def getregion(teamKey):
team = getTBAdata("team/" + teamKey + "/simple")
districts = getTBAdata("team/" + teamKey + "/districts")
if len(districts) != 0:
return districts[0]["abbreviation"].upper()
elif team["country"] not in ["USA", "Canada"]:
return team["country"]
else:
return team["state_prov"]
def eventDP(event):
teams = {}
statuses = getTBAdata("event/" + event + "/teams/statuses")
num = len(getTBAdata("event/" + event + "/teams/keys"))
matches = getTBAdata("event/" + event + "/matches/simple")
awards = getTBAdata("event/" + event + "/awards")
for key, t in statuses.items():
if t is None: continue
if t["qual"] is None: teams[key] = 0
else:
teams[key] = ceil(
7.676 * erfinv(0.934579 + 1.86916 *
(1 - t["qual"]["ranking"]["rank"]) / num) + 12)
if t["alliance"] is not None and t["qual"] is not None:
teams[key] += (
(17 -
t["alliance"]["number"]) if t["alliance"]["pick"] < 2 else
t["alliance"]["number"]) if t["alliance"]["pick"] < 3 else 0
if t["playoff"] is not None:
cnt = 0
for lvl in ["qf", "sf", "f"]:
if [0, 0, 10, 20][[
"ef", "qf", "sf", "f"
].index(lvl)] < ([0, 0, 10, 20][["ef", "qf", "sf", "f"].index(
t["playoff"]["level"])] if t["playoff"]["status"]
== "eliminated" else 30):
for m in matches:
if m["comp_level"] != lvl: continue
if key in m["alliances"]["blue"]["team_keys"] and m[
"winning_alliance"] == "blue":
cnt += 5
if key in m["alliances"]["red"]["team_keys"] and m[
"winning_alliance"] == "red":
cnt += 5
teams[key] += cnt
for a in awards:
if a["award_type"] not in awarddp: continue
for t in a["recipient_list"]:
if t["team_key"] is None: continue
if t["team_key"] not in teams:
print("^^^^ " + t["team_key"])
continue
teams[t["team_key"]] += awarddp[a["award_type"]]
return teams
for a in awards:
if a["award_type"] not in awarddp: continue
for t in a["recipient_list"]:
if t["team_key"] is None: continue
if t["team_key"] not in teams:
print("^^^^ " + t["team_key"])
continue
teams[t["team_key"]] += awarddp[a["award_type"]]
return teams
data = {}
years = range(2011, 2019)
for year in years:
yeardp = {}
events = getTBAdata("events/" + str(year))
for event in events:
if event["event_type"] > 5 or len(event["division_keys"]) > 0: continue
print(event["key"])
eventdp = eventDP(event["key"])
for key, dp in eventdp.items():
if key not in yeardp: yeardp[key] = [0, 0]
yeardp[key][0] += dp * [1, 1, 1.1, 1.2, 1, 1.1
][event["event_type"]]
yeardp[key][1] += 1 if event["event_type"] != 4 else 0
for key, t in yeardp.items():
if key not in data: data[key] = {}
data[key][year] = t
with open("data_award.csv", "w+") as file:
file.write("Team,")
from functions import getTBAdata
avgs = {}
events = getTBAdata("events/2018")
for event in events:
if event["event_type"] > 1: continue
print(event["key"])
dps = getTBAdata("event/" + event["key"] + "/district_points")["points"]
avgs[event["key"]] = (sum([dps[t]["total"]
for t in dps.keys()]) / len(dps), len(dps))
with open("avgs.csv", "w+") as file:
file.write("Event,AvgDP,# Teams\n")
for event, avg in avgs.items():
file.write(event + "," + str(avg[0]) + "," + str(avg[1]) + "\n")
import random
import math
from functions import getTBAdata
import csv
DPs = {}
with open("DistrictRankings/SingleYearDP/2018_world_DP.csv") as file:
