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GGIG Graphical Interface Generator User Guide

1. L CAPRI tAbrit capri gams kodba s View Handling Windows 4 Supply details cluster view 0 7 mya Years Scenarios View type 2020 MTR_RD X Table iv Cereals Revenues Cereals Income Cereals Yield Cereals Crop Oilseeds Revenues Oilseeds Income Oilseeds Yield Oilseeds Crop Other arable crops Other arable crops Other arable crops Other arable crops Vege Euro ha or head Euro ha or head kg or 1 1000 share Animal Euro ha or head Euro ha or head kg or 1 1000 share Animal Revenues Income Yield Crop share Animal Perm head ha or head density head ha or head density Euro ha or head Euro ha or head kg or 11000 density Rever or 0 01 or 0 01 head ha or head or 0 01 Euro bal animals ha animals ha animals ha European Union 27 818 70 468 75 5524 26 30 49 893 92 17 03 2806 03 4 90 3274 41 1309 49 22201 53 3 96 a European Union 25 839 28 482 20 5758 41 30 13 994 25 566 36 3105 66 4 28 3261 98 1242 50 23464 87 4 03 E European Union 15 952 81 513 61 6318 16 25 80 1065 26 566 93 3388 98 3 49 3529 39 1301 68 23704 28 4 25 European Union 12 609 81 400 97 4278 35 42 65 722 94 475 00 2187 93 8 54 2286 71 1232 57 16985 51 3 18 European Union 10 578 69 419 93 4513 20 48 02 861 86 585 72 2563 58 7 56 1688 16 848 92 22102 42 3 10 Belgium 1177 16 561 93 8640 45 24 77 1409 88 778 13 4336 85 3 78 4412 24 1833 10 43975 38 12 23 Denmark 1013 76 352 26 6855 01 53 84 1249 95 497 01 3778 61 3 26 2916 66
2. Add Data ua ag New Group Laver Copy es Paste Layverts and in the case of the HSMUs add the HSMU_EU27 shp shapefile x Look in E EA caprit GIs cam es Folder Ea capri shp Shapetile Eilcapri_ MS shp shapefile SHSM ELIZ shp shapefile Name HSMU_EU2 shp Add show of type Datasets and Layers lpr Lancel Then choose add layers again and add the dfb file you have generated in the step explained above You may also add the file with the meta data Wolfgang Britz Version January 2015 93 GGIG Graphical Interface Generator User Guide x Look ir E E CAPRIgis El sam c Ei SI shrinked shp Shapefile SK cs Text File E SE_shrinked shp Shapefile smu dbf dBASE Table SMULESY Text File Eg solagra shp Shapefile EN Shapefile Hftest dbf dBASE Table test_meta dbf dBASE Table EA E UK cosy Text File Mame Jtest dbf Add Cancel show of type Datasets and Layers lyr Next we need to connect the HSMU geometry with the newly loaded data a process called joining in ArcGis In the context of HSMU EU27 choose Join and Relates then Join 29 Arc Toolbox 3D Analyst Tools Analysis Tools E e Layers E gg E caprit ors HSMU_EUZ7 E Ea Copy cols E ogg 6 CAPRIigis gt als Remove test IS Open Atkribute Table ability Tools L I lt zoom To Layer Remove Joints H
3. 73 Coals SILC ALLO IC LINO Casciato es det nad Sa sesa ae esas ene Votes teed T E 73 Integration distribution information in the map window c cc ceeeeeseeecceeeeeeeeeeeeeeeeeeeeaas 76 CONOR TAI ie a ansipecitneceeedet saniad suatudleen at aiaigecipsmnuedbseaed andes 76 Changing the way the lesend 18 Gra W Messi eases decantetebucniieedcasvetens oe a E eae 80 Chano me Metco Ine Map er cicadas base uke anita anni ecceseminaciee 82 Zooming in and out and navigating in the MAP ccececccccccccceeseseeeeeeceeeeeeeeeeeeeeceeeeeneas 82 Crettine ata TOR SpeciliC POlVGONS icine an teece tide lara deeb hee Arent denser ehduass 83 Highlighting specific regions in the map enessssssssoeeeesssssssseeersssssseseeresssssssseerresssssseee 84 NB a Ne Map ena E a 88 Addins region labelto TMS IMA ccnia ands asinct stoi a aE 88 Showing river ANGHCITICS aiisies as cs vanns code Wesnnsdceanacdevaacsvaxasoanddubessavishahacdseasssuaxainen eebenaacladabes 89 Wolfgang Britz Version January 2015 5 GGIG Graphical Interface Generator User Guide Stonne and reloading VOUP SCLIN OS asook a a a E a 90 Copying the map to the clipboard or to a file on disk sssssssoennssssssseseenssssssssseerrsssssssse 90 Schemes shown with the mapping viewer esssssssssooeesssssssseceersssssssscerrrsssssseereeessss 91 Popup menu Imta Dle Serina a 91 Exporting the data to ArcGIS sascun E E Et 92 Machine Tear ie sognene i A r E anil wcm
4. fert_out user input name type dims records long text When the task exploit gdx files is selected by pressing the related button four buttons are shown in the task panel The first one labelled load gdx files will open a file selection menu when pressed When the ok button of the dialogue is operated the content of the gdx file is partially loaded and a table is added to the right upper window of the application showing the parameters and sets comprised in the gdx files along with their number of dimensions and records When the close button next to the table is pressed the table is deleted Pressing the load gdx file again will add more tables One parameter from each table may be selected pressing the crtl key when clicking with the mouse de selects If several parameters from one file need to be loaded the user may open the same file several time The content of the different parameters is merged together and the parameters themselves span an additional data dimension If the user does not provide input in the first column of the tables labelled user input the program will generate names automatically The data loaded are shown in the table tool described above The user can use view definitions stored in a XML file to the tables by pressing the enabling the Use table definitions from tick box and may use the Set XML table definition file button to change the file to
5. Utilities Equation and variable viewer Background and motivation Complex GAMS code and related models such as the market model of CAPRI with its 70 000 equations and variables are very hard to debug The model listing produced by GAMS from such a model is quite long and filtering out e g all lines belonging to a certain market not possible with all editors Further on linking the listing to the equation structure of the model is also far from easy That paper describes a utility linked into the GGIG the GUI generator used by CAPRI which supports working with large model outputs and more generally complex GAMS projects with many symbols The new tool also incorporates the functionality of the existing GDX Viewer comprised in the GUI The tool can be used to track changes to symbols in the GAMS code by producing a range of GDX files currently up to 5 at different execution points Wolfgang Britz Version January 2015 127 GGIG Graphical Interface Generator User Guide An overview on the viewer S Selection Selection v_GLDemandFS AFR_LDC __ y_GLDemandFS AFR_REST Variable selection C DemandFS AL000000 v_GLDemandFS ALG E Use indents in equation output E Use small font for non selected var terms S Gams includes m T britz capri gams capmod gms List of tables loaded from GDX file s gams util acronyms gms gams util global_settings gms gams sets gms Sont
6. Selection dialog for Table rows x Enter search pattern in Field and use buttons or use mouse to define selections pKoo1_2_3 Clear selection add pattern to labels Clear selection add pattern to keys Add pattern to ka list of selected items and define the selected items according ti Remove pattern From labels Remove pattern From keys DKOOL 2 3 4H22676 DKOOL 2 3 4H22677 DKOOL 2 3 4H22678 DKOOL 2 3 4H22679 DKOOL 2 3 4H22680 DKOOL 2 3 4H22681 DKOOL 2 3 4H22682 DKOOL 2 3 4H22683 DKOOL 2 3 4H22684 DKOOL 2 3 4H22685 DKOOL 2 3 4H22686 DKOOL 2 3 4H22687 OK Cancel Now we may e g select only the HSMU belonging to the FSS region DKOOO_1_2_3 by typing DKOO1 2 3 in the left input box and then choosing Clear selection add pattern to labels Afterwards the map will look as shown below CAPRI e caprii gams e 215 x View Handling Windows Exploitation of spatial results Data iew 1 a p 101 x Activity Items Table uaa wd No 5 a Mineral Fertilizer Consumption Nitrogen kg N ha gri Env indicators driving forces Scenario BASE SaaS es Ess E E A 0 00 lt 0 00 lt 15 34 lt 31 18 lt 61 94 lt 450 86 CAPRI GUI Version 1 2 3 March 2007 User name Wolfgang Britz User type Administrator The tabular view opens up the possibility of using numeric filters an option discussed in the following Take for example
7. Definitions found in DATARM WORPRICES GMS Name Type Description WorPrices capreg capmod Parameter Symbol usage in the file Wolfgang Britz Version January 2015 125 GGIG Graphical Interface Generator User Guide Example for a page for the a set CAPRI technical documentation Automatically generated from t britz capri gams captrd ref open all close all 4 Types H Parameters Ey Sets captrd capreg _ capmod at least in one project gt Files Equations Variables Elements captrd C capreg C capmod W E at least in one project H 0 Models H Acronyms H Functions SourceFiles C captrd capreg C capmod at least in one project File list CAPRI technical documentation Automatically generated from t britz capri gams captrd_ref t britz capri gams capreg ref t britz capri gams capmod ref at 21 07 2008 09 30 24 H Equations Variables captrd capreg C capmod gt at least in one project ES Elements captrd capreg capmod at least in one project H Models H Acronyms H Functions El SourceFiles captrd L capreg capmod Ul at least in one project A K M la Top Definitions Assignments References Ele Set MAACT Name MAACT MPACT Type Set Description Animal production activities comprised in model Number of dimension
8. Endogenous bio fuel markets in global market model ON Policy blocks additional geographical layery OFF Endogenous margins between trade block and country prices OFF Endogenous young animal markets ON Regional CGEs OFF Number of terations 99 0 Use lower price iterations weights after tteration 20 0 Alternative GAMS license file for GHG emission estimation gamslice_cplex defauit Agaregates for activties and commodities ON Environmental Indcators ON T bntz capn_liatse gams Life cycle assessment for energy ON t britz resuits_liaise Multi functionality indicators ON t britz capri_haise dat Iteration tracking ON null Sensitivty experiments with features in supply model ON Endogenous net migration ON fun Do 24 Jul 14 07 40 32 scen fortran Do 24 Jul 14 07 53 19 0 9gig an 12 min and 46 secs Run scenano RUN with market undefined m scenario 0_1Ist Fixed budget for factor subsidies ON Capital stock DPSV rule default Labor supply Wage curve default Oe ed a ollie Oak I odo itt Wolfgang Britz Version January 2015 120 GGIG Graphical Interface Generator User Guide Utilities Generate GAMS documentation in HTML pages Graph Panel to steer GAMS documentation generation GAMS documentation generation Directory with input files t britz capri codeDocinput S
9. Producing input for the view with GAMS The viewer can be used in different configurations which are available via the File run menu Wolfgang Britz Version January 2015 128 GGIG Graphical Interface Generator User Guide File Load only GDX files into viewer Load GAMS files and if existing GDX files into viewer Load convert output into viewer Load convert output and GAMS file into viewer e Load only GDX files into viewer comprises basically the same functionality as the existing GDX Viewer However the selection panel and the view on the symbol are both visible at the same time ssq Use indents in equation output vB Variable selection Equation selection ie F Use table definitions from null Use small font for non selected var terms vo 2 i pv_bevFuncIntAddFac m i E m E Sort code lists F Show dialog to link GDX dimensions to sets List of tables loaded from GDX file s T britz capri gams convert_market_model_2 gdx user input name Belgium and Luxembourg Denmark Germany a O m m m m m rm e Load GAMS files and if existing GDX files into viewer With a GAMS file and one or several GDX file browse the source code and click on highlighted symbols to load them from the GDX file s That is basica
10. User Guide 5 Map option dialogue 23 T Treat zeros as missing values T Use area weights for classification Draw in high quality Emboss map gt 0 gray O none lt 0 colored embossing o Scaling model for flows Linear Log Poly European Union 27 European Union 25 European Union 15 European Union 10 Bulgaria and Romania Europe Non EU Mediterranean countries induding Turkey and Morocco Middle East Africa North America USA Canada Mexico Middle and South America Asia Australia and New Zealand European Union 27 European Union 25 European Union 15 European Union 12 European Union 10 Bulgaria and Romania x i Select sources to show Flows Min Display Width 0 i Flows Max Display Width 25 Show histogram V Show distribution circles for observations 4 Show distribution rectangles for dasses Region labels Label options Legend Separate rectangles v Draw outline of all polygons X Standard map title v Dimension shown in columns of result window for current region Exporter X Dimension shown in rows of result window for current region Activity X Resolution factor for printing file output compared to screen 15 ok J apply store settings load settings The main options of interest for flow maps are the scaling model and the display width The following scaling models are available e Linear the width is determined by relating the flow qu
11. as always with maps be placed in the rows of the underlying tables and the cakes are calculated from the data in the columns It 1s possible to produce maps for different scenarios when those are placed in the column groups as shown below The size of the charts depends mainly on the bounds of the underlying polygon so that smaller countries have smaller pies The settings for pie chart diagrams see Pie charts can be applied to that view Colored thematic maps For CAPRI the GUI currently provides geometries for NUTS 2 regions Member States the regions with behavioral functions in the market model trade blocks in the market model and finally the Homogenous Soil Mapping Units 1x1 km resolution underlying the spatial down scaling component The geometries are always linked to the rows of the underlying table Wolfgang Britz Version January 2015 68 GGIG Graphical Interface Generator User Guide The most obvious way to visualize results is the use of thematic maps This holds true for NUTS2 results but even more so for the results at the HSMU level When starting the GUI the mapping view uses some pre sets which can be interactively changed as described below The following screen shot shows the result of first loading the base year results from the spatial dis aggregation for Denmark and then switching from the tabular to the mapping view As with other views the content of the map can be changed by working with th
12. or update to revision to download the version to compare to from the server Wolfgang Britz Version January 2015 139 GGIG Graphical Interface Generator User Guide CAPRI worksteps Result exploetation CAPRI tasks Country selection ES Span FR France tional database Prepare na amp Finish national database IT italy Find No of fts in Nuts2 PAE The Netherlands IAT Austria Define fts from FSS Build regional time series Build regional database Build global database build HSMU database Year selection pais There are now different way how to proceed GGIG as GDXDIFF One can mimic the behavior of GDXDIFF by using as the view No table plrv sizs o of olec a OE e g That allows scrolling through any cell but requires familiarity with the codes and the structure of the data set one analyzes One might end up with a view as below the first to do is to pivot POTA TOMA OFRU GTR TAGR TABO Wolfgang Britz Version January 2015 140 GGIG Graphical Interface Generator User Guide Imagine you want to check acreages across the regions A good way to proceed is to put the regions in the rows and the years in the columns as shown below S Transposing and i Table control area Animation Box 1 Product 250 Box 2 versions 2 Box 3 Activity 205 0 Table column groups 26 Table columns years 26 387 Tabl
13. 42 93 43 81 49 50 53 63 50 74 50 15 51 97 51 53 50 86 47 69 A 4805 70 4598 54 4774 46 5476 63 6087 76 6257 88 6464 73 6691 29 6946 60 7028 16 90 36 90 33 30 15 89 94 30 05 89 69 89 77 89 59 89 28 89 67 Utilized agricultural area Oil 4 1073 71 1489 72 1752 25 6 26 7 24 11 59 Rape 11 96 16 81 Comparing two GDX files with GGIG File GUI Settings Help A GDX Viewer e CSV to GDX Start Command prompt Start equation and variable viewer CA Build HTML documentation SVN update Use t britz capri gams util cleanUpGamsDir bat to clean up source directory Find No of fts in Nuts2 GGIG also comprises a GDX viewer Pefneftsfrom rss Into which several GDX files can be loaded and compared as discussed above Index Batch execution 115 Equation and variable viewer 129 Clipboard export 35 Export to file 36 Column and row selection 27 GDX viewer 136 Data export 36 Generate GAMS documentation 122 Data export to ArcGIS 93 Generating coordinate files 137 Data export to EXCEL 40 Graphics 48 Drop down boxes for selections 26 Bar charts 55 Wolfgang Britz Version January 2015 143 GGIG Graphical Interface Generator User Guide Box and whisker charts 60 Clipboard export 53 Cummulative distribution 62 Deviation renderer 63 Export to file 52 Histograms 61 Line and point charts 56 Line chart with mean min max 64 Markov charts 66 Pie charts 58 Setting colors 51 Spider plots 59 Histog
14. However the GAMS processor will run some finalisation tasks as removing temporary files and directories Format of the batch execution steering file e Generally each line in the file comprises a keyword following by an equal sign and the related setting e Comment lines start with an asterisk Blocks comment are between the keyword ontext and offtext which thus allows easily excluding blocks of liens from execution e The keyword exit prevents further processing Header A batch execution file starts with a header which defines settings otherwise entered by user under settings dialogue of the GUI 1 e directories the GAMS engine the use and some further settings Wolfgang Britz Version January 2015 115 GGIG Graphical Interface Generator User Guide Oe E R R E gams engine d GAH 23 9 gams exe user wolfgangb work dir t britz capri gams where the HTML page and the listings will be stored output dir d temp batch tCribritz results d 45crdir res dir scr dir gams options scrdir d scrdir threads on the following settings will write the results into different directories The directory structure will be automatically generated restartOutDir t britz capri restart resultsOutDir t britz results number of processors 36 processor speed relative 168 number of iterations 99 Settings for tasks Each include file generated by GG
15. but useful while playing around with classification methods and class definition are the distribution dots which can be added They carry additional information on the locationof values in different classes C _ a ea D o eee 0 00 49 28 71 56 82 68 450 86 Finally switching to linear or logarithmic may be a way to help reading the map a 43 7283 451 Color table The color table or color map defines the colors used for the classes When choosing the color model keep in mind that colors carry a meaning red e g is generally interpreted as dangerous Equally it is important to think about the final medium with which the map will Wolfgang Britz Version January 2015 76 GGIG Graphical Interface Generator User Guide be published Exporting colored maps to a black white device will render it almost impossible to read the map It is best to try different color tables and different classification methods on your data The following color models are currently available named according to the data order from minimal to maximal value e Green Yellow Red standard Normally the middle class is drawn in yellow smaller values in shades between yellow and green and larger ones from green to red This should be applied e g to environmental indicators where the damage increases with the value of the indicator e Red Yellow Green as above only that high values are shown in green Should be
16. follows the green box shows the first Q1 to third quartile Q3 so that the width of the box is equal to the so called inner quartile range IRQ The blue whiskers are defined by Q1 minus 1 5 times IQR and Q3 plus 1 5 times IQR but bounded by the minimum and maximum of the observations In many applications any value falling outside that range is classified as a mild outlier The red dotted whiskers are at Q1 minus 3 times IQR and Q3 plus 3 times IQR but bounded by the minimum and maximum of the observations In many applications any value falling outside that range 1s classified as a stronger outlier The user can restrict the plotted range as to exclude stronger outliers If outliers are present the red dotted whiskers at the tail with strong outliers are removed The blue dotted lines show the mean and one standard deviation around the mean For a normal distribution that would cover around 2 3 of the observations The black dotted lines in the histogram show the class limits used for the colour model The bottom reports some descriptive statistics The technical implementation is set up according to the way maps are drawn the population consists of all values in the rows and the columns of the table and thus differs from the outlier control which treats each column as a separate set of observations Wolfgang Britz Version January 2015 33 GGIG Graphical Interface Generator User Guide Histogram for Build reg
17. 17 317 oo o 5 lt 586 84 586 835 Ta fT Cummulative distribution graph Frequency groups 1 oo JV Draw mean and 1 std dev Cummulative distribution graph v Frequency groups 10H V Draw mean and 1 std dev 0 00 51 86 112 82 0 00 51 86 112 82 i it i 1227 i oj io 0 00 293 42 586 84 0 00 i i 293 42 586 84 55 96 141 55 55 96 141 55 Show small circles showing distribution of regions n 1230 0 Show small circles showing distribution of regions n 1230 0 in 0 0 Reena Min 0 0 IV Show rectangle representating distribution of classes hean 55 963432 V Show rectangle representating distribution of classes Mean 55 963432 i Median 30 241 Median 30 241 L d S ti tangl v Legend Separate rectangles v Sci asi sic Max 586 8354 Max 586 8354 oraw outline in same color v Std Dev 85 59119 praw outline in same color v Std Dev 85 59119 Etandard map title v Etandard map title v Dimension shown in columns of result window For current region Scenario v Dimension shown in columns of result window for current region Scenario v Dimension shown in rows of result window for current region hide X Dimension shown in rows of result window For current region hide z ok store settings load settings ok store settings load settings Manual set colors Finally the user can choose its own colors by double clicking in a color field in the legend table That should only be done
18. 55 449 85 200 11 2525 70 22 00 7 14 red4 23 44 2980 59 451 59 201 50 2528 99 22 00 7 15 red5 22 67 2985 35 453 17 202 68 2532 18 22 00 7 16 22 01 2986 51 453 38 202 64 2533 13 22 00 7 16 redT 21 35 2987 75 453 57 202 55 253417 22 00 7145 redg 20 70 2989 09 453 73 202 35 2535 36 22 00 7 45 20 04 2990 52 453 89 202 15 2536 62 22 00 7 15 redi 19 33 2992 08 454 18 202 11 2537 90 22 00 7 45 Fee tee EE 25 71 2980 48 451 46 201 29 2529 02 22 00 7 44 ed redi 25 41 2940 22 437 50 190 10 2502 72 22 00 7 05 red 24 75 2938 59 437 07 189 89 I 2501 52 22 00 7 05 cans 24 10 2937 43 436 64 189 51 2500 79 22 00 T04 g 23 43 2938 74 437 02 189 74 2501 71 22 00 7 05 reds 22 80 2937 10 436 33 189 04 2500 77 22 00 7 04 ae 22 13 2939 59 437 03 189 44 2502 56 22 00 7 04 The full functionality is only available if a table definition file see programmer guide matching the structure of the parameters in the GDX file 1s provided The multi dimensional viewer with pivoting and exporting possibilities The results are as mentioned above loaded from one or several GDX containers and comprise the content of one or several GAMS parameters with up to 10 dimensions The resulting data cube is loaded in a spreadsheet like viewer with pivot possibilities The user may switch between a tabular view of the data or different types of graphs line bar pie spider or maps Scroll down boxes allow the user to rotate through data dimensio
19. 757 41 22763 14 6 34 Germany 1059 39 441 45 7527 86 39 25 1314 72 638 80 4251 82 7 29 3260 80 1405 04 44224 29 4 69 Austria 889 55 497 57 6973 35 21 66 947 31 675 02 2404 66 3 17 2177 94 729 63 40199 86 3 16 Reload Netherlands 1266 88 711 29 8827 19 Copy to Clipboard 868 24 764 83 3095 68 0 52 9119 67 3764 04 48370 33 13 47 Fa 1085 12 438 20 7479 60 Export Data 014 91 456 67 3405 41 6 27 3865 74 1820 07 42422 31 3 03 Pivoting Portugal 746 24 356 13 3898 35 Gustamizeannle 191 71 144 97 497 99 0 60 3672 36 32871 44 41242 75 0 22 er Statistics Spain 593 53 532 23 3498 86 433 16 473 81 1072 65 1 29 2071 26 698 01 4844 85 6 19 Classify 4 Classify numeric Greece 794 69 891 07 4133 29 76 33 1655 66 0 04 4215 46 3829 68 2709 12 8 62 m Clasify nominal C jew a Italy 1053 24 706 05 5754 93 Do not classify 142 60 2871 15 1 68 4297 29 2961 06 11189 96 2 55 Table View Ireland 1082 81 676 66 8583 71 urs 1320 34 889 34 3681 85 0 02 7271 07 1208 30 16318 50 0 73 Finland 477 95 393 91 3614 87 47 08 417 17 512 714 1258 13 3 25 2517 05 965 92 23951 47 2 04 Sweden 751 59 251 31 5491 85 29 06 900 79 381 42 2741 29 1 62 2865 73 893 00 30978 91 3 04 United Kingdom 1188 89 616 00 7806 05 17 47 1285 81 755 39 3666 38 3 59 4194 67 2695 73 30938 21 2 92 Czech Republic 730 23 604 25 5049 95 45 72 869 85 663 61 2396 48 13 74 1956 81 726 90 20829 30 5 08 Estonia 462 43 364 06 4001 38 44 74 775 63 579 09 2255 56 10 52 1419 67 706 33 8587 71 0 81 _ Torna _ _ neco cer
20. A zoom To Make visible Relate Visible Scale Range b Remove Relates P Use Symbol Levels Selection Label Features Convert Labels to Annotation Convert Features to Graphics Convert Symbology to Representation Data Save 44s Layer File Properties That will open the join dialogue as shown below Wolfgang Britz Version January 2015 94 GGIG Graphical Interface Generator User Guide x Join lets you append additional data to this layer s attribute table so you can for example symbolize the layers features using this data What do wou want to jor to this layer Join attributes from a table 1 Choose the field in this layer that the join will be based on FID GAIDCODE M Show the attribute tables of layers in this list 3 Choose the field in the table to base the join on Advanced About Jomning Data Ik Cancel Make sure that Join attributes from a table is set in the first drop down box and under 1 select HSMU 1 e the filed in the HSMU_27 geometry where the codes for the HSMU polygons are stored Use the name of the exported dbf table under 2 and select the field Regions a the field name are restriced to 10 chars under 3 Then press the button labeled advanced and chose the radiobutton keep only matching records If you are asked to build index confirm Wolfgang Britz Version January 2015 95 GGIG Graphical Interfac
21. Animal density Class numeric Class Class numeric Num v Visualize All Remove 1096 43 2190 78 The reader can manually remove attributes and the reduced set of attributes will then passed to the filter and classifier However the attribute selection is not maintained when new data are loaded The Visualize All button produces graphs of all current attributes Wolfgang Britz Version January 2015 107 GGIG Graphical Interface Generator User Guide Summary The integration of algorithms from machine learning based on the WEKA library and GUI offers new possibilities to systematic analysis of result sets Thanks to the open source policy of WEKA it was possible to integrate these powerful tools transparently in the CAPRI GUI Depending on the experiences made over the next months further links might be included e g rending clusters in maps References Ian H Witten Eibe Frank Mark A Hall 2011 Data Mining Practical Machine Learning Tools and Techniges Third edition Elsevier Amsterdam 630 pages Remco R Bouckaert Eibe Frank Mark Hall Richard Kirkby Peter Reutemann Alex Seewald David Scuse 2011 WEKA Manual for Version 3 6 5 June 28 2011 University of Waikato Hamilton New Zealand Robert J McQueen Stephen R Garner Craig G Nevill Manning Ian H Witten 1995 Applying machine learning to agricultural data Computers and Electr
22. ON Sensitivity experiments with features in supply model ON Endogenous net migration ON Fixed budget for factor subsidies ON Capital stock DPSU rule Labor supply Wage curve Capital mobility Sluggish Labor mobility Sluggish Land mobility Sluggish Closure current account and trade balance Exchange rate Closure household account Spending Closure government account Spending Load meta information from older task ON Solution printing Suppress Determine point price elasticities OFF Print gams code to listing offListing Solprint On Limrow 6 6 Limcol 6 6 Maximum number of pre steps market model 15 6 Solution print at preparatory solve OFF Abort after preparatory solve OFF Solution print for pre steps in 1st iteration with abort OFF Plus iterlim to zero for 1st pre steps in 1st iteration OFF Number of presteps before abort 1 86 Kill simini file OFF Additional result type identifier execute gamsrun SOFFTEXT end batch execution file Settings which do not change between tasks need not to be repeated executing e g different scenarios is then simply done by changing the scenario file followed by the keyword execute as shown below Wolfgang Britz Version January 2015 117 GGIG Graphical Interface Generator User Guide scen name HTR DECPL execute gamsrun scen name HTR GREENGRASS execute gamsrun scen name HTR GREENCKOPD execute gamsrun scen name HTR GREENSET execu
23. RS Quotas SUGB Y DATA RS Quotas SUGA SSIMY DATA RS Quotas SUGB SSIMY declarations of interfact to regional CGEs model in GEMPACK Sifi tregcget on SINCLUDE regcge declarations gms definition of environmental permit trading module SifI tghgAbatement ON Sinclude permits ghg emission trade model gms v_actLevl L RS MPACT A DATA RS MPACT LEVL Y rAd p technFact RS MPACT LEVL delete results for regions not in curernt run Loading symbols The GAMS code highlights in blue all symbols sets parameter variables and equations found in the GDX file These symbols can be opened in the GDX viewer by a mouse click in the GAMS file viewer If several GDX files are provided the symbol will be loaded from all the GDX files where there are non empty records That allows for a very rapid inspection of the data Alternatively select the GDX symbol table from the Views menu sx 2 Symbols in GDX List of tables loaded from GDX file s os es T britz capri gams convert_market_model_2 gdx W W In table above symbols can be selected by the mouse As in the GDX Viewer one might select several symbols with the same number of dimensions Wolfgang Britz Version January 2
