public void TestSimpleGravityModelSolution()
{
var data = CreateData();
var gm = new GravityModel( data, null, 0.0f, 300 );
var o = SparseArray<float>.CreateSparseArray( new int[] { 1, 2 }, new float[] { 2, 2 } );
var d = SparseArray<float>.CreateSparseArray( new int[] { 1, 2 }, new float[] { 1.5f, 2.5f } );
var ret = gm.ProcessFlow( o, d, new int[] { 1, 2 } );
var result = ret.GetFlatData();
Assert.AreEqual( 0.5f, result[0][0], 0.0001f );
Assert.AreEqual( 1.5f, result[0][1], 0.0001f);
Assert.AreEqual( 1f, result[1][0], 0.0001f);
Assert.AreEqual( 1f, result[1][1], 0.0001f);
}
private IEnumerable<SparseTwinIndex<float>> CPUDoublyConstrained(IZone[] zones, IEnumerator<SparseArray<float>> ep, IEnumerator<SparseArray<float>> ea, IEnumerator<IDemographicCategory> ec)
{
float completed = 0f;
var frictionSparse = this.Root.ZoneSystem.ZoneArray.CreateSquareTwinArray<float>();
var productions = new List<SparseArray<float>>();
var attractions = new List<SparseArray<float>>();
var cats = new List<IDemographicCategory>();
// We need to pre load all of our generations in order to handle blending properly
while ( ep.MoveNext() & ea.MoveNext() & ec.MoveNext() )
{
productions.Add( ep.Current );
attractions.Add( ea.Current );
cats.Add( ec.Current );
}
var ret = this.Root.ZoneSystem.ZoneArray.CreateSquareTwinArray<float>();
SparseArray<float> production = this.Root.ZoneSystem.ZoneArray.CreateSimilarArray<float>();
SparseArray<float> attraction = this.Root.ZoneSystem.ZoneArray.CreateSimilarArray<float>();
this.CurrentMultiSetIndex = -1;
foreach ( var multiset in this.MultiBlendSets )
{
this.CurrentMultiSetIndex++;
var numberOfSubsets = multiset.Subsets.Count;
var productionSet = new float[numberOfSubsets][][];
var attractionSet = new float[numberOfSubsets][][];
var multiCatSet = new IDemographicCategory[numberOfSubsets][];
SetupFrictionData( productions, attractions, cats, multiset, productionSet, attractionSet, multiCatSet );
this.ComputeFriction( zones, multiCatSet, productionSet, attractionSet,
frictionSparse.GetFlatData(), production.GetFlatData(), attraction.GetFlatData() );
string balanceFileName;
SparseArray<float> balanceFactors = GetWarmBalancingFactors( attraction, out balanceFileName );
if ( this.CullSmallValues )
{
var tempValues = new GravityModel( frictionSparse, null, this.Epsilon, this.MaxIterations )
.ProcessFlow( production, attraction, production.ValidIndexArray(), balanceFactors );
this.Cull( tempValues, frictionSparse.GetFlatData(), production.GetFlatData(), attraction.GetFlatData() );
if ( !String.IsNullOrWhiteSpace( this.SaveFrictionFileName ) )
{
this.SaveFriction( frictionSparse.GetFlatData() );
}
}
yield return new GravityModel( frictionSparse, ( p => this.Progress = ( p * ( 1f / ( this.MultiBlendSets.Count ) ) + ( completed / ( this.MultiBlendSets.Count ) ) ) ), this.Epsilon, this.MaxIterations )
.ProcessFlow( production, attraction, production.ValidIndexArray(), balanceFactors );
if ( balanceFileName != null )
{
SaveBalanceFactors( balanceFileName, balanceFactors );
}
completed += 1f;
}
}
private void InitializeFlows()
{
this.Progress = 0;
// we are going to need to split based on this information
this.ZoneArray = this.Root.ZoneSystem.ZoneArray;
var occupations = this.Root.Demographics.OccupationCategories;
var validZones = this.ZoneArray.ValidIndexies().ToArray();
var numberOfZones = validZones.Length;
//[Occupation][O , D]
var distribution = occupations.CreateSimilarArray<SparseTwinIndex<float>>();
//Generate the place of work place of residence OD's
SparseArray<float> O = this.ZoneArray.CreateSimilarArray<float>();
SparseArray<float> D = this.ZoneArray.CreateSimilarArray<float>();
var occupationIndexes = occupations.ValidIndexies().ToArray();
var numCat = Categories.Count;
// Start burning that CPU
Thread.CurrentThread.Priority = ThreadPriority.Highest;
