Comments (6)
Tough call to pick one because they're each wrong in different ways, I think.
Simple isn't visually pleasing but is arguably the least wrong.
Intensity is wrong because it should (I think) peak at the z-score, then fade out to white again. And it doesn't handle z-score overlap, as you've said.
Mixing is arguably the most visually pleasing (especially if you added a fade-in from white and maybe a fade out to white) but will always be wrong in general, because the rate of blending will vary with the data — and will vary between biomarkers within a single model, potentially requiring a colour bar for each biomarker.
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What about something like the intensity colour bar but plotted separately for each z-score? So in this example three colour bars next to each other, labelled above with z=1, z=2 and z=3 and then each colour bar scale labelled as probability from 0 to 1.
As an aside, I was thinking at some point it would be nice to add PVDs for plotting the average z-score progression pattern. They'd take MCMC samples of stage_value from _calculate_likelihood_stage and plot the average z-score at each stage over the MCMC samples.
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Personally think mixing the least wrong of the 3 options but agree with Neil having 0 as white blending up to Z=1 (similar to latex script on BrainPainter)
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I'm not keen on the mixing, I find it much less clear as it implies you're interpreting the value of the trajectory, when it's the uncertainty in the position. I think representing the mixing is less important than representing the uncertainty - the mixing only happens because the PVD is a 2d representation of the MCMC samples - the positions of the z-scores can't actually cross for an individual biomarker.
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How about using the maths of the z-score model to generate the colour bar? (and even the PVD: replace the mixing)
"Something Something Gaussian linear etc. etc."
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I'm keen on that - one PVD for uncertainty in the positions and another for the average trajectory across samples would be a nice solution
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