pidp_tools.pid module¶
This module contains a collection of PID functions.
- pidp_tools.pid.DIRC(particle_df)[source]¶
Identifies particles based on their likelihood values produced by the GlueX Detection of Internally Reflected Cherenkov Radiation (DIRC) detector.
Parameters¶
- particle_df :
pandas.DataFrame
A dataframe containing particles to be identified. The supplied dataframe must have the following columns: “px”,”py”,”pz”, “Hypothesis”, “lp”, “lk”, “lpi”, and “lele”.
Returns¶
- predictions :
pandas.Series
The predictions based on DIRC likelihood cuts.
- particle_df :
- pidp_tools.pid.TOF(particle_df)[source]¶
Identifies particles based on their best-available time of flight, as measured by the GlueX Barrel Calorimeter (BCal), Time of Flight (TOF) detector, Forward Calorimeter (FCal), or the Start Counter (SC).
Parameters¶
- particle_df :
pandas.DataFrame
A dataframe containing particles to be identified. The supplied dataframe must have the following columns: “px”,”py”,”pz”, “Hypothesis”, “tShower”, “BCal Calculated Time of Flight”, “TOF Time of Flight”, “TOF Calculated Time of Flight”, “FCal Calculated Time of Flight”, “SC Time of Flight”, and “SC Calculated Time of Flight”.
Returns¶
- predictions :
pandas.Series
The predictions based on best-available TOF cuts.
- particle_df :
- pidp_tools.pid.TOF_BCal(particle_df)[source]¶
Identifies particles based on their time of flight, as measured by the GlueX Barrel Calorimeter (BCal).
Parameters¶
- particle_df :
pandas.DataFrame
A dataframe containing particles to be identified. The supplied dataframe must have the following columns: “px”,”py”,”pz”, “Hypothesis”, “tShower”, and “BCal Calculated Time of Flight”.
Returns¶
- predictions :
pandas.Series
The predictions based on BCal TOF cuts.
- particle_df :
- pidp_tools.pid.TOF_FCal(particle_df)[source]¶
Identifies particles based on their time of flight, as measured by the GlueX Forward Calorimeter (FCal).
Parameters¶
- particle_df :
pandas.DataFrame
A dataframe containing particles to be identified. The supplied dataframe must have the following columns: “px”,”py”,”pz”, “Hypothesis”, “tShower”, and “FCal Calculated Time of Flight”.
Returns¶
- predictions :
pandas.Series
The predictions based on FCal TOF cuts.
- particle_df :
- pidp_tools.pid.TOF_SC(particle_df)[source]¶
Identifies particles based on their time of flight, as measured by the GlueX Start Counter (SC).
Parameters¶
- particle_df :
pandas.DataFrame
A dataframe containing particles to be identified. The supplied dataframe must have the following columns: “px”,”py”,”pz”, “Hypothesis”, “SC Time of Flight”, and “SC Calculated Time of Flight”.
Returns¶
- predictions :
pandas.Series
The predictions based on SC TOF cuts.
- particle_df :
- pidp_tools.pid.TOF_TOF(particle_df)[source]¶
Identifies particles based on their time of flight, as measured by the GlueX Time of Flight (TOF) detector.
Parameters¶
- particle_df :
pandas.DataFrame
A dataframe containing particles to be identified. The supplied dataframe must have the following columns: “px”,”py”,”pz”, “Hypothesis”, “TOF Time of Flight”, and “TOF Calculated Time of Flight”.
Returns¶
- predictions :
pandas.Series
The predictions based on TOF TOF cuts.
- particle_df :
- pidp_tools.pid.dEdx_CDC(particle_df)[source]¶
Identifies particles based on their ionization energy loss in the GlueX Central Drift Chamber (CDC).
Parameters¶
- particle_df :
pandas.DataFrame
A dataframe containing particles to be identified. The supplied dataframe must have the following columns: “px”,”py”,”pz”, “Hypothesis”, and “CDC dEdx”.
Returns¶
- predictions :
pandas.Series
The predictions based on CDC ionization energy loss cuts.
- particle_df :
- pidp_tools.pid.dEdx_FDC(particle_df)[source]¶
Identifies particles based on their ionization energy loss in the GlueX Forward Drift Chambers (FDC).
Parameters¶
- particle_df :
pandas.DataFrame
A dataframe containing particles to be identified. The supplied dataframe must have the following columns: “px”,”py”,”pz”, “Hypothesis”, and “FDC dEdx”.
Returns¶
- predictions :
pandas.Series
The predictions based on FDC ionization energy loss cuts.
- particle_df :
- pidp_tools.pid.dEdx_SC(particle_df)[source]¶
Identifies particles based on their ionization energy loss in the GlueX Start Counter (SC).
Parameters¶
- particle_df :
pandas.DataFrame
A dataframe containing particles to be identified. The supplied dataframe must have the following columns: “px”,”py”,”pz”, “Hypothesis”, and “SC dEdx”.
Returns¶
- predictions :
pandas.Series
The predictions based on SC ionization energy loss cuts.
- particle_df :
- pidp_tools.pid.dEdx_TOF(particle_df)[source]¶
Identifies particles based on their ionization energy loss in the GlueX Time of Flight (TOF) detector.
Parameters¶
- particle_df :
pandas.DataFrame
A dataframe containing particles to be identified. The supplied dataframe must have the following columns: “px”,”py”,”pz”, “Hypothesis”, and “TOF dEdx”.
Returns¶
- predictions :
pandas.Series
The predictions based on TOF ionization energy loss cuts.
- particle_df :