1 / 8

Generic architecture for analyses on calibrated images

Generic architecture for analyses on calibrated images. Gijs Verdoes Kleijn OmegaCEN Kapteyn Astronomical Institute. Facilitating analysis beyond the calibrated image stage. Analysis software Image differencing: VODIA/OmegaTranS Photometric redshifts: PhotZ

guy
Download Presentation

Generic architecture for analyses on calibrated images

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Generic architecture for analyses on calibrated images Gijs Verdoes Kleijn OmegaCEN Kapteyn Astronomical Institute

  2. Facilitating analysis beyond the calibrated image stage • Analysis software • Image differencing: VODIA/OmegaTranS • Photometric redshifts: PhotZ • Galaxy surface photometry: galfit(/galphot) • Astro-WISE users likely use/develop more in future…… • Goal: • Easy running • Easy exploring input/output • Easy access final results • Method: make new classes which run routine, contain input/output, plus connections to its dependencies. • Status: design ready: presented now for final input

  3. Bi-furcation in kind of analysis • Immediate modelling of image data • galfit, PhotZ, (galphot) • Take input from SourceLists Case A SourceLists Case B • Further manipulation of images first • OmegaTranS/Vodia • Take input from RegriddedFrame RegriddedFrames (,ReducedScienceFrame, CoaddedRegriddedFrame)

  4. Case A: starting from SourceList • Modelling input+output stored in objects which also contain unique model ID, SourceListID (SLID)+SourceID (SID) General parameters: GalPhotModel (config parameters,creation_date,…. SLID,SID,GPID) Why two objects?: practical reason:make post-run searching fast GalPhot run on one galaxy Parameters one ellipse: GalPhotEllipse (r,dr,flux,dflux,… SLID,SID,GPID)

  5. PhotZ example A sourcelist for each filter PhotZ run on one galaxy redshift parameters: PhotZData (z,dz,<z>,… SLID1,SID1,PhotZID) redshift parameters: PhotZData (z,dz,<z>,… SLID2,SID2,PhotZID) redshift parameters: PhotZData (z,dz,<z>,… SLID3,SID3,PhotZID) redshift parameters: PhotZData (z,dz,<z>,… SLID4,SID4,PhotZID) …………………………….. Why copy for each Sourcelist?: practical reason:make-post run searching fast

  6. Case B: starting from frames • Vodia/OmegaTranS: adding points to existing lightcurve VodiaLightCurvePoint Parameters single difference image (ap_phot,err_ap_phot,…. RegriddedFrame1,VodiaID) Vodia runs on one star VodiaLightCurvePoint Parameters single difference image (ap_phot,err_ap_phot,…. RegriddedFrame2,VodiaID) .………………….. VodiaLightCurve: (config,…,[RegriddedFrame1,RegriddedFrame2,…],VodiaID)

  7. Search examples • Give all GalPhotModels for source SID23 in SLID9: awe> q=(GalPhotModel.SLID==SLID9) & (GalPhotModel.SID==SID23) • Give all GalPhotEllipses for source SID23 in SLID9: awe> q=(GalPhotEllipse.SLID==SLID9) & (GalPhotEllipse.SID==SID23) • Give all GalPhotEllipses for GPID=GPID13: awe> q=(GalPhotEllipse.GPID==GPID13) • Give last-made GalPhotModel for source SID23 in SLID9: awe> q=(GalPhotModel.SLID==SLID9) & (GalPhotModel.SID==SID23) awe> lastmodel=q.max(‘GPID’)

  8. Summary • Two kinds of ways to connect analysis on reduced data sources to image data: • Case A: Via SourceLists • Case B: Via Regridded(/Reduced/Coadd) Further add-ons: • Planned:Favorite model flag • Possible: authorname in objects?

More Related