Transform
2 nodes — Signal normalisation and range remapping
Transform nodes remap the full input array to a target numeric range in a single pass. They operate on the entire series rather than a rolling window, making them the natural last step before combining or displaying indicators.
Normalize vs Scale: Use Normalize when you want the output range to always span exactly [targetMin, targetMax] based on actual data extremes. Use Scale when you know the theoretical bounds of the input upfront and want a deterministic mapping regardless of current data.
Normalize
Rescales the entire array to [targetMin, targetMax] using the series' own min and max. Ideal for multi-indicator scoring and ML feature preparation.
Full-seriesScale
Linear mapping from a known input range to a desired output range. Use when theoretical bounds are fixed (e.g., RSI 0–100 → −1 to +1).
Full-series