def _basic_tbn(fh, stands, nframes, **kwargs):
"""
Private function for generating a basic TBN signal.
"""
start_time = kwargs['start_time']
filter = kwargs['filter']
verbose = kwargs['verbose']
noise_strength = kwargs['noise_strength']
sample_rate = TBNFilters[filter]
maxValue = 127
samplesPerFrame = 512
upperSpike = sample_rate / 4.0
lowerSpike = -sample_rate / 4.0
if verbose:
print("Simulating %i frames of TBN Data @ %.2f kHz for %i stands:" % \
(nframes, sample_rate/1e3, len(stands)))
for i in range(nframes):
if i % 1000 == 0 and verbose:
print(" frame %i" % (i + 1))
t = int(start_time * dp_common.fS) + int(
i * dp_common.fS * samplesPerFrame / sample_rate)
tFrame = t / dp_common.fS - start_time + numpy.arange(
samplesPerFrame, dtype=numpy.float32) / sample_rate
for stand in stands:
cFrame = tbn.SimFrame(stand=stand,
pol=0,
central_freq=40e6,
gain=20,
frame_count=i + 1,
obs_time=t)
cFrame.data = numpy.zeros(samplesPerFrame,
dtype=numpy.singlecomplex)
cFrame.data += numpy.random.randn(
samplesPerFrame) + 1j * numpy.random.randn(samplesPerFrame)
cFrame.data *= maxValue * noise_strength
cFrame.data += maxValue * numpy.exp(
2j * numpy.pi * upperSpike * tFrame)
cFrame.write_raw_frame(fh)
cFrame = tbn.SimFrame(stand=stand,
pol=1,
central_freq=40e6,
gain=20,
frame_count=i + 1,
obs_time=t)
cFrame.data = numpy.zeros(samplesPerFrame,
dtype=numpy.singlecomplex)
cFrame.data += numpy.random.randn(
samplesPerFrame) + 1j * numpy.random.randn(samplesPerFrame)
cFrame.data *= maxValue * noise_strength
cFrame.data += maxValue * numpy.exp(
2j * numpy.pi * lowerSpike * tFrame)
cFrame.write_raw_frame(fh)
def test_sim_frame(self):
"""Test the tbn.SimFrame class."""
# Read in a TBN frame from the test file
fh = open(tbnFile, 'rb')
origFrame = tbnReader.read_frame(fh)
fh.close()
fakeFrame = tbnWriter.SimFrame()
fakeFrame.load_frame(origFrame)
# Test the validity of the SimFrame
self.assertTrue(fakeFrame.is_valid())
def test_frame_header_errors(self):
"""Test the header error scenarios when validating a TBN SimFrame."""
# Read in a TBN frame from the test file
fh = open(tbnFile, 'rb')
origFrame = tbnReader.read_frame(fh)
fh.close()
# Try to validate frame with the wrong stand number
fakeFrame = tbnWriter.SimFrame()
fakeFrame.load_frame(copy.deepcopy(origFrame))
fakeFrame.stand = 300
self.assertRaises(ValueError, fakeFrame.is_valid, raise_errors=True)
def test_frame_data_errors(self):
"""Test the data error scenarios when validating a TBN SimFrame."""
# Read in a TBN frame from the test file
fh = open(tbnFile, 'rb')
origFrame = tbnReader.read_frame(fh)
fh.close()
# Try to validate frame with the wrong data type
fakeFrame = tbnWriter.SimFrame()
fakeFrame.load_frame(copy.deepcopy(origFrame))
fakeFrame.data = fakeFrame.payload.data.real
self.assertRaises(ValueError, fakeFrame.is_valid, raise_errors=True)
# Try to validate frame with the wrong data size
fakeFrame = tbnWriter.SimFrame()
fakeFrame.load_frame(copy.deepcopy(origFrame))
fakeFrame.data = None
self.assertRaises(ValueError, fakeFrame.is_valid, raise_errors=True)
fakeFrame = tbnWriter.SimFrame()
fakeFrame.load_frame(copy.deepcopy(origFrame))
fakeFrame.data = fakeFrame.payload.data[0:50]
self.assertRaises(ValueError, fakeFrame.is_valid, raise_errors=True)
def _point_source_tbn(fh, stands, src, nframes, **kwargs):
"""
Private function to build TBN point sources.
"""
central_freq = kwargs['central_freq']
filter = kwargs['filter']
start_time = kwargs['start_time']
phase_center = kwargs['phase_center']
verbose = kwargs['verbose']
noise_strength = kwargs['noise_strength']
sample_rate = TBNFilters[filter]
maxValue = 127
samplesPerFrame = 512
freqs = (numpy.fft.fftfreq(samplesPerFrame,
d=1.0 / sample_rate)) + central_freq
freqs = numpy.fft.fftshift(freqs)
aa = _get_antennaarray(lwa_common.lwa1, stands, start_time, freqs)
if verbose:
print("Simulating %i frames of TBN Data @ %.2f kHz for %i stands:" % \
(nframes, sample_rate/1e3, len(stands)))
for i in range(nframes):
if i % 1000 == 0 and verbose:
print(" frame %i" % (i + 1))
t = int(start_time * dp_common.fS) + int(
i * dp_common.fS * samplesPerFrame / sample_rate)
tFrame = t / dp_common.fS - start_time + numpy.arange(
samplesPerFrame, dtype=numpy.float32) / sample_rate
# Get the source parameters
src_params = _get_source_parameters(aa, tFrame[0], src)
# Generate the time series response of each signal at each frequency
tdSignalsX = _build_signals(aa,
stands,
src_params,
tFrame * 1e9,
pol='x',
phase_center=phase_center)
tdSignalsY = _build_signals(aa,
stands,
src_params,
tFrame * 1e9,
pol='y',
phase_center=phase_center)
j = 0
for stand in stands:
cFrame = tbn.SimFrame(stand=stand.stand.id,
pol=0,
central_freq=central_freq,
gain=19,
frame_count=i + 1,
obs_time=t)
cFrame.data = numpy.zeros(samplesPerFrame,
dtype=numpy.singlecomplex)
cFrame.data += numpy.random.randn(
samplesPerFrame) + 1j * numpy.random.randn(samplesPerFrame)
cFrame.data *= maxValue * noise_strength
cFrame.data += maxValue * tdSignalsX[j, :].astype(
numpy.singlecomplex)
cFrame.write_raw_frame(fh)
cFrame = tbn.SimFrame(stand=stand.stand.id,
pol=1,
central_freq=central_freq,
gain=19,
frame_count=i + 1,
obs_time=t)
cFrame.data = numpy.zeros(samplesPerFrame,
dtype=numpy.singlecomplex)
cFrame.data += numpy.random.randn(
samplesPerFrame) + 1j * numpy.random.randn(samplesPerFrame)
cFrame.data *= maxValue * noise_strength
cFrame.data += maxValue * tdSignalsY[j, :].astype(
numpy.singlecomplex)
cFrame.write_raw_frame(fh)
j += 1