Image Analysis with CASA - ESO

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specfit to perform spectral line fits in data cubes Spectral Line Fitting data averaged across a region (multifit=False) or on pixel by pixel basis (multifit=True) fit a Gaussian (poly=1, default) or polynomials (e.g. poly=6) can fit multi Gaussian (e.g. ngauss=3) but will need to input a guess file (estimates='guess.txt') The file should contain for each component: peak intensity, center, fwhm, optional fixed parameter string # peak intensity in map unit # center, fwhm in pixel # fourth input is any combination of pcf, indicating which parameter is to be kept constant the result of the fit can be a Python dictionary (as seen in slide about imstat): fitresults=specfit(imagename='my.image', region='region.rgn') Gaussian fits results (and their errors) can be written in images, named from input parameters: amp, amperr, center, centererr, fwhm, fwhmerr, integral, integralerr model and residual images can also be created (specify their names as input) 28
ToolKit For (very?) advanced users, image analysis tools: <strong>CASA</strong>>: ia. # then press TAB to get a compact list Display all 110 possibilities? (y or n) ia.__class__ ia.collapse ia.fromshape ia.moments ia.rotate ia.__delattr__ ia.continuumsub ia.getchunk ia.name ia.sepconvolve ia.__doc__ ia.convertflux ia.getregion ia.newimage ia.set ia.__format__ ia.convolve ia.getslice ia.newimagefromarray ia.setboxregion ia.__getattribute__ ia.convolve2d ia.hanning ia.newimagefromfile ia.setbrightnessunit ia.__hash__ ia.coordmeasures ia.haslock ia.newimagefromfits ia.setcoordsys ia.__init__ ia.coordsys ia.histograms ia.newimagefromimage ia.sethistory ia.__new__ ia.decompose ia.history ia.newimagefromshape ia.setmiscinfo ia.__reduce__ ia.deconvolvecomponentlist ia.imagecalc ia.open ia.setrestoringbeam ia.__reduce_ex__ Ia.deconvolvefrombeam ia.imageconcat ia.outputvariant ia.shape ia.__repr__ ia.done ia.insert ia.pbcor ia.statistics ia.__setattr__ ia.echo ia.isconform ia.pixelvalue ia.subimage ia.__sizeof__ ia.fft ia.isopen ia.putchunk ia.summary ia.__str__ ia.findsources ia.ispersistent ia.putregion ia.toASCII ia.__subclasshook__ ia.fitcomponents ia.lock ia.rebin ia.tofits ia.adddegaxes ia.fitpolynomial ia.makearray ia.regrid ia.topixel ia.addnoise ia.fitprofile ia.makecomplex ia.remove ia.torecord ia.boundingbox ia.fromarray ia.maketestimage ia.removefile ia.toworld ia.brightnessunit ia.fromascii ia.maskhandler ia.rename ia.transpose ia.calc ia.fromfits ia.maxfit ia.reorder ia.twopointcorrelation ia.calcmask ia.fromimage ia.miscinfo ia.replacemaskedpixels ia.type ia.close ia.fromrecord ia.modify ia.restoringbeam ia.unlock 29
Page 1 and 2: Image Analysis with CASA Sebastien
Page 3 and 4: View images Extract information fro
Page 5 and 6: Working with images: General tasks
Page 7 and 8: Viewer CASA> viewer and then use th
Page 9 and 10: Header hdkey for reference beammaj
Page 11 and 12: Defining box / region - Command lin
Page 13 and 14: Image Statistics imstat : calculate
Page 15 and 16: Mathematical operations on images i
Page 17 and 18: Smooth images imsmooth - Image conv
Page 19 and 20: If only 1 Gaussian component (defau
Page 21 and 22: Working with spectral data cube
Page 23 and 24: Extract a spectrum - Script mode Us
Page 25 and 26: Moments Images Sometimes, informati
Page 27: Spectral Lines Search 1) Use SPLATA

Image Analysis with CASA - ESO

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