24. Scatter pots Y Los 4 s06 d 1 05 4 Los 4 0 150 7 03 4 102 4 1 01 4 0 125 4 rj 100 4 ze B oo 4 0 100 4 p 0 98 4 R 0 97 0 075 S 0 96 4 0 95 7 0 94 4 n 0 050 4 0 93 4 eg 0 025 7 0 01 4 0 90 4 o o00 H ik I 0 900 0 925 0 950 0 975 1 000 1 025 1 050 0 800 0 825 0 850 0 675 0 900 0 925 0 950 0 975 00 e Gr ns and Crops Livesteck and Meat Products Processed Pood 0 300 4 n me pre _ 0 275 4 le ee 9 25 o gt o g o 3 a amp 0 9 o S bg Ae A Fe me E 00004 tae E o a alll a la Y J o y o 2 o a aes i il ooo n iy fa i i i i i i i i i i i 0 800 0 525 0 550 0 575 0 900 0 925 0 950 0 975 1 000 1 025 0 91 0 92 0 93 0 94 0 95 0 96 0 97 0 98 0 99 1 00 mns a pa Livestock and Mast Products Processed Food gt Fa amp ax artha a fre eo O f 0 5 Aa F p g Bo Pi P Fo A 0 075 4 7 _ 5 ze gt eee gt aoso 4 B il Il l I 1 aon 1a I i 0 9 0 91 0 92 0 93 0 94 0 95 0 96 0 97 0 98 0 99 1 00 1 04 on or or feat Prod Processed food m ned Reg n Une The histograms can be customized as discussed in the section above the way the observation is organized is identical to histograms as well For the scatter plots three options can be changed Options for Heat Maps and scatter plots Show last column Show regression line in scatter plots Bins for xy scatter zero default rule o Dot size for scatter plots 2 Changing th
25. Wolfgang Britz Version January 2015 87 GGIG Graphical Interface Generator User Guide Updating the map Generally the map is updated automatically when the user changes an option with an impact on its layout as long as the number of visible polygons is below 20 000 If that amount is exceeded the classification dialogue is updated immediately but not the underlying map In order to apply the changes the apply button must be clicked on The user is informed that the ok button will also update the map so that an apply immediately before an ok is not necessary Adding region label to the map In the map option dialogue tick the box Show regions labels in map k _ Region labels to add labels to the largest polygon for each region as shown below fe ix SSADMHARS By clicking on the button the Region label steering dialogue box opens which allows changing some settings For maps with just a few regions or when zooming it might be worthwhile trying to play around with the action to improve labeling Region labels steering Font size For region labels N x location for region labels y location for region labels Labels Only short labels C Use shadow effect Use mass center Weight For distances to neighbouring labels Weight For overlap Wolfgang Britz Version January 2015 88 GGIG Graphical Interface Generator User Guide Showing rive
26. a robust estimator for the mean The IQR is multiplied with a user defined factor B added to Q3 respectively subtracted from Q1 to define the lower and upper bound for regular values The default value for factor P is 1 5 In opposite to the mean and the standard deviation the quartiles and the median are not affected by outliers at the tails of the distribution allowing for a rather robust way to filter outliers 03 Bigg TOR gt x gt Q1 Bigg TOR Conformity based on relation of distances Here the following formulae are used taken from Last amp Kandel 2001 Wolfgang Britz Version January 2015 45 GGIG Graphical Interface Generator User Guide L a 1er C Xitm in TA 9f sexp Aes Xi A They define conformity from below and above by comparing the distance from the current value to its neighbour in relation to the average distance for a predefined group size m Before the formulae are applied the values are sorted In opposite to the outliers based on first and second moment the method is also able to detect outliers in between clusters of values Inside such a cluster differences in distances between values are small so that the relation between the distance to the next neighbour and the average distance between the neighbour and its m th neighbour is around unity The big advantage of the approach 1s that it does neither assume a certain functional form for the distribution as in
27. a a File Settings Utilities GUI Help CAPRI worksteps Scenario description Build database Enter scenario name Generate baseline Run scenario CAPRI tasks Enter scenario description Define scenario Run scenario with market model Run scenario without market model Scenario elements Downscale scenario results t britz capri gams scen base_scenarios mtr_rd gms Define basis scenario file Sontext i Run policy experiment with CGE Scenario categories 3 J base scenarios e fi bio fuels demand shocks german renewable energy legislation ghg emission abatement CAPRI project GAMS file MTR_RD GMS input demand ne purpose Health check scenario with rural development elements en Current baseline scenario NLimits eee author Torbj rn Jansson SLU set aside date 09 02 10 trade policies refDoc yield shocks seeAlso calledBy Sofftext GGIG INCLUDE policy mtr market gms n a GAMS Graphical User Interface Generator Wolfgang Britz 2012 i L x University Bonn INCLUDE pol_input mtr_hc gms Institute for wricle62 ome sas Food and Resource Economics Store scenario CAPRI Ini file caprinew ini User name undefined User type administrator Choosing the scenario editor adds the panel with GUI elements shown above The panel consist of two major panes 1 A top pane where the user can enter
28. a name for his new scenario and a description text Wolfgang Britz Version January 2015 109 GGIG Graphical Interface Generator User Guide 2 A bottom pane where the user can define the base scenario to start with currently in the trunk MTR RD gms and the snippet to add The available snippets and their structure are shown on the left hand side in an expandable tree which shows the sub directories found under gams scen with the exclusion of a sub directory called baseScenarios and the svn directories Empty directories are not shown The user may select any number of snippets even several from the same sub directory Double clicking on one of the snippets shows the content of the file on the right hand side so that the user can inspect the code as seen below in more detail GAMS keywords are shown in red comments in yellow and strings in green He can also edit the file changes are shown in blue Once changes had been saved the tree shows a user modified behind the category The user can also remove the changes from snippets Scenario elements D TS2009 gams scen baseScenarios mtrstd gms Define basis scenario file Scenario categories A 5 Biofuels biof D10E2 B B Premiums 9 Coupling Fully decoupled C partial decoupling H Distribution Farm premium option kill COPT 5 WTO Policy wtohrb s MBE corti Coupling degree for each payment and member state BLOOO
29. at a later time e Ensures that each new run generates its own listing file which can be opened from the HTML page e Allows storing the output of the different runs in a separate directory while reading input from unchanged result directories The purpose of the batch execution facility is therefore at least twofold On the one hand it allows setting up test suits for the GAMS code of a project such as checking for compilation without errors for all tasks and different settings such as with and without market parts etc Secondly production runs of e g different scenarios can be started automatically Timer facilities allow starting the batch execution at a pre scheduled time Along with functionalities Wolfgang Britz Version January 2015 114 GGIG Graphical Interface Generator User Guide to compare in a more or less automated way differences in results between versions the batch facility is one important step towards quality control The batch execution allows starting a file defining settings and tasks from the different CAPRI work steps and executing them without user intervention Once started the batch processor may be stopped so that the currently running GAMS program ends on its own end batch execution after next finalised GAMS step or by sending a CTRL C to the GAMS program It will continue to run until the GAMS processor notices the CTRL C which may take a while and then end with an error code
30. attributes in many cases reflecting the correlation between attributes In order to use the result from the filter run click on the result set in the result list and chose Use output for classification Wolfgang Britz Version January 2015 106 GGIG Graphical Interface Generator User Guide 5 Weka Explorer GUI Supply details mapping view 0 all Cereals Income 2020 MTR_RDQuantile 20 26 35 Classify Cluster Filter view and Select Attribute Evaluator Choose CfsSubsetEval Search Method Choose GeneticSearch Z 20 G 20 C 0 6 M 0 033 R 20 51 Attribute Selection Mode Attribute selection output full aS Ur IIIT voy tuto iy is eu T ee ort a CaL etles 0 48977 0 44828 l 2 5 14 1 19 21 22 24 30 31 36 37 39 Cross validation Folds 10 0 52524 0 56472 256 86 1417 20 21 22 24 30 31 33 34 3 Seed 1 0 53106 0 58384 25681417 19 20 22 27 31 36 37 39 40 i Attribute Subset Evaluator supervised Class numeric 46 Class numeric Num Class numeric CFS Subset Evaluator stat Stop Including locally predictive attributes Result list right click For options 20 26 51 GeneticSearch Selected attributes 1 2 5 6 7 10 17 19 20 21 22 27 31 37 39 15 Coxeals Revenues als Income Use output for classification Do not longer use output for classification 115 Production per UAAR keds Revenues View in main window keds Income View in separate window peds Production per UAAR
31. current implementation is based on the interaction of two views e A map or a table using classification colors it defines the class attribute dependent variable of the data to classify For classification algorithms which require nominal values the assigned class from the classification defining the color scheme is used e A table with the explanatory attributes Both tables must be as conventionally in the exploitation tools the observations in the rows For maps each map carries the data for a region But one might also work with tables where the observations are not strictly geo referenced entities such as farm types The GUI will automatically send new data to the WEKA GUI if either the map or the table using classification colors or the table providing the explanatory attributes is updated by a user action The basic data flow is shown in the graphic below Class attribute Preprocess numeric or nominal select attributes remove obs WEKA Filter i Visualize bridge select attributes a _ Classify Additional attributes Wolfgang Britz Version January 2015 102 GGIG Graphical Interface Generator User Guide Interaction between the GGIG GUI and WEKA Let s construct an example based on CAPRI we want to check if the income change in cereals in a simulation depends on the crop shares of cereals and the yields In order to do so we first render our map as usual table Farm details ma
32. even if a different table is chosen e Show histogram A histogram is shown additionally to the current view as a separate window The current window might however hide the histogram window The Windos menu can be used to bring the histogram windows to the front EE a g md eta Supply details 0 Histogram for Supply details 0 European Union e Use classification colors for tables Use the colours which would be used to colour the regions in a thematic map to colour the numbers shown in tables e Use of short code and or long texts Normally long texts are shown to the user Experience model developers might prefer to use with the actual GAMS code short code e Comparison output the exploitation tools can add different types of comparison output They also affect what is shown in maps and graphics Comparison output Values and normalisation Only percentage difference Only absolute difference Data dimensions used for comparisons Wormalisation Values and GTAP difference Only GTAP difference Normalisation means that the value is divided by the comparison points allowing e g also to calculate shares The GTAP difference is a compromise between a percentage and an absolute difference it multiplies the difference in the logs with the difference thanks to Rob McDougall from the GTAP team in Purdue for the proposal In tables the and options will show two lines in each d
33. gms 2_1 24 07 2014 08 06 2 1 Datel 18 KB _ fortran gms 3_1 24 07 2014 08 19 3_1 Datei 18 KB _ fortran gms 4_1 24 07 2014 08 32 4 1 Date 18 KB _ fortran gms 5_1 24 07 2014 08 45 5_1 Datei 18 KE Additionally a HTML page reports all tasks which have been started the return code of the GAMS process and all major setting as well as link to open the listing file with the editor The following screen shot shows the first part of the HTML page resulting from executing a batch file Tasks which did yield a non zero GAMS return code and errors are shown in red CAPRI batch execution report Runs are generated from d temp batch 24 07 2014_07 40 32 batch html at Do 24 Jul 14 07 40 32 Directories work result Gams Started Ended T ime Workstep Task User options used Settings RC Listing Gaxdiff dat restart Scenario description liatse MTR_B1Tech_ad Scenario description CGE cge_rd_noChg default Generate GAMS child processes on different threads ON Use new global version ON EU28 false default Base year 2004 default Simulation years 2050 Countnes BL000000 Belgum and Luxembourg DKO000000 Denmark DE000000 Germany EL000000 Greece ES000000 Spain FR000000 France IRO00000 Irland 1T000000 Italy NLOOO000 The Netherlands ATOO0000 Austria PTOO0000 Portugal SEG00000 Sweden FI000000 Fintan Regional breakdown NUTS2 Global spatial multi commodity model ON
34. i o E Beispieltext Beispieltext i CS Options for Heat Map Color for series 33 V Show last column Options for all charts Font size relative to tables in With a button panel which shows the currently active color ramp for the series Pressing on of the buttons opens a color choser as shown above which allows to change manually the colors used Walking through the data As the maximal numbers of elements shown is restricted see above typically not all columns and or rows will be shown in a graph The user basically has two possibilities to change the visible columns or rows Firstly columns and rows can be selected by the selection dialogues Secondly the user can click with the right or left mouse button on the buttons for table dimensions to move one row or TUp Ol view Region 2 eles Product Balances Danmark gt 3 500 40 000 4 View Region Product Balances Danmark ne ne p ow a o o D p a Pe 88888 8 8 8 8B 8 g 88 8 5 000 2500 a o Alsoods Ohar arable feld cropa Vegetables and Permanent All other cropa Fodder crops Product ls Exporting the graphic to file The graphics can be saved to file in different formats by pressing the export button The dialogue shown below will appear which allows the user to define the file and to select from different file formats The Options button opens an additional dialogue which
35. information and description links to symbol ORD_O O OrdC COLS OrdCMax OrdR ROWS OrdRMax OrdT Ordering of the set of years and subdirectory and the compiler will raise an error when it is used out of scope Wolfgang Britz Version January 2015 Jump to list for specific r discussion inside the network and gt 124 GGIG Graphical Interface Generator User Guide Example for a Symbol page CAPRI technical documentation Automatically generated from t britz capri gams captrd_ref ei open all close all 3 Types H Parameters 34 Sets C captrd capreg C capmod at least in one project H Files Equations Variables C captrd capreg C capmod ll at least in one project A 3 Elements C captrd capreg 1 capmod at least in one project Models a Acronyms Functions SourceFiles ranted lt Name with Top Definitions Assignments References Elements Variable AREQ Domains Name AREQ A Type Variable Description Requirements per head and day Files where the symb ol Number of dimensions 4 Used by capreg iS declared Used by capmod AREQ is declared in Opens declaration in Editor GAMS SUPPLY SUPPLY MODEL GMS capreg cajpax AREQ is assigned in GAMS FE
36. is export Wolfgang Britz Version January 2015 50 GGIG Graphical Interface Generator User Guide type dependent for PDF to give an example the paper size orientation etc can be changed Generally high quality are achieved if vector formats are used PDF SVG EPS EMF These formats are however not supported by all applications in opposite to e g bitmaps BMP which require a lot of disk space and JPEG which implies a loss of quality It might therefore pay off to try several formats for import into other applications For MS Office users the Windows Enhanced Metafile EMF format is interesting as it allows changing later the graphics manually e g by adding new text and changing colors The Resolution factor field allows to improve the quality of the saved file for non vector formats such as JPEG by drawing the original graphic with more pixels which however drives up disk space 4 Supply details mapping view 0 4 e gt Activity Item Year Utilized agricultural area v Income Euro ha or head 2020 1200 00 1150 00 1100 00 1050 00 1000 00 950 00 900 00 850 00 800 00 750 00 700 00 650 00 600 00 RES_2 0820MTR_RD 550 00 500 00 450 00 s Enhanced Metafile emf Bitmap Formats 400 00 eeHEP Graphics Interchange Format gif eeHEP RAW Image Format raw 350 00 eeHEP UNIX Portable PixMap Format ppm 300 00 250 00 200 00 Exporting the graphic
37. of which have additionally options which can be edited by users A multiple linear regression using the Akaide criterion for model selection is used as the default assuming that most people will start with using numerical values as class attributes Please not that switching between nominal and numerical class attributes might trigger error messages if the currently selected classifier cannot handle the newly selected class attribute type e tis recommended for our purposes to use under Test options Use training set the default in our implementation as we are typically not interested in an out of sample test of the prediction quality Wolfgang Britz Version January 2015 105 GGIG Graphical Interface Generator User Guide e The actual classification can be started with the start button If the data in the background are updated the actually chosen classifier with the chosen options will be started on the new data set automatically In absence of errors the Classifier output on the RHS will hence typically show results based on the latest selected data e The results can be visualized by clicking with the mouse on an item in the result list the last on in the list always being the newest If one has tried several classifiers the old results remain available However if the data in the background change the old results are automatically removed The reader should note that all the functionality describe
38. shades of blue Treat zeros as missing values 1885 20 F Remove last col 1885 10 1885 00 1884 90 1884 80 1884 70 1884 60 1884 50 1884 40 A 1884 30 3 And use the graphic dialogue to select as many series as statistics selected in the above example 4 Markov charts A still explorative type of graphics visualizes flows between entities which are placed in a two dimensional co ordinate system It is currently not yet used in CAPRI itself but applied to show flows between farm groups classified by economic size and specialization As with the flow maps below the major code based for the graphics is based on work of Doantam Phan The positions on the x and y co ordinate are deducted from the codes taken from a specific section of the underlying XML definitions which refers to a matching of sub strings of the codes and x respectively y positions The size of the dots is taken from the diagonal elements gt Flow Map Layout Doantam Phan Ling Xiaol Ron Yeh1 Pat Hanrahan and Terry Winograd Stanford University see http graphics stanford edu papers flow_map_layout flow_map_layout pdf I would like to thank Doantam Phan for letting the CAPRI team use and modify his source code Wolfgang Britz Version January 2015 65 GGIG Graphical Interface Generator User Guide FB MARKO 0 BB MARKO 0 5 View type Markov chart EG DHR ee M Pics sma sviGM_smar BEEF_SMAL MIXL_SM
39. tables and Permanent crops Income tables and Permanent crops Crop share Animal dens tables and Permanent crops Production per UAAR r activities Revenues Save result buffer Delete result buffer Visualize reduced data r activities Income Set aside and fallow land Income All cattle activities Revenues Beef meat activities Income Beef meat activities Crop share Animal density The last selected filter will be automatically restarted if a new data set is implicitly loaded change of the map or of the data in the cluster table with the explanatory results In order to switch off the use of the filter select Do not longer use output for classification Attribute viewing and selection The last panel available is especially interesting to quickly analyze statistics of the underlying data B Weka Explorer GUI Supply details mapping view 1 Quantile 20 46 17 n Classify Filter View and Select Use modified data for classification Filter Choose None Apply Current relation Selected attribute Relation Supply details mapping view 1 Quantile 20 46 17 Name Revenues Type Numeric Instances 300 Attributes 5 Missing 0 0 Distinct 300 Unique 300 100 Attributes Statistic Value Minimum 2 076 all l None Invert Pattern Maximum 2190 78 r Mean 877 02 No Name StdDev 352 113 1 Revenues 2 Income a fYield 4 Crop share
40. to determine empty cells H2876 77 86 H2877 126 38 V Use default pivoting for tables 7 Show histogram Use classification colors for tables n hissas PP EA S E A i H2880 60 65 Show all items highlight selected w Long texts only z H2881 241 39 k H2882 241 38 H2883 124 49 N j H2884 108 58 Element used for comparisons France H2885 105 87 H2886 73 94 ok define colors l define statistics l store settings l load settings H2887 136 51 H2888 83 92 H2889 108 16 Column width 750 Row width 750 When we now draw the outlines of the selected polygons only see map option dialogue the map will draw the outline of the selected regions in cyan and thus highlight them The row selection will be maintained when the pivot or the table is changed as long as one of the selected items can be found in the rows of the new table The example map shown below is certainly not so interesting as changed class limits could have done basically the same job However we could switch e g to grass land shares to see if fertilizer input is more often found on arable or on grass land Exploitation of spatial results Data iew 1 18 x Activity Items Table ce a Q Q ae ll Map WwW Juaa Ye no 5 a Mineral Fertilizer Consumption Nitrogen kg N ha x Agri Env indicators driving forces ud Scenario BASE he 0 00 0 00 0 00 49 28 49 28 74 08 74 08 lt 8645 86 45 450 86
41. use Utilities Generating coordinate files for the exploitations tools from Shapefiles The exploitations tools use a proprietary format to store coordinate files The utility allows to build from shape files a file in that proprietary format Wolfgang Britz Version January 2015 135 GGIG Graphical Interface Generator User Guide Batch execution Generate GUI geometry from shapefile Coo file generation from shape file ShapeFile input Shapefile input Shapefile input Shapefile input Sd Shapefile input 0 id Shapefile input O Coordinate file output Id string NUTSIL v Namestring NUTSI w Scaling for coordinates 0 001 Fill up mask for ids Id string NAME 7 ing v Scaling for coordinates 0 001 Fill up mask for ids Id string _INT_NAME ing i Scaling for coordinates 0 001 Fill up mask for ids Id string l i l v Scaling for coordinates 1 Fill up mask for ids Id string Name string l 7 Scaling for coordinates 1 Fill up mask for ids Id string l Name string uw Scaling for coordinates 1 Fill up mask for ids a E Simplify 7 Store holes Minimum size for polygon 50 PFAFSTETTE 1 0 3 MAINDRAIN_ 5000 4 INT_NAME Oka Volga 4 WINDOW 2013 5 MAIN PER Wy 5 OBJECTID 1 6 SHAPE Leng 3710847 47957 7 4 L Note Files and settings shown above are the ones used to generate the NUTS II map in CAPRI the shape files can be found in the addon gis folder As a first step
42. 0000 2474 04 2621 66 2408 91 24 0 00 0 00 0 93 1 95 1 51 EL000000 506 60 438 80 387 80 369 70 357 11 350 51 309 33 280 74 309 78 307 67 4 67 0 87 3 15 3 52 2 96 2 4 1 50 3 17 2 96 1 16 ES000000 2038 83 1817 29 1898 56 2012 36 2163 35 2100 96 1736 56 1686 57 1526 07 1338 84 li 2 48 1 49 1 48 1 49 1 00 1 00 0 51 2 48 3 86 2 42 FR000000 5025 58 4695 08 4600 89 4611 01 4500 03 4820 48 4868 61 4770 03 4769 83 4440 35 44 1 51 1 86 3 71 4 41 5 12 3 05 166 2 53 2 02 3 00 IR000000 72 19 70 65 72 75 56 38 58 60 60 70 70 45 86 56 91 06 79 20 6 34 5 35 2 96 2 46 3 43 2 54 0 50 0 00 0 4 0 50 Tr000000 1375 60 1213 49 1190 63 1133 53 1050 04 1104 07 1009 22 953 70 963 35 872 49 11 4 1 21 2 88 0 50 0 99 0 50 0 00 0 01 0 50 0 88 Here three combined options in the dialogue can help 1 Use hide empty and empty columns to throw out missing values or hidden cells 2 Use a approximate cut off for the value to show e g start only with acreage gt 1000 1000 ha 3 Hide cells where the difference is below a threshold e g 1 Tahoma 11 plain v Fraction digits and decimal separator 2 7 Separator between merged data dimensions l Column width 140 Row width 140 J Hide empty rows V Hide empty columns Cut off limit to determine empty cells 1000 00 Use default pivoting for tables Show histogra
43. 015 132 GGIG Graphical Interface Generator User Guide Working with the equation and variable viewer Equations and variables can be loaded in the equation and variable viewers the two windows in the lower part of the main window by working with the selection boxes see tab selection These windows are thought as a replacement of inspecting the equation listings with an editor If an equation is selected with the equation selection control the equation window will show it in linearized form 1 e any non linear functions and interactions terms with other variables are converted in a constant The variable window will report the level and the lower and upper bound for all variables found in the equation The user can add or remove equations with the control as well If a variable is selected with the variable selection control the variable window will report the level and the lower and upper bound for the selected variable s The user can add or remove variables with the control as well Double clicking on a variable in the equation window will show that variable in the variable window as well as load it in the GDX viewer Double clicking on a variable in the variable window will load all the equations comprising the variable and also show in the variable window all the variables found in these equations The first line of selection boxes shown below first allows to select all instances of a variable or
44. 1 4 lt 298 00 ee ss SS 80 83 Show distribution rectangles for dasses Tity labels Min cty size 95000 0 E Rivers Min width 4 E Region labels Options for info window Legend Continous bar linear scale Draw outline in same color Standard map title Dimension shown in columns of result window for current region Dimension shown in rows of result window for current region hide Resolution factor for printing file output compared to screen i ___ Ss Chose coordinate set to use It offers different options to change the way the map is drawn on screen and information supporting the classification Changing the coordinate set Reset coordinates mee Pressing the button opens a file dialogue Suchen in GUI gt Be E t EE zip MT zip ra EL zip NLzip Zuletzt EPIC ZIP non_eu_balkan_hsu2 zip ES zip NUTSILzip eu28_ch_no_hsu2 zip PL zip faostat zip PT zip zip Flzip RM ZIP FR zip RMS ZIP HSMU zip RO zip HU zip russia_hsu2 zip IR zip SE zip IT zip SLzip LT zip SK zip LV zip test zip MS zip turkey_hsu2 zip Dateiname NUTSII zip Dateityp zip CAPRI geometry files which allows selecting an appropriate coordinate set Wolfgang Britz Version January 2015 70 Current class definitions labels GGIG Graphical Interface Generator User Guide The map viewers assume that the regions are the in rows and searches the short keys for each r
45. 14 1887 49 1886 48 1885 78 1885 77 1885 47 1886 44 1886 29 188 15 1887 49 1886 49 1886 63 1888 38 1888 21 1888 10 1886 73 188 16 1887 44 1886 70 1886 04 1886 06 1886 38 1886 28 1886 86 18 d17 1887 66 1887 78 1886 97 1886 42 1887 85 1886 81 1887 87 18 d18 1886 99 1886 80 1887 06 1887 40 1887 45 1886 71 1886 03 188 d19 1888 64 1887 80 1886 66 1885 83 1885 22 1885 55 1884 59 18 1 Add the stastistic which you want to show 2 LANA HERBAMO A p View Handling Windows a Region Activity Product Om Levi im above sea levi 2 3 5 y d1 1883 85 1883 4 d2 1885 39 1884 60 d3 1886 75 1889 34 d4 1885 50 1884 6 d5 1886 39 1887 30 d6 1886 07 1886 4 d7 1886 68 1886 74 d3 Set factor for mean sigma 2 1886 35 1886 11 d9 Set maximum percentage of outliers 24 ea asst d10 i 1884 95 1884 85 dit Set outlier detection method Standard deviation around mean 1888 33 1887 62 d12 Select statistics 1886 50 1885 9 az Nobs 1885 70 1885 41 Median d15 ace 1886 73 1886 84 a ama ar d17 a3 1887 87 1887 62 d18 min 1886 03 1886 22 d19 max 1884 59 1884 31 minOutlier 1887 70 1887 2 maxOutlier d24 1884 60 1885 67 a22 la 1906 84 seese d23 1887 57 1887 1 d24 5 5 1888 14 1889 3 d25 1888 46 1888 26 1888 33 1888 23 1887 28 1886 81 1886 93 1886 9 d26 1886 50 1885 81 1885 40 1885 09 1884 73 1884 16 1884 26 1883 6 wn ARRT AR 4RR7 OR ARRT RA 4RR7 AR ARRA TR ARRA TN ARRA 7A ARRA RAF 2 Switch to line chart views Attention the statis
46. 2 Outlier detection 45 Pop up menu 48 54 Sorting 41 Statistics 42 View options 30 Classification colors for tables 32 Column and row width 31 Comparison output 32 Cut off limit to determine empty cells 32 Fonts 31 Hiding empty columns or rows 31 Histogram window 32 Number formatting and rounding 31 Percentage differences 32 Short codes and or long texts 32 View Selection 25 View type selection tables graphs maps 29 145
47. 200 00 4 100 00 4 E sioF_02e2 BloF_D10E10 Histograms As for whisker charts and statistics shown in tables the observations are taken from rows and different columns are charted individually Please note that it is also possible to generate a separate Histogram window but then the observations refer to all columns simultaneously Exploit scenario results 0 Table Production activity Item Years view type Supply details mapping view Cereals w Income Euro ha or head 2013 wv a v 16 5 16 0 15 5 15 0 14 5 14 0 13 5 13 0 12 5 12 0 11 5 11 0 10 5 BIOF D2E2 BIOF_D10E10 Some tips Wolfgang Britz Version January 2015 59 GGIG Graphical Interface Generator User Guide e Ifthe data set comprises zeros which should be interpreted as missing values check the box Treat zeros as missing values Otherwise the value axis will show a zero as the lower bound even if Include zero in value axis range is not ticked e The number of bars the so called bins can be set with a spinner in the second lower panel in the graphic dialogue The zero as the default value determines the number of bins automatically as the minimum of 100 or the number of observations divided by 5 e It might be worth to increase with transparency of the bars to better capture overlapping parts of the distribution It might also be worth to use unfilled bars e In order to dra
48. 57 99 215 6 mns GLES 675351 38 08 121 6 Sat achte end fellow S42 EEI 129 1 24 w 13837 10 160 90 2348 156 war Af cattle acthitinn isas bms s3 w 1 8 33592 54 96 05 9053 35 sese 43 45 Sa Tae 3468 0579 58 wn se n IWI sw 10526 54 16 55 7 34 Ea Scenario exploitation Data View 1 Table Region Yours Sle gt Bichon as s Pg Bar chart gt z Supply detalis European union 27 2013 iE gt Ei 2 0 4 amp 2 500 m Po o 2 75 000 4 p J FI a 25 i 230 B nn oor Z 10 000 GD P a 2 o o 2 4 00 000 z 1 00000 S A 000 o P P D D ag gay E o A A 8 10 x0 x F ream 2s 2 Gi aay Zz gt S sor 50 2 Fi 00 G 260 g 2 50 2 A P P Cereals Oilseeds Other arable crops Vegetables and Permanent Fodder activities crops Scenanos Be D Ees Wolfgang Britz Version January 2015 53 E ox GGIG Graphical Interface Generator User Guide Options for bar charts and histograms Maximal number of plots h Maximal number of bar blocks 5 Maximal number of bars per blocks 10 Foreground transparency in o 10 7 3D effect gt Stacked W Plot vertical Cylinder only for 3D non stacked Draw outline Draw shadow Filled bars Show mean median q 1 93 The user has a number of options for the bar charts By pressing the button in the toolbar a dialog box including the section of Options for bar charts opens The number of plots refers to the number o
