def test_002_t (self): #print "TEST: discarded carriers and num sync words" # set up fg test_len = 200 vlen = 20 ts_len = test_len/vlen discarded_carriers = (-8,-4,-2,1,2,3,9) num_sync_words = 2 in_data0 = [0]*test_len in_data1 = [0]*test_len for k in range(test_len): in_data0[k] = complex(k-4, k+1) in_data1[k] = complex(k+3, k-2) src0 = blocks.vector_source_c(in_data0) s2v0 = blocks.stream_to_vector(8,vlen) s2ts0 = blocks.stream_to_tagged_stream(8,vlen,ts_len,'packet_len') src1 = blocks.vector_source_c(in_data1) s2v1 = blocks.stream_to_vector(8,vlen) s2ts1 = blocks.stream_to_tagged_stream(8,vlen,ts_len,'packet_len') div = radar.ofdm_divide_vcvc(vlen,vlen,discarded_carriers,num_sync_words) v2s = blocks.vector_to_stream(8,vlen) snk = blocks.vector_sink_c() self.tb.connect(src0,s2v0,s2ts0) self.tb.connect(src1,s2v1,s2ts1) self.tb.connect((s2ts0,0),(div,0)) self.tb.connect((s2ts1,0),(div,1)) self.tb.connect(div,v2s,snk) self.tb.run () # get ref data discarded_carriers_shift = [0]*len(discarded_carriers) for k in range(len(discarded_carriers)): discarded_carriers_shift[k] = discarded_carriers[k] + vlen/2 ref_data = [0]*test_len for k in range(test_len/vlen): for l in range(vlen): if k < num_sync_words: # do not process sync words with discarded carriers ref_data[vlen*k+l] = in_data0[vlen*k+l]/in_data1[vlen*k+l] else: # process discarded carriers if l in discarded_carriers_shift: # if actual item shall be discarded ref_data[vlen*k+l] = 0 else: # if actual item shall NOT be discarded ref_data[vlen*k+l] = in_data0[vlen*k+l]/in_data1[vlen*k+l] # check data #print "REF" #print ref_data out_data = snk.data() #print "DATA" #print out_data for k in range(len(out_data)): self.assertAlmostEqual(ref_data[k], out_data[k],4)
def test_001_t(self):
#print "TEST: division without discarded carriers and sync words"
# set up fg
test_len = 20
vlen = 5
ts_len = test_len / vlen / 2
in_data0 = [0] * test_len
in_data1 = [0] * test_len
for k in range(test_len):
in_data0[k] = complex(k - 4, k + 1)
in_data1[k] = complex(k + 3, k - 2)
src0 = blocks.vector_source_c(in_data0)
s2v0 = blocks.stream_to_vector(8, vlen)
s2ts0 = blocks.stream_to_tagged_stream(8, vlen, ts_len, 'packet_len')
src1 = blocks.vector_source_c(in_data1)
s2v1 = blocks.stream_to_vector(8, vlen)
s2ts1 = blocks.stream_to_tagged_stream(8, vlen, ts_len, 'packet_len')
div = radar.ofdm_divide_vcvc(vlen, 2 * vlen, (), 0)
v2s = blocks.vector_to_stream(8, 2 * vlen)
snk = blocks.vector_sink_c()
self.tb.connect(src0, s2v0, s2ts0)
self.tb.connect(src1, s2v1, s2ts1)
self.tb.connect((s2ts0, 0), (div, 0))
self.tb.connect((s2ts1, 0), (div, 1))
self.tb.connect(div, v2s, snk)
self.tb.run()
# get ref data
ref_data = [0] * test_len * 2
for k in range(test_len // vlen):
for l in range(vlen):
ref_data[2 * vlen * k +
l] = in_data0[vlen * k + l] / in_data1[vlen * k + l]
# check data
out_data = snk.data()
for k in range(len(out_data)):
self.assertAlmostEqual(ref_data[k], out_data[k], 4)
def test_001_t (self): #print "TEST: division without discarded carriers and sync words" # set up fg test_len = 20 vlen = 5 ts_len = test_len/vlen/2 in_data0 = [0]*test_len in_data1 = [0]*test_len for k in range(test_len): in_data0[k] = complex(k-4, k+1) in_data1[k] = complex(k+3, k-2) src0 = blocks.vector_source_c(in_data0) s2v0 = blocks.stream_to_vector(8,vlen) s2ts0 = blocks.stream_to_tagged_stream(8,vlen,ts_len,'packet_len') src1 = blocks.vector_source_c(in_data1) s2v1 = blocks.stream_to_vector(8,vlen) s2ts1 = blocks.stream_to_tagged_stream(8,vlen,ts_len,'packet_len') div = radar.ofdm_divide_vcvc(vlen,2*vlen,(),0) v2s = blocks.vector_to_stream(8,2*vlen) snk = blocks.vector_sink_c() self.tb.connect(src0,s2v0,s2ts0) self.tb.connect(src1,s2v1,s2ts1) self.tb.connect((s2ts0,0),(div,0)) self.tb.connect((s2ts1,0),(div,1)) self.tb.connect(div,v2s,snk) self.tb.run () # get ref data ref_data = [0]*test_len*2 for k in range(test_len/vlen): for l in range(vlen): ref_data[2*vlen*k+l] = in_data0[vlen*k+l]/in_data1[vlen*k+l] # check data out_data = snk.data() for k in range(len(out_data)): self.assertAlmostEqual(ref_data[k], out_data[k],4)
