def get_sales_score(competition_name):
results = parse_columns(competition_name + "/sales.tsv")
scores = {}
for car in results:
carNum = car["Car Number"] if "Car Number" in car else car["Car No."]
score = car ['Final Score']
if carNum not in scores or scores[carNum] < float(score):
scores[carNum] = float(score)
return scores
def get_design_score(competition_name):
scores = {}
path_name = competition_name + "/design.tsv"
if not os.path.isfile(path_name):
return scores
results = parse_columns(path_name)
for car in results:
carNum = car["Car Number"] if "Car Number" in car else car["Car No."]
score = car ['Final Score']
scores[carNum] = float(score)
return scores
def get_design_score(competition_name):
scores = {}
path_name = competition_name + "/design.tsv"
if not os.path.isfile(path_name):
return scores
results = parse_columns(path_name)
for car in results:
carNum = car["Car Number"] if "Car Number" in car else car["Car No."]
score = car['Final Score']
scores[carNum] = float(score)
return scores
def get_accel_score(competition_name):
debug = False
worst = 0
best = 1000
results = parse_columns(competition_name + "/accel.tsv")
#first make sure that only each car's best results are represented
corrected_results = {}
for car in results:
time = float(car['Time'])
carNum = car["Car Number"] if "Car Number" in car else car["Car No."]
if carNum in corrected_results:
if corrected_results[carNum] > time and time > 0:
corrected_results[carNum] = time
elif time > 0:
corrected_results[carNum] = time
for time in corrected_results.values():
if time < best:
best = time
if time > worst:
worst = time
#if the slowest car is really slow, there is a floor on the worst time
if worst > 1.5 * best:
worst = 1.5 * best
if debug:
print worst
print best
scores = {}
for carNum in corrected_results.keys():
time = corrected_results[carNum]
if time > worst:
scores[carNum] = 0
else:
score = 75 * (worst - time) / (worst - best)
scores[carNum] = score
if debug:
print scores['35']
return scores
def get_hill_score(competition_name):
max_points = 75
result = {}
scores = parse_columns(competition_name + "/hill.tsv")
#first figure out the scores of those who made it
fastest_complete_time = float("inf")
max_distance = 0
max_distance_no_finish = 0
min_distance_no_finish = float("inf")
for score in scores:
time = float(score["Time"])
if get_distance(score) > max_distance_no_finish:
max_distance_no_finish = get_distance(score)
if get_distance(score) < min_distance_no_finish:
min_distance_no_finish = get_distance(score)
if time > 0 and time < fastest_complete_time:
max_distance = get_distance(score)
fastest_complete_time = time
for score in scores:
time = float(score["Time"])
if time > 0:
car_number = score[
"Car Number"] if "Car Number" in score else score["Car No."]
points = max_points * fastest_complete_time / time
add_better_score(result, points, car_number)
lowest_full_complete_score = float("inf")
for current_points in result.values():
if current_points < lowest_full_complete_score:
lowest_full_complete_score = current_points
#now do everyone else
for score in scores:
car_number = score["Car Number"] if "Car Number" in score else score[
"Car No."]
if max_distance is 0:
points = 75 * (get_distance(score) - min_distance_no_finish) / (
max_distance_no_finish - min_distance_no_finish)
else:
points = lowest_full_complete_score * get_distance(
score) / max_distance
add_better_score(result, points, car_number)
return result
def get_accel_score(competition_name):
debug = False
worst = 0
best = 1000
results = parse_columns(competition_name + "/accel.tsv")
#first make sure that only each car's best results are represented
corrected_results = {}
for car in results:
time = float(car['Time'])
carNum = car["Car Number"] if "Car Number" in car else car["Car No."]
