def __init__(self, interp, taps=None, atten=100):
gr.hier_block2.__init__(self, "pfb_interpolator_ccf",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self._interp = interp
self._taps = taps
if (taps is not None) and (len(taps) > 0):
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.99
made = False
while not made:
try:
self._taps = optfir.low_pass(self._interp, self._interp, bw, bw+tb, ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print("Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps." % (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if(ripple >= 1.0):
raise RuntimeError("optfir could not generate an appropriate filter.")
self.pfb = filter.pfb_interpolator_ccf(self._interp, self._taps)
self.connect(self, self.pfb)
self.connect(self.pfb, self)
def __init__(self, rate, taps=None, flt_size=32, atten=100):
gr.hier_block2.__init__(self, "pfb_arb_resampler_ccc",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
self._rate = rate
self._size = flt_size
if (taps is not None) and (len(taps) > 0):
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.1
#self._taps = filter.firdes.low_pass_2(self._size, self._size, bw, tb, atten)
made = False
while not made:
try:
self._taps = optfir.low_pass(self._size, self._size, bw, bw+tb, ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print("Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps." % (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if(ripple >= 1.0):
raise RuntimeError("optfir could not generate an appropriate filter.")
self.pfb = filter.pfb_arb_resampler_ccc(self._rate, self._taps, self._size)
#print "PFB has %d taps\n" % (len(self._taps),)
self.connect(self, self.pfb)
self.connect(self.pfb, self)
def __init__(self, n_chans, n_filterbanks=1, taps=None, outchans=None,
atten=100, bw=1.0, tb=0.2, ripple=0.1):
if n_filterbanks > n_chans:
n_filterbanks = n_chans
if outchans is None:
outchans = range(n_chans)
gr.hier_block2.__init__(
self, "pfb_channelizer_hier_ccf",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(len(outchans), len(outchans), gr.sizeof_gr_complex))
if taps is None:
taps = optfir.low_pass(1, n_chans, bw, bw+tb, ripple, atten)
taps = list(taps)
extra_taps = int(math.ceil(1.0*len(taps)/n_chans)*n_chans - len(taps))
taps = taps + [0] * extra_taps
# Make taps for each channel
chantaps = [list(reversed(taps[i: len(taps): n_chans])) for i in range(0, n_chans)]
# Convert the input stream into a stream of vectors.
self.s2v = blocks.stream_to_vector(gr.sizeof_gr_complex, n_chans)
# Create a mapping to separate out each filterbank (a group of channels to be processed together)
# And a list of sets of taps for each filterbank.
low_cpp = int(n_chans/n_filterbanks)
extra = n_chans - low_cpp*n_filterbanks
cpps = [low_cpp+1]*extra + [low_cpp]*(n_filterbanks-extra)
splitter_mapping = []
filterbanktaps = []
total = 0
for cpp in cpps:
splitter_mapping.append([(0, i) for i in range(total, total+cpp)])
filterbanktaps.append(chantaps[total: total+cpp])
total += cpp
assert(total == n_chans)
# Split the stream of vectors in n_filterbanks streams of vectors.
self.splitter = blocks.vector_map(gr.sizeof_gr_complex, [n_chans], splitter_mapping)
# Create the filterbanks
self.fbs = [filter.filterbank_vcvcf(taps) for taps in filterbanktaps]
# Combine the streams of vectors back into a single stream of vectors.
combiner_mapping = [[]]
for i, cpp in enumerate(cpps):
for j in range(cpp):
combiner_mapping[0].append((i, j))
self.combiner = blocks.vector_map(gr.sizeof_gr_complex, cpps, combiner_mapping)
# Add the final FFT to the channelizer.
self.fft = fft.fft_vcc(n_chans, forward=True, window=[1.0]*n_chans)
# Select the desired channels
if outchans != range(n_chans):
selector_mapping = [[(0, i) for i in outchans]]
self.selector = blocks.vector_map(gr.sizeof_gr_complex, [n_chans], selector_mapping)
