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beautified
This commit is contained in:
ltcptgeneral
parent
ef81273d4a
commit
20f082b760
@ -1,7 +1,7 @@
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#Titan Robotics Team 2022: Super Script
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#Written by Arthur Lu & Jacob Levine
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#Notes:
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#setup:
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# Titan Robotics Team 2022: Super Script
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# Written by Arthur Lu & Jacob Levine
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# Notes:
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# setup:
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__version__ = "1.0.6.001"
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@ -43,7 +43,7 @@ __changelog__ = """changelog:
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__author__ = (
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"Arthur Lu <arthurlu@ttic.edu>, "
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"Jacob Levine <jlevine@ttic.edu>,"
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)
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)
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import firebase_admin
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from firebase_admin import credentials
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@ -60,6 +60,7 @@ import time
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import tbarequest as tba
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import csv
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def titanservice():
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print("[OK] loading data")
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@ -67,15 +68,16 @@ def titanservice():
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start = time.time()
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source_dir = 'data'
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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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# supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
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file_list = glob.glob(source_dir + '/*.csv')
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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('scores') or 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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if not (os.path.basename(fn).startswith('scores') or 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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data.append(analysis.load_csv(i))
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#print(files)
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# print(files)
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stats = []
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measure_stats = []
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@ -86,111 +88,113 @@ def titanservice():
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print("[OK] loaded data in " + str(end - start) + " seconds")
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#assumes that team number is in the first column, and that the order of teams is the same across all files
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#unhelpful comment
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for measure in data: #unpacks 3d array into 2ds
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# assumes that team number is in the first column, and that the order of teams is the same across all files
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# unhelpful comment
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for measure in data: # unpacks 3d array into 2ds
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measure_stats = []
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for i in range(len(measure)): #unpacks into specific teams
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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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#ofbest_curve = [None]
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#r2best_curve = [None]
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line = measure[i]
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line = measure[i]
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#print(line)
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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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#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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# 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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# 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)))
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measure_stats.append(teams[i] + list(analysis.basic_stats(
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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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for i in range(len(scores)):
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#print(scores)
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# print(scores)
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ofbest_curve = [None]
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r2best_curve = [None]
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ofbest_curve = [None]
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r2best_curve = [None]
