def __init__(self, fg, parent,
y_per_div=10, ref_level=50, sample_rate=1,
title='', stripsize=4,
size=default_stripchartsink_size,xlabel="X",
ylabel="Y", divbase=0.025,
parallel=False, scaling=1.0, autoscale=False):
stripchart_sink_base.__init__(self, input_is_real=True,
y_per_div=y_per_div, ref_level=ref_level,
sample_rate=sample_rate,
stripsize=stripsize,
xlabel=xlabel, ylabel=ylabel,
divbase=divbase, title=title,
parallel=parallel,
scaling=scaling, autoscale=autoscale)
if (parallel == True):
one = gr.keep_one_in_n (gr.sizeof_float*stripsize, 1)
sink = gr.message_sink(gr.sizeof_float*stripsize, self.msgq, True)
else:
one = gr.keep_one_in_n (gr.sizeof_float, 1)
sink = gr.message_sink(gr.sizeof_float, self.msgq, True)
fg.connect (one, sink)
gr.hier_block.__init__(self, fg, one, sink)
self.win = stripchart_window(self, parent, size=size)
def __init__(
self,
parent,
y_per_div=10,
ref_level=50,
sample_rate=1,
title="",
stripsize=4,
size=default_stripchartsink_size,
xlabel="X",
ylabel="Y",
divbase=0.025,
parallel=False,
scaling=1.0,
autoscale=False,
):
if parallel == False:
gr.hier_block2.__init__(
self, "stripchart_sink_f", gr.io_signature(1, 1, gr.sizeof_float), gr.io_signature(0, 0, 0)
)
else:
gr.hier_block2.__init__(
self, "stripchart_sink_f", gr.io_signature(1, 1, gr.sizeof_float * stripsize), gr.io_signature(0, 0, 0)
)
stripchart_sink_base.__init__(
self,
input_is_real=True,
y_per_div=y_per_div,
ref_level=ref_level,
sample_rate=sample_rate,
stripsize=stripsize,
xlabel=xlabel,
ylabel=ylabel,
divbase=divbase,
title=title,
parallel=parallel,
scaling=scaling,
autoscale=autoscale,
)
if parallel == True:
one = gr.keep_one_in_n(gr.sizeof_float * stripsize, 1)
sink = gr.message_sink(gr.sizeof_float * stripsize, self.msgq, True)
else:
one = gr.keep_one_in_n(gr.sizeof_float, 1)
sink = gr.message_sink(gr.sizeof_float, self.msgq, True)
self.connect(self, one, sink)
self.win = stripchart_window(self, parent, size=size)
def __init__(self, fg, parent, unit='',base_value=0,minval=-100.0,maxval=100.0,factor=1.0,
decimal_places=10, ref_level=50, sample_rate=1, #number_size=512,
number_rate=default_number_rate, average=False, avg_alpha=None,
label='', size=default_numbersink_size, peak_hold=False):
number_sink_base.__init__(self, unit=unit, input_is_real=True, base_value=base_value,
minval=minval,maxval=maxval,factor=factor,
decimal_places=decimal_places, ref_level=ref_level,
sample_rate=sample_rate, #number_size=number_size,
number_rate=number_rate,
average=average, avg_alpha=avg_alpha, label=label,
peak_hold=peak_hold)
number_size=1
#s2p = gr.stream_to_vector(gr.sizeof_float, number_size)
one_in_n = gr.keep_one_in_n(gr.sizeof_float,
max(1, int(sample_rate/number_rate)))
#c2mag = gr.complex_to_mag(number_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, number_size)
# FIXME We need to add 3dB to all bins but the DC bin
#log = gr.nlog10_ff(20, number_size,
# -20*math.log10(number_size)-10*math.log10(power/number_size))
sink = gr.message_sink(gr.sizeof_float , self.msgq, True)
#fg.connect (s2p, one_in_n, fft, c2mag, self.avg, log, sink)
fg.connect(self.avg,one_in_n,sink)
gr.hier_block.__init__(self, fg, self.avg, sink)
self.win = number_window(self, parent, size=size,label=label)
self.set_average(self.average)
def __init__(self, parent, unit='',base_value=0,minval=-100.0,maxval=100.0,factor=1.0,
decimal_places=10, ref_level=50, sample_rate=1,
number_rate=default_number_rate, average=False, avg_alpha=None,
label='', size=default_numbersink_size, peak_hold=False):
gr.hier_block2.__init__(self, "number_sink_f",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(0, 0, 0)) # Output signature
number_sink_base.__init__(self, unit=unit, input_is_real=True, base_value=base_value,
minval=minval,maxval=maxval,factor=factor,
decimal_places=decimal_places, ref_level=ref_level,
sample_rate=sample_rate, number_rate=number_rate,
average=average, avg_alpha=avg_alpha, label=label,
peak_hold=peak_hold)
number_size=1
one_in_n = gr.keep_one_in_n(gr.sizeof_float,
max(1, int(sample_rate/number_rate)))
self.avg = gr.single_pole_iir_filter_ff(1.0, number_size)
sink = gr.message_sink(gr.sizeof_float , self.msgq, True)
self.connect(self, self.avg, one_in_n, sink)
self.win = number_window(self, parent, size=size,label=label)
self.set_average(self.average)
self.set_peak_hold(self.peak_hold)
def __init__(self,subdev_spec=None,gain=None,length=1,alpha=1.0,msgq=None,loopback=False,verbose=False,debug=False):
self._subdev_spec = subdev_spec
self._gain = gain
self._length = length
self._alpha = alpha
self._msgq = msgq
self._loopback = loopback
self._verbose = verbose
self._debug = debug
self._tb = gr.top_block()
self._u = usrp.source_c(fpga_filename='usrp_sounder.rbf')
if not self._loopback:
if self._subdev_spec == None:
self._subdev_spec = pick_subdevice(self._u)
self._u.set_mux(usrp.determine_rx_mux_value(self._u, self._subdev_spec))
self._subdev = usrp.selected_subdev(self._u, self._subdev_spec)
if self._verbose:
print "Using", self._subdev.name(), "for sounder receiver."
self.set_gain(self._gain)
self._vblen = gr.sizeof_gr_complex*self._length
if self._debug:
print "Generating impulse vectors of length", self._length, "byte length", self._vblen
self._s2v = gr.stream_to_vector(gr.sizeof_gr_complex, self._length)
if self._verbose:
print "Using smoothing alpha of", self._alpha
self._lpf = gr.single_pole_iir_filter_cc(self._alpha, self._length)
self._sink = gr.message_sink(self._vblen, self._msgq, True)
self._tb.connect(self._u, self._s2v, self._lpf, self._sink)
def __init__(
self,
parent,
baseband_freq=0,
y_per_div=10,
ref_level=50,
sample_rate=1,
fac_size=512,
fac_rate=default_fac_rate,
average=False,
avg_alpha=None,
title="",
size=default_facsink_size,
peak_hold=False,
):
fac_sink_base.__init__(
self,
input_is_real=False,
baseband_freq=baseband_freq,
y_per_div=y_per_div,
ref_level=ref_level,
sample_rate=sample_rate,
fac_size=fac_size,
fac_rate=fac_rate,
average=average,
avg_alpha=avg_alpha,
title=title,
peak_hold=peak_hold,
)
s2p = gr.stream_to_vector(gr.sizeof_gr_complex, self.fac_size)
self.one_in_n = gr.keep_one_in_n(
gr.sizeof_gr_complex * self.fac_size, max(1, int(self.sample_rate / self.fac_size / self.fac_rate))
)
# windowing removed ...
fac = gr.fft_vcc(self.fac_size, True, ())
c2mag = gr.complex_to_mag(fac_size)
