public void CompareSequencesOfMersennes()
{
Random rnd = new Random();
for (int i = 0; i < 10; i++)
{
int seed = rnd.Next();
var m1 = new MT19937();
m1.init_genrand((ulong)seed);
var m2 = new RandomMT((ulong)seed);
var m3 = new SharpDevs.Randomization.MersenneTwister(seed);
var m4 = new Random(seed);
for (int j = 0; j < 10; j++)
{
var r1 = m1.genrand_int32();
var r2 = m2.RandomInt();
var r3 = m3.GetNextULong();
var r4 = m4.Next();
Console.WriteLine("{0}\t{1}\t{2}\t{3}", r1, r2, r3, r4);
//Assert.AreEqual(r1, r2);
//Assert.AreEqual(r2, r3);
}
Console.WriteLine();
}
}
public void CompareDistributionOfMersennes()
{
Random rnd = new Random();
int baseSeed = rnd.Next();
var m1 = new MT19937();
m1.init_genrand((ulong)baseSeed);
var m2 = new RandomMT((ulong)baseSeed);
var m3 = new SharpDevs.Randomization.MersenneTwister(baseSeed);
var m4 = new Random(baseSeed);
var maxRange = 1000;
var iterations = 10000000;
var dist1 = CalculateDistribution(() => m1.RandomRange(0, maxRange - 1), maxRange, iterations);
var dist2 = CalculateDistribution(() => m2.RandomRange(0, maxRange - 1), maxRange, iterations);
var dist3 = CalculateDistribution(() => m3.GetNext(0, maxRange), maxRange, iterations);
var dist4 = CalculateDistribution(() => m4.Next(0, maxRange), maxRange, iterations);
var distribution1 = AnalyzeDistribution(dist1, iterations);
var distribution2 = AnalyzeDistribution(dist2, iterations);
var distribution3 = AnalyzeDistribution(dist3, iterations);
var distribution4 = AnalyzeDistribution(dist4, iterations);
Console.WriteLine("{0}\t{1}\t{2}\t{3}",
distribution1, distribution2, distribution3, distribution4);
var expectedFill = (decimal)iterations / maxRange;
Console.WriteLine("Przy oczekiwanym napełnieniu: " + expectedFill);
Console.WriteLine("Co daje procentowo:");
Console.WriteLine("{0}\t{1}\t{2}\t{3}",
distribution1 / expectedFill * 100,
distribution2 / expectedFill * 100,
distribution3 / expectedFill * 100,
distribution4 / expectedFill * 100);
}
public void CompareSequencesOfMersennes()
{
Random rnd = new Random();
for (int i = 0; i < 10; i++)
{
int seed = rnd.Next();
var m1 = new MT19937();
m1.init_genrand((ulong)seed);
var m2 = new RandomMT((ulong)seed);
var m3 = new SharpDevs.Randomization.MersenneTwister(seed);
var m4 = new Random(seed);
for (int j = 0; j < 10; j++)
{
var r1 = m1.genrand_int32();
var r2 = m2.RandomInt();
var r3 = m3.GetNextULong();
var r4 = m4.Next();
Console.WriteLine("{0}\t{1}\t{2}\t{3}", r1, r2, r3, r4);
//Assert.AreEqual(r1, r2);
//Assert.AreEqual(r2, r3);
}
Console.WriteLine();
}
}
//--------------------------------------------------------------------------------------------------
//初期値をランダムに設定 (0,1]
public static double[,] initMatrix(int N, int M)
{
RandomMT rand = new RandomMT();
double[,] A = new double[N, M];
for (int i = 0; i < N; i++)
for (int j = 0; j < M; j++)
A[i, j] = 10 * rand.Double32OC();
return A;
}
/// <summary>
/// ステージ初期化の処理を書く。
/// </summary>
private void _initialize()
{
_rand = new RandomMT();
_player = new GameObject(ClientSize.Width / 2, ClientSize.Height * 3 / 4);
_enemies = new List <Enemy2>();
_bullets = new List <Bullet>();
_createBullet = false;
_enter = false;
for (var i = 0; i < 20; i++)
{
var newEnemy = new Enemy2(_rand.Int(ClientSize.Width - 20), _rand.Int(ClientSize.Height / 2 - 20));
_enemies.Add(newEnemy);
}
}
static void Main(string[] args)
{
RandomMT mt = new RandomMT(0x7449BBFF801FED0B);
