\u7a7a\u95f4\u4fe1\u606f：\u76ee\u6807\u7684\u5b9e\u65f6\u4f4d\u7f6e\u3001\u8fd0\u52a8\u8def\u5f84<\/p>\n<\/li>\n
\u65f6\u95f4\u4fe1\u606f：\u76ee\u6807\u5728\u4e0d\u540c\u65f6\u95f4\u70b9\u7684\u72b6\u6001<\/p>\n<\/li>\n
\u8fd0\u52a8\u5b66\u4fe1\u606f：\u901f\u5ea6\u3001\u52a0\u901f\u5ea6\u3001\u822a\u5411\u53d8\u5316<\/p>\n<\/li>\n
\u73af\u5883\u4fe1\u606f：\u9ad8\u5ea6\u3001\u5730\u5f62\u5173\u8054\u3001\u6c14\u8c61\u5f71\u54cd<\/p>\n<\/li>\n
\u6218\u672f\u4fe1\u606f：\u4f5c\u6218\u610f\u56fe\u3001\u5a01\u80c1\u7b49\u7ea7\u3001\u8fd0\u52a8\u6a21\u5f0f<\/p>\n<\/li>\n<\/ul>\n
1.2 \u8f68\u8ff9\u53ef\u89c6\u5316\u7684\u6311\u6218<\/h4>\n
\u8f68\u8ff9\u53ef\u89c6\u5316\u9762\u4e34\u591a\u65b9\u9762\u7684\u6280\u672f\u6311\u6218：<\/p>\n
![\"\"](\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260121101654-6970a79652ca0.png\")
<\/p>\n
1.3 PyVista\u5728\u8f68\u8ff9\u53ef\u89c6\u5316\u4e2d\u7684\u4f18\u52bf<\/h4>\n
PyVista\u63d0\u4f9b\u4e86\u5b8c\u6574\u76843D\u8f68\u8ff9\u53ef\u89c6\u5316\u89e3\u51b3\u65b9\u6848：<\/p>\n
\u4e30\u5bcc\u7684\u51e0\u4f55\u4f53\u652f\u6301：\u652f\u6301\u70b9\u3001\u7ebf\u3001\u9762\u3001\u4f53\u7b49\u591a\u79cd\u51e0\u4f55\u8868\u793a<\/p>\n<\/li>\n
\u7075\u6d3b\u7684\u989c\u8272\u6620\u5c04：\u652f\u6301\u8fde\u7eed\u3001\u79bb\u6563\u7684\u989c\u8272\u6620\u5c04\u65b9\u6848<\/p>\n<\/li>\n
\u9ad8\u6548\u7684\u7ba1\u7ebf\u67b6\u6784：\u652f\u6301\u5927\u89c4\u6a21\u8f68\u8ff9\u6570\u636e\u7684\u5feb\u901f\u6e32\u67d3<\/p>\n<\/li>\n
\u5b8c\u5584\u7684\u65f6\u95f4\u652f\u6301：\u652f\u6301\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u7684\u52a8\u6001\u5c55\u793a<\/p>\n<\/li>\n
\u4ea4\u4e92\u5f0f\u5206\u6790\u5de5\u5177：\u652f\u6301\u8f68\u8ff9\u7684\u9009\u53d6\u3001\u6d4b\u91cf\u3001\u5206\u6790<\/p>\n<\/li>\n
2. \u6570\u636e\u51c6\u5907：\u8f68\u8ff9\u6570\u636e\u7684\u683c\u5f0f\u4e0e\u5904\u7406<\/h3>\n2.1 \u5e38\u89c1\u7684\u8f68\u8ff9\u6570\u636e\u683c\u5f0f<\/h4>\n
\u8f68\u8ff9\u6570\u636e\u53ef\u4ee5\u6709\u591a\u79cd\u683c\u5f0f，\u6211\u4eec\u9700\u8981\u6839\u636e\u6570\u636e\u6e90\u7684\u7279\u70b9\u9009\u62e9\u5408\u9002\u7684\u5904\u7406\u65b9\u6cd5：<\/p>\n
# 1. CSV\u683c\u5f0f\u793a\u4f8b
\ncsv_data_example = """timestamp,object_id,latitude,longitude,altitude,speed,course
\n2024-01-01 12:00:00,001,39.9042,116.4074,10000,250,45
\n2024-01-01 12:00:10,001,39.9055,116.4101,10100,255,46
\n2024-01-01 12:00:20,001,39.9068,116.4128,10200,260,47"""<\/p>\n
# 2. JSON\u683c\u5f0f\u793a\u4f8b
\njson_data_example = {
\n "trajectory": {
\n "id": "001",
\n "points": [
\n {"t": 0, "x": 100, "y": 200, "z": 3000, "v": 250},
\n {"t": 10, "x": 150, "y": 220, "z": 3100, "v": 255}
\n ]
\n }
\n}<\/p>\n
# 3. \u4e8c\u8fdb\u5236\u683c\u5f0f（\u9002\u5408\u5927\u89c4\u6a21\u6570\u636e）
\nimport struct
\nbinary_format = struct.Struct('3f2f') # x,y,z,v,heading<\/p>\n
2.2 \u8f68\u8ff9\u6570\u636e\u5904\u7406\u57fa\u7c7b<\/h4>\n
\u521b\u5efa\u4e00\u4e2a\u901a\u7528\u7684\u8f68\u8ff9\u6570\u636e\u5904\u7406\u57fa\u7c7b，\u652f\u6301\u591a\u79cd\u6570\u636e\u683c\u5f0f：<\/p>\n
import pandas as pd
\nimport numpy as np
\nimport json
\nimport csv
\nfrom datetime import datetime, timedelta
\nimport math<\/p>\n
class TrajectoryData:
\n """\u8f68\u8ff9\u6570\u636e\u5904\u7406\u57fa\u7c7b"""<\/p>\n
def __init__(self):
\n self.trajectories = {} # \u8f68\u8ff9\u5b57\u5178 {id: Trajectory}
\n self.coordinate_system = 'cartesian' # \u5750\u6807\u7cfb\u7c7b\u578b
\n self.time_zone = 'UTC' # \u65f6\u533a<\/p>\n
class TrajectoryPoint:
\n """\u8f68\u8ff9\u70b9\u7c7b"""<\/p>\n
def __init__(self, timestamp, position, **kwargs):
\n self.timestamp = timestamp
\n self.position = np.array(position, dtype=float) # [x, y, z]<\/p>\n
# \u8fd0\u52a8\u5b66\u53c2\u6570
\n self.velocity = kwargs.get('velocity', 0.0) # \u901f\u5ea6
\n self.heading = kwargs.get('heading', 0.0) # \u822a\u5411
\n self.pitch = kwargs.get('pitch', 0.0) # \u4fef\u4ef0
\n self.acceleration = kwargs.get('acceleration', 0.0) # \u52a0\u901f\u5ea6<\/p>\n
# \u5176\u4ed6\u53c2\u6570
\n self.attributes = kwargs # \u6240\u6709\u5c5e\u6027<\/p>\n
def __repr__(self):
\n return f"Point(t={self.timestamp}, pos={self.position}, v={self.velocity})"<\/p>\n
class Trajectory:
\n """\u8f68\u8ff9\u7c7b"""<\/p>\n
def __init__(self, trajectory_id, object_type="unknown", color=None):
\n self.id = trajectory_id
\n self.object_type = object_type
\n self.color = color
\n self.points = [] # TrajectoryPoint\u5217\u8868
\n self.start_time = None
\n self.end_time = None
\n self.duration = 0.0
\n self.total_distance = 0.0<\/p>\n
def add_point(self, point):
\n """\u6dfb\u52a0\u8f68\u8ff9\u70b9"""
\n if not self.points:
\n self.start_time = point.timestamp
\n self.points.append(point)
\n self.end_time = point.timestamp<\/p>\n
# \u8ba1\u7b97\u7d2f\u79ef\u8ddd\u79bb
\n if len(self.points) > 1:
\n last_point = self.points[-2]
\n distance = np.linalg.norm(point.position – last_point.position)
\n self.total_distance += distance<\/p>\n
# \u8ba1\u7b97\u6301\u7eed\u65f6\u95f4
\n if self.start_time and self.end_time:
\n if isinstance(self.start_time, (int, float)) and isinstance(self.end_time, (int, float)):
\n self.duration = self.end_time – self.start_time
\n else:
\n # \u5982\u679c\u662fdatetime\u5bf9\u8c61
\n self.duration = (self.end_time – self.start_time).total_seconds()<\/p>\n
def get_point_at_time(self, timestamp):
\n """\u83b7\u53d6\u6307\u5b9a\u65f6\u95f4\u7684\u8f68\u8ff9\u70b9（\u63d2\u503c）"""
\n if not self.points:
\n return None<\/p>\n
# \u627e\u5230\u6700\u63a5\u8fd1\u7684\u4e24\u4e2a\u70b9
\n for i in range(len(self.points) – 1):
\n p1 = self.points[i]
\n p2 = self.points[i + 1]<\/p>\n
if p1.timestamp <= timestamp <= p2.timestamp:
\n # \u7ebf\u6027\u63d2\u503c
\n ratio = (timestamp – p1.timestamp) \/ (p2.timestamp – p1.timestamp)<\/p>\n
# \u4f4d\u7f6e\u63d2\u503c
\n position = p1.position + (p2.position – p1.position) * ratio<\/p>\n
# \u901f\u5ea6\u63d2\u503c
\n velocity = p1.velocity + (p2.velocity – p1.velocity) * ratio<\/p>\n
# \u521b\u5efa\u63d2\u503c\u70b9
\n interpolated_point = self.__class__.TrajectoryPoint(
\n timestamp=timestamp,
\n position=position,
\n velocity=velocity,
\n heading=p1.heading + (p2.heading – p1.heading) * ratio
\n )<\/p>\n
return interpolated_point<\/p>\n
return None<\/p>\n
def resample(self, interval=1.0):
\n """\u91cd\u65b0\u91c7\u6837\u8f68\u8ff9\u70b9"""
\n if not self.points or len(self.points) < 2:
\n return<\/p>\n
resampled_points = []
\n current_time = self.start_time<\/p>\n
while current_time <= self.end_time:
\n point = self.get_point_at_time(current_time)
\n if point:
\n resampled_points.append(point)
\n current_time += interval<\/p>\n
self.points = resampled_points<\/p>\n
def get_statistics(self):
\n """\u83b7\u53d6\u8f68\u8ff9\u7edf\u8ba1\u4fe1\u606f"""
\n if not self.points:
\n return {}<\/p>\n
speeds = [p.velocity for p in self.points]
\n altitudes = [p.position[2] for p in self.points]
\n headings = [p.heading for p in self.points]<\/p>\n
return {
\n 'point_count': len(self.points),
\n 'duration': self.duration,
\n 'total_distance': self.total_distance,
\n 'avg_speed': np.mean(speeds) if speeds else 0,
\n 'max_speed': max(speeds) if speeds else 0,
\n 'min_altitude': min(altitudes) if altitudes else 0,
\n 'max_altitude': max(altitudes) if altitudes else 0,
\n 'avg_heading': np.mean(headings) if headings else 0
\n }<\/p>\n
def load_from_csv(self, filepath, time_column='timestamp', id_column='object_id',
\n x_column='x', y_column='y', z_column='z', **kwargs):
\n """\u4eceCSV\u6587\u4ef6\u52a0\u8f7d\u8f68\u8ff9\u6570\u636e"""
\n print(f"\u52a0\u8f7dCSV\u6587\u4ef6: {filepath}")<\/p>\n
try:
\n df = pd.read_csv(filepath)
\n print(f"\u6570\u636e\u5f62\u72b6: {df.shape}")
\n print(f"\u5217\u540d: {list(df.columns)}")<\/p>\n
# \u6309\u76ee\u6807ID\u5206\u7ec4
\n if id_column in df.columns:
\n grouped = df.groupby(id_column)<\/p>\n
for obj_id, group in grouped:
\n print(f"\u5904\u7406\u76ee\u6807 {obj_id}，\u6570\u636e\u70b9: {len(group)}")<\/p>\n
# \u521b\u5efa\u8f68\u8ff9
\n trajectory = self.Trajectory(str(obj_id))<\/p>\n
# \u5904\u7406\u6bcf\u4e2a\u6570\u636e\u70b9
\n for _, row in group.iterrows():
\n # \u89e3\u6790\u65f6\u95f4
\n timestamp = row[time_column]
\n if isinstance(timestamp, str):
\n try:
\n timestamp = pd.to_datetime(timestamp)
\n except:
\n # \u8f6c\u6362\u4e3a\u65f6\u95f4\u6233
\n timestamp = float(timestamp)<\/p>\n
# \u89e3\u6790\u4f4d\u7f6e
\n x = float(row[x_column]) if x_column in row else 0.0
\n y = float(row[y_column]) if y_column in row else 0.0
\n z = float(row[z_column]) if z_column in row else 0.0<\/p>\n
# \u83b7\u53d6\u5176\u4ed6\u5c5e\u6027
\n attributes = {}
\n for col, val in row.items():
\n if col not in [time_column, id_column, x_column, y_column, z_column]:
\n try:
\n attributes[col] = float(val)
\n except:
\n attributes[col] = val<\/p>\n
# \u521b\u5efa\u8f68\u8ff9\u70b9
\n point = self.TrajectoryPoint(
\n timestamp=timestamp,
\n position=[x, y, z],
\n **attributes
\n )<\/p>\n
trajectory.add_point(point)<\/p>\n
# \u6dfb\u52a0\u5230\u8f68\u8ff9\u5b57\u5178
\n self.trajectories[trajectory.id] = trajectory<\/p>\n
else:
\n print(f"\u8b66\u544a: \u672a\u627e\u5230ID\u5217 '{id_column}'")<\/p>\n
except Exception as e:
\n print(f"\u52a0\u8f7dCSV\u6587\u4ef6\u5931\u8d25: {e}")
\n import traceback
\n traceback.print_exc()<\/p>\n
def load_from_json(self, filepath):
\n """\u4eceJSON\u6587\u4ef6\u52a0\u8f7d\u8f68\u8ff9\u6570\u636e"""
\n with open(filepath, 'r', encoding='utf-8') as f:
\n data = json.load(f)<\/p>\n
if isinstance(data, list):
\n for item in data:
\n self._load_single_trajectory_from_dict(item)
\n elif isinstance(data, dict):
\n if 'trajectories' in data:
\n for traj_data in data['trajectories']:
\n self._load_single_trajectory_from_dict(traj_data)
\n else:
\n self._load_single_trajectory_from_dict(data)<\/p>\n
def _load_single_trajectory_from_dict(self, data):
\n """\u4ece\u5b57\u5178\u52a0\u8f7d\u5355\u4e2a\u8f68\u8ff9"""
\n traj_id = data.get('id', str(len(self.trajectories)))
\n traj_type = data.get('type', 'unknown')<\/p>\n
trajectory = self.Trajectory(traj_id, traj_type)<\/p>\n
points = data.get('points', [])
\n for point_data in points:
\n timestamp = point_data.get('t', 0)
\n x = point_data.get('x', 0.0)
\n y = point_data.get('y', 0.0)
\n z = point_data.get('z', 0.0)<\/p>\n
point = self.TrajectoryPoint(
\n timestamp=timestamp,
\n position=[x, y, z],
\n velocity=point_data.get('v', 0.0),
\n heading=point_data.get('heading', 0.0)
\n )<\/p>\n
trajectory.add_point(point)<\/p>\n
self.trajectories[trajectory.id] = trajectory<\/p>\n
def convert_coordinates(self, from_system='wgs84', to_system='cartesian'):
\n """\u5750\u6807\u8f6c\u6362（\u7b80\u5316\u7248\u672c）"""
\n if from_system == 'wgs84' and to_system == 'cartesian':
\n # \u7b80\u5316\u7684WGS84\u5230\u7b1b\u5361\u5c14\u5750\u6807\u8f6c\u6362
\n for traj_id, trajectory in self.trajectories.items():
