beautified

This commit is contained in:
ltcptgeneral 2019-04-03 13:34:31 -05:00
parent ef81273d4a
commit 20f082b760
2 changed files with 234 additions and 203 deletions

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@ -1,7 +1,7 @@
#Titan Robotics Team 2022: Super Script
#Written by Arthur Lu & Jacob Levine
#Notes:
#setup:
# Titan Robotics Team 2022: Super Script
# Written by Arthur Lu & Jacob Levine
# Notes:
# setup:
__version__ = "1.0.6.001"
@ -43,7 +43,7 @@ __changelog__ = """changelog:
__author__ = (
"Arthur Lu <arthurlu@ttic.edu>, "
"Jacob Levine <jlevine@ttic.edu>,"
)
)
import firebase_admin
from firebase_admin import credentials
@ -60,6 +60,7 @@ import time
import tbarequest as tba
import csv
def titanservice():
print("[OK] loading data")
@ -67,15 +68,16 @@ def titanservice():
start = time.time()
source_dir = 'data'
file_list = glob.glob(source_dir + '/*.csv') #supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
# supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
file_list = glob.glob(source_dir + '/*.csv')
data = []
files = [fn for fn in glob.glob('data/*.csv')
if not (os.path.basename(fn).startswith('scores') or os.path.basename(fn).startswith('teams') or os.path.basename(fn).startswith('match') or os.path.basename(fn).startswith('notes') or os.path.basename(fn).startswith('observationType') or os.path.basename(fn).startswith('teamDBRef'))] #scores will be handled sperately
if not (os.path.basename(fn).startswith('scores') or os.path.basename(fn).startswith('teams') or os.path.basename(fn).startswith('match') or os.path.basename(fn).startswith('notes') or os.path.basename(fn).startswith('observationType') or os.path.basename(fn).startswith('teamDBRef'))] # scores will be handled sperately
for i in files:
data.append(analysis.load_csv(i))
data.append(analysis.load_csv(i))
#print(files)
# print(files)
stats = []
measure_stats = []
@ -86,111 +88,113 @@ def titanservice():
print("[OK] loaded data in " + str(end - start) + " seconds")
#assumes that team number is in the first column, and that the order of teams is the same across all files
#unhelpful comment
for measure in data: #unpacks 3d array into 2ds
# assumes that team number is in the first column, and that the order of teams is the same across all files
# unhelpful comment
for measure in data: # unpacks 3d array into 2ds
measure_stats = []
for i in range(len(measure)): #unpacks into specific teams
for i in range(len(measure)): # unpacks into specific teams
#ofbest_curve = [None]
#r2best_curve = [None]
#ofbest_curve = [None]
#r2best_curve = [None]
line = measure[i]
line = measure[i]
#print(line)
# print(line)
#x = list(range(len(line)))
#eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
#x = list(range(len(line)))
#eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
#print(eqs, rmss, r2s, overfit)
#print(eqs, rmss, r2s, overfit)
#ofbest_curve.append(beqs)
#ofbest_curve.append(brmss)
#ofbest_curve.append(br2s)
#ofbest_curve.append(boverfit)
#ofbest_curve.pop(0)
# ofbest_curve.append(beqs)
# ofbest_curve.append(brmss)
# ofbest_curve.append(br2s)
# ofbest_curve.append(boverfit)
# ofbest_curve.pop(0)
#print(ofbest_curve)
# print(ofbest_curve)
#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
#r2best_curve.append(beqs)
#r2best_curve.append(brmss)
#r2best_curve.append(br2s)
#r2best_curve.append(boverfit)
#r2best_curve.pop(0)
# r2best_curve.append(beqs)
# r2best_curve.append(brmss)
# r2best_curve.append(br2s)
# r2best_curve.append(boverfit)
# r2best_curve.pop(0)
#print(r2best_curve)
# print(r2best_curve)
measure_stats.append(teams[i] + list(analysis.basic_stats(line, 0, 0)) + list(analysis.histo_analysis(line, 1, -3, 3)))
measure_stats.append(teams[i] + list(analysis.basic_stats(
line, 0, 0)) + list(analysis.histo_analysis(line, 1, -3, 3)))
stats.append(list(measure_stats))
nishant = []
for i in range(len(scores)):
#print(scores)
# print(scores)
ofbest_curve = [None]
r2best_curve = [None]
ofbest_curve = [None]
r2best_curve = [None]
line = scores[i]
line = scores[i]
if len(line) < 4:
if len(line) < 4:
nishant.append('no_data')
nishant.append('no_data')
continue
continue
#print(line)
# print(line)
#print(line)
# print(line)
x = list(range(len(line)))
eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
x = list(range(len(line)))
eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
beqs, brmss, br2s, boverfit = analysis.select_best_regression(
eqs, rmss, r2s, overfit, "min_overfit")
#print(eqs, rmss, r2s, overfit)
#print(eqs, rmss, r2s, overfit)
ofbest_curve.append(beqs)
ofbest_curve.append(brmss)
ofbest_curve.append(br2s)
ofbest_curve.append(boverfit)
ofbest_curve.pop(0)
ofbest_curve.append(beqs)
ofbest_curve.append(brmss)
ofbest_curve.append(br2s)
ofbest_curve.append(boverfit)
ofbest_curve.pop(0)
#print(ofbest_curve)
# print(ofbest_curve)
beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
beqs, brmss, br2s, boverfit = analysis.select_best_regression(
eqs, rmss, r2s, overfit, "max_r2s")
r2best_curve.append(beqs)
r2best_curve.append(brmss)
r2best_curve.append(br2s)
r2best_curve.append(boverfit)
r2best_curve.pop(0)
r2best_curve.append(beqs)
r2best_curve.append(brmss)
r2best_curve.append(br2s)
r2best_curve.append(boverfit)
r2best_curve.pop(0)
#print(r2best_curve)
# print(r2best_curve)
z = len(scores[0]) + 1
nis_num = []
z = len(scores[0]) + 1
nis_num = []
nis_num.append(eval(str(ofbest_curve[0])))
nis_num.append(eval(str(r2best_curve[0])))
nis_num.append(eval(str(ofbest_curve[0])))
nis_num.append(eval(str(r2best_curve[0])))
nis_num.append((eval(ofbest_curve[0]) + eval(r2best_curve[0])) / 2)
nis_num.append((eval(ofbest_curve[0]) + eval(r2best_curve[0])) / 2)
nishant.append(teams[i] + nis_num)
nishant.append(teams[i] + nis_num)
json_out = {}
score_out = {}
for i in range(len(teams)):
score_out[str(teams[i][0])] = (nishant[i])
score_out[str(teams[i][0])] = (nishant[i])
location = db.collection(u'stats').document(u'stats-noNN')
for i in range(len(teams)):
@ -199,49 +203,59 @@ def titanservice():
for j in range(len(files)):
json_out[str(teams[i][0])] = (stats[j][i])
name = os.path.basename(files[j])
general_general_stats.document(name).set({'stats':json_out.get(teams[i][0])})
general_general_stats.document(name).set(
{'stats': json_out.get(teams[i][0])})
for i in range(len(teams)):
nnum = location.collection(teams[i][0]).document(u'nishant_number').set({'nishant':score_out.get(teams[i][0])})
nnum = location.collection(teams[i][0]).document(
u'nishant_number').set({'nishant': score_out.get(teams[i][0])})
def pulldata():
teams = analysis.load_csv('data/teams.csv')
scores = []
for i in range(len(teams)):
team_scores = []
#print(teams[i][0])
request_data_object = tba.req_team_matches(teams[i][0], 2019, "UDvKmPjPRfwwUdDX1JxbmkyecYBJhCtXeyVk9vmO2i7K0Zn4wqQPMfzuEINXJ7e5")
# print(teams[i][0])
request_data_object = tba.req_team_matches(
teams[i][0], 2019, "UDvKmPjPRfwwUdDX1JxbmkyecYBJhCtXeyVk9vmO2i7K0Zn4wqQPMfzuEINXJ7e5")
json_data = request_data_object.json()
for match in range(len(json_data) - 1, -1, -1):
if json_data[match].get('winning_alliance') == "":
#print(json_data[match])
# print(json_data[match])
json_data.remove(json_data[match])
json_data = sorted(json_data, key=lambda k: k.get('actual_time', 0), reverse=False)
json_data = sorted(json_data, key=lambda k: k.get(
'actual_time', 0), reverse=False)
for j in range(len(json_data)):
if "frc" + teams[i][0] in json_data[j].get('alliances').get('blue').get('team_keys'):
team_scores.append(json_data[j].get('alliances').get('blue').get('score'))
team_scores.append(json_data[j].get(
'alliances').get('blue').get('score'))
elif "frc" + teams[i][0] in json_data[j].get('alliances').get('red').get('team_keys'):
team_scores.append(json_data[j].get('alliances').get('red').get('score'))
team_scores.append(json_data[j].get(
'alliances').get('red').get('score'))
scores.append(team_scores)
with open("data/scores.csv", "w+", newline = '') as file:
writer = csv.writer(file, delimiter = ',')
with open("data/scores.csv", "w+", newline='') as file:
writer = csv.writer(file, delimiter=',')
writer.writerows(scores)
list_teams = teams
