Ejemplo n.º 1
0
def check_tangent_matrix( conf, vec_x0, fun, fun_grad ):
    """Verify the correctness of the tangent matrix as computed by fun_grad()
    by comparing it with its finite difference approximation evaluated by
    repeatedly calling fun() with vec_x items perturbed by a small delta."""
    vec_x = vec_x0.copy()
    delta = conf.delta

    vec_r = fun( vec_x ) # Update state.
    mtx_a0 = fun_grad( vec_x )

    mtx_a = mtx_a0.tocsc()
    mtx_d = mtx_a.copy()
    mtx_d.data[:] = 0.0

    vec_dx = nm.zeros_like( vec_r )

    for ic in range( vec_dx.shape[0] ):
        vec_dx[ic] = delta
        xx = vec_x.copy() - vec_dx
        vec_r1 = fun( xx )

        vec_dx[ic] = -delta
        xx = vec_x.copy() - vec_dx
        vec_r2 = fun( xx )

        vec_dx[ic] = 0.0;

        vec = 0.5 * (vec_r2 - vec_r1) / delta

##         ir = mtx_a.indices[mtx_a.indptr[ic]:mtx_a.indptr[ic+1]]
##         for ii in ir:
##             mtx_d[ii,ic] = vec[ii]

        ir = mtx_a.indices[mtx_a.indptr[ic]:mtx_a.indptr[ic+1]]
        mtx_d.data[mtx_a.indptr[ic]:mtx_a.indptr[ic+1]] = vec[ir]


    vec_r = fun( vec_x ) # Restore.

    tt = time.clock()
    print mtx_a, '.. analytical'
    print mtx_d, '.. difference'
    import sfepy.base.plotutils as plu
    plu.plot_matrix_diff( mtx_d, mtx_a, delta, ['difference', 'analytical'],
                        conf.check )

    return time.clock() - tt
Ejemplo n.º 2
0
Archivo: nls.py Proyecto: certik/sfepy
def check_tangent_matrix( conf, vec_x0, mtx_a0, evaluator ):
    vec_x = vec_x0.copy()
    delta = conf.delta

    vec_r, status = evaluator.eval_residual( vec_x ) # Update state.
    mtx_a0, status = evaluator.eval_tangent_matrix( vec_x, mtx_a0 )

    mtx_a = mtx_a0.tocsc()
    mtx_d = mtx_a.copy()
    mtx_d.data[:] = 0.0

    vec_dx = nm.zeros_like( vec_r )

    for ic in range( vec_dx.shape[0] ):
        vec_dx[ic] = delta
        xx = vec_x.copy()
        evaluator.update_vec( xx, vec_dx )
        vec_r1, status = evaluator.eval_residual( xx )

        vec_dx[ic] = -delta
        xx = vec_x.copy()
        evaluator.update_vec( xx, vec_dx )
        vec_r2, status = evaluator.eval_residual( xx )

        vec_dx[ic] = 0.0;

        vec = 0.5 * (vec_r2 - vec_r1) / delta

##         ir = mtx_a.indices[mtx_a.indptr[ic]:mtx_a.indptr[ic+1]]
##         for ii in ir:
##             mtx_d[ii,ic] = vec[ii]

        ir = mtx_a.indices[mtx_a.indptr[ic]:mtx_a.indptr[ic+1]]
        mtx_d.data[mtx_a.indptr[ic]:mtx_a.indptr[ic+1]] = vec[ir]


    vec_r, status = evaluator.eval_residual( vec_x ) # Restore.

    tt = time.clock()
    print mtx_a, '.. analytical'
    print mtx_d, '.. difference'
    plu.plot_matrix_diff( mtx_d, mtx_a, delta, ['difference', 'analytical'],
                        conf.check )

    return time.clock() - tt