/// <summary>
/// Constructor
/// </summary>
/// <param name="rTemplate"></param>
/// <param name="newRect"></param>
/// <param name="rOutputRaster"></param>
public PointDensity(Raster rDEM, Vector vPointCloud, Raster OutputRaster, RasterOperators.KernelShapes eKernel, decimal fSize)
: base(new List <Raster>() { rDEM }, OutputRaster)
{
_vinput = vPointCloud;
_routput = OutputRaster;
_kshape = eKernel;
_fsize = (double)fSize;
_fsizedec = fSize;
// set the rows to be a certain multiple of fSize windows
chunkRows = (int)Math.Ceiling((NUMWINDOWS * fSize) / Math.Abs(rDEM.Extent.CellHeight));
// Calling this again after setting the rows will give us a nicer chunk size
SetOpExtent(OpExtent);
VectorChunkExtent = ChunkExtent.Buffer(_fsizedec);
switch (eKernel)
{
case RasterOperators.KernelShapes.Circle:
area = Math.PI * Math.Pow((double)fSize, 2);
break;
case RasterOperators.KernelShapes.Square:
area = Math.Pow((double)fSize * 2, 2);
break;
}
}
/// <summary>
/// Chunk op implementation
/// </summary>
/// <param name="data"></param>
/// <param name="outChunk"></param>
protected override void ChunkOp(List <double[]> data, List <double[]> outBuffers)
{
// Get all the points in this chunk
VectorChunkExtent = ChunkExtent.Buffer(_fsizedec);
List <Geometry>[,] bins = BinPoints(_vinput.GeometriesIntersectExtent(VectorChunkExtent));
for (int cid = 0; cid < outBuffers[0].Length; cid++)
{
// Save us a metric Tonne of effort by giving up on nodatavals in the DEM
if (data[0][cid] == inNodataVals[0])
{
outBuffers[0][cid] = outNodataVals[0];
}
else
{
double outval = 0;
decimal[] cidxy = ChunkExtent.Id2XY(cid);
Geometry pt2 = new Geometry(wkbGeometryType.wkbPoint);
pt2.AddPoint((double)cidxy[0], (double)cidxy[1], 0);
List <int[]> bins2test = GetRelevantBins(pt2);
// create a circle and then buffer it.
foreach (int[] binids in bins2test)
{
if (binids[0] < bins.GetLength(0) && binids[1] < bins.GetLength(1))
{
foreach (Geometry pt in bins[binids[0], binids[1]])
{
// If we're a circle we have to do a more expensive operation now
if (_kshape == RasterOperators.KernelShapes.Circle)
{
if (InsideRadius(pt, pt2))
{
outval++;
}
}
else if (InsideSquare(pt, pt2))
{
outval++;
}
}
}
}
outBuffers[0][cid] = outval / area;
}
}
}
/// <summary>
///
/// </summary>
/// <param name="data"></param>
/// <param name="id"></param>
/// <returns></returns>
protected override void CellOp(List <double[]> data, List <double[]> outputs, int id)
{
outputs[0][id] = outNodataVals[0];
// Speed things up by ignoring nodatas
if (data[0][id] == inNodataVals[0])
{
return;
}
// With multimethod errors we need to do some fancy footwork
if (_hasVectorPolymask)
{
if (_shapemask.Count > 0)
{
decimal[] ptcoords = ChunkExtent.Id2XY(id);
// Is this point in one (or more) of the shapes?
List <string> shapes = _polymask.ShapesContainPoint((double)ptcoords[0], (double)ptcoords[1], _fieldname);
// Now we need to decide what to do based on how many intersections we found.
if (shapes.Count == 1)
{
outputs[0][id] = CellChangeCalc(shapes[0], data, id);
}
else if (shapes.Count > 1)
{
throw new NotImplementedException("Overlapping shapes is not yet supported");
}
}
}
else if (_hasRasterizedPolymask)
{
// The rasterized polymask layer will always be Raster [1].