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line = scores[i]
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line = scores[i]
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if len(line) < 4:
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if len(line) < 4:
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nishant.append('no_data')
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nishant.append('no_data')
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continue
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continue
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#print(line)
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# print(line)
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#print(line)
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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(
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eqs, rmss, r2s, overfit, "min_overfit")
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#print(eqs, rmss, r2s, 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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# 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(
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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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# print(r2best_curve)
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z = len(scores[0]) + 1
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nis_num = []
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z = len(scores[0]) + 1
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nis_num = []
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nis_num.append(eval(str(ofbest_curve[0])))
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nis_num.append(eval(str(r2best_curve[0])))
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nis_num.append(eval(str(ofbest_curve[0])))
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nis_num.append(eval(str(r2best_curve[0])))
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nis_num.append((eval(ofbest_curve[0]) + eval(r2best_curve[0])) / 2)
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nis_num.append((eval(ofbest_curve[0]) + eval(r2best_curve[0])) / 2)
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nishant.append(teams[i] + nis_num)
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nishant.append(teams[i] + nis_num)
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json_out = {}
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score_out = {}
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for i in range(len(teams)):
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score_out[str(teams[i][0])] = (nishant[i])
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score_out[str(teams[i][0])] = (nishant[i])
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location = db.collection(u'stats').document(u'stats-noNN')
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for i in range(len(teams)):
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for j in range(len(files)):
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json_out[str(teams[i][0])] = (stats[j][i])
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name = os.path.basename(files[j])
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general_general_stats.document(name).set({'stats':json_out.get(teams[i][0])})
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general_general_stats.document(name).set(
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{'stats': json_out.get(teams[i][0])})
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for i in range(len(teams)):
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nnum = location.collection(teams[i][0]).document(u'nishant_number').set({'nishant':score_out.get(teams[i][0])})
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nnum = location.collection(teams[i][0]).document(
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u'nishant_number').set({'nishant': score_out.get(teams[i][0])})
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def pulldata():
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teams = analysis.load_csv('data/teams.csv')
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scores = []
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for i in range(len(teams)):
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team_scores = []
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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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# print(teams[i][0])
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request_data_object = tba.req_team_matches(
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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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json_data = sorted(json_data, key=lambda k: k.get(
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'actual_time', 0), reverse=False)
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for j in range(len(json_data)):
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if "frc" + teams[i][0] in json_data[j].get('alliances').get('blue').get('team_keys'):
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team_scores.append(json_data[j].get('alliances').get('blue').get('score'))
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team_scores.append(json_data[j].get(
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'alliances').get('blue').get('score'))
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elif "frc" + teams[i][0] in json_data[j].get('alliances').get('red').get('team_keys'):
