private SparseTwinIndex <float> CreateRelativeDifference <T>(SparseTwinIndex <float> runData, SparseTwinIndex <float> baseData, SparseArray <T> refernceArray, Func <IZone, int> getAgg)
{
var ret = refernceArray.CreateSquareTwinArray <float>();
var truth = refernceArray.CreateSquareTwinArray <float>();
var zones = Root.ZoneSystem.ZoneArray.GetFlatData();
var flatRun = runData.GetFlatData();
var flatBaseData = baseData.GetFlatData();
for (int i = 0; i < flatRun.Length; i++)
{
var oAgg = getAgg(zones[i]);
for (int j = 0; j < flatRun[i].Length; j++)
{
var jAgg = getAgg(zones[j]);
ret[oAgg, jAgg] += flatRun[i][j];
truth[oAgg, jAgg] += flatBaseData[i][j];
}
}
var factor = Sum(truth) / Sum(ret);
var flatRetData = ret.GetFlatData();
var flatTruthData = truth.GetFlatData();
for (int i = 0; i < flatRetData.Length; i++)
{
for (int j = 0; j < flatRetData[i].Length; j++)
{
flatRetData[i][j] = (flatRetData[i][j] * factor) / flatTruthData[i][j];
}
}
return(ret);
}
public SparseTwinIndex <float> ProcessFlow(SparseArray <float> O, SparseArray <float> D, int[] validIndexes, SparseArray <float> attractionStar = null)
{
int length = validIndexes.Length;
Productions = O;
Attractions = D;
if (attractionStar == null)
{
AttractionsStar = D.CreateSimilarArray <float>();
}
else
{
AttractionsStar = attractionStar;
}
FlowMatrix = Productions.CreateSquareTwinArray <float>();
if (Friction == null)
{
InitializeFriction(length);
}
var flatAttractionStar = AttractionsStar.GetFlatData();
float[] oldTotal = new float[flatAttractionStar.Length];
var flatAttractions = Attractions.GetFlatData();
for (int i = 0; i < length; i++)
{
flatAttractionStar[i] = 1f;
oldTotal[i] = flatAttractions[i];
}
int iteration = 0;
float[] columnTotals = new float[length];
var balanced = false;
do
{
if (ProgressCallback != null)
{
// this doesn't go to 100%, but that is alright since when we end, the progress
// of the calling model should assume we hit 100%
ProgressCallback(iteration / (float)MaxIterations);
}
Array.Clear(columnTotals, 0, columnTotals.Length);
if (Vector.IsHardwareAccelerated)
{
VectorProcessFlow(columnTotals, FlowMatrix.GetFlatData());
}
else
{
ProcessFlow(columnTotals);
}
balanced = Balance(columnTotals, oldTotal);
} while((++iteration) < MaxIterations && !balanced);
if (ProgressCallback != null)
{
ProgressCallback(1f);
}
return(FlowMatrix);
}
public void IterationStarting(int iteration, int totalIterations)
{
Iteration = iteration;
lock (this)
{
ZoneSystem = Root.ZoneSystem.ZoneArray;
if (RecordedData == null)
{
RecordedData = ZoneSystem.CreateSquareTwinArray <float>().GetFlatData();
}
else
{
for (int i = 0; i < RecordedData.Length; i++)
{
Array.Clear(RecordedData[i], 0, RecordedData[i].Length);
}
}
for (int i = 0; i < AnalyzeModes.Length; i++)
{
ValidModeNames.Add(AnalyzeModes[i].ModeName);
}
Activities = ActivitiesToCapture.Select(a => a.Activity).ToArray();
}
}
public static SparseTwinIndex <float> Process(SparseArray <float> production, float[] friction)
{
var ret = production.CreateSquareTwinArray <float>();
var flatRet = ret.GetFlatData();
var flatProduction = production.GetFlatData();
var numberOfZones = flatProduction.Length;
try
{
// Make all of the frictions to the power of E
Parallel.For(0, friction.Length, new ParallelOptions()
{
MaxDegreeOfParallelism = Environment.ProcessorCount
},
delegate(int i)
{
friction[i] = (float)Math.Exp(friction[i]);
});
Parallel.For(0, numberOfZones, new ParallelOptions()
{
MaxDegreeOfParallelism = Environment.ProcessorCount
},
delegate(int i)
{
float sum = 0f;
var iIndex = i * numberOfZones;
// gather the sum of the friction
for (int j = 0; j < numberOfZones; j++)
{
sum += friction[iIndex + j];
}
if (sum <= 0)
{
return;
}
sum = 1f / sum;
for (int j = 0; j < numberOfZones; j++)
{
flatRet[i][j] = flatProduction[i] * (friction[iIndex + j] * sum);
}
});
}
catch (AggregateException e)
{
if (e.InnerException is XTMFRuntimeException)
{
