Home
LTPDA Introduction, NPL, 9th August 2010
Contents
1. V uwewoTHs MlecenniocaiNonness Mm p Set A Introduction NPL 9th August 2010 Monday June 20 11 Parameter list editing Current Parameters Value aX Key FIGURE v RE es M Re es 5 24 uneworHs MILEGENDS IMIILEGENDLOCATNorthEast LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Different parameter sets Parameter Key Parameter value Open Special editor 48 Parameter list editing Different parameter sets Parameter Parameter value Open special editor Current Parameters Key Value aS z FIGURE 4 EE gem zT Anemon pe hawana Lla MivRRUU et v LEGENDS AMBBSERDLOCATINortnEast 0 parameter M LINEWIDTHS 14 A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Parameter list editing Different parameter sets Parameter Current Parameters Parameter value Open special editor
2. e usersQaei mpg de e http lists aei mpg de cgi bin mailman listinfo Itpda users e for LI PDA users dev aei mpg de http lists aei mpg de cgi bin mailman listinfo Itpda dev e for core development team e toda cvsQaei mpg de e http lists aei mpg de cgi bin mailman listinfo Itpda cvs e for LTPDA CVS commit mails e tp da meetingQaei mpg de e http lists aei mpg de cgi bin mailman listinfo Itp da meeting e tor meeting announcements LA LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Installation Download latest version from IUPCECEUCUES ONU 1 1 http www lisa aei hannover de fItpda weis 5 wrap strings 8 0 Unzip to somewhere icum otart MATLAB File gt Set Path Click Add with Subfolders Navigate to the Itpda toolbox folder you unzippeo 7 On MATLAB terminal 1 gt gt startup 7 1 1 you can add this command to you normal startup m file 8 oet preferences G 1 for now just click Apply and close the GUI O O1 Co A Introduction NPL 9th August 2010 Monday June 20 11 Cancel Apply Post installation steps e est installation gt gt un tests e Install graonviz see user manual gt gt doc e PDA Toolbox e Getting Started with the LTPDA Toolbox e Additional 3rd party software nttp www lisa aei hannover de
3. 2 O lt X tib Topicl Topic2 gt Topic3 gt Topic4 gt Topics Pipelines Library E lt ui t amp 1 1 T 1 1 T T T 1 gt _ 9 4 4 4 4 4 4 1 7 47 20 11 Introducing the workbench oes File m Et S O a Aia Pipelines Library lt Properties Controls tpda training workbench lwb Edit View Format Pipeline Tools Window Help Topicl Topic2 gt Topic3 gt Topic4 5 20 11 Graphical editor for commands Create multiple pipelines in one workbench filter x 0000 y 000 2 47 Introducing the workbench training workbench lwb File Edit Format Pipeline Tools Window Help Cielo XC e Topicl Topic2 gt Topic3 gt Topic4 5 Pipelines Library
4. A Introduction NPL 9th August 2010 Monday June 20 11 30 Class diagram ob gt v history 20 others A Introduction NPL 9th August 2010 Monday June 20 11 N 30 Class diagram history 2O others LA Monday June 20 11 LTPDA Introduction NPL 9th August 2010 30 Class diagram history 2O others LA Monday June 20 11 LTPDA Introduction NPL 9th August 2010 30 Class diagram history 2O others ES Monday June 20 11 LTPDA Introduction NPL 9th August 2010 30 Parameter lists e Essentially all methods constructors are configured by parameter lists plists e parameter list has e a list of parameters e a name inherited e a description inherited ea UUID inherited e Each parameter has a key and a value e oy String e yalue MATLAB primitive or LTPDA object http en wikipedia org wiki UUID LIPDA Introduction NPL August 2010 31 Monday June 20 11 Examples LA Monday gt gt pl plist plist 01 Empty Parameter List n params 0 description 9g9ef3a6 52f1 4fbf a442 f83d9d7b6b88 Parameter list with two parameters a key A val 1 and D param 2 key B val two
5. SHA UNIVERSITA DEGLI STUDI DI TRENTO What is LI PDA M Hewitson for the LTP Team NPL 9th August 2010 Institut d Estudis Espacials de Catalunya I Dis wii 2 Monday June 20 11 AEI Hannover Leibniz Universitat Hannover FONDAZIONE BRUNO KESSLER Outline e Why LI PDA e Formalities e Installation e 1 Introducing LI PDA the basics e 2 Preprocessing data e 9 Spectral analysis e 4 Transfer functions ana digital filters e 5 Fitting data A LIPDA Introduction NPL 9th August 2010 Who e Born in Carlisle e First o years of my working life as electrician e and PhD from University of Glasgow e Thesis On aspects of characterising and calibrating the interferometric gravitational wave detector GEO 600 e years building commissioning and calibrating e Past 3 years as head of LIP Data Analysis team e Married two you children A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Tne team S5 475 lt 7 0 2 Martin Hewitson CES Miquel Nofrarias Huele mg Luigi Ferraioli nneke Giuseppe Congedo Heather Audley Fabrizio De Marchi gt lt wow Andrea Mattioli Eric Plagniol Institut d Estudis Espacials de
6. gt Parameter Lists gt Simulation modelling v B Signal Pre processing in LTPDA Downsampling data Upsampling data Resampling data Interpolating data Spikes reduction in data Data gap filling Noise whitening Signal Processing in LTPDA B Graphical User Interfaces in LTPDA Working with an LTPDA Repository Class descriptions Functions By Category NN IB LTPDA Training Session 1 20 11 Signal Pre processing in Signal pre processing in LTPDA consists on a set of functions intended to pre process data prior to further analysis Pre processing tools are focused on data sampling rates manipulation data interpolation spike cleaning and gap filling functions The following pages describe the different pre processing tools available in the LTPDA toolbox Downsampling data e Upsampling data e Resampling data e interpolating data ikes r tion in data e Data gap filling e Noise Whitening e Gas ain models to ini filters Downsampling data LIPDA Introduction NPL 9th August 2010 56 Resampling e Integer factor e Down sample ao downsample e for example to reduce data loaq e Up sample ao upsample e for example to match sample rates do better filtering e Re sample ao resample out P Q fs in P and Q are integers A Introduction NPL
7. lt ut Properties Controls Monday June 20 11 eae HS Create multiple PIPEINES f pp 4 47 Introducing the workbench e O Itpda_training_workbench lwb File Edit F Format Pipeline Tools Window Help 88 e ar Topic zi Graphical editor for TODA commands gt Topics Create pipelines 1 la One workbench 1 m Edit parameter IIStS IN lt E rd a ui Create e V Monday June 20 11 Introducing the workbench AAA Itpda training workbench lwb File Edit View Format Pipeline Tools Window Help DORE Topicl editor commanas J Topic2 gt Topic3 gt Topic4 gt Shelf Library Pipelines Edit Block parameter ists la 52 perties Pro Create reusable subsystems Controls Monday June 20 11 Parameter list editing Current Parameters Key Value Edit FIGURE COLORS 10 80000000000 _ ARRANGEMEN stacked FUNCTION 1 LINESTY
8. Key Value v 5 v LEGENDS IMIXERRU ACtIvVate ae actlvaie a M a z FIGURE V EI Bir peu ger Mveru p fe parameter MIXSCALES Set A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Add remove a parameter 48 Parameter list editing Different parameter sets Parameter Parameter value Open special editor Current Parameters 44 lt Value z FIGURE lt v v zm E v gt v v ens v LEGENDS M XERRL x IMIXERRU parameter IIXSCALES CSC Set at gt Du 2 pom pe Lv Add remove a parameter Set a parameter set A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Special blocks LA Monday June 20 11 JSR u LIPDA Introduction NPL 9th August 2010 49 Special blocks Annotation Seen eee _ 244103 4 13 44 EH n E IN j pe MQ 4 e 7 A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Special blocks Annotation MATLAB LILI LI E
9. NFFT 1e 03 WINZBH32 OLAP 0 661 ORDER 0 KDES 100 IDES 1e 03 5 simplify units 1400158 EXCEPTION S B filter GDOFF BAN K parallel noise Ws v EFORM noise Sab s 1 FS 1 MSECS 1e 04 YURITS A 1 F 1 23 PHI 0 TO 1970 01 01 na noise Ip Filter maise 2nois e Ip FilEer maise noise 4 plus ern pty plist 8 miir 1x Txpzmoa del hist FS 1 9 pzrnadel filter POLES 1xpz AI 10 INIT S S ZEROS I 10 ao WAY EFORM noise SIGMA 3 FS 1 MSEC S 1e 04 YURITS 4 4 1 F 1 23 PHI 0 T 1970 01 01 TOFF 0 XUMITS s RAND STATE 3 52e 08 5 2 1808 TOFF 0 XUNITS s RAND STATE 3 62 08 5 21 08 TOFF 0 XUNITS s RAND 5 3 62 08 5 21 08 setDesceipeee DESCRIPTION Nowe outp Am m gt s IE s lt 2 B O I IU save FILENAME ol_nl xmD cc a ac FILEN AME Users La seiName N AME o1 whten INMODEL MAXITER 50 POLETYPE 2 MINORDER 17 MAXORDER 25 WEIGHTS 2 PLOT tue DISP true RMSEV FITTOLERANCE 0 05 KDES 100 JDES 1e 03 LMIN 0 WIN 1xspecwin OLAP 1 ORDER 4 SCALE PSD RAND STATE 2
10. 11 93 20 11 Topic 4 Transfer function models and digital filters e ransfer function models in s domain e Pole zero representation e Rational representation e Partial fraction representation e ransformation between representations e Modeling a system e Filtering data e discretizing a model e setting filter properties e O lemperature example A Introduction NPL 9th August 2010 95 Monday June 20 11 Overview e general scheme input output a transfer function e Aim of this topic e How to model the transfer function H In continuous domain H e How to discretize our model H s gt H z e How to filter data with H z e How to define H z from filter properties A Introduction NPL 9th August 2010 Monday June 20 11 96 Tools used here A Introduction NPL 9th August 2010 Monday June 20 11 97 Tools used here 1 Continuous domain A Introduction NPL 9th August 2010 Monday June 20 11 97 Tools used here 1 Continuous domain bozmodel divide rational simplify etc E LIPDA Introduction NPL 9th August 2010 Monday June 20 11 97 Tools used here 1 Continuous domain bozmodel divide rational simplify etc 2 Discrete domain A LIPDA
11. A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 49 ohortcut keys comment out block s LTPDA Introduction NPL August 2010 50 Monday June 20 11 Workbench FIX e copy reset m to lt somewhere gt ltpda_toolbox_2 3 ltpda classes eL TPDAworkbench reset m A LIPDA Introduction NPL August 2010 Monday June 20 11 51 20 11 Interferometer lemperature example e VVe have a data analysis exercise which will develop fully over the course of the training session e his Is the first part reading and preparing the data e Vyork through section e 1 e FO Temperature Example Introduction IFO A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 53 20 11 Topic 2 Pre processing data Why e data preparation for further analysis e PDA contains a bunch of functions for e resampling data e interpolation of data e de trending data e noise whitening e data selection A Introduction NPL 9th August 2010 Monday June 20 11 55 ook in the help Q Search mM gt Toolbox Signal Pre processing in U LTPDA Toolbox contents gt LTPDA Toolbox gt gt Getting Started with the Toolbox 4 Examples gt Introducing Objects
12. PDA Toolbox LIPDA Training Session 1 Topic 2 e FO Temp example A Introduction NPL 9th August 2010 Monday June 20 11 63 20 11 Power Spectral Density Estimation 1 Definition 2 f m f Estimates the one siqeq PSD e f co 2P 1 Os f lt LIPDA Introduction NPL 9th August 2010 65 Power Spectral Density Estimation 2 he PSD at each frequency is estimated via the Welch method e 3iven discretized signal of length Data are divided into segments of length L and multiplied by a WIndow e this also reduces the edge effects simulating a periodic sequence e The PSD at each frequency f is estimated as where Palf FG v SIMA 2Ti w n x f 2 lrlexp r2 LIPDA Introduction NPL 9th August 2010 Monday June 20 11 66 Power Spectral Density Estimation 3 e Methods e ao psa linear frequency scale e ao Ipsd log frequency scale e implements spectral windows A Introduction NPL 9th August 2010 Monday June 20 11 67 Power spectral Density Estimation 4 ea ao with time series data e S a osd plist win win nfft nfft olap olap order order scale scale Or add a block on a workbe
13. description UUID d4b59063 292c 4254 b562 0fef3fb11c17 LIPDA Introduction NPL 9th August 2010 32 June 20 11 Building objects e Objects built using class constructors e object class name arguments Examples gt gt empty analysis object gt gt ao 1 analysis object with a single data value gt gt a ao plist vals 1 as above using plist gt gt s smodelC a x b symbolic model of a straight line gt gt s mfir filter xml build an FIR filter by loading it from a file gt gt pl plistC filename filter xml gt gt s mfir pl as above using a plist A LIPDA Introduction NPL 9th August 2010 33 Monday June 20 11 Getting How do know which parameters to put in my plist gt gt help mfir MFIR FIR filter object class constructor 207070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070 DESCRIPTION MFIR FIR filter object class constructor Create mfir object CONSTRUCTORS f mfir creates empty mflr object Parameter Sets VERSION Id mfir m v 1 103 2010 05 05 09 30 07 ingo Exp 5 SEE ALSO miir Ltpda_filter ltpda_uoh ltpda_uo ltpda obj plist 20707207070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070
