discontinuitypy

standardize_plasma_data

 standardize_plasma_data (data:polars.lazyframe.frame.LazyFrame,
                          meta:space_analysis.ds.meta.PlasmaMeta)

*Standardize plasma data columns across different datasets.

Notes: meta will be updated with the new column names*

source

IDsConfig

 IDsConfig (name:str=None, mag_data:polars.lazyframe.frame.LazyFrame=None,
            ts:datetime.timedelta=None, tau:datetime.timedelta=None,
            events:polars.dataframe.frame.DataFrame=None,
            method:Literal['fit','derivative']='fit',
            mag_meta:space_analysis.ds.meta.Meta=Meta(dataset=None,
            parameters=None), bcols:list[str]=None,
            plasma_data:polars.lazyframe.frame.LazyFrame=None, plasma_meta
            :space_analysis.ds.meta.PlasmaMeta=PlasmaMeta(dataset=None,
            parameters=None, density_col=None, velocity_cols=None,
            speed_col=None, temperature_col=None),
            ion_temp_data:polars.lazyframe.frame.LazyFrame=None, ion_temp_
            meta:space_analysis.ds.meta.TempMeta=TempMeta(dataset=None,
            parameters=None, para_col=None, perp_cols=None),
            e_temp_data:polars.lazyframe.frame.LazyFrame=None, e_temp_meta
            :space_analysis.ds.meta.TempMeta=TempMeta(dataset=None,
            parameters=None, para_col=None, perp_cols=None),
            timerange:list[datetime.datetime]=None, split:int=1,
            fmt:str='arrow', **extra_data:Any)

*Extend the IDsDataset class to provide additional functionalities:

Export and load data
Standardize data
Split data to handle large datasets*

source

SpeasyIDsConfig

 SpeasyIDsConfig (name:str=None,
                  mag_data:polars.lazyframe.frame.LazyFrame=None,
                  ts:datetime.timedelta=None, tau:datetime.timedelta=None,
                  events:polars.dataframe.frame.DataFrame=None,
                  method:Literal['fit','derivative']='fit',
                  mag_meta:space_analysis.ds.meta.Meta=Meta(dataset=None,
                  parameters=None), bcols:list[str]=None,
                  plasma_data:polars.lazyframe.frame.LazyFrame=None, plasm
                  a_meta:space_analysis.ds.meta.PlasmaMeta=PlasmaMeta(data
                  set=None, parameters=None, density_col=None,
                  velocity_cols=None, speed_col=None,
                  temperature_col=None),
                  ion_temp_data:polars.lazyframe.frame.LazyFrame=None, ion
                  _temp_meta:space_analysis.ds.meta.TempMeta=TempMeta(data
                  set=None, parameters=None, para_col=None,
                  perp_cols=None),
                  e_temp_data:polars.lazyframe.frame.LazyFrame=None, e_tem
                  p_meta:space_analysis.ds.meta.TempMeta=TempMeta(dataset=
                  None, parameters=None, para_col=None, perp_cols=None),
                  timerange:list[datetime.datetime]=None, split:int=1,
                  fmt:str='arrow', provider:str='cda', **extra_data:Any)

Based on speasy Variables to get the data