Finding magnetic discontinuities
It can be divided into two parts:
- Finding the discontinuities, see this notebook
Corresponding to limited feature extraction / anomaly detection
Output should contain the following:
- “tstart” and “tstop” of the event
- Calculating the properties of the discontinuities, see this notebook
- One can use higher time resolution data
Processing the whole dataset
Notes that the candidates only require a small portion of the data so we can compress the data to speed up the processing.
ids_finder
ids_finder (detection_df:polars.lazyframe.frame.LazyFrame, bcols=None, detect_func:Callable[...,polars.lazyframe.frame.LazyFrame]=<f unction detect_variance>, detect_kwargs:dict={}, extract_df:polars.lazyframe.frame.LazyFrame=None, **kwargs)
Type | Default | Details | |
---|---|---|---|
detection_df | LazyFrame | data used for anomaly dectection (typically low cadence data) | |
bcols | NoneType | None | |
detect_func | Callable | detect_variance | |
detect_kwargs | dict | {} | |
extract_df | LazyFrame | None | data used for feature extraction (typically high cadence data), |
kwargs |