reader = csv.DictReader(file)
for row in reader:
DPs[row["Team"]] = float(row["Adj DP"])
event = input("event: ")
teams = getTBAdata("event/" + event + "/teams/keys")
num_matches = int(input("Matches per Team: "))
with open("DistrictRankings/Event Predictor/schedules/" + str(len(teams)) +
"_" + str(num_matches) + ".csv") as file:
matches = file.readlines()
matches = [[int(x) for x in match.strip().split(",")[0::2]]
for match in matches]
runs = int(input("Iterations: "))
results = {team: [0] * len(teams) for team in teams}
avg = {team: 0 for team in teams}
for i in range(runs):
print(i)
random.shuffle(teams)
ev = {team: [0, 0] for team in teams}
for match in matches:
playing = [teams[x - 1] for x in match]
redwins = random.random() <= 1 / (
1 + math.exp(-(sum([DPs[team] for team in playing[:3]]) -
from functions import getTBAdata
years = range(2002, 2020)
all_events = []
for year in years:
events = getTBAdata("events/" + str(year) + "/keys")
for event in events:
print(event)
teams = getTBAdata("event/" + event + "/teams")
if len(teams) == 0:
continue
rookie = sum([1 if t["rookie_year"]==year else 0 for t in teams])
all_events.append((event, rookie, len(teams)))
all_events = sorted(all_events, key=lambda x:x[1]/x[2], reverse=True)
print(all_events)
with open("rookie_percent.csv", "w+") as file:
file.write("Event,Rookies,Total,% Rookies\n")
for e in all_events:
file.write(e[0] + "," + str(e[1]) + "," + str(e[2]) + "," + str(e[1]/e[2]) + "\n")
"wins"]
self.ties += status["qual"]["ranking"]["record"][
"ties"]
self.losses += status["qual"]["ranking"]["record"][
"losses"]
if status["playoff"] is not None:
if status["playoff"]["record"] is not None:
self.wins += status["playoff"]["record"]["wins"]
self.ties += status["playoff"]["record"]["ties"]
self.losses += status["playoff"]["record"]["losses"]
teams = {}
file = open("winning_season.csv", "w+")
events = getTBAdata("events/2018")
for event in events:
if 0 <= event["event_type"] <= 3 or event["event_type"] == 5:
if len(event["division_keys"]) == 0:
print(event["key"])
statuses = getTBAdata("event/" + str(event["key"]) +
"/teams/statuses")
for teamKey in statuses:
if teamKey in teams:
teams[teamKey].add_event(statuses[teamKey])
else:
teams[teamKey] = Team(statuses[teamKey])
file.write("Team,Wins,Losses,Ties,Ratio\n")
for teamKey in teams:
print(teamKey)
districts = getTBAdata("team/" + teamKey + "/districts")
if len(districts) != 0:
return districts[0]["abbreviation"].upper()
elif team["country"] not in ["USA", "Canada"]:
return team["country"]
else:
return team["state_prov"]
years = range(2010, 2019)
regions = {}
for year in years:
print(year)
cmp_awards = []
events = getTBAdata("events/"+str(year))
for event in events:
if event["event_type"] in [3, 4]:
print(event["key"])
awards = getTBAdata("event/"+event["key"]+"/awards")
for award in awards:
if award["award_type"] in [0, 9, 10, 69]:
for recipient in award["recipient_list"]:
if recipient["team_key"] not in cmp_awards:
cmp_awards.append(recipient["team_key"])
print(cmp_awards)
yearly = {}
for teamKey in cmp_awards:
region = getregion(teamKey)
if region not in yearly:
yearly[region] = 0
self.numevents[year]) + ","
else:
tmp += ",,,,"
return tmp
teams = {}
file = open("yearly_dp_.csv", "w+")