\n for point in trajectory.points:
\n # \u83b7\u53d6\u7ecf\u7eac\u9ad8
\n lon, lat, alt = point.position<\/p>\n
# \u8f6c\u6362\u4e3a\u5f27\u5ea6
\n lat_rad = math.radians(lat)
\n lon_rad = math.radians(lon)<\/p>\n
# \u7b80\u5316\u7684\u8f6c\u6362（\u9002\u5408\u5c0f\u8303\u56f4\u533a\u57df）
\n R = 6371000 # \u5730\u7403\u534a\u5f84（\u7c73）
\n x = (R + alt) * math.cos(lat_rad) * math.cos(lon_rad)
\n y = (R + alt) * math.cos(lat_rad) * math.sin(lon_rad)
\n z = (R + alt) * math.sin(lat_rad)<\/p>\n
point.position = np.array([x, y, z])<\/p>\n
def get_trajectory(self, trajectory_id):
\n """\u83b7\u53d6\u6307\u5b9aID\u7684\u8f68\u8ff9"""
\n return self.trajectories.get(trajectory_id)<\/p>\n
def get_all_trajectories(self):
\n """\u83b7\u53d6\u6240\u6709\u8f68\u8ff9"""
\n return list(self.trajectories.values())<\/p>\n
def get_summary(self):
\n """\u83b7\u53d6\u6570\u636e\u6458\u8981"""
\n return {
\n 'trajectory_count': len(self.trajectories),
\n 'total_points': sum(len(t.points) for t in self.trajectories.values()),
\n 'trajectory_ids': list(self.trajectories.keys())
\n }<\/p>\n
2.3 \u8f68\u8ff9\u6570\u636e\u91c7\u6837\u4e0e\u4f18\u5316<\/h4>\n
\u5bf9\u4e8e\u5927\u89c4\u6a21\u8f68\u8ff9\u6570\u636e，\u9700\u8981\u8fdb\u884c\u91c7\u6837\u548c\u4f18\u5316\u4ee5\u63d0\u9ad8\u53ef\u89c6\u5316\u6027\u80fd：<\/p>\n
class TrajectoryOptimizer:
\n """\u8f68\u8ff9\u4f18\u5316\u5668"""<\/p>\n
@staticmethod
\n def douglas_peucker(points, epsilon):
\n """\u9053\u683c\u62c9\u65af-\u666e\u514b\u7b97\u6cd5\u7b80\u5316\u8f68\u8ff9"""
\n if len(points) < 3:
\n return points<\/p>\n
# \u627e\u5230\u8ddd\u79bb\u6700\u8fdc\u7684\u70b9
\n dmax = 0
\n index = 0<\/p>\n
for i in range(1, len(points) – 1):
\n d = TrajectoryOptimizer._perpendicular_distance(
\n points[i], points[0], points[-1]
\n )
\n if d > dmax:
\n dmax = d
\n index = i<\/p>\n
# \u9012\u5f52\u7b80\u5316
\n if dmax > epsilon:
\n left = TrajectoryOptimizer.douglas_peucker(points[:index+1], epsilon)
\n right = TrajectoryOptimizer.douglas_peucker(points[index:], epsilon)
\n return left[:-1] + right
\n else:
\n return [points[0], points[-1]]<\/p>\n
@staticmethod
\n def _perpendicular_distance(point, line_start, line_end):
\n """\u8ba1\u7b97\u70b9\u5230\u76f4\u7ebf\u7684\u5782\u76f4\u8ddd\u79bb"""
\n if np.array_equal(line_start, line_end):
\n return np.linalg.norm(point – line_start)<\/p>\n
# \u8ba1\u7b97\u70b9\u5230\u76f4\u7ebf\u7684\u8ddd\u79bb
\n n = np.linalg.norm(line_end – line_start)
\n distance = np.linalg.norm(
\n np.cross(line_end – line_start, line_start – point)
\n ) \/ n<\/p>\n
return distance<\/p>\n
@staticmethod
\n def uniform_sampling(points, target_count):
\n """\u5747\u5300\u91c7\u6837"""
\n if len(points) <= target_count:
\n return points<\/p>\n
indices = np.linspace(0, len(points) – 1, target_count, dtype=int)
\n return [points[i] for i in indices]<\/p>\n
@staticmethod
\n def temporal_sampling(trajectory, time_interval):
\n """\u65f6\u95f4\u5747\u5300\u91c7\u6837"""
\n if not trajectory.points:
\n return trajectory<\/p>\n
resampled = TrajectoryData.Trajectory(trajectory.id, trajectory.object_type)<\/p>\n
current_time = trajectory.start_time
\n while current_time <= trajectory.end_time:
\n point = trajectory.get_point_at_time(current_time)
\n if point:
\n resampled.add_point(point)
\n current_time += time_interval<\/p>\n
return resampled<\/p>\n
@staticmethod
\n def speed_based_sampling(trajectory, speed_threshold=0.1):
\n """\u57fa\u4e8e\u901f\u5ea6\u53d8\u5316\u7684\u91c7\u6837"""
\n if len(trajectory.points) < 2:
\n return trajectory<\/p>\n
simplified_points = [trajectory.points[0]]<\/p>\n
for i in range(1, len(trajectory.points) – 1):
\n # \u8ba1\u7b97\u901f\u5ea6\u53d8\u5316
\n speed_change = abs(
\n trajectory.points[i].velocity – trajectory.points[i-1].velocity
\n )<\/p>\n
# \u5982\u679c\u901f\u5ea6\u53d8\u5316\u663e\u8457，\u4fdd\u7559\u8be5\u70b9
\n if speed_change > speed_threshold:
\n simplified_points.append(trajectory.points[i])<\/p>\n
simplified_points.append(trajectory.points[-1])<\/p>\n
simplified_traj = TrajectoryData.Trajectory(trajectory.id, trajectory.object_type)
\n for point in simplified_points:
\n simplified_traj.add_point(point)<\/p>\n
return simplified_traj<\/p>\n
3. \u57fa\u7840\u8f68\u8ff9\u53ef\u89c6\u5316\u6280\u672f<\/h3>\n3.1 \u7b80\u5355\u8f68\u8ff9\u7ebf\u7ed8\u5236<\/h4>\n
\u6700\u57fa\u672c\u7684\u8f68\u8ff9\u53ef\u89c6\u5316\u662f\u7ed8\u5236\u8fde\u63a5\u8f68\u8ff9\u70b9\u7684\u7ebf：<\/p>\n
import pyvista as pv
\nimport numpy as np<\/p>\n
class BasicTrajectoryVisualizer:
\n """\u57fa\u7840\u8f68\u8ff9\u53ef\u89c6\u5316\u5668"""<\/p>\n
def __init__(self):
\n self.plotter = None
\n self.trajectory_meshes = {}<\/p>\n
def create_simple_line(self, points, color='white', line_width=2, name=None):
\n """\u521b\u5efa\u7b80\u5355\u8f68\u8ff9\u7ebf"""
\n if len(points) < 2:
\n return None<\/p>\n
# \u8f6c\u6362\u4e3aNumPy\u6570\u7ec4
\n points_array = np.array(points)<\/p>\n
# \u521b\u5efa\u7ebf
\n line = pv.lines_from_points(points_array)<\/p>\n
# \u6dfb\u52a0\u5c5e\u6027
\n line['distance'] = np.linspace(0, 1, len(points_array))<\/p>\n
return line<\/p>\n
def create_spline(self, points, resolution=100, degree=3, name=None):
\n """\u521b\u5efa\u6837\u6761\u66f2\u7ebf"""
\n if len(points) < 2:
\n return None<\/p>\n
# \u8f6c\u6362\u4e3aNumPy\u6570\u7ec4
\n points_array = np.array(points)<\/p>\n
# \u521b\u5efa\u6837\u6761\u66f2\u7ebf
\n spline = pv.Spline(points_array, resolution)<\/p>\n
return spline<\/p>\n
def create_tube(self, points, radius=0.5, n_sides=8, name=None):
\n """\u521b\u5efa\u7ba1\u9053\u8f68\u8ff9"""
\n if len(points) < 2:
\n return None<\/p>\n
# \u521b\u5efa\u6837\u6761\u66f2\u7ebf
\n spline = self.create_spline(points)
\n if spline is None:
\n return None<\/p>\n
# \u521b\u5efa\u7ba1\u9053
\n tube = spline.tube(radius=radius, n_sides=n_sides)<\/p>\n
return tube<\/p>\n
def add_trajectory_line(self, trajectory, style='line', **kwargs):
\n """\u6dfb\u52a0\u8f68\u8ff9\u7ebf\u5230\u573a\u666f"""
\n if not trajectory.points:
\n return None<\/p>\n
# \u63d0\u53d6\u4f4d\u7f6e\u70b9
\n points = [p.position for p in trajectory.points]<\/p>\n
# \u6839\u636e\u6837\u5f0f\u521b\u5efa\u8f68\u8ff9
\n if style == 'line':
\n mesh = self.create_simple_line(points, **kwargs)
\n elif style == 'spline':
\n mesh = self.create_spline(points, **kwargs)
\n elif style == 'tube':
\n mesh = self.create_tube(points, **kwargs)
\n else:
\n mesh = self.create_simple_line(points, **kwargs)<\/p>\n
if mesh is None:
\n return None<\/p>\n
# \u6dfb\u52a0\u5230\u8f68\u8ff9\u7f51\u683c\u5b57\u5178
\n traj_id = trajectory.id
\n self.trajectory_meshes[traj_id] = mesh<\/p>\n
return mesh<\/p>\n
def visualize_trajectories(self, trajectories, window_size=(1200, 800),
\n show_axes=True, show_grid=True):
\n """\u53ef\u89c6\u5316\u591a\u6761\u8f68\u8ff9"""
\n # \u521b\u5efa\u7ed8\u56fe\u7a97\u53e3
\n self.plotter = pv.Plotter(window_size=window_size, title="\u8f68\u8ff9\u53ef\u89c6\u5316")<\/p>\n
# \u6dfb\u52a0\u8f68\u8ff9
\n for trajectory in trajectories:
\n # \u968f\u673a\u989c\u8272
\n color = np.random.rand(3)<\/p>\n
# \u521b\u5efa\u8f68\u8ff9\u7ebf
\n mesh = self.add_trajectory_line(
\n trajectory,
\n style='tube',
\n radius=0.3,
\n color=color
\n )<\/p>\n
if mesh and self.plotter:
\n # \u6dfb\u52a0\u8f68\u8ff9\u7ebf
\n self.plotter.add_mesh(
\n mesh,
\n color=color,
\n opacity=0.8,
\n name=f'trajectory_{trajectory.id}',
\n show_edges=False
\n )<\/p>\n
# \u6dfb\u52a0\u8f68\u8ff9\u70b9
\n points = np.array([p.position for p in trajectory.points])
\n if len(points) > 0:
\n # \u5747\u5300\u91c7\u6837\u70b9
\n sample_indices = np.linspace(0, len(points)-1, 20, dtype=int)
\n sample_points = points[sample_indices]<\/p>\n
points_mesh = pv.PolyData(sample_points)
\n self.plotter.add_mesh(
\n points_mesh,
\n color=color,
\n point_size=5,
\n render_points_as_spheres=True,
\n name=f'points_{trajectory.id}'
\n )<\/p>\n
# \u8bbe\u7f6e\u573a\u666f
\n if show_axes:
\n self.plotter.add_axes()<\/p>\n
if show_grid:
\n self.plotter.show_grid()<\/p>\n
# \u8bbe\u7f6e\u76f8\u673a
\n self.plotter.camera_position = [(100, 100, 100), (0, 0, 0), (0, 0, 1)]
\n self.plotter.set_background('black')<\/p>\n
# \u663e\u793a
\n self.plotter.show()<\/p>\n
3.2 \u989c\u8272\u6620\u5c04\u4e0e\u8f68\u8ff9\u5c5e\u6027\u53ef\u89c6\u5316<\/h4>\n
\u8f68\u8ff9\u7684\u4e0d\u540c\u5c5e\u6027\u53ef\u4ee5\u901a\u8fc7\u989c\u8272\u6620\u5c04\u6765\u53ef\u89c6\u5316：<\/p>\n
class EnhancedTrajectoryVisualizer(BasicTrajectoryVisualizer):
\n """\u589e\u5f3a\u8f68\u8ff9\u53ef\u89c6\u5316\u5668（\u652f\u6301\u989c\u8272\u6620\u5c04）"""<\/p>\n
def create_colored_trajectory(self, trajectory, color_by='speed',
\n colormap='plasma', style='tube', **kwargs):
\n """\u521b\u5efa\u5e26\u989c\u8272\u6620\u5c04\u7684\u8f68\u8ff9"""
\n if not trajectory.points:
\n return None<\/p>\n
# \u63d0\u53d6\u4f4d\u7f6e\u70b9\u548c\u5c5e\u6027
\n points = np.array([p.position for p in trajectory.points])<\/p>\n
# \u6839\u636e\u5c5e\u6027\u83b7\u53d6\u989c\u8272\u503c
\n if color_by == 'speed':
\n scalars = np.array([p.velocity for p in trajectory.points])
\n elif color_by == 'altitude':
\n scalars = np.array([p.position[2] for p in trajectory.points])
\n elif color_by == 'time':
\n # \u5f52\u4e00\u5316\u65f6\u95f4
\n times = np.array([p.timestamp for p in trajectory.points])
\n if isinstance(times[0], (int, float)):
\n scalars = (times – times.min()) \/ (times.max() – times.min() + 1e-10)
\n else:
\n # \u5982\u679c\u662fdatetime，\u8f6c\u6362\u4e3a\u65f6\u95f4\u6233
\n timestamps = np.array([t.timestamp() for t in times])
\n scalars = (timestamps – timestamps.min()) \/ (timestamps.max() – timestamps.min() + 1e-10)
\n elif color_by == 'distance':
\n # \u8ba1\u7b97\u7d2f\u79ef\u8ddd\u79bb
\n distances = [0]
\n for i in range(1, len(points)):
\n dist = np.linalg.norm(points[i] – points[i-1])
\n distances.append(distances[-1] + dist)
\n scalars = np.array(distances)
\n else:
\n scalars = np.linspace(0, 1, len(points))<\/p>\n
# \u521b\u5efa\u8f68\u8ff9\u51e0\u4f55
\n if style == 'line':
\n mesh = self.create_simple_line(points, **kwargs)
\n elif style == 'spline':
\n mesh = self.create_spline(points, **kwargs)
\n elif style == 'tube':
\n mesh = self.create_tube(points, **kwargs)<\/p>\n
if mesh is None:
\n return None<\/p>\n
# \u6dfb\u52a0\u6807\u91cf\u6570\u636e
\n # \u7531\u4e8e\u6837\u6761\u63d2\u503c，\u9700\u8981\u5c06\u6807\u91cf\u6570\u636e\u6620\u5c04\u5230\u65b0\u7684\u70b9
\n if len(scalars) > 0:
\n # \u5bf9\u4e8e\u6837\u6761\u6216\u7ba1\u9053，\u9700\u8981\u63d2\u503c\u6807\u91cf
\n if style in ['spline', 'tube']:
\n # \u521b\u5efa\u53c2\u6570\u5316\u8868\u793a
\n t = np.linspace(0, 1, len(points))
\n t_new = np.linspace(0, 1, len(mesh.points))<\/p>\n
# \u7ebf\u6027\u63d2\u503c\u6807\u91cf
\n from scipy import interpolate
\n if len(t) > 1:
\n interp_func = interpolate.interp1d(t, scalars,
