def __init__(self, decoder_list_0, input_size, output_size):
gr.hier_block2.__init__(
self, "Threaded Decoder",
gr.io_signature(1, 1, input_size*1),
gr.io_signature(1, 1, output_size*1))
self.decoder_list_0 = decoder_list_0
self.deinterleave_0 = blocks.deinterleave(input_size,
fec.get_decoder_input_size(decoder_list_0[0]))
self.generic_decoders_0 = []
for i in range(len(decoder_list_0)):
self.generic_decoders_0.append(fec.decoder(decoder_list_0[i],
input_size, output_size))
self.interleave_0 = blocks.interleave(output_size,
fec.get_decoder_output_size(decoder_list_0[0]))
for i in range(len(decoder_list_0)):
self.connect((self.deinterleave_0, i), (self.generic_decoders_0[i], 0))
for i in range(len(decoder_list_0)):
self.connect((self.generic_decoders_0[i], 0), (self.interleave_0, i))
self.connect((self, 0), (self.deinterleave_0, 0))
self.connect((self.interleave_0, 0), (self, 0))
def __init__(self, decoder_obj_list, threading, ann=None, puncpat='11',
integration_period=10000, flush=None, rotator=None):
gr.hier_block2.__init__(self, "extended_decoder",
gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(1, 1, gr.sizeof_char))
self.blocks=[]
self.ann=ann
self.puncpat=puncpat
self.flush=flush
if(type(decoder_obj_list) == list):
if(type(decoder_obj_list[0]) == list):
gr.log.info("fec.extended_decoder: Parallelism must be 1.")
raise AttributeError
else:
# If it has parallelism of 0, force it into a list of 1
decoder_obj_list = [decoder_obj_list,]
message_collector_connected=False
##anything going through the annihilator needs shifted, uchar vals
if fec.get_decoder_input_conversion(decoder_obj_list[0]) == "uchar" or \
fec.get_decoder_input_conversion(decoder_obj_list[0]) == "packed_bits":
self.blocks.append(blocks.multiply_const_ff(48.0))
if fec.get_shift(decoder_obj_list[0]) != 0.0:
self.blocks.append(blocks.add_const_ff(fec.get_shift(decoder_obj_list[0])))
elif fec.get_decoder_input_conversion(decoder_obj_list[0]) == "packed_bits":
self.blocks.append(blocks.add_const_ff(128.0))
if fec.get_decoder_input_conversion(decoder_obj_list[0]) == "uchar" or \
fec.get_decoder_input_conversion(decoder_obj_list[0]) == "packed_bits":
self.blocks.append(blocks.float_to_uchar());
const_index = 0; #index that corresponds to mod order for specinvert purposes
if not self.flush:
flush = 10000;
else:
flush = self.flush;
if self.ann: #ann and puncpat are strings of 0s and 1s
cat = fec.ULLVector();
for i in fec.read_big_bitlist(ann):
cat.append(i);
synd_garble = .49
idx_list = self.garbletable.keys()
idx_list.sort()
for i in idx_list:
if 1.0/self.ann.count('1') >= i:
synd_garble = self.garbletable[i]
print 'using syndrom garble threshold ' + str(synd_garble) + 'for conv_bit_corr_bb'
print 'ceiling: .0335 data garble rate'
self.blocks.append(fec.conv_bit_corr_bb(cat, len(puncpat) - puncpat.count('0'),
len(ann), integration_period, flush, synd_garble))
if self.puncpat != '11':
self.blocks.append(fec.depuncture_bb(len(puncpat), read_bitlist(puncpat), 0))
if fec.get_decoder_input_conversion(decoder_obj_list[0]) == "packed_bits":
self.blocks.append(blocks.uchar_to_float())
self.blocks.append(blocks.add_const_ff(-128.0))
self.blocks.append(digital.binary_slicer_fb())
self.blocks.append(blocks.unpacked_to_packed_bb(1,0))
if(len(decoder_obj_list) > 1):
if(fec.get_history(decoder_obj_list[0]) != 0):
gr.log.info("fec.extended_decoder: Cannot use multi-threaded parallelism on a decoder with history.")
