ImagingHandler

This module makes images and cubes out of the uv data products created by VisHandler.

Requires CASA to run.

phangsPipeline.ImagingHandler.loop_imaging(self, do_all=False, imaging_method='tclean', imaging_method_override=None, do_dirty_image=False, do_revert_to_dirty=False, do_read_clean_mask=False, do_multiscale_clean=False, do_revert_to_multiscale=False, do_singlescale_mask=False, singlescale_mask_high_snr=None, singlescale_mask_low_snr=None, singlescale_mask_absolute=False, do_singlescale_clean=False, do_revert_to_singlescale=False, do_export_to_fits=False, convergence_fracflux=0.01, convergence_noise_z_threshold=None, singlescale_threshold_value=1.0, extra_ext_in=None, suffix_in=None, extra_ext_out=None, recipe='phangsalma', make_directories=True, dynamic_sizing=True, force_square=False, export_dirty=False, export_multiscale=False, overwrite=False)

Loops over the full set of targets, products, and configurations to do the imaging. Toggle the parts of the loop using the do_XXX booleans. Other choices affect algorithms used.

The clean convergence is set by the convergence_fracflux and convergence_noise_z_threshold parameters.

  • convergence_fracflux is the fractional flux threshold between imaging loops.

    Convergence is reached when the fractional flux change is less than this value.

  • convergence_noise_z_threshold is the noise threshold in z-scores.

    Convergence is reached when the z-score test is less than this value. By default, this is disabled by setting to None. We suggest setting this to 2.0 when enabled as a conservative choice.

Parameters:

  • do_all (bool) – If True, do all steps.

  • imaging_method (str) – ‘tclean’ or ‘sdintimaging’

  • do_dirty_image (bool) – If True, make a dirty image.

  • do_revert_to_dirty (bool) – If True, revert to dirty image.

  • do_read_clean_mask (bool) – If True, read clean mask.

  • do_multiscale_clean (bool) – If True, multiscale clean.

  • do_revert_to_multiscale (bool) – If True, revert to multiscale clean.

  • do_singlescale_mask (bool) – If True, make singlescale mask.

  • singlescale_mask_high_snr (float) – High SNR threshold for singlescale mask.

  • singlescale_mask_low_snr (float) – Low SNR threshold for singlescale mask.

  • singlescale_mask_absolute (bool) – If True, use absolute threshold for singlescale mask.

  • do_singlescale_clean (bool) – If True, singlescale clean.

  • do_revert_to_singlescale (bool) – If True, revert to singlescale clean.

  • do_export_to_fits (bool) – If True, export ms data folders into fits-format image cube files.

  • convergence_fracflux (float) – Fractional flux convergence threshold for multiscale clean. Default is 0.01.

  • convergence_noise_z_threshold (float) – Noise convergence threshold for multiscale clean. Default is None. A suggested value to use is 2.0, i.e. the null hypothesis is rejected if the z-score is greater than 2.0.

  • singlescale_threshold_value (float) – Threshold value for singlescale clean. Default is 1.0.

  • extra_ext_in (str) – Extra extension for input files.

  • suffix_in (str) – Suffix for input files.

  • extra_ext_out (str) – Extra extension for output files.

  • recipe (str) – The recipe. Default is ‘phangsalma’.

  • make_directories (bool) – Create missing directories.

  • dynamic_sizing (bool) – Use dynamic sizing.

  • force_square (bool) – Force the image size to be square.

  • export_dirty (bool) – If True, export dirty images.

  • export_multiscale (bool) – If True, export multiscale images.

  • overwrite (bool) – Overwrite existing files.