CLASS tutorials. Collected works. Jérôme PETY, Sébastien BARDEAU, & Pierre GRATIER. 8 th IRAM 30m Summer School Sep , 2015, Pradollano

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1 CLASS tutorials Collected works Jérôme PETY, Sébastien BARDEAU, & Pierre GRATIER 8 th IRAM 30m Summer School Sep , 2015, Pradollano

2 CLASS tutorial I. Basics Sébastien BARDEAU (IRAM/Grenoble) on behalf of the CLASS developers J. Pety, S. Guilloteau 8 th IRAM 30m Summer School Sep Sep , Pradollano

3 Need help? GILDAS web page: CLASS documentations and cookbooks: Widget>Help>Class>... Online help: LAS> HELP! Summary of all commands, gathered by language... LAS\ ACCUMULATE ASSOCIATE AVERAGE BASE BOX CATALOG CONSISTENCY COPY DROP DUMP EXTRACT FILE... LAS> HELP LAS\! (with backslash) Language help with short command description LAS\ Command Language Summary ACCUMULATE Add R and T observation. ASSOCIATE Add an Associated Array to the R observation AVERAGE Average all the observations of the current index.... LAS> help average! Command help LAS\AVERAGE [/RESAMPLE [NX Xref Xval Xinc Unit]] [/NOCHECK [SOURCE POSITION LINE SPECTROSCOPY CALIBRATION]] Average all the spectra of the current index using the current weighting function (see SET WEIGHT).... LAS> help average /resample! Command + subtopic help... Helpdesk (Questions? Comments? Bug reports?): gildas@iram.fr CLASS tutorial S. Bardeau & J. Pety, 2015

4 Data exploration: I. What does the file contain? LAS> file in demo LAS> find LAS> list Current index contains: N;V Source Line Telescope Lambda Beta Sys Sca Sub ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq ;4 B CO(1-0) 30M-V02-B Eq LAS> Too many information. CLASS tutorial S. Bardeau & J. Pety, 2015

5 Data exploration: I. What does the file contain? LAS> list /scan... B CO(1-0) 30M-V02-B : Eq B CO(1-0) 30M-V01-A : Eq B CO(1-0) 30M-V02-B : Eq B CO(1-0) 30M-V01-A : Eq B CO(1-0) 30M-V02-B : Eq B CO(1-0) 30M-V01-A : Eq B CO(1-0) 30M-V02-B : Eq B CO(1-0) 30M-V01-A : Eq B CO(1-0) 30M-V02-B : Eq B CO(1-0) 30M-V01-A : Eq B CO(1-0) 30M-V02-B : Eq B CO(1-0) 30M-V01-A : Eq B CO(1-0) 30M-V02-B : Eq B CO(1-0) 30M-V01-A : Eq LAS> One line per scan and front-end/back-end combination CLASS tutorial S. Bardeau & J. Pety, 2015

6 Data exploration: I. What does the file contain? LAS> list /scan /brief Current index contains: 9608: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 146 LAS> Just the list of scans and the number of dumps per scan. CLASS tutorial S. Bardeau & J. Pety, 2015

7 Data exploration: I. What does the file contain? LAS> list /toc equivalent to LAS> list /toc source line telescope Current index contains: Number of sources... 1 B (100.0%) Number of lines CO(1-0) 8614 (100.0%) Number of backends M-V01-A ( 50.0%) 30M-V02-B ( 50.0%) Number of setups... 2 B CO(1-0) 30M-V01-A ( 50.0%) B CO(1-0) 30M-V02-B ( 50.0%) LAS> Default table of contents. CLASS tutorial S. Bardeau & J. Pety, 2015

8 Data exploration: I. What does the file contain? LAS> list /toc observed scan Number of observation dates 1 12-SEP (100.0%) Number of scans ( 1.7%) ( 1.7%) ( 1.7%) ( 1.7%) ( 1.7%) ( 1.7%) ( 1.7%)... Number of setups SEP ( 1.7%) 12-SEP ( 1.7%) 12-SEP ( 1.7%) 12-SEP ( 1.7%) 12-SEP ( 1.7%) 12-SEP ( 1.7%) 12-SEP ( 1.7%)... LAS> Customized table of content. CLASS tutorial S. Bardeau & J. Pety, 2015

9 Data exploration: II. Is the data set in the current index consistent? LAS> set nomatch! OTF data => disable consistency on spectra positions LAS> consistency Consistency checks: Checking Data type and regular x-axis sampling Checking Source Name Checking Position information Leaving Offset position Checking Line Name Checking Spectroscopic information Checking Calibration information Reference spectrum: Source Name : B Coordinate System : EQUATORIAL Proj. Center (rad): lambda , beta , tolerance 4.8E-08 Line Name : 12CO(1-0) Frequency (MHz) : rest E+03, resol 3.906E-02, offset 0.000E+00 Velocity (km/s) : resol E-01, offset E+01 Alignment (chan) : tolerance 10.0% Calibration : beeff 0.950,gain W-CONSISTENCY, Obs #74 differs. Inconsistent: W-CONSISTENCY, F range (left) : E+05, E+05 (-2.56E+02 channels) W-CONSISTENCY, F range (right): E+05, E+05 (-2.56E+02 channels) W-CONSISTENCY, V range (left) : E+02, E+02 (-2.56E+02 channels) W-CONSISTENCY, V range (right): E+02, E+02 (-2.56E+02 channels) E-CONSISTENCY, Index is inconsistent Inconsistent spectroscopic information in index. CLASS tutorial S. Bardeau & J. Pety, 2015

10 Data exploration: II. Is the data set in the current index consistent? LAS> consistency W-CONSISTENCY, Already checked Spectroscopic information:inconsistent Check not repeated (it avoids long waiting time) CLASS tutorial S. Bardeau & J. Pety, 2015

