Assumption of sorting data for sklearn agents is too strong.

[maffettone]

Decomposition general preforms stronger and appears more intuitive if the data is sorted. The current assumptions for DecompositionAgentBase and [for ClusterAgentBase] will also only work for 1-d independent data.

Expected Behavior

• Work for n-d independent vars
• Potentially don't sort for clustering?

Current Behavior

Sorting higher dims causes value errors.

Possible Solution

partial solution for 2D that needs extension:

try:
    sorted_independents, sorted_observables = zip(
        *sorted(zip(self.independent_cache, self.observable_cache))
    )
except ValueError:
    # Multidimensional case
    sorted_independents, sorted_observables = zip(
        *sorted(zip(self.independent_cache, self.observable_cache), key=lambda x: (x[0][0], x[0][1]))
    )