Hello Everything plots/charts/works just fine when I use the GUI, but when I call corrgram(.......) using the api in C++ it does not show the graph. The function does compute and display the LAG ACF PACF Q-stat. [p-value], but it does not show the ACF and PACF charts. I have also tired correlogram_plot (...), I get the following "Gnuplot is broken or too old: must be >= version 5.0", but as you see below my Gnuplot is >= 5.0 and when I use the GUI it plots the ACF and PACF just fine. GNU Plot Version 5.2 patchlevel 8 last modified 2019-12-01. OS = Ubuntu 18 GCC = version 7.4.0 (Ubuntu 7.4.0-1ubuntu1~18.04.1) Below is the c++ code that calls the corrgram(...). There are 3 separate functions involved. The first two functions on this page are helper functions and the final function at the end is were I call corrgram(...). Thank you for your help Riley template<typename T> void ToGretl(std::vector<T> &data, DATASET *gretl_data_set, int pd, int structure, std::string variable_name){ /* typedef struct { int v; number of variables int n; number of observations int pd; periodicity or frequency of data int structure; time series, cross section or whatever double sd0; float representation of stobs int t1, t2; start and end of current sample char stobs[OBSLEN]; string representation of starting obs (date) char endobs[OBSLEN]; string representation of ending obs double **Z; data array char **varname; array of names of variables VARINFO **varinfo; array of specific info on vars char markers; NO_MARKERS (0), REGULAR MARKERS or DAILY_DATE_STRINGS char modflag; binary flag for dataset modified or not char **S; to hold observation markers char *descrip; to hold info on data sources etc. char *submask; subsampling mask char *restriction; record of sub-sampling restriction char *padmask; record of padding to re-balance panel data unsigned int rseed; resampling seed int auxiliary; = 0 for regular dataset, 1 for aux dataset char *pangrps; panel-only: name of series holding group names int panel_pd; panel-only: panel time-series frequency double panel_sd0; panel-only: time-series start } DATASET; */ int nobs = data.size(); gretl_data_set->pd = pd; gretl_data_set->structure = structure;//1=time series //gretl_data_set = create_new_dataset (1,nobs, 0); gretl_data_set->v = 1;//# of vars +1 becuase the dataset requires a constant gretl_data_set->n = nobs; gretl_data_set->t1 = 0;//this should be the same as i in for loop below; gretl_data_set->t2 = nobs;//data.size();//this should be the same as i in for loop below; //char f_[] = variable_name.c_str(); gretl_data_set->varname = (char **) malloc(sizeof(char *));//malloc(f_* sizeof(f_)); *gretl_data_set->varname = (char *) malloc(sizeof(char));//malloc(f_* size strcpy(*gretl_data_set->varname, const_cast<char*>(variable_name.c_str())); allocate_Z(gretl_data_set, OPT_B); if(gretl_data_set != NULL){ int size_ = sizeof(gretl_data_set->Z)/sizeof(double); for(int i = 0; i<nobs;++i){ gretl_data_set->Z[0][i] = data[i]; std::cout<<gretl_data_set->Z[0][i]<<std::endl; } } } template void ToGretl<double>(std::vector<double> &, DATASET *, int , int , std::string ); int CorrgramGretl(int varno, int order, int nparam, DATASET *dset, gretlopt opt, PRN *prn){ int err = 0; err = corrgram (varno, order, nparam, dset, opt, prn); return 0; } void DataEDA(){ for(auto it:cat_id_by_day){ Stats::Histogram hist_st; auto cat_id = all_data.cat_id_map.find(it.first); if(cat_id != all_data.cat_id_map.end()){ std::cout<<"Cat_Id "<<cat_id->second<<std::endl; Stats::CalcSimpleStats(it.second, hist_st, 10, true); //Stats::PlotLine() libgretl_init(); DATASET *gretl_data_set; PRN *prn; MODEL *model; gretl_data_set = datainfo_new(); //gretl_data_set->stobs = all_data.calendar_data.begin()->first.copy(); char* p2 = const_cast<char*>(all_data.calendar_data.begin()->first.c_str()); strcpy(gretl_data_set->stobs, p2); char* p3 = const_cast<char*>(all_data.calendar_data.rbegin()->first.c_str()); strcpy( gretl_data_set->endobs, p3); MyData::ToGretl(it.second,gretl_data_set,7,1, "test"); int err=0; prn = gretl_print_new(GRETL_PRINT_STDOUT, NULL); if (err) { errmsg(err, prn); exit(EXIT_FAILURE); } gretlopt opt = OPT_R; // err = gnuplot_graph_wanted (PLOT_CORRELOGRAM, opt); if (err) { errmsg(err, prn); } std::cout<<"GNU Plot version "<<gnuplot_version()<<std::endl; gretl_matrix *acf_mat;//const gretl_matrix *PM // acf_mat = gretl_matrix_alloc(m, 100); acf_mat = acf_matrix(gretl_data_set->Z[0], 100, gretl_data_set, gretl_data_set->n,&err); const char *vname = "V2"; const double *acf=const_cast<const double* >( &acf_mat->val[0]); const double *pacf=const_cast<const double* >( &acf_mat->val[1]); int m = 30; double pm = 1.0; // err = correlogram_plot (vname,acf,pacf,acf_mat,m, pm,opt); if (err) { errmsg(err, prn); } err = Stats::CorrgramGretl(0, 100, 0, gretl_data_set, opt, prn); if (err) { errmsg(err, prn); } // err = Stats::ArmaEstimateGretl(gretl_data_set, prn, model, 1,1,1,0); destroy_dataset(gretl_data_set); gretl_print_destroy(prn); libgretl_cleanup(); // working got putting arma_estimate into Stat.cpp function // cleaning this funtion up and moving thing to their respective function } } }