public void Setup()
{
_randGen = new GMacRandomGenerator(10);
_frame = GaNumFrame.CreateConformal(5);
_frame.SetProductsImplementation(ProductsImplementation);
_mv1 = _randGen.GetNumKVector(_frame.GaSpaceDimension, Grade);
_mv2 = _randGen.GetNumKVector(_frame.GaSpaceDimension, Grade);
}
public string Execute()
{
LogComposer.Clear();
var randGen = new GMacRandomGenerator(10);
var mvList = new List <GaSymMultivector>(10);
for (var i = 0; i < 10; i++)
{
mvList.Add(randGen.GetSymMultivector(Frame.GaSpaceDimension));
}
//var mvA = GaMultivector.CreateSymbolic(Frame.GaSpaceDimension, "A");
//var mvB = GaMultivector.CreateSymbolic(Frame.GaSpaceDimension, "B");
var cacheMisses1 = SymbolicUtils.Cas.Connection.CacheMisses;
var elapsedTime1 = SymbolicUtils.Cas.Connection.Stopwatch.Elapsed;
var resultList = new List <GaSymMultivector>(mvList.Count * mvList.Count);
foreach (var mv1 in mvList)
{
foreach (var mv2 in mvList)
{
resultList.Add(Frame.Gp[mv1, mv2]);
}
}
var cacheMisses2 = SymbolicUtils.Cas.Connection.CacheMisses;
var elapsedTime2 = SymbolicUtils.Cas.Connection.Stopwatch.Elapsed;
//LogComposer
// .AppendAtNewLine("A = ")
// .AppendLine(mvA.ToString());
//LogComposer
// .AppendAtNewLine("B = ")
// .AppendLine(mvB.ToString())
// .AppendLine();
//LogComposer
// .AppendAtNewLine("A gp B = ")
// .AppendLine(gp.ToString())
// .AppendLine();
LogComposer
.AppendAtNewLine("Symbolic Computations Count: ")
.AppendLine(cacheMisses2 - cacheMisses1)
.AppendAtNewLine("Symbolic Computations Time: ")
.AppendLine(elapsedTime2 - elapsedTime1);
return(LogComposer.ToString());
}
public void Setup()
{
_randGen = new GMacRandomGenerator(10);
_frame = GaNumFrame.CreateConformal(5);
//_frame.SelectBilinearProductsImplementation(ProductsImplementation);
_mv1 = _randGen.GetNumMultivectorFull(_frame.GaSpaceDimension);
_mv2 = _mv1.Terms.ToDictionary(t => t.Key, t => t.Value);
_mv3 = GaNumMultivector.CreateZero(_frame.GaSpaceDimension);
//_mv4 = new Dictionary<int, double>();
//_mv5 = new double[_frame.GaSpaceDimension];
}
public string Execute()
{
var randGen = new GMacRandomGenerator(10);
var frame = GaNumFrame.CreateEuclidean(3);
//var mv = randGen.GetNumMultivectorByGrades(frame.GaSpaceDimension, 2);
//var dotGraph = mv.ToGraphViz(true, true);
var bilinearMap = frame.ComputedLcp.ToTreeMap();
var dotGraph = bilinearMap.ToGraphViz(false, true);
//var unilinearMap = frame.NonOrthogonalMetric.BaseToDerivedCba.ToTreeMap();
//var dotGraph = unilinearMap.ToGraphViz(true, true);
return(dotGraph.GenerateDotCode());
}
public string Execute()
{
var randGen = new GMacRandomGenerator(10);
var textComposer = new LinearComposer();
var numFrame = GaNumFrame.CreateConformal(5);
var symFrame = GaSymFrame.CreateConformal(5);
var numMv1 = randGen.GetNumMultivectorFull(numFrame.GaSpaceDimension);
var numMv2 = randGen.GetNumMultivectorFull(numFrame.GaSpaceDimension);
var symMv1 = numMv1.ToSymbolic();
var symMv2 = numMv2.ToSymbolic();
var symMvGp = symFrame.Gp[symMv1, symMv2];
