trfp

Muon g-2 field "trfp" Python module for analyzing trolley/fixed probe correlations.

Dependencies

This module requires:

1. numpy

2. scipy

3. pandas

4. Simon Corrodi's gm2 package (for interfacing with root), found here.

Overview

Current as of 24 Sept 2019.

1. Data is read directly from the tier 1 ROOT files using S. Corrodi's gm2 package. This can either be done in real time or ahead of time, saving the data into pandas DataFrames. Import using the root_to_pandas function in analysis_helper.py. This creates an "Interpolation DataFrame."

2. The Interpolation DataFrame is turned into a "Moment DataFrame" using the trolley and fixed probe change of basis matrices. This is in the calc_moment_df function in analysis_helper.py. At this point, blinds can also be applied from the file blinds.txt (see data_run_analysis.ipynb for example).

3. The trolley moment dataframes are processed to remove the trolley image from the fixed probe stations. This is done using trolley_footprint_replacement in helper_function_candidates.py.

4. The baseline sync values for the trolley and fixed probes are calculated using trolley_run_station_average in helper_function_candidates.py.

5. The fixed probe moment dataframes are transformed into virtual trolley measurement dataframes using the sync values and the Jacobian matrices. This is in vtm_calc inanalysis_helper.py.

6. The resulting vtm dataframe can be averaged in any way desired. Simple time-binning and naive azimuthal averaging are demonstrated in 9day_analysis.ipynb.