using Core.Utils.Cloners;
using System.Text.Json.Serialization;
namespace Core.Utils.Collections;
///
/// Array of ProbabilityObjectArray which allow to randomly draw of the contained objects
/// based on the relative probability of each of its elements.
/// The probabilities of the contained element is not required to be normalized.
///
/// Example:
/// po = new ProbabilityObjectArray(
/// new ProbabilityObject("a", 5),
/// new ProbabilityObject("b", 1),
/// new ProbabilityObject("c", 1)
/// );
/// res = po.draw(10000);
/// // count the elements which should be distributed according to the relative probabilities
/// res.filter(x => x==="b").reduce((sum, x) => sum + 1 , 0)
///
///
///
///
public class ProbabilityObjectArray : List>
{
private readonly ICloner _cloner;
private readonly MathUtil _mathUtil;
public ProbabilityObjectArray(
MathUtil mathUtil,
ICloner cloner,
ICollection>? items = null
) : base(items ?? [])
{
_mathUtil = mathUtil;
_cloner = cloner;
}
///
/// Calculates the normalized cumulative probability of the ProbabilityObjectArray's elements normalized to 1
///
/// The relative probability values of which to calculate the normalized cumulative sum
/// Cumulative Sum normalized to 1
public List CumulativeProbability(List probValues)
{
var sum = _mathUtil.ListSum(probValues);
var probCumsum = _mathUtil.ListCumSum(probValues);
probCumsum = _mathUtil.ListProduct(probCumsum, 1D / sum);
return probCumsum;
}
///
/// Filter What is inside ProbabilityObjectArray
///
///
/// Filtered results
public ProbabilityObjectArray Filter(Predicate> predicate)
{
var result = new ProbabilityObjectArray(_mathUtil, _cloner, new List>());
foreach (var probabilityObject in this)
if (predicate.Invoke(probabilityObject))
result.Add(probabilityObject);
return result;
}
///
/// Deep clone this ProbabilityObjectArray
///
/// Deep Copy of ProbabilityObjectArray
public ProbabilityObjectArray Clone()
{
var clone = _cloner.Clone(this);
var probabilityObjects = new ProbabilityObjectArray(
_mathUtil,
_cloner,
new List>()
);
probabilityObjects.AddRange(clone);
return probabilityObjects;
}
///
/// Drop an element from the ProbabilityObjectArray
///
/// The key of the element to drop
/// ProbabilityObjectArray without the dropped element
public ProbabilityObjectArray Drop(K key)
{
return (ProbabilityObjectArray)this.Where((r) => !r.Key?.Equals(key) ?? false);
}
///
/// Return the data field of an element of the ProbabilityObjectArray
///
/// The key of the element whose data shall be retrieved
/// Stored data object
public V? Data(K key)
{
var element = this.FirstOrDefault(r => r.Key?.Equals(key) ?? false);
return element == null ? default : element.Data;
}
///
/// Get the relative probability of an element by its key
///
/// Example:
/// po = new ProbabilityObjectArray(new ProbabilityObject("a", 5), new ProbabilityObject("b", 1))
/// po.maxProbability() // returns 5
///
/// Key of element whose relative probability shall be retrieved
/// The relative probability
public double? Probability(K key)
{
var element = this.FirstOrDefault(r => r.Key.Equals(key));
return element?.RelativeProbability;
}
/**
* Get the maximum relative probability out of a ProbabilityObjectArray
*
* Example:
* po = new ProbabilityObjectArray(new ProbabilityObject("a", 5), new ProbabilityObject("b", 1))
* po.maxProbability() // returns 5
*
* @return {number} the maximum value of all relative probabilities in this ProbabilityObjectArray
*/
public double MaxProbability()
{
return this.Max(x => x.RelativeProbability).Value;
}
///
/// Get the minimum relative probability out of a ProbabilityObjectArray
/// * Example:
/// po = new ProbabilityObjectArray(new ProbabilityObject("a", 5), new ProbabilityObject("b", 1))
/// po.minProbability() // returns 1
///
/// the minimum value of all relative probabilities in this ProbabilityObjectArray
public double MinProbability()
{
return this.Min(x => x.RelativeProbability.Value);
}
/**
* Draw random element of the ProbabilityObject N times to return an array of N keys.
* Drawing can be with or without replacement
* @param count The number of times we want to draw
* @param removeAfterDraw Draw with or without replacement from the input dict (true = dont remove after drawing)
* @param lockList list keys which shall be replaced even if drawing without replacement
* @returns Array consisting of N random keys for this ProbabilityObjectArray
*/
public List Draw(int drawCount = 1, bool removeAfterDraw = true, List? neverRemoveWhitelist = null)
{
neverRemoveWhitelist ??= [];
if (Count == 0) return [];
var totals = this.Aggregate(
new { probArray = new List(), keyArray = new List() },
(acc, x) =>
{
acc.probArray.Add(x.RelativeProbability.Value);
acc.keyArray.Add(x.Key);
return acc;
}
);
var probCumsum = CumulativeProbability(totals.probArray);
var drawnKeys = new List();
for (var i = 0; i < drawCount; i++)
{
var rand = Random.Shared.NextDouble();
var randomIndex = (int)probCumsum.FindIndex((x) => x > rand);
// We cannot put Math.random() directly in the findIndex because then it draws anew for each of its iteration
if (removeAfterDraw || neverRemoveWhitelist.Contains(totals.keyArray[randomIndex]))
{
// Add random item from possible value into return array
drawnKeys.Add(totals.keyArray[randomIndex]);
}
else
{
// We draw without replacement -> remove the key and its probability from array
var key = totals.keyArray[randomIndex];
totals.keyArray.RemoveAt(randomIndex);
_ = totals.probArray[randomIndex];
totals.probArray.RemoveAt(randomIndex);
drawnKeys.Add(key);
probCumsum = CumulativeProbability(totals.probArray);
// If we draw without replacement and the ProbabilityObjectArray is exhausted we need to break
if (totals.keyArray.Count < 1) break;
}
}
return drawnKeys;
}
}
///
/// A ProbabilityObject which is use as an element to the ProbabilityObjectArray array
/// It contains a key, the relative probability as well as optional data.
///
///
///
public class ProbabilityObject
{
public ProbabilityObject()
{
}
/**
* constructor for the ProbabilityObject
* @param {string} key The key of the element
* @param {number} relativeProbability The relative probability of this element
* @param {any} data Optional data attached to the element
*/
public ProbabilityObject(K key, double? relativeProbability, V? data)
{
Key = key;
RelativeProbability = relativeProbability;
Data = data;
}
[JsonPropertyName("key")]
public K? Key { get; set; }
///
/// Weighting of key compared to other ProbabilityObjects
///
[JsonPropertyName("relativeProbability")]
public double? RelativeProbability { get; set; }
[JsonPropertyName("data")]
public V? Data { get; set; }
}