adaptive VS Prophet

Imagine you have a drawing with lots of hills and valleys, and you want to understand the shape of the landscape. Instead of measuring the height at every single point, Adaptive helps you measure the height at the most important points. It focuses on areas where the hills and valleys change a lot, so you can understand the drawing with fewer measurements.

Yes! Check it out at https://github.com/python-adaptive/adaptive/

Explore and star ⭐️ the repo on github.com/python-adaptive/adaptive, and check out the documentation at adaptive.readthedocs.io.

Also, Quatro will require a YAML annotation at the top of the file that will always be visible, e.g., a notebook on GitHub: https://github.com/python-adaptive/adaptive/blob/main/docs/source/tutorial/tutorial.DataSaver.md

Getting Python to calculate the equation for you shouldn't be a problem. The problem is that it may be having trouble figuring out which points to sample from. Using a uniformly spaced set of points won't necessarily result in the best looking curve, especially after interpolation. There is the adaptive package which does smart sampling of expensive functions. The idea is you give the function, and the adaptive library will learn the best x values to use and also return f(x).

https://facebook.github.io/prophet/

"Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well."