sleap.io.format.sleap_analysis#

Adaptor to read and write analysis HDF5 files.

These contain location and track data, but lack other metadata included in a full SLEAP dataset file.

Note that this adaptor will use default track names and skeleton node names if these cannot be read from the HDF5 (some files have these, some don’t).

To determine whether this adaptor can read a file, we check it’s an HDF5 file with a track_occupancy dataset.

class sleap.io.format.sleap_analysis.SleapAnalysisAdaptor[source]#
property all_exts#

List of all file extensions supported by adaptor.

can_read_file(file: FileHandle)[source]#

Returns whether this adaptor can read this file.

can_write_filename(filename: str)[source]#

Returns whether this adaptor can write format of this filename.

property default_ext#

The default file extension, e.g., ‘json’ (without ‘.’).

does_read() → bool[source]#

Returns whether this adaptor supports reading.

does_write() → bool[source]#

Returns whether this adaptor supports writing.

property handles#

Returns the type of object that can be read/written.

The Dispatch class calls this method on all registered adaptors to determine which to use for reading/writing.

property name#

Human-reading name of the file format

classmethod read(file: FileHandle, video: Union[Video, str], *args, **kwargs) → Labels[source]#

Reads the file and returns the appropriate deserialized object.

classmethod write(filename: str, source_object: Labels, source_path: Optional[str] = None, video: Optional[Video] = None)[source]#

Writes analysis file for Labels source_object.

Parameters:

  • filename – The filename for the output file.

  • source_object – The Labels from which to get data from.

  • video – The Video from which toget data from. If no video is specified, then the first video in source_object videos list will be used. If there are no Labeled Frame`s in the `video, then no analysis file will be written.