14. 20 11 Topic 5 Fitting to data 5 see If we will have time LIPDA Introduction NPL August 2010 113 Monday June 20 11
15. 9th August 2010 57 Monday June 20 11 Topic 2 Exercises 1 2 3 e Open MATLAB documentation e in the MATLAB terminal e gt gt e Help gt Product Help work through e Toolbox Training Session 1 Topic 2 e Downsampling e Upsampling Resampling A Introduction NPL 9th August 2010 Monday June 20 11 58 Interpolation Figure File Edit View Insert Tools Desktop ndow hb lt 2 OB am rigin 19 0 01 01 00 00 00 000 OAL ANE AN OO ALA AN i SNR Amplitude V work through lopic 2 interpolation d LIPDA Introduction NPL August 2010 Monday June 20 11 Interpolation vertices new time grid interpolation methods linear linear interpolation spline spline interpolation cubic cubic Interpolation nearest nearest neighbour work through Figure 4 e Edit View Insert Tools Desktop Window Help ndo 555 9g9gsx 9 hs 0 Time origin 1970 01 01 2 00 AAC OPN 0 8 l SN CENT DEEE NOT 4 LN Time 5 lopic 2 interpolation LTPDA Introduction NPL 9th August 2010 20 11 Detrending data e Remove trends by e subtracting polynomial fit from data e ao detrend calls MATLABs S 10
16. Catalunya Adrien Grynagier ynag Michele Armano Marc Diaz Aguil LIPDA Introduction NPL 9th August 2010 4 Not a commercial product A Introduction NPL 9th August 2010 Monday June 20 11 Not commercial product e nave about 2 FIES currently working on the toolbox LIPDA Introduction NPL August 2010 Monday June 20 11 Not commercial product e nave about 2 FIES currently working on the toolbox LIPDA Introduction NPL August 2010 Monday June 20 11 Not a commercial product e nave about 2 FIES currently working on the toolbox e otal effort so far is about 10 years LIPDA Introduction NPL August 2010 Not a commercial product e nave about 2 FIES currently working on the toolbox e otal effort so far is about 10 years LIPDA Introduction NPL August 2010 Not a commercial product e nave about 2 FIES currently working on the toolbox e otal effort so far is about 10 years e Feedback 5 essential LIPDA Introduction NPL August 2010 Not a commercial product e nave about 2 FIES currently working on the toolbox e otal effort so far is about 10 years e Feedback 5 essential LIPDA Introduction NPL August 2010 Not a commercial product e nave about 2 FIES currently working on the toolbox e ota
17. Itpda usermanual ua additional proas html A Introduction NPL 9th August 2010 10 Monday June 20 11 Updating the toolbox e Remove old toolbox from MATLAB path e File gt Set Path e Select all in list containing Ltpda_toolbox Click Remove install new toolbox as per previous Instructions A Introduction NPL 9th August 2010 Monday June 20 11 11 oubmitting a bug or feature request e Go to https ed fbk eu Itpda mantis e Self sign up e click Signup for a new account e Once your account is active you can log in e o report an issue e First search the existing Issues case your problem 1 covered e Click Report Issue e Choose project e Select bug report or change request e Complete the form with as much information as possible A Introduction NPL 9th August 2010 Monday June 20 11 12 20 11 Topic 1 e basics e Object oriented programming for beginners e Analysis Objects e How history tracking works e Other objects e Parameter lists MEM LLLI e Building objects e Setting object properties ZA Viewing history EN 2 5 e Making time series AOs Aans Basic math NNNN 777 e Saving and loading i e Reading data files Welcome to LTPDA Toolbox Writing LI PDA scripts V Release
18. R20100 e Hands on Date 30 07 10 A Introduction NPL August 2010 Monday June 20 11 Object oriented programming carn these words Class e object e instance method constructor e property e inheritance LIPDA Introduction NPL August 2010 Monday June 20 11 15 Class class is a description of an object e Examples e aeroplane house vehicle animal algorithm colour sentence A Introduction NPL 9th August 2010 Monday June 20 11 Class class is a description of an object e Examples e aeroplane house vehicle animal algorithm colour sentence A LIPDA Introduction NPL August 2010 Monday June 20 11 Object instance e An object is an instance of a class e Examples e Airforce 1 aeroplane me person garfield cartoon cat e mean algorithm red color isn t this easy sentence A Introduction NPL 9th August 2010 Monday June 20 11 17 Object instance e An object is an instance of a class Examples e Airforce 1 aeroplane me person garfield cartoon cat mean algorithm red color isn t this easy sentence A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 17 method e Something that acts on an object instance of a class e Examples e start car Start is a m
19. e using matlab e suitable for small history trees only a2812886 aoC plistC ao o 92818225 setName a2812886 plist NAME bob 5 5 Ltpda_uoh a out a2818295 9 gt Introduction NPL 9th August 2070 40 Monday June 20 11 Build a time series e AOs can contain different types of data e ime series data are stored in a tsdata object e n this case the ao data field will be a tsdata object e also have properties 7 tO of first sample xunits X axis units yunits Y axis units Constructors a ao vector sample rate ea ao plist tsfcn t 2 t 10 nsecs 1000 others gt gt help ao click Parameter Sets A LIPDA Introduction NPL 9th August 2010 41 Monday June 20 11 Basic Math You operate AOS using a large set of methods e n particular many typical Math operations are available overloaded e Further details at htto www lisa ael hannover de Itoda documents files operator_rules paf 1 ao 2 l ao 1 ao 2 3 1 b 2 2 ao 4 C a b c a bD LIPDA Introduction NPL 9th August 201 Monday June 20 11 oaving and loading objects e All User Objects can be saved to and loaded from file in e XML format e binary MAT format lt xml version 1 0 encoding utf 8 gt ltpda object Ltpda version
