Interface for uploading data to and downloading from the Opasnet Base. <a href="http://en.opasnet.org/w/Image:Opasnet_base_connection.ANA">Wiki description</a> Jouni Tuomisto 9. maata 2008 10:42 ktluser 25. Mayta 2009 23:05 48,24 1,0,0,1,1,1,0,0,0,0 1,4,8,586,623,17 2,102,90,476,224 Arial, 15 0,Linkmodule Op_en2676,2,2,-32763,1,Opasnet base connection.ANA 100,1,1,1,1,9,2970,2100,15,0 This module saves model results into the Opasnet Base. You need your Opasnet username and password for that. You must fill in all tables before the process is completed. Fill in the data below from top to bottom. If an object with the same Ident already exists in the Opasnet Base, the information will be added to that object. Before you start, make sure that you have created an object page in the Opasnet wiki for each object (study or variable) you want to upload. 276,76,-1 268,68 0 272,156,1 160,12 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Opasnet_username 0 272,180,1 160,12 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Opasnet_password 0 272,340,1 152,12 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 N_indices 360,584,1 48,12 2,31,25,825,451 [Alias Upload_data1] 0 276,548,1 156,12 1,0,0,1,0,0,0,90,0,1 52425,39321,65535 Object_info1 Upload a data table. Indices are determinants of your study objects, such as sex or observation year. Parameters are those that are measured, such as body weight or pollutant concentration. 272,344,-1 160,144 1,0,0,1,0,1,0,,0, 2,693,146,476,224 Finally, fill in the name (a description that may be longer than an identifier) and the unit of measurement. Then press the button Upload data. 276,516,-1 268,20 0 272,317,1 152,13 1,0,0,1,0,0,0,158,0,1 52425,39321,65535 Study_ident ktluser 1. Aprta 2009 9:38 48,24 152,784,1 48,24 1,0,0,1,1,1,0,,0, 1,599,9,670,624,17 3) Upload an Analytica model. First, switch the choice "Data table or model?" to "Analytica model". Note! You can insert several variables at the same time. Each variable or study MUST have at least one index. Analytica identifiers are used to find the right nodes. Ident is the identifier of the description page in the Opasnet wiki. If Probabilistic? is 1, a sample of the distribution is stored; otherwise, the mean or the point estimate is stored. 320,350,-5 304,89 1,0,0,1,0,1,0,,0, jtue 24. maata 2009 9:36 48,24 176,648,1 48,24 1,556,21,610,490,17 Makes a table to be written to the Loc table. index j:= ['id','Std_id','Obj_id_i','Location','Roww','Description']; var a:= Locations[.j=j]; var b:= a[j='Obj_id_i']; var c:= textify(cardinals[table1='Loc']+a[@j=1]); a:= array(j,[c, c, findid(b,Obj,'Ident'), a, textify(a), a]) 440,208,1 48,16 2,156,83,476,245 2,642,68,606,278,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 100,1,1,1,1,9,2970,2100,15,0 [] [Sys_localindex('I'),16,Sys_localindex('I'),1,Sys_localindex('J'),1] Slices fields that are needed in the Locres table from Inp_locres. index j:= ['id','Cell_id','Loc_id']; var a:= Loccells; var b:= textify(findid(a[.j='Loc_id'], Obj, 'Ident')); var c:= textify(a[.j='Location']); b:= findid(b&'+'&c, (if Loc.j='Obj_id_i' then Loc&'+'&Loc[.j='Location'] else Loc), 'Obj_id_i'); a:= a[.j=j]; a:= array(j,[(a+cardinals[table1='Loccell']),(a+cardinals[table1='Cell']), b]); textify(a) 424,312,1 48,16 2,776,90,476,487 2,72,177,619,303,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [] Slices the fields that are needed in the Res table. Removes duplicate rows. index j:= ['id','Obj_id_v','Obj_id_r','Mean','SD','N']; var a:= loccells1; {index i:= unique(a[.j='Cell_id'], a.i); ivar a:= a[.i=i];} var b:= a[.j='Cell_id']+cardinals[table1='Cell']; a:= a[.j=j]; var c:= findid(a[@j=2], Obj, 'Ident'); var d:= w_obj[.j='Ident']; d:= findid(d, Obj, 'Ident')[@.i=size(w_obj.i)]; a:= array(j, [textify(b),c, d, a, a, textify(a)]); if a=null then '' else a 424,256,1 48,16 2,799,214,476,379 2,85,264,505,368,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] Names of different wikis used. Table(Self)( 'Op_en','Op_fi','Heande','En','Fi','Erac','Beneris','Intarese','Piltti','Kantiva','Bioher','Heimtsa') [1,2,3,4,5,8,9,10,11,13,14,15] 304,24,1 48,16 65535,52427,65534 [Self] Types of different objects that may exist in Analytica or Opasnet Base. Types that have the same number are treated equally in these systems. Table(Self)( 'Variable','Dimension','Method','Model','Class','Index','Nugget','Encyclopedia article','Run','Chance','Decision','Objective','Constant','Determ','Module','Library','Form') [1,2,3,4,5,6,7,8,9,1,10,1,1,1,4,4,4] 64,312,1 48,20 2,56,132,476,224 2,674,34,416,606,0,MIDM 2,636,151,416,390,0,MIDM 65535,52427,65534 Selects relevant information for the Obj table from Objects1 node. index j:= ['id','Ident','Name','Unit','Objtype_id','Page','Wiki_id']; var a:= Objects; var b:= if a[.j='Ident'] = 0 then -1 else a[.j='Ident']; b:= findid(b, Obj, 'Ident'); b:= if b='0' then cardinals[table1='Obj']+a[.j='id'] else b; a:= if a.j='id' then b else a; a:= a[.j=j]; a:= if j='Ident' and a[j='Ident']='' then a[j='id'] else a; a:= if j='Ident' and a.i='Run' and isnumber(append_to_run) then append_to_run else a; textify(a) 424,120,1 48,16 2,510,138,476,508 2,6,67,1023,259,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [] [] If the result is not a number, then the actual result text can be written into the Description field of the Descr table. Makes a list of text values to be written into the Descr table. index j:= ['id','Restext']; var a:= Results; index i:= subset(a[.j='Restext']); a:= a[.j=j, .i=i]; a:= array(j, [textify(a+Cardinals[table1='Res']), a]) 424,384,1 48,16 2,674,46,476,259 2,670,328,416,303,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] Makes a list of objects that contains some additional information to be written into the Inf table. index j:= ['Obj_id','Acttype_id','Who','Comments']; var a:= Objects; var b:= if a[.j='Ident'] = 0 then -1 else a[.j='Ident']; b:= findid(b, Obj, 'Ident'); b:= if b='0' then cardinals[table1='Obj']+a[.j='id'] else b; a:= if j='Obj_id' then b else a[.j=j]; a:= if a = null or a='' then 0 else a; index i:= subset(if sum(a, j) = 0 then 0 else 1); a:= a[.i=i]; a:= if a=null or a=0 then '' else a&'' 424,72,1 48,16 2,773,40,476,340 2,34,427,690,274,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [] [Sys_localindex('J'),1,Sys_localindex('I'),1,Sys_localindex('J'),1] index j:= ['id','Cell_id','Obs','Result']; var a:= Results; index i:= subset(if a[.j='Result']=null and a[.j='Description']=0 then 0 else 1); a:= a[.j=j, .i=i]; a:= array(j, [textify(a+Cardinals[table1='Res']), textify(a+ Cardinals[table1='Cell']), textify(a),a]); if a=null then '' else a 424,416,1 48,13 2,629,191,582,297 2,54,89,609,375,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] [] Additional information for each index and decision node. Description node is the name of a node containing information about the locations of the index. It must be indexed by the index. 