0 1 1 2 0 0 ktluser 3. Augta 2008 18:31 ktluser 13. Septa 2008 1:36 48,24 1,16,13,668,392,17 Arial, 15 0,Model Rdbreader,2,2,0,1,C:\Documents and Settings\ktluser\Local Settings\Temp\RDB_reader-3.ANA ['var_name','var_unit','result_id','result','sample','dim_name','location','run_method','run_id'] 304,128,1 48,12 [Variable Rdb_variable2] ['var_name','var_unit','result_id','result','sample','dim_name','location','run_method','run_id'] 1..1080 304,152,1 48,12 [Variable Rdb_variable2] 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','Analytica 4.1.0.9, 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) 304,96,1 48,24 2,72,82,1023,486,0,MIDM 2,33,352,1162,304,0,MIDM 65535,52427,65534 [In3,In4] [In3,In4] [Variable Rdb_variable2] [0,1,1,0] Stakeholder ['Passenger','Society'] 584,184,1 48,12 [Sys_localindex('I'),Create_these_indices] ['item 1','item 2'] Transport mode ['Car','Composite'] 584,208,1 48,16 ['item 1','item 2'] Cost type ['Vehicle','Driver','Driving','Parking','Parking land','Emissions','Time','Accidents','Ticket'] 584,240,1 48,12 ['item 1','item 2','item 3','item 4','item 5','item 6','item 7','item 8','item 9'] ODBC 'Driver={MySQL ODBC 5.1 Driver};Server=10.66.10.102;Database=resultdb;User=result_reader; Password=ora4ever;Option=3' 64,24,1 48,12 (var_name:text, run_id:optional) Readdata Reads the data about the var_name variable from the result database. Uses the run_id run if specified; otherwise uses the newest run of that variable. if isnotspecified(run_id) then run_id:= newestrun(var_name); index i:= DBquery(odbc,'SELECT Variable.var_name, var_unit, result, sample, dim_name, Ind_name, location FROM `Variable` , Result, Loc_of_result, Location, Dimension, Run_list, Run WHERE Variable.var_name = "'&Var_name&'" AND Run.run_id = '&Run_id&' AND Variable.var_id = Loc_of_result.var_id AND Loc_of_result.result_id = Result.result_id AND Loc_of_result.loc_id = Location.loc_id AND Location.dim_id = Dimension.dim_id AND Result.result_id = Run_list.result_id AND Run_list.run_id = Run.run_id'); index j:= dblabels(i); dbtable(i,j) 64,56,1 48,16 2,40,206,516,428 39325,65535,39321 var_name,run_id (var_name:text) Newestrun index i:= DBquery(odbc,'SELECT Run_id FROM `Variable` , Loc_of_result, Run_list WHERE Variable.var_name = "'&Var_name&'" AND Variable.var_id = Loc_of_result.var_id AND Loc_of_result.result_id = Run_list.result_id'); index j:= dblabels(i); max(max(dbtable(i,j),i),j) 64,88,1 48,16 2,687,222,476,436 39325,65535,39321 var_name 3D data var data:= rdb_test_data; var a:= data[in3='dim_name']; index j:= a[in4=unique(a,in4)]; a:= data[in3='location']; index i:= a[in4=unique(a,in4)]; a:= data[in3='result_id']; index result_id:= a[in4=unique(a,in4)]; var x:= 1; a:= null; while x<= size(in4) do ( var b:= data[@in4=x]; a:= if i = b[in3='location'] and j = b[in3='dim_name'] and result_id = b[in3='result_id'] then b[in3='result_id'] else a; x:= x+1); var c:= result_id; x:= 1; while x<=size(j) do ( c:= if c= a[i=evaluate(j[@j=x]), @j=x] then result_id else 0; x:=x+1); c:= sum(c,result_id); a:= Rdb_test_data[in3='sample']; index sample:= a[in4=unique(a,in4)]; x:= 1; a:= null; while x<= size(in4) do ( var b:= data[@in4=x]; a:= if c = b[in3='result_id'] and sample = b[in3='sample'] then b[in3='result'] else a; x:= x+1); a[sample=run] 304,216,1 48,24 2,660,26,476,622 2,708,29,519,519,0,MEAN [Transport_mode,Cost_type] [0,1,1,0] ['dim_name','location'] [Stakeholder,2,Sys_localindex('SAMPLE'),5,Cost_type,1,Transport_mode,2] Old parts 576,40,1 48,24 1,0,1,1,1,1,0,,0, Concatenation UDFs 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 48,24 116,40,1 68,24 1,0,0,1,1,1,0,0,0,0 1,39,36,798,452,23 (A1, A2, A3: ArrayType; I1, I2, I3, J: IndexType ) Concat3 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 ) Concat4 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) Concat9 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 ) Concat5 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 ) Concat6 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 ) Concat7 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 ) Concat8 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) Concat10 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) ConcatRows (A,I,J,K) 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 2,30,320,478,260 A,RowIndex,ColIndex,ResultIndex Create these indices index i:= ['dim_name','location']; var a:= Rdb_test_data[in3=i]; index j:= unique(a,in4); a:= a[in4=j]; index ind_name:= a[j=unique(a[i='dim_name'],j), i='dim_name']; a:= if ind_name=a[i='dim_name'] then a[i='location']; 96,55,1 48,31 2,112,416,476,224 2,708,29,416,333,0,MIDM [Sys_localindex('IND_NAME'),Sys_localindex('J')] ['dim_name','location'] RDB variable NOTE! The indexes that are defined by the dimensions and locations of the variable must be defined before running this node. Also the Sample (the size of the Run index) must be set to a right value, preferably to that found in the RDB for this variable. If Run is larger than the sample size in the RDB, the remaining cells are replaced by null; if it is smaller, some data from the RDB is lost. This node divides into 5 sections. a is the local variable that gradually develops into what we want. d is a temporary variable mainly for making new indices. c is a local variable that is needed because the definition of a has two branches that divide and then merge again. 1) Defines an index that has all the result_id's that exist for the variable in question. 2) Makes a table that has all dimensions and locations for each result. However, the problem is that each result is listed as many times as there are dimensions. What we want is one row for each result. 3) Reduces the number of rows into the right amount, i.e. one row for each result_id. 4) However, now the columns Value and Run are incorrect, and the right values must be picked from elsewhere. This is done in the fourth section. 5) Finally makes the multidimensional array. The Result_id column is dropped before that, because it is not needed any more. var e := Rdb_test_data[in3='result_id']; index res_id:= e[in4=unique(e,in4)]; e := Rdb_test_data[in3='dim_name']; e:= if e=dims then dims.indname else ''; e:= jointext(e,e.indname); var d:= e[in4=unique(e,in4)]; index i:= concat(d,['Result_id','Run','Value']); var a:= if e=i then Rdb_test_data[in3='location'] else ''; a:= if i='Value' then Rdb_test_data[in3='result'] else a; a:= if i='Run' then Rdb_test_data[in3='sample'] else a; a:= if i='Result_id' then Rdb_test_data[in3='result_id'] else a; var c:= a[.i=concat(d,['Result_id'])]; index l:= unique(c,in4); c:= a[in4=l]; c:= if c[.i='Result_id']=res_id then c else ''; c:= jointext(c,l); c:= if c.i= 'Result_id' then res_id else c; index m:= unique(a[.i=['Result_id','Run']],in4); a:= a[in4=m]; c:= c[res_id=a[.i='Result_id']]; a:= if