# Convert stream of vectors to a normal stream.
self.v2ss = blocks.vector_to_streams(gr.sizeof_gr_complex, len(outchans))
self.connect(self, self.s2v, self.splitter)
for i in range(0, n_filterbanks):
self.connect((self.splitter, i), self.fbs[i], (self.combiner, i))
self.connect(self.combiner, self.fft)
if outchans != range(n_chans):
self.connect(self.fft, self.selector, self.v2ss)
else:
self.connect(self.fft, self.v2ss)
for i in range(0, len(outchans)):
self.connect((self.v2ss, i), (self, i))
def __init__(self, interp, taps=None, atten=100):
gr.hier_block2.__init__(self, "pfb_interpolator_ccf",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self._interp = interp
self._taps = taps
if (taps is not None) and (len(taps) > 0):
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.99
made = False
while not made:
try:
self._taps = optfir.low_pass(self._interp, self._interp, bw, bw+tb, ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print("Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps." % (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if(ripple >= 1.0):
raise RuntimeError("optfir could not generate an appropriate filter.")
self.pfb = filter.pfb_interpolator_ccf(self._interp, self._taps)
self.connect(self, self.pfb)
self.connect(self.pfb, self)
def __init__(self, rate, taps=None, flt_size=32, atten=100):
gr.hier_block2.__init__(self, "pfb_arb_resampler_fff",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self._rate = rate
self._size = flt_size
if (taps is not None) and (len(taps) > 0):
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.1
#self._taps = filter.firdes.low_pass_2(self._size, self._size, bw, tb, atten)
made = False
while not made:
try:
self._taps = optfir.low_pass(self._size, self._size, bw, bw+tb, ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print("Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps." % (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if(ripple >= 1.0):
raise RuntimeError("optfir could not generate an appropriate filter.")
self.pfb = filter.pfb_arb_resampler_fff(self._rate, self._taps, self._size)
#print "PFB has %d taps\n" % (len(self._taps),)
self.connect(self, self.pfb)
self.connect(self.pfb, self)
def __init__(self, rate, taps=None, flt_size=32, atten=100):
gr.hier_block2.__init__(self, "pfb_arb_resampler_fff",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self._rate = rate
self._size = flt_size
if (taps is not None) and (len(taps) > 0):
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
# If rate >= 1, we need to prevent images in the output,
# so we have to filter it to less than half the channel
# width of 0.5. If rate < 1, we need to filter to less
# than half the output signal's bw to avoid aliasing, so
# the half-band here is 0.5*rate.
percent = 0.80
if(self._rate < 1):
halfband = 0.5*self._rate
bw = percent*halfband
tb = (percent/2.0)*halfband
ripple = 0.1
# As we drop the bw factor, the optfir filter has a harder time converging;
# using the firdes method here for better results.
self._taps = filter.firdes.low_pass_2(self._size, self._size, bw, tb, atten,
filter.firdes.WIN_BLACKMAN_HARRIS)
else:
halfband = 0.5
bw = percent*halfband
tb = (percent/2.0)*halfband
ripple = 0.1
made = False
while not made:
try:
self._taps = optfir.low_pass(self._size, self._size, bw, bw+tb, ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print("Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps." % (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if(ripple >= 1.0):
raise RuntimeError("optfir could not generate an appropriate filter.")
self.pfb = filter.pfb_arb_resampler_fff(self._rate, self._taps, self._size)
#print "PFB has %d taps\n" % (len(self._taps),)
self.connect(self, self.pfb)
self.connect(self.pfb, self)
def __init__(self,
decim,
taps=None,
channel=0,
atten=100,
use_fft_rotators=True,
use_fft_filters=True):
gr.hier_block2.__init__(self, "pfb_decimator_ccf",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self._decim = decim
self._channel = channel
if (taps is not None) and (len(taps) > 0):
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.1
made = False
while not made:
try:
self._taps = optfir.low_pass(1, self._decim, bw, bw + tb,
ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print(
"Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps."