\n bounds_error=False,
\n fill_value='extrapolate')
\n mesh_scalars = interp_func(t_new)
\n else:
\n mesh_scalars = np.ones(len(mesh.points)) * scalars[0]
\n else:
\n mesh_scalars = scalars<\/p>\n
mesh[color_by] = mesh_scalars<\/p>\n
return mesh<\/p>\n
def add_color_mapped_trajectory(self, trajectory, color_by='speed',
\n colormap='plasma', style='tube', **kwargs):
\n """\u6dfb\u52a0\u989c\u8272\u6620\u5c04\u8f68\u8ff9\u5230\u573a\u666f"""
\n mesh = self.create_colored_trajectory(
\n trajectory, color_by, colormap, style, **kwargs
\n )<\/p>\n
if mesh is None:
\n return None<\/p>\n
traj_id = trajectory.id
\n self.trajectory_meshes[traj_id] = mesh<\/p>\n
return mesh<\/p>\n
def visualize_with_color_mapping(self, trajectories, color_by='speed',
\n colormap='plasma', window_size=(1400, 900)):
\n """\u53ef\u89c6\u5316\u5e26\u989c\u8272\u6620\u5c04\u7684\u8f68\u8ff9"""
\n self.plotter = pv.Plotter(window_size=window_size,
\n title=f"\u8f68\u8ff9\u53ef\u89c6\u5316 – \u989c\u8272\u6620\u5c04: {color_by}")<\/p>\n
for trajectory in trajectories:
\n # \u521b\u5efa\u989c\u8272\u6620\u5c04\u8f68\u8ff9
\n mesh = self.add_color_mapped_trajectory(
\n trajectory,
\n color_by=color_by,
\n colormap=colormap,
\n style='tube',
\n radius=0.3
\n )<\/p>\n
if mesh and self.plotter:
\n # \u6dfb\u52a0\u8f68\u8ff9（\u5e26\u989c\u8272\u6620\u5c04）
\n self.plotter.add_mesh(
\n mesh,
\n scalars=color_by,
\n cmap=colormap,
\n opacity=0.8,
\n clim=[mesh[color_by].min(), mesh[color_by].max()],
\n show_scalar_bar=True,
\n scalar_bar_args={'title': f'{color_by}'},
\n name=f'trajectory_{trajectory.id}',
\n show_edges=False
\n )<\/p>\n
# \u6dfb\u52a0\u8f68\u8ff9\u8d77\u59cb\u70b9
\n if trajectory.points:
\n start_point = trajectory.points[0].position
\n end_point = trajectory.points[-1].position<\/p>\n
# \u8d77\u59cb\u70b9
\n start_mesh = pv.Sphere(center=start_point, radius=0.5)
\n self.plotter.add_mesh(
\n start_mesh,
\n color='green',
\n name=f'start_{trajectory.id}'
\n )<\/p>\n
# \u7ec8\u70b9
\n end_mesh = pv.Sphere(center=end_point, radius=0.5)
\n self.plotter.add_mesh(
\n end_mesh,
\n color='red',
\n name=f'end_{trajectory.id}'
\n )<\/p>\n
# \u8bbe\u7f6e\u573a\u666f
\n self.plotter.add_axes()
\n self.plotter.show_grid()<\/p>\n
# \u8bbe\u7f6e\u76f8\u673a
\n self.plotter.camera_position = [(100, 100, 100), (0, 0, 0), (0, 0, 1)]
\n self.plotter.set_background('black')<\/p>\n
# \u663e\u793a
\n self.plotter.show()<\/p>\n
4. \u6848\u4f8b1：\u76ee\u6807\u98de\u884c\u8f68\u8ff9\u53ef\u89c6\u5316<\/h3>\n4.1 \u6570\u636e\u751f\u6210\u4e0e\u52a0\u8f7d<\/h4>\n
\u9996\u5148，\u6211\u4eec\u521b\u5efa\u4e00\u4e2a\u6a21\u62df\u7684\u76ee\u6807\u98de\u884c\u8f68\u8ff9\u6570\u636e\u96c6：<\/p>\n
def generate_flight_trajectory(num_points=100, trajectory_id='001'):
\n """\u751f\u6210\u6a21\u62df\u98de\u884c\u8f68\u8ff9\u6570\u636e"""
\n from datetime import datetime, timedelta<\/p>\n
# \u521d\u59cb\u53c2\u6570
\n start_time = datetime(2024, 1, 1, 12, 0, 0)
\n start_pos = np.array([0, 0, 1000]) # \u8d77\u59cb\u4f4d\u7f6e
\n start_speed = 200 # \u8d77\u59cb\u901f\u5ea6 (m\/s)<\/p>\n
trajectory = TrajectoryData.Trajectory(trajectory_id, 'aircraft')<\/p>\n
# \u751f\u6210\u8f68\u8ff9\u70b9
\n for i in range(num_points):
\n t = i * 10 # 10\u79d2\u95f4\u9694<\/p>\n
# \u8ba1\u7b97\u4f4d\u7f6e（\u5706\u5468\u8fd0\u52a8 + \u722c\u5347）
\n angle = math.radians(t * 2) # \u6bcf10\u79d2\u8f6c2\u5ea6
\n radius = 5000 # \u534a\u5f84<\/p>\n
x = start_pos[0] + radius * math.cos(angle)
\n y = start_pos[1] + radius * math.sin(angle)
\n z = start_pos[2] + t * 5 # \u6bcf10\u79d2\u722c\u534750\u7c73<\/p>\n
# \u8ba1\u7b97\u901f\u5ea6（\u9010\u6e10\u52a0\u901f）
\n speed = start_speed + t * 0.2 # \u6bcf\u79d2\u52a0\u901f0.2m\/s<\/p>\n
# \u8ba1\u7b97\u822a\u5411
\n heading = math.degrees(angle + math.pi\/2) # \u5207\u7ebf\u65b9\u5411<\/p>\n
# \u521b\u5efa\u8f68\u8ff9\u70b9
\n timestamp = start_time + timedelta(seconds=t)
\n point = TrajectoryData.TrajectoryPoint(
\n timestamp=timestamp,
\n position=[x, y, z],
\n velocity=speed,
\n heading=heading
\n )<\/p>\n
trajectory.add_point(point)<\/p>\n
return trajectory<\/p>\n
def save_trajectory_to_csv(trajectory, filename='flight_trajectory.csv'):
\n """\u4fdd\u5b58\u8f68\u8ff9\u5230CSV\u6587\u4ef6"""
\n data = []<\/p>\n
for point in trajectory.points:
\n row = {
\n 'timestamp': point.timestamp,
\n 'object_id': trajectory.id,
\n 'x': point.position[0],
\n 'y': point.position[1],
\n 'z': point.position[2],
\n 'speed': point.velocity,
\n 'heading': point.heading
\n }
\n data.append(row)<\/p>\n
df = pd.DataFrame(data)
\n df.to_csv(filename, index=False)
\n print(f"\u8f68\u8ff9\u5df2\u4fdd\u5b58\u5230: {filename}")<\/p>\n
return df<\/p>\n
4.2 \u5b8c\u6574\u7684\u6848\u4f8b1\u5b9e\u73b0<\/h4>\n
\u73b0\u5728，\u6211\u4eec\u5b9e\u73b0\u4e00\u4e2a\u5b8c\u6574\u7684\u98de\u884c\u8f68\u8ff9\u53ef\u89c6\u5316\u6848\u4f8b：<\/p>\n
class FlightTrajectoryDemo:
\n """\u98de\u884c\u8f68\u8ff9\u6f14\u793a\u7c7b"""<\/p>\n
def __init__(self):
\n self.trajectory_data = TrajectoryData()
\n self.visualizer = EnhancedTrajectoryVisualizer()<\/p>\n
def load_or_generate_data(self):
\n """\u52a0\u8f7d\u6216\u751f\u6210\u8f68\u8ff9\u6570\u636e"""
\n # \u5c1d\u8bd5\u4ece\u6587\u4ef6\u52a0\u8f7d
\n try:
\n self.trajectory_data.load_from_csv(
\n 'flight_trajectory.csv',
\n time_column='timestamp',
\n id_column='object_id',
\n x_column='x',
\n y_column='y',
\n z_column='z'
\n )
\n print("\u4ece\u6587\u4ef6\u52a0\u8f7d\u8f68\u8ff9\u6570\u636e\u6210\u529f")
\n except FileNotFoundError:
\n print("\u672a\u627e\u5230\u8f68\u8ff9\u6587\u4ef6，\u751f\u6210\u6a21\u62df\u6570\u636e…")
\n # \u751f\u6210\u6a21\u62df\u8f68\u8ff9
\n trajectory = generate_flight_trajectory(100, '001')
\n self.trajectory_data.trajectories['001'] = trajectory
\n # \u4fdd\u5b58\u5230\u6587\u4ef6
\n save_trajectory_to_csv(trajectory)<\/p>\n
return self.trajectory_data.get_summary()<\/p>\n
def create_terrain(self, plotter):
\n """\u521b\u5efa\u5730\u5f62"""
\n # \u521b\u5efa\u7b80\u5355\u5730\u5f62\u7f51\u683c
\n x = np.linspace(-10000, 10000, 50)
\n y = np.linspace(-10000, 10000, 50)
\n xx, yy = np.meshgrid(x, y)<\/p>\n
# \u521b\u5efa\u8d77\u4f0f\u5730\u5f62
\n z = 1000 + 200 * np.sin(0.0005 * xx) * np.cos(0.0005 * yy)<\/p>\n
terrain = pv.StructuredGrid(xx, yy, z)
\n terrain['elevation'] = z.ravel()<\/p>\n
plotter.add_mesh(
\n terrain,
\n cmap='terrain',
\n scalars='elevation',
\n opacity=0.7,
\n show_edges=False,
\n name='terrain'
\n )<\/p>\n
return terrain<\/p>\n
def add_aircraft_model(self, plotter, position, scale=10.0, color='white'):
\n """\u6dfb\u52a0\u98de\u673a\u6a21\u578b"""
\n # \u7b80\u5316\u98de\u673a\u6a21\u578b
\n fuselage = pv.Cylinder(center=[0, 0, 0], direction=[1, 0, 0],
\n radius=1*scale, height=6*scale)
\n wing = pv.Box(bounds=[-0.5*scale, 0.5*scale, -4*scale, 4*scale,
\n -0.2*scale, 0.2*scale])
\n tail = pv.Box(bounds=[-3*scale, -2*scale, -1.5*scale, 1.5*scale,
\n -0.5*scale, 0.5*scale])<\/p>\n
aircraft = fuselage.boolean_union(wing)
\n aircraft = aircraft.boolean_union(tail)<\/p>\n
# \u5b9a\u4f4d
\n aircraft.translate(position, inplace=True)<\/p>\n
plotter.add_mesh(aircraft, color=color, name='aircraft_model')<\/p>\n
return aircraft<\/p>\n
def add_info_panel(self, plotter, trajectory):
\n """\u6dfb\u52a0\u4fe1\u606f\u9762\u677f"""
\n if not trajectory.points:
\n return<\/p>\n
# \u8f68\u8ff9\u7edf\u8ba1
\n stats = trajectory.get_statistics()<\/p>\n
info_text = f"\u98de\u884c\u8f68\u8ff9\u4fe1\u606f\\\\n"
\n info_text += f"\u76ee\u6807ID: {trajectory.id}\\\\n"
\n info_text += f"\u76ee\u6807\u7c7b\u578b: {trajectory.object_type}\\\\n"
\n info_text += f"\u8f68\u8ff9\u70b9\u6570: {stats['point_count']}\\\\n"
\n info_text += f"\u6301\u7eed\u65f6\u95f4: {stats['duration']:.1f}s\\\\n"
\n info_text += f"\u603b\u8ddd\u79bb: {stats['total_distance']:.1f}m\\\\n"
\n info_text += f"\u5e73\u5747\u901f\u5ea6: {stats['avg_speed']:.1f}m\/s\\\\n"
\n info_text += f"\u6700\u5927\u901f\u5ea6: {stats['max_speed']:.1f}m\/s\\\\n"
\n info_text += f"\u9ad8\u5ea6\u8303\u56f4: {stats['min_altitude']:.1f}-{stats['max_altitude']:.1f}m\\\\n"<\/p>\n
# \u6dfb\u52a0\u6587\u672c
\n plotter.add_text(
\n info_text,
\n position='upper_left',
\n font_size=10,
\n color='white',
\n name='info_panel'
\n )<\/p>\n
def add_time_slider(self, plotter, trajectory):
\n """\u6dfb\u52a0\u65f6\u95f4\u6ed1\u5757"""
\n if not trajectory.points:
\n return<\/p>\n
# \u521b\u5efa\u65f6\u95f4\u70b9
\n times = [p.timestamp for p in trajectory.points]<\/p>\n
# \u5982\u679c\u662fdatetime，\u8f6c\u6362\u4e3a\u65f6\u95f4\u6233
\n if isinstance(times[0], datetime):
\n time_values = [t.timestamp() for t in times]
\n else:
\n time_values = times<\/p>\n
time_min = min(time_values)
\n time_max = max(time_values)<\/p>\n
# \u521b\u5efa\u6ed1\u5757
\n def update_time(value):
\n # \u627e\u5230\u6700\u63a5\u8fd1\u7684\u65f6\u95f4\u70b9
\n idx = np.argmin(np.abs(np.array(time_values) – value))
\n if 0 <= idx < len(trajectory.points):
\n point = trajectory.points[idx]<\/p>\n
# \u66f4\u65b0\u98de\u673a\u4f4d\u7f6e
\n if 'aircraft_model' in plotter.actors:
\n plotter.remove_actor(plotter.actors['aircraft_model'])<\/p>\n
self.add_aircraft_model(plotter, point.position)<\/p>\n
# \u66f4\u65b0\u65f6\u95f4\u6587\u672c
\n time_text = f"\u65f6\u95f4: {point.timestamp}\\\\n"
\n time_text += f"\u4f4d\u7f6e: {point.position}\\\\n"
\n time_text += f"\u901f\u5ea6: {point.velocity:.1f}m\/s\\\\n"
\n time_text += f"\u822a\u5411: {point.heading:.1f}\u00b0"<\/p>\n
if 'time_info' in plotter.actors:
\n plotter.remove_actor(plotter.actors['time_info'])<\/p>\n
plotter.add_text(
\n time_text,
\n position='upper_right',
\n font_size=10,
\n color='yellow',
\n name='time_info'
\n )<\/p>\n
# \u6dfb\u52a0\u6ed1\u5757
\n plotter.add_slider_widget(
\n update_time,
\n [time_min, time_max],
\n value=time_min,
\n title='\u65f6\u95f4',
\n pointa=(0.1, 0.9),
\n pointb=(0.4, 0.9),
\n style='modern'
\n )<\/p>\n
def run_demo(self, color_by='speed'):
\n """\u8fd0\u884c\u6f14\u793a"""
\n print("\u98de\u884c\u8f68\u8ff9\u53ef\u89c6\u5316\u6f14\u793a")
\n print("=" * 50)<\/p>\n
# \u52a0\u8f7d\u6570\u636e
\n summary = self.load_or_generate_data()
\n print(f"\u6570\u636e\u6458\u8981: {summary}")<\/p>\n
# \u83b7\u53d6\u8f68\u8ff9
\n trajectories = self.trajectory_data.get_all_trajectories()
\n if not trajectories:
\n print("\u6ca1\u6709\u627e\u5230\u8f68\u8ff9\u6570\u636e")
\n return<\/p>\n
trajectory = trajectories[0]<\/p>\n
# \u521b\u5efa\u53ef\u89c6\u5316\u7a97\u53e3
\n plotter = pv.Plotter(window_size=(1600, 1000),
\n title=f"\u98de\u884c\u8f68\u8ff9\u53ef\u89c6\u5316 – \u989c\u8272\u6620\u5c04: {color_by}")<\/p>\n
# \u6dfb\u52a0\u5730\u5f62
\n self.create_terrain(plotter)<\/p>\n
# \u6dfb\u52a0\u8f68\u8ff9（\u5e26\u989c\u8272\u6620\u5c04）
\n mesh = self.visualizer.create_colored_trajectory(
\n trajectory,
\n color_by=color_by,
\n colormap='plasma',
\n style='tube',
\n radius=50
\n )<\/p>\n
if mesh:
\n plotter.add_mesh(
\n mesh,
\n scalars=color_by,
\n cmap='plasma',
\n opacity=0.8,
\n clim=[mesh[color_by].min(), mesh[color_by].max()],
\n show_scalar_bar=True,
\n scalar_bar_args={
\n 'title': f'{color_by}',
\n 'vertical': True,
\n 'position_x': 0.85,
\n 'position_y': 0.3,
\n 'height': 0.4
\n },
\n name='trajectory',
\n show_edges=False
\n )<\/p>\n
# \u6dfb\u52a0\u8f68\u8ff9\u8d77\u59cb\u70b9
\n if trajectory.points:
\n # \u8d77\u59cb\u70b9
\n start_point = trajectory.points[0].position
\n start_mesh = pv.Sphere(center=start_point, radius=100)
\n plotter.add_mesh(
\n start_mesh,
\n color='green',
\n name='start_point'
\n )<\/p>\n
# \u7ec8\u70b9
\n end_point = trajectory.points[-1].position
\n end_mesh = pv.Sphere(center=end_point, radius=100)
\n plotter.add_mesh(
\n end_mesh,
\n color='red',
\n name='end_point'
\n )<\/p>\n
# \u6dfb\u52a0\u98de\u673a\u6a21\u578b（\u5728\u8d77\u59cb\u4f4d\u7f6e）
\n self.add_aircraft_model(plotter, start_point, scale=20)<\/p>\n
# \u6dfb\u52a0\u8f68\u8ff9\u70b9（\u91c7\u6837\u663e\u793a）
\n points = np.array([p.position for p in trajectory.points])
\n if len(points) > 0:
\n # \u5747\u5300\u91c7\u6837
\n sample_indices = np.linspace(0, len(points)-1, 20, dtype=int)
\n sample_points = points[sample_indices]<\/p>\n
points_mesh = pv.PolyData(sample_points)
\n plotter.add_mesh(
\n points_mesh,
\n color='white',
\n point_size=10,
\n render_points_as_spheres=True,
\n name='trajectory_points'
\n )<\/p>\n
# \u6dfb\u52a0\u70b9\u6807\u7b7e
\n for i, idx in enumerate(sample_indices):
\n if idx < len(trajectory.points):
\n point = trajectory.points[idx]
\n label_text = f"t={point.timestamp if isinstance(point.timestamp, (int, float)) else point.timestamp.strftime('%H:%M:%S')}"
\n plotter.add_point_labels(
\n [point.position],
\n [label_text],
\n font_size=8,
\n point_color='white',
\n point_size=0,
\n name=f'label_{i}'
\n )<\/p>\n
# \u6dfb\u52a0\u4fe1\u606f\u9762\u677f
\n self.add_info_panel(plotter, trajectory)<\/p>\n
# \u6dfb\u52a0\u65f6\u95f4\u6ed1\u5757
\n self.add_time_slider(plotter, trajectory)<\/p>\n
# \u8bbe\u7f6e\u573a\u666f
\n plotter.add_axes()
\n plotter.show_grid()<\/p>\n
# \u8bbe\u7f6e\u76f8\u673a
\n plotter.camera_position = [(20000, 20000, 10000), (0, 0, 5000), (0, 0, 1)]
\n plotter.set_background('linear_gradient', bottom='#0a0a2a', top='#1a1a3a')<\/p>\n
# \u6dfb\u52a0\u63a7\u5236\u8bf4\u660e
\n controls = "\u63a7\u5236\u8bf4\u660e:\\\\n"
\n controls += "\u9f20\u6807\u62d6\u62fd: \u65cb\u8f6c\u89c6\u89d2\\\\n"
\n controls += "\u9f20\u6807\u53f3\u952e\u62d6\u62fd: \u5e73\u79fb\u89c6\u89d2\\\\n"
\n controls += "\u9f20\u6807\u6eda\u8f6e: \u7f29\u653e\\\\n"
\n controls += "R\u952e: \u91cd\u7f6e\u89c6\u89d2\\\\n"
\n controls += "1\u952e: \u6309\u901f\u5ea6\u7740\u8272\\\\n"
\n controls += "2\u952e: \u6309\u9ad8\u5ea6\u7740\u8272\\\\n"
\n controls += "3\u952e: \u6309\u65f6\u95f4\u7740\u8272\\\\n"
\n controls += "4\u952e: \u6309\u8ddd\u79bb\u7740\u8272\\\\n"<\/p>\n
plotter.add_text(
\n controls,
\n position='lower_left',
\n font_size=10,
\n color='cyan',
\n name='controls'
\n )<\/p>\n
# \u6dfb\u52a0\u952e\u76d8\u4e8b\u4ef6
\n def set_color_by_speed():
\n plotter.remove_actor(plotter.actors['trajectory'])
\n mesh = self.visualizer.create_colored_trajectory(
\n trajectory,
\n color_by='speed',
\n colormap='plasma',
\n style='tube',
\n radius=50
\n )
\n plotter.add_mesh(
\n mesh,
\n scalars='speed',
\n cmap='plasma',
\n opacity=0.8,
\n name='trajectory',
\n show_edges=False
\n )
\n print("\u989c\u8272\u6620\u5c04: \u901f\u5ea6")<\/p>\n
def set_color_by_altitude():
\n plotter.remove_actor(plotter.actors['trajectory'])
\n mesh = self.visualizer.create_colored_trajectory(
\n trajectory,
\n color_by='altitude',
\n colormap='terrain',
\n style='tube',
\n radius=50
\n )
\n plotter.add_mesh(
\n mesh,
\n scalars='altitude',
\n cmap='terrain',
\n opacity=0.8,
\n name='trajectory',
\n show_edges=False
\n )
\n print("\u989c\u8272\u6620\u5c04: \u9ad8\u5ea6")<\/p>\n
def set_color_by_time():
\n plotter.remove_actor(plotter.actors['trajectory'])
\n mesh = self.visualizer.create_colored_trajectory(
\n trajectory,
\n color_by='time',
\n colormap='viridis',
\n style='tube',
\n radius=50
\n )
\n plotter.add_mesh(
\n mesh,
\n scalars='time',
\n cmap='viridis',
\n opacity=0.8,
\n name='trajectory',
\n show_edges=False
\n )
\n print("\u989c\u8272\u6620\u5c04: \u65f6\u95f4")<\/p>\n
def set_color_by_distance():
\n plotter.remove_actor(plotter.actors['trajectory'])
\n mesh = self.visualizer.create_colored_trajectory(
\n trajectory,
\n color_by='distance',
\n colormap='hot',
\n style='tube',
\n radius=50
\n )
\n plotter.add_mesh(
\n mesh,
\n scalars='distance',
\n cmap='hot',
\n opacity=0.8,
\n name='trajectory',
\n show_edges=False
\n )
\n print("\u989c\u8272\u6620\u5c04: \u8ddd\u79bb")<\/p>\n
plotter.add_key_event("1", set_color_by_speed)
\n plotter.add_key_event("2", set_color_by_altitude)
\n plotter.add_key_event("3", set_color_by_time)
\n plotter.add_key_event("4", set_color_by_distance)<\/p>\n
print("\\\\n\u6f14\u793a\u5df2\u542f\u52a8")
\n print("\u4f7f\u7528\u952e\u76d81-4\u952e\u5207\u6362\u989c\u8272\u6620\u5c04")<\/p>\n
# \u663e\u793a
\n plotter.show()<\/p>\n
# \u8fd0\u884c\u6848\u4f8b1
\ndef run_case1():
\n demo = FlightTrajectoryDemo()
\n demo.run_demo(color_by='speed')<\/p>\n
if __name__ == "__main__":
\n run_case1()<\/p>\n
5. \u6848\u4f8b2：\u591a\u76ee\u6807\u8f68\u8ff9\u5bf9\u6bd4\u5206\u6790<\/h3>\n5.1 \u591a\u76ee\u6807\u6570\u636e\u751f\u6210<\/h4>\n
\u521b\u5efa\u591a\u4e2a\u76ee\u6807\u7684\u8f68\u8ff9\u6570\u636e\u7528\u4e8e\u5bf9\u6bd4\u5206\u6790：<\/p>\n
def generate_multiple_trajectories(num_trajectories=3, points_per_trajectory=50):
\n """\u751f\u6210\u591a\u4e2a\u76ee\u6807\u7684\u8f68\u8ff9\u6570\u636e"""
\n trajectories = []<\/p>\n
for i in range(num_trajectories):
\n traj_id = f"T{i+1:03d}"<\/p>\n
# \u4e0d\u540c\u7c7b\u578b\u7684\u8f68\u8ff9
\n if i == 0:
\n # \u76f4\u7ebf\u98de\u884c
\n trajectory = generate_straight_trajectory(traj_id, points_per_trajectory)
\n elif i == 1:
\n # \u5706\u5468\u98de\u884c
\n trajectory = generate_circular_trajectory(traj_id, points_per_trajectory)
\n else:
\n # \u968f\u673a\u98de\u884c
\n trajectory = generate_random_trajectory(traj_id, points_per_trajectory)<\/p>\n
trajectories.append(trajectory)<\/p>\n
return trajectories<\/p>\n
def generate_straight_trajectory(traj_id, num_points):
\n """\u751f\u6210\u76f4\u7ebf\u98de\u884c\u8f68\u8ff9"""
\n from datetime import datetime, timedelta<\/p>\n
start_time = datetime(2024, 1, 1, 12, 0, 0)
\n start_pos = np.array([-5000, -5000, 1000])<\/p>\n
trajectory = TrajectoryData.Trajectory(traj_id, 'aircraft')<\/p>\n
for i in range(num_points):
\n t = i * 10
\n x = start_pos[0] + t * 20
\n y = start_pos[1] + t * 15
\n z = start_pos[2] + t * 2<\/p>\n
timestamp = start_time + timedelta(seconds=t)
\n point = TrajectoryData.TrajectoryPoint(
\n timestamp=timestamp,
\n position=[x, y, z],
\n velocity=200 + i * 0.5,
\n heading=45
\n )<\/p>\n
trajectory.add_point(point)<\/p>\n
return trajectory<\/p>\n
def generate_circular_trajectory(traj_id, num_points):
\n """\u751f\u6210\u5706\u5468\u98de\u884c\u8f68\u8ff9"""
\n from datetime import datetime, timedelta<\/p>\n
start_time = datetime(2024, 1, 1, 12, 0, 0)
\n center = np.array([0, 0, 2000])
\n radius = 3000<\/p>\n
trajectory = TrajectoryData.Trajectory(traj_id, 'aircraft')<\/p>\n
for i in range(num_points):
\n t = i * 10
\n angle = math.radians(t * 3) # \u6bcf10\u79d2\u8f6c3\u5ea6<\/p>\n
x = center[0] + radius * math.cos(angle)
\n y = center[1] + radius * math.sin(angle)
\n z = center[2] + math.sin(angle * 2) * 500<\/p>\n
# \u8ba1\u7b97\u901f\u5ea6（\u5706\u5468\u8fd0\u52a8\u901f\u5ea6）
\n angular_speed = math.radians(3) # \u5f27\u5ea6\/\u79d2
\n speed = radius * angular_speed<\/p>\n
# \u8ba1\u7b97\u822a\u5411（\u5207\u7ebf\u65b9\u5411）
\n heading = math.degrees(angle + math.pi\/2)<\/p>\n
timestamp = start_time + timedelta(seconds=t)
\n point = TrajectoryData.TrajectoryPoint(
\n timestamp=timestamp,
\n position=[x, y, z],
\n velocity=speed,
\n heading=heading
\n )<\/p>\n
trajectory.add_point(point)<\/p>\n
return trajectory<\/p>\n
def generate_random_trajectory(traj_id, num_points):
\n """\u751f\u6210\u968f\u673a\u98de\u884c\u8f68\u8ff9"""
\n from datetime import datetime, timedelta
\n import random<\/p>\n
start_time = datetime(2024, 1, 1, 12, 0, 0)
\n start_pos = np.array([5000, 5000, 1500])<\/p>\n
trajectory = TrajectoryData.Trajectory(traj_id, 'aircraft')<\/p>\n
# \u968f\u673a\u884c\u8d70
\n current_pos = start_pos.copy()
\n current_heading = 0
\n current_speed = 180<\/p>\n
for i in range(num_points):
\n t = i * 10<\/p>\n
# \u968f\u673a\u53d8\u5316
\n heading_change = random.uniform(-10, 10)
\n speed_change = random.uniform(-5, 5)
\n altitude_change = random.uniform(-20, 20)<\/p>\n
current_heading += heading_change
\n current_speed = max(100, min(300, current_speed + speed_change))<\/p>\n
# \u8ba1\u7b97\u65b0\u4f4d\u7f6e
\n heading_rad = math.radians(current_heading)
\n dx = current_speed * 10 * math.cos(heading_rad)
\n dy = current_speed * 10 * math.sin(heading_rad)
\n dz = altitude_change * 10<\/p>\n
new_pos = current_pos + np.array([dx, dy, dz])
\n current_pos = new_pos<\/p>\n
timestamp = start_time + timedelta(seconds=t)
\n point = TrajectoryData.TrajectoryPoint(
\n timestamp=timestamp,
\n position=new_pos.tolist(),
\n velocity=current_speed,
\n heading=current_heading
\n )<\/p>\n
trajectory.add_point(point)<\/p>\n
return trajectory<\/p>\n
5.2 \u5b8c\u6574\u7684\u6848\u4f8b2\u5b9e\u73b0<\/h4>\n
\u5b9e\u73b0\u591a\u76ee\u6807\u8f68\u8ff9\u5bf9\u6bd4\u5206\u6790\u7684\u53ef\u89c6\u5316\u7cfb\u7edf：<\/p>\n
class MultiTrajectoryAnalysisDemo:
\n """\u591a\u76ee\u6807\u8f68\u8ff9\u5206\u6790\u6f14\u793a"""<\/p>\n
def __init__(self):
\n self.trajectories = []
\n self.visualizer = EnhancedTrajectoryVisualizer()
\n self.plotter = None
\n self.color_palette = [
\n [1, 0, 0], # \u7ea2\u8272
\n [0, 1, 0], # \u7eff\u8272
\n [0, 0, 1], # \u84dd\u8272
\n [1, 1, 0], # \u9ec4\u8272
\n [1, 0, 1], # \u7d2b\u8272
\n [0, 1, 1], # \u9752\u8272
\n ]<\/p>\n
def generate_data(self, num_trajectories=4):
\n """\u751f\u6210\u591a\u76ee\u6807\u8f68\u8ff9\u6570\u636e"""
\n print(f"\u751f\u6210 {num_trajectories} \u4e2a\u76ee\u6807\u7684\u8f68\u8ff9\u6570\u636e…")<\/p>\n
self.trajectories = generate_multiple_trajectories(num_trajectories, 50)<\/p>\n
# \u6253\u5370\u7edf\u8ba1\u4fe1\u606f
\n for i, traj in enumerate(self.trajectories):
\n stats = traj.get_statistics()
\n print(f"\u8f68\u8ff9 {traj.id}: {stats['point_count']}\u4e2a\u70b9, "
\n f"\u8ddd\u79bb{stats['total_distance']:.0f}m, "
\n f"\u5e73\u5747\u901f\u5ea6{stats['avg_speed']:.1f}m\/s")<\/p>\n
def create_comparison_plot(self, plotter):
\n """\u521b\u5efa\u5bf9\u6bd4\u5206\u6790\u56fe\u8868"""
\n if not self.trajectories:
