# Copyright CNRS/Inria/UNS
# Contributor(s): Eric Debreuve (since 2019)
#
# eric.debreuve@cnrs.fr
#
# This software is governed by the CeCILL  license under French law and
# abiding by the rules of distribution of free software.  You can  use,
# modify and/ or redistribute the software under the terms of the CeCILL
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# "http://www.cecill.info".
#
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import brick.processing.dijkstra_1_to_n as dk_
from brick.component.extension import extension_t
from brick.component.soma import soma_t
from brick.general.type import array_t, site_h, site_path_h

import itertools as it_
from typing import Callable, Sequence, Tuple

import cython as cy_
import numpy as np_


def CandidateConnections(
    somas: Sequence[soma_t],
    influence_map: array_t,
    dist_to_closest: array_t,
    extensions: Sequence[extension_t],
    max_straight_sq_dist: cy_.double = np_.inf,
) -> list:
    #
    candidate_conn_nfo = []  # conn=connection

    extensions = filter(lambda ext: ext.is_unconnected, extensions)
    for soma, extension in it_.product(somas, extensions):
        new_candidates = extension.EndPointsForSoma(soma.uid, influence_map)
        candidate_conn_nfo.extend(
            (ep_idx, soma, extension, end_point)
            for ep_idx, end_point in enumerate(new_candidates)
            if dist_to_closest[end_point] <= max_straight_sq_dist
        )
    candidate_conn_nfo.sort(key=lambda elm: dist_to_closest[elm[3]])

    return candidate_conn_nfo


def ShortestPathFromToN(
    point: site_h,
    costs: array_t,
    candidate_points_fct: Callable,
    max_straight_sq_dist: cy_.double = np_.inf,
) -> Tuple[site_path_h, cy_.double]:
    #
    candidate_points, candidate_indexing = candidate_points_fct(
        point, max_straight_sq_dist
    )
    if candidate_points is None:
        return (), np_.inf

    costs[point] = 0.0
    costs[candidate_indexing] = 0.0
    path, length = dk_.DijkstraShortestPath(costs, point, candidate_points)
    costs[point] = np_.inf
    costs[candidate_indexing] = np_.inf

    return path, length