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diff --git a/gr-trellis/src/lib/trellis_siso_f.cc b/gr-trellis/src/lib/trellis_siso_f.cc
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+++ b/gr-trellis/src/lib/trellis_siso_f.cc
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+/* -*- c++ -*- */
+/*
+ * Copyright 2004 Free Software Foundation, Inc.
+ *
+ * This file is part of GNU Radio
+ *
+ * GNU Radio is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 2, or (at your option)
+ * any later version.
+ *
+ * GNU Radio is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with GNU Radio; see the file COPYING. If not, write to
+ * the Free Software Foundation, Inc., 59 Temple Place - Suite 330,
+ * Boston, MA 02111-1307, USA.
+ */
+
+#ifdef HAVE_CONFIG_H
+#include "config.h"
+#endif
+
+#include <trellis_siso_f.h>
+#include <gr_io_signature.h>
+#include <stdexcept>
+#include <assert.h>
+#include <iostream>
+
+static const float INF = 1.0e9;
+
+trellis_siso_f_sptr
+trellis_make_siso_f (
+ const fsm &FSM,
+ int K,
+ int S0,
+ int SK,
+ bool POSTI,
+ bool POSTO,
+ trellis_siso_type_t SISO_TYPE)
+{
+ return trellis_siso_f_sptr (new trellis_siso_f (FSM,K,S0,SK,POSTI,POSTO,SISO_TYPE));
+}
+
+trellis_siso_f::trellis_siso_f (
+ const fsm &FSM,
+ int K,
+ int S0,
+ int SK,
+ bool POSTI,
+ bool POSTO,
+ trellis_siso_type_t SISO_TYPE)
+ : gr_block ("siso_f",
+ gr_make_io_signature (1, -1, sizeof (float)),
+ gr_make_io_signature (1, -1, sizeof (float))),
+ d_FSM (FSM),
+ d_K (K),
+ d_S0 (S0),
+ d_SK (SK),
+ d_POSTI (POSTI),
+ d_POSTO (POSTO),
+ d_SISO_TYPE (SISO_TYPE),
+ d_alpha(FSM.S()*(K+1)),
+ d_beta(FSM.S()*(K+1))
+{
+ int multiple;
+ if (d_POSTI && d_POSTO)
+ multiple = d_FSM.I()+d_FSM.O();
+ else if(d_POSTI)
+ multiple = d_FSM.I();
+ else if(d_POSTO)
+ multiple = d_FSM.O();
+ else
+ throw std::runtime_error ("Not both POSTI and POSTO can be false.");
+ //printf("constructor: Multiple = %d\n",multiple);
+ set_output_multiple (d_K*multiple);
+ //what is the meaning of relative rate for this?
+ // it was suggested to use the one furthest from 1.0
+ // let's do it.
+ set_relative_rate ( multiple / ((double) d_FSM.I()) );
+}
+
+
+void
+trellis_siso_f::forecast (int noutput_items, gr_vector_int &ninput_items_required)
+{
+ int multiple;
+ if (d_POSTI && d_POSTO)
+ multiple = d_FSM.I()+d_FSM.O();
+ else if(d_POSTI)
+ multiple = d_FSM.I();
+ else if(d_POSTO)
+ multiple = d_FSM.O();
+ else
+ throw std::runtime_error ("Not both POSTI and POSTO can be false.");
+ //printf("forecast: Multiple = %d\n",multiple);
+ assert (noutput_items % (d_K*multiple) == 0);
+ int input_required1 = d_FSM.I() * (noutput_items/multiple) ;
