verde 0.1a0

Disclaimer

This package is in early stages of design and implementation.

We welcome any feedback and ideas! Let us know by submitting issues on Github or send us a message on our Gitter chatroom.

About

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.

Advantages of using Green’s functions include:

• Easily apply weights to data points. This is a linear least-squares problem.

• Perform model selection using established machine learning techniques, like k-fold or holdout cross-validation.

• The estimated model can be easily stored for later use, like spherical-harmonic coefficients are used in gravimetry.

Project goals

• Provide a machine-learning inspired interface for Green’s functions gridding of spatial data

• Integration with the Scipy stack: numpy, pandas (for xyz data), and xarray (for grids)

• Include functions for common processing and data preparation tasks, like blocked means and medians

• Support for gridding scalar and vector data (like wind speed or GPS velocities)

• Support for both Cartesian and geographic coordinates

Contacting Us

• Most discussion happens on Github. Feel free to open an issue or comment on any open issue or pull request.

• We have chat room on Gitter where you can ask questions and leave comments.

Contributing

License

This is free software: you can redistribute it and/or modify it under the terms of the BSD 3-clause License. A copy of this license is provided in LICENSE.txt.