283 lines
14 KiB
Python
283 lines
14 KiB
Python
# target_simulator/gui/ppi_display.py
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"""
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A reusable Tkinter widget that displays a Plan Position Indicator (PPI)
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using Matplotlib, capable of showing both live targets and trajectory previews,
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and comparing simulated vs. real-time data.
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"""
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import tkinter as tk
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from tkinter import ttk
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import math
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import logging
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import numpy as np
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import collections
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from matplotlib.figure import Figure
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from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
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from typing import List, Dict, Union
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from target_simulator.core.models import Target, Waypoint, ManeuverType, NM_TO_FT
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class PPIDisplay(ttk.Frame):
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"""
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A custom widget for the PPI radar display.
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"""
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TRAIL_LENGTH = 100
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def __init__(self, master, max_range_nm: int = 100, scan_limit_deg: int = 60, trail_length: int = None):
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super().__init__(master)
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self.max_range = max_range_nm
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self.scan_limit_deg = scan_limit_deg
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self.sim_target_artists, self.real_target_artists = [], []
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self.sim_trail_artists, self.real_trail_artists = [], []
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self.target_label_artists = []
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self.trail_length = trail_length or self.TRAIL_LENGTH
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self._trails = {
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"simulated": collections.defaultdict(lambda: collections.deque(maxlen=self.trail_length)),
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"real": collections.defaultdict(lambda: collections.deque(maxlen=self.trail_length)),
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}
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self.preview_artists = []
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self.show_sim_points_var = tk.BooleanVar(value=True)
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self.show_real_points_var = tk.BooleanVar(value=True)
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self.show_sim_trail_var = tk.BooleanVar(value=False)
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self.show_real_trail_var = tk.BooleanVar(value=True)
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self.canvas = None
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self._create_controls()
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self._create_plot()
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def _on_display_options_changed(self):
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if self.canvas:
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# We need to redraw everything to show/hide elements
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self.update_targets({}) # This is a trick to trigger a full redraw
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self.canvas.draw()
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def _create_controls(self):
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top_frame = ttk.Frame(self)
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top_frame.pack(side=tk.TOP, fill=tk.X, padx=5, pady=5)
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self.controls_frame = ttk.Frame(top_frame)
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self.controls_frame.pack(side=tk.LEFT, fill=tk.X, expand=True)
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ttk.Label(self.controls_frame, text="Range (NM):").pack(side=tk.LEFT)
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all_steps = [10, 20, 40, 80, 100, 160, 240, 320]
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valid_steps = sorted([s for s in all_steps if s <= self.max_range])
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if not valid_steps or self.max_range not in valid_steps:
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valid_steps.append(self.max_range)
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valid_steps.sort()
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self.range_var = tk.IntVar(value=self.max_range)
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self.range_selector = ttk.Combobox(
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self.controls_frame, textvariable=self.range_var,
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values=valid_steps, state="readonly", width=5
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)
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self.range_selector.pack(side=tk.LEFT, padx=5)
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options_frame = ttk.LabelFrame(top_frame, text="Display Options")
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options_frame.pack(side=tk.RIGHT, padx=(10, 0))
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cb_sim_points = ttk.Checkbutton(options_frame, text="Sim Points", variable=self.show_sim_points_var, command=self._on_display_options_changed)
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cb_sim_points.grid(row=0, column=0, sticky='w', padx=5)
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cb_real_points = ttk.Checkbutton(options_frame, text="Real Points", variable=self.show_real_points_var, command=self._on_display_options_changed)
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cb_real_points.grid(row=0, column=1, sticky='w', padx=5)
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cb_sim_trail = ttk.Checkbutton(options_frame, text="Sim Trail", variable=self.show_sim_trail_var, command=self._on_display_options_changed)
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cb_sim_trail.grid(row=1, column=0, sticky='w', padx=5)
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cb_real_trail = ttk.Checkbutton(options_frame, text="Real Trail", variable=self.show_real_trail_var, command=self._on_display_options_changed)
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cb_real_trail.grid(row=1, column=1, sticky='w', padx=5)
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legend_frame = ttk.Frame(top_frame)
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legend_frame.pack(side=tk.RIGHT, padx=(10, 5))
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sim_sw = tk.Canvas(legend_frame, width=16, height=12, highlightthickness=0)
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sim_sw.create_rectangle(0, 0, 16, 12, fill='green', outline='black')
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sim_sw.pack(side=tk.LEFT, padx=(0, 4))
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ttk.Label(legend_frame, text="Simulated").pack(side=tk.LEFT, padx=(0, 8))
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real_sw = tk.Canvas(legend_frame, width=16, height=12, highlightthickness=0)