file.write("Team #,")
for year in range(2010, 2018 + 1):
file.write(
str(year) + " DP," + str(year) + " OPR," + str(year) + " Rank," +
str(year) + " Num Events,")
events = getTBAdata("events/" + str(year))
for event in events:
if 0 <= event["event_type"] <= 3 or event["event_type"] == 5:
if len(event["division_keys"]) == 0:
print(event["key"])
statuses = getTBAdata("event/" + event["key"] +
"/teams/statuses")
oprs = getTBAdata("event/" + event["key"] + "/oprs")["oprs"]
for teamKey in statuses:
print(statuses[teamKey])
if teamKey in oprs:
if teamKey in teams:
teams[teamKey].add_event(event, statuses[teamKey],
oprs[teamKey])
else:
teams[teamKey] = Team(event, statuses[teamKey],
21: "ENGINEERING_EXCELLENCE",
22: "ENTREPRENEURSHIP",
23: "EXCELLENCE_IN_DESIGN",
27: "IMAGERY",
29: "INNOVATION_IN_CONTROL",
30: "SPIRIT",
31: "WEBSITE"
}
with open("output.txt", "w+") as file:
file.write("data = {\n")
teams = {}
i = 0
while True:
tmp = getTBAdata("teams/2018/" + str(i) + "/keys")
if len(tmp) == 0: break
for team in tmp:
print(team)
awards = getTBAdata("team/" + team + "/awards")
teams[team] = {
"WINNER": [],
"FINALIST": [],
"CHAIRMANS": [],
"ENGINEERING_INSPIRATION": [],
"CREATIVITY": [],
"ENGINEERING_EXCELLENCE": [],
"INDUSTRIAL_DESIGN": [],
"INNOVATION_IN_CONTROL": [],
"QUALITY": [],
"ENTREPRENEURSHIP": [],
from functions import getTBAdata
import traceback
years = range(2010, 2020)
data = {y: [0] * 8 for y in years}
for year in years:
print(year)
events = getTBAdata("events/" + str(year))
for event in events:
if event["event_type"] > 5 or len(event["division_keys"]) > 0: continue
alliances = getTBAdata("event/" + event["key"] + "/alliances")
print(event["key"])
if alliances is None: continue
for i, a in enumerate(alliances):
try:
if a["status"] == "unknown": continue
if a["status"]["level"] == "f":
try:
print(i + 1)
data[year][i] += 1
except:
traceback.print_exc()
print(a)
except:
traceback.print_exc()
print(a)
with open("finals.csv", "w+") as file:
file.write("Year," + ",".join([str(x) for x in range(1, 9)]) + "\n")
for year, alliances in data.items():
file.write(str(year) + ",")
import math
from functions import getTBAdata
DPs = {}
with open("DistrictRankings/Ranking Points/world_RP.csv") as file:
allteams = file.readlines()
titles = allteams[0].strip().split(",")
for team in allteams[1:]:
team = team.strip().split(",")
key = ("frc" if team[0][:2] == "frc" else "") + team[0]
DPs[key] = {}
for i, element in enumerate(team[1:], start=1):
DPs[key][titles[i]] = float(element)
event = input("event: ")
teams = getTBAdata("event/" + event + "/teams/keys")
matches = getTBAdata("event/" + event + "/matches/simple")
runs = int(input("Iterations: "))
results = {team: [0] * len(teams) for team in teams}
avg = {team: 0 for team in teams}
match_results = [0] * len(matches)
auto_results = [[0, 0] for i in matches]
climb_results = [[0, 0] for i in matches]
for i in range(runs):
print(i)
ev = {team: [0, 0] for team in teams}
for match in matches:
if match["comp_level"] != "qm": continue
playing = match["alliances"]["red"]["team_keys"] + match["alliances"][
"blue"]["team_keys"]
"2019mosl", "2019azfl", "2019flor", "2019mxcm", "2019azpx", "2019flwp",
