THE NEXT GENERATION OF THE MONTAGE IMAGE MOSAIC ENGINE

G. Bruce Berriman, John C. Good and Ben RusholmeIPAC, Caltech, USAThomas Robitaille

MPIA, Heidelberg, Germanyhttp://montage.ipac.caltech.edu

[ascl:1010.036]

A New Landscape of Data And Software

What Will Next Generation Montage Do?Version 4.0 – October 2015

Support for processing multi-dimensional data sets (“cubes”)Command-line visualization toolPython wrapper for visualization toolIndexing and fast spatial searches for large image data sets (November 10, 2015) (mSearch)

Version 5.0 – October 2016Support for HEALPix

Support for WWT/TOAST

Integration with Python – C API

Tools for astronomers to process data in the cloud.

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See Creating A Multiwavelength Galactic Plane Atlas With Amazon Web Services – Berriman et al. (2015). Tools for Astronomical Big Data http://www.noao.edu/meetings/bigdata/files/Berriman.pdf

Dedicated modules for data cubesModule PurposemProjectCube Reproject data cube (4 dimensions).mAddCube Co-adds reprojected cubes.mShrinkCube Averages data in spatial or physical

dimensions.mSubCube Creates cutouts of cubes.mTranspose Transpose axes of data cubes.

Download from GitHub https://github.com/Caltech-IPAC/MontageBackwards compatible with earlier releases.

ANSI -C.

Formal testing on RedHat Enterprise Linux Server 5.9 and on Mac OS X 10.9.x.All the benefits of the Montage architecture.

Galactic Arecibo L-band Feed Array HI (GALFA-HI) Survey. 21-cm maps of neutral hydrogen near the Milky Way. 40 deg x 40 deg area mosaic processed by Montage.

Computing a mosaic of a cubeSteps in creating this mosaic of 5 GALFA images (1.1 GB each; 2048 velocity planes).

1. Average 10 velocity planes to reduce processing time:mShrinkCube -m 10 narrow/GALFA_HI_RA+DEC_004.00+18.35_N.fits narrow_shrunk/GALFA_HI_RA+DEC_004.00+18.35_N_m10_1.fits 1[struct stat="OK”]

2. Create an image list of the shrunken images:mImgtbl narrow_shrunk/ images-narrow.tbl

3. Create a header template for the mosaic:mMakeHdr images-narrow.tbl template-narrow.hdr

4. Reproject images:mProjectCube narrow_shrunk/GALFA_HI_RA+DEC_004.00+18.35_N_m10_1.fits proj-narrow/GALFA_HI_RA+DEC_004.00+18.35_N_m10_1_proj.fits template-narrow

5. Create an image metadata file for the reprojected images:mImgtbl proj-narrow/ proj-images-narrow.tbl

6. Co-add images: mAddCube -p proj-narrow proj-images-narrow.tbl template-narrow.hdr final/GALFAmosaic.fits

7. Create a PNG of the mosaic:mViewer -ct 4 -gray GALFAmosaic.fits[0][99]-2s max gaussian-log -out GALFA102.png

Processing Data Cubes OnThe Amazon Web Services Platform

•Credit from the SKA/AWS “Astrocompute In The Cloud” program.

•Process all GALFA-HI DR-1Walltime: 5 1/2 hrsResources CfnCluster: 5 m4.2xlarge: 1 head node (on-demand)

+ 4 workers (spot). 8 vcpu, 32 GB ram each.

Input 184 fields, 8.53° on a side (114 GB)Output 10 fields, 35 x 39.3°, offset 30° RA ( 941 files, 857

GB).Price us-west-2a: $0.504/hr on demand, $0.0821 spot/hr .

Processing cost $5.

Sky Coverage of the GALFA survey

Command-line Visualizer• mViewer creates PNG or

JPEGs • User control over stretch• Coordinate grids • Astronomical source (catalog)

scaled symbols • Image metadata (outlines) • Markers (individual symbols) • Labels

• Uses “sticky” directives mViewer -color ffff00 -symbol 1.0 circle -scalecol j_m 16.0 mag \-catalog fp_2mass.tbl -gray SDSS_g.fits 0s max gaussian-log out catalog.png

Python interface Command-line visualizer (beta)

import astroMontage.mViewer as mv

viewer = mv.mViewer()

viewer.set_red_file("SDSS_r.fits")viewer.set_red_stretch("0.1s", "max", "gaussian-log")

viewer.set_green_file("SDSS_g.fits")viewer.set_green_stretch("0.1s", "max", "gaussian-log")

viewer.set_blue_file("SDSS_u.fits")viewer.set_blue_stretch("0.1s", "max", "gaussian-log")

viewer.set_current_color("8080ff") viewer.add_grid("Equ J2000")

viewer.set_current_color("90ff90") viewer.add_img_info("mipssed.tbl")

viewer.set_current_color("ff9090") viewer.add_img_info("irspeakup.tbl")

…

More than mosaics!• A command-line toolkit for managing, visualizing

and analyzing the contents of FITS files and their metadata.

• A community resource• Supporting KELT in

developing coverage maps of their fields.

• Finding charts for Kepler Follow-Up program.

• Advising on optimizing processing plan for Herschel Hi-GAL Galactic Plane Survey.

Resources• http://montage.ipac.caltech.edu• Follow us on Facebook: Montage Image Mosaic Software• Twitter feed @bruceberriman• Blog https://montageblog.wordpress.com/

McLeod et al. 2015 “The Pillars of Creation revisited with MUSE: gas kinematics and high-mass stellar feedback traced by optical spectroscopy.”MNRAS, In press.