C++ timer::current_time方法代码示例

 /**
  * Called after an iteration has finished.
  */
 void after_iteration(int iteration, graphchi_context &ginfo) {
   logstream(LOG_DEBUG)<<mytimer.current_time() << "iteration: " << iteration << " changes: " << changes << std::endl;
   if (changes == 0)
     ginfo.set_last_iteration(iteration);
   changes = 0;
   iter++;
 }

void training_rmse(int iteration, graphchi_context &gcontext){
    last_training_rmse = dtraining_rmse;
    dtraining_rmse = 0;
#pragma omp parallel for reduction(+:dtraining_rmse)
    for (int i=0; i< (int)M; i++){
      dtraining_rmse += latent_factors_inmem[i].rmse;
    }
    dtraining_rmse = sqrt(dtraining_rmse / pengine->num_edges());
    std::cout<< std::setw(10) << mytimer.current_time() << ") Iteration: " << std::setw(3) <<iteration<<" Training RMSE: " << std::setw(10)<< dtraining_rmse;
 }

  /**
   *  Vertex update function - computes the least square step
   */
  void update(graphchi_vertex<VertexDataType, EdgeDataType> &vertex, graphchi_context &gcontext) {

  if (vertex.id() >= M)
    return;

  vertex_data & vdata = latent_factors_inmem[vertex.id()];
  int howmany = N*knn_sample_percent;
  assert(howmany > 0 );
  vec distances = vec::Zero(howmany);
  ivec indices = ivec(howmany);
  for (int i=0; i< howmany; i++){
    indices[i]= -2;
  }
  std::vector<bool> curratings;
  curratings.resize(N);
  for(int e=0; e < vertex.num_edges(); e++) {
  //no need to calculate this rating since it is given in the training data reference
    curratings[vertex.edge(e)->vertex_id() - M] = true;
  }
   if (knn_sample_percent == 1.0){
     for (uint i=M; i< M+N; i++){
        if (curratings[i-M])
          continue;
        vertex_data & other = latent_factors_inmem[i];
        double dist;
        als_predict(vdata, other, 0, dist); 
        indices[i-M] = i-M;
        distances[i-M] = dist;
     }
  }
  else for (int i=0; i<howmany; i++){
        int random_other = ::randi(M, M+N-1);
        vertex_data & other = latent_factors_inmem[random_other];
        double dist;
        als_predict(vdata, other, 0, dist); 
        indices[i-M] = i-M;
        distances[i-M] = dist;
   }
  
  vec out_dist(num_ratings);
  ivec indices_sorted = reverse_sort_index2(distances, indices, out_dist, num_ratings);
  assert(indices_sorted.size() <= num_ratings);
  assert(out_dist.size() <= num_ratings);
  vdata.ids = indices_sorted;
  vdata.ratings = out_dist;
  if (debug)
    printf("Closest is: %d with distance %g\n", (int)vdata.ids[0], vdata.ratings[0]);

  if (vertex.id() % 1000 == 0)
    printf("Computing recommendaitons for user %d at time: %g\n", vertex.id()+1, mytimer.current_time());
  
  
  }

int main(int argc,  const char *argv[]) {

  logstream(LOG_WARNING)<<"CE_Graph parsers library is written by Danny Bickson (c). Send any "
    " comments or bug reports to [email protected] " << std::endl;
  global_logger().set_log_level(LOG_INFO);
  global_logger().set_log_to_console(true);

  CE_Graph_init(argc, argv);

  debug = get_option_int("debug", 0);
  dir = get_option_string("file_list");
  lines = get_option_int("lines", 0);
  omp_set_num_threads(get_option_int("ncpus", 1));
  mytime.start();

  FILE * f = fopen(dir.c_str(), "r");
  if (f == NULL)
    logstream(LOG_FATAL)<<"Failed to open file list!"<<std::endl;

  while(true){
    char buf[256];
    int rc = fscanf(f, "%s\n", buf);
    if (rc < 1)
      break;
    in_files.push_back(buf);
  }

  if (in_files.size() == 0)
    logstream(LOG_FATAL)<<"Failed to read any file names from the list file: " << dir << std::endl;

