function success = openThisDataSet(datasetnum, windowWidth, windowHeight)
%last two args are optional, and assume the measurement is in pixels

%structuredShowmesmallMain does some initial setup, then
%calls this function. Pressing 'v' calls this function directly

%this main function uses the following functions:
% clickMapCallback, clickCallback, similarityClick
% adjacencyClickCycling, adjacencyClick, keyPressCallback
% (kpcb uses allBackOn), makeNewWindowWithVisible, getNextFigNum,
% myFigureCloseRequest, ...

% after set up also calls: createWindowDisplayWithCoords,
% createFigureInfoWindow


global theVars;
global nextFigNum;
global freedFigNums;
global menubarheight;
global scrollbarwidth;
global bottompadding; %to make sure the images aren't clipped by the window
global openDataSets;

success = 1; %assume all is well at first

%establish window number
myFigNum=getNextFigNum; %ensures non-corruption of nextFigNum

if(isempty(openDataSets))
  openDataSets(1).dataSetNum = datasetnum;
  openDataSets(1).figNums = [myFigNum];
else
  datasetindex = find(cat(1,openDataSets.dataSetNum)==datasetnum);
  if(isempty(datasetindex))
    openDataSets(end+1,1).dataSetNum = datasetnum;
    openDataSets(end,1).figNums = [myFigNum]; 
    %end--> we've already added a row
  else
    openDataSets(datasetindex,1).figNums(1,end+1) = myFigNum;
  end;
end;

theVars(myFigNum).coordsHighlightIndex=1; %used by findElementWindow
theVars(myFigNum).isFocused=0;
theVars(myFigNum).currentCellFocus=0;
theVars(myFigNum).currCellFocusName='';
theVars(myFigNum).clickBehaviorChar= 's'; %starts in 'similarity mode' by default
theVars(myFigNum).clickLevelNum=1; %default is a subgraph 1 level deep
theVars(myFigNum).allIndicesExpanded=[]; %clear
theVars(myFigNum).allIndicesDisplayed=[];
theVars(myFigNum).theAxesHandles=[]; 
theVars(myFigNum).theRelSimilarityMatrix = []; 
theVars(myFigNum).theAbsSimilarityMatrix = []; 
theVars(myFigNum).theRel2SimilarityMatrix = []; 
theVars(myFigNum).theFullRelSimilarityMatrix = [];
theVars(myFigNum).theFullAbsSimilarityMatrix= [];
theVars(myFigNum).theFullRel2SimilarityMatrix= [];
theVars(myFigNum).theRelSimSimMatrix = [];
theVars(myFigNum).theAbsSimSimMatrix = [];
theVars(myFigNum).theRel2SimSimMatrix = [];
theVars(myFigNum).theFullRelSimSimMatrix = [];
theVars(myFigNum).theFullAbsSimSimMatrix = [];
theVars(myFigNum).theFullRel2SimSimMatrix = [];

theVars(myFigNum).names={};
theVars(myFigNum).targets = [];
theVars(myFigNum).basecolor=0.9*[1 1 1]; %used by colorhinton
theVars(myFigNum).visThreshold=0.99; %----*****default THRESHOLD*****----------
theVars(myFigNum).thresholdTesters=[];

%load the data-- assume ROWS are data elements
[data,origData]=loadVerbInputDatasms(datasetnum,myFigNum);
if(isempty(data))
  success = 0;
  return;%EXIT-->invalid dataset
end; 


numinputs = size(data,1);
theVars(myFigNum).lastValidDataIndex=numinputs;
theVars(myFigNum).origNuminputs = numinputs; %for spawning
theVars(myFigNum).allOrigData = origData; %the feature vectors
theVars(myFigNum).numrows = ceil(sqrt(numinputs));
theVars(myFigNum).numcols = theVars(myFigNum).numrows;
theVars(myFigNum).origNumrows=theVars(myFigNum).numrows;%for spawning
theVars(myFigNum).origNumcols=theVars(myFigNum).numcols;%for spawning
theVars(myFigNum).rowColSpanInOrig=[1,theVars(myFigNum).numrows,1,theVars(myFigNum).numcols];%for spawning
theVars(myFigNum).myDataSetNum = datasetnum;

%helper function: determineSizingsms.m
%SETS theVar(myFigNum).foo, for foo= {mytitlefontsize,
%desiredlinewidth, highlightWidth, desirednumpixelspersubcell,
%desirednumpixelsperpadding, desiredheight, desiredwidth}
if(nargin == 1)
  determineSizingsms(myFigNum);
else
  determineSizingsms(myFigNum, windowWidth, windowHeight);
end;

%datasize dependant initialization
theVars(myFigNum).latestSimilarityRanking=zeros(numinputs,2); %initialize to empty
theVars(myFigNum).lsrIndex=numinputs; % to loop BACKWARDS through the lsr list
theVars(myFigNum).nameHandles=zeros(numinputs,1);

%create an appropriate color assignment assoc with each input
%helper function: makeColorValuesMatrix.m
theVars(myFigNum).borderColors = makeColorValuesMatrix(theVars(myFigNum).numrows,theVars(myFigNum).numcols);

theVars(myFigNum).patchColors = theVars(myFigNum).borderColors;
%NOTE: patchColors never changes, but the borderColors matrix
%shrinks when a new subwindow is spawned

%finally, create the relSimilarity and absSimilarity matrices
[rsim, asim, r2sim]=calcSimilaritiesInOrigData(origData);
%NOTE: theFull{Abs}RelSimilarityMatrix never changes, but the non-'Full' matrices
%shrink when a new subwindow is spawned
theVars(myFigNum).theRelSimilarityMatrix=rsim;
theVars(myFigNum).theAbsSimilarityMatrix=asim;
theVars(myFigNum).theRel2SimilarityMatrix=r2sim;
theVars(myFigNum).theFullRelSimilarityMatrix=rsim;
theVars(myFigNum).theFullAbsSimilarityMatrix=asim;
theVars(myFigNum).theFullRel2SimilarityMatrix=r2sim;

%createRecursiveSimTables
[rsimsim, asimsim, r2simsim]=calcSimilaritiesInSimData(myFigNum);
theVars(myFigNum).theRelSimSimMatrix = rsimsim;
theVars(myFigNum).theAbsSimSimMatrix = asimsim;
theVars(myFigNum).theRel2SimSimMatrix = r2simsim;
theVars(myFigNum).theFullRelSimSimMatrix = rsimsim;
theVars(myFigNum).theFullAbsSimSimMatrix = asimsim;
theVars(myFigNum).theFullRel2SimSimMatrix = r2simsim;

theVars(myFigNum).simMode = 2; %pearson's r
theVars(myFigNum).fni = 1; %make sure we're using the right names!!
%simModes 1,2,3 use fni 1, but the recursive modes (4,5,6) use fni 2

%pad the data with placeholders if numinputs is not a perfect square
%data=rsim; %uncomment and correct this line if using something
%other than simMode 2 (pearson) to start

extras=theVars(myFigNum).numrows^2-numinputs;
data = [data,repmat(0,numinputs,extras);...
	repmat(0,extras,numinputs+extras)];
theVars(myFigNum).outofboundsIndexList = numinputs+[1:extras];
theVars(myFigNum).inboundsIndexes = [1:numinputs];

%!!!!!!!make sure 2nd last arg is the dataset corresponding to
%simMode, and has been PADDED with 0's as needed
createWindowDisplayWithCoords(myFigNum,1,theVars(myFigNum).numrows,...
		       1,theVars(myFigNum).numcols,data,0); 
createFigureInfoWindow(myFigNum, datasetnum); %for user feedback

clear data origData; %we've saved this into our data struct
clear rsim asim r2sim rsimsim asimsim r2simsim;