Closed rolyp closed 8 months ago
Some initial notes on algorithm. Emailed first author for link to repo.
Added notes on couple of the preprocessing steps (that we could either ignore by only considering the output of those steps, or include in order to illustrate something else).
Now we have the repo, I guess one thing to try to answer soon is how much of the BMA algorithm we can likely implement in Fluid (and if the answer is “not much”, what the alternative is).
@JosephBond It might be useful to start enumerating the key components (e.g. scipy.optimize.linear_sum_assignment
) and thinking about what it would be realistic to implement.
Currently, it doesn't seem like there will be any inherent issues with implementing this in Fluid, with the caveat that we may need to introduce a method to draw random numbers in the language. This would be a good first effect to add to Fluid if we need to, as it doesn't in theory add any complications relative to slicing (as we slice against a given execution). I will mark the subtasks we will need in terms of understanding, as well as in terms of implementation here.
IntInfty = Int x | Infinity
Dropped for now (see #756).
Used in climate model evaluation. Potentially interesting because it (non-monotonically) aligns data points from different time series, and so could be a good example for linked inputs. Could contrast with other “monotonic” approaches such as Dynamic Time Warping.
See the paper.
Details of the algorithm
Thoughts on what we might be able to actually show