def base_case_test(self):
"""base_case_test: this test is used to check the function for searching the maximum value -- using artificial data"""
ARRAY_TUPLED = namedtuple(
'ARRAY_TUPLED', 'AXC AYC AZC GXC GYC GZC AVMC GVMC'
' AXT AYT AZT GXT GYT GZT AVMT GVMT ANNOT')
target_list_base = [[[1, 1, 1, 1, 1, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 0]],
[[2, 2, 2, 2, 2, 2, 2, 2, 0],
[2, 2, 2, 2, 2, 2, 2, 2, 2, 0]],
[[3, 3, 3, 3, 3, 3, 3, 3, 2],
[3, 3, 3, 3, 3, 3, 3, 3, 0]]]
source_list = [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2],
[2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2],
[3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2]]
data_pool_base = []
for temp_data in source_list:
source_line = ARRAY_TUPLED(*temp_data)
data_pool_base.append(source_line)
result_list = searchmax.micAn(data_pool_base)
for i in range(len(target_list_base)):
for j in range(len(target_list_base[0])):
temp = target_list_base[0]
for k in range(len(temp)):
self.assertAlmostEqual(target_list_base[i][j][k],
result_list[i][j][k])
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):
"""micro_test: this test is used to check the function for searching the maximum value"""
ARRAY_TUPLED = namedtuple('ARRAY_TUPLED', 'AXC AYC AZC GXC GYC GZC AVMC GVMC'
' AXT AYT AZT GXT GYT GZT AVMT GVMT ANNOT')
data_pool =[]
targetList = [[[0.9398233871,0.1540502688,-0.1714986559,2.5631636763,1.4646649579,-1.4646649579,0.9676834571,
3.2954961553,2],[0.9474754032,0.0440576613,0.2685430108,0.7323324789,-1.8308311974,0.3661662395,
0.9857819566,2.0055750916,0]],
[[0.9261432796,0.1331620968,-0.1741370968,2.9293299158,
2.9293299158,-1.8308311974,0.9517338109,4.5292262456,0],[0.9685012097,0.0307068548,0.2496505376,0.3661662395,
-0.7323324789,0.7323324789,1.0006312483,1.0984987184,2]],
[[0.9179352151,0.1305510753,-0.1926061828,1.0984987184,
5.1263273526,-1.0984987184,0.9469666224,5.3565502887,2],[0.9553600806,0.0146858871,0.2577473118,-0.7323324789,
-1.4646649579,0.7323324789,0.9896273216,1.7938408955,0]]]
rawsourceList = [[0.9398233871,0.1540502688,-0.1714986559,2.5631636763,1.4646649579,-1.4646649579,0.9676834571,3.2954961553,
0.9474754032,0.0440576613,0.2685430108,0.7323324789,-1.8308311974,0.3661662395,0.9857819566,2.0055750916,2],
[0.9261432796,0.1331620968,-0.1741370968,2.9293299158,2.9293299158,-1.8308311974,0.9517338109,4.5292262456,
0.9685012097,0.0307068548,0.2496505376,0.3661662395,-0.7323324789,0.7323324789,1.0006312483,1.0984987184,2],
[0.9179352151,0.1305510753,-0.1926061828,1.0984987184,5.1263273526,-1.0984987184,0.9469666224,5.3565502887,
0.9553600806,0.0146858871,0.2577473118,-0.7323324789,-1.4646649579,0.7323324789,0.9896273216,1.7938408955,2]]
for temp_data in rawsourceList:
sourceList = ARRAY_TUPLED(*temp_data)
data_pool.append(sourceList)
resultList = searchmax.micAn(data_pool)
#self.assertAlmostEqual(targetListnonFalls,sourceListnonFalls)
for i in range(len(targetList)):
for j in range(len(targetList[0])):
temp = targetList[0]
for k in range(len(temp)):
self.assertAlmostEqual(targetList[i][j][k],resultList[i][j][k])
def micro_test(self):
ARRAY_TUPLED = namedtuple('ARRAY_TUPLED', 'AXC AYC AZC GXC GYC GZC AVMC GVMC'
' AXT AYT AZT GXT GYT GZT AVMT GVMT ANNOT')
data_pool =[]
targetList = [[[0.9398233871,0.1540502688,-0.1714986559,2.5631636763,1.4646649579,-1.4646649579,0.9676834571,
3.2954961553,2],[0.9474754032,0.0440576613,0.2685430108,0.7323324789,-1.8308311974,0.3661662395,
0.9857819566,2.0055750916,0]],
[[0.9261432796,0.1331620968,-0.1741370968,2.9293299158,
2.9293299158,-1.8308311974,0.9517338109,4.5292262456,0],[0.9685012097,0.0307068548,0.2496505376,0.3661662395,
-0.7323324789,0.7323324789,1.0006312483,1.0984987184,2]],
[[0.9179352151,0.1305510753,-0.1926061828,1.0984987184,
5.1263273526,-1.0984987184,0.9469666224,5.3565502887,2],[0.9553600806,0.0146858871,0.2577473118,-0.7323324789,
-1.4646649579,0.7323324789,0.9896273216,1.7938408955,0]]]
rawsourceList = [[0.9398233871,0.1540502688,-0.1714986559,2.5631636763,1.4646649579,-1.4646649579,0.9676834571,3.2954961553,
0.9474754032,0.0440576613,0.2685430108,0.7323324789,-1.8308311974,0.3661662395,0.9857819566,2.0055750916,2],
[0.9261432796,0.1331620968,-0.1741370968,2.9293299158,2.9293299158,-1.8308311974,0.9517338109,4.5292262456,
0.9685012097,0.0307068548,0.2496505376,0.3661662395,-0.7323324789,0.7323324789,1.0006312483,1.0984987184,2],
[0.9179352151,0.1305510753,-0.1926061828,1.0984987184,5.1263273526,-1.0984987184,0.9469666224,5.3565502887,
0.9553600806,0.0146858871,0.2577473118,-0.7323324789,-1.4646649579,0.7323324789,0.9896273216,1.7938408955,2]]
for temp_data in rawsourceList:
sourceList = ARRAY_TUPLED(*temp_data)
data_pool.append(sourceList)
resultList = searchmax.micAn(data_pool)
#self.assertAlmostEqual(targetListnonFalls,sourceListnonFalls)
for i in range(len(targetList)):
for j in range(len(targetList[0])):
temp = targetList[0]
for k in range(len(temp)):
self.assertAlmostEqual(targetList[i][j][k],resultList[i][j][k])