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Proton beam polarization measurement with recoil p-Carbon polarimeters

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Introduction

cnipol is a software package designed to acquire and analyze data from the Relativistic Heavy Ion Collider (RHIC) polarimeters at the Brookhaven National Lab (BNL). The first objective of this package is usually referred to as the "online" layer and designed to support the data acquisition and to provide a quick feedback by carrying out a fast online analysis. The second objective is to execute a more rigorous "offline" data analysis and present the results in a systematic way. It is normally referred to as the "offline" layer of cnipol.

There is a wiki page with some details about the RHIC polarimetry:

https://wiki.bnl.gov/rhicspin/Polarimetry

The results obtained with cnipol can be found at

http://www.phy.bnl.gov/cnipol/

How to configure and install cnipol

The development of cnipol is done using the git version control system. Good manuals can be found at:

Obtaining the code

The best way to start with the analysis is to clone the latest version of the code from the git repository. From the location where the package will be installed on your machine issue a following command:

git clone https://github.com/rhicspin/cnipol.git
cd cnipol

This will create a cnipol directory with your local cnipol repository.

Syncing changes with central repository

In order to sync your changes in your local copy with the central repository you will need to have have them commited to your local repository first. To do that you need to first "stage" them using

git add -p

This will interactively ask you which changes you want to stage. If there are new files that you would like to add to the repository use

git add path/to/new/file

To check what changes are staged use git status and git diff --staged. To unstage all of the changes use git reset. After staging the changes use git commit -m "your commit message here" to turn them into a commit. Use git log -p to see list of local commits.

The newly created commit will only exist in your local repository. To synchronize with the common repository issue:

git pull --rebase
git push

Later should ask for your github credentials. If you plan to push oftenб it is a good idea to generate an ssh key and add it to gihub: https://help.github.com/articles/connecting-to-github-with-ssh/

It is important to sync your changes in a timely manner. Letting your changes pile locally for too long increases chance of having a merge conflict.

Compiling the code

The analysis framework depends on a few external libraries and programs including

  • ROOT5
  • MySQL
  • sqlite3
  • boost (through opencdev)

These (except ROOT) are typically readily available on most linux systems.

Before the code can be compiled and executed a number of environment variables must be set. We provide an example bash script script/setup.sh with predefined paths which should work on the eic cluster of the RACF (RHIC and ATLAS Computing Facility). Review and modify this script as needed to match your specific system configuration. An example is the variable CNIPOL_DIR, which the directory you setup the code. This script can be ran with an optional argument for the RHIC run number, e.g. run_id = 9|11|12|13|15|17, execute in the terminal (Note: You need to be in a bash shell. Type bash):

source script/setup.sh [run_id]

Once the environment variables are set the cnipol package can be built in $CNIPOL_DIR as:

mkdir build
cd build
cmake28 .. -DCMAKE_BUILD_TYPE=RelWithDebInfo
make

The compiled executables should appear in this build directory along with the cnipol libraries.

How to run cnipol

Make sure the following environment variables are set to valid locations before running the cnipol executables

$CNIPOL_DATA_DIR
$CNIPOL_RESULTS_DIR

asym accepts a number of options which can be listed by running it with a -h option. Here we just give a few most common examples used to process regular and calibration data.

To analyze a regular data file simply do in the build directory:

./asym -r <meas_id>

where <meas_id> is a unique name of a measurement, e.g. 12345.001. Note that usually <file_name> = <meas_id>.data. The program searches for the input <file_name> file in $CNIPOL_DATA_DIR and creates an output directory <meas_id> in $CNIPOL_RESULTS_DIR. Typically, the output directory contains a ROOT file with a predefined set of histograms, a log file (stdoe.log) with the entire output of the program, a PHP file with information about the measurement and results to display on the web, and a file with calibration results.

To analyze an alpha or pulser measurement use the --alpha option:

./asym --alpha -r <meas_id>

Batch processing multiple data files

Once in a while, when, for example, the cnipol code is modified one may need to re-analyze a large number of data files. This can be achieved in several ways by utilizing common linux tools. Here for completeness we provide a simple shell script that takes a text file containing a list of measurements (one <meas_id> per line) as a single argument and starts a certain number of parallel jobs in the background. The scripts for energy calibration and regular runs can be executed respectively as:

script/run_asym_alpha.sh <meas_list>
script/run_asym.sh <meas_list>

How to produce summary plots

Before you begin you should source the setup file as decribed above.

Often it is useful to see how polarization or other observables change from measurement to measurement during some period of time. To study such time dependence we developed masym, a program that runs on a set of measurements analyzed with asym. The output ROOT files produced by asym are used as input to masym. Executing the following command will create a <meas_list> directory in $CNIPOL_RESULTS_DIR with a ROOT file containing summary histograms:

./masym -m <meas_list>

Here <meas_list> is a plain text file with a list of measurements to process. This file is assumed to exist in $CNIPOL_RESULTS_DIR/runXX/lists/ and to have one <meas_id> per line.

Optionally, the analyzer can provide a plain text file $CNIPOL_RESULTS_DIR/runXX/hjet_pol with H-Jet polarization values. Information from these text files will be used by masym in the summary plots.

Similarly to masym, we provide a program to study time dependences in a set of alpha-calibration measurements. This program is called malpha and can be invoked as:

./malpha -m <meas_list> -o <output_file>

where <meas_list> is a file in $CNIPOL_RESULTS_DIR/runXX/lists/ with a list of unique names corresponding to measurements recorded by the polarimeters when no beam was present in the RHIC.

