On 2012-11-20 18:09, Pauli Virtanen wrote:
> 20.11.2012 15:24, Virgil Stokes kirjoitti:
> [clip]
>> I am aware that they are both correct; but, if you are doing covariance
>> QR decomposition then you almost surely are interested in the positive
>> results (which is the default for MATLAB and most papers/books on this
>> subject).
> I get exactly identical results from MATLAB (R2011b), Octave, Numpy, and
> Scipy. Can you give an example matrix which behaves differently?
>
> Note that Numpy and Scipy return exactly what LAPACK's *GEQRF routines
> give, and Octave seems also to do this.
>
Here are two that had opposite signs compared to MATLAB:
array([[ 7.07106781e+02, -2.32273270e+04, -2.46173719e+04],
[ -3.53553391e+01, -2.31566171e+04, -2.46173719e+04],
[ 2.32273276e+04, -3.97555166e+00, -1.39003725e+03],
[ 2.25202208e+04, -6.48214647e-04, -1.39004432e+03],
[ 2.46527272e+04, 1.31933390e+03, 1.66675481e-19],
[ 2.46173719e+04, 1.39401993e+03, -7.07106781e-03],
[ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00],
[ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00],
[ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00]])
array([[ 3.66711160e+04, 3.36224799e+04, 7.60569110e+02,
-1.19158202e+03],
[ 3.24652853e+03, 0.00000000e+00, -2.32192233e+04,
-2.46276301e+04],
[ -1.71055253e+04, 0.00000000e+00, 0.00000000e+00,
-8.47443620e+01],
[ 1.15905933e+04, -3.36224799e+04, -7.60569110e+02,
1.19158202e+03],
[ -1.72015604e+04, 0.00000000e+00, 2.32192233e+04,
2.46276301e+04],
[ -1.72015604e+04, 0.00000000e+00, 0.00000000e+00,
8.47443620e+01],
[ 3.00000000e+01, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00]])
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