20. f 2 1 Hz Q Q 0 5 0 5 underdampedl critically damped Im Re A Introduction NPL 9th August 2010 Monday June 20 11 Im He 99 About poles and zeros notation e Simple pole f 1 Hz e Pole pairs f 2 1 Hz Q Q 0 5 Q 0 5 underdampedl critically damped Im Im Re 2x Re A Introduction NPL 9th August 2010 Monday June 20 11 Im He 99 About poles and zeros notation e Simple pole f 1 Hz e Pole pairs f 2 1 Hz Q Q 0 5 Q 0 5 Q lt 0 5 critically damped overdamped Im Im Re 2x Re A Introduction NPL 9th August 2010 Monday June 20 11 Re 99 About poles and zeros notation e Simple pole f 1 Hz Re e Pole pairs f 2 1 Hz Q Q 0 5 Q 0 5 Q lt 0 5 underdampedl critically damped overdamped Introduction NPL August 2010 Monday June 20 11 Pole zero models Working example Compute pole zero response e Topic 4 gt Create transfer function gt Create pole zero model Key Value GAIN 5 POLES f 1 Hz Q 2 ZEROS f 1 Hz f 0 1 Hz Figure 2 File Edit View Insert Tools Desktop Window Help k resptunknown 10 il E I 10 10 10 10 Frequenc Hz Phase dee 8 8 8 8 A LTPDA Introduction NPL 9th Auc Monday June 20 11 100 Rational mode
21. power psd psdconf pwelch quasiSweptSine rdivide real rebuild removeVal report resample rms rotate round sDomainFit save scale scatterData search select setDescription setDx setDy setFs setMdlfile setName setPlotinfo setProcinfo setTO SetUUID setX setxY setXunits setY setYunits setZ sign simplifyYunits sin sineParams smallvector Lincom smallvectorfit smoother sort spectrogram spikecleaning split spsd sqrt std straightLineFit string submit sum sumjoin svd svd fit tO table tan tdfit tfe timeaverage timedomainfit times timeshift transpose type uminus unwrap update upsample validate var viewHistory whiten1D whiten2D X xcorr xfit xunits y yunits zDomainFit zeropad 24 Tracking history A Introduction NPL 9th August 2010 Monday June 20 11 25 Tracking history E LIPDA Introduction NPL 9th August 2010 Monday June 20 11 25 Tracking history name version gt PPS it qata version input histories params A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 25 Tracking history name version Ep ED data version input histories params version input histories params A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 25 Tracking history EEE Input histories params na
22. 0 Hz work through TTC Topic 2 Removing trends A LIPDA Introduction NPL 9th August 2010 60 Whitening e he LIDA Toolbox offers various ways to whiten your data e with a known filter e bulla filter and apply it to your data e With a known model of spectral content e use whiten1D e for single uncorrelated data streams e whiten2D e for a pair of correlated data streams e without model Exercise e jet whiten1D fit a model to the spectrum of your data work through Topic 2 whitening A LIPDA Introduction NPL 9th August 2010 61 Monday June 20 11 Select amp find split amp join e Chose the samples you want to analyse e find select data samples by its properties e sample numbers select e Query for x and y values fina e Split data Dy e intervals times frequencies samples e Group of functions helps you to e for find select exactly the data you want split your data Into pieces and eventually e join them back together work through lopic 2 select find split ana Join LIPDA Introduction NPL 9th August 2010 LA Monday June 20 11 62 Pre processing the IFO Temp data e is a useful function which cleans up the data e consolidate e consolidate fixes our two data streams such that e they start at the same time e they nave the same sampling rate e the are evenly sample on the same grid e VVork througn e
23. 10 Monday June 20 11 86 Cross Power Spectral Density Parameters u WIN order LA Monday June 20 11 A Spectral Window to 6 92 or Rectangular User multiply the data by name or object oreterences Length of the window 1 one window length data set lenatn Or length number of points Order of segment 1 no detrending detrending onor to mean subtraction windowing order N polynomial trend subtraction ercentage overlap 1 taken window parameters between adjacent no overlap 1 segments 100 total overlap LIPDA Introduction NPL 9th August 2010 87 Transfer Function Estimation e Methods e ao tfe linear frequency scale e ao Itfe log frequency scale e Definition e Use Welch method again A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 88 Transfer Function Estimation 2 pl plist Win Wlnh nfft nfft Olap 0Llap Order order scale scale Txy tfe x y pl LIPDA Introduction NPL 9th August 2010 Monday June 20 11 89 Transfer Function Estimation Parameters WE Description Default x A Spectral window to BH92 or Rectangular win User multioly the data by name or oreterences ff Length of the window 1 one window length data set length Or length number of points Order of segment 1 n
24. 1e 05 Ins JDES 16 03 KDES 100 LMIN 0 WIN xspecwm OLAP 0 661 ORDER 0 SCALE PSD Introduction NPL August 2010 Monday June 20 11 Reliving history obj typeC file output commanas needed to rebuild this object obj rebuild rebuild this object LA Monday June 20 11 LIPDA Introduction NPL 9th August 2010 28 Objects Objects Everywhere e he Toolbox is fully object oriented e user deals with user objects e MATLAB primitives strings doubles logicals etc e We have 13 User Classes ao collection filterbank matrix mfir miir pest pzmodel rational smodel ssm timespan e wo helper classes 01151 time A Introduction NPL 9th August 2010 Monday June 20 11 29 Class diagram A LIPDA Introduction NPL August 2010 Monday June 20 11 30 Class diagram pda nuo pda obi d LIPDA Introduction NPL August 2010 Monday June 20 11 30 Class diagram LA Monday June 20 11 LIPDA Introduction NPL August 2010 30 Class diagram ob gt A Introduction NPL 9th August 2010 Monday June 20 11 30 Class diagram history 20 others
25. 2 0 R2008b gt object shape 1x1 gt property prop name data shape 1x1 type fsdata gt object shape 1x1 type fsdata gt property prop name t0 shape 1x1 type time gt Y Y gt gt save a foo xmLl setae alt Augg 22 save a foo mat property prop name utc epoch milli shape 1x1 gt gt save plist foo xml lt property timezone shape 1x1 type s Y i property prop name timeformat shape 1x23 type gt gt b aoc foo xml property prop name time str shape 0x0 type c gt gt C ao foo mat property prop name version shape 1x53 type c lt object gt gt gt d ao plist filename foo xml property prop name navs 1 1 type double gt 1 lt property prop 5 1 1 type double 1000 property prop_name enbw 1 1 type double gt 0 2 property prop name version shape 1x55 gt 3 property prop name xunits shape 1x1 type unit d lt object shape 1x1 type unit property prop name strs shape 1x1 type cell LTPDA Introduction NPL 9th August 2010 43 Monday June 20 11 Reading existing data files e You can construct AOs from existing ASCII raw data Tiles ao topicl simpleASCII txt 5105 ao plist filename topici multicolumnASC
