public void SeesCorrectSubmatrixWhenTrainingWith0_5Coverage()
{
var inputsize = 10;
var size = (uint)inputsize / 2;
var coverage = 0.5;
var layer = new Spatial2DLayer(SpatialLayerType.Gaussian, size, size, coverage, true, 1000);
var list = from i in Enumerable.Range(0, inputsize)
select (double)i;
var matrix = new SparseMatrix(inputsize, inputsize);
for (int i = 0; i < matrix.RowCount; ++i)
{
matrix.SetRow(i, list.ToArray());
}
// for each node in the 2D layer
for (int nodeRow = 0; nodeRow < layer.Height; nodeRow++)
{
for (int nodeCol = 0; nodeCol < layer.Width; nodeCol++)
{
// Act
var subMatrix = layer.GetSubMatrixForNodeAt(nodeRow, nodeCol, matrix);
// check if its 2D input is ok
var width = inputsize / size + coverage * (inputsize - inputsize / size);
var delta = (inputsize - width) / (size - 1);
for (int i = 0; i < (int)width; i++)
{
for (int j = 0; j < (int)width; j++)
{
Assert.AreEqual(nodeCol * delta + j, subMatrix[i, j]);
}
}
}
}
}
public void SeesCorrectSubmatrixWhenCloneTrainingWith0Coverage()
{
var inputsize = 10;
var size = (uint)inputsize / 2;
var coverage = 0.0;
var layer = new Spatial2DLayer(SpatialLayerType.Gaussian, size, size, coverage, true, 1000);
var list = from i in Enumerable.Range(0, inputsize)
select (double)i;
var matrix = new SparseMatrix(inputsize, inputsize);
for (int i = 0; i < matrix.RowCount; ++i)
{
matrix.SetRow(i, list.ToArray());
}
// Act
var subMatrix = layer.GetSubMatrixForNodeAt(layer.ClonedNodeRow, layer.ClonedNodeCol, matrix);
//
var width = inputsize / size + coverage * (inputsize - inputsize / size);
var delta = (inputsize - width) / (size - 1);
var centerRow = layer.Height / 2;
var centerCol = layer.Width / 2;
for (int i = 0; i < (int)width; i++)
{
for (int j = 0; j < (int)width; j++)
{
Assert.AreEqual(centerCol * delta + j, subMatrix[i, j]);
}
}
}