nabu.preproc.ctf_cuda module¶
- class nabu.preproc.ctf_cuda.CudaCTFPhaseRetrieval(shape, geo_pars, delta_beta, padded_shape='auto', padding_mode='reflect', translation_vh=None, normalize_by_mean=False, lim1=1e-05, lim2=0.2, use_rfft=True, fftw_num_threads=None, fft_num_threads=None, logger=None, cuda_options=None, fft_backend='skcuda')[source]¶
Bases:
CTFPhaseRetrieval
Cuda back-end of CTFPhaseRetrieval
Initialize a Contrast Transfer Function phase retrieval.
- Parameters:
geo_pars (GeoPars) – the geometry description
delta_beta (float) – the delta/beta ratio
padded_shape (str or tuple, optional) – Padded image shape, in the form (num_rows, num_columns) i.e (vertical, horizontal). By default, it is twice the image shape.
padding_mode (str) – Padding mode. It must be valid for the numpy.pad function
translation_vh (array, optional) – Shift in the form (y, x). It is used to perform a translation of the image before applying the CTF filter.
normalize_by_mean (bool) – Whether to divide the (padded) image with its mean before applying the CTF filter.
lim1 (float >0) – the regulariser strenght at low frequencies
lim2 (float >0) – the regulariser strenght at high frequencies
use_rfft (bool, optional) – Whether to use real-to-complex (R2C) FFT instead of usual complex-to-complex (C2C).
fftw_num_threads (bool or None or int, optional) – DEPRECATED - please use fft_num_threads instead.
fft_num_threads (bool or None or int, optional) – Number of threads to use for FFT. If a number is provided: number of threads to use for FFT. You can pass a negative number to use N - fft_num_threads cores.
logger (optional) – a logger object
- set_input(data)¶