26. 70707070707070707070707070 A LIPDA Introduction NPL 9th August 2010 34 Monday June 20 11 Getting How do know which parameters to put in my plist gt gt help mfir MFIR FIR filter object class constructor 207070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070707070 DESCRIPTION MFIR FIR filter object class constructor Create mfir object CONSTRUCTORS f mfir creates empty mflr object Parameter Sets here Id mfir m v 1 103 2010 05 05 09 30 07 ingo Exp SEE ALSO miir Ltpda filter Ltpda_uoh ltpda uo ltpda obj plist 902090909090209020909020909090209020209090902090209090209020902090202090209020002090202090909020902020202090209020209020902090202020209090902090202090209020 A LIPDA Introduction NPL 9th August 2010 34 Monday June 20 11 LTPDA Toolbox Method Report for mfir mfir contents Some information of the method mfir mfir are listed below Class name mfir Method name mfir Category Constructor CVS Version Sid mfir m v 1 103 2010 05 05 09 30 07 ingo Exp 5 Min input args 0 input args 1 Min output args 1 Max output args 1 Sets for this method Default From MAT File From XML File From Repository From Built in Model From Standard Type From Pzmodel From A From Default Key Default Value NAM
27. E None DESCRIPTION back to top Monday June 20 11 Description The name of the constructed FIR filter The description of the constructed FIR filter 39 Getting more help e PDA Toolbox has a decent amount of documentation e gt gt doc e Which methods are available e gt gt methods class name e example gt gt methods mfir Methods for class mfir Contents display mfir setA setPlotinfo update bsubmit eq ne setDescription setProcinfo viewHistory char get rebuild setHistout SetUUID CODy impresp redesign setlIunits simplifyUnits created index report setMdlfile string creator 15 resp setName submit csvexport 1svalid save setOunits type A LIPDA Introduction NPL August 2010 36 Monday June 20 11 oetting object properties e Properties of an object can be set using setter methods or during construction gt gt a ao plist name bob on CLS ee name bob data None hist ao Id ao m v 1 315 2010 06 25 13 55 38 ingo Exp mdlfile empty description UUID 500458d6 2a4d 4289 8d25 3fe5ebd1548f gt gt gt gt a setName mismas ELI DOD en name bob data None hist ltpda_uoh setName Id setName m v 1 12 2010 06 07 16 35 26 ingo Exp mdlfile empty description A UUID 7172543d e69d 4fcf abdd b111b9c16434 37 Monday June 20 11 Modifying or CO
28. I NA VA NS CINSI I Z CI I 7 Qua SUN I DT 80 PSD Exercise 3 e Passing values as parameter values E LIPDA Introduction NPL 9th August 2010 Monday June 20 11 PSD Exercise 3 iplot plist Ime piot Plot settings ao setYunits vunits JDES 2000 E LIPDA Introduction NPL 9th August 2010 Monday June 20 11 82 Cross Power Spectral Density Estimation DENON C f gt 2 4 Estimates the one sided PSI er co 2 2P f 0s fa LIPDA Introduction NPL 9th August 2010 Cross Power Spectral Density Estimation 2 Use Welch method as in PSD e he CPSD at each frequency f is estimated as X Y CT TIU where 2 HD n LIPDA Introduction NPL 9th August 2010 94 Cross Power Spectral Density Estimation 3 VV e Methods e ao cpsa linear frequency scale e ao lcpsa log frequency scale oimilarly we can evaluate coherence c Coh f P 7 XX yy Methods ao cohere linear frequency scale ao Icohere log frequency scale A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 85 Cross Power Spectral Density Estimation 4 pl plist Win Wlnh nfft nfft Olap 1 Order order scale scale y pl A LIPDA Introduction NPL 9th August 20
29. II txt columns 1 3 1 5 name i sin2 sin4 yunits i m m description i sine wave at 2Hz sine wave at 4Hz A LIPDA Introduction NPL 9th August 2010 44 Monday June 20 11 Hands the keys e You can work through these concepts in the relevant section of the documentation e Training Session 1 B LTPDA Training Session 1 This series of help pages consitute the first training session of LTPDA The various data packs used throughout the tutorials are available for download on the web site 1 Topic 1 The basics of LTPDA 2 Topic 2 Pre processing of data 3 Topic 3 Spectral Analysis 4 Topic 4 Transfer function models and digital filtering 5 Topic 5 Model fitting A Introduction NPL 9th August 2010 45 Monday June 20 11 20 11 Introducing the workbench AAA File Edit Pry Format EL e elol CONNIE Topicl 2 gt Topic3 gt Topic4 gt Topics Shelf Library Pipelines Properties Controls Monday June 20 11 Window Help ort ZH E Tw Wn Fic D 222 47 Introducing the workbench eee tpda training workbench lwt gt gt File Edit View Format Pipeline Tools Window Help
30. Introduction NPL 9th August 2010 Monday June 20 11 97 Tools used here 1 Continuous domain 2 Discrete domain ozmodel divide rational simplify etc resp setlunits setOunits A LIPDA Introduction NPL 9th August 2010 97 Monday June 20 11 Tools used here 1 Continuous domain 074001010 ww divide rational simplify etc Discretize resp setlunits setOunits A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 97 Tools used here Discretize 1 Continuous domain 2 Discrete domain Setting properties ozmodel resp divide rational simplify etc resp setlunits setOunits A LIPDA Introduction NPL 9th August 2010 97 Monday June 20 11 Tools used here 1 Continuous domain A Monday June 20 11 Discretize 2 Discrete domain Setting properties 074001010 ww divide rational simplify etc resp setlunits setOunits 3 Filter data LIPDA Introduction NPL 9th August 2010 97 Tools used here Discretize 2 Discrete domain 1 Continuous domain Setting properties resp 074001010 divide setlunits simplify rational setOunits etc 3 Filter data E LIPDA Introduction NPL 9th August 2010 97 Monday June 20 11 Pole zero models pole zero m
