alt Hacker NewsIf you have tons of datapoints, one cool trick is to do intensity modulation of the graph instead of simple "binary" display. Basically for each pixel you'd count how many datapoints it covers and map that value to color/brightness of that pixel. That way you can visually make out much more detail about the data.
In electronics world this is what "digital phosphor" etc does in oscilloscopes, which started out as just emulating analog scopes. Some examples are visible here https://www.hit.bme.hu/~papay/edu/DSOdisp/gradient.htm
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Great suggestion - density mapping is a really effective technique for overplotted data. Instead of drawing 1M points where most overlap, you're essentially rendering a heatmap of point concentration. WebGPU compute shaders would be perfect for this - bin the points into a grid, count per cell, then render intensity. Could even do it in a single pass. I've been thinking about this for scatter plots especially, where you might have clusters that just look like solid blobs at full zoom-out. A density mode would reveal the structure. Added to the ideas list - thanks for the suggestion!
agreed, heatmaps with logarithmic cell intensity are the way to go for massive datasets in things like 10,000-series line charts and scatter plots. you can generally drill downward from these, as needed.