#!/usr/bin/env python
from nose.tools import *
from nose import SkipTest
from nose.plugins.attrib import attr
import networkx

# Example from
# A. Langville and C. Meyer, "A survey of eigenvector methods of web
# information retrieval."  http://citeseer.ist.psu.edu/713792.html


class TestHITS:

    def setUp(self):
        
        G=networkx.DiGraph()

        edges=[(1,3),(1,5),\
           (2,1),\
           (3,5),\
           (5,4),(5,3),\
           (6,5)]
           
        G.add_edges_from(edges,weight=1)
        self.G=G
        self.G.a=dict(zip(sorted(G),[0.000000, 0.000000, 0.366025,
                             0.133975, 0.500000, 0.000000]))
        self.G.h=dict(zip(sorted(G),[ 0.366025, 0.000000, 0.211325, 
                              0.000000, 0.211325, 0.211325]))


    def test_hits(self):
        G=self.G
        h,a=networkx.hits(G,tol=1.e-08)
        for n in G:
            assert_almost_equal(h[n],G.h[n],places=4)
        for n in G:
            assert_almost_equal(a[n],G.a[n],places=4)

    def test_hits_nstart(self):
        G = self.G
        nstart = dict([(i, 1./2) for i in G])
        h, a = networkx.hits(G, nstart = nstart)

    @attr('numpy')
    def test_hits_numpy(self):
        try:
            import numpy as np
        except ImportError:
            raise SkipTest('NumPy not available.')


        G=self.G
        h,a=networkx.hits_numpy(G)
        for n in G:
            assert_almost_equal(h[n],G.h[n],places=4)
        for n in G:
            assert_almost_equal(a[n],G.a[n],places=4)


    def test_hits_scipy(self):
        try:
            import scipy as sp
        except ImportError:
            raise SkipTest('SciPy not available.')

        G=self.G
        h,a=networkx.hits_scipy(G,tol=1.e-08)
        for n in G:
            assert_almost_equal(h[n],G.h[n],places=4)
        for n in G:
            assert_almost_equal(a[n],G.a[n],places=4)


    @attr('numpy')
    def test_empty(self):
        try:
            import numpy
        except ImportError:
            raise SkipTest('numpy not available.')
        G=networkx.Graph()
        assert_equal(networkx.hits(G),({},{}))
        assert_equal(networkx.hits_numpy(G),({},{}))
        assert_equal(networkx.authority_matrix(G).shape,(0,0))
        assert_equal(networkx.hub_matrix(G).shape,(0,0))

    def test_empty_scipy(self):
        try:
            import scipy
        except ImportError:
            raise SkipTest('scipy not available.')
        G=networkx.Graph()
        assert_equal(networkx.hits_scipy(G),({},{}))


    @raises(networkx.PowerIterationFailedConvergence)
    def test_hits_not_convergent(self):
        G = self.G
        networkx.hits(G, max_iter=0)