List of functions and classes (API)#

Interpolators#

`Spline`([damping, force_coords, parallel])	Biharmonic spline interpolation using Green's functions.
`SplineCV`([dampings, force_coords, cv, ...])	Cross-validated biharmonic spline interpolation.
`KNeighbors`([k, reduction])	Nearest neighbor interpolation.
`Linear`([rescale])	Piecewise linear interpolation.
`Cubic`([rescale])	Piecewise cubic interpolation.
`VectorSpline2D`([poisson, mindist, damping, ...])	Elastically coupled interpolation of 2-component vector data.

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

Vector(components)

Fit an estimator to each component of multi-component vector data.

`train_test_split`(coordinates, data[, ...])	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.
`BlockShuffleSplit`([block_size, block_shape, ...])	Random permutation of spatial blocks cross-validator.
`BlockKFold`([block_size, block_shape, ...])	K-Folds over spatial blocks cross-validator.

`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.
`inside`(coordinates, region)	Determine which points fall inside a given region.
`rolling_window`(coordinates, size[, spacing, ...])	Select points on a rolling (moving) window.
`expanding_window`(coordinates, center, sizes)	Select points on windows of changing size around a center point.

`project_region`(region, projection)	Calculate the bounding box of a region in projected coordinates.
`project_grid`(grid, projection[, method, ...])	Apply the given map projection to a grid and re-sample it.

`distance_mask`(data_coordinates, maxdist[, ...])	Mask grid points that are too far from the given data points.
`convexhull_mask`(data_coordinates[, ...])	Mask grid points that are outside the convex hull of the given data points.

`maxabs`(*args[, nan])	Calculate the maximum absolute value of the given array(s).
`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.
`make_xarray_grid`(coordinates, data, data_names)	Create an `xarray.Dataset` grid from 2D numpy arrays
`median_distance`(coordinates[, k_nearest, ...])	Median distance between the k nearest neighbors of each point.

load_surfer(fname[, dtype])

Read data from a Surfer ASCII grid file.

synthetic.CheckerBoard([amplitude, region, ...])

Generate synthetic data in a checkerboard pattern.

`base.BaseGridder`()	Base class for gridders.
`base.BaseBlockCrossValidator`([block_size, ...])	Base class for spatially blocked cross-validators.
`base.n_1d_arrays`(arrays, n)	Get the first n elements from a tuple/list, convert to arrays, and ravel.
`base.least_squares`(jacobian, data, weights)	Solve a weighted least-squares problem with optional damping regularization