1 1 2 0 [] 1 1 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 4. Febta 2010 6:52 48,24 1,0,0,1,1,1,0,0,0,0 1,18,25,734,523,17 2,102,90,476,316 Arial, 15 0,Model Op_en2676,2,2,0,1,C:\temp\Opasnet base connection_temp.ANA 100,1,1,1,1,9,2970,2100,15,0 2,40,50,640,600 This module saves original data or model results (a study or a variable, respectively) into the Opasnet Base. You need your Opasnet username and password to do that. You must fill in all tables and fields below before the process can be 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. 260,84,-1 252,76 0 168,244,1 160,12 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Opasnet_username TabIndex:1 TextAlways 0 168,268,1 160,12 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Opasnet_password TabIndex:2 TextAlways 456,548,1 48,12 2,527,95,484,451 ktluser 1. Aprta 2009 9:38 48,24 328,456,1 60,32 1,0,0,1,1,1,0,,0, 1,744,88,353,272,17 0 140,60,1 116,12 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 N_variables 3 Analytica model: 140,28,-1 124,12 1,0,0,1,0,1,0,,0, 65535,65532,19661 140,140,-1 124,100 1,0,0,1,0,1,0,,0, 0 140,84,1 116,13 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 Object_info3 0 140,108,1 116,12 1,0,0,1,0,0,0,78,0,1 52425,39321,65535 Index_info 0 140,132,1 116,12 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 Replace_data_ 0 204,380,1 196,12 1,0,0,1,0,0,0,254,0,1 Data_source 456,788,1 48,20 2,102,90,476,300 0 168,316,1 160,12 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Platform 0 168,292,1 160,12 1,0,0,1,0,0,0,142,0,1 52425,39321,65535 Writerpsswd 456,740,1 48,20 2,31,25,825,576 C) 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). 264,748,-1 256,68 1,0,0,1,0,1,0,,0, jtue 8. kesta 2009 14:27 48,24 372,184,1 116,16 1,681,15,586,564,17 Follow these instructions if you have Analytica Enterprise and have an ODBC connection to the Opasnet Base. Read also the simplified help; not everything is repeated here. 284,36,-1 276,28 1,0,0,1,0,1,0,,0, 65535,65532,19661 Platform: You must choose THL computer if you are not using the AWP web interface. 284,92,-1 276,20 1,0,0,1,0,1,0,,0, Writerpsswd: You must know the writer password for the Opasnet Base if you are not using the AWP web interface. 284,149,-1 276,29 1,0,0,1,0,1,0,,0, Object info: - Data source: 1 means that you are copy-pasting data to the 'Observations' field. 2 means that you have a 2D table in an Analytica node. The node must have column index .j (note: it is a local index!) and row index .i. The names of the columns must be in the index .j, and the first row must contain data. 3 means that you have a typical Analytica node with n indices; one of the indices may be Run. The node is transformed into a 2D table using MDArrayToTable. - Analytica identifier is the identifier of the node to be used. The name must be given between 'quotation marks', i.e. as text. - Ident: like in the simplified upload. - Number of indices: like in the simplified upload if data source 2 is used; for 3, the number of indices comes from the node, and this entry is ignored. - Parameter name: like in the simplified upload if data source 2 is used; for 3, the parameter is implicit, and this entry is ignored. - Probabilistic?: like in the simplified upload if data source 2 is used; for 3, if this entry is 1, the sample mode is used and the full distribution is saved, if the entry is not 1, the mid mode is used. - Append to upload: like in the simplified upload. 284,357,-1 276,173 1,0,0,1,0,1,0,,0, 456,631,1 48,31 2,422,44,825,430 B) Upload so that the actual data is not visible without a password. Metadata is visible anyway. 264,624,-1 256,48 1,0,0,1,0,1,0,,0, 2,693,146,476,224 Upload data: 264,516,-1 256,12 1,0,0,1,0,1,0,,0, 65535,65532,19661 A) The default: Upload all data directly to Opasnet Base. 264,548,-1 256,20 1,0,0,1,0,1,0,,0, jtue 8. kesta 2009 14:27 48,24 128,184,1 120,16 1,684,5,586,824,17 Object info: * You must give your Opasnet username and password to upload data. The username will be stored together with the upload information. *Object info contains the most important metadata about your data. - Data source must be 1 when using AWP. - Analytica identifier is ignored when using AWP. - Ident is the page identifier in Opasnet. If your study or variable does not already have a page, you must create one. The identifier is found in the metadata