NumpyFFTWBackend.norm_scores#
- NumpyFFTWBackend.norm_scores(arr, exp_sq, sq_exp, n_obs, eps, out)[source]#
Normalizes
arrby the standard deviation ensuring numerical stability.- Parameters:
- arrBackendArray
The input array to be normalized.
- exp_sqBackendArray
Non-normalized expectation square.
- sq_expBackendArray
Non-normalized expectation.
- n_obsint
Number of observations for normalization.
- epsfloat
Numbers below this threshold will be ignored in division.
- outBackendArray
Output array to write the result to.
- Returns:
- BackendArray
The normalized array with the same shape as arr.
See also
tme.matching_exhaustive.flc_scoring()