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source: branches/3140_NumberSymbol/HeuristicLab.ExtLibs/HeuristicLab.SimSharp/3.3.2/SimSharp-3.3.2/Analysis/SampleMonitor.cs @ 18091

Last change on this file since 18091 was 18023, checked in by jkarder, 3 years ago

#3065: update Sim# to 3.3.2

File size: 10.6 KB
Line 
1#region License Information
2/*
3 * This file is part of SimSharp which is licensed under the MIT license.
4 * See the LICENSE file in the project root for more information.
5 */
6#endregion
7
8using System;
9using System.Collections.Generic;
10using System.Linq;
11using System.Text;
12
13namespace SimSharp {
14  /// <summary>
15  /// This class calculates some descriptive statistics by
16  /// remembering all data. All observed values are equally weighed.
17  ///
18  /// It can be used to calculate e.g. lead times of processes.
19  /// </summary>
20  public sealed class SampleMonitor : ISampleMonitor {
21    /// <summary>
22    /// Can only be set in the constructor.
23    /// When it is true, median and percentiles can be computed and a
24    /// histogram can be printed. In addition <see cref="Samples"/>
25    /// may return all the remembered values for further processing.
26    /// </summary>
27    public bool Collect { get; }
28
29    /// <summary>
30    /// The monitor can be set to suppress updates. When it is set
31    /// to false, the statistics will not be updated and new samples
32    /// are ignored.
33    /// </summary>
34    public bool Active { get; set; }
35
36    /// <summary>
37    /// The name of the variable that is being monitored.
38    /// Used for output in <see cref="Summarize(bool, int, double?, double?)"/>.
39    /// </summary>
40    public string Name { get; set; }
41
42    public int Count { get; private set; }
43
44    public double Min { get; private set; }
45    public double Max { get; private set; }
46    public double Total { get; private set; }
47    double INumericMonitor.Sum { get { return Total; } }
48    public double Mean { get; private set; }
49    public double StdDev { get { return Math.Sqrt(Variance); } }
50    public double Variance { get { return (Count > 0) ? variance / Count : 0.0; } }
51    private double variance;
52    public double Last { get; private set; }
53
54    private List<double> samples;
55    /// <summary>
56    /// Returns the list of collected values, or an empty enumerable
57    /// when <see cref="Collect"/> was initialized to false.
58    /// </summary>
59    public IEnumerable<double> Samples { get { return samples != null ? samples.AsEnumerable() : Enumerable.Empty<double>(); } }
60
61
62    /// <summary>
63    /// Calls <see cref="GetPercentile(double)"/>.
64    /// </summary>
65    /// <remarks>
66    /// Median can only be computed when the monitor was initialized to collect the data.
67    ///
68    /// The data is preprocessed on every call, the runtime complexity of this method is therefore O(n * log(n)).
69    /// </remarks>
70    /// <returns>The median (50th percentile) of the samples.</returns>
71    public double GetMedian() {
72      return GetPercentile(0.5);
73    }
74
75    /// <summary>
76    /// Calculates the p-percentile of the samples.
77    /// </summary>
78    /// <remarks>
79    /// Percentiles can only be computed when the monitor was initialized to collect the data.
80    ///
81    /// The data is preprocessed on every call, the runtime complexity of this method is therefore O(n * log(n)).
82    /// </remarks>
83    /// <exception cref="ArgumentException">Thrown when <paramref name="p"/> is outside the valid range.</exception>
84    /// <param name="p">The percentile has to be in the range [0;1].</param>
85    /// <returns>The respective percentile of the samples.</returns>
86    public double GetPercentile(double p) {
87      if (p < 0 || p > 1) throw new ArgumentException("Percentile must be between 0 and 1", "p");
88      if (!Collect) return double.NaN;
89      return GetPercentile(samples, p);
90    }
91
92    private static double GetPercentile(IList<double> s, double p) {
93      if (p < 0 || p > 1) throw new ArgumentException("Percentile must be between 0 and 1", "p");
94      if (s.Count == 0) return double.NaN;
95      var n = s.Count * p;
96      var k = (int)Math.Ceiling(n);
97      if (n < k)
98        return s.OrderBy(x => x).Skip(k - 1).First();
99      return s.OrderBy(x => x).Skip(k - 1).Take(2).Average();
100    }
101
102    public SampleMonitor(string name = null, bool collect = false) {
103      Active = true;
104      Name = name;
105      Collect = collect;
106      if (collect) samples = new List<double>(64);
107    }
108
109    public void Reset() {
110      Count = 0;
111      Min = Max = Total = Mean = 0;
112      variance = 0;
113      Last = 0;
114      if (Collect) samples.Clear();
115    }
116
117    public void Add(double value) {
118      if (!Active) return;
119
120      if (double.IsNaN(value) || double.IsInfinity(value))
