horusmapper.py

#!/usr/bin/env python2.7
#
#   Project Horus - Browser-Based Chase Mapper
#
#   Copyright (C) 2018  Mark Jessop <vk5qi@rfhead.net>
#   Released under GNU GPL v3 or later
#
import json
import logging
import flask
from flask_socketio import SocketIO
import os.path
import pytz
import sys
import time
import traceback
from threading import Thread
from datetime import datetime, timedelta
from dateutil.parser import parse

from chasemapper.config import *
from chasemapper.earthmaths import *
from chasemapper.geometry import *
from chasemapper.gps import SerialGPS
from chasemapper.gpsd import GPSDAdaptor
from chasemapper.atmosphere import time_to_landing
from chasemapper.listeners import OziListener, UDPListener, fix_datetime
from chasemapper.predictor import predictor_spawn_download, model_download_running
from chasemapper.habitat import HabitatChaseUploader, initListenerCallsign, uploadListenerPosition
from chasemapper.logger import ChaseLogger
from chasemapper.bearings import Bearings
from chasemapper.tawhiri import get_tawhiri_prediction


# Define Flask Application, and allow automatic reloading of templates for dev work
app = flask.Flask(__name__)
app.config['SECRET_KEY'] = 'secret!'
app.config['TEMPLATES_AUTO_RELOAD'] = True
app.jinja_env.auto_reload = True

# SocketIO instance
socketio = SocketIO(app)


# Chase Logger Instance (Initialised in main)
chase_logger = None

# Global stores of data.

# These settings are shared between server and all clients, and are updated dynamically.
chasemapper_config = {}

# Pointers to objects containing data listeners.
# These should all present a .close() function which will be called on
# listener profile change, or program exit.
data_listeners = []

# These settings are not editable by the client!
pred_settings = {}

# Offline map settings, again, not editable by the client.
map_settings = {'tile_server_enabled': False}

# Payload data Stores
current_payloads = {} #  Archive data which will be passed to the web client
current_payload_tracks = {} # Store of payload Track objects which are used to calculate instantaneous parameters.

# Chase car position
car_track = GenericTrack()

# Bearing store
bearing_store = None

# Habitat Chase-Car uploader object
habitat_uploader = None

# Copy out any extra fields from incoming telemetry that we want to pass on to the GUI.
# At the moment we're really only using the burst timer field.
EXTRA_FIELDS = ['bt', 'temp', 'humidity', 'sats', 'snr']


#
#   Flask Routes
#

@app.route("/")
def flask_index():
    """ Render main index page """
    return flask.render_template('index.html')

@app.route("/get_telemetry_archive")
def flask_get_telemetry_archive():
    return json.dumps(current_payloads)


@app.route("/get_config")
def flask_get_config():
    return json.dumps(chasemapper_config)


@app.route("/get_bearings")
def flask_get_bearings():
    return json.dumps(bearing_store.bearings)

# Some features of the web interface require comparisons with server time,
# so provide a route to grab it.
@app.route('/server_time')
def flask_get_server_time():
    return json.dumps(time.time())


@app.route("/tiles/<path:filename>")
def flask_server_tiles(filename):
    """ Serve up a file from the tile server location """
    global map_settings
    if map_settings['tile_server_enabled']:
        _filename = flask.safe_join(map_settings['tile_server_path'], filename)
        if os.path.isfile(_filename):
            return flask.send_file(_filename)
        else:
            flask.abort(404)
    else:
        flask.abort(404)


def flask_emit_event(event_name="none", data={}):
    """ Emit a socketio event to any clients. """
    socketio.emit(event_name, data, namespace='/chasemapper') 


@socketio.on('client_settings_update', namespace='/chasemapper')
def client_settings_update(data):
    global chasemapper_config, habitat_uploader

    _predictor_change = "none"
    if (chasemapper_config['pred_enabled'] == False) and (data['pred_enabled'] == True):
        _predictor_change = "restart"
    elif (chasemapper_config['pred_enabled'] == True) and (data['pred_enabled'] == False):
        _predictor_change = "stop"


    _habitat_change = "none"
    if (chasemapper_config['habitat_upload_enabled'] == False) and (data['habitat_upload_enabled'] == True):
        _habitat_change = "start"
    elif (chasemapper_config['habitat_upload_enabled'] == True) and (data['habitat_upload_enabled'] == False):
        _habitat_change = "stop"