1 176,408,1 48,22 2,140,217,476,224 2,605,351,664,303,0,MIDM 2,506,220,684,303,0,MIDM [Formnode Number_of_variables1] 52425,39321,65535 [] [] [1,1,0,1] var a:= if data_table_or_model_ = 'Data table' then 1 else N_variables; 'Var'&1..a 176,344,1 48,13 1,1,1,1,1,1,0,,0, 2,107,331,416,303,0,MIDM [1,1,1,0] ['Var1'] Additional information for each index and decision node. Description node is the name of a node containing information about the locations of the index. It must be indexed by the index. Table(Variable1,Varinfo)( 'world_population1','Op_en3058',0 ) 176,312,1 48,22 2,140,217,476,224 2,11,16,553,630,0,MIDM 2,506,220,684,303,0,MIDM [Formnode Variables1] 52425,39321,65535 [Varinfo,Variable1] [Varinfo,Variable1] [0,1,1,0] 3 176,256,1 48,20 [Formnode Number_of_indices1] 52425,39321,65535 [1,1,0,1] Table(Object_info,Object1)( 'Population of the World','Country codes used by WHO','Year','Sex','Age', '#','-','a','-','a' ) 176,72,1 48,13 2,102,90,476,349 2,571,27,659,478,0,MIDM 2,184,194,660,316,0,MIDM [Formnode Study_or_variable_i1] 52425,39321,65535 [Object_info,Object1] [Object_info,Object1] ['Name','Unit'] 176,96,1 48,12 Makes a list of all locations in all results in all variables. The list is as long as is needed for the Loccell table. A subset is taken then for the Cell table. 1) Initialises local variables, and slices variables from Object1. 2)-4) Does the process for each variable one at a time. This happens in function Loccell. 5) Makes i the row index. , @observation=@cell_id+1 var output:= 0; output:= if data_table_or_model_ = 'Data table' then Doloccell(Data_table) else ( var e:= 0; var f:= 0; var x:= 1; while x<= size(variable1) do ( var a:= sample(evaluate(List_of_variables[@variable1=x, varinfo='Analytica identifier'])); var b:= sdeviation(a); a:= mean(a); index temp:= concat(indexnames(a),['Result']); index i:= 1..size(a); a:= mdarraytotable(a, i, temp); b:= mdarraytotable(b, i, temp); index j:= concat(temp,['SD']); index temp2:= ['Result']; a:= concat(a, b[temp=temp2], temp, temp2, j); a:= Doloccell(a, x, e, f); e:= e+size(a.i); f:= f+size(i); output:= if x=1 then a else for y:= output.j do ( concat(output[.j=y], a[.j=y]) ); x:= x+1) ; output); {index i:= 1..size(output)/size(output.j); for y:= output.j do (slice(output[.j=y],i))} 304,312,1 48,16 2,708,12,526,596 2,31,123,731,488,0,MIDM [Sys_localindex('J'),Sys_localindex('I'),Undefined,Undefined,Undefined,1] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] [Undefined] [Sys_localindex('CONV2'),1,Parameter,1,Sys_localindex('L'),1] The usage of local variables: a: the temporary variable that is being edited. e: cardinal of the Cell table. f: cardinal of the Res table. j: output column headings. i: output row numbers. NOTE! ONLY THE DETERMINISTIC VERSION WORKS AT THE MOMENT. 1) Only one piece of information (Observations) is included. 2)-5) The process is done for each variable one at a time (this is indexed by x). 3) Several within-loop local variables are initiated. 4) The variable is given index runn which is equal to run if probabilistic and [0] if not. The array is flattened first to 2-D, the value only is kept. 5) Variables are concatenated to each other. 6) Index i is made the index of the implicit index. NOTE! This node MUST be formatted to Integer, otherwise Res_id will be stored in a wrong format. var output:= 0; output:= if data_table_or_model_ = 'Data table' then Doresult(Data_table, 0) else ( var e:= 0; var f:= 0; var x:= 1; while x<= size(variable1) do ( var a:= sample(evaluate(List_of_variables[@variable1=x, varinfo='Analytica identifier'])); index j:= concat(indexnames(max(a,run)),['Result']); index i:= 1..size(max(a,run)); a:= mdarraytotable(a, i, j); a:= Doresult(a, List_of_variables[@variable1=x, varinfo='Probabilistic?'], e, f); e:= max(a[.j='Cell_id'],a.i); f:= max(a[.j='id'],a.i); output:= if x=1 then a else for y:= output.j do ( concat(output[.j=y], a[.j=y]) ); x:= x+1) ; output); index i:= 1..size(output)/size(output.j); output:= for y:= output.j do (slice(output[.j=y],i)) 304,384,1 48,16 2,642,17,585,615 2,28,187,469,411,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [Run,2,Sys_localindex('J'),1,Sys_localindex('I'),1] The format of this node MUST be integer, so that the id and Roww values are stored correctly. var output:= 0; output:= if data_table_or_model_ = 'Data table' then Dolocation(Data_table) else ( var x:= 1; while x<= size(variable1) do ( var a:= mean(evaluate(List_of_variables[@variable1=x, varinfo='Analytica identifier'])); index j:= concat(indexnames(a),['Result']); index i:= 1..size(a); a:= mdarraytotable(a, i, j); a:= Dolocation(a); output:= if x=1 then a else for y:= output.j do ( concat(output[.j=y], a[.j=y]) ); x:= x+1) ; output); index i:= 1..size(output)/size(output.j); output:= for y:= output.j do (slice(output[.j=y],i)); output:= if output.j='id' then i else output; {if output.j='Description' then va5[@who_country_code=@output.i] else output} 304,208,1 48,16 2,549,55,476,581 2,482,15,746,348,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [0] [Sys_localindex('D'),1,Object_all3,1,Age,1] index h:= data_table2[@.i=1, @.j=1..N_indices]; index j:= concat(h,['Parameter','Result']); index parameter:= data_table2[@.i=1, @.j=N_indices+(1..size(data_table2.j)-N_indices)]; index i:= 1..(size(data_table2.i)-1)*(size(parameter)); index loccell_id:= 1..(size(i)*size(h)); var conv:= if j='Result' then @parameter+N_indices else @j; index conv2:= 1..size(data_table2.i)-1; var a:= data_table2[@.j=conv, @.i=conv2+1]; a:= if j='Parameter' then parameter else a; a:= concatrows(a, parameter, conv2, i); if j='Result' then evaluate(a) else a var data:= if Data_table_name = '' then data_table2 else evaluate(Data_table_name); index h:= data.j[@.j=1..N_indices]; var c:= if parameter_name='' then 'Parameter' else parameter_name; index j:= concat(h,[c,'Result']); index parameter:= data.j[@.j=N_indices+(1..size(data.j)-N_indices)]; index temp:= 1..size(data.i)*size(parameter); var conv:= if j='Result' then @parameter+N_indices else @j; var a:= data[@.j=conv]; a:= if @j=size(j)-1 then parameter else a; a:= concatrows(a, parameter, a.i, temp); a:= if j='Result' then evaluate(a[j='Result']) else a; index i:= Subset(a[j='Result']<>null); a[temp=i] 176,208,1 48,13 2,97,51,482,359 2,625,86,611,523,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [1,1,1,0] [Sys_localindex('I'),9,Sys_localindex('PARAMETER'),1,Sys_localindex('J'),1] ['Analytica identifier','Ident','Probabilistic?'] 