Hello! I'm trying to write a program that read data from the usrp, then preforms a fft and plots the values of the maximum frequency and correspondent amplitude in real time. I've come across this problem: - At first I was using vector_sink but it gave me problems with memory management, always crashing after a few moments. - Now I've implemented a message queue system. With a queue for the frequency values and one for the amplitude. - I've noticed that it became much slower (about 10 fft's per second, 2 per message) - I need to have a much higher number to do what I want in the final version Is there any way to speed up the process? (Have more values per message or more messages per second maybe..) Following is my code: class top(gr.top_block): def __init__(self): gr.top_block.__init__(self) #Settings rx_subdev_spec = (0, 0) decim = 256 freq = None gain = 10 self.u = usrp.source_c(decim_rate=decim) self.u.set_mux(usrp.determine_rx_mux_value(self.u, rx_subdev_spec)) # determine the daughterboard subdevice we're using self.subdev = usrp.selected_subdev(self.u, rx_subdev_spec) # FFT Parameters fftsize = 4096 mywin = window.blackmanharris(fftsize) fft = gr.fft_vcc(fftsize, True, mywin) # Get Maximum Value c2m = gr.complex_to_mag(fftsize) imax = gr.argmax_fs(fftsize) # index amax = gr.max_ff(fftsize) # amplitude s2f1 = gr.short_to_float() s2f2 = gr.short_to_float() p0 = gr.probe_signal_f() p1 = gr.probe_signal_f() # Vector Sink/Source ss2v = gr.stream_to_vector(gr.sizeof_gr_complex, fftsize) v2ss = gr.vector_to_stream(gr.sizeof_float, fftsize) # Message Settings self.qsize = 10 self.msgq0 = gr.msg_queue(self.qsize) # queue frequency self.msgq1 = gr.msg_queue(self.qsize) # queue amplitude # Message sink for frequency(0) and amplitude(1) m_sink0 = gr.message_sink(gr.sizeof_float, self.msgq0, True) m_sink1 = gr.message_sink(gr.sizeof_float, self.msgq1, True) self.connect(self.u, ss2v, fft, c2m, (imax,0), s2f1, m_sink0) self.connect((imax,1), s2f2, p1) self.connect(c2m, amax, m_sink1) # set initial values if gain is None: # if no gain was specified, use the mid-point in dB g = self.subdev.gain_range() gain = float(g[0]+g[1])/2 if freq is None: freq = 10.7e6 self.set_gain(gain) if not(self.set_freq(freq)): pass else: if freq is None: freq = 10.7e6 self.set_gain(gain) if not(self.set_freq(freq)): pass def set_freq(self, target_freq): r = usrp.tune(self.u, 0, self.subdev, target_freq) return False def set_gain(self, gain): self.subdev.set_gain(gain) def shift(x,size=4096): """ Shifts indexes so that the first half corresponds to FS-FS/2 and the second half to FS+FS/2. @ x: index number """ if x <= (size/2): return x+(size/2)-1 elif x > (size/2): return x-(size/2)-1 def fill_buffer(buffer, data, buffer_size=1000): """ Fill a buffer in a circular form. When buffer_size is reached the oldest values are discarded. The number of values discarded depend on the size of new ones to add to the buffer. @ buffer: vector to add the values @ data: list of values to add @ buffer_size: 1000 by default @ out: final buffer with data values added """ if len(buffer) < buffer_size: out = concatenate((buffer,data)) elif len(buffer) >= buffer_size: out = concatenate((buffer[len(data):],data)) return out def main (): # Start Top Block tb = top() #Start Flowgraph tb.start() # Set Buffers yf=[] ya=[] fftsize=4096 # Read first message fmsg = tb.msgq0.delete_head() # get first frequency message amsg = tb.msgq1.delete_head() # get first amplitude message raw_f = fmsg.to_string() # raw frequency data raw_a = amsg.to_string() # raw amplitude data f_data = numpy.fromstring(raw_f, numpy.float32, count = int(fmsg.arg2())) # converted frequency data a_data = numpy.fromstring(raw_a, numpy.float32, count = int(amsg.arg2())) # converted amplitude data # fill frequency buffer yf = fill_buffer(yf,f_data) # fill frequency buffer ya = fill_buffer(ya,a_data) # Set Initial Plot Values x = [i for i in range(len(yf))] a_data = 10.0*scipy.log10(a_data) yf = [shift(i,fftsize) for i in yf] # index shifting yf = [10.7e6+i*250e3/fftsize-125e3 for i in yf] # convertion from index to frequency pylab.ion() (....) pylab.draw() while(True): fmsg = tb.msgq0.delete_head() # get first frequency message amsg = tb.msgq1.delete_head() # get first amplitude message raw_f = fmsg.to_string() # raw frequency data raw_a = amsg.to_string() # raw amplitude data f_data = numpy.fromstring(raw_f, numpy.float32, count = int(fmsg.arg2())) # converted frequency data a_data = numpy.fromstring(raw_a, numpy.float32, count = int(amsg.arg2())) # converted amplitude data a_data = 10.0*scipy.log10(a_data) f_data = [shift(i,fftsize) for i in f_data] # index shifting f_data = [10.7e6+i*250e3/fftsize-125e3 for i in f_data] # convertion from index to frequency # fill frequency buffer yf = fill_buffer(yf, f_data) # fill frequency buffer ya = fill_buffer(ya, a_data) (....) pylab.draw() if __name__ == '__main__': main () -- View this message in context: http://www.nabble.com/Slow-message-queues...-How-t... 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on 2009-03-18 17:45

on 2009-03-18 18:00

On Wed, Mar 18, 2009 at 09:44:05AM -0700, E. Ornelas wrote: > management, always > crashing after a few moments. > - Now I've implemented a message queue system. With a queue for the > frequency values and > one for the amplitude. > - I've noticed that it became much slower (about 10 fft's per second, 2 per > message) > - I need to have a much higher number to do what I want in the final version > > Is there any way to speed up the process? (Have more values per message or > more messages per second maybe..) First off, depending on the machine you are running this on, you may or may not have enough cycles to get the job done. You want to do as little as possible in python. That is, be sure that there's no python on the critical path. Consider writing a C++ block that scans the fft output vectors and computes the value that you want. It sounds like you want something that looks at each fft output vector, and for each vector returns the index of the bin with the most power, and the magnitude of that bin. Eric