General Description of Directory Layout

  • $CNIPOL_DATA_DIR — directory containing raw input data files that are read by asym. Typically points to /eicdata/eic0005/run??/data where ?? is the run number.
  • $CNIPOL_RESULTS_DIR — output directory for asym (it creates $CNIPOL_RESULTS_DIR/<meas_id> subdirectories). Also input and output directory for masym (it reads asym output and produces its output in $CNIPOL_RESULTS_DIR/<meas_list>). Typically points to /eicdata/eic0005/run??/root.
  • Another input directory for masym is /eicdata/eic0005/runXX (literally XX) that is a local git repository clone of https://github.com/rhicspin/runXX. It contains plain text files with lists of measurements, target statuses and H-Jet polarizations. I also contains text cdev logs, but these are not used anymore. Due to some bug masym will look for it in $CNIPOL_RESULTS_DIR/runXX, which we working around by creating a symlink like ln -s /eicdata/eic0005/runXX /eicdata/eic0005/run17/root/runXX.

Automating the Process

First, you need to follow the link below to set up a tunnel to the blue and yellow pC machines at IP 12. This will provide you with a tunnel into the machines without requiring a password.

https://wiki.bnl.gov/rhicspin/Automated_pC_setup

The name of the script to execute is run_asym_daemon.sh. However, the first line in the script should be changed to the location of the setup.sh and the run number.

After the tunnel has been established you can start the automated process by executing the following command:

nohup ./run_asym_daemon.sh > some_output_file_name

and you can put an ampersand at the end of the process if you want to hide it. The ampersand will allow you to continue working in your current terminal. Regardless, the process will be running and looking for new files every 60 seconds.

Maintaining local copies of GPM logs

There are currently two interfaces to query Gpm log data (such as bias currents, beam luminosities, ags polarization measurements):

  • SshLogReader (with caching optionally provided by CachingLogReader wrapper)
  • opencdev::LocalLogReader

The first one requires starting a new ssh connection to a machine in the CAD network to run exportLoggerData for each query. This method is generally slow and it is not working reliably with large volumes of parallel queries (which you get when you have multiple instances of asym running). The second method is fast and doesn't require tunnel at runtime, but it needs a full copy of the data available locally (on disk at path defined by $SLOW_CONTROL_LOG_DIR environment variable). There is a small script (cdev_export.py) to maintain such a copy.

Installing dependencies for cdev_export.py

To have get it working you will need freetds and python-sybase libraries installed first:

wget http://mirrors.ibiblio.org/freetds/stable/freetds-0.91.tar.gz
tar zxf freetds-0.91.tar.gz
pushd freetds-0.91
./configure --prefix=$HOME/local && make && make install
popd
wget --no-check-certificate https://sourceforge.net/projects/python-sybase/files/python-sybase/python-sybase-0.40pre2/python-sybase-0.40pre2.tar.gz
tar zxf python-sybase-0.40pre2.tar.gz
pushd python-sybase-0.40pre2
mkdir -p $HOME/local/lib64/python2.6/site-packages/
SYBASE=$HOME/local CFLAGS="-DHAVE_FREETDS -UWANT_BULKCOPY" PYTHONPATH=$PYTHONPATH:$HOME/local/lib64/python2.6/site-packages python setup.py install --prefix=$HOME/local
popd

You also need to get most recent version of opencdev:

git clone https://github.com/rhicspin/opencdev.git

Running cdev_export.py

The tool needs a connection to the database:

ssh yellowpc -L 5000:acnlinbd:5000 -Nf

Environment variables need to be setup to point to the libraries:

export SYBASE=$HOME/local
export PYTHONPATH=$PYTHONPATH:$HOME/local/lib64/python2.6/site-packages
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$HOME/local/lib

The script is ran as:

opencdev/tools/cdev_export.py

It should iteratively download Gpm index database from remote Sybase server and save the contents into ./sql directory. The sql files should be rendered to local Sqlite database using find sql -exec cat {} \; | sqlite db.sqlite command. Then raw SDDS files with the data itself are downloaded to ./run_fyXX directory. Both db.sqlite and data files need to go into the directory pointed by $SLOW_CONTROL_LOG_DIR.

Alpha Calibration File

During the course of the run, a long alpha measurment should occur and create the alpha calibration files needed for properly processing the measurments. Once this file is created you will need to edit the following code to include the file name of the alpha calibration. You can find the code at the following:

/contrib/RunPeriod.inc

Make sure to change the start_time, the polarimeter_id, the alpha_calib_run_name, and possibly the gain_slope (may not need to include the gain_slope at all). The other parameters are the default tdc and adc cuts on the bananas plots.

General remarks

The code for the analysis of the RHIC polarimeters data has changed significantly starting 2010. Nevertheless, one may still find it useful to look through the older documentation which can be found at

http://www4.rcf.bnl.gov/~cnipol/Analysis/pC/index.html

Other polarimetry software packages

Different people have been working on analysing polarimetry data. Some notable packages used for this purpose are:

ags_cni

Code for AGS data analysis.

AGS has a jet polarimeter much like the one at RHIC. Analysis code has branched a long time ago and is now supported by CAD.

hjet-analysis

Code for the H-jet polarimeter data analysis

Supported by the RHIC Spin group and provides the official polarization numbers.

new hjet analysis

An analysis by Andrei Poblaguev that pioneered support of the new JLAB fADC250 VME DAQ system.