shiftnd¶
- image_registration.fft_tools.shift.shiftnd(data, offset, phase=0, nthreads=1, use_numpy_fft=False, return_abs=False, return_real=True)[source]¶
FFT-based sub-pixel image shift. Will turn NaNs into zeros
Shift Theorem:
\[FT[f(t-t_0)](x) = e^{-2 \pi i x t_0} F(x)\]- Parameters:
- datanp.ndarray
Data to shift
- offset(int,)*ndim
Offsets in each direction. Must be iterable.
- phasefloat
Phase, in radians
- Returns:
- The input array shifted by offsets
- Other Parameters:
- use_numpy_fftbool
Force use numpy’s fft over fftw? (only matters if you have fftw installed)
- nthreadsbool
Number of threads to use for fft (only matters if you have fftw installed)
- return_realbool
Return the real component of the shifted array
- return_absbool
Return the absolute value of the shifted array