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))

	%}