Hello Mastodon! Here's an #introduction.
We're Fatiando a Terra (https://www.fatiando.org), a community of geoscientists and software developers building #OpenSource tools in #python for #Geophysics #EarthScience and #DataScience. See the thread below for an overview.
First, a little trivia: "Fatiando a Terra" is Portuguese for "Slicing the Earth", a reference to the project's Brazilian roots and ambitious goals to model the entire planet.
for tool in fatiando:
help(tool)
Tool number 1 - Verde: Gridding, machine learning style.
Verde offers #Geospatial data processing and interpolation (gridding) with a sprinkling of #MachineLearning.
Tool number 2 - Pooch: Easily download datasets.
Pooch is the easiest way to download #data files to your computer. It is used to manage sample data downloads not only by our own tools but also other popular Scientific Python libraries: scikit-image, SciPy, MetPy, xarray, @shtools, satpy, icepack, histolab, yt, napari, and more.
Tool number 3 - Harmonica: All things potential fields.
Harmonica is our library for processing, forward modeling, and inversion of #gravity and #magnetic data. Our goal is to incentivise good practices by carefully designing the software and offering state-of-the-art methods with efficient implementations.
Tool number 4 - Boule: Ellipsoids and normal gravity.
Boule defines reference ellipsoids for calculating normal #gravity of the Earth and other #planetary bodies (Moon, Mars, Venus, Mercury).
Tool number 5 - Ensaio: Practice datasets to probe your code.
Ensaio makes it easy to download our #OpenAccess sample datasets. It taps into the Fatiando a Terra FAIR data collection (https://github.com/fatiando-data) which is designed for use in tutorials, documentation, and #teaching.
Interested? Come say " Hi!" at https://www.fatiando.org/contact and get to know our awesome community!
We're always looking for new contributors to join us, whether it's writing code, docs, and examples or providing feedback.
@fatiando I've seen a 3d prisms inversion many years before (with a something like harvester and seeder functions). Is there still this kind of inversion ?
@Ewaca we used to have that in our Python 2.7 package. It's been a slow road to getting all of that functionality into our new tools but we're almost there. The groundwork for implementing that particular is pretty much ready now (and much better than it used to be) so we're hoping to get that implemented in the near future.