if carNum in corrected_results:
if corrected_results[carNum] > time and time > 0:
corrected_results[carNum] = time
elif time > 0:
corrected_results[carNum] = time
for time in corrected_results.values():
if time < best:
best = time
if time > worst:
worst = time
#if the slowest car is really slow, there is a floor on the worst time
if worst > 1.5 * best:
worst = 1.5 * best
if debug:
print worst
print best
scores = {}
for carNum in corrected_results.keys():
time = corrected_results[carNum]
if time > worst:
scores[carNum] = 0
else:
score = 75 * (worst - time) / (worst - best)
scores[carNum] = score
if debug:
print scores['35']
return scores
def get_cost_score(competition_name):
debug = False
path_name = competition_name + "/cost.tsv"
if not os.path.isfile(path_name):
return {}
results = parse_columns(path_name)
scores = {}
for car in results:
carNum = car["Car Number"] if "Car Number" in car else car["Car No."]
score = car ['Final Score']
scores[carNum] = float(score)
if debug:
print scores['1']
return scores
def get_cost_score(competition_name):
debug = False
path_name = competition_name + "/cost.tsv"
if not os.path.isfile(path_name):
return {}
results = parse_columns(path_name)
scores = {}
for car in results:
carNum = car["Car Number"] if "Car Number" in car else car["Car No."]
score = car['Final Score']
scores[carNum] = float(score)
if debug:
print scores['1']
return scores
def get_hill_score(competition_name):
max_points = 75
result = {}
scores = parse_columns(competition_name + "/hill.tsv")
#first figure out the scores of those who made it
fastest_complete_time = float("inf")
max_distance = 0
max_distance_no_finish = 0
min_distance_no_finish = float("inf")
for score in scores:
time= float(score["Time"])
if get_distance(score) > max_distance_no_finish:
max_distance_no_finish = get_distance(score)
if get_distance(score) < min_distance_no_finish:
min_distance_no_finish = get_distance(score)
if time > 0 and time < fastest_complete_time:
max_distance = get_distance(score)
fastest_complete_time = time
for score in scores:
time= float(score["Time"])
if time > 0:
car_number = score["Car Number"] if "Car Number" in score else score["Car No."]
points = max_points * fastest_complete_time / time
add_better_score(result, points, car_number)
lowest_full_complete_score = float("inf")
for current_points in result.values():
if current_points < lowest_full_complete_score:
lowest_full_complete_score = current_points
#now do everyone else
for score in scores:
car_number = score["Car Number"] if "Car Number" in score else score["Car No."]
if max_distance is 0:
points = 75 * (get_distance(score) - min_distance_no_finish) / (max_distance_no_finish - min_distance_no_finish)
else:
points = lowest_full_complete_score * get_distance(score) / max_distance
add_better_score(result, points, car_number)
return result
def get_manuv_score(competition_name, time_column):
debug = False
worst = 0
best = 1000
results = parse_columns(competition_name + "/manuverability.tsv")
corrected_results = {}
for car in results:
time = float(car[time_column])
carNum = car["Car Number"] if "Car Number" in car else car["Car No."]
if carNum in corrected_results:
if corrected_results[carNum] > time and time > 0:
corrected_results[carNum] = time
elif time > 0:
corrected_results[carNum] = time
for time in corrected_results.values():
if time < best and time > 0:
best = time
if time > worst:
worst = time
if debug:
print worst
print best
if worst > 2.5 * best:
worst = 2.5 * best
scores = {}
for carNum in corrected_results.keys():
time = float(corrected_results[carNum])
if time > worst:
scores[carNum] = 0
else:
ratio = (worst - time) / (worst - best)
scores[carNum] = 75 * ratio
if debug:
print scores['35']
return scores
def get_manuv_score(competition_name, time_column):
debug = False
worst = 0
best = 1000
results = parse_columns(competition_name + "/manuverability.tsv")
corrected_results = {}
for car in results:
time = float(car[time_column])
carNum = car["Car Number"] if "Car Number" in car else car["Car No."]
