scipy - Preconditioned Conjugate Gradient and LinearOperator in python -


[homework] going solve linear system ax=b preconditioned conjugate gradient method, , use spilu function scipy.sparse.linalg preconditioner. sparse symmetric 162*162 matrix. since spilu gives approximation inverse of a, m approximates a, , spilu(a) gives m^-1, preconditioner. find can directly gives preconditioner in python conjugate gradient function, code below not work.

m_inverse=scipy.sparse.linalg.spilu(a) m2=scipy.sparse.linalg.linearoperator((162,162),m_inverse.solve) x3=scipy.sparse.linalg.cg(a,b,m2) typeerror                                 traceback (most recent call last) <ipython-input-84-86f8f91df8d2> in <module>() ----> 1 x3=scipy.sparse.linalg.cg(a,b,m2)  /users/ruobinghan/anaconda/lib/python3.4/site-packages/scipy/sparse/linalg/isolve/iterative.py in cg(a, b, x0, tol, maxiter, xtype, m, callback)  /users/ruobinghan/anaconda/lib/python3.4/site-packages/scipy/sparse/linalg/isolve/iterative.py in non_reentrant(func, *a, **kw)      83     try:      84         d['__entered'] = true ---> 85         return func(*a, **kw)      86     finally:      87         d['__entered'] = false  /users/ruobinghan/anaconda/lib/python3.4/site-packages/scipy/sparse/linalg/isolve/iterative.py in cg(a, b, x0, tol, maxiter, xtype, m, callback)     219 @non_reentrant     220 def cg(a, b, x0=none, tol=1e-5, maxiter=none, xtype=none, m=none, callback=none): --> 221     a,m,x,b,postprocess = make_system(a,m,x0,b,xtype)     222      223     n = len(b)  /users/ruobinghan/anaconda/lib/python3.4/site-packages/scipy/sparse/linalg/isolve/utils.py in make_system(a, m, x0, b, xtype)     108         x = zeros(n, dtype=xtype)     109     else: --> 110         x = array(x0, dtype=xtype)     111         if not (x.shape == (n,1) or x.shape == (n,)):     112             raise valueerror('a , x have incompatible dimensions')  typeerror: float() argument must string or number, not 'linearoperator'

also, question hints need use linearoperator interface, not understand linearoperator doing , why need here.

any suggestion appreciated! in advance!

i think parameters in wrong order,

x3=scipy.sparse.linalg.cg(a,b,m2)

in error message:

220 def cg(a, b, x0=none, tol=1e-5, maxiter=none, xtype=none, m=none,  callback=none): --> 221     a,m,x,b,postprocess = make_system(a,m,x0,b,xtype)

m2 in place of x0 - initial guess of solution not preconditioner. in host, correct order, class-linearoperator functioning well.

correct version

x3=scipy.sparse.linalg.cg(a,b,m=m2)

please use "key word" arguments possible.


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