\n return<\/p>\n
# \u63d0\u53d6\u7edf\u8ba1\u6570\u636e
\n traj_ids = []
\n avg_speeds = []
\n total_distances = []
\n durations = []<\/p>\n
for traj in self.trajectories:
\n stats = traj.get_statistics()
\n traj_ids.append(traj.id)
\n avg_speeds.append(stats['avg_speed'])
\n total_distances.append(stats['total_distance'])
\n durations.append(stats['duration'])<\/p>\n
# \u521b\u5efa\u5b50\u56fe
\n plotter.subplot(0, 1)<\/p>\n
# \u5e73\u5747\u901f\u5ea6\u6761\u5f62\u56fe
\n y_pos = np.arange(len(traj_ids))<\/p>\n
# \u521b\u5efa\u6761\u5f62\u56fe\u7f51\u683c
\n bar_width = 0.6
\n bars = []<\/p>\n
for i, (traj_id, speed) in enumerate(zip(traj_ids, avg_speeds)):
\n bar = pv.Box(bounds=[
\n i – bar_width\/2, i + bar_width\/2,
\n 0, speed\/50, # \u7f29\u653e\u901f\u5ea6\u503c
\n 0, 1
\n ])
\n bars.append(bar)<\/p>\n
# \u5408\u5e76\u6761\u5f62
\n if bars:
\n bar_mesh = bars[0]
\n for bar in bars[1:]:
\n bar_mesh = bar_mesh.merge(bar)<\/p>\n
# \u4e3a\u6bcf\u4e2a\u6761\u5f62\u8bbe\u7f6e\u989c\u8272
\n colors = []
\n for i, traj_id in enumerate(traj_ids):
\n color_idx = i % len(self.color_palette)
\n colors.extend([self.color_palette[color_idx]] * bar_mesh.n_points)<\/p>\n
bar_mesh['colors'] = colors<\/p>\n
plotter.add_mesh(
\n bar_mesh,
\n scalars='colors',
\n rgb=True,
\n name='speed_bars',
\n show_edges=True
\n )<\/p>\n
# \u8bbe\u7f6e\u5750\u6807\u8f74
\n plotter.add_text(
\n "\u5e73\u5747\u901f\u5ea6 (m\/s)",
\n position='upper_center',
\n font_size=10,
\n name='speed_title'
\n )<\/p>\n
# \u6dfb\u52a0\u8f68\u8ff9ID\u6807\u7b7e
\n for i, traj_id in enumerate(traj_ids):
\n plotter.add_text(
\n traj_id,
\n position=(i, -0.5, 0),
\n font_size=8,
\n name=f'label_{traj_id}'
\n )<\/p>\n
plotter.subplot(0, 0) # \u8fd4\u56de\u4e3b\u56fe<\/p>\n
def add_legend(self, plotter):
\n """\u6dfb\u52a0\u56fe\u4f8b"""
\n if not self.trajectories:
\n return<\/p>\n
legend_text = "\u8f68\u8ff9\u56fe\u4f8b:\\\\n"<\/p>\n
for i, traj in enumerate(self.trajectories):
\n color_idx = i % len(self.color_palette)
\n color = self.color_palette[color_idx]
\n color_hex = '#{:02x}{:02x}{:02x}'.format(
\n int(color[0]*255), int(color[1]*255), int(color[2]*255)
\n )<\/p>\n
stats = traj.get_statistics()
\n legend_text += f"<span style='color:{color_hex}'>\u25a0<\/span> "
\n legend_text += f"{traj.id}: {stats['avg_speed']:.1f}m\/s, "
\n legend_text += f"{stats['total_distance']:.0f}m\\\\n"<\/p>\n
plotter.add_text(
\n legend_text,
\n position='upper_right',
\n font_size=9,
\n name='legend',
\n font='arial'
\n )<\/p>\n
def add_trajectory_controls(self, plotter):
\n """\u6dfb\u52a0\u8f68\u8ff9\u63a7\u5236"""
\n if not self.trajectories:
\n return<\/p>\n
def toggle_trajectory(traj_index, visible):
\n """\u5207\u6362\u8f68\u8ff9\u663e\u793a"""
\n if 0 <= traj_index < len(self.trajectories):
\n traj = self.trajectories[traj_index]
\n actor_name = f'trajectory_{traj.id}'<\/p>\n
if visible:
\n # \u663e\u793a\u8f68\u8ff9
\n if actor_name in plotter.actors:
\n plotter.remove_actor(plotter.actors[actor_name])<\/p>\n
# \u521b\u5efa\u8f68\u8ff9
\n mesh = self.visualizer.create_colored_trajectory(
\n traj,
\n color_by='speed',
\n colormap='plasma',
\n style='tube',
\n radius=30
\n )<\/p>\n
if mesh:
\n plotter.add_mesh(
\n mesh,
\n scalars='speed',
\n cmap='plasma',
\n opacity=0.7,
\n name=actor_name,
\n show_edges=False
\n )
\n else:
\n # \u9690\u85cf\u8f68\u8ff9
\n if actor_name in plotter.actors:
\n plotter.remove_actor(plotter.actors[actor_name])<\/p>\n
# \u4e3a\u6bcf\u4e2a\u8f68\u8ff9\u6dfb\u52a0\u590d\u9009\u6846
\n for i, traj in enumerate(self.trajectories):
\n plotter.add_checkbox_button_widget(
\n lambda state, idx=i: toggle_trajectory(idx, state),
\n value=True,
\n position=(10, 10 + i*30),
\n size=20,
\n border_size=2,
\n color_on='green',
\n color_off='red',
\n background_color='white'
\n )<\/p>\n
# \u6dfb\u52a0\u6807\u7b7e
\n plotter.add_text(
\n traj.id,
\n position=(40, 10 + i*30),
\n font_size=10,
\n color='white',
\n name=f'checkbox_label_{i}'
\n )<\/p>\n
def add_time_synchronization(self, plotter):
\n """\u6dfb\u52a0\u65f6\u95f4\u540c\u6b65"""
\n if not self.trajectories:
\n return<\/p>\n
# \u627e\u5230\u5171\u540c\u7684\u65f6\u95f4\u8303\u56f4
\n all_times = []
\n for traj in self.trajectories:
\n if traj.points:
\n times = [p.timestamp for p in traj.points]
\n if isinstance(times[0], datetime):
\n times = [t.timestamp() for t in times]
\n all_times.extend(times)<\/p>\n
if not all_times:
\n return<\/p>\n
time_min = min(all_times)
\n time_max = max(all_times)<\/p>\n
# \u6dfb\u52a0\u65f6\u95f4\u6ed1\u5757
\n def update_all_trajectories(time_value):
\n """\u66f4\u65b0\u6240\u6709\u8f68\u8ff9\u7684\u65f6\u95f4\u70b9"""
\n for traj in self.trajectories:
\n # \u627e\u5230\u5bf9\u5e94\u65f6\u95f4\u7684\u70b9
\n point = traj.get_point_at_time(time_value)
\n if point:
\n # \u66f4\u65b0\u6807\u8bb0\u70b9
\n marker_name = f'marker_{traj.id}'
\n if marker_name in plotter.actors:
\n plotter.remove_actor(plotter.actors[marker_name])<\/p>\n
# \u521b\u5efa\u6807\u8bb0
\n marker = pv.Sphere(center=point.position, radius=50)
\n color_idx = self.trajectories.index(traj) % len(self.color_palette)
\n color = self.color_palette[color_idx]<\/p>\n
plotter.add_mesh(
\n marker,
\n color=color,
\n name=marker_name
\n )<\/p>\n
plotter.add_slider_widget(
\n update_all_trajectories,
\n [time_min, time_max],
\n value=time_min,
\n title='\u540c\u6b65\u65f6\u95f4',
\n pointa=(0.7, 0.1),
\n pointb=(0.9, 0.1),
\n style='modern'
\n )<\/p>\n
def run_demo(self, num_trajectories=4):
\n """\u8fd0\u884c\u6f14\u793a"""
\n print("\u591a\u76ee\u6807\u8f68\u8ff9\u5bf9\u6bd4\u5206\u6790\u6f14\u793a")
\n print("=" * 50)<\/p>\n
# \u751f\u6210\u6570\u636e
\n self.generate_data(num_trajectories)<\/p>\n
# \u521b\u5efa\u7ed8\u56fe\u7a97\u53e3
\n self.plotter = pv.Plotter(window_size=(1800, 900),
\n shape=(1, 2),
\n title="\u591a\u76ee\u6807\u8f68\u8ff9\u5bf9\u6bd4\u5206\u6790")<\/p>\n
# \u4e3b\u56fe (3D\u8f68\u8ff9)
\n self.plotter.subplot(0, 0)<\/p>\n
# \u6dfb\u52a0\u5730\u5f62
\n x = np.linspace(-10000, 10000, 50)
\n y = np.linspace(-10000, 10000, 50)
\n xx, yy = np.meshgrid(x, y)
\n z = 1000 + 300 * np.sin(0.0005 * xx) * np.cos(0.0005 * yy)
\n terrain = pv.StructuredGrid(xx, yy, z)
\n terrain['elevation'] = z.ravel()<\/p>\n
self.plotter.add_mesh(
\n terrain,
\n cmap='terrain',
\n scalars='elevation',
\n opacity=0.5,
\n show_edges=False,
\n name='terrain'
\n )<\/p>\n
# \u6dfb\u52a0\u8f68\u8ff9
\n for i, traj in enumerate(self.trajectories):
\n color_idx = i % len(self.color_palette)
\n color = self.color_palette[color_idx]<\/p>\n
# \u521b\u5efa\u8f68\u8ff9
\n mesh = self.visualizer.create_colored_trajectory(
\n traj,
\n color_by='speed',
\n colormap='plasma',
\n style='tube',
\n radius=30
\n )<\/p>\n
if mesh:
\n self.plotter.add_mesh(
\n mesh,
\n scalars='speed',
\n cmap='plasma',
\n opacity=0.7,
\n name=f'trajectory_{traj.id}',
\n show_edges=False
\n )<\/p>\n
# \u6dfb\u52a0\u8d77\u59cb\u70b9\u548c\u7ec8\u70b9
\n if traj.points:
\n # \u8d77\u59cb\u70b9
\n start_mesh = pv.Sphere(center=traj.points[0].position, radius=100)
\n self.plotter.add_mesh(
\n start_mesh,
\n color='green',
\n name=f'start_{traj.id}'
\n )<\/p>\n
# \u7ec8\u70b9
\n end_mesh = pv.Sphere(center=traj.points[-1].position, radius=100)
\n self.plotter.add_mesh(
\n end_mesh,
\n color='red',
\n name=f'end_{traj.id}'
\n )<\/p>\n
# \u8bbe\u7f6e\u4e3b\u56fe
\n self.plotter.add_axes()
\n self.plotter.show_grid()
\n self.plotter.camera_position = [(20000, 20000, 10000), (0, 0, 5000), (0, 0, 1)]
\n self.plotter.set_background('linear_gradient', bottom='#0a0a2a', top='#1a1a3a')<\/p>\n
# \u6dfb\u52a0\u56fe\u4f8b
\n self.add_legend(self.plotter)<\/p>\n
# \u6dfb\u52a0\u8f68\u8ff9\u63a7\u5236
\n self.add_trajectory_controls(self.plotter)<\/p>\n
# \u6dfb\u52a0\u65f6\u95f4\u540c\u6b65
\n self.add_time_synchronization(self.plotter)<\/p>\n
# \u5bf9\u6bd4\u5206\u6790\u56fe\u8868
\n self.create_comparison_plot(self.plotter)<\/p>\n
# \u6dfb\u52a0\u63a7\u5236\u8bf4\u660e
\n controls = "\u63a7\u5236\u8bf4\u660e:\\\\n"
\n controls += "\u5de6\u4fa7\u590d\u9009\u6846: \u663e\u793a\/\u9690\u85cf\u8f68\u8ff9\\\\n"
\n controls += "\u65f6\u95f4\u6ed1\u5757: \u540c\u6b65\u65f6\u95f4\u70b9\\\\n"
\n controls += "\u9f20\u6807\u4ea4\u4e92: \u65cb\u8f6c\/\u5e73\u79fb\/\u7f29\u653e\\\\n"<\/p>\n
self.plotter.add_text(
\n controls,
\n position='lower_left',
\n font_size=9,
\n color='cyan',
\n name='controls'
\n )<\/p>\n
print("\\\\n\u6f14\u793a\u5df2\u542f\u52a8")
\n print("\u4f7f\u7528\u5de6\u4fa7\u590d\u9009\u6846\u63a7\u5236\u8f68\u8ff9\u663e\u793a")
\n print("\u4f7f\u7528\u65f6\u95f4\u6ed1\u5757\u540c\u6b65\u67e5\u770b\u4e0d\u540c\u65f6\u95f4\u70b9\u7684\u4f4d\u7f6e")<\/p>\n
# \u663e\u793a
\n self.plotter.show()<\/p>\n
# \u8fd0\u884c\u6848\u4f8b2
\ndef run_case2():
\n demo = MultiTrajectoryAnalysisDemo()
\n demo.run_demo(num_trajectories=4)<\/p>\n
if __name__ == "__main__":
\n run_case2()<\/p>\n
6. \u6848\u4f8b3：\u96f7\u8fbe\u63a2\u6d4b\u5386\u53f2\u53ef\u89c6\u5316<\/h3>\n6.1 \u96f7\u8fbe\u63a2\u6d4b\u6570\u636e\u751f\u6210<\/h4>\n
\u6a21\u62df\u96f7\u8fbe\u63a2\u6d4b\u5386\u53f2\u6570\u636e：<\/p>\n
def generate_radar_detection_history(num_targets=3, detection_points_per_target=20):
\n """\u751f\u6210\u96f7\u8fbe\u63a2\u6d4b\u5386\u53f2\u6570\u636e"""
\n from datetime import datetime, timedelta
\n import random<\/p>\n
detections = []
\n start_time = datetime(2024, 1, 1, 12, 0, 0)<\/p>\n
# \u96f7\u8fbe\u4f4d\u7f6e
\n radar_position = np.array([0, 0, 0])<\/p>\n
for target_idx in range(num_targets):
\n target_id = f"Target{target_idx+1:03d}"<\/p>\n
# \u76ee\u6807\u8d77\u59cb\u4f4d\u7f6e
\n if target_idx == 0:
\n start_pos = np.array([-5000, 0, 2000])
\n elif target_idx == 1:
\n start_pos = np.array([0, 5000, 2500])
\n else:
\n start_pos = np.array([5000, 0, 3000])<\/p>\n
# \u76ee\u6807\u901f\u5ea6
\n speed = 200 + random.uniform(-50, 50)<\/p>\n
for i in range(detection_points_per_target):
\n t = i * 30 # 30\u79d2\u95f4\u9694<\/p>\n
# \u8ba1\u7b97\u76ee\u6807\u4f4d\u7f6e
\n if target_idx == 0:
\n # \u76f4\u7ebf\u8fd0\u52a8
\n x = start_pos[0] + t * 20
\n y = start_pos[1] + t * 10
\n z = start_pos[2] + t * 2
\n elif target_idx == 1:
\n # \u5706\u5468\u8fd0\u52a8
\n angle = math.radians(t * 2)
\n radius = 4000
\n x = radius * math.cos(angle)
\n y = radius * math.sin(angle)
\n z = start_pos[2] + math.sin(angle) * 200
\n else:
\n # \u968f\u673a\u8fd0\u52a8
\n x = start_pos[0] + random.uniform(-100, 100) * t
\n y = start_pos[1] + random.uniform(-100, 100) * t
\n z = start_pos[2] + random.uniform(-5, 5) * t<\/p>\n
target_position = np.array([x, y, z])<\/p>\n
# \u8ba1\u7b97\u96f7\u8fbe\u63a2\u6d4b\u53c2\u6570
\n range_vec = target_position – radar_position
\n distance = np.linalg.norm(range_vec)<\/p>\n
# \u8ba1\u7b97\u89d2\u5ea6
\n azimuth = math.degrees(math.atan2(range_vec[1], range_vec[0]))