    # Overwrite local config data with data from the client.
    chasemapper_config = data

    if _predictor_change == "restart":
        # Wait until any current predictions have finished.
        while predictor_semaphore:
            time.sleep(0.1)
        # Attempt to start the predictor.
        initPredictor()
    elif _predictor_change == "stop":
        # Wait until any current predictions have finished.
        while predictor_semaphore:
            time.sleep(0.1)
        
        predictor = None

    # Start or Stop the Habitat Chase-Car Uploader.
    if _habitat_change == "start":
        if habitat_uploader == None:
            habitat_uploader = HabitatChaseUploader(update_rate = chasemapper_config['habitat_update_rate'],
                callsign=chasemapper_config['habitat_call'])

    elif _habitat_change == "stop":
        habitat_uploader.close()
        habitat_uploader = None

    # Update the habitat uploader with a new update rate, if one has changed.
    if habitat_uploader != None:
        habitat_uploader.set_update_rate(chasemapper_config['habitat_update_rate'])
        habitat_uploader.set_callsign(chasemapper_config['habitat_call'])


    # Push settings back out to all clients.
    flask_emit_event('server_settings_update', chasemapper_config)



def handle_new_payload_position(data):

    _lat = data['lat']
    _lon = data['lon']
    _alt = data['alt']
    _time_dt = data['time_dt']
    _callsign = data['callsign']
    
    _short_time = _time_dt.strftime("%H:%M:%S")

    if _callsign not in current_payloads:
        # New callsign! Create entries in data stores.
        current_payload_tracks[_callsign] = GenericTrack()

        current_payloads[_callsign] = {
            'telem': {'callsign': _callsign, 'position':[_lat, _lon, _alt], 'max_alt':0.0, 'vel_v':0.0, 'speed':0.0, 'short_time':_short_time, 'time_to_landing':"", 'server_time':time.time()},
            'path': [],
            'pred_path': [],
            'pred_landing': [],
            'burst': [],
            'abort_path': [],
            'abort_landing': [],
            'max_alt': 0.0,
            'snr': -255.0
        }

    # Add new data into the payload's track, and get the latest ascent rate.
    current_payload_tracks[_callsign].add_telemetry({'time': _time_dt, 'lat':_lat, 'lon': _lon, 'alt':_alt, 'comment':_callsign})
    _state = current_payload_tracks[_callsign].get_latest_state()
    if _state != None:
        _vel_v = _state['ascent_rate']
        _speed = _state['speed']
        # If this payload is in descent, calculate the time to landing.
        # Use < -1.0, to avoid jitter when the payload is on the ground.
        if _vel_v < -1.0:
            # Try and get the altitude of the chase car - we use this as the expected 'ground' level.
            _car_state = car_track.get_latest_state()
            if _car_state != None:
                _ground_asl = _car_state['alt']
            else:
                _ground_asl = 0.0

            # Calculate
            _ttl = time_to_landing(_alt, _vel_v, ground_asl=_ground_asl)
            if _ttl is None:
                _ttl = ""
            elif _ttl == 0:
                _ttl = "LANDED"
            else:
                _min = _ttl // 60
                _sec = _ttl % 60
                _ttl = "%02d:%02d" % (_min,_sec)
        else:
            _ttl = ""

    else:
        _vel_v = 0.0
        _ttl = ""

    # Now update the main telemetry store.
    current_payloads[_callsign]['telem'] = {
        'callsign': _callsign, 
        'position':[_lat, _lon, _alt], 
        'vel_v':_vel_v,
        'speed':_speed,
        'short_time':_short_time,
        'time_to_landing': _ttl,
        'server_time':time.time()
        }

    current_payloads[_callsign]['path'].append([_lat, _lon, _alt])

    # Copy out any extra fields we may want to pass onto the GUI.
    for _field in EXTRA_FIELDS:
        if _field in data:
            current_payloads[_callsign]['telem'][_field] = data[_field]

    # Check if the current payload altitude is higher than our previous maximum altitude.
    if _alt > current_payloads[_callsign]['max_alt']:
        current_payloads[_callsign]['max_alt'] = _alt

    # Add the payload maximum altitude into the telemetry snapshot dictionary.
    current_payloads[_callsign]['telem']['max_alt'] = current_payloads[_callsign]['max_alt']

    # Update the web client.
    flask_emit_event('telemetry_event', current_payloads[_callsign]['telem'])

    # Add the position into the logger
    if chase_logger:
        chase_logger.add_balloon_telemetry(data)


def handle_modem_stats(data):
    """ Basic handling of modem statistics data. If it matches a known payload, send the info to the client. """

    if data['source'] in current_payloads:
        flask_emit_event('modem_stats_event', {'callsign': data['source'], 'snr': data['snr']})


