public virtual double[] solve(double[] b)
{
double[] b1 = LU.new_copy(b);
LU.solve(this.m_LU, this.m_pivot, b1);
return(b1);
}
public LU(double[][] A)
{
this.m_LU = LU.new_copy(A);
this.m_pivot = new int[A.Length];
LU.factor(this.m_LU, this.m_pivot);
}
public static double measureLU(int N, double min_time, Random R)
{
// compute approx Mlfops, or O if LU yields large errors
double[][] A = RandomMatrix(N, N, R);
double[][] lu = new double[N][];
for (int i = 0; i < N; i++)
{
lu[i] = new double[N];
}
int[] pivot = new int[N];
Stopwatch clock = new Stopwatch();
Stopwatch watch = new Stopwatch();
int cycles = 1;
long copyTime = 0;
long factorTime = 0;
while (true)
{
clock.Start();
for (int i = 0; i < cycles; i++)
{
watch.Start();
CopyMatrix(lu, A);
watch.Stop();
copyTime += watch.ElapsedMilliseconds;
watch.Reset();
watch.Start();
LU.factor(lu, pivot);
watch.Stop();
factorTime += watch.ElapsedMilliseconds;
watch.Reset();
}
clock.Stop();
if (clock.Elapsed.TotalSeconds >= min_time)
{
break;
}
cycles *= 2;
}
Console.WriteLine("Time spent in measureLU:\nCopyMatrix: {0} ms\nLU.factor: {1} ms\ncycles: {2}", copyTime, factorTime, cycles);
// verify that LU is correct
double[] b = RandomVector(N, R);
double[] x = NewVectorCopy(b);
LU.solve(lu, pivot, x);
const double EPS = 1.0e-12;
if (normabs(b, matvec(A, x)) / N > EPS)
{
return(0.0);
}
// else return approx Mflops
//
return(LU.num_flops(N) * cycles / clock.Elapsed.TotalMilliseconds * 1.0e-3);
}
