A Crash Course in CASA With a focus on calibration

Transcription

1 A Crash Course in CASA With a focus on calibration CASA team NRAO Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very Long Baseline Array

2 CASA Common Astronomy Software Applications The offline data reduction package for ALMA and VLA HANDLES BOTH INTERFEROMETRIC AND SINGLE-DISH DATA Current version: NEW RELEASES ABOUT EVERY 6 MONTHS (BUT THIS MAY CHANGE..) CASA home: DOWNLOAD, COOKBOOK, REFERENCE, EXAMPLE SCRIPTS, MAILING LISTS Training material on CASAguides wiki: NRAO helpdesk: ALMA helpdesk:

3 Outline CASA interface: Python, tools, and tasks Structure of CASA data Key CASA tasks for data reduction/calibration CASA tasks for examining your data Clean Visualization Tools

4 casapy Shell Start CASA by typing casapy VERSION NUMBER AND LOGGER WILL APPEAR, YOU GET AN IPYTHON PROMPT Python tips (tutorials at o Indentation matters! So careful with cut/paste (a few lines at a time) o or use cpaste (type cpaste, paste code, end with a line of -- ) o Run shell commands with leading!, e.g.,!du hc o To run a script: execfile( scriptname.py ) " o Python is zero based: 0 n-1"

5 Tasks Tasks high-level functionality o Python wrapper around the toolkit and pythoncode o Accessed via python function call or parameter setting interface o List CASA tasks with command tasklist or taskhelp" o Most data reduction and tutorials and CASA guides focus on tasks"

6 Tools Tools low level, complete functionality o Interface to underlying C++ code o Intended for power users, less user-friendly, less well-documented o Objects: call with <tool>.<method>" o List available tools with command toolhelp" o Check casa.nrao.edu for documentation on all available methods

7 Task Syntax get detailed help with help(<taskname>)" Two ways to call tasks: o As a function with arguments: UNSPECIFIED PARAMETERS USE DEFAULT VALUES gaincal(vis= mydata.ms, caltable= caltable.cal, field= 2 )" o Standard, interactive task mode: OMITTING TASKNAME OPERATES ON CURRENT TASK default(<taskname>) sets task s parameters to default values inp(<taskname>) see task s parameter settings (input values) saveinputs(<taskname>) tget(<taskname>) saves parameters to <taskname>.saved retrieves parameters (<taskname>.last)"

8 Standard Task Interface Examine task parameters (inputs) with inp :

9 Standard Task Interface Default values in BLACK

10 Standard Task Interface Expandable parameters are highlighted Sub-parameters indented

11 Standard Task Interface User set values in BLUE Erroneous values in RED

12 Outline CASA interface: Python, tools, and tasks Structure of CASA data Key CASA tasks for data reduction/calibration CASA tasks for examining your data Clean Visualization Tools

13 Measurement Set CASA stores u-v data in directories called Measurement Sets TO DELETE THEM USE rmtables( my_data.ms ) OR " os.system( rm rf my_data.ms )" These data sets store two copies of the data (called columns ): Data Column Contains the raw, unprocessed measurements. Corrected Column Usually created by applying one or more calibration terms to the data. Additionally a model may be stored separately. THIS IS USED TO CALCULATE WHAT THE TELESCOPE SHOULD HAVE OBSERVED. Each data point may also be flagged, i.e., marked bad. IN THIS CASE IT IS IGNORED (TREATED AS MISSING) BY CASA OPERATIONS.

14 listobs! Measurement sets contain a mix of data: o One or more spectral windows o One or more fields (e.g., source, phase calibrator, flux calibrator) o Data from several antennas o Data organized into discrete scans Inspect the contents of your measurement set using listobs.

15 listobs! Measurement sets contain a mix of data: o One or more spectral windows o One or more fields (e.g., source, phase calibrator, flux calibrator) o Data from several antennas o Data organized into discrete scans Inspect the contents of your measurement set using listobs.

