Python getTrialList示例

示例#1

def setupClassifier(path):
	l = p.getTrialList(path)
	for x in l:
		features = f.Features(x)
		data.append(features.feature)
		if x.head.target == 'good':
			label.append(1)
		else:
			label.append(0)

示例#2

文件： 2.py 项目： hibazinga/KinectErgonomics

def getTrainingData(path):
	l = p.getTrialList(path)
	for x in l:
		features = f.Features(x)
		data.append(features.feature)
		if x.head.target == 'good' or path[-2] != 'k':
			label.append(1)
		else:
			label.append(0)
	 	print data[-1], label[-1]

示例#3

def getTestingData(path):
	l = p.getTrialList(path)
	for x in l:
		features = f.Features(x, path[-2])
		data_test.append(features.feature)
		if x.head.target == 'good':
			label_test.append(1)
		else:
			label_test.append(0)
	 	print data_test[-1], label_test[-1]

示例#4

文件： 2.py 项目： yanbinren/KinectErgonomics

def getTrainingData(path):
    l = p.getTrialList(path)
    for x in l:
        features = f.Features(x)
        data.append(features.feature)
        if x.head.target == 'good' or path[-2] != 'k':
            label.append(1)
        else:
            label.append(0)
        print data[-1], label[-1]

示例#5

def setupClassifier(path):
    data = []
    label = []
    l = p.getTrialList(path)
    for x in l:
        features = f.Features(x, path[-2])
        data.append(features.feature)
        if x.head.target == 'good':
            label.append(1)
        else:
            label.append(0)
    return knn.knn(data, label)

示例#6

文件： classify.py 项目： hibazinga/KinectErgonomics

def setupClassifier(path):
	data  = []
	label = []
	l = p.getTrialList(path)
	for x in l:
		features = f.Features(x,path[-2])
		data.append(features.feature)
		if x.head.target == 'good':
			label.append(1)
		else:
			label.append(0)
	return knn.knn(data, label)