11 Data exploration: II. Is the data set in the current index consistent? LAS> find /tel 30M-V01-A100 LAS> consistency Consistency checks: Checking Data type and regular x-axis sampling Checking Source Name Checking Position information Leaving Offset position Checking Line Name Checking Spectroscopic information Checking Calibration information Reference spectrum: Source Name : B Coordinate System : EQUATORIAL Proj. Center (rad): lambda , beta , tolerance 4.8E-08 Line Name : 12CO(1-0) Frequency (MHz) : rest E+03, resol 3.906E-02, offset 0.000E+00 Velocity (km/s) : resol E-01, offset E+01 Alignment (chan) : tolerance 10.0% Calibration : beeff 0.950,gain I-CONSISTENCY, Index is consistent find enforces a new consistency check from scratch. Selection of a data subset Consistent index. CLASS tutorial S. Bardeau & J. Pety, 2015

12 Data exploration: III. Where do we observe? LAS> go where One point per spectrum Lambda + Beta scanning Mapping experiment CLASS tutorial S. Bardeau & J. Pety, 2015

13 Data exploration: III. What does the data look like? Many different lines of different species in the same spectrum Spectral axis default unit is FREQUENCY and the VELOCITY unit is meaningful only close to the rest frequency F0. How to display one spectrum with channels on a pixel screen? CLASS tutorial S. Bardeau & J. Pety, 2015

14 Data exploration: III. What does the data look like? Interactive browsing of a spectrum and automatic annotation of potential lines from a line catalog. LAS> type mycatalog.cat DCOp-1-0! cdms CCD-1-0! cdms CCS! jpl DCN-1-0! cdms CCS! jpl OCS! jpl... LAS> let browse%cat mycatalog.cat LAS> go browse Authors: S.Bardeau & J.Pety ( ) Left clic: Center zoom at cursor location Right clic: Exit Press SPACE key: Center zoom at cursor location Press Z key: Zoom at cursor location Press U key: Unzoom at cursor location Press B key: Reset zoom factor to default Press D key: Default zoom width and location Press V key: Values at cursor location Press N key: Shift forward the zoom window by half its size Press P key: Shift backward the zoom window by half its size Press Y key: Zoom Y axis scale (Intensity) Press T key: Back to full scale for Y axis Press E key: Exit loop Press H key: Help display Y scales are ruled by the current SET MODE Y value CLASS tutorial S. Bardeau & J. Pety, 2015

15 Data exploration: III. What does the data look like? See also the lectures Line surveys by J. Pety. Line identification with LINEDB and WEEDS by P. Gratier. CLASS tutorial S. Bardeau & J. Pety, 2015

16 Data exploration: III. What does the data look like? Extracting a subset around the line rest frequency and plotting it with a meaningful velocity axis LAS> extract F! => Extract 30 MHz from to MHz LAS> modify frequency ! => Align the velocity axis on the new rest frequency LAS> plot! => Plot the extracted spectrum CLASS tutorial S. Bardeau & J. Pety, 2015

17 Data exploration: III. What does the data look like? LAS> set unit v f LAS> get first LAS> plot! => Bottom axis in velocity, top axis in frequency! Get first spectrum of index Line + Spike visible. LAS> get next LAS> plot LAS> get next LAS> plot times a bit long... CLASS tutorial S. Bardeau & J. Pety, 2015

18 Data exploration: III. What does the data look like? LAS> set nomatch LAS> set align f c LAS> average LAS> plot! Disable check about position consistency! Toggle frequency resampling! Average all spectra in index Line + Spike + platforming visible. CLASS tutorial S. Bardeau & J. Pety, 2015

19 Data exploration: III. What does the data look like? LAS> set mode x 60 80! => Zoom on spike LAS> plot LAS> set mode x tot! => Zoom back LAS> plot CLASS tutorial S. Bardeau & J. Pety, 2015

20 Data exploration: III. What does the data look like? LAS> find /tel 30M-V01-A100 LAS> load! Load the spectra in the current index as an image LAS> plot /index! Plot the image Line + Spike visible. Variation of continuum level before baselining spectra displayed at the same time. Possibility to quickly swap between average and image: LAS> plot LAS> plot /index LAS> plot CLASS tutorial S. Bardeau & J. Pety, 2015

21 Data exploration: III. What does the data look like? LAS> set mode x LAS> set mode y -1 5 LAS> set mode z LAS> plot /index! Velocity zoom! Intensity zoom! Index part zoom Line + Spike visible. Image saturation due to variation of the continuum level. CLASS tutorial S. Bardeau & J. Pety, 2015

22 Data exploration: III. What does the data look like? All previous possibilities integrated in an exploration tool: Look at the Explore Data File in the CLASS main menu. CLASS tutorial S. Bardeau & J. Pety, 2015

23 Data reduction: I. Windowing LAS> average LAS> plot LAS> set window LAS> draw window! Define the windows! Overplot the windows One window to avoid the signal two windows to avoid the spikes CLASS tutorial S. Bardeau & J. Pety, 2015

24 Data reduction: II. Selecting baseline order LAS> base 0 /plot! Fit 0-order baseline and overplot baseline polynomial I-POLYNO, degree: 0 rms: 7.942E-02 area: 7.87 v0: width: LAS> swap! Get back averaged spectrum before baselining LAS> clear segment! Clear overplotted baseline LAS> base 1 /plot! Increase baseline polynomial order and check residual rms I-POLYNO, degree: 1 rms: 3.559E-02 area: 7.58 v0: width: LAS> swap; clear segment LAS> base 2 /plot! Increase baseline polynomial order and check residual rms I-POLYNO, degree: 2 rms: 2.292E-02 area: 7.02 v0: width: LAS> plot! Plot baselined spectra CLASS tutorial S. Bardeau & J. Pety, 2015

25 Data reduction: III. Signal dependent window LAS> plot /index LAS> set window /poly 1! Plot the whole set of spectrum! Define 1 polygon CLASS tutorial S. Bardeau & J. Pety, 2015

26 Data reduction: III. Looping on the index Implicit loops provided by some commands (/INDEX option): LAS> extract... LAS> extract... /index! Process current spectrum only (updated in memory)! Process all spectra in index (FILE IN to FILE OUT) Explicit loops for custom processing: LAS> file in... LAS> find...! Load the current index of spectra LAS> file out... LAS> quiet! Turn off informational messages LAS> for ient 1 to found! Loop over the current index entries LAS> get next! Get next spectrum in index into R LAS>...! Your job here LAS> write! Write updated R version LAS> next ient LAS> verbose! Turn on informational messages Messages in terminal (there can be millions) slow down the processing. Turn them on/off through symbols (command aliases): LAS> symbol verbose "sic message class s+i"! Add (+) infos (i) to screen (s) LAS> symbol quiet "sic message class s-i"! Remove (-) infos (i) from screen (s) CLASS tutorial S. Bardeau & J. Pety, 2015

27 Data reduction: IV. Baselining LAS> LAS> LAS> LAS> LAS> LAS> LAS> LAS> LAS> file out a100-base single /over get zero quiet for ient 1 to found get next base 3 write next ient verbose CLASS tutorial!!!!!!! Open output file in single and overwrite modes Reset index counter to zero Turn off informational messages Loop over the index entries Get next spectra in index Fit baseline and compute residual spectrum Write residual spectrum in output file! Turn on informational messages S. Bardeau & J. Pety, 2015

28 Data reduction: V. Baseline RMS LAS> clear plot LAS> file in a100-base! Open file of residual spectra as input LAS> find LAS> variable base /index! Fill variable IDX%HEAD%BAS% with values from all spectra LAS> g\limit /var idx%num idx%head%bas%sigfi LAS> g\box LAS> g\set marker LAS> g\point idx%num idx%head%bas%sigfi LAS> g\label "Observation number" /X LAS> g\label "rms [K]" /Y CLASS tutorial S. Bardeau & J. Pety, 2015

29 Data reduction: VI. Despiking LAS> file out a100-fill single /over LAS> find LAS> for ient 1 to found LAS> get next LAS> fill /noise! File contaminated channels with Gaussian noise LAS> write LAS> next ient CLASS tutorial S. Bardeau & J. Pety, 2015

30 Data reduction: VII.1 Platforming diagnostic Platforming affects a single scan (#9621) Copy all the 2nd receiver data in a file where correction will happen in-place. LAS> set sort none LAS> file out b100-plat multiple /over! Multiple occurences of one spectrum enabled LAS> copy CLASS tutorial S. Bardeau & J. Pety, 2015

31 Data reduction: VII.2 Platforming correction #1 LAS> find /scan 9621 LAS> get first LAS> define real ty /like ry LAS> get zero LAS> get next LAS> plot LAS> set window LAS> base 2 /pl LAS> let ty ry /where rx.gt.-42.3! Define an intermediate array of intensities! Reset index counter to zero CLASS tutorial S. Bardeau & J. Pety, 2015

32 Data reduction: VII.3 Platforming correction #2 LAS> set window LAS> base 0 /pl LAS> let ry ty /where rx.gt CLASS tutorial S. Bardeau & J. Pety, 2015

33 Data reduction: VII.4 After platforming correction CLASS tutorial S. Bardeau & J. Pety, 2015

34 LAS> set unit f v LAS> set mode a tot LAS> file in off-positions LAS> find /off LAS> consistency LAS> aver LAS> plot Data analysis: VIII.1 Line fitting CLASS tutorial S. Bardeau & J. Pety, 2015

35 Data analysis: VIII.2 Line fitting LAS> fold LAS> plot CLASS tutorial S. Bardeau & J. Pety, 2015

36 Data analysis: VIII.3 Line fitting LAS> set mode x LAS> set window LAS> base 3 /plot CLASS tutorial S. Bardeau & J. Pety, 2015

37 Data analysis: VIII.4 Line fitting LAS> method gauss LAS> lines 1 " " LAS> minimize I-MIDGAUSS, Input Parameters: Area Position Fwhm I-MIDGAUSS, I-FITGAUSS, RMS of Residuals : Base = 4.17E-02 Line = 3.59E-02 I-FITGAUSS, RMS of Residuals : Base = 4.03E-02 Line = 3.76E-02 I-FITGAUSS, Number of calls: 56 Observation 0 RMS of Residuals : Base = 4.03E-02 Line = 3.76E-02 Fit results Line Area Position Width Tpeak ( 0.011) ( 0.022) ( 0.048) LAS> visu /pen 2 CLASS tutorial S. Bardeau & J. Pety, 2015

38 Data analysis: VIII.5 Line fitting LAS> iterate I-ITERATE, Starting iteration # 1 I-MIDGAUSS, Input Parameters: Area Position Fwhm I-MIDGAUSS, I-FITGAUSS, RMS of Residuals : Base = 4.17E-02 Line = 3.59E-02 I-FITGAUSS, RMS of Residuals : Base = 4.03E-02 Line = 3.76E-02 I-FITGAUSS, Number of calls: 25 Observation 0 RMS of Residuals : Base = 4.03E-02 Line = 3.76E-02 Fit results Line Area Position Width Tpeak ( 0.011) ( 0.022) ( 0.048) LAS> plot LAS> visu /pen 2 CLASS tutorial S. Bardeau & J. Pety, 2015

39 Data analysis: VIII.6 Line fitting LAS> residual LAS> plot CLASS tutorial S. Bardeau & J. Pety, 2015

40 Data analysis: VIII.7 Line fitting LAS> result LAS> plot CLASS tutorial S. Bardeau & J. Pety, 2015

41 CLASS tutorial II. Imaging Single-Dish Data Jérôme PETY (IRAM/Obs. de Paris) on behalf of the CLASS developers S. Bardeau, S. Guilloteau 8 th IRAM 30m Summer School Sep , 2015, Pradollano

42 Typical data reduction: I. Divide to conquer LAS> file in spectraodp! Complex setup => Huge data file LAS> list in /toc! Check file content LAS> file out 12co21 single! New file for a single line => Smaller data file LAS> find /line 12co21! Find everything concerning 12co21 LAS> copy LAS> file in 12co21! From now on, work on the smaller data file LAS> find LAS> consistency! Start real work by checking the data consistency... LAS> set tel * LAS> file out merged single /over LAS> file in spectraodp1 LAS> list in /toc LAS> find /line 12co21 LAS> copy LAS> file in spectraodp2 LAS> list in /toc LAS> find /line 12co21 LAS> copy LAS> file in merged LAS> list in /toc Merging data sets CLASS tutorial J. Pety & S. Bardeau, 2015