if carNum in corrected_results:
if corrected_results[carNum] > time and time > 0:
corrected_results[carNum] = time
elif time > 0:
corrected_results[carNum] = time
for time in corrected_results.values():
if time < best and time > 0:
best = time
if time > worst:
worst = time
if debug:
print worst
print best
if worst > 2.5 * best:
worst = 2.5 * best
scores = {}
for carNum in corrected_results.keys():
time = float(corrected_results[carNum])
if time > worst:
scores[carNum] = 0
else :
ratio = (worst-time)/(worst-best)
scores[carNum] = 75*ratio
if debug:
print scores['35']
return scores
def get_st_score(competition_name, time_column):
debug = False
max_points = 75
result = {}
scores = parse_columns(competition_name + "/suspTraction.tsv")
#first figure out the scores of those who made it
fastest_complete_time = float("inf")
max_distance = 0
for score in scores:
time = float(score[time_column])
if time > 0 and time < fastest_complete_time:
max_distance = get_distance(score)
fastest_complete_time = time
if (debug):
print("Fastest complete time: " + str(fastest_complete_time))
print("Max distance: " + str(max_distance))
for score in scores:
time = float(score[time_column])
if time > 0:
car_number = score[
"Car Number"] if "Car Number" in score else score["Car No."]
points = max_points * fastest_complete_time / time
add_better_score(result, points, car_number)
lowest_full_complete_score = float("inf")
for current_points in result.values():
if current_points < lowest_full_complete_score:
lowest_full_complete_score = current_points
if (debug):
print("Lowest complete score: " + str(lowest_full_complete_score))
#now do everyone else
for score in scores:
car_number = score["Car Number"] if "Car Number" in score else score[
"Car No."]
points = lowest_full_complete_score * get_distance(
score) / max_distance
add_better_score(result, points, car_number)
return result
def get_st_score(competition_name, time_column):
debug = False
max_points = 75
result = {}
scores = parse_columns(competition_name + "/suspTraction.tsv")
#first figure out the scores of those who made it
fastest_complete_time = float("inf")
max_distance = 0
for score in scores:
time= float(score[time_column])
if time > 0 and time < fastest_complete_time:
max_distance = get_distance(score)
fastest_complete_time = time
if(debug):
print("Fastest complete time: " + str(fastest_complete_time))
print("Max distance: " + str(max_distance))
for score in scores:
time= float(score[time_column])
if time > 0:
car_number= score["Car Number"] if "Car Number" in score else score["Car No."]
points = max_points * fastest_complete_time / time
add_better_score(result, points, car_number)
lowest_full_complete_score = float("inf")
for current_points in result.values():
if current_points < lowest_full_complete_score:
lowest_full_complete_score = current_points
if(debug):
print("Lowest complete score: " + str(lowest_full_complete_score))
#now do everyone else
for score in scores:
car_number= score["Car Number"] if "Car Number" in score else score["Car No."]
points = lowest_full_complete_score * get_distance(score) / max_distance
add_better_score(result, points, car_number)
return result
def get_endurance_score(competition_name):
debug = False
path_name = competition_name + "/endurance.tsv"
if not os.path.isfile(path_name):
return {}
results = parse_columns(path_name)
scores = {}
max_laps = 0
min_laps = float("inf")
carsOnLeadLap = 0
for car in results:
laps = int(car['# of Laps'])
if laps > max_laps:
max_laps = laps
if laps < min_laps and laps > 0:
min_laps = laps
#figure out bonus points
for car in results:
laps = int(car['# of Laps'])
if laps == max_laps:
carsOnLeadLap += 1
if debug:
print("Number of cars on lead lap: " + str(carsOnLeadLap))
for car in results:
carNum = car["Car Number"] if "Car Number" in car else car["Car No."]
laps = float(car['# of Laps'])
if laps < min_laps:
scores[carNum] = 0
else:
scores[carNum] = 400 * (laps - min_laps) / (
max_laps - min_laps) + calc_bonus(car, carsOnLeadLap)
return scores