#--------------------------------------------------------------------------------- # Obtain image statistics #--------------------------------------------------------------------------------- # # in the viewer: # - Open image source2.continuum.fits, as a raster map # - Select a region # - use the "region panel" to obtain flux densities around the image # - use the "polygon icon" to obtain flux density for the whole galaxy # - obtain the rms: region outside the emitting region # #------------------ # in the command line: imstat # flux density of the whole image imstat(imagename = 'NGC1614_continuum.image') # flux density in a region (the most intense clump) imstat(imagename = 'NGC1614_continuum.fits', box='182,190,189,195') # Results are shown in the CASA log and returned as a dictionary in the terminal # these can be stored as variables and use later mystats=imstat(imagename = 'source2.continuum.fits', box='182,190,189,195') mystats['flux'][0] # obtain rms in a signal-free region mystats=imstat(imagename = 'source2.continuum.fits', box='25,25,100,100') mystats['rms'][0] #--------------------------------------------------------------------------------- # Source fitting #--------------------------------------------------------------------------------- # # in the viewer: # - select a region # - use the interactive 2D fitting icon # Results are shown in the CASA log # an output file can be created to save results # #------------------ # in the command line: imfit # Using similar region as before for imstat imfit(imagename = 'NGC1614_continuum.image', region='circle [ [ 185pix , 193pix] ,8pix ]') # Results shown in the CASA log and also in the terminal # Store the results in variables: myfit=imfit(imagename = 'source2.continuum.fits', region='circle [ [ 185pix , 193pix] ,8pix ]') myfit['results']['component0']['flux'] # NOTE: 'results' show the source sizes convolved with the beam: myfit['results']['component0']['shape']['majoraxis'] myfit['results']['component0']['shape']['minoraxis'] # while 'deconvolved' can show smaller "physical" sizes myfit['deconvolved']['component0']['shape']['majoraxis'] myfit['deconvolved']['component0']['shape']['minoraxis'] # save results information from the CASA log in a logfile imfit(imagename = 'source2.continuum.fits', region='circle [ [ 185pix , 193pix] ,8pix ]', logfile = 'myfit.txt') #--------------------------------------------------------------------------------- # Contour level maps #--------------------------------------------------------------------------------- # # in the viewer: # - use the "manage images" icon to change the view to contour # - open "display options" # Note the default values correspond to a fraction of the maximum peak in the image # - change the basic settings to show contours as a multiple of the rms (unit), with # first two contour levels to be -3 and +3 sigma (rms) # - with that contour continuum map, open the CO 6-5 image as a colour map (raster) # #------------------ # in the command line: imview # this is a useful command to create and save raster and contour maps # we use an example to obtain the same contour image: imview(contour={'file': 'NGC1614_continuum.image', 'levels': [-3, 3, 5, 10, 15, 20], 'unit': 0.0008}, zoom=3, out='ngc1614-continuum.png') imview(raster={'file': 'NGC1614_CO6-5.image', 'range': [-0.05, 0.35], 'colormap': 'Rainbow 2'}, zoom={'channel': 25, 'blc': [110,125], 'trc': [260,260]}) imview(contour={'file': 'NGC1614_continuum.image', 'levels': [-3, 3, 5, 10, 15, 20], 'unit': 0.0008}, raster={'file': 'NGC1614_continuum.image', 'range': [-0.0035, 0.018], 'colormap': 'Rainbow 2', 'colorwedge': True}, zoom={'blc': [110,125], 'trc': [260,260]}) #--------------------------------------------------------------------------------- # Image header: imhead #--------------------------------------------------------------------------------- # # Obtain basic information about the image # mode='summary' (default) will print out a summary of the image properties in the log imhead('NGC1614_continuum.image') imhead('NGC1614_CO6-5.image') # Note the frequency axis has shape between the continuum and line images # mode='list' prints out a list of the header keywords and values to the terminal imhead('source2.continuum.fits', mode='list') # which again, we can store in variable for latter use myhead=imhead('NGC1614_continuum.image', mode='list') myhead['beammajor'] myhead['beamminor'] # This can also be done by using mode='get' mybmaj = imhead('source2.continuum.fits',mode='get',hdkey='beammajor') mybmaj # imhead can also be used to modify header parameters, with mode='put' # This could be helpful to, e.g. modify the position center to overlay # with other images, etc.. # BUT use with caution: we *only* replace the current value of the header, # for any transformation on the image, e.g. modify coordinate system, # or velocity frame, etc, one needs to use other CASA tasks! # #--------------------------------------------------------------------------------- # Spectral images: the spectral profile tool #--------------------------------------------------------------------------------- # # in the viewer: # - Open image # - use the "animators panel" to explore the image in different channels # - select a region and open the spectral profile tool, and # explore panel options and line emission in different regions # - Line identification: go to "line overlays" # * select a region of the spectra to search for lines in splatalogue # * include the source velocity! # * it is possible to search for an specific molecule and filter by kind of source. # - Extract spectra: disk icon in the top panel # will create a txt file table with frequencies and intensities # NOTE the frequencies extracted are sky frequencies! # and that intensity scale may be wrong! # #------------------ # there are also tools for line identification in the command line: # slsearch and splattotable # # slsearch: it searches in splatalogue (default), following the selection options, e.g. slsearch(freqrange=[freq1,freq2], verbose=True) # verbose=True will print the search results in the CASA log # see other search options with inp slsearch # we can also create a table slsearch(outfile='mylines.tbl', freqrange=[freq1,freq2]) # This table can be explored with browsetable: browsetable('mylines.tbl') # shows more columns (energy levels, catalog source, etc.) not shown in the spectral # viewer search table # It is possible to search in an existing tbl, for an specific species, etc. e.g. slsearch(tablename = 'mylines.tbl', freqrange = [freq1,freq2], species = ['mymolecule'], verbose=True) # splattotable: creates tables