a.i='Run' or a.i='Value' then a else c; index n:= concat(d,['Run','Value']); a:= a[.i=n]; mdtable(a,m,n,,'average')} 96,48,1 48,24 2,801,7,476,652 2,594,17,595,303,0,MIDM [In4,Sys_localindex('I')] [Index In3, Index In4, Variable Rdb_test_data, Variable Dims] ['var_name'] [Run,1] Dims index i:= ['dim_name','location']; var a:= Rdb_test_data[in3='dim_name']; index b:= unique(a,in4); index indname:= 'Index'&(1..size(b)); a:= a[in4=b]; a[@b=@indname] 96,40,1 48,24 2,112,416,476,224 2,817,121,416,333,0,MIDM Table(Nullindex1,Nullindex2)( [Variable Rdb_variable2] ['dim_name','location'] RDB data index in1:= DBquery(odbc,'SELECT Variable.var_name, var_unit, result, sample, dim_name, Ind_name, location FROM `Variable` , Result, Loc_of_result, Location, Dimension, Run_list, Run WHERE Variable.var_name = "'&Var_name&'" AND Run.run_id = '&Run_id&' AND Variable.var_id = Loc_of_result.var_id AND Loc_of_result.result_id = Result.result_id AND Loc_of_result.loc_id = Location.loc_id AND Location.dim_id = Dimension.dim_id AND Loc_of_result.result_id = Run_list.result_id AND Run_list.run_id = Run.run_id'); index in2:= dblabels(In1); dbtable(in1,in2) 96,40,1 48,16 2,740,43,476,436 2,88,98,583,568,0,MIDM 39325,65535,39321 [Sys_localindex('IN2'),Sys_localindex('IN1')] Var_name 'Bw1' 96,37,1 48,13 1,1,1,1,1,1,0,0,0,0 52425,39321,65535 Run_id 9 96,61,1 48,13 1,1,1,1,1,1,0,0,0,0 52425,39321,65535 RDB variable NOTE! The indexes that are defined by the dimensions and locations of the variable must be defined before running this node. Also the Sample (the size of the Run index) must be set to a right value, preferably to that found in the RDB for this variable. If Run is larger than the sample size in the RDB, the remaining cells are replaced by null; if it is smaller, some data from the RDB is lost. This node divides into 5 sections. a is the local variable that gradually develops into what we want. d is a temporary variable mainly for making new indices. c is a local variable that is needed because the definition of a has two branches that divide and then merge again. 1) Defines an index that has all the result_id's that exist for the variable in question. 2) Makes a table that has all dimensions and locations for each result. However, the problem is that each result is listed as many times as there are dimensions. What we want is one row for each result. 3) Reduces the number of rows into the right amount, i.e. one row for each result_id. 4) However, now the columns Value and Run are incorrect, and the right values must be picked from elsewhere. This is done in the fourth section. 5) Finally makes the multidimensional array. The Result_id column is dropped before that, because it is not needed any more. var e := Rdb_test_data[in3='result_id']; index res_id:= e[in4=unique(e,in4)]; e := Rdb_test_data[in3='dim_name']; e:= if e=dims then dims.indname else ''; e:= jointext(e,e.indname); var d:= e[in4=unique(e,in4)]; index i:= concat(d,['Result_id','Run','Value']); var a:= if e=i then Rdb_test_data[in3='location'] else ''; a:= if i='Value' then Rdb_test_data[in3='result'] else a; a:= if i='Run' then Rdb_test_data[in3='sample'] else a; a:= if i='Result_id' then Rdb_test_data[in3='result_id'] else a; var c:= a[.i=concat(d,['Result_id'])]; index l:= unique(c,in4); c:= a[in4=l]; c:= if c[.i='Result_id']=res_id then c else ''; c:= jointext(c,l); c:= if c.i= 'Result_id' then res_id