tra-analysis/data analysis/dep/2019/superscript_nishant_only.py

293 lines
7.9 KiB
Python

# Titan Robotics Team 2022: Super Script
# Written by Arthur Lu & Jacob Levine
# Notes:
# setup:
__version__ = "1.0.6.001"
__changelog__ = """changelog:
1.0.6.001:
- fixed multiple bugs
- works now
1.0.6.000:
- added pulldata function
- service now pulls in, computes data, and outputs data as planned
1.0.5.003:
- hotfix: actually pushes data correctly now
1.0.5.002:
- more information given
- performance improvements
1.0.5.001:
- grammar
1.0.5.000:
- service now iterates forever
- ready for production other than pulling json data
1.0.4.001:
- grammar fixes
1.0.4.000:
- actually pushes to firebase
1.0.3.001:
- processes data more efficiently
1.0.3.000:
- actually processes data
1.0.2.000:
- added data reading from folder
- nearly crashed computer reading from 20 GiB of data
1.0.1.000:
- added data reading from file
- added superstructure to code
1.0.0.000:
- added import statements (revolutionary)
"""
__author__ = (
"Arthur Lu <arthurlu@ttic.edu>, "
"Jacob Levine <jlevine@ttic.edu>,"
)
import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore
import analysis
#import titanlearn
import visualization
import os
import sys
import warnings
import glob
import numpy as np
import time
import tbarequest as tba
import csv
def titanservice():
print("[OK] loading data")
start = time.time()
source_dir = 'data'
# 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
for i in files:
data.append(analysis.load_csv(i))
# print(files)
stats = []
measure_stats = []
teams = analysis.load_csv("data/teams.csv")
scores = analysis.load_csv("data/scores.csv")
end = time.time()
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
#measure_stats = []
# for i in range(len(measure)): #unpacks into specific teams
#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)
#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(ofbest_curve)
#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)
# print(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 = []
for i in range(len(scores)):
# print(scores)
ofbest_curve = [None]
r2best_curve = [None]
line = scores[i]
if len(line) < 4:
nishant.append('no_data')
continue
# print(line)
# print(line)
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")
#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(ofbest_curve)
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)
# 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)
json_out = {}
score_out = {}
for i in range(len(teams)):
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)):
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")
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])
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)):
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'))
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'))
scores.append(team_scores)
with open("data/scores.csv", "w+", newline='') as file:
writer = csv.writer(file, delimiter=',')
writer.writerows(scores)
def service():
while True:
pulldata()
start = time.time()
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")
else:
print("[ERROR] failed to compute data, skipping")
fucked = True
end = time.time()
if (fucked == True):
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
warnings.simplefilter("ignore")
# Use a service account
try:
cred = credentials.Certificate('keys/firebasekey.json')
except:
cred = credentials.Certificate('keys/keytemp.json')
firebase_admin.initialize_app(cred)
db = firestore.client()
service() # finally we write something that isn't a function definition
# titanservice()