Esempio n. 1
0
    def process_running(self, sport, data, exercise_index=0):
        if sport not in list(self.sports_lists.keys()):
            self.sports_lists[sport] = []

        filtered = {}

        filtered['start_time'] = utils.polar_datetime_to_python_datetime_str(
            data['exercises'][exercise_index]['startTime'])

        has_route = 'recordedRoute' in data['exercises'][0]['samples']
        if has_route:
            first_route_point = data['exercises'][0]['samples'][
                'recordedRoute'][0]
            utils.get_weather_data_file(first_route_point,
                                        filtered['start_time'])
            filtered['landmark'], filtered['state'], filtered[
                'country'] = utils.get_initial_location(
                    first_route_point, filtered['start_time'])
        else:
            filtered['landmark'], filtered['state'], filtered['country'] = (
                const.empty_value, const.empty_value, const.empty_value)

        # Checking for no distance recorded
        if 'distance' not in data['exercises'][exercise_index]:
            filtered[
                'distance'] = 1  # if there is no distance recorded, I'll assume it is 1km
        else:
            filtered['distance'] = utils.get_km(
                data['exercises'][exercise_index]['distance'])

        filtered['duration'] = utils.polar_time_to_python_time(
            data['exercises'][exercise_index]['duration'])

        filtered['avg_speed'] = utils.round_speed(
            data['exercises'][exercise_index]['speed']['avg'])
        filtered['max_speed'] = utils.round_speed(
            data['exercises'][exercise_index]['speed']['max'])

        # Checking for zero speed
        if filtered['avg_speed'] == 0:
            filtered['avg_speed'] = utils.calculate_speed(
                filtered['distance'], filtered['duration'])
            filtered['max_speed'] = filtered['avg_speed']

        filtered['avg_pace'] = utils.get_pace(filtered['avg_speed'])
        filtered['max_pace'] = utils.get_pace(filtered['max_speed'])

        # Checking for no heart rate recorded
        if 'heartRate' not in data['exercises'][exercise_index]:
            filtered['avg_heart_rate'] = const.empty_value
            filtered['max_heart_rate'] = filtered['avg_heart_rate']
        else:
            filtered['avg_heart_rate'] = data['exercises'][exercise_index][
                'heartRate']['avg']
            filtered['max_heart_rate'] = data['exercises'][exercise_index][
                'heartRate']['max']

        filtered['age'] = utils.get_age(filtered['start_time'])

        filtered['body_max_heart_rate'] = 220 - filtered['age']

        try:
            filtered['avg_heart_rate_as_percentage'] = round(
                filtered['avg_heart_rate'] / filtered['body_max_heart_rate'] *
                10000) / 100.0
            filtered['max_heart_rate_as_percentage'] = round(
                filtered['max_heart_rate'] / filtered['body_max_heart_rate'] *
                10000) / 100.0
        except:
            filtered['avg_heart_rate_as_percentage'] = const.empty_value
            filtered['max_heart_rate_as_percentage'] = filtered[
                'avg_heart_rate_as_percentage']

        if has_route:
            _, _, _, filtered['has_negative_split'] = utils.get_data_at_dist(
                filtered['distance'],
                data['exercises'][exercise_index]['samples']['distance'])
            if filtered['has_negative_split'] == const.empty_value:
                _, _, _, filtered[
                    'has_negative_split'] = utils.get_data_at_dist(
                        filtered['distance'] - 0.01, data['exercises']
                        [exercise_index]['samples']['distance'])