#
#   Predictor Code
#
predictor = None
predictor_semaphore = False

predictor_thread_running = True
predictor_thread = None
def predictorThread():
    """ Run the predictor on a regular interval """
    global predictor_thread_running, chasemapper_config
    logging.info("Predictor loop started.")

    while predictor_thread_running:
        run_prediction()
        for i in range(int(chasemapper_config['pred_update_rate'])):
            time.sleep(1)
            if predictor_thread_running == False:
                break

    logging.info("Closed predictor loop.")


def run_prediction():
    ''' Run a Flight Path prediction '''
    global chasemapper_config, current_payloads, current_payload_tracks, predictor, predictor_semaphore

    if (chasemapper_config['pred_enabled'] == False):
        return
    
    if (chasemapper_config['offline_predictions'] == True) and (predictor == None):
        return

    # Set the semaphore so we don't accidentally kill the predictor object while it's running.
    predictor_semaphore = True
    _payload_list = list(current_payload_tracks.keys())
    for _payload in _payload_list:

        # Check the age of the data.
        # No point re-running the predictor if the data is older than 30 seconds.
        _pos_age = current_payloads[_payload]['telem']['server_time']
        if (time.time()-_pos_age) > 30.0:
            logging.debug("Skipping prediction for %s due to old data." % _payload)
            continue

        _current_pos = current_payload_tracks[_payload].get_latest_state()
        _current_pos_list = [0,_current_pos['lat'], _current_pos['lon'], _current_pos['alt']]

        _pred_ok = False
        _abort_pred_ok = False

        if _current_pos['is_descending']:
            _desc_rate = _current_pos['landing_rate']
        else:
            _desc_rate = chasemapper_config['pred_desc_rate']

        if _current_pos['alt'] > chasemapper_config['pred_burst']:
            _burst_alt = _current_pos['alt'] + 100
        else:
            _burst_alt = chasemapper_config['pred_burst']


        if predictor == "Tawhiri":
            logging.info("Requesting Prediction from Tawhiri for %s." % _payload)
            # Tawhiri requires that the burst altitude always be higher than the starting altitude.
            if _current_pos['is_descending']:
                _burst_alt = _current_pos['alt'] + 1

            # Tawhiri requires that the ascent rate be > 0 for standard profiles.
            if _current_pos['ascent_rate'] < 0.1:
                _current_pos['ascent_rate'] = 0.1

            _tawhiri = get_tawhiri_prediction(
                launch_datetime=_current_pos['time'],
                launch_latitude=_current_pos['lat'],
                launch_longitude=_current_pos['lon'],
                launch_altitude=_current_pos['alt'],
                burst_altitude=_burst_alt,
                ascent_rate=_current_pos['ascent_rate'],
                descent_rate=_desc_rate,
            )

            if _tawhiri:
                _pred_path = _tawhiri['path']
                _dataset = _tawhiri['dataset'] + " (Online)"
                # Inform the client of the dataset age
                flask_emit_event('predictor_model_update',{'model':_dataset})
            
            else:
                _pred_path = []

        else:
            logging.info("Running Offline Predictor for %s." % _payload)
            _pred_path = predictor.predict(
                launch_lat=_current_pos['lat'],
                launch_lon=_current_pos['lon'],
                launch_alt=_current_pos['alt'],
                ascent_rate=_current_pos['ascent_rate'],
                descent_rate=_desc_rate,
                burst_alt=_burst_alt,
                launch_time=_current_pos['time'],
                descent_mode=_current_pos['is_descending'])

        if len(_pred_path) > 1:
            # Valid Prediction!
            _pred_path.insert(0,_current_pos_list)
            # Convert from predictor output format to a polyline.
            _pred_output = []
            for _point in _pred_path:
                _pred_output.append([_point[1], _point[2], _point[3]])

            current_payloads[_payload]['pred_path'] = _pred_output
            current_payloads[_payload]['pred_landing'] = _pred_output[-1]

            if _current_pos['is_descending']:
                current_payloads[_payload]['burst'] = []
            else:
                # Determine the burst position.
                _cur_alt = 0.0
                _cur_idx = 0
                for i in range(len(_pred_output)):
                    if _pred_output[i][2]>_cur_alt:
                        _cur_alt = _pred_output[i][2]
                        _cur_idx = i

                current_payloads[_payload]['burst'] = _pred_output[_cur_idx]

            _pred_ok = True
            logging.info("Prediction Updated, %d data points." % len(_pred_path))
        else:
            current_payloads[_payload]['pred_path'] = []
            current_payloads[_payload]['pred_landing'] = []
            current_payloads[_payload]['burst'] = []
            logging.error("Prediction Failed.")