176,368,1 48,12 2,90,166,416,303,0,MIDM ['Analytica identifier','Ident','Probabilistic?'] Index j:= ['id','Ident','Name','Unit','Objtype_id','Acttype_id','Page','Wiki_id', 'Who','Comments','Probabilistic?','Description node']; index i:= concat(Object1,['Run']); var a:= if j='Ident' and i = 'Var1' then study_ident else null; a:= if data_table_or_model_ = 'Data table' then a else List_of_variables[Variable1=i, Varinfo=j]; a:= if a=null then Object_info1[Object1=i, Object_info=j] else a; var b:= findintext(wikis,a[j='Ident']); var c:= sum(if b=0 then 0 else @wikis,wikis); b:= sum(if b=0 then 0 else b+textlength(Wikis),wikis); b:= if b = 0 then 2664 else selecttext(a[j='Ident'],b); a:= array(j,[ @i, if @i>size(variable1) and @i<size(i) then i else a, if i ='Run' then 'Analytica '&Analyticaedition&', ('&Analyticaplatform&'), Version: '&Analyticaversion&', Samplesize: '&samplesize else a, a, if @i<=size(variable1) then 1 else if @i=size(i) then 9 else 6, if @i<=size(variable1) then 11 else 1, if i='Run' then '2817' else b&'', if c=0 then 1&'' else c&'', opasnet_username, '', a, '']); a:= if a = null then '' else a 304,72,1 48,16 2,669,75,479,551 2,106,165,754,315,0,MIDM [Sys_localindex('I'),Sys_localindex('J')] reset; var a:= indexnames(evaluate(List_of_variables[Varinfo='Analytica identifier'])); a:= if a='Variable1' or a='Run' then 0 else 1; a:= subset(a); a:= if data_table_or_model_ = 'Data table' then Data_table.j[@.j=1..size(data_table.j)-1] else a; var b:= if data_table_or_model_ = 'Data table' then "['Var1']" else "variable1"; concat(evaluate(b),a) 176,120,1 48,13 2,59,17,630,338 2,852,136,416,303,0,MIDM [Year,Who_country_code] 'Op_en3058' 176,32,1 48,16 [Formnode Study_ident1] 52425,39321,65535 [1,1,0,1] 'Municipality_fin Age Males 2013 Females 2013 Males 2020 Females 2020 Males 2030 Females 2030 Espoo - Esbo 0-4 9218 8791 9509 9067 9414 8976 Espoo - Esbo 5-9 8461 8019 8881 8418 9064 8590 Espoo - Esbo 10-14 7651 7276 8392 7983 8733 8316 Espoo - Esbo 15 - 19 7878 7665 7942 7634 8689 8302 Espoo - Esbo 20 - 24 9703 8254 9166 7700 9825 8164 Espoo - Esbo 25 - 29 9221 8671 10075 9363 9319 8580 Espoo - Esbo 30 - 34 10158 9887 10229 9855 9967 9545 Espoo - Esbo 35 - 39 9996 9824 10385 10112 10850 10446 Espoo - Esbo 40 - 44 8736 8672 9910 9754 10095 9833 Espoo - Esbo 45 - 49 9360 9789 8846 8897 9846 9866 Espoo - Esbo 50 - 54 8366 8843 8759 9227 9231 9424 Espoo - Esbo 55 - 59 7045 7880 8205 8891 7947 8322 Espoo - Esbo 60 - 64 6384 7645 6740 7617 7590 8370 Espoo - Esbo >=65 14543 19580 18716 25250 24301 32210 Helsinki - Helsingfors 0-4 14140 13613 14296 13762 13869 13349 Helsinki - Helsingfors 5-9 12102 11791 12391 12025 12387 12017 Helsinki - Helsingfors 10-14 11734 11389 11942 11544 12172 11764 Helsinki - Helsingfors 15 - 19 13797 14187 12321 12858 12862 13419 Helsinki - Helsingfors 20 - 24 21478 25254 19377 22926 19565 23290 Helsinki - Helsingfors 25 - 29 25056 27208 26650 28556 23965 25708 Helsinki - Helsingfors 30 - 34 24082 23867 23944 23568 22855 22377 Helsinki - Helsingfors 35 - 39 21005 19952 21072 20381 21649 20718 Helsinki - Helsingfors 40 - 44 17917 17261 19664 18761 19607 18751 Helsinki - Helsingfors 45 - 49 19971 20571 17476 17035 18919 18668 Helsinki - Helsingfors 50 - 54 18613 20147 18035 19002 18068 18226 Helsinki - Helsingfors 55 - 59 16671 19310 18191 20058 16135 16722 Helsinki - Helsingfors 60 - 64 15464 19421 15627 18273 16109 17856 Helsinki - Helsingfors >=65 37669 60241 45258 69319 55248 80147 Kauniainen - Grankulla 0-4 222 195 226 198 222 195 Kauniainen - Grankulla 5-9 276 238 280 251 283 253 Kauniainen - Grankulla 10-14 311 279 318 265 324 275 Kauniainen - Grankulla 15 - 19 376 315 327 281 339 288 Kauniainen - Grankulla 20 - 24 305 247 267 222 277 227 Kauniainen - Grankulla 25 - 29 183 144 207 154 184 140 Kauniainen - Grankulla 30 - 34 153 171 155 171 150 165 Kauniainen - Grankulla 35 - 39 214 254 219 255 228 262 Kauniainen - Grankulla 40 - 44 268 267 289 288 290 288 Kauniainen - Grankulla 45 - 49 337 371 281 293 305 312 Kauniainen - Grankulla 50 - 54 307 326 290 316 284 290 Kauniainen - Grankulla 55 - 59 259 239 280 285 248 238 Kauniainen - Grankulla 60 - 64 230 245 248 240 246 254 Kauniainen - Grankulla >=65 740 1083 826 1219 971 1410 Vantaa - Vanda 0-4 6782 6498 6962 6669 6825 6537 Vantaa - Vanda 5-9 6228 5945 6502 6217 6577 6287 Vantaa - Vanda 10-14 5745 5561 6201 6022 6416 6253 Vantaa - Vanda 15 - 19 5970 6078 5905 5880 6397 6356 Vantaa - Vanda 20 - 24 6480 6548 5971 5993 6343 6284 Vantaa - Vanda 25 - 29 6797 6815 7354 7326 6735 6657 Vantaa - Vanda 30 - 34 7706 7428 7753 7434 7499 7153 Vantaa - Vanda 35 - 39 7766 7459 7910 7643 8249 7909 Vantaa - Vanda 40 - 44 7038 6770 7835 7445 7925 7520 Vantaa - Vanda 45 - 49 7909 7710 7156 6898 7880 7556 Vantaa - Vanda 50 - 54 7126 7130 7340 7266 7518 7323 Vantaa - Vanda 55 - 59 6129 6602 7029 7211 6558 6544 Vantaa - Vanda 60 - 64 5659 6536 5774 6124 6384 6514 Vantaa - Vanda >=65 12282 16668 15717 21344 19879 26286' 64,160,1 52,16 2,637,65,476,362 [Formnode Observations3] 52425,39321,65535 var a:= splittext(textreplace(Observations2, chr(10),'',true),chr(13)); index i:= 1..size(a); a:= slice(a,i); a:= splittext(a, chr(9)); index j:= 1..size(a)/size(i); for y:= i do (slice(a[i=y],j)) var a:= splittext(textreplace(Observations2, chr(10),'',true),chr(13)); index j:= splittext(slice(a,1), chr(9)); index i:= 1..size(a)-1; a:= slice(a,i+1); a:= splittext(a, chr(9)); for y:= i do (slice(a[i=y],@j)) 64,208,1 48,16 2,98,65,476,362 2,8,352,629,303,0,MIDM [Sys_localindex('I'),Sys_localindex('J')] [1,1,1,0] ['Municipality_fin Age Males 2013 Females 2013 Males 2020 Females 2020 Males 2030 Females 2030','Espoo - Esbo 0-4 9218 8791 9509 9067 9414 8976','Espoo - Esbo 5-9 8461 8019 8881 8418 9064 8590','Espoo - Esbo 10-14 7651 7276 8392 7983 8733 8316','Espoo - Esbo 15 - 19 7878 7665 7942 7634 8689 8302','Espoo - Esbo 20 - 24 9703 8254 9166 7700 9825 8164','Espoo - Esbo 25 - 29 9221 8671 10075 9363 9319 8580','Espoo - Esbo 30 - 34 10158 9887 10229 9855 9967 9545','Espoo - Esbo 35 - 39 9996 9824 10385 10112 10850 10446','Espoo - Esbo 40 - 44 8736 8672 9910 9754 10095 9833','Espoo - Esbo 45 - 49 9360 9789 8846 8897 9846 9866','Espoo - Esbo 50 - 54 8366 8843 8759 9227 9231 9424','Espoo - Esbo 55 - 59 7045 7880 8205 8891 7947 8322','Espoo - Esbo 60 - 64 6384 7645 6740 7617 7590 8370','Espoo - Esbo >=65 14543 19580 18716 25250 24301 32210','Helsinki - Helsingfors 0-4 14140 13613 14296 13762 13869 13349','Helsinki - Helsingfors 5-9 12102 11791 12391 12025 12387 12017','Helsinki - Helsingfors 10-14 11734 11389 11942 11544 12172 11764','Helsinki - Helsingfors 15 - 19 13797 14187 12321 12858 12862 13419','Helsinki - Helsingfors 20 - 24 21478 25254 19377 22926 19565 23290','Helsinki - Helsingfors 25 - 29 25056 27208 26650 28556 23965 25708','Helsinki - Helsingfors 30 - 34 24082 23867 23944 23568 22855 22377','Helsinki - Helsingfors 35 - 39 21005 19952 21072 20381 21649 20718','Helsinki - Helsingfors 40 - 44 17917 17261 19664 18761 19607 18751','Helsinki - Helsingfors 45 - 49 19971 20571 17476 17035 18919 18668','Helsinki - Helsingfors 50 - 54 18613 20147 18035 19002 18068 18226','Helsinki - Helsingfors 55 - 59 16671 19310 18191 20058 16135 16722','Helsinki - Helsingfors 60 - 64 15464 19421 15627 18273 16109 17856','Helsinki - Helsingfors >=65 37669 60241 45258 69319 55248 80147','Kauniainen - Grankulla 0-4 222 195 226 198 222 195','Kauniainen - Grankulla 5-9 276 238 280 251 283 253','Kauniainen - Grankulla 10-14 311 279 318 265 324 275','Kauniainen - Grankulla 15 - 19 376 315 327 281 339 288','Kauniainen - Grankulla 20 - 24 305 247 267 222 277 227','Kauniainen - Grankulla 25 - 29 183 144 207 154 184 140','Kauniainen - Grankulla 30 - 34 153 171 155 171 150 165','Kauniainen - Grankulla 35 - 39 214 254 219 255 228 262','Kauniainen - Grankulla 40 - 44 268 267 289 288 290 288','Kauniainen - Grankulla 45 - 49 337 371 281 293 305 312','Kauniainen - Grankulla 50 - 54 307 326 290 316 284 290','Kauniainen - Grankulla 55 - 59 259 239 280 285 248 238','Kauniainen - Grankulla 60 - 64 230 245 248 240 246 254','Kauniainen - Grankulla >=65 740 1083 826 1219 971 1410','Vantaa - Vanda 0-4 6782 6498 6962 6669 6825 6537','Vantaa - Vanda 5-9 6228 5945 6502 6217 6577 6287','Vantaa - Vanda 10-14 5745 5561 6201 6022 6416 6253','Vantaa - Vanda 15 - 19 5970 6078 5905 5880 6397 6356','Vantaa - Vanda 20 - 24 6480 6548 5971 5993 6343 6284','Vantaa - Vanda 25 - 29 6797 6815 7354 7326 6735 6657','Vantaa - Vanda 30 - 34 7706 7428 7753 7434 7499 7153','Vantaa - Vanda 35 - 39 7766 7459 7910 7643 8249 7909','Vantaa - Vanda 40 - 44 7038 6770 7835 7445 7925 7520','Vantaa - Vanda 45 - 49 7909 7710 7156 6898 7880 7556','Vantaa - Vanda 50 - 54 7126 7130 7340 7266 7518 7323','Vantaa - Vanda 55 - 59 6129 6602 7029 7211 6558 6544','Vantaa - Vanda 60 - 64 5659 6536 5774 6124 6384 6514','Vantaa - Vanda >=65 12282 16668 15717 21344 19879 26286'] who_country_code ['item 1'] 64,368,1 48,24 [1,0,0,0] ['item 1'] ['item 1'] 64,400,1 48,12 Slices the fields that are needed in the Res table. Removes duplicate rows. (if w_cell.j = 'Mean' then '' else W_cell) 536,256,1 48,16 2,782,213,476,379 2,85,231,505,368,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] '' 304,120,1 48,20 1,1,1,1,1,1,0,0,0,0 [Formnode Append_to_run1] 52425,39321,65535 'Age' 176,160,1 48,20 1,1,1,1,1,1,0,0,0,0 [Formnode Parameter_name1] 52425,39321,65535 'world_population1' 64,256,1 48,22 [Formnode Data_table4] 52425,39321,65535 Makes a list of all locations in all results in all variables. The list is as long as is needed for the Loccell table. A subset is taken then for the Cell table. 1) Initialises local variables, and slices variables from Object1. 2)-4) Does the process for each variable one at a time. This happens in function Loccell. 5) Makes i the row index. , @observation=@cell_id+1 index j:= ['Dummy','Result','SD']; var output:= 0; output:= if data_table_or_model_ = 'Data table' then Doloccell(array(j, [0, Data_table[@.j=size(data_table.j)],''])) else ( var e:= 0; var f:= 0; var x:= 1; while x<= size(variable1) do ( var a:= sample(evaluate(List_of_variables[@variable1=x, varinfo='Analytica identifier'])); var b:= sdeviation(a); a:= mean(a); index temp:= concat(indexnames(a),['Result']); index i:= 1..size(a); a:= mdarraytotable(a, i, temp); b:= mdarraytotable(b, i, temp); a:= array(j, [0,a[temp='Result'], b[temp='Result']]); { index j:= concat(temp,['SD']); index temp2:= ['Result']; a:= concat(a, b[temp=temp2], temp, temp2, j); } a:= Doloccell(a, x, e, f); e:= e+size(a.i); f:= f+size(i); output:= if x=1 then a else for y:= output.j do ( concat(output[.j=y], a[.j=y]) ); x:= x+1) ; output); {index i:= 1..size(output)/size(output.j); for y:= output.j do (slice(output[.j=y],i))} 304,256,1 48,16 2,54,15,526,639 2,31,123,731,488,0,MIDM [Sys_localindex('J'),Sys_localindex('I'),Undefined,Undefined,Undefined,1] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] [Undefined] [Sys_localindex('CONV2'),1,Parameter,1,Sys_localindex('L'),1] 496,572,1 48,20 Choice(Self,1,False) 56,648,1 48,24 [Formnode Data_table_or_model1] 52425,39321,65535 ['Data table','Analytica model'] [1,1,0,0] 0 176,21,1 160,13 1,0,0,1,0,0,0,142,0,1 Data_table_or_model_ 0 156,372,1 140,12 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 N_variables 0 156,396,1 140,13 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 List_of_variables ktluser 3. Augta 2008 18:31 jtue 9. lokta 2008 14:01 48,24 176,712,1 48,24 1,1,1,1,1,1,0,0,0,0 1,785,211,477,445,17 Arial, 15 (vident:text, runident:optional) Reads the mean data about the vident variable from the Opasnet Base. Uses the runident run if specified; otherwise uses the newest run of that variable. PARAMETERS: * Vident: the Ident of the variable in the Opasnet Base. * Runident: the Ident of the run from which the results will be brought. If omitted, the newest result will be brought. if isnotspecified(runident) then runident:= identfind(newestrun(vident)); var a:= ' SELECT Var.Ident as Vident, Var.Name as Vname, Var.Unit as Vunit, Cell.id, Ind.Ident as Iident, Location, Mean, N, Run.Name as Rname, Run.Ident AS Runident FROM Obj as Var, Cell, Loccell, Loc, Obj as Ind, Obj as Run WHERE Cell.Obj_id_r = Run.id AND Cell.Obj_id_v = Var.id AND Loccell.Cell_id = Cell.id AND Loccell.Loc_id = Loc.id AND Loc.Obj_id_i = Ind.id AND Var.Ident = '&chr(39)&vident&chr(39)&' AND Run.ident = '&chr(39)&runident&chr(39) ; index i:= DBquery(Odbc,a); index j:= dblabels(i); dbtable(i,j) 56,88,1 48,12 2,585,25,516,589 39325,65535,39321 vident,runident (vident:text) This function checks for the newest result (according to run_id) of the variable. The function is used if the user does not define the run_id as an optional parameter in functions Read_mean and Read_sample. PARAMETERS: * Vident: the Ident of the variable in the Opasnet Base. index i:= DBquery(Odbc,' SELECT Obj_id_r FROM Cell, Obj as Var WHERE Var.id = Cell.Obj_id_v AND Var.Ident = "'&vident&'" GROUP BY Var.id, Obj_id_r '); index j:= dblabels(i); max(max(dbtable(i,j),i),j) 56,16,1 48,12 2,678,59,476,566 39325,65535,39321 vident (vident:text, runident:optional) Reads the sample data about the vident variable from the Opasnet Base. Uses the runident run if specified; otherwise uses the newest run of that variable. PARAMETERS: * Vident: the name of the variable in the Opasnet Base. * Runident: the Ident of the run from which the results will be brought. If omitted, the newest result will be brought. if