pysteps.utils

Implementation of miscellaneous utility functions.

pysteps.utils.interface

Interface for the utils module.

get_method(name, **kwargs)

Return a callable function for the utility method corresponding to the given name.

pysteps.utils.arrays

Utility methods for creating and processing arrays.

compute_centred_coord_array(M, N)

Compute a 2D coordinate array, where the origin is at the center.

pysteps.utils.cleansing

Data cleansing routines for pysteps.

decluster(coord, input_array, scale[, ...])	Decluster a set of sparse data points by aggregating, that is, taking the median value of all values lying within a certain distance (i.e., a cluster).
detect_outliers(input_array, thr[, coord, ...])	Detect outliers in a (multivariate and georeferenced) dataset.

pysteps.utils.conversion

Methods for converting physical units.

to_rainrate(R, metadata[, zr_a, zr_b])	Convert to rain rate [mm/h].
to_raindepth(R, metadata[, zr_a, zr_b])	Convert to rain depth [mm].
to_reflectivity(R, metadata[, zr_a, zr_b])	Convert to reflectivity [dBZ].

pysteps.utils.dimension

Functions to manipulate array dimensions.

aggregate_fields(data, window_size[, axis, ...])	Aggregate fields along a given direction.
aggregate_fields_time(R, metadata, ...[, ...])	Aggregate fields in time.
aggregate_fields_space(R, metadata, space_window)	Upscale fields in space.
clip_domain(R, metadata[, extent])	Clip the field domain by geographical coordinates.
square_domain(R, metadata[, method, inverse])	Either pad or crop a field to obtain a square domain.

pysteps.utils.fft

Interface module for different FFT methods.

get_numpy(shape[, fftn_shape])
get_scipy(shape[, fftn_shape])
get_pyfftw(shape[, fftn_shape, n_threads])

pysteps.utils.images

Image processing routines for pysteps.

morph_opening(input_image, thr, n)

Filter out small scale noise on the image by applying a binary morphological opening, that is, erosion followed by dilation.

pysteps.utils.interpolate

Interpolation routines for pysteps.

idwinterp2d(xy_coord, values, xgrid, ygrid)	Inverse distance weighting interpolation of a sparse (multivariate) array.
rbfinterp2d(xy_coord, values, xgrid, ygrid, ...)	Radial basis function interpolation of a sparse (multivariate) array.

pysteps.utils.spectral

Utility methods for processing and analyzing precipitation fields in the Fourier domain.

corrcoef(X, Y, shape[, use_full_fft])	Compute the correlation coefficient between two-dimensional arrays in the spectral domain.
mean(X, shape)	Compute the mean value of a two-dimensional array in the spectral domain.
rapsd(field[, fft_method, return_freq, d, ...])	Compute radially averaged power spectral density (RAPSD) from the given 2D input field.
remove_rain_norain_discontinuity(R)	Function to remove the rain/no-rain discontinuity.
std(X, shape[, use_full_fft])	Compute the standard deviation of a two-dimensional array in the spectral domain.

pysteps.utils.tapering

Implementations of window functions for computing of the FFT.

compute_mask_window_function(mask, func, ...)	Compute window function for a two-dimensional area defined by a non-rectangular mask.
compute_window_function(m, n, func, **kwargs)	Compute window function for a two-dimensional rectangular region.

pysteps.utils.transformation

Methods for transforming data values.

boxcox_transform(R[, metadata, Lambda, ...])	The one-parameter Box-Cox transformation.
dB_transform(R[, metadata, threshold, ...])	Methods to transform precipitation intensities to/from dB units.
NQ_transform(R[, metadata, inverse])	The normal quantile transformation as in Bogner et al (2012).
sqrt_transform(R[, metadata, inverse])	Square-root transform.

pysteps.utils.reprojection

Reprojection tools to reproject grids and adjust the grid cell size of an input field to a destination field.

reproject_grids(src_array, dst_array, ...)

Reproject precipitation fields to the domain of another precipitation field.