arithmeticmeancurve

Calculates arithmetic mean curves for a sample of curves. Speciality of this module is the extrapolation of the sample curves by the algorithm described in "David Scheliga: Experimentelle Untersuchung des Rissausbreitungsverhaltens von nanopartikelverstärktem Polyamid 6. 2013"

Installation

    $ pip install arithmeticmeancurve

If available the latest development state can be installed from gitlab.

    $ pip install git+https://gitlab.com/david.scheliga/arithmeticmeancurve.git@dev

Beta Development Status

The current development state of this project is beta. Towards the stable release

• naming of modules, classes and methods may change.
• Code inspections are not finished.
• Testing is not complete, as it is added during the first test phase.

Basic Usage

Read-the-docs for a more detailed documentation.

A curve within armithmeticmeancurves is defined by a pandas.DataFrame. Curves for arithmetic mean curve calculation needs to provide equal column names.

# Creation of 3 random curves
# ===========================

import numpy as np
from pandas import DataFrame, Index
from scipy.interpolate import CubicSpline

cubic_spline = CubicSpline(x=[0.0, 0.2, 0.8, 1.0], y=[0.0, 0.3, 0.9, 1.0])
x_values = np.linspace(0.0, 1, num=11)
curvature = cubic_spline(x_values)
base_curve = np.stack((x_values, curvature), axis=1)

three_seeds = np.random.standard_normal(6).reshape(3, 2)
three_random_points = np.array([1.0, 10.0]) + np.array([0.09, 1]) * three_seeds

curves = []
for random_point in three_random_points:
    raw_curve = base_curve * random_point
    sample_curve = DataFrame(
        raw_curve[:, 1], columns=["sample"], index=Index(raw_curve[:, 0], name="x")
    )
    curves.append(sample_curve)

# The mean curve calculation
# ==========================

from arithmeticmeancurve import ArithmeticMeanCurve
a_mean_curve = ArithmeticMeanCurve(curves=curves)


# Plotting
# ========

import matplotlib.pyplot as plt

plt.plot(a_mean_curve.mean_curve, "-ko", label="arithmetic mean curve")
for label, curve in a_mean_curve.family_of_curves.iteritems():
    plt.plot(curve, "-", label="label")
plt.plot(a_mean_curve.scatter_curve, "--k", label="scatter curve")
plt.plot(a_mean_curve.std_circle, "--r", label="std circle")
plt.legend()
plt.show()

Contribution

Any contribution by reporting a bug or desired changes are welcomed. The preferred way is to create an issue on the gitlab's project page, to keep track of everything regarding this project.

Contribution of Source Code

Code style

This project follows the recommendations of PEP8. The project is using black as the code formatter.

Workflow

1. Fork the project on Gitlab.
2. Commit changes to your own branch.
3. Submit a pull request from your fork's branch to our branch 'dev'.

Authors

• David Scheliga @gitlab @Linkedin
  • Initial work
  • Maintainer

License

This project is licensed under the GNU GENERAL PUBLIC LICENSE - see the LICENSE file for details

Acknowledge

Code style: black

Changelog

This changelog is inspired by Keep a Changelog.

[0.3.2b1] - 2021-03-12

Fixed

• Missing test plots within the documentation on read-the-docs.

[0.3.1b1] - 2021-03-12

Fixed

• Incorrect default keyword settings leading to missing plots within the documentation.

Added

• Reasoable default excludes to .coveragerc
• Covered parts of the MeanCurvePlotter

[0.3.0b1] - 2021-03-11

Added

• setup.cfg, .coveragerc, tox.ini, .travis.yml
• new test-file test_mean_curve_calculation.py
• Added new tests

Changed

• Development status from alpha to beta
• README.md
• Code maintenance in arithmeticmeancurve.py
• Updated requirements.txt
• Changed setuptools layout from setup.py to setup.cfg
• Changed plain text GPLv3 to markdown version
• Maintained existing tests

Removed

• dependency from dicthandling

[0.2a9] - 2021-01-13

Fixed

• Fixed doctests.

Added

• Text and additional plots to the chapter A look inside the extrapolation within the documentation.

Changed

• Executing python -m arithmeticmeancurve triggers a doctest.