# Things go off into the weeds if we try for an inverse FFT so a forward FFT will have to do...
fac_fac = gr.fft_vfc(self.fac_size, True, ())
fac_c2mag = gr.complex_to_mag(fac_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, fac_size)
log = gr.nlog10_ff(
20, self.fac_size, -20 * math.log10(self.fac_size)
) # - 20*math.log10(norm) ) # - self.avg[0] )
sink = gr.message_sink(gr.sizeof_float * fac_size, self.msgq, True)
self.connect(s2p, self.one_in_n, fac, c2mag, fac_fac, fac_c2mag, self.avg, log, sink)
# gr.hier_block2.__init__(self, fg, s2p, sink)
self.win = fac_window(self, parent, size=size)
self.set_average(self.average)
self.wxgui_connect(self, s2p)
def __init__(self, fg, parent, baseband_freq=0,
y_per_div=10, ref_level=50, sample_rate=1, fft_size=512,
fft_rate=default_fft_rate, average=False, avg_alpha=None,
title='', size=default_fftsink_size, peak_hold=False):
fft_sink_base.__init__(self, input_is_real=True, baseband_freq=baseband_freq,
y_per_div=y_per_div, ref_level=ref_level,
sample_rate=sample_rate, fft_size=fft_size,
fft_rate=fft_rate,
average=average, avg_alpha=avg_alpha, title=title,
peak_hold=peak_hold)
s2p = gr.stream_to_vector(gr.sizeof_float, self.fft_size)
self.one_in_n = gr.keep_one_in_n(gr.sizeof_float * self.fft_size,
max(1, int(self.sample_rate/self.fft_size/self.fft_rate)))
mywindow = window.blackmanharris(self.fft_size)
fft = gr.fft_vfc(self.fft_size, True, mywindow)
power = 0
for tap in mywindow:
power += tap*tap
c2mag = gr.complex_to_mag(self.fft_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, self.fft_size)
# FIXME We need to add 3dB to all bins but the DC bin
log = gr.nlog10_ff(20, self.fft_size,
-20*math.log10(self.fft_size)-10*math.log10(power/self.fft_size))
sink = gr.message_sink(gr.sizeof_float * self.fft_size, self.msgq, True)
fg.connect (s2p, self.one_in_n, fft, c2mag, self.avg, log, sink)
gr.hier_block.__init__(self, fg, s2p, sink)
self.win = fft_window(self, parent, size=size)
self.set_average(self.average)
def __init__(self, parent, baseband_freq=0,
y_per_div=10, sc_y_per_div=0.5, sc_ref_level=40, ref_level=50, sample_rate=1, fft_size=512,
fft_rate=15, average=False, avg_alpha=None, title='',
size=default_ra_fftsink_size, peak_hold=False, ofunc=None,
xydfunc=None):
gr.hier_block2.__init__(self, "ra_fft_sink_f",
gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(0, 0, 0))
ra_fft_sink_base.__init__(self, input_is_real=True, baseband_freq=baseband_freq,
y_per_div=y_per_div, sc_y_per_div=sc_y_per_div,
sc_ref_level=sc_ref_level, ref_level=ref_level,
sample_rate=sample_rate, fft_size=fft_size,
fft_rate=fft_rate,
average=average, avg_alpha=avg_alpha, title=title,
peak_hold=peak_hold, ofunc=ofunc,
xydfunc=xydfunc)
self.binwidth = float(sample_rate/2.0)/float(fft_size)
s2p = gr.serial_to_parallel(gr.sizeof_float, fft_size)
one_in_n = gr.keep_one_in_n(gr.sizeof_float * fft_size,
max(1, int(sample_rate/fft_size/fft_rate)))
mywindow = window.blackmanharris(fft_size)
fft = gr.fft_vfc(fft_size, True, mywindow)
c2mag = gr.complex_to_mag(fft_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, fft_size)
log = gr.nlog10_ff(20, fft_size, -20*math.log10(fft_size))
sink = gr.message_sink(gr.sizeof_float * fft_size, self.msgq, True)
self.connect (self, s2p, one_in_n, fft, c2mag, self.avg, log, sink)
self.win = fft_window(self, parent, size=size)
self.set_average(self.average)
def __init__(self,
parent,
title='',
sample_rate=1,
size=default_scopesink_size,
frame_decim=default_frame_decim,
samples_per_symbol=10,
num_plots=100,
v_scale=default_v_scale,
t_scale=None,
num_inputs=1,
**kwargs):
gr.hier_block2.__init__(
self, "datascope_sink_f",
gr.io_signature(num_inputs, num_inputs, gr.sizeof_float),
gr.io_signature(0, 0, 0))
msgq = gr.msg_queue(2) # message queue that holds at most 2 messages
self.st = gr.message_sink(gr.sizeof_float, msgq, dont_block=1)
self.connect((self, 0), self.st)
self.win = datascope_window(datascope_win_info(msgq, sample_rate,
frame_decim, v_scale,
t_scale, None, title),
parent,
samples_per_symbol=samples_per_symbol,
num_plots=num_plots)
def __init__(self, parent, baseband_freq=0,
y_per_div=10, ref_level=50, sample_rate=1, fft_size=512,
fft_rate=default_fft_rate, average=False, avg_alpha=None,
title='', size=default_fftsink_size, **kwargs):
gr.hier_block2.__init__(self, "waterfall_sink_f",
gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(0,0,0))
waterfall_sink_base.__init__(self, input_is_real=True, baseband_freq=baseband_freq,
sample_rate=sample_rate, fft_size=fft_size,
fft_rate=fft_rate,
average=average, avg_alpha=avg_alpha, title=title)
self.s2p = gr.serial_to_parallel(gr.sizeof_float, self.fft_size)
self.one_in_n = gr.keep_one_in_n(gr.sizeof_float * self.fft_size,
max(1, int(self.sample_rate/self.fft_size/self.fft_rate)))
mywindow = window.blackmanharris(self.fft_size)
self.fft = gr.fft_vfc(self.fft_size, True, mywindow)
self.c2mag = gr.complex_to_mag(self.fft_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, self.fft_size)
self.log = gr.nlog10_ff(20, self.fft_size, -20*math.log10(self.fft_size))
self.sink = gr.message_sink(gr.sizeof_float * self.fft_size, self.msgq, True)
self.connect(self, self.s2p, self.one_in_n, self.fft, self.c2mag, self.avg, self.log, self.sink)
self.win = waterfall_window(self, parent, size=size)
self.set_average(self.average)
def __init__(self, parent, title, vlen, decim,gsz): self._vlen = vlen self._parent = parent self._title = title print "Initing block: %s" % title self.plotQueue = Queue.Queue() self.win = matplotsink.matplotsink(parent,title, self.plotQueue,gsz) self._item_size = self._size*self._vlen #init hier block gr.hier_block2.__init__( self, 'plot_sink', gr.io_signature(1, 1, self._item_size), gr.io_signature(0, 0, 0), ) #create blocks self._msgq = gr.msg_queue(2) message_sink = gr.message_sink(self._item_size, self._msgq, False) #connect self.connect(self, message_sink) #setup thread threading.Thread.__init__(self) self.setDaemon(True) self.start()
def __init__(self, parent, title, vlen, decim):
self._vlen = vlen
self._parent = parent
self._title = title
print "Initing block: %s" % title
self.plotQueue = Queue.Queue()
self.win = matplotsink.matplotsink(parent, title, self.plotQueue)
self._item_size = self._size * self._vlen
#init hier block
gr.hier_block2.__init__(
self,
'plot_sink',
gr.io_signature(1, 1, self._item_size),
gr.io_signature(0, 0, 0),
)
#create blocks
self._msgq = gr.msg_queue(2)
message_sink = gr.message_sink(self._item_size, self._msgq, False)
#connect
self.connect(self, message_sink)
#setup thread
threading.Thread.__init__(self)
self.setDaemon(True)
self.start()
def __init__(self, packet_source=None, payload_length=0):
if not payload_length: #get payload length
payload_length = DEFAULT_PAYLOAD_LEN
if payload_length % self._item_size_in != 0: #verify that packet length is a multiple of the stream size
raise ValueError, 'The payload length: "%d" is not a mutiple of the stream size: "%d".' % (
payload_length, self._item_size_in)
#initialize hier2
gr.hier_block2.__init__(
self,
"ofdm_mod",
gr.io_signature(1, 1, self._item_size_in), # Input signature
gr.io_signature(
1, 1,
packet_source._hb.output_signature().sizeof_stream_item(
0)) # Output signature
)
#create blocks
msgq = gr.msg_queue(DEFAULT_MSGQ_LIMIT)
msg_sink = gr.message_sink(self._item_size_in, msgq,
False) #False -> blocking
#connect
self.connect(self, msg_sink)
self.connect(packet_source, self)
#start thread
_packet_encoder_thread(msgq, payload_length, packet_source.send_pkt)
def __init__(self,subdev_spec=None,gain=None,length=1,alpha=1.0,msgq=None,loopback=False,verbose=False,debug=False):
self._subdev_spec = subdev_spec
self._gain = gain
self._length = length
self._alpha = alpha
self._msgq = msgq
self._loopback = loopback
self._verbose = verbose
self._debug = debug
self._fg = gr.flow_graph()
self._u = usrp.source_c(fpga_filename='usrp_sounder.rbf')
if not self._loopback:
if self._subdev_spec == None:
self._subdev_spec = pick_subdevice(self._u)
self._u.set_mux(usrp.determine_rx_mux_value(self._u, self._subdev_spec))
self._subdev = usrp.selected_subdev(self._u, self._subdev_spec)
if self._verbose:
print "Using", self._subdev.name(), "for sounder receiver."
