from spectralc1 import spectral
import h5py
with h5py.File('C:/Users/Olivier/Downloads/D4.mat', 'r') as file:
y = list(file['D'])
fs = 3200
y = np.array(y).T
plt.figure()
plt.plot(y)
#plt.plot(t,y)
#plt.xlabel('t(s)')
sp0 = spectral(fs, fs, overlap=0.75, win='hann', averaging='lin', nAverage=50)
#sp1 = spec.spectral(fs, fs*10, overlap=0.75, win='blackman', averaging='lin',nAverage=10)
#sp2 = spec.spectral(fs, fs*10, overlap=0.75, win='flattop', averaging='lin',nAverage=10)
#sp3 = spec.spectral(fs, fs*10, overlap=0.75, win='boxcar', averaging='lin',nAverage=10)
Y0 = []
f = []
i = 0
def cb():
global Y0, f, i
i += 1
Y0, f = sp0.get()
print(np.max(Y0[10:]))
cnt = 0
buffer = collections.deque() #read/outgoing data buffer
buffer2 = collections.deque() #spectrum outgoing data buffer
df = 1 #FFT resolution (s)
fftlines = fs / df
#fft_block_size = fftlines*10 #data block for FFT calculation (set larger than FFT lines to allow averaging)
ntracks = 3
spectrum = []
for i in range(ntracks):
spectrum.append(
spectral(fs,
fftlines,
overlap=0.75,
win='hann',
averaging='lin',
nAverage=10))
def read_from_port(s, appendData, appendData2):
syncB(s, s.read(l_fmt * 2)) #sync data with 2 samples
while True:
if s.inWaiting() > l_fmt * l_packet:
read_byte = s.read(l_fmt * l_packet) #read 0.1 s of data
if read_byte is not None:
appendData(read_byte) #append element to right of buffer
appendData2(read_byte)
time.sleep(0.09) #reduce CPU load
l_fmt = struct.calcsize(fmt)
l_fmt2 = struct.calcsize(fmt2)
stopped = False
cnt = 0
buffer = collections.deque() #read/outgoing data buffer
buffer2 = collections.deque() #spectrum outgoing data buffer
df = 1 #FFT resolution (s)
fftlines = fs/df
ntracks = 3
spectrum = []
for i in range(ntracks):
spectrum.append(spectral(fs, fftlines, overlap=0.75, win='hann', averaging='exp',nAverage=10))
#create hdf5 file
if os.path.exists("file.h5"):
shutil.copy2("file.h5","file_old.h5")
os.remove("file.h5")
file = h5py.File('file.h5')
#timeseries: contains all tracks, raw int16 data (as downloaded)
dsts = file.create_dataset('ts', (ntracks,0), maxshape=(ntracks, None), chunks=(ntracks, l_packet), dtype='i2', compression="lzf")
dsts_cnt = 0
def read_from_port(s, appendData, appendData2):
syncB(s, s.read(l_fmt*2)) #sync data with 2 samples
while True:
if s.inWaiting() > l_fmt*l_packet:
read_byte = s.read(l_fmt*l_packet) #read 0.1 s of data
}
}
#open serial connection with Arduno
try:
ser = serial.Serial(port, baud, timeout=1)
except serial.SerialException:
ser.close()
raise
spectrum = []
for i in range(ntracks):
spectrum.append(
spectral(fs,
fftlines,
overlap=overlap,
win='hann',
averaging='exp',
nAverage=10))
#create hdf5 file
if os.path.exists("file.h5"):
shutil.copy2("file.h5", "file_old.h5")
os.remove("file.h5")
file = h5py.File('file.h5')
#timeseries: contains all tracks, raw int16 data (as downloaded)
dsts = file.create_dataset('ts', (ntracks, 0),
maxshape=(ntracks, None),
chunks=(ntracks, l_packet),
dtype='i2',
compression="lzf")
dsts_cnt = 0