public BitmapSource Render(RenderSourceType render_source)
{
IImageRaster <IRaster2DInteger, ElementValueType> rendered_image = inner_renderer.Render(render_source);
BitmapFast bitmap_fast = new BitmapFast(rendered_image.Raster.Size0, rendered_image.Raster.Size1);
bitmap_fast.Lock();
for (int y_index = 0; y_index < rendered_image.Raster.Size1; y_index++)
{
for (int x_index = 0; x_index < rendered_image.Raster.Size0; x_index++)
{
bitmap_fast.SetPixel(x_index, y_index, converter.Compute(rendered_image.GetElementValue(rendered_image.Raster.GetElementIndex(x_index, y_index))));
}
}
bitmap_fast.Unlock();
return(ToolsRendering.CreateBitmapSourceFromBitmap(bitmap_fast.Bitmap));
}
public BitmapFast Render(RenderSourceType render_source)
{
IImageRaster <IRaster2DInteger, ElementValueType> rendered_image = inner_renderer.Render(render_source);
BitmapFast bitmap_fast = new BitmapFast(rendered_image.Raster.Size0, rendered_image.Raster.Size1);
bitmap_fast.Lock();
//for (int y_index = 0; y_index < rendered_image.Raster.SizeY; y_index++)
//{
Parallel.For(0, rendered_image.Raster.Size1, y_index =>
{
for (int x_index = 0; x_index < rendered_image.Raster.Size0; x_index++)
{
bitmap_fast.SetPixel(x_index, y_index, converter.Compute(rendered_image.GetElementValue(rendered_image.Raster.GetElementIndex(x_index, y_index))));
}
});
bitmap_fast.Unlock();
return(bitmap_fast);
}
public void Render(BitmapFast bitmap_fast, Tuple <IImageRaster2D <bool>, IImageRaster2D <Color> > render_image)
{
IImageRaster2D <bool> mask = render_image.Item1;
IImageRaster2D <Color> color = render_image.Item2;
bitmap_fast.Lock();
for (int y_index = 0; y_index < bitmap_fast.Height; y_index++)
{
for (int x_index = 0; x_index < bitmap_fast.Width; x_index++)
{
if (mask.GetElementValue(x_index, y_index))
{
bitmap_fast.SetPixel(x_index, y_index, color.GetElementValue(x_index, y_index));
}
}
}
bitmap_fast.Unlock();
}
public BitmapFast Render(Tuple <double[][], Color[]> render_image)
{
double[][] points = render_image.Item1;
Color[] colors = render_image.Item2;
double [][] projected_points = new double [points.Length][];
int[] coordinates = new int[3];
for (int point_index = 0; point_index < points.Length; point_index++)
{
projected_points[point_index] = (projection_matrix * (points[point_index] - offset_matrix)).ToArray1DFloat64();
}
Raster2DInteger bitmap_raster = new Raster2DInteger(bitmap_size_x, bitmap_size_y);
BitmapFast destination_image = new BitmapFast(this.bitmap_size_x, this.bitmap_size_y);
destination_image.Lock();
for (int index_y = 0; index_y < bitmap_raster.Size1; index_y++)
{
for (int index_x = 0; index_x < bitmap_raster.Size0; index_x++)
{
destination_image.SetPixel(index_x, index_y, Color.Black);
}
}
for (int element_index = 0; element_index < points.Length; element_index++)
{
int x_target = (int)(projected_points[element_index][0] * this.scale) + (bitmap_raster.Size0 / 2);
int y_target = (int)(projected_points[element_index][1] * this.scale) + (bitmap_raster.Size1 / 2);
if (bitmap_raster.ContainsCoordinates(x_target, y_target))
{
destination_image.SetPixel(x_target, y_target, colors[element_index]);
}
}
destination_image.Unlock();
return(destination_image);
}
private static void ProccessDataSetNominalPCA(IDataSet <int, int> training_set, IDataSet <int, int> test_set)
{
int cluster_count = 10;
int instance_count = training_set.InstanceCount;
ITemplateClusteringCentroid <int, IDataSet <int> > template_cluster = new TemplateClusteringKMeansNominal(cluster_count);
TemplateDimensionReductionPCADefault template_pca = new TemplateDimensionReductionPCADefault(3);
IDataSet <int> training_set_unlabeled = training_set;
IClusteringCentroid <int> clustering = template_cluster.Cluster(training_set_unlabeled);
double[][] transformed_data1 = new double[instance_count][];
for (int instance_index = 0; instance_index < instance_count; instance_index++)
{
transformed_data1[instance_index] = clustering.Transform(training_set_unlabeled.GetInstanceFeatureData(instance_index));
}
IDataSet <double> data_set_transformed1 = new DataSet <double, int>(transformed_data1);
ITransform transform = template_pca.GenerateTransform(data_set_transformed1);
double[][] transformed_data2 = new double[instance_count][];
int[][] label_data = training_set.LabelData;
Color[] instance_colors = new Color[instance_count];
Color[] label_colors = ToolsColor.GetPallete(training_set.DataContext.GetLabelDescriptor(0).ValueCount);
for (int instance_index = 0; instance_index < instance_count; instance_index++)
{
transformed_data2[instance_index] = transform.TransformForward(data_set_transformed1.GetInstanceFeatureData(instance_index));
instance_colors[instance_index] = label_colors[label_data[instance_index][0]];
}
RendererPoints <Matrix <double> > renderer = new RendererPoints <Matrix <double> >(new AlgebraLinearReal64MathNet(), 1000, 1000, (AngleRadian)0, (AngleRadian)0, 10);
BitmapFast bitmap = renderer.Render(new Tuple <double[][], Color[]>(transformed_data2, instance_colors));
bitmap.Bitmap.Save("test.png");
}
