MagentroPy

References

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)

[2] J. J. Stickel, Comput. Chem. Eng. 34, 467 (2010)

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.

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.

During data processing, the magnetic moment is differentiated with respect to temperature and integrated with respect to the magnetic field to calculate the entropy. Smoothing is performed on the magnetization data using Tikhonov regularization in order to reduce noise in the derivative. See [1] and [2] for additional information.

Plotting methods are provided for creating line plots and heat maps. These methods can be used with matplotlib for flexible and extensive plotting functionality.

An experimental bootstrap() method is implemented to estimate the error in the smoothed moment.

See the Quickstart for installation, logging, and usage.

Just-in-time compilation

Certain methods, such as process_data(), are accelerated using numba’s just-in-time (JIT) compilation. JIT functions will have a noticeable compilation overhead the first time they are run; however, the results are cached on disk, so all subsequent runs will be faster.

If desired, JIT compilation can be disabled globally as follows:

from numba import config

config.DISABLE_JIT = True

Contents

• Quickstart
  • Installation
  • Logging
  • The MagentroData class
  • Reading data
  • Processing data
  • Plotting Data
  • Writing output
• Examples
  • Reading Data
  • Processing Data
  • Plotting Data
  • Units and Conversions
  • Bootstrap Estimates
• API Reference
  • MagentroData
  • Errors
  • Typing
• License
• Index

License

This project is licensed under the MIT License.