% (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if (ripple >= 1.0):
raise RuntimeError(
"optfir could not generate an appropriate filter.")
self.s2ss = blocks.stream_to_streams(gr.sizeof_gr_complex, self._decim)
self.pfb = filter.pfb_decimator_ccf(self._decim, self._taps,
self._channel, use_fft_rotators,
use_fft_filters)
self.connect(self, self.s2ss)
for i in xrange(self._decim):
self.connect((self.s2ss, i), (self.pfb, i))
self.connect(self.pfb, self)
def __init__(self, numchans, taps=None, oversample_rate=1, atten=100):
gr.hier_block2.__init__(
self, "pfb_channelizer_ccf",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(numchans, numchans, gr.sizeof_gr_complex))
self._nchans = numchans
self._oversample_rate = oversample_rate
if taps is not None:
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.1
made = False
while not made:
try:
self._taps = optfir.low_pass(1, self._nchans, bw, bw + tb,
ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print(
"Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps."
% (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if (ripple >= 1.0):
raise RuntimeError(
"optfir could not generate an appropriate filter.")
self.s2ss = gr.stream_to_streams(gr.sizeof_gr_complex, self._nchans)
self.pfb = filter.pfb_channelizer_ccf(self._nchans, self._taps,
self._oversample_rate)
self.connect(self, self.s2ss)
for i in xrange(self._nchans):
self.connect((self.s2ss, i), (self.pfb, i))
self.connect((self.pfb, i), (self, i))
def __init__(self, decim, taps=None, channel=0, atten=100,
use_fft_rotators=True, use_fft_filters=True):
gr.hier_block2.__init__(self, "pfb_decimator_ccf",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self._decim = decim
self._channel = channel
if (taps is not None) and (len(taps) > 0):
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.1
made = False
while not made:
try:
self._taps = optfir.low_pass(1, self._decim, bw, bw+tb, ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print("Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps." % (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if(ripple >= 1.0):
raise RuntimeError("optfir could not generate an appropriate filter.")
self.s2ss = blocks.stream_to_streams(gr.sizeof_gr_complex, self._decim)
self.pfb = filter.pfb_decimator_ccf(self._decim, self._taps, self._channel,
use_fft_rotators, use_fft_filters)
self.connect(self, self.s2ss)
for i in xrange(self._decim):
self.connect((self.s2ss,i), (self.pfb,i))
self.connect(self.pfb, self)
def __init__(self, numchans, taps=None, oversample_rate=1, atten=100):
gr.hier_block2.__init__(self, "pfb_channelizer_ccf",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(numchans, numchans, gr.sizeof_gr_complex))
self._nchans = numchans
self._oversample_rate = oversample_rate
if taps is not None:
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.1
made = False
while not made:
try:
self._taps = optfir.low_pass(1, self._nchans, bw, bw+tb, ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print("Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps." % (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if(ripple >= 1.0):
raise RuntimeError("optfir could not generate an appropriate filter.")
self.s2ss = gr.stream_to_streams(gr.sizeof_gr_complex, self._nchans)
self.pfb = filter.pfb_channelizer_ccf(self._nchans, self._taps,
self._oversample_rate)
self.connect(self, self.s2ss)
for i in xrange(self._nchans):
self.connect((self.s2ss,i), (self.pfb,i))
self.connect((self.pfb,i), (self,i))
def __init__(self,
n_chans,
n_filterbanks=1,
taps=None,
outchans=None,
atten=100,
bw=1.0,
tb=0.2,
ripple=0.1):
if n_filterbanks > n_chans:
n_filterbanks = n_chans
if outchans is None:
outchans = range(n_chans)
gr.hier_block2.__init__(
self, "pfb_channelizer_hier_ccf",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(len(outchans), len(outchans),
gr.sizeof_gr_complex))
if taps is None:
taps = optfir.low_pass(1, n_chans, bw, bw + tb, ripple, atten)
taps = list(taps)
extra_taps = int(
math.ceil(1.0 * len(taps) / n_chans) * n_chans - len(taps))
taps = taps + [0] * extra_taps
# Make taps for each channel
chantaps = [
list(reversed(taps[i:len(taps):n_chans]))
for i in range(0, n_chans)
]