49. 9 282 3 149 28 lt 74 08 74 08 4 74 08 lt 86 45 86 447 aga 5 86 45 lt 450 86 450 861 E pahat sime od daad reais Data Views 1 jaiz Ay iem tee rey j oes So ES ETS aioe corm a IAI 0 00 49 2740 45 406 ii i 0 00 225 43 450 86 J Show small circles showing distribution of regions n 1312 0 J Show rectangle representating distribution of classes Min 0 0 Mean 60 723194 J Draw outline of polygons Median 60 272877 Max 450 86072 Std Dey 2399 8152 J Set value for color change from Green yellow red Dimension shown in columns of result window For current region Scenario bd Dimension shown in rows of result window For current region items v ok CAPRI ON Meen 0 2 1 Porh 7007 ieor seme Wogan Dte ppe Ainte Mot Bowicre Wem m he Flere j amije jater iu omn pecan rein enr jek Aitwe S aa akada E E Highlighting specific regions in the map Sometimes it may be interesting to see the spatial distribution of specific data or data constellations All views open the possibility to de select columns and rows allowing e g to use the NUTS code in front of the numerical HSMU code to select only the HSMU belonging to specific administrative regions That possibility is explained in short First double click the row selection button Open selection dialog for table rows which will open the following dialogue Wolfgang Britz Version January 2015 84 GGIG Graphical Interface Generator User Guide
50. AL ARAB_SMAL PERM_SMAL POLT_MEDI POLT LARG SMAL 571 00 SHGM SMA 25149 3 mas 1108 00 248 00 6457 00 138 00 s 135 00 190 DARY SMAL 251 00 HER NATL i ay NR naL i p UNF SMAL 937 90 122 40 132 00 480 00 T MT 4 Working with maps Flow maps Flow maps visualize flows between regions The maps are constructed by taken the elements in the rows as the origins of the flows and the elements in the columns as the destinations Flows from the same origin are drawn in the same color the width of the flows relates to their size Counterfactuals are taken from the column groups and receive a specific dash The picture below shows a screen shot of a flow map for two scenarios Table Activity Product f Export flows map Exported quantities 10002 w Cereds M turopean Union European Unton Neon EU European Union European Union Iorway Bulgar and Western tee Y SM 2 25 15 1 tur 182784 73 176330 1 RET 174922 19 2008 42 askos 5354 19 Union 15 Eur ore 1162 92 3069 49 208 469321 1644 O18 Union 10 Norway st 157 1907 31 1st morn Datgerte and 15672 57 497 44 4683 1 ma 10635 9174 73 Romarna p 36 59 2892 13864 34 2342 s30 1 53 balcans Rest of 103 42 10342 1086 37 103 00 LEL Europe When pressing the map option button aj the following dialogue is opened Wolfgang Britz Version January 2015 66 GGIG Graphical Interface Generator
51. E 0 873587 1 471440 E 1 471441 2 068693 E 2 068694 3 354081 E 3 354082 147674546176 0000 Sa E CaPRI gis test test_meta Machine learning Motivation A serious challenge for large scale economic models is the dimensionality of the results generated by model runs These reflect the high level of dis aggregation in different dimensions and the many aspects dealt with in these tools such as relating to economic social and environmental indicators A single simulation run e g with CAPRI based on the farm type modules produces over 20 Mio non zeros Clearly any of these numbers is generated by a deterministic computer based model and should hence be a non probabilistic outcome depending on the input and the code used Specifically the relation between the input and any single number outputted 1s determined by the model structure and parameterization and pre and post processing code It must hence be possible to track any change quantitatively back to the shock analyzed But that rather theoretical point of view has very little to do with the task at hand when one has to distill an analysis from a set of model outcomes The questions here are what are the most important results 1 e salient to the questions underlying the analysis and large enough to matter and how can they be explained For the client the story behind the results is often at least equally important as th
52. ED FEDTRM_ CAL GMS capreg capmod GAMS CAPREG GMS capreg GAMS BASELINE FEDTRM PREP GMS capmod Proj ects where the AREQ is referenced in declaration is found GAMS SUPPLY SUPPLY MODEL GMS capreg capmod GAMS FEED FEDTRM MOD GMS capreg capmod GAMS FEED FEDTRM _ CAL GMS capreg capmod GAMS CAPREG GMS capreg GAMS BASELINE FEDTRM _FIN GMS capmod Example for a GamsSourceFile page CAPRI technical documentation Automatically generated from t britz capri gams captrd_ref open all close all Parameters Sets captrd capreg C capmod at least in one project Q Files Q Equations Variables lt j Elements C captrd capreg C capmod at least in one project J Models Acronyms gt Functions Sj SourceFiles C captrd capreg capmod T E E De at least in one project Top Definitions Assignments References Elements SourceFile DAT ARM WORPRICES GMS Name DAT ARM WORPRICES GMS Type SourceFile Used by capreg SVN version of working copy 1603 SVN last commited version 1110 E information SVN last author who committed alexanderg SVN last changed date on server Fri Nov 09 18 09 55 CET 2007 Normal i Current status Opens editor Edit Declarations found in DAT ARM WORPRICES GMS Name Type Description WorPrices capreg capmod Parameter
53. GAMS is shown ii A panel to select data to view and to start their exploitation iu The exploitation tools 4 A small window in the left lower corner which present a logo Before using a GGIG based interface the users need to edit some project specific settings see next chapter Wolfgang Britz Version January 2015 11 GGIG Graphical Interface Generator User Guide Initialization General interface settings The interface has a few standard settings which can also be accessed via the edit settings dialogue These are e Certain file locations the directory where GDX files for results are assumed to be stored resDir and three directories which can be used to adjust the specific model application the root of the GAMS file workDir in GAMS called modelDir a directory for restart files and one for data files Option model files directory sie ae T britz promok2014 results Result Directory bs t E Restart Directory bil aa dat Data Files Directory These file locations are passed to GAMS and can be used in the GAMS code to read include Rename gamsName st etc by task I st 7 Generate REF and EXP file files from the correct locations on disk In order to make an initialization file portable locations can be defined relative to the GUI directory The following screen shot shows entries in the include files generated based on the
54. GGIG Graphical Interface Generator User Guide Wolfgang Britz August 2010 Version January 2015 GGIG Graphical Interface Generator User Guide The following user guide documents the outcome of a collaborative effort of University Bonn and the author Larger parts of the Java code underlying GGIG had been developed over the years in the context of projects related to the CAPRI modelling system which received considerably funds from the EU research framework programs Following the general policy in CAPRI the GGIG pre compiled code can be used for other scientific projects as well without charge The document comprises to a larger extent the content of earlier versions of the CAPRI user guide of which the GUI is now realized in GGIG The author would like to acknowledge the contribution of Alexander Gocht vTI Braunschweig to the CAPRI GUI coding efforts All errors remain with the author Wolfgang Britz Version January 2015 2 GGIG Graphical Interface Generator User Guide Content GGIG Graphical Interface GreneralOn siteres a a a aa l SS C0 deene a A A iatidd tact ai eddaleanad ehaiaas l COMICME tani seassrsshuaaniaceseraiee teats A 3 CVT ic sae A ce esate oa ec ceca eee EEE E 9 AXTPO VeVi W Onn Ne Gr UL isrcie poatestrsieraad ss leesecdesqonecnins auseesleslssaad sie euee er aeasceie uence dt oesand temean eeeaonei eee 11 Initialization General nterrace Setn Sron een AE AENEA EEEE 12 GAMS and R related setine S er
55. Generator User Guide In that case it will replace working with the output of solprint 1 in combination with limrow limcol The necessary output can be produced as seen in the example below from arm prep market gms in the CAPRI code Siftheni abortAafterFirstMarketSolve on generate convert output to be accessed with interface option DHLP Convert execute echo gams convert_market_model gms gt convert opt execute echo dict convert_market_model txt gt gt convert opt m globMarket solprint 2 m globMarket optfile 1 m globMarket limrow m globMarket limcol SOLVE m_globMarket USING DHLP Minimizing v dummy execute unload convert market _model gdx abort Program stopped after first test solve of market model convert output generated data Sendif r Includes When the viewer is started only the code for selected GAMS file is loaded in the window titled GAMS The window titled GAMS includes will show all the direct includes used by that GAMS file which could be successfully read globals are not yet treated it is planned to merge the tool with the HTML doc generation such that includes reflect the compilation stage of the GAMS code In order to open included files e either double click on a node in the GAMS includes tree view e orona S bat include in the GAMS code view marked in red As seen below the GAMS code in new file will
56. I installation e g without the large geometries for the 1x km layer and the necessary results files to view can then be copied to a local directory At first start the user must then only enter where the results had been copied to if the result files are not parallel to the GUID and save the information to his new CAPRIJINI file CAPRI capri gams Seg File Options Yersioncontrol Help ott geet Set XML table definition file C Use table definitions from null Sort code lists Show dialog to link GDX dimensions to sets Exploit gdx files List of tables loaded from GDX file s Nachricht Load gdx file Load selected tables s CAPRI GUI ersion 2 0 March 2009 Ini file capri ini User name User type exploiter The interface is set up such that only the results of those work steps are visible where result files are found For a training session concentrating on analysing scenarios only those result files can be distributed An installation with four scenarios at NUTS2 level plus all the necessary GUI files will require under 100 MByte disk space Wolfgang Britz Version January 2015 18 GGIG Graphical Interface Generator User Guide Option User Settings CAPRI System Settings SVN Other options dad TSCheltenham2010 results Result Directory Rename capmod lst etc by task settings Ist Save in capri ini A Once the user has optionally entered the
57. IG comprises a block commented out from use by GAMS which can be pasted into a batch execution file see example below Wolfgang Britz Version January 2015 116 GGIG Graphical Interface Generator User Guide I amp e e ee e o e e e e e m Setting for executing the task in batch file mode 1 3 i l M M a e e l l SONTEXT task Run scenario with market model Scenario description caprese subCaprese caprese_1 Scenario description CGE cge rd_noChg Generate GANS child processes on different threads ON Use new global version OFF EU28 OFF Base year 2664 Simulation years 2626 Countries BL666666 Belgium and Luxembourg DK666666 Denmark DEG66666 Germany EL666666 Greece ES666666 Spain Regional breakdown Countries Global spatial multi commodity model ON Endogenous bio fuel markets in global market model ON Policy blocks additional geographical layer OFF Endogenous margins between trade block and country prices OFF Endogenous young animal markets ON Regional CGEs OFF Number of iterations 99 6 Use lower price iterations weights after iteration 26 6 Alternative GAMS license file for GHG emission estimation gamslice_cplex Aggregates for activities and commodities ON Environmental Indicators ON Life cycle assessment for energy ON Multi functionality indicators ON Iteration tracking
58. Ino 10 a Cropping Livestock pattern livestock density Livestock units ha UAA X les Fs Map option dialooue Classification method Quantile ba Number of classes 54 Number of regions with small values to remove from class definition o Scenario Number of regions with large values to remove from class definition BASE Treat zeros as missing values J Use area weights for classification I Draw in high quality JV Shrink polygons according to share of UAA J Set value For middle color 1 39 v EE cumulative distribution graph Frequency groups 1004 IV Draw me 0 00 1 1229 8 1 39 1 5 j j I 3 i i l I 1 l l 0 i I I 1 I i 1 1 1 I 1 Preview 0 00 i 0 99 Oo m Sample Text Sample Text 0 33 0 98 1 a E m J Show small circles showing distribution of regions n 1230 0 el A lb JV Show rectangle representating distribution of classes a epee Cancel Reset tt g1 Legend Separate rectangles v yeaa oe aia lela lt A nee praw outline in same color v Std Dev 064539707 Etandard map title v Dimension shown in columns of result window For current region Jenrio o Sd Dimension shown in rows of result window For current region he gt H ok store settings load settings JNo 1U a Cropping Livestock pattern livestock density LLIvestock units Na UAAJ Yj amp Map option dialogue IH
59. Interface Generator User Guide THE output tom Watch CXCCU toiaren E E A oszenke 119 Utilities Generate GAMS documentation in HTML pages esssnnnnensssssssseerrsssssssseerees 121 Smac OF The TIM Paes canonar R etsan a inter vecniv atte latest 121 Tagsedin Mne Commen S assena AE AE 122 Refactoring Consequences for Gams Code cccccccccccsssssssseccceeeeeeeeeseeecceeeeeseaaeseeeeeeees 123 General OV EI VIC Worec intar dene tiuen ital ai tae toned E A tal eaieee 124 Example fora Symbol Pate ee A 125 Exaimple for a GamsSourceFile PAS Cia aiiece Se stiah od osuta ooa E 125 Example fora page Tor hea Set ira a e A E 126 EM E A T E EE AE A T AAE T A A T AE EN AAA EE 126 Sote lement Stren mee a ree eee 127 Utihties Equation and Vartable View Cf aesir E 127 Baer Osc Mova Osee E 127 AMOVEN eW Onie VIEW CL seirian nE E EE E 128 Producing input for the view with GAMS ssseeeessssssseseerssssssssecrresssssssecreessssssseceresssssssees 128 TNC UGE eaa a a T E 131 POAC INS SIM DONS 2 cstees a dis aaah a aetna eeca nage tecieed ete eee 132 Working with the equation and variable viewer cccccccccssssseeeeeceeeeeeeaeeeeseeeeeeeeaaas 133 MES GX TeS INVI SW Ol xe setsucnnssenwsantys cinsslozem ten r EE 134 Utilities Generating coordinate files for the exploitations tools from shapefiles 135 Analysis differences in GAMS based data using GGIG 2 0 cecccccccccceeeeeeseeeeeeeeeesaaeeenees 139 Bea Srl lssaee ce ater
60. Jal Files x Cancel BL21H2884 BL21H2885 zi RI JAHIRRR CAPRI GUI Version 1 2 4 Oct 2007 User name Wolfgang Britz User type Administrator loading 250392 data Wolfgang Britz Version January 2015 37 GGIG Graphical Interface Generator User Guide If desired the pane allows openening selection lists for the different data dimensions These selection only work if the only the currently active table is exported in which case the table selection next panel should be left empty l Please choose a file format for Export Data Set Export Dimensions Export selection for Region Export selection for Items Export selection for Origins Selection will only work if only current table is exported You can next the tables for export Please choose a file format for amp Set Tables to Export Leave selection empty to only export current table and to use selections larkets Di d by institution rkets Demand by product rkets Demand by product bar charts for scenario comparison rkets Demand by product per capita in larkets Di d by product per capita in map rkets Factor demand rkets Intermediate demand rkets Markets balance overview Flow schemer jel overview Income per capita lel overview Income per capita map jel overview Model properties jel overview Price schemer jel overview Regional aggregation Only export aggregates for pro
61. L SET RSST RALL Set NCNC COLS Common nutrient coefficients SET NCNC_POS Sinclude reports rep sets gms ALIAS SIMY SIMY1 SET SIMYY1 ALIAS STEP STEP1 STEP2 e Load convert output into viewer with Convert output only Convert is a solver shipped with GAMS which generates a linearized version of a model with obfuscated variable and equation names e g to ship it to a solver developer for testing Convert can produce a dictionary file which allows to link it to the obfuscated names lz Options Options i 7 _bevFuncSubsExpCorrFact a Use table definitions from null Use indents in equation output _constShareBuying es Variable selection feedConv i Mi Show dialog to link GDX dimensions to sets Use small font for non selected var terms _constShareRelease 2 Symbol from GDX 4 Symbols in GDX arm2Val_ List of tables loaded from GDX file s Dim2 Levl Marginal T britz capri gams convert_market_model_2 gdx a r r O m B m rm r rm 4 Equations fe tr arm2Val_ NO000000 OFRU Value of imports pv_bevFuncIntAddFac 1 159 374 10 0 upp 1 593 741 19 9 45232123664149e 7 v_armlPrice EU010000 POTA v_armlQuant EU015000 OLIO Armington first stage price v_arm1Price E
62. MS program which uses rules about the importance of data items to concentrate on changes which matter In the CAPRI RD project to give an example outlier statistics for many time series for EU Member States were calculated leading to thousands of potentially suspicious values It is clearly impossible to check manually each and every case so that algorithms have to deal with the majority of the cases The expensive manual checks have to concentrate on the items which are deemed important Hence by using e g national and EU crop shares animal stocking densities and shares on sectoral revenues a matrix of importance was constructed which assign a numeric indicator to each time series A combination of that importance metric for a time series and its outlier statistics combined with a threshold delivers then the potential outliers to compare manually The following will describe a third way to proceed based on the in built functionalities of the exploitation tools Comparing two data sets in GGIG example from CAPRI Generally each task in CAPRI also allows viewing its results and selecting Scenarios The example below show the task Build regional time series On the disk several versions where located and these can be compared as if they were scenario If one e g wants to compare the current version against the trunk or an earlier release one can rename the current one e g to current gdx and then use update
63. OOO DKOO00000 DEO00000 ELO00000 ES000000 FROOOOOO IR0O0000O0 DPGRCU 2006 eps eps eps eps 40 25 eps DPPULS 2006 100 100 100 100 100 100 1o07 DPDWHETR 2006 eps eps eps eps eps eps eps DPDWHEES 2006 100 100 100 100 100 100 100 DPPARI 2006 100 100 100 100 100 100 100 DPSILA 2006 eps eps eps eps eps eps eps DPPARI fa 2006 eps eps eps eps eps eps eps DPSCOW 2006 eps eps eps 100 100 100 eps DPBULF 2006 eps 75 eps eps eps eps eps DPDCOW 2006 eps eps eps eps eps eps eps DPSHGN 2006 eps 50 eps eps 50 50 eps DPEXTENS 2006 eps eps eps eps eps eps eps DPPOTA 2006 60 60 60 60 60 60 60 DPNE_SHGM 2006 eps eps eps eps eps eps eps DPNE Dcow 2006 eps eps eps eps eps eps eps DPNE_ MEAT 2006 eps eps eps eps eps eps eps DPSL_ADCT 2006 100 eps eps eps 40 40 eps DPSL_CALY 2006 100 eps eps eps 100 100 eps DPNATMILK 2006 100 100 100 100 100 100 100 DPENERCRP 2006 100 100 100 100 100 100 100 Storing the scenario then generates a file as shown below user name the reference to CAPMOD GMS and the date and time are automatically added by the GUI The files will be added to the files stored in gams pol input Meta data handling Why meta data Meta data are data about data In many GAMS projects it is impossible or cumbersome to tell exactly based on which shocks and settings results of a model run had been generated especially if results are stored separately from the listing file e g in GDX containers or Wolfgang Britz Version Janu
64. R as a include file 4 Exploitation of results from GAMS runs by providing an interface to define the necessary interfacing definitions in text file to load results from a GAMS into the CAPRI exploitation tools 5 Access to a set of GAMS related utilities This include e g a viewer for GDX files a utility to build a HTML based documentation of the GAMS code or a batch execution utility That guide is thought for users of GGIG generated interfaces It will be typically be complemented with a user guide which is specific for the project such as the CAPRI user interface documentation The GGIG programming guide comprises the necessary information to set up interfaces based on GGIG The main parts of GGIG are graphically depicted below At its core stands the GGIG Control generator based on Java code Based on a XML based definition file provided by the project it generates a project specific GUI which can be operated by the user The state of these controls such as numerical settings on off settings or n of m selection can be passed to The code can also be used from inside Java but that feature is not discussed in the documentation Wolfgang Britz Version January 2015 9 GGIG Graphical Interface Generator User Guide GAMS by an automatically generated include file which also contains generated meta data documenting the state of the controls The user can also execute GAMS from the GUI The GUI can equally load numer
65. Region view Region view Region Product Balances Danmark Product Balances Danmark Product Balances Danmark b Product Balances IReemerk 1 gt sac a Lc ae B E7 e e fe 7 Supply Supply 1000 t 1000 t 1000 t 9244 00 A 250 54 4371 75 4371 75 Oilseeds Sa arable 248 46 348 46 ield erone 5005 67 5005 67 5005 67 38944 26 38944 26 erana 2168 92 2168 92 field crops 38944 26 7655 62 7655 62 25601 70 25601 70 2168 92 Senca i Other Animal 7655 62 nrodiucte 1116 83 1116 83 Permanent crops 25601 70 z Fertiliser 965 77 Fertiliser 965 77 Adding statistics The user may add different statistics as rows to the table as reported in the following table The observations are assumed to be mapped into the rows of the current views Zeros can be treated as missing values The statistics summarize the observations rows separately for each column Note The statistics are only calculated for the cells currently visible Trying to show e g percentage differences of statistics against items not visible e g a region in drop down box which is not the currently selected one will not yield usable results Wolfgang Britz Version January 2015 41 GGIG Graphical Interface Generator User Guide Statistics Shortcut oO Minimum limit for outlier detection as minOutlier defined from user settings Maximum limit for outlier detection as max Outlier defined from user settings Free chosen a
66. S TR600000 TR700000 1057 54 iy An interesting option here is to use the GTAP difference which is defined as Wolfgang Britz Version January 2015 142 GGIG Graphical Interface Generator User Guide m log x log y abs x y The first term looks at relative differences which are weighted with absolute ones Using the table definitions For those not familiar with the codes it might be easier to work with the pre defined tables As those tables are not always constructed e g to be used with time series it might be required to pivot them as well Supply details 0 pesma Region versions Item Hide lt 5 0 Percentage diff to E versions tame Spain v RES_TIME_SERIES y Hectares or herd size 1000 ha or hds RES_TIME_SERIES161111 x 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 Y v Utilized agricultural area Oilseeds 1073 71 1489 72 1752 25 6 26 7 24 11 59 WS 1094 70 1045 33 1036 32 1029 74 1062 57 912 60 927 55 918 26 838 66 725 81 7 15 8 08 7 49 6 27 7 99 8 03 11 25 12 05 16 16 7 88 Fodder activities 9275 60 5 05 Set aside and fallow 3560 38 land 10 78 All cattle activities 3524 90 3699 85 3676 01 3692 47 3725 92 3786 42 3808 13 3845 82 3886 38 3759 79 27 01 29 77 33 48 36 58 37 17 37 11 38 48 39 29 39 98 41 61 Rance 607 87 752 53 818 96 928 83 1007 36 1049 77 1116 77 1210 29 1320 02 1453 83
67. S t fire we Classification method Quantile F Number of classes 54 Number of regions with small values to remove From class definition o Scenario Number of regions with large values to remove from class definition oj BASE Treat zeros as missing values Use area weights For classification I Draw in high quality JV Shrink polygons according to share of UAA Color table Start color __Midcolor Endeolor Manual start midjend Y 7 Set value for middle color 1 39 a es a 25 61 18 618 0 00 1 08 1 39 1 56 i 0 00 i 0 99 0 33 0 98 1 62 Show small circles showing distribution of regions n 1230 0 Min 0 0 J Show rectangle representating distribution of classes Mean 0 97628593 re ey oe S e m Legend Separate rectangles He or motores ax 0 00 0 00 AURS Draw outline in same color Std Dev 0 64539707 btandard map title v Dimension shown in columns of result window For current region Scenario hd Dimension shown in rows of result window for current region hide v ok store settings load settings Wolfgang Britz Version January 2015 78 GGIG Graphical Interface Generator User Guide Changing the value for the middle color Normally the medium color yellow or gray is assigned to the middle class Sometimes the user may wish to change the class where the color switches First the Set value for color change must be ticked Next in the now enabl
68. U010000 POTA 1 1 366 538 10 136 654 upp 13 665 38 9 45232123664149e 7 v_entryPriceDriver EU015000 BRA CITR v_feedInpCoeff Buro utility point v_intervStockChange EU015000 BEEF pv_bevFuncIntAddFac EEEE a ca v_impPrice NO000000 MED CITR v_tradeFlows NO000000 MED CITR v_armlQuant EU015000 OLIO i iene ee ee upp 773 444 418 v_impPrice NO000000 RUS RAPO v_tradeFlows NO000000 RUS RAPO E 0 PAON Some v_entryPriceDriver EU015000 BRA CITR S scrion of specifie sarisfs 1 1 313 661 10 131 366 upp 131 366 103 expQuant_ USA OFRU Sum of exports of each region v_expQuant ASOCE_REST RYEM rae aja A desc 1 348 142 upp 7 118 406 0 00287156316980887 pv_bevFuncIntAddFac v_feedInpCoeff pg ing per hemd amd yem i2 1260 538 lo 0 upp 605 384 883 0 00287156316980887 v_tradeFlows TUR RUS SUNO Import price for goods from 0 00287156316980887 v_tradeFlows MER_OTH EU015000 WMIO v_impPrice NO000000 MED CITR Ta teed 1 1 231 977 10 123 198 upp 123 197 701 0 00287156316980887 v_tradeFlows CH U015000 BUTT Euro ton 0 00287156316980887 v_tradeFlows IND AFR_LDC PULS Import price for goods from 0 00287156316980887 v_tradeFlows CHN THAI OCER v_impPrice NO000000 RUS RAPO ancora ROM 1 2 554 018 1o 255 402 upp 255 401 839 e __ 0 002871563169R0887 y tradeFlows IAP SKOR SMTP Euro ton Wolfgang Britz Version January 2015 130 GGIG Graphical Interface
69. XSLX is selected with the data export utility each view table selected by the user will be exported to a separate sheet A subsequent export to an existing workbook will overwrite only these sheets which match the names of currently exported views The sheets will take over formatting options from the exploitation tools such as the number of digits or if percentages or absolute number are selected As sheets are overwritten the user should store e g graphics or formatted tables on other sheets and use references Wolfgang Britz Version January 2015 39 GGIG Graphical Interface Generator User Guide Demand by institution 3 Table x Demand by institution FF Region World Items Quantity 4 Origins Total Grains and C 5 6 7 Total 8 Household demand 9 Government demand 10 Intermediate demand 11 Investment demand 12 Export demand 13 International transport demand 14 15 Source GGIG 13 Dezember 2014 16 17 18 19 20 Table x Demand by institution o FF Demand by institution ld 4b bl Demand b Sorting The rows can be sorted by one or several columns by clicking with the left mouse button in the column headers Repeatedly clicking will change the sort order and then return to the unsorted list Adding additional sorting columns is achieved by pressing the shift key and then using the mouse as explained before A
70. able rows Table cells area Activity 83 Wolfgang Britz Version January 2015 29 GGIG Graphical Interface Generator User Guide Scenarios The boxes show the data dimension and their lengths They can be dragged to the different viewport dimensions as shown in the screen shot above Assigning several Table columns dimensions to the columns leads to spanned BIOF D ZE Income Euro ha or head dimensions Alternatively columns and rows can have additional block BIOF_D2E2 Income 438 65 454 55 E 30 01 Hectares or herd 59217 85 8335 37 1000 ha or hds 2 08 13 24 Yield 4958 80 2271 59 kg or 1 1000 headha or head 3 58 6 17 BIOF_D10E1 Income 533 21 649 48 0 E 0 00 0 00 Hectares or herd size 60473 37 9607 46 1000 ha or hds 0 00 0 00 Yield 5142 97 2421 03 kg or 1 1000 headha or head 0 00 0 00 In combination with the selections for columns and rows and column and row blocks the view can be adjusted to the need of the user e g to export the data in a specific ordering to an external file The pivot can alternatively changed by mouse clicks in the text field above a selection box e A left mouse click puts the items from the selection box into the rows while moving the items from the rows into a selection box A double left click generates row groups e A right mouse click puts the items from the selection box into the columns while moving the item
71. after the final definition of the class limits is set as otherwise the manually set color will be lost Wolfgang Britz Version January 2015 79 GGIG Graphical Interface Generator User Guide x Classification method Quantile hd Number of classes Number of regions with small values to remove From class definition Number of regions with large values to remove from class definition Treat zeros as missing values Use area weights For classification Draw in high quality JV Shrink polygons according to share of UAA Set value For middle color a T El E ae aa ae ae A V V p EEEREN LL ae L ae aa E aes ae aaa ae aa ae aa Preview 0 00 m Sample Text Sample Text Show small circl a H a 0O Sample Text Sample Text EE J Show rectangle OK Cancel Reset Legend Separate ax oraw outline in same color v Std Dev 0 64539707 btandard map title v Dimension shown in columns of result window For current region Scenario Dimension shown in rows of result window for current region hide v ok store settings load settings Changing the way the legend is drawn The map viewer always puts the legend below the map Currently it offers three options how legends are drawn 1 Separate equally sized rectangles which show the upper class limit with the exemption of the lowest cla
