bundles / numpy 2.5.0.dev0+git20251130.2de293a / numpy / ma / core / correlate
function
numpy.ma.core:correlate
source: build-install/usr/lib/python3.14/site-packages/numpy/ma/core.py :8300
Signature
def correlate ( a , v , mode = valid , propagate_mask = True ) Summary
Cross-correlation of two 1-dimensional sequences.
Parameters
a, v: array_likeInput sequences.
mode: {'valid', 'same', 'full'}, optionalRefer to the
np.convolvedocstring. Note that the default is 'valid', unlike convolve, which uses 'full'.propagate_mask: boolIf True, then a result element is masked if any masked element contributes towards it. If False, then a result element is only masked if no non-masked element contribute towards it
Returns
out: MaskedArrayDiscrete cross-correlation of
aandv.
Examples
Basic correlation:a = np.ma.array([1, 2, 3]) v = np.ma.array([0, 1, 0]) np.ma.correlate(a, v, mode='valid')Correlation with masked elements:
a = np.ma.array([1, 2, 3], mask=[False, True, False]) v = np.ma.array([0, 1, 0]) np.ma.correlate(a, v, mode='valid', propagate_mask=True)Correlation with different modes and mixed array types:
a = np.ma.array([1, 2, 3]) v = np.ma.array([0, 1, 0]) np.ma.correlate(a, v, mode='full')
See also
- numpy.correlate
Equivalent function in the top-level NumPy module.
Aliases
-
numpy.ma.correlate