box in the top right corner of the Opasnet page. - Number of indices is the number of columns that contain explanatory information (see below). - Parameter name is a common name for all data columns. If omitted, 'Parameter' is used. See below for more details. - If "Probabilistic?" is 1, then each row of the data table is considered a random draw from a data pool. Note that it is assumed that the index values are assumed the same in all rows, and only the index values of the first row are stored. - Append to upload: Typically, each data upload event is given a separate identifier. If you want to continue an existing upload of the same object, you can give the number of that upload, and the new data will be appended. 284,408,-1 276,176 1,0,0,1,0,1,0,,0, Data structure: * Data must be uploaded in the format of a two-dimensional table. The table has rows, one observation in each row, and columns (fields). * There are two kinds of columns. A) Index columns (also called independent variables in statistics) contain determinants of the actual data, such as sex of the observed individuals, or the observation year. B) Parameter columns (also called dependent variables) contain the actual data about the observations, given the index information. * The first row must contain the names of the columns, i.e. the indices and parameters. These names are used when creating indices in the Opasnet Base. 284,128,-1 276,96 1,0,0,1,0,1,0,,0, Observations: * The data are copy-pasted into the field 'Observations'. The source of the data can be any spreadsheet or text processor, as long as each column is separated by a tab, and each row by a line break. Note that the pasted data should be between 'quotation marks'. 284,640,-1 276,48 1,0,0,1,0,1,0,,0, Data info: Fill in the additional information about the data. These are asked for the object, and also for all the indices and the parameter. Note that is an entry with the identical Ident already exists in the Opasnet Base, this information will NOT be uploaded but the existing information will be used instead. All information should be between 'quotation marks' so that they are not mistakenly interpreted as Analytica node identifiers. - Name: a description that may be longer than an identifier. This is typically identical to the respective page in Opasnet. - Unit: unit of measurement. 284,788,-1 276,92 1,0,0,1,0,1,0,,0, Follow these instructions if you are using the Internet interface (AWP). 284,20,-1 276,12 1,0,0,1,0,1,0,,0, 65535,65532,19661 Uploading: * There are two ways of uploading data. A) 'Upload data' is a public format, and all details are openly available. B) 'Upload non-public data' stores the actual data (the values in the parameter columns) into a database that requires a password for reading. However, all other information (including upload metadata and the data in the index fields) are openly available. 284,944,-1 276,56 1,0,0,1,0,1,0,,0, Provide general information: 264,220,-1 256,12 1,0,0,1,0,1,0,,0, 65535,65532,19661 <a href="http://en.opasnet.org/w/Image:Opasnet_base_connection.ANA">Wiki description</a> 592,40,-1 48,28 Choose the format of input data. 264,356,-1 256,12 1,0,0,1,0,1,0,,0, 65535,65532,19661 48,24 72,456,1 60,32 1,701,26,554,389,17 0 164,268,1 112,12 1,0,0,1,0,0,0,78,0,1 52425,39321,65535 Index_info Copy-paste a data table. 304,168,-1 252,120 1,0,0,1,0,1,0,,0, 2,693,146,476,224 Providing upload data: 304,36,-1 252,12 1,0,0,1,0,1,0,,0, 65535,65532,19661 0 308,152,1 248,80 1,0,0,1,0,0,0,366,0,1 52425,39321,65535 Observations2 TabIndex:3 1 452,269,1 104,13 1,0,0,1,0,0,0,72,0,1 Data_table Check that your data table looks sensible. 408,244,-1 148,12 0 160,245,1 112,13 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 Object_info1_2 The largest id values for the selected Opasnet Base tables. The table is updated by pressing the R_cardinals button. get_mean(Object_info_for_lap[Info='Ident']) 288,328,1 88,16 2,440,279,476,332 2,193,270,416,303,0,MIDM 2,43,59,735,421,0,MIDM 39325,65535,39321 [Sys_localindex('IN1'),Sys_localindex('IN2')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [Sys_localindex('IN3'),1,Sys_localindex('IN4'),1,Sys_localindex('IN5'),1,Sys_localindex('IN6'),1,Sys_localindex('IN7'),1,Sys_localindex('IN8'),13,Sys_localindex('IN2'),1,Sys_localindex('IN1'),1] 48,24 200,456,1 60,32 1,729,57,382,341,17 ['Age','Weight'] 224,272,1 48,12 [Formnode Columns1] ['Age','Weight'] 0 172,125,1 116,13 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 N_rows First row must contain values, not column names! 