43 Typical data reduction: I. Extract to conquer LAS> file in spectraodp! Complex setup => Huge data file LAS> list in /toc! Check file content LAS> file out 12co21 single! New file for a single line => Smaller data file LAS> find /line 12co21! Find everything concerning 12co21 LAS> extract f /index LAS> file in 12co21! From now on, work on the smaller data file LAS> find LAS> consistency! Start real work by checking the data consistency... LAS> set tel * LAS> file out merged single /over LAS> file in spectraodp1 LAS> list in /toc LAS> find /line 12co21 LAS> copy LAS> file in spectraodp2 LAS> list in /toc LAS> find /line 12co21 LAS> copy LAS> file in merged LAS> list in /toc Merging data sets CLASS tutorial J. Pety & S. Bardeau, 2015

44 Typical data reduction: II. Choose global baseline windows on averaged spectrum LAS> set nomatch LAS> set align f c LAS> average LAS> plot LAS> set window...! Disable check about position consistency! Toggle frequency resampling! Average all spectra in index Line + Spikes. Baseline at negative level. CLASS tutorial J. Pety & S. Bardeau, 2015

45 Typical data reduction: III. Fit a low order baseline (0 or 1) on every dumped spectra LAS> find LAS> for ient 1 to found LAS> get next LAS> base 0 LAS> write LAS> next ient CLASS tutorial J. Pety & S. Bardeau, 2015

46 Typical data reduction: IV. Filter using clever statistical tools LAS> clear plot LAS> variable base /index LAS> g\limit /var idx%num idx%head%bas%sigfi LAS> g\box LAS> g\set marker LAS> g\point idx%num idx%head%bas%sigfi LAS> g\label "Observation number" /X LAS> g\label "rms [K]" /Y CLASS tutorial J. Pety & S. Bardeau, 2015

47 LAS> table 12co21 new /range v LAS> xy_map 12co21 LAS> let name 12co21 LAS> let type lmv LAS> go view Typical data reduction: V. Grid the data If lucky: Stop here! Else: Griding is a linear operation. Griding increases signal-to-noise ratio. Goal: Higher order baseline on grided data. CLASS tutorial J. Pety & S. Bardeau, 2015

48 Typical data reduction: VI. Import LMV file and import (or define) local baseline windows LAS> file out 12co21 single LAS> lmv 12co21.lmv LAS> file in 12co21 LAS> find LAS> load LAS> plot /index One fixed window for spikes. Varying windows from another tracer (good quality 12co10 data): The 12co10 window widths are enlarged by 40% to avoid possible biases. CLASS tutorial J. Pety & S. Bardeau, 2015

49 Typical data reduction: VII. High-order baselining LAS> find LAS> for ient 1 to found LAS> get next LAS> set window /var windows[,ient]! Load baseline windows from a SIC array LAS> base 5 LAS> write LAS> next ient CLASS tutorial J. Pety & S. Bardeau, 2015

50 Typical data reduction: VIII. Place the baselined spectra in the original LMV grid LAS> find LAS> table 12co21-base /sigma LAS> let map%tele 30m! Because the telescope field was lost during the previous LMV command LAS> let map%like 12co21.lmv LAS> xy_map 12co21-base /nogrid LAS> let name 12co21-base LAS> let type lmv LAS> go view CLASS tutorial J. Pety & S. Bardeau, 2015

51 Visualization: I. GO VIEW LAS> let name 12co10 LAS> let type lmv LAS> go view CLASS tutorial J. Pety & S. Bardeau, 2015

52 Visualization: II. GO BIT LAS> let name 12co10 LAS> let type lmv LAS> go bit LAS> input bit CLASS tutorial J. Pety & S. Bardeau, 2015

53 Visualization: III. GO SPECTRUM LAS> let name 12co10 LAS> let type lmv LAS> go spectrum CLASS tutorial J. Pety & S. Bardeau, 2015

54 Visualization: IV. GO ROT LAS> let name 12co10 LAS> let type lmv LAS> let angle 45 LAS> go rot LAS> go view CLASS tutorial J. Pety & S. Bardeau, 2015

55 Visualization: V. GO 3VIEW LAS> let name 12co10-rot45deg LAS> let type lmv LAS> go 3view CLASS tutorial J. Pety & S. Bardeau, 2015

56 Analysis: Noise Estimation with MEAN LAS> let name 12co10 LAS> let type lmv LAS> let first 1 LAS> let last 1 LAS> go bit LAS> poly LAS> mean I-MEAN, Found 288 non-blanked pixels, of area: E-07 Radians squared I-MEAN, Integrated intensity: e-08 (Map Units * Radians squared) I-MEAN, Mean value: E-02, r.m.s.: CLASS tutorial J. Pety & S. Bardeau, 2015

57 CLASS tutorial III. Line surveys Jérôme PETY (IRAM/Obs. de Paris) with P. Gratier & S. Bardeau 8 th IRAM 30m Summer School Sep , 2015, Pradollano

58 Line survey example (Horsehead WHISPER, PI: J. Pety): channels, i.e., as many information as in a pixel image! CLASS tutorial J. Pety & S. Bardeau, 2015

59 Line names: I. From observations LAS> set sort line LAS> file in red/survey-1 LAS> find LAS> list /toc line LAS> set sort none Number of lines ( 3.3%) ( 1.1%) ( 3.3%) ( 0.8%) ( 2.5%) ( 1.1%) ( 3.3%) ( 1.1%) ( 3.3%) ( 0.8%) ( 2.5%) ( 0.8%) ( 2.5%) ( 1.1%) ( 3.3%) ( 1.4%) ( 4.1%) ( 1.1%) ( 3.3%) ( 1.1%) ( 3.3%) ( 3.0%) ( 0.7%) ( 7.7%) ( 0.8%) ( 2.2%) ( 1.6%) ( 2.4%) ( 1.9%) ( 5.1%) ( 1.4%) ( 3.5%) ( 0.8%) ( 3.9%) ( 0.8%) ( 2.4%) ( 1.9%) ( 2.4%) ( 1.4%) ( 5.5%) ( 1.1%) ( 4.1%) CLASS tutorial J. Pety & S. Bardeau, 2015