\n elevation = math.degrees(math.asin(range_vec[2] \/ distance))<\/p>\n
# \u6dfb\u52a0\u566a\u58f0
\n range_noise = random.gauss(0, 10) # \u8ddd\u79bb\u566a\u58f0
\n angle_noise = random.gauss(0, 0.5) # \u89d2\u5ea6\u566a\u58f0<\/p>\n
# \u63a2\u6d4b\u4fe1\u566a\u6bd4
\n snr = 20 – distance\/1000 + random.uniform(-5, 5)<\/p>\n
# \u521b\u5efa\u63a2\u6d4b\u70b9
\n timestamp = start_time + timedelta(seconds=t)
\n detection = {
\n 'timestamp': timestamp,
\n 'target_id': target_id,
\n 'position': target_position.tolist(),
\n 'distance': distance + range_noise,
\n 'azimuth': azimuth + angle_noise,
\n 'elevation': elevation + angle_noise,
\n 'snr': snr,
\n 'radar_position': radar_position.tolist(),
\n 'is_tracked': random.random() > 0.3 # 70%\u7684\u6982\u7387\u88ab\u8ddf\u8e2a
\n }<\/p>\n
detections.append(detection)<\/p>\n
return detections, radar_position<\/p>\n
def save_detections_to_csv(detections, filename='radar_detections.csv'):
\n """\u4fdd\u5b58\u63a2\u6d4b\u6570\u636e\u5230CSV"""
\n data = []<\/p>\n
for det in detections:
\n row = {
\n 'timestamp': det['timestamp'],
\n 'target_id': det['target_id'],
\n 'x': det['position'][0],
\n 'y': det['position'][1],
\n 'z': det['position'][2],
\n 'distance': det['distance'],
\n 'azimuth': det['azimuth'],
\n 'elevation': det['elevation'],
\n 'snr': det['snr'],
\n 'is_tracked': det['is_tracked']
\n }
\n data.append(row)<\/p>\n
df = pd.DataFrame(data)
\n df.to_csv(filename, index=False)
\n print(f"\u63a2\u6d4b\u6570\u636e\u5df2\u4fdd\u5b58\u5230: {filename}")<\/p>\n
return df<\/p>\n
6.2 \u5b8c\u6574\u7684\u6848\u4f8b3\u5b9e\u73b0<\/h4>\n
\u5b9e\u73b0\u96f7\u8fbe\u63a2\u6d4b\u5386\u53f2\u7684\u4e09\u7ef4\u53ef\u89c6\u5316：<\/p>\n
class RadarDetectionVisualizer:
\n """\u96f7\u8fbe\u63a2\u6d4b\u53ef\u89c6\u5316\u5668"""<\/p>\n
def __init__(self):
\n self.detections = []
\n self.radar_position = np.array([0, 0, 0])
\n self.plotter = None<\/p>\n
def load_detection_data(self, num_targets=3):
\n """\u52a0\u8f7d\u6216\u751f\u6210\u63a2\u6d4b\u6570\u636e"""
\n try:
\n # \u5c1d\u8bd5\u4ece\u6587\u4ef6\u52a0\u8f7d
\n df = pd.read_csv('radar_detections.csv')<\/p>\n
self.detections = []
\n for _, row in df.iterrows():
\n detection = {
\n 'timestamp': pd.to_datetime(row['timestamp']),
\n 'target_id': row['target_id'],
\n 'position': np.array([row['x'], row['y'], row['z']]),
\n 'distance': row['distance'],
\n 'azimuth': row['azimuth'],
\n 'elevation': row['elevation'],
\n 'snr': row['snr'],
\n 'is_tracked': bool(row['is_tracked'])
\n }
\n self.detections.append(detection)<\/p>\n
print(f"\u4ece\u6587\u4ef6\u52a0\u8f7d {len(self.detections)} \u4e2a\u63a2\u6d4b\u70b9")<\/p>\n
except FileNotFoundError:
\n print("\u672a\u627e\u5230\u63a2\u6d4b\u6570\u636e\u6587\u4ef6，\u751f\u6210\u6a21\u62df\u6570\u636e…")
\n self.detections, self.radar_position = generate_radar_detection_history(
\n num_targets, 20
\n )
\n save_detections_to_csv(self.detections)<\/p>\n
return len(self.detections)<\/p>\n
def group_detections_by_target(self):
\n """\u6309\u76ee\u6807\u5206\u7ec4\u63a2\u6d4b\u70b9"""
\n targets = {}<\/p>\n
for det in self.detections:
\n target_id = det['target_id']
\n if target_id not in targets:
\n targets[target_id] = []
\n targets[target_id].append(det)<\/p>\n
return targets<\/p>\n
def create_radar_model(self, plotter, radar_position, scale=100):
\n """\u521b\u5efa\u96f7\u8fbe\u6a21\u578b"""
\n # \u96f7\u8fbe\u57fa\u5ea7
\n base = pv.Cylinder(center=radar_position, direction=[0, 0, 1],
\n radius=scale, height=scale*0.5)<\/p>\n
# \u96f7\u8fbe\u5929\u7ebf
\n antenna = pv.Cone(center=radar_position + [0, 0, scale*0.75],
\n direction=[0, 0, 1], height=scale, radius=scale*0.3)<\/p>\n
# \u6dfb\u52a0\u96f7\u8fbe\u6a21\u578b
\n plotter.add_mesh(base, color='gray', name='radar_base')
\n plotter.add_mesh(antenna, color='darkgray', name='radar_antenna')<\/p>\n
return base, antenna<\/p>\n
def create_detection_points(self, detections, plotter, color_by='snr'):
\n """\u521b\u5efa\u63a2\u6d4b\u70b9\u53ef\u89c6\u5316"""
\n if not detections:
\n return None<\/p>\n
# \u63d0\u53d6\u4f4d\u7f6e\u548c\u5176\u4ed6\u5c5e\u6027
\n positions = []
\n snr_values = []
\n distances = []
\n target_ids = []
\n timestamps = []<\/p>\n
for det in detections:
\n positions.append(det['position'])
\n snr_values.append(det['snr'])
\n distances.append(det['distance'])
\n target_ids.append(det['target_id'])
\n timestamps.append(det['timestamp'])<\/p>\n
positions = np.array(positions)<\/p>\n
# \u521b\u5efa\u70b9\u4e91
\n points_mesh = pv.PolyData(positions)<\/p>\n
# \u6dfb\u52a0\u5c5e\u6027
\n points_mesh['snr'] = snr_values
\n points_mesh['distance'] = distances
\n points_mesh['target_id'] = target_ids<\/p>\n
# \u65f6\u95f4\u5c5e\u6027
\n if isinstance(timestamps[0], datetime):
\n timestamps_sec = [t.timestamp() for t in timestamps]
\n else:
\n timestamps_sec = timestamps<\/p>\n
time_min = min(timestamps_sec)
\n time_max = max(timestamps_sec)
\n time_norm = [(t – time_min) \/ (time_max – time_min + 1e-10) for t in timestamps_sec]
\n points_mesh['time'] = time_norm<\/p>\n
return points_mesh<\/p>\n
def create_detection_lines(self, detections_by_target, plotter):
\n """\u521b\u5efa\u63a2\u6d4b\u8fde\u7ebf"""
\n for target_id, detections in detections_by_target.items():
\n if len(detections) < 2:
\n continue<\/p>\n
# \u6309\u65f6\u95f4\u6392\u5e8f
\n detections_sorted = sorted(detections, key=lambda x: x['timestamp'])<\/p>\n
# \u63d0\u53d6\u4f4d\u7f6e
\n positions = [d['position'] for d in detections_sorted]
\n positions = np.array(positions)<\/p>\n
# \u521b\u5efa\u7ebf
\n line = pv.lines_from_points(positions)<\/p>\n
# \u6dfb\u52a0\u65f6\u95f4\u5c5e\u6027
\n timestamps = [d['timestamp'] for d in detections_sorted]
\n if isinstance(timestamps[0], datetime):
\n timestamps_sec = [t.timestamp() for t in timestamps]
\n else:
\n timestamps_sec = timestamps<\/p>\n
time_min = min(timestamps_sec)
\n time_max = max(timestamps_sec)
\n time_norm = [(t – time_min) \/ (time_max – time_min + 1e-10) for t in timestamps_sec]<\/p>\n
# \u7531\u4e8elines_from_points\u4f1a\u63d2\u503c，\u6211\u4eec\u9700\u8981\u5c06\u65f6\u95f4\u5c5e\u6027\u6620\u5c04\u5230\u7ebf\u4e0a
\n # \u4f7f\u7528\u53c2\u6570\u5316\u65b9\u6cd5
\n line_length = line.length
\n line['time'] = np.linspace(0, 1, line.n_points)<\/p>\n
# \u6839\u636e\u76ee\u6807ID\u9009\u62e9\u989c\u8272
\n target_colors = {
\n 'Target001': [1, 0, 0], # \u7ea2\u8272
\n 'Target002': [0, 1, 0], # \u7eff\u8272
\n 'Target003': [0, 0, 1], # \u84dd\u8272
\n 'Target004': [1, 1, 0], # \u9ec4\u8272
\n }<\/p>\n
color = target_colors.get(target_id, [0.5, 0.5, 0.5])<\/p>\n
# \u6dfb\u52a0\u8fde\u7ebf
\n plotter.add_mesh(
\n line,
\n color=color,
\n line_width=3,
\n opacity=0.6,
\n name=f'detection_line_{target_id}'
\n )<\/p>\n
def create_detection_cones(self, detections, plotter, radar_position, max_range=10000):
\n """\u521b\u5efa\u63a2\u6d4b\u9525\u4f53（\u8868\u793a\u96f7\u8fbe\u6ce2\u675f）"""
\n if not detections:
\n return<\/p>\n
# \u6309\u65f6\u95f4\u5206\u7ec4\u63a2\u6d4b\u70b9
\n time_groups = {}
\n for det in detections:
\n # \u7b80\u5316\u65f6\u95f4\u7cbe\u5ea6（\u630910\u79d2\u5206\u7ec4）
\n if isinstance(det['timestamp'], datetime):
\n time_key = det['timestamp'].replace(second=det['timestamp'].second\/\/10 * 10)
\n else:
\n time_key = det['timestamp'] \/\/ 10 * 10<\/p>\n
if time_key not in time_groups:
\n time_groups[time_key] = []
\n time_groups[time_key].append(det)<\/p>\n
# \u4e3a\u6bcf\u4e2a\u65f6\u95f4\u7ec4\u521b\u5efa\u63a2\u6d4b\u9525\u4f53
\n for time_key, time_detections in list(time_groups.items())[::3]: # \u6bcf3\u7ec4\u663e\u793a\u4e00\u4e2a
\n if not time_detections:
\n continue<\/p>\n
# \u8ba1\u7b97\u5e73\u5747\u65b9\u4f4d\u89d2\u548c\u4fef\u4ef0\u89d2
\n azimuths = [d['azimuth'] for d in time_detections]
\n elevations = [d['elevation'] for d in time_detections]<\/p>\n
avg_azimuth = np.mean(azimuths)
\n avg_elevation = np.mean(elevations)<\/p>\n
# \u521b\u5efa\u63a2\u6d4b\u9525\u4f53
\n cone_height = max_range * 0.8
\n cone_radius = cone_height * math.tan(math.radians(5)) # 5\u5ea6\u6ce2\u675f\u5bbd\u5ea6<\/p>\n
# \u521b\u5efa\u9525\u4f53（\u6307\u5411\u5e73\u5747\u65b9\u5411）
\n cone = pv.Cone(center=radar_position, direction=[1, 0, 0],
\n height=cone_height, radius=cone_radius)<\/p>\n
# \u65cb\u8f6c\u5230\u6b63\u786e\u65b9\u5411
\n cone.rotate_z(avg_azimuth, inplace=True)
\n cone.rotate_y(avg_elevation, inplace=True)<\/p>\n
# \u6dfb\u52a0\u9525\u4f53\u5230\u573a\u666f（\u534a\u900f\u660e）
\n plotter.add_mesh(
\n cone,
\n color='yellow',
\n opacity=0.1,
\n style='wireframe' if len(time_detections) > 1 else 'surface',
\n name=f'detection_cone_{time_key}'
\n )<\/p>\n
def add_time_animation(self, plotter, detections_by_target):
\n """\u6dfb\u52a0\u65f6\u95f4\u52a8\u753b\u63a7\u4ef6"""
\n if not detections_by_target:
\n return<\/p>\n
# \u6536\u96c6\u6240\u6709\u65f6\u95f4\u70b9
\n all_timestamps = []
\n for detections in detections_by_target.values():
\n for det in detections:
\n if isinstance(det['timestamp'], datetime):
\n all_timestamps.append(det['timestamp'].timestamp())
\n else:
\n all_timestamps.append(det['timestamp'])<\/p>\n
if not all_timestamps:
\n return<\/p>\n
time_min = min(all_timestamps)
\n time_max = max(all_timestamps)<\/p>\n
# \u5f53\u524d\u65f6\u95f4\u6307\u9488
\n self.current_animation_time = time_min
\n self.animation_speed = 1.0 # \u5b9e\u65f6\u901f\u5ea6
\n self.is_animating = False<\/p>\n
# \u65f6\u95f4\u6ed1\u5757
\n def update_time_slider(value):
\n self.current_animation_time = value
\n self._update_animation_frame(plotter, detections_by_target)<\/p>\n
plotter.add_slider_widget(
\n update_time_slider,
\n [time_min, time_max],
\n value=time_min,
\n title='\u65f6\u95f4',
\n pointa=(0.7, 0.9),
\n pointb=(0.9, 0.9),
\n style='modern'
\n )<\/p>\n
# \u64ad\u653e\/\u6682\u505c\u6309\u94ae
\n def toggle_animation():
\n self.is_animating = not self.is_animating
\n state = "\u64ad\u653e" if self.is_animating else "\u6682\u505c"
\n print(f"\u52a8\u753b{state}")<\/p>\n
plotter.add_checkbox_button_widget(
\n toggle_animation,
\n value=False,
\n position=(10, 10),
\n size=30,
\n color_on='green',
\n color_off='red',
\n background_color='white'
\n )<\/p>\n
# \u901f\u5ea6\u63a7\u5236
\n def set_animation_speed(value):
\n self.animation_speed = value
\n print(f"\u52a8\u753b\u901f\u5ea6: {value}x")<\/p>\n
plotter.add_slider_widget(
\n set_animation_speed,
\n [0.1, 5.0],
\n value=1.0,
\n title='\u901f\u5ea6',
\n pointa=(0.7, 0.8),
\n pointb=(0.9, 0.8),
\n style='modern'
\n )<\/p>\n
def _update_animation_frame(self, plotter, detections_by_target):
\n """\u66f4\u65b0\u52a8\u753b\u5e27"""
\n # \u6e05\u9664\u5f53\u524d\u5e27\u7684\u6807\u8bb0
\n for actor_name in list(plotter.actors.keys()):
\n if actor_name.startswith(('current_detection_', 'time_marker_')):
\n plotter.remove_actor(plotter.actors[actor_name])<\/p>\n