31. June 20 11 Log Scale Power Spectral Density Estimation e implementation of the algorithm described In e Measurement 39 2006 120 129 e same as psd but e Reduces individual point variance by adjusting the winaow length at each frequency e Frequency bins and number of averages are calculateo automatically e Slower because of requires use of DFT rather than FFT e Energy content of the spectrum Is preserved e Reduced resolution at high frequencies due to shorter window length e Lower uncertainty A Introduction NPL 9th August 2010 Monday June 20 11 f Log Scale Power Spectral Density Parameters e Parameters LONE rrF aes Desirea number of averages Anh Integer number 100 JOES integer number 1000 frequencies to calculate Emin Minimum segment length An integer number O E LIPDA Introduction NPL 9th August 2010 78 Monday June 20 11 Log scale Power Spectral Density Estimation Features e Multiple Inputs e S lpsd al a2 a3 plist e Matrix Inputs e S Ibsd fal a2 a9 a4 plist A Introduction NPL 9th August 2010 Monday June 20 11 79 PSD Exercise 3 e Using Ipsa e og scale psa calculation to reduce variance e Using MDC1 IFO data e Setting units e Setting plot features Simulated IFO data ASCII file window length window detrending 20 11 I PJ N
32. LES wee xs 1 MIILINEWIDTHS __ MIILEGENDS M LEGENDLOCAT NorthEast fp YERRU MIXSCALES rOa Set A Introduction NPL August 2010 Monday June 20 11 Parameter list editing Current Parameters Key Value Edit M FIGURE 0 80000000000 VIARRANGEWENstacked 00 FUNCTION po ll wes UNEWDTHS umawa IMILEGENDLOCATNonuhEast XE p p XSCALES IL A Introduction NPL August 2010 Monday June 20 11 Parameter list editing Current Parameters Key Value an FIGURE lt v T IMIARRANGEMENstacked FUNCTION bit LINECOLORS es 5 MIILINEWIDTHS ee MILEGENDS ee MJLEGENDLOCATNorthEast MixRR j C Fx j MIYRRL C wru EL XSCALES Set A Introduction NPL 9th August 2010 Monday June 20 11 Parameter list editing Current Parameters Different parameter sets Parameter Key Parameter value Key Value an M FIGURE TO ama ARRANGEMEN sac FUNCTION
33. PYING e Many methods can be used to modify existing objects some methods create new objects e gt gt a setName bob e the object a will be modified and its name changed e Copying gt gt b a setName bob e object will be copied The copy will get the name bob and a will be left intact e Some methods can not be used as modifiers A Introduction NPL 9th August 2010 Monday June 20 11 38 Help e Which properties does an object have e gt gt properties class name e gt gt properties object Note some properties are read only You need to check for the existence of a setter method like setName These methods take care of the history for you A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 39 Viewing history e We nave two static viewers e using graphviz recall the introduction e outputs vector graphics so can be used for huge history trees e using matlab e suitable for small history trees only e Use graphical explorer gt gt explorer ob e ook at the commands e gt gt type obj LTPDA Object explorer LTPDA Introduction NPL 9th August 2010 40 Monday June 20 11 Viewing history e We nave two static viewers e using graphviz recall the introduction e outputs vector graphics so can be used for huge history trees
34. d A Introduction NPL 9th August 2010 104 Monday June 20 11 Modeling system e Step by step 1 G OLG H G IS a pzmodel 2 Operate on setName simplify 3 CLG 1 1 OL CLG is NOT a pzmodel e Repeat loading H with delay e Working example Modeling a system e opic 4 gt Modeling a system A LIPDA Introduction NPL 9th August 2010 105 Monday June 20 11 Entering the discrete domain he LI PDA toolbox allows you to build digital filters e Discretizing your model e Example find the filters for H G OLG in our closed loop e Defining filter properties e xample Design a bandpass filter to evaluate power spectrum in a bandwidth e Filter constructors In LI PDA N M e MIIR IIR filters 7 2 0419 4 2 elk yin 0 e FIR filters Y b k z n k k 0 Introduction NPL August 2010 106 Monday June 20 11 By aiscretizing a transfer function e Syntax insert pzmodel into constructor INE Constructor Gd miir G plist fs 10 filter obj e Step by step 1 Discretize G H OLG 2 Compare continuous and digital response 3 Get filter coefficients e Delay is NOI used in the discretization e Working example Get filters for closed loop pzmodels e opic 4 gt How to filter data gt By discretizing Introduction NPL August 2010 107 M
35. ethod of the class Start my car use the method fly on my car e mean x use the method mean on the qata object x A Introduction NPL 9th August 2010 18 Monday June 20 11 method e Something that acts on an object instance of a class e Examples e start a car start is a method of the class car Start my car use the method fly on my car e mean x use the method mean on the data object x A LIPDA Introduction NPL August 2010 18 Monday June 20 11 Construct e special method of a class which builds an instance of the class builds an object e normally the method has the same name as the class e Examples e car blue builds a blue car e animall dog brown builds a brown dog which is a type of animal d LIPDA Introduction NPL 9th August 2010 Monday June 20 11 19 Construct e special method of a class which builds an instance of the class builds an object e normally the method has the same name as the class e Examples e car blue builds a blue e brown builds a brown dog which is a type of anima A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 19 property e property is one aspect of a class or object e Examples e car might have properties e make color top speed cost e an algorithm might have properties e inpu
36. gt gt al ao plist waveform noise type normal nsecs 1000 sigma 1 0 yunits m 5 gt gt 1plot al gt gt 51 al psd plist win BH92 gt gt P1 sqrt S1 gt gt 1plLot P1 A LIPDA Introduction NPL 9th August 2010 72 20 11 PSD Exercise 2 e More involved e Playing with parameters e Playing with windows BE e Adding block inputs outputs e Output to workspace Savi g O ut 9 ut q ata EGSE FEE y2 data individual plots 4 window length window detrending window overlap A Introduction NPL 9th August 2010 79 20 11 PSD Exercise 2 Spectral windows rx nn LTPDA Specwin Viewer Settings Build Window type BH92 a Window BH92 Window size 100 Window PSLL 100 PlotTime domain PlotFreq domain alpha 0 51 92 66 1 nenbw 2 0044 w3db 1 8962 flatness 0 8256 20 40 60 80 100 sample LA LIPDA Introduction NPL 9th August 2010 Monday June 20 11 PSD Exercise 2 e Adding inputs outputs to blocks Add output Copy Help Delete me Delete my pipes Q Playing with parameters Set name Set output pipe color Default Size v Toggle keep result A LIPDA Introduction NPL August 2010 75 Monday June 20 11 PSD Exercise 2 5 DSC A Introduction NPL 9th August 2010 Monday