172,148,-1 124,100 1,0,0,1,0,1,0,,0, 0 172,148,1 116,12 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 Analytica_table 0 172,101,1 116,13 1,0,0,1,0,0,0,72,0,1 Columns 2 Node formatted as data table: 172,36,-1 124,12 1,0,0,1,0,1,0,,0, 65535,65532,19661 0 172,172,1 116,13 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 Object_info1_2 0 172,196,1 116,12 1,0,0,1,0,0,0,78,0,1 52425,39321,65535 Index_info 48,24 456,456,1 60,32 1,770,118,445,300,17 1 96,36,0 48,12 1,1,1,1,1,1,0,0,0,0 52425,39321,65535 Ana_table 48,24 576,784,1 48,24 1,0,0,1,1,1,0,,0, 1,419,46,615,547,17 jtue 24. maata 2009 9:36 48,24 184,40,1 48,24 1,559,31,690,439,17 Makes a table to be written to the Loc table. var a:= Locations; var b:= a[.j='obj_id_i']; var c:= cardinals[table1='loc']+a[@.j=1]; a:= array(a.j,[c, c, findid(b,obj,'ident'), a, a, a]); textify(a) 432,240,1 48,16 2,84,125,476,245 2,642,68,606,278,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,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. var a:= Loccells; var b:= textify(findid(a[.j='id'], obj, 'ident')); var c:= textify(a[.j='loc_id']); b:= findid(b&'+'&c, (if Loc.j='obj_id_i' then Loc&'+'&Loc[.j='location'] else Loc), 'obj_id_i'); a:= array(a.j,[(@a.i+cardinals[table1='loccell']), (a+cardinals[table1='cell']), b]); textify(a) 432,328,1 48,16 2,776,90,476,487 2,178,73,453,537,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 Slices the fields that are needed in the Res table. Removes duplicate rows. var a:= Cells; a:= array(a.j, [ a[.j='id']+cardinals[table1='cell'], actobj_stat[@actobj_stat1=lap], a, a, a]); textify(a) 432,280,1 48,16 2,759,203,476,379 2,14,241,659,368,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 Selects relevant information for the Obj table from Objects1 node. 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; textify(a) 432,160,1 48,16 2,372,300,476,343 2,429,135,626,444,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [] Makes a list of objects that contains some additional information to be written into the Objinfo table. var a:= Acts; a:= if a.j='id' {or a.j='series_id'} then a+cardinals[table1='act'] else a; a:= if a=null or a=0 then '' else a&'' 432,200,1 48,16 2,66,82,476,340 2,34,242,690,459,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [Sys_localindex('J'),1,Sys_localindex('I'),1,Sys_localindex('J'),1] var a:= Results; index i:= subset(if a[.j='result']=null and a[.j='description']=0 then 0 else 1); a:= a[.i=i]; a:= array(a.j, [textify(a.i+Cardinals[table1='res']), textify(a+ Cardinals[table1='cell']), textify(a),a,a]); if a=null then '' else a 432,368,1 48,13 2,629,191,582,297 2,461,218,609,375,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] Additional information for each index and decision node. Description node is the name of a node containing information about the locations of the index. It must be indexed by the index. Object_info[N_vars=Lap] 176,312,1 48,20 2,140,217,476,224 2,653,25,488,226,0,MIDM 2,104,359,460,228,0,MIDM 52425,39321,65535 [N_vars,Info] [N_vars,Info] [1,1,1,0] Table(Ind_info,Indices)( 'Country','Year','Diagnosis','Sex',0, '-','a','ICD-10','-',0 ) 384,32,1 48,16 2,102,90,476,349 2,559,220,666,349,0,MIDM 2,184,194,660,316,0,MIDM [Formnode Study_or_variable_i1, Formnode Study_or_variable_i2, Formnode Study_or_variable_i3] 52425,39321,65535 [Ind_info,Indices] [Ind_info,Indices] [] ['name','unit'] 384,56,1 48,13 [] Makes a list of all locations in all results in all variables. The list is as long as is needed for the Loccell table. A subset is taken then for the Cell table. 1) Initialises local variables, and slices variables from Object1. 2)-4) Does the process for each variable one at a time. This happens in function Loccell. 