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team_scores.append(json_data[j].get('alliances').get('red').get('score'))
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team_scores.append(json_data[j].get(
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'alliances').get('red').get('score'))
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scores.append(team_scores)
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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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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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teams = db.collection('data').document(
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'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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reports = db.collection('data').document(
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'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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data = []
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data.append(db.collection('data').document('team-2022').collection("Central 2019").document(
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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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@ -267,11 +281,11 @@ def pulldata():
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#print(full[i][j].get(key).get('teamDBRef')[5:] in list_teams)
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#print(full[i][j].get(key).get('teamDBRef'))
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# print(full[i][j].get(key).get('teamDBRef'))
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#print(list(full[i][j].keys()))
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# print(list(full[i][j].keys()))
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#print(list_teams)
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# print(list_teams)
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if full[i][j].get(key).get('teamDBRef')[5:] in list_teams:
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@ -282,7 +296,8 @@ def pulldata():
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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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var[individual_keys[k]] = full[i][j].get(
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key).get(individual_keys[k])
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out.append(var)
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@ -316,7 +331,8 @@ def pulldata():
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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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team_index = list_teams.index(
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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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@ -324,11 +340,12 @@ def pulldata():
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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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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 = csv.writer(file, delimiter=',')
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writer.writerows(big_out[i])
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def service():
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while True:
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@ -347,7 +364,8 @@ def service():
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break
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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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print("[WARNING] failed, trying " +
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str(5 - i - 1) + " more times")
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else:
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print("[ERROR] failed to compute data, skipping")
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fucked = True
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@ -363,10 +381,11 @@ def service():
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print("[OK] waiting: " + str(300 - (end - start)) + " seconds" + "\n")
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time.sleep(300 - (end - start)) #executes once every 5 minutes
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time.sleep(300 - (end - start)) # executes once every 5 minutes
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warnings.simplefilter("ignore")
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#Use a service account
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# Use a service account
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try:
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cred = credentials.Certificate('keys/firebasekey.json')
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except:
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@ -375,5 +394,5 @@ firebase_admin.initialize_app(cred)
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db = firestore.client()
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service() #finally we write something that isn't a function definition
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#titanservice()
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service() # finally we write something that isn't a function definition
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# titanservice()
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@ -1,7 +1,7 @@
