VLA CASA Pipeline-CASA4.5.3

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Introduction

• With the start of Jansky VLA Full Operations (January 2013), we started a new operational model: – Deliver flagged and calibrated visibility data – You will self-calibrate and image visibility data to meet science goals, using resources at home institution or NRAO computing resources • Automated pipeline should run correctly on all “standard” Stokes I science SBs; “standard” means: – 128 MHz spws, but may work on other set-ups as well • Some constraints on strength of calibrators needed – Contains correctly labeled and complete scan intents • Current versions available: – “scripted” pipeline is a collection of python scripts that use CASA tasks wherever possible, but also uses toolkit calls; readable and easy to modify – CASA integrated pipeline is compatible with ALMA pipeline infrastructure, improved diagnostics in weblog, used as real-time pipeline since Sep 2015

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• Real-time pipeline: – Minimal human intervention • Pipeline is run automatically on every science SB as it completes (not just “continuum”) – Pipeline output undergoes quality assurance checks by NRAO staff upon request; reports generated are archived as pipeline products • At your home institution: – Instructions for installation and operation of the VLA CASA Calibration Pipeline are available at https://science.nrao.edu/facilities/vla/data-processing/pipeline • Uses CASA 4.3.1, similar to current real-time pipeline • CASA 4.5.2 currently being validated (you are helping with this!) • Scripted pipelines for CASA versions through 4.5.0 also available – Provides more flexibility in how to use the pipeline, options suitable for spectral line datasets, mixed correlator set-ups, multi-band observations, etc. – Working to incorporate these into the CASA integrated pipeline

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Data

Overview of the Pipeline procedures

Pipeline Requirements

Running the Pipeline

Assessing the Weblog

Pipeline Outputs

Re-running the pipeline

Applying Pipeline Results

Known Issues and Workarounds

Scripted Pipeline

Using the NRAO cluster batch processing