+ int input_required2 = d_FSM.O() * (noutput_items/multiple) ;
+ //printf("forecast: Output requirements: %d\n",noutput_items);
+ //printf("forecast: Input requirements: %d %d\n",input_required1,input_required2);
+ unsigned ninputs = ninput_items_required.size();
+ assert(ninputs % 2 == 0);
+ for (unsigned int i = 0; i < ninputs/2; i++) {
+ ninput_items_required[2*i] = input_required1;
+ ninput_items_required[2*i+1] = input_required2;
+ }
+}
+
+inline float min(float a, float b)
+{
+ return a <= b ? a : b;
+}
+
+inline float min_star(float a, float b)
+{
+ return (a <= b ? a : b)-log(1+exp(a <= b ? a-b : b-a));
+}
+
+void siso_algorithm(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector<int> &PS,
+ const std::vector<int> &PI,
+ int K,
+ int S0,int SK,
+ bool POSTI, bool POSTO,
+ float (*p2mymin)(float,float),
+ const float *priori, const float *prioro, float *post,
+ std::vector<float> &alpha,
+ std::vector<float> &beta)
+{
+ float norm,mm,minm;
+
+
+ if(S0<0) { // initial state not specified
+ for(int i=0;i<S;i++) alpha[0*S+i]=0;
+ }
+ else {
+ for(int i=0;i<S;i++) alpha[0*S+i]=INF;
+ alpha[0*S+S0]=0.0;
+ }
+
+ for(int k=0;k<K;k++) { // forward recursion
+ norm=INF;
+ for(int j=0;j<S;j++) {
+ minm=INF;
+ for(int i=0;i<I;i++) {
+ int i0 = j*I+i;
+ mm=alpha[k*S+PS[i0]]+priori[k*I+PI[i0]]+prioro[k*O+OS[PS[i0]*I+PI[i0]]];
+ minm=(*p2mymin)(minm,mm);
+ }
+ alpha[(k+1)*S+j]=minm;
+ if(minm<norm) norm=minm;
+ }
+ for(int j=0;j<S;j++)
+ alpha[(k+1)*S+j]-=norm; // normalize total metrics so they do not explode
+ }
+
+ if(SK<0) { // final state not specified
+ for(int i=0;i<S;i++) beta[K*S+i]=0;
+ }
+ else {
+ for(int i=0;i<S;i++) beta[K*S+i]=INF;
+ beta[K*S+SK]=0.0;
+ }
+
+ for(int k=K-1;k>=0;k--) { // backward recursion
+ norm=INF;
+ for(int j=0;j<S;j++) {
+ minm=INF;
+ for(int i=0;i<I;i++) {
+ int i0 = j*I+i;
+ mm=beta[(k+1)*S+NS[i0]]+priori[k*I+i]+prioro[k*O+OS[i0]];
+ minm=(*p2mymin)(minm,mm);
+ }
+ beta[k*S+j]=minm;
+ if(minm<norm) norm=minm;
+ }
+ for(int j=0;j<S;j++)
+ beta[k*S+j]-=norm; // normalize total metrics so they do not explode
+ }
+
+
+if (POSTI && POSTO)
+{
+ for(int k=0;k<K;k++) { // input combining
+ norm=INF;
+ for(int i=0;i<I;i++) {
+ minm=INF;
+ for(int j=0;j<S;j++) {
+ mm=alpha[k*S+j]+prioro[k*O+OS[j*I+i]]+beta[(k+1)*S+NS[j*I+i]];
+ minm=(*p2mymin)(minm,mm);
+ }
+ post[k*(I+O)+i]=minm;
+ if(minm<norm) norm=minm;
+ }
+ for(int i=0;i<I;i++)
+ post[k*(I+O)+i]-=norm; // normalize metrics
+ }
+
+
+ for(int k=0;k<K;k++) { // output combining
+ norm=INF;
+ for(int n=0;n<O;n++) {
+ minm=INF;
+ for(int j=0;j<S;j++) {
+ for(int i=0;i<I;i++) {
+ mm= (n==OS[j*I+i] ? alpha[k*S+j]+priori[k*I+i]+beta[(k+1)*S+NS[j*I+i]] : INF);
+ minm=(*p2mymin)(minm,mm);
+ }
+ }