            filtered['5km_time'], filtered['5km_avg_speed'], filtered[
                '5km_avg_pace'], filtered[
                    '5km_has_negative_split'] = utils.get_data_at_dist(
                        5, data['exercises'][0]['samples']['distance'])
            filtered['10km_time'], filtered['10km_avg_speed'], filtered[
                '10km_avg_pace'], filtered[
                    '10km_has_negative_split'] = utils.get_data_at_dist(
                        10, data['exercises'][0]['samples']['distance'])
            filtered['15km_time'], filtered['15km_avg_speed'], filtered[
                '15km_avg_pace'], filtered[
                    '15km_has_negative_split'] = utils.get_data_at_dist(
                        15, data['exercises'][0]['samples']['distance'])
            filtered['21km_time'], filtered['21km_avg_speed'], filtered[
                '21km_avg_pace'], filtered[
                    '21km_has_negative_split'] = utils.get_data_at_dist(
                        21, data['exercises'][0]['samples']['distance'])
            filtered['42km_time'], filtered['42km_avg_speed'], filtered[
                '42km_avg_pace'], filtered[
                    '42km_has_negative_split'] = utils.get_data_at_dist(
                        42, data['exercises'][0]['samples']['distance'])
        else:
            filtered['has_negative_split'] = const.empty_value
            filtered['5km_time'], filtered['5km_avg_speed'], filtered[
                '5km_avg_pace'], filtered['5km_has_negative_split'] = (
                    const.empty_value, const.empty_value, const.empty_value,
                    const.empty_value)
            filtered['10km_time'], filtered['10km_avg_speed'], filtered[
                '10km_avg_pace'], filtered['10km_has_negative_split'] = (
                    const.empty_value, const.empty_value, const.empty_value,
                    const.empty_value)
            filtered['15km_time'], filtered['15km_avg_speed'], filtered[
                '15km_avg_pace'], filtered['15km_has_negative_split'] = (
                    const.empty_value, const.empty_value, const.empty_value,
                    const.empty_value)
            filtered['21km_time'], filtered['21km_avg_speed'], filtered[
                '21km_avg_pace'], filtered['21km_has_negative_split'] = (
                    const.empty_value, const.empty_value, const.empty_value,
                    const.empty_value)
            filtered['42km_time'], filtered['42km_avg_speed'], filtered[
                '42km_avg_pace'], filtered['42km_has_negative_split'] = (
                    const.empty_value, const.empty_value, const.empty_value,
                    const.empty_value)

        filtered['day_link'] = utils.get_day_link(filtered['start_time'])
        # utils.pretty_print_json(filtered)
        # input()

        self.sports_lists[sport].append(filtered)
Esempio n. 2
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    def process_running(self, sport, data, exercise_index=0):
        if sport not in list(self.sports_lists.keys()):
            self.sports_lists[sport] = []

        filtered = {}

        tcx_file = f'{const.accesslink_tcx_file_prefix}{self.current_file_id}.json'

        filtered['start_time'] = self.current_file_id
        
        ### TODO:
        # Pegar a localização da primeira posição do percurso e descobrir o fuso-horário de lá
        # Os horários nos arquivos tcx estão em utc time zone

        with open(tcx_file, 'r') as f:
            tcx_data = json.load(f)

        has_route = False
        # if has_route:
        try:
            # Try to find the starting point in the first 10 positions
            got_starting_point = False
            for i in range(10):
                try:
                    first_route_point = {
                                            'latitude': float(tcx_data['TrainingCenterDatabase']['Activities']['Activity']['Lap'][0]['Track']['Trackpoint'][i]['Position']['LatitudeDegrees']),
                                            'longitude': float(tcx_data['TrainingCenterDatabase']['Activities']['Activity']['Lap'][0]['Track']['Trackpoint'][i]['Position']['LongitudeDegrees'])
                                        }
                    got_starting_point = True
                    break
                except:
                    pass

            if got_starting_point == False:
                raise Exception('Could not find starting point. Trying a different data format.')

