butools.trace.LagCorrelationsFromTrace¶

butools.trace.LagCorrelationsFromTrace()¶

Matlab:	acf = LagCorrelationsFromTrace(trace, K)
Mathematica:	acf = LagCorrelationsFromTrace[trace, K]
Python/Numpy:	acf = LagCorrelationsFromTrace(trace, K)

Returns the lag-k autocorrelation of a trace.

Parameters:	trace : vector of doubles The trace data K : int The number of lags to compute
Returns:	acf : column vector of doubles The lag-k autocorrelation function of the trace up to lag K

Examples

For Matlab:

>>> D0 = [-18., 1., 4.; 2., -18., 7.; 1., 3., -32.];
>>> D1 = [12., 1., 0.; 1., 8., 0.; 2., 1., 25.];
>>> tr = SamplesFromMAP(D0, D1, 1000000);
>>> acf = LagCorrelationsFromTrace(tr, 10);
>>> disp(acf);
  Columns 1 through 6
     0.043246     0.020421     0.012588    0.0071917    0.0033881    0.0013752
  Columns 7 through 10
    0.0015924  -0.00037795    0.0011809   -0.0002111
>>> macf = LagCorrelationsFromMAP(D0, D1, 10);
>>> disp(macf);
  Columns 1 through 6
     0.041288     0.021962     0.012085    0.0068325    0.0039434    0.0023103
  Columns 7 through 10
    0.0013679   0.00081587   0.00048904   0.00029412

For Mathematica:

>>> D0 = {{-18., 1., 4.},{2., -18., 7.},{1., 3., -32.}};
>>> D1 = {{12., 1., 0.},{1., 8., 0.},{2., 1., 25.}};
>>> tr = SamplesFromMAP[D0, D1, 1000000];
>>> acf = LagCorrelationsFromTrace[tr, 10];
>>> Print[acf];
{0.04171700392495588, 0.02236325130968886, 0.011816781009753847, 0.006580180898166265, 0.002870033223830658, 0.0012545187131443494, 0.0015889735659457254, -0.000499385277140403, 0.0006390034516353842, 0.000016288615554384205}
>>> macf = LagCorrelationsFromMAP[D0, D1, 10];
>>> Print[macf];
{0.04128838551112271, 0.021962312595973178, 0.012084710346466325, 0.006832495032493742, 0.003943351206134012, 0.0023102617023690345, 0.0013678941146099855, 0.0008158651499616962, 0.0004890400598515401, 0.0002941204987862201}

For Python/Numpy:

>>> D0 = ml.matrix([[-18., 1., 4.],[2., -18., 7.],[1., 3., -32.]])
>>> D1 = ml.matrix([[12., 1., 0.],[1., 8., 0.],[2., 1., 25.]])
>>> tr = SamplesFromMAP(D0, D1, 1000000)
>>> acf = LagCorrelationsFromTrace(tr, 10)
>>> print(acf)
[0.043090455671182491, 0.023571565460491006, 0.014064127972931892, 0.0085436481559293485, 0.0051488473491149676, 0.0033839569528235254, -0.00053777751233521638, 0.00055429070630664428, 0.00056428151275644746, -0.0018268950662940562]
>>> macf = LagCorrelationsFromMAP(D0, D1, 10)
>>> print(macf)
[ 0.04129  0.02196  0.01208  0.00683  0.00394  0.00231  0.00137  0.00082  0.00049  0.00029]