The ALMA TP data is generally reduced using the TP data reduction pipeline which performs calibration and imaging; only in exceptional cases are ALMA TP data manually reduced using standard scripts.
Pipeline: Look for a file "PPR...xml" in the "script" subdirectory. If such a file is present, your data was pipeline-reduced. You can also check the QA2 report.
Manual: You will find scripts “*.scriptForSDCalibration.py” in the script folder.
TP datasets will often consist of many execution blocks (EBs). Each of them was calibrated individually. Imaging is done on all calibrated data together.
Pipeline: TP calibration with the ALMA pipeline is described in the ALMA Science Pipeline User's Guide: https://almascience.org/processing/science-pipeline
Manual: For details on manual calibration of TP data, see: https://casaguides.nrao.edu/index.php/M100_Band3_SingleDish.
One important aspect of the calibration is the conversion of the data from K to Jy/beam. This is done per spectral window, antenna, and EB.
Pipeline: The Jy per K conversion factors can be found via the pipeline weblog in the "qa" directory or in the file "jyperk.csv" under the "calibration" directory of this package.
Manual: The values that were used to convert brightness temperature in Kelvin to Jy/beam are available at the end of each calibration script.
The conversion factors were derived from an observatory database for which the observatory conducts regular observations of standard single-dish calibrators and stores the measurements. This analysis is done using standard scripts. We are not providing those data by default to the users, but in case you would be interested to have them, you are welcome to contact the helpdesk of your region.
To perform your own imaging, you will first need to restore the calibrated measurement sets. See this article: https://help.almascience.org/kb/articles/470-how-do-i-obtain-a-file-of-calibrated-visibilities-measurement-set-for-alma-data
Please note that processing may take a significant amount of time and may need a significant amount of resources. To see how long the initial processing took, please see the "Execution Duration" which is shown on the home page of the pipeline weblog. The data to be processed in pipeline cannot exceed limits of 31GB of raw data for a reduction machine with 64GB of RAM.
Pipeline: As written in the Pipeline User’s Guide:
“After calibration with the script casa_pipescript.py, it is possible to re-image using the CASA Single Dish task, tsdimaging, with user-defined parameters. As mentioned earlier, the Single Dish Pipeline creates a calibrated MS with a filename extension of *.ms.atmcor.atmtype1_bl for each ASDM. The tsdimaging command will make images of all MS that are specified in the infiles parameter. For other parameters in tsdimaging, refer to the *casa_commands.log file.
Note that the images included in the delivery package have the native frequency resolution, and the cell size of one-ninth of the beam size, as recommended in the SD “CASA Guide” https://casaguides.nrao.edu/index.php/M100_Band3_SingleDish. If you want to change the frequency resolution and cell size, we recommend that you import the delivered FITS data cubes into CASA and regrid them using the CASA task imregrid.
It is also possible to revise the baseline subtraction using your preferred mask range instead of the pipeline-defined range. We recommend doing this on the images using the CASA tasks imcontsub or sdbaseline during your own manual calibration (refer to the CASA Guides).”
Manual: For the imaging, we recommend you use the provided script, as it contains certain values (e.g. beams) that must be set to a precise value. You may run the script step-by-step, as for the calibration scripts. Before doing that, you may need to update the paths to the calibrated data, in the msNames variable near the top of the script.