Beispiel #1
0
def logm(A,disp=1):
    """Matrix logarithm, inverse of expm."""
    # Compute using general funm but then use better error estimator and
    #   make one step in improving estimate using a rotation matrix.
    A = mat(asarray(A))
    F, errest = funm(A,log,disp=0)
    errtol = 1000*eps
    # Only iterate if estimate of error is too large.
    if errest >= errtol:
        # Use better approximation of error
        errest = norm(expm(F)-A,1) / norm(A,1)
        if not isfinite(errest) or errest >= errtol:
            N,N = A.shape
            X,Y = ogrid[1:N+1,1:N+1]
            R = mat(orth(eye(N,dtype='d')+X+Y))
            F, dontcare = funm(R*A*R.H,log,disp=0)
            F = R.H*F*R
            if (norm(imag(F),1)<=1000*errtol*norm(F,1)):
                F = mat(real(F))
            E = mat(expm(F))
            temp = mat(solve(E.T,(E-A).T))
            F = F - temp.T
            errest = norm(expm(F)-A,1) / norm(A,1)
    if disp:
        if not isfinite(errest) or errest >= errtol:
            print "Result may be inaccurate, approximate err =", errest
        return F
    else:
        return F, errest
Beispiel #2
0
def logm(A,disp=1):
    """Compute matrix logarithm.

    The matrix logarithm is the inverse of expm: expm(logm(A)) == A

    Parameters
    ----------
    A : array, shape(M,M)
        Matrix whose logarithm to evaluate
    disp : boolean
        Print warning if error in the result is estimated large
        instead of returning estimated error. (Default: True)

    Returns
    -------
    logA : array, shape(M,M)
        Matrix logarithm of A

    (if disp == False)
    errest : float
        1-norm of the estimated error, ||err||_1 / ||A||_1

    """
    # Compute using general funm but then use better error estimator and
    #   make one step in improving estimate using a rotation matrix.
    A = mat(asarray(A))
    F, errest = funm(A,log,disp=0)
    errtol = 1000*eps
    # Only iterate if estimate of error is too large.
    if errest >= errtol:
        # Use better approximation of error
        errest = norm(expm(F)-A,1) / norm(A,1)
        if not isfinite(errest) or errest >= errtol:
            N,N = A.shape
            X,Y = ogrid[1:N+1,1:N+1]
            R = mat(orth(eye(N,dtype='d')+X+Y))
            F, dontcare = funm(R*A*R.H,log,disp=0)
            F = R.H*F*R
            if (norm(imag(F),1)<=1000*errtol*norm(F,1)):
                F = mat(real(F))
            E = mat(expm(F))
            temp = mat(solve(E.T,(E-A).T))
            F = F - temp.T
            errest = norm(expm(F)-A,1) / norm(A,1)
    if disp:
        if not isfinite(errest) or errest >= errtol:
            print "Result may be inaccurate, approximate err =", errest
        return F
    else:
        return F, errest