On Tuesday, May 31, 2016 at 6:02:07 PM UTC-7, Rob Gaddi wrote: > You'll probably want to process it in blocks. Allocate a 3kB > bytearray, assign into it from the data coming in off Serial (less > the newlines) and when you fill it, call numpy.from_buffer to rip it.
Thanks Rob, numpy.frombuffer (no underscore in my version of Numpy, v.1.8) looks like it will be very helpful! > Then just print the first line of it. Decimating the data > rate radically will help with the print-induced load, and it's not > like you need to see every sample. > > Are you going to be trying to use this data realtime, or are you just > trying to datalog it and deal with it offline? Because at some point > you'll need to decide, all in, how much data you're willing to try to > hold in memory and what you intend to do with the rest of it. No, I don't need to print all the data... in fact, I don't plan to print any of it when I'm done. I do want to save every data packet for offline analysis. I also want to display real-time histograms of at least some of the data. I've already cobbled together (but have not optimized) a Matplotlib program that displays mock data at 16 FPS, which is fast enough. I used to work on flow cytometers. Look them up if you're interested in multi-dimensional, real-time data display. -- https://mail.python.org/mailman/listinfo/python-list
