'standard' + 'modified' both work fine

'hessian' + 'ltsa' both have issues

ltsa is printing:

RuntimeWarning: Diagonal number 2 is exactly zero. Singular matrix.

and then setting everything to -nan

i tried adding random noise and increasing n_neighbors -- but no dice

Fabian's suggestion is still under review --
https://github.com/scikit-learn/scikit-learn/pull/457



On Thu, Dec 8, 2011 at 11:39 AM, Fabian Pedregosa
<[email protected]> wrote:
> I reduced the problem to a difference of results with eigsh when
> working in shift-invert mode and when not. Notice that the following
> works with sigma=None but not with sigma=0. , thus seems to me that we
> should fall back to non invert-mode for singular matrices (see
> asociated pull request).
>
> ```
> In [8]: M = sparse.csr_matrix([[1, 1, 1], [1, 1, 1], [1, 1, 1.]])
>
> In [9]: linalg.eigsh(M, 1)
> Out[9]:
> (array([ 3.]),
>  array([[-0.57735027],
>       [-0.57735027],
>       [-0.57735027]]))
>
> In [10]: linalg.eigsh(M, 1, sigma=0.)
> ---------------------------------------------------------------------------
> RuntimeError                              Traceback (most recent call last)
> /home/fabian/dev/sandbox/<ipython-input-10-f646f5be93ec> in <module>()
> ----> 1 linalg.eigsh(M, 1, sigma=0.)
>
> /home/fabian/envs/p26/lib/python2.6/site-packages/scipy/sparse/linalg/eigen/arpack/arpack.pyc
> in eigsh(A, k, M, sigma, which, v0, ncv, maxiter, tol,
> return_eigenvectors, Minv, OPinv, mode)
>   1484             if OPinv is None:
>   1485                 Minv_matvec = get_OPinv_matvec(A, M, sigma,
> -> 1486                                                symmetric=True, 
> tol=tol)
>   1487             else:
>   1488                 OPinv = _aslinearoperator_with_dtype(OPinv)
>
> /home/fabian/envs/p26/lib/python2.6/site-packages/scipy/sparse/linalg/eigen/arpack/arpack.pyc
> in get_OPinv_matvec(A, M, sigma, symmetric, tol)
>   1004 def get_OPinv_matvec(A, M, sigma, symmetric=False, tol=0):
>   1005     if sigma == 0:
> -> 1006         return get_inv_matvec(A, symmetric=symmetric, tol=tol)
>   1007
>   1008     if M is None:
>
> /home/fabian/envs/p26/lib/python2.6/site-packages/scipy/sparse/linalg/eigen/arpack/arpack.pyc
> in get_inv_matvec(M, symmetric, tol)
>    997         if isspmatrix_csr(M) and symmetric:
>    998             M = M.T
> --> 999         return SpLuInv(M).matvec
>   1000     else:
>   1001         return IterInv(M, tol=tol).matvec
>
> /home/fabian/envs/p26/lib/python2.6/site-packages/scipy/sparse/linalg/eigen/arpack/arpack.pyc
> in __init__(self, M)
>    890     """
>    891     def __init__(self, M):
> --> 892         self.M_lu = splu(M)
>    893         LinearOperator.__init__(self, M.shape, self._matvec,
> dtype=M.dtype)
>    894         self.isreal = not np.issubdtype(self.dtype, np.complexfloating)
>
> /home/fabian/envs/p26/lib/python2.6/site-packages/scipy/sparse/linalg/dsolve/linsolve.pyc
> in splu(A, permc_spec, diag_pivot_thresh, drop_tol, relax, panel_size,
> options)
>    171         _options.update(options)
>    172     return _superlu.gstrf(N, A.nnz, A.data, A.indices, A.indptr,
> --> 173                           ilu=False, options=_options)
>    174
>    175 def spilu(A, drop_tol=None, fill_factor=None, drop_rule=None,
> permc_spec=None,
>
> RuntimeError: Factor is exactly singular
>
> In [11]:
> ```
>
> ------------------------------------------------------------------------------
> Cloud Services Checklist: Pricing and Packaging Optimization
> This white paper is intended to serve as a reference, checklist and point of
> discussion for anyone considering optimizing the pricing and packaging model
> of a cloud services business. Read Now!
> http://www.accelacomm.com/jaw/sfnl/114/51491232/
> _______________________________________________
> Scikit-learn-general mailing list
> [email protected]
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general

------------------------------------------------------------------------------
Cloud Services Checklist: Pricing and Packaging Optimization
This white paper is intended to serve as a reference, checklist and point of 
discussion for anyone considering optimizing the pricing and packaging model 
of a cloud services business. Read Now!
http://www.accelacomm.com/jaw/sfnl/114/51491232/
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general

Reply via email to