allen dataset: Create colab example with Allen demo dataset.

[abdelrahman725]

Description

Create a google colab notebook to show case the whole pipline of downloading, exporting, and interpolating allen dataset.

Follow up

Are there any visualizations you want in the notebook ? If yes, please explain why they are needed, this helps me learn really quickly while building !

Closes #102

[gitnotebooks]

Found 1 changed notebook. Review the changes at https://app.gitnotebooks.com/sensorium-competition/experanto/pull/139

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.

📢 Thoughts on this report? Let us know!

[Copilot]

Pull request overview

Adds a new Colab-oriented example notebook demonstrating how to export an Allen dataset via allen-exporter and then use Experanto to load and interpolate multiple modalities.

Changes:

• Added examples/allen_example.ipynb with Micromamba-based setup for allensdk compatibility in Colab.
• Added walkthrough code to export an Allen experiment, load it with experanto.Experiment, and run interpolation for all devices or a single device.

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[abdelrahman725]

Updates

Addressed only the relevant Copilot comments

[schewskone]

Thanks a lot for the PR, the colab setup and environment instantiation look good.
Please address the comments to make the example even more intuitive

[pollytur]

@abdelrahman725 please merge current main in your branch :)
The recent changes from @schewskone might also help with the issue you have seen before

[abdelrahman725]

Updates

Addressed review comments.

I decided to leave eye_tracker and treadmill visualization, because I wanted first to make sure that the current visualizations are what's intended.

[pollytur]

@abdelrahman725 please take a look on why the tests are failing. It's a bit suspicious cause adding a notebook should not change the tests but they were fine before. Maybe merging current main in there would be enough to solve.

Also please re-request review from me and Tom, when the PR is ready for another review

[pollytur]

@abdelrahman725 we found the issue with the tests - its now fixed
Please merge current main in your branch - then tests should be fine and not fail anymore
Sorry about it

[pollytur]

@abdelrahman725 At the end of the notebook in sections Eye tracker Interpolation and Treadmill Interpolation there are still TODOs - could this please be addressed? do you need our input to address it somehow?

[abdelrahman725]

@pollytur
I should proceed with the right visualizations for eye_tracker and treadmill after your review and an explanation for this:

please print shapes only and use plots for the rest

[abdelrahman725]

@abdelrahman725 At the end of the notebook in sections Eye tracker Interpolation and Treadmill Interpolation there are still TODOs - could this please be addressed? do you need our input to address it somehow?

Yes, as I mentioned above, I'm not sure what "please print shapes only and use plots for the rest" means and for which devices ?

[pollytur]

@abdelrahman725 At the end of the notebook in sections Eye tracker Interpolation and Treadmill Interpolation there are still TODOs - could this please be addressed? do you need our input to address it somehow?

Yes, as I mentioned above, I'm not sure what "please print shapes only and use plots for the rest" means and for which devices ?

It means that Its nice to have plots of Eye tracker / Treadmill channels activity over time same as you have it above for neurons
At some point it had a bunch of numbers displayed in the cell output - which is not great, hence, I asked to print shapes only
Does it make sense now?

[pollytur]

@abdelrahman725 like also here
its a bunch of numbers which make the output huge but not very meaningful.
Would be much better to print some shapes and maybe states / bynber of nans instead of displaying million of numbers
Or am I missing sth?

[pollytur]

for printing both neurons activity and behaviour activities please use '-o' setting (e.g. ax.plot(times, responses[:, neuron_idx], '-o', linewidth=0.8, color='steelblue')) - this would help to see where the actual points are (not so easy with just a solid line)

[pollytur]

@schewskone you downloaded the Visual Coding 2P Allen dataset right? https://allenswdb.github.io/physiology/ophys/visual-coding/vc2p-background.html

There was no water licking or behaviour in there or was it?

@abdelrahman725 wait for @schewskone reply but I think the explanation you give at the top is for the wrong dataset (e.g. Visual behaviour while it should be Visual Coding one)

[pollytur]

in the first markdown there is

Cheat sheet
See this helpful [cheat sheet](https://github.com/trendinafrica/TReND-CaMinA/blob/main/notebooks/Zambia25/07-to-10-Mon-toThu-AllenTutorial/Visual%20Coding%202P%20Cheat%20Sheet%20October2018.pdf) from CAMINA school

Cheat sheet for what? Give 1 sentence context what would they found there

Also add brief explanations in most of the markdown sections

• for example Download and export Allen dataset - what is the difference between download and export?
• Load experiment - what happens there (e.g. data was downloaded in this folder and we are now loading it with the help of experanto) - yes, I know its trivial from a coding perspective but the goal of example notebooks is to extremely clear and self-explanatory
• would be nice to have a comment on tiers split and what do these id mean here

[abdelrahman725]

@abdelrahman725 like also here
its a bunch of numbers which make the output huge but not very meaningful.
Would be much better to print some shapes and maybe states / bynber of nans instead of displaying million of numbers
Or am I missing sth?

@pollytur I agree, I can print the shapes in "Interplate from all devices" cell and maybe other minimal states , but I prefer to include other details like nans into each correpsonding modality cell below and before plotting.

[pollytur]

@abdelrahman725 like also here
its a bunch of numbers which make the output huge but not very meaningful.
Would be much better to print some shapes and maybe states / number of nans instead of displaying million of numbers
Or am I missing sth?

@pollytur I agree, I can print the shapes in "Interplate from all devices" cell and maybe other minimal states , but I prefer to include other details like nans into each correpsonding modality cell below and before plotting.

Sure, you are welcome to plot some details as suggested above. But this should be minimal meaningful prints instead of plain display of array parts

[schewskone]

Visual Behavior is the correct dataset not Visual Coding I'm not entirely sure about the difference but I followed the tutorials from here, which is for the Visual Behavior dataset.

[abdelrahman725]

Updates

• Addressed all review comments including Todos.
• Removed the cheat sheet pdf (see below)
• Each md section and code cell is updated and has clear and detailed explanation.

Thoughts

@pollytur, @schewskone

1. I believe the correct experiment is Visual behaviour and not Visual coding. That linked pdf cheat sheet is for Visual coding, so I decided to remove it.

2. About lick times and reward times: The visual behaviour experiment indeed mentions these in doc. However, I believe "lick times" and "reward" times were just ignored by allen-exporter during export ? that's why I can't see them in the exported and loaded experiment directory (allen_data/experiment_951980471). I mentiond this in the notebook.

3. Is there any additional eye_tracker signal worth plotting in addition to the already plotted ones pupil_area, eye_area, pupil_center_x, pupil_center_y and likely_blink ?