double rPolymaskVal = data[1][id];
if (rPolymaskVal != inNodataVals[1])
{
string fldVal = _rasterVectorFieldVals[(int)rPolymaskVal];
outputs[0][id] = CellChangeCalc(fldVal, data, id);
}
}
// Single method is easier
else
{
outputs[0][id] = CellChangeCalc("", data, id);
}
}
/// <summary>
/// The budget seggregator looks to see if a cell is inside any of the features
/// </summary>
/// <param name="data"></param>
/// <param name="id"></param>
private void VectorBudgetSegCellOp(List <double[]> data, int id)
{
if (_shapemask.Count > 0)
{
decimal[] ptcoords = ChunkExtent.Id2XY(id);
List <string> shapes = _polymask.ShapesContainPoint((double)ptcoords[0], (double)ptcoords[1], _fieldname, _shapemask);
if (shapes.Count > 0)
{
foreach (string fldVal in shapes)
{
if (!SegStats.ContainsKey(fldVal))
{
SegStats[fldVal] = new DoDStats(Stats);
}
CellChangeCalc(data, id, SegStats[fldVal]);
}
}
}
}
/// <summary>
/// The budget seggregator looks to see if a cell is inside any of the features
/// </summary>
/// <param name="data"></param>
/// <param name="id"></param>
private void VectorBudgetSegCellOp(List <double[]> data, int id)
{
if (_shapemask.Count > 0)
{
decimal[] ptcoords = ChunkExtent.Id2XY(id);
List <string> shapes = _polymask.ShapesContainPoint((double)ptcoords[0], (double)ptcoords[1], _fieldname, _shapemask);
if (shapes.Count > 0)
{
foreach (string fldVal in shapes)
{
if (!SegHistograms.ContainsKey(fldVal))
{
SegHistograms[fldVal] = new Histogram(_segNumBins, _inputRasters[0]);
}
SegHistograms[fldVal].AddBinVal(data[0][id]);
}
}
}
}
/// <summary>
/// Find the intersection of each cell
/// </summary>
/// <param name="data"></param>
/// <param name="outputs"></param>
/// <param name="id"></param>
protected override void CellOp(List <int[]> data, List <int[]> outputs, int id)
{
outputs[0][id] = outNodataVals[0];
if (_shapemask.Count > 0 && data[0][id] != inNodataVals[0])
{
decimal[] ptcoords = ChunkExtent.Id2XY(id);
List <string> shapes = _polymask.ShapesContainPoint((double)ptcoords[0], (double)ptcoords[1], _fieldname, _shapemask);
if (shapes.Count > 0)
{
// Add a dictionary entry if we need to
if (!_fieldvals.Contains(shapes[0]))
{
_fieldvals.Add(shapes[0]);
}
// 0 is our nodataval here so we pad the list by 1.
// Now we just need to remember that the raster is perpertually off by one
outputs[0][id] = _fieldvals.IndexOf(shapes[0]) + 1;
}
}
}
/// <summary>
/// The actual cell-by-cell operations
/// </summary>
/// <param name="data"></param>
/// <param name="id"></param>
/// <returns></returns>
protected override void CellOp(List <T[]> data, List <T[]> outputs, int id)
{
T val = outNodataVals[0];
// This is the raster and scalar case
if (_scalar)
{
if (!data[0][id].Equals(inNodataVals[0]))
{
switch (_type)
{
// Choose your math operation
case RasterOperators.MathOpType.Addition:
val = DynamicMath.Add(data[0][id], _operand);
break;
case RasterOperators.MathOpType.Subtraction:
val = DynamicMath.Subtract(data[0][id], _operand);
break;
case RasterOperators.MathOpType.Multipication:
val = DynamicMath.Multiply(data[0][id], _operand);
break;
case RasterOperators.MathOpType.Division:
val = DynamicMath.Divide(data[0][id], _operand);
break;
}
}
}
// This is the two raster case
else
{
bool masked = false;
// Pure vector method. (This is the slow way)
if (_hasVectorPolymask)
{
decimal[] ptcoords = ChunkExtent.Id2XY(id);
List <long> shapes = _polymask.ShapesContainPoint((double)ptcoords[0], (double)ptcoords[1], _shapemask);
if (shapes.Count == 0)
{
masked = true;
}
}
// Rasterized vector method
else if (_hasRasterizedPolymask && data.Count == 3 && data[2][id].Equals(inNodataVals[2]))
{
masked = true;
}
if (!data[0][id].Equals(inNodataVals[0]) && !data[1][id].Equals(inNodataVals[1]) && !masked)
{
switch (_type)
{
// Choose your math operation
case RasterOperators.MathOpType.Addition:
val = DynamicMath.Add(data[0][id], data[1][id]);
break;
case RasterOperators.MathOpType.Subtraction:
val = DynamicMath.Subtract(data[0][id], data[1][id]);
break;
case RasterOperators.MathOpType.Multipication:
val = DynamicMath.Multiply(data[0][id], data[1][id]);
break;
case RasterOperators.MathOpType.Division:
val = DynamicMath.Divide(data[0][id], data[1][id]);
break;
}
}
}
outputs[0][id] = val;
}
