Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

add Time Course feature #21

Open
john-judge opened this issue Aug 29, 2021 · 4 comments
Open

add Time Course feature #21

john-judge opened this issue Aug 29, 2021 · 4 comments
Assignees
Labels
enhancement New feature or request

Comments

@john-judge
Copy link
Owner

john-judge commented Aug 29, 2021

Feature

Time Course will be a right-hand column full tab that plots aggregated data over multiple files.

Layout: A plot viewer above controls. The plot x-axis is record #. Controls includes a listing of all .npy files in the current save directory; each can be selected or deselected. When selected, a file's aggregated data is plotted as a point in the plot.

Each slice's set of points in the plot is plotted with a different color. Each location in each slice group has a different line style. A legend is included.

The possible aggregations include: MaxAmp/SD, MaxAmp, Latency, RLI, MeanAmp/SD, MeanAmp. Aggregations are performed over the selected measure window and always over all trials for each record.

Each time course is pixel or region specific.

Implementation

This feature could just use the existing TraceViewer like current PhotoZ does? Or we can just inherit from TraceViewer and borrow a lot of features, but base the plots on TimeCourse objects rather than Trace objects.

@john-judge john-judge added the enhancement New feature or request label Aug 29, 2021
@john-judge john-judge self-assigned this Aug 29, 2021
@john-judge
Copy link
Owner Author

@ksscheuer I'm hoping to improve over PhotoZ's current Time Course, which just overlays the measured value for each file in the Trace Window (which is a bit non-intuitive with the lack of x-axis labeling). Any thoughts?

Keeping in mind the first use will probably be LTP experiments -- interested in whether pattern separation can be observed in mossy cells in DG, especially given the context of Yihe's latest paper on MC-MC synapses.

@ksscheuer
Copy link
Collaborator

Oh god, I'm so sorry for the late reply. I've been willfully ignoring email for the last week trying to do analysis. I actually don't mind the current way time course is set up, but maybe that's just because Meyer first showed it to me and explained it at the same time (rather than leaving me to figure it out on my own). Can you expand on how the lack of x-axis labelling might be confusing? If I remember correctly, time course essentially gives you a graph more or less like the one below (except that it would only contain red points or only contain blue points, not both at once) without the labels for time on the x-axis. Is that right?
image

@john-judge
Copy link
Owner Author

john-judge commented Sep 6, 2021 via email

@ksscheuer
Copy link
Collaborator

I didn't realize that the x-axis switched between msec and sec. That's not great. Your proof-of-concept is more intuitive. Clearly showing (and allowing more choice over) the specific files displayed is also a nice improvement.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

2 participants