SparseTwinIndex<float> workplaceDistribution = null;
SparseTwinIndex<float> prevWorkplaceDistribution = null;
float[] friction = null;
float[] nextFriction = null;
MultiRunGPUGravityModel multiRunGPU = null;
for ( int i = 0; i < numCat; i++ )
{
this.CurrentOccupationIndex = i;
Task assignToPopulation = null;
if ( i > 0 )
{
assignToPopulation = new Task( delegate()
{
if ( prevWorkplaceDistribution != null )
{
// We actually are assigning to the previous category with this data so we need i - 1
AssignToWorkers( prevWorkplaceDistribution, this.Categories[i - 1] );
prevWorkplaceDistribution = null;
}
} );
assignToPopulation.Start();
}
Task computeNextFriction = null;
if ( i + 1 < numCat )
{
computeNextFriction = new Task( delegate()
{
nextFriction = this.ComputeFriction( ZoneArray.GetFlatData(), this.Categories[i + 1], nextFriction );
} );
computeNextFriction.Start();
}
this.Categories[i].Generate( O, D );
if ( this.UseGPU )
{
if ( i == 0 )
{
try
{
Parallel.Invoke( () => friction = this.ComputeFriction( ZoneArray.GetFlatData(), this.Categories[i], friction ),
() => multiRunGPU = new MultiRunGPUGravityModel( O.GetFlatData().Length, ( progress => this.Progress = ( progress / numCat ) + ( (float)i / numCat ) ), this.Epsilon, this.MaxIterations ) );
}
catch ( AggregateException e )
{
throw new XTMFRuntimeException( e.InnerException.Message + "\r\n" + e.InnerException.StackTrace );
}
}
workplaceDistribution = multiRunGPU.ProcessFlow( friction, O, D );
}
else
{
GravityModel gravityModel = new GravityModel( ImpedenceFunction, ( progress => this.Progress = ( progress / numCat ) + ( (float)i / numCat ) ), this.Epsilon, this.MaxIterations );
workplaceDistribution = gravityModel.ProcessFlow( O, D, validZones );
}
this.Progress = ( (float)( i + 1 ) / numCat );
if ( assignToPopulation != null )
{
try
{
assignToPopulation.Wait();
assignToPopulation.Dispose();
assignToPopulation = null;
}
catch ( AggregateException e )
{
throw new XTMFRuntimeException( e.InnerException.Message + "\r\n" + e.InnerException.StackTrace );
}
}
if ( computeNextFriction != null )
{
try
{
computeNextFriction.Wait();
computeNextFriction.Dispose();
computeNextFriction = null;
}
catch ( AggregateException e )
{
throw new XTMFRuntimeException( e.InnerException.Message + "\r\n" + e.InnerException.StackTrace );
}
}
prevWorkplaceDistribution = workplaceDistribution;
var frictionTemp = friction;
friction = nextFriction;
nextFriction = friction;
}
friction = null;
nextFriction = null;
prevWorkplaceDistribution = null;
if ( multiRunGPU != null )
{
multiRunGPU.Dispose();
multiRunGPU = null;
}
AssignToWorkers( workplaceDistribution, this.Categories[numCat - 1] );
workplaceDistribution = null;
// ok now we can relax
Thread.CurrentThread.Priority = ThreadPriority.Normal;
GC.Collect();
}
public SparseTwinIndex<float> Distribute(SparseArray<float> productions, SparseArray<float> attractions)
{
var zoneSystem = this.Parent.ZoneSystem;
var zoneArray = zoneSystem.ZoneArray;
var flatZones = zoneArray.GetFlatData();
ZoneX = zoneArray.CreateSimilarArray<float>();
var flatX = ZoneX.GetFlatData();
ZoneY = zoneArray.CreateSimilarArray<float>();
var flatY = ZoneY.GetFlatData();
var numberOfZones = flatZones.Length;
for (int i = 0; i < numberOfZones; i++)
{
var zone = flatZones[i];
flatX[i] = zone.X;
flatY[i] = zone.Y;
}
SparseTwinIndex<float> data;
if (this.UseGPU)
{
float[] friction = this.ComputeFriction(flatX, flatY, flatZones);
data = new GPUGravityModel( friction, UpdateProgress, this.Epsilon, this.MaxBalanceIterations ).ProcessFlow( productions, attractions );
}
else
{
var validZones = zoneArray.ValidIndexies().ToArray();
data = new GravityModel(FrictionFunction, UpdateProgress, this.Epsilon, this.MaxBalanceIterations).ProcessFlow(productions, attractions, validZones);
}
this.Progress = 1;
return data;
}
