def __init__(self, record, ID, field):
self.record = record
self.ID = ID
self.field = field
self.fs = field['fs']
curr_date = field['comments'][2]
[curr_dy, curr_mo, curr_yr] = [curr_date[-10:-8], curr_date[-7:-5], curr_date[-4:]]
self.time = Time(int(curr_dy), int(curr_mo), int(curr_yr))
self.time.set_person_ID(self.ID)
SEG_LEN_IN_SEC = .5
seg_len = SEG_LEN_IN_SEC / (1./self.fs)
out = ecg.ecg(signal=self.record, sampling_rate=self.fs, show=False)
ecg_filtered, peaks = out[1], out[2]
USE_FILTERED = True
if USE_FILTERED:
sig_use = ecg_filtered
else:
sig_use = records[i]
segs = mf.get_segs(sig_use, peaks, seg_len, fs=self.fs)
self.segs = np.array(segs)
plt.show()
quit()
#plt.show()
TO_PLOT_PEAKS = False
if TO_PLOT_PEAKS:
ts = np.linspace(0,dt*len(sig_use),len(sig_use))
peak_xs = [x*dt for x in peaks]
peak_ys = [sig_use[x] for x in peaks]
fig = plt.figure(figsize=(8,6))
plt.plot(ts, sig[:,1])
plt.plot(peak_xs, peak_ys, 'ro')
my_funcs.config_plot('Time /s', 'Amplitude /mV')
plt.show()
segs = my_funcs.get_segs(ecg_filtered, peaks, seg_len, fs=fs)
qual_len = int(round(seg_len/1000. * fs)) # len of a complete QRS seg
qual_num = 0
seg_sum = [0] * qual_len
TO_PLOT_SEGS = False
if TO_PLOT_SEGS:
fig = plt.figure(figsize=(8,6))
for seg in segs:
segs_all.append(seg)
if len(seg) == qual_len:
qual_num += 1
print 'The ' + str(rec_ind_look) + '-th record is chosen.'
records = []
one_filename = curr_filenames[rec_ind_look] # One rec has many pulses
filename = one_filename[:-4]
sig, fields = wfdb.rdsamp(filename) #, sampto=1000) #, pbdl=0)
fs = fields['fs']
seg_len = SEG_LEN_IN_SEC / (1. / fs)
sig = np.array(sig)
sig_use = sig[:, channel_ind]
out = ecg.ecg(signal=sig_use, sampling_rate=fs, show=False)
ecg_filtered, peaks = out[1], out[2]
segs = mf.get_segs(sig_use, peaks, seg_len, fs=fs)
sigs_all = [sig[:, 0], sig[:, 1], ecg_filtered]
desp_all = [
'original signal', 'primary filtered signal', 'secondary filtered signal'
]
i = 0
for curr_sig in sigs_all:
fig = plt.figure(figsize=(8, 6))
plt.plot(curr_sig)
mf.config_plot('time', desp_all[i])
plt.show()
curr_segs = mf.get_segs(curr_sig, peaks, seg_len, fs=fs)
fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(10, 8))
j = 0
for ax in axes.flat:
fs = fields['fs']
dt = 1./fs
ann = wfdb.rdann(curr_ID, 'atr')
print ann[0][:5]
print ann[1][:5]
sig_len = 600
ts = np.arange(sig_len)*1./fs
curr_sig = sig[:sig_len, channel]
out = ecg.ecg(signal=curr_sig, sampling_rate=fs, show=False)
ecg_filtered, peaks = out[1], out[2]
seg_len = mf.SEG_LEN_IN_SEC/dt
segs = mf.get_segs(ecg_filtered, peaks, seg_len, fs)
#segs = np.array(segs)
#print segs.shape
#plt.plot(segs[1])
#plt.show()
# Display for looking
def tim2ind(t):
return int(round(t/dt))
## TODO: define a template fitting function, including parameter preparations
R_loc, R_color = peaks[0], 'blue' # color='blue'
plt.scatter(R_loc*dt, 0, color=R_color)
whole_range_ind = range(len(ecg_filtered)) #range(R_loc-50,R_loc+50,1)
whole_range_tim = [x*dt for x in whole_range_ind]
curr_foldername = 'Person_' + curr_ID_str
curr_filenames = glob.glob(curr_foldername + "/*.dat")
j = 0
for one_filename in curr_filenames: # One rec has many pulses
filename = one_filename[:-4]
sig, fields = wfdb.rdsamp(filename)#, sampto=1000) #, pbdl=0)
fs = fields['fs']
sig_use = sig[:,1]
out = ecg.ecg(signal=sig_use, sampling_rate=fs, show=False)
peaks = out[2]
segs = my_funcs.get_segs(sig_use, peaks, seg_len, fs=fs)
qual_len = int(round(seg_len/1000. * fs)) # len of a complete QRS seg
qual_num = 0
seg_sum = [0] * qual_len
for seg in segs:
if len(seg) == qual_len:
qual_num += 1
segs_all.append(seg)
labels_all.append(i)
seg_avg = [x/float(qual_num) for x in seg_sum]
j += 1
ts = np.linspace(0, dt * len(sig_use), len(sig_use))
peak_xs = [x * dt for x in peaks]
peak_ys = [sig_use[x] for x in peaks]
fig = plt.figure(figsize=(8, 6))
plt.plot(ts, sig[:, 1])
plt.plot(peak_xs, peak_ys, 'ro')
my_funcs.config_plot('Time /s', 'Amplitude /mV')
plt.show()
## after all these things, get segs by my own function
## Three options:
# sig[:,0], accuracy 87.8%
# sig[:,1], accuracy 87.8%
# ecg_filtered, accuracy 92.2%
segs = my_funcs.get_segs(sig[:, 0], peaks, seg_len, fs=fs)
qual_len = int(round(seg_len / 1000. *
fs)) # len of a complete QRS seg
qual_num = 0
seg_sum = [0] * qual_len
TO_PLOT_SEGS = False
if TO_PLOT_SEGS:
fig = plt.figure(figsize=(8, 6))
for seg in segs:
segs_all.append(seg)
if len(seg) == qual_len:
qual_num += 1