Opal

Opal converts one or more chronologically ordered numeric signals into the online monitor features used by the OPAL preparation pipeline. Be aware that this code expects you to submit data case wise. Thus no monitor reset would be performed if multiple cases are in the submitted series.

Installation

Install the local project with:

python -m pip install ./library

The same directory can be built into wheel and source distributions with:

python -m build library

Usage

Pass a pandas.Series directly:

from opal import monitor_features

features = monitor_features(frame["hr"])

Or select one or more columns from a dataframe:

features = monitor_features(frame, "hr")

features = monitor_features(
    frame,
    ["hr", "quot"],
)

For each selected signal using the default monitors the result contains these five columns, in this order:

• <signal>_angle
• <signal>_slope
• <signal>_angle_20
• <signal>_gauss_20
• <signal>_gauss_100 Signal prefixes and feature names are lower-case. Other monitors cann be supplied as monitor_supplier parameter. A path-like signal name such as Solar8000/HR becomes hr. The returned frame retains the corresponding input index; the input is not modified.

If a dataframe contains exactly one column, its selector can be omitted. A selector is required for wider dataframes so timestamp, identifier, or target columns are not monitored accidentally.