Matrix
The matrix module defines a number of 2D matrix objects, notably the
SparseMatrix() and DenseMatrix(). Matrix objects support indexed
addition, basic addition and subtraction operations, and provide a consistent
insterface for solving linear systems. Matrices can be converted to numpy arrays
via asarray.
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nutils.matrix.krylov(matvec, b, x0=None, tol=1e-05, restart=None, maxiter=0, precon=None, callback=None)[source]
solve linear system iteratively
restart=None: CG
restart=integer: GMRES
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nutils.matrix.parsecons(constrain, lconstrain, rconstrain, shape)[source]
parse constraints
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class nutils.matrix.Matrix((nrows, ncols))[source]
matrix base class
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cond(constrain=None, lconstrain=None, rconstrain=None)[source]
condition number
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res(x, b=0, constrain=None, lconstrain=None, rconstrain=None)[source]
residual
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class nutils.matrix.DenseSubMatrix(data, indices)[source]
dense but non-contiguous data
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class nutils.matrix.SparseMatrix(graph, ncols=None)[source]
sparse matrix
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reshape((nrows, ncols))[source]
reshape matrix
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clone()[source]
clone matrix
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matvec(other)[source]
matrix-vector multiplication
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T[source]
transpose
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toarray()[source]
convert to numpy array
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todense()[source]
convert to dense matrix
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rowsupp(tol=0)[source]
return row indices with nonzero/non-small entries
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solve(b=0, constrain=None, lconstrain=None, rconstrain=None, tol=0, x0=None, symmetric=False, maxiter=0, restart=999, title='solving system', callback=None, precon=None)[source]
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class nutils.matrix.DenseMatrix(shape)[source]
matrix wrapper class
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clone()[source]
clone matrix
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addblock(rows, cols, vals)[source]
add matrix data
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toarray()[source]
convert to numpy array
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matvec(other)[source]
matrix-vector multiplication
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T[source]
transpose
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solve(b=0, constrain=None, lconstrain=None, rconstrain=None, title='solving system', **dummy)[source]