本文整理匯總了Python中sfepy.discrete.Variables.has_virtuals方法的典型用法代碼示例。如果您正苦於以下問題：Python Variables.has_virtuals方法的具體用法？Python Variables.has_virtuals怎麽用？Python Variables.has_virtuals使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類sfepy.discrete.Variables的用法示例。
在下文中一共展示了Variables.has_virtuals方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: Equations
# 需要導入模塊: from sfepy.discrete import Variables [as 別名]
# 或者: from sfepy.discrete.Variables import has_virtuals [as 別名]
#.........這裏部分代碼省略.........
def create_matrix_graph(self, any_dof_conn=False, rdcs=None, cdcs=None,
shape=None, active_only=True, verbose=True):
"""
Create tangent matrix graph, i.e. preallocate and initialize the
sparse storage needed for the tangent matrix. Order of DOF
connectivities is not important.
Parameters
----------
any_dof_conn : bool
By default, only volume DOF connectivities are used, with
the exception of trace surface DOF connectivities. If True,
any kind of DOF connectivities is allowed.
rdcs, cdcs : arrays, optional
Additional row and column DOF connectivities, corresponding
to the variables used in the equations.
shape : tuple, optional
The required shape, if it is different from the shape
determined by the equations variables. This may be needed if
additional row and column DOF connectivities are passed in.
active_only : bool
If True, the matrix graph has reduced size and is created with the
reduced (active DOFs only) numbering.
verbose : bool
If False, reduce verbosity.
Returns
-------
matrix : csr_matrix
The matrix graph in the form of a CSR matrix with
preallocated structure and zero data.
"""
if not self.variables.has_virtuals():
output('no matrix (no test variables)!')
return None
shape = get_default(shape, self.variables.get_matrix_shape())
output('matrix shape:', shape, verbose=verbose)
if nm.prod(shape) == 0:
output('no matrix (zero size)!')
return None
rdcs, cdcs = self.get_graph_conns(any_dof_conn=any_dof_conn,
rdcs=rdcs, cdcs=cdcs,
active_only=active_only)
if not len(rdcs):
output('no matrix (empty dof connectivities)!')
return None
output('assembling matrix graph...', verbose=verbose)
tt = time.clock()
nnz, prow, icol = create_mesh_graph(shape[0], shape[1],
len(rdcs), rdcs, cdcs)
output('...done in %.2f s' % (time.clock() - tt), verbose=verbose)
output('matrix structural nonzeros: %d (%.2e%% fill)' \
% (nnz, float(nnz) / nm.prod(shape)), verbose=verbose)
data = nm.zeros((nnz,), dtype=self.variables.dtype)
matrix = sp.csr_matrix((data, icol, prow), shape)
return matrix