def data_gen():
#endless loop which gets data
while True:
data = np.zeros(0)
while c.hasSampleAvailable():
sample = c.getSampleFromBuffer()
data = np.append(data, sample[0])
yield data
def data_gen():
#endless loop which gets data
# filter = MyAmazingFilter(...)
while True:
data = np.zeros(0)
while c.hasSampleAvailable():
sample = c.getSampleFromBuffer()
data = np.append(data,sample[0])
# for filtering add here:
# data = filter.dofilter(data)
yield data
def getDataThread(qtPanningPlot1, qtPanningPlot2):
"""
Takes unfiltered data from input and filters out the noise.
"""
# creates stopband filter for 50Hz
scale = 2**11 # scale for input (raw data between -1 and 1)
fs = 250
fc = 50
sos = sig.butter(2, [(fc - 5) / fs * 2, (fc + 5) / fs * 2],
'stop',
output='sos')
filt = IIRFilter(sos)
global data # data collected for future figures
# i and last used to create a time buffer
# used to reduce the number of times each word is printed
# and reduce the influence of the wire noise
i = 0
last = 0
# endless loop with sleeps not for timing but for multitasking
# collects data from input
while running:
# loop as fast as we can to empty the kernel buffer
while c.hasSampleAvailable():
sample = c.getSampleFromBuffer()
sample = sample[channel] * scale # scales input
# filters out 50Hz
sample2 = filt.filter(int(np.round(sample)))
# adds samples to real time graphs
qtPanningPlot1.addData(sample)
qtPanningPlot2.addData(sample2)
# saves unfiltered data for figures later
data.append(sample)
# detects whether the object was pushed or pulled
if sample2 >= 200 and i >= last:
print('PULL')
last = i + 200
elif sample2 <= -100 and i >= last:
print('PUSH')
last = i + 150
else:
i += 1
# let Python do other stuff and sleep a bit
sleep(0.1)
def getDataThread(qtPanningPlot1,qtPanningPlot2):
# any filter initialisation goes here
# filter1 = MyAmazingFilterClass(...)
# filter2 = MyAmazingFilterClass(...)
# endless loop which sleeps not for timing but for multitasking
while running:
# loop as fast as we can to empty the kernel buffer
while c.hasSampleAvailable():
sample = c.getSampleFromBuffer()
v1 = sample[channel_of_window1]
v2 = sample[channel_of_window2]
# for filtering of data just add a filter function:
# v1 = filter1.dofilter(v1)
# v2 = filter2.dofilter(v2)
qtPanningPlot1.addData(v1)
qtPanningPlot2.addData(v2)
# let Python do other stuff and sleep a bit
sleep(0.1)
def getDataThread(qtPanningPlot1, qtPanningPlot2, ringbuffer, frequency, n):
############################################
#set up variables
#normalise (Wn for butterworth filter is in half-cycles / sample)
norm = 2 / fs
plotbuffer = []
#calculate coefficients
wide = np.array([(frequency - 11) * norm, (frequency + 11) * norm])
#sos
sos_wide = sig.butter(10, wide, btype='bandpass', output='sos')
#access master IIR filter with coefficients
master_wide = iir.IIR_filter(sos_wide)
############################################
while running:
# loop as fast as we can to empty the kernel buffer
while c.hasSampleAvailable():
sample = c.getSampleFromBuffer()
v1 = 10**2 * sample[channel_of_window1]
#filter data
v2 = master_wide.dofilter(v1)
#detect strength of peak
detect = ((th * m * 10 * abs(v2)))
print(detect)
#if in range
if detect > n:
#digital outputs
#3 = red light
#2 = blue light
c.digital_out(3, 1)
c.digital_out(2, 0)
#if it is close
elif n > detect > 2:
c.digital_out(3, 0)
c.digital_out(2, 1)
#if no signal is detected
else:
c.digital_out(3, 0)
c.digital_out(2, 0)
#add filtered data to ringbuffer
ringbuffer = np.append(ringbuffer, v2)
#plot incoming signal
qtPanningPlot1.addData(v1)
#check if there is data in the ringbuffer
#if data is found then add it to plotbuffer and reset ringbuffer
if not ringbuffer == []:
result = ringbuffer
ringbuffer = []
plotbuffer = np.append(plotbuffer, result)
#only keep the most recent 50 samples of data
plotbuffer = plotbuffer[-50:]
#calculate the spectrum
spectrum = np.fft.rfft(plotbuffer)
# absolute value
spectrum2 = m * np.absolute(spectrum) / len(spectrum)
#plot spectrum
qtPanningPlot2.addData(spectrum2)