SoFiA Tutorial
Contents
1. Input Data Products Files and settings Data cube fhome SoFiA_Test sofiatestcube Fits E Select Mask cube Lom Select Weights cube E Select Weights Function Figure 2 Selecting an input data cube for source finding 3 2 Selecting a source finding algorithm We will skip the Input Filter tab at this point and proceed straight to the Source Finding tab to select and set up a source finding algorithm You will note that the Smooth Clip Finder is already selected by default see Fig 3 and we will use this algorithm in our example as well The S C finder works by iteratively smoothing the data cube both spatially and spectrally on multi ple scales and including from each iteration all pixels whose flux is above a given threshold Sev eral parameters of the algorithm can be set in the GUI by the user SoFiA Tutorial 3 Setting up a basic source finding run Threshold This defines the relative detection threshold to be used in each smoothing iteration It is given in multiples of the rms noise level o of the data The default setting is 6 which is rather conservative so let s change this to a slightly lower value of 5 o by typing 5 0 into the Threshold field Edge mode This defines how the smoothing kernel should treat pixels near the edges of the cube The default setting is constant which means that pixels outside the data cube are as sumed to be zero for the purpose of convolu2. row The Output tab should then look as in Fig 6 below Input Input Filter Source Finding Merging Farameterisation Output Filter Output Output Data Products Files and settings Base name Output directory E Select Source catalogue W ASCII W VO table Data products ered cube M Mask M9 Mom 0 amp Mom 1 Cubelets Compression Enable Overwrite Files 3 Enable Fa Output Parameters Figure 6 View of the output tab with selected source catalogues and data products 3 6 Running the source finding pipeline Once we are satisfied with all our settings we can launch the pipeline The easiest way is to click the Run Pipeline button in the tool bar or alternatively the corresponding item in the Pipe line section of the menu bar The pipeline should then start and produce all kinds of status mes 3 Setting up a basic source finding run SoFiA Tutorial SoFiA Source Catalogue ai a x geo z geo xX y z x min a 113 536 174 377 23 092 113 408 174 465 91 654 104 72 38 188 93 419 103 812 114 692 20 742 32 854 114 151 20 91 134 263 18 573 79 8096 135 18 18 265 Sort by id bd descending Reload E Close Figure 7 Displaying the output catalogue with the SoFiA catalogue viewer sages in the Pipeline Messages window of the GUI If successful the pipeline will print the mes sage Pipeline finished with exit code 0 at the end of the run in green colour and no
3. SoFiA Tutorial T Westmeier N Giese R Jurek J M van der Hulst Version 1 2 07 12 2015 Table of Contents 1 Introduction 2 Getting started 2 1 Obtaining the SoFiA test data ibe 2 2 Launching SoFiA aoe 3 Setting up a basic source gt finding run 3 1 Selecting the input data cube PE 3 2 Selecting a source finding algorithm sprite begs eee hen E S E 3 3 Assigning detected pixels 10 SOUICES nan sansauwacwsdvanninaain cieesweuraneacdwansubusentiareweememenna 3A S rece parameterisaHon SENINE S avacecartuaraorensersvasanadeqwetacseescnsqeasnusesiaadoriebesacamaen 3 5 Sele CHS ouput data EOC NCS seeserscrrorsirerer ner naan nae E E 3 6 Running the source finding pipeline s u uu us sse o se o ae o ae o me oe oo o ae o a a 0 oe o oe o an e ae oe o be o an b be oe e oe e an a a a e ee e ae o an a ae e e e eee PADER TAG TOG a E E E E E anne EE 3 8 Next steps 4 Advanced e INES 4 1 Other source Mading algorithms 4 2 Improving completeness and reliability o PUMENG 1A LORI ATION oganconsanucinananeems cence E E E E E E E EE NIN WD OB SB KBD KD KH e m m m OA wmm CO O 1 Introduction The SoFiA software is a versatile stand alone source finding pipeline written in Python and C The name SoFiA stands for Source Finding Application and is a reference to the Greek word for wisdom cog a SoFiA was originally written for the automated detection of the HI emission of galaxies
4. C finder with a threshold of 50 left 30 centre and 3 o reliability threshold of 0 9 right Note the great improvement in re liability in the latter case as well as the merging of the two halves of the edge on galaxy near the southern edge of the cube into a single source Fortunately SoFiA comes to the rescue with a powerful algorithm that allows us to determine the reliability of each detected source in a statistical way This Reliability Calculation method can be found under the Parameterisation tab in the GUI The algorithm makes the fundamental as sumption that all astronomical signal in the data cube will have positive flux whereas all negative signals must be due to statistical noise In addition the assumption is made that the noise is sym metric about zero i e the flux distribution of positive noise peaks is the same as that of negative noise peaks Based on these assumptions the algorithm then determines the density of positive and negative sources in an N dimensional source parameter space around the position of each positive detection and uses these to calculate the probability of the positive signal being a genuine source as opposed to a noise peak Of course this method will only produce meaningful results if enough positive and negative noise peaks have been detected to ensure that the calculated probability is statistically significant Therefore the reliability calculation algorithm will usually only work
5. but the pipeline is general enough to be suitable for a wider range of applications The purpose of this tutorial is to provide a basic set of instructions on how to use the different components of SoFiA in an effective way This tutorial is not likely to remain static but will pre sumably expand and improve over time Note SoFiA s graphical user interface comes with its own built in help browser with detailed infor mation of how to set up and run SoFiA It can be accessed by selecting SoFiA User Manual from the Help item in the menu bar 2 Getting started SoFiA Tutorial 2 Getting started We assume that you managed to install SoFiA on your computer including the graphical user 2 1 Obtaining the SoFiA test data cube The examples in this tutorial use the dedicated SoFiA test data cube which is available from the ply download the test data set and extract its content into a new folder following the instructions on the wiki page The test data cube named sofiatestcube fits is a small HI cube that contains detectable emission from four galaxies It also comes with examples of SoFiA output data products but these will usually get overwritten again by the examples shown in this tutorial 2 2 Launching SoFiA SoFiA operates by reading in a so called parameter file that contains all the parameter settings required to run the different modules of the pipeline Parameter files are really just simple text fi
6. 01 8 12h0o Right Ascension J2000 Right Ascension J2000 Figure 11 Application of the 2D 1D wavelet decomposition filter on a channel map of the SoFiA test data cube left creates a noise free map of wavelet components right A simple threshold finder can then be applied to extract the three galaxies labelled here with arbitrary numbers finder designed to apply a simple flux threshold to the data Under the Source Finding tab we enable the threshold finder and disable the S C and CNHI finders In the threshold finder we then set the clip mode to absolute and the threshold to 0 0005 i e 0 5 mJy In addition the Min size X Y Z settings under the Merging tab should be set to a value of 10 Next we run the source finding pipeline again and if everything is correctly set up SoFiA should detect all three galaxies present in the data cube again breaking up the edge on galaxy near the southern edge of the cube into two separate detections hence four detections overall Another interesting thing to do is to take a look at the actual reconstructed cube This can be done by checking the Filtered cube option in the Data products settings of the Output Data Products section under the Output tab Rerunning the pipeline should then produce an additional file called sofiatestcube_filtered fits that contains a copy of the reconstructed cube A single channel map from that cube is shown in the right han
7. and set the threshold to 0 9 which should be its default value We will leave all other parame 14 SoFiA Tutorial 4 Advanced techniques N J N log SNRmax log SNRmax 0 8 0 8 0 6 0 6 Mca he oe eee o KA e 0 4 Ap o ar LS 2 0 D 3 0 35 4 0 4 5 LS 2 25 30 35 40 45 5O log NRvox log SNRsum Figure 13 Two projections of the three dimensional parameter space in which SoFiA calculates the re liability of detections Sources with positive flux are shown in blue negative sources in red The three isolated blue dots corresponding to the three galaxies in the data cube populate a highly reliable re gion of parameter space where there are no negative signals ters at their default values This will calculate the reliability of each detection and then remove all detections from the catalogue whose reliability is found to be below 90 Running the pipeline again with the reliability calculation turned on will now result in a catalogue of only 3 sources corresponding to the three galaxies contained in the cube Note that all false positives got re moved from the catalogue right hand panel of Fig 12 and Fig 13 Most importantly thanks to our lower detection threshold the two halves of the edge on galaxy near the southern edge of the cube have now been merged into a single object Note The reliability calculation module offers on option to produce diagnostic plots in PDF format that can be used to inspe
