<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def compute_boundaries(self, synt_anchors):
 """ Compute the min cost path between the two waves, and return a list of boundary points, representing the argmin values with respect to the provided ``synt_anchors`` timings. If ``synt_anchors`` has ``k`` elements, the returned array will have ``k+1`` elements, accounting for the tail fragment. :param synt_anchors: the anchor time values (in seconds) of the synthesized fragments, each representing the begin time in the synthesized wave of the corresponding fragment :type synt_anchors: list of :class:`~aeneas.exacttiming.TimeValue` Return the list of boundary indices. :rtype: :class:`numpy.ndarray` (1D) """

        self._setup_dtw()
        if self.dtw is None:
            self.log(u"Inner self.dtw is None => returning artificial boundary indices")
            begin = self.real_wave_mfcc.middle_begin
            end = self.real_wave_mfcc.tail_begin
            n = len(synt_anchors)
            step = float(end - begin) / n
            boundary_indices = [begin + int(i * step) for i in range(n)] + [end]
            return numpy.array(boundary_indices)

        self.log(u"Computing path...")
        real_indices, synt_indices = self.compute_path()
        self.log(u"Computing path... done")

        self.log(u"Computing boundary indices...")
        # both real_indices and synt_indices are w.r.t. the full wave
        self.log([u"Fragments:        %d", len(synt_anchors)])
        self.log([u"Path length:      %d", len(real_indices)])
        # synt_anchors as in seconds, convert them in MFCC indices
        # see also issue #102
        mws = self.rconf.mws
        sample_rate = self.rconf.sample_rate
        samples_per_mws = mws * sample_rate
        if samples_per_mws.is_integer:
            anchor_indices = numpy.array([int(a[0] / mws) for a in synt_anchors])
        else:
            #
            # NOTE this is not elegant, but it saves the day for the user
            #
            self.log_warn(u"The number of samples in each window shift is not an integer, time drift might occur.")
            anchor_indices = numpy.array([(int(a[0] * sample_rate / mws) / sample_rate) for a in synt_anchors])
        #
        # right side sets the split point at the very beginning of "next" fragment
        #
        # NOTE clip() is needed since searchsorted() with side="right" might return
        #      an index == len(synt_indices) == len(real_indices)
        #      when the insertion point is past the last element of synt_indices
        #      causing the fancy indexing real_indices[...] below might fail
        begin_indices = numpy.clip(numpy.searchsorted(synt_indices, anchor_indices, side="right"), 0, len(synt_indices) - 1)
        # first split must occur at zero
        begin_indices[0] = 0
        #
        # map onto real indices, obtaining "default" boundary indices
        #
        # NOTE since len(synt_indices) == len(real_indices)
        #      and because the numpy.clip() above, the fancy indexing is always valid
        #
        boundary_indices = numpy.append(real_indices[begin_indices], self.real_wave_mfcc.tail_begin)
        self.log([u"Boundary indices: %d", len(boundary_indices)])
        self.log(u"Computing boundary indices... done")
        return boundary_indices