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In numpy >= 1.8 the modes are
mode : {'reduced', 'complete', 'r', 'raw', 'full', 'economic'}, optional
If K = min(M, N), then
'reduced' : returns q, r with dimensions (M, K), (K, N) (default)
'complete' : returns q, r with dimensions (M, M), (M, N)
'r' : returns r only with dimensions (K, N)
'raw' : returns h, tau with dimensions (N, M), (K,)
'full' : alias of 'reduced', deprecated
'economic' : returns h from 'raw', deprecated.
The options 'reduced', 'complete, and 'raw' are new in numpy 1.8,
see the notes for more information. The default is 'reduced' and to
maintain backward compatibility with earlier versions of numpy both
it and the old default 'full' can be omitted. Note that array h
returned in 'raw' mode is transposed for calling Fortran. The
'economic' mode is deprecated. The modes 'full' and 'economic' may
be passed using only the first letter for backwards compatibility,
but all others must be spelled out. See the Notes for more
explanation.
Whereas scipy has
mode : {'full', 'r', 'economic', 'raw'}, optional
Determines what information is to be returned: either both Q and R
('full', default), only R ('r') or both Q and R but computed in
economy-size ('economic', see Notes). The final option 'raw'
(added in Scipy 0.11) makes the function return two matrices
(Q, TAU) in the internal format used by LAPACK.
Note that full
has different meanings in the two cases, which was one reason for the addition of the modes complete
and reduced
in numpy, plus the fact that numpy did not have a complete
mode ('full' in scipy).