deepof.data

Data structures for preprocessing and wrangling of motion tracking output data. This is the main module handled by the user.

There are three main data structures to pay attention to: - Project, which serves as a configuration hub for the whole pipeline - Coordinates, which acts as an intermediary between project configuration and data, and contains a plethora of processing methods to apply, and - TableDict, which is the main data structure to store the data, having experiment IDs as keys and processed time-series as values in a dictionary-like object.

For a detailed tutorial on how to use this module, see the advanced tutorials in the main section.

Functions

load_project(project_path)

Load a pre-saved pickled Coordinates object.

Classes

Coordinates(project_path, project_name, ...)	Class for storing the results of a ran project.
Project([animal_ids, arena, bodypart_graph, ...])	Class for loading and preprocessing motion tracking data of individual and multiple animals.
TableDict(tabs, typ[, arena, arena_dims, ...])	Main class for storing a single dataset as a dictionary with individuals as keys and pandas.DataFrames as values.