pysteps.motion.darts.DARTS¶
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pysteps.motion.darts.DARTS(Z, **kwargs)¶ Compute the advection field from a sequence of input images by using the DARTS method. [RCW11]
Parameters: - Z : array-like
Array of shape (T,m,n) containing a sequence of T two-dimensional input images of shape (m,n).
Returns: - out : ndarray
Three-dimensional array (2,m,n) containing the dense x- and y-components of the motion field.
Other Parameters: - N_x : int
Number of DFT coefficients to use for the input images, x-axis (default=50).
- N_y : int
Number of DFT coefficients to use for the input images, y-axis (default=50).
- N_t : int
Number of DFT coefficients to use for the input images, time axis (default=4). N_t must be strictly smaller than T.
- M_x : int
Number of DFT coefficients to compute for the output advection field, x-axis (default=2).
- M_y : int
Number of DFT coefficients to compute for the output advection field, y-axis (default=2).
- fft_method : str
A string defining the FFT method to use, see utils.fft.get_method. Defaults to ‘numpy’.
- output_type : {“spatial”, “spectral”}
The type of the output: “spatial”=apply the inverse FFT to obtain the spatial representation of the advection field, “spectral”=return the (truncated) DFT representation.
- n_threads : int
Number of threads to use for the FFT computation. Applicable if fft_method is ‘pyfftw’.
- print_info : bool
If True, print information messages.
- lsq_method : {1, 2}
The method to use for solving the linear equations in the least squares sense: 1=numpy.linalg.lstsq, 2=explicit computation of the Moore-Penrose pseudoinverse and SVD.
- verbose : bool
if set to True, it prints information about the program