isnotspecified(runident) then runident:= identfind(newestrun(vident)); var a:= ' SELECT Temp.id, Obs, Result, Restext FROM (SELECT Cell.id, Res.id AS Res_id, Obs, Result, Obj_id_r FROM Cell, Res, Obj AS Run, Obj AS Var WHERE Var.Ident = '&chr(39)&vident&chr(39)&' AND Cell.Obj_id_v = Var.id AND Cell.Obj_id_r = Run.id AND Run.Ident = '&chr(39)&Runident&chr(39)&' AND Res.Cell_id = Cell.id) AS Temp LEFT JOIN Resinfo ON Temp.Res_id = Resinfo.id '; index i:= DBquery(Odbc,a); index j:= dblabels(i); dbtable(i,j) 56,120,1 48,22 2,700,47,516,612 39325,65535,39321 vident,runident 'Op_en1912' 168,83,1 48,27 [Formnode Enter_variable1] 52425,39321,65535 0 288,24,1 176,13 1,0,0,1,0,0,0,170,0,1 52425,39321,65535 Enter_variable newestrun(Enter_variable) 288,60,1 48,12 read_mean(Enter_variable) 288,108,1 48,12 2,56,66,1205,308,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] (a,inde) The input table a must have a structure that is also used as input for MDTable function. The function removes one column with location information and makes a dimension (index) with the locations in the column. Inde is the (local) index that will be added. Note that unlike MDTable function, this can use local indices in the output. if size(a.m)= 1 then a else ( a:= if inde = a[@.m=1] then a else 0; index m:= slice(a.m,(2..size(a.m))); a:= a[.m=m]) 56,176,1 48,12 2,283,62,476,224 a,inde (a) Makes a multi-dimensional array with the same structure as the original variable that was stored into the Opasnet Base. However, the indices do not have original names. They are named In1, In2,... The contents of the array are the res.ids of the variable. The input parameter must be a 2D table with the structure that comes from the Read_mean function. 1) Slices the necessary columns from the input table and converts that to a 2D table that has the same structure as is used for input to the function MDTable. 2) Defines the local indices (up to 10), and changes a location column to a dimension one at a time until all columns have been changed. index k:= ['Iident','Location','id']; a:= a[.j=k]; index L:= a[@k=1]&'+'&textify(a[@k=3]); index m:= concat(a[.i=unique(a[@k=1],a.i), @k=1],['Result']); index n:= a[.i=unique(a[@k=3],a.i), @k=3]; a:= a[@.i=@L]; a:= a[L=(m)&'+'&textify(n), @k=2]; a:= if m='Result' then n else a; index in1:= a[n=unique(a[@m=1],n),@m=1]; index in2:= a[n=unique(a[@m=2],n),@m=2]; index in3:= a[n=unique(a[@m=3],n),@m=3]; index In4:= a[n=unique(a[@m=4],n),@m=4]; index In5:= a[n=unique(a[@m=5],n),@m=5]; index in6:= a[n=unique(a[@m=6],n),@m=6]; index in7:= a[n=unique(a[@m=7],n),@m=7]; index in8:= a[n=unique(a[@m=8],n),@m=8]; index in9:= a[n=unique(a[@m=9],n),@m=9]; index in10:= a[n=unique(a[@m=10],n),@m=10]; a:= makeind(a, in1); a:= makeind(a, in2); a:= makeind(a, in3); a:= makeind(a, in4); a:= makeind(a, in5); a:= makeind(a, in6); a:= makeind(a, in7); a:= makeind(a, in8); a:= makeind(a, in9); a:= makeind(a, in10); sum(sum(a,a.m),a.n) 56,152,1 48,12 2,669,44,476,545 a get_mean(Enter_variable) 288,132,1 48,12 2,547,35,416,622,0,MIDM [Sys_localindex('IN2'),Sys_localindex('IN3')] [Sys_localindex('IN1'),1,Sys_localindex('IN4'),1,Sys_localindex('IN5'),1,Sys_localindex('IN3'),1,Sys_localindex('IN2'),1] (vident:text, runident:optional) Gives the mean result of a (multidimensional) variable stored in the Opasnet Base. The procedure is simple because it utilises the variable structure (with res_ids) derived by the get_res_id function. var a:= read_mean(vident, runident); index o:= a[.j='id']; var output:= a[@.i=@o, .j='Mean']; a:= get_res_id(a); output[o=a] 56,200,1 48,12 2,665,82,476,428 vident,runident (vident:text, runident:optional) Gives the sample result of a (multidimensional) variable stored in the Opasnet Base. The procedure is simple because it utilises the variable structure (with res_ids) derived by the get_res_id function. Note that if the Analytica samplesize is smaller than the samplesize stored in the Opasnet Base, the extra samples will be discarded. If the samplesize is larger, the remaining rows will be null. 1) Brings the data into the right structure. 2) Chooses whether the actual result is numerical (in the Result column) or text (in the Description column). var a:= read_sample(vident, runident); var b:= textify(get_res_id(read_mean(vident,runident))); index k:= textify(a[.j='id'])&'+'&textify(a[.j='Obs']); index runn:= textify(min(a[.j='Obs'])..max(a[.j='Obs'])); a:= a[@.i=@k]; a:= a[k=b&'+'&runn]; a:= if max(runn)=0 then a[@runn=1] else a[@runn=@run]; var c:= if a[.j='Restext']='' then 0 else 1; c:= sum(sum(sum(sum(sum(sum(sum(sum(sum(sum(c)))))))))); if c=0 then a[.j='Result'] else a[.j='Restext'] 56,224,1 48,12 2,641,28,476,556 vident,runident get_sample(Enter_variable) 288,156,1 48,12 2,226,324,416,303,0,MEAN [Sys_localindex('IN5'),Sys_localindex('IN3')] [Sys_localindex('IN1'),1,Sys_localindex('IN2'),1,Sys_localindex('IN4'),1,Sys_localindex('IN3'),1,Sys_localindex('J'),1,Sys_localindex('IN5'),1] (runid) Finds the Ident for the run (or another object) that has the id runid. index i:= DBquery(Odbc,' SELECT Ident FROM Obj WHERE Obj.id = "'&runid&'" '); index j:= dblabels(i); var a:= dbtable(i,j); a[@i=1, @j=1] 56,64,1 48,12 2,732,65,516,589 39325,65535,39321 runid Describes the runs of the defined variable. This should be made a function. var_run_info(Enter_variable) 288,84,1 48,12 2,136,146,1111,285,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] (vident:text) This function checks for the newest result (according to run_id) of the variable. The function is used if the user does not define the run_id as an optional parameter in functions Read_mean and Read_sample. PARAMETERS: * Vident: the Ident of the variable in the Opasnet Base. var a:= ' SELECT Var.Ident, Var.Name, Var.Unit, Run.Ident AS Runident, Act.When, Act.Who, Run.Name as Method FROM Obj as Var, Obj as Run, Cell, Objinfo AS Act WHERE Var.Ident = '&chr(39)&vident&chr(39)&' AND Var.id = Cell.Obj_id_v AND Run.id = Cell.Obj_id_r AND Run.id = Act.id GROUP BY Var.id, Run.id '; index i:= DBquery(Odbc,a); index j:= dblabels(i); dbtable(i,j) 56,40,1 48,13 2,678,59,476,566 39325,65535,39321 vident Use these functions to retireve data from the Opasnet base: * Newest_run: finds the newest run of the object. * Var_run_info: Finds the run information of the object. * Read_mean: Reads the means of each cell. * Get_mean * Get_sample: Reads the whole sample. Note! These should be updated when we get experience about what we actually want out. 280,285,-1 168,101 (a) Changes an integer of any length to a text value. This bypasses the number formatting problem that tends to convert e.g. 93341 to '93.34K'. If the number is not integer, up to three digits after the decimal point will be taken as well. a&'' {for y[]:= a do ( if istext(y) then y else ( var x:= 1; var b:= ''; var c:= if y<1 then 1 else floor(logten(y))+1; while x<= c do ( b:= (y-floor(y/10)*10)&b; y:= floor(y/10); x:= x+1); b) )} 56,248,1 48,12 2,102,90,476,371 a 2,F,4,14,0,0,4,0,$,0,"ABBREV",0 ktluser 8. Decta 2008 3:01 48,24 56,712,1 48,24 1,30,113,495,453,17 (a; file:texttype) a:= '"'&a&'"'; a:= jointext(a,a.j,';'); Writetextfile('c:\temp\'&file, a) 168,368,1 48,13 2,44,303,476,224 a,file 2,F,4,14,0,0,4,0,$,0,"ABBREV",0 (a; x:optional = 1; e, f:optional=0) 1) Size(h) is size(a.j)-2 because j contains 'Result' and 'SD'. 2) Only the deterministic information about variables are considered (therefore mean). Makes a 2D table of the locres info. 3) Makes a table with fields required by the Loccell and Cell tables. 4) Reduces one dimension by expanding the length from the length of Cell to that of Loccell. index j:= ['id', 'Location', 'Cell_id', 'Loc_id', 'Obj_id_v', 'Obj_id_r', 'Mean', 'SD', 'N']; index h:= a.j[@.j=1..size(a.j)-2]; index i:= 1..size(a.i)*size(h); var c:= Objects[@.i=x]; a:= array(j,[ i[@i=@a.i+size(a.i)*(@h-1)]+e, a[.j=h]&'', a.i+f, h, c[.j='Ident'], '', a[.j='Result'], a[.j='SD'], if c[.j='Probabilistic?']=1 then samplesize else 0]); concatrows(a,h,a.i,i) 400,280,1 48,13 2,627,78,556,561 a,x,e,f (a: prob; probabilistic; e, f: optional=0) index runn:= if Probabilistic=1 then copyindex(run) else [0]; index i:= (1..size(max(a.i,run))*size(runn))+f; a:= if Probabilistic=1 then a[run=runn] else (if runn=0 then a else a); a:= a[.j='Result']; index j:= ['id','Cell_id','Obs','Result','Restext']; a:= array(j,[0, a.i+e, runn, (if istext(a) then 0 else a) , (if istext(a) then a else 0)]); a:= concatrows(a,a.i,runn, i); a:= if j='id' then i else a 400,256,1 48,13 2,687,174,476,526 a,probabilistic,e,f (a) var b:= [0]; var c:= [0]; var e:= [0]; var f:= [0]; var x:= 1; while x<= size(a.j)-1 do ( var h:= a[@.j=x]; var d:= h[.i=unique(h,h.i)]; b:= concat(b,d); c:= concat(c,(if d=0 then slice(a.j,x) else slice(a.j,x))); e:= concat(e,1..size(d)); x:= x+1); index i:= 1..size(b)-1; index j:= ['id','Obj_id_i', 'Location', 'Roww', 'Description']; array(j,[i, slice(c,i+1), slice(b,i+1)&'', slice(e,i+1), '']); 400,232,1 48,12 2,671,164,503,486 a This library contains functions to make various instances of concatenation more convenient. Concat3 thru Concat10 are generalizations of the built-in Concat function which concatenate from 3 to 10 arrays in a single call (while the built-in Concat concatenates two arrays). ConcatRows concatenates all the rows of a single array. David Kendall & Lonnie Chrisman Mon, Jan 26, 2004 8:49 AM Lonnie Wed, Sep 05, 2007 3:23 PM 48,24 184,328,1 68,20 1,0,0,1,1,1,0,0,0,0 1,50,200,488,454,23 (A1, A2, A3: ArrayType; I1, I2, I3, J: IndexType ) Concatenates three arrays, A1, A2, and A3. I1, I2, and I3 are the indexes that are joined; J is the index of the new array; J usually is the concatenation of I1, I2, and I3 Index I12 := Concat(I1,I2); Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, J ) 88,64,1 48,26 2,56,56,986,596 A1,A2,A3,I1,I2,I3,J (A1, A2, A3, A4: ArrayType; I1, I2, I3, I4, J: IndexType ) Concatenates four arrays, A1, A2, A3, and A4. I1, I2, I3, and I4 are the indexes that are joined; J is the index of the new array; J usually is the concatenation of I1, I2, I3, and I4. Index I12 := Concat(I1,I2); Index I123:= Concat(I12, I3); Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, J); 192,64,1 48,24 2,30,30,986,596 A1,A2,A3,A4,I1,I2,I3,I4,J 0 (A1, A2, A3, A4, A5, A6, A7, A8, A9: ArrayType; I1, I2, I3, I4, I5, I6, I7, I8, I9, J: IndexType) Concatenates nine arrays, A1, ..., A9. I1, ..., I9 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I9. Index I12 := Concat(I1,I2); Index I123 := Concat(I12, I3); Index I1234 := Concat(I123, I4); Index I12345 := Concat(I1234, I5); Index I123456 := Concat(I12345, I6); Index I1234567 := Concat(I123456, I7); Index I12345678 := Concat(I1234567, I8); Concat( Concat( Concat( Concat( Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, I12345), A6, I12345, I6, I123456), A7, I123456, I7, I1234567), A8, I1234567, I8, I12345678), A9, I12345678, I9, J); 88,232,1 48,24 2,27,120,469,638 A1,A2,A3,A4,A5,A6,A7,A8,A9,I1,I2,I3,I4,I5,I6,I7,I8,I9,J 0 (A1, A2, A3, A4, A5: ArrayType; I1, I2, I3, I4, I5, J: IndexType ) Concatenates five arrays, A1, ..., A5. I1, ..., I5 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I5. Index I12 := Concat(I1,I2); Index I123:= Concat(I12, I3); Index I1234 := Concat(I123, I4); Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, J); 88,120,1 48,24 2,160,160,986,596 A1,A2,A3,A4,A5,I1,I2,I3,I4,I5,J (A1, A2, A3, A4, A5, A6: ArrayType; I1, I2, I3, I4, I5, I6, J: IndexType ) Concatenates six arrays, A1, ..., A6. I1, ..., I6 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I6. Index I12 := Concat(I1,I2); Index I123:= Concat(I12, I3); Index I1234 := Concat(I123, I4); Index I12345 := Concat(I1234, I5); Concat( Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, I12345), A6, I12345, I6, J); 192,120,1 48,24 2,644,94,602,712 A1,A2,A3,A4,A5,A6,I1,I2,I3,I4,I5,I6,J 0 (A1, A2, A3, A4, A5, A6, A7: ArrayType; I1, I2, I3, I4, I5, I6, I7, J: IndexType ) Concatenates seven arrays, A1, ..., A7. I1, ..., I7 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I7. Index I12 := Concat(I1,I2); Index I123:= Concat(I12, I3); Index I1234 := Concat(I123, I4); Index I12345 := Concat(I1234, I5); Index I123456 := Concat(I12345, I6); Concat( Concat( Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, I12345), A6, I12345, I6, I123456), A7, I123456, I7, J); 88,176,1 48,24 2,580,98,551,565 A1,A2,A3,A4,A5,A6,A7,I1,I2,I3,I4,I5,I6,I7,J (A1, A2, A3, A4, A5, A6, A7, A8: ArrayType; I1, I2, I3, I4, I5, I6, I7, I8, J: IndexType ) Concatenates eight arrays, A1, ..., A8. I1, ..., I8 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I8. Index I12 := Concat(I1,I2); Index I123:= Concat(I12, I3); Index I1234 := Concat(I123, I4); Index I12345 := Concat(I1234, I5); Index I123456 := Concat(I12345, I6); Index I1234567 := Concat(I123456, I7); Concat( Concat( Concat( Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, I12345), A6, I12345, I6, I123456), A7, I123456, I7, I1234567), A8, I1234567, I8, J); 192,176,1 48,24 2,12,98,561,737 A1,A2,A3,A4,A5,A6,A7,A8,I1,I2,I3,I4,I5,I6,I7,I8,J 0 (A1, A2, A3, A4, A5, A6, A7, A8, A9, A10: ArrayType; I1, I2, I3, I4, I5, I6, I7, I8, I9, I10, J: IndexType) Concatenates ten arrays, A1, ..., A10. I1, ..., I10 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I10. Index I12 := Concat(I1,I2); Index I123 := Concat(I12, I3); Index I1234 := Concat(I123, I4); Index I12345 := Concat(I1234, I5); Index I123456 := Concat(I12345, I6); Index