Library for the numerical inversion of a scan grid detecting the magnetic signal from magnetic sources using a multipole expansion of the magnetic potential of the sources. The mathematical background of this method and its application to experimental data of a synthetic sample is developed in
D. Cortés-Ortuño, K. Fabian, L. V. de Groot Single Particle Multipole Expansions From Micromagnetic Tomography Geochemistry, Geophysics, Geosystems 22(4), e2021GC009663 (2021) DOI: https://doi.org/10.1029/2021GC009663
This library is developed as part of the Mimatom / MMT project.
This library has two main modules
-
multipole_inversion/magnetic_sample.py
: contains theMagneticSample
class to create a magnetic system with magnetic point sources (dipole or higher order multipole sources) and generate the scan signal. This class also has methods to save the scan signal data innpz
format and the scan grid specifications injson
format. -
multipole_inversion/multipole_inversion.py
: contains theMultipoleInversion
class to perform a numerical inversion from a scan signal data. This class requires scan surface specifications, particle (point source) locations and the scan signal data. These can be passed from theMagneticSample
output or be specified manually (useful for combining with other workflows such as micromagnetic simulations).
An additional module to plot results from the inversions is provided in
multipole_inversion/plot_tools.py
. Magnetic susceptibility and magnetic field
functions can be found in the main library as well, although not all of them
are documented in the tutorial yet.
Via PyPI
pip install mmt-multipole-inversion
or from this repository using pip .
or poetry install
or poetry build
(which can be used with pip
). Poetry is recommended for development.
See the documentation for more details.
This library contains an optional Nvidia CUDA library to populate the forward
matrix in the multipole_inversion
code. To build this library you need to set
the CUDAHOME
or CUDA_PATH
environment variables to the location of CUDA in
your system. Alternatively, the nvcc
compiler path can be set in the PATH
variable. This is only necessary to install or build the library using
poetry install
or poetry build
.
The compilation of the CUDA extension is currently setup for a Turing card
with computing capability 7.5. If using an older or newer card, you can
modify the -arch=sm_XX
option in the build_extension.py
script. Links to
check Nvidia cards architectures and capabilities are commented in this file.
Additionally, if nvcc
complains about the gcc
compiler version, you can
set a specific gcc
using the -ccbin=
flag (see the build script).
For now you can visualize the Jupyter notebooks from the jupytext
scripts in
the doc/tutorial/
folder. These notebooks can also be generated from their
associated jupytext
script, for example,
jupytext --to notebook multipoles_inversion_test.py
The documentation of the classes can be generated using sphinx
and the
scripts to do this are located in the doc
folder. Future releases of this
library will include an online documentation of this code.
If you find this library useful please cite us (you might need LaTeX's
url
package)
@Misc{Cortes2022,
author = {Cortés-Ortuño, David and Fabian, Karl and de Groot, Lennart V.},
title = {{MMT Numerical Libraries: Multipole Inversion}},
publisher = {Zenodo},
note = {Github: \url{https://github.com/Micromagnetic-Tomography/mmt_multipole_inversion}},
year = {2022},
doi = {10.5281/zenodo.6473257},
url = {https://doi.org/10.5281/zenodo.6473257},
}
If you have a new version of biblatex
you can also use @Software
instead of
@Misc
, and add a version={}
entry. You can also cite the paper with the
theoretical framework of this library:
@article{Cortes2021,
author = {Cortés-Ortuño, David and Fabian, Karl and de Groot, Lennart V.},
title = {Single Particle Multipole Expansions From Micromagnetic Tomography},
journal = {Geochemistry, Geophysics, Geosystems},
volume = {22},
number = {4},
pages = {e2021GC009663},
keywords = {magnetism, micromagnetic tomography, multipole, paleomagnetism, rock magnetism},
doi = {https://doi.org/10.1029/2021GC009663},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021GC009663},
eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2021GC009663},
note = {e2021GC009663 2021GC009663},
year = {2021}
}