def test_008_connect_invalid_dst_port_exceeds(self):
hblock = gr.hier_block2("test_block",
gr.io_signature(1, 1, gr.sizeof_int),
gr.io_signature(1, 1, gr.sizeof_int))
nop1 = blocks.null_sink(gr.sizeof_int)
nop2 = blocks.null_sink(gr.sizeof_int)
self.assertRaises(ValueError, lambda: hblock.connect(nop1, (nop2, 1)))
def test_008_connect_invalid_dst_port_exceeds(self):
hblock = gr.hier_block2("test_block",
gr.io_signature(1,1,gr.sizeof_int),
gr.io_signature(1,1,gr.sizeof_int))
nop1 = blocks.null_sink(gr.sizeof_int)
nop2 = blocks.null_sink(gr.sizeof_int)
self.assertRaises(ValueError,
lambda: hblock.connect(nop1, (nop2, 1)))
def test01(self):
sps = 4
rolloff = 0.35
bw = 2 * math.pi / 100.0
ntaps = 45
# Create pulse shape filter
rrc_taps = filter.firdes.root_raised_cosine(sps, sps, 1.0, rolloff,
ntaps)
# The frequency offset to correct
foffset = 0.2 / (2.0 * math.pi)
# Create a set of 1's and -1's, pulse shape and interpolate to sps
random.seed(0)
data = [2.0 * random.randint(0, 2) - 1.0 for i in xrange(200)]
self.src = blocks.vector_source_c(data, False)
self.rrc = filter.interp_fir_filter_ccf(sps, rrc_taps)
# Mix symbols with a complex sinusoid to spin them
self.nco = analog.sig_source_c(1, analog.GR_SIN_WAVE, foffset, 1)
self.mix = blocks.multiply_cc()
# FLL will despin the symbols to an arbitrary phase
self.fll = digital.fll_band_edge_cc(sps, rolloff, ntaps, bw)
# Create sinks for all outputs of the FLL
# we will only care about the freq and error outputs
self.vsnk_frq = blocks.vector_sink_f()
self.nsnk_fll = blocks.null_sink(gr.sizeof_gr_complex)
self.nsnk_phs = blocks.null_sink(gr.sizeof_float)
self.nsnk_err = blocks.null_sink(gr.sizeof_float)
# Connect the blocks
self.tb.connect(self.nco, (self.mix, 1))
self.tb.connect(self.src, self.rrc, (self.mix, 0))
self.tb.connect(self.mix, self.fll, self.nsnk_fll)
self.tb.connect((self.fll, 1), self.vsnk_frq)
self.tb.connect((self.fll, 2), self.nsnk_phs)
self.tb.connect((self.fll, 3), self.nsnk_err)
self.tb.run()
N = 700
dst_data = self.vsnk_frq.data()[N:]
expected_result = len(dst_data) * [
-0.20,
]
self.assertFloatTuplesAlmostEqual(expected_result, dst_data, 4)
def test_001(self):
# Just running some data through null source/sink
src = blocks.null_source(gr.sizeof_float)
hed = blocks.head(gr.sizeof_float, 100)
dst = blocks.null_sink(gr.sizeof_float)
self.tb.connect(src, hed, dst)
self.tb.run()
def test_001(self):
# Just running some data through null source/sink
src = blocks.null_source(gr.sizeof_float)
hed = blocks.head(gr.sizeof_float, 100)
dst = blocks.null_sink(gr.sizeof_float)
self.tb.connect(src, hed, dst)
self.tb.run()
def test01(self):
sps = 4
rolloff = 0.35
bw = 2 * math.pi / 100.0
ntaps = 45
# Create pulse shape filter
rrc_taps = filter.firdes.root_raised_cosine(sps, sps, 1.0, rolloff, ntaps)
# The frequency offset to correct
foffset = 0.2 / (2.0 * math.pi)
# Create a set of 1's and -1's, pulse shape and interpolate to sps
random.seed(0)
data = [2.0 * random.randint(0, 2) - 1.0 for i in xrange(200)]
self.src = blocks.vector_source_c(data, False)
self.rrc = filter.interp_fir_filter_ccf(sps, rrc_taps)
# Mix symbols with a complex sinusoid to spin them
self.nco = analog.sig_source_c(1, analog.GR_SIN_WAVE, foffset, 1)
self.mix = blocks.multiply_cc()
# FLL will despin the symbols to an arbitrary phase
self.fll = digital.fll_band_edge_cc(sps, rolloff, ntaps, bw)
# Create sinks for all outputs of the FLL
# we will only care about the freq and error outputs
self.vsnk_frq = blocks.vector_sink_f()
self.nsnk_fll = blocks.null_sink(gr.sizeof_gr_complex)
self.nsnk_phs = blocks.null_sink(gr.sizeof_float)
self.nsnk_err = blocks.null_sink(gr.sizeof_float)
# Connect the blocks
self.tb.connect(self.nco, (self.mix, 1))
self.tb.connect(self.src, self.rrc, (self.mix, 0))
self.tb.connect(self.mix, self.fll, self.nsnk_fll)
self.tb.connect((self.fll, 1), self.vsnk_frq)
self.tb.connect((self.fll, 2), self.nsnk_phs)
self.tb.connect((self.fll, 3), self.nsnk_err)
self.tb.run()
N = 700
dst_data = self.vsnk_frq.data()[N:]
expected_result = len(dst_data) * [-0.20]
self.assertFloatTuplesAlmostEqual(expected_result, dst_data, 4)
def mpsk_snr_est_setup(self, op):
result = []
for i in xrange(1,6):
src_data = [b+(i*n) for b,n in zip(self._bits, self._noise)]
src = blocks.vector_source_c(src_data)
dst = blocks.null_sink(gr.sizeof_gr_complex)
tb = gr.top_block()
tb.connect(src, op)
tb.connect(op, dst)
tb.run() # run the graph and wait for it to finish
result.append(op.snr())
return result
def mpsk_snr_est_setup(self, op):
result = []
for i in xrange(1, 6):
src_data = [b + (i * n) for b, n in zip(self._bits, self._noise)]
src = blocks.vector_source_c(src_data)
dst = blocks.null_sink(gr.sizeof_gr_complex)
tb = gr.top_block()
tb.connect(src, op)
tb.connect(op, dst)
tb.run() # run the graph and wait for it to finish
result.append(op.snr())
return result
