Adaptive: parallel active learning of mathematical functions.
adaptive is an open-source Python library designed to make adaptive parallel function evaluation simple. With
adaptive you just supply a function with its bounds, and it will be evaluated at the “best” points in parameter space, rather than unnecessarily computing all points on a dense grid.
With just a few lines of code you can evaluate functions on a computing cluster, live-plot the data as it returns, and fine-tune the adaptive sampling algorithm.
adaptive excels on computations where each function evaluation takes at least ≈50ms due to the overhead of picking potentially interesting points.
Start with the 1D function learning tutorial.