Pysteps

- cascade.decomposition:
- add a method for recomposing the cascade
- add option to normalize the cascade levels
- make computation of the cascade level statistics (mean and std) optional
- add options to choose the input and output domains: spatial or spectral
- in addition, implement option to use compact output in the spectral domain
- use lowercase names for the field and mask arguments
- cascade.interface:
- modify get_method so that two functions are returned: one for decomposing and one for recomposing the cascade
- extrapolation.semilagrangian:
- add option to specify arbitrary time steps
- motion.lucaskanade:
- fix error when only one sparse vector is found
- noise.fftgenerators:
- add option to choose the output domain for the noise: spatial or spectral
- nowcasts.sprog and nowcasts.steps:
- add option to choose the domain for the computations: spatial or spectral
- nowcasts.utils:
- remove computation of mean and std from stack_cascades
- use utils.tapering module to compute window functions
- io.importers
- add import_saf_crri importer
- timeseries.autoregression:
- add VAR models
- add OLS estimation of AR/VAR parameters
- add localized estimation of AR/VAR parameters
- add differencing option to compute integrated AR/VAR methods
- use lowercase names for variables and revise docstrings
- timeseries.correlation:
- add options for localization and differencing
- add computation of correlation coefficients in the spectral domain
- add method for the estimation of multivariate temporal autocorrelation
- travis:
- run brew update-reset and brew update before installing gcc-9
- utils.spectral:
- add methods for computing mean, standard deviation and correlation coefficient in the spectral domain
- add option to normalize the RAPSD
- visualizations.basemaps
- add future deprecation warning for Basemap dependency

- Code formatting and bug fixes
- Implement GeoTIFF exporter
- Improve existing exporters
- Add postprocessing method to compute the band-depth of an ensemble
- Add method to merge verification objects
- Modify LK default parameters to increase the number of corners to track
- Improve documentation

- Code formatting and bug fixes
- Refactor build system to adopt PEP517/518 standards
- Automate pytests with tox
- Add Proesmans optical flow method
- Refactor Lucas-Kanade optical flow method
- Fix bugs in vet function
- Optimize vet function
- Update io interface (odim_hdf5 -> opera_hdf5)
- Add z-r parameters to MCH, FMI and KNMI importers
- Implement FMI GeoTIFF importer
- Add new scores:
- Normalized MSE
- Matthews correlation coefficient (MCC) score
- F1 score (harmonic mean of precision and sensitivity)
- Implement accumulation of FSS scores from multiple forecast/observation fields
- Distinguish between type 1 and type 2 conditional biases
- Improve documentation:
- Release guidelines

- Bug fixes, code cleanups, and syntax improvements.
- Improve documentation.
- Implement max correlation approach for constant motion field estimation.
- Implement new outlier detection in LK.
- Implement new version of SSEPS nowcasting.
- Increase code coverage.
- Add example scripts and tutorials.

- Change pysteps license to the less restrictive BSD-3
- Move documentation to Read the Docs ([https://pysteps.readthedocs.io/](https://pysteps.readthedocs.io/))
- Include a [gallery of examples](https://pysteps.readthedocs.io/en/latest/auto_examples/index.html)
- Modify `setup.py` to explicitly link libraries in macOS
- Include [Travis](https://travis-ci.com/pySTEPS/pysteps) CI and [Codecov](https://codecov.io/gh/pySTEPS/pysteps)
- Add test suites for interfaces, and the io and verification modules
- Remove legacy config module
- Add [CONTRIBUTING.rst](https://github.com/pySTEPS/pysteps/blob/master/CONTRIBUTING.rst)
- Several docstring improvements
- Add exporter for KINEROS2 Rainfall files (`io.exporters` module)
- Add importer for MeteoSwiss AZC radar composites (`io.importers` module)
- Add importer for KNMI HDF5 radar composites (`io.importers` module)
- Add scripts for estimating velocity perturbator parameters
- Add modules for deriving the auto-correlation function (ACF) and estimating precipitation lifetime
- Implement a separate module `nowcasts.sprog` for S-PROG nowcasts
- Add nowcasting module `nowcasts.sseps`, an experimental version of STEPS that allows for localization
- Implement interfaces for initializing and calling different FFT methods
- Rework of the extrapolation interface
- Faster implementation of the rank histogram with bug fixes
- Improve subplot handling in `plot_precip_field`
- Add visualization of Fourier spectra
- Rework interfaces for verification scores
- Add support for MaskedArray in `motion.dense_lucaskanade`
- Improve masking in `nowcasts.steps` module

Change log since the previous release:

- Bug fixes.
- Performance and syntax improvements.
- Improve documentation to several modules and methods.
- Add the Variational Echo Tracking (VET) method from MAPLE to the motion module.
- Replace the config module with a JSON pystepsrc configuration file.
- More efficient computation of the FFT in the cascade decomposition and noise generation by using the real FFT instead of the complex FFT, i.e. rfft2/irfft2 instead of fft2/ifft2.
- More sensible naming of several main modules: optflow -> motion, advection -> extrapolation and postproc -> postprocessing.
- New utility methods to clip the domain by geographical coordinates.
- New data transformation methods: normal quantile, square-root and logarithmic transformations.
- New importer for MeteoSwiss' metranet data format.
- New "shift and scale" post-processing method.
- Implement the S-PROG method with probability matching.
- New intensity-scale verification method.
- New visualization methods: cartopy backend, exceedance probabilities and plotting motion fields on a map.
- Support for Swiss projection when using cartopy.
- New interface module for different FFT methods and allow the user to choose the method.
- Fix incorrect separation into components when using the bps method for adding perturbations to the advection field.
- Two different methods for adjusting the temporal autocorrelation coefficients in order to guarantee stationarity of the resulting AR(2) models.
- Modify the STEPS method to have the same number of positional arguments as the other methods in the nowcasts module and reorganize the keyword arguments.
- Move the deterministic S-PROG mask computation outside the stochastic part of the STEPS method to avoid repeated computations.