>>> run init.py
>>> np.loadtxt('ex7_py.txt')
array([[0., 0., 1., 1., 3., 4.],
       [1., 4., 2., 5., 4., 5.],
       [1., 1., 1., 1., 1., 1.]])
>>> X = np.loadtxt('ex7_py.txt')
>>> S = coo((X[2,:], (X[0,:],X[1,:])),shape=(6,6))
>>> B = S.todense()
>>> print(B)
>>> import networkx as nx
>>> G = nx.from_scipy_sparse_array(S)
>>> nx.draw(G,with_labels=True)
>>> plt.show()
>>> import scipy.io
>>> X =  scipy.io.loadmat('Bmat.mat')
>>> X.items
<function dict.items>
>>> X.items()
dict_items([('__header__', b'MATLAB 5.0 MAT-file, Platform: SOL2, Created on: Thu Oct  4 20:19:16 2001'), ('__version__', '1.0'), ('__globals__', []), ('Problem', array([[(array(['1SYMMETRIC MATRIX, FE APPROXIMATION TO BIHARMONIC OPERATOR ON PLATE     '],
              dtype='<U72'), <Compressed Sparse Column sparse matrix of dtype '>f8'
        	with 15844 stored elements and shape (960, 960)>, array(['HB/nos3'], dtype='<U7')) ]],
      dtype=[('title', 'O'), ('A', 'O'), ('name', 'O')]))])
>>> T = Bmat['Problem']
>>> T = X['Problem']
>>> T.items()
>>> S = T[0,0][];
>>> S = T[0,0][1];
>>> print(S)
>>> G = nx.from_scipy_sparse_array(S)
>>> nx.draw(G,with_labels=False)
>>> plt.show()
>>> plt.show()
>>> nx.draw(G,with_labels=False)
>>> plt.show()
>>> history -o -p -f  Sep16_py