from splatalogue files (Export CASA fields) splattotable(filenames = ['splatalogue.tsv'], table = 'splatalogue.tbl') # which can be latter searched for using slsearch # similar .tsv files can be prepared from other catalogues, # just be careful with the format! #------------------ # extract spectra in the command line: imval # simple example extracting spectra in one pixel xval=imval(imagename='NGC1614_CO6-5.image', box='184,165', chans='0~40') # type the following to see all the results xval # similar to other tasks, we can extract the quantity we are interested in # peak is at: xval['data'][17] # and the corresponding freq is: xval['coords'][17][3] # to see it in MHz xval['coords'][17][3]*1E-06 # NOTE it is still sky frequency! # but from the source velocity we can compute the frequency shift and apply # the imval command above can be scripted to extract the spectra for all # frequencies and different regions of the image #--------------------------------------------------------------------------------- # Focus on one line: data visualization #--------------------------------------------------------------------------------- # # multiple panels plot: # # - Open image # - open the "panel display options" # - select 3x3 panels, adjust the margings, and character size, etc. as needed # - move to select the best velocities to show using the channels animator, e.g. # around the central velocity of the source # # Spectral viewer: # - go back to one panel # - open the spectral profile tool # - select one or two regions to explore the spectra in both sources # NOTE: the higher angular and spectral resolution wrt the product images # #--------------------------------------------------------------------------------- # Focus on one line: line fitting #--------------------------------------------------------------------------------- # # in the viewer: spectral profile tool # - select a region and open the spectral profile tool # - adjust the velocity range to consider # - fit one gaussian --> check results in the opened window and the fitted profile # It is possible to save the output results checking the corresponding box # before performing the fit # - repeat, now selecting a region with a complex profile and try to fit two gaussians # Now in the viewer we see the fits for each and the total fit to the line # Note in the results window the different central velocities and widths # - It is also possible to include initial guesses for the line fit: # * double-click in the table and introduce by hand the numbers, or select # graphycally on the line profile # * or using the Estimates button # #------------------ # in the command line: specfit # # two-gaussian fit example specfit(imagename='NGC1614_CO6-5.image', box='178,159,191,172', chans='5~40', ngauss=2, multifit=False) # multifit=False, will average the axis pixels and do a single fit to that average profile # Fit results are shown in the CASA log and in the terminal as a dictionary. # it is also possible to save into a logfile specfit(imagename='NGC1614_CO6-5.image', box='178,159,191,172', chans='5~40', ngauss=2, multifit=False, logfile='myfit.txt') # multifit=True, allows to fit a profile along the desired axis at each pixel in the region. # NOTE that fitting a multiple gaussian could complicate the fitting, and initial estimates # might be necessary, even for one gaussian # It allows to save images of the obtained fitting results that can be opened in the viewer # Simple example: fit one gaussian in same box as previous, save velocity and width: specfit(imagename='NGC1614_CO6-5.image', box='178,159,191,172', chans='5~40', ngauss=1, multifit=True, center = 'NGC1614_CO6-5-fit.velo', fwhm = 'NGC1614_CO6-5-fit.width') # Now open the images .velo and .width in the viewer # there are many bad fits outside the emitting region, adjust the levels # (using the wedge values) for a better image # to solve this issue it might be necessary to include/exclude pixels (select a # threshold for pixels to be included or not in the fit) # #--------------------------------------------------------------------------------- # Focus on one line: position-velocity diagrams #--------------------------------------------------------------------------------- # # in the viewer: # - select in the cursor panel: "P/V tool" # - draw a line along the desired direction # - open the "regions panel" and go to the pV tab # - generate P/V will open a new viewer display with the pv diagram # #------------------ # in the command line: impv # # Example for NGC1614_CO6-5 impv(imagename='NGC1614_CO6-5.image', outfile='NGC1614_CO6-5_pv.image', chans='', mode='length', center= ['04h34m00.0s','-08d34m45.6s'], length='2.8arcsec', pa='90deg') # center can be obtained from the cursor panel # and length and pa from the pv tab in regions # open the obtained pv images in the viewer # #--------------------------------------------------------------------------------- # Focus on one line: moment maps #--------------------------------------------------------------------------------- # # in the viewer: # - Open the image NGC1614_CO6-5.image # - open the calculate moments/collapse tool # - select a large region in the image including all the emission # - in the collapse tool, select channels to collapse: 4450-4950 # - select moment to compute: moment 0 --> push collapse button # a new image will be created in the display # # Similarly, we can obtain the other moments... # - do moments 1, without any threshold # * note we don't see anything in the obtained moment image # open the display tool: the data range is too large # --> we need to set a threshold using includepix/excludepix # * explore values to use in includepix: some multiple of the rms # - do moment 2, # * start with same pixel values above # * if it looks a noisy try higher values # #------------------ # in the command line: immoments # # moment 0 map, no threshold: immoments(imagename = 'NGC1614_CO6-5.image', moments = [0], box = '130,135,235,240' chans = '5~55', outfile = 'NGC1614_CO6-5.mom0') # moment 1 and 2, with threshold: immoments(imagename = 'NGC1614_CO6-5.image', moments = [1,2], box = '130,135,235,240', chans = '5~55', includepix = [0.080,1000], outfile = 'NGC1614_CO6-5.mom') # outfile: If a single moment is chosen, the outfile specifies the exact name of the # output image. If multiple moments are chosen, then outfile will be used as the root # of the output filenames, which will get different suffixes for each moment. # open moment images in the viewer, move between them with the animators panel # change the moment0 map to contours to overly to the higher moment maps