import logging
from typing import Tuple

import numpy as np

from .base_road_generator import BaseRoadGenerator
from road_gen.prefabs import prefabs
from road_gen.integrator.integrator import integrate_road

from pg_rad.configs import defaults


logger = logging.getLogger(__name__)


class SegmentedRoadGenerator(BaseRoadGenerator):
    def __init__(
        self,
        length: int | float | list[int | float],
        ds: int | float,
        velocity: int | float,
        mu: float = 0.7,
        g: float = 9.81,
        seed: int | None = None
    ):
        """Initialize a SegmentedRoadGenerator with given or random seed.

        Args:
            length (int | float): The total length of the road in meters.
            ds (int | float): The step size in meters.
            velocity (int | float): Velocity in meters per second.
            mu (float): Coefficient of friction. Defaults to 0.7 (dry asphalt).
            g (float): Acceleration due to gravity (m/s^2). Defaults to 9.81.
            seed (int | None, optional): Set a seed for the generator.
                Defaults to random seed.
        """

        if isinstance(length, list):
            length = sum(
                [seg_len for seg_len in length if seg_len is not None]
            )
        super().__init__(length, ds, velocity, mu, g, seed)

    def generate(
            self,
            segments: list[str],
            lengths: list[int | float] | None = None,
            angles: list[int | float] | None = None,
            alpha: float = defaults.DEFAULT_ALPHA,
            min_turn_angle: float = defaults.DEFAULT_MIN_TURN_ANGLE,
            max_turn_angle: float = defaults.DEFAULT_MAX_TURN_ANGLE
    ) -> Tuple[np.ndarray, np.ndarray]:
        """Generate a curvature profile from a list of segments.

        Args:
            segments (list[str]): List of segments.
            alpha (float, optional): Dirichlet concentration parameter.
                A higher value leads to more uniform apportionment of the
                length amongst the segments, while a lower value allows more
                random apportionment. Defaults to 1.0.
            min_turn_angle (float, optional): Minimum turn angle in degrees for
                random sampling of turn radius. Does nothing if `angle_list` is
                provided or no `turn_*` segement is specified in the `segments`
                list.
            min_turn_angle (float, optional): Maximum turn angle in degrees for
                random sampling of turn radius. Does nothing if `angle_list` is
                provided or no `turn_*` segement is specified in the `segments`
                list.
        Raises:
            ValueError: Raised when a turn
                is too tight given its segment length and the velocity.
                To fix this, you can try to reduce the amount of segments or
                increase length. Increasing alpha
                (Dirichlet concentration parameter) can also help because this
                reduces the odds of very small lengths being assigned to
                turn segments.

        Returns:
            Tuple[np.ndarray, np.ndarray]: x and y coordinates of the
                waypoints describing the random road.
        """
        existing_prefabs = prefabs.PREFABS.keys()
        if not all(segment in existing_prefabs for segment in segments):
            raise ValueError(
                "Invalid segment type provided. Available choices"
                f"{existing_prefabs}"
            )

        self.segments = segments
        self.alpha = alpha
        num_points = np.ceil(self.length / self.ds).astype(int)

        # divide num_points into len(segments) randomly sized parts.
        if isinstance(self.length, list):
            parts = self.length
        else:
            parts = self._rng.dirichlet(
                np.full(len(segments), alpha),
                size=1)[0]
            parts = parts * num_points
            parts = np.round(parts).astype(int)

            # correct round off so the sum of parts is still total length L.
            if sum(parts) != num_points:
                parts[0] += num_points - sum(parts)

        curvature = np.zeros(num_points)
        current_index = 0

        for seg_name, seg_length in zip(segments, parts):
            seg_function = prefabs.PREFABS[seg_name]

            if seg_name == 'straight':
                curvature_s = seg_function(seg_length)
            else:
                R_min_angle = seg_length / np.deg2rad(max_turn_angle)
                R_max_angle = seg_length / np.deg2rad(min_turn_angle)

                # physics limit
                R_min = max(self.min_radius, R_min_angle)

                if R_min > R_max_angle:
                    raise ValueError(
                        f"{seg_name} with length {seg_length} does not have "
                        "a possible radius. The minimum for the provided "
                        "velocity and friction coefficient is "
                        f"{self.min_radius}, but the possible range is "
                        f"({R_min}, {R_max_angle})"
                    )

                rand_radius = self._rng.uniform(R_min, R_max_angle)

                if seg_name.startswith("u_turn"):
                    curvature_s = seg_function(rand_radius)
                else:
                    curvature_s = seg_function(seg_length, rand_radius)

            curvature[current_index:(current_index + seg_length)] = curvature_s
            current_index += seg_length

            x, y = integrate_road(curvature)

        return x * self.ds, y * self.ds