pysteps.noise.fftgenerators.initialize_nonparam_2d_fft_filter(field, **kwargs)#

Takes one ore more 2d input fields and produces one non-parametric, global and anisotropic fourier filter.

  • field (array-like) – Two- or three-dimensional array containing one or more input fields. All values are required to be finite. If more than one field are passed, the average fourier filter is returned. It assumes that fields are stacked by the first axis: [nr_fields, y, x].

  • win_fun ({'hann', 'tukey', None}) – Optional tapering function to be applied to the input field, generated with pysteps.utils.tapering.compute_window_function() (default ‘tukey’).

  • donorm (bool) – Option to normalize the real and imaginary parts. Default: False

  • rm_rdisc (bool) – Whether or not to remove the rain/no-rain disconituity (default True). It assumes no-rain pixels are assigned with lowest value.

  • fft_method (str or tuple) – A string or a (function,kwargs) tuple defining the FFT method to use (see “FFT methods” in pysteps.utils.interface.get_method()). Defaults to “numpy”.


out – A dictionary containing the keys field and input_shape. The first is a two-dimensional array of shape (m, int(n/2)+1) that defines the filter. The second one is the shape of the input field for the filter.

It can be passed to pysteps.noise.fftgenerators.generate_noise_2d_fft_filter().

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