        # Abort predictions
        if chasemapper_config['show_abort'] and (_current_pos['alt'] < chasemapper_config['pred_burst']) and (_current_pos['is_descending'] == False):

            if predictor == "Tawhiri":
                logging.info("Requesting Abort Prediction from Tawhiri for %s." % _payload)

                # Tawhiri requires that the ascent rate be > 0 for standard profiles.
                if _current_pos['ascent_rate'] < 0.1:
                    _current_pos['ascent_rate'] = 0.1

                _tawhiri = get_tawhiri_prediction(
                    launch_datetime=_current_pos['time'],
                    launch_latitude=_current_pos['lat'],
                    launch_longitude=_current_pos['lon'],
                    launch_altitude=_current_pos['alt'],
                    burst_altitude=_current_pos['alt'] + 200,
                    ascent_rate=_current_pos['ascent_rate'],
                    descent_rate=_desc_rate,
                )

                if _tawhiri:
                    _abort_pred_path = _tawhiri['path']

                else:
                    _abort_pred_path = []

            else:
                logging.info("Running Offline Abort Predictor for: %s." % _payload)

                _abort_pred_path = predictor.predict(
                        launch_lat=_current_pos['lat'],
                        launch_lon=_current_pos['lon'],
                        launch_alt=_current_pos['alt'],
                        ascent_rate=_current_pos['ascent_rate'],
                        descent_rate=_desc_rate,
                        burst_alt=_current_pos['alt']+200,
                        launch_time=_current_pos['time'],
                        descent_mode=_current_pos['is_descending'])

            if len(_pred_path) > 1:
                # Valid Prediction!
                _abort_pred_path.insert(0,_current_pos_list)
                # Convert from predictor output format to a polyline.
                _abort_pred_output = []
                for _point in _abort_pred_path:
                    _abort_pred_output.append([_point[1], _point[2], _point[3]])

                current_payloads[_payload]['abort_path'] = _abort_pred_output
                current_payloads[_payload]['abort_landing'] = _abort_pred_output[-1]

                _abort_pred_ok = True
                logging.info("Abort Prediction Updated, %d data points." % len(_pred_path))
            else:
                logging.error("Prediction Failed.")
                current_payloads[_payload]['abort_path'] = []
                current_payloads[_payload]['abort_landing'] = []
        else:
            # Zero the abort path and landing
            current_payloads[_payload]['abort_path'] = []
            current_payloads[_payload]['abort_landing'] = []

        # Send the web client the updated prediction data.
        if _pred_ok or _abort_pred_ok:
            _client_data = {
                'callsign': _payload,
                'pred_path': current_payloads[_payload]['pred_path'],
                'pred_landing': current_payloads[_payload]['pred_landing'],
                'burst': current_payloads[_payload]['burst'],
                'abort_path': current_payloads[_payload]['abort_path'],
                'abort_landing': current_payloads[_payload]['abort_landing']
            }
            flask_emit_event('predictor_update', _client_data)

            # Add the prediction run to the logger.
            if chase_logger:
                chase_logger.add_balloon_prediction(_client_data)

    # Clear the predictor-running semaphore
    predictor_semaphore = False


def initPredictor():
    global predictor, predictor_thread, chasemapper_config, pred_settings

    if chasemapper_config['offline_predictions']:
        # Attempt to initialize an Offline Predictor instance
        try:
            from cusfpredict.predict import Predictor
            from cusfpredict.utils import gfs_model_age, available_gfs
            
            # Check if we have any GFS data
            _model_age = gfs_model_age(pred_settings['gfs_path'])
            if _model_age == "Unknown":
                logging.error("No GFS data in directory.")
                chasemapper_config['pred_model'] = "No GFS Data."
                flask_emit_event('predictor_model_update',{'model':"No GFS data."})
                chasemapper_config['offline_predictions'] = False
            else:
                # Check model contains data to at least 4 hours into the future.
                (_model_start, _model_end) = available_gfs(pred_settings['gfs_path'])
                _model_now = datetime.utcnow() + timedelta(0,60*60*4)
                if (_model_now < _model_start) or (_model_now > _model_end):
                    # No suitable GFS data!
                    logging.error("GFS Data in directory does not cover now!")
                    chasemapper_config['pred_model'] = "Old GFS Data."
                    flask_emit_event('predictor_model_update',{'model':"Old GFS data."})
                    chasemapper_config['offline_predictions'] = False

                else:
                    chasemapper_config['pred_model'] = _model_age + " (Offline)"
                    flask_emit_event('predictor_model_update',{'model':_model_age + " (Offline)"})
                    predictor = Predictor(bin_path=pred_settings['pred_binary'], gfs_path=pred_settings['gfs_path'])

