# encoding: utf-8
"""
leuvenmapmatching.matcher.base
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Base Matcher and Matching classes.

:author: Wannes Meert
:copyright: Copyright 2015-2018 DTAI, KU Leuven and Sirris.
:license: Apache License, Version 2.0, see LICENSE for details.
"""
from __future__ import print_function

import math
import sys
import logging
import time
from collections import OrderedDict, defaultdict, namedtuple
MYPY = False
if MYPY:
    from typing import List, Tuple, Dict, Any
from typing import Optional, Set

import numpy as np

from ..util.segment import Segment
from ..util import approx_equal, approx_leq


logger = logging.getLogger("be.kuleuven.cs.dtai.mapmatching")
approx_value = 0.0000000001
ema_const = namedtuple('EMAConst', ['prev', 'cur'])(0.7, 0.3)
default_label_width = 25


class BaseMatching(object):
    """Matching object that represents a node in the Viterbi lattice."""
    __slots__ = ['matcher', 'edge_m', 'edge_o',
                 'logprob', 'logprobema', 'logprobe', 'logprobne',
                 'obs', 'obs_ne', 'dist_obs',
                 'prev', 'prev_other', 'stop', 'length']

    def __init__(self, matcher: 'BaseMatcher', edge_m: Segment, edge_o: Segment,
                 logprob=-np.inf, logprobema=-np.inf, logprobe=-np.inf, logprobne=-np.inf,
                 dist_obs: float=0.0, obs: int=0, obs_ne: int=0,
                 prev: Optional[Set['BaseMatching']]=None, stop: bool=False, length: int=1,
                 **_kwargs):
        self.edge_m: Segment = edge_m
        self.edge_o: Segment = edge_o
        self.logprob: float = logprob        # max probability
        self.logprobe: float = logprobe      # Emitting
        self.logprobne: float = logprobne    # Non-emitting
        self.logprobema: float = logprobema  # exponential moving average log probability  # TODO: Not used anymore?
        self.obs: int = obs  # reference to path entry index (observation)
        self.obs_ne: int = obs_ne  # number of non-emitting states for this observation
        self.dist_obs: float = dist_obs  # Distance between map point and observation
        self.prev: Set[BaseMatching] = set() if prev is None else prev  # Previous best matching objects
        self.prev_other: Set[BaseMatching] = set()  # Previous matching objects with lower logprob
        self.stop: bool = stop
        self.length: int = length
        self.matcher: BaseMatcher = matcher

    def next(self, edge_m: Segment, edge_o: Segment, obs: int=0, obs_ne: int=0):
        """Create a next lattice Matching object with this Matching object as the previous one in the lattice."""
        new_stop = False
        if edge_m.is_point() and edge_o.is_point():
            # node to node
            dist = self.matcher.map.distance(edge_m.p1, edge_o.p1)
            proj_m = edge_m.p1
            proj_o = edge_o.pi
        elif edge_m.is_point() and not edge_o.is_point():
            # node to edge
            dist, proj_o, t_o = self.matcher.map.distance_point_to_segment(edge_m.p1, edge_o.p1, edge_o.p2)
            proj_m = edge_m.p1
            edge_o.pi = proj_o
            edge_o.ti = t_o
        elif not edge_m.is_point() and edge_o.is_point():
            # edge to node
            dist, proj_m, t_m = self.matcher.map.distance_point_to_segment(edge_o.p1, edge_m.p1, edge_m.p2)
            if not self.matcher.only_edges and (approx_equal(t_m, 0.0) or approx_equal(t_m, 1.0)):
                if __debug__ and logger.isEnabledFor(logging.DEBUG):
                    logger.debug(f"   | Stopped trace: Too close to end, {t_m}")
                    new_stop = True
                else:
                    return None
            edge_m.pi = proj_m
            edge_m.ti = t_m
            proj_o = edge_o.pi
        elif not edge_m.is_point() and not edge_o.is_point():
            # edge to edge
            dist, proj_m, proj_o, t_m, t_o = self.matcher.map.distance_segment_to_segment(edge_m.p1, edge_m.p2,
                                                                                          edge_o.p1, edge_o.p2)
            edge_m.pi = proj_m
            edge_m.ti = t_m
            edge_o.pi = proj_o
            edge_o.ti = t_o
        else:
            raise Exception(f"Should not happen")

        logprob_trans, props_trans = self.matcher.logprob_trans(self, edge_m, edge_o,
                                                                is_prev_ne=(self.obs_ne != 0),
                                                                is_next_ne=(obs_ne != 0))
        logprob_obs, props_obs = self.matcher.logprob_obs(dist, self, edge_m, edge_o,
                                                          is_ne=(obs_ne != 0))
        new_logprob_delta = logprob_trans + logprob_obs
        if obs_ne == 0:
            new_logprobe = self.logprob + new_logprob_delta
            new_logprobne = 0
            new_logprob = new_logprobe
            new_length = self.length + 1
        else:
            # "* e^(ne_length_factor_log)" or "- ne_length_factor_log" for every step to a non-emitting
            # state to prefer shorter paths
            new_logprobe = self.logprobe + self.matcher.ne_length_factor_log
            new_logprobne = self.logprobne + new_logprob_delta
            # "+ 1" to punish non-emitting states a bit less. Otherwise it would be
            # similar to (Pr_tr*Pr_obs)**2, which punishes just one non-emitting state too much.
            new_logprob = new_logprobe + new_logprobne / (obs_ne + 1)
            new_length = self.length
        new_logprobema = ema_const.cur * new_logprob_delta + ema_const.prev * self.logprobema
        new_stop |= self.matcher.do_stop(new_logprob / new_length, dist, logprob_trans, logprob_obs)
        if not new_stop or (__debug__ and logger.isEnabledFor(logging.DEBUG)):
            m_next = self.__class__(self.matcher, edge_m, edge_o,
                                    logprob=new_logprob, logprobne=new_logprobne,
                                    logprobe=new_logprobe, logprobema=new_logprobema,
                                    obs=obs, obs_ne=obs_ne, prev={self}, dist_obs=dist,
                                    stop=new_stop, length=new_length, **props_trans, **props_obs)
            return m_next
        else:
            return None

    @classmethod
    def first(cls, logprob_init, edge_m, edge_o, matcher, dist_obs):
        """Create an initial lattice Matching object."""
        logprob_obs, props_obs = matcher.logprob_obs(dist_obs, None, edge_m, edge_o)
        logprob = logprob_init + logprob_obs
        new_stop = matcher.do_stop(logprob, dist_obs, logprob_init, logprob_obs)
        if not new_stop or logger.isEnabledFor(logging.DEBUG):
            m_next = cls(matcher, edge_m=edge_m, edge_o=edge_o,
                         logprob=logprob, logprobema=logprob, logprobe=logprob, logprobne=0,
                         dist_obs=dist_obs, obs=0, stop=new_stop, **props_obs)
            return m_next
        else:
            return None

    def update(self, m_next):
        """Update the current entry if the new matching object is better.

