static void
generate_vector_array(vector_t p[])
{
data_t (*rand_next[3])();
int dist, i;
for (i = 0; i < 3; i++) {
dist = fixed_flag ? 2 : rand_func()%3;
switch (dist) {
case 0: /* [-1, 1) */
min = -1.0;
max = 1.0;
rand_next[i] = rand_uniform;
break;
case 1: /* N(0, 1) */
m = 0.0;
sigma = 1.0;
rand_next[i] = rand_normal;
break;
default: /* La(0, 1) */
mu = 0.0;
b = 1.0;
rand_next[i] = rand_laplace;
break;
}
}
for (i = 0; i < N; i++) {
p[i].x = rand_next[0]();
p[i].y = rand_next[1]();
p[i].z = rand_next[2]();
}
}
static void
generate_mass_array(data_t a[])
{
data_t (*rand_next)();
int dist, i;
m = mu = 1.0/(data_t)N;
min = m*0.5;
max = m*1.5;
dist = fixed_flag ? 2 : rand_func()%3;
switch (dist) {
case 0: /* [1/2N, 3/2N) */
rand_next = rand_uniform;
break;
case 1: /* N(1/N, 1/10N) */
sigma = m*1e-1;
rand_next = rand_normal;
break;
default: /* La(1/N, 1/10N) */
b = m*1e-1;
rand_next = rand_laplace;
break;
}
for (i = 0; i < N; i++)
do a[i] = rand_next();
while (a[i] < min || a[i] > max);
}
void roll_for_attack (int attacking, int defending, long (*rand_func)(long max), int *attack_loss, int *defend_loss) {
int red[3], white[2], i;
bzero(&red, 3*sizeof(int));
bzero(&white, 2*sizeof(int));
for(i=0; i<attacking; i++) {
red[i] = rand_func(6) + 1;
}
if (defending > attacking) defending = attacking;
for(i=0; i<defending; i++) {
white[i] = rand_func(6) + 1;
}
cmp_and_swap(red, 0, 1, i);
cmp_and_swap(red, 0, 2, i);
cmp_and_swap(red, 1, 2, i);
cmp_and_swap(white, 0, 1, i);
*attack_loss = *defend_loss = 0;
for (i=0; i < defending; i++) {
if (red[i] > white[i]) {
(*defend_loss)++;
} else {
(*attack_loss)++;
}
}
}
//---------------------------------------------------------
int main()
{
Py_Initialize();
{
boost::python::object main_module=boost::python::import("__main__");
boost::python::object main_namespace=main_module.attr("__dict__");
boost::python::exec("print('Hello, world')", main_namespace);
}
{
boost::python::object main_module=boost::python::import("__main__");
boost::python::object main_namespace=main_module.attr("__dict__");
boost::python::exec("import random", main_namespace);
boost::python::object rand=boost::python::eval("random.random()", main_namespace);
std::cout<<boost::python::extract<double>(rand)<<std::endl;
}
{
boost::python::object main_module=boost::python::import("__main__");
boost::python::object main_namespace=main_module.attr("__dict__");
boost::python::object rand_mod=boost::python::import("random");
boost::python::object rand_func=rand_mod.attr("random");
boost::python::object rand=rand_func();
std::cout<<boost::python::extract<double>(rand)<<std::endl;
}
{
boost::python::object main_module=boost::python::import("__main__");
boost::python::object main_namespace=main_module.attr("__dict__");
// boost::python::object rand_mod=boost::python::import("base");
// boost::python::object rand_func=rand_mod.attr("f");
// boost::python::object rand=rand_func(8, 9);
}
{
try
{
boost::python::object rand_mod=boost::python::import("fake_module");
}
catch(const boost::python::error_already_set& e)
{
//std::string perror_str=parse_python_exception();
//std::cout<<"Error in Python: "<<perror_str<<std::endl;
}
}
Py_Finalize();
return 0;
}
void
load_data(data_t m[], vector_t x[], vector_t v[])
{
char fname[256], pname[256];
#ifdef USE_RANDOM_DATA
random_flag = 1;
#endif
#ifdef USE_FIXED_DATA
fixed_flag = 1;
#endif
set_seed();
if (!random_flag) {
if (!fixed_flag) prob_no = rand_func()%nprobs;
sprintf(fname, "%s/%d/prob%d.dat", data_dir, N, prob_no);
if (!read_data_file(fname, m, x, v)) random_flag = 1;
}
if (random_flag) {
if (fixed_flag) prob_no = nprobs;
generate_mass_array(m);
generate_vector_array(x);
generate_vector_array(v);
}
if (pid == 0) {
if (!random_flag || fixed_flag)
sprintf(pname, "%d", prob_no);
else
strcpy(pname, "random");
printf("\n*** Simulation parameters ***\n"
"Number of particles: %d\n"
"Number of time steps: %d\n"
"Interval of time steps: %.1g\n"
"Data set No.: %s\n",
N, T, DT, pname);
}
}
static __inline data_t
rand_regular()
{
return rand_norm*rand_func();
}
static __inline data_t
rand_laplace()
{
return rand_func()%2 ? mu-b*log_func(1.0-rand_regular())
: mu+b*log_func(1.0-rand_regular());
}
