Fatiando a Terra

Fatiando a Terra

An open toolbox for the Geosciences.

Fatiando provides Python libraries for data processing, modeling, and inversion across the Geosciences.

It is built by a community of geoscientists and software developers with a passion for well-designed tools and helping our peers.

All of our software is free and open-source.

Getting started

Want to learn about our software? The best place to learn about each of our software libraries is their documentation. The docs always contain the most up-to-date information. See links to each project below.

New to Python? Take the Software Carpentry lessons (online or in-person) to learn the basics. There are more lessons than just Python and everything they teach is definitely work learning!

Rather watch a tutorial? Our YouTube channel has video tutorials about some of our tools. The tutorials are always accompanied by code but they can get outdated over time.

Screenshot from our Harmonica tutorial at Transform 2021.

Meet our libraries

Verde: Gridding, machine learning style

Verde offers spatial data processing and interpolation (gridding) with a sprinkling of machine learning.

Vertical ground velocity in California interpolated from GPS data with and without weights based on data uncertainty.

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. 

import pooch
import xarray as xr

# The Digital Object Identifier of the data
doi = "10.6084/m9.figshare.13643837"
# Known MD5 checksum (from figshare)
checksum = "md5:16c94a792003714efee2bdb4f3181d3a"
# Download the netCDF file and check integrity
fname = pooch.retrieve(
    url=f"doi:{doi}/australia-ground-gravity.nc",
    known_hash=checksum,
)
# fname is the path to the file
data = xr.load_dataset(fname)
Running this code multiple times will only result in a single download because the data are cached automatically.

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.

Residual gravity disturbances of the Bushveld Complex, South Africa, gridded to a uniform height with equivalent sources.

Boule: Ellipsoids and normal gravity

Boule defines reference ellipsoids for coordinate conversions and calculating normal gravity of the Earth and other planetary bodies (Moon, Mars, Venus, Mercury, and more).

Normal gravity of the WGS84 ellipsoid calculated at the Earth's surface using an analytical expression (no free-air correction required).

Ensaio: Practice datasets to probe your code

Ensaio makes it easy to download our open-access sample datasets. It taps into the Fatiando a Terra FAIR data collection which is designed for use in tutorials, documentation, and teaching.

A sample of the datasets available in Ensaio. From the top-left: gravity, geoid height, bathymetry, GPS velocity, global relief, and magnetic anomaly.

Choclo: Kernel functions for geophysical models

Optimized numba-compatible forward modelling functions for gravity and magnetic fields, specially tailored to be reused by other libraries, like Harmonica, Magali, and SimPEG. 

import choclo

# Define observation point
easting, northing, upward = 10.4e3, -5.6e3, 110.
# Define prism boundaries and physical properties
prism = [4e3, 12e3, -10e3, -2e3, -300., 20.]
magnetization = [1.2, -2.3, 1.0]
# Compute magnetic field of the prism
b_e, b_n, b_u = choclo.prism.magnetic_field(
    easting, northing, upward, *prism, *magnetization
)
This code for calculating the magnetic field generated by a prism can be put in a loop inside a numba.jit function to speed it up.

Bordado: Create and split geographic coordinates

Bordado can generate coordinates for regular grids and meshes, split points based on spatial blocks and rolling windows, and perform other operations on spatially distributed points.

Animation of splitting a set of random points along the globe using rolling windows with equal area. The yellow points are the window centers.

Interested?

We are always happy to welcome anyone who is interested in getting involved! Whether it be coding, teaching, designing, or just hanging out. Getting involved in open-source can be a great way to meet new people, improve your coding skills, and make an impact in your field.

Happy community members at one of our regular Fatiando open calls, where we discuss the project and future plans.