user manual 2014.03.07
Contents
1. signal to noise is computed as follows signal integration time std yes we violate the first normal form for convenience Also note that the STD is computed assuming the detector has a read noise of Detector RN documented in the MOSFIRE Pre Ship Review as 21 electron per fowler sample Thus the final STD is 21 electron STD v detected electron N Nreaas assuming the gain in Detector gain Note that there is no shot noise from dark current which was measured to be negligible at pre ship review An example of what the output looks like is here sn 9 Longslit Reductions The longslit reductions require transferring the Longslit_Driver py file into the reduction directory A few key parameters have to be adjusted in Longslit_Driver py to help the pipeline figure out where to extract the longslit from IO cd path to LONGSLIT cp mosdrp drivers Driver Longslit py Check all the txt files to make sure your observations are included You may have to merge files from various LONGSLII directories This happens when your observations use a shorter longslit than the calibrations edit Driver Longslit py a Change band FILL to the band b Examine a longslit image see figure below and adjust yrange 709 13501 to the vertical range c From the same examined longslit select row position so that it is uncontaminated See Figure 2 d The result should look like Figure 3 Decide if you want to2. the pipeline in this way Also some steps require output files from previous steps A future version of the pipeline will autopopulate these fields for you First steps with the driver file are as follows 1 Edit driver py 2 Set maskname and band The driver files line 14 and 15 will look like 14 maskname Q0105msfr2 ws 15 band H An example Driver file is 5 Flats Flats generate a pixel flat and slit edge tracing Uncomment the line that starts with Flat and run the DRP as mospy Driver py ramekin3 mospy Driver py Truncated output Flat written to combflat 2d H fits 00 Finding Slit Edges for BX113 ending at 1901 Slit composed of 3 CSU slits 01 Finding Slit Edges for BX129 ending at 1812 Slit composed of 2 CSU slits 02 Finding Slit Edges for xS15 ending at 1768 Slit composed of 1 CSU slits Skipping wavelength pixel 10 03 Finding Slit Edges for BX131 ending at 1680 Slit composed of 2 CSU slits The slit names should look familiar At the end I recommend you check the output in dso ramekins ds9 pixelflat 2d H fits region slit edges H reg The output should look something like Pare FI yqa Se ee O a NA mi a 7 7 q s 5 x t 7 e 3 9 step failed All values should be around 1 0 There are some big features in the detector that you will become familiar with over time KH g O go ign O O 5 O N N ct ct an jab O O ct Ey O
3. use Neon or sky lines for the wavelength solution For each step in a section uncomment the necessary line and run mosdrp on the Driver file Once the apply lambda simple step is complete fill in the lambda_solution_wave_stack_ line with the correct wave stack file You now have two options based on the results If the night sky lines are not bright enough to identify in the interactive step you should use arclamps In the following instructions replace wavefiles with Ne txt AAAH File Edit View Frame Zoom Scale Color Region WCS meow File wave stack H m130923 0347 0349 fits Object HIP16095 Value 205 325 FK5 03 27 21 495 35 12 44 12 88 Physical x 629 000 y 1127 000 Image x 829 000 Y 1127 000 pa Pagba 4 Frame1 Zoom 1 000 Angle SaaS RO file edit view frame bin T zoom scale color region ow help linear g power square root square d histogram min max J zscale l ro Figure 2 An example of an uncontaminated row 1127 in the longslit II Jelp bugs to http mosfire googlecode com Instructions 1 edit band to band Y or J or fi or K e g band J 2 edit 709 1350 to be the pixel values at the beginning and end of the long slit Look at the raw data 3 edit row_position to be a location where the standard star is not import os time import MOSFIRE from MOSFIRE import Background Combine Detector Flat
4. we interactively fit the lines This step is interactive The call looks like Wavelength fit lambda_interactively maskname band Offset 1 5 txt waveops This code uses Offset_1 5 txt to load the wave stack file generated in the previous step When you run this step a GUI window appears eoo X Figure 1 g a mm wavelength 0 0 0 2 0 4 0 6 0 8 1 0 these buttons NGO GG Figure 1 The interactive wavelength solving window This is a J band night sky spectrum Your goal is to help the pipeline by identifying the night sky lines in the center of each slit Once you come up with a good solution in the center the pipeline will propagate it outwards The pipeline uses Press to see a list of commands in the console window The steps you need to take are as follows First zoom in z and check to see if the orange lines match up with obvious night sky lines If not move the plots by pressing the c button The button shifts the measured spectrum in the wavelength direction Once the spectrum is aligned with the known night sky positions press f to fit A Chebyshev polynomial f such that fpixel returns the wavelength in Angstrom Continue this until you see the red Done text in the center of your screen Plotted in the gui will be a sky line spectrum and vertical lines denoting posi tions and wavelengths of the sky lines You will interactively fit a wavelength solution to th
