kopia lustrzana https://github.com/projecthorus/chasemapper
Update log parse to overlay GFS data for descent trace.
Mark Jessop
rodzic
ca4c22a018
commit
c4ce14d234
98
log_parse.py
98
log_parse.py
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@ -16,6 +16,7 @@ import matplotlib.pyplot as plt
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from chasemapper.earthmaths import *
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from chasemapper.geometry import *
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from dateutil.parser import parse
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from cusfpredict.reader import *
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def read_file(filename):
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@ -79,14 +80,18 @@ def extract_data(log_entries):
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def flight_stats(telemetry, ascent_threshold = 3.0, descent_threshold=-5.0, landing_threshold = 0.5):
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def flight_stats(telemetry, ascent_threshold = 3.0, descent_threshold=-5.0, landing_threshold = 3.0):
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""" Process a set of balloon telemetry, and calculate some statistics about the flight """
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asc_rate_avg_length = 5
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_stats = {
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'ascent_rates': np.array([]),
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'positions': []
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'positions': [],
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'raw_ascent_rates': [],
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'altitudes': [],
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'speeds': [],
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'headings': []
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}
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_flight_segment = "UNKNOWN"
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@ -115,9 +120,20 @@ def flight_stats(telemetry, ascent_threshold = 3.0, descent_threshold=-5.0, lan
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'alt': _entry['alt']
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}
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_stats['positions'].append([_position['time'], _position['lat'], _position['lon'], _position['alt']])
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_state = _track.add_telemetry(_position)
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print(_state)
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if _state == None:
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continue
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_stats['altitudes'].append(_state['alt'])
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_stats['raw_ascent_rates'].append(_state['ascent_rate'])
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_stats['speeds'].append(_state['speed'])
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_stats['headings'].append(_state['heading'])
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if len(_stats['ascent_rates']) < asc_rate_avg_length:
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# Not enough data to make any judgements about the state of the flight yet.
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_stats['ascent_rates'] = np.append(_stats['ascent_rates'], _state['ascent_rate'])
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@ -157,6 +173,7 @@ def flight_stats(telemetry, ascent_threshold = 3.0, descent_threshold=-5.0, lan
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continue
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if _flight_segment == "DESCENT":
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print(abs(_mean_asc_rate))
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if abs(_mean_asc_rate) < landing_threshold:
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_stats['landing'] = [parse(_entry['log_time']), _state['lat'], _state['lon'], _state['alt']]
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logging.info("Detected Landing: %s, %.5f, %.5f, %dm" %
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@ -165,6 +182,8 @@ def flight_stats(telemetry, ascent_threshold = 3.0, descent_threshold=-5.0, lan
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_flight_segment = "LANDED"
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return _stats
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print(_flight_segment)
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return _stats
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@ -210,6 +229,7 @@ def calculate_predictor_error(predictions, landing_time, lat, lon, alt):
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parse(_predict_time),
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_pos_info['great_circle_distance']/1000.0,
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_pos_info['bearing'],
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_predict_altitude
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])
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return _output
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@ -262,6 +282,7 @@ def calculate_abort_error(predictions, landing_time, lat, lon, alt):
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parse(_predict_time),
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_pos_info['great_circle_distance']/1000.0,
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_pos_info['bearing'],
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_predict_altitude
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])
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return _output
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@ -283,12 +304,14 @@ def plot_predictor_error(flight_stats, predictor_errors, abort_predictor_errors=
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# Generate datasets of time-since-launch and altitude.