5) Makes i the row index. var a:= Data_table; index h:= a.j[@.j=1..size(a.j)-2]; a:= a[.j=h]; var d:= max(Data_table[.j='obs'],Data_table.i); a:= if 1-proba then (index itemp:= copyindex(a.i); a[.i=itemp]) else ( index grun:= 1..d; index itemp:= 1..size(a.i)/d; a:= a[@.i=(itemp-1)*d+grun]; a:= a[@grun=1]); index j:= ['id', 'cell_id', 'loc_id']; index i:= 1..size(a); a:= array(j,[h, @a.itemp, a]); concatrows(a,h,a.itemp,i) 320,328,1 48,16 2,643,26,526,596 2,70,181,552,488,0,MIDM [Sys_localindex('J'),Sys_localindex('I'),Undefined,Undefined,Undefined,1] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] [Sys_localindex('J'),2,Sys_localindex('ITEMP'),1,Sys_localindex('H'),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 e:= 0; var f:= 0; var a:= Data_table[.j='result']; var d:= max(Data_table[.j='obs'],Data_table.i); var b:= if 1-proba then @a.i else ( floor((@a.i-1)/d)+1); index j:= ['id','cell_id','obs','result','restext']; array(j,[0, b, Data_table[.j='obs'], (if istext(a) then '' else a) , (if istext(a) then a else '')]) 320,368,1 48,16 2,634,23,581,615 2,662,12,469,411,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [Run,2,Sys_localindex('J'),1,Sys_localindex('I'),1] The format of this node MUST be integer, so that the id and Roww values are stored correctly. var a:= data_table; var b:= [0]; var c:= [0]; var x:= 1; while x<= size(a.j)-2 do ( var h:= a[@.j=x]; var d:= h[.i=unique(h,h.i)]; b:= concat(b,d); c:= concat(c,(if d=0 then slice(a.j,x) else slice(a.j,x))); x:= x+1); index i:= 1..size(b)-1; index j:= ['id', 'std_id', 'obj_id_i', 'location', 'description']; a:= array(j,[i, i, slice(c,i+1), slice(b,i+1), '']) 320,240,1 48,16 2,68,138,476,581 2,92,398,746,259,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [Sys_localindex('D'),1,Object_all3,1,Age,1] var N_indices:= Object_info_for_lap[Info='number of indices']; var b:= evaluate(selecttext(Data_source,1,1)); var a:= if b=1 then data_table2 else if b=2 then analytica_table else analytica_node; if b>=3 then a else ( index h:= a.columns[@a.columns=1..N_indices]; var c:= Object_info_for_lap[Info='parameter name', @N_vars=1]; c:= if c='' or c=0 then 'parameter' else c; index j:= concat(h,[c,'result','obs']); index parameter:= a.columns[@a.columns=N_indices+(1..size(a.columns)-N_indices)]; index temp:= 1..size(a.rows)*size(parameter); var conv:= if j='result' then @parameter+N_indices else @j; a:= a[@.columns=conv]; a:= if @j=size(j)-2 then parameter else a; a:= if @j=size(j) then @a.rows else a; a:= concatrows(a, parameter, a.rows, temp); a:= if j='result' then (var d:= a[j='result']; if evaluate(d)=null then d else evaluate(d)) else a; index i:= Subset(a[j='result']<>null); a[temp=i]); ana_table 176,184,1 48,16 2,4,175,482,501 2,17,71,736,338,0,MIDM [Formnode Data_table1] [Sys_localindex('I'),Sys_localindex('J')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [1,1,1,0] [Sys_localindex('I'),1,Sys_localindex('J'),1] ['Analytica identifier','ident','name','unit','number of indices','parameter name','probabilistic?'] 240,48,1 48,13 2,102,90,476,379 2,90,166,416,303,0,MIDM [] ['Analytica identifier','ident','name','unit','number of indices','parameter name','probabilistic?'] 19.10.2009 Jouni Tuomisto The Run/Name = Method cell is problematic. It was designed for one-variable uploads, and now it contains both upload-specific and variable-specific information. This should be solved somehow but I don't know how. So, I just make it technically work and don't worry about it now. Some variable-specific info is omitted, some is taken from the first variable. 5.1.2010 Jouni Tuomisto Variable-specific parts are simply rejected. Index j:= ['id','ident','name','unit','objtype_id','page','wiki_id']; index i:= concat(N_vars,indices); var Ident:= if @i <= size(N_vars) then Object_info[Info='ident', @N_vars=@i] else i; var a:= Index_info[indices=i, Ind_info=j]; a:= if a=null then '' else a; var e:= Object_info[N_vars=i, Info=j]; a:= if e=null then a else e; var b:= sum(findintext(wikis,ident)*@wikis,wikis); var c:= if b=0 then '' else wikis[@wikis=b]; c:= if b=0 then '2664' else selecttext(ident,1+textlength(c)); a:= array(j,[ @i, ident, a, a, if @i<= size(N_vars) then 1 else 6, if i='run' then '2817' else c&'', if b=0 then '1' else b&'']) 320,160,1 48,16 2,573,29,547,724 2,11,31,656,283,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] [Indices,1,Sys_localindex('J'),1,Sys_localindex('I'),1] 'Test1 Value 1 2nh 2 30' 64,232,1 52,16 2,586,79,476,465 [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 columns:= splittext(slice(a,1), chr(9)); index rows:= 1..size(a)-1; a:= slice(a,rows+1); a:= splittext(a, chr(9)); for y:= rows do (slice(a[rows=y],@columns)) 64,184,1 48,16 2,7,115,476,362 2,761,412,476,386,0,MIDM [Sys_localindex('COLUMNS'),Sys_localindex('ROWS')] [1,1,1,0] Table(Time,Testindex)( uniform(0,1), uniform(1,2), uniform(2,3) ) 