60 Line names: II. 2SB Receivers LAS> file in red/survey-1 LAS> find /line LAS> list /toc Number of setups... 6 HORSEHEAD ME0HUI-F01 8 ( 16.7%) HORSEHEAD ME0VUI-F02 8 ( 16.7%) HORSEHEAD ME0HUO-F05 8 ( 16.7%) HORSEHEAD ME0HLO-F06 8 ( 16.7%) HORSEHEAD ME0VUO-F07 8 ( 16.7%) HORSEHEAD ME0VLO-F08 8 ( 16.7%) CLASS tutorial J. Pety & S. Bardeau, 2015

61 Line names: III. How to modify them LAS> set var spectro write LAS> file out red/survey-2 single /overwrite LAS> file in red/survey-1 LAS> find LAS> quiet LAS> for ient 1 to found LAS> get next LAS> let r%head%spe%line min( frequency+rx[1], frequency+rx[channels] ) /format f12.1 LAS> write LAS> next ient LAS> verbose LAS> set var spectro CLASS tutorial J. Pety & S. Bardeau, 2015

62 Line names: IV. Result LAS> set sort line LAS> file in red/survey-2 LAS> find LAS> list /toc line LAS> set sort none Number of lines ( 0.8%) ( 1.1%) ( 1.4%) ( 1.1%) ( 0.8%) ( 0.8%) ( 0.8%) ( 1.9%) ( 1.1%) ( 0.8%) ( 1.4%) ( 0.8%) ( 1.4%) ( 1.4%) ( 0.8%) ( 1.4%) ( 1.1%) ( 1.1%) ( 0.7%) ( 0.8%) ( 1.1%) ( 1.1%) ( 0.8%) ( 1.4%) ( 0.7%) ( 1.1%) ( 1.1%) ( 0.8%) ( 0.8%) ( 1.1%) ( 0.8%) ( 1.4%) ( 0.7%) ( 2.0%) ( 0.7%) ( 0.8%) ( 0.7%) ( 1.4%) ( 1.6%) ( 1.1%) ( 1.1%) ( 1.9%) ( 0.8%) ( 0.7%) ( 1.4%) ( 0.8%) ( 1.1%) ( 0.8%) ( 0.8%) ( 0.5%) ( 0.8%) ( 0.8%) ( 0.3%) ( 1.9%) ( 1.1%) ( 0.8%) ( 1.4%) ( 1.2%) ( 1.1%) ( 1.1%) ( 1.1%) ( 1.1%) ( 1.1%) ( 1.4%) ( 1.1%) ( 0.8%) ( 0.8%) ( 0.8%) ( 1.1%) ( 0.8%) ( 0.8%) ( 1.1%) ( 0.8%) ( 0.8%) ( 0.8%) CLASS tutorial J. Pety & S. Bardeau, 2015

63 Line names: V. Using the modified line names LAS> set sort line LAS> file in red/survey-2 LAS> find LAS> quiet LAS> sic output freq-range LAS> for ient 1 to found LAS> get next LAS> say line telescope frequency+rx[1] frequency+rx[channels] - LAS-? /format a15 a15 f15.3 f15.3 LAS> next ient LAS> sic output LAS> verbose LAS> set sort none LAS> type freq-range.dat ME0VLO-F ME0HLO-F ME0VLO-F ME0HLO-F ME0VLO-F ME0HLO-F ME0HLO-F ME0VLO-F ME0VLO-F ME0HLO-F ME0HLO-F ME0VLO-F ME0VLO-F ME0HLO-F ME0VLO-F ME0HLO-F CLASS tutorial J. Pety & S. Bardeau, 2015

64 Averaging: I. From CLASS tutorial J. Pety & S. Bardeau, 2015

65 Averaging: II. To CLASS tutorial J. Pety & S. Bardeau, 2015

66 Averaging: III. Per observing setup LAS> set bad and LAS> file out red/survey-3 single /over LAS> file in red/survey-2 LAS> find LAS> list /toc line tele off1 off2 LAS> quiet LAS> for isetup 1 to toc%nsetup LAS> find /line toc%setup[isetup,1] /tele toc%setup[isetup,2] - LAS-? /offset toc%setup[isetup,3] toc%setup[isetup,4] LAS> if (found.ne.0) then LAS> average /resample LAS> write LAS> endif LAS> next isetup LAS> verbose CLASS tutorial J. Pety & S. Bardeau, 2015

67 Stitching: I. Commands LAS> set bad and LAS> file out red/survey-4 single /over LAS> file in red/survey-3 LAS> find LAS> list /toc off1 off2 LAS> quiet LAS> define double frange[2,3] LAS> let frange[1] LAS> let frange[2] LAS> let frange[3] LAS> define character lines*12[3] teles*12[3] LAS> let lines "signal" "signal" "signal" LAS> let teles "3mm" "2mm" "1mm" LAS> for ifrange 1 to 3 LAS> for isetup 1 to toc%nsetup LAS> find /freq frange[1,ifrange] frange[2,ifrange] - LAS-? /offset toc%setup[isetup,1] toc%setup[isetup,2] LAS> if (found.ne.0) then LAS> stitch /line lines[ifrange] /tele teles[ifrange] LAS> write LAS> endif LAS> next isetup LAS> next ifrange CLASS tutorial J. Pety & S. Bardeau, 2015

68 LAS> file in red/survey-4 LAS> find LAS> get f LAS> set unit f LAS> set format long LAS> plot Stitching: II. Visualization CLASS tutorial J. Pety & S. Bardeau, 2015

69 Browsing through wide spectra: I. Zooming in frequency LAS> go browse CLASS tutorial J. Pety & S. Bardeau, 2015

70 Browsing through wide spectra: II. Zooming in intensity LAS> go browse CLASS tutorial J. Pety & S. Bardeau, 2015

71 Baselining: I. From CLASS tutorial J. Pety & S. Bardeau, 2015

72 Baselining: II. To CLASS tutorial J. Pety & S. Bardeau, 2015

73 Baselining: III. Through CLASS tutorial J. Pety & S. Bardeau, 2015

74 Baselining: IV. Wavelets (Experimental!) Hypotheses Lines and baselines have different spectral signatures LAS> file out red/survey-5 single /over LAS> file in red/survey-3 LAS> find LAS> quiet LAS> for ient 1 to found LAS> get next LAS> wavelet /base 5 LAS> write LAS> next ient LAS> verbose CLASS tutorial J. Pety & S. Bardeau, 2015

