regridding

Resample arrays defined on curvilinear grids.

Functions

fill(a[, where, axis, method])	Fill an array with missing values by interpolating from the valid points.
find_indices(coordinates_input, ...[, ...])	Find the index of the input cell which contains the output vertex.
ndarray_linear_interpolation(a, indices[, ...])	Interpolate a numpy.ndarray onto a new grid.
regrid(coordinates_input, ...[, ...])	Regrid an array of values defined on a logically-rectangular curvilinear grid onto a new logically-rectangular curvilinear grid.
regrid_from_weights(weights, shape_input, ...)	Regrid an array of values using weights computed by regridding.weights().
transpose_weights(weights)	Transpose the sparse matrix of weights calculated by regridding.weights().
transpose_weights_conservative(weights, ...)	Transpose matrix of weights and normalize to be conservative.
weights(coordinates_input, coordinates_output)	Save the results of a regridding operation as a sequence of weights, which can be used in subsequent regridding operations on the same grid.

Modules

geometry	Numba-compiled computational geometry routines needed for regridding operations.
math	Compiled versions of fundamental mathematical functions.