hist-unmix
Parametric unmixing of distorted magnetic hysteresis loops
Science Score: 67.0%
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Repository
Parametric unmixing of distorted magnetic hysteresis loops
Basic Info
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- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 3
Metadata Files
README.md
Hist-unmix
Hist-unmix is an open-sourced package, in Python language (ipynb-file), to separate susceptibility components of distorted hysteresis curves through a phenomenological model. The Hist-unmix package allows the user to adjust a forward model of up to three ferromagnetic components and a dia/paramagnetic contribution. Optimization of all of the parameters is achieved through least squares fit (Levenberg-Marquardt method) providing an uncertainty for the inverted parameters through a Monte Carlo error propagation. For each ferromagnetic component, it is possible to calculate magnetization saturation (Ms), magnetization saturation of remanence (Mrs), and the mean coercivity (Bc).
Here is a quick tutorial to install the required libraries to run Hist-unmix.
1. Firstly, download the zip file containing the Hist-unmix.ipyfile and the Hist-unmix_functions.py file.
2. Put these files together in a folder of your preference.
3. Hist-unmix is, essentially, an ipynb-file. So Jupyter Notebook is mandatory! Go ahead to https://www.anaconda.com/ and download and execute the ANACONDA graphical installer (depending on your operating system).
If you already have ANACONDA installed on your machine, skip this step.
4. Because Python libraries are constantly updated, the best way of guaranteeing that Hist-unmix is working is to use an envonrment.yml file as:
Create an env: Open the Anaconda prompt and type each of the lines below (one per time, pressing ENTER between each of those):
cd your/directory/where/the/code/files/are
conda env create -f environment.yml
5. Launching Jupyter Notebook:
Close the Anaconda prompt, reopen it and type (sequentially press ENTER):
conda activate Hist-unmix
jupyter notebook
6. After launching Jupyter Notebook, search for your folder and double-click on the Hist-unmix.ipyfile to open it.
7. The environment is set to run your models!
PS: Always make sure to have your csv-data file within the same folder where Hist-unmix is.
Owner
- Name: Ualisson Donardelli Bellon
- Login: bellon-donardelli
- Kind: user
- Location: São Paulo, Brazil
- Company: USPmag, University of São Paulo (BR)
- Repositories: 1
- Profile: https://github.com/bellon-donardelli
Geologist, with a Master's degree in Geophysics, and Ph.D. student in Geophysics (IAG-USP, BR). Interested in magnetic mineralogy and paleomagnetic sciences.
Citation (CITATION.cff)
Hist-unmix: 1.0.2
message: "If you use this software, please cite it as below."
authors:
- family-names: "Bellon"
given-names: "Ualisson Donardelli"
orcid: "https://orcid.org/0000-0002-4599-6548"
- family-names: "Trindade"
given-names: "Ricardo Ivan Ferreira"
orcid: "https://orcid.org/0000-0001-9848-9550"
- family-names: "Williams"
given-names: "Wyn"
orcid: "https://orcid.org/0000-0001-9210-7574"
title: "bellon-donardelli/Hist-unmix: Hist-unmin_v1.0.0"
version: 1.0
date-released: 2023-05-15
doi: https://doi.org/10.5281/zenodo.7941088
publication: 10.1029/2023GC011048
url: "https://github.com/bellon-donardelli/Hist-unmix.git"
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Dependencies
- ipython ==8.12.0
- ipywidgets ==8.0.4
- jupyterlab ==3.6.3
- matplotlib ==3.8.0
- numpy ==1.24.3
- pandas ==1.5.3
- plotly ==5.9.0
- python ==3.11.3
- scipy ==1.10.1
- seaborn ==0.12.2