75 Baselining: V. Wavelet example #1 CLASS tutorial J. Pety & S. Bardeau, 2015

76 Baselining: V. Wavelet example #2 CLASS tutorial J. Pety & S. Bardeau, 2015

77 Baselining: V. Wavelet artefact #1 CLASS tutorial J. Pety & S. Bardeau, 2015

78 Baselining: V. Wavelet artefact #2 CLASS tutorial J. Pety & S. Bardeau, 2015

79 Other problems Spikes. Limited sideband rejection. CLASS tutorial J. Pety & S. Bardeau, 2015

80 CLASS tutorial IV. Interfacing GILDAS and line catalogs P. GRATIER (Obs. de Bordeaux) with J. Pety & S. Bardeau 8 th IRAM 30m Summer School Sep , 2015, Pradollano

81 LINEDB vs WEEDS LINEDB GILDAS kernel language to query online or local spectroscopic databases (Developed by M. Lonjaret, S. Bardeau, S. Maret, & J. Pety). WEEDS Adaptation of LINEDB to the CLASS environment (see Maret et al. 2011, A&A, 256, 47). It enables Interactive use of line catalogs with CLASS spectra. LTE line modeling and production of synthetic spectra. Compiled automatically if python (v 2.6) and numpy are installed (including the developer packages). CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

82 Prerequisite: Plotting a spectra in CLASS LAS> file in mydata.30m LAS> find LAS> get first LAS> plot CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

83 Connecting the input line catalog(s) LAS> use in cdms! Online access to the CDMS database I-USE, cdms (online) selected or LAS> use in jpl! Online access to the JPL database I-USE, jpl (online) selected or LAS> use in mydb.db! Offline access to a local file called! mydb.db previously created by LINEDB I-USE, mydb.db (offline) selected or LAS> use in cdms jpl mydb.db! Concurrent access to these 3 input! => Be careful to duplicate lines I-USE, cdms (online) selected I-USE, jpl (online) selected I-USE, mydb.db (offline) selected CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

84 Find all the lines of a given species in the current connected line catalogs LAS> lfind CH3CN! Create an index of all the lines associated of CH3CN I-LFIND, 11 lines found in the frequency range to MHz LAS> l\list! List them with their spectroscopic properties # Species Freq[MHz] Err[MHz] Eup[K] Gup Aij[s-1] Upper level -- Lower level Origin 1 CH3CN e jpl 2 CH3CN e jpl 3 CH3CN e jpl 4 CH3CN e jpl 5 CH3CN e jpl 6 CH3CN e jpl 7 CH3CN e jpl 8 CH3CN e jpl 9 CH3CN e jpl 10 CH3CN e jpl 11 CH3CN e jpl CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

85 Plotting the frequency range associated to a single line of the current line index LAS> lget 3! Get frequency range around line #3 of current index I-LGET, Found line frequency in the current scan # Species Freq[MHz] Err[MHz] Eup[K] Gup Aij[s-1] Upper level -- Lower level Origin 1 CH3CN e jpl LAS> lplot! Plot the corresponding frequency range CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

86 Enlarge the plotted frequency range LAS> lplot 1000! Plot 1000 channels instead of the default 100 channels CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

87 Identifying a line on an already plotted spectrum LAS> lid! Call the interactive cursor and list the lines in the current! index that are nearby the selected frequency I-LID, 9 lines found in the frequency range to MHz # Species Freq[MHz] Err[MHz] Eup[K] Gup Aij[s-1] Upper level -- Lower level Origin 1 H2CCHCN e cdms 2 CH2CHC-15-N e jpl 3 ag-diethyl ether e cdms 4 CH3CN, v= e cdms 5 CH3CN e jpl 6 Phenol e cdms 7 Phenol e cdms 8 CH3C-13-H2CN, v= e cdms 9 DNO e jpl CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

88 Creating a synthetic LTE spectrum LAS> type ch3cn.mod! Display the content of the ch3cn.mod file! species dcol Tex size Voff DV! (cm-2) (K) (") (km/s) (km/s) CH3CN 1e LAS> modsource ch3cn.mod 30 /verbose! Create the synthetic spectrum I-MODSOURCE, 5 lines found in the frequency range to MHz I-MODSOURCE, 5 CH3CN lines found in the frequency range I-MODSOURCE, log10 of the partition function at 25.0 K from jpl is # Species Freq[MHz] Err[MHz] Eup[K] Gup Aij[s-1] Upper level -- Lower level Origin Tau 1 CH3CN e jpl 3.05e-04 2 CH3CN e jpl 8.03e-03 3 CH3CN e jpl 2.20e-02 4 CH3CN e jpl 5.90e-02 5 CH3CN e jpl 8.20e-02 I-MODEL, Blanking value: I-RESAMPLE, Frequency resolution: MHz (observatory), MHz (rest frame) I-MODSOURCE, Model has been stored in memory CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

89 Overplotting a synthetic LTE spectrum LAS> modshow! Overplot the synthetic spectrum CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

90 Importing a private catalog in JPL ASCII format from your spectroscopic specialist Two files requested species.cat The description of the species lines. localhost> more ch3sh.cat CH3SH partfunc.cat The description of the partition function associated to the species. localhost> more partfunc.cat species CH3SH temperatures qpart LAS> use in ch3sh.cat LAS> use out ch3sh.db LAS> select LAS> insert LAS> use in ch3sh.db! Open the input ascii file! Open the output mysql database! Select all the lines of the input catalog! Insert all the selected lines into the output catalog! Makes the mysql database the input catalog CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

91 An example: Make a local copy of the CDMS database to work in the flight from the observatory LAS> sic delete mycdms.db LAS> use in cdms LAS> use out mycdms.db LAS> find real fmin fmax LAS> let fmin 0 LAS> for /while fmax.lt.1e6 LAS> let fmax fmin+2e4 LAS> say fmin fmax LAS> select /freq fmin fmax LAS> insert LAS> let fmin fmin+2e4 LAS> next LAS> use in mycdms.db LAS> select CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

92 WEEDS was used to detect the first branched alkyl (isopropylcyanide) in the ISM with ALMA data (Belloche et al. 2014, Science, 345) CLASS tutorial P. Gratier, J. Pety & S. Bardeau, 2015