                    # Start up the predictor thread if it is not running.
                    if predictor_thread == None:
                        predictor_thread = Thread(target=predictorThread)
                        predictor_thread.start()

                    # Set the predictor to enabled, and update the clients.
                    chasemapper_config['offline_predictions'] = True

        except Exception as e:
            traceback.print_exc()
            logging.error("Loading predictor failed: " + str(e))
            flask_emit_event('predictor_model_update',{'model':"Failed - Check Log."})
            chasemapper_config['pred_model'] = "Failed - Check Log."
            print("Loading Predictor failed.")
            predictor = None
        
    else:
        # No initialization required for the online predictor
        predictor = "Tawhiri"
        flask_emit_event('predictor_model_update',{'model':"Tawhiri"})

        # Start up the predictor thread if it is not running.
        if predictor_thread == None:
            predictor_thread = Thread(target=predictorThread)
            predictor_thread.start()


    flask_emit_event('server_settings_update', chasemapper_config)



def model_download_finished(result):
    """ Callback for when the model download is finished """
    global chasemapper_config
    if result == "OK":
        # Downloader reported OK, restart the predictor.
        chasemapper_config["offline_predictions"] = True
        initPredictor()
    else:
        # Downloader reported an error, pass on to the client.
        flask_emit_event('predictor_model_update',{'model':result})


@socketio.on('download_model', namespace='/chasemapper')
def download_new_model(data):
    """ Trigger a download of a new weather model """
    global pred_settings, model_download_running
    # Don't action anything if there is a model download already running

    logging.info("Web Client Initiated request for new predictor data.")

    if pred_settings['pred_model_download'] == "none":
        logging.info("No GFS model download command specified.")
        flask_emit_event('predictor_model_update',{'model':"No model download cmd."})
        return
    else:
        _model_cmd = pred_settings['pred_model_download']
        flask_emit_event('predictor_model_update',{'model':"Downloading Model."})

        _status = predictor_spawn_download(_model_cmd, model_download_finished)
        flask_emit_event('predictor_model_update',{'model':_status})



# Data Clearing Functions
@socketio.on('payload_data_clear', namespace='/chasemapper')
def clear_payload_data(data):
    """ Clear the payload data store """
    global predictor_semaphore, current_payloads, current_payload_tracks
    logging.warning("Client requested all payload data be cleared.")
    # Wait until any current predictions have finished running.
    while predictor_semaphore:
        time.sleep(0.1)

    current_payloads = {}
    current_payload_tracks = {}


@socketio.on('car_data_clear', namespace='/chasemapper')
def clear_car_data(data):
    """ Clear out the car position track """
    global car_track
    logging.warning("Client requested all chase car data be cleared.")
    car_track = GenericTrack()


@socketio.on('bearing_store_clear', namespace='/chasemapper')
def clear_bearing_data(data):
    """ Clear all bearing data """
    global bearing_store
    logging.warning("Client requested bearing data be cleared.")
    bearing_store.flush()



@socketio.on('mark_recovered', namespace='/chasemapper')
def mark_payload_recovered(data):
    """ Mark a payload as recovered, by uploading a station position """

    _callsign = data['recovery_title']
    _lat = data['last_pos'][0]
    _lon = data['last_pos'][1]
    _alt = data['last_pos'][2]
    _msg = data['message']
    _timestamp = "Recovered at " + datetime.utcnow().strftime("%Y-%m-%d %H:%MZ")

    try:
        initListenerCallsign(_callsign, radio=_msg, antenna=_timestamp)
        uploadListenerPosition(_callsign, _lat, _lon, _alt, chase=False)
    except Exception as e:
        logging.error("Unable to mark %s as recovered - %s" % (data['payload_call'], str(e)))
        return

    logging.info("Payload %s marked as recovered." % data['payload_call'])


# Incoming telemetry handlers

def ozi_listener_callback(data):
    """ Handle a OziMux input message """
    # OziMux message contains:
    # {'lat': -34.87915, 'comment': 'Telemetry Data', 'alt': 26493.0, 'lon': 139.11883, 'time': datetime.datetime(2018, 7, 16, 10, 55, 49, tzinfo=tzutc())}
    output = {}
    output['lat'] = float(data['lat'])
    output['lon'] = float(data['lon'])
    output['alt'] = float(data['alt'])
    output['callsign'] = "Payload"
    output['time_dt'] = data['time']

    logging.info("OziMux Data: %.5f, %.5f, %.1f" % (data['lat'], data['lon'], data['alt']))

    try:
        handle_new_payload_position(output)
    except Exception as e:
        logging.error("Error Handling Payload Position - %s" % str(e))



def udp_listener_summary_callback(data):
    ''' Handle a Payload Summary Message from UDPListener '''

