"""Well-formatted presentation of the results of fitting models to datasets.
Fitting itself is a quite complicated process, and it is crucial for routine
use to have the results presented in automatically generated reports that
are well-formatted presentations of the results of fitting a model to a
dataset. Key to a useful report is a uniform formatting with the same
information always on the same place, allowing for easily comparing
different fits.
"""
import copy
import os.path
import aspecd.plotting
import aspecd.report
import fitpy.analysis
import fitpy.plotting
[docs]class LaTeXFitReporter(aspecd.report.LaTeXReporter):
"""LaTeX Reporter for fit results.
In addition to the functionality provided by its superclass,
this reporter automatically creates an overview figure based on the
dataset it gets supplied. The figure is saved using a generic name
derived from the filename of the rendered report.
Examples
--------
For convenience, a series of examples in recipe style (for details of
the recipe-driven data analysis, see :mod:`aspecd.tasks`) is given below
for how to make use of this class. The examples focus each on a single
aspect.
.. note::
Usually, you will have set another ASpecD-derived package as
default package in your recipe for processing and analysing your data.
Hence, you need to provide the package name (fitpy) in the ``kind``
property, as shown in the examples.
In its simplest form, you just define a template and a filename for the
resulting report.
.. code-block:: yaml
- kind: fitpy.report
type: LaTeXFitReporter
properties:
template: simplefit.tex
filename: test_report.tex
compile: true
Here, we make use of the ``simplefit.tex`` template. The results will be
stored in ``test_report.tex`` and the LaTeX file will be compiled into a
PDF document automatically (setting ``compile`` to true).
"""
def __init__(self):
super().__init__()
self.package = "fitpy"
self.dataset = None
def _render(self):
if self.dataset and self.filename:
self._create_figure()
super()._render()
def _create_figure(self):
dataset = copy.deepcopy(self.dataset)
plotter = fitpy.plotting.SinglePlotter1D()
plotter.parameters["tight_layout"] = True
plotter.parameters["tight"] = "x"
plotter.parameters["show_legend"] = True
basename, _ = os.path.splitext(self.filename)
figure_filename = "".join([basename, "-fig", ".pdf"])
saver = aspecd.plotting.Saver()
saver.filename = figure_filename
plot = dataset.plot(plotter)
plot.save(saver)
self.context["figure_filename"] = figure_filename
self.includes.append(figure_filename)
[docs]class LaTeXLHSFitReporter(LaTeXFitReporter):
"""LaTeX Reporter for fit results using LHS.
In addition to the functionality provided by its superclass,
this reporter automatically extracts the statistics from the dataset
supplied and creates a figure showing the robustness of the LHS approach.
The figure is saved using a generic name derived from the filename of
the rendered report.
Examples
--------
For convenience, a series of examples in recipe style (for details of
the recipe-driven data analysis, see :mod:`aspecd.tasks`) is given below
for how to make use of this class. The examples focus each on a single
aspect.
.. note::
Usually, you will have set another ASpecD-derived package as
default package in your recipe for processing and analysing your data.
Hence, you need to provide the package name (fitpy) in the ``kind``
property, as shown in the examples.
In its simplest form, you just define a template and a filename for the
resulting report.
.. code-block:: yaml
- kind: fitpy.report
type: LaTeXLHSFitReporter
properties:
template: lhsfit.tex
filename: test_report.tex
compile: true
Here, we make use of the ``lhsfit.tex`` template. The results will be
stored in ``test_report.tex`` and the LaTeX file will be compiled into a
PDF document automatically (setting ``compile`` to true).
"""
def _create_figure(self):
super()._create_figure()
dataset = copy.deepcopy(self.dataset)
analysis = fitpy.analysis.ExtractLHSStatistics()
analysis = dataset.analyse(analysis)
plotter = aspecd.plotting.SinglePlotter1D()
plotter.parameters["tight_layout"] = True
plotter.properties.drawing.linestyle = ""
plotter.properties.drawing.marker = "o"
basename, _ = os.path.splitext(self.filename)
figure_filename = "".join([basename, "-lhsfig", ".pdf"])
saver = aspecd.plotting.Saver()
saver.filename = figure_filename
plot = analysis.result.plot(plotter)
plot.save(saver)
self.context["lhs_figure_filename"] = figure_filename
self.includes.append(figure_filename)