tiled.adapters.hdf5.HDF5Adapter

Adapter for HDF5 files

This map the structure of an HDF5 file onto a “Tree” of array structures.

Parameters:

treedict: A dictionary representing the HDF5 file or group. The keys are the names of the groups or datasets, and the values are either dictionaries (representing groups) or None (representing datasets). HDF5 datasets will be mapped to HDF5ArrayAdapter instances, and groups will be mapped to HDF5Adapter instances. The tree is rooted at the ‘dataset’ node.
data_urisstr: The URI of the file, or a list of URIs if the dataset spans multiple files.
datasetstr: The dataset to read, for example, “/path/to/dataset” within the file. If supplied, this path will effectively become the root of the adapter.
metadatadict: Metadata for the adapter
specslist: A list of specs for the adapter
kwargsdict: Additional keyword arguments, such as swmr, libver, etc. – they are not stored as separate attributes

Examples

From the root node of a file given a filepath

>>> import h5py
>>> HDF5Adapter.from_uri("file://localhost/path/to/file.h5")

__init__(tree: dict[str, Any] | Sentinel, *data_uris: str, dataset: str | None = None, structure: ArrayStructure | None = None, metadata: Dict[str, str | int | float | bool | Dict[str, Dict[str, str | int | float | bool | Dict[str, JSON] | List[JSON]]] | List[Dict[str, str | int | float | bool | Dict[str, JSON] | List[JSON]]]] | None = None, specs: List[Spec] | None = None, **kwargs: Any | None) → None[source]

Methods

`__init__`(tree, *data_uris[, dataset, ...])
`from_catalog`(data_source, node, /[, ...])
`from_uris`(*data_uris[, dataset, swmr, libver])
`get`(key, *args)	Overwrite to always raise KeyErrors for broken links and missing items
`inlined_contents_enabled`(depth)
`items`()
`keys`()
`metadata`()
`read`([fields])
`search`(query)
`structure`()
`values`()

Attributes