#pragma omp parallel for
  for (uint i=0; i< in_files.size(); i++)
    parse(i);

  std::cout << "Finished in " << mytime.current_time() << std::endl << "\t direct tweets found: " << links_found  <<
    " \t global tweets: " << wide_tweets << 
    "\t http links: " << http_links << 
    "\t retweets: " << retweet_found <<
    "\t total lines in input file : " << total_lines << 
    " \t invalid records (missing names) " << missing_names <<  std::endl;

  save_map_to_text_file(string2nodeid, outdir + "map.text");
  save_map_to_text_file(nodeid2hash, outdir + "reverse.map.text");
  save_map_to_text_file(tweets_per_user, outdir + "tweets_per_user.text");

  out_file fout("mm.info");
  fprintf(fout.outf, "%%%%MatrixMarket matrix coordinate real general\n");
  fprintf(fout.outf, "%u %u %lu\n", maxfrom+1, maxto+1, links_found);
  return 0;
}

int main(int argc,  const char *argv[]) {

	logstream(LOG_WARNING)<<"GraphChi parsers library is written by Danny Bickson (c). Send any "
		" comments or bug reports to [email protected] " << std::endl;
	global_logger().set_log_level(LOG_INFO);
	global_logger().set_log_to_console(true);

	graphchi_init(argc, argv);

	debug = get_option_int("debug", 0);
	dir = get_option_string("file_list");
	lines = get_option_int("lines", 0);
	omp_set_num_threads(get_option_int("ncpus", 1));
	from_val = get_option_int("from_val", from_val);
	to_val = get_option_int("to_val", to_val);
	mid_val = get_option_int("mid_val", mid_val);
	if (from_val == -1)
		logstream(LOG_FATAL)<<"Must set from/to " << std::endl;
	mytime.start();

	FILE * f = fopen(dir.c_str(), "r");
	if (f == NULL)
		logstream(LOG_FATAL)<<"Failed to open file list!"<<std::endl;

	while(true){
		char buf[256];
		int rc = fscanf(f, "%s\n", buf);
		if (rc < 1)
			break;
		in_files.push_back(buf);
	}

	if (in_files.size() == 0)
		logstream(LOG_FATAL)<<"Failed to read any file frommap from the list file: " << dir << std::endl;

#pragma omp parallel for
	for (int i=0; i< (int)in_files.size(); i++)
		parse(i);

	std::cout << "Finished in " << mytime.current_time() << std::endl;

	save_map_to_text_file(frommap.string2nodeid, outdir + dir + "map.text");
	return 0;
}

  /**
   *  Vertex update function.
   */
  void update(CE_Graph_vertex<VertexDataType, EdgeDataType> &v, CE_Graph_context &gcontext) {
    if (debug)
      printf("Entered iteration %d with %d - edges %d\n", gcontext.iteration, v.id(), v.num_edges());

    /* even iteration numbers:
     * 1) load a subset of items into memory (pivots)
     * 2) Find which subset of items needs to compared to the users
     */
    if (gcontext.iteration % 2 == 0) {
      if (adjcontainer->is_pivot(v.id())){
        adjcontainer->load_edges_into_memory(v);         
        if (debug)
          printf("Loading pivot %d intro memory\n", v.id());
      }
    }
    else {

      for (vid_t i=adjcontainer->pivot_st; i< adjcontainer->pivot_en; i++){
        //since metric is symmetric, compare only to pivots which are smaller than this item id
        if (i >= v.id())
          continue;
        
        dense_adj &pivot_edges = adjcontainer->adjs[i - adjcontainer->pivot_st];
        //pivot is not connected to this item, continue
        if (get_val(pivot_edges.edges, v.id()) == 0)
            continue;

        double dist = adjcontainer->calc_distance(v, i, distance_metric);
        item_pairs_compared++;
        if (item_pairs_compared % 1000000 == 0)
          logstream(LOG_INFO)<< std::setw(10) << mytimer.current_time() << ")  " << std::setw(10) << item_pairs_compared << " pairs compared " << std::endl;
        if (debug)
          printf("comparing %d to pivot %d distance is %lg\n", i+ 1, v.id() + 1, dist);
        if (dist != 0){
          fprintf(out_files[omp_get_thread_num()], "%u %u %.12lg\n", v.id()+1, i+1, (double)dist);//write item similarity to file
          //where the output format is: 
          //[item A] [ item B ] [ distance ] 
          written_pairs++;
        }
      }
    }//end of iteration % 2 == 1
  }//end of update function