"2019mxmo", "2019paca", "2019bcvi", "2019hiho", "2019mxto", "2019qcmo",
"2019caav", "2019iacf", "2019ndgf", "2019qcqc", "2019cada", "2019idbo",
"2019nvlv", "2019scmb", "2019cadm", "2019ilch", "2019nyli", "2019tnkn",
"2019cafr", "2019ilpe", "2019nyli2", "2019tuis", "2019cala", "2019ksla",
"2019nyny", "2019tuis2", "2019caln", "2019lake", "2019nyro", "2019utwv",
"2019camb", "2019mndu", "2019nysu", "2019wila", "2019caoc", "2019mndu2",
"2019nytr", "2019wimi"
]
districts = [
"2019chs", "2019fim", "2019fnc", "2019in", "2019isr", "2019ne", "2019pch",
"2019pnw", "2019tx", "2019ont", "2019fma"
]
for event in regionals:
teams = getTBAdata("event/" + event + "/teams/keys")
ranked = []
for t in teams:
try:
ranked.append((t, allteams[t]))
except:
ranked.append((t, 0))
ranked = sorted(ranked, key=lambda x: x[1], reverse=True)
print(event)
picks[event] = ranked
for district in districts:
teams = getTBAdata("district/" + district + "/teams/keys")
ranked = []
for t in teams:
try:
from functions import getTBAdata
import csv
from scipy.stats.mstats import gmean
from numpy import std
dps = {}
with open("DistrictRankings/YearlyPredictor/data_award.csv") as file:
reader = csv.DictReader(file)
for row in reader:
dps[row["Team"]] = float(row["Avg"])
scores = []
events = getTBAdata("events/2019/keys")
for event in events:
print(event)
teams = getTBAdata("event/" + event + "/teams/keys")
if len(teams) < 2: continue
localdps = [dps[t] if t in dps and dps[t]!=0 else 1 for t in teams]
scores.append((event, gmean(localdps), std(localdps)))
scores = sorted(scores, key=lambda x:x[1]/x[2], reverse=True)
with open("DistrictRankings/YearlyPredictor/ranked_events.csv", "w+") as file:
file.write("Event,Mean,StDev,Score\n")
for e in scores:
file.write(e[0] + "," + str(e[1]) + "," + str(e[2]) + "," + str(e[1]/e[2]) + "\n")
from functions import getTBAdata
data = {}
events = getTBAdata("events/2018/simple")
for event in events:
if event["event_type"] > 0: continue
print(event["key"])
DPs = getTBAdata("event/" + event["key"] + "/district_points")["points"]
statuses = getTBAdata("event/" + event["key"] + "/teams/statuses")
ranking = []
for teamKey, dp in DPs.items():
try:
alliance = {"alliance":statuses[teamKey]["alliance"]["number"], "pick":statuses[teamKey]["alliance"]["pick"]+1}
except:
alliance = {"alliance":-1, "pick":-1}
if dp["award_points"]<10:
ranking.append({"key":teamKey, "DP":dp, "qual":statuses[teamKey]["qual"]["ranking"]["rank"], "alliance":alliance})
ranking.sort(key=lambda x:(x["DP"]["total"],
x["DP"]["elim_points"],
x["DP"]["alliance_points"],
x["DP"]["qual_points"]),reverse=True)
data[event["key"]] = ranking
with open("DistrictRankings/RegionalDistribution/regionals.csv", "w+") as file:
file.write("Event,Team,DP Rank,Qual Rank,Alliance #,Alliance Pick,Qual DP,Alliance DP,Playoff DP,Awards DP,Total DP\n")
for event, ranking in data.items():
for i, team in enumerate(ranking, start=1):
file.write(event + "," +
team["key"] + "," +
str(i) + "," +
str(team["qual"]) + "," +
import tkinter as tk
from tkinter import filedialog
from operator import itemgetter
from functions import getTBAdata
DPs = {}
tk.Tk().withdraw()
with open(filedialog.askopenfilename()) as file:
allteams = file.readlines()
titles = allteams[0].strip().split(",")
for team in allteams[1:]:
team = team.strip().split(",")
DPs["frc" + team[0]] = {}
for i, element in enumerate(team[1:], start=1):
DPs["frc" + team[0]][titles[i]] = element
teams = []
competing = getTBAdata("event/" + input("Event Key: ") + "/teams/keys")
for team in competing:
teams.append((team, float(DPs[team]["AdjDP"])))
teams = sorted(teams, key=itemgetter(1), reverse=True)
print(teams)
team = team.strip().split(",")
teams[team[0]] = (float(team[1]), float(team[2]))
m = Basemap(projection='mill',
llcrnrlon=-130,
llcrnrlat=15,
urcrnrlon=-66,
urcrnrlat=55)
# m = Basemap(projection='merc',llcrnrlat=-60,urcrnrlat=80,llcrnrlon=-180,urcrnrlon=180)
m.drawcoastlines()
m.drawmapboundary(fill_color='gray')
m.fillcontinents(color='white', zorder=0)
m.drawcountries(linewidth=1.2)
m.drawstates(linewidth=.3)
events = getTBAdata("events/2018")
for event in events:
if event["event_type"] > 2: continue
print(event["key"])
# color = ["red", "blue", "#38b9ff"][event["event_type"]]
color = [
"#ff4444", "#33ffff", "#f3ae09", "#68a429", "#6b3232", "#727211",
"#33ccff"
][event["week"]]
# color = "purple"
teamkeys = getTBAdata("event/" + event["key"] + "/teams/keys")
for teamkey in teamkeys:
try:
m.drawgreatcircle(teams[teamkey[3:]][1],
teams[teamkey[3:]][0],
from functions import getTBAdata
teams = {}
events = getTBAdata("events/2018/simple")
for event in events:
if event["event_type"] <= 5:
print(event["key"])
matches = getTBAdata("event/" + event["key"] + "/matches")
for match in matches:
if match["comp_level"] == "qm":
for alliance in ["blue", "red"]:
for team in match["alliances"][alliance]["team_keys"]:
if team not in teams: teams[team] = [0, 0, 0, 0]
teams[team][0] += 1
teams[team][1] += 2 if match[
"winning_alliance"] == alliance else 0
teams[team][2] += 1 if match["score_breakdown"][
alliance]["autoQuestRankingPoint"] else 0
teams[team][3] += 1 if match["score_breakdown"][
alliance]["faceTheBossRankingPoint"] else 0
with open("world_RP.csv", "w+") as file:
file.write("Team,Avg Win RP,Adj Auto RP,Avg Climb RP\n")
for team in teams:
file.write(team + "," + str(teams[team][1] / teams[team][0]) + "," +
str(teams[team][2] / teams[team][0]) + "," +
str(teams[team][3] / teams[team][0]) + "\n")
from functions import getTBAdata
file = open("champs_ranking.csv", "w+")
file.write("Team #,DP,DivDP,OPR,CCWM,Region\n")
for event, cmp in ([
"carv", "gal", "hop", "new", "roe", "tur", "arc", "cars", "cur", "dal",
"dar", "tes"
], ["tx"] * 6 + ["mi"] * 6):
print(event)
teams = getTBAdata("event/2018" + event + "/district_points")["points"]
metrics = getTBAdata("2018" + event + "/oprs")
for teamKey in teams:
DP = teams[teamKey]["total"]
try:
if getTBAdata("team/" + teamKey + "/event/2018" + event +
"/status")["playoff"]["status"] == "won":
print("einstein! " + str(DP))
einstein_matches = getTBAdata("team/" + teamKey +
"/event/2018cmp" + cmp +
"/matches")
for match in einstein_matches:
DP += 5 if (
teamKey in match["alliances"]["blue"]["team_keys"]
) != (match['winning_alliance'] == "red") else 0
einstein_awards = getTBAdata("team/" + teamKey +
"/event/2018cmp" + cmp +
"/awards")
for award in einstein_awards:
DP += 12 if award["award_type"] == 0 else 10 if award[
"award_type"] == 69 else 0
except: