def readSigfile(self, filename):
""" Load BVP signal.
Must return a 1-dim (row array) signal
"""
gtTrace = []
gtTime = []
gtHR = []
with open(filename, 'r') as f:
x = f.readlines()
s = x[0].split(' ')
s = list(filter(lambda a: a != '', s))
gtTrace = np.array(s).astype(np.float64)
t = x[2].split(' ')
t = list(filter(lambda a: a != '', t))
gtTime = np.array(t).astype(np.float64)
hr = x[1].split(' ')
hr = list(filter(lambda a: a != '', hr))
gtHR = np.array(hr).astype(np.float64)
data = np.array(gtTrace)
time = np.array(gtTime)
self.SIG_SampleRate = np.round(1 / np.mean(np.diff(time)))
return BVPsignal(data, self.SIG_SampleRate)
def readSigfile(self, filename):
"""
Load BVP signal. Must return a 1-dim (row array) signal
"""
tree = ET.parse(filename)
# get all bvp elements and their values
bvp_elements = tree.findall('.//*/value2')
bvp = [int(item.text) for item in bvp_elements]
n_bvp_samples = len(bvp)
last_bvp_time = int((n_bvp_samples * 1000) / self.SIG_SampleRate)
vid_xml_filename = path.join(
path.dirname(filename),
'cv_camera_sensor_timer_stream_handler.xml')
tree = ET.parse(vid_xml_filename)
root = tree.getroot()
last_vid_time = int(float(root[-1].find('value1').text))
diff = ((last_bvp_time - last_vid_time) / 1000)
assert diff >= 0, 'Unusable data.'
print("Skipping %.2f seconds..." % diff)
diff_samples = round(diff * self.SIG_SampleRate)
data = np.array(bvp[diff_samples:])
return BVPsignal(data, self.SIG_SampleRate)
def readSigfile(self, filename):
""" Load BVP signal.
Must return a 1-dim (row array) signal
"""
f = h5py.File(filename, 'r')
data = np.array(f['pulse']) # load the signal
data = data.reshape(1, len(data)) # monodimentional signal
return BVPsignal(data, self.SIG_SampleRate)
def readSigfile(self, filename):
""" Load BVP signal.
Must return a 1-dim (row array) signal
"""
bvp = []
with open(filename) as json_file:
json_data = json.load(json_file)
for p in json_data['/FullPackage']:
bvp.append(p['Value']['waveform'])
data = np.array(bvp)
return BVPsignal(data, self.SIG_SampleRate)
def readSigfile(self, filename):
""" Load BVP signal.
Must return a 1-dim (row array) signal
"""
gtTrace = []
gtTime = []
gtHR = []
with open(filename, 'r') as csvfile:
xmp = csv.reader(csvfile)
for row in xmp:
gtTrace.append(float(row[3]))
gtTime.append(float(row[0]) / 1000.)
gtHR.append(float(row[1]))
data = np.array(gtTrace)
time = np.array(gtTime)
hr = np.array(gtHR)
self.SIG_SampleRate = np.round(1 / np.mean(np.diff(time)))
'''import matplotlib.pyplot as plt
plt.plot(hr)
plt.show()'''
return BVPsignal(data, self.SIG_SampleRate)