Module H5S¶
Low-level interface to the “H5S” family of data-space functions.
Functional API¶
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h5py.h5s.create(INT class_code) → SpaceID¶ Create a new HDF5 dataspace object, of the given class. Legal values are
SCALARandSIMPLE.
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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.
Dataspace objects¶
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class
h5py.h5s.SpaceID¶ Bases:
h5py._objects.ObjectIDRepresents a dataspace identifier.
Properties:
- shape
Numpy-style shape tuple with dimensions.
Hashable: No
Equality: Unimplemented
Can be pickled if HDF5 1.8 is available.
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encode() → STRING¶ Serialize a dataspace, including its selection. Bear in mind you can also use the native Python pickling machinery to do this.
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extent_copy(SpaceID source)¶ Replace this dataspace’s extent with another’s, changing its typecode if necessary.
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get_regular_hyperslab() -> (TUPLE start, TUPLE stride, TUPLE count, TUPLE block)¶ Retrieve a regular hyperslab selection.
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get_select_bounds() -> (TUPLE start, TUPLE end)¶ Determine the bounding box which exactly contains the current selection.
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get_select_elem_npoints() → LONG npoints¶ Determine the number of elements selected in point-selection mode.
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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).
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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.
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get_select_hyper_nblocks() → LONG nblocks¶ Get the number of hyperslab blocks currently selected.
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get_select_npoints() → LONG npoints¶ Determine the total number of points currently selected. Works for all selection techniques.
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get_select_type() → INT select_code¶ Determine selection type. Return values are:
SEL_NONESEL_ALLSEL_POINTSSEL_HYPERSLABS
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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.
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get_simple_extent_ndims() → INT rank¶ Determine the rank of a “simple” (slab) dataspace.
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get_simple_extent_npoints() → LONG npoints¶ Determine the total number of elements in a dataspace.
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get_simple_extent_type() → INT class_code¶ Class code is either
SCALARorSIMPLE.
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is_regular_hyperslab() → BOOL¶ Determine whether a hyperslab selection is regular.
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is_simple() → BOOL is_simple¶ Determine if an existing dataspace is “simple” (including scalar dataspaces). Currently all HDF5 dataspaces are simple.
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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.
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select_all()¶ Select all points in the dataspace.
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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.
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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.
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select_none()¶ Deselect entire dataspace.
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select_valid() → BOOL¶ Determine if the current selection falls within the dataspace extent.
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set_extent_none()¶ Remove the dataspace extent; typecode changes to
NO_CLASS.
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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.
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shape¶ Numpy-style shape tuple representing dimensions. () == scalar.
Module constants¶
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h5py.h5s.ALL¶ Accepted in place of an actual dataspace; means “every point”
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h5py.h5s.UNLIMITED¶ Indicates an unlimited maximum dimension