8. error messages printed in red colour should have occurred along the way although there may be a few warnings also printed in red in particular about the automatic overwriting of output files Alternatively the pipeline can be launched on the command line rather than through the GUI This option is useful for running SoFiA repeatedly on a large set of data cubes or running SoFiA as part of a script To do so simply open a terminal window change into the directory where the SoFiA parameter file is stored and then launch the pipeline by calling sofia_pipeline py lt parameter_file gt where lt parameter_file gt is the name of the parameter file that you wish to process e g SoFiA_ Tutorial Section_3_S C par for the file associated with this section of the tuto rial make sure that the path to the input data cube defined by the parameter import inFile is the correct one on your computer There is no practical difference in running SoFiA via the GUI or on the command line the GUI simply calls the command line script whenever you push the Run Pipeline button 3 7 Checking the results If the Output directory field in the Output tab is left blank all output files will automatically be written to the same directory in which the input data cube is located Listing the contents of that directory should now show the following additional files sofiatestcube cat ascil sofiatestcube_ cat xml sofiatestcube mask fits sof
9. format Simply select View Catalogue from the Analysis section of the menu bar to display the catalogue Fig 7 3 Setting up a basic source finding run SoFiA Tutorial With our settings as described above SoFiA should have detected four sources in the test data cube as shown in Fig 7 and 9 In the mask cube sofiatestcube_mask fits all pixels iden tified as part of a source are marked with the respective source ID number as listed in the cata logue Fig 8 This allows the location of individual sources from the catalogue to be identified based on their ID Finally the moment 0 and 1 images sofiatestcube_mom0 fits and sofiatestcube_mom1 fits show the integrated flux and velocity field of all detected sources Fig 9 Mask cubes and moment maps are provided as FITS files and can be viewed in 3 8 Next steps In our example above SoFiA detected four sources in the test data cube Visual inspection of the data cube reveals that sources 3 and 4 are not actually two different objects but rather the two halves of a single rotating edge on disc galaxy Due to the steep rotation curve however the emission near the systemic velocity of that galaxy is so faint that it fell below the detection threshold used in our example and the galaxy got broken up into two separate sources as a result In Section 4 2 we will introduce ways of decreasing our detection threshold without increasing the number of false detections due to noi
10. ault set of kernels for now The S C finder settings should now look as in Fig 3 below Input Input Filter Source Finding Merging Parameterisation Output Filter Output Smooth Clip Finder X Enable Threshold 5 0 Kernels 0 0 0 b 0 0 3 b 0 O 7 b 0 0 15 b L 3 3 0 b J 3 3 3 b 3 3 7 b 3 Edge mode Sosiaal 3 15 b L 6 6 O b LL 6 6 3 b LL 6 6 7 b LL 6 6 15 b RMS mode Gaussian Fit to negative Fluxes Kernelunits Pixels Figure 3 The Smooth Clip Finder section of the Source Finding tab 3 3 Assigning detected pixels to sources The source finder will detect all pixels above the given detection threshold but these pixels will still need to be assigned to individual sources This step is set up in the fourth tab Merging There are two basic settings here 3 Setting up a basic source finding run SoFiA Tutorial Radius X Y Z These define the radii across which detected pixels are merged into the same source in the three dimensions of the cube They all default to 3 but we will set all of them to 1 here to ensure that only neighbouring connected pixels are considered to be part of the same source whereas unconnected pixels are treated as separate sources Min size X Y Z These define the minimum required size of a source in each of the three di mensions after merging Any collection of significant pixels that does not f
11. ct the distribution of positive and negative sources in parameter space see Fig 13 for an example This can be helpful in assessing whether there are enough positive and negative detections for accurate reliability determination The higher the density of nega tive signals in parameter space the more accurate the reliability calculation will be To enable diagnostic plots simply activate the corresponding check box in the Reliability Calculation section of the Parameterisation tab in the GUI 15 5 Further information SoFiA Tutorial 5 Further information The SoFiA test data set comes with its own example parameter file that makes use of some of the more sophisticated algorithms in SoFiA to improve the source finding and parameterisation results Feel free to load that parameter file into the GUI and play around with its settings Note that you will need to modify the path of the input data cube in the Input tab first so it points to the correct location of the cube on your machine Some of the additional methods applied in the example parameter file are explained in Section 4 More information about SoFiA can be found on the SoFiA GitHub site at The website contains the latest version of the SoFiA source code installation requirements and in structions a trouble shooting page addressing a few commonly encountered installation prob lems and a wiki with detailed information about the individual parameter set