int main(int argc,  const char *argv[]) {

  Rcpp::Rcout<<"GraphChi parsers library is written by Danny Bickson (c). Send any "
    " comments or bug reports to [email protected] " << std::endl;
  global_logger().set_log_level(LOG_INFO);
  global_logger().set_log_to_console(true);

  graphchi_init(argc, argv);

  debug = get_option_int("debug", 0);
  dir = get_option_string("file_list");
  lines = get_option_int("lines", 0);
  omp_set_num_threads(get_option_int("ncpus", 1));
  mytime.start();

  FILE * f = fopen(dir.c_str(), "r");
  if (f == NULL)
    logstream(LOG_FATAL)<<"Failed to open file list!"<<std::endl;

  while(true){
    char buf[256];
    int rc = fscanf(f, "%s\n", buf);
    if (rc < 1)
      break;
    in_files.push_back(buf);
  }

  if (in_files.size() == 0)
    logstream(LOG_FATAL)<<"Failed to read any file names from the list file: " << dir << std::endl;

//#pragma omp parallel for
  for (uint i=0; i< in_files.size(); i++)
    parse(i);

  std::cout << "Finished in " << mytime.current_time() << std::endl << 
    "\t total lines in input file : " << total_lines <<  "\t max from: " << maxfrom << "\t max to: " <<maxto << std::endl;

  return 0;
}

    /**
     *  Vertex update function.
     */
    void update(graphchi_vertex<VertexDataType, edge_data> &v, graphchi_context &gcontext) {
        if (debug)
            printf("Entered iteration %d with %d\n", gcontext.iteration, is_item(v.id()) ? (v.id() - M + 1): v.id());

        /* Even iteration numbers:
         * 1) load a subset of users into memory (pivots)
         * 2) Find which subset of items is connected to the users
         */
        if (gcontext.iteration % 2 == 0) {
            if (adjcontainer->is_pivot(v.id()) && is_user(v.id())) {
                adjcontainer->load_edges_into_memory(v);
                if (debug)
                    printf("Loading pivot %d intro memory\n", v.id());
            }
        }
        /* odd iteration number:
        * 1) For any item connected to a pivot item
        *       compute itersection
        */
        else {
            assert(is_item(v.id()));

            for (int i=0; i< v.num_edges(); i++) {
                if (!adjcontainer->is_pivot(v.edge(i)->vertex_id()))
                    continue;
                if (debug)
                    printf("comparing user pivot %d to item %d\n", v.edge(i)->vertex_id()+1 , v.id() - M + 1);

                adjcontainer->compute_ratings(v, v.edge(i)->vertex_id(), v.edge(i)->get_data().up_weight);
                item_pairs_compared++;

                if (item_pairs_compared % 1000000 == 0)
                    Rcpp::Rcout<< std::setw(10) << mytimer.current_time() << ")  " << std::setw(10) << item_pairs_compared << " pairs compared " << std::endl;
            }
        }//end of iteration % 2 == 1
    }//end of update function

void parse(int i){    
	in_file fin(in_files[i]);
	out_file fout((outdir + ".out"));

	size_t linesize = 0;
	char * saveptr = NULL, * linebuf = NULL;
	size_t line = 1;
	uint from,to;
	bool matrix_market = false;

	while(true){
		int rc = getline(&linebuf, &linesize, fin.outf);
		if (rc < 1)
			break;
		if (strlen(linebuf) <= 1){ //skip empty lines
			line++;
			continue;
		}

		if (has_header_titles && line == 1){
			line++;
			continue;
		} 
		//skipping over matrix market header (if any) 
		if (!strncmp(linebuf, "%%MatrixMarket", 14)){
			matrix_market = true;
			continue;
		}
		if (matrix_market && linebuf[0] == '%'){
			continue;
		}
		if (matrix_market && linebuf[0] != '%'){
			matrix_market = false;
			continue;
		}

