def get_slip_to_traction(m, tectosaur_cfg):
    import tectosaur
    from tectosaur.ops.sparse_integral_op import make_integral_op
    from tectosaur.constraint_builders import free_edge_constraints, continuity_constraints
    from tectosaur.constraints import build_constraint_matrix
    from tectosaur.ops.mass_op import MassOp
    from scipy.sparse.linalg import spsolve
    pts, tris = m
    tectosaur.logger.setLevel(tectosaur_cfg['log_level'])
    n_dofs = tris.shape[0] * 9
    cs = []
    # cs.extend(traction_continuity_constraints(pts, tris, np.array([])))
    cs = continuity_constraints(tris, np.array([]))
    # cs.extend(free_edge_constraints(tris))
    cm, c_rhs = build_constraint_matrix(cs, n_dofs)
    all_tri_idxs = np.arange(tris.shape[0])
    hypersingular_op = make_integral_op(
        pts, tris, 'elasticH3', [tectosaur_cfg['sm'], tectosaur_cfg['pr']],
        tectosaur_cfg, all_tri_idxs, all_tri_idxs)
    traction_mass_op = MassOp(tectosaur_cfg['quad_mass_order'], pts, tris)
    constrained_traction_mass_op = cm.T.dot(traction_mass_op.mat.dot(cm))

    def slip_to_traction(slip):
        rhs = hypersingular_op.dot(slip.reshape(-1))
        # rhs = cm.dot(cm.T.dot(hypersingular_op.dot(slip.reshape(-1))))
        out = spsolve(traction_mass_op.mat, rhs)
        # out = cm.dot(spsolve(constrained_traction_mass_op, cm.T.dot(rhs)))
        return out

    return slip_to_traction
示例#2
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文件: solve.py 项目: wangyf/tectosaur
def direct_solve(iop, constraints, rhs=None):
    cm, c_rhs = build_constraint_matrix(constraints, iop.shape[0])
    cm = cm.tocsr()
    cmT = cm.T
    iop_constrained = cmT.dot(cmT.dot(iop.mat.T).T)
    if rhs is None:
        rhs_constrained = cmT.dot(-iop.mat.dot(c_rhs))
    else:
        rhs_constrained = cmT.dot(rhs - iop.mat.dot(c_rhs))
    soln_constrained = np.linalg.solve(iop_constrained, rhs_constrained)
    soln = cm.dot(soln_constrained)
    return soln
示例#3
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    def setup_edge_bcs(self):
        cs = free_edge_constraints(self.m.get_tris('fault'))
        cm, c_rhs, _ = build_constraint_matrix(cs, self.m.n_dofs('fault'))

        constrained_slip = np.ones(cm.shape[1])
        self.ones_interior = cm.dot(constrained_slip)

        self.field_inslipdir_interior = self.ones_interior.copy()
        self.field_inslipdir = self.field_inslipdir_interior.copy()
        for d in range(3):
            val = self.cfg.get('slipdir', (1.0, 0.0, 0.0))[d]
            self.field_inslipdir_interior.reshape(-1, 3)[:, d] *= val
            self.field_inslipdir.reshape(-1, 3)[:, d] = val

        self.field_inslipdir_edges = (self.field_inslipdir -
                                      self.field_inslipdir_interior)
示例#4
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文件: solve.py 项目: wangyf/tectosaur
def iterative_solve(iop, constraints, rhs=None, tol=1e-8):
    timer = Timer(output_fnc=logger.debug)
    cm, c_rhs, _ = build_constraint_matrix(constraints, iop.shape[1])
    timer.report('Build constraint matrix')
    cm = cm.tocsr()
    timer.report('constraint matrix tocsr')
    cmT = cm.T
    if rhs is None:
        rhs_constrained = cmT.dot(-iop.dot(c_rhs))
    else:
        rhs_constrained = cmT.dot(rhs - iop.dot(c_rhs))
    timer.report('constrain rhs')

    n = rhs_constrained.shape[0]

    iter = [0]

    def mv(v):
        iter[0] += 1
        logger.debug('iteration # ' + str(iter[0]))
        return cmT.dot(iop.dot(cm.dot(v)))

