333 lines
13 KiB
Python
333 lines
13 KiB
Python
# target_simulator/core/models.py
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"""
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Defines the core data models for the application, including 3D dynamic Targets
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with programmable trajectories and Scenarios.
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"""
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from __future__ import annotations
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import math
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from enum import Enum
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from dataclasses import dataclass, field, fields
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from typing import Dict, List, Optional, Tuple
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# --- Constants ---
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MIN_TARGET_ID = 0
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MAX_TARGET_ID = 15
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KNOTS_TO_FPS = 1.68781
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FPS_TO_KNOTS = 1 / KNOTS_TO_FPS
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NM_TO_FT = 6076.12
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class ManeuverType(Enum):
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FLY_TO_POINT = "Fly to Point"
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FLY_FOR_DURATION = "Fly for Duration"
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@dataclass
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class Waypoint:
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"""Represents a segment of a target's trajectory, defining a maneuver."""
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maneuver_type: ManeuverType = ManeuverType.FLY_FOR_DURATION
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# Parameters used by both maneuver types
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duration_s: Optional[float] = 10.0
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target_altitude_ft: Optional[float] = 10000.0
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# Final state parameters for FLY_TO_POINT and dynamic for FLY_FOR_DURATION
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target_velocity_fps: Optional[float] = None
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target_heading_deg: Optional[float] = None
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# Position parameters for FLY_TO_POINT
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target_range_nm: Optional[float] = None
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target_azimuth_deg: Optional[float] = None
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def to_dict(self) -> Dict:
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"""Serializes the waypoint to a dictionary."""
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data = {"maneuver_type": self.maneuver_type.value}
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for f in fields(self):
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# Exclude private fields and the already-handled maneuver_type
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if not f.name.startswith('_') and f.name != "maneuver_type":
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val = getattr(self, f.name)
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if val is not None:
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data[f.name] = val
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return data
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@dataclass
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class Target:
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"""Represents a dynamic 3D target with a programmable trajectory."""
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target_id: int
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trajectory: List[Waypoint] = field(default_factory=list)
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active: bool = True
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traceable: bool = True
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use_spline: bool = False
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# --- Current simulation state (dynamic) ---
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current_range_nm: float = field(init=False, default=0.0)
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current_azimuth_deg: float = field(init=False, default=0.0)
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current_altitude_ft: float = field(init=False, default=0.0)
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current_velocity_fps: float = field(init=False, default=0.0)
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current_heading_deg: float = field(init=False, default=0.0)
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current_pitch_deg: float = field(init=False, default=0.0)
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# Internal Cartesian position in feet
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_pos_x_ft: float = field(init=False, repr=False, default=0.0)
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_pos_y_ft: float = field(init=False, repr=False, default=0.0)
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_pos_z_ft: float = field(init=False, repr=False, default=0.0)
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# Simulation time and pre-calculated path
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_sim_time_s: float = field(init=False, default=0.0)
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_total_duration_s: float = field(init=False, default=0.0)
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# Path format: List of (timestamp_s, x_ft, y_ft, z_ft)
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_path: List[Tuple[float, float, float, float]] = field(init=False, repr=False, default_factory=list)
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def __post_init__(self):
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"""Validates ID and initializes the simulation state."""
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if not (MIN_TARGET_ID <= self.target_id <= MAX_TARGET_ID):
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raise ValueError(f"Target ID must be between {MIN_TARGET_ID} and {MAX_TARGET_ID}.")
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self.reset_simulation()
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def reset_simulation(self):
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"""
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Resets the simulation time and pre-calculates the entire trajectory path
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based on the waypoints. This is the core of the refactored logic.
