/// <summary>
/// Generates a histogram from some samples, grouping by a show function.
/// </summary>
/// <param name="scale">Scale factor. Defaults to 40</param>
public static string Finite <A>(Samples <A> itemProbs, Func <A, string> showFunc = null, double scale = DEFAULT_SCALE)
{
if (!itemProbs.Weights.Any())
{
return("No data to graph.");
}
if (showFunc == null)
{
showFunc = a => a.ToString();
}
var normalized = Importance.Normalize(CompactUnordered(itemProbs, showFunc));
var sb = new StringBuilder();
var display = normalized.Weights.Select(ip => new Tuple <string, int, Prob>(showFunc(ip.Item), (int)Math.Floor(ip.Prob.Value * scale), ip.Prob));
var maxWidth = display.Select(d => d.Item1.Length).Max();
var barScale = BarScale(display.Select(d => d.Item2), scale);
foreach (var line in display)
{
var item = line.Item1;
var barLength = (int)(line.Item2 * barScale);
sb.AppendLine($"{item.PadLeft(maxWidth)} {line.Item3,6} {Bar(barLength)}");
}
return(sb.ToString());
}
/// <summary>
/// Finite uniform distribution over list of items.
/// Only composable with other finite distributions.
/// </summary>
public static FiniteDist <A> EnumUniformF <A>(IEnumerable <A> items)
{
var uniform = Samples(items.Select(i => new ItemProb <A>(i, Prob(1))));
return(new FiniteDist <A>(Importance.Normalize(uniform)));
}
public static Samples <A> Normalize <A>(this Samples <A> self)
{
return(Importance.Normalize(self));
}
/// <summary>
/// Aggregate & normalize samples
/// The samples are arranged in ascending order
/// </summary>
public static Samples <A> Enumerate <A, Key>(FiniteDist <A> dist, Func <A, Key> keyFunc) where A : IComparable <A>
{
return(Importance.Normalize(Compact(dist.Explicit, keyFunc)));
}