    # Modem stats messages are also passed in via this callback.
    # handle them separately.
    if data['type'] == 'MODEM_STATS':
        handle_modem_stats(data)
        return

    # Otherwise, we have a PAYLOAD_SUMMARY message.

    # Extract the fields we need.
    # Convert to something generic we can pass onwards.
    output = {}
    output['lat'] = float(data['latitude'])
    output['lon'] = float(data['longitude'])
    output['alt'] = float(data['altitude'])
    output['callsign'] = data['callsign']

    if 'time' in data.keys():
        _time = data['time']
    else:
        _time = "??:??:??"

    logging.info("Horus UDP Data: %s, %s, %.5f, %.5f, %.1f" % (output['callsign'], _time, output['lat'], output['lon'], output['alt']))

    # Process the 'short time' value if we have been provided it.
    if 'time' in data.keys():
        output['time_dt'] = fix_datetime(data['time'])
        #_full_time = datetime.utcnow().strftime("%Y-%m-%dT") + data['time'] + "Z"
        #output['time_dt'] = parse(_full_time)
    else:
        # Otherwise use the current UTC time.
        
        output['time_dt'] = pytz.utc.localize(datetime.utcnow())

    # Copy out any extra fields that we want to pass on to the GUI.
    for _field in EXTRA_FIELDS:
        if _field in data:
            output[_field] = data[_field]

    try:
        handle_new_payload_position(output)
    except Exception as e:
        logging.error("Error Handling Payload Position - %s" % str(e))


def udp_listener_car_callback(data):
    ''' Handle car position data '''
    # TODO: Make a generic car position function, and have this function pass data into it
    # so we can add support for other chase car position inputs.
    global car_track, habitat_uploader, bearing_store
    _lat = float(data['latitude'])
    _lon = float(data['longitude'])
    
    # Handle when GPSD and/or other GPS data sources return a n/a for altitude.
    try:
        _alt = float(data['altitude'])
    except ValueError:
        _alt = 0.0

    _comment = "CAR"
    _time_dt = pytz.utc.localize(datetime.utcnow())

    logging.debug("Car Position: %.5f, %.5f" % (_lat, _lon))

    _car_position_update = {
        'time'  :   _time_dt,
        'lat'   :   _lat,
        'lon'   :   _lon,
        'alt'   :   _alt,
        'comment':  _comment
    }
    # Add in true heading data if we have been supplied it
    # (Which will be the case once I end up building a better car GPS...)
    if 'heading' in data:
        _car_position_update['heading'] = data['heading']

    car_track.add_telemetry(_car_position_update)

    _state = car_track.get_latest_state()
    _heading = _state['heading']
    _speed = _state['speed']

    # Push the new car position to the web client
    flask_emit_event('telemetry_event', {'callsign': 'CAR', 'position':[_lat,_lon,_alt], 'vel_v':0.0, 'heading': _heading, 'speed':_speed})

    # Update the Habitat Uploader, if one exists.
    if habitat_uploader != None:
        habitat_uploader.update_position(data)

    # Update the bearing store with the current car state (position & bearing)
    if bearing_store != None:
        bearing_store.update_car_position(_state)

    # Add the car position to the logger, but only if we are moving (>10kph = ~3m/s)
    if (_speed > 3.0) and chase_logger:
        _car_position_update['speed'] = _speed
        _car_position_update['heading'] = _heading
        chase_logger.add_car_position(_car_position_update)


def udp_listener_bearing_callback(data):
    global bearing_store, chase_logger

    if bearing_store != None:
        bearing_store.add_bearing(data)
        if chase_logger:
            chase_logger.add_bearing(data)


# Data Age Monitoring Thread
data_monitor_thread_running = True
def check_data_age():
    """ Regularly check the age of the payload data, and clear if latest position is older than X minutes."""
    global current_payloads, chasemapper_config, predictor_semaphore

    while data_monitor_thread_running:
        _now = time.time()
        _callsigns = list(current_payloads.keys())

        for _call in _callsigns:
            try:
                _latest_time = current_payloads[_call]['telem']['server_time']
                if (_now - _latest_time) > (chasemapper_config['payload_max_age']*60.0):
                    # Data is older than our maximum age!
                    # Make sure we do not have a predictor cycle running.
                    while predictor_semaphore:
                        time.sleep(0.1)

