def rankings(self):
sessionCheck()
self.database_exists()
conn = sql.connect(self.datapath())
conn.row_factory = sql.Row
cursor = conn.cursor()
events = conn.cursor().execute("SELECT * from Events").fetchall()
conn.close()
rankings = {}
# Grab latest rankings and match data from TBA
headers = {
"X-TBA-Auth-Key":
"n8QdCIF7LROZiZFI7ymlX0fshMBL15uAzEkBgtP1JgUpconm2Wf49pjYgbYMstBF"
}
m = requests.get(
"http://www.thebluealliance.com/api/v3/event/{0}/matches".format(
getEvent()),
params=headers)
r = requests.get(
"http://www.thebluealliance.com/api/v3/event/{0}/rankings".format(
getEvent()),
params=headers)
if 'feed' in m:
raise cherrypy.HTTPError(
503, "Unable to retrieve data about this event.")
if r.text != '[]':
r = r.json()
else:
raise cherrypy.HTTPError(
503, "Unable to retrieve rankings data for this event.")
if m.text != '[]':
m = m.json()
else:
raise cherrypy.HTTPError(
503, "Unable to retrieve match data for this event.")
# Process current rankings into dict
for item in r["rankings"]:
rankings[item["team_key"][3:]] = {
'rp':
round(item["sort_orders"][0] * item["matches_played"], 0),
'matchScore':
round(item["sort_orders"][1] * item["matches_played"], 0),
'currentRP':
round(item["sort_orders"][0] * item["matches_played"], 0),
'currentMatchScore':
round(item["sort_orders"][1] * item["matches_played"], 0)
}
# Iterate through all matches
for match in m:
if match['comp_level'] == 'qm':
# Un-played matches show a score of -1. Predict the outcome
if match['alliances']['blue']['score'] == -1:
blueTeams = [
match['alliances']['blue']['team_keys'][0][3:],
match['alliances']['blue']['team_keys'][1][3:],
match['alliances']['blue']['team_keys'][2][3:]
]
blueResult = game.predictScore(getEvent(), blueTeams)
blueRP = blueResult['RP1'] + blueResult['RP2']
redTeams = [
match['alliances']['red']['team_keys'][0][3:],
match['alliances']['red']['team_keys'][1][3:],
match['alliances']['red']['team_keys'][2][3:]
]
redResult = game.predictScore(getEvent(), redTeams)
redRP = redResult['RP1'] + redResult['RP2']
if blueResult['score'] > redResult['score']:
blueRP += 2
elif redResult['score'] > blueResult['score']:
redRP += 2
else:
redRP += 1
blueRP += 1
for team in blueTeams:
rankings[team]['rp'] += blueRP
rankings[team]['matchScore'] += blueResult['score']
for team in redTeams:
rankings[team]['rp'] += redRP
rankings[team]['matchScore'] += redResult['score']
# Sort rankings, then output into table
sorted_rankings = sorted(
rankings.items(),
key=keyFromItem(lambda k, v: (v['rp'], v['matchScore'])),
reverse=True)
tmpl = loader.load('rankings.xhtml')
page = tmpl.generate(rankings=sorted_rankings,
session=cherrypy.session,
events=events)
return page.render('html', doctype='html')
def matches(self, n=''):
sessionCheck()
# Get match data
m = self.getMatches(getEvent())
output = ''
if 'feed' in m:
raise cherrypy.HTTPError(
503, "Unable to retrieve data about this event.")
# assign weights, so we can sort the matches
for match in m:
match['value'] = match['match_number']
type = match['comp_level']
if type == 'qf':
match['value'] += 1000
elif type == 'sf':
match['value'] += 2000
elif type == 'f':
match['value'] += 3000
m = sorted(m, key=lambda k: k['value'])
# For each match, generate a row in the table
for match in m:
level = "quals"
if match['comp_level'] != 'qm':
match['num'] = match['comp_level'].upper() + str(
match['set_number']) + '_' + str(match['match_number'])
level = "playoffs"
else:
match['num'] = match['match_number']
if match['alliances']['blue']['score'] == -1:
match['alliances']['blue']['score'] = ""
if match['alliances']['red']['score'] == -1:
match['alliances']['red']['score'] = ""
blueTeams = [
match['alliances']['blue']['team_keys'][0][3:],
match['alliances']['blue']['team_keys'][1][3:],
match['alliances']['blue']['team_keys'][2][3:]
]
match['bluePredict'] = game.predictScore(getEvent(), blueTeams,
level)
redTeams = [
match['alliances']['red']['team_keys'][0][3:],
match['alliances']['red']['team_keys'][1][3:],
match['alliances']['red']['team_keys'][2][3:]
]
match['redPredict'] = game.predictScore(getEvent(), redTeams,
level)
conn = sql.connect(self.datapath())
conn.row_factory = sql.Row
events = conn.cursor().execute("SELECT * from Events").fetchall()
conn.close()
tmpl = loader.load('matches.xhtml')
page = tmpl.generate(session=cherrypy.session,
matches=m,
events=events)
return page.render('html', doctype='html')
def rankings(self):
event = self.getevent()
datapath = 'data_' + event + '.db'
self.database_exists(event)
conn = sql.connect(datapath)
conn.row_factory = sql.Row
cursor = conn.cursor()
rankings = {}
#Grab latest rankings and match data from TBA
headers = {"X-TBA-App-Id": "frc2067:scouting-system:v02"}
m = requests.get(
"http://www.thebluealliance.com/api/v2/event/{0}/matches".format(
event),
params=headers)
r = requests.get(
"http://www.thebluealliance.com/api/v2/event/{0}/rankings".format(
event),
params=headers)
if 'feed' in m:
raise cherrypy.HTTPError(
503, "Unable to retrieve data about this event.")