        :param m_next: The new matching object representing the same node in the lattice.
        :return: True if the current object is replaced, False otherwise
        """
        # if self.length != m_next.length:
        #     slogprob_norm = self.logprob / self.length
        #     nlogprob_norm = m_next.logprob / m_next.length
        # else:
        #     slogprob_norm = self.logprob
        #     nlogprob_norm = m_next.logprob
        # if (self.stop == m_next.stop and slogprob_norm < nlogprob_norm) or (self.stop and not m_next.stop):
        #     self._update_inner(m_next)
        #     return True
        # elif abs(slogprob_norm - nlogprob_norm) < approx_value and self.stop == m_next.stop:
        #     self.prev.update(m_next.prev)
        #     self.stop = m_next.stop
        #     return False
        assert self.length == m_next.length
        if (self.stop and not m_next.stop) or (self.stop == m_next.stop and self.logprob < m_next.logprob):
            self._update_inner(m_next)
            return True
        else:
            self.prev_other.update(m_next.prev)
            return False

    def _update_inner(self, m_other: 'BaseMatching'):
        self.edge_m = m_other.edge_m
        self.edge_o = m_other.edge_o
        self.logprob = m_other.logprob
        self.logprobe = m_other.logprobe
        self.logprobne = m_other.logprobne
        self.logprobema = m_other.logprobema
        self.dist_obs = m_other.dist_obs
        self.obs = m_other.obs
        self.obs_ne = m_other.obs_ne
        self.prev_other.update(self.prev)  # Do we use this?
        self.prev = m_other.prev
        self.stop = m_other.stop
        self.length = m_other.length

    def is_nonemitting(self):
        return self.obs_ne != 0

    def is_emitting(self):
        return self.obs_ne == 0

    def last_emitting_logprob(self):
        if self.is_emitting():
            return self.logprob
        elif self.prev is None or len(self.prev) == 0:
            return 0
        else:
            return next(iter(self.prev)).last_emitting_logprob()

    def __str__(self, label_width=None):
        stop = "x" if self.stop else ""
        if label_width is None:
            label_width = default_label_width
        repr_tmpl = "{:<2} | {:<"+str(label_width)+"} | {:10.5f} | {:10.5f} | {:10.5f} | {:10.5f} | " +\
                    "{:<3} | {:10.5f} | {:<" + str(label_width) + "} |"
        return repr_tmpl.format(stop, self.label, self.logprob, self.logprob / self.length,
                                self.logprobema, self.logprobne, self.obs,
                                self.dist_obs, ",".join([str(prev.label) for prev in self.prev]))

    @staticmethod
    def repr_header(label_width=None, stop=""):
        if label_width is None:
            label_width = default_label_width
        repr_tmpl = "{:<2} | {:<"+str(label_width)+"} | {:<10} | {:<10} | {:<10} | {:<10} | " + \
                    "{:<3} | {:<10} | {:<"+str(label_width)+"} |"
        return repr_tmpl.format(stop, "", "lg(Pr)", "nlg(Pr)", "slg(Pr)", "lg(Pr-ne)", "obs", "d(obs)", "prev")

    @staticmethod
    def repr_static(fields, label_width=None):
        if label_width is None:
            label_width = default_label_width
        default_fields = ["", "", float('nan'), float('nan'), float('nan'), float('nan'), "", float('nan'), "", ""]
        repr_tmpl = "{:<2} | {:<" + str(label_width) + "} | {:10.5f} | {:10.5f} | {:10.5f} | {:10.5f} | " + \
                    "{:<3} | {:10.5f} | {:<" + str(label_width) + "} |"
        if len(fields) < 8:
            fields = list(fields) + default_fields[len(fields):]
        return repr_tmpl.format(*fields)

    @property
    def label(self):
        if self.edge_m.p2 is None:
            return "{}---{}-{}".format(self.edge_m.l1, self.obs, self.obs_ne)
        else:
            return "{}-{}-{}-{}".format(self.edge_m.l1, self.edge_m.l2, self.obs, self.obs_ne)

    @property
    def cname(self):
        if self.edge_m.l2 is None:
            return "{}_{}_{}".format(self.edge_m.l1, self.obs, self.obs_ne)
        else:
            return "{}_{}_{}_{}".format(self.edge_m.l1, self.edge_m.l2, self.obs, self.obs_ne)

    @property
    def key(self):
        """Key that indicates the node or edge, observation and non-emitting step.
        This is the unique key that is used in the lattice.
        """
        if self.edge_m.l2 is None:
            return tuple([self.edge_m.l1, self.obs, self.obs_ne])
        else:
            return tuple([self.edge_m.l1, self.edge_m.l2, self.obs, self.obs_ne])

    @property
    def shortkey(self):
        """Key that indicates the node or edge. Irrespective of the current observation."""
        if self.edge_m.l2 is None:
            return self.edge_m.l1
        else:
            return tuple([self.edge_m.l1, self.edge_m.l2])

    @property
    def nodes(self):
        if self.edge_m.l2 is None:
            return [self.edge_m.l1]
        else:
            return [self.edge_m.l1, self.edge_m.l2]

    def __hash__(self):
        return self.cname.__hash__()


class BaseMatcher:

    def __init__(self, map_con, obs_noise=1, max_dist_init=None, max_dist=None, min_prob_norm=None,
                 non_emitting_states=True, max_lattice_width=None,
                 only_edges=True, obs_noise_ne=None, matching=BaseMatching,
                 non_emitting_length_factor=0.75, **kwargs):
        """Initialize a matcher for map matching.

        Distances are in meters when using latitude-longitude.

