Verde is a Python library for processing spatial data (bathymetry, geophysics surveys, etc) and interpolating it on regular grids (i.e., gridding). Most gridding methods in Verde use a Green’s functions approach. A linear model is estimated based on the input data and then used to predict data on a regular grid (or in a scatter, a profile, as derivatives). The models are Green’s functions from (mostly) elastic deformation theory. This approach is very similar to machine learning so we implement gridder classes that are similar to scikit-learn regression classes. The API is not 100% compatible but it should look familiar to those with some scikit-learn experience.
Keywords for this software
References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Leonardo Uieda; Santiago Rubén Soler; Rémi Rampin; Hugo van Kemenade; Matthew Turk; Daniel Shapero; Anderson Banihirwe; John Leeman: Pooch: A friend to fetch your data files (2020) not zbMATH
- Tobias Stål, Anya M. Reading: A Grid for Multidimensional and Multivariate Spatial Representation and Data Processing (2020) not zbMATH
- Leonardo Uieda: Verde: Processing and gridding spatial data using Green’s functions (2018) not zbMATH