Overview

Overview#

Magali is a Python library for the forward modeling, inversion, and analysis of magnetic microscopy data,with a particular focus on paleomagnetism and rock magnetism applications. It provides tools to infer the magnetic properties of individual mineral grains from high-resolution magnetic microscopy images, such as those acquired by quantum diamond microscopes (QDMs).

Its main goals are:

  • Offer robust and efficient implementations of dipole modeling and inversion methods tailored for magnetic microscopy data.

  • Enable the semi-automatic detection, localization, and characterization of hundreds to thousands of magnetic sources in a single microscopy image.

  • Support reproducible research and community-driven development by providing well-documented open-source code.

  • Facilitate methodological innovation by offering a modular and extensible platform for the development and testing of new techniques.

Conventions#

Magali adopts the following conventions across its API:

  • All physical quantities follow the International System of Units (SI) , with a few exceptions:

    • Magnetic fields are expressed in nanoTesla (nT).

    • Magnetic moments are expressed in Ampere square meters (A·m²).

  • All coordinates are expressed in micrometers (µm) and are represented in right-handed Cartesian coordinate system, defined as:

    • The x-axis runs horizontally across the image and is analogous to easting.

    • The y-axis lies in the image plane, perpendicular to x, and is analogous to northing.

    • The z-axis points upward, away from the sample surface (i.e., out of the image plane).

This orientation follows the right-hand rule: if you point your right-hand fingers along the x-axis and curl them toward the y-axis, your thumb will point in the direction of the z-axis.

Note

While the x and y axes may resemble easting and northing, microscopy data lacks a globally georeferenced frame. Instead, axis orientation depends on the acquisition setup or sample mounting. To ensure correct modeling and interpretation, always define and maintain a consistent axis convention throughout your workflow.

The library#

All functionality in magali is available from the base namespace of the magali package. This means that you can access all of them with a single import:

# magali is usually imported as mg
import magali as mg

See also

Checkout the List of functions and classes (API) for a comprehensive list of the available functions and classes in Magali.

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