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Update superscript.py

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jlevine18 2019-03-21 16:55:04 -05:00 committed by GitHub
parent 75cec13414
commit bd79ddff6b
1 changed files with 109 additions and 22 deletions
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131
data analysis/superscript.py
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@ -67,7 +67,7 @@ def titanservice():
file_list = glob.glob(source_dir + '/*.csv') #supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
data = []
files = [fn for fn in glob.glob('data/*.csv')
if not (os.path.basename(fn).startswith('teams'))] #scores will be handled sperately
if not (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))
@ -89,40 +89,44 @@ def titanservice():
for i in range(len(measure)): #unpacks into specific teams
ofbest_curve = [None]
r2best_curve = [None]
print(i)
print(measure)
print(len(measure))
#ofbest_curve = [None]
#r2best_curve = [None]
line = measure[i]
#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)
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)
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)
measure_stats.append(teams[i] + list(analysis.basic_stats(line, 0, 0)) + list(analysis.histo_analysis(line, 1, -3, 3)) + ofbest_curve + r2best_curve)
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 = []
@ -197,11 +201,11 @@ def pulldata():
#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)
for j in range(len(json_data)):
@ -214,6 +218,89 @@ def pulldata():
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=[]
for team in teams:
tms.append(team.id)
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())
full.append(data)
quant_keys = []
out = []
var = {}
for i in range(len(full)):
for j in range(len(full[i])):
for key in list(full[i][j].keys()):
if "Quantitative" in key:
quant_keys.append(key)
if full[i][j].get(key).get('teamDBRef')[5:] in list_teams:
var = {}
measured_vars = []
for k in range(len(list(full[i][j].get(key).keys()))):
individual_keys = list(full[i][j].get(key).keys())
var[individual_keys[k]] = full[i][j].get(key).get(individual_keys[k])
out.append(var)
sorted_out = []
for i in out:
j_list = []
key_list = []
sorted_keys = sorted(i.keys())
for j in sorted_keys:
key_list.append(i[j])
j_list.append(j)
sorted_out.append(key_list)
var_index = 0
team_index = 0
big_out = []
for j in range(len(i)):
big_out.append([])
for t in range(len(list_teams)):
big_out[j].append([])
for i in sorted_out:
team_index = list_teams.index(sorted_out[sorted_out.index(i)][j_list.index('teamDBRef')][5:])
for j in range(len(i)):
big_out[j][team_index].append(i[j])
for i in range(len(big_out)):
with open('data/' + j_list[i] + '.csv', "w+", newline = '') as file:
writer = csv.writer(file, delimiter = ',')
writer.writerows(big_out[i])
def service():
@ -228,10 +315,10 @@ def service():
fucked = False
for i in range(0, 5):
try:
#try:
titanservice()
break
except:
#except:
if (i != 4):
print("[WARNING] failed, trying " + str(5 - i - 1) + " more times")
else: