tmp_video = filename + "_tmp." + ext output_video = filename + "_hud." + ext camera = camera.VirtualCamera() camera.load(args.camera, local_config, args.scale) cam_yaw, cam_pitch, cam_roll = camera.get_ypr() K = camera.get_K() dist = camera.get_dist() print('Camera:', camera.get_name()) print('K:\n', K) print('dist:', dist) if os.path.exists(ekf_error): correction.load_horiz(ekf_error) data, flight_format = flight_loader.load(args.flight) print("imu records:", len(data['imu'])) print("gps records:", len(data['gps'])) if 'air' in data: print("airdata records:", len(data['air'])) print("filter records:", len(data['filter'])) if 'pilot' in data: print("pilot records:", len(data['pilot'])) if 'act' in data: print("act records:", len(data['act'])) if len(data['imu']) == 0 and len(data['gps']) == 0: print("not enough data loaded to continue.") quit() interp = flight_interp.InterpolationGroup(data) iter = flight_interp.IterateGroup(data)
from aurauas_flightdata import flight_loader, flight_interp parser = argparse.ArgumentParser(description='nav filter') parser.add_argument('flight', help='flight data log') parser.add_argument('--wind-time', type=float, help='force a wind re-estimate with this time factor.') args = parser.parse_args() r2d = 180.0 / math.pi d2r = math.pi / 180.0 m2nm = 0.0005399568034557235 # meters to nautical miles mps2kt = 1.94384 # m/s to kts path = args.flight data, flight_format = flight_loader.load(path) print("imu records:", len(data['imu'])) imu_dt = (data['imu'][-1]['time'] - data['imu'][0]['time']) \ / float(len(data['imu'])) print("imu dt: %.3f" % imu_dt) print("gps records:", len(data['gps'])) if 'air' in data: print("airdata records:", len(data['air'])) if len(data['imu']) == 0 and len(data['gps']) == 0: print("not enough data loaded to continue.") quit() # make data frames for easier plotting df0_imu = pd.DataFrame(data['imu']) df0_imu.set_index('time', inplace=True, drop=False)