# \u66f4\u65b0\u6bcf\u4e2a\u76ee\u6807\u7684\u5f53\u524d\u4f4d\u7f6e\u6807\u8bb0
\n for target_id, detections in detections_by_target.items():
\n # \u627e\u5230\u6700\u63a5\u8fd1\u5f53\u524d\u65f6\u95f4\u7684\u63a2\u6d4b\u70b9
\n closest_det = None
\n min_time_diff = float('inf')<\/p>\n
for det in detections:
\n if isinstance(det['timestamp'], datetime):
\n det_time = det['timestamp'].timestamp()
\n else:
\n det_time = det['timestamp']<\/p>\n
time_diff = abs(det_time – self.current_animation_time)
\n if time_diff < min_time_diff:
\n min_time_diff = time_diff
\n closest_det = det<\/p>\n
if closest_det and min_time_diff < 30: # 30\u79d2\u5185\u8ba4\u4e3a\u6709\u6548
\n # \u521b\u5efa\u5f53\u524d\u4f4d\u7f6e\u6807\u8bb0
\n marker = pv.Sphere(center=closest_det['position'], radius=100)<\/p>\n
target_colors = {
\n 'Target001': [1, 0, 0],
\n 'Target002': [0, 1, 0],
\n 'Target003': [0, 0, 1],
\n 'Target004': [1, 1, 0],
\n }<\/p>\n
color = target_colors.get(target_id, [0.5, 0.5, 0.5])<\/p>\n
plotter.add_mesh(
\n marker,
\n color=color,
\n name=f'current_detection_{target_id}'
\n )<\/p>\n
# \u6dfb\u52a0\u65f6\u95f4\u6807\u7b7e
\n time_text = closest_det['timestamp'].strftime('%H:%M:%S') if isinstance(closest_det['timestamp'], datetime) else str(closest_det['timestamp'])
\n label_text = f"{target_id}\\\\n{time_text}\\\\nSNR: {closest_det['snr']:.1f}dB"<\/p>\n
plotter.add_point_labels(
\n [closest_det['position']],
\n [label_text],
\n font_size=8,
\n point_color=color,
\n point_size=0,
\n name=f'time_marker_{target_id}'
\n )<\/p>\n
# \u66f4\u65b0\u65f6\u95f4\u663e\u793a
\n if 'time_display' in plotter.actors:
\n plotter.remove_actor(plotter.actors['time_display'])<\/p>\n
current_time_str = datetime.fromtimestamp(self.current_animation_time).strftime('%Y-%m-%d %H:%M:%S') if self.current_animation_time > 0 else str(self.current_animation_time)
\n time_text = f"\u5f53\u524d\u65f6\u95f4: {current_time_str}"<\/p>\n
plotter.add_text(
\n time_text,
\n position='upper_center',
\n font_size=12,
\n color='white',
\n name='time_display'
\n )<\/p>\n
def add_animation_callback(self, plotter, detections_by_target):
\n """\u6dfb\u52a0\u52a8\u753b\u56de\u8c03\u51fd\u6570"""
\n self.last_animation_time = time.time()<\/p>\n
def animation_callback():
\n if not self.is_animating:
\n return<\/p>\n
current_time = time.time()
\n delta_time = current_time – self.last_animation_time
\n self.last_animation_time = current_time<\/p>\n
# \u66f4\u65b0\u65f6\u95f4
\n time_delta = delta_time * self.animation_speed
\n self.current_animation_time += time_delta<\/p>\n
# \u68c0\u67e5\u65f6\u95f4\u8303\u56f4
\n all_timestamps = []
\n for detections in detections_by_target.values():
\n for det in detections:
\n if isinstance(det['timestamp'], datetime):
\n all_timestamps.append(det['timestamp'].timestamp())
\n else:
\n all_timestamps.append(det['timestamp'])<\/p>\n
if all_timestamps:
\n time_max = max(all_timestamps)
\n if self.current_animation_time > time_max:
\n self.current_animation_time = min(all_timestamps) # \u5faa\u73af\u64ad\u653e<\/p>\n
# \u66f4\u65b0\u5e27
\n self._update_animation_frame(plotter, detections_by_target)<\/p>\n
plotter.add_callback(animation_callback, interval=50) # 20fps<\/p>\n
def create_statistics_panel(self, plotter, detections_by_target):
\n """\u521b\u5efa\u7edf\u8ba1\u4fe1\u606f\u9762\u677f"""
\n if not detections_by_target:
\n return<\/p>\n
stats_text = "\u96f7\u8fbe\u63a2\u6d4b\u7edf\u8ba1\\\\n"
\n stats_text += "=" * 20 + "\\\\n"<\/p>\n
total_detections = 0
\n for target_id, detections in detections_by_target.items():
\n stats_text += f"{target_id}:\\\\n"
\n stats_text += f" \u63a2\u6d4b\u70b9\u6570: {len(detections)}\\\\n"<\/p>\n
if detections:
\n snr_values = [d['snr'] for d in detections]
\n distances = [d['distance'] for d in detections]<\/p>\n
stats_text += f" \u5e73\u5747SNR: {np.mean(snr_values):.1f}dB\\\\n"
\n stats_text += f" \u5e73\u5747\u8ddd\u79bb: {np.mean(distances):.0f}m\\\\n"
\n stats_text += f" \u8ddf\u8e2a\u7387: {sum(1 for d in detections if d['is_tracked'])\/len(detections)*100:.1f}%\\\\n"<\/p>\n
stats_text += "\\\\n"
\n total_detections += len(detections)<\/p>\n
stats_text += f"\u603b\u63a2\u6d4b\u70b9: {total_detections}\\\\n"<\/p>\n
plotter.add_text(
\n stats_text,
\n position='upper_left',
\n font_size=10,
\n color='white',
\n name='statistics_panel'
\n )<\/p>\n
def create_visibility_controls(self, plotter):
\n """\u521b\u5efa\u53ef\u89c6\u5316\u63a7\u5236"""
\n controls = {
\n 'show_detection_points': True,
\n 'show_detection_lines': True,
\n 'show_detection_cones': False,
\n 'show_radar_model': True
\n }<\/p>\n
# \u63a2\u6d4b\u70b9\u663e\u793a\u63a7\u5236
\n def toggle_detection_points(state):
\n controls['show_detection_points'] = state
\n self._update_visibility(plotter, controls)<\/p>\n
plotter.add_checkbox_button_widget(
\n toggle_detection_points,
\n value=True,
\n position=(10, 50),
\n size=25,
\n color_on='green',
\n color_off='red'
\n )
\n plotter.add_text("\u63a2\u6d4b\u70b9", position=(40, 50), font_size=10, color='white')<\/p>\n
# \u63a2\u6d4b\u7ebf\u663e\u793a\u63a7\u5236
\n def toggle_detection_lines(state):
\n controls['show_detection_lines'] = state
\n self._update_visibility(plotter, controls)<\/p>\n
plotter.add_checkbox_button_widget(
\n toggle_detection_lines,
\n value=True,
\n position=(10, 85),
\n size=25,
\n color_on='green',
\n color_off='red'
\n )
\n plotter.add_text("\u63a2\u6d4b\u7ebf", position=(40, 85), font_size=10, color='white')<\/p>\n
# \u63a2\u6d4b\u9525\u4f53\u663e\u793a\u63a7\u5236
\n def toggle_detection_cones(state):
\n controls['show_detection_cones'] = state
\n self._update_visibility(plotter, controls)<\/p>\n
plotter.add_checkbox_button_widget(
\n toggle_detection_cones,
\n value=False,
\n position=(10, 120),
\n size=25,
\n color_on='green',
\n color_off='red'
\n )
\n plotter.add_text("\u63a2\u6d4b\u6ce2\u675f", position=(40, 120), font_size=10, color='white')<\/p>\n
# \u96f7\u8fbe\u6a21\u578b\u663e\u793a\u63a7\u5236
\n def toggle_radar_model(state):
\n controls['show_radar_model'] = state
\n self._update_visibility(plotter, controls)<\/p>\n
plotter.add_checkbox_button_widget(
\n toggle_radar_model,
\n value=True,
\n position=(10, 155),
\n size=25,
\n color_on='green',
\n color_off='red'
\n )
\n plotter.add_text("\u96f7\u8fbe\u6a21\u578b", position=(40, 155), font_size=10, color='white')<\/p>\n
return controls<\/p>\n
def _update_visibility(self, plotter, controls):
\n """\u66f4\u65b0\u53ef\u89c6\u5316\u5143\u7d20\u663e\u793a\u72b6\u6001"""
\n # \u66f4\u65b0\u63a2\u6d4b\u70b9\u663e\u793a
\n for actor_name in list(plotter.actors.keys()):
\n if actor_name.startswith('detection_points'):
\n plotter.actors[actor_name].SetVisibility(controls['show_detection_points'])<\/p>\n
# \u66f4\u65b0\u63a2\u6d4b\u7ebf\u663e\u793a
\n for actor_name in list(plotter.actors.keys()):
\n if actor_name.startswith('detection_line'):
\n plotter.actors[actor_name].SetVisibility(controls['show_detection_lines'])<\/p>\n
# \u66f4\u65b0\u63a2\u6d4b\u9525\u4f53\u663e\u793a
\n for actor_name in list(plotter.actors.keys()):
\n if actor_name.startswith('detection_cone'):
\n plotter.actors[actor_name].SetVisibility(controls['show_detection_cones'])<\/p>\n
# \u66f4\u65b0\u96f7\u8fbe\u6a21\u578b\u663e\u793a
\n for actor_name in list(plotter.actors.keys()):
\n if actor_name.startswith('radar_'):
\n plotter.actors[actor_name].SetVisibility(controls['show_radar_model'])<\/p>\n
plotter.update()<\/p>\n
def run_demo(self, num_targets=3):
\n """\u8fd0\u884c\u96f7\u8fbe\u63a2\u6d4b\u5386\u53f2\u53ef\u89c6\u5316\u6f14\u793a"""
\n print("\u96f7\u8fbe\u63a2\u6d4b\u5386\u53f2\u53ef\u89c6\u5316\u6f14\u793a")
\n print("=" * 50)<\/p>\n
# \u52a0\u8f7d\u6570\u636e
\n detection_count = self.load_detection_data(num_targets)
\n print(f"\u52a0\u8f7d\u4e86 {detection_count} \u4e2a\u63a2\u6d4b\u70b9")<\/p>\n
# \u6309\u76ee\u6807\u5206\u7ec4
\n detections_by_target = self.group_detections_by_target()
\n print(f"\u68c0\u6d4b\u5230 {len(detections_by_target)} \u4e2a\u76ee\u6807")<\/p>\n
# \u521b\u5efa\u7ed8\u56fe\u7a97\u53e3
\n self.plotter = pv.Plotter(window_size=(1600, 900),
\n title="\u96f7\u8fbe\u63a2\u6d4b\u5386\u53f2\u53ef\u89c6\u5316")<\/p>\n
# \u8bbe\u7f6e\u573a\u666f
\n self.plotter.set_background('linear_gradient', bottom='#0a0a1a', top='#1a1a2a')
\n self.plotter.add_axes()
\n self.plotter.show_grid()<\/p>\n
# \u6dfb\u52a0\u5730\u5f62
\n x = np.linspace(-10000, 10000, 30)
\n y = np.linspace(-10000, 10000, 30)
\n xx, yy = np.meshgrid(x, y)
\n z = 100 + 50 * np.sin(0.001 * xx) * np.cos(0.001 * yy)
\n terrain = pv.StructuredGrid(xx, yy, z)
\n terrain['elevation'] = z.ravel()<\/p>\n
self.plotter.add_mesh(
\n terrain,
\n cmap='terrain',
\n scalars='elevation',
\n opacity=0.3,
\n show_edges=False,
\n name='terrain'
\n )<\/p>\n
# \u6dfb\u52a0\u96f7\u8fbe\u6a21\u578b
\n radar_scale = 200
\n self.create_radar_model(self.plotter, self.radar_position, radar_scale)<\/p>\n
# \u6dfb\u52a0\u63a2\u6d4b\u70b9
\n all_detections = []
\n for target_detections in detections_by_target.values():
\n all_detections.extend(target_detections)<\/p>\n
points_mesh = self.create_detection_points(all_detections, self.plotter, 'snr')
\n if points_mesh is not None:
\n self.plotter.add_mesh(
\n points_mesh,
\n scalars='snr',
\n cmap='hot',
\n point_size=8,
\n render_points_as_spheres=True,
\n opacity=0.8,
\n name='detection_points',
\n show_scalar_bar=True,
\n scalar_bar_args={'title': '\u4fe1\u566a\u6bd4 (dB)'}
\n )<\/p>\n
# \u6dfb\u52a0\u63a2\u6d4b\u8fde\u7ebf
\n self.create_detection_lines(detections_by_target, self.plotter)<\/p>\n
# \u6dfb\u52a0\u63a2\u6d4b\u9525\u4f53
\n self.create_detection_cones(all_detections, self.plotter, self.radar_position)<\/p>\n
# \u6dfb\u52a0\u65f6\u95f4\u52a8\u753b\u63a7\u4ef6
\n self.add_time_animation(self.plotter, detections_by_target)<\/p>\n
# \u6dfb\u52a0\u52a8\u753b\u56de\u8c03
\n self.add_animation_callback(self.plotter, detections_by_target)<\/p>\n
# \u6dfb\u52a0\u7edf\u8ba1\u4fe1\u606f\u9762\u677f
\n self.create_statistics_panel(self.plotter, detections_by_target)<\/p>\n
# \u6dfb\u52a0\u53ef\u89c6\u5316\u63a7\u5236
\n controls = self.create_visibility_controls(self.plotter)<\/p>\n
# \u6dfb\u52a0\u63a7\u5236\u8bf4\u660e
\n instructions = "\u63a7\u5236\u8bf4\u660e:\\\\n"
\n instructions += "\u5de6\u4fa7\u590d\u9009\u6846: \u663e\u793a\/\u9690\u85cf\u5143\u7d20\\\\n"
\n instructions += "\u65f6\u95f4\u6ed1\u5757: \u624b\u52a8\u63a7\u5236\u65f6\u95f4\\\\n"
\n instructions += "\u64ad\u653e\u6309\u94ae: \u5f00\u59cb\/\u6682\u505c\u52a8\u753b\\\\n"
\n instructions += "\u901f\u5ea6\u6ed1\u5757: \u8c03\u6574\u52a8\u753b\u901f\u5ea6\\\\n"
\n instructions += "\u9f20\u6807\u4ea4\u4e92: \u65cb\u8f6c\/\u5e73\u79fb\/\u7f29\u653e\u89c6\u89d2\\\\n"<\/p>\n
self.plotter.add_text(
\n instructions,
\n position='lower_left',
\n font_size=10,
\n color='cyan',
\n name='instructions'
