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)
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)
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)
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)