Hi @user-77aaeb! Yes. All Neon models can record pupil diameter. You can read more about the measurements here and how to extract them here

Hi @user-f89b02 , just to clarify, did you mean "what is the recommended way" or "why is the recommended way"?

And, recording.start_time is relative to when the recording started, so the moment that the white button is pushed (or the moment that the device.recording_start() command is received by the device). The sensors always need to warm up and start a bit later, after recording start.

Hi @user-451948. Yes, it's possible to buy just a module and Companion device, and also to return the frame if that's what you want. With that said, I assume the faulty module you're referring to is the one we discussed in the troubleshooting ticket? Because we haven't yet diagnosed whether the fault lies with the module or the bare metal nest. If it's the nest, e.g. a loose connection, then you might not need a new module.

Since you mention you have a new frame, it would be worth putting your module into it. If it everything works as expected, then it's just your bare metal nest which is broken. If the problem follows the module, then we know the module will need fixing.

Hi @user-13d297! Could you expand a bit on what you mean by no fixations being mapped? For example, is this about mapping fixations to AOIs via an enrichment, such as Reference Image Mapper? Or something else?

Hi @user-9a1aed , pl-neon-recording has a fixations stream that already contains the data you are looking for. You can simply sample the fixations data at the same timestamps as those 200 gaze points, similar to here.

May I ask if there is a reason to not upgrade to the latest version of pl-neon-recording?

Ok, in that case, it depends on how exactly you want to match the timestamps. You could try using np.searchsorted from numpy and then check if the matched timestamps are close enough for your purposes. You could also just find the timestamp with smallest difference from the target timestamp with something like np.min(np.abs(events.start_time - target_time)).

Alternatively, you can adapt the match_ts function for version 1.0.3.

Hi @user-e544ee , after loading the recording into Neon Player, you then need to export it, by either pressing the E key or clicking the button that looks like a download symbol. Make sure also that the World Video Exporter is enabled. To clarify, the .npy files are an intermediate format that are not meant for typical usage. If that does not resolve it, then just let us know.

Hi @user-3c26e4 , thanks; wishing the same to you.

While you can share select recordings from a Workspace (right click and choose Share recording), it is not possible to do either of the following:

• Restrict a member of a Workspace to seeing only some recordings
• Nor, give a Workspace member a Viewer role for some recordings and an Editor role for others.

If you would like to see either of these features added, be sure to add them to the 💡 features-requests list.

Hi @user-3d4b81 👋. We generally recommend our Python client as a starting point because it has the most extensive documentation and examples. It is our most widely used entry point for developers. That said, the C++ client is a valid option, but less widely used and discussed. Architecturally, both the Python and C++ clients abstract the API protocols (see under-the-hood). So you can choose the client that best fits your existing stack.

Hi @user-7413e1 , it seems that this Enrichment was potentially already started? Could you click the red Cancel button and then do the following:

• Go back to the Enrichments tab.
• Hard refresh the browser tab -> Ctrl+Shift+R on Windows and Linux; Cmd+Shift+R in Chrome on MacOS

Then, either try to re-start that Enrichment or create a new one. Let us know how it goes.

Hi @user-3c26e4 , thanks. My colleague, @user-cdcab0 , is responsible for handling this feedback. Perhaps sharing a screen recording could help determine what is going on?

Hi @user-72e42a , if you want to work within the free 2 hour recording quota, then you do not need an Unlimited Plan. If you simply want to access the data that is currently there, you can analyze & download the 2 hours worth of data, then delete those, and work with the next 2 hour chunk. Just note that deleting recordings on Pupil Cloud will permanently remove them from Pupil Cloud, so be sure to make local backups if you go with this approach.

If you rather want to obtain an Unlimited Plan, it is not exactly a subscription. You obtain a Plan in yearly units and decide in advance, when it should start & end.

And, yes, academic discount is available for Unlimited Plans.

Whichever method is most ideal for your situation.

Could you clarify what you mean though by "the files are corrupted when we analyze"?

If you use the Unlimited Plan calculator, it will show you the academic discount at the bottom left, as it depends on how many devices and years you wish to include in your Plan.

Hi @user-13078d , may I first briefly ask why you are using LSL for real-time streaming? That is not really its principal design focus.

Hi @user-7413e1 , is it the naming of the events or the timestamps that are discrepant? Do I understand correctly that you also confirmed the discrepancy against the original code that sent the Events?

Hi @user-ffc425 👋 ! Could you clarify a bit more what you’re running exactly? Which code are you using, and how are you opening or rendering the video?

A few things that might explain what you’re seeing:

• Color change (red ↔ blue):
  If you’re using OpenCV, note that it works in BGR color order by default, not RGB. So a red overlay drawn in RGB can appear blue if the image isn’t converted first or your brown table look blueish. You’d typically want to convert with something like cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) before visualising.

• Red vs numbered circles:
  The red circle is usually the gaze point, while the numbered circles typically indicate the fixation scanpath, which usually appears when you’re using video renderer (exported in Cloud) rather than the raw scene camera video.

• Timing / alignment issues:
  If you downloaded a rendered video from Cloud, it may not have the same length as the raw scene video (see gray frames explanation here https://discord.com/channels/285728493612957698/1047111711230009405/1364251433612087416) . That could explain the misalignment you’re seeing.

If you can share whether you’re using the raw scene video, a Cloud-rendered video, or your own rendering code, we can narrow this down further.