butools.trace.PdfFromWeightedTrace
==================================

.. currentmodule:: butools.trace

.. np:function:: PdfFromWeightedTrace

    .. list-table::
        :widths: 25 150

        * - Matlab:
          - :code:`[x, y] = PdfFromWeightedTrace(trace, weights, intBounds)`
        * - Mathematica:
          - :code:`{x, y} = PdfFromWeightedTrace[trace, weights, intBounds]`
        * - Python/Numpy:
          - :code:`x, y = PdfFromWeightedTrace(trace, weights, intBounds)`

    Returns the empirical density function of a trace 
    consisting of weighted data.

    Parameters
    ----------
    trace : vector of doubles
        The trace data
    weights : vector of doubles
        The weights corresponding to the trace data
    intBounds : vector of doubles
        The array of interval boundaries. The pdf is the 
        number of samples falling into an interval divided by
        the interval length.

    Returns
    -------
    x : vector of doubles
        The center of the intervals (the points where the 
        empirical pdf is calculated)
    y : vector of doubles
        The values of the empirical pdf at the given points

    Examples
    ========
    For Matlab:

    >>> wtrace = [0.12, 1.23, 0.546, 0.6765, 1.34, 2.34];
    >>> weights = [12., 1., 34., 23., 8., 2.];
    >>> x = (0.0:0.1:3.0);
    >>> [x, y] = PdfFromWeightedTrace(wtrace, weights, x);
    >>> plot(x, y)

    For Mathematica:

    >>> wtrace = {0.12, 1.23, 0.546, 0.6765, 1.34, 2.34};
    >>> weights = {12., 1., 34., 23., 8., 2.};
    >>> x = Range[0.0,3.0,0.1];
    >>> {x, y} = PdfFromWeightedTrace[wtrace, weights, x];
    >>> ListLinePlot[{Transpose[{x, y}]}]

    For Python/Numpy:

    >>> wtrace = [0.12, 1.23, 0.546, 0.6765, 1.34, 2.34]
    >>> weights = [12., 1., 34., 23., 8., 2.]
    >>> x = np.arange(0.0,3.1,0.1)
    >>> x, y = PdfFromWeightedTrace(wtrace, weights, x)
    >>> plt.plot(x, y)