12. d panel of Fig 11 and illustrates the capability of the 2D 1D wavelet algorithm to suppress noise in a data cube and highlight the underlying source emission on larger spatial and spectral scales Finally it should be noted at this stage that the 2D 1D wavelet algorithm implemented in SoFiA has not yet been optimised and currently occupies a large amount of memory about 40 times the size of the input data cube Improving the algorithm s memory footprint is work in progress 4 2 Improving completeness and reliability The aim of any source finding effort is to detect as many sources as possible right down to the sta tistical noise level of the data cube However when decreasing the detection threshold to pick up fainter sources we will also inevitably increase the number of false positives most of which will be noise peaks or signals from radio frequency interference In other words increasing the com pleteness of our catalogue will at the same time decrease its reliability 13 4 Advanced techniques SoFiA Tutorial 62 20 62 20 62 20 62 10 62 10 62 10 Declination J2000 Declination J2000 Declination J2000 62 00 62 00 62 00 ietoga ie ge Teroa ite 0 je 9a 8 jietos 1202m 12 01 12700 121043 12503 125pm ehga fe 00 Right Ascension J2000 Right Ascension J2000 Right Ascension J2000 12h94 Figure 12 Moment 0 maps of the SoFiA test data cube after running the S
13. efine the minimum and maximum size of the spectral regions to be tested The maximum scale parameter can be set to 1 in which case it defaults to half the size of the spectral axis We will explicitly set both to 10 and 25 respectively Median test If enabled the CNHI finder will additionally require all regions identified as possi ble sources to have a median greater than that of the remaining data We will leave this option enabled which is the default setting The CNHI Finder section should now look as shown in Fig 10 In addition to these settings we also need to modify some of the settings in the Merging tab from those established in Sec tion 3 3 Specifically we need to increase the values of the Min size X Y Z parameters from 5 to 8 We then run the pipeline again and SoFiA should detect all four sources that were also found by the S C finder run described in Section 3 As noted before the CNHI finder uses statistical methods to detect sources Its different settings are therefore less intuitive and some level of experimentation is usually required to optimise its performance It should also be noted that the SoFiA test data cube is not a particularly suitable data set for this algorithm because the galaxies contained in the cube are spatially extended whereas the CNHI finder works best for sources that are spatially unresolved or only marginally resolved such as galaxies at higher redshift 11 4 Ad
14. filters to be run on the data cube prior to source finding Source Finding Selecting and setting up the source finding algorithm to be used Setting up how detected pixels in the cube are merged into sources arameterisation Setting up how the observational parameters of the detected sources are extracted and measured Output Filter Filtering the source catalogue by defining allowed ranges of observational parameters Output Selecting the desired output data products and parameters e g source cat alogues moment maps etc In the next section we will step through these tabs one by one and demonstrate how to set up a simple source finding run on an HI data cube This tutorial is accompanied by several example parameter files that contain the parameter settings for each of the examples presented in the following sections These files can be obtained and executed either through the GUI or alternatively on the command line Note that prior to ex ecuting the files the input data cube path will need to be changed in each file to point to the ac tual location of the SoFiA example cube on your computer Note Never rely on SoFiA s default settings While SoFiA does provide default settings for all available parameters any serious source finding effort will require these settings to be modified and fine tuned to the specific data cube and problem Relying on the default settings will almost certainly result in sub optimal results and a sou
15. iatestcube mom0 fits sofiatestcube mom1 fits SoFiA Tutorial 3 Setting up a basic source finding run Velocity 1168 02 km s Velocity 1168 02 km s 62 20 62 20 X 462 10 S 62 10 c c O O BE He wo wo E E ep o I amp 62 00 a 6e 00 128904 12893 12 902 125017 12700 t2 04 12 08 12 02 12 01 12 00 Right Ascension J2000 Right Ascension J2000 Figure 8 An individual channel map of the test data cube left and the corresponding channel map from the output mask cube produced by SoFiA right Detected sources are labelled with their ID 62 20 62 20 aa oO N Bepi X 62 10 X 62 10 5 gt O Q i g 5 62 00 A 62 00 z 12904 12 03 12 02 12 01 12 00 itoan Joaga 12m2 iim agoa Right Ascension J2000 Right Ascension J2000 Figure 9 Moment 0 left and 1 right images produced by SoFiA from the test data cube showing the four sources detected by SoFiA labelled with their ID using the settings described in Section 3 If the Base name field in the Output tab is left blank all output files produced by SoFiA will by default use the same name as the input cube with an additional extension to indicate the nature of the data product The source catalogue can either be viewed in a text editor ASCII format or in the built in catalogue viewer provided by SoFiA XML
