correlate2d_norm¶
- threadcount.mpdaf_ext.correlate2d_norm(self, other, interp='no')[source]¶
Return the cross-correlation of the image with an array.
Uses scipy.signal.correlate2d. This function normalizes the other image and now properly carries treats the variance. By that I mean: each element of other is squared before it is correlated in scipy. In this way, I hope that propagation of errors is done right.
- Parameters:
other (2d-array) – Second 2d-array.
interp ('no' | 'linear' | 'spline') – if ‘no’, data median value replaced masked values. if ‘linear’, linear interpolation of the masked values. if ‘spline’, spline interpolation of the masked values.
- Return type: