Summary
ChoppinessIndex is RTTA's streaming implementation of: CHOP range/trend measure based on true range versus high-low range.
Update API
result = rtta.ChoppinessIndex().update(close, high, low)
The update(...) call consumes one observation using close, high, low. advance(...)
uses the same inputs when the caller wants to update state without materializing
a Python return value.
Theory Of Operation
ChoppinessIndex maintains rolling extrema, ranges, or envelopes. The C++ state updates the relevant window/range statistics once per input sample.
Recurrence
Let \(z_t = (close_t, high_t, low_t)\) denote the observation consumed by one
update(...) call and let \(\theta\) denote constructor parameters such as
window lengths, thresholds, and smoothing constants.
The return value is the current scalar indicator value.
Implementation Notes
The recurrence is implemented in src/rtta/indicator.cpp in class ChoppinessIndex.