# -*- 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
# OTHER AUTHORS - MACROSCOPIC CHANGES
"""
Abstract dataset plot
=====================
The :mod:`~gemseo.post.dataset.dataset_plot` module implements the abstract
:class:`.DatasetPlot` class
whose purpose is to build a graphical representation
of a :class:`.Dataset` and to display it on screen or save it to a file.
This abstract class has to be overloaded by concrete ones implementing
at least method :meth:`!DatasetPlot._run`.
"""
from __future__ import absolute_import, division, unicode_literals
from numbers import Number
import matplotlib
import pylab
from future import standard_library
from six import string_types
standard_library.install_aliases()
[docs]class DatasetPlot(object):
""" Abstract plot class for dataset. """
def __init__(self, dataset):
"""Constructor.
:param Dataset dataset: dataset
"""
if dataset.is_empty():
raise ValueError("Dataset is empty.")
self.dataset = dataset
self.output_files = []
[docs] def execute(
self, save=True, show=False, file_path=None, extension="pdf", **plot_options
):
"""
Executes the post processing
:param show: if True, displays the plot windows. Default: False.
:type show: bool
:param save: if True, exports plot to pdf. Default: False.
:type save: bool
:param file_path: the base paths of the files to export. Default: None.
:type file_path: str
:param extension: file extension. Default: 'pdf'.
:type extension: str
:param plot_options: options passed to the _plot() method.
"""
self._run(save, show, file_path, extension, **plot_options)
def _run(self, save, show, file_path, extension, **plot_options):
"""Define run of the post processing, calling _plot() and saving
or displaying figure.
:param plot_options: options passed to the _plot() method.
:param show: if True, displays the plot windows. Default: False.
:type show: bool
:param save: if True, exports plot to pdf. Default: False.
:type save: bool
:param file_path: the base paths of the files to export. Default: None.
:type file_path: str
:param extension: file extension. Default: 'pdf'.
:type extension: str
:param plot_options: options passed to the _plot() method.
"""
fig = self._plot(**plot_options)
if isinstance(fig, list):
for index, subfig in enumerate(fig):
subfig.tight_layout()
filename = self.__class__.__name__ + str(index)
self._save_and_show(
subfig,
filename=filename,
save=save,
show=show,
file_path=file_path,
extension=extension,
)
else:
fig.tight_layout()
self._save_and_show(
fig,
filename=self.__class__.__name__,
save=save,
show=show,
file_path=file_path,
extension=extension,
)
def _plot(self, **options):
"""Define plot of the post processing,
to be implemented in subclasses
:param options: plotting options according to associated json file
"""
raise NotImplementedError
def _save_and_show(
self, fig, filename, save=True, show=False, file_path=None, extension="pdf"
):
"""
Saves figures and or shows it depending on options
:param fig: matplotlib figure
:param str filename: name of the file to save the plot
:param bool save: save the figure (default: True)
:param bool show: show the figure (default: False)
:param str file_path: file path to save the plot (default: None)
:param str extension: file extension (default: 'pdf')
"""
matplotlib.rcParams.update({"font.size": 10})
if save:
file_path = file_path or self.dataset.name
fpath = file_path + "_" + filename
fpath += "." + extension
fig.savefig(fpath, bbox_inches="tight")
if fpath not in self.output_files:
self.output_files.append(fpath)
if show:
try:
pylab.plt.show(fig)
except TypeError:
pylab.plt.show()
def _get_varnames(self, df_columns):
"""Get varnames from columns of a pandas dataframe.
:param list(tuple) dataframe: pandas dataframe
"""
new_columns = []
for column in df_columns:
if self.dataset.sizes[column[1]] == 1:
new_columns.append(column[1])
else:
new_columns.append(column[1] + "(" + str(column[2]) + ")")
return new_columns
def _get_label(self, varname):
"""Returns string label associated to a variable name,
as well as refactored variable name.
:param varname: variable name, either a string
or a (str, int) tuple.
"""
if isinstance(varname, string_types):
label = varname
varname = (self.dataset.get_group(varname), varname, "0")
elif hasattr(varname, "__len__") and len(varname) == 3:
is_string = isinstance(varname[0], string_types)
is_string = is_string and isinstance(varname[1], string_types)
is_number = isinstance(varname[2], Number)
if is_string and is_number:
label = varname[1] + "(" + str(varname[2]) + ")"
varname[2] = str(varname[2])
varname = tuple(varname)
else:
raise TypeError(
"varname must be either a string or a tuple"
" whose first component is a string and second"
" one is an integer."
)
else:
raise TypeError(
"varname must be either a string or a tuple"
" whose first component is a string and second"
" one is an integer."
)
return label, varname