544,440,1 48,24 2,40,50,416,303,0,MIDM [Time,Testindex] [Time,Testindex] [1,0,0,0] ['item 1'] 544,472,1 48,12 2,102,90,476,224 ['item 1'] Slices the fields that are needed in the Res table. Removes duplicate rows. (if w_cell.j = 'mean' then '' else W_cell) 544,280,1 48,16 2,782,213,476,379 2,41,191,618,368,0,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 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. var a:= Data_table[@.j=size(Data_table.j)-1]; index j:= ['id', 'actobj_id', 'mean', 'sd', 'n']; var d:= max(Data_table[.j='obs'],Data_table.i); index temp:= ['mean','sd']; a:= if 1-proba then array(temp,[a,'']) else ( index grun:= 1..d; index i:= 1..size(a.i)/d; a:= a[@.i=(i-1)*d+grun]; a:= array(temp,[mean(a,grun), sdeviation(a[j='mean'],grun)]) ); a:= array(j,[ @a.i, '', a[temp='mean'], a[temp='sd'], d]) 320,280,1 48,16 2,721,20,526,639 2,304,464,608,328,0,MIDM [Sys_localindex('J'),Sys_localindex('I'),Undefined,Undefined,Undefined,1] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] [N_vars,2,Sys_localindex('I'),1,Sys_localindex('J'),1] 19.10.2009 Jouni Tuomisto If the variable is deterministic, Obs is 0. It is not clear whether it should be or not. This should be checked with other upload methods (1-3) to see that they are consistent. 0 {var a:= Object_info_for_lap[Info='Analytica identifier']; index jtemp:= concat(indexnames(getfract(evaluate(a),0.5)),['result','obs']); index j:= textreplace(jtemp,'.',''); a:= if proba then sample(evaluate(a)) else evaluate(a); index temp:= concat(indexnames(a),['result']); index i:= 1..size(a); a:= Mdarraytotable(a, i, temp); a:= if j='obs' and proba then a[temp='Run'] else a[temp=jtemp]; a:= a[@jtemp = @j]; a:= if a=null then 0 else a} 64,312,1 48,20 2,53,195,476,444 2,56,66,630,303,0,MIDM [Sys_localindex('I'),Sys_localindex('J')] [1,1,1,0] [N_vars,1,Sys_localindex('J'),1,Sys_localindex('I'),1] var a:= Object_info_for_lap[Info='probabilistic?']; (a=1 or a='Yes' or a='Y' or a='yes' or a='y') 176,368,1 48,16 Choice(Self,4,False) 176,136,1 48,16 2,102,90,476,224 [Formnode Data_source1] 52425,39321,65535 ['1 Copy-paste table','2 Node to be formatted as data table','3 Analytica model','4 Ready-made data table node'] [1,1,0,0] 1.. (if selecttext(Data_source,1,1)='3' then N_variables else 1) 240,72,1 48,12 [] [1] 1 240,96,1 48,12 [Formnode N_variables1] 52425,39321,65535 1 64,368,1 48,16 [0,1,0,1] copyindex(Find_ind) 384,76,1 48,12 2,140,321,476,409 2,40,50,416,303,0,MIDM [] Table(Self)( 1,2,3) ['item 1','item 2','item 3'] 544,384,1 48,24 [1,1,0,1] 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(Info,N_vars)( 'Total_mortality', 'Op_en2778', 'WHO mortality data', '#', 1, 'Weight', 0 ) 240,24,1 48,16 2,140,217,476,224 2,277,418,982,328,0,MIDM 2,590,303,460,228,0,MIDM 52425,39321,65535 [Info,N_vars] [N_vars,Info] [] [1,1,1,0] Table(Columns,Rows)( 1,2,3, 4,5,6 ) 64,56,1 48,24 2,248,258,416,303,0,MIDM [Formnode Analytica_table2] 52425,39321,65535 [Columns,Rows] [Columns,Rows] 1..N_rows 64,88,1 48,12 [1,2,3] 3 64,112,1 48,12 1,1,1,1,1,1,0,0,0,0 [Formnode N_rows1] 52425,39321,65535 5.1.2010 Jouni Tuomisto I separated Acts and Objects. Index j:= ['id', 'acttype_id','who','comments']; index i:= ['create','upload']; var a:= array(j,[ @i, array(i,[1, (if selecttext(replace_data_,1,1)='Y' then 4 else 5)]), opasnet_username, if i ='upload' then 'Analytica '&Analyticaedition&', ('&Analyticaplatform&'), Version: '&textify(Analyticaversion) else '']); a 320,200,1 48,16 2,29,37,525,724 2,88,339,694,283,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] ['',''] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] Upload type 1. 64,200,-1 56,56 1,0,0,1,0,1,0,,0, Upload type 2. 64,72,-1 56,64 1,0,0,1,0,1,0,,0, Upload type 3. 120,332,-1 112,60 1,0,0,1,0,1,0,,0, Makes a list of objects that contains some additional information to be written into the Objinfo table. var a:= actobj2; if a.j='series_id' and acts[.j= 'acttype_id', .i='upload'] = 5 then Series[.i = a.i] else a; 592,112,1 48,16 2,250,25,476,340 2,44,195,690,459,0,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] var a:= Data_table.j[@.j=1..(size(Data_table.j)-2)]; a:= jointext(a,,','); var b:= Object_info[Info='Analytica identifier']; var c:= ['Run']; var x:= 1; while x<=size(b) do ( c:= concat(c,indexnames(evaluate(slice(b,x)))); x:= x+1); c:= textreplace(c, '.' , ''); index temp:= 1..size(c); c:= slice(c, temp); c:= c[temp= unique(c,temp)]; index i:= 1..