raise AttributeError
if threading == 'capillary':
self.blocks.append(capillary_threaded_decoder(decoder_obj_list,
fec.get_decoder_input_item_size(decoder_obj_list[0]),
fec.get_decoder_output_item_size(decoder_obj_list[0])))
elif threading == 'ordinary':
self.blocks.append(threaded_decoder(decoder_obj_list,
fec.get_decoder_input_item_size(decoder_obj_list[0]),
fec.get_decoder_output_item_size(decoder_obj_list[0])))
else:
self.blocks.append(fec.decoder(decoder_obj_list[0],
fec.get_decoder_input_item_size(decoder_obj_list[0]),
fec.get_decoder_output_item_size(decoder_obj_list[0])))
if fec.get_decoder_output_conversion(decoder_obj_list[0]) == "unpack":
self.blocks.append(blocks.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST));
self.connect((self, 0), (self.blocks[0], 0));
self.connect((self.blocks[-1], 0), (self, 0));
for i in range(len(self.blocks) - 1):
self.connect((self.blocks[i], 0), (self.blocks[i+1], 0));
def __init__(self,
decoder_obj_list,
ann=None,
puncpat='11',
integration_period=10000,
flush=None,
rotator=None,
lentagname=None):
gr.hier_block2.__init__(self, "extended_decoder",
gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(1, 1, gr.sizeof_char))
self.blocks = []
self.ann = ann
self.puncpat = puncpat
self.flush = flush
if (type(decoder_obj_list) == list):
# This block doesn't handle parallelism of > 1
# We could just grab encoder [0][0], but we don't want to encourage this.
if (type(decoder_obj_list[0]) == list):
gr.log.info(
"fec.extended_tagged_decoder: Parallelism must be 1.")
raise AttributeError
decoder_obj = decoder_obj_list[0]
# Otherwise, just take it as is
else:
decoder_obj = decoder_obj_list
# If lentagname is None, fall back to using the non tagged
# stream version
if type(lentagname) == str:
if (lentagname.lower() == 'none'):
lentagname = None
message_collector_connected = False
##anything going through the annihilator needs shifted, uchar vals
if fec.get_decoder_input_conversion(decoder_obj) == "uchar" or \
fec.get_decoder_input_conversion(decoder_obj) == "packed_bits":
self.blocks.append(blocks.multiply_const_ff(48.0))
if fec.get_shift(decoder_obj) != 0.0:
self.blocks.append(blocks.add_const_ff(fec.get_shift(decoder_obj)))
elif fec.get_decoder_input_conversion(decoder_obj) == "packed_bits":
self.blocks.append(blocks.add_const_ff(128.0))
if fec.get_decoder_input_conversion(decoder_obj) == "uchar" or \
fec.get_decoder_input_conversion(decoder_obj) == "packed_bits":
self.blocks.append(blocks.float_to_uchar())
const_index = 0
#index that corresponds to mod order for specinvert purposes
if not self.flush:
flush = 10000
else:
flush = self.flush
if self.ann: #ann and puncpat are strings of 0s and 1s
cat = fec.ULLVector()
for i in fec.read_big_bitlist(ann):
cat.append(i)
synd_garble = .49
idx_list = self.garbletable.keys()
idx_list.sort()
for i in idx_list:
if 1.0 / self.ann.count('1') >= i:
synd_garble = self.garbletable[i]
print 'using syndrom garble threshold ' + str(
synd_garble) + 'for conv_bit_corr_bb'
print 'ceiling: .0335 data garble rate'
self.blocks.append(
fec.conv_bit_corr_bb(cat,
len(puncpat) - puncpat.count('0'),
len(ann), integration_period, flush,
synd_garble))
if self.puncpat != '11':
self.blocks.append(
fec.depuncture_bb(len(puncpat), read_bitlist(puncpat), 0))
if fec.get_decoder_input_conversion(decoder_obj) == "packed_bits":
self.blocks.append(blocks.uchar_to_float())
self.blocks.append(blocks.add_const_ff(-128.0))
self.blocks.append(digital.binary_slicer_fb())
self.blocks.append(blocks.unpacked_to_packed_bb(1, 0))
else:
if (not lentagname):
self.blocks.append(
fec.decoder(decoder_obj,
fec.get_decoder_input_item_size(decoder_obj),
fec.get_decoder_output_item_size(decoder_obj)))
else:
self.blocks.append(
fec.tagged_decoder(
decoder_obj,
fec.get_decoder_input_item_size(decoder_obj),
fec.get_decoder_output_item_size(decoder_obj),
lentagname))
if fec.get_decoder_output_conversion(decoder_obj) == "unpack":
self.blocks.append(blocks.packed_to_unpacked_bb(
1, gr.GR_MSB_FIRST))
self.connect((self, 0), (self.blocks[0], 0))
self.connect((self.blocks[-1], 0), (self, 0))
for i in range(len(self.blocks) - 1):
self.connect((self.blocks[i], 0), (self.blocks[i + 1], 0))
def __init__(self, decoder_list_0, input_size, output_size):
gr.hier_block2.__init__(self, "Capillary Threaded Decoder",
gr.io_signature(1, 1, input_size * 1),
gr.io_signature(1, 1, output_size * 1))
self.decoder_list_0 = decoder_list_0
check = math.log10(len(self.decoder_list_0)) / math.log10(2.0)
if (abs(check - int(check)) > 0):
gr.log.info(
"fec.capillary_threaded_decoder: number of decoders must be a power of 2."
