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io.load_poses

_validate_movement_schema​

def _validate_movement_schema(ds: xr.Dataset) -> None

Validate that a Dataset matches the movement-format pose schema VAME expects.

Aggregates all problems into a single ValueError so users see the full set of issues at once instead of fixing them one at a time.

load_pose_estimation​

def load_pose_estimation(
        pose_estimation_file: Path | str,
        source_software: Literal["DeepLabCut", "SLEAP", "LightningPose", "NWB",
                                 "auto", "movement"] = "auto",
        video_file: Optional[Path | str] = None,
        fps: Optional[float] = None,
        processing_module_key: str = "behavior",
        pose_estimation_key: str = "PoseEstimation") -> xr.Dataset

Load pose estimation data.

Parameters

  • pose_estimation_file (Path or str): Path to the pose estimation file. Dispatched through movement's unified loader, which auto-detects format from extension and contents.
  • source_software (str, optional): Source software used for pose estimation. Defaults to "auto", which lets movement infer the format from the file. Explicit values ("DeepLabCut", "SLEAP", "LightningPose", "NWB") are passed straight through. "movement" reads a netCDF file written in the movement library's xarray schema directly (bypassing movement's format-specific loaders) and validates it against the pose schema VAME requires; the file may also include extra scalar time series with dims (time,) that ride through preprocessing.
  • video_file (Path or str, optional): Path to the video file. Stored as a dataset attribute.
  • fps (float, optional): Sampling rate of the video. Ignored when source_software is "NWB" or "movement" (fps is read from the file).
  • processing_module_key (str, optional): Only used when source_software="NWB". Name of the NWB processing module that contains the pose estimation container. Default is "behavior".
  • pose_estimation_key (str, optional): Only used when source_software="NWB". Name of the ndx_pose.PoseEstimation object inside the processing module. Default is "PoseEstimation".

Returns

  • xr.Dataset: Movement-format pose estimation dataset.

load_vame_dataset​

def load_vame_dataset(ds_path: Path | str) -> xr.Dataset

Load VAME dataset.

Parameters

  • ds_path (Path or str): Path to the netCDF dataset.

Returns

  • xr.Dataset: VAME dataset

nc_to_dataframe​

def nc_to_dataframe(nc_data)

read_pose_estimation_file​

def read_pose_estimation_file(
    file_path: str,
    file_type: Optional[Literal["csv", "nwb", "slp", "h5"]] = None
) -> Tuple[pd.DataFrame, np.ndarray, xr.Dataset]

Read pose estimation file.

Parameters

  • file_path (str): Path to the pose estimation file.
  • file_type (str, optional): Unused; retained for backwards compatibility.

Returns

  • Tuple[pd.DataFrame, np.ndarray, xr.Dataset]: Pose estimation data as a DataFrame, numpy array, and xarray Dataset.