Comments (5)
with the new Makie update, https://discourse.julialang.org/t/ann-makie-update-figures-and-integrated-layouts/52800, it's probably easier to do this now! Though maybe we should wait a bit first for the bugs to get worked out. (maybe @SimonDanisch can help us when the time comes too 😄).
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Closed as of #29!
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Can you slightly raise priority level for this? @SimonDanisch @hannahilea What needs to be converted? If it's a single (relatively isolated) function to plot I can try my hand.
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I think it's these functions:
Lines 228 to 428 in 66cbc09
The plotting is already fairly nicely separated from getting the data to plot, so I think it shouldn't be tooo hard. I think we also shouldn't try to always translate 1-1 between Plots and AbstractPlotting, but rather just try to make each subplot plot the thing it is supposed to do on its own (which might be easier than trying to get it exactly the same).
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I started to port a few recipes over to BeaconPlots: https://github.com/beacon-biosignals/BeaconPlots.jl/pull/34/.
Not sure if we want to leave them there going forward, but it makes things easier for me right now.
Should be easy to move if we want them somewhere else :)
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Related Issues (20)
- In `EvaluationRow`, use `Matrix{Int64}` instead of `Array{Int64}`
- Update doc examples to use meaningful test data
- Add "abstract" logging interface
- Remove LearnLogger? HOT 3
- Update `log_evaluation_row!` to not special case Spearman correlation coefficient HOT 3
- Add `log_confusion_matrix` to logging interface
- The great `evaluation_metrics_row` refactor! HOT 1
- Path to `EvaluationRow` deprecation
- Support custom soft label hardening in `TradeoffMetricsRow` calculations
- `evaluation_metrics_plot` fails when IRA fields are in the input `EvaluationRow` for multiclass result HOT 3
- RFC: Remove training harness wrappers (`learn!`, `evaluate!`) from Lighthouse.jl? HOT 3
- `plot_confusion_matrix` cannot change `annotation_text_size` HOT 8
- Docs should mention that a Makie backend needs to be loaded
- Update confusion matrix to give both counts and normalized values in one figure HOT 2
- upgrade to Legolas 0.5
- Compute AUC without needing specific thresholds HOT 1
- `binary_statistics` reports sensitivies as 1 instead of NaN when no actual positives HOT 1
- `true_negatives` in `binary_statistics()` is incorrect
- Package is unsupported on Apple Silicon (M1/M2 chips) HOT 2
- compute cohen's kappa from confusion matrix
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