(size(c)-1); c:= slice(c, i+1); b:= jointext(c,c.i,','); a:= if selecttext(Data_source,1,1)='3' then b else a; splittext(a,',') 384,104,1 48,12 2,102,90,476,385 [Self,Sys_localindex('I')] ['Run'] Table(Actobj_stat1)( '602','603' ) 544,216,1 48,16 [1,2] 544,240,1 48,12 [1,2] for x[]:= actobj2.i do ( var a:= query(' SELECT MAX(act.id) FROM actobj LEFT JOIN act ON actobj.act_id = act.id WHERE obj_id = '&chr(39)&actobj2[.j = 'obj_id', .i = x]&chr(39)&' AND acttype_id = 4 '); a[@.j = 1, @.i=1] ) 480,112,1 48,12 2,258,57,416,303,0,MIDM 39325,65535,39321 [Sys_localindex('I'),Sys_localindex('J')] index j:= ['id', 'act_id', 'obj_id', 'series_id']; var a:= W_obj; var b:= a[.j = 'id']= textify(@a.i+cardinals[table1='obj']); index k1:= subset(b); b:= array(j, ['', w_act[@.j=1, @.i=1], a[.i = k1, .j='id'], '' ]); index k2:= subset(a[.j='objtype_id']='1'); a:= array(j, ['', w_act[@.j=1, @.i=2], a[.i =k2, .j='id'], w_act[@.j=1, @.i=2] ]); index i:= 1..(size(k1)+size(k2)); a:= concat(a, b, k2, k1, i); if j='id' then textify(i+cardinals[table1='actobj']) else a 544,160,1 48,16 2,83,399,416,303,0,MIDM [Sys_localindex('I'),Sys_localindex('J')] [Sys_localindex('I'),1,Sys_localindex('J'),1,Sys_localindex('I'),1] index j:= ['Country','Year','Diagnosis','Sex','Age','result','obs']; var a:= Total_mortality[@.j = @j]; a:= if j = 'obs' then 0 else a; if j = 'result' then evaluate(a) else a 168,56,0 48,12 1,1,1,1,1,1,0,0,0,0 [Alias Ana_table1] 52425,39321,65535 [Sys_localindex('I'),Sys_localindex('J')] ktluser 3. Augta 2008 18:31 jtue 9. lokta 2008 14:01 48,24 312,40,1 48,24 1,1,1,1,1,1,0,0,0,0 1,601,119,477,429,17 Arial, 15 (vident:text, seriesid:optional) Reads the mean data about the vident variable from the Opasnet Base. Uses the run with runid as run.id if specified; otherwise uses the newest run of that variable. PARAMETERS: * Vident: the ident of the variable in the Opasnet Base. * Runid: the id of the run from which the results will be brought. If omitted, the newest result will be brought. Change run to act if isnotspecified(seriesid) or istext(seriesid) then seriesid:= Newest_series(vident); query( ' SELECT obj.ident, obj.name, obj.unit, cell.id as cell_id, mean, sd, n, act_id, comments, time, std.location, ind.ident AS iident, ind.name AS iiname, actobj.series_id FROM obj LEFT JOIN actobj ON obj.id = actobj.obj_id LEFT JOIN act ON act.id = actobj.act_id LEFT JOIN cell ON cell.actobj_id = actobj.id LEFT JOIN loccell ON loccell.cell_id = cell.id LEFT JOIN loc ON loccell.loc_id = loc.id LEFT JOIN loc as std ON loc.std_id = std.id LEFT JOIN obj as ind ON std.obj_id_i = ind.id WHERE obj.ident = '&chr(39)&vident&chr(39)&' AND actobj.series_id = '&chr(39)&seriesid&chr(39) ) 56,80,1 48,12 2,585,25,516,589 39325,65535,39321 vident,seriesid (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:= query(' SELECT actobj.series_id, var.ident FROM obj AS var LEFT JOIN actobj ON var.id = actobj.obj_id LEFT JOIN act ON actobj.act_id = act.id WHERE var.ident = "'&vident&'" '); max(a[@.j=1],a.i) 56,22,1 48,22 2,678,59,476,566 39325,65535,39321 vident (vident:text, seriesid: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. * Runid: the id of the run from which the results will be brought. If omitted, the newest result will be brought. chenge run to act add restext if isnotspecified(seriesid) or istext(seriesid) then seriesid:= Newest_series(vident); query( ' SELECT obj.id AS obj_id, obj.ident, obj.unit, ind.ident as iident, cell.id AS cell_id, location, mean, n, obs, result, restext FROM obj LEFT JOIN actobj ON actobj.obj_id = obj.id LEFT JOIN act ON actobj.act_id = act.id LEFT JOIN cell ON cell.actobj_id = actobj.id LEFT JOIN loccell ON loccell.cell_id = cell.id LEFT JOIN loc ON loccell.loc_id = loc.id LEFT JOIN obj as ind ON loc.obj_id_i = ind.id LEFT JOIN res ON res.cell_id = cell.id WHERE obj.ident = '&chr(39)&vident&chr(39)&' AND actobj.series_id = '&chr(39)&seriesid&chr(39) ) 56,112,1 48,22 2,55,35,516,612 39325,65535,39321 vident,seriesid '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 Newest_series(Enter_variable) 288,61,1 48,22 2,200,56,416,303,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] read_mean(Enter_variable) 288,116,1 48,12 2,28,65,1144,438,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] (a,b,x) 