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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!
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.. grid-item-card:: :octicon:`info` Getting started
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New to Verde? Start here!
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.. grid-item-card:: :octicon:`comment-discussion` Need help?
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Ask on our community channels.
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Join the conversation :octicon:`link-external`
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A list of modules and functions.
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.. grid-item-card:: :octicon:`bookmark` Using Verde for research?
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Citations help support our work!
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.. seealso::
Verde is a part of the
`Fatiando a Terra `__ project.
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:caption: Getting Started
tutorials/overview.rst
install.rst
gallery/index.rst
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:caption: User Guide
tutorials/grid_coordinates.rst
tutorials/trends.rst
tutorials/decimation.rst
tutorials/projections.rst
tutorials/chain.rst
tutorials/model_evaluation.rst
tutorials/model_selection.rst
tutorials/weights.rst
tutorials/vectors.rst
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api/index.rst
citing.rst
references.rst
changes.rst
compatibility.rst
versions.rst
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:caption: Community
Join the community
How to contribute
Code of Conduct
Source code on GitHub
The Fatiando a Terra project