magentropy 0.1.1

Perform magnetoentropic mapping of magnetic materials based on DC magnetization data.

MagentroPy

Please cite the following in any published work that makes use of this package:

> [1] J. D. Bocarsly et al.,
> [Phys. Rev. B 97, 100404(R) (2018)](https://doi.org/10.1103/PhysRevB.97.100404)
>
> [2] J. J. Stickel,
> [Comput. Chem. Eng. 34, 467 (2010)](https://dx.doi.org/10.1016/j.compchemeng.2009.10.007)

The first version of the `magentropy` code was included as supplementary
material in [1]. The Tikhonov regularization procedure was described
in [2] and was originally implemented by Stickel in the package
[scikit.datasmooth](https://github.com/jjstickel/scikit-datasmooth).

Overview

MagentroPy provides a class, MagentroData, that can be used to calculate magnetocaloric quantities from DC magnetization data supplied as magnetic moment vs. temperature sweeps (monotonic) taken under several different magnetic fields. The class is set up to work out-of-the-box with .dat data files produced by a Quantum Design Vibrating Sample Magnetometer or a Quantum Design MPMS3 SQUID Magnetometer. However, pandas.DataFrames or delimited files such as .csv are also acceptable inputs.

View the documentation

Installation

Install MagentroPy with pip:

pip install magentropy

Or, with conda:

conda install -c conda-forge magentropy

License

This project is licensed under the MIT License.