		//read [FROM]
		char *pch = strtok_r(linebuf,string_to_tokenize, &saveptr);
		if (!pch){ logstream(LOG_ERROR) << "Error when parsing file: " << in_files[i] << ":" << line << "[" << linebuf << "]" << std::endl; return; }
		assign_id(string2nodeid, from, pch, true);

		//read [TO]
		pch = strtok_r(NULL,string_to_tokenize, &saveptr);
		if (!pch){ logstream(LOG_ERROR) << "Error when parsing file: " << in_files[i] << ":" << line << "[" << linebuf << "]" << std::endl; return; }
		assign_id(single_domain ? string2nodeid:string2nodeid2, to, pch, single_domain ? true : false);

		//read the rest of the line
		if (!binary){
			if (ignore_rest_of_line)
				pch = strtok_r(NULL, string_to_tokenize, &saveptr);
			else
				pch = strtok_r(NULL, "\n", &saveptr);
			if (!pch){ logstream(LOG_ERROR) << "Error when parsing file: " << in_files[i] << ":" << line << "[" << linebuf << "]" << std::endl; return; }
		}
		if (tsv)
			fprintf(fout.outf, "%u\t%u\t%s\n", from, to, binary? "": pch);
		else if (csv)
			fprintf(fout.outf, "%u %u %s\n", from, to, binary? "" : pch);
		else 
			fprintf(fout.outf, "%u %u %s\n", from, to, binary? "" : pch);
		nnz++;

		line++;
		total_lines++;
		if (lines && line>=lines)
			break;

		if (debug && (line % 50000 == 0))
			logstream(LOG_INFO) << mytimer.current_time() << ") Parsed line: " << line << " map size is: " << string2nodeid.size() << std::endl;
		if (string2nodeid.size() % 500000 == 0)
			logstream(LOG_INFO) << mytimer.current_time() << ") Hash map size: " << string2nodeid.size() << " at time: " << mytime.current_time() << " edges: " << total_lines << std::endl;
	} 

	logstream(LOG_INFO) <<"Finished parsing total of " << line << " lines in file " << in_files[i] << endl <<
		"total map size: " << string2nodeid.size() << endl;

}

 /// \cond GRAPHLAB_INTERNAL
 inline double get_current_time() const {
   return ti.current_time();
 }

int main(int argc,  const char *argv[]) {
	logstream(LOG_WARNING)<<"GraphChi parsers library is written by Danny Bickson (c). Send any "
		" comments or bug reports to [email protected] " << std::endl;
	global_logger().set_log_level(LOG_INFO);
	global_logger().set_log_to_console(true);

	graphchi_init(argc, argv);
	mytimer.start();

	outdir = get_option_string("output","");
	debug = get_option_int("debug", 0);
	dir = get_option_string("file_list","");
	filename = get_option_string("training","");
	lines = get_option_int("lines", 0);
	omp_set_num_threads(get_option_int("ncpus", 1));
	tsv = get_option_int("tsv", 0); //is this tab seperated file?
	csv = get_option_int("csv", 0); // is the comma seperated file?
	binary = get_option_int("binary", 0);
	single_domain = get_option_int("single_domain", 0);
	has_header_titles = get_option_int("has_header_titles", has_header_titles);
	ignore_rest_of_line = get_option_int("ignore_rest_of_line", ignore_rest_of_line);
	mytime.start();


	string_to_tokenize = spaces;
	if (tsv)
		string_to_tokenize = tsv_spaces;
	else if (csv)
		string_to_tokenize = csv_spaces;

	if (dir != ""){
		FILE * f = fopen(dir.c_str(), "r");
		if (f == NULL)
			logstream(LOG_FATAL)<<"Failed to open file list!"<<std::endl;

		while(true){
			char buf[256];
			int rc = fscanf(f, "%s\n", buf);
			if (rc < 1)
				break;
			in_files.push_back(buf);
		}
	}
	else if (filename != "")
		in_files.push_back(filename);

	if (in_files.size() == 0)
		logstream(LOG_FATAL)<<"Failed to read any file names from the list file: " << dir << std::endl;

