# numpy.ma.correlate#

Cross-correlation of two 1-dimensional sequences.

Parameters:
a, varray_like

Input sequences.

mode{‘valid’, ‘same’, ‘full’}, optional

Refer to the np.convolve docstring. Note that the default is ‘valid’, unlike `convolve`, which uses ‘full’.

If 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:

Discrete cross-correlation of a and v.

`numpy.correlate`

Equivalent function in the top-level NumPy module.

Examples

Basic correlation:

```>>> a = np.ma.array([1, 2, 3])
>>> v = np.ma.array([0, 1, 0])
>>> np.ma.correlate(a, v, mode='valid')
fill_value=999999)
```

```>>> a = np.ma.array([1, 2, 3], mask=[False, True, False])
>>> v = np.ma.array([0, 1, 0])
fill_value=999999,
dtype=int64)
```

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')