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#include <functional> |
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#include <cassert> |
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#include <fstream> |
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#include <algorithm> |
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#include <vector> |
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#include <iostream> |
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|
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#include "math/SeqRandNumGen.hpp" |
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#ifdef IS_MPI |
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#include <mpi.h> |
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#include "math/ParallelRandNumGen.hpp" |
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#endif |
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using namespace OpenMD; |
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using namespace std; |
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|
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void testUniform(){ |
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SeqRandNumGen randNumGen(823645754); |
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const int N = 100; |
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std::vector<unsigned long int> histogram(N, 0); |
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const unsigned long int num = 10000000; |
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for (int i = 0; i <num; ++i) { |
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int index = randNumGen.randInt(N -1 ); |
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++histogram[index]; // rantInt returns an integer in [0, N-1] |
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} |
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std::ofstream uniform("uniform.dat"); |
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double avg = num / N; |
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double tolerance = 0.01*avg; |
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for (int i = 0; i < N; ++i) { |
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//assert((histogram[i] - avg) /avg <= tolerance); |
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uniform << i << "\t" << histogram[i] << std::endl; |
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} |
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} |
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|
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void testGaussian(){ |
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SeqRandNumGen randNumGen(823645754); |
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double mean = 100.0; |
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double variance = 1.0; |
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const unsigned long int num = 1000000; |
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double interval = 0.1; |
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const int size = 2000; |
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vector<unsigned long int> histogram(size , 0); |
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vector<double> normalizedHistogram(size); |
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for (unsigned long int i = 0; i < num; ++i) { |
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int index = static_cast<int>(randNumGen.randNorm(mean, variance) / interval); |
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++histogram[index]; |
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} |
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|
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std::transform(histogram.begin(), histogram.end(), normalizedHistogram.begin(), std::bind2nd(std::divides<double>(), num)); |
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std::ofstream gaussian("gaussian.dat"); |
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for (int i = 0; i < size; ++i) { |
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gaussian << i*interval << "\t" << normalizedHistogram[i] << std::endl; |
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} |
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} |
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#ifdef IS_MPI |
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void testParallelRandNumGen(){ |
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const unsigned long int seed = 324271632; |
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const unsigned long int nloops = 1000000; |
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MPI_Status istatus; |
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ParallelRandNumGen mpiRandNumGen(seed); |
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const int masterNode = 0; |
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int myRank; |
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MPI_Comm_rank( MPI_COMM_WORLD, &myRank ); |
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if (myRank == masterNode) { |
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|
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SeqRandNumGen singleRandNumGen(seed); |
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std::ofstream singleOs("single.dat"); |
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std::ofstream parallelOs("parallel.dat"); |
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int nProcessors; |
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MPI_Comm_size(MPI_COMM_WORLD, &nProcessors); |
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std::vector<unsigned long int> mpiRandNums(nProcessors); |
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std::vector<unsigned long int> singleRandNums(nProcessors); |
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|
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for (unsigned long int i = 0; i < nloops; ++i) { |
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mpiRandNums[masterNode] = mpiRandNumGen.randInt(); |
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|
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for (int j = 0; j < nProcessors; ++j) { |
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if (j != masterNode) { |
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MPI_Recv(&mpiRandNums[j], 1, MPI_UNSIGNED_LONG, j, i, MPI_COMM_WORLD, &istatus); |
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} |
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|
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singleRandNums[j] = mpiRandNumGen.randInt(); |
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} |
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|
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for (int j = 0; j < nProcessors; ++j) { |
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singleOs << singleRandNums[j] << "\n"; |
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parallelOs << singleRandNums[j] << "\n"; |
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} |
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} |
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|
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|
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|
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} else { |
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|
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unsigned long int randNum; |
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for (unsigned long int i = 0; i < nloops; ++i) { |
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randNum = mpiRandNumGen.randInt(); |
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MPI_Send(&randNum, 1, MPI_INT, masterNode, i, MPI_COMM_WORLD); |
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} |
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|
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} |
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|
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} |
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#endif |
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int main(int argc, char* argv[]) { |
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#ifdef IS_MPI |
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MPI_Init(&argc, &argv); |
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std::cout << "begin test" << std::endl; |
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if (worldRank == 0 ) { |
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testUniform(); |
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testGaussian(); |
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} |
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|
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testParallelRandNumGen(); |
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|
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MPI_Finalize(); |
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#else |
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std::cout << "begin test" <<std::endl; |
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testUniform(); |
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testGaussian(); |
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#endif |
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std::cout << "test done" << std::endl; |
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return 0; |
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} |
