Preprocessing partial fit
The online form of the data steps
A Pipeline is a host of the online step (ADR 0142), and the data steps before its row owner take the step in the form their class allows. A row-local step folds a block of observations and emits the block its transform gives it, through PortfolioOptimisers.partial_fit_transform: PricesToReturns keeps the last price row it saw, PriceGapFill with a CarriedPrice keeps the carried prices, and MissingDataFilter keeps its missing counts. Each reads its fitted Result out through fit_preprocessing with no data. A window-valued configuration answers PortfolioOptimisers.supports_partial_fit false, and the Pipeline refuses it at warm-up by name.
PortfolioOptimisers.fit_preprocessing — Method
fit_preprocessing(ptr::PricesToReturns)Reads a stepped PricesToReturns out: the conversion is stateless to a reader, so its fitted object is the estimator with the state dropped, exactly what the batch fit returns.
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PortfolioOptimisers.fit_preprocessing — Method
fit_preprocessing(est::PriceGapFill)Reads a stepped PriceGapFill out as the PriceGapFillResult the batch fit over the same rows gives: the assets observed so far, each with its last observed price, and the last timestamp folded as the end of the training window.
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PortfolioOptimisers.fit_preprocessing — Method
fit_preprocessing(mdf::MissingDataFilter)Reads a stepped MissingDataFilter out as the MissingDataFilterResult the batch fit over the same rows gives.
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