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Verde v1.7.0

Getting Started

  • Overview
  • Installing
  • Gallery
    • K-Fold cross-validation with blocks
    • Blocked reduction operations
    • Using weights in blocked reduction
    • Using weights in blocked means
    • Mask grid points by convex hull
    • Mask grid points by distance
    • Projection of gridded data
    • Gridding with Scipy
    • Gridding with splines
    • Gridding with splines (cross-validated)
    • Gridding with splines and weights
    • Splitting data into train and test sets
    • Polynomial trend
    • Trends in vector data
    • Gridding 2D vectors

User Guide

  • Sample Data
    • [DEPRECATED] Bathymetry data from Baja California
    • [DEPRECATED] GPS velocities from California
    • Checkerboard function
    • [DEPRECATED] Magnetic data from Rio de Janeiro
    • [DEPRECATED] Wind speed data from Texas
  • Grid Coordinates
  • Trend Estimation
  • Data Decimation
  • Geographic Coordinates
  • Chaining Operations
  • Evaluating Performance
  • Model Selection
  • Using Weights
  • Vector Data

Reference documentation

  • List of functions and classes (API)
    • verde.Spline
    • verde.SplineCV
    • verde.VectorSpline2D
    • verde.ScipyGridder
    • verde.BlockReduce
    • verde.BlockMean
    • verde.Trend
    • verde.Chain
    • verde.Vector
    • verde.train_test_split
    • verde.cross_val_score
    • verde.BlockShuffleSplit
    • verde.BlockKFold
    • verde.grid_coordinates
    • verde.scatter_points
    • verde.profile_coordinates
    • verde.get_region
    • verde.pad_region
    • verde.inside
    • verde.block_split
    • verde.rolling_window
    • verde.expanding_window
    • verde.project_region
    • verde.project_grid
    • verde.distance_mask
    • verde.convexhull_mask
    • verde.maxabs
    • verde.variance_to_weights
    • verde.grid_to_table
    • verde.make_xarray_grid
    • verde.median_distance
    • verde.load_surfer
    • verde.synthetic.CheckerBoard
    • verde.datasets.locate
    • verde.datasets.fetch_baja_bathymetry
    • verde.datasets.setup_baja_bathymetry_map
    • verde.datasets.fetch_california_gps
    • verde.datasets.setup_california_gps_map
    • verde.datasets.fetch_texas_wind
    • verde.datasets.setup_texas_wind_map
    • verde.datasets.fetch_rio_magnetic
    • verde.datasets.setup_rio_magnetic_map
    • verde.base.BaseGridder
    • verde.base.BaseBlockCrossValidator
    • verde.base.n_1d_arrays
    • verde.base.check_fit_input
    • verde.base.least_squares
  • Citing Verde
  • Changelog
  • References
  • Documentation for other versions

Community

  • Join the community
  • How to contribute
  • Code of Conduct
  • Source code on GitHub
  • The Fatiando a Terra project
Theme by the Executable Book Project

Gallery

Gallery¶

This gallery contains a selection examples of what Verde can do.

K-Fold cross-validation with blocks

K-Fold cross-validation with blocks¶

Blocked reduction operations

Blocked reduction operations¶

Using weights in blocked reduction

Using weights in blocked reduction¶

Using weights in blocked means

Using weights in blocked means¶

Mask grid points by convex hull

Mask grid points by convex hull¶

Mask grid points by distance

Mask grid points by distance¶

Projection of gridded data

Projection of gridded data¶

Gridding with Scipy

Gridding with Scipy¶

Gridding with splines

Gridding with splines¶

Gridding with splines (cross-validated)

Gridding with splines (cross-validated)¶

Gridding with splines and weights

Gridding with splines and weights¶

Splitting data into train and test sets

Splitting data into train and test sets¶

Polynomial trend

Polynomial trend¶

Trends in vector data

Trends in vector data¶

Gridding 2D vectors

Gridding 2D vectors¶

Gallery generated by Sphinx-Gallery

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Installing

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K-Fold cross-validation with blocks

© Copyright 2017-2022, The Verde Developers.
Last updated on Mar 25, 2022.