                    # Remove this payload from our global data stores.
                    current_payloads.pop(_call)
                    current_payload_tracks.pop(_call)

                    logging.info("Payload %s telemetry older than maximum age - removed from data store." % _call)
            except Exception as e:
                logging.error("Error checking payload data age - %s" % str(e))

        time.sleep(2)


def start_listeners(profile):
    """ Stop any currently running listeners, and startup a set of data listeners based on the supplied profile 
    
    Args:
        profile (dict): A dictionary containing:
            'name' (str): Profile name
            'telemetry_source_type' (str): Data source type (ozimux or horus_udp)
            'telemetry_source_port' (int): Data source port
            'car_source_type' (str): Car Position source type (none, horus_udp or gpsd)
            'car_source_port' (int): Car Position source port
    """
    global data_listeners
    # Stop any existing listeners.
    for _thread in data_listeners:
        try:
            _thread.close()
        except Exception as e:
            logging.error("Error closing thread - %s" % str(e))

    # Reset the listeners array.
    data_listeners = []

    # Start up a OziMux listener, if we are using one.
    if profile['telemetry_source_type'] == "ozimux":
        logging.info("Using OziMux data source on UDP Port %d" % profile['telemetry_source_port'])
        _ozi_listener = OziListener(telemetry_callback=ozi_listener_callback, port=profile['telemetry_source_port'])
        data_listeners.append(_ozi_listener)


    # Start up UDP Broadcast Listener (which we use for car positions even if not for the payload)

    # Case 1 - Both telemetry and car position sources are set to horus_udp, and have the same port set. Only start a single UDP listener
    if (profile['telemetry_source_type'] == "horus_udp") and (profile['car_source_type'] == "horus_udp") and (profile['car_source_port'] == profile['telemetry_source_port']):
        # In this case, we start a single Horus UDP listener.
        logging.info("Starting single Horus UDP listener on port %d" % profile['telemetry_source_port'])
        _telem_horus_udp_listener = UDPListener(summary_callback=udp_listener_summary_callback,
                                            gps_callback=udp_listener_car_callback,
                                            bearing_callback=udp_listener_bearing_callback,
                                            port=profile['telemetry_source_port'])
        _telem_horus_udp_listener.start()
        data_listeners.append(_telem_horus_udp_listener)

    else:
        if profile['telemetry_source_type'] == "horus_udp":
            # Telemetry via Horus UDP - Start up a listener
            logging.info("Starting Telemetry Horus UDP listener on port %d" % profile['telemetry_source_port'])
            _telem_horus_udp_listener = UDPListener(summary_callback=udp_listener_summary_callback,
                                            gps_callback=None,
                                            bearing_callback=udp_listener_bearing_callback,
                                            port=profile['telemetry_source_port'])
            _telem_horus_udp_listener.start()
            data_listeners.append(_telem_horus_udp_listener)

        if profile['car_source_type'] == "horus_udp":
            # Car Position via Horus UDP - Start up a listener
            logging.info("Starting Car Position Horus UDP listener on port %d" % profile['car_source_port'])
            _car_horus_udp_listener = UDPListener(summary_callback=None,
                                            gps_callback=udp_listener_car_callback,
                                            bearing_callback=udp_listener_bearing_callback,
                                            port=profile['car_source_port'])
            _car_horus_udp_listener.start()
            data_listeners.append(_car_horus_udp_listener)

        elif profile['car_source_type'] == "gpsd":
            # GPSD Car Position Source 
            logging.info("Starting GPSD Car Position Listener.")
            _gpsd_gps = GPSDAdaptor(hostname=chasemapper_config['car_gpsd_host'],
                port=chasemapper_config['car_gpsd_port'],
                callback=udp_listener_car_callback)
            data_listeners.append(_gpsd_gps)

        elif profile['car_source_type'] == "serial":
            # Serial GPS Source.
            logging.info("Starting Serial GPS Listener.")
            _serial_gps = SerialGPS(serial_port=chasemapper_config['car_serial_port'],
                serial_baud=chasemapper_config['car_serial_baud'],
                callback=udp_listener_car_callback)
            data_listeners.append(_serial_gps)

        else:
            # No Car position.
            logging.info("No car position data source.")


