Source code for gemseo.mlearning.core.factory
# -*- coding: utf-8 -*-
# Copyright 2021 IRT Saint Exupéry, https://www.irt-saintexupery.com
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License version 3 as published by the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
# Contributors:
# INITIAL AUTHORS - initial API and implementation and/or initial
# documentation
# :author: Matthias De Lozzo, Syver Doving Agdestein
# OTHER AUTHORS - MACROSCOPIC CHANGES
"""
Machine learning algorithm factory
==================================
This module contains a factory to instantiate a :class:`.MLAlgo` from its class
name. The class can be internal to |g| or located in an external module whose
path is provided to the constructor. It also provides a list of available
machine learning algorithm types and allows you to test if a machine learning
algorithm type is available.
"""
from __future__ import absolute_import, division, unicode_literals
import pickle
from os.path import join
from future import standard_library
from gemseo.core.factory import Factory
from gemseo.mlearning.core.ml_algo import MLAlgo
standard_library.install_aliases()
from gemseo import LOGGER
[docs]class MLAlgoFactory(object):
"""This factory instantiates a :class:`.MLAlgo`
from its class name. The class can be internal to |g| or located in an
external module whose path is provided to the constructor.
"""
def __init__(self):
"""Initializes the factory: scans the directories to search for
subclasses of MLAlgo. Searches in "GEMSEO_PATH" and gemseo.mlearning.
"""
self.factory = Factory(MLAlgo, ("gemseo.mlearning",))
[docs] def create(self, ml_algo, **options):
"""Create machine learning algorithm.
:param str ml_algo: name of the machine learning algorithm (its
classname).
:param options: machine learning algorithm options.
:return: MLAlgo
"""
return self.factory.create(ml_algo, **options)
@property
def models(self):
"""Lists the available classes.
:returns: list of class names.
:rtype: list(str)
"""
return self.factory.classes
[docs] def is_available(self, ml_algo):
"""Checks the availability of a cache.
:param str ml_algo: name of the machine learning algorithm (its class
name).
:returns: True if the machine learning algorithm is available.
:rtype: bool
"""
return self.factory.is_available(ml_algo)
[docs] def load(self, directory):
"""Load a machine learning algorithm from the disk.
:param str directory: directory name.
"""
with open(join(str(directory), MLAlgo.FILENAME), "rb") as handle:
objects = pickle.load(handle)
model = self.factory.create(
objects.pop("algo_name"),
data=objects.pop("data"),
**objects.pop("parameters")
)
for key, value in objects.items():
setattr(model, key, value)
model.load_algo(directory)
return model