72. al documents The directory for exp ref files defines where those files will be stored The batch language allows definition of a timer 1 e to start the execution at a specified time The output from batch execution As it is assumed that batch execution will not be monitored by the user during execution a logging mechanism is established Listing files and generated include files are stored in sub directories of the output dir defined in the batch execution file where the HTML page and the listings will be stored output dir d temp batch The sub directory is named after the time point where the batch execution is started 4 07 2014 07 54 12 24 07 2014 08 57 Dateiordner 4 072014 07 40 32 24 07 2014 08 57 Dateiordner d b These sub directories comprise the listing files and generated include files labelled according their starting sequences e g Wolfgang Britz Version January 2015 119 GGIG Graphical Interface Generator User Guide O 1 fst 24 07 2014 07 53 LST Datei 158 317 KB 1_1 ist 24 07 2014 08 06 LST Datei 158 403 KB 21 Ist 24 07 2014 08 19 LST Datei 172 658 KB 3_1 st 24 07 2014 08 32 L5T Datei 172 673 KB 4 1 ist 24 07 2014 08 45 LST Datei 156 906 KB 5_1 Ist 24 07 2014 08 57 LST Datei 955 KB E batch html 24 07 2014 07 53 HTML Dokument 15 KB _ fortran gms 0_1 24 07 2014 07 40 0_1 Datei 18 KB _ fortran grms 1_1 24 07 2014 07 53 1_1 Datei 18 KE _ fortran
73. an equation Variables v_GLDemandFS Equations ArmBali_ z UA 7 za 3 The other boxes show all items found on the dimension of all symbols and allow to filter further In order to see e g all equations which have on the first dimension AFR LDC and on the second APPL put the selection controls as seen below 1 AFR_LDC w 2 APPL H CPeeeeeeeee eee eer rere re rere reer errr teeter eee eee er etre That produces an equation output as seen below Wolfgang Britz Version January 2015 133 GGIG Graphical Interface Generator User Guide ArmBall AFR _LDC APPL Adding up of human consumption feed and processing 0 0114645139135529 v_ consQuant AFR_LDC APPL 0 0114645139135529 y armiQuant AFR LDC APPL E 0 CPri AFR LDC APPL Consumer price linked with fixed margin to first stage price 0 00187949947079955 v7 armlPrice AFR LDC APPL 0 00187949947079955 yv consPrice AFR_LDC APPL E 0 284525356696553 GLDemandGiS AFR LDC APPL Part of GL demand function 0 35213994338001686 0 308934628613077 1 14603816746872 sqrt 0 00188303864092867 v_ consPrice AFR_LDC MATIZ 1 37181255843937 sqrt 0 00188303864092867 v_ consPrice AFR LDC OCER Note currently the viewer will not show more than 100 equations and 1000 variables simultaneously Utilities Gdx file s viewer GDX files are generated by GAMS and typically serve either an exchange format between d
74. antity to the sum of all flows for the same scenario e Log the width is determined by multiplying the log of the relation between the flow quantity and the minimal flow with the log of the relation of the maximal and minimal flows for the same scenario e Polynomial the relation between the current flow and the maximal flow is raised to a power determined by taking the log of the relation between the maximal and minimal display width divided by the log of the regional between the maximal and minimal flow The user can prevent that small flows are drawn by setting a minimal width relative to the size of the window equally the maximal possible size of a flow relative to the size of the window can be determined gt v In order to show only a selection of the flows the selection buttons can be used The lower left one relates to the rows of the underlying tables and thus allows excluding origins from the maps The lower right one opens a dialogue to exclude destinations whereas the upper right one allows exclusion of scenarios Wolfgang Britz Version January 2015 67 GGIG Graphical Interface Generator User Guide Most options described below for thematic maps such as zooming and dragging are also available for flow maps However classifications and color models cannot be supported Pie chart maps Another rarely used application of maps is the possibility to place pie charts above the geometry The regions must
75. arts Maximal number of plots Maximal number of series Foreground transparency in E 30 effect W Plot vertical V Draw lines Draw Shapes Sort values Draw cummulative Common range for plots The options for line and area charts are similar to the ones for bar charts The number of plots refers to the column groups the number of series to the rows of the table Area charts are equivalent to stacked bars i e the observations are added The number of observations is linked to the columns Wolfgang Britz Version January 2015 55 GGIG Graphical Interface Generator User Guide Pie charts Pie charts are useful to show shares on total as e g trade flows The shares are calculated from the columns whereas each column group typically scenarios receives its own pie Only one row is allowed Table Importer Activity cos DENR d __Import flows market model aggregated Norway Imported quantities 1000 t 2013 BOF _D2E2 O E eee Z oa a turopean Norway Buigaria and Western Rest of Europe Russia Mercosur Rest ot india Chim Japan Amuiraa and Turkey Mor No Union 27 Romania balcans Belarus and America New Zealand gia Ukraine Gini 6I 1107 33 2 43 440 ESS 3 30 1 115 417 98 003 Other arable san mus field cropa Vegetabte ear wn ar sar 361 50 nu nss wm 4 F3 Scenario exploitation Data View 1 Importer Activity Years xy Pie chart dj JOE Import flows market
76. ary 2015 110 GGIG Graphical Interface Generator User Guide EXCEL sheets But even with a listing file important settings such the state of environment variables e g used in if statements might not be reported And typically listing files are regularly overwritten Later on result users are often left guessing what exactly the settings underlying the run might have been In order to overcome that problem the GGIG drawing on CAPRI GUI concepts passes all interface settings plus the user name and the current time forward to GAMS in one SET called META A correctly defined interface with GGIG should allow to steer all run specific settings If that is the case the meta data generated by GGIG will provide an exact and sufficient definition of all run specific inputs ensuring that all relevant meta data about a run are stored along with quantitative results in the same GDX file Accordingly GDX files shipped to other desks or committed e g toa SVN server still carry all necessary information to identify exactly the run Technical concept The meta handling is straight forward The state of the different control is reported as elements of the set META and related long text descriptions report the state of the control as shown below from an example application SET META Scenario description my test scenario Choose model type CGE Relative weight flows 30 Use demand elasticities
77. assification and color model to visualize the distribution of the values reports some basic statistics and shows a box and whisker diagram 0 SESAR 2SHaAea Sd Dev 264 09 Wolfgang Britz Version January 2015 71 GGIG Graphical Interface Generator User Guide Shrinking polygons according to UAA share The optical impression received of a map where colors are used to distinguish between values depends to large extent on the area covered by a certain color If the majority of the pixels is drawn in red that will send a warning message to the user In the case of the HSMUs and information relating to agriculture that message can be strongly biased as almost all HSMU comprise some other land cover then agriculture and some of the HSMU comprise only very little agriculture but e g forest shrub lands water bodies or artificial land cover The HSMU geometry therefore comprises the information about the share of UAA assigned in the base year to each HSMU That information can be used to shrink the area of the polygons when drawn on screen accordingly That is done by drawing all points of the polygons towards the centroid of the polygon and then multiplying the distance between the point and the centroid with the square root of the share of the UAA In the original HSMU geometry such polygons had been broken down to simpler ones where the connection between a point and a centroid would cut through a segment of the polygon In suc
78. ata cell one with the observations and one with the comparison output as seen below Wolfgang Britz Version January 2015 32 GGIG Graphical Interface Generator User Guide BIOF_D2E2 gt Income Hectares or Yield Supply Euro ha or herd size kg or 111000 1000 t or 1000 head 1000 ha or head ha or animals head 438 65 59217 85 4958 80 293649 34 17 73 2 08 3 58 5 58 Cereals 454 55 8335 37 2271 59 18934 54 30 01 13 24 5 17 18 50 Oilseeds Other arable 1693 24 7938 25 32743 16 259923 47 crops 4 26 2 27 2 99 0 78 The Data dimensions used for comparisons allows to select one or several dimensions used for comparisons A typical application is the comparison against a scenario The use of more than one dimension allows e g to compare values against a specific year of the reference scenario For each comparison dimension a drop down list allows to select the Element used for comparisons defined the comparison point If statistics had been added to a view these can be used for comparisons as well they can be found at the bottom of the selection list Showing a histogram window The system offers different ways to retrieve information about the distribution For maps and tables the user can show an additional window with a box and whisker diagram a histogram and some descriptive statistics as shown below The box and whisker diagram is defined as
79. ated below El Build regional database Data View 1 SEE gt Table Production activity View type Supply details mapping wiew Other arable crops oe amp Ka Income Euro ha or head Y iaa j Hobs 270 00 Mean 3164 16 StdDew 40975 38 Utrecht 43307 4 25 Acores 109324 0 438378 94 Ahvenanmiaa Aaland Implemented outlier detection algorithms The GUI offers different outlier detection algorithms as discussed below For all the methods the user may additionally define a maximum percentage of observations shown in which case only the largest or smallest outliers according to the outlier detection algorithm selected will be added to the table view Standard deviation around the mean The user can define the factor B applied to the standard deviation Observations are marked as outliers when their distance to the arithmetic mean exceeds the value defined by the multiplication of the standard deviation o and that user defined factor B a x 8 O gt X gt x B o Wolfgang Britz Version January 2015 44 GGIG Graphical Interface Generator User Guide That detection works well if the data are approximately normal distributed but might fail if large outliers are present which can easily bias the results as they will change both the mean and the standard deviation of the observation sample Further on many time series e g in the CAPRI data base have by definition a lower limit of zero so that the assumption o
80. ated whose members represented means of consecutive observations of the original one The members are set so that the number of observations from which the mean is calculated is not bigger then 1 500 of the original population size and that the spread of those observations is smaller than the minimum of 1 500 of the spread of the total population and 10 of the standard deviation The actual calculations are then done taking the size of the resulting classes into account Quantile The observations of the regions are split in a way so that approximately the same number of observations fall into each class Quantiles are cheap to calculate and are therefore the default setting and often appealing as colors occupy similar areas in the overall map as long as the polygons have approximately the same size If unique values are found at the end of a quantile the algorithm will either exclude all observation with that unique value from the class or include all of them The decision will be based on the fact 1f with or without inclusion the size of the class comes closer to the desired Wolfgang Britz Version January 2015 14 GGIG Graphical Interface Generator User Guide size If the user has e g chosen five classes the desired class size should cover 20 of the observations or area weights Quantile based classification work not well if the distribution is far from uniform in which case the differences between the classes might be rath
81. be opened in an additional tab In case the new file comprises includes they will be added to its node Wolfgang Britz Version January 2015 131 Gams includes D d capri gams capmod gms gams util lacronyms gms gams util global_settings gms gams sets gms gams util title 1 gms gams util kill_model gms gams capmod define_regional_sets c gams arm arm_sets gms gams policy policy_sets gms gamsyegcge yegcge_decl gms gams regcge yegcge_capri gms gams eports yep_sets gms gams envind sets_ammo gms gams feed feed_decl qms gams supply def_supply_model_par gams capmod create_sim_ini_gdx gn gams capmod Joad_sim_ini_gdx gms gams supply yield_elas gms gams capmod shift_yields gms gams inputs yieldIY gms gams capmod define_inputs gms gams yegcge yegcge_templ gms gams yegcge load_unload_ini gms gams supply supply_model gms gams sugar breakdown_quots gms gams capmod nflation_and_trend_ir gams capmod pil_price_transmission gams util title gms GGIG Graphical Interface Generator User Guide d capri gams capmod gms gams yegcge regcge _capri gms un Input rrom SCEnAarro rise Ir requrrtu ifi CALC MTR on Sbatinclude policy calc mtr top gms BAS definition of regional sugar beet quotas SInclude sugar breakdown_quots gms DATA RS Quotas SUGA Y DATA
82. cal disk not one on a file server should be chosen The GAMS options field allows the user to send its own settings to GAMS e g as shown above the page width used in GAMS listings and the number of maximal process dirs generates by GAMs The number of processors used in GAMS will determine how many parallel GAMS processes will be started with threads are in use The relative processor speed can be used by the GAMS code to e g determine if threads should be used or not The generated entries in the include file are shown below SONTEXT GAMS options SOFFTEXT SSETGLOBAL gamsPath L 4 24 34 SSETGLOBAL gamsArg SSETGLOBAL rExe SSETGLOBAL trollExe SSETGLOBAL NoCPU SSETGLOBAL procSpeedRelative 166 SSETGLOBAL JAVA ON SVN related settings SVN user id SVN password SVN URL for Gams https svn 1 agp uni bonn de svn capri trunk gams SVN URL for results https svn 1 agp uni bonn de svn capri trunk results reacge SVN URL for restart SVN URL for data Report SVN URLs and local modifications to include file The SVN settings can be used to perform checkout and updates in cases where the model code with related data restart files or result files is under versioning control on a SVN server If the model is not under version control the settings svn no renders the tabbed plan invisible The SVN settings are thus only optional Wolfgang Britz Version January 2015 14 GGIG Gra
83. calMod2 T britz capri_liaise gams arm market_model gms set countriesMeta Run scenario with market model Run scenario with market model sunLocalMod3 T britz capri_liaise gams pol_ input liaise liaise_ scen gms set countriesMeta Run scenario with market model Run scenario with market model synLocalMod4s T britz capri_liaise gams capmod set_and_store_dataout gms set countriesMeta Run scenario with market model Run scenario with market model synLocalModS T britz capri_liaise gams capmod oil_ price_transmission gms File menu 4 TAbritz da Utilities Font p MI FENPFINTF ba Wolfgang Britz Version January 2015 113 GGIG Graphical Interface Generator User Guide Settings menu Edit settings Load settings from ini file Save current settings to ini file Remove task specific settings Remove view specific settings The settings dialogue was already discussed above Utilities and GUI menu Most of the utilities are discussed below GUI Settings Batch execution Generate GUI geometry from shapefile These utilities are discussed below VUES OVI seTtungs Utilities Batch execution The batch execution facility is a tool which e Allows executing many different tasks after each other without requiring user input e Reports the settings used any errors and GAMS result codes in a HTML page from which they may queried
84. cess to some more often used functionalities Wolfgang Britz Version January 2015 91 GGIG Graphical Interface Generator User Guide Back to Table View Classify Classify current wiew by machine learning Customize Copy region info to clipboard Apply zom to all windows e Back to Table View Shows the data currently visualized as a table e Classify opens classification dialogue see Changing the classification and the legend e Classify current view by machine learning see Machine learning e Customize opens the dialogue for general view options see Changing view options fonts number formatting and rounding hiding empty cells comparisons e Copy region info to clipboard see the information on the info window in Getting data for specific polygons Its content is copied to clipboard e Apply zoom to all windows If several map windows are opens the currently zoom in regions will be tried to make also the zoom in all other map windows Exporting the data to ArcGIS The following section will briefly explain how to work with the data generated with the Export to file utility in DBF in ArcGIS Under Layers choose add Data Wolfgang Britz Version January 2015 92 GGIG Graphical Interface Generator User Guide r i Untitled ArcMap ArcInfo File Edit wiew Insert Selection Tools Window Help Os St BExXlo ols Gy id ees E EE Ll Ugh Dap ito I SE
85. ch give additional information on the columns and rows They will appear when the mouse is moved over the respective column or row header Y Income Hectares or herd size Yield Supply Crop share Euro ha or head 1000 ha or hds kg or 1 1000 head ha or head 1000 t or 1000 animals or 0 01 A iums Revenues variable costs according to the definition of Economic Accounts for Agriculture income available to Farmers to pay for land labour capital and profits JO DJ F 345 70 iJAl 1171 26 140 57 39192 45 5509 33 30713 87 14 4 PRA4AL PR 4116 05 _ aay Drill down Some views comprise hyper links to other tables Numbers with hyperlinks are shown in blue 2515 60 22 ble click to table Supply details and a tooltip will appear when the mouse is moved over them Double clicking in the cell will jump to the connected table Clipboard export The content of the currently shown view can be copied to the clipboard by pressing the button Tables are placed as tab delimited text in the clipboard so that they can be pasted into spreadsheets Graphics and maps are placed as graphics in the clipboard and can be copied e g into word processing Note If copying numbers from the clipboard to EXCEL it might be necessary to change the delimiter If the clipboard content is pasted into a spreadsheet program e g to generate nicely formatted tables or graphics it is recommended to past the raw data into one shee
86. ch observation of equal cumulative probability if the draw line shapes is switched on How to draw a line chart with mean min max etc over a time series Alternatively to a deviation renderer one can also show more Statistics as time series In order to do so e Put the observations 1 e the stochastic draws into the rows of a table e Put the time dimension in the columns e Use the pop up menu in the table under statistics to show the statistics you are interested in the table Wolfgang Britz Version January 2015 63 GGIG Graphical Interface Generator User Guide LANA HERBA View Handling Windows e Region Activity Product A Reserv Lev m above sale KE 2 3 4 5 6 7 8 Y di 1887 22 1886 60 1885 96 1885 36 1884 80 1884 30 1883 85 188 d2 Reload 1886 98 1887 24 1886 43 1885 43 1885 39 18 d3 Copy io Cipboasd 1887 70 1887 67 1887 72 1887 41 1886 75 188 d4 Epi Tta 1887 45 1887 52 1887 45 1886 91 1885 50 188 d5 aps 1889 03 1888 23 1888 23 1887 32 1886 39 18 d 1888 30 1888 54 1887 87 1886 53 1886 07 18 Customize Table 1885 80 1885 56 1885 88 1886 13 1886 68 18 dg Statistics 1886 91 1886 93 1886 85 1886 93 1886 35 18 d9 TE 1886 92 1886 98 1886 58 1885 71 1884 75 18 d10 1886 25 1885 01 1884 90 1885 45 1884 95 18 di oa 1888 40 1887 84 1888 18 1888 81 1888 33 18 d12 1886 97 1886 29 1885 86 1886 50 1886 50 13 dz Table View 1887 26 1888 27 1887 85 1886 50 1885 70 18 d
87. columns User View definitions GUI Selection pivot supplied filters Exploiting results For each work step pressing the Exploit results button CompileGams Start GAMS stop cams Exploit results Which will load the exploit result exploitation panel shown below Wolfgang Britz Version January 2015 22 GGIG Graphical Interface Generator User Guide Graph The interface in exploitation mode Result exploitation EU EU27 BL Belgium and Luxembourg DK Denmark i DE Germany EL Greece ES Spain FR France Scenario 4 IR Irland ET Italy INL The Netherlands Scenario 1 RES_2 0820ANIMWELF v Scenario 2 X Country selection Scenario 3 as Scenario 5 v Scenario 6 X 0 Regional level Scenario 7 X Scenario 8 X Base year selection 08 Scenario 9 v Scenario 10 X 21 Scenario 11 v 22 23 Scenario 12 i 24 Simulation year selection 25 Scenario 13 26 27 Scenario 14 X 28 29 i Scenario 15 v Show meta Dj Show results I Load content of files into GDX viewer Return The right hand side comprises a set of drop down boxes from which up to 15 different scenarios or result files can be selected Each box comprises the list of GDX files found in the result directory registered for that task The first element in each box is empty The user can thus select in each box a file or lea
88. cross sets and the like should be preceded by some explanatory comments 4 Symbols which are only used locally in a file should be deleted from memory by option kill 5 Before defining a new set one should check if not the very same collection of 99 4 elements is not already defined 6 Lengthy data tables should be moved into a gdx file to reduce the number of code lines 7 Data should be accompanied by meta data Clearly the standards and recommendatio must become part of a programming guide General overview CAPRI technical documentation Automatically generated fron t britz capri gams captrd ref t britz capri gams capreg ref t britz capri gams capmod ref at 21 07 2008 09 30 24 open all close all 4 Types Parameters AS Sets captre capreg capmod at least in one project H Files H Equations ES Variables captrd E capreg capmod at least in one project A 3 Elements captrd capreg A v A feature request was sent to GAMS to support local scope so that a symbol can be declared local for a file Project analyzed project Used in captrd capreg capmod any projects Paramep Used in project captrd open all close all W open HG A fm cC fa D fon E J F JH Le GE ot page Selection of symbols by type and project Alphabetical list of symbols with domain
89. d by their means to define eight classes This works well with rather skewed distributions Manual classification Finally the user may set the class limits by hand In order to do so double click the mouse on the appropriate row in the table with the classification results in the column class limit The value can now be changed with the keyboard When this is done click into another cell The labels will be adjusted accordingly Afterwards when all class limits are defined the user may also overwrite the label e g using words as low or high Wolfgang Britz Version January 2015 15 GGIG Graphical Interface Generator User Guide Please keep in mind that currently the values will be lost if you load other data or change the classification number of classes etc a TC 10 00 lt 0 00 i O i o 7 35S 51 86 CSTE 112 821 TES i S lt 586 84 586 835 17317 Integration distribution information in the map window The GUI allows the user to enter distribution information in the map in different ways The first possibility is to print a simple frequency diagram above the legend Ll box Show distribution rectangles For classes That gives a rather intuitive feel on how well the class limits represent the data distribution In our example below it is obvious that the majority of the values lie in the first class 0 00 49 28 682 58 450 86 Less suitable for final out
90. d is from the standard WEKA GUI so that the user manual from WEKA can be used for further information PS The cluster panel is not described 1t works quite similar Note however that filters are not applied to the cluster see below Filtering 4 Weka Explorer GUI Supply details mapping view 1 Quantile 20 46 17 Classify Filter view and Select Attribute Evaluator Choose CfsSubsetEval Search Method Choose BestFirst D 1 N5 Attribute Selection Mode Attribute selection output pees an abu Lmuciun lt Use Full training set Folds 10 Evaluator weka attributesSelection CfissubsetEval Seed i Search weka attributeSelection BestFirst D 1 N 5 Relation Supply details mapping view 1 Quantile 20 46 17 Instances 300 i Attributes 5 Result list right click for options 20 50 53 BestFirst CFsSubsetEval Crop share Animal density Class numeric Evaluation mode evaluate on all training data Attribute Selection on all input data Start set no attributes Search direction forwar d Stale search after 5 node expansions Total number of subsets evaluated 13 Merit of best subset found 0 388 Attribute Subset Evaluator supervised Class numeric 5 Class numeric CFS Subset Evaluator Including locally predictive attributes Selected attributes 1 4 2 Revenues Crop share Animal density The filter panel allows running different types of filters which remove
91. d then press remove result of filter from existing selection Activity hems l Generate baseline Ed Filter dialog xj nko Nha Define numerical selection Filter For table rows Ex Comparison operator Comparison value a 1 Ex gt kd 150 147 70 165 36 Ex Clear selection and select according to filter Han a Ex Add result of filter to existing selection 464 02 De Remove result of Filter From existing selection aa DK anc 130 30 99 590 H2873 160 19 H2874 134 93 H2875 29 19 H2876 7 36 H2877 126 3 Pahinenindieoecinicrion H2878 113 30 Now drawing a map with just those regions 1s not so interesting However with the tool dialogue we can highlight the selected value instead of hiding all others The selected rows are now shown in red in the tabular view Wolfgang Britz Version January 2015 86 GGIG Graphical Interface Generator User Guide Exploitation of spatial results Data iew 2 Activity Items Tabl Juaa Ino 5 a Mineral Fertilizer Consumption Nitrogen kg N ha v Jao Customize view Arial sal ii plain H2865 147 70 l Bree eee H2866 169 36 Fraction digits and decimal separator 2 w w H2867 176 21 i l H2868 164 02 Separator between merged data dimensions w H2869 99 38 l H2870 95 50 H2871 130 30 H2872 99 90 H2873 160 19 Hide empty rows T Hide empty columns H2874 134 93 H2875 29 19 Cut off limit
92. directory fields The entries with a R at the end such as resDirR use unique style forward slashes as delimiters and should be used with R projects The scratch directory stems from the GAMS settings tab discussed below SONTEXT Directory settings from ini file SOFFTEXT SSETGLOBAL curdir gams SSETGLOBAL curdirR gams SSETGLOBAL resdir T britz res_ microdata SSETGLOBAL resdirR T britz res_microdata SSETGLOBAL datdir dat SSETGLOBAL datdirR dat SSETGLOBAL restartdir restart SSETGLOBAL restartdirR frestart SSETGLOBAL scrdir d temp SSETGLOBAL scrdirR dif temp The Look and Feel L amp F which can be changed via the menu bar Wolfgang Britz Version January 2015 12 GGIG Graphical Interface Generator User Guide Batch execution Generate GUI geometry from shapefile System Metal Nimbus a ee The system L amp F is the default chosen and will render controls as close as possible to the standard of the operating system The Metal and Nimbus are L amp Fs which are portable across platform Especially Nimbus has a nice look compare with the screen shots above caera ronan a File Utilities GUI Settings Help CAPRI worksteps Build database Generate baseline Run scenario CAPRI General settings Scenario description 7 scenTemplateGHGAbatement iy g a CAPRI tasks D
93. ducts and activities Only export aggregates for regions Mode Model overview Income Mode Mode Beware the pre defined table structure will be lost with DBF format as will the long texts and units attached to the tables However in the case of DBF export a second file with that Wolfgang Britz Version January 2015 38 GGIG Graphical Interface Generator User Guide information will be automatically created If you solely want to export the table you have currently up front use the copy to clipboard button The clipboard export will retain the pivoting and further information 2 Please choose a file format for export l x Export Data Start Export Maximum number of non zero items to export 696122 Open File in Editor after file was created Define column List output no data dimension in columns List output no data dimension in columns Input and outputs Scenario Back Stark The last pane let you decide for DBF export if you want a list or if you want the data dimension spanned across the columns For exporting the HSMU tables it is recommended to put Inputs and outputs in the columns In case of DBF format if everything has worked well we should now find two files one with the data named as chosen in the file dialog and a second one with meta introduced before the file extension Working with EXCEL export If the format XLS or
94. e Generator User Guide oinData O OOO x Join lets pou append additional data to this layer s attribute table so you can ro rand Editor h Task create New Feature Target for example symbolize the layer s features using this data What do you want to join to this layer Advanced Join Options x Join attributes from a table C Keep all records default Ifa record in the target table doesn t have a B 1 _ 1 Choose the field in this layer that the join will be based on match in the join table that record is given D 2 m null values for all the fields being appended D HSMU z into the target table from the join table E Join table Target table Target table 2 Choose the table to join to this layer or load the table from disk Keep only matching records ms E test 7 If a record in the target table doesn t have a B 1 B BTT MV Show the attribute tables of layers in this list match in the join table that record is D 2 removed from the resulting target table D Note If the target table is the attribute table of a layer features that don t have data 3 Choose the field in the table to base the join on joined to them will not be represented in the Join table Target table Target table layer when you use this option Regions_a Cancel Advanced About Joining Data OK Cancel l x If anything has worked well you should now see the country or count
