From ea76761275b68744f05550ddab612f551baad75a Mon Sep 17 00:00:00 2001
From: Achilleas Anastasopoulos <anastas@umich.edu>
Date: Fri, 18 Feb 2011 20:35:23 -0500
Subject: core algorithms such as viterbi/siso were refactored and implemented
using templates. Minor renaming of some files
---
gr-trellis/src/lib/core_algorithms.cc | 710 ++++++++++++++++++++++++++++++++++
1 file changed, 710 insertions(+)
create mode 100644 gr-trellis/src/lib/core_algorithms.cc
(limited to 'gr-trellis/src/lib/core_algorithms.cc')
diff --git a/gr-trellis/src/lib/core_algorithms.cc b/gr-trellis/src/lib/core_algorithms.cc
new file mode 100644
index 0000000000..41ecaf1742
--- /dev/null
+++ b/gr-trellis/src/lib/core_algorithms.cc
@@ -0,0 +1,710 @@
+/* -*- 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 3, 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., 51 Franklin Street,
+ * Boston, MA 02110-1301, USA.
+ */
+
+#include <float.h>
+#include <stdexcept>
+#include "core_algorithms.h"
+#include "calc_metric.h"
+
+static const float INF = 1.0e9;
+
+template <class T>
+void viterbi_algorithm(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ const float *in, T *out)//,
+ //std::vector<int> &trace)
+{
+ std::vector<int> trace(S*K);
+ std::vector<float> alpha(S*2);
+ int alphai;
+ float norm,mm,minm;
+ int minmi;
+ int st;
+
+
+ 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;
+ }
+
+ alphai=0;
+ for(int k=0;k<K;k++) {
+ norm=INF;
+ for(int j=0;j<S;j++) { // for each next state do ACS
+ minm=INF;
+ minmi=0;
+ for(unsigned int i=0;i<PS[j].size();i++) {
+ //int i0 = j*I+i;
+ if((mm=alpha[alphai*S+PS[j][i]]+in[k*O+OS[PS[j][i]*I+PI[j][i]]])<minm)
+ minm=mm,minmi=i;
+ }
+ trace[k*S+j]=minmi;
+ alpha[((alphai+1)%2)*S+j]=minm;
+ if(minm<norm) norm=minm;
+ }
+ for(int j=0;j<S;j++)
+ alpha[((alphai+1)%2)*S+j]-=norm; // normalize total metrics so they do not explode
+ alphai=(alphai+1)%2;
+ }
+
+ if(SK<0) { // final state not specified
+ minm=INF;
+ minmi=0;
+ for(int i=0;i<S;i++)
+ if((mm=alpha[alphai*S+i])<minm) minm=mm,minmi=i;
+ st=minmi;
+ }
+ else {
+ st=SK;
+ }
+
+ for(int k=K-1;k>=0;k--) { // traceback
+ int i0=trace[k*S+st];
+ out[k]= (T) PI[st][i0];
+ st=PS[st][i0];
+ }
+
+}
+
+
+template
+void viterbi_algorithm<unsigned char>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ const float *in, unsigned char *out);
+
+
+template
+void viterbi_algorithm<short>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ const float *in, short *out);
+
+template
+void viterbi_algorithm<int>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ const float *in, int *out);
+
+
+
+//==============================================
+
+template <class Ti, class To>
+void viterbi_algorithm_combined(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<Ti> &TABLE,
+ trellis_metric_type_t TYPE,
+ const Ti *in, To *out
+)
+{
+ std::vector<int> trace(S*K);
+ std::vector<float> alpha(S*2);
+ float *metric = new float[O];
+ int alphai;
+ float norm,mm,minm;
+ int minmi;
+ int st;
+
+ 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;
+ }
+
+ alphai=0;
+ for(int k=0;k<K;k++) {
+ calc_metric(O, D, TABLE, &(in[k*D]), metric,TYPE); // calc metrics
+ norm=INF;
+ for(int j=0;j<S;j++) { // for each next state do ACS
+ minm=INF;
+ minmi=0;
+ for(unsigned int i=0;i<PS[j].size();i++) {
+ //int i0 = j*I+i;
+ if((mm=alpha[alphai*S+PS[j][i]]+metric[OS[PS[j][i]*I+PI[j][i]]])<minm)
+ minm=mm,minmi=i;
+ }
+ trace[k*S+j]=minmi;
+ alpha[((alphai+1)%2)*S+j]=minm;
+ if(minm<norm) norm=minm;
+ }
+ for(int j=0;j<S;j++)
+ alpha[((alphai+1)%2)*S+j]-=norm; // normalize total metrics so they do not explode
+ alphai=(alphai+1)%2;
+ }
+
+ if(SK<0) { // final state not specified
+ minm=INF;
+ minmi=0;
+ for(int i=0;i<S;i++)
+ if((mm=alpha[alphai*S+i])<minm) minm=mm,minmi=i;
+ st=minmi;
+ }
+ else {
+ st=SK;
+ }
+
+ for(int k=K-1;k>=0;k--) { // traceback
+ int i0=trace[k*S+st];
+ out[k]= (To) PI[st][i0];
+ st=PS[st][i0];
+ }
+
+ delete [] metric;
+
+}
+
+// Ti = s i f c
+// To = b s i
+
+//---------------
+
+template
+void viterbi_algorithm_combined<short,unsigned char>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<short> &TABLE,
