Cross-correlation of two 1-dimensional sequences. Parameters ---------- a, v : array_like Input sequences. mode : {'valid', 'same', 'full'}, optional Refer to the `np.convolve` docstring. Note that the default is 'valid', unlike `convolve`, which uses '
(a, v, mode='valid', propagate_mask=True)
| 7980 | |
| 7981 | |
| 7982 | def correlate(a, v, mode='valid', propagate_mask=True): |
| 7983 | """ |
| 7984 | Cross-correlation of two 1-dimensional sequences. |
| 7985 | |
| 7986 | Parameters |
| 7987 | ---------- |
| 7988 | a, v : array_like |
| 7989 | Input sequences. |
| 7990 | mode : {'valid', 'same', 'full'}, optional |
| 7991 | Refer to the `np.convolve` docstring. Note that the default |
| 7992 | is 'valid', unlike `convolve`, which uses 'full'. |
| 7993 | propagate_mask : bool |
| 7994 | If True, then a result element is masked if any masked element contributes towards it. |
| 7995 | If False, then a result element is only masked if no non-masked element |
| 7996 | contribute towards it |
| 7997 | |
| 7998 | Returns |
| 7999 | ------- |
| 8000 | out : MaskedArray |
| 8001 | Discrete cross-correlation of `a` and `v`. |
| 8002 | |
| 8003 | See Also |
| 8004 | -------- |
| 8005 | numpy.correlate : Equivalent function in the top-level NumPy module. |
| 8006 | """ |
| 8007 | return _convolve_or_correlate(np.correlate, a, v, mode, propagate_mask) |
| 8008 | |
| 8009 | |
| 8010 | def convolve(a, v, mode='full', propagate_mask=True): |
nothing calls this directly
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