        :param map_con: Map object to connect to map database
        :param obs_noise: Standard deviation of noise
        :param obs_noise_ne: Standard deviation of noise for non-emitting states (is set to obs_noise if not give)
        :param max_dist_init: Maximum distance from start location (if not given, uses max_dist)
        :param max_dist: Maximum distance from path (this is a hard cut, min_prob_norm should be better)
        :param min_prob_norm: Minimum normalized probability of observations (ema)
        :param non_emitting_states: Allow non-emitting states. A non-emitting state is a state that is
            not associated with an observation. Here we assume it can be associated with a location in between
            two observations to allow for pruning. It is advised to set min_prob_norm and/or max_dist to avoid
            visiting all possible nodes in the graph.
        :param max_lattice_width: Restrict the lattice (or possible candidate states per observation) to this value.
            If there are more possible next states, the states with the best likelihood so far are selected.
        :param only_edges: Do not include nodes as states, only edges. This is the typical setting for HMM methods.
        :param matching: Matching type
        :param non_emitting_length_factor: Reduce the probability of a sequence of non-emitting states the longer it
            is. This can be used to prefer shorter paths. This is separate from the transition probabilities because
            transition probabilities are averaged for non-emitting states and thus the length is also averaged out.

        To define a custom transition and/or emission probability distribtion, overwrite the following functions:

        - :meth:`logprob_trans`
        - :meth:`logprob_obs`

        """
        self.map = map_con
        if max_dist:
            self.max_dist = max_dist
        else:
            self.max_dist = np.inf
        if max_dist_init:
            self.max_dist_init = max_dist_init
        else:
            self.max_dist_init = self.max_dist
        if min_prob_norm:
            self.min_logprob_norm = math.log(min_prob_norm)
        else:
            self.min_logprob_norm = -np.inf
        logger.debug(f"Matcher.min_logprob_norm = {self.min_logprob_norm}, Matcher.max_dist = {self.max_dist}")
        self.obs_noise = obs_noise
        if obs_noise_ne is None:
            self.obs_noise_ne = obs_noise
        else:
            self.obs_noise_ne = obs_noise_ne

        self.path = None
        self.lattice = None  # dict[idx,dict[label,Matching]]
        self.lattice_best = None
        self.node_path = None
        self.matching = matching
        self.non_emitting_states = non_emitting_states
        self.non_emitting_states_maxnb = 100
        self.max_lattice_width = max_lattice_width
        self.only_edges = only_edges

        # Penalties
        self.ne_length_factor_log = math.log(non_emitting_length_factor)

    def logprob_trans(self, prev_m, edge_m, edge_o,
                      is_prev_ne=False, is_next_ne=False):
        # type: (BaseMatcher, BaseMatching, Segment, Segment, bool, bool) -> Tuple[float, Dict[str, Any]]
        """Transition probability.

        Note: In contrast with a regular HMM, this cannot be a probability density function, it needs
              to be a proper probability (thus values between 0.0 and 1.0).

        :return: probability, properties that are passed to the matching object
        """
        return 0, {}  # All probabilities are 1 (thus technically not a distribution)

    def logprob_obs(self, dist, prev_m, new_edge_m, new_edge_o, is_ne=False):
        """Emission probability.

        Note: In contrast with a regular HMM, this cannot be a probability density function, it needs
              to be a proper probability (thus values between 0.0 and 1.0).

        :return: probability, properties that are passed to the matching object
        """
        return 0, {}

    def match_gpx(self, gpx_file, unique=True):
        """Map matching from a gpx file"""
        from ..util.gpx import gpx_to_path
        path = gpx_to_path(gpx_file)
        return self.match(path, unique=unique)

    def do_stop(self, logprob_norm, dist, logprob_trans, logprob_obs):
        if logprob_norm < self.min_logprob_norm:
            logger.debug(f"   | Stopped trace: norm(log(Pr)) too small: {logprob_norm} < {self.min_logprob_norm}"
                         f"  -- lPr_t = {logprob_trans:.3f}, lPr_o = {logprob_obs:.3f}")
            return True
        if dist > self.max_dist:
            logger.debug(f"   | Stopped trace: distance too large: {dist} > {self.max_dist}")
            return True
        return False

    def _insert(self, m_next):
        if m_next.key in self.lattice[m_next.obs]:
            self.lattice[m_next.obs][m_next.key].update(m_next)
        else:
            self.lattice[m_next.obs][m_next.key] = m_next
        return self.lattice[m_next.obs][m_next.key]

    def match(self, path, unique=False, tqdm=None):
        """Dynamic Programming based (HMM-like) map matcher.

        If the matcher fails to match the entire path, the last matched index is returned.
        This index can be used to run the matcher again from that observation onwards.

        :param path: list[Union[tuple[lat, lon], tuple[lat, lon, time]]
        :param unique: Only retain unique nodes in the sequence (avoid repetitions)
        :param tqdm: Use a tqdm progress reporter (default is None)
        :return: Tuple of (List of state keys, index of last observation that was matched)
        """
        if __debug__:
            logger.debug("Start matching path of length {}".format(len(path)))

        # Initialisation
        self.path = path
        nb_start_nodes = self._create_start_nodes(use_edges=self.only_edges)
        if nb_start_nodes == 0:
            self.lattice_best = []
            return [], 0

        # Start iterating over observations 1..end
        t_start = time.time()
        iterator = range(1, len(path))
        if tqdm:
            iterator = tqdm(iterator)
        early_stop_idx = None
        for obs_idx in iterator:
            if __debug__:
                logger.debug("--- obs {} --- {} ---".format(obs_idx, self.path[obs_idx]))
            cnt_lat_size_not_zero = False
            for m_tmp in self.lattice[obs_idx - 1].values():
                if not m_tmp.stop:
                    cnt_lat_size_not_zero = True
                    break
            # if len(self.lattice[obs_idx - 1]) == 0:
            if not cnt_lat_size_not_zero:
                if __debug__:
                    logger.debug("No solutions found anymore")
                early_stop_idx = obs_idx
                logger.info(f'Stopped early at observation {early_stop_idx}')
                break
            self._match_states(obs_idx)
            if self.non_emitting_states:
                # Fill in non-emitting states between previous and current observation
                self._match_non_emitting_states(obs_idx - 1)
            if __debug__ and logger.isEnabledFor(logging.DEBUG):
                self.print_lattice(obs_idx=obs_idx, label_width=default_label_width)
                logger.debug(f"--- end obs {obs_idx} ---")

        t_delta = time.time() - t_start
        logger.info("--- end ---")
        logger.info("Build lattice in {} seconds".format(t_delta))

        # Backtrack to find best path
        if early_stop_idx:
            if early_stop_idx <= 1:
                self.lattice_best = []
                return [], 0
            start_idx = early_stop_idx - 2
        else:
            start_idx = len(self.path) - 1
        node_path = self._build_node_path(start_idx, unique)
        return node_path, start_idx

    def match_incremental(self, path, unique=True, tqdm=None, backtrace_len=None):
        """Dynamic Programming based (HMM-like) map matcher, continue building lattice with the new path.

        If the matcher fails to match the entire path, the last matched index is returned.
        This index can be used to run the matcher again from that observation onwards.