+ post[k*(I+O)+I+n]=minm;
+ if(minm<norm) norm=minm;
+ }
+ for(int n=0;n<O;n++)
+ post[k*(I+O)+I+n]-=norm; // normalize metrics
+ }
+}
+else if(POSTI)
+{
+ for(int k=0;k<K;k++) { // input combining
+ norm=INF;
+ for(int i=0;i<I;i++) {
+ minm=INF;
+ for(int j=0;j<S;j++) {
+ mm=alpha[k*S+j]+prioro[k*O+OS[j*I+i]]+beta[(k+1)*S+NS[j*I+i]];
+ minm=(*p2mymin)(minm,mm);
+ }
+ post[k*I+i]=minm;
+ if(minm<norm) norm=minm;
+ }
+ for(int i=0;i<I;i++)
+ post[k*I+i]-=norm; // normalize metrics
+ }
+}
+else if(POSTO)
+{
+ for(int k=0;k<K;k++) { // output combining
+ norm=INF;
+ for(int n=0;n<O;n++) {
+ minm=INF;
+ for(int j=0;j<S;j++) {
+ for(int i=0;i<I;i++) {
+ mm= (n==OS[j*I+i] ? alpha[k*S+j]+priori[k*I+i]+beta[(k+1)*S+NS[j*I+i]] : INF);
+ minm=(*p2mymin)(minm,mm);
+ }
+ }
+ post[k*O+n]=minm;
+ if(minm<norm) norm=minm;
+ }
+ for(int n=0;n<O;n++)
+ post[k*O+n]-=norm; // normalize metrics
+ }
+}
+else
+ throw std::runtime_error ("Not both POSTI and POSTO can be false.");
+
+}
+
+
+
+
+
+
+int
+trellis_siso_f::general_work (int noutput_items,
+ gr_vector_int &ninput_items,
+ gr_vector_const_void_star &input_items,
+ gr_vector_void_star &output_items)
+{
+ assert (input_items.size() == 2*output_items.size());
+ int nstreams = output_items.size();
+ //printf("general_work:Streams: %d\n",nstreams);
+ int multiple;
+ if (d_POSTI && d_POSTO)
+ multiple = d_FSM.I()+d_FSM.O();
+ else if(d_POSTI)
+ multiple = d_FSM.I();
+ else if(d_POSTO)
+ multiple = d_FSM.O();
+ else
+ throw std::runtime_error ("Not both POSTI and POSTO can be false.");
+
+ assert (noutput_items % (d_K*multiple) == 0);
+ int nblocks = noutput_items / (d_K*multiple);
+ //printf("general_work:Blocks: %d\n",nblocks);
+ //for(int i=0;i<ninput_items.size();i++)
+ //printf("general_work:Input items available: %d\n",ninput_items[i]);
+
+ float (*p2min)(float, float) = NULL;
+ if(d_SISO_TYPE == TRELLIS_MIN_SUM)
+ p2min = &min;
+ else if(d_SISO_TYPE == TRELLIS_SUM_PRODUCT)
+ p2min = &min_star;
+
+
+ for (int m=0;m<nstreams;m++) {
+ const float *in1 = (const float *) input_items[2*m];
+ const float *in2 = (const float *) input_items[2*m+1];
+ float *out = (float *) output_items[m];
+ for (int n=0;n<nblocks;n++) {
+ siso_algorithm(d_FSM.I(),d_FSM.S(),d_FSM.O(),
+ d_FSM.NS(),d_FSM.OS(),d_FSM.PS(),d_FSM.PI(),
+ d_K,d_S0,d_SK,
+ d_POSTI,d_POSTO,
+ p2min,
+ &(in1[n*d_K*d_FSM.I()]),&(in2[n*d_K*d_FSM.O()]),
+ &(out[n*d_K*multiple]),
+ d_alpha,d_beta);
+ }
+ }
+
+ for (unsigned int i = 0; i < input_items.size()/2; i++) {
+ consume(2*i,d_FSM.I() * noutput_items / multiple );
+ consume(2*i+1,d_FSM.O() * noutput_items / multiple );
+ }
+
+ return noutput_items;
+}
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