int main(int argc, char *argv[])
{
int nPixel1D = 512;
int option;
option = getopt(argc, argv, "n:");
switch(option)
{
case 'n':
nPixel1D = atoi(optarg);
default:
break;
}
/*
* Windows won't let us declare local (i.e. stack) variables this
* large (Linux will -- so there!), so we need to declare them
* static (i.e. global) for portability.
*/
double *z;
ALLOC_ARRAY(z, double, nPixel1D*nPixel1D);
//static double z[nPixel1D][nPixel1D];
sampleFunction(hemisphere, z, nPixel1D); // try "ripple" or your own function's name
printSquarePgm(z, nPixel1D);
return 0;
}
int main() {
std::cout << "Sample" << std::endl;
std::cout << "sample 2" << std::endl;
std::cout << "Code" << std::endl;
std::cout << "Test" << std::endl;
std::cout << "Test2" << std::endl;
sampleFunction();
return 0;
}
//Gets some test data
vector<std::tuple<float*, int*> > getTestData ()
{
vector<std::tuple<float*,int*> > trainingDataSet;
for (int x = -50; x != 50; ++x)
{
for (int y = -50; y != 50; ++y)
{
float* featureVector = new float[2];
featureVector[0] = ((float) x)/30.0; //normalize the data
featureVector[1] = ((float) y)/30.0; //normalize the data
int* targets = new int [1];
targets[0] = sampleFunction(x,y);;
trainingDataSet.push_back(std::make_tuple(featureVector, targets));
}
}
std::random_shuffle(trainingDataSet.begin(), trainingDataSet.end());
return trainingDataSet;
}
