def precompute_optimzation_S(laplacian_matrix,n_samples,relaxation_kwds):
relaxation_kwds.setdefault('<STR_LIT>',False)<EOL>relaxation_kwds.setdefault('<STR_LIT>','<STR_LIT>')<EOL>relaxation_kwds.setdefault('<STR_LIT>',False)<EOL>if relaxation_kwds['<STR_LIT>']:<EOL><INDENT>print ('<STR_LIT>')<EOL>print ('<STR_LIT>')<EOL><DEDENT>A, pairs = makeA(laplacian_matrix)<EOL>if relaxation_kwds['<STR_LIT>']:<EOL><INDENT>print ('<STR_LIT>')<EOL><DEDENT>Rk_tensor, nbk = compute_Rk(laplacian_matrix,A,n_samples)<EOL>ATAinv = np.linalg.pinv(A.T.dot(A).todense())<EOL>if relaxation_kwds['<STR_LIT>']:<EOL><INDENT>print ('<STR_LIT>')<EOL><DEDENT>if relaxation_kwds['<STR_LIT>']:<EOL><INDENT>raise NotImplementedError('<STR_LIT>')<EOL><DEDENT>return { '<STR_LIT>': Rk_tensor, '<STR_LIT>': nbk,<EOL>'<STR_LIT>': ATAinv, '<STR_LIT>': pairs, '<STR_LIT:A>': A }<EOL>
compute Rk, A, ATAinv, neighbors and pairs for projected mode