else c; index m:= unique(a[.i=['Result_id','Run']],in4); a:= a[in4=m]; c:= c[res_id=a[.i='Result_id']]; a:= if a.i='Run' or a.i='Value' then a else c; index n:= {if min(a[.i='Run'],m)=0 then concat(d,['Value']) else} concat(d,['Run','Value']); a:= a[.i=n]; mdtable(a,m,n,,'average') 96,120,1 48,24 2,743,9,476,652 2,594,17,595,303,0,MIDM [Run] ['var_name'] [Run,1] var a:= Rdb_test_data[in3='dim_name']; index result_id:= a[in4=unique(a,in4)]; result_id 96,48,1 48,24 2,722,29,416,303,0,MIDM [0,2,Null,Null] var a:= Rdb_test_data[in3='result_id']; index result_id:= a[in4=unique(a,in4)]; a:= Rdb_test_data[in3='sample']; index sample:= a[in4=unique(a,in4)]; var x:= 1; a:= null; while x<= size(in4) do ( var b:= Rdb_test_data[@in4=x]; a:= if result_id = b[in3='result_id'] and sample = b[in3='sample'] then b[in3='result'] else a; x:= x+1); a 96,48,1 48,24 2,14,55,416,303,0,MIDM [Sys_localindex('RESULT_ID'),Sys_localindex('SAMPLE')] 3D data var a:= Rdb_test_data[in3='dim_name']; index j:= a[in4=unique(a,in4)]; a:= Rdb_test_data[in3='location']; index i:= a[in4=unique(a,in4)]; a:= Rdb_test_data[in3='sample']; index sample:= a[in4=unique(a,in4)]; a:= Rdb_test_data[in3='result_id']; index result_id:= a[in4=unique(a,in4)]; var x:= 1; a:= null; while x<= size(in4) do ( var b:= Rdb_test_data[@in4=x]; a:= if i = b[in3='location'] and j = b[in3='dim_name'] and sample = b[in3='sample'] and result_id = b[in3='result_id'] then b[in3='result'] else a; x:= x+1); a 136,48,1 48,24 2,112,416,476,224 2,708,29,461,378,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] ['dim_name','location'] [Sys_localindex('SAMPLE'),5,Sys_localindex('RESULT_ID'),14,Sys_localindex('I'),1,Sys_localindex('J'),1] var a:= A3d_data; a[.i=stakeholder] 96,48,1 48,24 2,99,334,824,308,0,MIDM [Sys_localindex('SAMPLE'),Sys_localindex('J')] [Stakeholder,1,Sys_localindex('RESULT_ID'),13,Sys_localindex('J'),1,Sys_localindex('SAMPLE'),1] 3D data var a:= Rdb_test_data[in3='dim_name']; index j:= a[in4=unique(a,in4)]; a:= Rdb_test_data[in3='location']; index i:= a[in4=unique(a,in4)]; a:= Rdb_test_data[in3='result_id']; index result_id:= a[in4=unique(a,in4)]; var x:= 1; a:= null; while x<= size(in4) do ( var b:= Rdb_test_data[@in4=x]; a:= if i = b[in3='location'] and j = b[in3='dim_name'] and result_id = b[in3='result_id'] then b[in3='result_id'] else a; x:= x+1); var c:= a[i=evaluate(j[@j=1]), @j=1]; var d:= a[i=evaluate(j[@j=2]), @j=2]; var e:= a[i=evaluate(j[@j=3]), @j=3]; a:= if c=d and d=e and e=result_id then result_id else 0; sum(a,result_id) 96,136,1 48,24 2,455,202,476,418 2,708,29,519,519,0,MIDM [Stakeholder,Cost_type] ['dim_name','location'] [Transport_mode,2,Cost_type,1,Stakeholder,1] index j:= ['result_id','dim_name','location']; var a:= Rdb_test_data[.in3=j]; a:= a[in4=unique(a,in4)]; index i:= 1..size(a)/size(j); a:= for y:= j do (slice(a[j=y],i )); var c:= null; var x:= 1; while x<= size(a)/size(j) do ( var b:= slice(a,i,x); c:= if evaluate(b[j='dim_name']) = b[j='location'] then b[j='result_id'] else c; x:= x+1); c 96,48,1 48,24 2,714,197,416,303,0,MIDM [Transport_mode,Cost_type] [1,11,21,31,41,51,61,71,81,91,101,111,121,131,141,151,161,171,181,191,201,211,221,231,241,251,261,271,281,291,301,311,321,331,341,351,361,371,381,391,401,411,421,431,441,451,461,471,481,491,501,511,521,531,541,551,561,571,581,591,601,611,621,631,641,651,661,671,681,691,701,711,721,731,741,751,761,771,781,791,801,811,821,831,841,851,861,871,881,891,901,911,921,931,941,951,961,971,981,991,1001,1011,1021,1031,1041,1051,1061,1071] [Stakeholder,2,Cost_type,1,Transport_mode,1] index