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"""
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self._sim_time_s = 0.0
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self._generate_path()
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if self._path:
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# Set initial state from the first point of the generated path
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initial_pos = self._path[0]
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self._pos_x_ft = initial_pos[1]
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self._pos_y_ft = initial_pos[2]
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self._pos_z_ft = initial_pos[3]
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# Calculate initial heading and velocity from the first segment
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if len(self._path) > 1:
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next_pos = self._path[1]
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dx = next_pos[1] - self._pos_x_ft
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dy = next_pos[2] - self._pos_y_ft
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dz = next_pos[3] - self._pos_z_ft
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dt = next_pos[0] - initial_pos[0]
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dist_3d = math.sqrt(dx**2 + dy**2 + dz**2)
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dist_2d = math.sqrt(dx**2 + dy**2)
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self.current_heading_deg = math.degrees(math.atan2(dx, dy)) % 360 if dist_2d > 0.1 else 0.0
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self.current_pitch_deg = math.degrees(math.atan2(dz, dist_2d)) if dist_2d > 0.1 else 0.0
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self.current_velocity_fps = dist_3d / dt if dt > 0 else 0.0
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else:
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self.current_heading_deg = 0.0
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self.current_pitch_deg = 0.0
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self.current_velocity_fps = 0.0
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else:
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# No trajectory, reset to origin
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self._pos_x_ft = self._pos_y_ft = self._pos_z_ft = 0.0
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self.current_velocity_fps = 0.0
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self.current_heading_deg = 0.0
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self.current_pitch_deg = 0.0
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self._update_current_polar_coords()
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self.active = bool(self.trajectory) # A target is active if it has a trajectory
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def _generate_path(self):
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"""Instance method that uses the static path generator."""
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self._path, self._total_duration_s = Target.generate_path_from_waypoints(self.trajectory, self.use_spline)
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@staticmethod
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def generate_path_from_waypoints(waypoints: List[Waypoint], use_spline: bool) -> Tuple[List[Tuple[float, ...]], float]:
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"""
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Generates a time-stamped, Cartesian path from a list of waypoints.
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This is a static method so it can be used for previews without a Target instance.
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"""
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path = []
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total_duration_s = 0.0
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if not waypoints:
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return path, total_duration_s
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first_wp = waypoints[0]
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if first_wp.maneuver_type != ManeuverType.FLY_TO_POINT:
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return path, total_duration_s
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keyframes = []
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current_time = 0.0
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range_ft = (first_wp.target_range_nm or 0.0) * NM_TO_FT
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az_rad = math.radians(first_wp.target_azimuth_deg or 0.0)
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current_x = range_ft * math.sin(az_rad)
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current_y = range_ft * math.cos(az_rad)
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current_z = first_wp.target_altitude_ft or 0.0
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current_heading = first_wp.target_heading_deg or 0.0
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current_velocity = first_wp.target_velocity_fps or 0.0
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keyframes.append((current_time, current_x, current_y, current_z))
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for i, wp in enumerate(waypoints):
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if i == 0:
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continue
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duration = wp.duration_s or 0.0
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if wp.maneuver_type == ManeuverType.FLY_TO_POINT:
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target_range_ft = (wp.target_range_nm or 0.0) * NM_TO_FT
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target_az_rad = math.radians(wp.target_azimuth_deg or 0.0)
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current_x = target_range_ft * math.sin(target_az_rad)
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current_y = target_range_ft * math.cos(target_az_rad)
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current_z = wp.target_altitude_ft or current_z
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elif wp.maneuver_type == ManeuverType.FLY_FOR_DURATION:
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velocity_to_use = wp.target_velocity_fps if wp.target_velocity_fps is not None else current_velocity
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heading_to_use = wp.target_heading_deg if wp.target_heading_deg is not None else current_heading
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heading_rad = math.radians(heading_to_use)
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dist_moved = velocity_to_use * duration
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current_x += dist_moved * math.sin(heading_rad)
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current_y += dist_moved * math.cos(heading_rad)
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current_z = wp.target_altitude_ft or current_z
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current_heading = heading_to_use
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current_velocity = velocity_to_use
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total_duration_s += duration
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keyframes.append((total_duration_s, current_x, current_y, current_z))
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if len(keyframes) < 2:
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return keyframes, total_duration_s
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if use_spline and len(keyframes) >= 4:
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from target_simulator.utils.spline import catmull_rom_spline
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points_to_spline = [kf[1:] for kf in keyframes]
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num_spline_points = int(total_duration_s * 10)
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splined_points = catmull_rom_spline(points_to_spline, num_points=max(num_spline_points, 100))
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for i, point in enumerate(splined_points):
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time = (i / (len(splined_points) - 1)) * total_duration_s if len(splined_points) > 1 else 0.0
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path.append((time, point[0], point[1], point[2]))
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else:
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path = keyframes
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return path, total_duration_s
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def update_state(self, delta_time_s: float):
