def shortPR_test():
'''Find more accurate characteristic point position.'''
shortPR_folder = '/home/alex/LabGit/ECG_random_walk/experiments/record_test/shortQT/results0516/'
shortPR_outputfolder = '/home/alex/LabGit/ECG_random_walk/experiments/record_test/shortQT/mcmc_enhanced157_Tonset/'
import glob
files = glob.glob(shortPR_folder + '*.json')
loader = cLoader(2,1)
file_ind = 0
for result_file in files:
recordID = os.path.split(result_file)[-1]
recordID = recordID.split('.')[0]
print 'Processing record: %s' % recordID
file_ind += 1
print '%d records left.' % (len(files) - file_ind)
if os.path.exists(shortPR_outputfolder + '%s.json' % recordID) == True:
continue
sig = loader.loadID(recordID)
with open(result_file, 'r') as fin:
annots = json.load(fin)
annots = post_p(sig, annots, 500)
annots.sort(key = lambda x:x[0])
annots = post_p_mcmc(sig, annots, 500)
with open(shortPR_outputfolder + '%s.json' % recordID, 'w') as fout:
json.dump(annots, fout, indent = 4)
def test1():
'''Testing with changgeng data.'''
from randomwalk.changgengLoader import ECGLoader as cLoader
loader = cLoader(1, 1)
sig = loader.loadID('2259')
tool = PwavePicker()
tool.pick(sig, start_index=0)
pass
def post_p_mcmc_test():
'''Find more accurate characteristic point position.'''
loader = cLoader(2, 1)
recordID = '5395'
sig = loader.loadID(recordID)
with open('./data/tmpWT/%s.json' % recordID, 'r') as fin:
annots = json.load(fin)
annots = post_p(sig, annots, 500)
annots.sort(key=lambda x: x[0])
annots = post_p_mcmc(sig, annots, 500)
fig, ax = plt.subplots(1, 1)
plt.plot(sig)
plotExpertLabels(ax, sig, annots)
plt.show()
def enhance_test():
'''Find more accurate characteristic point position.'''
loader = cLoader(2, 1)
recordID = '54722'
sig = loader.loadID(recordID)
with open('./data/tmpWT/%s.json' % recordID, 'r') as fin:
annots = json.load(fin)
annots = post_p(sig, annots, 500)
annots.sort(key=lambda x: x[0])
x_range_list = list()
x_range_start = None
for ind in xrange(0, len(annots)):
pos, label = annots[ind]
if label == 'Ponset':
x_range_start = pos - 5
elif label == 'Poffset':
if x_range_start is not None:
x_range_list.append((x_range_start, pos + 5))
x_range_start = None
# MCMC testing
for x_range in x_range_list:
figID = recordID + '_x_%d' % x_range[0]
Pannots = map(
lambda x: [x[0] - x_range[0], x[1]],
filter(lambda x: x[0] >= x_range[0] and x[0] <= x_range[1],
annots))
pwave = PWave(sig, fs=500.0)
pwave.detectGaussian(sig[x_range[0]:x_range[1]],
Pannots,
500.0,
savefig_path='./data/%s.png' % figID,
figID=figID)
# pdb.set_trace()
print 'Annotations:'
print Pannots
fig, ax = plt.subplots(1, 1)
plt.plot(sig)
plotExpertLabels(ax, sig, annots)
plt.show()
def enhance_demo():
'''Find more accurate characteristic point position.'''
loader = cLoader(2, 1)
recordID = '54722'
sig = loader.loadID(recordID)
with open('./data/tmpWT/%s.json' % recordID, 'r') as fin:
annots = json.load(fin)
annots = post_p(sig, annots, 500)
x_range = (920, 1010)
Pannots = map(
lambda x: [x[0] - x_range[0], x[1]],
filter(lambda x: x[0] >= x_range[0] and x[0] <= x_range[1], annots))
pwave = PWave(sig, fs=500.0)
pwave.detectGaussian(sig[x_range[0]:x_range[1]], Pannots, 500.0)
print 'Annotations:'
print Pannots
fig, ax = plt.subplots(1, 1)
plt.plot(sig)
plotExpertLabels(ax, sig, annots)
plt.show()