Once this is all working, you could have get_iq_online() work in a separate thread so that you don't have to hit the network every time work() is called. Maybe buffer a small number of frames in a queue.
On Tue, Aug 16, 2022 at 10:13 AM Jeff Long <willco...@gmail.com> wrote: > Hi Carl, > > Use vectors only if data always needs to be grouped in exact quantities, > e.g., if the GR flowgraph needs to always handle blocks of 2^20 items. In > general, a 5-channel stream would be more flexible. The variation in the > number of items would be due to the output buffer sometimes being empty and > sometimes not. This depends on what is happening in downstream blocks, and > also on random scheduling of threads. Hope that answers some of your > questions. > > On Tue, Aug 16, 2022 at 9:49 AM Carl Laufer <ad...@rtl-sdr.com> wrote: > >> Hi All, >> >> I'm currently working on a GNU Radio source block for the KrakenSDR. So >> far my block mostly seems to work as expected, but I'm having some minor >> issues and questions. >> >> If you didn't know, the KrakenSDR is 5 RTL-SDR receivers, on the same >> clock with a noise source for coherence calibration of the channels. We're >> using it for applications like radio direction finding and passive >> radar, and mostly write our own code in Python. But having a GNU Radio >> source would be useful for others. >> >> With KrakenSDR there is a DAQ software called "heimdall" which handles >> all the coherent calibration automatically. In my source block, I'm able to >> successfully receive the data in the GNU Radio source block from heimdall >> via a socket connection. >> >> First so you know, the heimdall DAQ buffers an array of "cpi_size" (cpi = >> coherent processing interval) IQ data per channel, and outputs those arrays >> on the socket when it's filled. By default the cpi_size = 2^20. So in my >> GNU Radio source I'm receiving five, 2^20 long arrays of coherent complex >> IQ data every ~400ms. >> >> I believe in GNU Radio this is considered a vector? So should I make the >> output of the source block five port vectors, with out_sig=[(np.complex64, >> cpi_size)] * numChannels and set vlen to cpi_size in the yaml? >> >> Or instead should I have it as an output stream out_sig=[np.complex64] * >> numChannels, and be using Stream->Vector blocks when needed, with num_items >> set to cpi_size? >> >> I've tried both methods, and they both work. But I don't understand why >> when using the vector output implementation, the shape of output_items >> keeps flipping between (5, 2, 1048576) and (5, 1, 1048576)? >> >> Code is all at https://github.com/krakenrf/gr-krakensdr if anyone would >> care to take a look. Everything in Python. If anyone has any tips or >> comments please let me know. Thanks to anyone for your insights. >> >> Regards, >> Carl Laufer >> >
