series = {}
for record in RECORDS:
rec = DB_DIR + str(record)
mitr = load_MIT_record(rec)
set_sampling_freq(mitr.frequency)
slen = len(mitr.signal[0])
wlen = int(ms2sp(30 * 60 * 1000))
leads = get_leads(rec)
tmpann = 'tmp'
annotators = []
for lead in leads:
command = ['gqrs', '-r', rec, '-outputName', tmpann, '-s', lead]
subprocess.check_call(command)
annpath = rec + '.' + tmpann
annotators.append(read_annotations(annpath)[1:])
os.remove(annpath)
series[record] = np.array([[a.num for a in ann] for ann in annotators])
for i in range(len(leads)):
series[record][i] = series[record][i] / np.mean(series[record][i])
#bestann = annotators[best_quality_lead(mitr)]
annots = []
i = 0
while i < slen:
wannots = truncate_annotators(annotators, i, i + wlen)
bestann = best_quality_annotator(wannots, i)
annots.extend(
improve_annotations(bestann,
[ann
for ann in wannots if ann is not bestann]))
i += wlen
set_ADCGain(get_gain(args.r))
set_sampling_freq(get_sampling_frequency(args.r))
#The initial evidence is now obtained
if args.a is None:
#A temporary annotations file with the 'gqrs' application is created,
#loaded and immediately removed. We ensure that no collisions occur
#with other annotators.
aname = 0
gqname = 'gq{0:02d}'
rname, ext = os.path.splitext(args.r)
while os.path.exists(rname + '.' + gqname.format(aname)):
aname += 1
command = ['gqrs', '-r', rname, '-outputName', gqname.format(aname)]
subprocess.check_call(command)
annpath = rname + '.' + gqname.format(aname)
annots = read_annotations(annpath)
os.remove(annpath)
else:
rname, ext = os.path.splitext(args.r)
annots = read_annotations(rname + '.' + args.a)
t0 = time.time()
#Conduction or rhythm interpretation
if args.level == 'conduction':
from record_processing import process_record_conduction
length = 512000 if args.l == 0 else args.l
result = process_record_conduction(rname, annots, length, args.f,
args.t, args.exclude_pwaves,
args.exclude_twaves, args.v)
else:
from record_processing import process_record_rhythm
#Merge strategy
DB = '/tmp/mit/'
RECORDS = [
100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 111, 112, 113, 114, 115,
116, 117, 118, 119, 121, 122, 123, 124, 200, 201, 202, 203, 205, 207, 208,
209, 210, 212, 213, 214, 215, 217, 219, 220, 221, 222, 223, 228, 230, 231,
232, 233, 234
]
flut = collections.defaultdict(list)
plt.ioff()
for record in RECORDS:
rpath = DB + str(record)
try:
annots = iter(read_annotations(rpath + '.wbr'))
except IOError:
continue
rec = load_MIT_record(rpath)
while True:
try:
vfon = next(a for a in annots if a.code == ECGCodes.VFON)
vfoff = next(a for a in annots if a.code == ECGCodes.VFOFF)
flut[record].append(rec.signal[:, vfon.time:vfoff.time + 1])
except StopIteration:
break
for i in range(len(flut[record])):
fl = flut[record][i]
for l in (0, 1):
isvf = _is_VF(fl[l])
#FIXME this command only works if the _is_VF function internally
sg = np.sign(np.diff(sigfr))
idx = len(sg) - 1
while idx >= 0 and sg[idx] == sg[-1]:
idx -= 1
pts.append(idx + 1)
ann.time = beg + min(pts)
DB_DIR = '/tmp/mit/'
ORIG_ANNOTATOR = 'atr'
OUT_ANNOTATOR = 'batr'
RECORDS = [
100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 111, 112, 113, 114, 115,
116, 117, 118, 119, 121, 122, 123, 124, 200, 201, 202, 203, 205, 207, 208,
209, 210, 212, 213, 214, 215, 217, 219, 220, 221, 222, 223, 228, 230, 231,
232, 233, 234
]
#RECORDS = [101]
for record in RECORDS:
rec = DB_DIR + str(record)
mitr = load_MIT_record(rec)
set_sampling_freq(mitr.frequency)
slen = len(mitr.signal[0])
annots = read_annotations(rec + '.' + ORIG_ANNOTATOR)
for ann in (a for a in annots if is_qrs_annotation(a)):
move_to_qrs_onset(ann, mitr)
save_annotations(annots, rec + '.' + OUT_ANNOTATOR)
print('Record {0} processed.'.format(record))