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#Titan Robotics Team 2022: Super Script
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#Written by Arthur Lu & Jacob Levine
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#Notes:
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#setup:
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# Titan Robotics Team 2022: Super Script
|
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# Written by Arthur Lu & Jacob Levine
|
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# Notes:
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# setup:
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__version__ = "1.0.6.001"
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@ -38,12 +38,12 @@ __changelog__ = """changelog:
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- added superstructure to code
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1.0.0.000:
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- added import statements (revolutionary)
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"""
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"""
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__author__ = (
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"Arthur Lu <arthurlu@ttic.edu>, "
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"Jacob Levine <jlevine@ttic.edu>,"
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)
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)
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import firebase_admin
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from firebase_admin import credentials
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@ -60,22 +60,24 @@ import time
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import tbarequest as tba
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import csv
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def titanservice():
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print("[OK] loading data")
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start = time.time()
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source_dir = 'data'
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file_list = glob.glob(source_dir + '/*.csv') #supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
|
||||
# supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
|
||||
file_list = glob.glob(source_dir + '/*.csv')
|
||||
data = []
|
||||
files = [fn for fn in glob.glob('data/*.csv')
|
||||
if not (os.path.basename(fn).startswith('scores') or 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
|
||||
files = [fn for fn in glob.glob('data/*.csv')
|
||||
if not (os.path.basename(fn).startswith('scores') or 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))
|
||||
data.append(analysis.load_csv(i))
|
||||
|
||||
#print(files)
|
||||
# print(files)
|
||||
|
||||
stats = []
|
||||
measure_stats = []
|
||||
@ -86,150 +88,158 @@ def titanservice():
|
||||
|
||||
print("[OK] loaded data in " + str(end - start) + " seconds")
|
||||
|
||||
#assumes that team number is in the first column, and that the order of teams is the same across all files
|
||||
#unhelpful comment
|
||||
#for measure in data: #unpacks 3d array into 2ds
|
||||
# assumes that team number is in the first column, and that the order of teams is the same across all files
|
||||
# unhelpful comment
|
||||
# for measure in data: #unpacks 3d array into 2ds
|
||||
|
||||
#measure_stats = []
|
||||
#measure_stats = []
|
||||
|
||||
#for i in range(len(measure)): #unpacks into specific teams
|
||||
# for i in range(len(measure)): #unpacks into specific teams
|
||||
|
||||
#ofbest_curve = [None]
|
||||
#r2best_curve = [None]
|
||||
#ofbest_curve = [None]
|
||||
#r2best_curve = [None]
|
||||
|
||||
#line = measure[i]
|
||||
#line = measure[i]
|
||||
|
||||
#print(line)
|
||||
# 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)
|
||||
#print(eqs, rmss, r2s, overfit)
|
||||
|
||||
#print(ofbest_curve)
|
||||
# ofbest_curve.append(beqs)
|
||||
# ofbest_curve.append(brmss)
|
||||
# ofbest_curve.append(br2s)
|
||||
# ofbest_curve.append(boverfit)
|
||||
# ofbest_curve.pop(0)
|
||||
|
||||
#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
|
||||
# print(ofbest_curve)
|
||||
|
||||
#r2best_curve.append(beqs)
|
||||
#r2best_curve.append(brmss)
|
||||
#r2best_curve.append(br2s)
|
||||
#r2best_curve.append(boverfit)
|
||||
#r2best_curve.pop(0)
|
||||
#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
|
||||
|
||||
#print(r2best_curve)
|
||||
# r2best_curve.append(beqs)
|
||||
# r2best_curve.append(brmss)
|
||||
# r2best_curve.append(br2s)
|
||||
# r2best_curve.append(boverfit)
|
||||
# r2best_curve.pop(0)
|
||||
|
||||
|
||||
#measure_stats.append(teams[i] + list(analysis.basic_stats(line, 0, 0)) + list(analysis.histo_analysis(line, 1, -3, 3)))
|
||||
# print(r2best_curve)
|
||||
|
||||
#stats.append(list(measure_stats))
|
||||
#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 = []
|
||||
|
||||
|
||||
for i in range(len(scores)):
|
||||
|
||||
#print(scores)
|
||||
# print(scores)
|
||||
|
||||
ofbest_curve = [None]
|
||||
r2best_curve = [None]
|
||||
ofbest_curve = [None]
|
||||
r2best_curve = [None]
|
||||
|
||||
line = scores[i]
|
||||
line = scores[i]
|
||||
|
||||
if len(line) < 4:
|
||||
if len(line) < 4:
|
||||
|
||||
nishant.append('no_data')
|
||||
|
||||
continue
|
||||
nishant.append('no_data')
|
||||
|
||||
#print(line)
|
||||
continue
|
||||
|
||||
#print(line)
|
||||
# print(line)
|
||||
|
||||
x = list(range(len(line)))
|
||||
eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
|
||||
# print(line)
|
||||
|
||||
beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
|
||||
x = list(range(len(line)))
