Function aampdist_snippets

tests/naive.py:1712–1787

(
    T,
    m,
    k,
    percentage=1.0,
    s=None,
    mpdist_percentage=0.05,
    mpdist_k=None,
    p=2.0,
)

def aampdist_snippets(
    T,
    m,
    k,
    percentage=1.0,
    s=None,
    mpdist_percentage=0.05,
    mpdist_k=None,
    p=2.0,
):
    D = get_all_aampdist_profiles(T, m, percentage, s, mpdist_percentage, mpdist_k, p=p)

    pad_width = (0, int(m * np.ceil(T.shape[0] / m) - T.shape[0]))
    T_padded = np.pad(T, pad_width, mode="constant", constant_values=np.nan)
    n_padded = T_padded.shape[0]

    snippets = np.empty((k, m))
    snippets_indices = np.empty(k, dtype=np.int64)
    snippets_profiles = np.empty((k, D.shape[-1]))
    snippets_fractions = np.empty(k)
    snippets_areas = np.empty(k)
    Q = np.inf
    indices = np.arange(0, n_padded - m, m)
    snippets_regimes_list = []

    for snippet_idx in range(k):
        min_area = np.inf
        for i in range(D.shape[0]):
            profile_area = np.sum(np.minimum(D[i], Q))
            if min_area > profile_area:
                min_area = profile_area
                idx = i

        snippets[snippet_idx] = T[indices[idx] : indices[idx] + m]
        snippets_indices[snippet_idx] = indices[idx]
        snippets_profiles[snippet_idx] = D[idx]
        snippets_areas[snippet_idx] = np.sum(np.minimum(D[idx], Q))

        Q = np.minimum(D[idx], Q)

    total_min = np.min(snippets_profiles, axis=0)

    for i in range(k):
        mask = snippets_profiles[i] <= total_min
        snippets_fractions[i] = np.sum(mask) / total_min.shape[0]
        total_min = total_min - mask.astype(float)
        slices = _get_mask_slices(mask)
        snippets_regimes_list.append(slices)

    n_slices = []
    for regime in snippets_regimes_list:
        n_slices.append(regime.shape[0])

    snippets_regimes = np.empty((sum(n_slices), 3), dtype=np.int64)
    i = 0
    j = 0
    for n_slice in n_slices:
        for _ in range(n_slice):