Add indicator for |bias| > 0.7

[alexpiet]

Steps:

• Calculate bias online (@hanhou has a definition)
• Check for bias outside of a tolerance range at the start of each trial
• Alert the user through either a pop-up, mark on the trial graph, or a text warning (seek RA feedback here)
  • remove the matching plot
  • Moving the legends to the space where the matching plot is now
  • design some indicator for side bias
  • Can then remove the "hide legend" button

[alexpiet]

@hanhou Can you provide @micahwoodard a definition of how to compute bias online?

[alexpiet]

These two issues might be redundant: I think this issue is one method for computing bias: https://github.com/AllenNeuralDynamics/aind-behavior-blog/issues/314

I think the resolution of this issue is to compute bias, and remove the matching plot: https://github.com/AllenNeuralDynamics/aind-behavior-blog/issues/313

[hanhou]

As discussed here, we think we can try two biases, naive bias and logistic regression bias (and remove the old matching bias). But if we choose only one, I would prefer the logistic regression bias, for reasons mentioned earlier in that thread.

• Code for naive bias: https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-basic/blob/5bd0db90bf9182a969bcb3c52af77c8bb9a36f19/code/process_nwbs.py#L317

• Code for logistic regression bias: follow this and this.

@micahwoodard

[micahwoodard]

@alexpiet @hanhou the issue says calculate bias online. Are there instances of online calculations elsewhere in the repo or other places? I have not done that before so example code or direction would be helpful

[alexpiet]

@micahwoodard By "online" we mean after each trial in the GUI as opposed to calculating the bias "offline" after the session is over. So you will just use a normal function in the code repo that executes either in the main thread, or in a separate thread if its slow.

[micahwoodard]

Ohhhhhh okay thank you for that clarification

[micahwoodard]

@alexpiet @hanhou Do you want me to import the logistic regression bias functions in the aind-foraging-behavior-bonsai or just implement the functionality within the foraging repo? I see the the logistic regression function linked takes a nwb file as an argument, and I see that there is a TrasferToNWB py file within the foraging repo, but I'm not seeing where a nwb file is generated or used. Is the idea to generate a nwb based on the GenerateTrials class and then feed that into the logistic regression bias function?

[alexpiet]

@micahwoodard We want to implement the functionality into the task repo.

TransfertoNWB.py is going to be removed soon.

[micahwoodard]

Okay that makes sense. In the logistic regression bias function, it seems like it cycles through different models from different papers found here. Are we going with a particular model?

[alexpiet]

I defer to @hanhou on this topic

[hanhou]

Let's use Su2022. See this comparison: https://github.com/AllenNeuralDynamics/aind-dynamic-foraging-models?tab=readme-ov-file#comparison

[micahwoodard]

@hanhou Do you have an idea what values we should use for the logistic regression function? Right now I am just using all the defaults, but would love input on values to use.

[hanhou]

I haven't systematically explored the parameters but I think the default values should be fine.