37. is z installation nm Search Advances Filters 1 Create Peemalisk Foner fave Connon step record is kept of exactly what algorithm was applied to which object and I S RB9 with which parameters this way the result of a particular data analysis is one f System requirements Viewing Iseues 1 50 199 Print Reports Graad 1 Cov xaort 1 fest 122 4 nt 02 Category Severity Matus Updated Summary or more objects each containing the final result as numerical data together with a full processing history of how the result was achieved __ Downloads Latest version V2 3 k Release Schedule LTPOA includes algorithms and objects for lt 4 User manual DA LEPDA IDOUBOK resolved 2010 method to inherit from another 1 pre processing of time series data 4 Training Sessions 2 performing spectral analysis of various kinds XUNITS 3 performing digital filtering via IIR and FIR filters Documents eee dr ir 4 constructing pole zero models Bugs and features mE Papin is eines ay een SX 5 constructing state space models 6 and much more _ Troubleshooting Repository O MM 0 x LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Mailing lists e toda_releases aei mpg de e http lists aei mpg de cgi bin mailman listinfo Itpda releases e for releases of
38. l effort so far is about 10 years e Feedback Is essential e We will whenever we can A LIPDA Introduction NPL 9th August 2010 Why e Data analysis for LISA Pathfinder mission will be done on line e allow re planning of upcoming experiments ana investigations e Front line analysis done in STOC e ore planned data analysis pipelines for each experiment of the mission e Off line analysis e follow up problem solving etc e Hesults must have a long shelf life up to LISA commissioning e Requirements e flexible and robust data analysis environment e graphical user interface for non programming experts e high level of testing e automated capture of processing chain e data doesn t exist in isolation A Introduction NPL 9th August 2010 Monday June 20 11 Formalities e PDA e htto www lisa aei hnannover de Itoda e Bugs features e httos ed fok eu ltoda mantis LTPDA MATLABO toolbox for accountable and reproducible data analysis as Marte 2040 07 20 09 07 CEST Project PERROT Main My View Resort Daut Change 129 Account 1 Plugins LTPOA ts MATLAB toolbox that uses an object oriented approach to data analysts Objects are processed through data analysis pipeline At each analys
39. lgorithm version Parameter List Creation date time Input histories E Monday June 20 11 LIPDA Introduction NPL 9th August 2010 23 Methods gt gt methods Contents abs acos angle ao asin atan atan2 bilinfit bin data bsubmit LdWhitener1D cat char cohere complex compute confint conj consolidate conv convert COpy corr COS COV cpsd crbound created creator csvexport ctranspose curvefit de Lay delayEstimate demux det Monday June 20 11 detrend dft diag diff display dopplercorr downsamp le dropduplicates dsmean dx dy eig eq egmotion evaluateModel exp export fft fftfilt filtSubtract filter filtfilt find firwhiten fixfs fngen fromProcinfo fs gapfilling gapfillingoptim ge get getdof gnuplot gt heterodyne hist hist gauss hypot ifft imag index integrate interp interpmissing inv iplot iplotyy 15 1svalid join Lcohere lcpsd le len LinSubtract Lincom Linedetect linfit lisovfit log 10410 lpsd lscov Lt ltfe ltp ifo2acc max mcmc md5 mdci_contzact_utn mdci_1fo2acc_fd mdci_1fo2acc_fd_utn mdc1_1fo2acc_1inloop mdci ifo2cont utn mdci_1tfo2control 1 x2acc median min minus mode mpower mrdivide mtimes ne 15 noisegen2D norm normdist nsecs offset optSubtraction phase plot plus polyfit polynomfit
40. ls e rational model is defined by e Num and den coefficients L s bi s bo s e constructor RATIONAL e RATIONALS NOT be multiplied and divided e Working example Compute rational response e Topic 4 gt Create transfer func gt Create rational moael A Introduction NPL 9th August 2010 101 Monday June 20 11 Partial fraction models e partial fraction model is defined by e Poles residues and direct terms Ri 5 Pi N H s K s X pe e constructor PARFRAC e PARFRACs can be multiplied and divided e Working example Compute par frac response e opic 4 gt Create transfer func gt Create par frac model Introduction NPL August 2010 102 Monday June 20 11 Transforming models e Some of the possible transformations are Implemented in v2 3 e Works by inputting an object into constructor e e g rat rational ozm e Working example pzmodel gt rational ozmodel e 4 gt Transforming models between reoresentations Vive Introduction NPL August 2010 103 Monday June 20 11 Modeling system e Pole zero model e Modelling a closed loop system with pzmodel e Basic pzmodel operations Our system e problem e Assuming OLG and H known determine G an
41. me version input histories A LTPDA Introduction NPL params 10 Monday June 20 11 Tracking history name Version 2 Input 2 am params version EP ia i data version Input histories params version input histories A LTPDA Introduction NPL params 10 25 Monday June 20 11 mart alaorithms Algorithmic step Qu zm NL lt ascti import gt lt ascii import 2 Channel x12 Channel etal input history gt a k Algorithm history input ADI 02 history s P n M time series selection J time series selection 2 AOS hos 4 NEL M Ipsd with 15048 X IIR bandpass N 3 100 Kaiser Win 4 w d 1 0C mi Iz j Ke traceable results LIPDA Introduction NPL August 2010 26 Monday June 20 11 nistor Viewing aFILENAME mxuc2 12 20 COLUMNS 1 2 ROBUST no TYPE tsdata XUNITS Hxun YUNITS 1 xt COMMENT CHAR USE 5 FILEPATH setNiame NAME o nl YUNITS en a0 WV EFORM noise SIGMA 1 FS 1 MSEC S 1e 04 YURITS A 1 F21 23 PHI 0 T 1970 01 01 1 index l 1 422 FilEer mais e nois e z Itfe
