLE max_dims_tpl) → SpaceID

Create a simple (slab) dataspace from a tuple of dimensions. Every element of dims_tpl must be a positive integer.

You can optionally specify the maximum dataspace size. The special value UNLIMITED, as an element of max_dims, indicates an unlimited dimension.

h5py.h5s.decode(STRING buf) → SpaceID

Unserialize a dataspace. Bear in mind you can also use the native Python pickling machinery to do this.

Dataspace objects

class h5py.h5s.SpaceID

Bases: h5py._objects.ObjectID

Represents a dataspace identifier.

Properties:

shape
Numpy-style shape tuple with dimensions.
  • Hashable: No
  • Equality: Unimplemented

Can be pickled if HDF5 1.8 is available.

copy() → SpaceID

Create a new copy of this dataspace.

encode() → STRING

Serialize a dataspace, including its selection. Bear in mind you can also use the native Python pickling machinery to do this.

extent_copy(SpaceID source)

Replace this dataspace’s extent with another’s, changing its typecode if necessary.

get_select_bounds() -> (TUPLE start, TUPLE end)

Determine the bounding box which exactly contains the current selection.

get_select_elem_npoints() → LONG npoints

Determine the number of elements selected in point-selection mode.

get_select_elem_pointlist() → NDARRAY

Get a list of all selected elements. Return is a Numpy array of unsigned ints, with shape (<npoints>, <space rank).

get_select_hyper_blocklist() → NDARRAY

Get the current hyperslab selection. The returned array has shape:

(<npoints>, 2, <rank>)

and can be interpreted as a nested sequence:

[ (corner_coordinate_1, opposite_coordinate_1), ... ]

with length equal to the total number of blocks.

get_select_hyper_nblocks() → LONG nblocks

Get the number of hyperslab blocks currently selected.

get_select_npoints() → LONG npoints

Determine the total number of points currently selected. Works for all selection techniques.

get_select_type() → INT select_code

Determine selection type. Return values are:

get_simple_extent_dims(BOOL maxdims=False) → TUPLE shape

Determine the shape of a “simple” (slab) dataspace. If “maxdims” is True, retrieve the maximum dataspace size instead.

get_simple_extent_ndims() → INT rank

Determine the rank of a “simple” (slab) dataspace.

get_simple_extent_npoints() → LONG npoints

Determine the total number of elements in a dataspace.

get_simple_extent_type() → INT class_code

Class code is either SCALAR or SIMPLE.

is_simple() → BOOL is_simple

Determine if an existing dataspace is “simple” (including scalar dataspaces). Currently all HDF5 dataspaces are simple.

offset_simple(TUPLE offset=None)

Set the offset of a dataspace. The length of the given tuple must match the rank of the dataspace. If None is provided (default), the offsets on all axes will be set to 0.

select_all()

Select all points in the dataspace.

select_elements(SEQUENCE coords, INT op=SELECT_SET)

Select elements by specifying coordinates points. The argument “coords” may be an ndarray or any nested sequence which can be converted to an array of uints with the shape:

(<npoints>, <space rank>)

Examples:

>>> obj.shape
(10, 10)
>>> obj.select_elements([(1,2), (3,4), (5,9)])

A zero-length selection (i.e. shape (0, <rank>)) is not allowed by the HDF5 library.

select_hyperslab(TUPLE start, TUPLE count, TUPLE stride=None, TUPLE block=None, INT op=SELECT_SET)

Select a block region from an existing dataspace. See the HDF5 documentation for the meaning of the “block” and “op” keywords.

select_none()

Deselect entire dataspace.

select_valid() → BOOL

Determine if the current selection falls within the dataspace extent.

set_extent_none()

Remove the dataspace extent; typecode changes to NO_CLASS.

set_extent_simple(TUPLE dims_tpl, TUPLE max_dims_tpl=None)

Reset the dataspace extent via a tuple of dimensions. Every element of dims_tpl must be a positive integer.

You can optionally specify the maximum dataspace size. The special value UNLIMITED, as an element of max_dims, indicates an unlimited dimension.

shape

Numpy-style shape tuple representing dimensions. () == scalar.

Module constants

h5py.h5s.ALL

Accepted in place of an actual datapace; means “every point”

h5py.h5s.UNLIMITED

Indicates an unlimited maximum dimension

Dataspace class codes

h5py.h5s.NO_CLASS
h5py.h5s.SCALAR
h5py.h5s.SIMPLE

Selection codes

h5py.h5s.SELECT_NOOP
h5py.h5s.SELECT_SET
h5py.h5s.SELECT_OR
h5py.h5s.SELECT_AND
h5py.h5s.SELECT_XOR
h5py.h5s.SELECT_NOTB
h5py.h5s.SELECT_NOTA
h5py.h5s.SELECT_APPEND
h5py.h5s.SELECT_PREPEND
h5py.h5s.SELECT_INVALID

Existing selection type

h5py.h5s.SEL_NONE
h5py.h5s.SEL_POINTS
h5py.h5s.SEL_HYPERSLABS
h5py.h5s.SEL_ALL

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