.. _rascil_apps_performance_analysis:

.. py:currentmodule:: rascil.apps

.. toctree::
   :maxdepth: 3

====================
performance_analysis
====================

performance_analysis is a command line app written using RASCIL. It helps in analysis of performance
files written by rascil_imager.

The performance files can be obtained using a script to iterate over some parameter. For example::

    #!/usr/bin/env bash
    #
    results_dir=${HOME}/results/5km_resource_modelling
    for int_time in 2880 1440 720 360
      do
        mshome=${HOME}/data/int_time${int_time}
        for npixel in 512 1024 2048 4096 8192
        do
          results_dir=${HOME}/data/int_time${int_time}_npixel${npixel}
          mkdir -p ${results_dir}
          python3 ${RASCIL}/rascil/apps/rascil_imager.py --mode cip \
            --clean_nmoment 3 --clean_facets 4 --clean_nmajor 10 \
            --clean_threshold 3e-5 --clean_restore_facets 4 --clean_restore_overlap 32 \
            --use_dask True --imaging_context ng --imaging_npixel ${npixel} --imaging_pol stokesI --clean_restored_output list \
            --imaging_cellsize 5e-6 --imaging_weighting uniform --imaging_nchan 1 \
            --ingest_vis_nchan 100 --ingest_chan_per_vis 16 \
            --ingest_msname ${mshome}/SKA_MID_SIM.ms \
            --performance_file ${results_dir}/performance_rascil_imager_${int_time}_${npixel}.json
        done
      done

In addition, the memory usage can be tracked using a dask plugin. Currently this requires setting up the dask
scheduler with the plugin::

    ssh $scheduler dask-scheduler --port=8786 --preload dask_memusage --memusage-csv \
    ./performance_rascil_imager_${1}_${2}.csv  &


Command line arguments
++++++++++++++++++++++

.. argparse::
   :module: rascil.apps.performance_analysis
   :func: cli_parser
   :prog: performance_analysis