95. e drop down boxes or by de selecting columns and rows There are specific possibilities to change class limits colors and further features for maps which are discussed in the following Exploitation of spatial results Data iew 1 O x Table Indicator i No 5 a Mineral Fertilizer Consumption Nitrogen kg N ha 3 v Selection of table item Selection of tables will Button to open selection open popup menu dialog for table columns in case of several maps Button to open selection dialog for table rows HMUs 0 00 0 00 lt 26 41 51 66 112 62 566 84 Changing the classification and the legend In order to change the layout of the map click the mouse in the area of the legend or double click the map option button The following dialogue will open Wolfgang Britz Version January 2015 69 colors Click to show histogram window showing current class limits and GGIG Graphical Interface Generator User Guide User options to change colors and classification S Map option dialogue Number ofdasses 50 Number of regions with small large values exduded from classification o o limits colors 5 2k Treat zeros as missing values Use area weights for d C Draw in high quality Emboss map gt 0 gray O none lt 0 colored embossing Color tbe SSSR clr EAI een veo ss E Set value for middle color 2 of area ooo s
96. e g 1 will round all numbers to tens The numbers shown in graphics or tables are based on the rounded results is applied e Selections for columns column groups if present rows and row groups if present The buttons will open selection dialogues see the section on Column and row selection above e Manually settings for column and row width The buttons will open selection dialogues see the section on Column and row selection above Alternatively the row and column size can be changing by dragging with the mouse a double arrow resize cursor indicates that mode If the column size is dragged while the shift key is down the new column size will be applied to all columns e Hide empty rows and hide empty columns will suppress in the currently seen view any columns and rows which would show only blank cells e Cut off limit to determine empty cells In standard mode the interface will treat zeros as missing values and items will be shown as blanks But the user might also enter a Wolfgang Britz Version January 2015 31 GGIG Graphical Interface Generator User Guide different value any value in absolute terms below the threshold set by the user will be treated as if 1t was zero e Use default pivoting for table That is the normal mode where the pivot is defined by the table views By clicking that off the currently chosen pivot from the current table or manually defined will be kept
97. e inline code of CAPRI sometimes called doclets e g The following shows a possible implementation which is currently already operational start author W Britz docRef perfect aggregation of production seeAlso gams capreg cons_levels gms MODEL CONS LEVLS In the example above the REF file will comprise the information were the model CONS_LEVL will be declared and the JAVA application will search backwards for lines Wolfgang Britz Version January 2015 122 GGIG Graphical Interface Generator User Guide with tags Those tags will be linked to the object and integrated in the HTML pages The start tag must be used to declare the start of the documentation for the current symbol Refactoring Consequences for Gams Code l All files should carry a header which reports the purpose of the file and if possible an author contact person The file header should start with a line of stars and end with a line of stares All lines in the file header should start with a The use of GDXIN is discouraged as it may load in huge amounts of data at run time Equally it will load element codes comprised in the data sets even if they are not referenced later in the code The only exemption is when the symbol must be loaded at run time as in case of META data instead execute_load should be used An IF NOT EXIST myFile ABORT myFile is missing statement should be in the line bef
98. e number of bins affects the number of xy cells above the diagonal a value of 5 generates 5x5 25 cells and gives a graph as follows 1 06 J Gans a Cox o Oo ir r v v v v v 0 800 0 825 0 850 0 875 0 900 0 925 0 950 0 975 1 000 1 025 Wolfgang Britz Version January 2015 61 GGIG Graphical Interface Generator User Guide Changing the dot size can ease the visualization of the distribution Finally not shown here graphically the regression lines can be switched on and off Deviation renderer A deviation renderer shows the median of a series along with a symmetric quantile around it That makes only sense if one has an ordered series e g points in time 68 amp 8 amp amp FB amp a 4 N a 8 a o o o Ld o a c In order to produce such as graph e Put the observations e g years in the columns e Put the draws in the rows e Put the scenarios in the column groups The bandwidth of the graph can be changed with the Quantile around mean setting in the graphic dialogue below the bandwidth is 22 11 above and 11 below the median Wolfgang Britz Version January 2015 62 GGIG Graphical Interface Generator User Guide Options for Statistics Bins zero default rule d a Quantile around mean 11 K The deviation renderer can be expanded to resemble a contour plot which shows the density inside the band by lines which combine point for ea
99. e results themselves If the story is well told the black box character of the tool is removed and its usefulness in depicting major cause effect relations becomes evident Telling a good and right story requires however often quite some time in analyzing results in a systematic way Wolfgang Britz Version January 2015 99 GGIG Graphical Interface Generator User Guide The user will hence have to decide for which items of the huge data set a thorough analysis of underlying drivers is advisable Limited time and human resources will set tight limits to the extent of such systematic analysis Typically in any report only a few dozen key results perhaps complemented with a few maps showing several hundredths numbers will be presented But these key results such as changes in aggregate welfare farm income GHG emissions or the nitrogen balance are calculated from thousands of simulated items How can we discover the story behind the results 1 e which regions activities price or policy changes etc are most important for the aggregate changes communicated The exploitation tools of GGIG with a flexible on the fly approach to produce tables graphs and maps had been an important step to improve the efficiency in exploiting and analyzing results But in parallel tools such as CAPRI has grown in scope and scale It might be the time now to consider new approaches to analyze model outcomes Wikipedia gives the following defi
100. e rows Table cells area Region 387 Next one uses the option dialogue to configure the view such that e g percentage differences against the old version are displayed Lej Customize vew E Cna Tahoma y il plain 7 Fraction digits and decimal separator 2 w Separator between merged data dimensions l Column width 140 Row width 140 Hide empty rows Hide empty columns Cut off limit to determine empty cells oH Use default pivoting for tables Show histogram Use dassification colors for tables Show only selected items x Long texts only X Comparison output Values and percentage difference w versions RES_TIME_SERIES161111 Ca Cameos Caesia Carece Codeer That produces a view as seen below but it is clearly not inviting to scroll now through about thirty years and almost 400 regions Wolfgang Britz Version January 2015 141 GGIG Graphical Interface Generator User Guide Product versions Activity Percentage diff to G e uev Ly swe z RES TIME_SERIES161111 5 F 1984 1985 1987 1988 m 1990 E j 1993 ie ko000000 BL000000 191 82 193 53 193 94 198 26 217 70 219 46 218 99 213 93 214 54 211 95 1 23 1 33 0 19 1 43 1 25 0 03 0 40 0 32 0 50 0 98 DK000000 318 33 326 64 341 43 381 43 296 88 434 96 516 55 504 30 559 60 601 09 0 67 0 93 5 24 1 02 291 2 03 1 01 1 27 3 45 2 03 DE00
101. e the information where the GAMS executable can be found but also where the GAMS code of the project to start is stored see the discussion on settings above Viewing results exploitation tools The basic strategy of the GGIG exploitation tools roots in the CAPRI exploitation tools which require that all model results are stored into one GAMS parameter which can have up to 10 dimensions and saved to GDX container as a sparse matrix on disk One or several GDX containers with results are then read from disk and merged An additional dimension can be added if several files are loaded e g to compare scenarios or years A specific XML dialect defines views filters pivots view types into the cube and allows the user to load several result sets typically from different scenarios in parallel If no table definition file is present GIGG offers a GDX viewer which some interesting possibilities not found in the standard GDX viewer such as numerical sorting statistics selections For details see below Views as the basic concept for exploitation The concept of the GGIG exploitation tools is centred on the idea of a view Content wise each view may be understood as showing one or several indicators relating to results of working steps defined in GGIG e g environmental effects of farming prices or market balances Each view thus e extracts a certain collection of numerical values filtering e labels them so that they car
102. ed drop down box choose the class limit for which the middle color should be used The effect is shown below Before values in the class below 392 70 the middle class were drawn in yellow When the user now selects another class limit the colors assigned to the classes change Here one of the shades of green is dropped and shades of red are added Map option dialogue x Map option dialogue xj Classification method Manual v Number of classes 55 Classification method Manual v Number of classes 5 Number of regions with small values to remove From class definition o Number of regions with small values to remove From class definition l B Number of regions with large values to remove from class definition 4 Number of regions with large values to remove from class definition 4 J Treat zeros as missing values Use area weights for classification Treat zeros as missing values J Use area weights for classification 7 Draw in high quality JV Shrink polygons according to share of UAA J Draw in high quality V Shrink polygons according to share of UAA 7 JV Set value for middle color 112 82 E 0 1 0 00 lt 0 00 0 30 433 NS 1 0 00 lt 0 00 30 488 2 lt 28 41 28 407 17 398 M 2 lt 28 41 28 407 EDLO O i O 3 lt 51 86 51 865 17 398 m 3 51 86 51 865 EL O 4 lt 112 82 112 821 EDR o 4 lt 112 82 112 821 17 398 O S 5 lt 586 84 586 835
103. ee also http en wikipedia org wiki Box_plot Boxplots can be useful to display differences between populations without making any assumptions of the underlying statistical distribution they are non parametric The spacings between the different parts of the box help indicate the degree of dispersion spread and skewness in the data and identify outliers Boxplots can be drawn either horizontally or vertically text so far from Wikipedia The box and whisker chart uses the rows as the observations and generates an own graph per column The box shows 25 of the observations around the median which is shown as a grey line whereas the arithmetic mean is shown as a grey circle The whiskers show the median three times the inner quartile range Mild outliers are drawn as dots and strong outliers are indicated by arrows So far there are no specific options for that type of diagram Wolfgang Britz Version January 2015 58 GGIG Graphical Interface Generator User Guide Exploit scenario results 0 Table Production activity Item Years View type E GAl 3 Supply details mapping view Cereals w Income Eurosha or head v an v Box and Whisker chart w bd 2300 00 4 2200 00 4 2100 00 4 2000 00 4 1900 00 4 1800 00 4 1700 00 4 1600 00 4 1500 00 4 1400 00 4 1300 00 4 1200 00 4 1100 00 4 5 1000 00 iv 900 00 800 00 4 700 00 4 600 00 4 500 00 4 400 00 4 300 00 4
104. efine scenario Generate GAMS child processes on different threads _ ee Run scenario with market model Me Er Run scenario without market model Use new global version _ 2012 I Run scenario only with market model 2013 i Eu28 Downscale scenario results 2015 Countries Run policy experiment with CGE GHG abatement technology off x 2020 eee 2025 a Simulation years 1 2030 2035 i 2040 2045 Regia Compile GAMS Start GAMS Stop GAMS Exploit results GAMS output GAMS and R related settings Option User Settings System Settings aa L 24 3 gams exe GAMS scratch Directory asiten Path to R exe Path to Troll exe GAMS Options Number af processors used in GAYS Processor speed relative 100 2 4 GH Intel core 2 Save in caprinew ini The Path to Gams exe points to the actual GAMS engine to use It can be entered in the text field Alternatively you can use the button to the right of the field to navigate to the directory where GAMS EXE is found via a file selection dialogue Please do not only enter a Wolfgang Britz Version January 2015 13 GGIG Graphical Interface Generator User Guide directory but the full file name as shown above and choose GAMS EXE not the user interface of GAMS GAMSIDE EXE The Scratch Directory will be passed to GAMS and determines where GAMS stores temporary files A directory on a lo
105. elp CAPRI works GDX Viewer Build datz Start equation and variable viewer J Generate Build HTML documentation Run scen SVN update menu item c Utilitie S l SVN up date CAPRI tasks Use t britz capri gams util cleanUpGamsDir bat to clean up source directory l An up d ate will download updated versions of files into hidden directories and if the related files in the local working copy have not been modified will also replace the local files Choosing that menu item will open a dialogue with just one button termed update and an area into which messages from the SVN updates checkouts are reported SYN settings Pressing the update bottom will trigger an unpdate Possible conflicts merges etc are shown in the reporting area Wolfgang Britz Version January 2015 16 GGIG Graphical Interface Generator User Guide Update for t britz capri gui completed at revision 5310 Files sub directories updated t britz capri results I Update for t britz capri results completed at revision 5310 Update for t britz capri dat completed at revision 5310 Skipped ti britz capri restart fert fert FR gdx Files sub directories updated t britz capri restart fert Skipped t britz capri restart inputs LAB EXPTVAL GDX Files sub directories updated t britz capri restart inputs Files sub directories updated t britz capri restart 2 files were skipped probable conflict
106. enies 53 hne mad FOOLING enar S eana A E A E e tad meat ove 54 Pie CANIS ineen E E deeaecGededanasentennites 56 E 0 8 CE ae 0 CSI o A A E Nee A A E E E E E NE renner E ET 57 Wolfgang Britz Version January 2015 4 GGIG Graphical Interface Generator User Guide BOX An W TIS KOR iC AILS oboe closet E E E donee Seliawagare opmental 58 PIS TO SCAMS nna E E Sian hauen ane eiateuts 59 SCAU CE PIOS acetic adn ether slaw actrees ieee ls dle ta oS a tates Uae redid dette Snore eaten lets 6l PVCS PAC OI rendere oaser a S 62 How to draw a line chart with mean min max etc over a time series cccceeeeees 63 Markov Charis sesia A A 65 WOK ME Wt TAPS eee T ees lnsareiariakstablaaeiaetiehaaeineencemiehhakes 66 FOW Die a eal ees A ceed ee rola tg eteecsetioaens 66 Pie eMart MAPS ene ayoaceaaseaccatie dvaaesaiesaea ie aeeateas E N 68 CONOR CIS IIS Sie see casete eet Ri hes ease Scales Aes ath ote Swen A een sneecien 68 Changing the classification and the legend cc cccessseessecceceeceeaeeeseececeeeesaaaeeeeeeeeess 69 Cane OTe COOLMIMALC GEL aere E E 70 Adding a histogram window to a map seeeessssssssseressssssssceeresssssssccterssssssseeeressssssseeeeeee 71 Shrinking polygons according to UAA share cccccccsssseesececeeceeeaeeeeseecceeeeeeaaaeseeeeeees 12 Ared W CLS Ged CAS SHI CATON asen A dames nebo teen heeuaeeatanwen 73 Excluding zeros from classification and removing small and large values
107. er arable Euro ha or head Euros ha or head kg or 1 1000 share Animal Euros ha or head Euro ha or head kg or 11000 share Animal Revenues head ha or head density headha or head density Euros ha or F or 0 01 or 0 01 bd animals ha animals ha European Union 27 818 70 468 75 5524 26 30 49 893 92 517 03 2806 03 4 90 European Union 25 839 28 482 20 5758 41 30 13 994 25 566 36 3105 66 4 28 European Union 15 952 81 513 61 6318 16 25 80 1065 26 566 93 3388 98 3 49 European Union 12 609 81 400 97 4278 35 42 65 722 94 475 00 2187 93 8 54 European Union 10 578 69 419 93 4513 20 48 02 861 86 585 72 2563 58 7 56 Belgium 1177 16 561 93 8640 45 24 77 1409 88 778 13 4336 85 3 78 Denmark 1013 76 352 26 6855 01 53 84 1249 95 497 01 3778 61 3 26 Germany 1059 39 441 45 7527 86 39 25 4314 72 638 80 4251 82 7 29 Austria 889 55 497 57 6973 35 21 66 947 31 675 02 2404 66 3 17 Hetherlands 1266 88 711 29 8827 19 12 49 868 24 764 83 3095 68 0 52 France 1085 12 438 20 7479 60 29 96 1014 91 456 67 3405 41 6 27 Portugal 746 24 356 13 3898 35 6 25 191 71 144 97 497 99 0 60 Spain 593 53 532 23 3498 86 20 42 433 16 473 81 1072 65 1 29 Greece 794 69 891 07 4133 29 18 20 608 18 776 33 1655 66 0 04 Italy 1053 24 706 05 5754 93 28 54 874 83 542 60 2871 15 1 68 In order to start the clustering classification we click in the table to open its popup men and then select Classification
108. er different Equal interval The differences between the current minimum and maximum value is divided into classes of equal spread This may lead to rather curious class limits when outliers are present In those cases it may be appropriate to exclude some regions from the classification See below for details how to exclude regions from the classification Mean standard dev The class limits are defined according to the mean and the portions of the standard deviation of the data It works best with normally distributed data but may result in very small classes if the distribution is skewed e g long tailed The algorithm will always introduce at least four classes then six eight ten and twelve More than twelve classes are neglected The algorithm takes into account the spread of the data and sets the class limits accordingly If all observations fall into 25 of a standard deviation class limits are introduced at 25 and 10 for four classes If the number of classes is higher new limits are introduced at 5 2 9 1 and 0 5 In case of 50 the smallest class is dropped and 50 added and so forth up to 3 standard deviations Nested mean The nested mean classification will only work with 2 4 or 8 classes The classes will be defined such that one break is found at the mean of the sample The resulting two halves of population are then again divided by their mean to get four classes and the resulting quarters divide
109. ersion January 2015 73 GGIG Graphical Interface Generator User Guide graphs present in the map option dialogue to check to what extent the class limits chosen represent the data well It is generally recommendable to try out different classification The following classification methods are currently supported Natural breaks Natural breaks classification is a method to cluster the data into classes so that differences between the means of the classes become high while the standard deviation inside the classes becomes low FISHER W D 1958 On Grouping for Maximal Homogeneity Journal of the American Statistical Association 53 789 798 Code based on HARTIGAN J A 1975 Clustering Algorithms John Wiley amp Sons Inc New York pages 130 142 The algorithm does not only find the approximate best solution but often gives rather appealing class limit definitions It works rather well if no extreme outliers are present in the distribution In the latter case classes solely comprising the outliers will be generated and the vast majority of the values will be put in one or two classes Here it might help to exclude some very large and small values from calassification The clustering algorithm is rather expensive to calculate so that in cases in which the population exceeds 500 observations a somewhat simplified version is implemented in the CAPRI GUI From the original observations a condensed population 1s gener
110. es Sate clea N ho saan ia aljaendcnba dean ests 30 SOWA TALS COST ANT WU OW as setae sar ctranrecitc ero aastana tothe ear te waetts Deals de manent inuecaabes 33 Working With TADICS eeir a a TE T 34 TE TOOL e a a eee tee eee 34 ToolupsTotcolumiand rOW Deade tSarain a iaieteb aan iaesiad dab ralemeeeaeieiee ss 35 Dodo W Meesenoes an a e 35 CHP DOA Ae PON ena E R 35 EXPO tO Tl nenrean E E E aiadie ean 35 Working With XCEL Ex pO eee E EO 39 S10 eH Ot See eC ATES Ree ere eee Te Ree E Seer hr pee emer rere eer 40 Numerical filtering based on Cell contentseccininssesnnn a Des RENaeeaeetons 4 Changing the row height and column width with the MOUSE ceneeeeeeeeeeeeeeeees 4 Ada MESAS CS rae ecoctcacr a eaten vet cha aaa E aa ienetous 4 Implemented outlier detection algorithms cccccccsesessseceeceeceaeeseeseeceeeeeaseeeeeeeeeeeeenaas 44 Pop Up inei e te a caren tone pce a seuewe eee ans dune teed eiaedamoamaeneeten 46 Workin WISAN Sene aa eae a a e a Pandaecendsaieduenctivedea teaver 47 General handing of graphs wisserdccnesecwesvessiancsnaswasiainedeandergdnveatasdcandsndeue sadieadenncstadapsaaaddvaies 47 SCM CoO mM a a a E E EE 49 Walk ite Amoudi The Cadladccstattustein O OOE 50 EXMOrine the Crapmic 0 THC essien R tinea dteetidinuuetiluenctitnertaeetia 50 Exporine the orapnic t0 Clip DOardaciwiea at eae aa oktons 51 Popup mena OTA PICS saeaesics tees we A 52 Bare MAr ie E ostecaerba sense atenteaued uacmesostenecbesesaas aennua
111. et directory Directory for HTML documentation files t britz capri GAMSDoc Set directory b britz caprijcodeDocInput Baseline_calibration ref t britz caprijcodeDocInput Build_global_database ref bE britz caprijcodeDocInput Build HSMU database ref bE britz caprijcodeDocInput Build regional_ database ref bE britz caprijcodeDocInput Finish national database ref bE britz caprijcodeDocInput Generate _expost_results ref bE britz caprijcodeDocInputGenerate_policy_ shifts ref b britz caprijcodeDocInput Generate trend projection ref E britz caprijcodeDocInput Prepare_national_database ref t britz caprijcodeDocInput Run_sirnulation ref List of available EXP and REF files 4 iil Generate HTML documentation The GUI comprises a tool to generate for each GAMS file and each symbol used HTML pages which are interlinked For details on the code documentation facility see the technical document Javadoc like technical documentation for CAPRI to be found on the Capri web page under technical documents The controls on top allow the user e To define in which directory the EXP REF and GDX files are stored which serve as input into the documentation generator e To choose the directory where the HTML files will be generated e To select the tasks covered by the documentation generator Structure of the HTML pages There are basically two types of HTML pages 1 Pages for individual ob
112. executed it generates a GDX file which can be loaded with the GDX Viewer 4 GDX viewer View Handling Windows _4 TEST T britz capri GUI test gdx 0 gt area_ha Center v 396553 00 4811506 50 AT12 1919280 00 4747719 00 41477 nN 4794877 NN After a switch to mapping view and the newly generated coordinate set can be loaded and checked SJ GDX viewer View Handling Windows ocr eEle FONHA Gp fi Gee Center Dimi area_ha Center 1340 00 863904 00 274655100 393848675 472168500 16508714 00 Clearly that proceeding allows inspecting numerical features in a shapefile without requiring a GIS program Wolfgang Britz Version January 2015 138 GGIG Graphical Interface Generator User Guide Analysis differences in GAMS based data using GGIG Background In result analysis such as when comparing scenarios but also when comparing different releases of data sets against each other one frequently wants to see only those values with larger changes When working with values generated by GAMS one has different ways to proceed If the two data sets to compare are comprised in GDX files one can use the GDXDIFF utility from GAMS The dis advantage is that GDXDIFF does not have information about the logical structure of the data or its content such that it might be cumbersome to filter our large absolute or relative changes which matter The other extreme is to write a GA
113. ext gams util title 1 gms gams util kill_model gms gams capmod define_regional_sets gams arm arm_sets gms gams policy policy_sets gms gams yegcge yegcge_decl gms gams pegcge yegcge_capri gms gams reports rep_sets gms gams envind sets_ammo gms gams feed feed_decl gms gams supply def_supply_model_par gams capmod create_sim_ini_gdx gn CAPRI project GAMS file CAPMOD GMS purpose Top level of the CAPRI simulation engine author date since refDoc seeAlso W Britz A Gocht M Adenaeuver T Jansson et al 22 10 09 gams capmod joad_sim_ini_gdx gms gams supply yield_elas gms gams capmod shift_yields gms gams inputs yieldIY gms gams capmod define_inputs gms gams yegcge yeacge_templ gms Zore gamsyegcgeoad_unload_ini gms gams supply supply_model gms gams sugar breakdown_quots gms gams capmod nflation_and_trend_ir gams capmod pil_price_transmission gams util title gms gams policy def_policy gms gams policy del _policy gms X r Sofflisting Sofflog SSTARS Ssetglobal metawb off e save restart point for debugging purposes in the market model calibration amp l j Options Options Set XML table definition file _ Use table definitions from null Sort code lists F Show dialog to l
114. f columns in the underlying tables each column will receive an own plot with a matching value axis The bar blocks refer to the rows each bar block may comprise several bars taken from the column groups typically scenarios As seen above it 1s also possible to generate stacked bars from the column groups or to generate cylinders instead of cubes Line and point charts Line and point charts assume that the columns of the table present some ordered sets e g years or iterations There is currently a default of 25 such observations which can be increased by the user The different series to plot are taken from the table rows If different column groups are present those receive their own plot with an own value axis Wolfgang Britz Version January 2015 54 GGIG Graphical Interface Generator User Guide FA CAPRI time series Data View 1 um ns wis wes ng na an wees wan ma s ns mas mao mwr mm mae mn an wea s msa mo an mn asw a an ax sn Sn F CAPRI time series Data View 1 Table B Camran J ra 1 MEA AE F aoo DSE L N T S T E NE ns S 2 3 5 Vv Crop share Arinal density or 0 01 animals headstha oucsaBesssaghs oS SBEBREEESE 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 item gt Cereals O Oilseeds o Other arable crops Vegetables and Permanent crops gt Fodder activities N Options for line and area ch
115. f normally distributed data sets cannot hold Therefore other outlier detection methods are also implemented as discussed below The dialog allows changing the factor B from its default of 2 which covers 95 of the values for normally distributed data Standard deviation of values normalized by median The values are all divided by the median and the new series is classified as under the option discussed above The main advantage of that method is the shift to a mid point which 1s less vulnerable to large outliers in the observations Standard deviation of trend line error A regression 1s estimated by using the index position in the unsorted values as explanatory values The resulting errors are then classified according to the first option discussed above The typical application would be a table where consecutive time points e g years are shown along the rows Median and inner quartile range Box and whisker charts which are also supported by the graphics view are using the median and quartile to visualize the distribution They are also an easy and robust way to detect possible outliers First the so called inner quartile range IQR is calculated as the difference in values between the beginning value of the first and the ending value of the third quartile The IQR then consists of the 50 range of values around the median The IQR is often used as a robust replacement of the standard deviation similar to using the median as
116. face Generator User Guide Set element list Used in project capmod CAPRI Name of element technical open all close all Sets comprising the a documentation Pan elements with HTML Automatically generated from F 5 i 1c link oe i D t britz capri gams captrd ref LSE EENS ih t britz capr gams capreg ref EFUL_heavy ITEMS SOIL_TYPES SOIL_TYPES1 EFUL_light ITEMS SOIL_TYPES SOIL_TYPES1 t britz capri gams capmod_ref EFUL_medium ITEMS SOIL_TYPES SOIL_TYPES1 ENER_CONTENT ENER_ITEM ENERM 02_CONTENT ITEMS COPY_SET COPY_SET1 COPY_SET2 at 21 07 2008 09 30 24 ENER_LEVL ITEMS ITEMS_1 fg pS ENER_TOTAL ENER_ITEM COPY_SET COPY_SET1 COPY_SET2 H Equations s ENER_kg ITEMS ITEMS_I a Variables ENER_sqm ITEMS O captrd EN_SEED PROC1 Ener_Type Ener_Type_ANI Ener_proc capreg EXP YEARS capmod EXPORT ENER_ITEM COPY_SET COPY_SET1 COPY_SET2 COPY_SET3 at least in one project Elec_cons ITEMS DRY_ENER ITEMS ES Elements Ener_ds ITEMS captrd Ener_fs ITEMS capreg Ener_weight ITEMS capmod Exp_lifetime ITEMS at least in one project F H Models G H Acronyms H H Functions I ES SourceFiles K captrd HDL capreg M capmod H N at least in one project Ho wep hd lt a a gt
117. g for Table rows Enter search pattern in Field and use buttons or use mouse to define selections Clear selection add pattern to labels Clear selection add pattern to keys Add pattern to labels Add pattern to keys Remove pattern From labels Remove pattern From keys ERE GILS HARABE vegetables and Permanent crops PERM Fodder activities FODE Set aside and Fallow land SETIF All cattle activities Beef meat activities BEFM Mon cattle PEPL Cereals ERE Ces can be selected with the mous Soft wheat WHE Durum wheat E HE The selections can be done by mouse following the convention of the operation systems Additionally a selection string can be entered in the field above with the following possibilities 663099 o select all e C select all items starting with C C will select a string starting with C followed by any 3 characters After entering the selection string in the text field one of the three buttons must be right Clear selection add pattern to labels clicked The button will remove any selection and select l l dd pattern ta labels only those items which match the pattern entered in the text field will l Remove pattern From labels l keep the selection and add the matching items whereas will remove matching items from the selection Predefined selection groups For some tables pre defined selection groups are stored When the mouse is moved over the selection b
118. h cases shrinking could let the new polygon hide other ones The graphs below show the very same map same input data classification and coloring for the High Nature Value indicator for a part of Belgium The right hand side map draws the HSMwUs into their full size the one on the left hand side one uses shrinking The message perceived is probably very different In the unshrinked right map one may conclude that there is a lot of highly intensive agriculture low HNV indicator drawn in red in the lower diagonal triangle and some important areas of high nature farmland in the protruding area This optical impression differs strongly from the polygons drawn with corrected shares for agricultural cover It turns out that in the lower diagonal triangle the density of agriculture is often low and especially low in the intensively managed HSMUs Equally it turns out that the area covered by High Natural Farmland in the protruding part is relatively small Wolfgang Britz Version January 2015 72 GGIG Graphical Interface Generator User Guide 0 o OY ies ATH iar eg pie Ri a ee E Q all 0020au sllao22 _ E GS GS OO a O O eee E Ge Ge OO a ws M M eee 000 lt 02 lt lt 2 lt lt 71 lt 82 lt 988 0 lt 2 lt 30 lt 5 lt 62 lt 1 lt 8 80 lt 988 1 2 lt 3 lt 49 lt 58 000 lt 0 lt 1 2 39 lt 4 58 Area weighted classification The classification can be generally applied trea
