alu/tra-analysis
1
0
Fork 0
mirror of https://github.com/titanscouting/tra-analysis.git synced 2024-12-26 09:39:10 +00:00
Code Issues Packages Projects Releases Wiki Activity

lotta bug fixes

Browse Source
This commit is contained in:
ltcptgeneral 2019-03-04 16:38:40 -06:00
parent 67393e0e09
commit ecb6400b06
6 changed files with 77 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

BIN
data analysis/__pycache__/analysis.cpython-37.pyc
View File

Binary file not shown.

BIN
data analysis/__pycache__/titanlearn.cpython-37.pyc
View File

Binary file not shown.

2
data analysis/analysis.py
View File

@ -758,7 +758,7 @@ def optimize_regression(x, y, _range, resolution):#_range in poly regression is
x_test = []
y_test = []
for i in range (0, math.floor(len(x) * 0.4), 1):
for i in range (0, math.floor(len(x) * 0.5), 1):
index = random.randint(0, len(x) - 1)
x_test.append(x[index])

1
data analysis/data/scores.csv Normal file
View File

@ -0,0 +1 @@
2022, 21, 23, 39, 50, 89, 97, 191, 213, 233, 236, 272, 289, 308, 310, 314, 317, 329, 355, 428, 436 2011, 1, 25, 34, 106, 112, 132, 146, 167, 184, 223, 256, 267, 304, 337, 339, 370, 411, 460, 485, 494 1101, 7, 11, 55, 81, 92, 144, 151, 157, 165, 174, 177, 220, 241, 312, 320, 341, 343, 347, 419, 473 821374, 6, 9, 11, 28, 31, 194, 200, 201, 246, 298, 340, 351, 355, 364, 388, 395, 414, 422, 429, 442 5, 33, 73, 102, 103, 137, 183, 200, 212, 218, 242, 249, 264, 294, 302, 310, 378, 400, 408, 457, 473
1 2022 21 23 39 50 89 97 191 213 233 236 272 289 308 310 314 317 329 355 428 436 2011 1 25 34 106 112 132 146 167 184 223 256 267 304 337 339 370 411 460 485 494 1101 7 11 55 81 92 144 151 157 165 174 177 220 241 312 320 341 343 347 419 473 821374 6 9 11 28 31 194 200 201 246 298 340 351 355 364 388 395 414 422 429 442 5 33 73 102 103 137 183 200 212 218 242 249 264 294 302 310 378 400 408 457 473

82
data analysis/superscript.py
View File

@ -41,6 +41,7 @@ import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore
import analysis
import titanlearn
import visualization
import os
import sys
@ -59,7 +60,7 @@ 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')]
if not (os.path.basename(fn).startswith('teams'))] #scores will be handled sperately
for i in files:
data.append(analysis.load_csv(i))
@ -67,6 +68,7 @@ def titanservice():
stats = []
measure_stats = []
teams = analysis.load_csv("data/teams.csv")
scores = analysis.load_csv("data/scores.csv")
end = time.time()
@ -111,19 +113,82 @@ def titanservice():
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)) + ofbest_curve + r2best_curve)
stats.append(list(measure_stats))
json_out = {}
nishant = []
for i in range(len(scores)):
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)
for i in range(len(stats)):
json_out[files[i]]=str(stats[i])
ofbest_curve.append(beqs)
ofbest_curve.append(brmss)
ofbest_curve.append(br2s)
ofbest_curve.append(boverfit)
ofbest_curve.pop(0)
#print(json_out)
#print(ofbest_curve)
db.collection(u'stats').document(u'stats-noNN').set(json_out)
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 = {}
#print(stats)
for i in range(len(teams)):
json_out[str(teams[i][0])] = (stats[0][i])
for i in range(len(teams)):
score_out[str(teams[i][0])] = (nishant[i])
print(json_out)
#print(json_out.get('5'))
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)):
general_general_stats.document(files[j]).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])})
#general_general_stats.collection().document('stats').set()
#db.collection(u'stats').document(u'stats-noNN').set(score_out)
def pulldata():
#TODO
@ -173,3 +238,4 @@ firebase_admin.initialize_app(cred)
db = firestore.client()
service() #finally we write something that isn't a function definition
#titanservice()

2
data analysis/titanlearn.py
View File

@ -198,4 +198,4 @@ def retyuoipufdyu():
model = linear_nn(8, 100, 1, 20, act_fn = "relu")
print(model)
return train_sgd_simple(model,"regression", data, ground, learnrate=1e-4, iters=1000)
retyuoipufdyu()
#retyuoipufdyu()