for (int i = 0; i < 781; ++i)
{
if (i % 4 == 0)
{
Console.WriteLine();
Trace.WriteLine("");
}
Console.Write("0x{0:X}UL,", mt.RandomInt() | mt.RandomInt() << 32);
Trace.Write(string.Format("0x{0:X}UL,", mt.RandomInt() | mt.RandomInt() << 32));
}
}
private void MAKEDATA(ref double[,] _designmatrix, ref double[] _t, ref double[] _X)
{
var r = new RandomBoxMuller();
RandomMT rand = new RandomMT(1);
for (int i = 0; i < CONST.N; i++)
{
_X[i] = rand.Double() * Math.PI * 2;
_t[i] = System.Math.Sin(_X[i]) + r.next();
}
for (int j = 0; j < CONST.N; j++)
{
for (int i = 0; i < CONST.M; i++)
{
_designmatrix[j, i] = System.Math.Pow(_X[j], i);
if (i == 0)
{
_designmatrix[j, i] = 1;
}
}
}
}
public void CompareDistributionOfMersennes()
{
Random rnd = new Random();
int baseSeed = rnd.Next();
var m1 = new MT19937();
m1.init_genrand((ulong)baseSeed);
var m2 = new RandomMT((ulong)baseSeed);
var m3 = new SharpDevs.Randomization.MersenneTwister(baseSeed);
var m4 = new Random(baseSeed);
var maxRange = 1000;
var iterations = 10000000;
var dist1 = this.CalculateDistribution(() => m1.RandomRange(0, maxRange - 1), maxRange, iterations);
var dist2 = this.CalculateDistribution(() => m2.RandomRange(0, maxRange - 1), maxRange, iterations);
var dist3 = this.CalculateDistribution(() => m3.GetNext(0, maxRange), maxRange, iterations);
var dist4 = this.CalculateDistribution(() => m4.Next(0, maxRange), maxRange, iterations);
var distribution1 = this.AnalyzeDistribution(dist1, iterations);
var distribution2 = this.AnalyzeDistribution(dist2, iterations);
var distribution3 = this.AnalyzeDistribution(dist3, iterations);
var distribution4 = this.AnalyzeDistribution(dist4, iterations);
Console.WriteLine("{0}\t{1}\t{2}\t{3}",
distribution1, distribution2, distribution3, distribution4);
var expectedFill = (decimal)iterations / maxRange;
Console.WriteLine("Przy oczekiwanym napełnieniu: " + expectedFill);
Console.WriteLine("Co daje procentowo:");
Console.WriteLine("{0}\t{1}\t{2}\t{3}",
distribution1 / expectedFill * 100,
distribution2 / expectedFill * 100,
distribution3 / expectedFill * 100,
distribution4 / expectedFill * 100);
}
//----------------------------------------------------------------------------------
static void Update(out double[] alpha, out double[] beta, double[] gamma, out double[][] u, out double[][,] V)
{
RandomMT rnd = new RandomMT();
double[,] lo = new double[S, M];
double[,] r = new double[S, M];
double[] ita = new double[M];
alpha = new double[M]; beta = new double[M]; gamma = new double[M];
u = new double[M][];
V = new double[M][,];
for (int m = 0; m < M; m++)
{
alpha[m] = alpha0;
beta[m] = beta0;
gamma[m] = gamma0;
//u[m] = (double[])u0.Clone();
V[m] = (double[,])V0.Clone();
}
u = New.Array(M, m => matrixTojag(X)[rnd.Int(S)].ToArray());
double[] old_alpha = new double[M], old_beta = new double[M], old_gamma = new double[M];
var old_V = (double[][,])V.Clone();
double error;
do
{
//Update lo
for (int s = 0; s < S; s++)
for (int m = 0; m < M; m++)
{
double a = diGamma(alpha[m]);
double b = Enumerable.Range(1, D).Sum(dd => diGamma((gamma[m] + 1 - dd) / 2.0));
double c = Math.Log(Mt.Det(V[m]));
double d = -D / beta[m];
double e = -gamma[m] * Mt.QuadraticForm(V[m], Mt.Sub(getRow(X, s), u[m]));
lo[s, m] = Math.Exp(a + 0.5 * (b + c + d + e));
}
//Update r
for (int i = 0; i < S; i++)
{
double lo_sum = sumOfmatrix_row(lo, i);
for (int j = 0; j < M; j++)
{
if (lo_sum != 0)
