在MATLAB / Octave中交替使用spsolve和spdiag

Question

I have a python code which I am trying to convert to Matlab code. The code is for baseline correction for a wave.

def baseline_als(y, lam, p, niter=20):
    L = len(y)
    D = sparse.csc_matrix(np.diff(np.eye(L), 2))
    w = np.ones(L)
    for i in xrange(niter):
        W = sparse.spdiags(w, 0, L, L)
        Z = W + lam * D.dot(D.transpose())
        z = spsolve(Z, w*y)
        w = p * (y > z) + (1-p) * (y < z)
    return z

I have tried it converting like this.

function [z] = baseline_als(y, lam, p, niter=20)
    L = len(y)
    D = sparse.csc_matrix(diff(eye(L), 2))
    w = ones(L)
    for i = 1:niter
        W = sparse.spdiags(w, 0, L, L) %Not working
        Z = W + lam * dot(D,transpose(D))
        z = spsolve(Z, w*y) % Not working
        w = p * (y > z) + (1-p) * (y < z)
    end % End of For loop
end % End of function

However there are no functions named spsolve and spdiag in octave/matlab. Is there any alternate function that I can use?

Answer 1

Its quite easy if you know what spsolve does . Lets focus on that, as spidiag seems easier to solve , doesn't it?

spsolve "Solve the sparse linear system Ax=b, where b may be a vector or a matrix."

This is exactly what MATLABs \\ or mldivide does, it solves a system of Ax=b, for x. Happily for you, MATLAB can deal with both sparse and dense matrix with the same function, thus the change shoudl be as easy as:

from:

z = spsolve(Z, w*y)

to:

z= Z\(w*y);