Start of a sliding-window feedback loop for iteratively generating time-series rows. Together with
the TimeDelay Loop End node it builds autoregressive workflows in which each new row is computed
from the previous N time steps — typical use cases are multi-step forecasting and synthetic
time-series generation (e.g. recursively producing a Fibonacci sequence from a two-row seed).
The seed table at the input port must contain at least N rows, where N is the
configured size of the time set. On the first iteration the node emits a single wide row holding the last
N rows of the seed table side by side: every input column c is unrolled into N
lagged columns c(t - N-1), c(t - N-2), ... , c(t - 0), ordered from oldest to newest.
The body of the loop is expected to compute the next time step from these lagged features and pass it
through the TimeDelay Loop End node, which records the new row in the loop's accumulated output and feeds it
back to this node. On the next iteration the window slides forward by one step — the oldest time
step is dropped and the just-generated row becomes the new t = 0. The loop runs for the configured
number of iterations, producing that many generated rows in total.
c is unrolled into
N lagged columns c(t - k) for k = N-1 , ... , 0, ordered from oldest to
newest. On the first iteration these cells come from the last N rows of the seed table; on
later iterations the window has slid forward by one step, with the oldest time step dropped and the row
produced by the loop body in the previous iteration appended as the new t = 0.You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.
To use this node in KNIME, install the extension KNIME Data Generation from the below update site following our NodePit Product and Node Installation Guide:
A zipped version of the software site can be downloaded here.
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