I don't know about tel, but I use both pretty frequently (and usually together with rpy). R is great for some things, but I typically find that I need to use a general purpose language to acquire the data I'm processing. There are some processing steps that I easier in R though, so I offload things to that when it is more efficient. But for simpler things, I find that numpy is more than adequate for processing data that I've already got in a Python session.

I use them for bioinformatics analysis (large scale genomic comparisons and microarray data analysis). So the larger problem isn't the calculations, it's the data management. And for that Python wins over a pure R solution.