def test__002_t(self):
"""
Generate a signal with SNR as given below.
Calculate the RMSE.
"""
nsamples = 1024
n_trials = 100
samp_rate = 32000
SNR = 20 # in dB
self.siggen = siggen.signal_generator(n_sinusoids=1,
SNR=SNR,
samp_rate=samp_rate,
nsamples=nsamples * n_trials)
self.stream = gr.stream_to_vector(gr.sizeof_gr_complex, nsamples)
self.esprit = specest.esprit_vcf(n=1, m=64, nsamples=nsamples)
self.sink = gr.vector_sink_f(vlen=1)
# wire it up ...
self.tb.connect(self.siggen, self.stream, self.esprit, self.sink)
self.tb.run()
MSE = 0.0
omega = self.siggen.omegas()[0]
for i in range(n_trials):
MSE += (omega - self.sink.data()[i])**2.0
print '\n' + 70 * '-'
print 'Testing specest_esprit_vcf ...'
print 'Ran %u trials to estimate the frequency' % n_trials
print 'Used %u samples to estimate the frequency' % nsamples
print 'Sampling rate %s' % eng_notation.num_to_str(samp_rate)
print 'SNR of %u dB' % SNR
print 'Root mean square error %g' % numpy.sqrt(MSE / n_trials)
print 'Cramer-Rao Bound %g' % numpy.sqrt(
6 / 10**(SNR / 10.0) / nsamples**3)
print 70 * '-'
def test__002_t (self):
"""
Generate a signal with SNR as given below.
Calculate the RMSE.
"""
nsamples = 1024
n_trials = 100
samp_rate = 32000
SNR = 20 # in dB
self.siggen = siggen.signal_generator(n_sinusoids = 1,
SNR = SNR, samp_rate = samp_rate,
nsamples = nsamples * n_trials)
self.stream = gr.stream_to_vector(gr.sizeof_gr_complex, nsamples)
self.esprit = specest.esprit_vcf(n=1, m=64, nsamples = nsamples)
self.sink = gr.vector_sink_f(vlen=1)
# wire it up ...
self.tb.connect(self.siggen, self.stream, self.esprit, self.sink)
self.tb.run()
MSE = 0.0
omega = self.siggen.omegas()[0]
for i in range(n_trials):
MSE += (omega - self.sink.data()[i])**2.0
print '\n' + 70*'-'
print 'Testing specest_esprit_vcf ...'
print 'Ran %u trials to estimate the frequency' % n_trials
print 'Used %u samples to estimate the frequency' % nsamples
print 'Sampling rate %s' % eng_notation.num_to_str(samp_rate)
print 'SNR of %u dB' % SNR
print 'Root mean square error %g' % numpy.sqrt(MSE/n_trials)
print 'Cramer-Rao Bound %g' % numpy.sqrt(6/10**(SNR/10.0)/nsamples**3)
print 70*'-'
def test__001_t(self):
"""
Generate a signal with n_sinusoids sinusoids
and a SNR of SNR.
Another Check to see if it's working at all.
"""
n_sinusoids = 2
nsamples = 2048
samp_rate = 32000
SNR = 10 # in dB
decimals = 3
self.siggen = siggen.signal_generator(n_sinusoids=n_sinusoids,
SNR=SNR,
samp_rate=samp_rate,
nsamples=nsamples)
self.stream = gr.stream_to_vector(gr.sizeof_gr_complex, nsamples)
self.esprit = specest.esprit_vcf(n=n_sinusoids,
m=100,
nsamples=nsamples)
self.sink = gr.vector_sink_f(vlen=n_sinusoids)
# wire it up ...
self.tb.connect(self.siggen, self.stream, self.esprit, self.sink)
for i in range(100):
self.tb.run()
for (g, e) in zip(sorted(list(self.sink.data())),
self.siggen.omegas()):
self.assertAlmostEqual(g, e, decimals)
def test__001_t (self):
"""
Generate a signal with n_sinusoids sinusoids
and a SNR of SNR.
Another Check to see if it's working at all.
"""
n_sinusoids = 2
nsamples = 2048
samp_rate = 32000
SNR = 10 # in dB
decimals = 3
self.siggen = siggen.signal_generator(n_sinusoids = n_sinusoids,
SNR = SNR, samp_rate = samp_rate,
nsamples = nsamples)
self.stream = blocks.stream_to_vector(gr.sizeof_gr_complex, nsamples)
self.esprit = specest.esprit_vcf(n=n_sinusoids, m=100, nsamples = nsamples)
self.sink = blocks.vector_sink_f(vlen=n_sinusoids)
self.tb.connect(self.siggen, self.stream, self.esprit, self.sink)
for i in range(100):
self.tb.run()
for (g,e) in zip(sorted(list(self.sink.data())), self.siggen.omegas()):
self.assertAlmostEqual(g,e, decimals)