if r.text != '[]':
r = r.json()
else:
raise cherrypy.HTTPError(
503, "Unable to retrieve rankings data for this event.")
if m.text != '[]':
m = m.json()
else:
raise cherrypy.HTTPError(
503, "Unable to retrieve match data for this event.")
#Process current rankings into dict
del r[0]
for item in r:
rankings[str(item[1])] = {
'rp': round(item[2] * item[9], 0),
'matchScore': item[3],
'currentRP': round(item[2] * item[9], 0),
'currentMatchScore': item[3]
}
#Iterate through all matches
for match in m:
if match['comp_level'] == 'qm':
#Un-played matches show a score of -1. Predict the outcome
if match['alliances']['blue']['score'] == -1:
blueTeams = [
match['alliances']['blue']['teams'][0][3:],
match['alliances']['blue']['teams'][1][3:],
match['alliances']['blue']['teams'][2][3:]
]
blueResult = game.predictScore(self.datapath(), blueTeams)
blueRP = blueResult['fuelRP'] + blueResult['gearRP']
redTeams = [
match['alliances']['red']['teams'][0][3:],
match['alliances']['red']['teams'][1][3:],
match['alliances']['red']['teams'][2][3:]
]
redResult = game.predictScore(self.datapath(), redTeams)
redRP = redResult['fuelRP'] + redResult['gearRP']
if blueResult['score'] > redResult['score']:
blueRP += 2
elif redResult['score'] > blueResult['score']:
redRP += 2
else:
redRP += 1
blueRP += 1
for team in blueTeams:
rankings[team]['rp'] += blueRP
rankings[team]['matchScore'] += blueResult['score']
for team in redTeams:
rankings[team]['rp'] += redRP
rankings[team]['matchScore'] += redResult['score']
#Sort rankings, then output into table
output = ''
for index, out in enumerate(
sorted(
rankings.items(),
key=keyFromItem(lambda k, v: (v['rp'], v['matchScore'])),
reverse=True)):
output += '''
<tr role="row">
<td>{0}</td>
<td><a href="/team?n={1}">{1}</a></td>
<td class="hidden-xs">{2}</td>
<td class="hidden-xs">{3}</td>
<td class="hidden-xs">{4}</td>
<td class="hidden-xs">{5}</td>
<td class="rankingColumn rankColumn1 hidden-sm hidden-md hidden-lg hidden-xs" style="display: none;">{2}</td>
<td class="rankingColumn rankColumn2 hidden-sm hidden-md hidden-lg hidden-xs" style="display: none;">{3}</td>
<td class="rankingColumn rankColumn3 hidden-sm hidden-md hidden-lg hidden-xs" style="display: none;">{4}</td>
<td class="rankingColumn rankColumn4 hidden-sm hidden-md hidden-lg hidden-xs" style="display: none;">{5}</td>
</tr>
'''.format(index + 1, out[0], (int)(out[1]['rp']),
(int)(out[1]['matchScore']), (int)(out[1]['currentRP']),
(int)(out[1]['currentMatchScore']))
with open('web/rankings.html', 'r') as file:
page = file.read()
return page.format(output)
def alliances(self, b1='', b2='', b3='', r1='', r2='', r3='', level=''):
sessionCheck()
if level == '':
level = 'quals'
numsBlue = [b1, b2, b3]
numsRed = [r1, r2, r3]
averages = []
conn = sql.connect(self.datapath())
conn.row_factory = sql.Row
cursor = conn.cursor()
blueData = []
redData = []
# iterate through all six teams and grab data
for i, n in enumerate(numsBlue):
if not n.isdigit():
raise cherrypy.HTTPError(400, "Enter six valid team numbers!")