#pragma omp parallel for
	for (uint i=0; i< in_files.size(); i++)
		parse(i);

	std::cout << "Finished in " << mytime.current_time() << std::endl;
	M = string2nodeid.size();
	if (single_domain)
		N = M;
	else N = string2nodeid2.size();

	save_map_to_text_file(string2nodeid, outdir + ".user.map");
	if (!single_domain){
		save_map_to_text_file(string2nodeid2, outdir + ".item.map");
	}
	std::string filename = "matrix_market.info";
	if (in_files.size() == 1)
		filename = in_files[0] + ".out:info";
	logstream(LOG_INFO)<<"Writing matrix market header into file: " << filename << std::endl;
	out_file fout(filename.c_str());
	MM_typecode out_typecode;
	mm_clear_typecode(&out_typecode);
	mm_set_integer(&out_typecode); 
	mm_set_sparse(&out_typecode); 
	mm_set_matrix(&out_typecode);
	mm_write_banner(fout.outf, out_typecode);
	mm_write_mtx_crd_size(fout.outf, M, N, nnz);
	return 0;
}

void parse(int i){    
  in_file fin(in_files[i]);
  out_file fout((outdir + in_files[i] + ".out"));

  size_t linesize = 0;
  char * saveptr = NULL, * linebuf = NULL, buf1[256], linebuf_debug[1024];
  size_t line = 1;
  uint id;
  long int ptime;
  bool ok;
  bool first = true;

  while(true){
    int rc = getline(&linebuf, &linesize, fin.outf);
    strncpy(linebuf_debug, linebuf, 1024);
    total_lines++;
    if (rc < 1)
      break;
    if (strlen(linebuf) <= 1) //skip empty lines
      continue; 
    if (first){ first = false; continue; } //skip first line

    char *pch = strtok_r(linebuf," \r\n\t:/-", &saveptr);
    if (!pch){ logstream(LOG_ERROR) << "Error when parsing file: " << in_files[i] << ":" << line << "[" << linebuf << "]" << std::endl; return; }

    switch(*pch){
      case 'T':
        ok = convert_string_to_time(linebuf_debug, total_lines, i, saveptr, ptime);
        if (!ok)
          return;
        break;

      case 'U':
        ok = extract_user_name(linebuf_debug, total_lines, i, saveptr, buf1);
        if (ok)
          assign_id(id, buf1, line, in_files[i]);
        tweets_per_user[id]++;
        break;

      case 'W':
        ok = parse_links(linebuf_debug, total_lines, i, saveptr, id, ptime, fout.outf);
        if (debug && line < 20)
          printf("Found user: %s id %u time %ld\n", buf1, id, ptime);
        if (!ok)
          wide_tweets++;
        break;

      default:
        logstream(LOG_ERROR)<<"Error: expecting with T U or W first character" << std::endl;
        return;

    }

    line++;
    if (lines && line>=lines)
      break;

    if (debug && (line % 50000 == 0))
      logstream(LOG_INFO) << "Parsed line: " << line << " map size is: " << string2nodeid.size() << std::endl;
    if (string2nodeid.size() % 500000 == 0)
      logstream(LOG_INFO) << "Hash map size: " << string2nodeid.size() << " at time: " << mytime.current_time() << " edges: " << total_lines << std::endl;
  } 

  logstream(LOG_INFO) <<"Finished parsing total of " << line << " lines in file " << in_files[i] << endl <<
    "total map size: " << string2nodeid.size() << endl;

}

  /**
   *  Vertex update function - computes the least square step
   */
  void update(graphchi_vertex<VertexDataType, EdgeDataType> &vertex, graphchi_context &gcontext) {

