Imagine the data points sorted in numerical order by the size of their absolute values. So if data is clipped at the percentile, then up to one percent of the data can be infinitely strong noise. So I often clip at thrice the percentile. To find the quantile, it is not necessary to fully sort the data. That would be slow.
Different plots have different purposes.
After all, human perceptions are generally logarithmic. In our lab we generally use power laws. I find that replacing data points by their signed square roots generally compresses all signals into a visible range. When plotting field profiles with a very close trace spacing, it may be better to use the signed cube roots. Most of the data plots in this book use , t 2 gain, and clip at the percentile.