self.set_gain(self._gain)
self._vblen = gr.sizeof_gr_complex*self._length
if self._debug:
print "Generating impulse vectors of length", self._length, "byte length", self._vblen
self._s2v = gr.stream_to_vector(gr.sizeof_gr_complex, self._length)
if self._verbose:
print "Using smoothing alpha of", self._alpha
self._lpf = gr.single_pole_iir_filter_cc(self._alpha, self._length)
self._sink = gr.message_sink(self._vblen, self._msgq, True)
self._fg.connect(self._u, self._s2v, self._lpf, self._sink)
def publish_rx_spectrum(self,fftlen):
## RX Spectrum
fftlen = 256
my_window = window.hamming(fftlen) #.blackmanharris(fftlen)
rxs_sampler = vector_sampler(gr.sizeof_gr_complex,fftlen)
rxs_trigger = gr.vector_source_b(concatenate([[1],[0]*199]),True)
rxs_window = blocks.multiply_const_vcc(my_window)
rxs_spectrum = gr.fft_vcc(fftlen,True,[],True)
rxs_mag = gr.complex_to_mag(fftlen)
rxs_avg = gr.single_pole_iir_filter_ff(0.01,fftlen)
rxs_logdb = gr.nlog10_ff(20.0,fftlen,-20*log10(fftlen))
rxs_decimate_rate = gr.keep_one_in_n(gr.sizeof_float*fftlen,1)
msgq = gr.msg_queue(5)
rxs_msg_sink = gr.message_sink(gr.sizeof_float*fftlen,msgq,True)
self.connect(rxs_trigger,(rxs_sampler,1))
t = self.u if self.filter is None else self.filter
self.connect(t,rxs_sampler,rxs_window,
rxs_spectrum,rxs_mag,rxs_avg,rxs_logdb, rxs_decimate_rate,
rxs_msg_sink)
self.servants.append(corba_data_buffer_servant("spectrum",fftlen,msgq))
print "RXS trigger unique id", rxs_trigger.unique_id()
print "Publishing RX baseband under id: spectrum"
def __init__(self, fg, parent, baseband_freq=0,
ref_level=0, sample_rate=1, fft_size=512,
fft_rate=default_fft_rate, average=False, avg_alpha=None,
title='', size=default_fftsink_size, report=None, span=40, ofunc=None, xydfunc=None):
waterfall_sink_base.__init__(self, input_is_real=False,
baseband_freq=baseband_freq,
sample_rate=sample_rate,
fft_size=fft_size,
fft_rate=fft_rate,
average=average, avg_alpha=avg_alpha,
title=title)
s2p = gr.serial_to_parallel(gr.sizeof_gr_complex, self.fft_size)
self.one_in_n = gr.keep_one_in_n(gr.sizeof_gr_complex * self.fft_size,
max(1, int(self.sample_rate/self.fft_size/self.fft_rate)))
mywindow = window.blackmanharris(self.fft_size)
fft = gr.fft_vcc(self.fft_size, True, mywindow)
c2mag = gr.complex_to_mag(self.fft_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, self.fft_size)
log = gr.nlog10_ff(20, self.fft_size, -20*math.log10(self.fft_size))
sink = gr.message_sink(gr.sizeof_float * self.fft_size, self.msgq, True)
self.block_list = (s2p, self.one_in_n, fft, c2mag, self.avg, log, sink)
self.reconnect( fg )
gr.hier_block.__init__(self, fg, s2p, sink)
self.win = waterfall_window(self, parent, size=size, report=report,
ref_level=ref_level, span=span, ofunc=ofunc, xydfunc=xydfunc)
self.set_average(self.average)
def __init__(self, parent, baseband_freq=0,
y_per_div=10, ref_level=50, sample_rate=1, fft_size=512,
fft_rate=default_fft_rate, average=False, avg_alpha=None,
title='', size=default_fftsink_size):
gr.hier_block2.__init__(self, "waterfall_sink_f",
gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(0,0,0))
waterfall_sink_base.__init__(self, input_is_real=True, baseband_freq=baseband_freq,
sample_rate=sample_rate, fft_size=fft_size,
fft_rate=fft_rate,
average=average, avg_alpha=avg_alpha, title=title)
self.s2p = gr.serial_to_parallel(gr.sizeof_float, self.fft_size)
self.one_in_n = gr.keep_one_in_n(gr.sizeof_float * self.fft_size,
max(1, int(self.sample_rate/self.fft_size/self.fft_rate)))
mywindow = window.blackmanharris(self.fft_size)
self.fft = gr.fft_vfc(self.fft_size, True, mywindow)
self.c2mag = gr.complex_to_mag(self.fft_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, self.fft_size)
self.log = gr.nlog10_ff(20, self.fft_size, -20*math.log10(self.fft_size))
self.sink = gr.message_sink(gr.sizeof_float * self.fft_size, self.msgq, True)
self.connect(self, self.s2p, self.one_in_n, self.fft, self.c2mag, self.avg, self.log, self.sink)
self.win = waterfall_window(self, parent, size=size)
self.set_average(self.average)
def __init__(
self,
parent,
baseband_freq=0,
y_per_div=10,
ref_level=50,
sample_rate=1,
fac_size=512,
fac_rate=default_fac_rate,
average=False,
avg_alpha=None,
title="",
size=default_facsink_size,
peak_hold=False,
):
fac_sink_base.__init__(
self,
input_is_real=True,
baseband_freq=baseband_freq,
y_per_div=y_per_div,
ref_level=ref_level,
sample_rate=sample_rate,
fac_size=fac_size,
fac_rate=fac_rate,
average=average,
avg_alpha=avg_alpha,
title=title,
peak_hold=peak_hold,
)
s2p = gr.stream_to_vector(gr.sizeof_float, self.fac_size)
self.one_in_n = gr.keep_one_in_n(
gr.sizeof_float * self.fac_size, max(1, int(self.sample_rate / self.fac_size / self.fac_rate))
)
# windowing removed...
fac = gr.fft_vfc(self.fac_size, True, ())
c2mag = gr.complex_to_mag(self.fac_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, self.fac_size)
fac_fac = gr.fft_vfc(self.fac_size, True, ())
fac_c2mag = gr.complex_to_mag(fac_size)
# FIXME We need to add 3dB to all bins but the DC bin
log = gr.nlog10_ff(20, self.fac_size, -20 * math.log10(self.fac_size))
sink = gr.message_sink(gr.sizeof_float * self.fac_size, self.msgq, True)
self.connect(s2p, self.one_in_n, fac, c2mag, fac_fac, fac_c2mag, self.avg, log, sink)
# gr.hier_block.__init__(self, fg, s2p, sink)
self.win = fac_window(self, parent, size=size)
self.set_average(self.average)
self.wxgui_connect(self, s2p)
def __init__(self,
parent,
baseband_freq=0,
y_per_div=10,
ref_level=50,
sample_rate=1,
fac_size=512,
fac_rate=default_fac_rate,
average=False,
avg_alpha=None,
title='',
size=default_facsink_size,
peak_hold=False):
fac_sink_base.__init__(self,
input_is_real=False,
baseband_freq=baseband_freq,
y_per_div=y_per_div,
ref_level=ref_level,
sample_rate=sample_rate,
fac_size=fac_size,
fac_rate=fac_rate,
average=average,
avg_alpha=avg_alpha,
title=title,
peak_hold=peak_hold)
s2p = gr.stream_to_vector(gr.sizeof_gr_complex, self.fac_size)
self.one_in_n = gr.keep_one_in_n(
gr.sizeof_gr_complex * self.fac_size,
max(1, int(self.sample_rate / self.fac_size / self.fac_rate)))
# windowing removed ...
fac = gr.fft_vcc(self.fac_size, True, ())
c2mag = gr.complex_to_mag(fac_size)
# Things go off into the weeds if we try for an inverse FFT so a forward FFT will have to do...
fac_fac = gr.fft_vfc(self.fac_size, True, ())
fac_c2mag = gr.complex_to_mag(fac_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, fac_size)
log = gr.nlog10_ff(20, self.fac_size, -20 * math.log10(
self.fac_size)) # - 20*math.log10(norm) ) # - self.avg[0] )
sink = gr.message_sink(gr.sizeof_float * fac_size, self.msgq, True)
self.connect(s2p, self.one_in_n, fac, c2mag, fac_fac, fac_c2mag,
self.avg, log, sink)
# gr.hier_block2.__init__(self, fg, s2p, sink)
self.win = fac_window(self, parent, size=size)
self.set_average(self.average)
self.wxgui_connect(self, s2p)
def __init__(self,
parent,
baseband_freq=0,
y_per_div=10,
ref_level=50,
sample_rate=1,
fac_size=512,
fac_rate=default_fac_rate,
average=False,
avg_alpha=None,
title='',
size=default_facsink_size,
peak_hold=False):
fac_sink_base.__init__(self,
input_is_real=True,
baseband_freq=baseband_freq,
y_per_div=y_per_div,
ref_level=ref_level,
sample_rate=sample_rate,
fac_size=fac_size,
fac_rate=fac_rate,
average=average,
avg_alpha=avg_alpha,
title=title,
peak_hold=peak_hold)
s2p = gr.stream_to_vector(gr.sizeof_float, self.fac_size)
self.one_in_n = gr.keep_one_in_n(
gr.sizeof_float * self.fac_size,
max(1, int(self.sample_rate / self.fac_size / self.fac_rate)))