        :param path: list[Union[tuple[lat, lon], tuple[lat, lon, time]]
        :param unique: Only retain unique nodes in the sequence (avoid repetitions)
        :param tqdm: Use a tqdm progress reporter (default is None)
        :param backtrace_len: Length of the computed path throught the lattice.
          If None the path through the lattice will the length of the last given path.
          If -1, the full path is computed.
        :return: Tuple of (List of state keys, index of last observation that was matched)
        """
        if __debug__:
            logger.debug("Incrementally match path of length {}".format(len(path)))

        # Initialisation
        if self.path is None:
            start_obs_idx = 1
            self.path = path
            nb_start_nodes = self._create_start_nodes()
            if nb_start_nodes == 0:
                return [], 0
        else:
            start_obs_idx = len(self.path)
            for idx in range(len(self.path)):
                self.lattice[start_obs_idx + idx] = dict()
            self.path += path

        # Start iterating over observations 1..end
        t_start = time.time()
        iterator = range(start_obs_idx, len(self.path))
        if tqdm:
            iterator = tqdm(iterator)
        early_stop_idx = None
        for obs_idx in iterator:
            if __debug__:
                logger.debug(f"--- obs {obs_idx} --- {self.path[obs_idx]} ---")
            cnt_lat_size_not_zero = False
            for m_tmp in self.lattice[obs_idx - 1].values():
                if not m_tmp.stop:
                    cnt_lat_size_not_zero = True
                    break
            # if len(self.lattice[obs_idx - 1]) == 0:
            if not cnt_lat_size_not_zero:
                if __debug__:
                    logger.debug("No solutions found anymore")
                early_stop_idx = obs_idx
                logger.info(f'Stopped early at observation {early_stop_idx}')
                break
            self._match_states(obs_idx)
            if self.non_emitting_states and not self._skip_ne_states(obs_idx):
                # Fill in non-emitting states between previous and current observation
                self._match_non_emitting_states(obs_idx - 1)
            if __debug__:
                if logger.isEnabledFor(logging.DEBUG):
                    self.print_lattice(obs_idx=obs_idx, label_width=default_label_width)

        t_delta = time.time() - t_start
        logger.info("Build lattice in {} seconds".format(t_delta))

        # Backtrack to find best path
        if early_stop_idx:
            if early_stop_idx <= 1:
                return [], 0
            start_idx = early_stop_idx - 2
        else:
            start_idx = len(self.path) - 1
        if backtrace_len is None:
            max_depth = len(path)
        elif backtrace_len == -1:
            max_depth = None
        else:
            max_depth = backtrace_len
        node_path = self._build_node_path(start_idx, unique, max_depth=max_depth)
        return node_path, start_idx

    def _skip_ne_states(self, prev_m):
        # type: (BaseMatcher, BaseMatching) -> bool
        return False

    def _create_start_nodes(self, use_edges=True):
        """

        :return: Number of created start points.
        """
        # Initialisation on first observation
        t_start = time.time()
        self.lattice = dict()
        for idx in range(len(self.path)):
            self.lattice[idx] = dict()

        if use_edges:
            nodes = self.map.edges_closeto(self.path[0], max_dist=self.max_dist_init)
        else:
            nodes = self.map.nodes_closeto(self.path[0], max_dist=self.max_dist_init)
        if __debug__:
            logger.debug("--- obs {} --- {} ---".format(0, self.path[0]))
        t_delta = time.time() - t_start
        logger.info("Initialized map with {} starting points in {} seconds".format(len(nodes), t_delta))
        if len(nodes) == 0:
            logger.info(f'Stopped early at observation 0'
                        f', no starting points/edges x found for which '
                        f'|x - ({self.path[0][0]:.2f},{self.path[0][1]:.2f})| < {self.max_dist_init}')
            return 0
        if __debug__:
            logger.debug(self.matching.repr_header())
        logprob_init = 0  # math.log(1.0/len(nodes))
        if use_edges:
            # Search for nearby edges
            for dist_obs, label1, loc1, label2, loc2, pi, ti in nodes:
                if label2 == label1:
                    continue
                edge_m = Segment(label1, loc1, label2, loc2, pi, ti)
                edge_o = Segment(f"O{0}", self.path[0])
                m_next = self.matching.first(logprob_init, edge_m, edge_o, self, dist_obs)
                if m_next is not None:
                    if m_next.key in self.lattice[0]:
                        self.lattice[0][m_next.key].update(m_next)
                    else:
                        self.lattice[0][m_next.key] = m_next
                    if __debug__:
                        logger.debug(str(m_next))
        else:
            # Search for nearby nodes
            for dist_obs, label, loc in nodes:
                edge_m = Segment(label, loc)
                edge_o = Segment(f"O{0}", self.path[0])
                m_next = self.matching.first(logprob_init, edge_m, edge_o, self, dist_obs)
                if m_next is not None:
                    self.lattice[0][m_next.key] = m_next
                    if __debug__:
                        logger.debug(str(m_next))
        if self.max_lattice_width:
            self._prune_lattice(0)
            # if self.non_emitting_states:
            #     self._match_non_emitting_states(0, path)
        return len(self.lattice[0])

    def _match_states(self, obs_idx):
        """

        :param obs_idx:
        :return: True is new states have been found, False otherwise.
        """
        prev_lattice = [m for m in self.lattice[obs_idx - 1].values() if not m.stop]
        count = 0
        for m in prev_lattice:  # type: BaseMatching
            if m.stop:
                continue
            count += 1
            if m.edge_m.is_point():
                # == Move to neighbour from node ==
                nbrs = self.map.nodes_nbrto(m.edge_m.l1)
                # print("Neighbours for {}: {}".format(m, nbrs))
                if nbrs is None:
                    if __debug__:
                        logger.debug("No neighbours found for node {}".format(m.edge_m.l1))
                    continue
                if __debug__:
                    logger.debug("   Move to {} neighbours from node {}".format(len(nbrs), m.edge_m.l1))
                    logger.debug(m.repr_header())
                for nbr_label, nbr_loc in nbrs:
                    # === Move from node to node (or stay on node) ===
                    if not self.only_edges:
                        edge_m = Segment(nbr_label, nbr_loc)
                        edge_o = Segment(f"O{obs_idx}", self.path[obs_idx])
                        m_next = m.next(edge_m, edge_o, obs=obs_idx)
                        if m_next is not None:
                            self._insert(m_next)
                            if __debug__:
                                logger.debug(str(m_next))