42. nch LIPDA Introduction NPL 9th August 2010 68 Power Spectral Density Parameters CRE ET PSD gives Power Spectral Density Im 2 Hz 1 x ASD gives Amplitude Spectra Density Scale the output quantity im Hz 1 2 PS gives Power Spectrum m2 ASL gives Amplitude Spectrum Im Spectral window to multioly BH92 or Rectangular AS WIN user the data Dy iname or object oreterences 1 one window length ao data set id Or length number of points E Order of segment 1 no aetrenaing oraer detrending onor to O mean subtraction O WINGOWING N order N polynomial trend subtraction 1 taken trom window parameters ercentage overlap between adjacent segments i J 100 total overiap A 09 03 2009 LIPDA Training Session1 Hannover LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Power Spectral Density Estimation 5 e Features e Multiple Inputs e S psd al a2 a3 plist e Matrix Inputs e 5 1 a2 a3 a4 plist A Introduction NPL 9th August 2010 Monday June 20 11 70 PSD Exercise 1 Very simple idea White noise Parameters for psd all default A LIPDA Introduction NPL 9th August 2010 71 20 11 PSD Exercise 1 IDIOt Workbench implementation tsdata ao psd sart iplot white noise sart Matlab terminal implementation
43. o detrending oraer detrendina onor to O mean subtraction O windowing order N polynomial trend subtraction Percentage overlap 1 taken trom window parameters oetween adjacent O no overlap segments 100 total overlap Ana jor 1tfe 09 03 2009 LIPDA Training Session1 Hannover LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Exercise 1 e Using tfe e Simulated data input white noise e Band pass filter object e Filtering the Input noise e Adding output white noise e Estimate the transfer function filter object apply filter transfer function estimate A Introduction NPL 9th August 2010 91 Monday June 20 11 IFO Temperature Example e Estimating the empirical transfer function temperature gt position e preprocessed data e Evaluate PSD of T and x e Reduce the time range e Evaluate CPSD and cross coherence of T and x e Estimate the transfer function of Into x e Perform the noise projection Noise projection A Introduction NPL August 2010 Monday June 20 11 IFO Temperature Example e Ve are aiming to obtain sqrt Interferometer 7sqQrtitemp TIR FTN Il Hz amplitude 271 21 E LIPDA Introduction NPL 9th August 2010 Monday June 20
44. odel is defined by e Gain poles zeros delay H s GET 22 5 7 29 3 3 e s Do e PDA constructor PZMODEL e PZMODELS be multiplied and divided e Delay Is added or subtracted in such a case A Introduction NPL 9th August 2010 Monday June 20 11 98 About poles and zeros notation LIPDA Introduction NPL August 2010 Monday June 20 11 99 About poles zeros notation e Simple pole f 1 Hz A Introduction NPL 9th August 2010 Monday June 20 11 99 About poles and zeros notation e Simple pole f 1 Hz A Introduction NPL 9th August 2010 Monday June 20 11 Im He 99 About poles and zeros notation e Simple pole f 1 Hz e Pole pairs f 2 1 Hz Q A Introduction NPL 9th August 2010 Monday June 20 11 Im He 99 About poles and zeros notation e Simple pole f 1 Hz e Pole pairs f 2 1 Hz Q Q gt 0 5 underdamped A Introduction NPL 9th August 2010 Monday June 20 11 Im He 99 About poles and zeros notation e Simple pole f 1 Hz e Pole pairs f 2 1 Hz Q Q gt 0 5 underdamped Im He A Introduction NPL 9th August 2010 Monday June 20 11 Im He 99 About poles and zeros notation e Simple pole f 1 Hz e Pole pairs
45. onday June 20 11 By defining filter properties Design a bandpass filter ge 77 e Standard pre processing step used in LIP lab e Alternative to detrending 24 i 15 05 1 15 2 25 J 35 4 45 LH IX Time 5 s EE Edit View In He ud 2 Gd mir plist fs 32 47 order e Working example Bano Dass Introduction NPL August 2010 108 Monday June 20 11 IFO Temperature Example e Aim perform the analysis with toy model e Create transfer function models TMP IFO K2RAD e Discretize e Filter white noise data e Estimate transfer function topic 3 with synthetic data A LIPDA Introduction NPL August 2010 109 Monday June 20 11 IFO Temperature Example Figure 5 File Edit View Insert Tools Desktop Window Help The toy Uds RAS DS DE models amplitude rad resp K2RAD resp TMP gra TP NU E HI Phase deg L eS Frequency Hz Monday June 20 11 IFO Temperature Example e Step by step e 3enerate models e MP IFO K2RAD e Discretize e Build two white noise time series e Filter with the digital filters e Estimate transfer function e Project temperature noise Working example IFO rem ture LIPDA Introduction NPL Che LA Monday June 20 11
46. t type different configuration parameters A Introduction NPL 9th August 2010 20 Monday June 20 11 property e property is one aspect of a class or object e Examples ea car might have properties e make color top speed cost e an algorithm might have properties e input type different configuration parameters A LIPDA Introduction NPL August 2010 20 Monday June 20 11 nheritance e classes can inherit behaviour methods and properties from other classes vehicle color Start CN boat wheeled sails wheels bicycle Start LTPDA Introduction NPL 9th August 2010 21 20 11 nheritance e classes can inherit behaviour methods and properties from other classes vehicle color Start CN boat wheeled sails wheels bicycle Start LTPDA Introduction NPL 9th August 2010 20 11 20 11 Analysis Objects Aim to store data products Analysis Object creator date P address Hostname Operating System software versions Name Numerical data vectors Numerical x Provenance Creation date time Data Additional flags Additional Processing Name meta data x history ID number i i Comment pipeline file s A
47. xpressions JENN 2 A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 Special blocks Annotation eo ae pad Expressions gt E Eam Function A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 49 Special blocks Annotation MATLAB Expressions MATLAB Function uH LLERLLLLLLELLLCLLLLELLLE L 27 lt Constant A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 49 Special blocks Annotation MATLAB Expressions MATLAB Function Constant A LIPDA Introduction NPL 9th August 2010 Monday June 20 11 49 Special blocks Annotation T PE MATLAB Expressions gt EL MATLAB m Function ENS Constant Monday June 20 11 SSE LL Li EE LLLLLLL AS LLL LL LLL u m LLLI LL LL LL LLL LL Li LILI LIL LIL LI I TROT IE TT MEN ri A LIPDA Introduction NPL 9th August 2010 Export objects to workspace 49 Special blocks Import objects from another Annotation pipeline Export objects to workspace MATLAB Expression pressions l TE MEN MATLAB Function i Constant
Download Pdf Manuals
Related Search
Related Contents
Manhattan 475662 notebook accessory 紙幣払出機 BD-300 exemplar de assinante da imprensa nacional MDA200™ - Plantronics PNEUMATIC HAMMERS Carrier 33CS User's Manual H201-LUDL-96A602 / Issued prise en charge de l`hémochromatose liée au Eurit 547/557 - Swissvoice.net Copyright © All rights reserved.
Failed to retrieve file