# windowing removed...
fac = gr.fft_vfc(self.fac_size, True, ())
c2mag = gr.complex_to_mag(self.fac_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, self.fac_size)
fac_fac = gr.fft_vfc(self.fac_size, True, ())
fac_c2mag = gr.complex_to_mag(fac_size)
# FIXME We need to add 3dB to all bins but the DC bin
log = gr.nlog10_ff(20, self.fac_size, -20 * math.log10(self.fac_size))
sink = gr.message_sink(gr.sizeof_float * self.fac_size, self.msgq,
True)
self.connect(s2p, self.one_in_n, fac, c2mag, fac_fac, fac_c2mag,
self.avg, log, sink)
# gr.hier_block.__init__(self, fg, s2p, sink)
self.win = fac_window(self, parent, size=size)
self.set_average(self.average)
self.wxgui_connect(self, s2p)
def __init__(self, options):
gr.top_block.__init__(self)
if options.freq is not None:
u = usrp2.source(options)
elif options.infile is not None:
u = gr.file_source(gr.sizeof_gr_complex, options.infile)
else:
import sys
sys.stderr.write("--freq or --infile must be specified\n")
raise SystemExit
self.scope = None
if options.outfile is not None:
rx = gr.file_sink(gr.sizeof_gr_complex, options.outfile)
else:
rx = qam_rxtx.RX(options)
framebytes = rx.framebytes
if options.rxdata is not None:
if options.rxdata == '-':
self.connect(
rx,
gr.file_descriptor_sink(gr.sizeof_char * framebytes,
1))
else:
self.connect(
rx,
gr.file_sink(gr.sizeof_char * framebytes,
options.rxdata))
if options.berdata is not None:
# select one of the ber modes
ber = qam_rxtx.BER(framebytes, 100, mode=options.bermode)
data = qam_rxtx.make_data(framebytes)
self.connect(rx, (ber, 0))
self.connect(data, (ber, 1))
if options.berdata == '-':
# print it out
msgq = gr.msg_queue(16)
self.connect(ber,
gr.message_sink(gr.sizeof_float, msgq, True))
self.watcher = ofdm_rxtx.queue_watcher(msgq)
elif options.berdata == '.':
import scope
# scope it out
self.scope = scope.scope(self, ber, 'Frame BER')
else:
self.connect(
ber, gr.file_sink(gr.sizeof_float, options.berdata))
else:
pass
#self.connect(rx, gr.null_sink(symbol_size)) # XXX do we still need this?
self.connect(u, rx)
def __init__(
self,
baseband_freq=0,
ref_scale=2.0,
y_per_div=10,
y_divs=8,
ref_level=50,
sample_rate=1,
fft_size=512,
fft_rate=20,
average=False,
avg_alpha=None,
win=None,
use_persistence=False,
persist_alpha=None,
**kwargs
):
# ensure avg alpha
if avg_alpha is None:
avg_alpha = 2.0 / fft_rate
# ensure analog alpha
if persist_alpha is None:
actual_fft_rate = float(sample_rate / fft_size) / float(
max(1, int(float((sample_rate / fft_size) / fft_rate)))
)
# print "requested_fft_rate ",fft_rate
# print "actual_fft_rate ",actual_fft_rate
analog_cutoff_freq = 0.5 # Hertz
# calculate alpha from wanted cutoff freq
persist_alpha = 1.0 - math.exp(-2.0 * math.pi * analog_cutoff_freq / actual_fft_rate)
# init
gr.hier_block2.__init__(
self, "zmq_fft_sink", gr.io_signature(1, 1, gr.sizeof_gr_complex), gr.io_signature(0, 0, 0)
)
# blocks
fft_0 = fft.logpwrfft_c(
sample_rate=sample_rate,
fft_size=fft_size,
frame_rate=fft_rate,
ref_scale=ref_scale,
avg_alpha=avg_alpha,
average=average,
win=win,
)
msgq = gr.msg_queue(2)
sink = gr.message_sink(gr.sizeof_float * fft_size, msgq, True)
input_watcher(msgq)
# connect
self.connect(self, fft_0, sink)
def __init__(self, d_type, d_len, qt_box, d_type_numpy, samp_rate, center_f):
gr.hier_block2.__init__(self, "plot_sink",
gr.io_signature(1, 1, d_type * d_len),
gr.io_signature(0, 0, 0))
self.msgq = gr.msg_queue(1)
self.snk = gr.message_sink(d_type * d_len, self.msgq, True)
self.connect(self, self.snk)
self.watcher = QueueWatcherThread(self.msgq, d_len, d_type_numpy, samp_rate, center_f)
qt_box.connect(self.watcher,
Qt.SIGNAL("new_plot_data(PyQt_PyObject, PyQt_PyObject, PyQt_PyObject)"),
qt_box.plot_data)
def __init__(self):
gr.top_block.__init__(self, 'Message Blocks Test')
# initialize the queues
self.sink_queue = gr.msg_queue()
self.source_queue = gr.msg_queue()
# initialize the blocks
self.msg_source = gr.message_source(gr.sizeof_char, self.source_queue)
self.msg_sink = gr.message_sink(gr.sizeof_char, self.sink_queue, False)
self.connect((self.msg_source, 0), (self.msg_sink, 0))
def __init__(self):
gr.top_block.__init__(self, 'Message Blocks Test')
# initialize the queues
self.sink_queue = gr.msg_queue()
self.source_queue = gr.msg_queue()
# initialize the blocks
self.msg_source = gr.message_source(gr.sizeof_char, self.source_queue)
self.msg_sink = gr.message_sink(gr.sizeof_char, self.sink_queue, False)
self.connect((self.msg_source, 0), (self.msg_sink, 0))
def __init__(self, audio_input_dev):
gr.hier_block2.__init__(self, "audio_rx",
gr.io_signature(0, 0, 0), # Input signature
gr.io_signature(0, 0, 0)) # Output signature
sample_rate = 44100
src = audio.source(sample_rate, audio_input_dev)
src_scale = gr.multiply_const_ff(32767)
f2s = gr.float_to_short()
voice_coder = gsm_full_rate.encode_sp()
self.packets_from_encoder = gr.msg_queue()
packet_sink = gr.message_sink(33, self.packets_from_encoder, False)
self.connect(src, src_scale, f2s, voice_coder, packet_sink)
def __init__(self, audio_input_dev):
gr.hier_block2.__init__(self, "audio_rx",
gr.io_signature(0, 0, 0), # Input signature
gr.io_signature(0, 0, 0)) # Output signature
sample_rate = 8000
src = audio.source(sample_rate, audio_input_dev)
src_scale = gr.multiply_const_ff(32767)
f2s = gr.float_to_short()
voice_coder = gsm_full_rate.encode_sp()
self.packets_from_encoder = gr.msg_queue()
packet_sink = gr.message_sink(33, self.packets_from_encoder, False)
self.connect(src, src_scale, f2s, voice_coder, packet_sink)
def __init__(self,
parent,
baseband_freq=0,
ref_level=0,
sample_rate=1,
fft_size=512,
fft_rate=default_fft_rate,
average=False,
avg_alpha=None,
title='',
size=default_fftsink_size,
report=None,
span=40,
ofunc=None,
xydfunc=None):
gr.hier_block2.__init__(self, "waterfall_sink_c",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(0, 0, 0))
waterfall_sink_base.__init__(self,
input_is_real=False,
baseband_freq=baseband_freq,
sample_rate=sample_rate,
fft_size=fft_size,
fft_rate=fft_rate,
average=average,
avg_alpha=avg_alpha,
title=title)
s2p = gr.serial_to_parallel(gr.sizeof_gr_complex, self.fft_size)
self.one_in_n = gr.keep_one_in_n(
gr.sizeof_gr_complex * self.fft_size,
max(1, int(self.sample_rate / self.fft_size / self.fft_rate)))
mywindow = window.blackmanharris(self.fft_size)
fft = gr.fft_vcc(self.fft_size, True, mywindow)
c2mag = gr.complex_to_mag(self.fft_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, self.fft_size)
log = gr.nlog10_ff(20, self.fft_size, -20 * math.log10(self.fft_size))
sink = gr.message_sink(gr.sizeof_float * self.fft_size, self.msgq,
True)
self.connect(self, s2p, self.one_in_n, fft, c2mag, self.avg, log, sink)
self.win = waterfall_window(self,
parent,
size=size,
report=report,
ref_level=ref_level,
span=span,
ofunc=ofunc,
xydfunc=xydfunc)
self.set_average(self.average)
def publish_spectrum(self,fftlen):
spectrum = gr.fft_vcc(fftlen,True,[],True)
mag = gr.complex_to_mag(fftlen)
logdb = gr.nlog10_ff(20.0,fftlen,-20*log10(fftlen))
decimate_rate = gr.keep_one_in_n(gr.sizeof_gr_complex*fftlen,10)
msgq = gr.msg_queue(10)
msg_sink = gr.message_sink(gr.sizeof_float*fftlen,msgq,True)
self.connect(self.filter,gr.stream_to_vector(gr.sizeof_gr_complex,fftlen),
decimate_rate,spectrum,mag,logdb,msg_sink)
self.servants.append(corba_data_buffer_servant("tx_spectrum",fftlen,msgq))
def publish_ctf(self,unique_id):
"""
corbaname: ofdm_ti.unique_id
"""
config = self.config
vlen = config.data_subcarriers
msgq = gr.msg_queue(2)
msg_sink = gr.message_sink(gr.sizeof_float*vlen,msgq,True)
msg_sink_2 = gr.message_sink(gr.sizeof_float*vlen,msgq,True)
ctf = self.filter_ctf()
ctf_2 = self.filter_ctf_2()
self.connect( ctf, msg_sink )
self.connect( ctf_2, msg_sink_2 )
self.servants.append(corba_data_buffer_servant(str(unique_id),vlen,msgq))
self.servants.append(corba_data_buffer_servant(str(unique_id_2),vlen,msgq_2))
print "Publishing CTF under id: %s" % (unique_id)
print "Publishing CTF 2 under id: %s" % (unique_id_2)
def __init__( self, parent, unit='%', minval=0, maxval=100, decimal_places=5, sample_rate=1, number_rate=DEFAULT_NUMBER_RATE, label='Bit Error Rate', size=DEFAULT_WIN_SIZE, show_gauge=True, **kwargs #catchall for backwards compatibility ): gr.hier_block2.__init__( self, "number_sink", gr.io_signature(1, 1, self._item_size), gr.io_signature(0, 0, 0), ) #blocks sd = blks2.stream_to_vector_decimator( item_size=self._item_size, sample_rate=sample_rate, vec_rate=number_rate, vec_len=1, ) mult = gr.multiply_const_ff(100) add = gr.add_const_ff(1e-10) msgq = gr.msg_queue(2) sink = gr.message_sink(self._item_size, msgq, True) #connect self.connect(self, sd, mult, add, sink) #controller self.controller = pubsub() #start input watcher common.input_watcher(msgq, self.controller, MSG_KEY) #create window self.win = number_window( parent=parent, controller=self.controller, size=size, title=label, units=unit, real=self._real, minval=minval, maxval=maxval, decimal_places=decimal_places, show_gauge=show_gauge, msg_key=MSG_KEY, sample_rate_key=SAMPLE_RATE_KEY)
def _setup_connections(self):
if not self._length_set:
raise RuntimeError("Echo length not set.")
