def test_correlate_all():
    tstamps, Trace, previous_stamps, Count_zh, Count_sz, count_h, count_z, \
            prob_topics_aux, Theta_zh, Psi_sz, hyper2id, source2id = \
            dataio.initialize_trace(files.SIZE10, 2, 10)

    C = dynamic.correlate_counts(Count_zh, Count_sz, count_h, count_z, .1, \
            .1)

    assert_equal((2, 2), C.shape)
    assert C[0, 1] != 0
    assert (np.tril(C) == 0).all()
Пример #2
0
def test_correlate_all():
    tstamps, Trace, previous_stamps, Count_zh, Count_sz, count_h, count_z, \
            prob_topics_aux, Theta_zh, Psi_sz, hyper2id, source2id = \
            dataio.initialize_trace(files.SIZE10, 2, 10)
 
    C = dynamic.correlate_counts(Count_zh, Count_sz, count_h, count_z, .1, \
            .1)

    assert_equal((2, 2), C.shape)
    assert C[0, 1] != 0
    assert (np.tril(C) == 0).all()
def test_merge():
    tstamps, Trace, previous_stamps, Count_zh, Count_sz, count_h, count_z, \
            prob_topics_aux, Theta_zh, Psi_sz, hyper2id, source2id = \
            dataio.initialize_trace(files.SIZE10, 2, 10)

    kernel = ECCDFKernel()
    kernel.build(Trace.shape[0], Count_zh.shape[0], \
            np.array([1.0, Count_zh.shape[0] - 1]))

    Trace[:, 0] = 0
    Trace[:, 1] = 0
    Trace[:, 2] = 0
    Trace[:, 3] = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1]

    Count_sz[:] = 0
    Count_zh[:] = 0
    count_z[:] = 0
    count_h[:] = 0

    fast_populate(Trace, Count_zh, Count_sz, count_h, count_z)
    C = dynamic.correlate_counts(Count_zh, Count_sz, count_h, count_z, .1, \
            .1)

    alpha_zh, beta_zs, beta_zd = [0.1] * 3
    a_ptz = 1.0
    b_ptz = Count_zh.shape[0] - 1

    ll_per_z = np.zeros(2, dtype='f8')

    quality_estimate(tstamps, Trace, \
                previous_stamps, Count_zh, Count_sz, count_h, \
                count_z, alpha_zh, beta_zd, ll_per_z, \
                np.arange(Trace.shape[0], dtype='i4'), kernel)

    Trace_new, Count_zh_new, Count_sz_new, \
            count_z_new, new_stamps, _ = \
            dynamic.merge(tstamps, Trace, previous_stamps, Count_zh, Count_sz, \
            count_h, count_z, alpha_zh, beta_zs, ll_per_z, kernel)

    print(Trace_new)
    print(np.array(new_stamps._get_all(0)))
    assert len(new_stamps._get_all(0)) == 10
    assert Count_zh_new.shape[0] < Count_zh.shape[0]
    assert Count_zh_new.shape[1] == Count_zh.shape[1]

    assert Count_sz_new.shape[0] == Count_sz.shape[0]
    assert Count_sz_new.shape[1] < Count_sz.shape[0]

    assert count_z_new.shape[0] < count_z.shape[0]
Пример #4
0
def test_merge():
    tstamps, Trace, previous_stamps, Count_zh, Count_sz, count_h, count_z, \
            prob_topics_aux, Theta_zh, Psi_sz, hyper2id, source2id = \
            dataio.initialize_trace(files.SIZE10, 2, 10)
     
    kernel = ECCDFKernel()
    kernel.build(Trace.shape[0], Count_zh.shape[0], \
            np.array([1.0, Count_zh.shape[0] - 1]))
    
    Trace[:, 0] = 0
    Trace[:, 1] = 0
    Trace[:, 2] = 0
    Trace[:, 3] = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1]

    Count_sz[:] = 0
    Count_zh[:] = 0
    count_z[:] = 0
    count_h[:] = 0
    
    fast_populate(Trace, Count_zh, Count_sz, count_h, count_z)
    C = dynamic.correlate_counts(Count_zh, Count_sz, count_h, count_z, .1, \
            .1)
    
    alpha_zh, beta_zs, beta_zd = [0.1] * 3
    a_ptz = 1.0
    b_ptz = Count_zh.shape[0] - 1

    ll_per_z = np.zeros(2, dtype='f8')

    quality_estimate(tstamps, Trace, \
                previous_stamps, Count_zh, Count_sz, count_h, \
                count_z, alpha_zh, beta_zd, ll_per_z, \
                np.arange(Trace.shape[0], dtype='i4'), kernel)
    
    Trace_new, Count_zh_new, Count_sz_new, \
            count_z_new, new_stamps, _ = \
            dynamic.merge(tstamps, Trace, previous_stamps, Count_zh, Count_sz, \
            count_h, count_z, alpha_zh, beta_zs, ll_per_z, kernel)
    
    print(Trace_new)
    print(np.array(new_stamps._get_all(0)))
    assert len(new_stamps._get_all(0)) == 10
    assert Count_zh_new.shape[0] < Count_zh.shape[0]
    assert Count_zh_new.shape[1] == Count_zh.shape[1]

    assert Count_sz_new.shape[0] == Count_sz.shape[0]
    assert Count_sz_new.shape[1] < Count_sz.shape[0]

    assert count_z_new.shape[0] < count_z.shape[0]