chi2n_map¶
- image_registration.chi2n_map(im1, im2, err=None, boundary='wrap', nthreads=1, zeromean=False, use_numpy_fft=False, return_all=False, reduced=False)[source]¶
- Parameters:
- im1np.ndarray
- im2np.ndarray
The images to register.
- errnp.ndarray
Per-pixel error in image 2
- boundary‘wrap’,’constant’,’reflect’,’nearest’
Option to pass to map_coordinates for determining what to do with shifts outside of the boundaries.
- zeromeanbool
Subtract the mean from the images before cross-correlating? If no, you may get a 0,0 offset because the DC levels are strongly correlated.
- nthreadsbool
Number of threads to use for fft (only matters if you have fftw installed)
- reducedbool
Return the reduced \(\chi^2\) array, or unreduced? (assumes 2 degrees of freedom for the fit)
- Returns:
- chi2nnp.ndarray
the \(\chi^2\) array
- term1float
Scalar, term 1 in the \(\chi^2\) equation
- term2np.ndarray
Term 2 in the equation, -2 * cross-correlation(x/sigma^2,y)
- term3np.ndarray | float
If error is an array, returns an array, otherwise is a scalar float corresponding to term 3 in the equation