Model

This module provides classes for structuring, storing and loading trial data.

class gaitalytics.model.BaseTrial

Abstract base class for trials.

This class provides a common interface for trials to load and save data.

to_hdf5(file_path: Path, base_group: str | None = None)

Saves the trial data to an HDF5 file.

Parameters:

  • file_path – The path to the HDF5 file.

  • base_group – The base group to save the data.

  • None (Default =)

  • file. (the data will be saved in the root of the)

  • None

Raises:

  • FileExistsError – If the file already exists.

  • ValueError – If the trial is a segmented trial and

  • the file path is a single file. –

  • ValueError – If the trial is a trial and the file path is a folder.

class gaitalytics.model.DataCategory(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Enum class for the array categories.

This class provides the categories for the data arrays.

MARKERS

The marker’s category.

Type:

str

ANALOGS

The analog’s category.

Type:

str

ANALYSIS

The analysis category.

Type:

str

class gaitalytics.model.Trial

Represents a trial.

A trial is a collection of data arrays (typically markers & analogs) and events.

__init__()

Initializes a new instance of the Trial class.

add_channel(category: DataCategory, data: DataArray)

Adds a channel to the trial.

Parameters:

  • category – The category of the data.

  • data – The data array to be added.

add_data(category: DataCategory, data: DataArray)

Adds data to the trial.

Parameters:

  • category – The category of the data.

  • data – The data array to be added.

property events: DataFrame | None

Gets the events in the trial.

Returns:

A pandas DataFrame containing the events if present. None: If no events are present.

Return type:

pd.DataFrame

get_all_data() → dict[DataCategory, DataArray]

Gets all data from the trial.

Returns:

A dictionary containing the data arrays.

get_data(category: DataCategory) → DataArray

Gets the data from the trial.

Parameters:

category – The category of the data.

Returns:

The data array.

class gaitalytics.model.TrialCycles

Represents a segmented trial.

__init__()

Initializes a new instance of the SegmentedTrial class.

add_cycle(context: str, cycle_id: int, segment: Trial)

Adds a Cycle to the segmented trial.

Parameters:

  • context – The context of the cycle.

  • cycle_id – The id of the cycle.

  • segment – The segment to be added.

get_all_cycles() → dict[str, dict[int, Trial]]

Gets all cycles from the segmented trial.

Returns:

A nexted dictionary containing the cycles. Whereas the key of the first dictionary is the context and the second key is the cycle number.

get_cycle(context: str, cycle_id: int) → Trial

Gets a cycle from the segmented trial.

Parameters:

  • context – The context of the cycle.

  • cycle_id – The id of the cycle.

Raises:

KeyError – If the cycle does not exist.

get_cycles_per_context(context: str) → dict[int, Trial]

Gets all cycles from the segmented trial for a specific context.

Parameters:

context – The context of the cycles.

Returns:

A dictionary containing the cycles for the specified context.

gaitalytics.model.trial_from_hdf5(file_path: Path) → Trial | TrialCycles

Loads trial data from an HDF5 file.

Can be used to load a single trial or a segmented trial after saving it.

Parameters:

file_path – The path to the HDF5 file or folder with the expected structure.

Returns:

A new instance of the Trial class if file_path is a single file. TrialCycles: A new instance of the TrialCycles class if file_path is a folder.

Return type:

Trial