We are trying to download a specific performance metric across all of the mice who went through a specific experiment type, say
OPHYS_1_images_A. The jupyter notebooks provided with the AllenSDK are very helpful but the only way we can see how to do the above is through using get_behavior_ophys_experiment(experiment_id) where expirement_id will range over all the experiments of interest. The problem with this approach is that it is very data intensive, so we were wondering if there is a better way to get population-level data in an efficient way. I am sorry if I wasn’t very clear as this is my first time working with such an extensive dataset.
Unfortunately, the entire NWB file for an experiment needs to be downloaded in order to access any given attribute of that experiment. So if you want to access behavior data for a given subset of experiments, you’ll need to iteratively download the NWB files for those experiments and extract the metric of interest for each.
Thank you very much @DougOllerenshaw !
I will try to see if I can use some cloud service in order to do that.
That sounds like a good approach. If you find an efficient way to accomplish your specific goal, it’d probably be useful to post here as I’m sure others will face similar challenges.
I will make sure to do so