I1234567 := Concat(I123456, I7); Index I12345678 := Concat(I1234567, I8); Index I123456789 := Concat(I12345678, I9); Concat( Concat( Concat( Concat( Concat( Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, I12345), A6, I12345, I6, I123456), A7, I123456, I7, I1234567), A8, I1234567, I8, I12345678), A9, I12345678, I9, I123456789), A10, I123456789, I10, J); 192,232,1 48,24 2,542,93,632,744 A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,I1,I2,I3,I4,I5,I6,I7,I8,I9,I10,J 0 (A : ArrayType ; RowIndex,ColIndex,ResultIndex : IndexType) Takes an array, A indexed by RowIndex & ColIndex, and concatenates each row, henceforth flattening the array by one dimension. The result is indexed by ResultIndex, which must be an index with size(RowIndex) * size(ColIndex) elements. index L := [ identifier of RowIndex, identifier of ColIndex, "val"]; slice(Mdarraytotable(A,ResultIndex,L),L,3) 320,64,1 64,24 2,499,85,478,348 A,RowIndex,ColIndex,ResultIndex Lonnie Thu, Sep 11, 1997 2:15 PM Lonnie Tue, Feb 05, 2008 10:03 AM 48,24 56,328,1 52,20 1,1,1,1,1,1,0,0,0,0 1,20,272,499,462,17 Arial, 13 (A:ArrayType;I:IndexType;L:IndexType;row:IndexType;dbTableName) Generates the SQL "INSERT INTO" statement for one line of table A. A is a 2-D table indexed by rows I and columns L. L's domain serves as the column names in the database table. dbTableName is the name of the table in the database. The result begins with two semi-colons, since it will be used with an SQL statement preceeding it. 29.8.2008 Jouni Tuomisto I added the parameter IGNORE because it ignores rows that would cause duplicate-key violations. This way, there is no need to check for e.g. existing locations of new indices. 6.1.2009 Jouni Tuomisto I changed the A[I=row] to A[@I=@row] because the original function does not work correctly, if there are non-unique rows in the index. (';;INSERT IGNORE INTO ' & dbTableName & '(' & JoinText(L,L,',') & ') VALUES (' & Vallist(A[@I=@row],L)) & ') ' 184,32,1 52,24 2,591,203,487,469 A,I,L,row,dbTableName (V:ArrayType;I:IndexType) Takes a list of values, and returns a string which the concatenation of each value, separated by commas, and with each value quoted. JoinText( '''' & V & '''', I, ',') 72,32,0 52,24 2,642,360,476,224 V,I 1,F,4,14,0,0 (Tabl:ArrayType;RowIndex:IndexType;LabelIndex:IndexType;dbTableName) Returns the SQL that will write the table to the database table. This can be used as the second argument to DBWrite. This SQL statement replaces the entire contents of an existing table with the new data. 'DELETE FROM '& Dbtablename & JoinText(Insertrecsql(Tabl, Rowindex, Labelindex, Rowindex, Dbtablename),RowIndex) 328,32,1 88,24 2,728,341,510,476 Tabl,RowIndex,LabelIndex,dbTableName (Tabl:ArrayType;RowIndex:IndexType;LabelIndex:IndexType;dbTableName) Returns the SQL that will write the table to the database table. This can be used as the second argument to DBWrite. This SQL statement replaces the entire contents of an existing table with the new data. JoinText(Insertrecsql(Tabl, Rowindex, Labelindex, Rowindex, Dbtablename),RowIndex) 328,88,1 88,24 2,559,127,510,476 Tabl,RowIndex,LabelIndex,dbTableName (table:texttype) Brings the largest id number from the table defined in the parameter. index i:= DBquery(odbc,' SELECT MAX(id) AS id FROM '&table&' '); index j:= dblabels(i); max(max(DBTable(i, j ),i),j) 56,272,1 48,12 2,102,90,476,331 39325,65535,39321 table List of such tables in Opasnet Base that are being written to by this module. ['Obj','Cell','Loc','Loccell','Sett','Item','Res'] 280,256,1 48,13 2,15,594,158,227,0,MIDM [] ['Obj','Cell','Loc','Loccell','Sett','Item','Res'] The largest id values for the selected Opasnet Base tables. The table is updated by pressing the R_cardinals button. Table(Table1)( 758,443.096K,13.686K,1.535012M,47,146,1.432167M ) 280,232,1 48,12 2,634,394,476,332 2,193,270,416,303,0,MIDM 2,87,329,416,303,0,MIDM 39325,65535,39321 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [] (in, table; cond:texttype) This function gets an id from a table. in: the property for which the id is needed. In MUST be unique in cond and it must contain index i. table: the table from where the id is brought. The table MUST have .j as the column index, .i as the row index, and a column named 'id'. cond: the name of the field that is compared with in. Cond must be text. index L:= in[.i=unique(in, in.i)]; var a:= if (L&' ') = (table[.j=cond]&' ') then table[.j='id'] else 0; a:= textify(sum(a, table.i)); a[.L=in] 56,248,1 48,12 2,636,101,494,519 in,table,cond [] (type) Finds the objects that are of the object type "type" (the only parameter of this function). Based on the information in Objects1. var a:= if Objects1[.j='Typ_id']=type then 1 else 0; Objects1[Object_all=subset(a),.j='id'] 56,224,1 48,12 2,551,191,476,344 type (var, table) For Lumina AWP use the following should be used: 'Driver={MySQL ODBC 3.51 Driver};Server=193.167.179.97;Database=opasnet_base;User=resultwriter; Password=;Option=3' For internal THL use the following should be used: 'Driver={MySQL ODBC 5.1 Driver};Server=10.66.10.102;Database=opasnet_base;User=resultwriter; Password='&writerpsswd&';Option=3' if size(var)>0 then dbwrite((if platform = 'Lumina AWP' then 'Driver={MySQL ODBC 3.51 Driver};Server=193.167.179.97' else 'Driver={MySQL ODBC 5.1 Driver};Server=10.66.10.102')&';Database=opasnet_base;User=resultwriter; Password='&writerpsswd&';Option=3' , appendtablesql(var,var.i, var.j, table&' ')) 56,296,1 48,12 2,776,65,476,457 var,table For Lumina AWP use the following should be used: 'Driver={MySQL ODBC 3.51 Driver};Server=193.167.179.97;Database=opasnet_base;User=resultwriter; Password=;Option=3' For internal THL use the following should be used: 'Driver={MySQL ODBC 5.1 Driver};Server=10.66.10.102;Database=opasnet_base;User=resultwriter; Password='&writerpsswd&';Option=3' var a:= if platform='Lumina AWP' then 'Driver={MySQL ODBC 3.51 Driver};Server=193.167.179.97' else 'Driver={MySQL ODBC 5.1 Driver};Server=10.66.10.102'; a&';Database=opasnet_base;User=resultwriter; Password='&writerpsswd&';Option=3' 168,232,1 48,12 1,1,0,1,1,1,0,,0, 2,102,90,495,346 2,168,178,833,303,0,MIDM [] The username for Opasnet wiki 'Add username' 168,161,1 48,22 1,1,1,1,1,1,0,0,0,0 [Formnode Username1] 52425,39321,65535 The user's password for Opasnet wiki. 