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# ... (questo metodo rimane invariato)
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if not self.active or not self._path:
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return
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self._sim_time_s += delta_time_s
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current_sim_time = min(self._sim_time_s, self._total_duration_s)
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if current_sim_time >= self._total_duration_s:
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final_pos = self._path[-1]
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self._pos_x_ft, self._pos_y_ft, self._pos_z_ft = final_pos[1], final_pos[2], final_pos[3]
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self.current_velocity_fps = 0.0
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if self._sim_time_s >= self._total_duration_s:
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self.active = False
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else:
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p1 = self._path[0]
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p2 = self._path[-1]
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for i in range(len(self._path) - 1):
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if self._path[i][0] <= current_sim_time <= self._path[i+1][0]:
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p1 = self._path[i]
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p2 = self._path[i+1]
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break
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segment_duration = p2[0] - p1[0]
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progress = (current_sim_time - p1[0]) / segment_duration if segment_duration > 0 else 1.0
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prev_x, prev_y, prev_z = self._pos_x_ft, self._pos_y_ft, self._pos_z_ft
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self._pos_x_ft = p1[1] + (p2[1] - p1[1]) * progress
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self._pos_y_ft = p1[2] + (p2[2] - p1[2]) * progress
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self._pos_z_ft = p1[3] + (p2[3] - p1[3]) * progress
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dx = self._pos_x_ft - prev_x
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dy = self._pos_y_ft - prev_y
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dz = self._pos_z_ft - prev_z
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dist_moved_3d = math.sqrt(dx**2 + dy**2 + dz**2)
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dist_moved_2d = math.sqrt(dx**2 + dy**2)
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if delta_time_s > 0:
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self.current_velocity_fps = dist_moved_3d / delta_time_s
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if dist_moved_2d > 0.1:
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self.current_heading_deg = math.degrees(math.atan2(dx, dy)) % 360
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self.current_pitch_deg = math.degrees(math.atan2(dz, dist_moved_2d))
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self._update_current_polar_coords()
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def _update_current_polar_coords(self):
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# ... (questo metodo rimane invariato)
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self.current_range_nm = math.sqrt(self._pos_x_ft**2 + self._pos_y_ft**2) / NM_TO_FT
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self.current_azimuth_deg = math.degrees(math.atan2(self._pos_x_ft, self._pos_y_ft)) % 360
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self.current_altitude_ft = self._pos_z_ft
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def to_dict(self) -> Dict:
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# ... (questo metodo rimane invariato)
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return {
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"target_id": self.target_id,
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"active": self.active,
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"traceable": self.traceable,
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"trajectory": [wp.to_dict() for wp in self.trajectory],
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"use_spline": self.use_spline
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}
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class Scenario:
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def __init__(self, name: str = "Untitled Scenario"):
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self.name = name
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self.targets: Dict[int, Target] = {}
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def add_target(self, target: Target):
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self.targets[target.target_id] = target
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def get_target(self, target_id: int) -> Optional[Target]:
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return self.targets.get(target_id)
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def remove_target(self, target_id: int):
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if target_id in self.targets:
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del self.targets[target_id]
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def get_all_targets(self) -> List[Target]:
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return list(self.targets.values())
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def reset_simulation(self):
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"""Resets the simulation state for all targets in the scenario."""
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for target in self.targets.values():
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target.reset_simulation()
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def update_state(self, delta_time_s: float):
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"""Updates the state of all targets in the scenario."""
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for target in self.targets.values():
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target.update_state(delta_time_s)
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def is_finished(self) -> bool:
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"""Checks if all targets in the scenario have finished their trajectory."""
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return all(not target.active for target in self.targets.values())
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def to_dict(self) -> Dict:
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return {
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"name": self.name,
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"targets": [target.to_dict() for target in self.get_all_targets()]
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}
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@classmethod
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def from_dict(cls, data: Dict) -> Scenario:
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name = data.get("name", "Loaded Scenario")
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scenario = cls(name=name)
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for target_data in data.get("targets", []):
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try:
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waypoints = []
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for wp_data in target_data.get("trajectory", []):
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wp_data["maneuver_type"] = ManeuverType(wp_data["maneuver_type"])
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waypoints.append(Waypoint(**wp_data))
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target = Target(
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target_id=target_data["target_id"],
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active=target_data.get("active", True),
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traceable=target_data.get("traceable", True),
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trajectory=waypoints,
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use_spline=target_data.get("use_spline", False)
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)
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scenario.add_target(target)
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except Exception as e:
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print(f"Skipping invalid target data: {target_data}. Error: {e}")
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return scenario |