\n )<\/p>\n
# \u8bbe\u7f6e\u76f8\u673a
\n self.plotter.camera_position = [
\n (self.radar_position[0], self.radar_position[1] – 15000, 5000),
\n self.radar_position,
\n (0, 0, 1)
\n ]<\/p>\n
print("\\\\n\u6f14\u793a\u5df2\u542f\u52a8")
\n print("\u4f7f\u7528\u5de6\u4fa7\u590d\u9009\u6846\u63a7\u5236\u4e0d\u540c\u5143\u7d20\u7684\u663e\u793a")
\n print("\u4f7f\u7528\u65f6\u95f4\u63a7\u4ef6\u67e5\u770b\u4e0d\u540c\u65f6\u95f4\u7684\u63a2\u6d4b\u60c5\u51b5")<\/p>\n
# \u663e\u793a
\n self.plotter.show()<\/p>\n
# \u8fd0\u884c\u6848\u4f8b3
\ndef run_case3():
\n demo = RadarDetectionVisualizer()
\n demo.run_demo(num_targets=3)<\/p>\n
if __name__ == "__main__":
\n run_case3()<\/p>\n
7. \u77e5\u8bc6\u70b9\u603b\u7ed3\u4e0e\u6269\u5c55\u5e94\u7528<\/h3>\n7.1 \u6838\u5fc3\u6280\u672f\u8981\u70b9\u603b\u7ed3<\/h4>\n
1. \u8f68\u8ff9\u6570\u636e\u5904\u7406\u6280\u672f<\/p>\n
- \n
- \n
\u591a\u683c\u5f0f\u6570\u636e\u52a0\u8f7d（CSV\u3001JSON\u3001\u6570\u636e\u5e93）<\/p>\n<\/li>\n
- \n
\u5750\u6807\u7cfb\u7edf\u8f6c\u6362\u4e0e\u6570\u636e\u6807\u51c6\u5316<\/p>\n<\/li>\n
- \n
\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u5904\u7406\u4e0e\u63d2\u503c<\/p>\n<\/li>\n
- \n
\u8f68\u8ff9\u4f18\u5316\u4e0e\u91c7\u6837\u7b97\u6cd5<\/p>\n<\/li>\n<\/ul>\n
2. 3D\u53ef\u89c6\u5316\u6280\u672f<\/p>\n
- \n
- \n
\u591a\u79cd\u8f68\u8ff9\u8868\u793a\u65b9\u6cd5（\u7ebf\u3001\u6837\u6761\u3001\u7ba1\u9053）<\/p>\n<\/li>\n
- \n
\u989c\u8272\u6620\u5c04\u4e0e\u5c5e\u6027\u53ef\u89c6\u5316<\/p>\n<\/li>\n
- \n
\u52a8\u6001\u65f6\u95f4\u8f74\u4e0e\u52a8\u753b\u63a7\u5236<\/p>\n<\/li>\n
- \n
\u4ea4\u4e92\u5f0f\u63a7\u4ef6\u4e0e\u7528\u6237\u754c\u9762<\/p>\n<\/li>\n<\/ul>\n
3. \u96f7\u8fbe\u63a2\u6d4b\u53ef\u89c6\u5316<\/p>\n
- \n
- \n
\u63a2\u6d4b\u70b9\u4e91\u7684\u53ef\u89c6\u5316<\/p>\n<\/li>\n
- \n
\u96f7\u8fbe\u6ce2\u675f\u4e0e\u63a2\u6d4b\u8303\u56f4\u8868\u793a<\/p>\n<\/li>\n
- \n
\u591a\u76ee\u6807\u8ddf\u8e2a\u4e0e\u8f68\u8ff9\u91cd\u5efa<\/p>\n<\/li>\n
- \n
\u63a2\u6d4b\u8d28\u91cf（SNR）\u7684\u53ef\u89c6\u5316<\/p>\n<\/li>\n<\/ul>\n
7.2 \u6027\u80fd\u4f18\u5316\u6280\u5de7<\/h4>\n
\u5927\u89c4\u6a21\u8f68\u8ff9\u6570\u636e\u5904\u7406<\/p>\n
# 1. \u6570\u636e\u5206\u5757\u52a0\u8f7d
\ndef load_large_trajectory_chunked(filepath, chunk_size=10000):
\n """\u5206\u5757\u52a0\u8f7d\u5927\u89c4\u6a21\u8f68\u8ff9\u6570\u636e"""
\n chunks = []
\n for chunk in pd.read_csv(filepath, chunksize=chunk_size):
\n # \u5904\u7406\u6bcf\u4e2a\u6570\u636e\u5757
\n processed_chunk = process_trajectory_chunk(chunk)
\n chunks.append(processed_chunk)
\n return pd.concat(chunks)<\/p>\n# 2. \u7ec6\u8282\u5c42\u6b21（LOD）\u6280\u672f
\ndef create_lod_trajectory(trajectory, lod_levels=3):
\n """\u521b\u5efa\u591a\u7ec6\u8282\u5c42\u6b21\u8f68\u8ff9"""
\n lod_meshes = []
\n for level in range(lod_levels):
\n if level == 0: # \u6700\u9ad8\u7ec6\u8282
\n mesh = create_high_detail_trajectory(trajectory)
\n else: # \u8f83\u4f4e\u7ec6\u8282
\n sample_ratio = 1.0 \/ (2 ** level)
\n sampled_points = uniform_sampling(trajectory.points, sample_ratio)
\n mesh = create_simplified_trajectory(sampled_points)
\n lod_meshes.append(mesh)
\n return lod_meshes<\/p>\n\u5b9e\u65f6\u6e32\u67d3\u4f18\u5316<\/p>\n
# 1. \u5b9e\u4f8b\u5316\u6e32\u67d3
\ndef render_multiple_trajectories_instanced(trajectories):
\n """\u4f7f\u7528\u5b9e\u4f8b\u5316\u6e32\u67d3\u591a\u4e2a\u76f8\u4f3c\u8f68\u8ff9"""
\n base_mesh = create_base_trajectory_mesh()
\n instance_matrices = []<\/p>\nfor traj in trajectories:
\n # \u8ba1\u7b97\u53d8\u6362\u77e9\u9635
\n matrix = calculate_transform_matrix(traj)
\n instance_matrices.append(matrix)<\/p>\n# \u6279\u91cf\u6e32\u67d3
\n plotter.add_mesh(base_mesh, transforms=instance_matrices)<\/p>\n# 2. \u89c6\u9525\u4f53\u88c1\u526a
\ndef frustum_culling(trajectories, camera_frustum):
\n """\u89c6\u9525\u4f53\u88c1\u526a，\u53ea\u6e32\u67d3\u53ef\u89c1\u8f68\u8ff9"""
\n visible_trajectories = []
\n for traj in trajectories:
\n if is_trajectory_in_frustum(traj, camera_frustum):
\n visible_trajectories.append(traj)
\n return visible_trajectories<\/p>\n7.3 \u6269\u5c55\u5e94\u7528\u65b9\u5411<\/h4>\n
\u519b\u4e8b\u4eff\u771f\u5e94\u7528<\/p>\n
- \n
- \n
\u6218\u573a\u6001\u52bf\u5b9e\u65f6\u53ef\u89c6\u5316<\/p>\n<\/li>\n
- \n
\u5bfc\u5f39\u9632\u5fa1\u7cfb\u7edf\u6a21\u62df<\/p>\n<\/li>\n
- \n
\u7535\u5b50\u5bf9\u6297\u6548\u679c\u8bc4\u4f30<\/p>\n<\/li>\n
- \n
\u4f5c\u6218\u65b9\u6848\u63a8\u6f14\u9a8c\u8bc1<\/p>\n<\/li>\n<\/ul>\n
\u6c11\u7528\u9886\u57df\u5e94\u7528<\/p>\n
- \n
- \n
\u7a7a\u4e2d\u4ea4\u901a\u7ba1\u5236\u7cfb\u7edf<\/p>\n<\/li>\n
- \n
\u65e0\u4eba\u673a\u822a\u8ff9\u76d1\u63a7<\/p>\n<\/li>\n
- \n
\u8f66\u8f86\u8f68\u8ff9\u5206\u6790<\/p>\n<\/li>\n
- \n
\u8fd0\u52a8\u76ee\u6807\u884c\u4e3a\u5206\u6790<\/p>\n<\/li>\n<\/ul>\n
\u79d1\u5b66\u7814\u7a76\u5e94\u7528<\/p>\n
- \n
- \n
\u52a8\u7269\u8fc1\u5f99\u8f68\u8ff9\u7814\u7a76<\/p>\n<\/li>\n
- \n
\u6c14\u8c61\u6570\u636e\u53ef\u89c6\u5316<\/p>\n<\/li>\n
- \n
\u6d77\u6d0b\u6d0b\u6d41\u5206\u6790<\/p>\n<\/li>\n
- \n
\u5929\u4f53\u8fd0\u52a8\u8f68\u8ff9\u6a21\u62df<\/p>\n<\/li>\n<\/ul>\n
8. \u7ed3\u8bed<\/h3>\n
\u672c\u6587\u4ecb\u7ecd\u4e86\u4f7f\u7528PyVista\u8fdb\u884c\u96f7\u8fbe\u4e0e\u76ee\u6807\u8f68\u8ff9\u53ef\u89c6\u5316\u7684\u5b8c\u6574\u6280\u672f\u65b9\u6848，\u6db5\u76d6\u4e86\u4ece\u6570\u636e\u52a0\u8f7d\u5904\u7406\u5230\u9ad8\u7ea7\u53ef\u89c6\u5316\u7684\u5168\u6d41\u7a0b\u3002\u901a\u8fc7\u4e09\u4e2a\u5b9e\u6218\u6848\u4f8b，\u6211\u4eec\u5c55\u793a\u4e86：<\/p>\n
- \n
\u5355\u76ee\u6807\u98de\u884c\u8f68\u8ff9\u53ef\u89c6\u5316\u200b – \u57fa\u7840\u8f68\u8ff9\u8868\u793a\u4e0e\u5c5e\u6027\u6620\u5c04<\/p>\n<\/li>\n
- \n
\u591a\u76ee\u6807\u8f68\u8ff9\u5bf9\u6bd4\u5206\u6790\u200b – \u590d\u6742\u573a\u666f\u4e0b\u7684\u8f68\u8ff9\u7ba1\u7406\u4e0e\u6bd4\u8f83<\/p>\n<\/li>\n
- \n
\u96f7\u8fbe\u63a2\u6d4b\u5386\u53f2\u53ef\u89c6\u5316\u200b – \u65f6\u95f4\u5e8f\u5217\u6570\u636e\u7684\u52a8\u6001\u5c55\u793a<\/p>\n<\/li>\n
\u8fd9\u4e9b\u6280\u672f\u4e0d\u4ec5\u9002\u7528\u4e8e\u519b\u4e8b\u4eff\u771f\u9886\u57df，\u5728\u4ea4\u901a\u76d1\u63a7\u3001\u73af\u5883\u76d1\u6d4b\u3001\u79d1\u5b66\u7814\u7a76\u7b49\u4f17\u591a\u9886\u57df\u90fd\u6709\u5e7f\u6cdb\u5e94\u7528\u4ef7\u503c\u3002PyVista\u4f5c\u4e3a\u5f3a\u5927\u76843D\u53ef\u89c6\u5316\u5de5\u5177，\u4e3a\u8f68\u8ff9\u6570\u636e\u7684\u76f4\u89c2\u7406\u89e3\u548c\u6df1\u5ea6\u5206\u6790\u63d0\u4f9b\u4e86\u6709\u529b\u652f\u6301\u3002<\/p>\n
\u968f\u7740\u6570\u636e\u89c4\u6a21\u7684\u4e0d\u65ad\u6269\u5927\u548c\u5206\u6790\u9700\u6c42\u7684\u65e5\u76ca\u590d\u6742，\u8f68\u8ff9\u53ef\u89c6\u5316\u6280\u672f\u5c06\u7ee7\u7eed\u5411\u5b9e\u65f6\u5316\u3001\u667a\u80fd\u5316\u3001\u4ea4\u4e92\u5f0f\u65b9\u5411\u53d1\u5c55\u3002\u638c\u63e1\u8fd9\u4e9b\u6838\u5fc3\u6280\u672f，\u5c06\u4e3a\u5e94\u5bf9\u672a\u6765\u7684\u6570\u636e\u53ef\u89c6\u5316\u6311\u6218\u5960\u5b9a\u575a\u5b9e\u57fa\u7840\u3002<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"
\u6458\u8981\u5728\u519b\u4e8b\u4eff\u771f\u3001\u7a7a\u4e2d\u4ea4\u901a\u7ba1\u5236\u3001\u65e0\u4eba\u673a\u76d1\u63a7\u7b49\u9886\u57df，\u8f68\u8ff9\u6570\u636e\u7684\u53ef\u89c6\u5316\u662f\u7406\u89e3\u76ee\u6807\u884c\u4e3a\u3001\u5206\u6790\u8fd0\u52a8\u89c4\u5f8b\u3001\u8bc4\u4f30\u6218\u672f\u6548\u679c\u7684\u5173\u952e\u3002\u672c\u6587\u662f\\”PyVista\u96f7\u8fbe\u7535\u5b50\u5bf9\u6297\u6218\u573a\u6001\u52bf\u4eff\u771f\\”\u7cfb\u5217\u7684\u7b2c\u4e09\u7bc7，\u4e13\u6ce8\u4e8e\u96f7\u8fbe\u4e0e\u76ee\u6807\u8f68\u8ff9\u76843D\u53ef\u89c6\u5316\u6280\u672f\u3002\u6211\u4eec\u5c06\u6df1\u5165\u63a2\u8ba8\u5982\u4f55\u4ece\u5404\u79cd\u6570\u636e\u6e90\u52a0\u8f7d\u8f68\u8ff9\u6570\u636e，\u57283D\u7a7a\u95f4\u4e2d\u521b\u5efa\u76f4\u89c2\u7684\u52a8\u6001\u8f68\u8ff9\u5c55\u793a，\u4ee5\u53ca\u5982\u4f55\u901a\u8fc7\u989c\u8272\u6620\u5c04\u3001\u65f6\u95f4\u6807\u7b7e\u3001\u591a\u7ef4\u5ea6\u4fe1\u606f\u53e0\u52a0\u7b49\u65b9\u5f0f\u589e\u5f3a\u8f68\u8ff9\u7684\u53ef\u8bfb\u6027\u548c\u4fe1\u606f\u5bc6\u5ea6\u3002\u901a\u8fc7\u4e09\u4e2a\u5b8c\u6574\u7684\u5b9e\u6218\u6848\u4f8b，\u8bfb\u8005\u5c06\u638c\u63e1\u8f68<\/p>\n","protected":false},"author":2,"featured_media":63256,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[6688,81,5936,50,190,207,442],"topic":[],"class_list":["post-63257","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server","tag-gui","tag-python","tag-tkinter","tag-50","tag-190","tag-207","tag-442"],"yoast_head":"\n
PyVista\u6218\u573a\u53ef\u89c6\u5316\u5b9e\u6218\uff08\u4e09\uff09\uff1a\u96f7\u8fbe\u4e0e\u76ee\u6807\u8f68\u8ff9\u53ef\u89c6\u5316 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/63257.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PyVista\u6218\u573a\u53ef\u89c6\u5316\u5b9e\u6218\uff08\u4e09\uff09\uff1a\u96f7\u8fbe\u4e0e\u76ee\u6807\u8f68\u8ff9\u53ef\u89c6\u5316 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"og:description\" content=\"\u6458\u8981\u5728\u519b\u4e8b\u4eff\u771f\u3001\u7a7a\u4e2d\u4ea4\u901a\u7ba1\u5236\u3001\u65e0\u4eba\u673a\u76d1\u63a7\u7b49\u9886\u57df，\u8f68\u8ff9\u6570\u636e\u7684\u53ef\u89c6\u5316\u662f\u7406\u89e3\u76ee\u6807\u884c\u4e3a\u3001\u5206\u6790\u8fd0\u52a8\u89c4\u5f8b\u3001\u8bc4\u4f30\u6218\u672f\u6548\u679c\u7684\u5173\u952e\u3002\u672c\u6587\u662f"PyVista\u96f7\u8fbe\u7535\u5b50\u5bf9\u6297\u6218\u573a\u6001\u52bf\u4eff\u771f"\u7cfb\u5217\u7684\u7b2c\u4e09\u7bc7，\u4e13\u6ce8\u4e8e\u96f7\u8fbe\u4e0e\u76ee\u6807\u8f68\u8ff9\u76843D\u53ef\u89c6\u5316\u6280\u672f\u3002\u6211\u4eec\u5c06\u6df1\u5165\u63a2\u8ba8\u5982\u4f55\u4ece\u5404\u79cd\u6570\u636e\u6e90\u52a0\u8f7d\u8f68\u8ff9\u6570\u636e，\u57283D\u7a7a\u95f4\u4e2d\u521b\u5efa\u76f4\u89c2\u7684\u52a8\u6001\u8f68\u8ff9\u5c55\u793a，\u4ee5\u53ca\u5982\u4f55\u901a\u8fc7\u989c\u8272\u6620\u5c04\u3001\u65f6\u95f4\u6807\u7b7e\u3001\u591a\u7ef4\u5ea6\u4fe1\u606f\u53e0\u52a0\u7b49\u65b9\u5f0f\u589e\u5f3a\u8f68\u8ff9\u7684\u53ef\u8bfb\u6027\u548c\u4fe1\u606f\u5bc6\u5ea6\u3002\u901a\u8fc7\u4e09\u4e2a\u5b8c\u6574\u7684\u5b9e\u6218\u6848\u4f8b，\u8bfb\u8005\u5c06\u638c\u63e1\u8f68\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.wsisp.com\/helps\/63257.html\" \/>\n<meta property=\"og:site_name\" content=\"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"article:published_time\" content=\"2026-01-21T10:16:56+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260121101654-6970a79652ca0.png\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u4f5c\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\" \/>\n\t<meta name=\"twitter:data2\" content=\"35 \u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/63257.html\",\"url\":\"https:\/\/www.wsisp.com\/helps\/63257.html\",\"name\":\"PyVista\u6218\u573a\u53ef\u89c6\u5316\u5b9e\u6218\uff08\u4e09\uff09\uff1a\u96f7\u8fbe\u4e0e\u76ee\u6807\u8f68\u8ff9\u53ef\u89c6\u5316 - 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