def _read_frame(self, signo = -1):
#---------------------------------
if signo < 0 or signo in self.data_signals:
v = wfdb.WFDB_SampleArray(self._framesize)
while wfdb.getframe(v.cast()) == self._nsignals:
if signo < 0: yield [v[i] for i in xrange(self._framesize) if self._sigpoints[i]]
else: yield [v[i] for i in xrange(*self._offsets[n])]
def read(self, interval=None, segment=None, maxduration=None, maxpoints=None):
#----------------------------------------------------------------------------
"""
Read data from a Signal.
:param interval: The portion of the signal to read.
:type interval: :class:`~biosignaml.time.Interval`
:param segment: A 2-tuple with start and finishing data indices, with the end
point not included in the returned range.
:param maxduration: The maximum duration, in seconds, of a single returned segment.
:param maxpoints: The maximum length, in samples, of a single returned segment.
:return: An `iterator` returning :class:`~biosignalml.data.DataSegment` segments
of the signal data.
If both ``maxduration`` and ``maxpoints`` are given their minimum value is used.
"""
## Read is of a record's vector/frame...
## So check state of rec.vector or rec.frame and reposition record as needs be...
## Ideally read frame into 2D np.array and take appropriate slice when
## creating TimeSeries...
if interval is not None and segment is not None:
raise Exception("'interval' and 'segment' cannot both be specified")
if maxduration:
pts = int(self.rate*maxduration + 0.5)
if maxpoints: maxpoints = min(maxpoints, pts)
else: maxpoints = pts
if maxpoints is None or not (0 < maxpoints <= BSMLSignal.MAXPOINTS):
maxpoints = BSMLSignal.MAXPOINTS
# We need to be consistent as to what an interval is....
# Use model.Interval ??
if interval is not None:
segment = (self.rate*interval.start, self.rate*(interval.start+interval.duration))
if segment is None:
startpos = 0
length = len(self)
else:
if segment[0] <= segment[1]: seg = segment
else: seg = (segment[1], segment[0])
startpos = max(0, int(math.floor(seg[0])))
length = min(len(self), int(math.ceil(seg[1])) - startpos)
# Setup offsets into frame for each signal
siginfo = self._record._siginfo
offsets = [ (0, siginfo[0].spf) ] ## This is record wide data...
samplesperframe = siginfo[0].spf
for s in xrange(1, self._record._nsignals):
offsets.append((samplesperframe, siginfo[s].spf))
samplesperframe += siginfo[s].spf
v = wfdb.WFDB_SampleArray(samplesperframe)
s = self._signum
while length > 0:
if maxpoints > length: maxpoints = length
d = []
i = maxpoints
rpos = startpos
while i > 0:
global _WFDBLock
with _WFDBLock:
wfdb.tnextvec(s, rpos)
r = wfdb.getframe(v.cast())
if r <= 0: i = 0
else:
for n in xrange(offsets[s][0], offsets[s][0]+offsets[s][1]):
d.append(v[n])
i -= 1
rpos += 1
data = (np.array(d)-self._baseline)/self._gain
if len(data) <= 0: break
yield DataSegment(float(startpos)/self.rate, UniformTimeSeries(data, self.rate))
startpos += len(data)
length -= len(data)