j:= ['Stakeholder','Cost_type']; evaluate(j[@j=1]) 96,48,1 48,24 3D data var a:= Rdb_test_data[in3='dim_name']; index j:= a[in4=unique(a,in4)]; a:= Rdb_test_data[in3='location']; index i:= a[in4=unique(a,in4)]; a:= Rdb_test_data[in3='result_id']; index result_id:= a[in4=unique(a,in4)]; var x:= 1; a:= null; while x<= size(in4) do ( var b:= Rdb_test_data[@in4=x]; a:= if i = b[in3='location'] and j = b[in3='dim_name'] and result_id = b[in3='result_id'] then b[in3='result_id'] else a; x:= x+1); var c:= result_id; x:= 1; while x<=size(j) do ( c:= if c= a[i=evaluate(j[@j=x]), @j=x] then result_id else 0; x:=x+1); sum(c,result_id) 96,48,1 48,24 2,660,26,476,622 2,708,29,519,519,0,MIDM [Transport_mode,Cost_type] ['dim_name','location'] [Transport_mode,2,Cost_type,1,Stakeholder,1] (var_name:text; run_id:optional) RDB to var Brings the data from the result database and transforms it into variables of the correct form. Note that the syntax uses "dim_name" although the new version of the RDB uses Ind_name. NOTE! All necessary indices must be created before running this function. 1) Brings the data and makes indices for index list, locations, and result_id's. 2) Makes an array containing result_id, indexed by all indices and all locations. 3) Makes an array containing result_id, indexed by the indices of the variable itself. 4) Brings the results into the structure created in 3). Makes the sample fo along the index Run. var data:= evaluate(var_name) {readdata(var_name, run_id)}; var a:= data[in3='dim_name']; index j:= a[in4=unique(a,in4)]; a:= data[in3='location']; index i:= a[in4=unique(a,in4)]; a:= data[in3='result_id']; index result_id:= a[in4=unique(a,in4)]; var x:= 1; a:= null; while x<= size(in4) do ( var b:= data[@in4=x]; a:= if i = b[in3='location'] and j = b[in3='dim_name'] and result_id = b[in3='result_id'] then b[in3='result_id'] else a; x:= x+1); var c:= result_id; x:= 1; while x<=size(j) do ( c:= if c= a[i=evaluate(j[@j=x]), @j=x] then result_id else 0; x:=x+1); c:= sum(c,result_id); a:= Rdb_test_data[in3='sample']; index sample:= a[in4=unique(a,in4)]; x:= 1; a:= null; while x<= size(in4) do ( var b:= data[@in4=x]; a:= if c = b[in3='result_id'] and sample = b[in3='sample'] then b[in3='result'] else a; x:= x+1); if max(sample)>0 then a[sample=run] else a 64,120,1 48,16 2,654,102,476,501 var_name,run_id (var_name:text; run_id:optional) Do first if isnotspecified(run_id) then run_id:= newestrun(var_name); var data:= evaluate(var_name) {readdata(var_name, run_id)}; index i:= ['dim_name','location']; var a:= data[in3=i]; index j:= unique(a,in4); a:= a[in4=j]; index ind_name:= a[j=unique(a[i='dim_name'],j), i='dim_name']; a:= if ind_name=a[i='dim_name'] then a[i='location']; index b:= ['Sample size']; var d:= array(b,[max(data[in3='sample'])]); concat(a,d,j,b); 64,152,1 48,16 2,760,262,476,436 var_name,run_id do_first('Rdb_test_data',0) 408,216,1 48,24 2,168,178,416,417,0,MIDM [Sys_localindex('IND_NAME'),Sys_localindex('K')] ['','','','','','','','','','','','','','',''] [Sys_localindex('I'),2,Sys_localindex('K'),1,Sys_localindex('K'),1,Sys_localindex('IND_NAME'),1] rdb_to_var('rdb_test_data',0) 200,216,1 48,24 2,264,274,446,288,0,MEAN [Transport_mode,Cost_type] [Stakeholder,1,Cost_type,1,Transport_mode,1]