    //compute only for user nodes
    if (vertex.id() >= std::min(M,(uint)end_user) || vertex.id() < (uint)start_user)
      return;

    vertex_data & vdata = latent_factors_inmem[vertex.id()];
    int howmany = (int)(N*knn_sample_percent);
    assert(howmany > 0 );
    if (vertex.num_outedges() == 0){
       mymutex.lock();
       users_without_ratings++;
       mymutex.unlock();
    }

    vec distances = zeros(howmany);
    ivec indices = ivec::Zero(howmany);
    for (int i=0; i< howmany; i++){
      indices[i]= -1;
    }
    std::vector<bool> curratings;
    curratings.resize(N);
    for(int e=0; e < vertex.num_edges(); e++) {
      //no need to calculate this rating since it is given in the training data reference
      assert(vertex.edge(e)->vertex_id() - M >= 0 && vertex.edge(e)->vertex_id() - M < N);
      curratings[vertex.edge(e)->vertex_id() - M] = true;
    }
    if (knn_sample_percent == 1.0){
      for (uint i=M; i< M+N; i++){
        if (curratings[i-M])
          continue;
        vertex_data & other = latent_factors_inmem[i];
        double dist;
        if (algo == SVDPP)
          svdpp_predict(vdata, other, 0, dist); 
        else if (algo == BIASSGD) 
	  biassgd_predict(vdata, other, 0, dist);
        else if (algo == RBM)
          rbm_predict(vdata, other, 0, dist);
        else assert(false);
        indices[i-M] = i-M;
        distances[i-M] = dist + 1e-10;
      }
    }
    else for (int i=0; i<howmany; i++){
      int random_other = ::randi(M, M+N-1);
      vertex_data & other = latent_factors_inmem[random_other];
      double dist;
      if (algo == SVDPP)
        svdpp_predict(vdata, other, 0, dist); 
      else if (algo == BIASSGD)
        biassgd_predict(vdata, other, 0, dist);
      else if (algo == RBM)
        rbm_predict(vdata, other, 0, dist);
      else assert(false);
        
      indices[i] = random_other-M;
      distances[i] = dist;
    }

    vec out_dist(num_ratings);
    ivec indices_sorted = reverse_sort_index2(distances, indices, out_dist, num_ratings);
    assert(indices_sorted.size() <= num_ratings);
    assert(out_dist.size() <= num_ratings);
    vdata.ids = indices_sorted;
    vdata.ratings = out_dist;
    if (debug)
      printf("Closest is: %d with distance %g\n", (int)vdata.ids[0], vdata.ratings[0]);

    if (vertex.id() % 1000 == 0)
      printf("Computing recommendations for user %d at time: %g\n", vertex.id()+1, mytimer.current_time());
  }

vec lanczos( bipartite_graph_descriptor & info, timer & mytimer, vec & errest, 
            const std::string & vecfile){
   

   int nconv = 0;
   int its = 1;
   DistMat A(info);
   DistSlicedMat U(info.is_square() ? data_size : 0, info.is_square() ? 2*data_size : data_size, true, info, "U");
   DistSlicedMat V(0, data_size, false, info, "V");
   vec alpha, beta, b;
   vec sigma = zeros(data_size);
   errest = zeros(nv);
   DistVec v_0(info, 0, false, "v_0");
   if (vecfile.size() == 0)
     v_0 = randu(size(A,2));
   PRINT_VEC2("svd->V", v_0);
   
   DistDouble vnorm = norm(v_0);
   v_0=v_0/vnorm;
   PRINT_INT(nv);

   while(nconv < nsv && its < max_iter){
     std::cout<<"Starting iteration: " << its << " at time: " << mytimer.current_time() << std::endl;
     int k = nconv;
     int n = nv;
     PRINT_INT(k);
     PRINT_INT(n);

     alpha = zeros(n);
     beta = zeros(n);

     U[k] = V[k]*A._transpose();
     orthogonalize_vs_all(U, k, alpha(0));
     //alpha(0)=norm(U[k]).toDouble(); 
     PRINT_VEC3("alpha", alpha, 0);
     //U[k] = U[k]/alpha(0);

     for (int i=k+1; i<n; i++){
       std::cout <<"Starting step: " << i << " at time: " << mytimer.current_time() <<  std::endl;
       PRINT_INT(i);

       V[i]=U[i-1]*A;
       orthogonalize_vs_all(V, i, beta(i-k-1));
      
       //beta(i-k-1)=norm(V[i]).toDouble();
       //V[i] = V[i]/beta(i-k-1);
       PRINT_VEC3("beta", beta, i-k-1); 
      