self._setup_usrp()
self._vblen = gr.sizeof_gr_complex*self._length
self._s2v = gr.stream_to_vector(gr.sizeof_gr_complex, self._length)
self._sink = gr.message_sink(self._vblen, self._msgq, False)
self.connect(self._u, self._s2v, self._sink)
if self._verbose:
print "Generating echo vectors of length", self._length, \
"(samples)", self._vblen, "(bytes)"
self._connected = True
def _setup_connections(self):
if not self._length_set:
raise RuntimeError("Echo length not set.")
self._setup_usrp()
self._vblen = gr.sizeof_gr_complex * self._length
self._s2v = gr.stream_to_vector(gr.sizeof_gr_complex, self._length)
self._sink = gr.message_sink(self._vblen, self._msgq, False)
self.connect(self._u, self._s2v, self._sink)
if self._verbose:
print "Generating echo vectors of length", self._length, \
"(samples)", self._vblen, "(bytes)"
self._connected = True
def __init__(
self,
parent,
unit='%',
minval=0,
maxval=100,
decimal_places=5,
sample_rate=1,
number_rate=DEFAULT_NUMBER_RATE,
label='Bit Error Rate',
size=DEFAULT_WIN_SIZE,
show_gauge=True,
**kwargs #catchall for backwards compatibility
):
gr.hier_block2.__init__(
self,
"number_sink",
gr.io_signature(1, 1, self._item_size),
gr.io_signature(0, 0, 0),
)
#blocks
sd = blks2.stream_to_vector_decimator(
item_size=self._item_size,
sample_rate=sample_rate,
vec_rate=number_rate,
vec_len=1,
)
mult = gr.multiply_const_ff(100)
add = gr.add_const_ff(1e-10)
msgq = gr.msg_queue(2)
sink = gr.message_sink(self._item_size, msgq, True)
#connect
self.connect(self, sd, mult, add, sink)
#controller
self.controller = pubsub()
#start input watcher
common.input_watcher(msgq, self.controller, MSG_KEY)
#create window
self.win = number_window(parent=parent,
controller=self.controller,
size=size,
title=label,
units=unit,
real=self._real,
minval=minval,
maxval=maxval,
decimal_places=decimal_places,
show_gauge=show_gauge,
msg_key=MSG_KEY,
sample_rate_key=SAMPLE_RATE_KEY)
def publish_sinrsc(self,unique_id):
"""
corbaname: ofdm_ti.unique_id
"""
config = self.config
vlen = config.subcarriers
msgq = gr.msg_queue(2)
msg_sink = gr.message_sink(gr.sizeof_float*vlen,msgq,True)
sinrsc = self._sinr_measurement
self.connect( sinrsc, msg_sink )
self.servants.append(corba_data_buffer_servant(str(unique_id),vlen,msgq))
def publish_tm_window(self,unique_id):
"""
corbaname: ofdm_ti.unique_id
"""
raise SystemError,"Bad guy! Obey the gnuradio hierarchy ..."
config = self.config
msgq = gr.msg_queue(10)
msg_sink = gr.message_sink(gr.sizeof_float*config.fft_length,msgq,True)
sampler = vector_sampler(gr.sizeof_float,config.fft_length)
self.connect(self.receiver.timing_metric,(sampler,0))
self.connect(self.receiver.time_sync,delay(gr.sizeof_char,config.fft_length/2-1),(sampler,1))
self.connect(sampler,msg_sink)
self.servants.append(corba_data_buffer_servant(str(unique_id),config.fft_length,msgq))
def __init__(self, options):
gr.top_block.__init__(self)
if options.freq is not None:
u = usrp2.source(options)
elif options.infile is not None:
u = gr.file_source(gr.sizeof_gr_complex, options.infile)
else:
import sys
sys.stderr.write("--freq or --infile must be specified\n")
raise SystemExit
self.scope = None
if options.outfile is not None:
rx = gr.file_sink(gr.sizeof_gr_complex, options.outfile)
else:
rx = qam_rxtx.RX(options)
framebytes = rx.framebytes
if options.rxdata is not None:
if options.rxdata == '-':
self.connect(rx, gr.file_descriptor_sink(gr.sizeof_char * framebytes, 1))
else:
self.connect(rx, gr.file_sink(gr.sizeof_char * framebytes, options.rxdata))
if options.berdata is not None:
# select one of the ber modes
ber = qam_rxtx.BER(framebytes, 100, mode=options.bermode)
data = qam_rxtx.make_data(framebytes)
self.connect(rx, (ber,0))
self.connect(data, (ber,1))
if options.berdata == '-':
# print it out
msgq = gr.msg_queue(16)
self.connect(ber, gr.message_sink(gr.sizeof_float, msgq, True))
self.watcher = ofdm_rxtx.queue_watcher(msgq)
elif options.berdata == '.':
import scope
# scope it out
self.scope = scope.scope(self, ber, 'Frame BER')
else:
self.connect(ber, gr.file_sink(gr.sizeof_float, options.berdata))
else:
pass
#self.connect(rx, gr.null_sink(symbol_size)) # XXX do we still need this?
self.connect(u, rx)
def test_1(self):
data = ('hello', 'you', 'there')
tx_msgq = gr.msg_queue()
rx_msgq = gr.msg_queue()
for d in data:
tx_msgq.insert_tail(gr.message_from_string(d))
tb = gr.top_block()
src = gr.message_source(gr.sizeof_char, tx_msgq, "packet_length")
snk = gr.message_sink(gr.sizeof_char, rx_msgq, False, "packet_length")
tb.connect(src, snk)
tb.start()
time.sleep(1)
tb.stop()
for d in data:
msg = rx_msgq.delete_head()
contents = msg.to_string()
self.assertEqual(d, contents)
def test_1 (self):
data = ('hello', 'you', 'there')
tx_msgq = gr.msg_queue ()
rx_msgq = gr.msg_queue ()
for d in data:
tx_msgq.insert_tail(gr.message_from_string(d))
tb = gr.top_block()
src = gr.message_source(gr.sizeof_char, tx_msgq, "packet_length")
snk = gr.message_sink(gr.sizeof_char, rx_msgq, False, "packet_length")
tb.connect(src, snk)
tb.start()
time.sleep(1)
tb.stop()
for d in data:
msg = rx_msgq.delete_head()
contents = msg.to_string()
self.assertEqual(d, contents)
def publish_ctf(self,unique_id):
"""
corbaname: ofdm_ti.unique_id
"""
config = self.config
vlen = config.data_subcarriers
msgq = gr.msg_queue(2)
msg_sink = gr.message_sink(gr.sizeof_float*vlen,msgq,True)
ctf = self.filter_ctf()
self.connect( ctf, msg_sink )
self.servants.append(corba_data_buffer_servant(str(unique_id),vlen,msgq))
print "Publishing CTF under id: %s" % (unique_id)
def __init__(self, samp_rate, symbol_rate=31.25):
super(psk31_receiver, self).__init__(
"psk31_receiver",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(0, 0, 1))
self.symbol_rate = symbol_rate
self.costas = digital.costas_loop_cc(2*3.14/100, 4)
self.clock_recovery = digital.clock_recovery_mm_cc(
1.0*samp_rate/symbol_rate, 0.25 * 0.1*0.1, 0.05, 0.1, 0.001)
self.receiver = digital.constellation_receiver_cb(
digital.constellation_bpsk().base(), 2*3.14/100, -0.25, 0.25)
self.diff = gr.diff_decoder_bb(2)
self.decoder = ham.psk31_decode_bb(True)
self.msgq_out = gr.msg_queue()
self.snk = gr.message_sink(gr.sizeof_char, self.msgq_out, True)
self.connect(self, self.costas, self.clock_recovery,
self.receiver, self.diff, self.decoder, self.snk)
def __init__( self, parent, title='', sample_rate=1, size=(495,450), frame_rate=5, const_size=1024, mod='DBPSK'): #init gr.hier_block2.__init__( self, "const_sink", gr.io_signature(1, 1, gr.sizeof_gr_complex), gr.io_signature(0, 0, 0), ) self.sd = blks2.stream_to_vector_decimator( item_size=gr.sizeof_gr_complex, sample_rate=sample_rate, vec_rate=frame_rate, vec_len=const_size, ) self. agc = gr.agc2_cc(0.6e-1, 1e-3, 1, 1, 100) self.gain= gr.multiply_const_cc(utils.gain[mod]) msgq = gr.msg_queue(2) sink = gr.message_sink(gr.sizeof_gr_complex*const_size, msgq, True) #connect self.connect(self, self.agc, self.gain, self.sd, sink) #controller def setter(p, k, x): p[k] = x self.controller = pubsub() #initial update common.input_watcher(msgq, self.controller, MSG_KEY) #create window self.win = const_window( parent=parent, controller=self.controller, size=size, title=title, msg_key=MSG_KEY ) common.register_access_methods(self, self.win)