119. ical results and meta data in a specific GDX viewer The latter supports view definition 1 e pre defined reports to exploit the results The details of the different elements are discussed below data arical results Diagram Overview on information flow in GGIG Wolfgang Britz Version January 2015 10 GGIG Graphical Interface Generator User Guide An overview on the GUI S CgeRegEU t britz capri gams S xz File Settings Utilities CgeRegEU tasks General settings Methodological switches Calibrate CGE CgeRegEU General settings Run policy experiment Run test shocks Scenario description cge_rd_plus10 Use seperate threads V i Countries Compile GAMS StartGAMS Stop GAMS I Exploit results GAMS Graphical User Interface Generator Wolfgang Britz ILR University Bonn Institute for Food and Resource Economics 4 m CgeRegEU Ini file regcge ini i User name undefined User type runner As shown in the example above the GUI consists a few elements 1 A menu bar which allows to change some settings see the section on general interface settings 2 A workstep and task selection panel on the left hand side where the user can select between different tasks belonging to the project 3 A right hand side panel which either shows i The generated controls a button panel to start GAMS and a windows in which the message log from
120. ich require a lot of disk space and JPEG which implies a loss of quality It might therefore pay off to try several formats for import into other applications For MS Office users the Windows Enhanced Metafile EMF format is interesting as it allows changing later the graphics manually e g by adding new text and changing colors The Resolution factor field allows to improve the quality of the saved file for non vector formats such as JPEG by drawing the original graphic with more pixels which however drives up disk space Schemes shown with the mapping viewer Technially the mapping viewer colors polygons in appropriate columns and allows as indicated above to shrink the polygons according to the size of the numerical values That allows applying the mapping viewer to graphically depict modeling result in a kind of flow chart The example below depicts monetary flows in an economy simulated with a CGE shown as arrows and total account values as boxes Scenario RES O0820CGE_NO_ SHOCK 43879 04 Roe PRINIFAC 438799 04 LAND G LAB G ING CA 9 eytant c EANE P 4190 86 51 13 cao mAP 34260 75 25075 06 ING G 414 39 26741 13 Caprtar APP 18855 11 IND LAND 8803 98 INDICAB ZIP 75 18895 11 166548 03 0 00 lt 1764 34 lt 7875 11 lt 25075 06 lt 59579 65 lt 166548 03 Popup menu in tables A right click in the map opens a pop up menu which gives quick ac
121. ie n E ieee naeeies 13 SYN Teated SC UNG aana a bentua baton tieiuden alicia eniuabe domncadatetceeytatedadabeviuabe denne 14 Casc One XP liver and TUNNE he css 5 etic ties a E EAS 15 Usace for installation purposes sessen aE 17 Settings linked to theexplotation Tools sissien on eaeentwssiueneenanie 19 Help syste xis sistas a E E E 20 Strune GAMS TOn OOI Graa a a 20 Niewinne results EX PIOMaAUON OOl Suna dapiiaatacetiebsies aautece teehee 21 Views as the basic concept for exploitation ssssoeeesssssssseeeersssssssseeeressssssseeeressssssseeeeees 21 Explo TESUICS a A T 22 The multi dimensional viewer with pivoting and exporting possibilities ccccecceeee 24 Prede nNned Vie WS aena n arated esas ec teh sanae seen ie eset eaane ale EN 29 A See CULO tate E E EE E ce ae E A E EE E S A A E 29 Navi vanne toU a 0 View S eiee T A 26 Navigating in the outer dimensions of the viewport cccccccsssssseeeececeeeeaeeeeseeeeeeeeeaas 26 Column and TOW SCICCUION sns ieee A E daeakbeleaeee 21 Prederined s lection Groups rric aa a a a a 28 SEIECH OM OEE VIEW TY DC easi a isal Pale ini cued yale lomnirenn teas eaieatns 29 Manually chang me Me piv Ol sistostasepeiassshatees cisuseeindepen E 29 Wolfgang Britz Version January 2015 3 GGIG Graphical Interface Generator User Guide Changing view options fonts number formatting and rounding hiding empty cells SOURAV ALLS ONG ssc are a eerste irs gsr taic net savanna eas
122. iers 2 Set outlier detection method No outlier detection Select statistics Nobs minOutler maxOutler freeEval Free evaluation field ok _Cancel_ __ Update _ The free evaluation field follows the convention used for the definition of lt eval gt fields in table definition see programming guide that option targets experienced users and can be used to calculate an additional item in each column on the fly derived from the results to be added as an additional row A possible application is to e g normalize a specific item and then use the options to calculate percentage difference against the normalized results It should be noted that the evaluation field has to define items for the dimension s mapped into the rows to avoid arbitrary results The selected statistic will appear as the first rows of the table Wolfgang Britz Version January 2015 43 GGIG Graphical Interface Generator User Guide Supply details mapping view 0 Production activity Item Cereals v Income Euro ha or head Ea 01GWPBUR oo 7 301 00 i 573 32 Median 550 26 StdDev 625 66 410 20 q3 687 49 min 533 03 max 1667 07 minOutlier 678 00 maxOutlier 1824 64 European Union 27 646 43 European Union 25 672 55 European Union 15 732 82 European Union 10 534 48 824 52 Perhaps the most interesting option is to show only the outlier rows besides the statistics in the table as illustr
123. ies For Selected Symbolist Properties For All Symbols Reverse Sorting Remove Classies ombine Glasses Advanced Format Labels Edit Description ced _ Symbol Selector aj xj 7 x Category All Preview x Options Fill Color l al E Se eee OB BOCOCOODOEEE vote SS POOROSEe opene Oe eee More Smt E M N A E E a E a a a EEEN NEENEEEENE Save E p Semen E i gO ES AT g mo cere NE TTI IT More Colors Afterwards if everything went well you should see your map S Wolfgang Britz Version January 2015 98 GGIG Graphical Interface Generator User Guide 210 File Edit Yiew Insert Selection Tools Window Help Deusi rex oo 4 lim ESON Q Quxu Se 85h F er gt A HE me Bapao H E ao y E x ArcToolbox E S 3D Analyst Tools Analysis Tools Cartography Tools amp Conversion Tools amp S Coverage Tools Data Interoperability Tools c Data Management Tools an E S Geocoding Tools f a alee c Geostatistical Analyst Tools f k d Apen Pee ee Linear Referencing Tools Pe La rL fol S Network Analyst Tools LT tic PRs ae Oe 2 aay Ta ee nr Samples ee Se A a ee Cai Me Se Spatial Analyst Tools A e ee Ls fe el ue T Spatial Statistics Tools Layers E A E caprit GIs AU_EU27 test RUMI E 0 000000 0 873586
124. ies ean anata A a N ee uke 139 Comparing two data sets in GGIG example from CAPRI ie ececcccccccesseseeeeeeeeeenaes 139 GGA ion C1 BD 4 Bil 5 akemnmmmen a ne E a reer ener a eee Te 140 Sine the table CIS TMG ONS asa cater ratte arettrasd testis E 143 Companions two GDX fles wth GGIG cerise aaa a aE 143 EAOa E E E A E E T E T 143 Wolfgang Britz Version January 2015 7 GGIG Graphical Interface Generator User Guide Wolfgang Britz Version January 2015 GGIG Graphical Interface Generator User Guide Overview The GAMS Graphical Interface Generator GGIG is a tool to generate a basic Graphical User Interface GUI for a GAMS or R project with five main functionalities 1 Generation of user operable graphical controls from XML based definitions The XML file defines the project specific layout of the GUI The user can then interact with the GUI to change the state of the controls The state of each control component such as a checkbox can then be mapped to GAMS code SSETGLOBALS Set definitions settings for parameters It combines hence the basic functionality of a GUI generator and a rudimentary GAMS code generator 2 Generation of GAMS compatible meta data from the state of the control which can be stored in GAMS GDX format and later accessed so that scenario definitions are automatically stored along with results 3 Execution of a GAMS or R project while passing the state of the control to GAMS respectively
125. ifferent GAMS applications or for exploitation purposes as the GAMS IDE comprises a view for GDX files Further tools for GDX files are available from GAMS company and are described in different documents In opposite to listings generated by GAMS programs the GDX files store the data in full numerical precision in an internal format The new CAPRI version passes information from one task to the next with the help of GDX files so generates CoCo a gdx files with the time series at national level which is read by CAPREG And the regional time series generated by CAPREG are inputted by the trend projection tool CAPTRD These gdx files are accessed when the different tasks of Data base exploitation are chosen The user has on top the possibility to load one or several tables from one or several freely chosen gdx files The GDX exploitation utility can be reached via the menu bar GUI Help s GDX Viewer Start equation and variable viewer Build HTML documentation i SVN update Use t britz capri gams util cleanU pGamsDir bat to clean up source directory Wolfgang Britz Version January 2015 134 GGIG Graphical Interface Generator User Guide Graph Panel to GDX file exploitation Load gdx file Load selected tables s Set XML table definition file C Use table definitions from tables xml List of tables loaded from GDX file s T britz CAPRI results Capreg fert_out gdx user input po fert_out parameter
126. iieanttal sce 99 Mony IOn enh seats cutanal eatin tatatncneentataoes cata aa iat aasaasamncnreneataben casual aatuabanaeutmen tent aneety 99 Implementation Im G Gd UG aen a a a re nen Are I ner mn are 101 Interaction between the GGIG GUI and WEKA ssoeesssssssssssssssssseeeeerersessssssssssssssseeeeeeeeeeeee 103 LOEW EEA C1 Ul Merton E army et aurea eet ann ae ment errant aan oe meer een eee 105 Class ieaoo a a a a eouans aut temnasoeer ante weed soun Bese 105 EN iter cers casi E E ears Sas iat ai cocoon eats dieu dates cen tose eeeee 106 ADUE View ine and SCICC MOM ecet E NA 107 SAEN cess E A E A O ET E E E aire 108 FRU INC 5 EE E A A E A O E geo EE A E NE EEE A E 108 Scena o edito uresni a a a a a asdaisGesaceaattaxets 109 Mehi CA aA GI ates e a A 110 Wiy meti dald tesina A A ea toe nations seiuan 110 TechmcalConce Pinar a e Na S E 111 BUS AC E E E E N A E E A ETE AA T E E ER 113 Senes MENU ppr E E ea eatieeain 114 tlie sain GUV MEN erisir e a E A 114 GU bila Cece tel Fe alk ep exe FN 6 oeaan a a i eerewen Serene ary tneer eee ene ree ee rare ger 114 Format of the batch execution steering file isecsssa haevetetcccebilnce cans dees holeesintasesabolneeceeets 115 is Corel 0 lo ater rene renee ee ter er ere NT erene ne a eet ere ee ee 115 NC MUEII OS VOL TAS E E EE E E E E E A tavapacuiens 116 Using the bDatchexec tion Tac lity sisicaceceacteds cordeisnces taxes n EE 118 Wolfgang Britz Version January 2015 6 GGIG Graphical
127. ink GDX dimensions to sets T britz capri gams convert_market_model_2 gdx records long text 10001 SimulationYear Countries intslvl step SCEN afea o o ia ple el ele veanc T britz capri gams convert_market_model_1 gdx lines user input name set dims records long text 10001 dummyTrd META_STEP countriesMeta intslvl step SCEN ate Lol ra oa ee ee VEAnc 4 Equations amp l Variables ArmBall AFR_LDC APPL Adding up of human consumption feed and processing 0 0114645139135529 v_consQuant AFR_LDC APPL 0 0114645139135529 v_armlQuant AFR_LDC APPL E 0 v_consQuant AFR_LDC APPL Human cons umption 1000 tons 1 87 126 lo 0 upp 87 125 678 The viewer comprises a number of windows Selection A window where variables and equations can be selected and filters for variables and equations defined e Options A window with options for the GDX Viewer e Gams includes A tree view of the GAMS includes e GAMS A window showing the GAMS code e Symbol from GDX A view on a current selected GAMS symbol e Equations A view on the current selected equation s in linearized form e Variables A view on the currently selected variables The windows can be dragged resized and minized
128. ion errors Classification 4 Weka Explorer GUI Supply details mapping view 1 all Cereals Income 2020 MTR_RDQuantile 12 01 58 Classify Cluster Filter view and Select Classifier Choose LinearRegression S0 R 1 0E 8 Test options Classifier output Use training set D073 Fodder shania Revenues 0 0085 Fodder activities Income Supplied test set et 0 164 Set aside and fallow land Revenues 0 0042 Set aside and fallow land Income 0 1035 Set aside and fallow land Crop share Animal density Percentage split fo 66 0 0048 All cattle activities Income 0 0268 All cattle activities Yield Cross validation Folds 10 More options 0 005 Beef meat activities Revenues gt 0 0026 Beef meat activities Income E Class numeri 0 0207 Beef meat activities Yield 0 0019 Other animals Revenues start 0 0031 Other animals Income Result list right click for options 9 7609 12 02 01 rules ZeroR 12 02 28 functions LinearReagression Time taken to build model 0 04seconds Evaluation on training set Summary Correlation coefficient 0 807 Mean absolute error 2 4774 Root mean squared error 3 369 Relative absolute error 61 4055 Root relative squared error 59 051 Total Number of Instances 269 Ignored Class Unknown Instances 31 e The choose button will give access to a wide range of different classifiers many
129. ional database 0 OX Cummulative distribution graph Y Frequency groups EA nt Median plus 1 5 IQR 0 00 9838 51 271 Mean plus one std dev 11677 03 272 Arithmetic mean 0 00 1891 01 Median 3139 70 Mean 3493 46 Q3 4437 06 Max 11677 03 IQR 2546 05 Std Dev 2069 33 The colours are typically used to visualize the distribution in maps but as a second option they can also be applied to the numerical values in tables Alternatively histograms and box and whisker diagrams can be drawn via the graphics Working with tables Toolbar Controls for column and row selection E9 CAPRI t britz capri gams Handling Windows ns X funnlw dataile A SP ee Region 01GWPBUR Production per VAAR kg ha Crop share Animal density or 0 01 animalsha Yield kg or 1 1000 headha or head Supply 1000 t Hectares or herd size 1000 ha or hds Income Euro ha or head Cereals 394 15 6205 83 7487 76 46467 77 38 54 2885 66 Oilseeds 261 27 691 33 3676 42 2541 64 4 29 157 84 831 38 826 74 39804 98 32908 47 5 13 2043 62 Other arable crops The toolbar Region Years Scenarios a JEC hamai Germany Z020 01GWP Fes View bype Wolfgang Britz Version January 2015 gt GGIG Graphical Interface Generator User Guide Tooltips for column and row headers For predefined tables tooltips may be stored whi
130. ird parties or storing them on a SVN automatically also passes the meta data along A specific format for META data handling is available for CAPRI It is shown in the following screen shot which also reports how the checkbox Report SVN URLs and local modifications to include file can be used in conjunction in META to make even more information available with regard to the run available User Settings CAPRI System Settings GAMS and R SVN SVN user id oonneene SVN password TILLI SVN URL for Gams https svn1 agp uni bonn de svn capri trunk gams SVM URL for results https svn Lagp uni bonn de svn capri trunk results regcge SVN URL for restart SVN URL for data Report SVN URLs and local modifications to include file As seen below the include file will store the SVN URL for the different directories the related revision number and will also report which files had local modifications poe mutes sete eee eee set countriesMeta Run scenario with market model Run scenario with market model sunRev modelDir 3571 set countriesMeta Run scenario with market model Run scenario with market model sunURL modelDir syun capri trunk gams set countriesMeta Run scenario with market model Run scenario with market model synLocalMod1 T britz capri_liaise gams supply pmp_elas gms set countriesMeta Run scenario with market model Run scenario with market model synLo
131. ives its own axis whereas the column groups are the alternatives to compare The axis are not ticked with numerical values instead they are always scaled to cover the minimum and maximum found in any alternative F Scenario exploitation Data View 1 Table Region Years 5 E Multi Functionality overview European Union 27 vi 2013 vi BIOF_D2E2 292 75 2 78 Scenario exploitation Data View 1 s ox al Spider chart filled s ei La el Product Total Wolfgang Britz Version January 2015 57 GGIG Graphical Interface Generator User Guide Options For spidercharts Maximal number mo Maximal number of series Foreground transparency in Filled shapes The options for spider charts which are found under the button in the toolbar are rather limited The user can determine how many axes taken from the columns are included in the diagram and the maximum number of series which typically consist of scenarios Box and Whisker charts In descriptive statistics a box plot or boxplot also known as a box and whisker diagram or plot is a convenient way of graphically depicting groups of numerical data through their five number summaries the smallest observation sample minimum lower quartile Q1 median Q2 upper quartile Q3 and largest observation Sample maximum A boxplot may also indicate which observations if any might be considered outliers s
132. jects parameters sets variables equations models acronyms functions files and source files 2 Summary pages for classes of objects per project in alphabetical order An additional page lists all set elements Wolfgang Britz Version January 2015 121 iw GGIG Graphical Interface Generator User Guide The pages for the individual objects carry the following information e Name of the object e g DATA and type parameter set variable etc e Long text description as given in GAMS declaration e Domain information as hyperlinks to the domain sets e In which files and for which projects as capmod capreg the object is declared defined assigned and referenced e In the case of sets derived subsets and objects where the set is used as a domain Elements of the sets and the subsets e In the case of source files which symbols are declared defined assigned and references 1n the files Information from SVN version local modification s out of date with server Included files and files which include the file For GDX files where included and included by which file e Tagged in line comments taken from the source code files what is called doclet see e g Sun document about how to write Doc comment for JavaDoc in JAV ADOC see e g wikipedia article Tagged in line comments Similar to the element comments underlying JAVADOC see e g tagged in line comments are proposed for th
133. les showing distribution of regions n My Computer 32 78 90 76 1653 EOE Min IV Show rectangle representating distribution of classes Mean i Open x o efault leg Legend Separate rectangles v Median My Network Max Places Cancel braw outline in same color v Std Dey Etanderd map title v Dimension shown in columns of result window For current region Scenario v Dimension shown in rows of result window For current region hide ok apply store settings load settings Copying the map to the clipboard or to a file on disk In order to export the map to other applications the easiest way is to use the clipboard in order to do so press the copy to clipboard I button Afterwards the current map can be imported into other applications as e g MS Word Another possibility is to store the current map in different format on disk to do so use the button which will open a file dialog to choose the name of the file and select between different graphic formats The Options button opens an additional dialogue Wolfgang Britz Version January 2015 90 GGIG Graphical Interface Generator User Guide which is export type dependent for PDF to give an example the paper size orientation etc can be changed Generally high quality are achieved if vector formats are used PDF SVG EPS EMF These formats are however not supported by all applications in opposite to e g bitmaps BMP wh
134. lgebraic expression freeEval The above listed statistic options can be either found by pressing the define statistics statistics button in the customize dialogue box which opens by clicking the button on the toolbar using the define statistics button or by right clicking on any cell inside the table to open the popup menu and choosing Statistics Wolfgang Britz Version January 2015 42 GGIG Graphical Interface Generator User Guide Customize view ba oo MERIDA N Fraction digits and decimal separator 2 v Y Separator between merged data dimensions Y Column width 306 Row width 306 gt Hide empty rows Hide empty columns Cut off limit to determine empty cells of Reload 2400 79 Copy to Clipboard Use default pivoting For tables Export Data Pivoting 794 17 Show only selected items v Long texts only v Customize Table 3450 79 Comparison output Only values i i l View Vs 2618 16 Data dimension used for comparisons Region a Table view gt Element used for comparisons European Union 15 6088 17 define statistics store settings load settings 6049 71 The dialog allows to select the different statistics as shown above and allows to select a outlier detection method as described in low The setting related to the outlier detection method are dynamically changing depending on the chosen detection algorithm A Set maximum percentage of outl
135. lly a GDX viewer linked to the GAMS code The GDX files can be produced in GAMS with execute_unload someName gdx which will dump all GAMS symbols into a GDX file Wolfgang Britz Version January 2015 129 GGIG Graphical Interface Generator User Guide fo SB l Options Options Set XML table definition file Use indents in equation output Variable selection j Use table definitions from null Sort code lists Show dialog to link GDX dimensions to sets Use small font for non selected var terms 4 Gams includes fo eS l Gams JE T britz capri gams capmod gms T britz capri gams capmod gms t britz caprijgams util acronyms gms include capmod define regional_sets gms x 2 gdx set debugRegions Rall option kill debugRegions N CAL Nutrient content calories N_FAT Nutrient content fat load sets used by market model x x k N_PRO Nutrient content protein Sinclude arm arm sets gms policy set definitions and regional small producer Sinclude policy policy sets gms Siftheni tregcget on declaration part of regional CGEs Sinclude regcge regcge_decl gms p_firstCallcGE 1 declaration of links to CAPRI Sinclude regcge regcge_capri gms egeMSIncl cgeMSWork ms_Incl cgeMsWork YES Sendif set definitions for different type of reports SET RSS RAL
136. ly visible selection will be exported but as a default all tables which can be generated by choosing any combination of elements shown in the drop down boxes That can lead to large numbers of tables being exported If only the content of the current table is to be exported a clipboard export is generally recommended Alternatively the user can use selections see below but these only affect the export of the current table and no table should be selected as discussed below In order to export the data in a map or a graphic e g to GIS system the view must first be changed to tables Afterwards the button will open a file dialog as shown below For GIS export e g to ArcGIS DBF is the recommended format Wolfgang Britz Version January 2015 36 GGIG Graphical Interface Generator User Guide 3 Please choose a file format for export Export Data Select the format of the file to export HTML basic table format for internet browser DBASE data base file e g for ArcGIS or EXCEL comma separated text file for e g EXCEL as GAMS table C TABF text format tabulator separated TXT text format fixed field width Bin binary format for exploitation with exploit applet MSAccess MS Access Database F XLS MS Excel workbook 2003 and before XLSX MS Excel workbook 2010 Once next is pressed the next pane will open a file dialog to choose a file In the case of export t
137. m Use classification colors for tables Show only selected items Long texts only Comparison output Values and percentage difference w Hide lt 1 0 Percentage diff to RES_TIME_SERTESI61111 195 LS ES000000 2038 83 1817 29 1898 56 2012 36 1686 57 1526 07 1338 84 1297 10 1415 56 24 149 14856 14r La 356 24 LB TAGS FROOVODO 5025 58 4695 08 4600 89 4611 01 4500 03 4820 48 4868 61 4770 03 4769 83 4440 35 4467 07 4627 47 1 51 LN ins 4am SRi 105 146 2 53 242 3 00 imm 1 5 TTO00000 1375 60 1213 49 1190 63 819 87 13 1 21 2 i UKO00000 1889 67 1792 29 1923 56 1808 79 1794 32 1998 56 2070 91 2080 67 2071 56 1877 34 1994 24 2076 12 650 5 20 sns a 40 22 2 2 25 20 36 22 ns 14 08 1 nuoo0000 1081 65 889 00 1029 34 287 139 169 PL000000 2169 20 2289 32 1 1 0 BGODO000 1106 14 1027 75 1117 48 2 25 371 2 539 RO000000 2239 11 2333 25 212215 1446 26 2236 42 239237 243168 152 45 253 222 240 2 034 22 TUR 7529 32 2 70 E5400000 129209 1151 59 1199 15 127241 1371 26 1329 38 1095 53 1065 48 953 89 835 38 795 28 876 17 6 59 4 06 62 6 20 563 555 SN 659 7 7 aaa 677 6 939 FR200000 2527 83 2357 62 2323 67 2329 36 2269 87 2427 36 2407 82 2368 95 2333 69 2244 84 227075 2329 32 Ius 1 2 Eog sa ns am 3 79 4a ah 4m 47 ssim FR500000 830 44 832 52 821 23 89441 898 32 900 88 918 14 869 51 896 80 891 38 sss 78 7 93 14 243 3 23 244 341 MTh 4
138. m to default Choose colors see Setting colors manually Customize graphs see General handling of graphs Customize general options to customize views see Changing view options fonts number formatting and rounding hiding empty cells comparisons Bar charts Bar charts assume that the columns typically the table items have different definitions and units and consequently assign an own plot with a value axis to each column The observations are taken from the table rows and define the domain the horizontal axis Each groups of bar columns present typically the scenarios receives its own colour An example is given below FB Scenario exploitation Data View 1 OX Tabie Ragion years R R BEd Table Supply detalis European union 27 2013 7 mor metre mor mot income Hectares or herd Supply Crop shureAninal Procection Hectares or he Sepply Crop share Arena Production per VAAR Euroa of bead size ta 10001 Ikgta fur oma or head oe ha 10901 koha E B gt 1000 ha or hda 1 or 0 01 animais 11000 ha or bas ot head 0S or 6 01 animate i hal a sman E an nR m sana TI n 15341 Su 7308 65 ET ss 127 55 s 10095 96 237885 24015 so 138 78 Otherarablecreps Tas mwy 261606 73 azs wman n THES 3001 8 26075853 samo Veo and 31355619 In fase s57813 176 ARTO 3160 28 707 43 TRAINER orops activities 2120 09 1663592 12 2 6 0
139. mbols Normalization ici E27 GRIDCODE Classes z _Clessiy _ i Proportional symbols HSMU_EU2T n Dot density Color Ramp dol mall est Charts test GRAS Multiple Attributes Symbol Ran test LU test PLAP test ELEC tes EGAS test EFUL test N MIM test SAAB test PERM test PP test WAT SURF ae test NMIN_SWHE ed eee ee F Est _ Advanced coed too _ Afterwards under classification choose your preferred one As there are many small polygons the outline of the polygons should not be drawn Therefore click on one of the colors choose Properties for all symbols and under Outline color chose No Color Wolfgang Britz Version January 2015 97 GGIG Graphical Interface Generator User Guide Layer Properties axl General Source Selection Display symbology Fields Definition Query Labels Joins amp Relates Show Draw quantities using color to show values Import Features Categories Fields Classification Quantities Value test AL Kal ing Graduated colors R a Graduated symbols Normalization none 2 Proportional symbols Quantile Classes 5 Classify Dot density Color Ramp TAPE Bane tae O O U UOO Hultiple Attributes akite Ee m F ar le see OOOO 0 6 3586 ery eee BG 1 471440 Ramp Colors 4H 2 065693 3 354081 1476745461 76 000000 Propert
140. model agoregated Norway imported quantities 1000 t 2013 Sr m ie gt Product Cereals European Union European Urson ar 27 The user has the following options to modify the presentation of pie charts Options For pie charts Maximal number of plots Maximal number of observations Minimum percentage to draw label Foreground transparency in o 3D effect Circular pie F ma y Pas r BJ o i Labels inside of pies The maximum number of plots refers to the number of elements in the dimensions of the column group The example above shows two plots The number of observations defines the Wolfgang Britz Version January 2015 56 GGIG Graphical Interface Generator User Guide numbers of pies if more columns are available the cake will eventually give a wrong impression if not all values are used to define the sum and the shares The minimum percentage to draw label defines a lower cut off limit if a cake s size is below the threshold no label will be drawn As shown in the example above setting the threshold to 100 will erase the labels see Pie chart maps for an example It is also possible to place the labels in the pies and not outside of the cake as shown in the example above Spider plots Spider charts are useful to compare several dimensions simultaneously across a range of alternatives It is assumed that the columns show the items of which each rece
141. n not shown Both the GDX container and the interface work in sparse mode i e only non zero values require disk or memory space Introducing additional dimension has therefore limited impact on space requirements The viewer has proven to work with several 10 Million non zeros Wolfgang Britz Version January 2015 24 GGIG Graphical Interface Generator User Guide in the view port columns and rows Several data dimensions may be merged into one view port dimension The user can use column and rows groups and may apply selection to columns and rows as well as to columns and column groups Rows and columns which carry only zero values may be hidden Rows may be sorted by size of the numerical values in one or several columns The content of the current table may be copied to clipboard Alternatively all or a selection of tables may be exported to an external file in different formats HTML CSV tab separated GAMS fixed width tables There are further possibilities available such as changing fonts or the number of decimals The following chapters give details on the different functionalities available with the exploitation tools Pre defined views An XML file can define pre defined views for the result content of the tasks defined in GGIG Each view defines selections in the different data dimensions the view type table graph or map and the pivot plus some other information Pre defined views thus can provide a guided app
