/// <summary>
/// perform a test
/// </summary>
/// <param name="test_index">index number of the test to be performed</param>
private void PerformTest(int test_index)
{
// initialise
init();
switch (test_index)
{
case 0: // motion model
{
test_motion_model(true);
break;
}
case 1: // stereo ray models
{
bool mirror = false;
stereo_model.showProbabilities(grid_layer,
grid_dimension,
img_rays, standard_width, standard_height,
false, true, mirror);
break;
}
case 2: // gaussian distribution function
{
stereo_model.showDistribution(img_rays, standard_width, standard_height);
break;
}
case 3: // a single stereo ray model
{
createSingleRayModel(false);
break;
}
case 4: // sensor model lookups
{
createSensorModelLookup();
break;
}
case 5: // path planner
{
test_path_planner(200, 50);
break;
}
}
// make a larger image
byte[] img_large = image.downSample(img_rays, standard_width, standard_height,
standard_width * 2, standard_height * 2);
// display the results
imgOutput.Pixbuf = GtkBitmap.createPixbuf(standard_width * 2, standard_height * 2);
GtkBitmap.setBitmap(img_large, imgOutput);
}
private void gaussianFunctionToolStripMenuItem_Click(object sender, EventArgs e)
{
grid_layer = new float[grid_dimension, grid_dimension, 3];
pos3D_x = new float[4];
pos3D_y = new float[4];
stereo_model = new stereoModel();
robot_head = new stereoHead(4);
stereo_features = new float[900];
stereo_uncertainties = new float[900];
img_rays = new Byte[standard_width * standard_height * 3];
rays = new Bitmap(standard_width, standard_height, System.Drawing.Imaging.PixelFormat.Format24bppRgb);
picRays.Image = rays;
stereo_model.showDistribution(img_rays, standard_width, standard_height);
BitmapArrayConversions.updatebitmap_unsafe(img_rays, (Bitmap)picRays.Image);
}