16 Data Selection Syntax see Chapter 2.5 of Cookbook field - string with source name or field ID can use * as wildcard, first checks for name, then ID example: field = ; field = 3C* ; field = 0,1,4~5 spw - string with spectral window ID plus channels use : as separator of spw from optional channelization use ^ as separator of channels from step/width example: spw = 0~2 ; spw = 1:10~30;50~65 ; spw = 2~5:5~54^5 16

17 Selection Syntax see Chapter 2.5 of Cookbook antenna - string with antenna name or ID first check for name, then ID (beware VLA name 1-27, ID 0-26) example: antenna = 1~5,11 ; antenna = ea*,!va Baselines: ea01&ea10 timerange - string with date/time range specify T0~T1, missing parts of T1 default to T0, can give T0+dT example: timerange = 2007/10/16/01:00:00~06:30:00 17

18 Calibration Tables Calibration yields estimates of phase and amplitude corrections. E.G., AS A FUNCTION OF TELESCOPE, TIME, FREQUENCY, POLARIZATION. CASA stores these corrections in directories called calibration tables. TO DELETE THEM USE rmtables( my_data.ms )" These are created by calibration tasks: E.G., gaincal, bandpass, gencal" Applied via applycal to the data column and saved as corrected. Measurement Set ( Data Column) Calibration Table(s) applycal CASA Task" Measurement Set Data Column Still holds original data Corrected Column Now holds corrected data.

19 Basic Calibration Flow Define what the telescope SHOULD have seen. Measurement Set Model (defaults to point source) Define a model for the data (setjy) Measurement Set (with associated model)

20 Basic Calibration Flow Derive the corrections needed to make the data match the model. Measurement Set (with associated model) Calibration Task" (e.g., gaincal, bandpass) Calibration Table

21 Basic Calibration Flow Apply these corrections to derive the corrected (calibrated) data. Measurement Set Data Column Calibration Table Apply Calibration" applycal" Measurement Set Corrected column now holds calibrated data.

22 Basic Calibration Flow Define what the telescope SHOULD have seen. Measurement Set Model (defaults to point source) Define a model for the data (setjy) Measurement Set (with associated model) Derive the corrections needed to make the data match the model. Measurement Set (with associated model) Calibration Task" (e.g., gaincal, bandpass) Calibration Table Apply these corrections to derive the corrected (calibrated) data. Measurement Set Data Column Calibration Table Apply Calibration" applycal" Measurement Set Corrected column now holds calibrated data.

23 Schematic Calibration Calibrate the Amplitude and Phase vs. Frequency of Each Antenna ASSUME TIME & FREQUENCY RESPONSE SEPARABLE, REMOVE TIME VARIABILITY Calibrate the Amplitude and Phase vs. Time of Each Antenna ASSUME TIME & FREQUENCY RESPONSE SEPARABLE, REMOVE FREQ. VARIABILITY Set the Absolute Amplitude Scale With Reference to a Known Source PLANET (MODELLED), MONITORED QUASAR, ETC. Apply all corrections to produce calibrated data

24 Schematic Calibration Calibrate the Amplitude and Phase vs. Frequency of Each Antenna bandpass" Bandpass Calibration Table Calibrate the Amplitude and Phase vs. Time of Each Antenna gaincal" Phase Calibration Table Amplitude Calibration Table Set the Absolute Amplitude Scale With Reference to a Known Source fluxscale" Flux Calibration Table Apply all corrections to produce calibrated data applycal" Measurement Set Corrected column now holds calibrated data.

25 Outline CASA interface: Python, tools, and tasks Structure of CASA data Key CASA tasks for data reduction/calibration CASA tasks for examining your data Clean Visualization Tools

26 Key Tasks for Calibration Derive Calibration Tables setjy: set model (correct) visibilities using known model for a calibrator bandpass: calculate bandpass calibration table (amp/phase vs frequency) gaincal: calculate temporal gain calibration table (amp/phase vs time) fluxscale: apply absolute flux scaling to calibration table from known source Manipulate Your Measurement Set flagdata/flagcmd/flagmanager: flag (remove) bad data applycal: apply calibration table(s) from previous steps split: split off calibrated data from your ms (for imaging!) Inspect Your Data and Results plotms: inspect your data interactively plotcal: examine a calibration table

27 gaincal Measurement Set Data column holds observations. (Optional) One or More Calibration Tables (applied on the fly before solution)" (Optional) Associate a model (expected sky distribution) with the MS. (Else assume point source) gaincal" Solve for phase and amplitude response of each telescope as a function of time. (Solutions derived to give best match of data to model once they are applied.) o What time interval to solve over? o Requirements for a good solution. o Reference Antenna Calibration Table Later applied with applycal"

28 gaincal

29 gaincal Input Measurement Set (with model set, if needed)

30 gaincal Output Calibration Table (apply later with applycal)

31 gaincal Options to select which data to consider: e.g., select calibrator fields

32 gaincal Time interval over which to solve. (Only cross scan or spw boundaries with combine )

33 gaincal Reference Antenna (pick a central one with little or no flagging)

34 gaincal Requirements for a solution in terms of S/N and # of baselines contributing

35 gaincal Normalize solutions?

36 gaincal What to solve for? a mplitude p hase ap - both

37 gaincal Calibration tables to apply before solution: e.g., apply bandpass calibration before gaincal"

38 gaincal Measurement Set Data column holds observations. (Optional) One or More Calibration Tables (applied on the fly before solution)" (Optional) Associate a model (expected sky distribution) with the MS. (Else assume point source) gaincal" Solve for phase and amplitude response of each telescope as a function of time. (Solutions derived to give best match of data to model once they are applied.) o What time interval to solve over? o Requirements for a good solution. o Reference Antenna Calibration Table Later applied with applycal"

39 Outline CASA interface: Python, tools, and tasks Structure of CASA data Key CASA tasks for data reduction/calibration CASA tasks for examining your data Clean Visualization Tools

40 Imaging/Deconvolution Task CLEAN Performs Fourier Transform of the Visibilities in Measurement Set SPATIAL AND VELOCITY GRIDDING, MOSAICKING, DATA WEIGHTING STOKES IMAGES, DIRTY CUBE Deconvolution MAJOR CYCLES/MINOR CYCLES, INTERACTIVE CLEAN REGIONS CLEAN ITERATIONS, THRESHOLDS

41 Imaging/Deconvolution MS

42 Imaging/Deconvolution Field

43 Imaging/Deconvolution MFS for continuum Velocity for Spectral Line

44 Imaging/Deconvolution Image Size

45 Imaging/Deconvolution Pixel Size

46 Imaging/Deconvolution Weighting Scheme Natural/Uniform/Briggs

47 Imaging/Deconvolution Clean Algorithm

48 Imaging/Deconvolution Maximum Clean Iterations

49 Imaging/Deconvolution Clean Residual Threshold

50 Imaging/Deconvolution Interactive T/F

51 Outline CASA interface: Python, tools, and tasks Structure of CASA data Key CASA tasks for data reduction/calibration CASA tasks for examining your data Clean Visualization Tools

52 Visualization Tools Data needs to be displayed to understand it! Can be a challenge for large datasets Visibilities: plotms, msview Images: viewer, imview Calibration tables: plotcal (soon plotms) Any table values: browsetable Single dish: sdplot Plot anything: use Python s matplotlib 52

53 PlotMS plotms 53

54 Image Viewer Image Viewer 54

55 Image Viewer Displaying cubes Movies Channel maps Declination Right Ascension 55

56 Image Viewer Displaying cubes Movies Channel maps Declination Right Ascension 56

57 MSView MS Viewer 57

58 Plotcal MS Viewer 58

59 Plot Anything - matplotlib 59

60 Image Analysis Visualization CASA VIEWER Image Cubes MOMENT MAPS GAUSSIAN SPECTRAL LINE FITTING Continuum SPECTRAL INDEX MAPS SOURCE FITTING

61 Your Turn Point your web browser at the Synthesis Imaging School CASA guide. The site has contains links to the spectral line and the continuum EVLA tutorials We use a stable version of CASA 3.4 the full release will be available soon The SIW page contains links to the CASA 3.4 tasks, tools, and the Cookbook Launch: casapy ( casaviewer, casaplotms ) at NMT, casapy-stable ( casaviewer-stable, casaplotms-stable ) at NRAO ASK IF YOU NEED HELP!

62 Your Turn Point your web browser at the Synthesis Imaging School CASA guide. The site has contains links to the spectral line and the continuum EVLA tutorials We use a stable version of CASA 3.4 the full release will be available soon The SIW page contains links to the CASA 3.4 tasks, tools, and the Cookbook Launch: casapy ( casaviewer, casaplotms ) at NMT, casapy-stable ( casaviewer-stable, casaplotms-stable ) at NRAO ASK IF YOU NEED HELP!

63 Your Turn Point your web browser at the Synthesis Imaging School CASA guide. Decide whether to start with WVR and Tsys applied. Work end-to-end through the calibration of a single measurement set. THE FULL ONLINE GUIDES STEP THROUGH CALIBRATION FOR SEVERAL MSS. (Optional) Try writing a python script as you go. THIS IS VERY GOOD PRACTICE FOR ACTUAL REDUCTION. After lunch, we will image the results. DON T WORRY, WE HAVE PROVIDED CALIBRATED DATA FOR THE AFTERNOON! ASK IF YOU NEED HELP!