butools.trace.CdfFromTrace¶

butools.trace.CdfFromTrace()¶

Matlab:	[x, y] = CdfFromTrace(trace)
Mathematica:	{x, y} = CdfFromTrace[trace]
Python/Numpy:	x, y = CdfFromTrace(trace)

Returns the empirical distribution function of the trace.

Parameters:	trace : vector of doubles The trace data
Returns:	x : vector of doubles The points where the empirical cdf is calculated y : vector of doubles The values of the empirical cdf at the given points

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);
>>> [x, y] = CdfFromTrace(tr);
>>> plot(x, y)

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];
>>> {x, y} = CdfFromTrace[tr];
>>> ListLinePlot[{Transpose[{x, y}]}]

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)
>>> x, y = CdfFromTrace(tr)
>>> plt.plot(x, y)