Python beta_dist Examples

Example #1

def test_beta_dist():
    du2 = [randn(n_features, 1) for i in range(n_kernels)]
    for i in range(len(du2)):
        du2[i] /= norm(du2[i])

    assert_equal(0., beta_dist(du, du))
    assert_not_equal(0., beta_dist(du, du2))

    du2 = [randn(n_features + 2, 1) for i in range(n_kernels)]
    for i in range(len(du2)):
        du2[i] /= norm(du2[i])
    assert_raises(ValueError, beta_dist, du, du2)

Example #2

File: test_dict_metrics.py Project: sylvchev/mdla

def test_beta_dist():
    du2 = [randn(n_features, 1) for i in range(n_kernels)]
    for i in range(len(du2)):
        du2[i] /= norm(du2[i])

    assert_equal(0., beta_dist(du, du))
    assert_not_equal(0., beta_dist(du, du2))

    du2 = [randn(n_features+2, 1) for i in range(n_kernels)]
    for i in range(len(du2)):
        du2[i] /= norm(du2[i])
    assert_raises(ValueError, beta_dist, du, du2)

Example #3

File: experiment_dictionary_recovering.py Project: sylvchev/mdla

def callback_recovery(loc):
    d = loc['dict_obj']
    d.wc.append(emd(loc['dictionary'], d.generating_dict, 
                    'chordal', scale=True))
    d.wfs.append(emd(loc['dictionary'], d.generating_dict, 
                     'fubinistudy', scale=True))
    d.hc.append(hausdorff(loc['dictionary'], d.generating_dict, 
                          'chordal', scale=True))
    d.hfs.append(hausdorff(loc['dictionary'], d.generating_dict, 
                           'fubinistudy', scale=True))
    d.bd.append(beta_dist(d.generating_dict, loc['dictionary']))
    d.dr99.append(detection_rate(loc['dictionary'],
                                d.generating_dict, 0.99))
    d.dr97.append(detection_rate(loc['dictionary'],
                                d.generating_dict, 0.97))

Example #4

File: experiment_dictionary_recovering.py Project: sylvchev/mdla

def callback_recovery(loc):
    d = loc["dict_obj"]
    d.wc.append(
        emd(loc["dictionary"], d.generating_dict, "chordal", scale=True))
    d.wfs.append(
        emd(loc["dictionary"], d.generating_dict, "fubinistudy", scale=True))
    d.hc.append(
        hausdorff(loc["dictionary"], d.generating_dict, "chordal", scale=True))
    d.hfs.append(
        hausdorff(loc["dictionary"],
                  d.generating_dict,
                  "fubinistudy",
                  scale=True))
    d.bd.append(beta_dist(d.generating_dict, loc["dictionary"]))
    d.dr99.append(detection_rate(loc["dictionary"], d.generating_dict, 0.99))
    d.dr97.append(detection_rate(loc["dictionary"], d.generating_dict, 0.97))

Example #5

def test_beta_dict_length():
    du2 = [randn(n_features, 1) for i in range(n_kernels + 2)]
    for i in range(len(du2)):
        du2[i] /= norm(du2[i])

    assert_not_equal(0., beta_dist(du, du2))

Example #6

File: test_dict_metrics.py Project: sylvchev/mdla

def test_beta_dict_length():
    du2 = [randn(n_features, 1) for i in range(n_kernels+2)]
    for i in range(len(du2)):
        du2[i] /= norm(du2[i])
        
    assert_not_equal(0., beta_dist(du, du2))