r[i, j] = lo[i, j] / lo_sum;
}
}
//Update ita
for (int j = 0; j < M; j++)
ita[j] = sumOfmatrix_column(r, j);
//Update alpha,beta,gamma
old_alpha = (double[])alpha.Clone();
old_beta = (double[])beta.Clone();
old_gamma = (double[])gamma.Clone();
for (int j = 0; j < M; j++)
{
alpha[j] = alpha0 + ita[j];
beta[j] = beta0 + ita[j];
gamma[j] = gamma0 + ita[j];
}
//Update u
for (int j = 0; j < M; j++)
{
double[,] rX = Mt.Mul(X.T(), r);
for (int i = 0; i < D; i++)
u[j][i] = (beta0 * u0[i] + rX[i, j]) / beta[j];
}
//Update V
V.CopyTo(old_V);
double[,] A = new double[D, D];
double[,] B = new double[D, D];
double[,] rXsubu_adamar = new double[S, D];
double[,] Xsubu = new double[S, D];
for (int j = 0; j < M; j++)
{
for (int i = 0; i < D; i++)
for (int ii = 0; ii < D; ii++)
A[i, ii] = beta0 * (u[j][i] - u0[i]) * (u[j][ii] - u0[ii]);
for (int s = 0; s < S; s++)
for (int d = 0; d < D; d++)
{
rXsubu_adamar[s, d] = (X[s, d] - u[j][d]) * r[s, j];
Xsubu[s, d] = X[s, d] - u[j][d];
}
B = Mt.Mul(Xsubu.T(), rXsubu_adamar);
V[j] = Mt.Add(Mt.Add(V0_inv, A), B);
V[j] = V[j].Inverse();
}
error = errorCalc(alpha, old_alpha) + errorCalc(beta, old_beta) + errorCalc(gamma, old_gamma) + errorCalc(V, old_V);
} while (error > 1e-10);
}
//----------------------------------------------------------------------------------
static void predicted_Distribution_output(double[][] u, double[][,] V)
{
int Num = 300; //等高線描画用プロット数
int Ratio = 10000000;
RandomMT rand = new RandomMT();
double[][] x_toukou = new double[Num][]; //等高線描画用プロット点
for (int m = 0; m < M; m++)
{
double[,] U; //直交固有ベクトル行列
double[] lambda; //固有値
Tuple<double[,], double[]> tu;
tu = Mt.EigenValueDecompositionM(V[m]);
lambda = tu.Item2;
U = tu.Item1;
bool sign_flag = true;
for (int n = 0; n < Num; n++)
{
sign_flag = !sign_flag;
double[] y = new double[2];
y[1] = 2.0 * Math.Sqrt(lambda[0] * Ratio) * rand.Double() - Math.Sqrt(lambda[0] * Ratio); //楕円の定義域内に
if (sign_flag)
y[0] = Math.Sqrt(lambda[1] * Ratio - y[1] * y[1] * lambda[1] / lambda[0]); //次元を逆にしたら上手く等高線が書けたが．．．たぶん直交行列Uの構成の仕方が原因
else
y[0] = -Math.Sqrt(lambda[1] * Ratio - y[1] * y[1] * lambda[1] / lambda[0]);
x_toukou[n] = Mt.Add(Mt.Mul(U.Inverse(), y), u[m]);
}
CsvFileIO.CsvFileIO.WriteData("x_toukou(M=" + m + ").csv", jagTomatrix(x_toukou));
}
CsvFileIO.CsvFileIO.WriteData("mu_matrix.csv", jagTomatrix(u));
}
//----------------------------------------------------------------------------
static void init(int shift_flag, int fixed_flag, int baseNumForNoise)
{
//string input_filename = @"C:\Users\優\Desktop\音素材\GaPNMF\君の知らない_cq.csv";
string input_filename = @"C:\Users\優\Desktop\音素材\cq(mix4).csv";
string fixed_T_filename = @"C:\Users\優\Desktop\音素材\GaPNMF\Base_mix4.csv";
//string fixed_T_filename = @"C:\Users\優\Desktop\音素材\GaPNMF\piano_c4_cq_w.csv";
X = CsvFileIO.CsvFileIO.ReadData(input_filename);
I = X.GetLength(0);
J = X.GetLength(1);
if (fixed_flag == 0)
K = 4;
tau = 7;
fai = 48; //36がbetter
XdiviXhat = new double[I, J];
//T,Vの初期化
switch (shift_flag)
{
// only f shift
case 0:
tau = 1;
if (fixed_flag == 0)
T.Add(initMatrix(I, K));
else
{
double[,] baseMat=CsvFileIO.CsvFileIO.ReadData(fixed_T_filename);
RandomMT rand = new RandomMT();
T.Add(New.Array(I, baseMat.GetLength(1) + baseNumForNoise, (i, j) => { if (j < baseMat.GetLength(1)) return baseMat[i, j]; else { return 10 * rand.Double32OC(); } }));
K = T[0].GetLength(1);
}
break;
// f and time shift
case 1:
