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superscript.py - v 1.0.4.001

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changelog:
- grammar fixes
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ltcptgeneral 2019-02-26 23:18:26 -06:00
parent 2b1dd3ed9b
commit 9b9d6bcd23
2 changed files with 62 additions and 58 deletions
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data analysis/superscript.py
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@ -1,11 +1,13 @@
#Titan Robotics Team 2022: Data Analysis Script #Titan Robotics Team 2022: Super Script
#Written by Arthur Lu & Jacob Levine #Written by Arthur Lu & Jacob Levine
#Notes: #Notes:
#setup: #setup:
__version__ = "1.0.4.000" __version__ = "1.0.4.001"
__changelog__ = """changelog: __changelog__ = """changelog:
1.0.4.001:
- grammar fixes
1.0.4.000: 1.0.4.000:
- actually pushes to firebase - actually pushes to firebase
1.0.3.001: 1.0.3.001:
@ -37,82 +39,84 @@ import os
import glob import glob
import numpy as np import numpy as np
# Use a service account def titanservice():
cred = credentials.Certificate('keys/firebasekey.json')
firebase_admin.initialize_app(cred) # Use a service account
cred = credentials.Certificate('keys/firebasekey.json')
firebase_admin.initialize_app(cred)
db = firestore.client() db = firestore.client()
#get all the data #get all the data
analysis.generate_data("data/bdata.csv", 100, 5, -10, 10) analysis.generate_data("data/bdata.csv", 100, 5, -10, 10)
source_dir = 'data' source_dir = 'data'
file_list = glob.glob(source_dir + '/*.csv') #supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy file_list = glob.glob(source_dir + '/*.csv') #supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
data = [] data = []
files = [fn for fn in glob.glob('data/*.csv') files = [fn for fn in glob.glob('data/*.csv')
if not os.path.basename(fn).startswith('teams')] if not os.path.basename(fn).startswith('teams')]
#for file_path in file_list: #for file_path in file_list:
# if not os.path.basename(file_list).startswith("teams") # if not os.path.basename(file_list).startswith("teams")
# data.append(analysis.load_csv(file_path)) # data.append(analysis.load_csv(file_path))
for i in files: for i in files:
data.append(analysis.load_csv(i)) data.append(analysis.load_csv(i))
stats = [] stats = []
measure_stats = [] measure_stats = []
teams = analysis.load_csv("data/teams.csv") teams = analysis.load_csv("data/teams.csv")
#assumes that team number is in the first column, and that the order of teams is the same across all files #assumes that team number is in the first column, and that the order of teams is the same across all files
#unhelpful comment #unhelpful comment
for measure in data: #unpacks 3d array into 2ds 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] ofbest_curve = [None]
r2best_curve = [None] r2best_curve = [None]
line = measure[i] line = measure[i]
#print(line) #print(line)
x = list(range(len(line))) x = list(range(len(line)))
eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1) 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) #print(eqs, rmss, r2s, overfit)
ofbest_curve.append(beqs) ofbest_curve.append(beqs)
ofbest_curve.append(brmss) ofbest_curve.append(brmss)
ofbest_curve.append(br2s) ofbest_curve.append(br2s)
ofbest_curve.append(boverfit) ofbest_curve.append(boverfit)
ofbest_curve.pop(0) ofbest_curve.pop(0)
#print(ofbest_curve) #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(beqs)
r2best_curve.append(brmss) r2best_curve.append(brmss)
r2best_curve.append(br2s) r2best_curve.append(br2s)
r2best_curve.append(boverfit) r2best_curve.append(boverfit)
r2best_curve.pop(0) r2best_curve.pop(0)
#print(r2best_curve) #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)) + ["|"] + ofbest_curve + ["|"] + r2best_curve)
stats.append(list(measure_stats)) stats.append(list(measure_stats))
json_out = {} json_out = {}
for i in range(len(stats)): for i in range(len(stats)):
json_out[files[i]]=str(stats[i]) json_out[files[i]]=str(stats[i])
print(json_out) print(json_out)
db.collection(u'stats').document(u'stats-noNN').set(json_out) db.collection(u'stats').document(u'stats-noNN').set(json_out)