       U[i] = V[i]*A._transpose();
       orthogonalize_vs_all(U, i, alpha(i-k));
       //alpha(i-k)=norm(U[i]).toDouble();

       //U[i] = U[i]/alpha(i-k);
       PRINT_VEC3("alpha", alpha, i-k);
     }

     V[n]= U[n-1]*A;
     orthogonalize_vs_all(V, n, beta(n-k-1));
     //beta(n-k-1)=norm(V[n]).toDouble();
     PRINT_VEC3("beta", beta, n-k-1);

  //compute svd of bidiagonal matrix
  PRINT_INT(nv);
  PRINT_NAMED_INT("svd->nconv", nconv);
  n = nv - nconv;
  PRINT_INT(n);
  alpha.conservativeResize(n);
  beta.conservativeResize(n);

  PRINT_MAT2("Q",eye(n));
  PRINT_MAT2("PT",eye(n));
  PRINT_VEC2("alpha",alpha);
  PRINT_VEC2("beta",beta);
 
  mat T=diag(alpha);
  for (int i=0; i<n-1; i++)
    set_val(T, i, i+1, beta(i));
  PRINT_MAT2("T", T);
  mat a,PT;
  svd(T, a, PT, b);
  PRINT_MAT2("Q", a);
  alpha=b.transpose();
  PRINT_MAT2("alpha", alpha);
  for (int t=0; t< n-1; t++)
     beta(t) = 0;
  PRINT_VEC2("beta",beta);
  PRINT_MAT2("PT", PT.transpose());

  //estiamte the error
  int kk = 0;
  for (int i=nconv; i < nv; i++){
    int j = i-nconv;
    PRINT_INT(j);
    sigma(i) = alpha(j);
    PRINT_NAMED_DBL("svd->sigma[i]", sigma(i));
    PRINT_NAMED_DBL("Q[j*n+n-1]",a(n-1,j));
    PRINT_NAMED_DBL("beta[n-1]",beta(n-1));
    errest(i) = abs(a(n-1,j)*beta(n-1));
    PRINT_NAMED_DBL("svd->errest[i]", errest(i));
    if (alpha(j) >  tol){
//.........这里部分代码省略.........

void parse(int i){    
  in_file fin(in_files[i]);
  out_file fout((outdir + in_files[i] + ".out"));

  size_t linesize = 0;
  char * saveptr = NULL, * linebuf = NULL;
  size_t line = 1;
  uint id;

  while(true){
    std::map<uint,uint> wordcount;
    int rc = getline(&linebuf, &linesize, fin.outf);
    if (rc < 1)
      break;
    if (strlen(linebuf) <= 1) //skip empty lines
      continue; 

    char *pch = strtok_r(linebuf, spaces, &saveptr);
    if (!pch){ logstream(LOG_ERROR) << "Error when parsing file: " << in_files[i] << ":" << line << "[" << linebuf << "]" << std::endl; return; }
    assign_id(frommap, id, pch);
    wordcount[id]+= 1;

    while(pch != NULL){
      pch = strtok_r(NULL, spaces ,&saveptr);
      if (pch != NULL && strlen(pch) > 1){ 
        assign_id(frommap, id, pch);
        wordcount[id]+= 1;
      }
    }  

    total_lines++;

    std::map<uint,uint>::const_iterator it;
    for (it = wordcount.begin(); it != wordcount.end(); it++){
      if ((int)it->second >= min_threshold && (int)it->second <= max_threshold)
        fprintf(fout.outf, "%lu %u %u\n", line, it->first, it->second);
    }

    line++;
    if (lines && line>=lines)
      break;

    if (debug && (line % 50000 == 0))
      logstream(LOG_INFO) << "Parsed line: " << line << " map size is: " << frommap.string2nodeid.size() << std::endl;
    if (frommap.string2nodeid.size() % 500000 == 0)
      logstream(LOG_INFO) << "Hash map size: " << frommap.string2nodeid.size() << " at time: " << mytime.current_time() << " edges: " << total_lines << std::endl;
  } 

  logstream(LOG_INFO) <<"Finished parsing total of " << line << " lines in file " << in_files[i] << endl <<
    "total map size: " << frommap.string2nodeid.size() << endl;

}