def setUp(self):
# Init
self.Signal = plux.loadbpf("../signals/bvp.txt")
self.Signal = self.Signal[:, 3]
self.SamplingRate = float(Signal.header['SamplingFrequency'])
self.DataFolder = r'../signals/bvp'
self.Benchmark = 0
fname = os.path.split(fpath)[1]
# map file name to a subject
subId = db.subjects.get({'field': 'value'},
{'_id': 1})['docList'][0]['_id']
# create record
recId = db.records.add({
'experiment': '',
'subject': subId,
'supervisor': '',
'date': ''
})['recordId']
# load data
data = plux.loadbpf(fpath)
# add data
dataType = ''
metadata = {
'device': {
'name': '',
'channels': [0, 1],
'Vcc': data.header['Vcc'],
'version': data.header['Version']
},
'transducer': '',
'placement': '',
'units': {
'time': 'second',
'sensor': data.header['Units']
def setUp(self):
# Init
self.Signal = plux.loadbpf("../signals/resp.txt")
self.Signal = self.Signal[:, 3]
self.SamplingRate = float(Signal.header['SamplingFrequency'])
def testfeatures(self):
# Test if a dict is returned by the features function
self.res = features(Signal=self.Signal,
SamplingRate=self.SamplingRate)
assert type(
self.res
) is dict, "Returned value by the features function is not a dict."
# Test if the right exception is raised when no input signal is given
self.assertRaises(TypeError, features, None)
# ...
# ...
# Example:
# Load Data
RawSignal = plux.loadbpf("../signals/resp.txt")
RawSignal = RawSignal[:, 3]
SamplingRate = float(RawSignal.header['SamplingFrequency'])
# Unit conversion
RawSignal = RawSignal.toV()
# Filter
Signal = filt(Signal=RawSignal)['Signal'] #*losing bparray information
# Convert to bparray
Signal = plux.bparray(Signal, RawSignal.header)
# Time array
Time = np.linspace(0, len(Signal) / SamplingRate, len(Signal))
# Beat information
res = resp(Signal=Signal, SamplingRate=SamplingRate)
# Plot
fig = pl.figure()
ax = fig.add_subplot(111)
def testfeatures(self):
# Test if a dict is returned by the features function
self.res = features(Signal=self.Signal,
SamplingRate=self.SamplingRate)
assert type(
self.res
) is dict, "Returned value by the features function is not a dict."
# Test if the right exception is raised when no input signal is given
self.assertRaises(TypeError, features, None)
# ...
# ...
# Example:
# Load Data
RawSignal = plux.loadbpf("../signals/ecg.txt")
RawSignal = RawSignal[:, 3]
SamplingRate = float(RawSignal.header['SamplingFrequency'])
# Unit conversion
RawSignal = RawSignal.tomV()
# Filter
Signal = filt(Signal=RawSignal,
SamplingRate=SamplingRate,
UpperCutoff=30.0,
LowerCutoff=0.5)['Signal'] #*losing bparray information
# Convert to bparray
Signal = plux.bparray(Signal, RawSignal.header)
# Time array
Time = scipy.linspace(0, len(Signal) / SamplingRate, len(Signal))
# Beat information
res = ecg(Signal=Signal, SamplingRate=SamplingRate)
def cvp_files2db(config, datapath=r"Y:\\data\\CVP"):
# connect to DB
db = biomesh.biomesh(**config)
# add the experiments
db.experiments.add({
'name':
'T1',
'goals':
'ECG acquisition.',
'description':
'First session; ECG acquired from hands, in recumbent and sitting positions.'
})
db.experiments.add({
'name':
'T2',
'goals':
'ECG acquisition.',
'description':
'Second session; ECG acquired from hands, in recumbent and sitting positions.'
})
user_file_dict = {}
# add subjects
filename = '\\Lista de Participantes %s.xls'
for experiment in ['Cardiopneumologia', 'Enfermagem', 'Fisioterapia']:
# print experiment
if experiment == 'Cardiopneumologia': idx = 0
else: idx = -1
#add subjects
wb = xlrd.open_workbook(datapath + filename % experiment)
sheet = wb.sheet_by_index(0)
for rownum in range(1, sheet.nrows):
# 'N Aluno', 'Sexo', 'Nome', 'D.N.', 'Altura (cm)', 'Peso (Kg)', \
# 'Raca', 'E-Mail*', 'Telemovel*', 'Desporto', 'Desporto (2o teste)',\
# '1o teste Sentado', '1o teste Deitado', '2o Teste Sentado', '2o teste Deitado'
# print sheet.row_values(rownum), len(sheet.row_values(rownum))
birthdate = sheet.cell_value(rownum, 3)
year, month, day, hour, minute, sec = xlrd.xldate_as_tuple(
birthdate, wb.datemode)
birthdate = datetime.datetime(year, month, day, hour, minute,
sec).isoformat()
name = sheet.cell_value(rownum, 2)
gender = sheet.cell_value(rownum, 1)
fname1, fname2, fname3, fname4 = sheet.cell_value(
rownum, 11 +
idx), sheet.cell_value(rownum, 12 + idx), sheet.cell_value(
rownum, 13 + idx), sheet.cell_value(rownum, 14 + idx)
# MISSING FILEs
aux = numpy.array(
map(lambda pat: fname1.find(pat), [
'F2851', 'F2847', 'F2825', 'F2826', 'F2828', 'F2845',
