static void Main(string[] args)
{
if (args.Length != 3)
{
PrintHelp();
return;
}
else if (args.Length == 1)
{
if (args[0] == "--help" || args[0] == "-h")
{
PrintHelp();
return;
}
}
Int32 dimension = Int32.Parse(args[0]);
Int32 iteration_num = Int32.Parse(args[1]);
double sample_num_m = Convert.ToDouble(args[2]);
Console.Out.WriteLine("dimension: " + dimension);
Console.Out.WriteLine("iteration_num: " + iteration_num);
Console.Out.WriteLine("sample_num in million: " + sample_num_m);
Console.Out.Flush();
Gradient g =
new Gradient(dimension,
iteration_num,
sample_num_m);
long stamp = 0;
double elapsed = 0;
stamp = Stopwatch.GetTimestamp();
g.GenerateSamples();
elapsed = (double)(Stopwatch.GetTimestamp() - stamp) / (double)(Stopwatch.Frequency);
Console.Out.WriteLine("Generating samples(ms): {0:F2} ", 1000 * elapsed);
List <double> elapsed_list = new List <double>();
for (int i = 0; i < g.iteration_num_; ++i)
{
stamp = Stopwatch.GetTimestamp();
g.Advance();
elapsed = (double)(Stopwatch.GetTimestamp() - stamp) / (double)(Stopwatch.Frequency);
Console.Out.WriteLine("Iteration {0:D2} elapsed(ms): {1:F2} ", i, 1000 * elapsed);
elapsed_list.Add(1000 * elapsed);
}
Console.Out.WriteLine("Average gradient computation for {0:D2} iterations(ms): {1:F2} ",
g.iteration_num_, elapsed_list.Average(x => x));
}
