signal = np.zeros(N) # vektor dolžine N, kamor se shranjujejo vzorci
flag = False # flag to notify when vector signal is filled with samples
previousBOOL = False # na začetku je roka odprta - RMS signala je pod EMG_mejo
##################################
#print(plt.style.available)
##plt.style.use('/Users/iripuga/Documents/1.Delo/404/_bci_/BCI-Robotska-Roka/pythonCode/stylelib/bci-style.mplstyle')
# Uvoz podatkov
altfile = 'a-very-light-test.txt'
option = 'stream' #input("Read .txt file or start stream? Type 'txt' or 'stream' >> ")
print('option >>>', option)
if option == 'txt':
"""Read a multi-channel time series from file."""
nepopkolan = bci.importData(option) #uvozi offline podatke
data = np.array(bci.popcol(nepopkolan, 8)) #rešimo se stolpca z datumom - data je že numpy array
data = data[0, :, :] #3D matriko damo v 2D
print('Velikost numpy podatkovnega polja:', data.shape)
samples = data.shape[0]
x = np.arange(0, samples, 1)
print(x.shape)
# podatki
y1 = data[:, 1] # [vrstica, stolpec]
y2 = data[:, 2]
y3 = data[:, 3]
y4 = data[:, 4]
ax = data[:, 5]
N = 200 * 5
# sample spacing
toleranca = 0.01 # Med 0 in 1 - določa kakšna odstopanja od EMG_meje spremenijo bool vrednost
i = 0 # iterator za posodabljanje vzorcev v vektorju signal
#signal = np.zeros(N) # vektor dolžine N, kamor se shranjujejo vzorci
flag = False # flag to notify when vector signal is filled with samples
previousBOOL = False # na začetku je roka odprta - RMS signala je pod EMG_mejo
#initialize Serial connection
serial = roka.initializeServo()
#Acquire data
matrika = []
N_min = 0
N_max = N
podatki, knjiznica = bci.importData("txt")
size = knjiznica["EXG Channel 0"].size
for i in range(int(size / N)):
moc = (plot.PowerFromTxt(200, 1.0, 50.0, 35.0, N_min, N_max, knjiznica))
N_min = N_max
N_max = N_max + N
matrika.append(moc)
if (moc < 5.0):
roka.sendData("120,120,120,120,120", serial)
print("relax")
elif moc < 30.0:
roka.sendData("60,60,60,60,60", serial)
print("medium")
else:
roka.sendData("40,30,30,30,30", serial)
print("contracted")
def plotGraphFromTxt(Fs, low, high, Q, N_min, N_max):
# Sample rate and desired cutoff frequencies (in Hz).
fs = Fs
lowcut = low
highcut = high
f0 = 50.0 # Frequency to be removed from signal (Hz)
Q = Q # Quality factor
w0 = f0 / (Fs / 2) # Normalized Frequency
# Design notch filter
b, a = signal.iirnotch(w0, Q)
zi = signal.lfilter_zi(b, a)
#Import data
podatki, knjiznica = bci.importData("txt")
podatki = knjiznica["EXG Channel 0"]
podatki = podatki[N_min:N_max]
#print(podatki)
#Initialize plot diagram
#plt.xkcd()
fig, (ax_orig, ax_fft, ax_fft_bandpassFilters,
ax_fft_filtfilt) = plt.subplots(4, 1)
N = podatki.size
T = 1.0 / Fs
x = np.linspace(
0.0, N, N
) #preposto razporedim vse vzorce po času (kar je prb 48 min + 60s + 200Hz = 576000, kar je skor realna številka ki je 576178
ax_orig.plot(x, podatki)
ax_orig.set_title('Original Signal')
y = fft(podatki)
x = np.linspace(0.0, 100, N // 2)
ax_fft.plot(x, 2.0 / N * np.abs(y[0:N // 2]))
ax_fft.set_title('FFT Signal (not filtered)')
ax_fft.grid()
ax_fft.set_xlim([-5, 60])
xn = podatki #lahko bi isto naredil sfp.ifft(y) pa bi bil na istem
#Bandpass filter, da se znebiš motenj pri nizkih in visokih frekvencah
y = fft(butter_bandpass_filter(sfp.ifft(y), lowcut, highcut, fs, order=6))
x = np.linspace(0.0, 100, N // 2)
ax_fft_bandpassFilters.plot(x, 2.0 / N * np.abs(y[0:N // 2]))
ax_fft_bandpassFilters.set_title('FFT Signal bandpass filter')
ax_fft_bandpassFilters.grid()
ax_fft_bandpassFilters.set_xlim([-5, 60])
#Notch filter da se znebiš 50Hz motnje (ki jo dobiš iz omrežne frekvence/napetosti/elektrike)
y = fft(signal.filtfilt(b, a, xn))
y = fft(butter_bandpass_filter(sfp.ifft(y), lowcut, highcut, fs, order=6))
x = np.linspace(0.0, 100, N // 2)
ax_fft_filtfilt.plot(x, 2.0 / N * np.abs(y[0:N // 2]))
ax_fft_filtfilt.set_title('FFT Signal w/ notch and bandpass filter')
ax_fft_filtfilt.grid()
ax_fft_filtfilt.set_xlim([-5, 60])
y_fft = y
y = sfp.ifft(
y) #da iz frekvenčnega prostora prideš nazaj v časovni prostor
f, Pxx = signal.periodogram(y, fs=fs, return_onesided=False)
#print("f = ",f)
#print("Pxx = ",Pxx)
#print(len(f))
#plt.xkcd()
plt.figure(num=2)
#plt.xlim([0, 50])
plt.plot(f, Pxx) #močnostni diagram
plt.xlabel('frequency [Hz]')
plt.ylabel('PSD [V**2/Hz]')
plt.show()
return y, f, Pxx