entries = cursor.execute(
'SELECT * FROM ScoutRecords WHERE Team=? AND EventCode=? ORDER BY Match DESC',
(n, getEvent())).fetchall()
prevEvent = 0
teamData = []
teamData.append(getPitDisplayData(n))
if len(entries) < 3:
seasonEntries = cursor.execute(
'SELECT * FROM ScoutRecords WHERE Team=? ORDER BY Match DESC',
(n, )).fetchall()
if (len(seasonEntries) >= 3):
oldAverages = getAggregateData(Team=n, Mode="Averages")
assert len(
oldAverages
) < 2 # ensure there aren't two entries for one team
if len(oldAverages):
teamData.append(oldAverages[0])
prevEvent = 1
if prevEvent == 0:
average = getAggregateData(Team=n,
Event=getEvent(),
Mode="Averages")
if not len(average):
average = dict(game.SCOUT_FIELDS)
average.update(game.DISPLAY_FIELDS)
average.update(game.HIDDEN_DISPLAY_FIELDS)
average['Team'] = n
teamData.append(average)
else:
teamData.append(average[0])
blueData.append(teamData)
for i, n in enumerate(numsRed):
if not n.isdigit():
raise cherrypy.HTTPError(400, "Enter six valid team numbers!")
entries = cursor.execute(
'SELECT * FROM ScoutRecords WHERE Team=? AND EventCode=? ORDER BY Match DESC',
(n, getEvent())).fetchall()
prevEvent = 0
teamData = []
teamData.append(getPitDisplayData(n))
if len(entries) < 3:
seasonEntries = cursor.execute(
'SELECT * FROM ScoutRecords WHERE Team=? ORDER BY Match DESC',
(n, )).fetchall()
if (len(seasonEntries) >= 3):
oldAverages = getAggregateData(Team=n, Mode="Averages")
assert len(
oldAverages
) < 2 # ensure there aren't two entries for one team
if len(oldAverages):
teamData.append(oldAverages[0])
prevEvent = 1
if prevEvent == 0:
average = getAggregateData(Team=n,
Event=getEvent(),
Mode="Averages")
if not len(average):
average = dict(game.SCOUT_FIELDS)
average.update(game.DISPLAY_FIELDS)
average.update(game.HIDDEN_DISPLAY_FIELDS)
average['Team'] = n
teamData.append(average)
else:
teamData.append(average[0])
redData.append(teamData)
# Predict scores
blue_score = game.predictScore(getEvent(), numsBlue, level)['score']
red_score = game.predictScore(getEvent(), numsRed, level)['score']
blue_score = int(blue_score)
red_score = int(red_score)
# Calculate win probability. Currently uses regression from 2016 data, this should be updated
prob_red = 1 / (1 + math.e**(-0.08099 * (red_score - blue_score)))
events = conn.cursor().execute("SELECT * from Events").fetchall()
conn.close()
tmpl = loader.load('alliances.xhtml')
page = tmpl.generate(session=cherrypy.session,
red_win=round(prob_red * 100, 1),
red_score=red_score,
blue_score=blue_score,
red_data=redData,
blue_data=blueData,
columns=game.DISPLAY_FIELDS,
events=events,
pitColumns=game.PIT_DISPLAY_FIELDS)
return page.render('html', doctype='html')
def alliances(self,
b1='',
b2='',
b3='',
r1='',
r2='',
r3='',
mode='',
level=''):
if mode == '':
mode = 'averages'
if level == '':
level = 'quals'
numsBlue = [b1, b2, b3]
numsRed = [r1, r2, r3]
averages = []
conn = sql.connect(self.datapath())
conn.row_factory = sql.Row
cursor = conn.cursor()
teamsBlue = []
teamsRed = []
#iterate through all six teams and grab data
for i, n in enumerate(numsBlue):
if not n.isdigit():
raise cherrypy.HTTPError(
400, "You fool! Enter six valid team numbers!")
if mode == 'averages':
average = cursor.execute('SELECT * FROM averages WHERE team=?',
(n, )).fetchall()
else:
average = cursor.execute('SELECT * FROM maxes WHERE team=?',
(n, )).fetchall()
assert len(average) < 2
if len(average):
entry = average[0]
else:
entry = [0] * len(game.AVERAGE_FIELDS)
teamsBlue.append(n)
teamsBlue.extend(entry[1:-1])
for i, n in enumerate(numsRed):
if not n.isdigit():
raise cherrypy.HTTPError(
400, "You fool! Enter six valid team numbers!")
if mode == 'averages':
average = cursor.execute('SELECT * FROM averages WHERE team=?',
(n, )).fetchall()
else:
average = cursor.execute('SELECT * FROM maxes WHERE team=?',
(n, )).fetchall()
assert len(average) < 2
if len(average):
entry = average[0]
else:
entry = [0] * len(game.AVERAGE_FIELDS)
teamsRed.append(n)
teamsRed.extend(entry[1:-1])
#Predict scores
blue_score = game.predictScore(self.datapath(), numsBlue,
level)['score']
red_score = game.predictScore(self.datapath(), numsRed, level)['score']
blue_score = int(blue_score)
red_score = int(red_score)
#Calculate win probability. Currently uses regression from 2016 data, this should be updated
prob_red = 1 / (1 + math.e**(-0.08099 * (red_score - blue_score)))
conn.close()
with open('web/alliances.html', 'r') as file:
page = file.read()
return page.format(round((1 - prob_red) * 100,
1), blue_score, *teamsBlue,
round(prob_red * 100, 1), red_score, *teamsRed)