API Reference¶

Interpolators¶

 Spline([mindist, damping, force_coords, engine]) Biharmonic spline interpolation using Green’s functions. SplineCV([mindists, dampings, force_coords, …]) Cross-validated biharmonic spline interpolation. VectorSpline2D([poisson, mindist, damping, …]) Elastically coupled interpolation of 2-component vector data. ScipyGridder([method, extra_args]) A scipy.interpolate based gridder for scalar Cartesian data.

Data Processing¶

 BlockReduce(reduction[, spacing, region, …]) Apply a reduction/aggregation operation to the data in blocks/windows. BlockMean([spacing, region, adjust, …]) Apply a (weighted) mean to the data in blocks/windows. Trend(degree) Fit a 2D polynomial trend to spatial data.

Composite Estimators¶

 Chain(steps) Chain filtering operations to fit on each subsequent output. Vector(components) Fit an estimator to each component of multi-component vector data.

Model Selection¶

 train_test_split(coordinates, data[, weights]) Split a dataset into a training and a testing set for cross-validation. cross_val_score(estimator, coordinates, data) Score an estimator/gridder using cross-validation.

Coordinate Manipulation¶

 grid_coordinates(region[, shape, spacing, …]) Generate the coordinates for each point on a regular grid. scatter_points(region, size[, random_state, …]) Generate the coordinates for a random scatter of points. profile_coordinates(point1, point2, size[, …]) Coordinates for a profile along a straight line between two points. get_region(coordinates) Get the bounding region of the given coordinates. pad_region(region, pad) Extend the borders of a region by the given amount. project_region(region, projection) Calculate the bounding box of a region in projected coordinates. inside(coordinates, region) Determine which points fall inside a given region. block_split(coordinates[, spacing, adjust, …]) Split a region into blocks and label points according to where they fall.

Utilities¶

 test([doctest, verbose, coverage, figures]) Run the test suite. maxabs(\*args[, nan]) Calculate the maximum absolute value of the given array(s). distance_mask(data_coordinates, maxdist[, …]) Mask grid points that are too far from the given data points. variance_to_weights(variance[, tol, dtype]) Converts data variances to weights for gridding. grid_to_table(grid) Convert a grid to a table with the values and coordinates of each point. median_distance(coordinates[, k_nearest, …]) Median distance between the k nearest neighbors of each point.