teams=db.collection('data').document('team-2022').collection("Central 2019").get()
full=[]
tms=[]
teams = db.collection('data').document(
'team-2022').collection("Central 2019").get()
full = []
tms = []
for team in teams:
tms.append(team.id)
reports=db.collection('data').document('team-2022').collection("Central 2019").document(team.id).collection("matches").get()
reports = db.collection('data').document(
'team-2022').collection("Central 2019").document(team.id).collection("matches").get()
for report in reports:
data=[]
data.append(db.collection('data').document('team-2022').collection("Central 2019").document(team.id).collection("matches").document(report.id).get().to_dict())
data = []
data.append(db.collection('data').document('team-2022').collection("Central 2019").document(
team.id).collection("matches").document(report.id).get().to_dict())
full.append(data)
quant_keys = []
@ -267,11 +281,11 @@ def pulldata():
#print(full[i][j].get(key).get('teamDBRef')[5:] in list_teams)
#print(full[i][j].get(key).get('teamDBRef'))
# print(full[i][j].get(key).get('teamDBRef'))
#print(list(full[i][j].keys()))
# print(list(full[i][j].keys()))
#print(list_teams)
# print(list_teams)
if full[i][j].get(key).get('teamDBRef')[5:] in list_teams:
@ -282,7 +296,8 @@ def pulldata():
individual_keys = list(full[i][j].get(key).keys())
var[individual_keys[k]] = full[i][j].get(key).get(individual_keys[k])
var[individual_keys[k]] = full[i][j].get(
key).get(individual_keys[k])
out.append(var)
@ -316,7 +331,8 @@ def pulldata():
for i in sorted_out:
team_index = list_teams.index(sorted_out[sorted_out.index(i)][j_list.index('teamDBRef')][5:])
team_index = list_teams.index(
sorted_out[sorted_out.index(i)][j_list.index('teamDBRef')][5:])
for j in range(len(i)):
@ -324,11 +340,12 @@ def pulldata():
for i in range(len(big_out)):
with open('data/' + j_list[i] + '.csv', "w+", newline = '') as file:
with open('data/' + j_list[i] + '.csv', "w+", newline='') as file:
writer = csv.writer(file, delimiter = ',')
writer = csv.writer(file, delimiter=',')
writer.writerows(big_out[i])
def service():
while True:
@ -347,7 +364,8 @@ def service():
break
except:
if (i != 4):
print("[WARNING] failed, trying " + str(5 - i - 1) + " more times")
print("[WARNING] failed, trying " +
str(5 - i - 1) + " more times")
else:
print("[ERROR] failed to compute data, skipping")
fucked = True
@ -363,10 +381,11 @@ def service():
print("[OK] waiting: " + str(300 - (end - start)) + " seconds" + "\n")
time.sleep(300 - (end - start)) #executes once every 5 minutes
time.sleep(300 - (end - start)) # executes once every 5 minutes
warnings.simplefilter("ignore")
#Use a service account
# Use a service account
try:
cred = credentials.Certificate('keys/firebasekey.json')
except:
@ -375,5 +394,5 @@ firebase_admin.initialize_app(cred)
db = firestore.client()
service() #finally we write something that isn't a function definition
#titanservice()
service() # finally we write something that isn't a function definition
# titanservice()

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@ -1,7 +1,7 @@
#Titan Robotics Team 2022: Super Script
#Written by Arthur Lu & Jacob Levine
#Notes:
#setup:
# Titan Robotics Team 2022: Super Script
# Written by Arthur Lu & Jacob Levine
# Notes:
# setup:
__version__ = "1.0.6.001"
@ -43,7 +43,7 @@ __changelog__ = """changelog:
__author__ = (
"Arthur Lu <arthurlu@ttic.edu>, "
"Jacob Levine <jlevine@ttic.edu>,"
)
)
import firebase_admin
from firebase_admin import credentials
@ -60,6 +60,7 @@ import time
import tbarequest as tba
import csv
def titanservice():
print("[OK] loading data")
@ -67,15 +68,16 @@ def titanservice():
start = time.time()
source_dir = 'data'
file_list = glob.glob(source_dir + '/*.csv') #supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
# supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
file_list = glob.glob(source_dir + '/*.csv')
data = []
files = [fn for fn in glob.glob('data/*.csv')