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_predict_time = []
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_predict_alt = []
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_predict_error = []
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for _entry in predictor_errors:
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_ft = (_entry[0]-_launch_time).total_seconds()/60.0
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if _ft > 0:
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_predict_time.append(_ft)
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_predict_error.append(_entry[1])
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_predict_alt.append(_entry[3])
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# Altitude vs Time
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@ -320,6 +343,69 @@ def plot_predictor_error(flight_stats, predictor_errors, abort_predictor_errors=
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plt.title("Landing Prediction Error - %s" % callsign)
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plt.grid()
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plt.figure()
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_peak_idx = np.argmax(_predict_alt)
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plt.plot(_predict_error[_peak_idx:], _predict_alt[_peak_idx:])
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plt.xlabel("Prediction error (km)")
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plt.ylabel("Flight altitude (m)")
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plt.title("Landing Prediction Error - %s" % callsign)
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plt.grid()
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def plot_wind_trace(stats, title="", gfs_file=None, landing=None):
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""" Plot the wind trace for the descent part of the flight """
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_altitude = stats['altitudes']
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_speed = stats['speeds']
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_heading = stats['headings']
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# Find peak altitude
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_peak_idx = np.argmax(_altitude)
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# Only use descent data
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_altitude = np.array(_altitude[_peak_idx:])
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_speed = np.array(_speed[_peak_idx:])
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_heading = np.array(_heading[_peak_idx:])
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if gfs_file is not None:
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# Read in supplied GFS file.
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_gfs = read_cusf_gfs(gfs_file)
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logging.info("Read in GFS data for time %s." % _gfs['timestamp'].isoformat())
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_lat_idx = np.argmin(np.abs(_gfs['latitudes']-landing[0]))
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_lon_idx = np.argmin(np.abs(_gfs['longitudes']-landing[1]))
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_gfs_alts = _gfs['data'][:,_lat_idx, _lon_idx][:,0]
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_gfs_speed = _gfs['data'][:,_lat_idx, _lon_idx][:,3]
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_gfs_heading = _gfs['data'][:,_lat_idx, _lon_idx][:,4]
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# Speed plot
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plt.figure()
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plt.plot(_speed, _altitude, label=title)
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if gfs_file is not None:
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plt.plot(_gfs_speed, _gfs_alts, label='GFS')
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plt.ylabel("Altitude (m)")
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plt.xlabel("Absolute Speed (m/s)")
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plt.title("Descent Wind Speed - " + title)
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plt.grid()
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plt.legend()
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plt.figure()
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# Plot actual data
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plt.plot((_heading+180.0)%360.0, _altitude, label=title)
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if gfs_file is not None:
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plt.plot(_gfs_heading, _gfs_alts, label='GFS')
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plt.ylabel("Altitude (m)")
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plt.xlabel("Wind Heading (Degrees True)")
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plt.title("Descent Wind Heading - " + title)
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plt.grid()
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plt.legend()
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if __name__ == "__main__":
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@ -331,6 +417,8 @@ if __name__ == "__main__":
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parser.add_argument("--abort-predict-error", action="store_true", default=False, help="Calculate Abort Prediction Error.")
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parser.add_argument("--landing-lat", type=float, default=None, help="Override Landing Latitude")
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parser.add_argument("--landing-lon", type=float, default=None, help="Override Landing Longitude")
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parser.add_argument("--wind-trace", action="store_true", default=False, help="Plot wind trace.")
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parser.add_argument("--gfs-file", type=str, default=None, help="Overlay GFS data on wind trace.")
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args = parser.parse_args()
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# Configure logging
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@ -363,6 +451,8 @@ if __name__ == "__main__":
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_abort_predict_errors = None
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plot_predictor_error(_stats, _predict_errors, _abort_predict_errors, _call)
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plot_wind_trace(_stats, title=_call)
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elif 'landing' in _stats:
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_time = _stats['landing'][0]
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_lat = _stats['landing'][1]
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@ -376,10 +466,12 @@ if __name__ == "__main__":
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plot_predictor_error(_stats, _predict_errors, _abort_predict_errors, _call)
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plot_wind_trace(_stats, title=_call, gfs_file=args.gfs_file, landing=[_lat, _lon])
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else:
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logging.error("No landing position available.")
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if args.predict_error:
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if args.predict_error or args.wind_trace:
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plt.show()
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