Specifying coupling between fields/components in create_sparsity_pattern
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…tern`
This patch implements a new keyword argument `coupling` to
`create_sparsity_pattern` where the coupling between fields or
components in the DofHandler can be specified. `coupling` should be a
matrix of booleans, where rows are test functions and columns the
unknowns. Consider for example a system with (u, p) as unknowns, and (v,
q) as the corresponding test functions. If there is no coupling between
e.g. p and q the coupling matrix would be
u p
-------------
v | true true
q | true false
i.e. `coupling = [true true; true false]`. The coupling can also be
specified component wise (if one of the fields have multiple
components). For example, if (u, v) have two components, the equivalent
coupling specified by components would be
u1 u2 p
------------------
v1 | true true true
v2 | true true true
q | true true false
The resulting sparsity pattern will not have entries for components that
do not couple. By default full coupling is assumed (just like
before).
The new functionality is used in the stokes-flow.jl example, where there
are no coupling between test- and trial functions for the pressure.
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This patch implements a new keyword argument
couplingtocreate_sparsity_patternwhere the coupling between fields or components in the DofHandler can be specified.couplingshould be a matrix of booleans, where rows are test functions and columns the unknowns. Consider for example a system with (u, p) as unknowns, and (v, q) as the corresponding test functions. If there is no coupling between e.g. p and q the coupling matrix would bei.e.
coupling = [true true; true false]. The coupling can also be specified component wise (if one of the fields have multiple components). For example, if (u, v) have two components, the equivalent coupling specified by components would beThe resulting sparsity pattern will not have entries for components that do not couple. By default full coupling is assumed (just like before).