Metric for appropriate number of DTW clusters
You can use Silhouette with DTW as distance function.
But don't forget that this just a heuristic. A different k can be better by subjective use.
I am using dynamic time warping (DTW) as a similarity metric to cluster ~3500 time series using the k-means algorithm in Python. 
I am looking for a similar metric to the popular silhouette score used in sklearn.metrics.silhouette_score but relevant to DTW. 
Wondering if anyone can provide any help?