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io.load_poses

load_pose_estimation​

def load_pose_estimation(
    pose_estimation_file: Path | str, video_file: Path | str, fps: int,
    source_software: Literal["DeepLabCut", "SLEAP", "LightningPose"]
) -> xr.Dataset

Load pose estimation data.

Parameters

  • pose_estimation_file (Path or str): Path to the pose estimation file.
  • video_file (Path or str): Path to the video file.
  • fps (int): Sampling rate of the video.
  • source_software (Literal["DeepLabCut", "SLEAP", "LightningPose"]): Source software used for pose estimation.

Returns

  • ds (xarray.Dataset): 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[PoseEstimationFiletype] = None,
    path_to_pose_nwb_series_data: Optional[str] = None
) -> Tuple[pd.DataFrame, np.ndarray, xr.Dataset]

Read pose estimation file.

Parameters

  • file_path (str): Path to the pose estimation file.
  • file_type (PoseEstimationFiletype): Type of the pose estimation file. Supported types are 'csv' and 'nwb'.
  • path_to_pose_nwb_series_data (str, optional): Path to the pose data inside the nwb file, by default None

Returns

  • Tuple[pd.DataFrame, np.ndarray]: Tuple containing the pose estimation data as a pandas DataFrame and a numpy array.