Pymaginverse: A python package for global geomagnetic field modeling
Data-based geomagnetic models are key for mapping the global field, predicting the movement of magnetic poles, understanding the complex processes happening in the outer core, and describing the global expression of magnetic field reversals. There exists a wide range of models, which differ in a pri...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Applied Computing and Geosciences |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590197425000047 |
| _version_ | 1826852884693647360 |
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| author | Frenk Out Maximilian Schanner Liz van Grinsven Monika Korte Lennart V. de Groot |
| author_facet | Frenk Out Maximilian Schanner Liz van Grinsven Monika Korte Lennart V. de Groot |
| author_sort | Frenk Out |
| collection | DOAJ |
| description | Data-based geomagnetic models are key for mapping the global field, predicting the movement of magnetic poles, understanding the complex processes happening in the outer core, and describing the global expression of magnetic field reversals. There exists a wide range of models, which differ in a priori assumptions and methods for spatio-temporal interpolation. A frequently used modeling procedure is based on regularized least squares (RLS) spherical harmonic analysis, which has been used since the 1980s. The first version of this algorithm has been written in Fortran and inspired many different research groups to produce versions of the algorithm in other programming languages, either published open-access or only accessible within the institute. To open up the research field and allow for reproducibility of results between existing versions, we provide a user-friendly open-source Python version of this popular algorithm. We complement this method with an overview on background literature – concerning Maxwells equations, spherical harmonics, cubic B-Splines, and regularization – that forms the basis for RLS geomagnetic models. We included six spatial and two temporal damping methods from literature to further smooth the magnetic field in space and time. Computational resources are kept to a minimum by employing the banded structure of the normal equations involved and incorporating C-code (with Cython) for matrix formation, enabling a massive speed-up. This ensures that the algorithm can be executed on a simple laptop, and is as fast as its Fortran predecessor. Four tutorials with ample examples show how to employ the new lightweight and quick algorithm. With this properly documented open-source Python algorithm, we have the intention to encourage current and new users to employ and further develop the method. |
| first_indexed | 2025-02-16T17:15:24Z |
| format | Article |
| id | doaj.art-4873efc9d24b46508733abba8930a44b |
| institution | Directory Open Access Journal |
| issn | 2590-1974 |
| language | English |
| last_indexed | 2025-02-16T17:15:24Z |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Applied Computing and Geosciences |
| spelling | doaj.art-4873efc9d24b46508733abba8930a44b2025-01-28T04:14:52ZengElsevierApplied Computing and Geosciences2590-19742025-02-0125100222Pymaginverse: A python package for global geomagnetic field modelingFrenk Out0Maximilian Schanner1Liz van Grinsven2Monika Korte3Lennart V. de Groot4Paleomagnetic laboratory Fort Hoofddijk, Department of Earth Sciences, Utrecht University, Budapestlaan 17, 3584 CD Utrecht, The Netherlands; Corresponding author.Institute of applied mathematics, Potsdam University, Karl-Liebknecht-Str. 24-25, D-14476 Potsdam, Germany; Helmholtz Centre Potsdam, Deutsches GeoForschungsZentrum GFZ, Telegrafenberg, D-14473 Potsdam, GermanyPaleomagnetic laboratory Fort Hoofddijk, Department of Earth Sciences, Utrecht University, Budapestlaan 17, 3584 CD Utrecht, The NetherlandsHelmholtz Centre Potsdam, Deutsches GeoForschungsZentrum GFZ, Telegrafenberg, D-14473 Potsdam, GermanyPaleomagnetic laboratory Fort Hoofddijk, Department of Earth Sciences, Utrecht University, Budapestlaan 17, 3584 CD Utrecht, The NetherlandsData-based geomagnetic models are key for mapping the global field, predicting the movement of magnetic poles, understanding the complex processes happening in the outer core, and describing the global expression of magnetic field reversals. There exists a wide range of models, which differ in a priori assumptions and methods for spatio-temporal interpolation. A frequently used modeling procedure is based on regularized least squares (RLS) spherical harmonic analysis, which has been used since the 1980s. The first version of this algorithm has been written in Fortran and inspired many different research groups to produce versions of the algorithm in other programming languages, either published open-access or only accessible within the institute. To open up the research field and allow for reproducibility of results between existing versions, we provide a user-friendly open-source Python version of this popular algorithm. We complement this method with an overview on background literature – concerning Maxwells equations, spherical harmonics, cubic B-Splines, and regularization – that forms the basis for RLS geomagnetic models. We included six spatial and two temporal damping methods from literature to further smooth the magnetic field in space and time. Computational resources are kept to a minimum by employing the banded structure of the normal equations involved and incorporating C-code (with Cython) for matrix formation, enabling a massive speed-up. This ensures that the algorithm can be executed on a simple laptop, and is as fast as its Fortran predecessor. Four tutorials with ample examples show how to employ the new lightweight and quick algorithm. With this properly documented open-source Python algorithm, we have the intention to encourage current and new users to employ and further develop the method.http://www.sciencedirect.com/science/article/pii/S2590197425000047RLS geomagnetic modelsGeomagiaPaleomagnetismOpen research |
| spellingShingle | Frenk Out Maximilian Schanner Liz van Grinsven Monika Korte Lennart V. de Groot Pymaginverse: A python package for global geomagnetic field modeling Applied Computing and Geosciences RLS geomagnetic models Geomagia Paleomagnetism Open research |
| title | Pymaginverse: A python package for global geomagnetic field modeling |
| title_full | Pymaginverse: A python package for global geomagnetic field modeling |
| title_fullStr | Pymaginverse: A python package for global geomagnetic field modeling |
| title_full_unstemmed | Pymaginverse: A python package for global geomagnetic field modeling |
| title_short | Pymaginverse: A python package for global geomagnetic field modeling |
| title_sort | pymaginverse a python package for global geomagnetic field modeling |
| topic | RLS geomagnetic models Geomagia Paleomagnetism Open research |
| url | http://www.sciencedirect.com/science/article/pii/S2590197425000047 |
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