public double Overlap(ColorAssignment other)
{
double score = 0;
//score the two palettes
if (colors.Keys.SequenceEqual <String>(other.colors.Keys))
{
foreach (String key in colors.Keys)
{
if (other.colors[key] == this.colors[key])
{
score += 1;
}
}
score /= colors.Keys.Count();
}
else
{
//something is wrong
Console.WriteLine("The two palettes are not compatible");
throw new ArgumentException();
}
return(score);
}
public Bitmap RenderAssignment(ColorAssignment assignment)
{
int numMembers = assignment.Keys.Count();
int colorSize = 20;
int padding = 2;
int textWidth = 120;
int topPadding = 10;
Bitmap result = new Bitmap(textWidth + colorSize + padding, numMembers * colorSize + padding + topPadding);
Graphics pg = Graphics.FromImage(result);
pg.FillRectangle(new SolidBrush(Color.White), 0, 0, result.Width, result.Height);
Brush black = new SolidBrush(Color.Black);
Font headers = new Font("Arial", 9);
//write out the concept titles
for (int w = 0; w < numMembers; w++)
{
pg.DrawString(assignment.Keys[w], headers, black, 0, w * colorSize + topPadding);
}
//draw the assigned colors
for (int w = 0; w < assignment.Keys.Count(); w++)
{
int x = textWidth;
int y = w * colorSize + topPadding;
pg.FillRectangle(new SolidBrush(assignment.Get(assignment.Keys[w])), x, y, colorSize - padding, colorSize - padding);
}
return(result);
}
public ColorAssignment AssignColors(Category category)
{
//check that number of category members is less than number of palette colors
if (category.members.Count() > paletteHex.Count())
{
throw new ArgumentException("Too many category members, or not enough palette colors!");
}
//Get the images, if needed
SearchImages(category, 3);
//Compute the histograms
ComputeHistograms(category);
//Compute affinities and assign colors
double[,] affinities = ComputeAffinities(category);
//Since the Hungarian Algorithm minimizes sum of affinities, let's invert the affinities
//Assume that the number of category members is less than the number of palette colors
double[,] matrix = new double[paletteHex.Count(), paletteHex.Count()];
for (int c = 0; c < paletteHex.Count(); c++)
{
for (int w = 0; w < category.members.Count(); w++)
{
matrix[w, c] = 1 - affinities[c, w];
}
}
//create an assignment from colors to concept names
List <int> assignIds = HungarianAlgorithm.Solve(matrix);
ColorAssignment assignment = new ColorAssignment(category);
for (int w = 0; w < category.members.Count(); w++)
{
assignment.Set(category.members[w], paletteRGB[assignIds[w]]);
}
return(assignment);
}
public double Overlap(ColorAssignment other)
{
double score = 0;
//score the two palettes
if (colors.Keys.SequenceEqual<String>(other.colors.Keys))
{
foreach (String key in colors.Keys)
{
if (other.colors[key] == this.colors[key])
score += 1;
}
score /= colors.Keys.Count();
}
else
{
//something is wrong
Console.WriteLine("The two palettes are not compatible");
throw new ArgumentException();
}
return score;
}
public Bitmap RenderAssignment(ColorAssignment assignment)
{
int numMembers = assignment.Keys.Count();
int colorSize = 20;
int padding = 2;
int textWidth = 120;
int topPadding = 10;
Bitmap result = new Bitmap(textWidth + colorSize+padding, numMembers * colorSize + padding+topPadding);
Graphics pg = Graphics.FromImage(result);
pg.FillRectangle(new SolidBrush(Color.White), 0, 0, result.Width, result.Height);
Brush black = new SolidBrush(Color.Black);
Font headers = new Font("Arial", 9);
//write out the concept titles
for (int w = 0; w < numMembers; w++)
{
pg.DrawString(assignment.Keys[w], headers, black, 0, w * colorSize+topPadding);
}
//draw the assigned colors
for (int w = 0; w < assignment.Keys.Count(); w++)
{
int x = textWidth;
int y = w * colorSize+topPadding;
pg.FillRectangle(new SolidBrush(assignment.Get(assignment.Keys[w])), x, y, colorSize - padding, colorSize - padding);
}
return result;
}
public ColorAssignment AssignColors(Category category)
{
//check that number of category members is less than number of palette colors
if (category.members.Count() > paletteHex.Count())
throw new ArgumentException("Too many category members, or not enough palette colors!");
//Get the images, if needed
SearchImages(category, 3);
//Compute the histograms
ComputeHistograms(category);
//Compute affinities and assign colors
double[,] affinities = ComputeAffinities(category);
//Since the Hungarian Algorithm minimizes sum of affinities, let's invert the affinities
//Assume that the number of category members is less than the number of palette colors
double[,] matrix = new double[paletteHex.Count(), paletteHex.Count()];
for (int c=0; c<paletteHex.Count(); c++)
for (int w=0; w<category.members.Count(); w++)
matrix[w,c] = 1-affinities[c,w];
//create an assignment from colors to concept names
List<int> assignIds = HungarianAlgorithm.Solve(matrix);
ColorAssignment assignment = new ColorAssignment(category);
for (int w = 0; w < category.members.Count(); w++)
{
assignment.Set(category.members[w], paletteRGB[assignIds[w]]);
}
return assignment;
}