)
raise AttributeError
self.deinterleaves_0 = []
for i in range(int(math.log(len(decoder_list_0), 2))):
for j in range(int(math.pow(2, i))):
self.deinterleaves_0.append(
blocks.deinterleave(
input_size,
fec.get_decoder_input_size(decoder_list_0[0])))
self.generic_decoders_0 = []
for i in range(len(decoder_list_0)):
self.generic_decoders_0.append(
fec.decoder(decoder_list_0[i], input_size, output_size))
self.interleaves_0 = []
for i in range(int(math.log(len(decoder_list_0), 2))):
for j in range(int(math.pow(2, i))):
self.interleaves_0.append(
blocks.interleave(
output_size,
fec.get_decoder_output_size(decoder_list_0[0])))
rootcount = 0
branchcount = 1
for i in range(int(math.log(len(decoder_list_0), 2)) - 1):
for j in range(int(math.pow(2, i))):
self.connect((self.deinterleaves_0[rootcount], 0),
(self.deinterleaves_0[branchcount], 0))
self.connect((self.deinterleaves_0[rootcount], 1),
(self.deinterleaves_0[branchcount + 1], 0))
rootcount += 1
branchcount += 2
codercount = 0
for i in range(len(decoder_list_0) / 2):
self.connect((self.deinterleaves_0[rootcount], 0),
(self.generic_decoders_0[codercount], 0))
self.connect((self.deinterleaves_0[rootcount], 1),
(self.generic_decoders_0[codercount + 1], 0))
rootcount += 1
codercount += 2
rootcount = 0
branchcount = 1
for i in range(int(math.log(len(decoder_list_0), 2)) - 1):
for j in range(int(math.pow(2, i))):
self.connect((self.interleaves_0[branchcount], 0),
(self.interleaves_0[rootcount], 0))
self.connect((self.interleaves_0[branchcount + 1], 0),
(self.interleaves_0[rootcount], 1))
rootcount += 1
branchcount += 2
codercount = 0
for i in range(len(decoder_list_0) / 2):
self.connect((self.generic_decoders_0[codercount], 0),
(self.interleaves_0[rootcount], 0))
self.connect((self.generic_decoders_0[codercount + 1], 0),
(self.interleaves_0[rootcount], 1))
rootcount += 1
codercount += 2
if ((len(self.decoder_list_0)) > 1):
self.connect((self, 0), (self.deinterleaves_0[0], 0))
self.connect((self.interleaves_0[0], 0), (self, 0))
else:
self.connect((self, 0), (self.generic_decoders_0[0], 0))
self.connect((self.generic_decoders_0[0], 0), (self, 0))
def __init__(self, decoder_list_0, input_size, output_size):
gr.hier_block2.__init__(
self, "Capillary Threaded Decoder",
gr.io_signature(1, 1, input_size*1),
gr.io_signature(1, 1, output_size*1))
self.decoder_list_0 = decoder_list_0
check = math.log10(len(self.decoder_list_0)) / math.log10(2.0)
if(abs(check - int(check)) > 0):
gr.log.info("fec.capillary_threaded_decoder: number of decoders must be a power of 2.")
raise AttributeError
self.deinterleaves_0 = []
for i in range(int(math.log(len(decoder_list_0), 2))):
for j in range(int(math.pow(2, i))):
self.deinterleaves_0.append(blocks.deinterleave(input_size,
fec.get_decoder_input_size(decoder_list_0[0])))
self.generic_decoders_0 = []
for i in range(len(decoder_list_0)):
self.generic_decoders_0.append(fec.decoder(decoder_list_0[i], input_size, output_size))
self.interleaves_0 = []
for i in range(int(math.log(len(decoder_list_0), 2))):
for j in range(int(math.pow(2, i))):
self.interleaves_0.append(blocks.interleave(output_size,
fec.get_decoder_output_size(decoder_list_0[0])))
rootcount = 0
branchcount = 1
for i in range(int(math.log(len(decoder_list_0), 2)) - 1):
for j in range(int(math.pow(2, i))):
self.connect((self.deinterleaves_0[rootcount], 0), (self.deinterleaves_0[branchcount], 0))
self.connect((self.deinterleaves_0[rootcount], 1), (self.deinterleaves_0[branchcount + 1], 0))
rootcount += 1
branchcount += 2
codercount = 0
for i in range(len(decoder_list_0)/2):
self.connect((self.deinterleaves_0[rootcount], 0), (self.generic_decoders_0[codercount], 0))
self.connect((self.deinterleaves_0[rootcount], 1), (self.generic_decoders_0[codercount + 1], 0))
rootcount += 1
codercount += 2
rootcount = 0
branchcount = 1
for i in range(int(math.log(len(decoder_list_0), 2)) - 1):
for j in range(int(math.pow(2, i))):
self.connect((self.interleaves_0[branchcount], 0), (self.interleaves_0[rootcount], 0))