def __init__(self, parent, baseband_freq=0, ref_scale=2.0,
y_per_div=10, y_divs=8, ref_level=50, sample_rate=1, fft_size=512,
fft_rate=default_fft_rate, average=False, avg_alpha=None,
title='', size=default_fftsink_size, peak_hold=False, use_persistence=False,persist_alpha=0.2, **kwargs):
gr.hier_block2.__init__(self, "fft_sink_c",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(0,0,0))
fft_sink_base.__init__(self, input_is_real=False, baseband_freq=baseband_freq,
y_per_div=y_per_div, y_divs=y_divs, ref_level=ref_level,
sample_rate=sample_rate, fft_size=fft_size,
fft_rate=fft_rate,
average=average, avg_alpha=avg_alpha, title=title,
peak_hold=peak_hold, use_persistence=use_persistence,persist_alpha=persist_alpha)
self.s2p = gr.stream_to_vector(gr.sizeof_gr_complex, self.fft_size)
self.one_in_n = gr.keep_one_in_n(gr.sizeof_gr_complex * self.fft_size,
max(1, int(self.sample_rate/self.fft_size/self.fft_rate)))
mywindow = window.blackmanharris(self.fft_size)
self.fft = gr.fft_vcc(self.fft_size, True, mywindow)
power = 0
for tap in mywindow:
power += tap*tap
self.c2mag = gr.complex_to_mag(self.fft_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, self.fft_size)
# FIXME We need to add 3dB to all bins but the DC bin
self.log = gr.nlog10_ff(20, self.fft_size,
-10*math.log10(self.fft_size) # Adjust for number of bins
-10*math.log10(power/self.fft_size) # Adjust for windowing loss
-20*math.log10(ref_scale/2)) # Adjust for reference scale
self.sink = gr.message_sink(gr.sizeof_float * self.fft_size, self.msgq, True)
self.connect(self, self.s2p, self.one_in_n, self.fft, self.c2mag, self.avg, self.log, self.sink)
self.win = fft_window(self, parent, size=size)
self.set_average(self.average)
self.set_use_persistence(self.use_persistence)
self.set_persist_alpha(self.persist_alpha)
self.set_peak_hold(self.peak_hold)
def __init__(self, options):
gr.hier_block2.__init__(self, "sensing_path",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(0, 0, 0)) # Output signature
options = copy.copy(options) # make a copy so we can destructively modify
self._verbose = options.verbose
# linklab, fft size for sensing, different from fft length for tx/rx
self.fft_size = FFT_SIZE
# interpolation rate: sensing fft size / ofdm fft size
self.interp_rate = self.fft_size/FFT_SIZE #options.fft_length
self._fft_length = FFT_SIZE #options.fft_length
self._occupied_tones = FFT_SIZE #options.occupied_tones
self.msgq = gr.msg_queue()
# linklab , setup the sensing path
# FIXME: some components are not necessary
self.s2p = gr.stream_to_vector(gr.sizeof_gr_complex, self.fft_size)
mywindow = window.blackmanharris(self.fft_size)
self.fft = gr.fft_vcc(self.fft_size, True, mywindow)
power = 0
for tap in mywindow:
power += tap*tap
self.c2mag = gr.complex_to_mag(self.fft_size)
self.avg = gr.single_pole_iir_filter_ff(1.0, self.fft_size)
# linklab, ref scale value from default ref_scale in usrp_fft.py
ref_scale = 13490.0
# FIXME We need to add 3dB to all bins but the DC bin
self.log = gr.nlog10_ff(20, self.fft_size,
-10*math.log10(self.fft_size) # Adjust for number of bins
-10*math.log10(power/self.fft_size) # Adjust for windowing loss
-20*math.log10(ref_scale/2)) # Adjust for reference scale
self.sink = gr.message_sink(gr.sizeof_float * self.fft_size, self.msgq, True)
self.connect(self, self.s2p, self.fft, self.c2mag, self.avg, self.log, self.sink)
def __init__(self,
parent,
title='',
sample_rate=1,
size=(495, 450),
frame_rate=5,
const_size=1024,
mod='DBPSK'):
#init
gr.hier_block2.__init__(
self,
"const_sink",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(0, 0, 0),
)
self.sd = blks2.stream_to_vector_decimator(
item_size=gr.sizeof_gr_complex,
sample_rate=sample_rate,
vec_rate=frame_rate,
vec_len=const_size,
)
self.agc = gr.agc2_cc(0.6e-1, 1e-3, 1, 1, 100)
self.gain = gr.multiply_const_cc(utils.gain[mod])
msgq = gr.msg_queue(2)
sink = gr.message_sink(gr.sizeof_gr_complex * const_size, msgq, True)
#connect
self.connect(self, self.agc, self.gain, self.sd, sink)
#controller
def setter(p, k, x):
p[k] = x
self.controller = pubsub()
#initial update
common.input_watcher(msgq, self.controller, MSG_KEY)
#create window
self.win = const_window(parent=parent,
controller=self.controller,
size=size,
title=title,
msg_key=MSG_KEY)
common.register_access_methods(self, self.win)
def __init__(self, packet_source=None, payload_length=0): if not payload_length: #get payload length payload_length = DEFAULT_PAYLOAD_LEN if payload_length%self._item_size_in != 0: #verify that packet length is a multiple of the stream size raise ValueError, 'The payload length: "%d" is not a mutiple of the stream size: "%d".'%(payload_length, self._item_size_in) #initialize hier2 gr.hier_block2.__init__( self, "ofdm_mod", gr.io_signature(1, 1, self._item_size_in), # Input signature gr.io_signature(1, 1, packet_source._hb.output_signature().sizeof_stream_item(0)) # Output signature ) #create blocks msgq = gr.msg_queue(DEFAULT_MSGQ_LIMIT) msg_sink = gr.message_sink(self._item_size_in, msgq, False) #False -> blocking #connect self.connect(self, msg_sink) self.connect(packet_source, self) #start thread _packet_encoder_thread(msgq, payload_length, packet_source.send_pkt)
def __init__(self, vlen, decim, callback): self._vlen = vlen self._callback = callback self._item_size = self._size*self._vlen #init hier block gr.hier_block2.__init__( self, 'variable_sink', gr.io_signature(1, 1, self._item_size), gr.io_signature(0, 0, 0), ) #create blocks self._decimator = gr.keep_one_in_n(self._item_size, decim) self._msgq = gr.msg_queue(2) message_sink = gr.message_sink(self._item_size, self._msgq, False) #connect self.connect(self, self._decimator, message_sink) #setup thread threading.Thread.__init__(self) self.setDaemon(True) self.start()
def __init__(self,
type='BER',
win_size=default_win_size,
bits_per_symbol=2):
"""
Error rate constructor.
@param type a string 'BER' or 'SER'
@param win_size the number of samples to calculate over
@param bits_per_symbol the number of information bits per symbol (BER only)
"""
#init
gr.hier_block2.__init__(
self,
'error_rate',
gr.io_signature(2, 2, gr.sizeof_char),
gr.io_signature(1, 1, gr.sizeof_float),
)
assert type in ('BER', 'SER')
self._max_samples = win_size
self._bits_per_symbol = bits_per_symbol
#setup message queue
msg_source = gr.message_source(gr.sizeof_float, 1)
self._msgq_source = msg_source.msgq()
msgq_sink = gr.msg_queue(2)
msg_sink = gr.message_sink(gr.sizeof_char, msgq_sink,
False) #False -> blocking
inter = gr.interleave(gr.sizeof_char)
#start thread
self._num_errs = 0
self._err_index = 0
self._num_samps = 0
self._err_array = numpy.zeros(self._max_samples, numpy.int8)
if type == 'BER':
input_watcher(msgq_sink, self._handler_ber)
elif type == 'SER':
input_watcher(msgq_sink, self._handler_ser)
#connect
self.connect(msg_source, self)
self.connect((self, 0), (inter, 0))
self.connect((self, 1), (inter, 1))
self.connect(inter, msg_sink)
def __init__(self, vlen=1):
"""!
Queue sink base contructor.
