def get_vectors(self, nodes, region, field, filename=None):
normals = compute_nodal_normals(nodes, region, field)
if filename is not None:
_save_vectors(filename, normals, region, field.domain.mesh, 'n')
return normals
def __init__(self, name, regions, dof_names, dof_map_fun,
filename, variables, ts=None, functions=None):
MRLCBCOperator.__init__(self, name, regions, dof_names, dof_map_fun,
variables, functions=functions)
self.filename = filename
dim = self.region.dim
assert_(len(self.dof_names) == dim)
normals = compute_nodal_normals(self.mdofs, self.region, self.field)
can_save = (ts is None) or ((ts is not None) and ts.step == 0)
if can_save and self.filename is not None:
_save_vectors(self.filename, normals, self.region,
self.field.domain.mesh, 'n')
ii = nm.abs(normals).argmax(1)
n_nod, dim = normals.shape
irs = set(range(dim))
data = []
rows = []
cols = []
for idim in range(dim):
ic = nm.where(ii == idim)[0]
if len(ic) == 0: continue
ir = list(irs.difference([idim]))
nn = nm.empty((len(ic), dim - 1), dtype=nm.float64)
for ik, il in enumerate(ir):
nn[:,ik] = - normals[ic,il] / normals[ic,idim]
irn = dim * ic + idim
ics = [(dim - 1) * ic + ik for ik in range(dim - 1)]
for ik in range(dim - 1):
rows.append(irn)
cols.append(ics[ik])
data.append(nn[:,ik])
ones = nm.ones((nn.shape[0],), dtype=nm.float64)
for ik, il in enumerate(ir):
rows.append(dim * ic + il)
cols.append(ics[ik])
data.append(ones)
rows = nm.concatenate(rows)
cols = nm.concatenate(cols)
data = nm.concatenate(data)
n_np_dof = n_nod * (dim - 1)
mtx = sp.coo_matrix((data, (rows, cols)), shape=(n_nod * dim, n_np_dof))
self.n_mdof = n_nod * dim
self.n_new_dof = n_np_dof
self.mtx = mtx.tocsr()
def __init__(self, name, nodes, region, field, dof_names, filename=None):
Struct.__init__(self, name=name, nodes=nodes, dof_names=dof_names)
dim = region.dim
assert_(len(dof_names) == dim)
normals = compute_nodal_normals(nodes, region, field)
if filename is not None:
_save_vectors(filename, normals, region, field.domain.mesh, 'n')
ii = nm.abs(normals).argmax(1)
n_nod, dim = normals.shape
irs = set(range(dim))
data = []
rows = []
cols = []
for idim in xrange(dim):
ic = nm.where(ii == idim)[0]
if len(ic) == 0: continue
ir = list(irs.difference([idim]))
nn = nm.empty((len(ic), dim - 1), dtype=nm.float64)
for ik, il in enumerate(ir):
nn[:, ik] = -normals[ic, il] / normals[ic, idim]
irn = dim * ic + idim
ics = [(dim - 1) * ic + ik for ik in xrange(dim - 1)]
for ik in xrange(dim - 1):
rows.append(irn)
cols.append(ics[ik])
data.append(nn[:, ik])
ones = nm.ones((nn.shape[0], ), dtype=nm.float64)
for ik, il in enumerate(ir):
rows.append(dim * ic + il)
cols.append(ics[ik])
data.append(ones)
rows = nm.concatenate(rows)
cols = nm.concatenate(cols)
data = nm.concatenate(data)
n_np_dof = n_nod * (dim - 1)
mtx = sp.coo_matrix((data, (rows, cols)),
shape=(n_nod * dim, n_np_dof))
self.n_dof = n_np_dof
self.mtx = mtx.tocsr()
def __init__(self, name, nodes, region, field, dof_names, filename=None):
Struct.__init__(self, name=name, nodes=nodes, dof_names=dof_names)
dim = region.dim
assert_(len(dof_names) == dim)
normals = compute_nodal_normals(nodes, region, field)
if filename is not None:
_save_vectors(filename, normals, region, field.domain.mesh, 'n')
ii = nm.abs(normals).argmax(1)
n_nod, dim = normals.shape
irs = set(range(dim))
data = []
rows = []
cols = []
for idim in xrange(dim):
ic = nm.where(ii == idim)[0]
if len(ic) == 0: continue
ir = list(irs.difference([idim]))
nn = nm.empty((len(ic), dim - 1), dtype=nm.float64)
for ik, il in enumerate(ir):
nn[:,ik] = - normals[ic,il] / normals[ic,idim]
irn = dim * ic + idim
ics = [(dim - 1) * ic + ik for ik in xrange(dim - 1)]
for ik in xrange(dim - 1):
rows.append(irn)
cols.append(ics[ik])
data.append(nn[:,ik])
ones = nm.ones((nn.shape[0],), dtype=nm.float64)
for ik, il in enumerate(ir):
rows.append(dim * ic + il)
cols.append(ics[ik])
data.append(ones)
rows = nm.concatenate(rows)
cols = nm.concatenate(cols)
data = nm.concatenate(data)
n_np_dof = n_nod * (dim - 1)
mtx = sp.coo_matrix((data, (rows, cols)), shape=(n_nod * dim, n_np_dof))
self.n_dof = n_np_dof
self.mtx = mtx.tocsr()
