ValidPosesInputs

class movement.validators.datasets.ValidPosesInputs(*, position_array, confidence_array=None, individual_names=None, fps=None, source_software=None, keypoint_names=None)

Bases: _BaseDatasetInputs

Class for validating input data for a movement poses dataset.

The validator ensures that within the movement poses dataset:

• The required position_array is a numpy array with the space dimension containing 2 or 3 spatial coordinates.

• The optional confidence_array, if provided, is a numpy array with its shape matching that of the position_array, excluding the space dimension; otherwise, it defaults to an array of NaNs.

• The optional individual_names and keypoint_names, if provided, match the number of individuals and keypoints in the dataset, respectively; otherwise, default names are assigned.

• The optional fps is a positive float; otherwise, it defaults to None.

• The optional source_software is a string; otherwise, it defaults to None.

position_array

Array of shape (n_frames, n_space, n_keypoints, n_individuals) containing the poses.

Type:

np.ndarray

confidence_array

Array of shape (n_frames, n_keypoints, n_individuals) containing the point-wise confidence scores. If None (default), the scores will be set to an array of NaNs.

Type:

np.ndarray, optional

individual_names

List of unique names for the individuals in the video. If None (default), the individuals will be named “id_0”, “id_1”, etc.

Type:

list of str, optional

keypoint_names

List of unique names for the keypoints in the skeleton. If None (default), the keypoints will be named “keypoint_0”, “keypoint_1”, etc.

Type:

list of str, optional

fps

Frames per second of the video. Defaults to None.

Type:

float, optional

source_software

Name of the software from which the poses were loaded. Defaults to None.

Type:

str, optional

Raises:

ValueError – If the dataset does not meet the movement poses dataset requirements.

Methods

to_dataset()	Convert validated poses inputs to a movement poses dataset.
validate(ds)	Validate that the dataset has the required variables and dimensions.

to_dataset()

Convert validated poses inputs to a movement poses dataset.

Returns:

movement dataset containing the pose tracks, confidence scores, and associated metadata.

Return type:

xarray.Dataset

classmethod validate(ds)

Validate that the dataset has the required variables and dimensions.

Parameters:

ds (xarray.Dataset) – Dataset to validate.

Raises:

• TypeError – If the input is not an xarray Dataset.

• ValueError – If the dataset is missing required data variables or dimensions for a valid movement dataset.

Return type:

None