142. n secured parts of their file system The local directory for the GUI is simply taken from the start directory of the GUI whereas the SVN address for the GUI is stored in the default in1 file sild database Base year Simulation year 2020 EUO2 in scenario FuO25 anerate baseline tploit gdx Option qT User Settings CAPRI System Settings SYN Other options SVN user id selection SVN password wnscale g SVN URL for results https fisyn1 agp uni bonn de syn old trunk results tploit sce Scenario 5 Wolfgang Britz Version January 2015 15 GGIG Graphical Interface Generator User Guide The runner can enter the additional SVN urls relating to the different sub directories of a CAPRI installation That should give some flexibility when working with branches on the Server Option User Settings CAPRI System Settings GAMS SVN Other options SYN user id eeecceeee SVN password TTET SVN URL for Gams https svn1 agp uni bonn de synjold trunk gams SVN URL For results https svn agp uni bonn de svnjold trunk results SVN URL For restart https svn1 agp uni bonn de svnjold trunkfrestart SVN URL for data https f svni agp uni bonn de synjold trunk dat Save in T britz CAPRIVGUI capri ini Performing an update The second functionality for an exploiter and runner is to update all directories with the File Settings GUI H
143. ne acan naora can a gt acan an AD TA aano tH ADC IE DAITE AN acta 4 4 m r CAPRI GUI ersion 4 0 September 2011 Ini file capri ini User name Wolfgang Britz User type administrator DEW Bz qm Cb 18 09 2011 i We clicking one of the option if we can then decide to e use numerical classification methods such as different regression methods The observations in the map define the dependent variable e Use the class assigned by the maps input into nominal classification e To switch classification off A new window will be opened which shows the WEKA GUI see below Wolfgang Britz Version January 2015 104 GGIG Graphical Interface Generator User Guide The WEKA GUI The classification is based on the complete functionality of the WEKA GUI regarding attribute selection visualization filtering and classification see http www cs waikato ac nz ml index html There are very good manuals available from the site the latest user manual is also available from http www capri model org docs WekaManual 3 6 5 pdf so that only a few major tips are given below for fast start The tabs Classify Cluster Filter and View and select allow the user to access specific part of the WEKA functionality The result set from the current classification run can be shown in the lower left panel result list For each result set a popup menu opens options e g to show a graph with the predict
144. nition Machine learning a branch of artificial intelligence is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data such as from sensor data or databases Machine Learning is concerned with the development of algorithms allowing the machine to learn via inductive inference based on observation data that represent incomplete information about statistical phenomenon Classification which is also referred to as pattern recognition is a important task in Machine Learning by which machines learn to automatically recognize complex pattern to distinguish between exemplars based on their different patterns and to make intelligent decisions That is naturally a very general description Machine learning has been widely in a wide range of application fields A typical example is the analysis of which clients of a bank has been given credits We have many observations with credit granted or credit refused and probably a longer list of attributes of the clients age sex income amount of the credit asked for time since being a customer with the bank past bookings Machine learning could be applied to define a set of rules which based on past decisions predict if a credit would be granted for a new application or not Machine learning will in many cases also be able to tell something about the possible error range linked with the decisi
145. o a Microsoft Access Data Base the file must exist 2 CAPRI e capril gams i 10 x view Handling Windows Exploitation of spatial results Data iew 1 Table Indicator Agri Env indicators driving Forces cras x Bais E gt BASE frase ww BL21H2865 Sere oo x z Export Data BL21H2866 Set file name BL21H2867 Type of file to export BL21H2868 DBASE data base file e g For ArcGIS or EXCEL BL21H2869 Select the File to which you want to export BL21H2870 BL21H2871 Select a DBFfile x BL etieete Look in lo HSMU gdb v tote REEM Fe _odb 01R10601420 2764 sr lock 3 200000005 gdbindexes p E _odb D01R10601420 3112 sr lock E 200000005 adbtable My Recent E 200000001 Freelist E 200000005 adbtablx BL21H2875 Beshohe E a00000001 gdbindexes E a00000006 freelist E 200000001 adbtable E 200000006 adbindexes BL21H2876 200000001 gdbtablx E 200000006 gdbtable Desktop E 200000002 gdbtable E 200000006 adbtablx a E 200000002 adbtablx E 200000007 adbtable BL21H2878 lt a E a00000003 gdbindexes E a00000007 gdbtablx M e E a00000003 gdbtable E a00000008 gdbtable BL21H2879 E a00000003 gdbtablx E a00000008 gdbtablx E lt r E 200000004 gdbtable E 20000001 freelist am E 200000004 adbtablx E a0000001c gdbindexes BL21H2881 MBSE th a im BL21H2882 Filename BL_HSMU DBF Open My Network BL21H2883 Places Files of type
146. on That could e g allow the banks to make fast decisions in many cases and spend more time on the tricky ones The book by Witten et al 2011 gives many such real world examples It might be interesting to note that one of the often cited applications of the WEKA package used in CAPRI refers to agriculture Queen et al 2005 as the WEKA authors write New Zealand has several Wolfgang Britz Version January 2015 100 GGIG Graphical Interface Generator User Guide research centres dedicated to agriculture and horticulture which provided the original impetus for our work and many of our early applications The applications deal mostly with micro level data A recent application to price agricultural forecasting is found in Ticlavilca et al 2010 With the approach used by machine learning we can e g interpret the income changes in each farm type in a simulation compared to the baseline as an outcome we want to predict and the production program of each farm type and changes in prices and premiums as the attributes used to explain that outcome Some farm types might exhibit very large income changes other little ones What are Possible structural Drivers one and the other group common characteristics of the Simulation results e g crop shares in baseline Machine learning might then come up with a pattern e g based on a regression model Machine which determines the most learning important att
147. onics in Agriculture Volume 12 Issue 4 June 1995 Pages 275 293 ISSN 0168 1699 http www sciencedirect com science article p11 0168 169995986019 Ticlavilca A M Dillon M Feuz and Mac McKee 2010 Forecasting Agricultural Commodity Prices Using Multivariate Bayesian Machine Learning Regression Proceedings of the NCCC 134 Conference on Applied Commodity Price Analysis Forecasting and Market Risk Management St Louis MO http www farmdoc illinois edu nccc 134 Wolfgang Britz Version January 2015 108 GGIG Graphical Interface Generator User Guide Scenario editor The scenario editor is an optional tool to be embedded in a GGIG user interface which supports the user in setting up run specific include files where the content is not stemming from GUI controls That parallel way to define run specific input is typically necessary for more complex tools where e g policy scenarios are defined in GAMS code The scenario editor is a predefined task which must be named Define scenario e g 9 lt task gt lt name gt Define scenario lt name gt lt userLeuls gt runner Administrator developper debugger lt userLevls gt lt task gt A related setting stores the directory where the input files are found lt scenarioDdir gt lt attr gt scend attr gt lt scenariodir gt The screen shot below shows an example from CAPRI r S CAPRI t britz capri gams Sa Ee m a
148. ore execute load myFile someSymbols An IF EXIST myFile LOG myFile will be overwritten statement should be in the line before execute_unload myFile someSymbols All symbols should be declared with a clear long text description i e statement in the style SET A are discouraged Code in lengthy files should be moved into new files which are included so that a more modular structure is evolving The new file should have a clearly defined and encapsulated task which is described in the file header Symbol declaration should where necessary be preceded by a doclet of the form start or alternative a blank line DockRef reference to the methodological documentation optional seeAlso reference to other file or symbol optional Any comments Declaration as SET A The alternative technologies per production activty T1 T2 Symbols especially when they are not widely used across programs should carry meaningful names Other recommendations arising from analysing the files are 1 Single lines in the code should not exceed the size of a normal screen width when using medium sized fonts Wolfgang Britz Version January 2015 123 GGIG Graphical Interface Generator User Guide 2 Indentation should be used to render the program structure defined by loops if statements and the like more visible 3 Especially tricky statements which use complex operators several
149. ormalization by clicking on the customize button Frecton digts and deca separator 2 Seperstor between merged dats dmengons Coun width 7504 Rowen 750 Hide empty rows Hide empty columns Gat off iest to drtermne errpty cobs J Use defatt orroteg for tables Show Pesto are Use daseficaton cokes for tables Show orty selected iteme Long texts only Compansen ovpu Data dmension used for comparisons an additional column is automatically added to the info window showing the comparison value used That is especially helpful when the map shows only differences Wolfgang Britz Version January 2015 83 GGIG Graphical Interface Generator User Guide The content shown in the info window is not fixed rather the user can decide which data dimensions to use for the columns and rows by using the map option dialogue by clicking on the legend of the map If the user e g switches to items instead of activity the info window will look like shown below An alternative 1s to use a second tabular view in addition to the map Map option dialogue x I Color table Green yellow rec Classification method Quantile bd Number of classes 4 S Number of regions with small values to remove From class definition 4 0 Number of regions with large values to remove From class definition Legend 1 0 00 lt 0 00 2 10 00 lt 49 28 4
150. ow in the ids of the coordinate set Regions for which no matching id is found cannot be drawn If to give an example a coordinate set of EU Member States is used and the table comprises data at NUTS2 level only those NUTS2 regions will be drawn which are identical to an EU Member state In that case one needs to switch to the NUTSII zip coordinate In most cases the XML file which defines the view will already comprise the information about the appropriate coordinates to use The following message will appear if for none of the items in the rows a matching id is found That is most often the case if the regions are not shown in the rows L Supply details mapping view 0 nae nC ks Activity Region Year ec View type 4 gt Utilized agricultural area X European Union X 2020 X x kd d Q Q ll Map her the regions are not in the rows of the tables for these regions available in currently used COO file T britz capri GUNNUTSII zip The coordinate sets are typically stored in the GUI directory The map viewer uses a proprietary format which aims at minimizing disk space A utility see section on utilities allows generating the proprietary format based on a so called shapefile a format widely used in GIS work Adding a histogram window to a map In the map option dialogue tick Show histogram and a separate window with a Histogram will be shown It will use the current cl
151. phical Interface Generator User Guide Case one Exploiter and runner Entering the necessary information to link to the SVN server An exploiter by definition only accesses GDX files from the result directory He is not allowed to run GAMS programs and thus does not need access to the GAMS source code data and restart files read in by the different GAMS based working steps of CAPRI Accordingly in order to work with SVN only three pieces of information have to be entered CAPRI t britz capri gams File EA Utilities Help Wola aes LoauSsettings from ini file Ol Save current settings to ini file under Settings Edit Settings Remove task specificsettinas in the SVN tab e The SVN user id e The SVN password e The url of the result directory The first two fields are not visible and the related entries in the ini file are encrypted The last entry can be set to a specific branch relating e g to a training session That allows for CAPRI mini installations These mini installations do not need to be distributed as SVN installations as the SVN interface in the GUI will also allow to checkout over existing sub directories and files That ensures some additional safety regarding access information to sensible branches of the server a bystander cannot read the user id and password But users should always place local copies of such branches including the directory from which the GUI is started o
152. pping view use the option dialogue to show percentage changes against the baseline NEeNwHAQap gue The regions shown are our instances and the value plotted for a region defines the class attribute we want to analyze Any one instance consists of a vector of attributes of which one is the class value 1 e the value to classify which can be numeric or nominal The other attributes are used for classification or clustering and stem from a second table see below Classification methods which use nominal values can also be used In that case the class chosen for the region as seen from the color in which is drawn defines the class attributes In our example above each region would fall into one of five classes Next we open a second table with the data we want to use as explanatory attributes The latest trunk comprises the table Supply details cluster view which comprises promising attributes which are possible candidates to explain many changes in a simulation for all activity aggregates crop shares stocking densities revenues income yields Wolfgang Britz Version January 2015 103 GGIG Graphical Interface Generator User Guide LJ Supply details cluster view 0 Years Scenarios 2020 MTR_RD Cereals Revenues Cereals Income Cereals Yield Cereals Crop Oilseeds Revenues Oilseeds Income Oilseeds Yield Oilseeds Crop Oth
153. pter Welfare overview 0 Welfare gt CAP gt Markets gt Prices gt Supply details A Supply details mapping view n DNDC Income Indicators gt gt Environment b Labour use per activity Dual analysis gt Decomposition Multi Functionality gt Yield decomposition No table Mio Euro Output crops Mio Euro Output animals Costs Mio Euro EAA Input Mio Euro Crop specific Input ee o P Feed Distribution Income indicators mapping view Income indicators across Member States Land supply and use Revenues Further cost breakdown Energy and maintenance costs Fertilizer input n Animal specific Input Feed requirements Mio Euro Other Input Main crop areas Mio Euro Main crop area pie map Tax payers cost total Min Fiural 4 B C sugarbeet regime Navigating through views dep e The dark triangle to left and right of the view button allow navigating through to the list of available views The outer triangles in grey allow navigating through the previously visited VIEWS Navigating in the outer dimensions of the viewport In many views some data dimensions will not be shown in the columns and rows but as drop down boxes in the toolbar Use the mouse to select within the boxes You can also use the keyboard to search items by typing An example for these controls is shown here Region Years European Union 2 we 2015 Note
154. r and cities The NUTS2 map comprises geometry information about major rivers and cities above around 75 000 inhabitants which can be added to the map Rivers Min width 4 City labels Min city size 1000000 0 a The label size for the rivers can be set as discussed above however city labels are always Shown 1n bold Wolfgang Britz Version January 2015 89 GGIG Graphical Interface Generator User Guide Storing and re loading your settings Open the map option dialogue by pressing the map option button lel Change the settings according to your needs and then press the store settings button in the lower part of the dialogue Choose a file name and a location You may later use load settings to retrieve them again and apply them to another map Map option dialogue x Classification method Quantile X Number of classes 55 Number of regions with small values to remove from class definition 4 Number of regions with large values to remove from class definition 4 Treat zeros as missing values Use area weights for classification Draw in high quality JV Shrink polygons according to share of UAA Set value for middle color 90 76 1 2 ee 3 ee 4 lt 137 44 137 438 19 539 TEN 5 lt 370 97 370 969 20 375 a My Recent Documents Desktop i My Documents 0 00 346 36 o 16 42 86 87 157 31 e P Show small circ
155. ram 33 legend continuous linear scaling 81 continuous logarithmic scaling bar 82 Machine learning 100 Maps Classification Area weighted classification 74 Classification method 74 Color for middle class 80 Color table 77 Equal interval 76 Excluding zeros from classification 74 Manual classification 76 Mean standard dev 76 Natural breaks 75 Wolfgang Britz Version January 2015 Nested mean 76 Quantile 75 Clipboard export 91 Coordinates 71 Drag 83 File export 91 Flow maps 66 Frequency diagram in map 77 Full extent 83 Getting data for specific polygons 84 Highlighting specific regions in the map 85 Histogram window 72 Info pointer 84 Info pointer and window 84 Legend 81 Pie chart maps 68 Pop up menu 92 Regional labels in map 89 Rivers and cities 90 Schemes 92 Shrinking polygons according to UAA share 73 Store settings 91 Title 83 Updating the map 89 Zoom in 83 Zoom out 83 Zooming 83 Menubar 144 GGIG Graphical Interface Generator User Guide File menu 114 Starting GAMS 20 Settings menu 115 Tables Utilities and GUI menu 115 Meta data 111 Concept 111 SET META 112 SVN information 114 Numeric filter 86 Pie chart maps 69 Pivoting 29 Predefined selection groups 28 Scenario editor 110 Select scenarios 22 Set up Exploitation tools 19 GAMS EXE 13 SVN 14 Work directory 12 Setup 12 Result directory 12 Set up Look and feel 12 Wolfgang Britz Version January 2015 Drill down 35 Filtering 4
156. raphical Interface Generator User Guide changing certain properties for the current graph temporarily Additionally the export button can be used to save in different vector and bitmap formats to disk see below Some settings which will pertain can be edited by opening the graphics option dialogue press E Options for bar charts and histograms Maximal number of plots Maximal number of bar blocks Maximal number of bars per blocks AUF AE Ae aye Foreground transparency in 3D effect Plot vertical Draw outline Filled bars C Stacked E Cylinder only for 3D non stacked Draw shadow Show mean median g 1 q3 Options for spider charts Maximal number of axis Maximal number of series Foreground transparency in Options for Heat Map Show last column Options for all charts Font size relative to tables in Use shades of blue Indude zero in value axis range Show domain grid lines Options for line and area charts Maximal number of plots Maximal number of series Maximal number of observations AEA Ag ane Foreground transparency in 3D effect Draw lines Sort values Common range for plots Plot vertical Draw Shapes Draw cummulative Options for pie charts Maximal number of plots Maximal number of observations Minimum percentage to draw label Foreground transparency in 3D effect C Labels inside of pies E Circular pie Options for Statistics Bins zero defaul
157. re holes lake and similar features which are not part of a polygon are drawn by the mapping tool in while Attention that should not be used if regions are island inside other regions e Minimum size of polygons will drop polygons below the specified threshold Try O first to avoid that no output is generated The interface will assume treat line strings as river points as cities and polygons as regions The utility assumes that all shapefiles are in the same coordinate system and will simply store the coordinates one to one applying where set a scaling factor in the internal format used by GGIG It generates in parallel to the coordinates a file called with the same name as the outfile file with the extension zip in the example above that file would be called test gms it comprises the list of regions ids read from the shapefile and a GAMS parameter which Wolfgang Britz Version January 2015 137 GGIG Graphical Interface Generator User Guide reports any numerical fields found in the shapefile If no numerical fields are found the position of the regions are stored in the parameter The file has accordingly the structure shown below SET rr f ATA1 AT11 AT12 AT12 ATIS ATIS AT21 AT21 f PARAMETER TEST 7 ATAI1 area ha 396553 0 ATA Center 48115 06 3783 ATI2 area ha 1919280 0 ATIW2 Center 8747718 753942 fs execute unload test gdx TEST When it is
158. request can also be sent to GAMS stop GAMS Compile GAMS Start GAMS Stop GAMS Once started the GAMS project routes its output instead to the console the DOS prompt to the lower right part of the interface such that the user can follow the progress farm_constructor gms 91 3 Mb exp starter gms 74 3 Mb ini_herds gms 19 3 Mb title gms 30 3 Mb ini_herds gms 86 3 Mb exp starter gms 78 3 Mb decl gms 29 3 Mb exp starter gms 195 3 Mb title gms 30 3 Mb exp starter gms 202 3 Mb title gms 30 3 Mb exp starter gms 240 3 Mb Store_res gms 232 3 Mb exp starter gms 323 3 Mb title gms 30 3 Mb exp starter gms 325 3 Mb Store_res gms 232 3 Mb exp starter gms 344 3 Mb Status Normal completion Job exp starter gms Stop 12 01 10 21 06 06 elapsed 0 00 00 047 GAMS RC OD lt gt 2 v The pane with the content can be scrolled by a right mouse click in the pane to open a popup menu If an editor is added under other options the GAMS and the listing file can be opened as well Open gams file Open gams st file Scroll Lock The pane can hence be frozen so that e g the status of a model solve can be inspected while the project continues to run In order to successfully start a project the ini file for GGIG must Wolfgang Britz Version January 2015 20 GGIG Graphical Interface Generator User Guide compris
159. results directory and stored it to the ini file the user will face a rather clean interface which only allows to exploit existing scenarios and to exploit GDX files also that option could be removed for exploiters Settings linked to the exploitation tools User Settings System Settings GAMS and R svn Pestle ch vaea feels Mie a T britz capri GUI tables xml F Sort code lists in predefined tables agp pub soft kedit KEDITW32 EXE F Sort code lists if showing all el ts Path to Editor Language to load from tables xml English Clean window with GAMS output with each new GAMS compile start V Use task specific settings in interface Debug XML table definition output to OS prompt The Path to the view definition tables xml allows to load a XML which defines views into the results see chapter exploit results If you are using regularly a text editor you can register it under Path to Editor That will allow to open the GAMS listing and generator include files from the GUI Wolfgang Britz Version January 2015 19 GGIG Graphical Interface Generator User Guide Help system Many user operable controls are linked to context sensitive help which can be queried with F1 That will open PDFs files Starting GAMS from GGIG GGIG allows starting the GAMS project directly from the interface either in compile or run mode A break
160. ributes impacting income changes in a given simulation Machine learning Rules has thus a lot of similarities Correlations be feta with statistics indeed many methods can also be found in statistical packages but the focus to decide upon which attributes and relations matters 1s shifted to a certain extent from the human being to the computer And the tool box used in machine learning differs to a certain degree from classical statistics And not of least many of the algorithms had also been developed keeping computing time in mind Implementation in GGIG The implementation in GGIG is based on integrating the WEKA machine learning library Witten et al 2011 into the GGIG exploitations tool which is possible thanks to the GNU license which includes full access to the underlying Java source code WEKA is also integrated into other well known packages such as RapidMiner Relatively few code changes were necessary in the GGIG Java code to pass data from the tables and maps shown in the GUI to the WEKA library see below That is done automatically in the background with the aim to reduce user input in the process Wolfgang Britz Version January 2015 101 GGIG Graphical Interface Generator User Guide As a consequence a very powerful set of filtering and classification as well as related visualization tools from machine learning can be applied to the result sets from CAPRI inside the existing exploitation tools The
161. ribution of regions Min 418 65323 are Mean 358 84164 I Show rectangle representating distribution of classes Median 345 89148 Draw outline of all polygons v Max 1392 846 Std Dev 4468 262 Dimension shown in columns of result window For current region vears ss Dimension shown in rows of result window for current region Activity bd AR rite My eat low high Wolfgang Britz Version January 2015 81 GGIG Graphical Interface Generator User Guide Changing the title of the map When using output to clipboard or disk the user may often prefer to choose his own title or no title at all on top of the map This will be helpful when producing a caption for the map in another application In order to refrain from drawing a title on top of the map click into the legend part of the map and in the dialog at the bottom choose none in the row labeled Title on top of map Alternatively the user can simply write something in the box Standard map title B Standard map title No map title Zooming in and out and navigating in the map In order to zoom in part of the map press the amp button The mouse pointer will change to a magnifying glass with a cross in it You can then mark an area on the map by pressing the mouse button dragging and then releasing the mouse After the mouse is released solely the selected zone of the map will be drawn without changing the class limits or any other setting Clicking
162. ries you had in the original map There is a trap though If you export several tables or results for several scenarios your table will normally have several fields used as a row header e g year scenario activity If that is the case the join will not work properly as several rows for the same regions will be joined to the very same polygon Unfortunately ArcGIS will not warn you about that First you have to execute a definition query in the table while selecting the rows which you are later going to draw a map from In order to draw a thematic map now it may be helpful to add the file with the meta data to the map and to open the meta data table with the help of its context menu It will give us the long description and units belonging to the data fields in the exported data table Wolfgang Britz Version January 2015 96 GGIG Graphical Interface Generator User Guide E Attributes of test_meta LongText i h MIM o 5 a Mineral Fertilizer Consumption Mitragen MIM o 5 b Mineral Fertilizer Consumption Phosphorous MIM_SvVHE Mo 5 0c Mineral Nitrogen Application rate Soft wheat LAP o6 Consumption of Pesticides ofa Irrigation share o f b Irrigation abstraction o8 ay Energy Electricity o8 bi Energy Gas o8 gc Energy Fuels o 10 aj Cropping Livestock pattern livestock density Uhl 010 6 Croppping Livestock pattern ruminants density o 10 Cc Cropping Livestock pattern nan
163. roach to exploit model results such as showing market balances trade matrices crop budgets a welfare analysis or different environmental indicators Graph A pre defined view Lj Welfare overview 0 Region Year dep m a a it European Union X 2020 Eras AA RES 2 O820ANIMWELF Y v Total 20457780 00 Doto aaam Money metric 20435642 00 WL aaam Agricultural income 173051 80 Po tmo O aaam Premiums 51902 55 Pe beo eee EAA Output 495764 22 Moteo al Output crops 229820 02 Mo teo aaam Output animals 265944 19 Moteo aaae EAA Input 375461 16 Mio Euro Crop specific Input 96370 45 Mio Euro Animal specific Input 173872 92 Mio Euro View selection The currently selected view is shown as a description of the window title Welfare overview 0 The number behind the view gives the internal order of the views as several views can be opened in parallel Wolfgang Britz Version January 2015 25 GGIG Graphical Interface Generator User Guide The currently shown view in such as window can be changed by pressing the view S button Pressing the button opens a pop up menu to select another view The available views will depend on the results you have loaded The views are logically grouped under headings and moving the cursor on the heading will show the single views grouped under that heading Some views will be opened as graphics see chapter or maps see cha
164. ruminants density o10 di Cropping Livestock pattern arable land density o 10 Cd Cropping Livestock pattern grass land density o 10 Cd Cropping Livestock pattern permanent craps densityid o 12 a lov medium high input farming L21H2565 L21H2566 L21H2567 kg Mha kg Mha k Euro Ma irrigated fim raha rata raha ivestack units Sha UAA ivestack units ha Fodder area ivestack units fha UAA 1 i WAT _SURP ELE EGAS EFUL L T Cc clm mm 4 zlolols 1G ba gt a CIC ARAB GRAS M H2565 H2566 H2567 2068 L21H2666 20 Haeea _ pL21 Hea L a Haera _ eu2iHara U 27n aen dex O 2 m DE ee TTI il D Oo 7 D on oo Bo a oO me cn ta boa 0 I xi Assuming we want to draw a map now with the ruminant stocking density we find it in row 10 under the key RUMP In order to produce a map now we have to open the context menu of HSMU_EU27 and choose properties symbology and choose Quantities Under values choose RUMP the name before is the name of the DBF file General Source Selection Display Symbology Fields Definition Query Labels Joins amp Relates Show D raw quantities using color to show values Import Features Fields Classification Categories Quantities Value none hd Manual Graduated colors aE E ization Llassityy Graduated sy