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. index inde / slice(b.m, x) := b[.n = unique(b[@.m = x], b.n), @b.m = x]; a:= if inde = a[@.m=1] then a else 0; index m:= slice(a.m,(2..size(a.m))); a:= a[.m=m] 56,192,1 48,12 2,61,72,476,454 a,b,x (a) Makes a multi-dimensional array with the same structure as the original variable that was stored into the Opasnet Base. The contents of the array are the cell_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, and changes a location column to a dimension one at a time until all columns have been changed. NOTE! There is a problem that if there are two or more cells with the exactly same locations, only the one with a largest cell_id will be taken. index k:= ['iident','location','cell_id', 'act_id']; a:= a[.j=k]; a:= if a.k = 'iident' then textreplace(a, ' ', '_', true) else a; index L:= a[@k=1]&'+'&textify(a[@k=3]); index m:= concat(a[.i=unique(a[@k=1],a.i), @k=1],['act_id', 'result']); index n:= a[.i=unique(a[@k=3],a.i), @k=3]; a:= a[@.i=@L]; var c:= a[L=(m)&'+'&textify(n), @k=4, @m=1]; a:= a[L=(m)&'+'&textify(n), @k=2]; a:= if m='result' then n else a; a:= if m='act_id' then c else a; var b:= a; var x:= 1; a:= while x< size(b.m) do ( a:= makeind(a,b,x); x:= x+1; a); a:= max(a[@.m=1], a.n); if size(a.act_id)=1 then a[@.act_id = 1] else a 56,168,1 48,13 2,160,51,476,628 a get_mean(Enter_variable) 288,140,1 48,12 2,835,77,420,564,0,MIDM [Sys_localindex('ACT_ID'),Sys_localindex('MONTH')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [Sys_localindex('M'),1,Sys_localindex('N'),1,Sys_localindex('ACTION'),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='cell_id']; index j:= ['mean','sd']; var output:= a[@.i=@o, .j = j]; a:= Get_cell_id(a); {output[o=a]} 56,216,1 48,12 2,114,117,476,428 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_cell_id(read_mean(vident,runident))); index k:= textify(a[.j='cell_id'])&'+'&textify(a[.j='obs']); index runn:= min(a[.j='obs'],a.i)..max(a[.j='obs'],a.i); a:= if a[.j='restext'] = '' then a[.j='result'] else a[.j='restext']; a:= a[@.i=@k]; a:= a[k=b&'+'&runn]; a:= if max(runn)=0 then a[@runn=1] else a[@runn=@run]; 56,240,1 48,12 2,613,48,476,556 vident,runident get_sample(Enter_variable) 288,164,1 48,12 2,86,111,476,224 2,18,155,646,307,0,MEAN [Sys_localindex('OP_EN1899'),Sys_localindex('SALMON')] [Sys_localindex('OP_EN1898'),1,Sys_localindex('YEAR'),1,Sys_localindex('SALMON'),1,Sys_localindex('OP_EN1899'),1] Describes the runs of the defined variable. This should be made a function. var_run_info(Enter_variable) 288,92,1 48,12 2,41,152,1235,369,0,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. Change: objinfo to act run to act add objact query( ' SELECT obj.id AS ovj_id, obj.ident, obj.name, obj.unit, actobj.series_id, actobj.act_id, comments, act.time, act.who FROM obj LEFT JOIN actobj ON obj.id = actobj.obj_id LEFT JOIN act ON act.id = actobj.act_id WHERE obj.ident = '&chr(39)&vident&chr(39)&' ') 56,56,1 48,13 2,182,31,476,566 39325,65535,39321 vident Use these functions to retireve data from the Opasnet Base: * Newest_series: finds the newest upload of the object. * Obj_act_info: Finds the action information of the object. * Read_mean: Reads the means of each cell. * Get_mean: Makes read_mean table into an array. * Read_sample: Reads the whole sample. * Get_sample: Makes read_sample table into a probabilistic array. 280,294,-1 168,110 (a:text) Performs a query and results the standard table with columns .j and rows .i. Lap; index i:= DBquery(Odbc,a); index j:= dblabels(i); dbtable(i,j) 56,144,1 48,13 2,100,154,476,566 39325,65535,39321 a Names of different wikis used. Table(Self)( 'Op_en','Op_fi','Heande','En','Fit','Erac','Beneris','Intarese','Piltti','Kantiva','Bioher','Heimtsa') [1,2,3,4,5,8,9,10,11,13,14,15] 184,168,1 48,16 65535,52427,65534 [Self] [] (a) Changes a number to a text value with up to 15 significant numbers. This bypasses the number formatting problem that tends to convert e.g. 93341 to '93.34K'. If the input is null, the result is ''. if a = null then '' else a&'' 72,376,1 48,12 2,309,205,559,372 a 2,F,4,14,0,0,4,0,$,0,"ABBREV",0 (a; file:texttype) a:= '"'&a&'"'; a:= jointext(a,a.j,';'); Writetextfile('c:\temp\'&file, a) 72,352,1 48,13 2,44,303,476,224 65535,45873,39321 a,file 2,F,4,14,0,0,4,0,$,0,"ABBREV",0 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 48,24 488,40,1 