5. MOSFIRE SPECTROSCOPY DATA REDUCTION PIPELINE USER MANUAL Nicholas Konidaris March 7 2014 1 Preface This manual describes the installation of the MOSFIRE data reduction pipeline on a unix like computer The pipeline has been tested on OSX and Linux The MOSFIRE spectrograph data reduction pipeline was architected by the MOSFIRE commissioning team and written by Nick Konidaris with extensive checking and feedback from Chuck Steidel and other MOSFIRE team members The pipeline is maintained on an online code repository mosfire googlecode com Please use this website to track issues and and submit requests To post comments please send an email to you do not need to join the group or have a Google email account mosfire drp googlegroups com 2 Installing the Data Reduction Pipeline 1 The pipeline relies on the Ureka Python distribution produced by STScI and Gemini Observatory Follow the instructions at this link http ssb stsci edu ureka 1 0 2 Download the MOSFIRE DRP from mosfire googlecode com This command will create the mospy command which is a wrapper around python cd wget http www astro caltech edu npk mosdrp releases mosdrp cur tgz mkdir mosdrp cd mosdrp tar xzf mosdrp cur tgz cp apps mospy mospy chmod x mospy Edit mospy and update MOSPATH to the path mospy expand out the twidle to the full path name For instance on my computer at Caltech I ve copied the data red
6. O on je O O En ct g O A an Panaad a ct gt O a on O 5 ct ct ST O ct gt O gt jab ct 6 Wavelength Calibration Y J and H bands In the shorter wavebands when using the recommended exposure times the wavelength calibration is performed on night sky lines The mospy wa Wavelength module is responsbile for these operations See the example driver file in the appendix 6 1 Combine files First step is to produce a file with which you will train your wavelength solution Since we re using night sky lines for training the approach is to combine individual science exposures This is performed by the python Wavelength imcombine routine For a lot of users this will look something like Wavelength imcombine Offset _ 1 5 txt maskname band options The first parameter is Offset 1 5 txt which is a python string indicating the list of files in the first offset position Note that Offset_1 5 txt was generated by the handle command Suppose you want to exclude a file for reasons such as weather or telescope fault simply remove the offending file from Offset_i 5 txt Likewise you are welcome to add files in as you like Outputs of this step are Filename Contains wave_stac and _irange fits median combined image of the files to be used for the wavelength solution 6 2 Interactive wavelength fitting The DRP now needs to find the wavelength solution in the wave_stack_ file Here
7. bed above The final step is a merging step The second and final steps are described below 711 Neon lamp solution The neon lamp solution will use the generated sky solution as an initial guess You are welcome to interactively solve the neon lamp solution with the Wavelength fit lambda interactively however this interactive solutions should be rare Uncomment the line in Driver K py 33 Wavelength apply interactive maskname band waveops 34 apply Offset 1 5 txt to Ne txt neon True This step when run will produce output like slitno 1 STD 0 16 MAD 0 06 slitno 2 STD 0 03 MAD 0 02 slitno 3 STD 0 04 MAD 0 04 slitno 4 STD 0 05 MAD 0 01 For each slit a new solution is generated for the neon line The output mimics that described previously where STD is the standard deviation and MAD is the median absolute deviation in angstroms 7 1 2 Merge sky and neon lamp 8 Background Subtraction This DRP assumes that targets are nodded along the slit with integration times as described on the instrument web page The integration times described were selected such that the shot noise in the region between night lines is over 5x larger than the read noise of a 16 fowler sample For MOSFIRE we define this as background limited 8 Despite MOSFIRE s unprescedented f 2 o camera the desired integration time for background limited operation is longer than the time for the atmosphere to vary by several percent As a res
