def params(self, ncenters=3, ndims=2, std=0.2, seed=None, update='drift', interval=15, transition=None):

        random.seed(seed)
        if size(ncenters) == 1:
            centers = random.randn(ncenters, ndims) * 2
        else:
            centers = asarray(ncenters)
            ncenters = centers.shape[0]
        self.centers = centers
        self.ncenters = ncenters
        self.ndims = ndims
        self.std = std
        self.update = update
        self.interval = interval
        self.transition = transition

        return self
Set up parameters for a streaming kmeans algorithm demo.
dataset/ETHPy150Open freeman-lab/spark-ml-streaming/python/mlstreaming/kmeans.py/StreamingKMeans.params