# -*- 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
# :author: Syver Doving Agdestein
# OTHER AUTHORS - MACROSCOPIC CHANGES
"""
Machine learning API
--------------------
The machine learning API provides methods for creating new and loading
existing machine learning models. It also provides methods for listing
available models and options.
"""
from __future__ import absolute_import, division, unicode_literals
from future import standard_library
from gemseo.api import _get_schema
standard_library.install_aliases()
# pylint: disable=import-outside-toplevel
[docs]def get_mlearning_models():
"""Get available machine learning algorithms.
See also
--------
import_mlearning_model
create_mlearning_model
get_mlearning_options
import_mlearning_model
"""
from gemseo.mlearning.core.factory import MLAlgoFactory
factory = MLAlgoFactory()
return factory.models
[docs]def get_regression_models():
"""Get available regression models.
See also
--------
create_regression_model
get_regression_options
import_regression_model
"""
from gemseo.mlearning.regression.factory import RegressionModelFactory
factory = RegressionModelFactory()
return factory.models
[docs]def get_classification_models():
"""Get available classification models.
See also
--------
create_classification_model
get_classification_options
import_classification_model
"""
from gemseo.mlearning.classification.factory import ClassificationModelFactory
factory = ClassificationModelFactory()
return factory.models
[docs]def get_clustering_models():
"""Get available clustering models.
See also
--------
create_clustering_model
get_clustering_options
import_clustering_model
"""
from gemseo.mlearning.cluster.factory import ClusteringModelFactory
factory = ClusteringModelFactory()
return factory.models
[docs]def create_mlearning_model(name, data, transformer=None, **parameters):
"""Create machine learning algorithm from a learning data set.
:param str name: name of the machine learning algorithm.
:param Dataset data: learning data set.
:param dict(str) transformer: transformation strategy for data groups.
If None, do not transform data. Default: None.
:param parameters: machine learning algorithm parameters.
See also
--------
get_mlearning_models
get_mlearning_options
import_mlearning_model
"""
from gemseo.mlearning.core.factory import MLAlgoFactory
factory = MLAlgoFactory()
return factory.create(name, data=data, transformer=transformer, **parameters)
[docs]def create_regression_model(name, data, transformer=None, **parameters):
"""Create a regression model from a learning data set.
:param str name: name of the regression model.
:param Dataset data: learning data set.
:param dict(str) transformer: transformation strategy for data groups.
If None, do not transform data. Default: None.
:param parameters: regression model parameters.
See also
--------
get_regression_models
get_regression_options
import_regression_model
"""
from gemseo.mlearning.regression.factory import RegressionModelFactory
factory = RegressionModelFactory()
return factory.create(name, data=data, transformer=transformer, **parameters)
[docs]def create_classification_model(name, data, transformer=None, **parameters):
"""Create a classification model from a learning data set.
:param str name: name of the classification model.
:param Dataset data: learning data set.
:param dict(str) transformer: transformation strategy for data groups.
If None, do not transform data. Default: None.
:param parameters: classification model parameters.
See also
--------
get_classification_models
get_classification_options
import_classification_model
"""
from gemseo.mlearning.classification.factory import ClassificationModelFactory
factory = ClassificationModelFactory()
return factory.create(name, data=data, transformer=transformer, **parameters)
[docs]def create_clustering_model(name, data, transformer=None, **parameters):
"""Create a clustering model from a learning data set.
:param str name: name of the clustering model.
:param Dataset data: learning data set.
:param dict(str) transformer: transformation strategy for data groups.
If None, do not transform data. Default: None.
:param parameters: clustering model parameters.
See also
--------
get_clustering_models
get_clustering_options
import_clustering_model
"""
from gemseo.mlearning.cluster.factory import ClusteringModelFactory
factory = ClusteringModelFactory()
return factory.create(name, data=data, transformer=transformer, **parameters)
[docs]def import_mlearning_model(directory):
"""Import a machine learning algorithm from a directory.
:param str directory: directory name.
See also
--------
create_mlearning_model
get_mlearning_models
get_mlearning_options
"""
from gemseo.mlearning.core.factory import MLAlgoFactory
factory = MLAlgoFactory()
return factory.load(directory)
[docs]def import_regression_model(directory):
"""Import a regression model from a directory.
:param str directory: directory name.
See also
--------
create_regression_model
get_regression_models
get_regression_options
"""
from gemseo.mlearning.regression.factory import RegressionModelFactory
factory = RegressionModelFactory()
return factory.load(directory)
[docs]def import_classification_model(directory):
"""Import a classification model from a directory.
:param str directory: directory name.
See also
--------
create_classification_model
get_classification_models
get_classification_options
"""
from gemseo.mlearning.classification.factory import ClassificationModelFactory
factory = ClassificationModelFactory()
return factory.load(directory)
[docs]def import_clustering_model(directory):
"""Import a clustering model from a directory.
:param str directory: directory name.
See also
--------
create_clustering_model
get_clustering_models
get_clustering_options
"""
from gemseo.mlearning.cluster.factory import ClusteringModelFactory
factory = ClusteringModelFactory()
return factory.load(directory)
[docs]def get_mlearning_options(model_name, output_json=False, pretty_print=True):
"""
Lists the available options for a machine learning algorithm.
:param str model_name: Name of the machine learning algorithm.
:param bool output_json: Apply json format for the schema.
:param bool pretty_print: Print the schema in a pretty table.
:returns: Option schema (string) of the machine learning algorithm.
See also
--------
create_mlearning_model
get_mlearning_models
import_mlearning_model
"""
from gemseo.mlearning.core.factory import MLAlgoFactory
factory = MLAlgoFactory().factory
grammar = factory.get_options_grammar(model_name)
return _get_schema(grammar, output_json, pretty_print)
[docs]def get_regression_options(model_name, output_json=False, pretty_print=True):
"""
Lists the available options for a regression model.
:param str model_name: Name of the regression model.
:param bool output_json: Apply json format for the schema.
:param bool pretty_print: Print the schema in a pretty table.
:returns: Option schema (string) of the regression model.
See also
--------
create_regression_model
get_regression_models
import_regression_model
"""
from gemseo.mlearning.regression.factory import RegressionModelFactory
factory = RegressionModelFactory().factory
grammar = factory.get_options_grammar(model_name)
return _get_schema(grammar, output_json, pretty_print)
[docs]def get_classification_options(model_name, output_json=False, pretty_print=True):
"""
Lists the available options for a classification model.
:param str model_name: Name of the classification model.
:param bool output_json: Apply json format for the schema.
:param bool pretty_print: Print the schema in a pretty table.
:returns: Option schema (string) of the classification model.
See also
--------
create_classification_model
get_classification_models
import_classification_model
"""
from gemseo.mlearning.classification.factory import ClassificationModelFactory
factory = ClassificationModelFactory().factory
grammar = factory.get_options_grammar(model_name)
return _get_schema(grammar, output_json, pretty_print)
[docs]def get_clustering_options(model_name, output_json=False, pretty_print=True):
"""
Lists the available options for clustering model.
:param str model_name: Name of the clustering model.
:param bool output_json: Apply json format for the schema.
:param bool pretty_print: Print the schema in a pretty table.
:returns: Option schema (string) of the clustering model.
See also
--------
create_clustering_model
get_clustering_models
import_clustering_model
"""
from gemseo.mlearning.cluster.factory import ClusteringModelFactory
factory = ClusteringModelFactory().factory
grammar = factory.get_options_grammar(model_name)
return _get_schema(grammar, output_json, pretty_print)
