Example #1
0
    def test_simsearchSAX(self):
        db = PersistentDB(schema, 'pk', dbname='testdb', overwrite=True)
        n_add = 50
        mus = np.random.uniform(low=0.0, high=1.0, size=n_add)
        sigs = np.random.uniform(low=0.05, high=0.4, size=n_add)
        jits = np.random.uniform(low=0.05, high=0.2, size=n_add)
        for i, m, s, j in zip(range(n_add), mus, sigs, jits):
            db.insert_ts("ts-{}".format(i), tsmaker(m, s, j))

        m = np.random.uniform(low=0.0, high=1.0)
        s = np.random.uniform(low=0.05, high=0.4)
        j = np.random.uniform(low=0.05, high=0.2)
        query = tsmaker(m, s, j)

        closest = db.simsearch_SAX(query)
Example #2
0
    def test_simsearchSAX(self):
        db = PersistentDB(schema, 'pk', dbname='testdb', overwrite=True)
        n_add = 50
        mus = np.random.uniform(low=0.0, high=1.0, size=n_add)
        sigs = np.random.uniform(low=0.05, high=0.4, size=n_add)
        jits = np.random.uniform(low=0.05, high=0.2, size=n_add)
        for i, m, s, j in zip(range(n_add), mus, sigs, jits):
            db.insert_ts("ts-{}".format(i), tsmaker(m, s, j))

        m = np.random.uniform(low=0.0, high=1.0)
        s = np.random.uniform(low=0.05, high=0.4)
        j = np.random.uniform(low=0.05, high=0.2)
        query = tsmaker(m, s, j)

        closest = db.simsearch_SAX(query)