pysteps.noise.fftgenerators.initialize_nonparam_2d_fft_filter

pysteps.noise.fftgenerators.initialize_nonparam_2d_fft_filter(X, **kwargs)

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

Parameters:

X : 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].

Returns:

out : dict

A dictionary containing the keys F 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().

Other Parameters:  

win_type : {‘hanning’, ‘flat-hanning’}

Optional tapering function to be applied to X, generated with pysteps.noise.fftgenerators.build_2D_tapering_function() (default ‘flat-hanning’).

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 pysteps.utils.fft.get_method()). Defaults to “numpy”.