throw new XTMFRuntimeException(e.InnerException.Message);
}
else
{
throw new XTMFRuntimeException(e.InnerException.Message + "\r\n" + e.InnerException.StackTrace);
}
}
return(ret);
}
public static SparseTwinIndex<float> Process(SparseArray<float> production, float[] friction)
{
var ret = production.CreateSquareTwinArray<float>();
var flatRet = ret.GetFlatData();
var flatProduction = production.GetFlatData();
var numberOfZones = flatProduction.Length;
try
{
// Make all of the frictions to the power of E
Parallel.For( 0, friction.Length, new ParallelOptions() { MaxDegreeOfParallelism = Environment.ProcessorCount },
delegate(int i)
{
friction[i] = (float)Math.Exp( friction[i] );
} );
Parallel.For( 0, numberOfZones, new ParallelOptions() { MaxDegreeOfParallelism = Environment.ProcessorCount },
delegate(int i)
{
float sum = 0f;
var iIndex = i * numberOfZones;
// gather the sum of the friction
for ( int j = 0; j < numberOfZones; j++ )
{
sum += friction[iIndex + j];
}
if ( sum <= 0 )
{
return;
}
sum = 1f / sum;
for ( int j = 0; j < numberOfZones; j++ )
{
flatRet[i][j] = flatProduction[i] * ( friction[iIndex + j] * sum );
}
} );
}
catch ( AggregateException e )
{
if ( e.InnerException is XTMFRuntimeException )
{
throw new XTMFRuntimeException( e.InnerException.Message );
}
else
{
throw new XTMFRuntimeException( e.InnerException.Message + "\r\n" + e.InnerException.StackTrace );
}
}
return ret;
}
public void IterationStarting(int iteration)
{
ZoneSystem = Root.ZoneSystem.ZoneArray;
if (Data == null)
{
Data = ZoneSystem.CreateSquareTwinArray <float>().GetFlatData();
}
else
{
for (int i = 0; i < Data.Length; i++)
{
Array.Clear(Data[i], 0, Data[i].Length);
}
}
Activities = ActivitiesToCapture.Select(a => a.Activity).ToArray();
}
private void InitializeFriction(int length)
{
Friction = Productions.CreateSquareTwinArray <float>();
var flatFriction = Friction.GetFlatData();
Parallel.For(0, length, new ParallelOptions()
{
MaxDegreeOfParallelism = Environment.ProcessorCount
},
delegate(int i)
{
for (int j = 0; j < length; j++)
{
flatFriction[i][j] = (float)FrictionFunction(Productions.GetSparseIndex(i), Attractions.GetSparseIndex(j));
}
});
}
public SparseTwinIndex <float> ProcessFlow(float[] Friction, SparseArray <float> O, SparseArray <float> D)
{
float[] o = O.GetFlatData();
float[] d = D.GetFlatData();
var oLength = o.Length;
var dLength = d.Length;
var squareSize = oLength * dLength;
Stopwatch watch = new Stopwatch();
watch.Start();
gravityModelShader.NumberOfXThreads = length;
gravityModelShader.NumberOfYThreads = 1;
gravityModelShader.ThreadGroupSizeX = 64;
gravityModelShader.ThreadGroupSizeY = 1;
float[] balanced = new float[] { 0, this.Epsilon };
int iterations = 0;
var step1 = new int[] { oLength, 0, this.MaxIterations };
var step2 = new int[] { oLength, 1, this.MaxIterations };
if (flows == null || flows.Length != o.Length * d.Length)
{
flows = new float[squareSize];
}
SparseTwinIndex <float> ret = null;
Task createReturn = new Task(delegate()
{
ret = O.CreateSquareTwinArray <float>();
});
createReturn.Start();
FillAndLoadBuffers(o, d, Friction, balanced);
iterations = Balance(gpu, gravityModelShader, balancedBuffer, parameters, balanced, iterations, step1, step2);
gpu.Read(flowsBuffer, flows);
gravityModelShader.RemoveAllBuffers();
createReturn.Wait();
BuildDistribution(ret, O, D, oLength, flows);
watch.Stop();
using (StreamWriter writer = new StreamWriter("GPUPerf.txt", true))
{
writer.Write("Iterations:");
writer.WriteLine(iterations);
writer.Write("Time(ms):");
writer.WriteLine(watch.ElapsedMilliseconds);
}
return(ret);
}
private void ComputeDistances(SparseArray <IZone> zoneSparseArray)
{
var distances = zoneSparseArray.CreateSquareTwinArray <float>();
var flatDistnaces = distances.GetFlatData();
var zones = zoneSparseArray.GetFlatData();
var length = zones.Length;
// build all of the distances in parallel
Parallel.For(0, length, new ParallelOptions {
MaxDegreeOfParallelism = Environment.ProcessorCount
