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How to use the ampligraph.discovery.discovery.query_topn function in ampligraph

To help you get started, we’ve selected a few ampligraph examples, based on popular ways it is used in public projects.

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github Accenture / AmpliGraph / tests / ampligraph / discovery / test_discovery.py View on Github external
['a', 'z', 'f'],
                  ['c', 'z', 'f'],
                  ['b', 'z', 'f'],
                  ])

    model = ComplEx(k=2, batches_count=2)

    with pytest.raises(ValueError): # Model not fitted
        query_topn(model, top_n=2)

    model.fit(X)

    with pytest.raises(ValueError):
        query_topn(model, top_n=2)
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='y', tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='xx', relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='yakkety')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='sax')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', rels_to_consider=['y', 'z'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='f', rels_to_consider=['y', 'z', 'error'])
github Accenture / AmpliGraph / tests / ampligraph / discovery / test_discovery.py View on Github external
with pytest.raises(ValueError): # Model not fitted
        query_topn(model, top_n=2)

    model.fit(X)

    with pytest.raises(ValueError):
        query_topn(model, top_n=2)
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='y', tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='xx', relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='yakkety')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='sax')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', rels_to_consider=['y', 'z'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='f', rels_to_consider=['y', 'z', 'error'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', rels_to_consider='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', ents_to_consider=['zz', 'top'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', ents_to_consider=['a', 'b'])
github Accenture / AmpliGraph / tests / ampligraph / discovery / test_discovery.py View on Github external
['b', 'y', 'a'],
                  ['a', 'y', 'c'],
                  ['c', 'y', 'a'],
                  ['a', 'y', 'd'],
                  ['c', 'x', 'd'],
                  ['b', 'y', 'c'],
                  ['f', 'y', 'e'],
                  ['a', 'z', 'f'],
                  ['c', 'z', 'f'],
                  ['b', 'z', 'f'],
                  ])

    model = ComplEx(k=2, batches_count=2)

    with pytest.raises(ValueError): # Model not fitted
        query_topn(model, top_n=2)

    model.fit(X)

    with pytest.raises(ValueError):
        query_topn(model, top_n=2)
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='y', tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='xx', relation='y')
    with pytest.raises(ValueError):
github Accenture / AmpliGraph / tests / ampligraph / discovery / test_discovery.py View on Github external
model = ComplEx(k=2, batches_count=2)

    with pytest.raises(ValueError): # Model not fitted
        query_topn(model, top_n=2)

    model.fit(X)

    with pytest.raises(ValueError):
        query_topn(model, top_n=2)
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='y', tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='xx', relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='yakkety')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='sax')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', rels_to_consider=['y', 'z'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='f', rels_to_consider=['y', 'z', 'error'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', rels_to_consider='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', ents_to_consider=['zz', 'top'])
github Accenture / AmpliGraph / tests / ampligraph / discovery / test_discovery.py View on Github external
query_topn(model, top_n=2, head='a', tail='e', ents_to_consider=['a', 'b'])

    subj, pred, obj, top_n = 'a', 'x', 'e', 3

    Y, S = query_topn(model, top_n=top_n, head=subj, relation=pred)
    assert len(Y) == len(S)
    assert len(Y) == top_n
    assert np.all(Y[:, 0] == subj)
    assert np.all(Y[:, 1] == pred)

    Y, S = query_topn(model, top_n=top_n, relation=pred, tail=obj)
    assert np.all(Y[:, 1] == pred)
    assert np.all(Y[:, 2] == obj)

    ents_to_con = ['a', 'b', 'c', 'd']
    Y, S = query_topn(model, top_n=top_n, relation=pred, tail=obj, ents_to_consider=ents_to_con)
    assert np.all([x in ents_to_con for x in Y[:, 0]])

    rels_to_con = ['y', 'x']
    Y, S = query_topn(model, top_n=10, head=subj, tail=obj, rels_to_consider=rels_to_con)
    assert np.all([x in rels_to_con for x in Y[:, 1]])

    Y, S = query_topn(model, top_n=10, relation=pred, tail=obj)
    assert all(S[i] >= S[i + 1] for i in range(len(S) - 1))
github Accenture / AmpliGraph / tests / ampligraph / discovery / test_discovery.py View on Github external
with pytest.raises(ValueError):
        query_topn(model, top_n=2)
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='y', tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='xx', relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='yakkety')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='sax')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', rels_to_consider=['y', 'z'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='f', rels_to_consider=['y', 'z', 'error'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', rels_to_consider='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', ents_to_consider=['zz', 'top'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', ents_to_consider=['a', 'b'])

    subj, pred, obj, top_n = 'a', 'x', 'e', 3

    Y, S = query_topn(model, top_n=top_n, head=subj, relation=pred)
    assert len(Y) == len(S)
    assert len(Y) == top_n
github Accenture / AmpliGraph / tests / ampligraph / discovery / test_discovery.py View on Github external
with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='sax')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', rels_to_consider=['y', 'z'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='f', rels_to_consider=['y', 'z', 'error'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', rels_to_consider='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', ents_to_consider=['zz', 'top'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', ents_to_consider=['a', 'b'])

    subj, pred, obj, top_n = 'a', 'x', 'e', 3

    Y, S = query_topn(model, top_n=top_n, head=subj, relation=pred)
    assert len(Y) == len(S)
    assert len(Y) == top_n
    assert np.all(Y[:, 0] == subj)
    assert np.all(Y[:, 1] == pred)

