normalize_for_radar

rubin_sim.maf.run_comparison.normalize_for_radar(summary, norm_run='baseline', invert_cols=None, reverse_cols=None, mag_cols=[])

Normalize values in a dataframe to a given run, return output in a dataframe.

This provides a similar functionality as the normalize_metric_summaries method, and returns a similar dataframe. The options for specifying which columns to invert, reverse, or identify as ‘magnitudes’ are slightly different, instead of using a ‘metric_set’.

Parameters:

summarypandas.DataFrame

The data frame containing the metric summary stats to normalize (such as from get_metric_summaries). Note that this should contain only the runs and metrics to be normalized – e.g. summary.loc[[list of runs], [list of metrics]] summary should be indexed by the run name.

norm_runstr

The name of the run to use to define the normalization.

invert_colslist of str

A list of column names that should be inverted (e.g., columns that are uncertainties and are better with a smaller value)

reverse_colslist of str

Columns to reverse (e.g., magnitudes)

mag_colslist of str

Columns that are in magnitudes