    # P = sparse.linalg.spilu(cmT.dot(iop.nearfield_no_correction_dot(cm)))
    timer.report("Build preconditioner")

    def prec_f(x):
        # return P.solve(x)
        return x

    M = sparse.linalg.LinearOperator((n, n), matvec=prec_f)
    A = sparse.linalg.LinearOperator((n, n), matvec=mv)

    def report_res(R):
        logger.debug('residual: ' + str(R))
        pass

    soln = sparse.linalg.gmres(A,
                               rhs_constrained,
                               M=M,
                               tol=tol,
                               callback=report_res,
                               restart=200)
    timer.report("GMRES")
    return cm.dot(soln[0]) + c_rhs
示例#5
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def build_system(pts, tris, ops, slip):
    trac_cs = []
    trac_cs.extend(jump_constraints(np.zeros_like(slip), True))

    disp_cs = []
    disp_cs.extend(continuity_constraints(tris, np.array([])))
    disp_cs.extend(jump_constraints(slip, False))

    ND = tris.shape[0] * 9
    n_total_dofs = ND * 4
    cs = build_composite_constraints((trac_cs, 0), (disp_cs, 2 * ND))
    cm, c_rhs = build_constraint_matrix(cs, n_total_dofs)

    chunk_mat = gdbem(ops)
    ops_and_starts = []
    for i in range(4):
        for j in range(4):
            chunk = chunk_mat[i][j]
            if chunk == 0:
                continue
            ops_and_starts.append((chunk, i * ND, j * ND))
    lhs = CompositeOp(*ops_and_starts)
    rhs = -lhs.dot(c_rhs)
    return cm, lhs, rhs
示例#6
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def build_continuity(m, cfg):
    cs = tct.continuity_constraints(m.pts, m.tris, m.tris.shape[0])
    cs.extend(free_edge_constraints(m.get_tris('fault')))
    cm, c_rhs, _ = build_constraint_matrix(cs, m.n_dofs('fault'))
    return cm
示例#7
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import numpy as np
import scipy.sparse
import tectosaur.mesh as mesh
from tectosaur.constraints import constraints, build_constraint_matrix
from tectosaur.dense_integral_op import DenseIntegralOp

sm = 1.0
pr = 0.25
w = 4
corners = [[w, w, 0], [w, -w, 0], [-w, -w, 0], [-w, w, 0]]
m = mesh.make_rect(4, 4, corners)
cs = constraints(m[1], np.empty((0, 3)), m[0])
cm = build_constraint_matrix(cs, m[1].shape[0] * 9)
cm = cm[0].todense()

old_iop = None
for i, nq in enumerate(range(2, 20, 1)):
    eps = (2.0**-np.arange(0, nq)) / (6.7)
    # eps = np.linspace(1.1, 0.9, nq)
    # eps = [1.0, 0.3]
    # eps = np.linspace((1 + nq) / 10.0, 0.1, nq)
    # if i == 0:
    #     eps = [0.2, 0.1]
    # elif i == 1:
    #     eps = [0.2, 0.1, 0.05]
    # elif i == 2:
    #     eps = [0.2, 0.1, 0.05, 0.025]
    # elif i == 3:
    #     eps = [0.2, 0.1, 0.05, 0.025, 0.0125]

    print(eps)
示例#8
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def regularized_tester(K, sep, continuity, mass_op_factor=0.0, which=None):
    if which is None:
        raise Exception('select some operators!')