//textComposer.AppendLineAtNewLine("Symbolic Multivector 1: ").AppendLine(symMv1);
//textComposer.AppendLineAtNewLine("Numeric Multivector 1: ").AppendLine(numMv1);
//textComposer.AppendLineAtNewLine("Symbolic Multivector 2: ").AppendLine(symMv2);
//textComposer.AppendLineAtNewLine("Numeric Multivector 2: ").AppendLine(numMv2);
//textComposer.AppendLineAtNewLine("Symbolic Gp: ").AppendLine(symMvGp);
//textComposer.AppendLineAtNewLine("Numeric GP: ").AppendLine(numMvGp);
numFrame.SetProductsImplementation(GaBilinearProductImplementation.Computed);
GaNumMultivector.ResetAddFactorsCallCount();
var numMvGp = numFrame.Gp[numMv1, numMv2];
var callsCount = GaNumMultivector.AddFactorsCallCount;
var diff = symMvGp.ToNumeric() - numMvGp;
diff.Simplify();
GaNumMultivector.ResetAddFactorsCallCount();
textComposer
.AppendLineAtNewLine("Difference, Computed Tree: ")
.AppendLine(callsCount)
.AppendLine(diff);
numFrame.SetProductsImplementation(GaBilinearProductImplementation.LookupArray);
GaNumMultivector.ResetAddFactorsCallCount();
numMvGp = numFrame.Gp[numMv1, numMv2];
callsCount = GaNumMultivector.AddFactorsCallCount;
//var factorsCount = ((GaNumMapBilinearArray) numFrame.Gp).FactorsCount;
diff = symMvGp.ToNumeric() - numMvGp;
diff.Simplify();
GaNumMultivector.ResetAddFactorsCallCount();
textComposer
.AppendLineAtNewLine("Difference, Lookup Array: ")
.AppendLine(callsCount)
//.AppendLine(factorsCount)
.AppendLine(diff);
numFrame.SetProductsImplementation(GaBilinearProductImplementation.LookupHash);
GaNumMultivector.ResetAddFactorsCallCount();
numMvGp = numFrame.Gp[numMv1, numMv2];
callsCount = GaNumMultivector.AddFactorsCallCount;
//factorsCount = ((GaNumMapBilinearHash)numFrame.Gp).FactorsCount;
diff = symMvGp.ToNumeric() - numMvGp;
diff.Simplify();
GaNumMultivector.ResetAddFactorsCallCount();
textComposer
.AppendLineAtNewLine("Difference, Lookup Hash: ")
.AppendLine(callsCount)
//.AppendLine(factorsCount)
.AppendLine(diff);
numFrame.SetProductsImplementation(GaBilinearProductImplementation.LookupTree);
GaNumMultivector.ResetAddFactorsCallCount();
numMvGp = numFrame.Gp[numMv1, numMv2];
callsCount = GaNumMultivector.AddFactorsCallCount;
//factorsCount = ((GaNumMapBilinearTree)numFrame.Gp).FactorsCount;
diff = symMvGp.ToNumeric() - numMvGp;
diff.Simplify();
GaNumMultivector.ResetAddFactorsCallCount();
textComposer
.AppendLineAtNewLine("Difference, Lookup Tree: ")
.AppendLine(callsCount)
//.AppendLine(factorsCount)
.AppendLine(diff);
numFrame.SetProductsImplementation(GaBilinearProductImplementation.LookupCoefSums);
GaNumMultivector.ResetAddFactorsCallCount();
numMvGp = numFrame.Gp[numMv1, numMv2];
callsCount = GaNumMultivector.AddFactorsCallCount;
//factorsCount = ((GaNumMapBilinearCoefSums)numFrame.Gp).FactorsCount;
diff = symMvGp.ToNumeric() - numMvGp;
diff.Simplify();
GaNumMultivector.ResetAddFactorsCallCount();
textComposer
.AppendLineAtNewLine("Difference, Lookup CoefSums: ")
.AppendLine(callsCount)
//.AppendLine(factorsCount)
.AppendLine(diff);
return(textComposer.ToString());
}
