1. Run

   source /home/spxfp1/rhys_cory/frames/python_env 

2. access make-zero-noise-frame.sh file from Charlie's Github

This file uses pycbc_generate_hwinj to generate the waveform to be injected and pycbc_insert_frame_hwinj for the injection (see documentation here )

1. Edit /make-zero-noise-frame.sh. Edit any parameters that are you want to simulate. Finally, there is the place to set the path to where you will want to store the *txt's and *gwf's you create and store the files you produce in there. This is also where you will perform your PE run.
2. Run

    . make-zero-noise-frame.sh 

3. At this point frame files should be created which correspond to the waveform at each detector
4. type deactivate to remove the source ready to source the code for the pe runs

Once these steps are done, prepare the pe file

1. Go to directory containing Frame File

Source all the code installations:

source /home/spxfp1/opt/lalsuite/lalinference_o2_phenomHM/etc/lalsuiterc 

1. Source .ini file from Charlie's Github, The ini file will (currently will change this eventually) depend on whether you are doing nest or mcmc and how many detectors
2. In ini file modify webdir, baseurl and email, can modify other parameters as necessary

In general, if you want to know what a parameter means, refer to this page and/or read the outputs of

lalinference_mcmc --help
lalinference_nest --help 

1. Parse your “inifile” to setup the run:

    lalinference_pipe PE.ini -r ./ 

2. Follow instructions, if any appear i.e. run

    condor_submit_dag multidag.dag 

   At which point, your run should be started.

3. To monitor your run do:

   condor_q $USER 

   or

   watch condor_q $USER