93 CLASS Format Evolutions Sébastien BARDEAU (IRAM/Grenoble) on behalf of the CLASS developers J.Pety, S.Guilloteau 8 th IRAM 30m Summer School Sep. 11 Sep , Pradollano

94 CLASS Data Format Overview The CLASS Data Format is meant to: Provide a collection of spectra composed of: Metadata in a header in several sections (General, Position, Spectroscopic,...) One intensity array Fast search in the file (index), see command FIND in CLASS Past evolution: : minor revisions of the sections, 2008: MULTIPLE file: can store several versions of the same spectrum, vs SINGLE file: each spectrum can have only a single version in the file 2014: Binary format (Classic Binary Container) Version 2: Address former limits (e.g. file size > 1 TB) Easier evolution of the header sections 2015: updated Position section Backward compatibility: All previous versions supported for reading Write only to latest format References: CLASS Tutorial - S.Bardeau & J.Pety 2015

95 CLASS Data Format Updated Position section Updated in Class apr15 Unused elements removed Reordered for clarity Support for a non-zero projection angle => more projections supported, namely: NONE GNOMONIC ORTHOGRAPHIC AZIMUTHAL STEREOGRAPHIC LAMBERT AITOFF RADIO SFL Support in commands: MODIFY PROJECTION CONSISTENCY TABLE XY_MAP References: CHARACTER*12 R%HEAD%POS%SOURC [ ] Source name REAL*4 R%HEAD%POS%EQUINOX [year] Equinox of coordinates REAL*8 R%HEAD%POS%LAM [ rad] Lambda REAL*8 R%HEAD%POS%BET [ rad] Beta REAL*4 R%HEAD%POS%LAMOF [ rad] Offset in Lambda REAL*4 R%HEAD%POS%BETOF [ rad] Offset in Beta INTEGER*4 R%HEAD%POS%PROJ [code] Projection system REAL*8 R%HEAD%POS%SL0P [ rad] Lambda of descriptive REAL*8 R%HEAD%POS%SB0P [ rad] Beta of descriptive system REAL*8 R%HEAD%POS%SK0P [ rad] Angle of descriptive CHARACTER*12 R%HEAD%POS%SOURC [ ] Source name INTEGER*4 R%HEAD%POS%SYSTEM [code] Coordinate system REAL*4 R%HEAD%POS%EQUINOX [year] Equinox of coordinates INTEGER*4 R%HEAD%POS%PROJ [code] Projection system REAL*8 R%HEAD%POS%LAM [ rad] Lambda of projection center REAL*8 R%HEAD%POS%BET [ rad] Beta of projection center REAL*8 R%HEAD%POS%PANG [ rad] Projection angle REAL*4 R%HEAD%POS%LAMOF [ rad] Offset in Lambda REAL*4 R%HEAD%POS%BETOF [ rad] Offset in Beta CLASS Tutorial - S.Bardeau & J.Pety 2015

96 New concept in CLASS CLASS Data Format Associated Arrays section (1) Motivation: need to store additional physical quantities channelwise, i.e. arrays of the same size as the intensity array, described by the same X (frequency/velocity) axis. Examples: Weight array Mask array Wavelets (2D) Fitted model and residuals Created with the command ASSOCIATE or the Herschel-HIFI reader (next slides) Supported by commands like PLOT, SPECTRUM, EXTRACT, SMOOTH. More to come. Available as Sic variables in R%: R%ASSOC%FOO%DIM2 = 0! Integer GLOBAL RO R%ASSOC%FOO%UNIT =! Character*12 GLOBAL RO R%ASSOC%FOO%BAD = -1! Integer GLOBAL RO R%ASSOC%FOO%DATA is an integer Array of dimensions 8257 Still experimental, stable/official release in oct15 or nov15 (next slides) Reference: (document to be released, check GILDAS NEWS page) CLASS Tutorial - S.Bardeau & J.Pety 2015

97 CLASS Data Format Associated Arrays section (2)! Load a spectrum in R LAS> FILE IN demo.30m LAS> FIND /TEL 30M-V02-B100 LAS> AVERAGE /NOCHECK POS LAS> PLOT! Create an array LAS> define real test /like ry LAS> let test 0 LAS> let test[361:572] 1! Associate the array to R LAS> associate TEST test /bad -1! Show the R header contents LAS> dump... ASSOCIATED ARRAYS Number of associated arrays: 1 Associated array #1: TEST Unit: Format: -11 Bad: Dimensions: 2689 x 0 Data: ! Plot the Associated Array LAS> set mode y current LAS> spectrum TEST /pen 1 CLASS Tutorial - S.Bardeau & J.Pety 2015