                    # === Move from node to edge ===
                    if m.edge_m.l1 != nbr_label:
                        edge_m = Segment(m.edge_m.l1, m.edge_m.p1, nbr_label, nbr_loc)
                        edge_o = Segment(f"O{obs_idx}", self.path[obs_idx])
                        m_next = m.next(edge_m, edge_o, obs=obs_idx)
                        if m_next is not None:
                            self._insert(m_next)
                            if __debug__:
                                logger.debug(str(m_next))
                    else:
                        if __debug__:
                            logger.debug(self.matching.repr_static(('x', f'{nbr_label}-{nbr_label} <')))

            else:
                # == Move to neighbour from edge ==
                if __debug__:
                    logger.debug("   + Move to neighbour from edge {}".format(m.label))
                    logger.debug(m.repr_header())

                # === Stay on edge ===
                edge_m = Segment(m.edge_m.l1, m.edge_m.p1, m.edge_m.l2, m.edge_m.p2)
                edge_o = Segment(f"O{obs_idx}", self.path[obs_idx])
                m_next = m.next(edge_m, edge_o, obs=obs_idx)
                if m_next is not None:
                    self._insert(m_next)
                    if __debug__:
                        logger.debug(str(m_next))

                # === Move from edge to node ===
                if not self.only_edges:
                    edge_m = Segment(m.edge_m.l2, m.edge_m.p2)
                    edge_o = Segment(f"O{obs_idx}", self.path[obs_idx])
                    m_next = m.next(edge_m, edge_o, obs=obs_idx)
                    if m_next is not None:
                        self._insert(m_next)
                        if __debug__:
                            logger.debug(str(m_next))

                else:
                    # === Move from edge to next edge ===
                    nbrs = self.map.edges_nbrto((m.edge_m.l1, m.edge_m.l2))
                    if nbrs is None or len(nbrs) == 0:
                        if __debug__:
                            logger.debug(f"No neighbours found for edge {m.edge_m.label}")
                        continue
                    for nbr_label1, nbr_loc1, nbr_label2, nbr_loc2 in nbrs:
                        if m.edge_m.l2 != nbr_label2 and m.edge_m.l1 != nbr_label2:  # same edge is different action
                            edge_m = Segment(nbr_label1, nbr_loc1, nbr_label2, nbr_loc2)
                            edge_o = Segment(f"O{obs_idx}", self.path[obs_idx])
                            m_next = m.next(edge_m, edge_o, obs=obs_idx)
                            if m_next is not None:
                                self._insert(m_next)
                                if __debug__:
                                    logger.debug(str(m_next))
        if self.max_lattice_width:
            self._prune_lattice(obs_idx)
        if count == 0:
            if __debug__:
                logger.debug("No active solution found anymore")
            return False
        return True

    def _match_non_emitting_states(self, obs_idx):
        """Match sequences of nodes that all refer to the same observation at obs_idx.

        Assumptions:
        This method assumes that the lattice is filled up for both obs_idx and obs_idx + 1.

        :param obs_idx: Index of the first observation used (the second will be obs_idx + 1)
        :return: None
        """
        obs = self.path[obs_idx]
        if obs_idx < len(self.path) - 1:
            obs_next = self.path[obs_idx + 1]
        else:
            obs_next = None
        # The current states are the current observation's states
        cur_lattice = dict((m.key, m) for m in self.lattice[obs_idx].values() if not m.stop)
        lattice_toinsert = list()
        # The current best states are the next observation's states if you would ignore non-emitting states
        lattice_best = dict((m.shortkey, m)
                            for m in self.lattice[obs_idx + 1].values() if not m.stop)
        lattice_ne = set(m.shortkey
                         for m in self.lattice[obs_idx + 1].values() if not m.stop and self._skip_ne_states(m))
        # cur_lattice = set(self.lattice[obs_idx].values())
        nb_ne = 0
        while len(cur_lattice) > 0 and nb_ne < self.non_emitting_states_maxnb:
            nb_ne += 1
            if __debug__:
                logger.debug("--- obs {}:{} --- {} - {} ---".format(obs_idx, nb_ne, obs, obs_next))
            cur_lattice = self._match_non_emitting_states_inner(cur_lattice, obs_idx, obs, obs_next, nb_ne,
                                                                lattice_toinsert, lattice_best, lattice_ne)
            # Link to next observation
            self._match_non_emitting_states_end(cur_lattice, obs_idx + 1, obs_next,
                                                lattice_toinsert, lattice_best)
            if self.max_lattice_width is not None and len(cur_lattice) > self.max_lattice_width:
                ms = sorted(cur_lattice.values(), key=lambda t: t.logprob, reverse=True)
                cur_lattice = dict()
                for m in ms[:self.max_lattice_width]:
                    cur_lattice[m.key] = m
        # logger.info('Used {} levels of non-emitting states'.format(nb_ne))
        for m in lattice_toinsert:
            self._insert(m)

    def _node_in_prev_ne(self, m_next, label):
        """Is the given node already visited in the chain of non-emitting states.

        :param m_next:
        :param label: Node label
        :return: True or False
        """
        # for m in itertools.chain(m_next.prev, m_next.prev_other):
        for m in m_next.prev:  # type: BaseMatching
            if m.obs != m_next.obs:
                return False
            assert(m_next.obs_ne != m.obs_ne)
            # print('prev', m.shortkey, 'checking for ', label)
            # if label == m.shortkey:
            if label in m.nodes:
                return True
            if m.obs_ne == 0:
                return False
            if self._node_in_prev_ne(m, label):
                return True
        return False

    @staticmethod
    def _insert_tmp(m_next, lattice):
        if m_next.key in lattice:
            return lattice[m_next.key].update(m_next)
        else:
            lattice[m_next.key] = m_next
            return True

    def _match_non_emitting_states_inner(self, cur_lattice, obs_idx, obs, obs_next, nb_ne,
                                         lattice_toinsert, lattice_best, lattice_ne):
        cur_lattice_new = dict()
        for m in cur_lattice.values():  # type: BaseMatching
            if m.stop:
                continue
            if m.shortkey in lattice_ne:
                logger.debug(f"Skip non-emitting states from {m.label}")
                continue
            # == Move to neighbour edge from edge ==
            if m.edge_m.l2 is not None and self.only_edges:
                nbrs = self.map.edges_nbrto((m.edge_m.l1, m.edge_m.l2))
                # print("Neighbours for {}: {}".format(m, nbrs))
                if nbrs is None or len(nbrs) == 0:
                    if __debug__:
                        logger.debug(f"No neighbours found for edge {m.edge_m.label} ({m.label}, non-emitting)")
                    continue
                if __debug__:
                    logger.debug(f"   Move to {len(nbrs)} neighbours from edge {m.edge_m.label} "
                                 f"({m.label}, non-emitting)")
                    logger.debug(m.repr_header())
                for nbr_label1, nbr_loc1, nbr_label2, nbr_loc2 in nbrs:
                    if self._node_in_prev_ne(m, nbr_label2):
                        if __debug__:
                            logger.debug(self.matching.repr_static(('x', '{} <'.format(nbr_label2))))
                        continue
                    # === Move to next edge ===
                    if m.edge_m.l2 != nbr_label2 and m.edge_m.l1 != nbr_label2:
                        edge_m = Segment(nbr_label1, nbr_loc1, nbr_label2, nbr_loc2)
                        edge_o = Segment(f"O{obs_idx}", obs, f"O{obs_idx+1}", obs_next)
                        m_next = m.next(edge_m, edge_o, obs=obs_idx, obs_ne=nb_ne)
                        if m_next is not None:
                            if m_next.key in cur_lattice_new:
                                if m_next.shortkey in lattice_best:
                                    if approx_leq(m_next.dist_obs, lattice_best[m_next.shortkey].dist_obs):
                                        cur_lattice_new[m_next.key].update(m_next)
                                    elif __debug__ and logger.isEnabledFor(logging.DEBUG):
                                        logger.debug(f"   | Stopped trace: distance larger than best for key {m_next.shortkey}: "
                                                     f"{m_next.dist_obs} > {lattice_best[m_next.shortkey].dist_obs}")
                                        m_next.stop = True
                                else:
                                    cur_lattice_new[m_next.key].update(m_next)
                            else:
                                if m_next.shortkey in lattice_best:
                                    # if m_next.logprob > lattice_best[m_next.shortkey].logprob:
                                    if approx_leq(m_next.dist_obs, lattice_best[m_next.shortkey].dist_obs):
                                        cur_lattice_new[m_next.key] = m_next
                                        # lattice_best[m_next.shortkey] = m_next
                                        lattice_toinsert.append(m_next)
                                    else:
                                        if __debug__ and logger.isEnabledFor(logging.DEBUG):
                                            logger.debug(f"   | Stopped trace: distance larger than best for key {m_next.shortkey}: "
                                                         f"{m_next.dist_obs} > {lattice_best[m_next.shortkey].dist_obs}")
                                        m_next.stop = True
                                else:
                                    cur_lattice_new[m_next.key] = m_next
                                    # lattice_best[m_next.shortkey] = m_next
                                    lattice_toinsert.append(m_next)
                            # cur_lattice_new.add(m_next)
                            if __debug__:
                                logger.debug(str(m_next))
                    else:
                        if __debug__:
                            logger.debug(self.matching.repr_static(('x', f'{nbr_label1}-{nbr_label2} <')))
            # == Move to neighbour node from node==
            if m.edge_m.l2 is None and not self.only_edges:
                cur_node = m.edge_m.l1
                nbrs = self.map.nodes_nbrto(cur_node)
                if nbrs is None:
                    if __debug__:
                        logger.debug(
                            f"No neighbours found for node {cur_node} ({m.label}, non-emitting)")
                    continue
                if __debug__:
                    logger.debug(
                        f"   Move to {len(nbrs)} neighbours from node {cur_node} ({m.label}, non-emitting)")
                    logger.debug(m.repr_header())
                for nbr_label, nbr_loc in nbrs:
                    # print(f"self._node_in_prev_ne({m.label}, {nbr_label}) = {self._node_in_prev_ne(m, nbr_label)}")
                    if self._node_in_prev_ne(m, nbr_label):
                        if __debug__:
                            logger.debug(self.matching.repr_static(('x', '{} <'.format(nbr_label))))
                        continue
                    # === Move to next node ===
                    if m.edge_m.l1 != nbr_label:
                        edge_m = Segment(nbr_label, nbr_loc)
                        edge_o = Segment(f"O{obs_idx}", obs, f"O{obs_idx+1}", obs_next)
                        m_next = m.next(edge_m, edge_o, obs=obs_idx, obs_ne=nb_ne)
                        if m_next is not None:
                            if m_next.key in cur_lattice_new:
                                cur_lattice_new[m_next.key].update(m_next)
                            else:
                                if m_next.shortkey in lattice_best:
                                    # if m_next.logprob > lattice_best[m_next.shortkey].logprob:
                                    if m_next.dist_obs < lattice_best[m_next.shortkey].dist_obs:
                                        cur_lattice_new[m_next.key] = m_next
                                        lattice_best[m_next.shortkey] = m_next
                                        lattice_toinsert.append(m_next)
                                    elif __debug__ and logger.isEnabledFor(logging.DEBUG):
                                        m_next.stop = True
                                        lattice_toinsert.append(m_next)
                                else:
                                    cur_lattice_new[m_next.key] = m_next
                                    lattice_best[m_next.shortkey] = m_next
                                    lattice_toinsert.append(m_next)
                            # cur_lattice_new.add(m_next)
                            if __debug__:
                                logger.debug(str(m_next))
                    else:
                        if __debug__:
                            logger.debug(f"x  | {m.edge_m.l1}-{nbr_label} < self-loop")

        return cur_lattice_new

    def _match_non_emitting_states_end(self, cur_lattice, obs_idx, obs_next,
                                       lattice_toinsert, lattice_best):
        for m in cur_lattice.values():  # type: BaseMatching
            if m.stop:
                continue
            if m.edge_m.l2 is not None:
                # Move to neighbour edge from edge
                nbrs = self.map.edges_nbrto((m.edge_m.l1, m.edge_m.l2))
                # print("Neighbours for {}: {}".format(m, nbrs))
                if nbrs is None or len(nbrs) == 0:
                    if __debug__:
                        logger.debug("No neighbours found for edge {} ({})".format(m.edge_m.label, m.label))
                    continue
                if __debug__:
                    logger.debug(f"   Move to {len(nbrs)} neighbours from edge {m.edge_m.label} "
                                 f"({m.label}, non-emitting->emitting)")
                    logger.debug(m.repr_header())
                for nbr_label1, nbr_loc1, nbr_label2, nbr_loc2 in nbrs:
                    if self._node_in_prev_ne(m, nbr_label2):
                        if __debug__:
                            logger.debug(self.matching.repr_static(('x', '{} <'.format(nbr_label2))))
                        continue
                    # Move to next edge
                    if m.edge_m.l1 != nbr_label2 and m.edge_m.l2 != nbr_label2:
                        edge_m = Segment(nbr_label1, nbr_loc1, nbr_label2, nbr_loc2)
                        edge_o = Segment(f"O{obs_idx+1}", obs_next)
                        m_next = m.next(edge_m, edge_o, obs=obs_idx)
                        if m_next is not None:
                            if m_next.shortkey in lattice_best:
                                # if m_next.dist_obs < lattice_best[m_next.shortkey].dist_obs:
                                if m_next.logprob > lattice_best[m_next.shortkey].logprob:
                                    lattice_best[m_next.shortkey] = m_next
                                    lattice_toinsert.append(m_next)
                                elif __debug__ and logger.isEnabledFor(logging.DEBUG):
                                    m_next.stop = True
                                    lattice_toinsert.append(m_next)
                            else:
                                lattice_best[m_next.shortkey] = m_next
                                lattice_toinsert.append(m_next)
                            if __debug__:
                                logger.debug(str(m_next))
                    else:
                        if __debug__:
                            logger.debug(self.matching.repr_static(('x', '{} <'.format(nbr_label2))))
            else:  # m.edge_m.l2 is None:
                # Move to neighbour node from node
                cur_node = m.edge_m.l1
                nbrs = self.map.nodes_nbrto(cur_node)
                # print("Neighbours for {}: {}".format(m, nbrs))
                if nbrs is None:
                    if __debug__:
                        logger.debug("No neighbours found for node {}".format(cur_node, m.label))
                    continue
                if __debug__:
                    logger.debug(f"   Move to {len(nbrs)} neighbours from node {cur_node} "
                                 f"({m.label}, non-emitting->emitting)")
                    logger.debug(m.repr_header())
                for nbr_label, nbr_loc in nbrs:
                    if self._node_in_prev_ne(m, nbr_label):
                        if __debug__:
                            logger.debug(self.matching.repr_static(('x', '{} <'.format(nbr_label))))
                        continue
                    # Move to next node
                    if m.edge_m.l1 != nbr_label:
                        # edge_m = Segment(m.edge_m.l1, m.edge_m.p1, nbr_label, nbr_loc)
                        edge_m = Segment(nbr_label, nbr_loc)
                        edge_o = Segment(f"O{obs_idx+1}", obs_next)
                        m_next = m.next(edge_m, edge_o, obs=obs_idx)
                        if m_next is not None:
                            if m_next.shortkey in lattice_best:
                                # if m_next.dist_obs < lattice_best[m_next.shortkey].dist_obs:
                                if m_next.logprob > lattice_best[m_next.shortkey].logprob:
                                    lattice_best[m_next.shortkey] = m_next
                                    lattice_toinsert.append(m_next)
                                elif __debug__ and logger.isEnabledFor(logging.DEBUG):
                                    m_next.stop = True
                                    lattice_toinsert.append(m_next)
                            else:
                                lattice_best[m_next.shortkey] = m_next
                                lattice_toinsert.append(m_next)
                            if __debug__:
                                logger.debug(str(m_next))
                    else:
                        if __debug__:
                            logger.debug(self.matching.repr_static(('x', '{} <'.format(nbr_label))))

    def _prune_lattice(self, obs_idx):
        logger.debug('Prune lattice[{}] from {} to {}'
                     .format(obs_idx, len(self.lattice[obs_idx]), self.max_lattice_width))
        if len(self.lattice[obs_idx]) <= self.max_lattice_width:
            return
        top_m = [m for m in self.lattice[obs_idx].values() if not m.stop]
        top_m.sort(key=lambda m: m.logprobema, reverse=True)
        self.lattice[obs_idx] = dict((m.key, m) for m in top_m[:self.max_lattice_width])
        self._cleanup_lattice(obs_idx)
        if __debug__ and logger.isEnabledFor(logging.DEBUG):
            for m in self.lattice[obs_idx].values():
                logger.debug(str(m))

    def _cleanup_lattice(self, obs_idx):
        """Remove all lattice entries that cannot be part of a backtracking path starting at obs_idx."""
        # TODO make lattice smaller. Current version does not work as it creates gaps.
        # if obs_idx <= 1:
        #     return
        # all_prev = set()
        # for m in self.lattice[obs_idx].values():
        #     all_prev.update(m.prev)
        #
        # lattice_col = self.lattice[obs_idx - 1]
        # to_del = []
        # for label, m in lattice_col.items():
        #     if m not in all_prev:
        #         to_del.append(label)
        # for label in to_del:
        #     del lattice_col[label]

    def _build_node_path(self, start_idx, unique=True, max_depth=None):
        self.lattice_best = []
        node_max = None
        cur_depth = 0
        for m in self.lattice[start_idx].values():
            if node_max is None or m.logprob > node_max.logprob:
                node_max = m
        if node_max is None:
            raise Exception("Did not find a matching node for path point at index {}".format(start_idx))
        if __debug__ and logger.isEnabledFor(logging.DEBUG):
            logger.debug(self.matching.repr_header(stop="             "))
        logger.debug("Start ({}): {}".format(node_max.obs, node_max))
        node_path_rev = [node_max.shortkey]
        self.lattice_best.append(node_max)
        if node_max.is_emitting():
            cur_depth += 1
        # for obs_idx in reversed(range(start_idx)):
        if max_depth is None:
            max_depth = len(self.lattice) + 1
        while cur_depth < max_depth and len(node_max.prev) > 0:
            node_max_last = node_max
            node_max: Optional[BaseMatching] = None
            for prev_m in node_max_last.prev:
                if prev_m is not None and (node_max is None or prev_m.logprob > node_max.logprob):
                    node_max = prev_m
            if node_max is None:
                raise Exception("Did not find a matching node for path point at index {}".format(node_max_last.obs))
            logger.debug("Max   ({}): {}".format(node_max.obs, node_max))
            node_path_rev.append(node_max.shortkey)
            self.lattice_best.append(node_max)
            if node_max.is_emitting():
                cur_depth += 1

        self.lattice_best = list(reversed(self.lattice_best))
        if unique:
            self.node_path = []
            prev_node = None
            for node in reversed(node_path_rev):
                if node != prev_node:
                    self.node_path.append(node)
                    prev_node = node
        else:
            self.node_path = list(reversed(node_path_rev))
        return self.node_path

    def print_lattice(self, file=None, obs_idx=None, label_width=None):
        if file is None:
            file = sys.stdout
        # print("Lattice:", file=file)
        if obs_idx is not None:
            idxs = [obs_idx]
        else:
            idxs = range(len(self.lattice))
        for idx in idxs:
            if len(self.lattice[idx]) > 0:
                if label_width is None:
                    label_width = 0
                    for m in self.lattice[idx].values():
                        label_width = max(label_width, len(str(m.label)))
                print("--- obs {} ---".format(idx), file=file)
                print(self.matching.repr_header(label_width=label_width), file=file)
                for m in sorted(self.lattice[idx].values(), key=lambda t: str(t.label)):
                    print(m.__str__(label_width=label_width), file=file)