    Y, S = query_topn(model, top_n=top_n, relation=pred, tail=obj)
    assert np.all(Y[:, 1] == pred)
    assert np.all(Y[:, 2] == obj)

    ents_to_con = ['a', 'b', 'c', 'd']
    Y, S = query_topn(model, top_n=top_n, relation=pred, tail=obj, ents_to_consider=ents_to_con)
    assert np.all([x in ents_to_con for x in Y[:, 0]])

    rels_to_con = ['y', 'x']
    Y, S = query_topn(model, top_n=10, head=subj, tail=obj, rels_to_consider=rels_to_con)
    assert np.all([x in rels_to_con for x in Y[:, 1]])
github Accenture / AmpliGraph / tests / ampligraph / discovery / test_discovery.py View on Github external
with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='xx', relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='yakkety')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='sax')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', rels_to_consider=['y', 'z'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='f', rels_to_consider=['y', 'z', 'error'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', rels_to_consider='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', ents_to_consider=['zz', 'top'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', ents_to_consider=['a', 'b'])

    subj, pred, obj, top_n = 'a', 'x', 'e', 3

    Y, S = query_topn(model, top_n=top_n, head=subj, relation=pred)
    assert len(Y) == len(S)
    assert len(Y) == top_n
    assert np.all(Y[:, 0] == subj)
    assert np.all(Y[:, 1] == pred)

    Y, S = query_topn(model, top_n=top_n, relation=pred, tail=obj)
    assert np.all(Y[:, 1] == pred)
    assert np.all(Y[:, 2] == obj)

    ents_to_con = ['a', 'b', 'c', 'd']
    Y, S = query_topn(model, top_n=top_n, relation=pred, tail=obj, ents_to_consider=ents_to_con)
    assert np.all([x in ents_to_con for x in Y[:, 0]])
github Accenture / AmpliGraph / tests / ampligraph / discovery / test_discovery.py View on Github external
with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='y', tail='e')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='xx', relation='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='yakkety')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='sax')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', rels_to_consider=['y', 'z'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='f', rels_to_consider=['y', 'z', 'error'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', rels_to_consider='y')
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', relation='x', ents_to_consider=['zz', 'top'])
    with pytest.raises(ValueError):
        query_topn(model, top_n=2, head='a', tail='e', ents_to_consider=['a', 'b'])

    subj, pred, obj, top_n = 'a', 'x', 'e', 3

    Y, S = query_topn(model, top_n=top_n, head=subj, relation=pred)
    assert len(Y) == len(S)
    assert len(Y) == top_n
    assert np.all(Y[:, 0] == subj)
    assert np.all(Y[:, 1] == pred)

    Y, S = query_topn(model, top_n=top_n, relation=pred, tail=obj)
    assert np.all(Y[:, 1] == pred)
    assert np.all(Y[:, 2] == obj)

    ents_to_con = ['a', 'b', 'c', 'd']
github Accenture / AmpliGraph / tests / ampligraph / discovery / test_discovery.py View on Github external
assert np.all(Y[:, 0] == subj)
    assert np.all(Y[:, 1] == pred)

    Y, S = query_topn(model, top_n=top_n, relation=pred, tail=obj)
    assert np.all(Y[:, 1] == pred)
    assert np.all(Y[:, 2] == obj)

    ents_to_con = ['a', 'b', 'c', 'd']
    Y, S = query_topn(model, top_n=top_n, relation=pred, tail=obj, ents_to_consider=ents_to_con)
    assert np.all([x in ents_to_con for x in Y[:, 0]])

    rels_to_con = ['y', 'x']
    Y, S = query_topn(model, top_n=10, head=subj, tail=obj, rels_to_consider=rels_to_con)
    assert np.all([x in rels_to_con for x in Y[:, 1]])

    Y, S = query_topn(model, top_n=10, relation=pred, tail=obj)
    assert all(S[i] >= S[i + 1] for i in range(len(S) - 1))

ampligraph

A Python library for relational learning on knowledge graphs.

GitHub
Apache-2.0
Latest version published 3 months ago

Package Health Score

75 / 100
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