if not (os.path.basename(fn).startswith('scores') or os.path.basename(fn).startswith('teams') or os.path.basename(fn).startswith('match') or os.path.basename(fn).startswith('notes') or os.path.basename(fn).startswith('observationType') or os.path.basename(fn).startswith('teamDBRef'))] #scores will be handled sperately
if not (os.path.basename(fn).startswith('scores') or os.path.basename(fn).startswith('teams') or os.path.basename(fn).startswith('match') or os.path.basename(fn).startswith('notes') or os.path.basename(fn).startswith('observationType') or os.path.basename(fn).startswith('teamDBRef'))] # scores will be handled sperately
for i in files:
data.append(analysis.load_csv(i))
data.append(analysis.load_csv(i))
#print(files)
# print(files)
stats = []
measure_stats = []
@ -86,150 +88,158 @@ def titanservice():
print("[OK] loaded data in " + str(end - start) + " seconds")
#assumes that team number is in the first column, and that the order of teams is the same across all files
#unhelpful comment
#for measure in data: #unpacks 3d array into 2ds
# assumes that team number is in the first column, and that the order of teams is the same across all files
# unhelpful comment
# for measure in data: #unpacks 3d array into 2ds
#measure_stats = []
#measure_stats = []
#for i in range(len(measure)): #unpacks into specific teams
# for i in range(len(measure)): #unpacks into specific teams
#ofbest_curve = [None]
#r2best_curve = [None]
#ofbest_curve = [None]
#r2best_curve = [None]
#line = measure[i]
#line = measure[i]
#print(line)
# print(line)
#x = list(range(len(line)))
#eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
#x = list(range(len(line)))
#eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
#print(eqs, rmss, r2s, overfit)
#print(eqs, rmss, r2s, overfit)
#ofbest_curve.append(beqs)
#ofbest_curve.append(brmss)
#ofbest_curve.append(br2s)
#ofbest_curve.append(boverfit)
#ofbest_curve.pop(0)
# ofbest_curve.append(beqs)
# ofbest_curve.append(brmss)
# ofbest_curve.append(br2s)
# ofbest_curve.append(boverfit)
# ofbest_curve.pop(0)
#print(ofbest_curve)
# print(ofbest_curve)
#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
#r2best_curve.append(beqs)
#r2best_curve.append(brmss)
#r2best_curve.append(br2s)
#r2best_curve.append(boverfit)
#r2best_curve.pop(0)
# r2best_curve.append(beqs)
# r2best_curve.append(brmss)
# r2best_curve.append(br2s)
# r2best_curve.append(boverfit)
# r2best_curve.pop(0)
#print(r2best_curve)
# print(r2best_curve)
#measure_stats.append(teams[i] + list(analysis.basic_stats(line, 0, 0)) + list(analysis.histo_analysis(line, 1, -3, 3)))
#measure_stats.append(teams[i] + list(analysis.basic_stats(line, 0, 0)) + list(analysis.histo_analysis(line, 1, -3, 3)))
#stats.append(list(measure_stats))
# stats.append(list(measure_stats))
nishant = []
for i in range(len(scores)):
#print(scores)
# print(scores)
ofbest_curve = [None]
r2best_curve = [None]
ofbest_curve = [None]
r2best_curve = [None]
line = scores[i]
line = scores[i]
if len(line) < 4:
if len(line) < 4:
nishant.append('no_data')
nishant.append('no_data')
continue
continue
#print(line)
# print(line)
#print(line)
# print(line)
x = list(range(len(line)))
eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
x = list(range(len(line)))
eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
beqs, brmss, br2s, boverfit = analysis.select_best_regression(
eqs, rmss, r2s, overfit, "min_overfit")
#print(eqs, rmss, r2s, overfit)
#print(eqs, rmss, r2s, overfit)
ofbest_curve.append(beqs)
ofbest_curve.append(brmss)
ofbest_curve.append(br2s)
ofbest_curve.append(boverfit)
ofbest_curve.pop(0)
ofbest_curve.append(beqs)
ofbest_curve.append(brmss)
ofbest_curve.append(br2s)
ofbest_curve.append(boverfit)
ofbest_curve.pop(0)
#print(ofbest_curve)
# print(ofbest_curve)
beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
beqs, brmss, br2s, boverfit = analysis.select_best_regression(
eqs, rmss, r2s, overfit, "max_r2s")
r2best_curve.append(beqs)
r2best_curve.append(brmss)
r2best_curve.append(br2s)
r2best_curve.append(boverfit)
r2best_curve.pop(0)
r2best_curve.append(beqs)
r2best_curve.append(brmss)
r2best_curve.append(br2s)
