Sample rates question

[davepruitt]

I'm not sure what the best place to ask this, or who the best person to ask is. I am posting this here because my question is specific to the ZMQ Interface plug-in within Open Ephys, so this seems like the best place.

Anyway, here is my question:

I am currently writing a Python app that is going to control some of our experiments. The Python app is streaming some EMG data from OpenEphys using the ZMQ Interface plug-in. As of right now the application itself is still very simple, so there's not a lot going on - it's literally just streaming data and plotting it.

Within the OpenEphys GUI, my "signal chain" is quite simple. I am not even streaming data from a real device. I am just using the example data that is provided with the application. So, I open the example data data, and then I send the data over to my Python application via the ZMQ Interface plug-in. Here is the signal chain:

The example data claims it is sampled at 40 kHz. Thus, I would expect that my Python application would receive 40,000 samples per second. However, this is not the case. Typically, I seem to be received 2 messages via the ZMQ Interface per second, and each message contains 853 samples, so a total of 1706 samples per second.

Importantly, I am only reading from Channel 1 on the Python side. Actually, my code is pretty much taken directly from the example Python code on this repository. In fact, if I just run the actual example application on this repository it seems to also be streaming data at that same rate - 1706 samples per second.

So... I'm trying to understand what is going on here? Is there some configuration that I need to do so that the number of samples that I receive per second matches the actual sample rate of the data?

If I can't match the sample rate of the data, then how do I know which samples I am receiving via the ZMQ Interface? For all I know it could be sending me a batch of samples that are not "live" because it's not "keeping up" with the "live" data.

Any help would be appreciated. Thank you!