16. les and can either be create by hand or much more conveniently using the GUI In order to cre Analysis Settings Help F Ll of amp he Pipeline Messages 0 Input Input Filter Source Finding Merging Parameterisation Output Filter Output Ej Input Data Products a Files and settings Data cube Low Select Mask cube Lamy Select Weights cube me Select Weights Function Ej Subcube Ey Flagging z Catalogue based Source Finding Figure 1 View of the main window of SoFiA s graphical user interface SoFiA Tutorial 2 Getting started ate your first parameter file and run SoFiA on the test data cube simply open a terminal window and navigate to the directory where the test data cube is stored gt cd location of sofiatestcube fits Then launch SoFiA by typing gt SOFIA amp This should open the GUI and you should see the SoFiA main window approximately as shown in Fig 1 Note that SoFiA will adopt the native window design scheme of your desktop manager and hence will seamlessly integrate into the look amp feel of your system The example in Fig 1 shows the appearance on a Kubuntu Linux system under KDE The bottom half of the window contains seven different tabs in which the settings for the source finding pipeline can be chosen These are Input Setting up input data products and related information e g the data cube to be searched P Input Filter Setting up any
17. on tab with default settings SoFiA Tutorial 3 Setting up a basic source finding run This will tell SoFiA to measure standard observational parameters for each source including source position radial velocity integrated flux etc 3 5 Selecting output data products We will skip the Output Filter tab which has not yet been enabled and move straight to the last tab named Output to select the output data products we would like SoFiA to create There is a wide range of settings available here but for now we will only focus on the two most important output files source catalogues and data products Note By default SoFiA will write all output files into the same directory as the input data cube and all file names will be based on the name of the input data cube with additional extensions that indicate the nature of the data product This behaviour can be changed by specifying the Out put directory and Base name settings in the Output tab Creation of a source catalogue in ASCII format is already switched on by default but in addition let us also also create a VO compliant catalogue in XML format by checking the VO table box in the Source catalogue row The XML catalogue can later be read into any VO compliant analysis cube as well as moment 0 and 1 images showing all detected sources To enable these simply check the Mask Mom 0 and Mom 1 boxes in the Data products
18. r computer We will first need to set up the 2D 1D wavelet filter found under the Input Filter tab After en abling the filter we then apply the following settings Threshold This is the relative threshold in units of the rms noise level for wavelet components to be included in the reconstructed cube We will set it to 5 0 here which is its default value Iterations The number of iterations in the reconstruction process Again we will leave this at its default value of 3 Scale XY Z This defines the number of spatial spectral scales to be used in the reconstruction process Leaving both at their default value of 1 will tell SoFiA to automatically determine the optimal number of scales based on the cube dimensions Positivity We will enable this to ensure that only positive wavelet components are added to the reconstructed cube Otherwise both positive and negative signals whose absolute value is above the threshold will be included With the wavelet decomposition filter set up we will next have to choose and set up a source finding algorithm to run on the reconstructed cube The most obvious choice is SoFiA s threshold 12 SoFiA Tutorial 4 Advanced techniques Velocity 1168 02 km s Velocity 1168 02 km s 62 20 62 20 S S S 5 62 10 S 62 10 z O O 43 kE wo 49 is D 2 2 62 00 2 62 00 42 94 12 03 12 02 12 01 12 00 12 04 12 03 12 02 12