@socketio.on('profile_change', namespace='/chasemapper')
def profile_change(data):
    """ Client has requested a profile change """
    global chasemapper_config
    logging.info("Client requested change to profile: %s" % data)

    # Change the profile, and restart the listeners.
    chasemapper_config['selected_profile'] = data
    start_listeners(chasemapper_config['profiles'][chasemapper_config['selected_profile']])

    # Update all clients with the new profile selection
    flask_emit_event('server_settings_update', chasemapper_config)


class WebHandler(logging.Handler):
    """ Logging Handler for sending log messages via Socket.IO to a Web Client """

    def emit(self, record):
        """ Emit a log message via SocketIO """
        # Deal with log records with no content.
        if record.msg:
            if 'socket.io' not in record.msg:
                # Convert log record into a dictionary
                log_data = {
                    'level': record.levelname,
                    'timestamp': datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%SZ'),
                    'msg': record.msg
                }
                # Emit to all socket.io clients
                socketio.emit('log_event', log_data, namespace='/chasemapper')



if __name__ == "__main__":
    import argparse
    parser = argparse.ArgumentParser()
    parser.add_argument("-c", "--config", type=str, default="horusmapper.cfg", help="Configuration file.")
    parser.add_argument("-v", "--verbose", action="store_true", default=False, help="Verbose output.")
    parser.add_argument("-l", "--log", type=str, default=None, help="Custom log file name. (Default: ./log_files/<timestamp>.log")
    parser.add_argument("--nolog", action="store_true", default=False, help="Inhibit all logging.")
    args = parser.parse_args()

    # Configure logging
    if args.verbose:
        _log_level = logging.DEBUG
    else:
        _log_level = logging.INFO

    logging.basicConfig(format='%(asctime)s %(levelname)s:%(message)s', stream=sys.stdout, level=_log_level)
    # Make flask & socketio only output errors, not every damn GET request.
    logging.getLogger("requests").setLevel(logging.CRITICAL)
    logging.getLogger("urllib3").setLevel(logging.CRITICAL)
    logging.getLogger('werkzeug').setLevel(logging.ERROR)
    logging.getLogger('socketio').setLevel(logging.ERROR)
    logging.getLogger('engineio').setLevel(logging.ERROR)

    web_handler = WebHandler()
    logging.getLogger().addHandler(web_handler)

    # Start the Chase Logger (if logging not inhibited.)
    if not args.nolog:
        chase_logger = ChaseLogger(filename=args.log)
    else:
        logging.info("Chase Logging has been inhibited, not starting logger.")

    # Attempt to read in config file.
    chasemapper_config = read_config(args.config)
    # Die if we cannot read a valid config file.
    if chasemapper_config == None:
        logging.critical("Could not read configuration data. Exiting")
        sys.exit(1)

    # Copy out the predictor settings to another dictionary.
    pred_settings = {
        'pred_binary': chasemapper_config['pred_binary'],
        'gfs_path': chasemapper_config['pred_gfs_directory'],
        'pred_model_download': chasemapper_config['pred_model_download']
    }

    # Copy out Offline Map Settings
    map_settings = {
        'tile_server_enabled': chasemapper_config['tile_server_enabled'],
        'tile_server_path': chasemapper_config['tile_server_path']
    }

    # Initialise Bearing store
    bearing_store = Bearings(
        socketio_instance = socketio, 
        max_bearings = chasemapper_config['max_bearings'],
        max_bearing_age = chasemapper_config['max_bearing_age'])

    # Set speed gate for car position object
    car_track.heading_gate_threshold = chasemapper_config['car_speed_gate']

    # Start listeners using the default profile selection.
    start_listeners(chasemapper_config['profiles'][chasemapper_config['selected_profile']])

    # Start up the predictor, if enabled.
    if chasemapper_config['pred_enabled']:
        initPredictor()

    # Start up the Habitat Chase-Car Uploader, if enabled
    if chasemapper_config['habitat_upload_enabled']:
        habitat_uploader = HabitatChaseUploader(update_rate = chasemapper_config['habitat_update_rate'],
                callsign=chasemapper_config['habitat_call'])

    # Start up the data age monitor thread.
    _data_age_monitor = Thread(target=check_data_age)
    _data_age_monitor.start()

    # Run the Flask app, which will block until CTRL-C'd.
    logging.info("Starting Chasemapper Server on: http://%s:%d/" % (chasemapper_config['flask_host'], chasemapper_config['flask_port']))
    socketio.run(app, host=chasemapper_config['flask_host'], port=chasemapper_config['flask_port'])

    # Close the predictor and data age monitor threads.
    predictor_thread_running = False
    data_monitor_thread_running = False

    # Close the chase logger
    if chase_logger:
        chase_logger.close()

    if habitat_uploader != None:
        habitat_uploader.close()

    # Attempt to close the running listeners.
    for _thread in data_listeners:
        try:
            _thread.close()
        except Exception as e:
            logging.error("Error closing thread - %s" % str(e))