I am implementing an unconstrained/subsequence DTW algorithm (in R). The query of data which I am trying to find a match within the reference data is much smaller (as compared to reference). I have read in R's dtw library documentation that only normalizable step patterns can be used when dealing with unconstrained DTW. I started with asymmetric step pattern but read in the official library documentation that "the asymmetric step pattern limits time expansion to a factor of two; it would therefore be impossible to completely align a query with a reference more than twice as long". Given in my case reference data is much larger than query data this probably won't work.
I am implementing in R so I have these options available: http://finzi.psych.upenn.edu/library/dtw/html/stepPattern.html
Please note that I am not looking for guidance in terms of how to implement it in R. This is a purely statistical doubt I have. I am looking for the best step pattern that can be used in an unconstrained/subsequence DTW implementation.