19. rce catalogue of limited completeness or relia bility 3 Setting up a basic source finding run SoFiA Tutorial 3 Setting up a basic source finding run This section illustrates how to run SoFiA on the HI data cube provided for testing purposes on the directly loaded into SoFiA by selecting Open from the File entry in the menu Alternatively all parameters can be set manually by following the instructions below Note In order to get more information about a particular parameter setting ings Help you can first click on the What s this icon in the tool bar or the cor Me Re responding item in the help section of the menu bar and then on the corresponding field or button This should open a tool tip with some ba a sic information about the parameter and its possible values 3 1 Selecting the input data cube Navigate to the first tab Input In the Input Data Products section click on the Select button next to the Data cube field This will open a file selection window in which you can se lect and open the input data cube named sofiatestcube fits The full path of the data cube should now appear in the text field as shown below in Fig 2 In addition the small icon next to the section heading should have turned from red to green indicating that an input data cube has been specified Input Input Filter Source Finding Merging Parameterisation Output Filter Output
20. sa tion output 4 1 Other source finding algorithms While we have only used the S C finder so far SoFiA offers several alternative source finding al gorithms that may be more suitable to some problems and data sets Characterised Noise HI CNHI finder The CNHI finder is best suited for HI data cubes in which the sources are resolved in the spectral words instead of looking for sources the CNHI finder tries to identify regions that don t appear to be purely noise In order to use the CNHI finder all we need to do is navigate to the Source Finding tab in SoFiA disable the Smooth Clip Finder module and enable the CNHI Finder module Again there are several settings enabling us to control the CNHI finder These are provided in the file point to the location of the cube on your computer Given the statistical nature of the algorithm most of these parameters are somewhat less intuitive than those of the S C finder Probability This defines the probability as determined from Kupier s test below which the data are considered to be inconsistent with pure noise and hence treated as a source Useful values typically are in the range of 10 to 10 We will set this to a value of 1e 7 here Quality This is the Q value of Kuiper s test a heuristic parameter that is used to assess the accu racy of the probability calculated from Kuiper s test We will set this to a value of 5 0 Min Max scale These d
21. se at the same time This will lead to a better complete ness of our source catalogue without loss in reliability and will also address the issue of edge on galaxies being broken up into two separate detections as a result of their fast rotation We invite you at this stage to play around with the different settings in SoFiA to explore what ef fect they have on the source finding results For example what happens if you decrease the detec tion threshold of the S C finder from 5 to 3 o What effect does it have if the merging radii and source size requirements in the merging step are changed Playing around with these settings is easy simply change them as desired and then run the pipeline again to update the results and output files Note When setting up and running SoFiA from within the GUI a temporary parameter file will be created in the current directory called SoFiA session and the pipeline will read its set tings from that file If you wish to permanently keep the current set of settings defined in the GUI e g to rerun SoFiA on the same data cube in the future you will need to save the set tings by clicking on Save or Save as in the menu or tool bar 10 SoFiA Tutorial 4 Advanced techniques 4 Advanced techniques In this section we will introduce a few of the more sophisticated techniques and algorithms of fered by SoFiA for the purpose of improving the quality of the source finding and parameteri
22. tings in SoFiA SoFiA also comes with its own internal help system and build in user manual accessible through the Help menu of the graphical user interface A printable PDF file of the user manual can be obtained from the SoFiA wiki Lastly the details of SoFiA s philosophy and implementation are described in the peer reviewed SoFiA paper published in the Monthly Notices of the Royal Astronomical Society Should you find SoFiA useful and decide to use it in your own research we would appreciate a reference to the SoFiA paper in all publications resulting from that research 16
