Python peaks Examples

Example #1

 def test_peaks_cleanecg(self):
     t, s = loadtxt(path + 'cleanecg.txt')
     pr = array([
         20, 87, 156, 225, 291, 355, 418, 482, 550, 624, 694, 764, 834, 905,
         978
     ])
     assert_array_equal(pr, peaks(s, 75))

Example #2

File: processing_tools.py Project: JmdRodrigues/PhDProject

def BigPeaks(s, th, min_peak_distance=5, peak_return_percentage=0.1):
    p = peaks(s, th)
    pp = []
    if len(p) == 0:
        pp = []
    else:
        p = clean_near_peaks(s, p, min_peak_distance)

        if len(p) != 0:
            ars = argsort(s[p])
            pp = p[ars]

            num_peaks_to_return = int(ceil(len(p) * peak_return_percentage))

            pp = pp[-num_peaks_to_return:]
        else:
            pp == []
    return pp

Example #3

File: features.py Project: TSFDlib/TSFEL

def _bigPeaks(s, th, min_peak_distance=5, peak_return_percentage=0.1):
    pp = []
    if not list(s):
        return pp
    else:
        p = ni.peaks(s, th)
        if not list(p):
            return pp
        else:
            p = ni.clean_near_peaks(s, p, min_peak_distance)
            if not list(p):
                return pp
            else:
                ars = np.argsort(s[p])
                pp = p[ars]

                num_peaks_to_return = int(np.ceil(len(p) * peak_return_percentage))

                pp = pp[-num_peaks_to_return:]

            return pp

Example #4

File: ecg_noise_detector.py Project: rezasjourney/ecg_noise_detector

fs = 1000.

t = arange(len(ecg)) / fs
#Para retirar o DC e colocar o referencial na origem
media = mean(ecg)
ecg = ecg - media

subplot(2, 1, 1)
plot(t, ecg)
title('ECG')
xlabel('Time(ms)')
ylabel('ECG(mV)')
grid()

counter = ni.peaks(ecg, 400)

noise = zeros(len(ecg))

noise[min(counter):max(counter)] = 1

subplot(2, 1, 2)
plot(t, noise)
title('ECG NOISE DETECTOR')
xlabel('Time(ms)')
ylabel('Detection')
axis([0, 100, -1, 1.5])
grid()
plt.tight_layout()
show()

Example #5

File: test_peaks.py Project: vilut/novainstrumentation

 def test_peaks_eda(self):
     t, s = loadtxt(path + 'eda.txt')
     pr = array([95, 146, 346])
     assert_array_equal(pr, peaks(s, 600))

Example #6

File: classic.py Project: JmdRodrigues/PhDProject

dnx = np.diff(nx)
dny = np.diff(ny)

# Detection of straight segments
idx = dnx != 0
idy = dny == 0
vals = (idx * idy) + (~idx * ~idy)

figure()
subplot(131)
plot(nx, ny)
scatter(nx[vals], ny[vals], color='r')

# Looping detection
maxs_ny = ni.peaks(ny)
mins_ny = ni.peaks(-ny)

maxs_nx = ni.peaks(nx)
mins_nx = ni.peaks(-nx)

subplot(132)
plot(nx, ny)
scatter(nx[maxs_ny], ny[maxs_ny], color='r')
scatter(nx[mins_ny], ny[mins_ny], color='g')
scatter(nx[maxs_nx], ny[maxs_nx], color='b')
scatter(nx[mins_nx], ny[mins_nx], color='k')

e = hstack([maxs_ny, mins_ny, maxs_nx, mins_nx])
mask = hstack([
    ones(len(maxs_ny)),

Example #7

File: ecg_noise_detector.py Project: luisafialho/ecg_noise_detector

t=arange(len(ecg))/fs
#Para retirar o DC e colocar o referencial na origem
media=mean(ecg)
ecg=ecg-media


subplot(2,1,1)
plot(t, ecg)
title('ECG')
xlabel('Time(ms)')
ylabel('ECG(mV)')
grid()


counter = ni.peaks(ecg,400)

noise=zeros(len(ecg))

noise[min(counter):max(counter)]=1
        
subplot(2,1,2)
plot(t,noise)
title('ECG NOISE DETECTOR')
xlabel('Time(ms)')
ylabel('Detection')
axis([0, 100, -1, 1.5])
grid()
plt.tight_layout() 
show()

Example #8

File: test_peaks.py Project: DFNOsorio/novainstrumentation

 def test_peaks_eda(self):
     t, s = loadtxt(path + 'eda.txt')
     pr = array([95, 146, 346])
     assert_array_equal(pr, peaks(s, 600))

Example #9

File: test_peaks.py Project: DFNOsorio/novainstrumentation

 def test_peaks_cleanecg(self):
     t, s = loadtxt(path + 'cleanecg.txt')
     pr = array([20,  87, 156, 225, 291, 355, 418, 482, 550, 624, 694, 764, 834, 905, 978])
     assert_array_equal(pr, peaks(s, 75))