+ trellis_metric_type_t TYPE,
+ const short *in, unsigned char *out
+);
+
+template
+void viterbi_algorithm_combined<int,unsigned char>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<int> &TABLE,
+ trellis_metric_type_t TYPE,
+ const int *in, unsigned char *out
+);
+
+template
+void viterbi_algorithm_combined<float,unsigned char>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<float> &TABLE,
+ trellis_metric_type_t TYPE,
+ const float *in, unsigned char *out
+);
+
+template
+void viterbi_algorithm_combined<gr_complex,unsigned char>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<gr_complex> &TABLE,
+ trellis_metric_type_t TYPE,
+ const gr_complex *in, unsigned char *out
+);
+
+//---------------
+
+template
+void viterbi_algorithm_combined<short,short>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<short> &TABLE,
+ trellis_metric_type_t TYPE,
+ const short *in, short *out
+);
+
+template
+void viterbi_algorithm_combined<int,short>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<int> &TABLE,
+ trellis_metric_type_t TYPE,
+ const int *in, short *out
+);
+
+template
+void viterbi_algorithm_combined<float,short>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<float> &TABLE,
+ trellis_metric_type_t TYPE,
+ const float *in, short *out
+);
+
+template
+void viterbi_algorithm_combined<gr_complex,short>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<gr_complex> &TABLE,
+ trellis_metric_type_t TYPE,
+ const gr_complex *in, short *out
+);
+
+//--------------
+
+template
+void viterbi_algorithm_combined<short,int>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<short> &TABLE,
+ trellis_metric_type_t TYPE,
+ const short *in, int *out
+);
+
+template
+void viterbi_algorithm_combined<int,int>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<int> &TABLE,
+ trellis_metric_type_t TYPE,
+ const int *in, int *out
+);
+
+template
+void viterbi_algorithm_combined<float,int>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<float> &TABLE,
+ trellis_metric_type_t TYPE,
+ const float *in, int *out
+);
+
+template
+void viterbi_algorithm_combined<gr_complex,int>(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ int D,
+ const std::vector<gr_complex> &TABLE,
+ trellis_metric_type_t TYPE,
+ const gr_complex *in, int *out
+);
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+//===============================================
+
+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));
+ //return 0;
+}
+
+void siso_algorithm(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< 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;
+ std::vector<float> alpha(S*(K+1));
+ std::vector<float> beta(S*(K+1));
+
+
+ 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(unsigned int i=0;i<PS[j].size();i++) {
+ //int i0 = j*I+i;
+ mm=alpha[k*S+PS[j][i]]+priori[k*I+PI[j][i]]+prioro[k*O+OS[PS[j][i]*I+PI[j][i]]];
+ 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.");
+
+}
+
+
+//===========================================================
+
+void siso_algorithm_combined(int I, int S, int O,
+ const std::vector<int> &NS,
+ const std::vector<int> &OS,
+ const std::vector< std::vector<int> > &PS,
+ const std::vector< std::vector<int> > &PI,
+ int K,
+ int S0,int SK,
+ bool POSTI, bool POSTO,
+ float (*p2mymin)(float,float),
+ int D,
+ const std::vector<float> &TABLE,
+ trellis_metric_type_t TYPE,
+ const float *priori, const float *observations, float *post//,
+ //std::vector<float> &alpha,
+ //std::vector<float> &beta
+ )
+{
+ float norm,mm,minm;
+ std::vector<float> alpha(S*(K+1));
+ std::vector<float> beta(S*(K+1));
+ float *prioro = new float[O*K];
+
+
+ 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
+ calc_metric(O, D, TABLE, &(observations[k*D]), &(prioro[k*O]),TYPE); // calc metrics
+ norm=INF;
+ for(int j=0;j<S;j++) {
+ minm=INF;
+ for(unsigned int i=0;i<PS[j].size();i++) {
+ //int i0 = j*I+i;
+ mm=alpha[k*S+PS[j][i]]+priori[k*I+PI[j][i]]+prioro[k*O+OS[PS[j][i]*I+PI[j][i]]];
+ 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.");
+
+ delete [] prioro;
+
+}
+
--
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