23. tion with the kernel We will leave this as is for now RMS mode The S C finder will automatically measure the rms noise level of the data to convert the relative threshold set by the user to an absolute flux threshold The RMS mode setting al lows us to choose which algorithm should be used for measuring the noise The default setting is to fit a Gaussian function to the negative side of the flux histogram assuming that all nega tive signals in the data cube are due to noise This is usually the most robust algorithm but it could fail if there is significant source emission with negative flux e g extensive HI absorption or negative sidelobes In such cases the median absolute deviation might be a better choice The third option the standard deviation is the fastest of the three methods but it is not partic ularly robust and will only work if the entire cube consists of essentially noise Kernel units This defines whether the smoothing kernels are provided in pixel or world coordi nates We will leave it as is i e pixel Kernels Here we can define a list of spatial and spectral smoothing kernels to be used by the S C finder In each kernel the first two numbers specify the FWHM of the Gaussian used for spatial smoothing while the third number specifies the width of the spectral smoothing kernel The spectral kernel can be either Gaussian g or boxcar b default as specified by the fourth parameter We will keep the def
24. ulfil the size require ments will be discarded This is to ensure that signals such as noise peaks are filtered out and don t end up in the final source catalogue The defaults settings are 3 and 2 for the spatial and spectral size respectively As the sources in our test data cube are all well resolved we will in crease the settings for all three dimensions to 5 meaning that any of our sources will need to be at least five pixels across both spatially and spectrally The Merging tab should now look as in Fig 4 below _input Input Filter Source Finding Merging Parameterisation Output Filter Output F Merging of Detections b x Enable Radius X 1 Radius 1 Radius Z 1 Min size Xi 5 Min size 5 lale die ah ale ale ale Min size Z 5 Figure 4 View of the merging tab after changing the default settings 3 4 Source parameterisation settings In the fifth tab Parameterisation we can choose the source parameterisation settings pro vided by SoFiA Note that source parameterisation is already enabled by default and for now we will leave all other settings as they are The Parameterisation tab should then look as in Fig 5 Input Input Filter Source Finding Merging Parameterisation Output Filter Output Source Parameterisation Enable Optimise mask ellipse Optimise mask dilation Fit Busy Function Ej Reliability Calculation Figure 5 View of the parameterisati
25. vanced techniques SoFiA Tutorial 3 CNHI Finder X Enable Probability 12 7 Quality 5 Min scale 10 Max scale 25 dh ae Median test 8 Enable Verbosity Minimal i Figure 10 Settings of the CNHI finder used in the example in Section 4 1 2D 1D wavelet decomposition Another useful source finding method implemented in SoFiA is based on decomposition of the the spatial and spectral wavelet scales separately to account for the fact that the spatial extent of HI sources often differs from their spectral extent in terms of the number of pixels channels cov ered by the source hence the name 2D 1D wavelet decomposition referring to two spatial di mensions and one spectral dimension The 2D 1D wavelet decomposition algorithm does not constitute a source finder as such but is rather implemented as an input filter in SoFiA Hence it is found under the Input Filter tab in the GUI The algorithm essentially decomposes the cube into wavelet components on different scales and then reconstructs the entire cube by only including significant signal from the individ ual wavelet components This will generally get rid of most of the image noise but retain signal from sufficiently bright sources in the field see Fig 11 A simple threshold source finder can then be used to extract sources from the reconstructed cube The settings used in this example are pro input file path to point to the location of the cube on you
26. with very low detection thresholds of typically 3 o and lower The great advantage however is that we can use the calcu lated reliabilities to filter out all detections with low reliability from our catalogue and hence pro duce a much more reliable and complete source catalogue down to low flux detection thresholds Let s see how well the algorithm works by picking up our source finding example from Section 3 again As you may remember one of the galaxies got broken up into two separate sources in that example left hand panel of Fig 12 so let s see if we can rectify this issue by decreasing our de tection threshold without picking up any false positives at the same time The settings for this ex member to change the input file path to point to the location of the cube on your computer In our original parameter settings from Section 3 we first need to change the threshold of the S C finder from 5 0 to 3 0 If we now run the pipeline again with the lower threshold the number of detections in the final catalogue will increase dramatically from 4 to 71 A quick in spection of the moment images produced by SoFiA reveals that the overwhelming majority of these are false detections caused by noise peaks central panel of Fig 12 although some addi tional extra planar gas associated with the largest galaxy in the field is also detected Now we switch on the Reliability Calculation module in the Parameterisation tab of the GUI
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