Use uniform sampling as initial centers for k-means

Use uniform sampling as initial centers for k-means

The Wiener variance output has been sorted prior to the clustering,
which allows to directly use the uniform sampling as the initial
center points. It avoids empty cluster situations when the samples
are heavily distributed at two far ends and leave the middle empty.

Change-Id: I159fbfa6bbb4aafd19411fd005666d144cca30fc