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https://github.com/titanscouting/tra-analysis.git
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Update superscript.py
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jlevine18
GitHub
parent
75cec13414
commit
bd79ddff6b
@ -67,7 +67,7 @@ def titanservice():
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file_list = glob.glob(source_dir + '/*.csv') #supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
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data = []
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files = [fn for fn in glob.glob('data/*.csv')
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if not (os.path.basename(fn).startswith('teams'))] #scores will be handled sperately
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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
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for i in files:
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data.append(analysis.load_csv(i))
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@ -89,40 +89,44 @@ def titanservice():
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for i in range(len(measure)): #unpacks into specific teams
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ofbest_curve = [None]
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r2best_curve = [None]
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print(i)
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print(measure)
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print(len(measure))
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#ofbest_curve = [None]
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#r2best_curve = [None]
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line = measure[i]
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#print(line)
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x = list(range(len(line)))
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eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
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#x = list(range(len(line)))
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#eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
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beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
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#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
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#print(eqs, rmss, r2s, overfit)
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ofbest_curve.append(beqs)
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ofbest_curve.append(brmss)
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ofbest_curve.append(br2s)
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ofbest_curve.append(boverfit)
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ofbest_curve.pop(0)
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#ofbest_curve.append(beqs)
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#ofbest_curve.append(brmss)
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#ofbest_curve.append(br2s)
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#ofbest_curve.append(boverfit)
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#ofbest_curve.pop(0)
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#print(ofbest_curve)
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beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
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#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
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r2best_curve.append(beqs)
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r2best_curve.append(brmss)
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r2best_curve.append(br2s)
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r2best_curve.append(boverfit)
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r2best_curve.pop(0)
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#r2best_curve.append(beqs)
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#r2best_curve.append(brmss)
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#r2best_curve.append(br2s)
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#r2best_curve.append(boverfit)
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#r2best_curve.pop(0)
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#print(r2best_curve)
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measure_stats.append(teams[i] + list(analysis.basic_stats(line, 0, 0)) + list(analysis.histo_analysis(line, 1, -3, 3)) + ofbest_curve + r2best_curve)
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measure_stats.append(teams[i] + list(analysis.basic_stats(line, 0, 0)) + list(analysis.histo_analysis(line, 1, -3, 3)))
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stats.append(list(measure_stats))
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nishant = []
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@ -197,11 +201,11 @@ def pulldata():
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#print(teams[i][0])
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request_data_object = tba.req_team_matches(teams[i][0], 2019, "UDvKmPjPRfwwUdDX1JxbmkyecYBJhCtXeyVk9vmO2i7K0Zn4wqQPMfzuEINXJ7e5")
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json_data = request_data_object.json()
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for match in range(len(json_data) - 1, -1, -1):
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if json_data[match].get('winning_alliance') == "":
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print(json_data[match])
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#print(json_data[match])
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json_data.remove(json_data[match])
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json_data = sorted(json_data, key=lambda k: k.get('actual_time', 0), reverse=False)
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for j in range(len(json_data)):
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@ -214,6 +218,89 @@ def pulldata():
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with open("data/scores.csv", "w+", newline = '') as file:
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writer = csv.writer(file, delimiter = ',')
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writer.writerows(scores)
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list_teams = teams
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teams=db.collection('data').document('team-2022').collection("Central 2019").get()
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full=[]
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tms=[]
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for team in teams:
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tms.append(team.id)
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reports=db.collection('data').document('team-2022').collection("Central 2019").document(team.id).collection("matches").get()
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for report in reports:
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data=[]
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data.append(db.collection('data').document('team-2022').collection("Central 2019").document(team.id).collection("matches").document(report.id).get().to_dict())
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full.append(data)
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quant_keys = []
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out = []
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var = {}
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for i in range(len(full)):
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for j in range(len(full[i])):
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for key in list(full[i][j].keys()):
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if "Quantitative" in key:
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quant_keys.append(key)
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if full[i][j].get(key).get('teamDBRef')[5:] in list_teams:
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var = {}
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measured_vars = []
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for k in range(len(list(full[i][j].get(key).keys()))):
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individual_keys = list(full[i][j].get(key).keys())
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var[individual_keys[k]] = full[i][j].get(key).get(individual_keys[k])
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out.append(var)
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sorted_out = []
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for i in out:
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j_list = []
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key_list = []
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sorted_keys = sorted(i.keys())
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for j in sorted_keys:
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key_list.append(i[j])
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j_list.append(j)
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sorted_out.append(key_list)
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var_index = 0
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team_index = 0
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big_out = []
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for j in range(len(i)):
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big_out.append([])
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for t in range(len(list_teams)):
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big_out[j].append([])
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for i in sorted_out:
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team_index = list_teams.index(sorted_out[sorted_out.index(i)][j_list.index('teamDBRef')][5:])
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for j in range(len(i)):
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big_out[j][team_index].append(i[j])
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for i in range(len(big_out)):
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with open('data/' + j_list[i] + '.csv', "w+", newline = '') as file:
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writer = csv.writer(file, delimiter = ',')
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writer.writerows(big_out[i])
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def service():
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@ -228,10 +315,10 @@ def service():
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fucked = False
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for i in range(0, 5):
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try:
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#try:
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titanservice()
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break
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except:
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#except:
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if (i != 4):
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print("[WARNING] failed, trying " + str(5 - i - 1) + " more times")
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else:
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