    def lattice_dot(self, file=None):
        if file is None:
            file = sys.stdout
        print('digraph lattice {', file=file)
        print('\trankdir=LR;', file=file)
        for idx in range(len(self.lattice)):
            if len(self.lattice[idx]) == 0:
                continue
            cnames = [(m.obs_ne, m.cname, m.stop) for m in self.lattice[idx].values()]
            cnames.sort()
            cur_obs_ne = -1
            print('\t{\n\t\trank=same; ', file=file)
            for obs_ne, cname, stop, in cnames:
                if obs_ne != cur_obs_ne:
                    if cur_obs_ne != -1:
                        print('\t};\n\t{\n\t\trank=same; ', file=file)
                    cur_obs_ne = obs_ne
                if stop:
                    options = 'label="{} x",color=gray,fontcolor=gray'.format(cname)
                else:
                    options = 'label="{} ."'.format(cname)
                print('\t\t{} [{}];'.format(cname, options), file=file)
            print('\t};', file=file)
        for idx in range(len(self.lattice)):
            if len(self.lattice[idx]) == 0:
                continue
            for m in self.lattice[idx].values():
                for mp in m.prev:
                    if m.stop:
                        options = ',color=gray,fontcolor=gray'
                    else:
                        options = ''
                    print(f'\t {mp.cname} -> {m.cname} [label="{m.logprob}"{options}];', file=file)
                for mp in m.prev_other:
                    if m.stop:
                        options = ',color=gray,fontcolor=gray'
                    else:
                        options = ''
                    print(f'\t {mp.cname} -> {m.cname} [color=gray,label="{m.logprob}"{options}];', file=file)
        print('}', file=file)

    def print_lattice_stats(self, file=None, verbose=False):
        if file is None:
            file = sys.stdout
        print("Stats lattice", file=file)
        print("-------------", file=file)
        stats = OrderedDict()
        stats["nbr levels"] = len(self.lattice)
        total_nodes = 0
        max_nodes = 0
        min_nodes = 9999999
        sizes = []
        for idx in range(len(self.lattice)):
            level = self.lattice[idx]
            # stats["#nodes[{}]".format(idx)] = len(level)
            sizes.append(len(level))
            total_nodes += len(level)
            if len(level) < min_nodes:
                min_nodes = len(level)
            if len(level) > max_nodes:
                max_nodes = len(level)
        stats["nbr lattice"] = total_nodes
        if verbose:
            stats["nbr lattice[level]"] = ", ".join([str(s) for s in sizes])
        stats["avg lattice[level]"] = total_nodes/len(self.lattice)
        stats["min lattice[level]"] = min_nodes
        stats["max lattice[level]"] = max_nodes
        if len(self.lattice_best) > 0:
            stats["avg obs distance"] = np.mean([m.dist_obs for m in self.lattice_best])
            stats["last logprob"] = self.lattice_best[-1].logprob
            stats["last length"] = self.lattice_best[-1].length
            stats["last norm logprob"] = self.lattice_best[-1].logprob / self.lattice_best[-1].length
            if verbose:
                stats["best logprob"] = ", ".join(["{:.3f}".format(m.logprob) for m in self.lattice_best])
                stats["best norm logprob"] = \
                    ", ".join(["{:.3f}".format(m.logprob/m.length) for i, m in enumerate(self.lattice_best)])
                stats["best norm prob"] = \
                    ", ".join(["{:.3f}".format(math.exp(m.logprob/m.length)) for i, m in enumerate(self.lattice_best)])
        for key, val in stats.items():
            print("{:<24} : {}".format(key, val), file=file)

    def node_counts(self):
        counts = defaultdict(lambda: 0)
        for level in self.lattice.values():
            for m in level.values():
                counts[m.label] += 1
        return counts

    def copy_lastinterface(self, nb_interfaces=1):
        """Copy the current matcher and keep the last interface as the start point.

        This method allows you to perform incremental matching without keeping the entire
        lattice in memory.

        You need to run :meth:`match_incremental` on this object to continue from the existing
        (partial) lattice. Otherwise, if you use :meth:`match`, it will be overwritten.

        :param nb_interfaces: Nb of interfaces (columns in lattice) to keep. Default is 1, the last one.
        :return: new Matcher object
        """
        matcher = self.__class__(self.map, obs_noise=self.obs_noise, max_dist_init=self.max_dist_init,
                                 max_dist=self.max_dist, min_prob_norm=self.min_logprob_norm,
                                 non_emitting_states=self.non_emitting_states,
                                 max_lattice_width=self.max_lattice_width, only_edges=self.only_edges,
                                 obs_noise_ne=self.obs_noise_ne, matching=self.matching,
                                 avoid_goingback=self.avoid_goingback,
                                 non_emitting_length_factor=math.exp(self.ne_length_factor_log))
        matcher.lattice = []
        matcher.path = []
        for int_i in range(len(self.lattice) - nb_interfaces, len(self.lattice)):
            matcher.lattice.append(self.lattice[int_i])
            matcher.path.append(self.path[int_i])
        return matcher

    @property
    def path_pred(self):
        """The matched path, both nodes and/or edges (depending on your settings)."""
        return self.node_path

    @property
    def path_pred_onlynodes(self):
        """A list with all the nodes (no edges) the matched path passes through."""
        if self.node_path is None or len(self.node_path) == 0:
            return []
        nodes = []
        prev_state = self.node_path[0]
        if type(prev_state) is tuple:
            nodes.append(prev_state[0])
            nodes.append(prev_state[1])
            prev_node = prev_state[1]
        else:
            nodes.append(prev_state)
            prev_node = prev_state
        for state in self.node_path[1:]:
            if state == prev_state:
                continue
            if type(state) is not tuple:
                if state != prev_node:
                    nodes.append(state)
                    prev_node = state
            elif type(state) is tuple:
                if state[0] == prev_node:
                    if state[1] != prev_node:
                        nodes.append(state[1])
                        prev_node = state[1]
                elif state[1] == prev_node:
                    if state[0] != prev_node:
                        nodes.append(state[0])
                        prev_node = state[0]
                else:
                    raise Exception(f"State {state} does not have as previous node {prev_node}")
            else:
                raise Exception(f"Unknown type of state: {state} ({type(state)})")
            prev_state = state
        return nodes