# Convert the input stream into a stream of vectors.
self.s2v = blocks.stream_to_vector(gr.sizeof_gr_complex, n_chans)
# Create a mapping to separate out each filterbank (a group of channels to be processed together)
# And a list of sets of taps for each filterbank.
low_cpp = int(n_chans / n_filterbanks)
extra = n_chans - low_cpp * n_filterbanks
cpps = [low_cpp + 1] * extra + [low_cpp] * (n_filterbanks - extra)
splitter_mapping = []
filterbanktaps = []
total = 0
for cpp in cpps:
splitter_mapping.append([(0, i)
for i in range(total, total + cpp)])
filterbanktaps.append(chantaps[total:total + cpp])
total += cpp
assert (total == n_chans)
# Split the stream of vectors in n_filterbanks streams of vectors.
self.splitter = blocks.vector_map(gr.sizeof_gr_complex, [n_chans],
splitter_mapping)
# Create the filterbanks
self.fbs = [filter.filterbank_vcvcf(taps) for taps in filterbanktaps]
# Combine the streams of vectors back into a single stream of vectors.
combiner_mapping = [[]]
for i, cpp in enumerate(cpps):
for j in range(cpp):
combiner_mapping[0].append((i, j))
self.combiner = blocks.vector_map(gr.sizeof_gr_complex, cpps,
combiner_mapping)
# Add the final FFT to the channelizer.
self.fft = fft.fft_vcc(n_chans, forward=True, window=[1.0] * n_chans)
# Select the desired channels
if outchans != range(n_chans):
selector_mapping = [[(0, i) for i in outchans]]
self.selector = blocks.vector_map(gr.sizeof_gr_complex, [n_chans],
selector_mapping)
# Convert stream of vectors to a normal stream.
self.v2ss = blocks.vector_to_streams(gr.sizeof_gr_complex,
len(outchans))
self.connect(self, self.s2v, self.splitter)
for i in range(0, n_filterbanks):
self.connect((self.splitter, i), self.fbs[i], (self.combiner, i))
self.connect(self.combiner, self.fft)
if outchans != range(n_chans):
self.connect(self.fft, self.selector, self.v2ss)
else:
self.connect(self.fft, self.v2ss)
for i in range(0, len(outchans)):
self.connect((self.v2ss, i), (self, i))
def __init__(self, rate, taps=None, flt_size=32, atten=100):
gr.hier_block2.__init__(
self,
"pfb_arb_resampler_fff",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self._rate = rate
self._size = flt_size
if (taps is not None) and (len(taps) > 0):
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
# If rate >= 1, we need to prevent images in the output,
# so we have to filter it to less than half the channel
# width of 0.5. If rate < 1, we need to filter to less
# than half the output signal's bw to avoid aliasing, so
# the half-band here is 0.5*rate.
percent = 0.80
if (self._rate < 1):
halfband = 0.5 * self._rate
bw = percent * halfband
tb = (percent / 2.0) * halfband
ripple = 0.1
# As we drop the bw factor, the optfir filter has a harder time converging;
# using the firdes method here for better results.
self._taps = filter.firdes.low_pass_2(
self._size, self._size, bw, tb, atten,
filter.firdes.WIN_BLACKMAN_HARRIS)
else:
halfband = 0.5
bw = percent * halfband
tb = (percent / 2.0) * halfband
ripple = 0.1
made = False
while not made:
try:
self._taps = optfir.low_pass(self._size, self._size,
bw, bw + tb, ripple,
atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print(
"Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps."
% (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if (ripple >= 1.0):
raise RuntimeError(
"optfir could not generate an appropriate filter."
)
self.pfb = filter.pfb_arb_resampler_fff(self._rate, self._taps,
self._size)
#print "PFB has %d taps\n" % (len(self._taps),)
self.connect(self, self.pfb)
self.connect(self.pfb, self)
