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Adding computation and plotting of trial by trial metrics #26
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@hanhou @rachelstephlee @nkeesey @ZhixiaoSu This is ready for review. I'd like to merge it in quickly. It would be good to agree on names for metrics |
MIN_EVENTS = 2 | ||
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def compute_all_trial_metrics(nwb): |
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I have more trial-based metrics here that can be migrated to this function.
Most of my metrics are not binary variables, so they may not need smoothing.
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Tracking them in this issue: #27
Now the trial metrics are plotted in time-based plot. Do you think it makes sense to also add trial metrics to the trial-based session plot as well? Also, it would be great to have a plotly version of all these plots, esp time-based plots with FIP. Then it will be very easy to visualize in Streamlit or Jupyter notebook |
I'll go ahead and approve this for now. |
Tracking them in this consolidated issue: #27 |
Yes, made a separate issue here: #28 |
Updated plot_session_scroller to plot metrics
Trial by trial metrics:
Future work:
DEMO
Another example with baiting and generative reward probabilities