for (int tt = 0; tt < tau; tt++)
T.Add(initMatrix(I, K));
break;
}
for (int ff = 0; ff < fai; ff++)
V.Add(initMatrix(K, J));
//onesの初期化
ones = new double[I, J];
for (int i = 0; i < I; i++)
for (int j = 0; j < J; j++)
ones[i, j] = 1;
}
public static void SeedRNG(string seedString)
{
seed = seedString.GetHashCode ();
RNG = new RandomMT((ulong)seed);
}
//--------------------------------------------------------------------------------
//ガンマ分布に従う乱数生成
static double gamma_rnd(RandomMT rand, double shape, double scale)
{
double output;
double input = rand.Double();
output = scale * Mt.InverseIncompleteGamma(input, shape);
return output;
}
static void Main(string[] args)
{
var v = Environment.TickCount;
var rand = new RandomMT();
for (int i = 0; i < 100; i++)
{
random_(rand);
}
//string arenaRankingKey_ = "hwal2.ranking.arena";
//long start = 0;
//long stop = start + 101 - 1;
//int accountNo = 1;
//Order order = Order.Descending;
//var redis = ConnectionMultiplexer.Connect("10.11.35.12:6379").GetDatabase();
//var list = redis.SortedSetRangeByRankWithScores(arenaRankingKey_, start, stop, order);
//var rank = redis.SortedSetRank(arenaRankingKey_, accountNo, order);
//var total = redis.SortedSetLength(arenaRankingKey_);
//var val1 = (Convert.ToDouble(rank + 1) / total) * 100;
//var val2 = Convert.ToInt32(Math.Round(val1));
//var rating = Convert.ToInt32(((Convert.ToDouble(rank + 1) / total) * 100) + 0.5);
//var val3 = DateTime.Now.DayOfYear;
//GregorianCalendar cal = new GregorianCalendar(GregorianCalendarTypes.Localized);
//var val4 = cal.GetWeekOfYear(DateTime.Now, CalendarWeekRule.FirstFourDayWeek, DayOfWeek.Monday);
//var val5 = getWeekNum();
//var total = redis.SortedSetLength("hwal2:ranking:league:global:w:20151219");
//var list2 = redis.SortedSetRangeByRankWithScores("hwal2:ranking:league:global:w:20151219", 0, 100, Order.Descending);
//var rank = start;
//foreach (var item in list2)
//{
// ++rank;
// var key = Convert.ToInt32(item.Element);
// var val = Convert.ToDouble(item.Score);
// var rate = Math.Round((Convert.ToDouble(rank) / 10000) * 100, 5);
//}
// //
// return;
//int max = 50000000;
//int[] nums1 = Enumerable.Range(1, max).ToArray<int>();
//int[] nums2 = Enumerable.Range(1, max).ToArray<int>();
//ParallelFor(nums1);
//RangeParallelForEach(nums2);
//Presence presence = new Presence();
//t_Account account = new t_Account();
//account.Acctidx = 1;
//LobbyUser user = new LobbyUser();
//user.EnterPresence_();
//PresenceConnector presence = new PresenceConnector("10.11.35.21", 6379);
//presence.Connect();
//presence.Add("hwal2.1", new t_Account() { Acctidx = 1 }, DateTimeOffset.Now.AddSeconds(3000000));
//presence.Add("hwal2.2", new t_Account() { Acctidx = 2 }, DateTimeOffset.Now.AddSeconds(3000000));
//var account1 = presence.Get<t_Account>("hwal2.1");
//List<string> keys = new List<string>()
//{
// "hwal2.1",
// "hwal2.2",
// "hwal2.3"
//};
//var list = presence.Get<t_Account>(keys.ToArray());
//var exist = presence.Exist(keys[0]);
//var existList = presence.Exist(keys);
//var server = RedisConnectionMultiplexer.GetServer("10.11.35.21:6379");
//System.Console.WriteLine("******************************");
//using (var redis = ConnectionMultiplexer.Connect("10.11.35.21:6379"))
//{
// var db = redis.GetDatabase();
// using (var redis1 = ConnectionMultiplexer.Connect("10.11.35.21:6379"))
// {
// var db1 = redis.GetDatabase();
// }
//}
}
