We have an image analysis pipeline at work and one part of it involves peak detection. The peak detection algorithm we were using worked for normal data. One da

We have an image analysis pipeline at work and one part of it involves peak detection. The peak detection algorithm we were using worked for normal data. One day a scientist came to me with data that was abnormal in that it had peaks with a high dynamic range, which failed given the current algorithm. I thought about it a bit and was able to come up with a non-parametric test of randomness that detected whether a sequence of data was probably random or structured and it was able to detect not only the usual, large peaks but also those that were very small. The reason I was really please with the result is that it was a case of applying a little thought to the problem, getting a nice probabilistic theory in place, and the resulting code was so straight forward and performant that it looked like a simplistic hack!