            utils.get_weather_data_file(first_route_point, self.current_file_id)
            has_route = True
            filtered['landmark'], filtered['state'], filtered['country'] = utils.get_initial_location(first_route_point, filtered['start_time'])
        except:
            try:
                first_route_point = {
                                        'latitude': float(tcx_data['TrainingCenterDatabase']['Activities']['Activity']['Lap'][0]['Track'][0]['Trackpoint'][0]['Position']['LatitudeDegrees']),
                                        'longitude': float(tcx_data['TrainingCenterDatabase']['Activities']['Activity']['Lap'][0]['Track'][0]['Trackpoint'][0]['Position']['LongitudeDegrees'])
                                    }

                utils.get_weather_data_file(first_route_point, self.current_file_id)
                has_route = True
                filtered['landmark'], filtered['state'], filtered['country'] = utils.get_initial_location(first_route_point, filtered['start_time'])
            except:
                filtered['landmark'], filtered['state'], filtered['country'] = (const.empty_value, const.empty_value, const.empty_value)

        # Checking for no distance recorded
        if 'distance' not in data:
            filtered['distance'] = 1 # if there is no distance recorded, I'll assume it is 1km
        else:
            filtered['distance'] = utils.get_km(data['distance'])

        tcx_laps = tcx_data['TrainingCenterDatabase']['Activities']['Activity']['Lap']

        filtered['duration'] = utils.accesslink_time_to_python_time(data['duration'])

        filtered['avg_speed'] = utils.calculate_speed(filtered['distance'], filtered['duration'])

        try:
            filtered['max_speed'] = utils.find_tcx_max_speed(tcx_laps)
        except:
            filtered['max_speed'] = filtered['avg_speed']
        
        filtered['avg_pace'] = utils.get_pace(filtered['avg_speed'])
        filtered['max_pace'] = utils.get_pace(filtered['max_speed'])

        # Checking for no heart rate recorded
        try:
            filtered['avg_heart_rate'] = data['heart-rate']['average']
            filtered['max_heart_rate'] = data['heart-rate']['maximum']
        except:
            filtered['avg_heart_rate'] = const.empty_value
            filtered['max_heart_rate'] = filtered['avg_heart_rate']
            
        filtered['age'] = utils.get_age(filtered['start_time'])

        filtered['body_max_heart_rate'] = 220 - filtered['age']

        try:
            filtered['avg_heart_rate_as_percentage'] = round(filtered['avg_heart_rate']/filtered['body_max_heart_rate']*10000)/100.0
            filtered['max_heart_rate_as_percentage'] = round(filtered['max_heart_rate']/filtered['body_max_heart_rate']*10000)/100.0
        except:
            filtered['avg_heart_rate_as_percentage'] = const.empty_value
            filtered['max_heart_rate_as_percentage'] = filtered['avg_heart_rate_as_percentage']
        
        if has_route:
            samples = utils.convert_tcx_laps_to_downloaded_format(tcx_laps)

            _, _, _, filtered['has_negative_split'] = utils.get_data_at_dist(filtered['distance'], samples)
            if filtered['has_negative_split'] == const.empty_value:
                _, _, _, filtered['has_negative_split'] = utils.get_data_at_dist(filtered['distance'] - 0.01, samples)

