arithmeticmeancurve 0.2a4.dev1

Module for calculating an arithmetic mean curve from a family of curves.

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

Alpha Development Status

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

• naming of modules, classes and methods will change, since the final wording is not done.
• Code inspections are not finished.
• The documentation is broad or incomplete.
• Testing is not complete, as it is added during the first test phase. At this state mostly doctests are applied at class or function level.

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