# -*- coding: utf-8 -*-
from .base import Hypothesiser
from ..base import Property
from ..measures import Measure
from ..predictor import Predictor
from ..types.detection import MissedDetection
from ..types.hypothesis import SingleDistanceHypothesis
from ..types.multihypothesis import MultipleHypothesis
from ..updater import Updater


class DistanceHypothesiser(Hypothesiser):
    """Prediction Hypothesiser based on a Measure

    Generate track predictions at detection times and score each hypothesised
    prediction-detection pair using the distance of the supplied
    :class:`Measure` class.
    """

    predictor: Predictor = Property(doc="Predict tracks to detection times")
    updater: Updater = Property(doc="Updater used to get measurement prediction")
    measure: Measure = Property(
        doc="Measure class used to calculate the distance between two states.")
    missed_distance: float = Property(
        default=float('inf'),
        doc="Distance for a missed detection. Default is set to infinity")
    include_all: bool = Property(
        default=False,
        doc="If `True`, hypotheses beyond missed distance will be returned. Default `False`")

    def hypothesise(self, track, detections, timestamp):
        """ Evaluate and return all track association hypotheses.

        For a given track and a set of N available detections, return a
        MultipleHypothesis object with N+1 detections (first detection is
        a 'MissedDetection'), each with an associated distance measure..

        Parameters
        ----------
        track: :class:`~.Track`
            The track object to hypothesise on
        detections: :class:`list`
            A list of :class:`~Detection` objects, representing the available
            detections.
        timestamp: :class:`datetime.datetime`
            A timestamp used when evaluating the state and measurement
            predictions. Note that if a given detection has a non empty
            timestamp, then prediction will be performed according to
            the timestamp of the detection.

        Returns
        -------
        : :class:`~.MultipleHypothesis`
            A container of :class:`~SingleDistanceHypothesis` objects

        """
        hypotheses = list()

        # Common state & measurement prediction
        prediction = self.predictor.predict(track, timestamp=timestamp)
        # Missed detection hypothesis with distance as 'missed_distance'
        hypotheses.append(
            SingleDistanceHypothesis(
                prediction,
                MissedDetection(timestamp=timestamp),
                self.missed_distance
                ))

        # True detection hypotheses
        for detection in detections:

            # Re-evaluate prediction
            prediction = self.predictor.predict(
                track, timestamp=detection.timestamp)

            # Compute measurement prediction and distance measure
            measurement_prediction = self.updater.predict_measurement(
                prediction, detection.measurement_model)
            distance = self.measure(measurement_prediction, detection)

            if self.include_all or distance < self.missed_distance:
                # True detection hypothesis
                hypotheses.append(
                    SingleDistanceHypothesis(
                        prediction,
                        detection,
                        distance,
                        measurement_prediction))

        return MultipleHypothesis(sorted(hypotheses, reverse=True))