self.connect((self.interleaves_0[branchcount + 1], 0), (self.interleaves_0[rootcount], 1))
rootcount += 1
branchcount += 2
codercount = 0
for i in range(len(decoder_list_0)/2):
self.connect((self.generic_decoders_0[codercount], 0), (self.interleaves_0[rootcount], 0))
self.connect((self.generic_decoders_0[codercount + 1], 0), (self.interleaves_0[rootcount], 1))
rootcount += 1
codercount += 2
if ((len(self.decoder_list_0)) > 1):
self.connect((self, 0), (self.deinterleaves_0[0], 0))
self.connect((self.interleaves_0[0], 0), (self, 0))
else:
self.connect((self, 0), (self.generic_decoders_0[0], 0))
self.connect((self.generic_decoders_0[0], 0), (self, 0))
def __init__(
self,
decoder_obj_list,
ann=None,
puncpat="11",
integration_period=10000,
flush=None,
rotator=None,
lentagname=None,
mtu=1500,
):
gr.hier_block2.__init__(
self, "extended_decoder", gr.io_signature(1, 1, gr.sizeof_float), gr.io_signature(1, 1, gr.sizeof_char)
)
self.blocks = []
self.ann = ann
self.puncpat = puncpat
self.flush = flush
if type(decoder_obj_list) == list:
# This block doesn't handle parallelism of > 1
# We could just grab encoder [0][0], but we don't want to encourage this.
if type(decoder_obj_list[0]) == list:
gr.log.info("fec.extended_tagged_decoder: Parallelism must be 1.")
raise AttributeError
decoder_obj = decoder_obj_list[0]
# Otherwise, just take it as is
else:
decoder_obj = decoder_obj_list
# If lentagname is None, fall back to using the non tagged
# stream version
if type(lentagname) == str:
if lentagname.lower() == "none":
lentagname = None
message_collector_connected = False
##anything going through the annihilator needs shifted, uchar vals
if (
fec.get_decoder_input_conversion(decoder_obj) == "uchar"
or fec.get_decoder_input_conversion(decoder_obj) == "packed_bits"
):
self.blocks.append(blocks.multiply_const_ff(48.0))
if fec.get_shift(decoder_obj) != 0.0:
self.blocks.append(blocks.add_const_ff(fec.get_shift(decoder_obj)))
elif fec.get_decoder_input_conversion(decoder_obj) == "packed_bits":
self.blocks.append(blocks.add_const_ff(128.0))
if (
fec.get_decoder_input_conversion(decoder_obj) == "uchar"
or fec.get_decoder_input_conversion(decoder_obj) == "packed_bits"
):
self.blocks.append(blocks.float_to_uchar())
const_index = 0
# index that corresponds to mod order for specinvert purposes
if not self.flush:
flush = 10000
else:
flush = self.flush
if self.ann: # ann and puncpat are strings of 0s and 1s
cat = fec.ULLVector()
for i in fec.read_big_bitlist(ann):
cat.append(i)
synd_garble = 0.49
idx_list = self.garbletable.keys()
idx_list.sort()
for i in idx_list:
if 1.0 / self.ann.count("1") >= i:
synd_garble = self.garbletable[i]
print "using syndrom garble threshold " + str(synd_garble) + "for conv_bit_corr_bb"
print "ceiling: .0335 data garble rate"
self.blocks.append(
fec.conv_bit_corr_bb(
cat, len(puncpat) - puncpat.count("0"), len(ann), integration_period, flush, synd_garble
)
)
if self.puncpat != "11":
self.blocks.append(fec.depuncture_bb(len(puncpat), read_bitlist(puncpat), 0))
if fec.get_decoder_input_conversion(decoder_obj) == "packed_bits":
self.blocks.append(blocks.uchar_to_float())
self.blocks.append(blocks.add_const_ff(-128.0))
self.blocks.append(digital.binary_slicer_fb())
self.blocks.append(blocks.unpacked_to_packed_bb(1, 0))
else:
if not lentagname:
self.blocks.append(
fec.decoder(
decoder_obj,
fec.get_decoder_input_item_size(decoder_obj),
fec.get_decoder_output_item_size(decoder_obj),
)
)
else:
self.blocks.append(
fec.tagged_decoder(
decoder_obj,
fec.get_decoder_input_item_size(decoder_obj),
fec.get_decoder_output_item_size(decoder_obj),
lentagname,
mtu,
)
)
if fec.get_decoder_output_conversion(decoder_obj) == "unpack":
self.blocks.append(blocks.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST))
self.connect((self, 0), (self.blocks[0], 0))
self.connect((self.blocks[-1], 0), (self, 0))
for i in range(len(self.blocks) - 1):
self.connect((self.blocks[i], 0), (self.blocks[i + 1], 0))