butools.dmap.SamplesFromDMAP¶
-
butools.dmap.
SamplesFromDMAP
()¶ Matlab: x = SamplesFromDMAP(D0, D1, K, prec)
Mathematica: x = SamplesFromDMAP[D0, D1, K, prec]
Python/Numpy: x = SamplesFromDMAP(D0, D1, K, prec)
Generates random samples from a discrete Markovian arrival process.
Parameters: D0 : matrix, shape (M,M)
The D0 matrix of the discrete MAP.
D1 : matrix, shape (M,M)
The D1 matrix of the discrete MAP.
K : integer
The number of samples to generate.
prec : double, optional
Numerical precision to check if the input DMAP is valid. The default value is 1e-14.
Returns: x : vector, length(K)
The vector of random samples (inter-arrival times).
Examples
For Matlab:
>>> D0 = [0, 0.02, 0, 0; 0, 0.17, 0.2, 0.14; 0.16, 0.17, 0.02, 0.18; 0, 0, 0, 0.12]; >>> D1 = [0, 0.88, 0.1, 0; 0.18, 0.07, 0.14, 0.1; 0.13, 0.15, 0.15, 0.04; 0.31, 0.18, 0.12, 0.27]; >>> x = SamplesFromDMAP(D0, D1, 10000); >>> mt = MarginalMomentsFromTrace(x, 3); >>> disp(mt); 1.5171 3.0613 8.3949 >>> mm = MarginalMomentsFromDMAP(D0, D1, 3); >>> disp(mm); 1.4955 2.9542 7.8852
For Mathematica:
>>> D0 = {{0, 0.02, 0, 0},{0, 0.17, 0.2, 0.14},{0.16, 0.17, 0.02, 0.18},{0, 0, 0, 0.12}}; >>> D1 = {{0, 0.88, 0.1, 0},{0.18, 0.07, 0.14, 0.1},{0.13, 0.15, 0.15, 0.04},{0.31, 0.18, 0.12, 0.27}}; >>> x = SamplesFromDMAP[D0, D1, 10000]; >>> mt = MarginalMomentsFromTrace[x, 3]; >>> Print[mt]; {1.4932, 2.9154, 7.5202} >>> mm = MarginalMomentsFromDMAP[D0, D1, 3]; >>> Print[mm]; {1.4955358592094412, 2.9542479654368474, 7.885226907678561}
For Python/Numpy:
>>> D0 = ml.matrix([[0, 0.02, 0, 0],[0, 0.17, 0.2, 0.14],[0.16, 0.17, 0.02, 0.18],[0, 0, 0, 0.12]]) >>> D1 = ml.matrix([[0, 0.88, 0.1, 0],[0.18, 0.07, 0.14, 0.1],[0.13, 0.15, 0.15, 0.04],[0.31, 0.18, 0.12, 0.27]]) >>> x = SamplesFromDMAP(D0, D1, 10000) >>> mt = MarginalMomentsFromTrace(x, 3) >>> print(mt) [1.5088999999999999, 3.0240999999999998, 8.1935000000000002] >>> mm = MarginalMomentsFromDMAP(D0, D1, 3) >>> print(mm) [1.4955358592094412, 2.9542479654368474, 7.885226907678561]