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At the moment hctsa uses the system rng without controlling seeds, thus making impossible to control the output of stochastic operators. Ben would take care of this at some point in matlab land.
In in python land we will need to generate the bindings to stochastic operators to accept a rng seed and write a common unit test to catch non-determinism. @benfulcher can I assume that all the stochastic features are tagged as "stochastic"?
The text was updated successfully, but these errors were encountered:
Yeah I ran a test over all operations (running each I think 50 times) for a handful of test time series to produce a basic labeling of all operations as "stochastic" or not. It's not an easy process, because sometimes the stochasticity depends on the length of a time series (e.g., long timeseries are subsampled randomly), and sometimes the randomness comes at the level of rounding errors, or could potentially depend on the platform or version of Matlab. I will try to resolve this issue "in Matlab land" by the year's end.
At the moment hctsa uses the system rng without controlling seeds, thus making impossible to control the output of stochastic operators. Ben would take care of this at some point in matlab land.
In in python land we will need to generate the bindings to stochastic operators to accept a rng seed and write a common unit test to catch non-determinism. @benfulcher can I assume that all the stochastic features are tagged as "stochastic"?
The text was updated successfully, but these errors were encountered: