def micro_annotate_search(sourceFile):
flag = False
counter = 0
tempData = []
output = []
quemican = deque
ARRAY_TUPLED = namedtuple('ARRAY_TUPLED', 'AXC AYC AZC GXC GYC GZC AVMC GVMC'
' AXT AYT AZT GXT GYT GZT AVMT GVMT DUMMY ANNOT') #change this for OJ's data, add one element before ANNOT
print('start to re-annotate')
print('Please waiting! ....')
with open(sourceFile) as objectFile:
for line in objectFile:
dataread = line.split()
ori_data = [float(x) for x in dataread[:len(dataread)]]
data = ARRAY_TUPLED(*ori_data)
if data.ANNOT in FALL_SET: #change this for OJ's data
tempData.append(data)
if flag == False:
flag = True
elif (flag is True) and (data.ANNOT not in FALL_SET) :
micanDat = searchmax.micAn(tempData) #search for maximum value
for x in range(len(micanDat)):
output.append(micanDat[x])
flag = False
tempData = []
output.append(reannotright.reanotright(data))
else:
saveData = reannotright.reanotright(data)
output.append(saveData)
#write_csv(destFile, output)
return output
print('finish')
def micro_annotate_search(sourceFile):
flag = False
counter = 0
tempData = []
output = []
quemican = deque
ARRAY_TUPLED = namedtuple(
'ARRAY_TUPLED', 'AXC AYC AZC GXC GYC GZC AVMC GVMC'
' AXT AYT AZT GXT GYT GZT AVMT GVMT ANNOT')
print('start to re-annotate')
with open(sourceFile) as objectFile:
for line in objectFile:
dataread = line.split()
ori_data = [float(x) for x in dataread[:len(dataread)]]
data = ARRAY_TUPLED(*ori_data)
if data.ANNOT in FALL_SET: #change this for OJ's data
tempData.append(data)
if not flag:
flag = True
elif flag and (data.ANNOT not in FALL_SET):
micanDat = searchmax.micAn(tempData) #search for maximum value
for x in range(len(micanDat)):
output.append(micanDat[x])
flag = False
tempData = []
output.append(reannotright.reanotright(data))
else:
saveData = reannotright.reanotright(data)
output.append(saveData)
#write_csv(destFile, output)
return output
def micro_test(self):
targetList = [[0.9398233871,0.1540502688,-0.1714986559,2.5631636763,1.4646649579,-1.4646649579,0.9676834571,
3.2954961553,0],[0.9474754032,0.0440576613,0.2685430108,0.7323324789,-1.8308311974,0.3661662395,
0.9857819566,2.0055750916,0]]
sourceList = [0.9398233871,0.1540502688,-0.1714986559,2.5631636763,1.4646649579,-1.4646649579,0.9676834571,
3.2954961553,0.9474754032,0.0440576613,0.2685430108,0.7323324789,-1.8308311974,0.3661662395,
0.9857819566,2.0055750916,0]
resultList = reannotright.reanotright(sourceList)
for i in range(len(targetList)):
for j in range(len(targetList[0])):
self.assertAlmostEqual(targetList[i][j],resultList[i][j])
def micro_nonfall_test(self):
"""micro_nonfall_test: this test is used to check the micro-annotation fucntion for non-fall activities"""
targetList = [[0.9398233871,0.1540502688,-0.1714986559,2.5631636763,1.4646649579,-1.4646649579,0.9676834571,
3.2954961553,0],[0.9474754032,0.0440576613,0.2685430108,0.7323324789,-1.8308311974,0.3661662395,
0.9857819566,2.0055750916,0]]
sourceList = [0.9398233871,0.1540502688,-0.1714986559,2.5631636763,1.4646649579,-1.4646649579,0.9676834571,
3.2954961553,0.9474754032,0.0440576613,0.2685430108,0.7323324789,-1.8308311974,0.3661662395,
0.9857819566,2.0055750916,0]
resultList = reannotright.reanotright(sourceList)
for i in range(len(targetList)):
for j in range(len(targetList[0])):
self.assertAlmostEqual(targetList[i][j],resultList[i][j])