'Add password' 168,200,1 48,22 1,1,1,1,1,1,0,0,0,0 [Formnode Password1] 52425,39321,65535 Contains the parameters for the open database connectivity (ODBC). For Lumina AWP use the following should be used: 'Driver={MySQL ODBC 3.51 Driver};Server=193.167.179.97;Database=opasnet_base;User=result_reader; Password=ora4ever;Option=3' For THL internal use the following should be used: 'Driver={MySQL ODBC 5.1 Driver};Server=10.66.10.102;Database=opasnet_base;User=result_reader; Password=ora4ever;Option=3' var a:= if platform='Lumina AWP' then 'Driver={MySQL ODBC 3.51 Driver};Server=193.167.179.97' else 'Driver={MySQL ODBC 5.1 Driver};Server=10.66.10.102'; a&';Database=opasnet_base;User=result_reader; Password=ora4ever;Option=3' 168,128,1 48,12 1,1,0,1,1,1,0,,0, 2,102,90,508,420 2,56,66,918,303,0,MIDM index i:= copyindex(D_i); index j:= copyindex(D_j); Dim1[d_i=i, d_j=j] 400,160,1 48,13 1,1,0,1,1,1,0,0,0,0 2,89,98,476,224 2,635,328,556,489,0,MIDM 19661,54073,65535 [D_i,D_j] [Sys_localindex('J'),Sys_localindex('I')] index i:= copyindex(I_i); index j:= copyindex(I_j); Ind1[I_i=i, I_j=j] 400,184,1 48,13 1,1,0,1,1,1,0,0,0,0 2,380,47,476,296 2,490,110,649,655,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] index i:= copyindex(L_i); index j:= copyindex(L_j); Loc1[L_i=i, L_j=j] 400,96,1 48,13 1,1,0,1,1,1,0,0,0,0 2,370,45,476,445 2,43,42,1147,516,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. index i:= copyindex(O_i); index j:= copyindex(O_j); Obj2[O_i=i, O_j=j] 400,48,1 48,13 1,1,0,1,1,1,0,0,0,0 2,378,21,493,501 2,21,103,977,421,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] [] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] Standard versions 400,112,-1 72,100 1,0,0,1,0,1,0,,0, [0] 168,24,1 48,12 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22] ['id','Ident','Name'] 168,48,1 48,12 ['id','Ident','Name'] [0] 168,72,1 48,12 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34] ['id','Iident','Iname','Did','Dident','Dname'] 168,96,1 48,12 ['id','Iident','Iname','Did','Dident','Dname'] [0] 56,120,1 48,12 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['id','Std_id','Obj_id_i','Location','Roww','Description','id','Ident','Name','Unit','Objtype_id','Page','Wiki_id'] 56,144,1 48,12 ['id','Std_id','Obj_id_i','Location','Roww','Description','id','Ident','Name','Unit','Objtype_id','Page','Wiki_id'] [0] 56,24,1 48,13 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['id','Ident','Name','Unit','Objtype_id','Page','Wiki_id'] 56,48,1 48,13 ['id','Ident','Name','Unit','Objtype_id','Page','Wiki_id'] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. index i:= copyindex(S_i); index j:= copyindex(S_j); Sett1[S_i=i, S_j=j] 400,72,1 48,13 1,1,0,1,1,1,0,0,0,0 2,378,21,493,501 2,227,134,319,515,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. index i:= copyindex(It_i); index j:= copyindex(It_j); Item1[it_i=i, it_j=j] 400,120,1 48,13 1,1,0,1,1,1,0,0,0,0 2,378,21,493,501 2,298,216,382,519,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] [0] 56,168,1 48,13 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35] ['id','Sett_id','Obj_id','Fail'] 56,192,1 48,13 ['id','Sett_id','Obj_id','Fail'] [0] 56,72,1 48,13 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28] ['id','Obj_id','Settype_id'] 56,96,1 48,13 ['id','Obj_id','Settype_id'] 0 280,160,1 48,13 1,1,1,1,1,1,0,0,0,0 2,89,98,476,224 2,604,56,556,489,0,MIDM 39325,65535,39321 [D_i,D_j] [D_j,D_i] 0 280,184,1 48,13 1,1,1,1,1,1,0,0,0,0 2,380,47,476,296 2,232,242,874,303,0,MIDM 2,12,22,876,493,0,MIDM 39325,65535,39321 [I_j,I_i] [I_j,I_i] 0 280,96,1 48,13 1,1,1,1,1,1,0,0,0,0 2,370,45,476,445 2,518,523,725,303,0,MIDM 2,404,34,750,516,0,MIDM 39325,65535,39321 [L_j,L_i] [L_j,L_i] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. 0 280,48,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,152,162,1057,343,0,MIDM 2,573,21,700,421,0,MIDM 39325,65535,39321 [O_j,O_i] [O_j,O_i] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. 0 280,72,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,700,421,0,MIDM 39325,65535,39321 [S_j,S_i] [S_i,S_j] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. 0 280,120,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,700,421,0,MIDM 39325,65535,39321 [It_j,It_i] [It_i,It_j] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] (var, table) if size(var)>0 then appendtablesql(var,var.i, var.j, table&' ') 56,368,1 48,13 2,284,58,476,224 var,table '' 168,280,0 52,12 1,1,1,1,1,1,0,0,0,0 2,163,375,476,224 [Formnode Writerpsswd1] 52425,39321,65535 Choice(Self,2,False,1) 320,328,1 48,12 [Formnode Platform1] 52425,39321,65535 ['Lumina AWP','THL computer'] study_ident; n_indices; n_variables 56,400,1 48,12 1,1,1,1,1,1,0,0,0,0 320,376,1 48,24 2,588,98,476,224 0 176,44,1 160,12 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Platform 0 176,68,1 160,12 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Writerpsswd 0 176,237,1 160,13 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Data_table_name 2) Tell the identifier of the node that contains the observations. This is an alternative to filling in 'Observations'. The node is used if it is non-empty. The node must have index .j for columns and .i for rows. 320,212,-1 304,44 1,0,0,1,0,1,0,,0, 0 176,116,1 160,12 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Parameter_name 0 176,92,1 160,12 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Append_to_run 392,572,1 48,20 2,31,25,825,451 1 120,564,1 48,12 Upload_data Advanced options for providing upload data: 176,156,-1 160,12 1,0,0,1,0,1,0,,0, 65535,65532,19661 'Analytica model' for upload option 3. 480,20,-1 144,12 Selects the ODBC version. 480,44,-1 144,12 Not needed for an encrypted version. 480,68,-1 144,12 Add data to an existing upload (or run). 480,92,-1 144,12 Name for the dependent variable columns. 480,124,-1 144,20 Advanced options for uploading data: 176,460,-1 160,12 1,0,0,1,0,1,0,,0, 65535,65532,19661 A) The default: Upload all data directly to Opasnet Base. This is the same as on the first page. 124,536,-1 108,64 1,0,0,1,0,1,0,,0, B) For very large variables: Upload only the object and location information. Create csv files of other data to c:\temp\ and upload them separately (you need a direct access to the Opasnet Base). 440,536,-1 184,64 1,0,0,1,0,1,0,,0, Upload an Analytica model. This functionality does not work with the web version. It requires that you have Analytica Enterprise and an editable version of Opasnet Base Connection. 152,736,-1 144,80 1,0,0,1,0,1,0,,0, 2,693,146,476,224 432,775,1 48,31 2,422,44,825,430 For advanced users: you may upload whole models, or non-public data that can only be seen by people with a special permission. 276,628,-1 268,20 In case you want to upload data in a way that it is not visible without a password, press this button instead of "Upload data". 424,736,-1 120,80 1,0,0,1,0,1,0,,0, 2,693,146,476,224 0 272,440,1 152,12 1,0,0,1,0,0,0,158,0,1 52425,39321,65535 Observations2 Copy your data table into Observations. NOTE! 1) You must have field names in the first row. 2) Paste between 'exclamation marks'. 272,390,-1 152,38