Verde

Processing and gridding spatial data, machine-learning style

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Verde is a Python library for processing spatial data (bathymetry, geophysics surveys, etc) and interpolating it on regular grids (i.e., gridding).

Our core interpolation methods are inspired by machine-learning. As such, Verde implements an interface that is similar to the popular scikit-learn library. We also provide other analysis methods that are often used in combination with gridding, like trend removal, blocked/windowed operations, cross-validation, and more!


Getting started

New to Verde? Start here!

Overview

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Reference documentation

A list of modules and functions.

List of functions and classes (API)

Using Verde for research?

Citations help support our work!

Citing Verde


See also

Verde is a part of the Fatiando a Terra project.