environment_t test_environment()
{
row_t*row = row_new(4);
row->inputs[0] = variable_new_continuous(1.0);
row->inputs[1] = variable_new_continuous(2.0);
row->inputs[2] = variable_new_continuous(4.0);
row->inputs[3] = variable_new_categorical(5);
environment_t e;
e.row = row;
return e;
}
//--------------------helper functions --------------------------------
int add_item(example_t*e, int pos, PyObject*item)
{
if(pyint_check(item)) {
e->inputs[pos] = variable_new_continuous(pyint_as_long(item));
} else if(PyFloat_Check(item)) {
e->inputs[pos] = variable_new_continuous(PyFloat_AS_DOUBLE(item));
} else if(pystring_check(item)) {
e->inputs[pos] = variable_new_text(pystring_asstring(item));
} else {
PY_ERROR("bad object %s in list", item->ob_type->tp_name);
return 0;
}
return 1;
}
int main()
{
config_parse_remote_servers("servers.txt");
trainingdata_t* data = trainingdata_new();
int t;
for(t=0;t<256;t++) {
example_t*e = example_new(16);
int s;
for(s=0;s<16;s++) {
e->inputs[s] = variable_new_continuous((lrand48()%256)/256.0);
}
e->desired_response = variable_new_categorical(t%2);
trainingdata_add_example(data, e);
}
trainingdata_save(data, "/tmp/data.data");
trainingdata_destroy(data);
data = trainingdata_load("/tmp/data.data");
model_t*m = model_select(data);
char*code = model_generate_code(m, "python");
printf("%s\n", code);
free(code);
model_destroy(m);
trainingdata_destroy(data);
}
void test()
{
trainingdata_t* data = trainingdata_new();
int t;
for(t=0;t<256;t++) {
example_t*e = example_new(16);
int s;
for(s=0;s<16;s++) {
e->inputs[s] = variable_new_continuous((lrand48()%256)/256.0);
}
e->desired_response = variable_new_categorical(t%2);
trainingdata_add_example(data, e);
}
dataset_t*dataset = trainingdata_sanitize(data);
model_t*m = process_job_remotely("dtree", dataset);
if(m) {
printf("%s\n", m->name);
}
}