@param vlen the vector length
"""
self._vlen = vlen
#initialize hier2
gr.hier_block2.__init__(
self,
"queue_sink",
gr.io_signature(1, 1,
self._item_size * self._vlen), # Input signature
gr.io_signature(0, 0, 0) # Output signature
)
#create message sink
self._msgq = gr.msg_queue(4)
message_sink = gr.message_sink(self._item_size * self._vlen,
self._msgq, False) #False -> blocking
#connect
self.connect(self, message_sink)
self.arr = None
self.idx = 0
def __init__(
self,
parent,
baseband_freq=0,
ref_scale=2.0,
y_per_div=10,
y_divs=8,
ref_level=50,
sample_rate=1,
pspectrum_len=512,
specest_rate=specest_window.DEFAULT_FRAME_RATE,
average=False,
avg_alpha=None,
title='',
size=specest_window.DEFAULT_WIN_SIZE,
peak_hold=False,
use_persistence=False,
persist_alpha=None,
n = 1,
m = 150,
nsamples = 256,
estimator = 'esprit',
**kwargs #do not end with a comma
):
#ensure avg alpha
if avg_alpha is None: avg_alpha = 2.0/specest_rate
#ensure analog alpha
if persist_alpha is None:
actual_specest_rate=float(sample_rate/pspectrum_len)/float(max(1,int(float((sample_rate/pspectrum_len)/specest_rate))))
#print "requested_specest_rate ",specest_rate
#print "actual_specest_rate ",actual_specest_rate
analog_cutoff_freq=0.5 # Hertz
#calculate alpha from wanted cutoff freq
persist_alpha = 1.0 - math.exp(-2.0*math.pi*analog_cutoff_freq/actual_specest_rate)
#init
gr.hier_block2.__init__(
self,
"spectrum_sink",
gr.io_signature(1, 1, self._item_size),
gr.io_signature(0, 0, 0),
)
#blocks
fft = self._specest_chain(
sample_rate=sample_rate,
pspectrum_len=pspectrum_len,
frame_rate=specest_rate,
ref_scale=ref_scale,
avg_alpha=avg_alpha,
average=average,
n = n,
m = m,
nsamples = nsamples,
estimator = estimator
)
msgq = gr.msg_queue(2)
sink = gr.message_sink(gr.sizeof_float*pspectrum_len, msgq, True)
#controller
self.controller = pubsub()
self.controller.subscribe(AVERAGE_KEY, fft.set_average)
self.controller.publish(AVERAGE_KEY, fft.average)
self.controller.subscribe(AVG_ALPHA_KEY, fft.set_avg_alpha)
self.controller.publish(AVG_ALPHA_KEY, fft.avg_alpha)
self.controller.subscribe(SAMPLE_RATE_KEY, fft.set_sample_rate)
self.controller.publish(SAMPLE_RATE_KEY, fft.sample_rate)
#start input watcher
common.input_watcher(msgq, self.controller, MSG_KEY)
#create window
self.win = specest_window.specest_window(
parent=parent,
controller=self.controller,
size=size,
title=title,
real=self._real,
spectrum_len=pspectrum_len,
baseband_freq=baseband_freq,
sample_rate_key=SAMPLE_RATE_KEY,
y_per_div=y_per_div,
y_divs=y_divs,
ref_level=ref_level,
average_key=AVERAGE_KEY,
avg_alpha_key=AVG_ALPHA_KEY,
peak_hold=peak_hold,
msg_key=MSG_KEY,
use_persistence=use_persistence,
persist_alpha=persist_alpha,
)
common.register_access_methods(self, self.win)
setattr(self.win, 'set_baseband_freq', getattr(self, 'set_baseband_freq')) #BACKWARDS
setattr(self.win, 'set_peak_hold', getattr(self, 'set_peak_hold')) #BACKWARDS
#connect
self.wxgui_connect(self, fft, sink)
def __init__(
self,
sample_rate,
ber_threshold=0, # Above which to do search
ber_smoothing=0, # Alpha of BER smoother (0.01)
ber_duration=0, # Length before trying next combo
ber_sample_decimation=1,
settling_period=0,
pre_lock_duration=0,
#ber_sample_skip=0
**kwargs):
use_throttle = False
base_duration = 1024
if sample_rate > 0:
use_throttle = True
base_duration *= 4 # Has to be high enough for block-delay
if ber_threshold == 0:
ber_threshold = 512 * 4
if ber_smoothing == 0:
ber_smoothing = 0.01
if ber_duration == 0:
ber_duration = base_duration * 2 # 1000ms
if settling_period == 0:
settling_period = base_duration * 1 # 500ms
if pre_lock_duration == 0:
pre_lock_duration = base_duration * 2 #1000ms
print "Creating Auto-FEC:"
print "\tsample_rate:\t\t", sample_rate
print "\tber_threshold:\t\t", ber_threshold
print "\tber_smoothing:\t\t", ber_smoothing
print "\tber_duration:\t\t", ber_duration
print "\tber_sample_decimation:\t", ber_sample_decimation
print "\tsettling_period:\t", settling_period
print "\tpre_lock_duration:\t", pre_lock_duration
print ""
self.sample_rate = sample_rate
self.ber_threshold = ber_threshold
#self.ber_smoothing = ber_smoothing
self.ber_duration = ber_duration
self.settling_period = settling_period
self.pre_lock_duration = pre_lock_duration
#self.ber_sample_skip = ber_sample_skip
self.data_lock = threading.Lock()
gr.hier_block2.__init__(
self,
"auto_fec",
gr.io_signature(
1, 1,
gr.sizeof_gr_complex), # Post MPSK-receiver complex input
gr.io_signature3(
3, 3, gr.sizeof_char, gr.sizeof_float,
gr.sizeof_float)) # Decoded packed bytes, BER metric, lock
self.input_watcher = auto_fec_input_watcher(self)
default_xform = self.input_watcher.xform_lock
self.gr_conjugate_cc_0 = gr.conjugate_cc()
self.connect((self, 0), (self.gr_conjugate_cc_0, 0)) # Input
self.blks2_selector_0 = grc_blks2.selector(
item_size=gr.sizeof_gr_complex * 1,
num_inputs=2,
num_outputs=1,
input_index=default_xform.get_conjugation_index(),
output_index=0,
)
self.connect((self.gr_conjugate_cc_0, 0), (self.blks2_selector_0, 0))
self.connect((self, 0), (self.blks2_selector_0, 1)) # Input
self.gr_multiply_const_vxx_3 = gr.multiply_const_vcc(
(0.707 * (1 + 1j), ))
self.connect((self.blks2_selector_0, 0),
(self.gr_multiply_const_vxx_3, 0))
self.gr_multiply_const_vxx_2 = gr.multiply_const_vcc(
(default_xform.get_rotation(), )) # phase_mult
self.connect((self.gr_multiply_const_vxx_3, 0),
(self.gr_multiply_const_vxx_2, 0))
self.gr_complex_to_float_0_0 = gr.complex_to_float(1)
self.connect((self.gr_multiply_const_vxx_2, 0),
(self.gr_complex_to_float_0_0, 0))
self.gr_interleave_1 = gr.interleave(gr.sizeof_float * 1)
self.connect((self.gr_complex_to_float_0_0, 1),
(self.gr_interleave_1, 1))
self.connect((self.gr_complex_to_float_0_0, 0),
(self.gr_interleave_1, 0))
self.gr_multiply_const_vxx_0 = gr.multiply_const_vff((1, )) # invert
self.connect((self.gr_interleave_1, 0),
(self.gr_multiply_const_vxx_0, 0))
self.baz_delay_2 = baz.delay(
gr.sizeof_float * 1,
default_xform.get_puncture_delay()) # delay_puncture
self.connect((self.gr_multiply_const_vxx_0, 0), (self.baz_delay_2, 0))
self.depuncture_ff_0 = baz.depuncture_ff(
(_puncture_matrices[self.input_watcher.puncture_matrix][1]
)) # puncture_matrix
self.connect((self.baz_delay_2, 0), (self.depuncture_ff_0, 0))
self.baz_delay_1 = baz.delay(
gr.sizeof_float * 1,
default_xform.get_viterbi_delay()) # delay_viterbi
self.connect((self.depuncture_ff_0, 0), (self.baz_delay_1, 0))
self.swap_ff_0 = baz.swap_ff(
default_xform.get_viterbi_swap()) # swap_viterbi
self.connect((self.baz_delay_1, 0), (self.swap_ff_0, 0))
self.gr_decode_ccsds_27_fb_0 = gr.decode_ccsds_27_fb()
if use_throttle:
print "==> Using throttle at sample rate:", self.sample_rate
self.gr_throttle_0 = gr.throttle(gr.sizeof_float, self.sample_rate)
self.connect((self.swap_ff_0, 0), (self.gr_throttle_0, 0))
self.connect((self.gr_throttle_0, 0),
(self.gr_decode_ccsds_27_fb_0, 0))
else:
self.connect((self.swap_ff_0, 0),
(self.gr_decode_ccsds_27_fb_0, 0))
self.connect((self.gr_decode_ccsds_27_fb_0, 0),
(self, 0)) # Output bytes
self.gr_add_const_vxx_1 = gr.add_const_vff((-4096, ))
self.connect((self.gr_decode_ccsds_27_fb_0, 1),
(self.gr_add_const_vxx_1, 0))
self.gr_multiply_const_vxx_1 = gr.multiply_const_vff((-1, ))
