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reduce(a, axis=0, dtype=None, out=None, keepdims=False)

Reduces `a`'s dimension by one, by applying ufunc along one axis.

Let :math:`a.shape = (N_0, ..., N_i, ..., N_{M-1})`.  Then
:math:`ufunc.reduce(a, axis=i)[k_0, ..,k_{i-1}, k_{i+1}, .., k_{M-1}]` =
the result of iterating `j` over :math:`range(N_i)`, cumulatively applying
ufunc to each :math:`a[k_0, ..,k_{i-1}, j, k_{i+1}, .., k_{M-1}]`.
For a one-dimensional array, reduce produces results equivalent to:
::(more...)

src/s/p/Spherebot-Host-GUI-HEAD/InkscapePortable/App/Inkscape/python/Lib/site-packages/numpy/linalg/linalg.py   Spherebot-Host-GUI(Download)
    m = u.shape[0]
    n = vt.shape[1]
    cutoff = rcond*maximum.reduce(s)
    for i in range(min(n, m)):
        if s[i] > cutoff:

src/p/y/Pymol-script-repo-HEAD/modules/pdb2pqr/contrib/numpy-1.1.0/numpy/linalg/linalg.py   Pymol-script-repo(Download)
    m = u.shape[0]
    n = vt.shape[1]
    cutoff = rcond*maximum.reduce(s)
    for i in range(min(n, m)):
        if s[i] > cutoff:

src/n/u/nupic-linux64-HEAD/lib64/python2.6/site-packages/numpy/linalg/linalg.py   nupic-linux64(Download)
    m = u.shape[0]
    n = vt.shape[1]
    cutoff = rcond*maximum.reduce(s)
    for i in range(min(n, m)):
        if s[i] > cutoff:

src/m/i/MissionPlanner-HEAD/Lib/site-packages/numpy/linalg/linalg.py   MissionPlanner(Download)
    m = u.shape[0]
    n = vt.shape[1]
    cutoff = rcond*maximum.reduce(s)
    for i in range(min(n, m)):
        if s[i] > cutoff:

src/n/u/numpy-1.8.1/numpy/linalg/linalg.py   numpy(Download)
    m = u.shape[0]
    n = vt.shape[1]
    cutoff = rcond*maximum.reduce(s)
    for i in range(min(n, m)):
        if s[i] > cutoff: