Exemple #1
0
def test_glm():
    """
    Test PAC function: GLM
    1. Confirm consistency of output with example data
    2. Confirm PAC=1 when expected
    3. Confirm PAC=0 when expected
    """
    # Load data
    data = np.load(os.path.dirname(pacpy.__file__) + '/tests/exampledata.npy')
    assert np.allclose(
        glm(data, data, (13, 30), (80, 200)), 0.03243, atol=10 ** -5)

    # Test that the GLM function outputs close to 0 and 1 when expected
    lo, hi = genPAC1(glm_bias=True)
    assert glm(lo, hi, (4, 6), (90, 110)) > 0.99

    lo, hi = genPAC0()
    assert glm(lo, hi, (4, 6), (90, 110)) < 0.01
Exemple #2
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def test_glm():
    """
    Test PAC function: GLM
    1. Confirm consistency of output with example data
    2. Confirm PAC=1 when expected
    3. Confirm PAC=0 when expected
    """
    # Load data
    data = np.load(os.path.dirname(pacpy.__file__) + '/tests/exampledata.npy')
    assert np.allclose(glm(data, data, (13, 30), (80, 200)),
                       0.03243,
                       atol=10**-5)

    # Test that the GLM function outputs close to 0 and 1 when expected
    lo, hi = genPAC1(glm_bias=True)
    assert glm(lo, hi, (4, 6), (90, 110)) > 0.99

    lo, hi = genPAC0()
    assert glm(lo, hi, (4, 6), (90, 110)) < 0.01
Exemple #3
0
def test_glm():
    """
    Test PAC function: GLM
    1. Confirm consistency of output with example data
    2. Confirm consistency of output with example data using iir filter
    3. Confirm PAC=1 when expected
    4. Confirm PAC=0 when expected
    """
    # Load data
    data = np.load(os.path.dirname(pacpy.__file__) + '/tests/exampledata.npy')
    assert np.allclose(
        glm(data, data, (13, 30), (80, 200)), 0.03191, atol=10 ** -5)
    assert np.allclose(
        glm(data, data, (13, 30), (80, 200), filterfn=butterf), 0.03476, atol=10 ** -5)

    # Test that the GLM function outputs close to 0 and 1 when expected
    lo, hi = genPAC1(glm_bias=True)
    assert glm(lo, hi, (4, 6), (90, 110)) > 0.99

    lo, hi = genPAC0()
    assert glm(lo, hi, (4, 6), (90, 110)) < 0.01
    
    # Test that Filterfn = False works as expected
    datalo = firf(data, (13,30))
    datahi = firf(data, (80,200))
    pha = np.angle(hilbert(datalo))
    amp = np.abs(hilbert(datahi))
    assert np.allclose(
        glm(pha, amp, (13, 30), (80, 200), filterfn=False),
        glm(data, data, (13, 30), (80, 200)), atol=10 ** -5)