DTW with time-aware/variable Sakoe-Chiba radius

Question

I'm comparing two irregulary spaced time series with tslearn implementation of DTW. As both time-series are very irregulary sampled and their sampling isn't correlated, I would like to use Sakoe-Chiba radius to constrain range of compared observation to one hour (for example), if I would have regularly sampled time series in, let say, 1 minute intervals I would use Sakoe-Chiba radius equal to 60, but I don't have such data, it should exists more natural solution then data manipulation (interpolation to 1 minute time interval) for example variable Sakoe-Chiba radius (each observation have different S-Ch radius, precomputed to obtain equivalent of 1 hour constrain), is there reasons that would be computationally inefficient in comparison to constant S-Ch radius ?