8. cr2 mosfire 2013sep24 fits A lot of data summarizing the observations is outputed At this point you have a number of directories and files If you see an error message like Couldn t IO scr2 mosfire 2013sep24 you forgot to add a fits at the end of the command Suppose you want to reduce the data from mask Qo105msfr2 ws in H band Now you simply perform two steps 1 cd scr2 mpk m3 Qo105msfr2 ws 2013sep24 H 2 cp mosdrp drivers Driver py 3 NOTE If you are observing a K band mask you ll want to copy the K driver py file over An example output follows 00 2 ssh ea ramekin ls Aborted txt Ar txt Flat txt MIRA txt Offset_ 1 5 txt Unknown txt Align txt Dark txt Image txt Ne txt Of fset_1 5 txt ramekink cat Of Offset_ 1 5 txt Offset_1 5 txt ramekink cat Offset_1 5 txt Created by npk on Fri Jan 17 14 21 29 2014 scr2 mosfire 2 13sep24 Abs path to files optional m130924_0238 fits 178 93917 m130924_0240 fits 178 93917 m130924_0242 fits 178 93917 m130924_0244 fits 178 93917 m130924_0246 fits 178 93917 m130924_0248 fits 178 93917 m130924_0250 fits 178 93917 m130924_0252 fits 178 93917 m130924_0254 fits 178 93917 m130924_0256 fits 178 93917 s nununununnnnn wm ramekin cp mosdrp drivers Driver py ramekins fj 4 The driver py file The driver file controls all the pipeline steps The trick to running it is to uncomment and run one step at a time I assume you will operate
9. e sky line spectrum Options available on the gui are e c to center on the nearest peak first thing to do to shift the initial wavelength guess e c Center the nearest line at the cursor position e f Fit the data second thing to try e d Delete a point remove the wackadoos e n proceed to the Next object e p return to back to the Previous object e r Reset the current slit try this if the plot looks strange e zZ Zoom at cursor position e x Unzoom full screen e s Save figure to disk e h Help e q Quit and save results 7 Wavelength Calibration K band 7 1 K band only merge neon sky Note At the moment the Argon lamp is not supported please email mosfire drp googlegroups com 7f you would like to contribute this feature The night sky lines at the red end of the K band are too faint to achieve small fraction of a pixel RMS wavelength calibration You will have to observe a Neon arc lamp during your afternoon calibrations Because the beams emminating from the arclamp do not follow the same path as the beams coming from the sky there will be a slight difference between the two solutions For the afformentioned beam matching reason the most accurate solution is the night sky lines Thus the code has to be clever about merging the two solutions The merging process takes places in three steps The step is the same as those described in S6 2 The second step is to generate a full wavelength solution as descri
10. s IO Options Rectify from MOSFIRE import Wavelength Longslit import numpy as np pylab as pl pyfits as pf np seterr all ignore maskname longslit band J flatops Options flat waveops Options wavelength longslit yrange 709 1350 rowllposition 991 Flats handle_flats Flat txt maskname band flatops Wavelength imcombine Ne txt maskname band waveops wavefiles Offset_ txt Offset 13 33333 txt Offset 6 666667 txt Of fset_ 13 33333 txt Offset 6 666667 txt Wavelength imcombine wavefiles maskname band waveops Wavelength fit lambda interactively wavefiles band wavefiles waveops longslit longslit Driver Longslit py 46L 1427C written 29 9 Top Figure 3 Example of a modified Driver_Longslit py Notice that pixel 991 is selected as the row to perform the initial wavelength solution on In Figure 2 this is the equivalent of 1127 10 Some Hints 10 1 Pay attention to the wavelength fitting output I2 EO O paaa resid ang S01 p1006 resid ang S01 p1007 resid ang S01 p1008 resid ang S01 p1009 resid ang S01 p1010 resid ang S 1 p1011 resid ang S01 p1012 resid ang S01 p1013 resid ang S01 p1014 resid ang S01 p1015 resid ang S 1 p1016 resid ang S01 p1017 resid ang S01 p1018 resid ang S01 p119 resid ang S01 p1020 resid ang S01 p1021 resid ang S01 p1022 resid ang S01 p1023 resid ang S01 p1024 re