165. ry information to the user long texts units e chooses a matching presentation as a table map or graphic e and arranges them in a suitable way on screen The views can be linked to each others allowing a WEB like navigation through the data cube Views can be grouped to themes The user may open several views in parallel and she may change the views interactively according to her needs e g switch from a map to a tabular presentation or change the pivot of the table sort the rows add statistics introduce comparisons etc Internally each view is stored in a XML schema Technically a view can be understood as a combination of a pre defined selection query along with reporting information The XML Wolfgang Britz Version January 2015 21 GGIG Graphical Interface Generator User Guide schema allows to attach long texts units and tooltips to the items of a table and thus to show meta data information to the user The XML schema does hence replace look up tables in a DBMS It may equally store information regarding the pivoting the view type table map different graphic types and for maps classification colour ramp and number of classes The views can be grouped into logical entities and are shown as a popup menu to the user Tabular views may feature column and row groups Empty columns and rows can be hidden tables can be sorted by column with multiple sort columns supported Numerical filter can be applied to
166. s Update for t britz capri restart completed at revision 5310 Update for t britz capri gams completed at revision 5310 If the directory is not yet under version control the GUI will perform a checkout instead 1 e setting up the first installation of the hidden copies from the server Before an update a clean up operation will remove any possible local locks related to earlier unsuccessful SVN operations As long as an internet connection is available that should ensure smooth updates in most cases and avoid some of the more tricky problems TortoiseSVN users might face Case two Administrator An administrator can enter the same SVN directories as a runner but can trigger updates for the different parts separately SYN settings Update G4Ms Update results Update restart Update data Update SUI Usage for installation purposes Since quite a while the CAPRI network discusses how installations specifically for training sessions can be organized more easily The newly embedded SVN functionalities in the GUI Wolfgang Britz Version January 2015 17 GGIG Graphical Interface Generator User Guide should ease that task somewhat specifically in cases where only exploitation functionalities are asked for The installation of CAPRI based on the new functionality is relatively straightforward As before a JAVA run time engine must be installed for the GUI to run For an exploiter only a minimum GU
167. s Wolfgang Britz Version January 2015 26 GGIG Graphical Interface Generator User Guide e fan outer dimension does only comprise one element no drop box list is shown e If the toolbar gets too large e g by having several drop boxes with long item descriptions such that its full content cannot be seen it can be detached from the window by clicking on the line of small point under the icon and handled independently Supply details mapping view 0 L Supply details mapping view 0 Scenario RES 2 0820MTR_RD Item Yi z View t TP A Income Euro ha or head v X 1 heg 2 ma Q Q i tap JY i Toolbar Supply details mapping view 0 ii 4 Activity b Utilized agricultural area Column and row selection The user can selected select specific columns and rows groups to be hidden or included in the current view by using the buttons with the filter symbol shown below Alternatively selection buttons in the option dialogue can be used see Changing view options fonts number formatting and rounding hiding empty cells comparisons below Selection for column gro Selection for columns gt y T for rows Double clicking on one of these buttons will open a selection dialogue for the elements in that view dimension Wolfgang Britz Version January 2015 27 GGIG Graphical Interface Generator User Guide E Selection dialo
168. s 1 Elements cate ofthe current Used by capreg Used by capmod Subsets based on set MAACT open all close all 4 subsets elements ES MACT ES elements QD DCOL DCOH BULL BULH HEIL HEIH CALF 5 CALR MRUMI 0 MNRUMI 3 RUMILK C REQM_TO_MAACT C MAACT_TO_REQM B Dcow HEIF BULF CRURA Files which are not in normal SVN state or where a newer version is available on the server are highlighted Used in project capreg open all close all 4 open aD P DAT ARM WORPRICES GMS DAT BIOFUEL BIO_FUEL_PROD_DATA GMS DAT BIOFUEL COEFF GMS DAT CAPREG UKEXPERT DAT DAT FEED FAT DAT DAT FEED FEDCOF DAT DAT FEED PORKREQ DAT DAT FEED SHEEP_GOAT DAT DAT FERT FAO_FERT GMS DAT FERT IFA_DAT GMS DAT INPUTS BAYER_INPUT GM DAT INPUTS EST_FROM_FAY Ss DAT INPUTS ZSETTY GY BG 0 GAMS BIOFYAL TRIM_EXPOST GMS GAMS CAPREG GMS Modified GAMS CAPREG AGGREG_DATA GAMS CAPREG GCS 7 GAMS CAPREG CONS_INPUT GMS GAMS CAPREG CONS_LEVLS GMS Modified GAMS CAPREG CONS_SETA GMS Modified GAMS CAPREG CONS_YIELDS GMS GAMS CAPREG DEF_CRPR_COR GMS GAMS CAPREG DEF_EAA GMS GAMS CAPREG FSS_SETS GMS GAMS CAPREG HP_FILTER GMS GAMS CAPREG MAP_FROM_REGIO GMS GAMS CAPREG MAP_POL GMS GAMS CAPREG PRICE_YANI GMS GAMS CAPREG REGIO SFTS GMS HTML link to page for file Wolfgang Britz Version January 2015 GGIG Graphical Inter
169. s from the rows into a selection box A double right click generates column groups The row and columns can be switched by a left click on the pivot button Changing view options fonts number formatting and rounding hiding empty cells comparisons a A dialog opens when pressing the button to change various options of the current view Wolfgang Britz Version January 2015 30 GGIG Graphical Interface Generator User Guide C2 i n p Fraction digits and decimal separator 2 iy Y x Separator between merged data dimensions x Selection for Activity Selection for Item Column width 108 Row width 109 34 _ Hide empty rows _ Hide empty columns Cut off limit to determine empty cells 0 ka W Use default pivoting for tables _ Show histogram _ Use classification colors for tables Show only selected items v Long texts only Comparison output Only values Comparison threshold to hide values 0 5 Region Activity Data dimensions used for comparisons Item Year Scenario Element used for comparisons Region Denmark ok define colors define statistics store settings load settings e Fonts set font family size and style affects tabular views but also the different dialogues e Number formatting chose the number of digits and define the decimal separator The tool supports rounding numbers before the decimal point by allowing for negative fraction digits Choosing
170. sorting symbol will show sort direction and its size will show the sorting order 60473 37 9607 46 0 00 0 00 59217 85 8335 37 2 08 13 24 5142 97 2421 03 0 00 0 00 Wolfgang Britz Version January 2015 40 GGIG Graphical Interface Generator User Guide Numerical filtering based on cell content Clicking with the right mouse button on one of the column headers will open the filter dialog which can be used to apply numerical filters to remove rows not matching the filter from the view Filter dialog Define numerical selection Filter he rows Comparison operator By Clear selection and select according to filter Comparison value Add result of filter to existing selection Remove result of filter from existing selection Changing the row height and column width with the mouse While dragging with the mouse the bottom of the first row header the cell height of each row the height of each row is changed at the same time But the column width can be changed selectively per each desired column if you change the width on one column the widths of the other columns do not change The column width can be changed in a similar way by dragging the right border of the column header Alternatively the column and row width can be set in the Changing view options dialogue Build regional database DER Build regional database DER Build regional database DAR Build regional database view Region View
171. ss which shows the lower limit Legend Separate rectangles vw 0 00 49 28 lt 59 92 74 08 80 19 86 45 113 44 450 86 2 A continuous linear scaling bar That gives an optical idea about the distribution of the class limits Overlapping of the number is avoided by skipping class limits close to Wolfgang Britz Version January 2015 80 GGIG Graphical Interface Generator User Guide each other end Continous bar linear scale 0 00 49 28 74 08 113 44 450 86 3 A continuous logarithmic scaling bar Legend Continous bar log scale 0 00 1 57 49 28 74 08 113 44 450 86 In all the cases the tool dialogue can be used to set number of digits shown e g reducing the number of digits to zero leads to a linear bar as shown below 4960 74 86 113 451 O The reader is reminded that the label can be changed manually as shown below f Map option dialogue x pply details mapping view v N Pi ini gt ll i Ei Color table Green yellow red v Set value for color change for Green yellow red 345 89148 Years Classification method Quantile z Y Number of classes Number of regions with small values to remove from class definition OO Number of regions with large values to remove from class definition 4 Legend Separate rectangles z color 345 89 250 i 418 65 487 10 1392 85 Cummulative distribution graph v n 249 0 Show small circles showing dist
172. t from clipboard and place the formatted table or graphic in another one and use references to the raw data copied from the interface If an update of the raw data is then necessary e g after the simulation was repeated the old data might then be simply overwritten with a new paste from the clipboard and the formatting information is not lost Export to file Bon 4m A dialog opens when pressing the button to export the full dataset of the view to a file not only the currently seen part Wolfgang Britz Version January 2015 35 GGIG Graphical Interface Generator User Guide The action provoked by the button depends on the view type In tabular view in opposite to the clipboard export the export file will scroll through the outer dimensions and will copy all stacked tables after each other into a file Take the table below as an example Clipboard export will export the data for Belgium and 1984 File export fill export data for all regions and for all years if the user does not apply filters in the export dialog Prepare national database View Region Years Belgium v 1984 v Unit value EAA Quantity Production value 2515 60 22 00 Premiums Production value Cereals 2515 60 aes 4227 40 Generally the data underlying one or several views can be exported to a wider range of format as shown below However the user should be aware that not only the current
173. t rule Quantile around median Treat zeros as missing values Show axis titles Show range grid lines The chart type s specific settings are discussed in more detail below The general options should be self explanatory it is best to try them out interactively Setting colors manually The Set color button opens up a dialogue Wolfgang Britz Version January 2015 49 GGIG Graphical Interface Generator User Guide Graphics settings a Options for bar charts and histograms Options for line and area charts Maximal number of plots 4 Maximal number of plots Pick a color Maximal number of bar blocks 5 Maximal number of series Maximal number of bars per blocks 10 Maximal number of observq watches Foreground transparency in Chose colors for graphics rete lt i _Colortor series 1 V Plot vertical E Cylinder only fq a a JA E a E a E y e E T F Mmm PEE Eee Draw outline Draw shadow _Color for series 5 Sees J Filled bars Show mean me O_ ees se Color for series 9 B_ _ ISSR icles az eae eae FRERENENTTEENENNE EER ee el _ lel Maximal number of axis Color for series 13 Maximal number of series Color for series 17 Vorschau Foreground transparency in Color for series 21 Oo g J Beispieltext Beispieltext v Filed shapes Color for series 25
174. ta anew from disk useful e g when the files are re written in the background Copy to Clipboard see Clipboard export Export Data see Export to file Pivoting see Manually changing the pivot Customize see Changing view options fonts number formatting and rounding hiding empty cells comparisons Statistics see Adding statistics e Classify see Machine learning e View see Selection of the view type Working with graphics The exploitation tools allow showing the current content of a view as a graphic The underlying data are identical to those which would be found in a tabular view however in some cases size restrictions will prevent to e g show all columns and rows Most of the graphic types are based on the JFreeChart library see http www jfree org jfreechart While certain settings of the graphics can be changed such as fonts to some degree also colors the graphics are not predominantly built in to provide camera ready output for publications Here exporting the data e g via clipboard to a spreadsheet program is often the better option to control layout options General handling of graphs In the system the selection of the view type including the different types of graphs is opened View type Table by pressing the view type bottom in the tool bar which shows the current active view type here Table The following graphic types are currently supported
175. te gamsrun scen name HTR GREEW execute gamsrun scen name HTR COWU execute gamsrun scen name HTR GREEN CONU execute gamsrun Using the batch execution facility The batch execution utility can now be opened from the menu bar under GUI O SS GUI Settings Batch execution 7 Generate GUI geometry from shapefile aa It will open a separate windows as shown below Graph Batch execution panel Batch execution Batch file to execute t britz java trunk de capri task testBatchUni t t Set file Directory for exp ref files t britz capri codeDocinput Set directory Generate EXP and REF files For HTML documentation Start batch execution Pas Wolfgang Britz Version January 2015 End batch execution after next finalised GAMS step C Gnly compile the GAMS programs End batch execution immediately 118 e GGIG Graphical Interface Generator User Guide If the suite of tasks comprises execute statements those can be downgraded to compile with Only compile GAMS programs check box The check box Generate EXP REF files for HTML documentation adds settings to the GAMS calls which generate two specific reference files by the GAMS compiler which comprise information of files and symbols used by GAMS For details on the code documentation facility see the technical document Javadoc like technical documentation for CAPRI to be found on the Capri web page under technic
176. the case of the mean standard deviation approach nor a uni modal distribution as in the case of the IQR method and it is rather easy to compute It may be worth to continue with a literature research in the direction of similar outlier detection methods The factor B describes how distances between succeeding values are assessed Outliers are defined when the maximum of the above and below conformity is above a predefined threshold a max u u gt a Last amp Kandel have tested their algorithm for B 0 001 a 0 05 and m 10 There seems to be a rich literature on that kind of neighbourhood distance where outlier control based with different algorithms is analyzed in detail The different parameter can be set by the user interface Reference Last M amp Kandel M 2001 Automated Detection of Outliers in Real World Data Proc of the Second International Conference on Intelligent Technologies Pop up menu Selected options discussed above can be reached via the a pop up menu which opens after a right mouse click in the table Wolfgang Britz Version January 2015 46 GGIG Graphical Interface Generator User Guide 11079 93 1 26 73542 85 Reload Copy to Clipboard 105015 Export Data 88223 70 Pivoting Customize 17968 00 Statistics 4628 00 Classify aed gt View gt 20180 55 Table View b 32530 40 co T jn The different options had been mostly discussed already above e Reload Loads the da
177. the shapefiles must be analyzed by using the Get field from coofile button Wolfgang Britz Version January 2015 136 GGIG Graphical Interface Generator User Guide ae Coo file generation from shape file T Shapefile input shapefile input Sete shapefile input Sette shapefile nput shapefile nput shapefile put _ Coordinate file output Id string NUTSII y Name string NUTSII Scaling for coordinates 0 001 Fill up mask for ids Id string NAME v Name string Scaling for coordinates 0 001 Fill up mask for ids Id string INT_NAME Name string iy Scaling for coordinates 0 001 Fill up mask for ids Id string Name string Scaling for coordinates 1 Fill up mask for ids Id string Name string Scaling for coordinates 1 Fill up mask for ids Id string Name string Scaling for coordinates 1 Fill up mask for ids Simplify Store holes Minimum size for polygon 50 PFAFSTETTE 1 0 3 MAINDRAIN 5000 4 INT NAME Oka Volga 4 WINDOW 2013 5 MAIN PER Wy 5 OBJECTID 1 6 SHAPE Leng 3710847 47957 7 7 Get fields from cooFile Start coordinate generation Once that is done the fields from the shapefiles used for keys and the long texts can be chosen and some other settings e Simplify will simplify the geometry by shifting points using a pre defined distance in the coordinate room That distance is current hard coded and matches data sets in universal meters e Sto
178. the task to select all regions where the Nitrogen Fertilizer Consumption is between 100 and 150 kg ha First switch from map to tabular view In the Wolfgang Britz Version January 2015 85 GGIG Graphical Interface Generator User Guide table click with the right mouse button in the column header of that column holding the values to which the filter should be applied as shown below We will need to apply the filter step wise first e g selecting all values greater than 100 and then removing those which are above 150 lection view Handling Windows Build database Exploitation of spatial results Data iew 1 Generate baseline Activity Items Table Edit simulation uaa v No 5 a Mineral Fertilizer Consumption Nitrogen kg N ha v Agri Env indicators driving forces v Run simulation S gt BASE Ect aze NN eee ee Filter dialog x S Define numerical selection Filter for table rows Ex Comparison operator Comparison value Ex gt v f1o0 De Clear selection and select according to filter Add result of filter to existing selSStion Remove result of Filter from existing selection OK Cancel After clicking on clear selection and select according to filter and then on ok the table will only show such regions where the value in the column BASE is above 100 as shown below Next we must exclude the regions above 150 kg ha To do so set the filter to gt 150 m an
179. tics do not work correctly if several dimensions are merged in the rows Wolfgang Britz Version January 2015 GGIG Graphical Interface Generator User Guide LANA HERBAMO T britz lanz View Handling Windows Region Activity Product Scenario Lake Navaja Reservoir Levi m above sea levi a 1888 20 1888 10 1888 00 1887 90 1887 80 Options for bar charts and histograms Options for line and area charts 1887 70 Maximal number of plots gt Maximal number of plots 1887 60 Maximal number of bar blocks dnai 1887 50 5 ximal number of bars per blocks a g O Maxi e per K Z 1887 40 i Z Maximal number of observations 1887 30 a 1a 3 z Foreground transparency in tacked 1887 20 ffect 1887 10 j Cylinder only for 3D non stacked H Touran F Draw shadow v Draw lines 1886 90 7 T Show mean median q1 q3 Sort values 1886 80 E j i Options for pie charts 1886 70 Maximal number of plots 1886 60 A 1886 50 Maximal number of observations 1886 40 i Minimum percentage to draw label en Foreground transparency in 1886 20 Foreground transparency in 1886 10 7 Filled shapes 1886 00 nee E 1885 90 Fjar e gt 1885 80 aaia Options for Heat Map 1885 60 7 Show last column 1885 50 Options for all charts 1885 40 Font size relative to tables in 1885 30 Use
180. ting each region e g a NUTS II or a HSMU as an observation with equal weight or using the areas of the underlying polygons as weights Those weights are multiplied with the share of UAA 1f shrinking is used as explained above Excluding zeros from classification and removing small and large values In GAMS zeros and missing values cannot be distinguished For certain results zero results are therefore coded as very small numbers to allow for that distinction Zero observation can be excluded from classification and the polygons with zero observations will not be filled Equally a number of regions with small and large values can be excluded from classification which might help in finding an appropriate coloring scheme and legend k Number of regions with small large values exduded from dassification OF OF Classification method The classification method selects the ways the class limits are defined i e the lower and upper bounds for the numerical values drawn in the same color Generally the same quantitative information might generate quite different graphical impressions depending on how classes are defined and colored For all types of automatic classification methods a clean up procedure is used which removes classes with identical limits It is generally recommended to use a number of classes which can be easily identified by the user and to consult the frequency or cumulative distribution Wolfgang Britz V
181. to clipboard Alternatively the graphic can be placed into the clipboard where it is stored as a bitmap or as E jpeg by double clicking the copy to clipboard button Wolfgang Britz Version January 2015 51 GGIG Graphical Interface Generator User Guide Pop up menu in graphics Selected options discussed above can be reached via the a pop up menu which opens after a right mouse click in the table Eigenschaften Kopieren Speichern unter Drucken Hineinzoomen F Herauszoomen k Autojustage Chose colors Customize graph Customize 7 As seen above part of the pop up menu provided by the JFreeChart library adjust to the language of the Operating System The entries are briefly discussed below e Eigenschaften Properties Opens a dialogue where e g headlines can be entered description changes and fonts selected for specific elements Diagramm Eigenschaften axe e Kopieren Copy see Exporting the graphic to clipboard e Speichern untern Save as Open a dialogue which allows to store the graphics in png format e Hineinzoomen Zoom in Opens a dialogue which allows to choose the axis for zooming in e Herauszoomen Zoom out Opens a dialogue which allows to choose the axis for zooming in Wolfgang Britz Version January 2015 52 GGIG Graphical Interface Generator User Guide Autojustage auto adjust Reset the zoo
182. true Set substitution elasticty 6 0 Countries NL f That sets can then be stored with one GAMS statement as shown below in a GDX file along with the results execute_unload Ascenarlio_descriptions gdx MET RESULT The user might then select some scenario Wolfgang Britz Version January 2015 111 GGIG Graphical Interface Generator User Guide TRIMAG t britz trimag File Settings TRIMAG taks Scenario exploitation Start TRIMAG Scenario 1 my first scenario he Scenario 2 MA EEEa v Scenario 3 v Exploit scenarios Scenario 4 v Scenario 5 v PT TT RIMAG Graphical User Inter Ini file gig ini User name undefined And then by pressing show meta view the settings used for these scenarios TRIMAG t britz trimag View Handling Windows FA TRIMAG result exploitation meta data 0 mMm J PAB Ka my first scenario my test scenario Scenario description my first scenario my test scenario model type CGE Use demand elasticities RIMAG Graphical User Inter Ini file gig ini User type runner Wolfgang Britz Version January 2015 112 GGIG Graphical Interface Generator User Guide As the GDX container with the results comprises at the same time the numerical results and the meta data the information about the run is not lost as long as its result are not deleted Sending the results to th
183. used e g for income indicators or environmental benefits e Red Gray Green Green Gray Red more available for historic reasons as they mimic the color tables of the original JAVA applet e Blue Gray Green Green Gray Blue introduced on demand of DG AGRI A good choice if the good bad interpretation of the distribution is to be avoided e Shades of grey sometimes needed for publications when color printing is not available in the final hardcopy Beware to use a limited number of classes e Shades of blue useful where the notion of bad or good inheritably comprised in greenish and reddish colors is to be avoided If percentage or absolute difference or some other quantitative range is sued which has a natural middle point for difference that the zero case i e no difference one should use Set value for middle color 950 31 to chose the class closest to the natural middle point for the middle color see below Defining an self created color model Once a color model is chosen the user can re define the start middle and end color using the three buttons on the color table selection row as shown below given a lot of freedom to generate color ramps Wolfgang Britz Version January 2015 11 GGIG Graphical Interface Generator User Guide Exploitation of spatial results Data iew 1 Table Indicator Aari Eny indicators driving forces
184. utton and rests there for some time and such groups exists a dialogue will show as below where the groups can be selected Wolfgang Britz Version January 2015 28 GGIG Graphical Interface Generator User Guide CAPRI t britz capri gams view Handling Windows Product Balances 0 Region Years Germany 2020 Selection of predefined groups List of key words for groups 7 show all h E44 115 Cereals _ DUble clicky ITF 1 NUTBAL 3 sues 1 web cereals 11 dairy products 11 feed 12 Meat market 63 Other Animal products meat 4 3 Young animals z Selection of the view type As discussed below the data can be shown as tables graphics or maps to do so use the view selection drop down box Crop share A or 0 01 ani Manually changing the pivot Normally the predefined views will link the data dimension in an appropriate way to columns and rows However the user is free to change the pivot to e g generate a cross l l l nen aes sectional series A dialog opens when right clicking the E245 button to pivot the currently shown or selected part of the view not available with maps Transposing and Merging Table control area Animation Box 1 i Region 273 Bo hide 1 Box 3 Years 1 Box 4 Table area Table column groups Scenarios 2 Table columns Item 6 0 83 Table row groups T
185. ve it empty The text fields next to the boxes allow the user to replace the file name normally used as a description of the scenario by a user chosen text The left hand side shows depending on the work step selection control for countries the regional level base year and simulation year Operating these control filters out files from the disk shown in the drop down boxes In the example above only results files for the base 04 simulation year 20 and the regional level 2 NUTS2 can be selected At the bottom of the panel pressing the show results button will open the exploitation tools the screen shot shown an example The Show meta option is discussed in the section on Meta data and the GDX viewer under Utilities Wolfgang Britz Version January 2015 23 GGIG Graphical Interface Generator User Guide Shon meta Show rent E DAIRYDYN gams View Handling Windows Herd summary mean 0 Kex View type Farm RES _30COWS 2017 Cows Herd size Revenues Variable Costs of Gross margin Labour Milk yield Nu Heads Euro ha costs incl concentrates Euro hal hours ha liter head lac concentrates Euro ha and year lit Euroha ener 25 71 2980 48 451 46 201 29 2529 02 22 00 TA AS redt 25 68 2973 75 449 12 199 42 2524 63 22 00 73 n 25 01 2971 81 448 56 199 08 2523 25 22 00 7 13 red3 24 24 2975
186. w a continuous distribution instead of bars set draw outline and Filled bars to off and use Draw line which generates a graph as seen below e With Show mean median q1 q3 switch on the marker lines mean normal line median dotted q1 q3 dashed as seen in the graph below L Supply details mapping view 0 pce C s wz Activity Item Year View type gt 7 4 ner tE iaki Utilized agricultural area X Income Euro ha or head 2020 ho j Histogramm As the continuous distributions are drawn with a spline renderer they can be quite nicely smoothed if the number of bins is decreased in the example below from 1000 to 100 to 10 bins ere eee a m e TH wasem n E E nth i ASi Wolfgang Britz Version January 2015 60 GGIG Graphical Interface Generator User Guide Scatter plots Scatter plots are an extension of Histograms showing the one dimensional distribution of items on the diagonal panels as histograms their combined distribution on the off diagonal as a scatter plot below the diagonal The plots above the diagonal cut the x y observation range in equally sized cells and indicate by the intensity of the color how many observations are found in each cell Lg Demand by product 0 fs 4 gt Region Items Sectors and rstitusons mr a View type WY tai e World Price w Total El ER Glz
187. which are discussed in some detail in the following e Bar charts e Lune charts Wolfgang Britz Version January 2015 47 GGIG Graphical Interface Generator User Guide e Area chart e Spider chart e Pie chart e Box and Whisker chart e Histogram e Markov chart The selection of rows and columns shown in the graph can be set in three different ways for all types of graphics e Using the selection dialogs upper left corner of the table or the buttons next to the graphic type selection drop down box double click Selection for column groups ks Selection for columns E Selection forrows Selection for rows e Using these filter buttons in graphic mode single clicks with the left mouse button will scroll down in the list right mouse single clicks will scroll up e Scrolling the table with the scroll bar to a specific position The column row in the upper left corner of the table will define the starting point for the graphic All types of graphics support tooltips to query the numerical values underlying the graphic The tooltips appear when moving the mouse on a graphic element linked to the value as e g a bar OF DIEZ Other arable field crops 186 745 641 Perhaps an unexpected feature is the zooming in and out with the mouse The graphs support saving to the disk as a png file via a popup menu and printing The popup menu also allows Wolfgang Britz Version January 2015 48 GGIG G
188. with the mouse while being in zoom in mode will increase the map resolution step wise by 25 and center the map at the current mouse position lt lt zigiz oy iamnow ener ens aae y IFW I SE Q E A By clicking with the zoom out pointer 2 on a point of the map the point becomes the new center point of the map and the map resolution is reduced stepwise by 25 Equally you may drag the map while keeping the current resolution by choosing the drag pointer PI Finally in order to return to the original full sized map use the full extent button 1 The reader should note that the full extent button shows a rectangle around the arrows Wolfgang Britz Version January 2015 82 GGIG Graphical Interface Generator User Guide Getting data for specific polygons The info pointer l will open an additional window as shown below which displays 66599 1 information on the current polygon the circle above the 1 being the focus point The title bar of the new window shows the code and if available the long text of the polygon currently pointed to with the info pointer The content of the info window is continuously updated when the mouse is moved over the map and all polygons belonging to the same region as the one pointed on with the mouse is highlighted 2 DKOOFH24254 H2425 UAA If the user opts to use one of the comparison options to be shown percentages differences a n

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