self.connect((self.gr_add_const_vxx_1, 0),
(self.gr_multiply_const_vxx_1, 0))
self.connect((self.gr_multiply_const_vxx_1, 0),
(self, 1)) # Output BER
self.gr_single_pole_iir_filter_xx_0 = gr.single_pole_iir_filter_ff(
ber_smoothing, 1)
self.connect((self.gr_multiply_const_vxx_1, 0),
(self.gr_single_pole_iir_filter_xx_0, 0))
self.gr_keep_one_in_n_0 = blocks.keep_one_in_n(gr.sizeof_float,
ber_sample_decimation)
self.connect((self.gr_single_pole_iir_filter_xx_0, 0),
(self.gr_keep_one_in_n_0, 0))
self.const_source_x_0 = gr.sig_source_f(0, gr.GR_CONST_WAVE, 0, 0,
0) # Last param is const value
if use_throttle:
lock_throttle_rate = self.sample_rate // 16
print "==> Using lock throttle rate:", lock_throttle_rate
self.gr_throttle_1 = gr.throttle(gr.sizeof_float,
lock_throttle_rate)
self.connect((self.const_source_x_0, 0), (self.gr_throttle_1, 0))
self.connect((self.gr_throttle_1, 0), (self, 2))
else:
self.connect((self.const_source_x_0, 0), (self, 2))
self.msg_q = gr.msg_queue(
2 * 256
) # message queue that holds at most 2 messages, increase to speed up process
self.msg_sink = gr.message_sink(
gr.sizeof_float, self.msg_q,
dont_block=0) # Block to speed up process
self.connect((self.gr_keep_one_in_n_0, 0), self.msg_sink)
self.input_watcher.start()
def __init__(
self,
parent,
baseband_freq=0,
ref_level=50,
sample_rate=1,
fft_size=512,
fft_rate=waterfall_window.DEFAULT_FRAME_RATE,
average=False,
avg_alpha=None,
title='',
size=waterfall_window.DEFAULT_WIN_SIZE,
ref_scale=2.0,
dynamic_range=80,
num_lines=256,
win=None,
**kwargs #do not end with a comma
):
#ensure avg alpha
if avg_alpha is None: avg_alpha = 2.0 / fft_rate
#init
gr.hier_block2.__init__(
self,
"waterfall_sink",
gr.io_signature(1, 1, self._item_size),
gr.io_signature(0, 0, 0),
)
#blocks
fft = self._fft_chain(
sample_rate=sample_rate,
fft_size=fft_size,
frame_rate=fft_rate,
ref_scale=ref_scale,
avg_alpha=avg_alpha,
average=average,
win=win,
)
msgq = gr.msg_queue(2)
sink = gr.message_sink(gr.sizeof_float * fft_size, msgq, True)
#controller
self.controller = pubsub()
self.controller.subscribe(AVERAGE_KEY, fft.set_average)
self.controller.publish(AVERAGE_KEY, fft.average)
self.controller.subscribe(AVG_ALPHA_KEY, fft.set_avg_alpha)
self.controller.publish(AVG_ALPHA_KEY, fft.avg_alpha)
self.controller.subscribe(SAMPLE_RATE_KEY, fft.set_sample_rate)
self.controller.publish(SAMPLE_RATE_KEY, fft.sample_rate)
self.controller.subscribe(DECIMATION_KEY, fft.set_decimation)
self.controller.publish(DECIMATION_KEY, fft.decimation)
self.controller.subscribe(FRAME_RATE_KEY, fft.set_vec_rate)
self.controller.publish(FRAME_RATE_KEY, fft.frame_rate)
#start input watcher
common.input_watcher(msgq, self.controller, MSG_KEY)
#create window
self.win = waterfall_window.waterfall_window(
parent=parent,
controller=self.controller,
size=size,
title=title,
real=self._real,
fft_size=fft_size,
num_lines=num_lines,
baseband_freq=baseband_freq,
decimation_key=DECIMATION_KEY,
sample_rate_key=SAMPLE_RATE_KEY,
frame_rate_key=FRAME_RATE_KEY,
dynamic_range=dynamic_range,
ref_level=ref_level,
average_key=AVERAGE_KEY,
avg_alpha_key=AVG_ALPHA_KEY,
msg_key=MSG_KEY,
)
common.register_access_methods(self, self.win)
setattr(self.win, 'set_baseband_freq',
getattr(self, 'set_baseband_freq')) #BACKWARDS
#connect
self.wxgui_connect(self, fft, sink)
def __init__( self, baseband_freq =0, ref_scale = 2.0, y_per_div = 10, y_divs = 8, ref_level = 50, sample_rate = 1, fft_size = 512, fft_rate = 20, average = False, avg_alpha = None, title = '', size = (600, 300), peak_hold = False, win = None, use_persistence = False, persist_alpha = None, **kwargs ): #ensure avg alpha if avg_alpha is None: avg_alpha = 2.0 / fft_rate #ensure analog alpha if persist_alpha is None: actual_fft_rate = float(sample_rate / fft_size) / float(max(1, int(float((sample_rate / fft_size) / fft_rate)))) #print "requested_fft_rate ",fft_rate #print "actual_fft_rate ",actual_fft_rate analog_cutoff_freq = 0.5 # Hertz #calculate alpha from wanted cutoff freq persist_alpha = 1.0 - math.exp(-2.0*math.pi*analog_cutoff_freq/actual_fft_rate) #init gr.hier_block2.__init__( self, "zmq_fft_sink", gr.io_signature(1, 1, gr.sizeof_gr_complex), gr.io_signature(0, 0, 0), ) #blocks fft_0 = fft.logpwrfft_c( sample_rate = sample_rate, fft_size = fft_size, frame_rate = fft_rate, ref_scale = ref_scale, avg_alpha = avg_alpha, average = average, win = win, ) msgq = gr.msg_queue(2) sink = gr.message_sink(gr.sizeof_float*fft_size, msgq, True) #controller #self.controller = pubsub() #self.controller.subscribe(AVERAGE_KEY, fft_0.set_average) #self.controller.publish(AVERAGE_KEY, fft_0.average) #self.controller.subscribe(AVG_ALPHA_KEY, fft_0.set_avg_alpha) #self.controller.publish(AVG_ALPHA_KEY, fft_0.avg_alpha) #self.controller.subscribe(SAMPLE_RATE_KEY, fft_0.set_sample_rate) #self.controller.publish(SAMPLE_RATE_KEY, fft_0.sample_rate) #start input watcher input_watcher(msgq) #connect self.connect(self, fft_0, sink)
def __init__(self, options):
gr.top_block.__init__(self)
if options.rx_freq is not None:
u = uhd_receiver(options.args, options.bandwidth, options.rx_freq,
options.rx_gain, options.spec, options.antenna,
options.verbose)
elif options.infile is not None:
u = gr.file_source(gr.sizeof_gr_complex, options.infile)
else:
import sys
sys.stderr.write("--freq or --infile must be specified\n")
raise SystemExit
self.scope = None
if options.outfile is not None:
rx = gr.file_sink(gr.sizeof_gr_complex, options.outfile)
else:
rx = ofdm_rxtx.RX(options)
data_tones = rx.params.data_tones
if options.rxdata is not None:
if options.rxdata == '.':
import scope
# scope it out
rxs = gr.vector_to_stream(gr.sizeof_gr_complex, data_tones)
self.connect(rx, rxs)
self.scope = scope.scope(self,
rxs,
'Frame SNR',
isComplex=True)
else:
if options.char > 0:
# rail and scale
self.connect(
rx,
gr.vector_to_stream(gr.sizeof_float,
data_tones * 2),
gr.multiply_const_ff(128.0 * (2**0.5) /
options.char),
gr.rail_ff(-128.0, 127.0), gr.float_to_char(),
gr.file_sink(gr.sizeof_char, options.rxdata))
else:
self.connect(
rx,
gr.file_sink(data_tones * gr.sizeof_gr_complex,
options.rxdata))
if options.snrdata is not None:
# select one of the snr modes
snr = ofdm_rxtx.SNR(rx.params.data_tones,
options.size,
mode=options.snrmode)
if options.char > 0:
# NOTE: we use repeat, assuming the file is long enough or properly aligned
data = gr.stream_to_vector(gr.sizeof_float, data_tones * 2)
self.connect(
gr.file_source(gr.sizeof_char,
options.txdata,
repeat=True), gr.char_to_float(),
gr.multiply_const_ff(options.char * (2**-0.5) / 128.0),
data)
else:
data = ofdm_rxtx.make_data(rx.params.data_tones,
options.size, options.txdata)
self.connect(rx, (snr, 0))
self.connect(data, (snr, 1))
if options.snrdata == '-':
# print it out
msgq = gr.msg_queue(16)
self.connect(snr,
gr.message_sink(gr.sizeof_float, msgq, True))
self.watcher = ofdm_rxtx.queue_watcher(msgq)
elif options.snrdata == '.':
import scope
# scope it out
self.scope = scope.scope(self, snr, 'Frame SNR')
else:
self.connect(
snr, gr.file_sink(gr.sizeof_float, options.snrdata))
else:
pass
#self.connect(rx, gr.null_sink(symbol_size)) # XXX do we still need this?
self.connect(u, rx)
