ublas_pkg_usage.pycmd

// ublas_pkg_usage.pycmd
// 
// Copyright (c) 2014 - Michele De Stefano (micdestefano@users.sourceforge.net)
// 
// Distributed under the MIT License (See accompanying file LICENSE)


/**
 * \example    ublas_pkg_usage.pycmd
 * 
 * Shows the usage of the ublas_pkg_usage extension from the Python prompt.
 * Furthermore, it shows how to reuse classes wrapped by the
 * mds_utils.ublas.ublas.py module.
 *
 * Before using the ublas_pkg_usage module, ensure that your
 * PYTHONPATH environment variable contains the path to reach the
 * mds_utils Python package. For example, if the mds_utils package has
 * been built but not installed yet, it is typically found into the
 * mds-utils/python/build/lib.linux-<arch>-<Python version> directory
 * (for a Linux build) and you have to add this path to your PYTHONPATH
 * variable. After that, you can import the ublas_pkg_usage module and
 * try it.
 */

>>> import ublas_pkg_usage as ubpu
>>> v = ubpu.create_vector()
>>> v
<mds_utils.ublas.ublas.vector_d; proxy of <Swig Object of type 'boost::numeric::ublas::vector< double > *' at 0x7f9257478ea0> >
>>> print(v)
[3](1.1,2.2,3.3)
>>> v.__str__
<bound method vector_d.__str__ of <mds_utils.ublas.ublas.vector_d; proxy of <Swig Object of type 'boost::numeric::ublas::vector< double > *' at 0x7f9257478ea0> >>
>>> v.__str__()
'[3](1.1,2.2,3.3)'
>>> v.to_array()
array([ 1.1,  2.2,  3.3])
>>> [t for t in v]
[1.1, 2.2, 3.3]
>>> M = ubpu.create_compressed_matrix()
>>> M
<mds_utils.ublas.ublas.compressed_matrix_drow; proxy of <Swig Object of type 'boost::numeric::ublas::compressed_matrix< double,boost::numeric::ublas::row_major > *' at 0x22171e0> >
>>> print(M)
[4,3]((0,0,2.2),(1.1,0,0),(0,0,0),(0,3.3,0))
>>> sp_M = M.to_sparse_mtx()
>>> sp_M
<4x3 sparse matrix of type '<type 'numpy.float64'>'
   with 3 stored elements in Compressed Sparse Row format>
>>> sp_M.todense()
matrix([[ 0. ,  0. ,  2.2],
        [ 1.1,  0. ,  0. ],
        [ 0. ,  0. ,  0. ],
        [ 0. ,  3.3,  0. ]])
>>> M.to_dense()
array([[ 0. ,  0. ,  2.2],
       [ 1.1,  0. ,  0. ],
       [ 0. ,  0. ,  0. ],
       [ 0. ,  3.3,  0. ]])
>>> v1 = ubpu.my_vec()
>>> import numpy as np
>>> v1.from_array(np.array([11.1,22.2,33.3]))
>>> print(v1)
[3](11.1,22.2,33.3)
>>> v1[0]
11.1
>>> v1[1]
22.2