matmodel.descriptor package

Submodules

matmodel.descriptor.descriptor module

MAT-Tools: Python Framework for Multiple Aspect Trajectory Data Mining

The present application offers a tool, to support the user in the modeling of multiple aspect trajectory data. It integrates into a unique framework for multiple aspects trajectories and in general for multidimensional sequence data mining methods. Copyright (C) 2022, MIT license (this portion of code is subject to licensing from source project distribution)

Created on Apr, 2024 Copyright (C) 2024, License GPL Version 3 or superior (see LICENSE file)

Authors:

• Tarlis Portela

• Vanessa Lago Machado

class matmodel.descriptor.descriptor.DataDescriptor(idDesc=None, labelDesc=None, attributes=[])

Bases: object

Represents a data descriptor that describes the structure of data, including the ID, label, and attributes.

Attributes:

idDesc (FeatureDescriptor):

Descriptor for the ID feature.

labelDesc (FeatureDescriptor):

Descriptor for the label feature.

attributes (list):

List of feature descriptors for the attributes.

dependencies (dict):

A dictionary mapping dependency groups to the associated attributes (optional).

Methods:

__iter__():

Initializes the iterator for the attributes.

__next__():

Iterates through the attributes.

feature_names():

Returns a list of names (text) for all the attributes.

instantiate(json_obj):

Static method to instantiate a DataDescriptor from a JSON object.

property feature_names

static instantiate(json_obj)

class matmodel.descriptor.descriptor.FeatureDescriptor(order, text, dtype='nominal', comparator=None, weight=None)

Bases: object

Represents a descriptor for a single feature (attribute) in the dataset.

Attributes:

order (int):

The order of the feature in the dataset.

dtype (str):

The data type of the feature (e.g., ‘nominal’, ‘numeric’, ‘boolean’).

text (str):

The textual description or name of the feature.

weight (float):

The weight associated with this feature for comparisons (optional).

comparator (str):

The instance of the class comparator used to compare feature values (optional).

dependency_group (str):

The dependency group name for this feature (optional).

Methods:

name():

Property to return the name (text) of the feature.

__repr__():

Returns a string representation of the feature descriptor.

instantiate(json_obj):

Static method to instantiate a FeatureDescriptor from a JSON object.

static instantiate(json_obj)

property name

matmodel.descriptor.descriptor.descriptor2json(dataDescriptor)

Converts a DataDescriptor object into a JSON-like dictionary.

Args:

dataDescriptor (DataDescriptor):

The DataDescriptor object to convert.

Returns:

dict:

A JSON-like dictionary representation of the DataDescriptor.

matmodel.descriptor.descriptor.df2descriptor(df, tid_col='tid', label_col='label')

Converts a pandas DataFrame into a DataDescriptor based on the column types and names.

Args:

df (DataFrame):

The pandas DataFrame of trajectory data to be described.

tid_col (str):

The name of the column used as the TID feature.

label_col (str):

The name of the column used as the label feature.

Returns:

DataDescriptor:

A descriptor that represents the structure of the DataFrame.

matmodel.descriptor.descriptor.readDescriptor(file_path)

Reads a descriptor file and returns a DataDescriptor instance.

Args:

file_path (str):

The path to the descriptor file.

Returns:

DataDescriptor:

The instantiated DataDescriptor object from the file.

Module contents