98 CLASS Data Format Herschel-HIFI section Motivation: part of the Herschel-HIFI reader (see next slide) => metadata specific to Herschel-HIFI for a complete support INTEGER*8 R%HEAD%HER%OBSID [ ] Observation id CHARACTER*8 R%HEAD%HER%INSTRUMENT [str ] Instrument name CHARACTER*24 R%HEAD%HER%PROPOSAL [str ] Proposal name CHARACTER*68 R%HEAD%HER%AOR [str ] Astronomical INTEGER*4 R%HEAD%HER%OPERDAY [day ] Operational day number CHARACTER*28 R%HEAD%HER%DATEOBS [str ] Start date (ISO date) CHARACTER*28 R%HEAD%HER%DATEEND [str ] End date (ISO date) CHARACTER*40 R%HEAD%HER%OBSMODE [str ] Observing mode REAL*4 R%HEAD%HER%VINFO [km/s] Informative source velocity in LSR frame REAL*8 R%HEAD%HER%POSANGLE [rad ] Spacecraft pointing position angle REAL*8 R%HEAD%HER%REFLAM [rad ] Sky reference (a.k.a. OFF), lambda coordinate REAL*8 R%HEAD%HER%REFBET [rad ] Sky reference (a.k.a. OFF), beta coordinate REAL*8 R%HEAD%HER%HIFAVELAM [rad ] ON average H and V coordinate (HIFI), lambda coordinate REAL*8 R%HEAD%HER%HIFAVEBET [rad ] ON average H and V coordinate (HIFI), beta coordinate REAL*4 R%HEAD%HER%ETAMB [ ] Main beam efficiency used when applying doantennatemp REAL*4 R%HEAD%HER%ETAL [ ] Forward efficiency used when applying doantennatemp REAL*4 R%HEAD%HER%ETAA [ ] Telescope aperture efficiency REAL*4 R%HEAD%HER%HPBW [rad ] Azimuthally-averaged half-power beam width CHARACTER*8 R%HEAD%HER%TEMPSCAL [str ] Temperature scale in use REAL*8 R%HEAD%HER%LODOPAVE [MHz ] Average LO frequency Doppler corrected to freqframe (SPECSYS) REAL*4 R%HEAD%HER%GIM0 [ ] Sideband gain polynomial coeff 0 applied REAL*4 R%HEAD%HER%GIM1 [ ] Sideband gain polynomial coeff 1 applied REAL*4 R%HEAD%HER%GIM2 [ ] Sideband gain polynomial coeff 2 applied REAL*4 R%HEAD%HER%GIM3 [ ] Sideband gain polynomial coeff 3 applied REAL*4 R%HEAD%HER%MIXERCURH [ma ] Calibrated mixer junction current, horizontal REAL*4 R%HEAD%HER%MIXERCURV [ma ] Calibrated mixer junction current, vertical CHARACTER*28 R%HEAD%HER%DATEHCSS [str ] Processing date (ISO date) CHARACTER*24 R%HEAD%HER%HCSSVER [str ] HCSS version CHARACTER*16 R%HEAD%HER%CALVER [str ] Calibration version REAL*4 R%HEAD%HER%LEVEL [ ] Pipeline level Still experimental, stable/official release in oct15 or nov15 (next slides) Reference: (document to be released, check GILDAS NEWS page) CLASS Tutorial - S.Bardeau & J.Pety 2015

99 CLASS Data Format Importing Herschel-HIFI data CNES + IRAM collaboration: S.Bardeau, D.Teyssier (ESAC/Madrid), D.Rabois (IRAP/Toulouse), J.Pety Command LAS\FITS can detect and import spectra from the scientific FITS (levels 2.0 and 2.5, minimum version 12 or 13) found in the Herschel Science Archive. Sections filled in the Class headers: General Position Spectroscopy Frequency Switch (if relevant) Calibration (subset) Herschel-HIFI Associated Arrays: LINE (flag for spectral line), and BLANKED (flag for bad data) LAS> file out myfile.hifi single LAS> fits read herschel-hifi.fits LAS> file in myfile.hifi LAS> find LAS> get first LAS> plot Official release: in Class oct15 or nov15 Reference (exhaustive description of the filler): (document to be released, check GILDAS NEWS page) CLASS Tutorial - S.Bardeau & J.Pety 2015

100 CLASS Data Format Other telescopes (1) Native support of the Class Data Format from: APEX, SOFIA/GREAT, Effelsberg,... Class recognizes the following telescopes through naming convention in TELESCOPE name: AP- APEX 12M- Kitt Peak MED- Medicina SMT- ARO's SubMillimeter Telescope GBT- Green Bank Telescope OAN- Yebes 40m CLASS Tutorial - S.Bardeau & J.Pety 2015

101 CLASS Data Format Other telescopes (2) You can create Class spectra with: MODEL: create an observation from scratch SET VARIABLE WRITE: fill the observation header by hand Class can process any spectroscopic data thanks to: SET OBSERVATORY: customize the observatory (needed for Doppler) MAP% used by XY_MAP: customize the beam size Reference: class-filler.pdf Example: gag_demo:demo-telwrite! Open a new CLASS file file out classdemo.30m single /overwrite set variable sections write! Allow to change the section status let r%head%presec no! Disable all sections except... set variable general write set variable position write set variable spectro write for ispec 1 to 100! Data let data[ichan] sin(2.*pi*ichan/mynchan)**2 model data /xaxis V! General let r%head%gen%teles "MYTELES"...! Position let r%head%pos%sourc "MYSOURCE"...! Spectro let r%head%spe%line "MYLINE"... write next ispec CLASS Tutorial - S.Bardeau & J.Pety 2015

102 CLASS Data Format Importing FITS cubes (1) Command V\FITS (Greg): convert any positionposition-freq/velo FITS cube (e.g. ALMA data) to Gildas Data Format (GDF) cube, use Greg tools (e.g. GO VIEW) for analysis. Command LMV (Class): convert a GDF cube into a collection of Class spectra, e.g. FITS -> GDF -> Class Data Format Class -> GDF/LMV -> Class Data Format (gridded data) GREG> V\FITS mycube.fits TO mycube.lmv GREG> GO VIEW LAS> FILE OUT mycube.bin SINGLE LAS> LMV mycube.lmv LAS> LAS> FILE IN mycube.bin LAS> FIND LAS> AVERAGE /NOCHECK POSITION LAS> PLOT CLASS Tutorial - S.Bardeau & J.Pety 2015

103 CLASS Data Format Importing FITS cubes (2) Command FILE IN: can ingest directly a VLM cube (new since apr15) Cubes are usually position-position-freq/velo (LMV): convert to freq/velo-position-position (VLM) with V\TRANSPOSE. LAS> FILE IN mycube.vlm I-INPUT, mycube.vlm successfully opened LAS> FIND /OFFSET I-FIND, 1 observation found LAS> GET FIRST I-GET, Observation 820; Vers 1 Scan 17 LAS> PLOT CLASS Tutorial - S.Bardeau & J.Pety 2015

104 CLASS Data Format Importing FITS cubes (3) Beware of empty spectra (cube not fully sampled) LAS> FILE IN mycube.vlm I-INPUT, 13co10.vlm successfully opened LAS> FIND I-FIND, 6161 observations found LAS> GO WHERE LAS> GET FIRST I-GET, Observation 1; Vers 1 Scan 1 W-MINMAX, No valid data found CLASS Tutorial - S.Bardeau & J.Pety 2015

105 CLASS Data Format Importing FITS cubes (4) Cube not fully sampled: use FIND /MASK for cubes produced by XY_MAP LAS> FILE IN mycube.vlm I-INPUT, 13co10.vlm successfully opened LAS> FIND /MASK mycube.wei I-FIND, 5421 observations found LAS> GO WHERE CLASS Tutorial - S.Bardeau & J.Pety 2015