[0.2a8] - 2021-01-12

Fixed

• Fixed of rare occurrence of mean curve being not cut correctly at the target arithmetic ending value.

Added

• Possibility to set a predefined Extrapolates-Object as the extrapolation method within an ArithmeticMeanCurve.

[0.2a7] - 2021-01-08

Fixed

• Fixed rare occurrence of searched y-value leading to exception.

Removed

• outsourced function to meld_along_columns of trashpanda

[0.2a6] - 2021-01-07

Fixed

• Package dependencies for pip installation.
• Duplicated indexes within curves lead to an exception raised by pandas. Now only first duplicates are kept.

[0.2a5] - 2021-01-05

Fixed

• Bug within documentation due to usage of removed version attribute.

Added

• Section within documentation showing results of test cases.
• Abstract class Extrapolates defining an extrapolation interface for testing.
• MeanCurvePlotter providing 3 plotting methods related to mean curves.
• ExtrapolationIterationTester to achieve deeper insight into iterations in combination with doctests.
• Arithmetic end point into default plot.

Changed

• Reworked the arithmetic mean curve calculation.
• Enable testing within a deeper level of the curve extrapolation.
• ArithmeticMeanCurve forwards the extrapolation behavior.
• FamilyOfCurveStatistics.repr prints a table of mean and standard deviation values.

Fixed

• Bug in _find_positions_in_between which lead to wrong positions in case of examplecurves.Static.create("VerticalLinear1").

Removed

• Removed deprecated functions _all_ndarrays_have_equal_column_count, _all_dataframes_have_equal_column_count, _ndarray_has_monotonic_increasing_x, _dataframe_has_monotonic_increasing_x, _dataframes_are_valid_for_calculation, _ndarrays_are_valid_for_calculation, _input_curves_are_valid_for_calculation
• Removed deprecated methods FamilyOfCurveStatistics.extract_end_points_from_family

[0.1a1] - 2020-12-17

Fixed

• Bug resulting in missing mean curve values, if the mean value of the ending abscissa values (x-values) was less then the end cap or end section.

Changed

• Versioning via setuptools purely by git tags.
• examplecurves>=0.2a1 are required.

[0.1a0] - 2020-12-06

Added

• Class VisualIterationTester for calculating and plotting the iterations during the extrapolation process of the mean curve calculation.

Changed

• Outsourced examplecurves into an individual module at http://gitlab.com/david.scheliga/examplecurves
• Fixed documentation in regard of the outsourced examplecurves module

Removed

• Unintentional private method in arithmeticmeancurves.__all__
• Module examplecurves from setup.py.

[0.0a1.post3] - 2020-12-03

Added

• Basic usage to README.md and the sphinx documentation

Fixed

• Minor wrong definitions within README.md
• Wrong compilation of basic_usage.rst at readthedocs.org

[0.0a1] - 2020-12-02

• First code release of arithmeticmeancurve

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Later license versions may give you additional or different permissions. However, no additional obligations are imposed on any author or copyright holder as a result of your choosing to follow a later version.

15. Disclaimer of Warranty.

THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.

16. Limitation of Liability.

IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

17. Interpretation of Sections 15 and 16.

If the disclaimer of warranty and limitation of liability provided above cannot be given local legal effect according to their terms, reviewing courts shall apply local law that most closely approximates an absolute waiver of all civil liability in connection with the Program, unless a warranty or assumption of liability accompanies a copy of the Program in return for a fee.

END OF TERMS AND CONDITIONS

How to Apply These Terms to Your New Programs

If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.

To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found.

    Copyright (C)   

    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.

    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 General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with this program.  If not, see .

Also add information on how to contact you by electronic and paper mail.

If the program does terminal interaction, make it output a short notice like this when it starts in an interactive mode:

      Copyright (C)   
    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
    This is free software, and you are welcome to redistribute it
    under certain conditions; type `show c' for details.

The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License. Of course, your program's commands might be different; for a GUI interface, you would use an "about box".

You should also get your employer (if you work as a programmer) or school, if any, to sign a "copyright disclaimer" for the program, if necessary. For more information on this, and how to apply and follow the GNU GPL, see .

The GNU General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Lesser General Public License instead of this License. But first, please read .