The terrible irony of this post is that they use a completely wrong definition of expected value. They write down an integral...but then implement something totally different.

You cannot calculate the EV of a random variable X by taking the mean of random samples drawn from the distribution of X (e.g. try it with the Cauchy distribution—see if you get something approaching the actual EV). The only thing they accomplished is building up a very convoluted way of calculating a sample mean—which is already trivial with Numpy or just standard Python. Why do this? I’m perplexed.

This is the issue with software engineers writing scientific code—they often flagrantly misunderstand basic mathematical definitions, and then obfuscate this misunderstanding with their “pure” and “robust” code.

Sorry for the harsh criticism, but I’m tired of seeing this kind of thing.