def test_010_vc(self):
vector_length = 10
repeats = 10
value = [complex(5,2)+i for i in range(0, vector_length)]
src_data = value * repeats
src = gr.vector_source_c(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vector_length)
dst = gr.probe_signal_vc(vector_length)
self.tb.connect(src, s2v, dst)
self.tb.run()
output = dst.level
self.assertEqual(len(output), vector_length)
self.assertComplexAlmostEqual(value[3], output[3], places=6)
def test_010_vc(self):
vector_length = 10
repeats = 10
value = [complex(5, 2) + i for i in range(0, vector_length)]
src_data = value * repeats
src = gr.vector_source_c(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vector_length)
dst = gr.probe_signal_vc(vector_length)
self.tb.connect(src, s2v, dst)
self.tb.run()
output = dst.level
self.assertEqual(len(output), vector_length)
self.assertComplexAlmostEqual(value[3], output[3], places=6)
def __init__(self, system, fftwidth=256, n=128, cutoff=100):
"""
Add blocks to the top_blocks that will be used for extracting the fft
from the flow graph for detection.
Args:
system: A wrapper for the top block.
fftwidth: The width of the fft used for detection.
n: The fft is only updated every 1 in n times.
cutoff: How sharp peaks need to be, to be detected.
"""
self.system = system
self.fftwidth = fftwidth
self.n = n
self.cutoff = cutoff
self.stream_to_vector = gr.stream_to_vector(gr.sizeof_gr_complex, fftwidth)
self.keep_one_in_n = gr.keep_one_in_n(gr.sizeof_gr_complex*fftwidth, n)
self.fft = gr.fft_vcc(fftwidth, True, window.blackmanharris(fftwidth))
self.probe = gr.probe_signal_vc(fftwidth)
system.connect(system.out, self.stream_to_vector, self.keep_one_in_n,
self.fft, self.probe)