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model.sol(<tag>).feature(<ftag>).createSparseMatrixVal(<mname>,<M>,<N>,<Nnz>,<isReal>) creates a sparse matrix <mname> stored in feature <ftag>. Here, <mname>, is one of “K”, “D”, “E”, “N”, “NF” and <M> is the number of rows, <N> is the number of columns, <Nnz> is the number of nonzeros, and <isReal> is true if the matrix is real.
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model.sol(<tag>).feature(<ftag>).addSparseMatrixVal(<mname>,<row>,<col>,<val>) adds the values stored in <val> to the sparse matrix <mname> stored in feature <ftag>. Here, <mname>, is one of “K”, “D”, “E”, “N”, “NF”, and <row> is the rows, <col> is the columns, and <val> is the values of the entries.
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model.sol(<tag>).feature(<ftag>).createVector(<mname>,<M>,<isReal) creates a vector <mname> stored in feature <ftag>. Here, <mname> is one of “L”, “M”, and <M> is the size of the vector and <isReal> is true if the vector is real.
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model.sol(<tag>).feature(<ftag>).setVector(<mname>,<val>) sets the real part of the vector <mname> stored in feature <ftag>. Here, <mname> is one of “L”, “M”, and <val> is the values to store in the vector.
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model.sol(<tag>).feature(<ftag>).addSparseMatrixValImag(<mname>,<row>,<col>,<val>) creates the imaginary part of the sparse matrix values of matrix <mname> stored in feature <ftag>. Here, <mname> is one of “K”, “D”, “E”, “N”, or “NF”, and <row> is the rows, <col> is the columns, and <val> is the imaginary values of the entries.
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model.sol(<tag>).feature(<ftag>).setVectorImag(<mname>,<val>) sets the imaginary part of the vector <mname> stored in feature <ftag>. Here, <mname> is one of “L”, “M”, and <val> is the imaginary values to store in the vector.
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model.sol(<tag>).feature(<ftag>).setVectorBlock(<mname>,<vals>,<startpos>) sets a subset of the real part of the vector values set by setVector(<mname>,<vals>), the subvector from the position <startpos>. Here, <mname> is one of “L”, “M”.
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