5.0.0

sparse_matrix.i
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			%include "sparse_matrix.hh"

			%pythoncode %{
			import scipy.sparse
			import numpy as _np
			class AkantuSparseMatrix (scipy.sparse.coo_matrix) :

			def __init__(self,aka_sparse):

			self.aka_sparse = aka_sparse
			matrix_type = self.aka_sparse.getSparseMatrixType()
			sz = self.aka_sparse.size()
			row = self.aka_sparse.getIRN()[:,0] -1
			col = self.aka_sparse.getJCN()[:,0] -1
			data = self.aka_sparse.getA()[:,0]

			row = row.copy()
			col = col.copy()
			data = data.copy()

			if matrix_type == _symmetric:
			non_diags = (row != col)
			row_sup = col[non_diags]
			col_sup = row[non_diags]
			data_sup = data[non_diags]
			col = _np.concatenate((col,col_sup))
			row = _np.concatenate((row,row_sup))
			data = _np.concatenate((data,data_sup))

			scipy.sparse.coo_matrix.__init__(self,(data, (row,col)),shape=(sz,sz))

			%}