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 48,24 496,96,1 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 List of such tables in Opasnet Base that are being written to by this module. ['act','actobj','cell','obj','loc','loccell','obj','res'] 296,216,1 48,12 2,396,363,377,227,0,MIDM The largest id values for the selected Opasnet Base tables. The table is updated by pressing the R_cardinals button. for x[]:= table1 do ( var a:= query('SELECT MAX(id) AS id FROM '&x&' '); max(max(a,a.i),a.j)) 296,192,1 48,12 2,634,394,476,332 2,193,270,416,303,0,MIDM 2,659,299,416,303,0,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] 72,280,1 48,12 2,636,101,494,519 in,table,cond (var, table) 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&' ')) 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=result_writer; Password='&writerpsswd&';Option=3' , appendtablesql(var,var.i, var.j, table&' ')) 72,304,1 48,12 2,751,65,501,457 65535,45873,39321 var,table The username for Opasnet wiki 'Add username' 72,176,1 48,22 1,1,1,1,1,1,0,0,0,0 2,102,90,476,398 [Formnode Username1] 52425,39321,65535 [] The user's password for Opasnet wiki. 'Add password' 72,232,1 48,22 1,1,1,1,1,1,0,0,0,0 2,102,90,476,520 [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' 184,136,1 48,12 1,1,0,1,1,1,0,,0, 2,180,61,508,420 2,56,66,918,303,0,MIDM Lap; query(' SELECT loc.*, ind.* FROM loc, obj as ind WHERE loc.obj_id_i = ind.id ') 296,160,1 48,13 1,1,0,1,1,1,0,0,0,0 2,370,45,476,445 2,43,42,1147,516,0,MIDM 39325,65535,39321 [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. Lap; query('SELECT * FROM obj ') 296,136,1 48,13 1,1,0,1,1,1,0,0,0,0 2,378,21,493,501 2,218,87,977,421,0,MIDM 39325,65535,39321 [Sys_localindex('J'),Sys_localindex('I')] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] (var, table) if size(var)>0 then appendtablesql(var,var.i, var.j, table&' ') 72,328,1 48,13 2,284,58,476,224 var,table '' 184,200,0 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) 72,136,1 48,12 [Formnode Platform1] 52425,39321,65535 ['Lumina AWP','THL computer'] subtable(Object_info[Info=Info1_2, @n_vars=1]) 184,248,1 48,24 2,102,90,476,373 2,39,314,416,303,0,MIDM 2,599,363,416,303,0,MIDM [Formnode Object_info7, Formnode Object_info8] 52425,39321,65535 [N_vars,Info1_2] [Self,Ind_info] ['','',''] ['ident','name','unit','number of indices','parameter name','probabilistic?'] 184,280,1 48,13 1,1,1,1,1,1,0,0,0,0 296,312,1 48,24 2,247,178,476,459 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. subtable(Object_info[Info=Info3]) 184,320,1 48,16 2,140,217,476,224 2,417,216,703,359,0,MIDM 2,752,344,460,228,0,MIDM [Formnode Object_info6] 52425,39321,65535 [Info3,N_vars] [N_vars,Info] [0,1,1,0] ['Analytica identifier','ident','name','unit','probabilistic?'] 184,352,1 48,13 1,1,1,1,1,1,0,0,0,0 This is a temporary node that is ovewritten when Upload_data and Upload_results are being run. '' 296,352,1 48,16 Choice(Self,1,False) 296,256,1 48,22 [Formnode Replace_data_1] 52425,39321,65535 ['Yes, replace previous data','No, append to previous data'] [] "index vehicle_type:= ['Bus','Minibus','Car d','Car g']; var Car_maintenance:= Triangular( 0.03, 0.058, 0.086 ); var Fuel_price:= (var a:= 0.95*triangular(0.8,1,1.2); var b:= 1.22*triangular(0.8,1,1.2); array(Vehicle_type,[a,a,a,b])); var Fuel_consumption:= (var a:= (8.7/100)*Triangular(0.75,1,1.25); var b:= (5.7/100)*Triangular(0.75,1,1.25); var c:= (8/100)*Triangular(0.5,1,1.5); a:= array(Vehicle_type,[a,a,b,c]); ); fuel_price*fuel_consumption+car_maintenance" 496,280,1 48,24 [Formnode Enter_anacode1] 52425,39321,65535 0 432,448,1 160,56 1,0,0,1,0,0,0,182,0,1 52425,39321,65535 Enter_anacode index vehicle_type:= ['Bus','Minibus','Car d','Car g']; var Car_maintenance:= Triangular( 0.03, 0.058, 0.086 ); var Fuel_price:= (var a:= 0.95*triangular(0.8,1,1.2); var b:= 1.22*triangular(0.8,1,1.2); array(Vehicle_type,[a,a,a,b])); var Fuel_consumption:= (var a:= (8.7/100)*Triangular(0.75,1,1.25); var b:= (5.7/100)*Triangular(0.75,1,1.25); var c:= (8/100)*Triangular(0.5,1,1.5); a:= array(Vehicle_type,[a,a,b,c]); ); fuel_price*fuel_consumption+car_maintenance 496,216,1 48,24 evaluate(Enter_anacode) 496,336,1 48,16 2,104,114,416,303,0,SAMP [Undefined,Sys_localindex('VEHICLE_TYPE'),Undefined,Undefined,Undefined,1] [1,0,0,0] Provide data in the format you selected. 264,412,-1 256,12 1,0,0,1,0,1,0,,0, 65535,65532,19661