In theory they should be useful when know that the underlying process should be monotone. I think in the past I found them more sensitive to noise and wondered if monotone approximation might not be better than monotone interpolation for that reason.
I added class comments to each class which explain the high level implementation details. Clamping is supported with natural cubic splines, and this is done by taking the slopes at each endpoint.
Monotonicity is currently not supported (for cubic splines).
Interesting. Isn’t there a selection bias on the level of which pictures, of which restaurant, of which food by what type of people are actually taken and shared… I think this might skew what we see, away from an unbiased random selection of food impressions from the entire menu from each of all the (web-listed) restaurants, even with a perfect random selection of available images?