    n_m = 30
    full_K_name = f'elastic{K}3'
    full_RK_name = f'elasticR{K}3'
    m, surf1_idxs, surf2_idxs = make_meshes(n_m=n_m, sep=sep)
    if sep == 0.0:
        surf2_idxs = surf1_idxs

    near_threshold = 2.0
    nq_near = 5
    nq_far = 2

    if any_nearfield(m[0], m[1], surf1_idxs, surf2_idxs, near_threshold):
        nearfield = True
    else:
        nearfield = False

    def sparse_unregularized(far_op, Kn):
        return SparseIntegralOp(6,
                                nq_far,
                                nq_near,
                                near_threshold,
                                Kn, [1.0, 0.25],
                                m[0],
                                m[1],
                                np.float32,
                                farfield_op_type=far_op,
                                obs_subset=surf1_idxs,
                                src_subset=surf2_idxs)

    def change_K_tri_tri(to):
        def f(*args, to=to):
            args = list(args)
            args[1] = to
            return TriToTriDirectFarfieldOp(*args)

        return f

    def add_sparse_reg(farfield_K, farfield_type):
        ops.append(
            SumOp([
                RegularizedSparseIntegralOp(10,
                                            10,
                                            6,
                                            nq_far,
                                            nq_near,
                                            near_threshold,
                                            full_RK_name,
                                            farfield_K, [1.0, 0.25],
                                            m[0],
                                            m[1],
                                            np.float32,
                                            farfield_type,
                                            obs_subset=surf1_idxs,
                                            src_subset=surf2_idxs),
                MultOp(MassOp(3, m[0], m[1][surf1_idxs]), mass_op_factor)
            ]))

    ops = [sparse_unregularized(PtToPtDirectFarfieldOp, full_K_name)]

    if 'pt_to_pt_fmm' in which:
        ops.append(
            sparse_unregularized(PtToPtFMMFarfieldOp(150, 2.5, 5),
                                 full_K_name))

    if 'tri_farfield_regularized' in which:
        ops.append(
            sparse_unregularized(change_K_tri_tri(full_RK_name), full_K_name))

    if 'dense_regularized' in which:
        ops.append(
            SumOp([
                RegularizedDenseIntegralOp(10,
                                           10,
                                           6,
                                           nq_far,
                                           nq_near,
                                           near_threshold,
                                           full_RK_name,
                                           full_RK_name, [1.0, 0.25],
                                           m[0],
                                           m[1],
                                           np.float32,
                                           obs_subset=surf1_idxs,
                                           src_subset=surf2_idxs),
                MultOp(MassOp(3, m[0], m[1][surf1_idxs]), mass_op_factor)
            ]))

    if 'sparse_regularized' in which:
        add_sparse_reg(full_RK_name, TriToTriDirectFarfieldOp)

    if 'sparse_regularized_fmm' in which:
        add_sparse_reg(full_K_name, PtToPtFMMFarfieldOp(150, 2.5, 5))

    if 'sparse_regularized_but_unregularized_far':
        add_sparse_reg(full_K_name, change_K_tri_tri(full_K_name))

    print('built ops')

    x = build_x_field(m, surf1_idxs, surf2_idxs)
    x_flat = x.flatten()
    outs = [o.dot(x_flat) for o in ops]

    if continuity:
        from tectosaur.constraint_builders import continuity_constraints, \
            free_edge_constraints
        from tectosaur.constraints import build_constraint_matrix
        cs = continuity_constraints(m[1][surf1_idxs], np.array([]))
        cs.extend(free_edge_constraints(m[1][surf1_idxs]))
        cm, c_rhs = build_constraint_matrix(cs, outs[0].shape[0])
        final_outs = [cm.T.dot(v) for v in outs]
        plot_outs = [cm.dot(v) for v in final_outs]
    else:
        plot_outs = outs
        final_outs = outs

    should_plot = True
    if should_plot:
        plot_fnc(m, surf1_idxs, surf2_idxs, x, plot_outs)

    for i in range(len(final_outs)):
        for j in range(i + 1, len(final_outs)):
            print(i, j, final_outs[i] / final_outs[j])
            np.testing.assert_almost_equal(final_outs[i], final_outs[j], 6)