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real_sw.create_rectangle(0, 0, 16, 12, fill='red', outline='black')
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real_sw.pack(side=tk.LEFT, padx=(2, 4))
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ttk.Label(legend_frame, text="Real").pack(side=tk.LEFT)
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def _create_plot(self):
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fig = Figure(figsize=(5, 5), dpi=100, facecolor="#3E3E3E")
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fig.subplots_adjust(left=0.05, right=0.95, top=0.9, bottom=0.05)
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self.ax = fig.add_subplot(111, projection="polar", facecolor="#2E2E2E")
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self.ax.set_theta_zero_location("N")
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self.ax.set_theta_direction(1)
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self.ax.set_rlabel_position(90)
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self.ax.set_ylim(0, self.range_var.get())
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angles_deg = np.arange(0, 360, 30)
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labels = [f'{(a - 360) if a > 180 else a}°' for a in angles_deg]
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self.ax.set_thetagrids(angles_deg, labels)
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self.ax.tick_params(axis="x", colors="white", labelsize=8)
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self.ax.tick_params(axis="y", colors="white", labelsize=8)
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self.ax.grid(color="white", linestyle="--", linewidth=0.5, alpha=0.5)
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self.ax.spines["polar"].set_color("white")
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self.ax.set_title("PPI Display", color="white")
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(self._path_plot,) = self.ax.plot([], [], "g--", linewidth=1.5)
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(self._start_plot,) = self.ax.plot([], [], "go", markersize=8)
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(self._waypoints_plot,) = self.ax.plot([], [], "y+", markersize=10, mew=2)
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self.preview_artists = [self._path_plot, self._start_plot, self._waypoints_plot]
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limit_rad = np.deg2rad(self.scan_limit_deg)
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(self._scan_line_1,) = self.ax.plot([limit_rad, limit_rad], [0, self.max_range], "y--", linewidth=1)
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(self._scan_line_2,) = self.ax.plot([-limit_rad, -limit_rad], [0, self.max_range], "y--", linewidth=1)
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self.canvas = FigureCanvasTkAgg(fig, master=self)
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self.canvas.draw()
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self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=True)
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self.range_selector.bind("<<ComboboxSelected>>", self._on_range_selected)
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self._update_scan_lines()
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def update_targets(self, targets_data: Union[List[Target], Dict[str, List[Target]]]):
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sim_data = targets_data.get("simulated", []) if isinstance(targets_data, dict) else (targets_data if isinstance(targets_data, list) else [])
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real_data = targets_data.get("real", []) if isinstance(targets_data, dict) else []
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for artists in [self.sim_target_artists, self.real_target_artists, self.sim_trail_artists, self.real_trail_artists, self.target_label_artists]:
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for artist in artists:
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artist.remove()
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artists.clear()
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if self.show_sim_points_var.get() or self.show_sim_trail_var.get():
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for t in sim_data:
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if t.active:
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pos = (np.deg2rad(-t.current_azimuth_deg), t.current_range_nm)
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self._trails["simulated"][t.target_id].append(pos)
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if self.show_real_points_var.get() or self.show_real_trail_var.get():
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for t in real_data:
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if t.active:
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pos = (np.deg2rad(-t.current_azimuth_deg), t.current_range_nm)
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self._trails["real"][t.target_id].append(pos)
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if self.show_sim_points_var.get():
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self._draw_target_visuals([t for t in sim_data if t.active], 'green', self.sim_target_artists)
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if self.show_real_points_var.get():
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self._draw_target_visuals([t for t in real_data if t.active], 'red', self.real_target_artists)
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if self.show_sim_trail_var.get():
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self._draw_trails(self._trails["simulated"], 'limegreen', self.sim_trail_artists)
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if self.show_real_trail_var.get():
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self._draw_trails(self._trails["real"], 'tomato', self.real_trail_artists)
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if self.canvas:
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self.canvas.draw()
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def _draw_target_visuals(self, targets: List[Target], color: str, artist_list: List):
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vector_len_nm = self.range_var.get() / 20.0
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logger = logging.getLogger(__name__)
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for target in targets:
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# Plotting position (theta, r)
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r_nm = target.current_range_nm
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theta_rad_plot = np.deg2rad(-target.current_azimuth_deg)
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(dot,) = self.ax.plot(theta_rad_plot, r_nm, "o", markersize=6, color=color)
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artist_list.append(dot)
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# --- Robust Vector Calculation ---
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# 1. Convert target position to internal Cartesian (x=East, y=North)
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# Use math.* for scalar computations to avoid accidental array behaviors
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az_rad_model = math.radians(target.current_azimuth_deg)
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x_start_nm = r_nm * math.sin(az_rad_model)
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y_start_nm = r_nm * math.cos(az_rad_model)
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# 2. Calculate vector displacement in Cartesian from heading
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# Heading is defined as degrees clockwise from North (0 = North),
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# so the unit vector in Cartesian (East, North) is (sin(h), cos(h)).
