1. Developing Animated Scatter Plots
Simon Cleall
PSI conference 2017

2. Why do we…
Collect data over time Present those data as a series of cross sections?

3. Patient-level data

4. Linear Interpolation b0 bn

5. Quadratic Interpolationb0 bn b1

6. Quadratic Interpolationb0 bn b1

7. Quadratic Interpolationb0 bn b1

8. Cubic Interpolation b0 bn b1 b2

9. Cubic Interpolation b0 bn b1 b2

10. Requirements for b1,b2 Objective:
Gradient of b0-b1 line = Gradient of b2-bn line in previous interval b1 b0 bn b2

11. Requirements for b1,b2 b1 b0 bn b2 Subjective:
Distance b1:b0 and b2:bn drives “curviness”

12. Implementation: interpolation
Create Bezier splines (vs time) for each patient
Map interpolated points to equally spaced time values.
Step 1 gives equally spaced points in terms of λ not equally spaced on the time axis
For Each Measure:

13. Implementation: plots
Subset data to include just “day x” data
Create scatter plot
save with desired properties
Trade-off resolution, image dimensions and file-size
For Each Timepoint:
Attributes consistent across plots

14. Implementation: animating
System call of ffmpeg