Module mds_algos

:param ndim: :type ndim: ``int,>0,K``

:param C: :type C: ``array[NxN]``

:rtype: ``array[KxN],directions``

Computes the euclidean distance matrix for the given points.

:param S: :type S: ``array[KxN]``

:rtype: ``array[NxN](>=0)``

:param ndim: :type ndim: ``int,>1,K``

:param C: :type C: ``array[NxN]``

:rtype: ``array[KxN]``

       Best embedding of inner product matrix based on 
       randomized projections. 
   


:param ndim: 
:type ndim:  ``int,>0,K``

:param C: 
:type C:  ``array[NxN]``

:rtype:  ``array[KxN]``

:param ndim: :type ndim: ``int,>0,K``

:param C: :type C: ``array[NxN]``

:rtype: ``array[KxN]``

:param ndim: :type ndim: ``K,int,>=1``

:param D: :type D: ``array[MxM](>=0)``

:rtype: ``array[KxM]``

MDS based on randomized projections.

:param ndim: :type ndim: ``K,int,>=1``

:param D: :type D: ``array[MxM](>=0)``

:rtype: ``array[KxM]``

:param distances: :type distances: ``array[N](>=0)``

:param references: :type references: ``array[KxN]``

:param ndim: :type ndim: ``int,>0,K``

:param C: :type C: ``array[NxN]``

:rtype: ``array[KxN],directions``