r2best_curve.append(boverfit)
r2best_curve.pop(0)
#print(r2best_curve)
# print(r2best_curve)
z = len(scores[0]) + 1
nis_num = []
z = len(scores[0]) + 1
nis_num = []
nis_num.append(eval(str(ofbest_curve[0])))
nis_num.append(eval(str(r2best_curve[0])))
nis_num.append(eval(str(ofbest_curve[0])))
nis_num.append(eval(str(r2best_curve[0])))
nis_num.append((eval(ofbest_curve[0]) + eval(r2best_curve[0])) / 2)
nis_num.append((eval(ofbest_curve[0]) + eval(r2best_curve[0])) / 2)
nishant.append(teams[i] + nis_num)
nishant.append(teams[i] + nis_num)
json_out = {}
score_out = {}
for i in range(len(teams)):
score_out[str(teams[i][0])] = (nishant[i])
score_out[str(teams[i][0])] = (nishant[i])
location = db.collection(u'stats').document(u'stats-noNN')
#for i in range(len(teams)):
#general_general_stats = location.collection(teams[i][0])
# for i in range(len(teams)):
#general_general_stats = location.collection(teams[i][0])
#for j in range(len(files)):
# json_out[str(teams[i][0])] = (stats[j][i])
# name = os.path.basename(files[j])
# general_general_stats.document(name).set({'stats':json_out.get(teams[i][0])})
# for j in range(len(files)):
# json_out[str(teams[i][0])] = (stats[j][i])
# name = os.path.basename(files[j])
# general_general_stats.document(name).set({'stats':json_out.get(teams[i][0])})
for i in range(len(teams)):
nnum = location.collection(teams[i][0]).document(u'nishant_number').set({'nishant':score_out.get(teams[i][0])})
nnum = location.collection(teams[i][0]).document(
u'nishant_number').set({'nishant': score_out.get(teams[i][0])})
def pulldata():
teams = analysis.load_csv('data/teams.csv')
scores = []
for i in range(len(teams)):
team_scores = []
#print(teams[i][0])
request_data_object = tba.req_team_matches(teams[i][0], 2019, "UDvKmPjPRfwwUdDX1JxbmkyecYBJhCtXeyVk9vmO2i7K0Zn4wqQPMfzuEINXJ7e5")
# print(teams[i][0])
request_data_object = tba.req_team_matches(
teams[i][0], 2019, "UDvKmPjPRfwwUdDX1JxbmkyecYBJhCtXeyVk9vmO2i7K0Zn4wqQPMfzuEINXJ7e5")
json_data = request_data_object.json()
for match in range(len(json_data) - 1, -1, -1):
if json_data[match].get('winning_alliance') == "":
#print(json_data[match])
# print(json_data[match])
json_data.remove(json_data[match])
json_data = sorted(json_data, key=lambda k: k.get('actual_time', 0), reverse=False)
json_data = sorted(json_data, key=lambda k: k.get(
'actual_time', 0), reverse=False)
for j in range(len(json_data)):
if "frc" + teams[i][0] in json_data[j].get('alliances').get('blue').get('team_keys'):
team_scores.append(json_data[j].get('alliances').get('blue').get('score'))
team_scores.append(json_data[j].get(
'alliances').get('blue').get('score'))
elif "frc" + teams[i][0] in json_data[j].get('alliances').get('red').get('team_keys'):
team_scores.append(json_data[j].get('alliances').get('red').get('score'))
team_scores.append(json_data[j].get(
'alliances').get('red').get('score'))
scores.append(team_scores)
with open("data/scores.csv", "w+", newline = '') as file:
writer = csv.writer(file, delimiter = ',')
with open("data/scores.csv", "w+", newline='') as file:
writer = csv.writer(file, delimiter=',')
writer.writerows(scores)
def service():
while True:
@ -248,7 +258,8 @@ def service():
break
except:
if (i != 4):
print("[WARNING] failed, trying " + str(5 - i - 1) + " more times")
print("[WARNING] failed, trying " +
str(5 - i - 1) + " more times")
else:
print("[ERROR] failed to compute data, skipping")
fucked = True
@ -264,10 +275,11 @@ def service():
print("[OK] waiting: " + str(300 - (end - start)) + " seconds" + "\n")
time.sleep(300 - (end - start)) #executes once every 5 minutes
time.sleep(300 - (end - start)) # executes once every 5 minutes
warnings.simplefilter("ignore")
#Use a service account
# Use a service account
try:
cred = credentials.Certificate('keys/firebasekey.json')
except:
@ -276,5 +288,5 @@ firebase_admin.initialize_app(cred)
db = firestore.client()
service() #finally we write something that isn't a function definition
#titanservice()
service() # finally we write something that isn't a function definition
# titanservice()