            filtered['5km_time'], filtered['5km_avg_speed'], filtered['5km_avg_pace'], filtered['5km_has_negative_split'] = utils.get_data_at_dist(5, samples)
            filtered['10km_time'], filtered['10km_avg_speed'], filtered['10km_avg_pace'], filtered['10km_has_negative_split'] = utils.get_data_at_dist(10, samples)
            filtered['15km_time'], filtered['15km_avg_speed'], filtered['15km_avg_pace'], filtered['15km_has_negative_split'] = utils.get_data_at_dist(15, samples)
            filtered['21km_time'], filtered['21km_avg_speed'], filtered['21km_avg_pace'], filtered['21km_has_negative_split'] = utils.get_data_at_dist(21, samples)
            filtered['42km_time'], filtered['42km_avg_speed'], filtered['42km_avg_pace'], filtered['42km_has_negative_split'] = utils.get_data_at_dist(42, samples)
        else:
            filtered['has_negative_split'] = const.empty_value
            filtered['5km_time'], filtered['5km_avg_speed'], filtered['5km_avg_pace'], filtered['5km_has_negative_split'] = (const.empty_value, const.empty_value, const.empty_value, const.empty_value)
            filtered['10km_time'], filtered['10km_avg_speed'], filtered['10km_avg_pace'], filtered['10km_has_negative_split'] = (const.empty_value, const.empty_value, const.empty_value, const.empty_value)
            filtered['15km_time'], filtered['15km_avg_speed'], filtered['15km_avg_pace'], filtered['15km_has_negative_split'] = (const.empty_value, const.empty_value, const.empty_value, const.empty_value)
            filtered['21km_time'], filtered['21km_avg_speed'], filtered['21km_avg_pace'], filtered['21km_has_negative_split'] = (const.empty_value, const.empty_value, const.empty_value, const.empty_value)
            filtered['42km_time'], filtered['42km_avg_speed'], filtered['42km_avg_pace'], filtered['42km_has_negative_split'] = (const.empty_value, const.empty_value, const.empty_value, const.empty_value)

        filtered['day_link'] = utils.get_day_link(filtered['start_time'])
        # utils.pretty_print_json(filtered)
        # input()

        self.sports_lists[sport].append(filtered)
Esempio n. 3
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    def process_distance_based_sport(self, sport, data, exercise_index=0):
        if sport not in list(self.sports_lists.keys()):
            self.sports_lists[sport] = []

        filtered = {}

        filtered['start_time'] = utils.polar_datetime_to_python_datetime_str(
            data['exercises'][exercise_index]['startTime'])

        has_route = 'recordedRoute' in data['exercises'][0]['samples']
        if has_route:
            first_route_point = data['exercises'][0]['samples'][
                'recordedRoute'][0]
            utils.get_weather_data_file(first_route_point,
                                        filtered['start_time'])
            filtered['landmark'], filtered['state'], filtered[
                'country'] = utils.get_initial_location(
                    first_route_point, filtered['start_time'])
        else:
            filtered['landmark'], filtered['state'], filtered['country'] = (
                const.empty_value, const.empty_value, const.empty_value)

        # Checking for no distance recorded
        if 'distance' not in data['exercises'][exercise_index]:
            filtered['distance'] = const.empty_value
        else:
            filtered['distance'] = utils.get_km(
                data['exercises'][exercise_index]['distance'])

        filtered['duration'] = utils.polar_time_to_python_time(
            data['exercises'][exercise_index]['duration'])

        try:
            filtered['avg_speed'] = utils.round_speed(
                data['exercises'][exercise_index]['speed']['avg'])
            filtered['max_speed'] = utils.round_speed(
                data['exercises'][exercise_index]['speed']['max'])
        except:
            try:
                filtered['avg_speed'] = utils.calculate_speed(
                    filtered['distance'], filtered['duration'])
            except:
                filtered['avg_speed'] = const.empty_value
            filtered['max_speed'] = filtered['avg_speed']

        try:
            filtered['avg_pace'] = utils.get_pace(filtered['avg_speed'])
        except:
            filtered['avg_pace'] = const.empty_value

        # Checking for no heart rate recorded
        if 'heartRate' not in data['exercises'][exercise_index]:
            filtered['avg_heart_rate'] = const.empty_value
            filtered['max_heart_rate'] = filtered['avg_heart_rate']
        else:
            filtered['avg_heart_rate'] = data['exercises'][exercise_index][
                'heartRate']['avg']
            filtered['max_heart_rate'] = data['exercises'][exercise_index][
                'heartRate']['max']

        filtered['age'] = utils.get_age(filtered['start_time'])

        filtered['body_max_heart_rate'] = 220 - filtered['age']

