Source code for

# -*- coding: utf-8 -*-
# Copyright 2021 IRT Saint Exupéry,
# 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
# 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: Francois Gallard
"""A factory to create or execute a post-processor from its class name."""
from __future__ import division, unicode_literals

import logging
from typing import Dict, List, Optional, Set, Union

from matplotlib.figure import Figure

from gemseo.algos.opt_problem import OptimizationProblem
from gemseo.core.factory import Factory
from import OptPostProcessor, OptPostProcessorOptionType
from gemseo.utils.py23_compat import Path, string_types

LOGGER = logging.getLogger(__name__)

[docs]class PostFactory(object): """Post-processing factory to run optimization post-processors. List the available post-processors on the current configuration and execute them on demand. Work both from memory, from a ran optimization problem, and from disk, from a serialized optimization problem. """ def __init__(self): self.factory = Factory(OptPostProcessor, ("",)) self.executed_post = [] @property def posts(self): # type: (...) -> List[str] """The available post processors.""" return self.factory.classes
[docs] def is_available( self, name, # type: str ): # type: (...) -> bool """Check the availability of a post-processor. Args: name: The name of the post-processor. Returns: Whether the post-processor is available. """ return self.factory.is_available(name)
[docs] def create( self, opt_problem, # type: OptimizationProblem post_name, # type: str ): # type: (...) -> OptPostProcessor """Create a post-processor from its class name. Args: opt_problem: The optimization problem to be post-processed. post_name: The name of the post-processor. """ return self.factory.create(post_name, opt_problem=opt_problem)
[docs] def execute( self, opt_problem, # type: Union[str,OptimizationProblem] post_name, # type: str save=True, # type: bool show=False, # type: bool file_path=None, # type: Optional[Union[str,Path]] directory_path=None, # type: Optional[Union[str,Path]] file_name=None, # type: Optional[str] file_extension=None, # type: Optional[str] **options # type: OptPostProcessorOptionType ): # type: (...) -> Dict[str,Figure] """Post-process an optimization problem. Args: opt_problem: The optimization problem to be post-processed. post_name: The name of the post-processor. save: If True, save the figure. show: If True, display the figure. file_path: The path of the file to save the figures. If the extension is missing, use ``file_extension``. If None, create a file path from ``directory_path``, ``file_name`` and ``file_extension``. directory_path: The path of the directory to save the figures. If None, use the current working directory. file_name: The name of the file to save the figures. If None, use a default one generated by the post-processing. file_extension: A file extension, e.g. 'png', 'pdf', 'svg', ... If None, use a default file extension. **options: The options of the post-processor. """ if isinstance(opt_problem, string_types): opt_problem = OptimizationProblem.import_hdf(opt_problem) post = self.create(opt_problem, post_name) post.execute( save=save, show=show, file_path=file_path, file_name=file_name, file_extension=file_extension, directory_path=directory_path, **options ) self.executed_post.append(post) return post
[docs] def list_generated_plots(self): # type:(...) -> Set[str] """The generated plot files.""" plots = [] for post in self.executed_post: plots.extend(post.output_files) return set(plots)