11. s The step creates a set of directories organized as maskname date band Aborted txt Aborted files Align txt Alignment frames Ar txt Argon spectra Dark txt Darks Flat txt Flat fields Image txt Imaging mode MIRA txt MIRA focus images Ne txt Neon lamp spectra Unknown txt Unknown files Offset p txt Science frames The output directory structure is designed to make finding reduced data easy and to seaprate reductions of the same mask across multiple dates You will then edit a provided driver file to reduce the data There are three provided driver files that are nominally located in mosdrp drivers Driver py K_Driver py and Longslit_Driver py The Driver and K_Driver will reduce your science data The K band requires a special approach because there are too few bright night sky emission lines at the red end and so the K_Driver synthesizes arclamps and night sky lines The Longslit_Driver handles the longslit observations of single objects First you need to setup your directories On my computer the data are copied from Keck and stored in scr2 mosfire NOTE You must preserve Keck s naming convention The output directory I ve chosen is scr2 npk m3 Please adjust these instructions according to where you want to place your directories For the sake of simplicity the pipeline will output results to the current directory Steps to perform 1 cd scr2 npk m3 Go to your output directory 2 mospy handle s
12. sid ang S01 p1025 resid ang S01 p1026 resid ang S01 p1027 resid ang S01 p1028 resid ang S01 p1029 resid ang S01 p1030 1 ssh 0 16 rms 0 09 mad shift 7 0 17 rms 0 10 mad shift 7 0 15 rms 0 10 mad shift 7 0 20 rms 0 11 mad shift 7 0 14 rms 0 09 mad shift 6 0 15 rms 0 08 mad shift 6 0 19 rms 0 13 mad shift 6 0 18 shift 6 63 64 9 81 mad shift 6 6 21 rms 0 54 mad shift 6 17 31 rms 12 09 mad shift 2 2 11 rms 1 07 mad shift11 7 58 rms 2 19 mad shift11 14 52 rms 11 85 mad shift 2 14 15 rms 7 68 mad shift 2 13 09 rms 6 07 mad shift 2 4 36 rms 2 80 mad shift10 9 49 rms 3 13 mad shift10 5 90 rms 2 14 mad shift10 6 19 rms 3 04 mad shift10 9 69 rms 7 25 mad shift 1 9 61 rms 7 04 mad shift 1 4 19 rms 2 26 mad shift10 The output above shows that up to pixel 1015 the RMS was 0 27 Angstrom level and then dramatically jumped to 60 angstrom Look at the image and examine pixel 1016 figure out what happened You may have to adjust your input files or remove a file from the set 10 2 Look at rectified wave stack files Look at rectified wave stack files and make sure the night sky lines are vertical on the detector 13
13. uction pipeline to scr2 mosfire DRP mosfire 00 4 ssh Na bin csh f alias ur_setup eval home npk ureka ur setup csh alias ur forget eval home npk ureka ur forget csh setenv MOSPATH Bcr2 mosfire DRP mosfire setenv PYTHONPATH PYTHONPATH MOSPATH ur_setup if S argv then echo Starting MOSFIRE Python ipython pylab colors Linux mospy 41L 8 8C written The installation has now e Installed the data reduction pipeline to mosdrp including o The bad pixel mask to mosdrp badpixels o The data reduction pipeline code to mosdrp MOSFIRE o Mospy applications including what useful pretty printer for files handle the entry point for creating driver files more later o Example Driver files mosdrp Driver py and one for the K band in mosdrp K driver py Created an executable shell script called mospy in From now on if you want to run any pipeline commands you will always execute mospy Did you use a previous version of the pipeline If so you will notice that the concept of a default input output directory is now gone You also don t need to install mercurial Now that s progress 3 First Step Handle Note This has changed compared to the stsci python version of MOSDRP The pipeline needs to know what files you have The handle step will parses the FITS header information and determine what files are associated with each of your mask
14. ult a further background subtraction step is required to remove the residual features The step is performed by a function called background subtract helper and follows the notation and procedure outlined in Kasen 2003 PASP 115 For most users you ll want to use the standard Driver file and not worry about the details 8 1 Output Files The background subtraction step produces the following files Table 1 Background subtraction step unrectified outputs These files are used later in the DRP Filename Content units sub masknamel bandnamel iplanl fits Signal e7 s bsub tmasknamel 1 bandname iplanl fits Background subtracted signal e7 s bmod masknamel t bandnamel planl fits Background model signal e s std_imaskname _ bandname _Iplan fits Total noise e7 itime masknamel bandname iplanl fits Integration time s As usual elements in brackets are replaced with the value for that mask Recitified outputs are also computed as tabulated in Table 2 Table 2 Background subtracted and rectified outputs The following files are not used in the later steps of the DRP they are provided for convenience Filename Content units imaskname _pair_i bandname _iplan fits Signal electron second maskname _pair_itime_ bandname _ plan fits Integration time second masknamel pair std bandnamel planl fits Standard deviation electron masknamel pair sn bandnamel iplanl fits Signal to noise Q Note that
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