}, delegate(int i)
{
for (int j = 0; j < length; j++)
{
flatDistnaces[i][j] = (i == j) ? zones[i].InternalDistance
: CalcDistance(zones[i], zones[j]);
}
});
Distances = distances;
}
public void IterationStarting(int iteration)
{
ZoneSystem = Root.ZoneSystem.ZoneArray;
if(Data == null)
{
Data = ZoneSystem.CreateSquareTwinArray<float>().GetFlatData();
}
else
{
for(int i = 0; i < Data.Length; i++)
{
Array.Clear(Data[i], 0, Data[i].Length);
}
}
Activities = ActivitiesToCapture.Select(a => a.Activity).ToArray();
}
public SparseTwinIndex<float> ProcessFlow(float[] Friction, SparseArray<float> O, SparseArray<float> D)
{
float[] o = O.GetFlatData();
float[] d = D.GetFlatData();
var oLength = o.Length;
var dLength = d.Length;
var squareSize = oLength * dLength;
Stopwatch watch = new Stopwatch();
watch.Start();
gravityModelShader.NumberOfXThreads = length;
gravityModelShader.NumberOfYThreads = 1;
gravityModelShader.ThreadGroupSizeX = 64;
gravityModelShader.ThreadGroupSizeY = 1;
float[] balanced = new float[] { 0, this.Epsilon };
int iterations = 0;
var step1 = new int[] { oLength, 0, this.MaxIterations };
var step2 = new int[] { oLength, 1, this.MaxIterations };
if ( flows == null || flows.Length != o.Length * d.Length )
{
flows = new float[squareSize];
}
SparseTwinIndex<float> ret = null;
Task createReturn = new Task( delegate()
{
ret = O.CreateSquareTwinArray<float>();
} );
createReturn.Start();
FillAndLoadBuffers( o, d, Friction, balanced );
iterations = Balance( gpu, gravityModelShader, balancedBuffer, parameters, balanced, iterations, step1, step2 );
gpu.Read( flowsBuffer, flows );
gravityModelShader.RemoveAllBuffers();
createReturn.Wait();
BuildDistribution( ret, O, D, oLength, flows );
watch.Stop();
using ( StreamWriter writer = new StreamWriter( "GPUPerf.txt", true ) )
{
writer.Write( "Iterations:" );
writer.WriteLine( iterations );
writer.Write( "Time(ms):" );
writer.WriteLine( watch.ElapsedMilliseconds );
}
return ret;
}
public SparseTwinIndex<float> ProcessFlow(SparseArray<float> O, SparseArray<float> D, int[] validIndexes, SparseArray<float> attractionStar = null)
{
int length = validIndexes.Length;
Productions = O;
Attractions = D;
if(attractionStar == null)
{
AttractionsStar = D.CreateSimilarArray<float>();
}
else
{
AttractionsStar = attractionStar;
}
FlowMatrix = Productions.CreateSquareTwinArray<float>();
if(Friction == null)
{
InitializeFriction(length);
}
var flatAttractionStar = AttractionsStar.GetFlatData();
float[] oldTotal = new float[flatAttractionStar.Length];
var flatAttractions = Attractions.GetFlatData();
for(int i = 0; i < length; i++)
{
flatAttractionStar[i] = 1f;
oldTotal[i] = flatAttractions[i];
}
int iteration = 0;
float[] columnTotals = new float[length];
var balanced = false;
do
{
if(ProgressCallback != null)
{
// this doesn't go to 100%, but that is alright since when we end, the progress
// of the calling model should assume we hit 100%
ProgressCallback(iteration / (float)MaxIterations);
}
Array.Clear(columnTotals, 0, columnTotals.Length);
if(Vector.IsHardwareAccelerated)
{
VectorProcessFlow(columnTotals, FlowMatrix.GetFlatData());
}
else
{
ProcessFlow(columnTotals);
}
balanced = Balance(columnTotals, oldTotal);
} while((++iteration) < MaxIterations && !balanced);
if(ProgressCallback != null)
{
ProgressCallback(1f);
}
return FlowMatrix;
}
private void ComputeDistances(SparseArray<IZone> zoneSparseArray)
{
var distances = zoneSparseArray.CreateSquareTwinArray<float>();
var flatDistnaces = distances.GetFlatData();
var zones = zoneSparseArray.GetFlatData();
var length = zones.Length;
// build all of the distances in parallel
Parallel.For( 0, length, new ParallelOptions() { MaxDegreeOfParallelism = Environment.ProcessorCount }, delegate(int i)
{
for ( int j = 0; j < length; j++ )
{
flatDistnaces[i][j] = ( i == j ) ? zones[i].InternalDistance
: CalcDistance( zones[i], zones[j] );
}
} );
Distances = distances;
}