        try:
            filtered['avg_heart_rate_as_percentage'] = round(
                filtered['avg_heart_rate'] / filtered['body_max_heart_rate'] *
                10000) / 100.0
            filtered['max_heart_rate_as_percentage'] = round(
                filtered['max_heart_rate'] / filtered['body_max_heart_rate'] *
                10000) / 100.0
        except:
            filtered['avg_heart_rate_as_percentage'] = const.empty_value
            filtered['max_heart_rate_as_percentage'] = filtered[
                'avg_heart_rate_as_percentage']

        filtered['day_link'] = utils.get_day_link(filtered['start_time'])
        # utils.pretty_print_json(filtered)
        # input()

        self.sports_lists[sport].append(filtered)
Esempio n. 4
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    def process_distance_based_sport(self, sport, data, exercise_index=0):
        if sport not in list(self.sports_lists.keys()):
            self.sports_lists[sport] = []

        filtered = {}

        tcx_file = f'{const.accesslink_tcx_file_prefix}{self.current_file_id}.json'

        filtered['start_time'] = self.current_file_id
        
        ### TODO:
        # Pegar a localização da primeira posição do percurso e descobrir o fuso-horário de lá
        # Os horários nos arquivos tcx estão em utc time zone

        try:
            with open(tcx_file, 'r') as f:
                tcx_data = json.load(f)
        except:
            pass

        has_route = False
        # if has_route:
        try:
            first_route_point = {
                                    'latitude': float(tcx_data['TrainingCenterDatabase']['Activities']['Activity']['Lap'][0]['Track']['Trackpoint'][0]['Position']['LatitudeDegrees']),
                                    'longitude': float(tcx_data['TrainingCenterDatabase']['Activities']['Activity']['Lap'][0]['Track']['Trackpoint'][0]['Position']['LongitudeDegrees'])
                                }
            utils.get_weather_data_file(first_route_point, self.current_file_id)
            has_route = True
            filtered['landmark'], filtered['state'], filtered['country'] = utils.get_initial_location(first_route_point, filtered['start_time'])
        except:
            filtered['landmark'], filtered['state'], filtered['country'] = (const.empty_value, const.empty_value, const.empty_value)

        # Checking for no distance recorded
        if 'distance' not in data:
            filtered['distance'] = const.empty_value
        else:
            filtered['distance'] = utils.get_km(data['distance'])

        filtered['duration'] = utils.accesslink_time_to_python_time(data['duration'])

        try:
            filtered['avg_speed'] = utils.calculate_speed(filtered['distance'], filtered['duration'])
        except:
            filtered['avg_speed'] = const.empty_value

        try:
            filtered['max_speed'] = utils.find_tcx_max_speed(tcx_laps)
        except:
            filtered['max_speed'] = filtered['avg_speed']
        
        filtered['avg_pace'] = utils.get_pace(filtered['avg_speed'])

        # Checking for no heart rate recorded
        try:
            filtered['avg_heart_rate'] = data['heart-rate']['average']
            filtered['max_heart_rate'] = data['heart-rate']['maximum']
        except:
            filtered['avg_heart_rate'] = const.empty_value
            filtered['max_heart_rate'] = filtered['avg_heart_rate']
            
        filtered['age'] = utils.get_age(filtered['start_time'])

        filtered['body_max_heart_rate'] = 220 - filtered['age']

        try:
            filtered['avg_heart_rate_as_percentage'] = round(filtered['avg_heart_rate']/filtered['body_max_heart_rate']*10000)/100.0
            filtered['max_heart_rate_as_percentage'] = round(filtered['max_heart_rate']/filtered['body_max_heart_rate']*10000)/100.0
        except:
            filtered['avg_heart_rate_as_percentage'] = const.empty_value
            filtered['max_heart_rate_as_percentage'] = filtered['avg_heart_rate_as_percentage']
        
        filtered['day_link'] = utils.get_day_link(filtered['start_time'])
        # utils.pretty_print_json(filtered)
        # input()

        self.sports_lists[sport].append(filtered)