given a dataframe with a multilevel index, the line/dot colors should be determined from the outermost index. line thickness of the outermost index should be scaled by a factor of L (number-of-levels).
For each "lower" level in turn, reduce the line thickness by 1 and opacity by some amount (play around with it to see what looks good).
E.g., suppose a dataframe contains the levels timepoints --> trials --> subjects --> experiments.
Each "experiment" should show the average trajectory (or scatterplot) for everything below it, with large/thick and mostly opaque dots/markers, in one color (or colormap) per experiment. Each "subject" should show that subject's average trajectory/scatterplot within that experiment, colored the same as the experiment but smaller/thinner/less opaque. Each trial should show the timecourse across timepoints (in even smaller/thinner/less opaque lines/dots), again colored the same as the subjects/experiments.
The idea is to show a summary of each part of the dataset, but with subtle details added to show (as subtlety increases) more and more low-level detail.
given a dataframe with a multilevel index, the line/dot colors should be determined from the outermost index. line thickness of the outermost index should be scaled by a factor of L (number-of-levels).
For each "lower" level in turn, reduce the line thickness by 1 and opacity by some amount (play around with it to see what looks good).
E.g., suppose a dataframe contains the levels timepoints --> trials --> subjects --> experiments.
Each "experiment" should show the average trajectory (or scatterplot) for everything below it, with large/thick and mostly opaque dots/markers, in one color (or colormap) per experiment. Each "subject" should show that subject's average trajectory/scatterplot within that experiment, colored the same as the experiment but smaller/thinner/less opaque. Each trial should show the timecourse across timepoints (in even smaller/thinner/less opaque lines/dots), again colored the same as the subjects/experiments.
The idea is to show a summary of each part of the dataset, but with subtle details added to show (as subtlety increases) more and more low-level detail.