'F2871', 'F2908'
]))
if numpy.any(aux >= 0):
print "skipped %s" % fname1
continue
ext = '.txt'
fname1, fname2, fname3, fname4 = fname1 + ext, fname2 + ext, fname3 + ext, fname4 + ext
if gender == 'M':
# print gender, fname1, fname2, fname3, fname4
for timest in ['-T1', '-T2']:
rawdatapath = datapath + '\\' + experiment + '\\' + experiment + timest
ext = '*.txt'
for fname in glob.glob(os.path.join(rawdatapath, ext)):
fsplt = fname.split('\\')[-1]
# print fsplt
# print fname1, fname2, fname3, fname4
if fsplt in [fname1, fname2, fname3, fname4]:
newfname = fname.replace('F', 'M')
try:
os.rename(fname, newfname)
print "corrected %s to %s" % (fname, newfname)
except Exception as e:
# pass
print fname
print e
fname1 = fname1.replace('F', 'M')
fname2 = fname2.replace('F', 'M')
fname3 = fname3.replace('F', 'M')
fname4 = fname4.replace('F', 'M')
info = {
'number': sheet.cell_value(rownum, 0),
'sex': gender,
'name': name,
'birthdate': birthdate,
'heigth': sheet.cell_value(rownum, 4),
'weigth': sheet.cell_value(rownum, 5),
# 'ethnicity': sheet.cell_value(rownum,6),
'email': sheet.cell_value(rownum, 7)
} #,
# 'mobilenr': sheet.cell_value(rownum,8),
# 'sport1': sheet.cell_value(rownum,9),
# 'sport2': sheet.cell_value(rownum,10),
# 'file': {
# '1Sentado': fname1,
# '1Deitado': fname2,
# '2Sentado': fname3,
# '2Deitado': fname4}}
# add the subject
subId = db.subjects.add(info)['subjectId']
# print subId
user_file_dict[str(fname1)] = subId
user_file_dict[str(fname2)] = subId
user_file_dict[str(fname3)] = subId
user_file_dict[str(fname4)] = subId
# add data
for source in ['Cardiopneumologia', 'Enfermagem', 'Fisioterapia']:
for timest in ['-T1', '-T2']:
# data path
rawdatapath = datapath + '\\' + source + '\\' + source + timest
ext = '*' + timest + '*.txt'
for fname in glob.glob(os.path.join(rawdatapath, ext)):
print fname
fsplt = fname.split('\\')[-1]
try:
subId = user_file_dict[fsplt]
except Exception as e:
print "skipped %s" % fname
continue
# Read samples file
data = plux.loadbpf(fname)
data = data[:, 3]
# datetime
date = data.header['StartDateTime'].replace(' ', 'T')
# get record
out = db.records.getAll({
'experiment': timest[1:],
'subject': subId
})['idList']
if len(out) == 0:
recId = db.records.add({
'date': date,
'experiment': timest[1:],
'subject': subId,
'source': source
})['recordId']
else:
recId = out[0]
if 'Deit' in fsplt:
position = 'Recumbent'
elif 'Sent' in fsplt:
position = 'Sitting'
mdata = {
'labels': ['ECG'],
'device': {
'Vcc': data.header['Vcc'],
'version': data.header['Version']
},
'units': {
'time': 'second',
'sensor': data.header['Units']
},
'sampleRate': data.header['SamplingFrequency'],
'resolution': data.header['SamplingResolution']
}
db.records.addSignal(recId, '/ECG/hand/' + position + '/raw',
data, mdata)
# close db
db.close()
import sync
import tools as tls
reload(bvp)
reload(eda)
reload(edafc)
pl.ioff()
fname = '../data/PN11 12.12.txt'
#fname='../data/PN12 13.12.txt'
#fname='../data/PN13 13.12.txt'
print "loading " + fname
Raw = plux.loadbpf(fname)
SamplingRate = 10.
# SamplingRate=20
DownSampling = Raw.header['SamplingFrequency'] / SamplingRate
Data = Raw[::DownSampling, :]
print "switch events"
Switch = sync.step(Raw[:, 1]) #Switch=sync.step(Data[:,1])
Switch['Event'] /= Raw.header['SamplingFrequency'] / SamplingRate
print "eda events"
EDA = eda.scr(Signal=Data[:, 3].touS(),
SamplingRate=SamplingRate,
Filter={'UpperCutoff': 0.05})
# for file in glob.glob(os.path.join(self.DataFolder, '*.txt')):
# self.Signal = plux.loadbpf(file)
# self.Signal = self.Signal[:,3]
# self.SamplingRate = float(Signal.header['SamplingFrequency'])
# self.res = filt(Signal=self.Signal, SamplingRate=self.SamplingRate)
# self.res = pulse(Signal=self.res['Signal'], SamplingRate=self.SamplingRate)
# self.NrBeats =
# if(len(self.res['Onset']) == self.NrBeats):
# self.Benchmark+=1
# # ...
# ...
# ...
# Example:
# Load Data
RawSignal = plux.loadbpf("../signals/bvp.txt")
RawSignal = RawSignal[:, 3]
SamplingRate = float(RawSignal.header['SamplingFrequency'])
# Unit conversion
RawSignal = RawSignal.tomV()
# Filter
Signal = filt(
Signal=RawSignal,
SamplingRate=SamplingRate)['Signal'] #*losing bparray information
# Convert to bparray
Signal = plux.bparray(Signal, RawSignal.header)
# Normalization: 0-1
Signal = (Signal - min(Signal)) / (max(Signal) - min(Signal))
# Time array
Time = np.linspace(0, len(Signal) / SamplingRate, len(Signal))
# Pulse information