xoa.filter

Filtering utilities

Functions

convolve(data, kernel[, normalize, ...])	N-dimensional convolution that takes care of nans
decimate(obj, radius[, method, stack_dim, ...])	Decimate a data array or dataset by removing too close points
demerliac(da[, na_thres, dt_tol])	Apply a dermerliac filter on a data array
erode_coast(data[, until, kernel, xdim, ydim])	Just like erode_mask() but specialized for the horizontal dimensions
erode_mask(data[, until, kernel])	Erode the horizontal mask using smoothing
generate_isotropic_kernel(shape, window_func)	Generate an nD istropic kernel given a shape and a window function
generate_kernel(kernel, data[, window_func, ...])	Generate a kernel that is compatible with a given data array
generate_orthogonal_kernel(kernels[, ...])	Generate an nD kernel from orthogonal 1d kernels
get_window_func(window, **kwargs)	Get a window function from its name
shapiro_kernel(dims)	Generate a shapiro kernel
smooth(data, kernel, **kwargs)	A short to convolve(data, kernel, normalize=True)

Classes

decimation_methods([value])

Supported regrid1d() methods