diff options
Diffstat (limited to 'numpy/core/numeric.py')
| -rw-r--r-- | numpy/core/numeric.py | 39 |
1 files changed, 37 insertions, 2 deletions
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py index 26ef27dc9..50e3fd75b 100644 --- a/numpy/core/numeric.py +++ b/numpy/core/numeric.py @@ -6,7 +6,7 @@ __all__ = ['newaxis', 'ndarray', 'flatiter', 'ufunc', 'set_numeric_ops', 'can_cast', 'asarray', 'asanyarray', 'ascontiguousarray', 'asfortranarray', 'isfortran', 'empty_like', 'zeros_like', - 'correlate', 'convolve', 'inner', 'dot', 'outer', 'vdot', + 'correlate', 'acorrelate', 'convolve', 'inner', 'dot', 'outer', 'vdot', 'alterdot', 'restoredot', 'roll', 'rollaxis', 'cross', 'tensordot', 'array2string', 'get_printoptions', 'set_printoptions', 'array_repr', 'array_str', 'set_string_function', @@ -579,11 +579,46 @@ def correlate(a,v,mode='valid'): -------- convolve : Discrete, linear convolution of two one-dimensional sequences. - + acorrelate: Discrete correlation following the usual signal processing + definition for complex arrays, and without assuming that + correlate(a, b) == correlate(b, a) """ mode = _mode_from_name(mode) return multiarray.correlate(a,v,mode) +def acorrelate(a, v, mode='valid'): + """ + Discrete, linear correlation of two 1-dimensional sequences. + + This function computes the correlation as generally defined in signal + processing texts: + + z[k] = sum_n a[n] * conj(v[n+k]) + + with a and v sequences being zero-padded where necessary and conj being the + conjugate. + + Parameters + ---------- + a, v : array_like + Input sequences. + mode : {'valid', 'same', 'full'}, optional + Refer to the `convolve` docstring. Note that the default + is `valid`, unlike `convolve`, which uses `full`. + + Note + ---- + This is the function which corresponds to matlab xcorr. + + See Also + -------- + convolve : Discrete, linear convolution of two + one-dimensional sequences. + correlate: Deprecated function to compute correlation + """ + mode = _mode_from_name(mode) + return multiarray.acorrelate(a, v, mode) + def convolve(a,v,mode='full'): """ |