diff options
Diffstat (limited to 'numpy/ma/core.py')
| -rw-r--r-- | numpy/ma/core.py | 83 |
1 files changed, 79 insertions, 4 deletions
diff --git a/numpy/ma/core.py b/numpy/ma/core.py index c4a54acb4..4466dc0af 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -56,10 +56,10 @@ __all__ = [ 'argmax', 'argmin', 'argsort', 'around', 'array', 'asanyarray', 'asarray', 'bitwise_and', 'bitwise_or', 'bitwise_xor', 'bool_', 'ceil', 'choose', 'clip', 'common_fill_value', 'compress', 'compressed', - 'concatenate', 'conjugate', 'copy', 'cos', 'cosh', 'count', 'cumprod', - 'cumsum', 'default_fill_value', 'diag', 'diagonal', 'diff', 'divide', - 'dump', 'dumps', 'empty', 'empty_like', 'equal', 'exp', 'expand_dims', - 'fabs', 'filled', 'fix_invalid', 'flatten_mask', + 'concatenate', 'conjugate', 'convolve', 'copy', 'correlate', 'cos', 'cosh', + 'count', 'cumprod', 'cumsum', 'default_fill_value', 'diag', 'diagonal', + 'diff', 'divide', 'dump', 'dumps', 'empty', 'empty_like', 'equal', 'exp', + 'expand_dims', 'fabs', 'filled', 'fix_invalid', 'flatten_mask', 'flatten_structured_array', 'floor', 'floor_divide', 'fmod', 'frombuffer', 'fromflex', 'fromfunction', 'getdata', 'getmask', 'getmaskarray', 'greater', 'greater_equal', 'harden_mask', 'hypot', @@ -7366,6 +7366,81 @@ outer.__doc__ = doc_note(np.outer.__doc__, outerproduct = outer +def _convolve_or_correlate(f, a, v, mode, propagate_mask): + """ + Helper function for ma.correlate and ma.convolve + """ + if propagate_mask: + # results which are contributed to by either item in any pair being invalid + mask = ( + f(getmaskarray(a), np.ones(np.shape(v), dtype=np.bool), mode=mode) + | f(np.ones(np.shape(a), dtype=np.bool), getmaskarray(v), mode=mode) + ) + data = f(getdata(a), getdata(v), mode=mode) + else: + # results which are not contributed to by any pair of valid elements + mask = ~f(~getmaskarray(a), ~getmaskarray(v)) + data = f(filled(a, 0), filled(v, 0), mode=mode) + + return masked_array(data, mask=mask) + + +def correlate(a, v, mode='valid', propagate_mask=True): + """ + 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 'full'. + propagate_mask : bool + 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 + ------- + out : MaskedArray + Discrete cross-correlation of `a` and `v`. + + See Also + -------- + numpy.correlate : Equivalent function in the top-level NumPy module. + """ + return _convolve_or_correlate(np.correlate, a, v, mode, propagate_mask) + + +def convolve(a, v, mode='full', propagate_mask=True): + """ + Returns the discrete, linear convolution of two one-dimensional sequences. + + Parameters + ---------- + a, v : array_like + Input sequences. + mode : {'valid', 'same', 'full'}, optional + Refer to the `np.convolve` docstring. + propagate_mask : bool + If True, then if any masked element is included in the sum for a result + element, then the result is masked. + If False, then the result element is only masked if no non-masked cells + contribute towards it + + Returns + ------- + out : MaskedArray + Discrete, linear convolution of `a` and `v`. + + See Also + -------- + numpy.convolve : Equivalent function in the top-level NumPy module. + """ + return _convolve_or_correlate(np.convolve, a, v, mode, propagate_mask) + + def allequal(a, b, fill_value=True): """ Return True if all entries of a and b are equal, using |