def convert2TimeIntervalLst(self):
sem_lst = core.msk2Semlst(self.getYArray(), self.getYArray(), \
self.getTArray())
res = []
for sem in sem_lst:
res.append((sem[0][0], sem[0][-1]))
return res
def applyMaskByName(self, msk_name):
'''Apply mask on signal to get segments of signal'''
msk_seg = self.getMaskByName(msk_name)
if msk_seg != None:
sem_lst = core.msk2Semlst(msk_seg.getYArray(), self.getYArray(), \
self.getTArray())
seg_lst = []
for sem in sem_lst:
seg_lst.append(StrainTimeSeriesSeg(sem, self.getSensorName()))
return seg_lst
else:
return None
def createMeaningfulTimeIntervalLstFromAccel(accel_tss, filter_type = 'threshold_121'):
'''Create meaninful time interval list from accelTimeSeriesSeg data,
the filter is learnt in threhold_121 related method'''
assert isinstance(accel_tss ,sb.AccelTimeSeriesSeg) == True,\
'Must be AccelTimeSeriesSeg type'
meaningful_time_interval_lst = []
data_arr = accel_tss.getYArray()
tag_arr = accel_tss.getTArray()
# Filter data
if filter_type == 'threshold_121':
mask_arr,occ_lst = wf.occFilterThres_seg121(data_arr, tag_arr)
sem_lst = core.msk2Semlst(mask_arr, data_arr, tag_arr)
#create list of AccelTimeSeriesSeg
for sem in sem_lst:
meaningful_time_interval_lst.append([sem[0][0],sem[0][-1]])
return meaningful_time_interval_lst