コード例 #1
0
    def __init__(self, encoder_list_0, input_size, output_size):
        gr.hier_block2.__init__(
            self, "Threaded Encoder",
            gr.io_signature(1, 1, input_size*1),
            gr.io_signature(1, 1, output_size*1))

        self.encoder_list_0 = encoder_list_0

        self.fec_deinterleave_0 = blocks.deinterleave(input_size,
                                                      fec.get_encoder_input_size(encoder_list_0[0]))

        self.generic_encoders_0 = [];
        for i in range(len(encoder_list_0)):
            self.generic_encoders_0.append(fec.encoder(encoder_list_0[i],
                                                       input_size, output_size))

        self.fec_interleave_0 = blocks.interleave(output_size,
                                               fec.get_encoder_output_size(encoder_list_0[0]))

        for i in range(len(encoder_list_0)):
            self.connect((self.fec_deinterleave_0, i), (self.generic_encoders_0[i], 0))

        for i in range(len(encoder_list_0)):
            self.connect((self.generic_encoders_0[i], 0), (self.fec_interleave_0, i))

        self.connect((self, 0), (self.fec_deinterleave_0, 0))
        self.connect((self.fec_interleave_0, 0), (self, 0))
コード例 #2
0
    def __init__(self, encoder_list_0, input_size=gr.sizeof_char, output_size=gr.sizeof_char):
        gr.hier_block2.__init__(self, "Capillary Threaded Encoder",
                                gr.io_signature(1, 1, input_size),
                                gr.io_signature(1, 1, output_size))

        self.encoder_list_0 = encoder_list_0

        check = math.log10(len(self.encoder_list_0)) / math.log10(2.0)
        if(abs(check - int(check)) > 0.0):
            gr.log.info("fec.capillary_threaded_encoder: number of encoders must be a power of 2.")
            raise AttributeError

        self.deinterleaves_0 = [];
        for i in range(int(math.log(len(encoder_list_0), 2))):
            for j in range(int(math.pow(2, i))):
                self.deinterleaves_0.append(blocks.deinterleave(input_size,
                                                                fec.get_encoder_input_size(encoder_list_0[0])))

       	self.generic_encoders_0 = [];
        for i in range(len(encoder_list_0)):
            self.generic_encoders_0.append(fec.encoder(encoder_list_0[i],
                                                       input_size, output_size))

        self.interleaves_0 = [];
        for i in range(int(math.log(len(encoder_list_0), 2))):
            for j in range(int(math.pow(2, i))):
                self.interleaves_0.append(blocks.interleave(output_size,
                                                            fec.get_encoder_output_size(encoder_list_0[0])))

        rootcount = 0;
        branchcount = 1;
        for i in range(int(math.log(len(encoder_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(encoder_list_0)/2):
            self.connect((self.deinterleaves_0[rootcount], 0), (self.generic_encoders_0[codercount], 0))
            self.connect((self.deinterleaves_0[rootcount], 1), (self.generic_encoders_0[codercount + 1], 0))
            rootcount += 1;
            codercount += 2;


        rootcount = 0;
        branchcount = 1;
        for i in range(int(math.log(len(encoder_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(encoder_list_0)/2):
            self.connect((self.generic_encoders_0[codercount], 0), (self.interleaves_0[rootcount], 0))
            self.connect((self.generic_encoders_0[codercount + 1], 0), (self.interleaves_0[rootcount], 1))
            rootcount += 1;
            codercount += 2;

       	if((len(self.encoder_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_encoders_0[0], 0))
            self.connect((self.generic_encoders_0[0], 0), (self, 0))
コード例 #3
0
    def __init__(self,
                 encoder_list_0,
                 input_size=gr.sizeof_char,
                 output_size=gr.sizeof_char):
        gr.hier_block2.__init__(self, "Capillary Threaded Encoder",
                                gr.io_signature(1, 1, input_size),
                                gr.io_signature(1, 1, output_size))

        self.encoder_list_0 = encoder_list_0

        check = math.log10(len(self.encoder_list_0)) / math.log10(2.0)
        if (abs(check - int(check)) > 0.0):
            gr.log.info(
                "fec.capillary_threaded_encoder: number of encoders must be a power of 2."
            )
            raise AttributeError

        self.deinterleaves_0 = []
        for i in range(int(math.log(len(encoder_list_0), 2))):
            for j in range(int(math.pow(2, i))):
                self.deinterleaves_0.append(
                    blocks.deinterleave(
                        input_size,
                        fec.get_encoder_input_size(encoder_list_0[0])))

        self.generic_encoders_0 = []
        for i in range(len(encoder_list_0)):
            self.generic_encoders_0.append(
                fec.encoder(encoder_list_0[i], input_size, output_size))

        self.interleaves_0 = []
        for i in range(int(math.log(len(encoder_list_0), 2))):
            for j in range(int(math.pow(2, i))):
                self.interleaves_0.append(
                    blocks.interleave(
                        output_size,
                        fec.get_encoder_output_size(encoder_list_0[0])))

        rootcount = 0
        branchcount = 1
        for i in range(int(math.log(len(encoder_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(encoder_list_0) / 2):
            self.connect((self.deinterleaves_0[rootcount], 0),
                         (self.generic_encoders_0[codercount], 0))
            self.connect((self.deinterleaves_0[rootcount], 1),
                         (self.generic_encoders_0[codercount + 1], 0))
            rootcount += 1
            codercount += 2

        rootcount = 0
        branchcount = 1
        for i in range(int(math.log(len(encoder_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(encoder_list_0) / 2):
            self.connect((self.generic_encoders_0[codercount], 0),
                         (self.interleaves_0[rootcount], 0))
            self.connect((self.generic_encoders_0[codercount + 1], 0),
                         (self.interleaves_0[rootcount], 1))
            rootcount += 1
            codercount += 2

        if ((len(self.encoder_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_encoders_0[0], 0))
            self.connect((self.generic_encoders_0[0], 0), (self, 0))