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hdg_rad = math.radians(target.current_heading_deg)
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dx_nm = vector_len_nm * math.sin(hdg_rad)
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dy_nm = vector_len_nm * math.cos(hdg_rad)
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# 3. Find end point in Cartesian
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x_end_nm = x_start_nm + dx_nm
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y_end_nm = y_start_nm + dy_nm
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# 4. Convert start and end points to plotting coordinates (theta_plot, r)
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r_end_nm = math.hypot(x_end_nm, y_end_nm)
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theta_end_rad_plot = -math.atan2(x_end_nm, y_end_nm)
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(line,) = self.ax.plot([theta_rad_plot, theta_end_rad_plot], [r_nm, r_end_nm], color=color, linewidth=1.2)
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artist_list.append(line)
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# Debug log: useful to diagnose heading vs plotting coordinates
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try:
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logger.debug(
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"PPIDisplay: TID %s az=%.6f hdg=%.6f theta0_deg=%.3f theta1_deg=%.3f x_start=%.3f y_start=%.3f x_end=%.3f y_end=%.3f",
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target.target_id,
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target.current_azimuth_deg,
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target.current_heading_deg,
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math.degrees(theta_rad_plot),
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math.degrees(theta_end_rad_plot),
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x_start_nm,
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y_start_nm,
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x_end_nm,
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y_end_nm,
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)
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except Exception:
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pass
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txt = self.ax.text(theta_rad_plot, r_nm + (vector_len_nm * 0.5), str(target.target_id), color="white", fontsize=8, ha="center", va="bottom")
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self.target_label_artists.append(txt)
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def _draw_trails(self, trail_data: Dict, color: str, artist_list: List):
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for trail in trail_data.values():
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if len(trail) > 1:
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thetas, rs = zip(*trail)
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(line,) = self.ax.plot(thetas, rs, color=color, linestyle='-', linewidth=0.8, alpha=0.7)
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artist_list.append(line)
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def clear_trails(self):
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self._trails["simulated"].clear()
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self._trails["real"].clear()
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self.update_targets({})
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def _update_scan_lines(self):
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max_r = self.ax.get_ylim()[1]
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limit_rad = np.deg2rad(self.scan_limit_deg)
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self._scan_line_1.set_data([limit_rad, limit_rad], [0, max_r])
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self._scan_line_2.set_data([-limit_rad, -limit_rad], [0, max_r])
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def _on_range_selected(self, event=None):
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self.ax.set_ylim(0, self.range_var.get())
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self._update_scan_lines()
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if self.canvas:
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self.canvas.draw()
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def clear_previews(self):
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for artist in self.preview_artists:
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artist.set_data([], [])
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if self.canvas:
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self.canvas.draw()
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def draw_trajectory_preview(self, waypoints: List[Waypoint], use_spline: bool):
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self.clear_previews()
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self.clear_trails()
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if not waypoints or waypoints[0].maneuver_type != ManeuverType.FLY_TO_POINT: return
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path, _ = Target.generate_path_from_waypoints(waypoints, use_spline)
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if not path: return
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path_thetas, path_rs = [], []
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for point in path:
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x_ft, y_ft = point[1], point[2]
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r_ft = math.sqrt(x_ft**2 + y_ft**2)
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az_rad_plot = -math.atan2(x_ft, y_ft)
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path_rs.append(r_ft / NM_TO_FT)
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path_thetas.append(az_rad_plot)
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self._path_plot.set_data(path_thetas, path_rs)
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wp_thetas, wp_rs = [], []
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for wp in waypoints:
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if wp.maneuver_type == ManeuverType.FLY_TO_POINT:
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r_nm = wp.target_range_nm or 0.0
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az_rad_plot = np.deg2rad(-(wp.target_azimuth_deg or 0.0))
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wp_rs.append(r_nm)
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wp_thetas.append(az_rad_plot)
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self._waypoints_plot.set_data(wp_thetas, wp_rs)
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start_wp = waypoints[0]
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start_r = start_wp.target_range_nm or 0.0
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start_theta = np.deg2rad(-(start_wp.target_azimuth_deg or 0.0))
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self._start_plot.set_data([start_theta], [start_r])
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if self.canvas:
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self.canvas.draw()
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def reconfigure_radar(self, max_range_nm: int, scan_limit_deg: int):
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self.max_range, self.scan_limit_deg = max_range_nm, scan_limit_deg
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steps = [10, 20, 40, 80, 100, 160, 240, 320]
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valid_steps = sorted([s for s in steps if s <= max_range_nm] + ([max_range_nm] if max_range_nm not in steps else []))
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self.range_selector["values"] = valid_steps
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if self.range_var.get() not in valid_steps:
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self.range_var.set(max_range_nm)
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self._on_range_selected()
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def set_connect_callback(self, cb):
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self._connect_callback = cb
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def update_connect_state(self, is_connected: bool):
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# This method should only reflect state, not change UI elements.
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# The parent window is responsible for enabling/disabling controls.
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pass |