Routines and procedures for calibrating and reducing raw COMAP spectroscopic single-dish radio data.

Prerequisites are listed in an approximate order in which they should be installed:

• Python 3.X.X
• SLALIB - Astronomical libraries for any spherical trig.
• OPENMPI/MPICH - The pipeline requires MPI to run, either backend will work fine.
• MPI4PY - MPI4Py must be compiled against the mpi library above.
• HDF5 --parallel-enabled - An mpi ready version of the HDF5 libraries (see link for instructions)
• H5PY - Must be compiled against above HDF5 library (not the one included with anaconda )
• HEALPY - Either against your local version of HEALPix or a pre-compiled version from pip.

Other standard libraries such as NumPy, SciPy, matplotlib, etc... are assumed to be installed already.

After all prerequistites are installed first install the library by

cd /path/to/COMAPreduce/
python setup.py install

You will then need to setup a working directory that will contain:

• run.py
• All the .ini files
• COMAP_FEEDS.dat

mkdir /path/to/working/directory/
cp /path/to/COMAPreduce/run.py  /path/to/working/directory/
cp /path/to/COMAPreduce/*.ini /path/to/working/directory/
cp /path/to/COMAPreduce/COMAP_FEEDS.dat /path/to/working/directory/

Three example parameter files (the .ini files) have been provided.

To run the pipeline you will need to both choose a parameter file and generate a list of files. In

COMAPreduce/comancpipeline/scripts/io/

there is script called createFileList.py that can help to generate a filelist, it is executed as

python createFileList -D /path/to/level1/files -o "string describing observation you need (e.g. TauA)" -F output_filelist_name.dat

Finally, to run the pipeline you invoke in your working directory

python run.py -P parameterfile.ini -F filelist.dat

and for MPI executions

mpiexec -n X python run.py -P parameterfile.ini -F filelist.dat

where X is the number of cores you want to use.