|
||||
eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
|
||||
|
||||
#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)
|
||||
beqs, brmss, br2s, boverfit = analysis.select_best_regression(
|
||||
eqs, rmss, r2s, overfit, "min_overfit")
|
||||
|
||||
#print(ofbest_curve)
|
||||
#print(eqs, rmss, r2s, overfit)
|
||||
|
||||
beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
|
||||
ofbest_curve.append(beqs)
|
||||
ofbest_curve.append(brmss)
|
||||
ofbest_curve.append(br2s)
|
||||
ofbest_curve.append(boverfit)
|
||||
ofbest_curve.pop(0)
|
||||
|
||||
r2best_curve.append(beqs)
|
||||
r2best_curve.append(brmss)
|
||||
r2best_curve.append(br2s)
|
||||
r2best_curve.append(boverfit)
|
||||
r2best_curve.pop(0)
|
||||
# print(ofbest_curve)
|
||||
|
||||
#print(r2best_curve)
|
||||
|
||||
z = len(scores[0]) + 1
|
||||
nis_num = []
|
||||
beqs, brmss, br2s, boverfit = analysis.select_best_regression(
|
||||
eqs, rmss, r2s, overfit, "max_r2s")
|
||||
|
||||
nis_num.append(eval(str(ofbest_curve[0])))
|
||||
nis_num.append(eval(str(r2best_curve[0])))
|
||||
r2best_curve.append(beqs)
|
||||
r2best_curve.append(brmss)
|
||||
r2best_curve.append(br2s)
|
||||
r2best_curve.append(boverfit)
|
||||
r2best_curve.pop(0)
|
||||
|
||||
nis_num.append((eval(ofbest_curve[0]) + eval(r2best_curve[0])) / 2)
|
||||
# print(r2best_curve)
|
||||
|
||||
z = len(scores[0]) + 1
|
||||
nis_num = []
|
||||
|
||||
nis_num.append(eval(str(ofbest_curve[0])))
|
||||
nis_num.append(eval(str(r2best_curve[0])))
|
||||
|
||||
nis_num.append((eval(ofbest_curve[0]) + eval(r2best_curve[0])) / 2)
|
||||
|
||||
nishant.append(teams[i] + nis_num)
|
||||
|
||||
nishant.append(teams[i] + nis_num)
|
||||
|
||||
json_out = {}
|
||||
score_out = {}
|
||||
|
||||
for i in range(len(teams)):
|
||||
score_out[str(teams[i][0])] = (nishant[i])
|
||||
score_out[str(teams[i][0])] = (nishant[i])
|
||||
|
||||
location = db.collection(u'stats').document(u'stats-noNN')
|
||||
#for i in range(len(teams)):
|
||||
#general_general_stats = location.collection(teams[i][0])
|
||||
|
||||
#for j in range(len(files)):
|
||||
# json_out[str(teams[i][0])] = (stats[j][i])
|
||||
# name = os.path.basename(files[j])
|
||||
# general_general_stats.document(name).set({'stats':json_out.get(teams[i][0])})
|
||||
# for i in range(len(teams)):
|
||||
#general_general_stats = location.collection(teams[i][0])
|
||||
|
||||
# for j in range(len(files)):
|
||||
# json_out[str(teams[i][0])] = (stats[j][i])
|
||||
# name = os.path.basename(files[j])
|
||||
# general_general_stats.document(name).set({'stats':json_out.get(teams[i][0])})
|
||||
|
||||
for i in range(len(teams)):
|
||||
nnum = location.collection(teams[i][0]).document(u'nishant_number').set({'nishant':score_out.get(teams[i][0])})
|
||||
nnum = location.collection(teams[i][0]).document(
|
||||
u'nishant_number').set({'nishant': score_out.get(teams[i][0])})
|
||||
|
||||
|
||||
def pulldata():
|
||||
teams = analysis.load_csv('data/teams.csv')
|
||||
scores = []
|
||||
for i in range(len(teams)):
|
||||
team_scores = []
|
||||
#print(teams[i][0])
|
||||
request_data_object = tba.req_team_matches(teams[i][0], 2019, "UDvKmPjPRfwwUdDX1JxbmkyecYBJhCtXeyVk9vmO2i7K0Zn4wqQPMfzuEINXJ7e5")
|
||||
# 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)
|
||||
|
||||
json_data = sorted(json_data, key=lambda k: k.get(
|
||||
'actual_time', 0), reverse=False)
|
||||
for j in range(len(json_data)):
|
||||
if "frc" + teams[i][0] in json_data[j].get('alliances').get('blue').get('team_keys'):
|
||||
team_scores.append(json_data[j].get('alliances').get('blue').get('score'))
|
||||
team_scores.append(json_data[j].get(
|
||||
'alliances').get('blue').get('score'))
|
||||
elif "frc" + teams[i][0] in json_data[j].get('alliances').get('red').get('team_keys'):
|
||||
team_scores.append(json_data[j].get('alliances').get('red').get('score'))
|
||||
team_scores.append(json_data[j].get(
|
||||
'alliances').get('red').get('score'))
|
||||
scores.append(team_scores)
|
||||
|
||||
with open("data/scores.csv", "w+", newline = '') as file:
|
||||
writer = csv.writer(file, delimiter = ',')
|
||||
with open("data/scores.csv", "w+", newline='') as file:
|
||||
writer = csv.writer(file, delimiter=',')
|
||||
writer.writerows(scores)
|
||||
|
||||
|
||||
|
||||
def service():
|
||||
|
||||
while True:
|
||||
@ -241,14 +251,15 @@ def service():
|
||||
print("[OK] starting calculations")
|
||||
|
||||
fucked = False
|
||||
|
||||
|
||||
for i in range(0, 5):
|
||||
try:
|
||||
titanservice()
|
||||
break
|
||||
except:
|
||||
if (i != 4):
|
||||
print("[WARNING] failed, trying " + str(5 - i - 1) + " more times")
|
||||
print("[WARNING] failed, trying " +
|
||||
str(5 - i - 1) + " more times")
|
||||
else:
|
||||
print("[ERROR] failed to compute data, skipping")
|
||||
fucked = True
|
||||
@ -259,15 +270,16 @@ def service():
|
||||
break
|
||||
|
||||
else:
|
||||
|
||||
|
||||
print("[OK] finished calculations")
|
||||
|
||||
print("[OK] waiting: " + str(300 - (end - start)) + " seconds" + "\n")
|
||||
|
||||
time.sleep(300 - (end - start)) #executes once every 5 minutes
|
||||
time.sleep(300 - (end - start)) # executes once every 5 minutes
|
||||
|
||||
|
||||
warnings.simplefilter("ignore")
|
||||
#Use a service account
|
||||
# Use a service account
|
||||
try:
|
||||
cred = credentials.Certificate('keys/firebasekey.json')
|
||||
except:
|
||||
@ -276,5 +288,5 @@ firebase_admin.initialize_app(cred)
|
||||
|
||||
db = firestore.client()
|
||||
|
||||
service() #finally we write something that isn't a function definition
|
||||
#titanservice()
|
||||
service() # finally we write something that isn't a function definition
|
||||
# titanservice()
|
||||
|
||||
Loading…
Reference in New Issue
Block a user