def test_compare_sde_computations(n_samples=1000, n_bins=10):
    y, pred, weights, bins, groups = generate_binned_dataset(n_samples=n_samples, n_bins=n_bins)
    target_efficiencies = RandomState().uniform(size=3)
    a = compute_sde_on_bins(pred[:, 1], mask=(y == 1), bin_indices=bins,
                            target_efficiencies=target_efficiencies, sample_weight=weights)
    b = compute_sde_on_groups(pred[:, 1], mask=(y == 1), groups_indices=groups,
                              target_efficiencies=target_efficiencies, sample_weight=weights)
    assert numpy.allclose(a, b)
Exemple #2
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def test_compare_sde_computations(n_samples=1000, n_bins=10):
    y, pred, weights, bins, groups = generate_binned_dataset(
        n_samples=n_samples, n_bins=n_bins)
    target_efficiencies = RandomState().uniform(size=3)
    a = compute_sde_on_bins(pred[:, 1],
                            mask=(y == 1),
                            bin_indices=bins,
                            target_efficiencies=target_efficiencies,
                            sample_weight=weights)
    b = compute_sde_on_groups(pred[:, 1],
                              mask=(y == 1),
                              groups_indices=groups,
                              target_efficiencies=target_efficiencies,
                              sample_weight=weights)
    assert numpy.allclose(a, b)
def test_cvm_sde_limit(size=2000):
    """ Checks that in the limit CvM coincides with MSE """
    effs = numpy.linspace(0, 1, 2000)
    y_pred = random.uniform(size=size)
    y = random.uniform(size=size) > 0.5
    sample_weight = random.exponential(size=size)
    bin_indices = random.randint(0, 10, size=size)
    y_pred += bin_indices * random.uniform()
    mask = y == 1

    val1 = bin_based_cvm(y_pred[mask], sample_weight=sample_weight[mask], bin_indices=bin_indices[mask])
    val2 = compute_sde_on_bins(y_pred, mask=mask, bin_indices=bin_indices, target_efficiencies=effs,
                               sample_weight=sample_weight)

    assert numpy.allclose(val1, val2 ** 2, atol=1e-3, rtol=1e-2)
Exemple #4
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def test_cvm_sde_limit(size=2000):
    """ Checks that in the limit CvM coincides with MSE """
    effs = numpy.linspace(0, 1, 2000)
    y_pred = random.uniform(size=size)
    y = random.uniform(size=size) > 0.5
    sample_weight = random.exponential(size=size)
    bin_indices = random.randint(0, 10, size=size)
    y_pred += bin_indices * random.uniform()
    mask = y == 1

    val1 = bin_based_cvm(y_pred[mask],
                         sample_weight=sample_weight[mask],
                         bin_indices=bin_indices[mask])
    val2 = compute_sde_on_bins(y_pred,
                               mask=mask,
                               bin_indices=bin_indices,
                               target_efficiencies=effs,
                               sample_weight=sample_weight)

    assert numpy.allclose(val1, val2**2, atol=1e-3, rtol=1e-2)