Quickstart ========== Once installed, you can activate the virtual environment inside the project directory and run the CLI tool. The help message for the CLI can be accessed via the ``--help`` flag: .. code-block:: console $ source /.venv/bin/activate $ ska-sdp-continuum-imaging-qa --help usage: ska-sdp-continuum-imaging-qa [-h] [--output-dir OUTPUT_DIR] [--snr-threshold SNR_THRESHOLD] fits_image oskar_lsm Compute QA metrics for an input FITS image. positional arguments: fits_image Path to the FITS image file. oskar_lsm Path to the OSKAR-compatible ASCII LSM (stand-in for GSM). options: -h, --help show this help message and exit --output-dir OUTPUT_DIR Directory to write output files to (default: a directory named after the input image stem). --snr-threshold SNR_THRESHOLD Minimum SNR for sources included in QA metrics (default: 10.0). Generating the QA metrics -------------------------- The only mandatory arguments are the paths to the input files, a FITS image and a reference sky model, supplied to the CLI command via the two positional arguments: .. code-block:: console ska-sdp-continuum-imaging-qa image.fits reference_lsm.txt The command writes output files into the directory given by ``--output-dir`` or, if omitted, into a directory named after the FITS image stem under the current working directory. In the above case, the output files will be written to a directory named ``image/`` under the current working directory. .. note:: The following must be true of the two mandatory positional arguments: - The first positional argument is a FITS image file output by ``WSClean``. - The second positional argument is an ``OSKAR``-compatible `fixed-format ASCII LSM `_ file. A successful run of the above command will produce the following output files in the output directory: .. code-block:: console $ ls image/ image_flux_density_ratios.npy image_positional_offsets.npy image_qametrics.txt image_matched_catalogue.csv image_qa_summary.png