Esempio n. 1
0
def heat4():
	from template import Pts4 as HOOP
	HOOP /= 2
	HOOP = HOOP[2]
	route = '../data/heat4.route.npy'
	routes = np.load(route)
	
	team = routes[-1,:,1]
	coord = np.array( map(np.vstack, routes[...,0]))
	m, n, _ = coord.shape
	coord = movingaverage(coord.reshape(-1, 2*n), 10).reshape(m,n,2)
	
	polar = cart2polar(coord.reshape(-1, 2), HOOP).reshape(m,n,2)
	defScore = defenceScore(polar, team)
	pScore = pickScore(polar, team)

	
	sampleData = pickVector(polar,team)
	
	sampleData = np.hstack((sampleData, defVector(polar,team), coord.reshape(-1, 8)))
	#sampleData = defScore[0,:]
	#import ipdb; ipdb.set_trace()
	grammar = PR_tactic4()
	#grammar = pickGrammar()
	#grammar = defGrammar()
	#grammar = blockGrammar()
	model = PCFG(grammar)
	#import ipdb; ipdb.set_trace()
	lik, tree = model.decode(sampleData)
	decodes = []
	for x in tree.BFS():
		#if x[1][0] == x[1][1]:
		decodes.append(x)
	for x in sorted(decodes, key=lambda x:x[1][0]):
		print x
Esempio n. 2
0
def parse(ptables):
	pdict, length, idx = buildTable(ptables)
	#g = grammar()
	#g = sampleGrammar()
	g = grammarWithNA()
	model = PCFG(g)
	#import ipdb; ipdb.set_trace()
	lik, tree = model.ptable(pdict, length)
	#for k, v in model.viterbi_.iteritems():
	#	if not np.isinf(v):
	#		print k, v
	decodes = []
	d = []
	for x in tree.BFS():
		print x
		if isinstance(x[0], Terminal):
			d.append(x)	
	return d
Esempio n. 3
0
def recognition(args):
	from template import Pts4 as HOOP
	import pandas as pd
	hoop = HOOP / 2

	routes = np.load(args['route'])
	#import ipdb; ipdb.set_trace()
	dst = args['dst']
	team = routes[-1,:,1]
	coord = np.array( map(np.vstack, routes[...,0]))
	m, n, _ = coord.shape
	coord = movingaverage(coord.reshape(-1, 2*n), 10).reshape(m,n,2)
	
	if np.mean(coord[...,0]) > 800:
		hoop = hoop[2]
		team = np.logical_not(team)
	else:
		hoop = hoop[0]
	print hoop
	polar = cart2polar(coord.reshape(-1, 2), hoop).reshape(m,n,2)
	
	sampleData = np.hstack((pickVector(polar,team), defVector(polar,team), coord.reshape(-1, 8)))
	grammar = prGrammar()
	model = PCFG(grammar)
	#import ipdb; ipdb.set_trace()
	lik, tree = model.decode(sampleData)
	df = pd.DataFrame(model._dtable)
	df.plot(subplots=True)
	#plt.show()
	
	decodes = []
	for x in tree.BFS():
		if x[1][0] == x[1][1]: 
			decodes.append(x)

	with open(dst, "wb") as csv_file:
		writer = csv.writer(csv_file, delimiter=',')
		for a, (b,c), d, e in sorted(decodes, key=lambda x:x[1][0]):
			writer.writerow([a, b, d, e])