def __init__(self,
encoder_obj_list,
puncpat=None,
lentagname=None,
mtu=1500):
gr.hier_block2.__init__(self, "extended_tagged_encoder",
gr.io_signature(1, 1, gr.sizeof_char),
gr.io_signature(1, 1, gr.sizeof_char))
self.blocks = []
self.puncpat = puncpat
# If it's a list of encoders, take the first one, unless it's
# a list of lists of encoders.
if (type(encoder_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(encoder_obj_list[0]) == list):
gr.log.info(
"fec.extended_tagged_encoder: Parallelism must be 0 or 1.")
raise AttributeError
encoder_obj = encoder_obj_list[0]
# Otherwise, just take it as is
else:
encoder_obj = encoder_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
if fec.get_encoder_input_conversion(encoder_obj) == "pack":
self.blocks.append(blocks.pack_k_bits_bb(8))
if (not lentagname):
self.blocks.append(
fec.encoder(encoder_obj, gr.sizeof_char, gr.sizeof_char))
else:
self.blocks.append(
fec.tagged_encoder(encoder_obj, gr.sizeof_char, gr.sizeof_char,
lentagname, mtu))
if self.puncpat != '11':
self.blocks.append(
fec.puncture_bb(len(puncpat), read_bitlist(puncpat), 0))
# Connect the input to the encoder and the output to the
# puncture if used or the encoder if not.
self.connect((self, 0), (self.blocks[0], 0))
self.connect((self.blocks[-1], 0), (self, 0))
# If using the puncture block, add it into the flowgraph after
# the encoder.
for i in range(len(self.blocks) - 1):
self.connect((self.blocks[i], 0), (self.blocks[i + 1], 0))
def __init__(self, encoder_obj_list, puncpat=None, lentagname=None):
gr.hier_block2.__init__(self, "extended_tagged_encoder",
gr.io_signature(1, 1, gr.sizeof_char),
gr.io_signature(1, 1, gr.sizeof_char))
self.blocks=[]
self.puncpat=puncpat
# If it's a list of encoders, take the first one, unless it's
# a list of lists of encoders.
if(type(encoder_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(encoder_obj_list[0]) == list):
gr.log.info("fec.extended_tagged_encoder: Parallelism must be 0 or 1.")
raise AttributeError
encoder_obj = encoder_obj_list[0]
# Otherwise, just take it as is
else:
encoder_obj = encoder_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
if fec.get_encoder_input_conversion(encoder_obj) == "pack":
self.blocks.append(blocks.pack_k_bits_bb(8))
if(not lentagname):
self.blocks.append(fec.encoder(encoder_obj,
gr.sizeof_char,
gr.sizeof_char))
else:
self.blocks.append(fec.tagged_encoder(encoder_obj,
gr.sizeof_char,
gr.sizeof_char,
lentagname))
if self.puncpat != '11':
self.blocks.append(fec.puncture_bb(len(puncpat), read_bitlist(puncpat), 0))
# Connect the input to the encoder and the output to the
# puncture if used or the encoder if not.
self.connect((self, 0), (self.blocks[0], 0));
self.connect((self.blocks[-1], 0), (self, 0));
# If using the puncture block, add it into the flowgraph after
# the encoder.
for i in range(len(self.blocks) - 1):
self.connect((self.blocks[i], 0), (self.blocks[i+1], 0));
def __init__(self, encoder_obj_list, threading, puncpat=None):
gr.hier_block2.__init__(self, "extended_encoder",
gr.io_signature(1, 1, gr.sizeof_char),
gr.io_signature(1, 1, gr.sizeof_char))
self.blocks = []
self.puncpat = puncpat
if (type(encoder_obj_list) == list):
if (type(encoder_obj_list[0]) == list):
gr.log.info("fec.extended_encoder: Parallelism must be 1.")
raise AttributeError
else:
# If it has parallelism of 0, force it into a list of 1
encoder_obj_list = [
encoder_obj_list,
]
if fec.get_encoder_input_conversion(encoder_obj_list[0]) == "pack":
self.blocks.append(blocks.pack_k_bits_bb(8))
if threading == 'capillary':
self.blocks.append(
capillary_threaded_encoder(encoder_obj_list, gr.sizeof_char,
gr.sizeof_char))
elif threading == 'ordinary':
self.blocks.append(
threaded_encoder(encoder_obj_list, gr.sizeof_char,
gr.sizeof_char))
else:
self.blocks.append(
fec.encoder(encoder_obj_list[0], gr.sizeof_char,
gr.sizeof_char))
if fec.get_encoder_output_conversion(
encoder_obj_list[0]) == "packed_bits":
self.blocks.append(blocks.packed_to_unpacked_bb(
1, gr.GR_MSB_FIRST))
if self.puncpat != '11':
self.blocks.append(
fec.puncture_bb(len(puncpat), read_bitlist(puncpat), 0))
# Connect the input to the encoder and the output to the
# puncture if used or the encoder if not.
self.connect((self, 0), (self.blocks[0], 0))
self.connect((self.blocks[-1], 0), (self, 0))
# If using the puncture block, add it into the flowgraph after
# the encoder.
for i in range(len(self.blocks) - 1):
self.connect((self.blocks[i], 0), (self.blocks[i + 1], 0))
def __init__(self, encoder_obj_list, threading, puncpat=None):
gr.hier_block2.__init__(self, "extended_encoder",
gr.io_signature(1, 1, gr.sizeof_char),
gr.io_signature(1, 1, gr.sizeof_char))
self.blocks=[]
self.puncpat=puncpat
if(type(encoder_obj_list) == list):
if(type(encoder_obj_list[0]) == list):
gr.log.info("fec.extended_encoder: Parallelism must be 1.")
raise AttributeError
else:
# If it has parallelism of 0, force it into a list of 1
encoder_obj_list = [encoder_obj_list,]
if fec.get_encoder_input_conversion(encoder_obj_list[0]) == "pack":
self.blocks.append(blocks.pack_k_bits_bb(8))
if threading == 'capillary':
self.blocks.append(capillary_threaded_encoder(encoder_obj_list,
gr.sizeof_char,
gr.sizeof_char))
elif threading == 'ordinary':
self.blocks.append(threaded_encoder(encoder_obj_list,
gr.sizeof_char,
gr.sizeof_char))
else:
self.blocks.append(fec.encoder(encoder_obj_list[0],
gr.sizeof_char,
gr.sizeof_char))
if fec.get_encoder_output_conversion(encoder_obj_list[0]) == "packed_bits":
self.blocks.append(blocks.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST))
if self.puncpat != '11':
self.blocks.append(fec.puncture_bb(len(puncpat), read_bitlist(puncpat), 0))
# Connect the input to the encoder and the output to the
# puncture if used or the encoder if not.
self.connect((self, 0), (self.blocks[0], 0));
self.connect((self.blocks[-1], 0), (self, 0));
# If using the puncture block, add it into the flowgraph after
# the encoder.
for i in range(len(self.blocks) - 1):
self.connect((self.blocks[i], 0), (self.blocks[i+1], 0));
