本文整理汇总了C++中Distribution::ascii_print方法的典型用法代码示例。如果您正苦于以下问题：C++ Distribution::ascii_print方法的具体用法？C++ Distribution::ascii_print怎么用？C++ Distribution::ascii_print使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Distribution的用法示例。
在下文中一共展示了Distribution::ascii_print方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: main
int main(void) {
int var, i, j, nb_variable, nb_component;
const int nb_vector = 500;
double *pweight = NULL;
bool *fparam = NULL;
int* perm;
StatError error;
const char * mixpath= "./tmp.mix", * spmixpath= "./tmp_sp.mix";
const char * gnupath = "./tmp_mix", * gnu_datapath = "./tmp_mix_data";
const char * margpath= "./marg_mix", * gnu_tmppath = "./tmp_mix_d";
const char * np_modelpath= "./np_model.mix", * gnu_tmpnppath = "./tmp_mix_d";
const char * entropy_data= "cluster_vectors.vec";
const char * output_path = "tmp_entropy_output.vec";
Distribution *marginal = NULL;
DiscreteDistributionData *marginal_histo = NULL;
Vectors *vec = NULL;
MultivariateMixture *mv1 = NULL, *mv_cp = NULL;
MultivariateMixture *mv_np1 = NULL, *mv_np_estim = NULL;
MultivariateMixture *mv_estim = NULL;
MultivariateMixtureData *mv_data = NULL, *cluster = NULL;
DiscreteParametric **dt1 = NULL, **dt2 = NULL;
DiscreteParametricProcess **ppcomponent = NULL;
// constructors of Mv_Mixture
mv1 = new MultivariateMixture();
// destructor of MultivariateMixture
delete mv1;
mv1= NULL;
nb_variable = 2;
nb_component = 3;
dt1 = new DiscreteParametric*[nb_component];
dt2 = new DiscreteParametric*[nb_component];
pweight = new double[nb_component];
ppcomponent = new DiscreteParametricProcess*[nb_variable];
pweight[0] = 0.1;
pweight[1] = 0.2;
pweight[2] = 0.7;
dt1[0] = new DiscreteParametric(0, BINOMIAL, 2, 12, D_DEFAULT, 0.1);
dt1[1] = new DiscreteParametric(0, BINOMIAL, 0, 10, D_DEFAULT, 0.5);
dt1[2] = new DiscreteParametric(0, BINOMIAL, 3, 10, D_DEFAULT, 0.8);
dt2[0] = new DiscreteParametric(0, POISSON, 2, I_DEFAULT, 8.0, D_DEFAULT);
dt2[1] = new DiscreteParametric(0, POISSON, 4, I_DEFAULT, 5.0, D_DEFAULT);
dt2[2] = new DiscreteParametric(0, POISSON, 0, I_DEFAULT, 2.0, D_DEFAULT);
cout << "Observation distributions for variable 1:" << endl;
for (i = 0; i < nb_component; i++) {
dt1[i]-> ascii_print(cout);
}
ppcomponent[0] = new DiscreteParametricProcess(nb_component, dt1);
ppcomponent[1] = new DiscreteParametricProcess(nb_component, dt2);
for (i = 0; i < nb_component; i++) {
delete dt1[i];
dt1[i] = NULL;
delete dt2[i];
dt2[i] = NULL;
}
cout << endl;
mv1 = new MultivariateMixture(nb_component, pweight, nb_variable, ppcomponent, NULL);
cout << "Mixture of " << nb_component << " components with " <<
nb_variable << " variables:" << endl;
mv1->ascii_write(cout, true);
cout << endl;
// copy
mv_cp = new MultivariateMixture(*mv1);
cout << "Copy constructor of MultivariateMixture: " << endl;
mv_cp->ascii_write(cout);
cout << endl;
// destructor of MultivariateMixture
delete mv_cp;
mv_cp= NULL;
delete mv1;
mv1= NULL;
cout << "MultivariateMixture_building (print into file " << mixpath << "): " << endl;
mv1 = multivariate_mixture_building(error , nb_component ,
nb_variable, pweight, ppcomponent, NULL);
if (mv1 == NULL)
cout << error;
else {
//.........这里部分代码省略.........