121        throw new ArgumentException("Not a valid double", "value");
122      Count++;
123      Total += value;
124      Last = value;
125      if (Collect) samples.Add(value);
126
127      if (Count == 1) {
128        Min = Max = Mean = value;
129      } else {
130        if (value < Min) Min = value;
131        if (value > Max) Max = value;
132
133        var oldMean = Mean;
134        Mean = oldMean + (value - oldMean) / Count;
135        variance = variance + (value - oldMean) * (value - Mean);
136      }
137
138      OnUpdated();
139    }
140
141    public event EventHandler Updated;
142    private void OnUpdated() {
143      Updated?.Invoke(this, EventArgs.Empty);
144    }
145
146    string IMonitor.Summarize() {
147      return Summarize();
148    }
149
150    /// <summary>
151    /// Provides a summary of the statistics in a certain format.
152    /// If the monitor is configured to collect data, it may also print a histogram.
153    /// </summary>
154    /// <param name="withHistogram">Whether to suppress the histogram.
155    /// This is only effective if <see cref="Collect"/> was set to true, otherwise
156    /// the data to produce the histogram is not available in the first place.</param>
157    /// <param name="maxBins">The maximum number of bins that should be used.
158    /// Note that the bin width and thus the number of bins is also governed by
159    /// <paramref name="binWidth"/> if it is defined.
160    /// This is only effective if <see cref="Collect"/> and <paramref name="withHistogram"/>
161    /// was set to true, otherwise the data to produce the histogram is not available
162    /// in the first place.</param>
163    /// <param name="histMin">The minimum for the histogram to start at or the sample
164    /// minimum in case the default (null) is given.
165    /// This is only effective if <see cref="Collect"/> and <paramref name="withHistogram"/>
166    /// was set to true, otherwise the data to produce the histogram is not available
167    /// in the first place.</param>
168    /// <param name="binWidth">The interval for the bins of the histogram or the
169    /// range (<see cref="Max"/> - <see cref="Min"/>) divided by the number of bins
170    /// (<paramref name="maxBins"/>) in case the default value (null) is given.
171    /// This is only effective if <see cref="Collect"/> and <paramref name="withHistogram"/>
172    /// was set to true, otherwise the data to produce the histogram is not available
173    /// in the first place.</param>
174    /// <returns>A formatted string that provides a summary of the statistics.</returns>
175    public string Summarize(bool withHistogram = true, int maxBins = 20, double? histMin = null, double? binWidth = null) {
176      var nozero = Collect ? samples.Where(x => x != 0).ToList() : new List<double>();
177      var nozeromin = nozero.Count > 0 ? nozero.Min() : double.NaN;
178      var nozeromax = nozero.Count > 0 ? nozero.Max() : double.NaN;
179      var nozeromean = nozero.Count > 1 ? nozero.Average() : double.NaN;
180      var nozerostdev = nozero.Count > 2 ? Math.Sqrt(nozero.Sum(x => (x - nozeromean) * (x - nozeromean)) / (nozero.Count - 1.0)) : double.NaN;
181      var sb = new StringBuilder();
182      sb.Append("Statistics");
183      if (!string.IsNullOrEmpty(Name))
184        sb.Append(" of " + Name);
185      sb.AppendLine();
186      sb.AppendLine("                all             excl.zero       zero           ");
187      sb.AppendLine("--------------- --------------- --------------- ---------------");
188      sb.AppendLine(string.Format("{0,15} {1,15} {2,15} {3,15}", "Count", Formatter.Format15(Count), Formatter.Format15(Collect ? nozero.Count : double.NaN), Formatter.Format15(Collect ? Count - nozero.Count : double.NaN)));
189      sb.AppendLine(string.Format("{0,15} {1,15} {2,15}", "Mean", Formatter.Format15(Mean), Formatter.Format15(nozeromean)));
190      sb.AppendLine(string.Format("{0,15} {1,15} {2,15}", "Std.dev", Formatter.Format15(StdDev), Formatter.Format15(nozerostdev)));
191      sb.AppendLine();
192      sb.AppendLine(string.Format("{0,15} {1,15} {2,15}", "Minimum", Formatter.Format15(Min), Formatter.Format15(nozeromin)));
193      if (Collect) {
194        sb.AppendLine(string.Format("{0,15} {1,15} {2,15}", "Percentile-5%", Formatter.Format15(GetPercentile(0.05)), Formatter.Format15(GetPercentile(nozero, 0.05))));
195        sb.AppendLine(string.Format("{0,15} {1,15} {2,15}", "Median", Formatter.Format15(GetMedian()), Formatter.Format15(GetPercentile(nozero, 0.5))));
196        sb.AppendLine(string.Format("{0,15} {1,15} {2,15}", "Percentile-95%", Formatter.Format15(GetPercentile(0.95)), Formatter.Format15(GetPercentile(nozero, 0.95))));
197      }
198      sb.AppendLine(string.Format("{0,15} {1,15} {2,15}", "Maximum", Formatter.Format15(Max), Formatter.Format15(nozeromax)));
199
200      if (Collect && withHistogram) {
201        var min = histMin ?? Min;
202        var interval = binWidth ?? (Max - Min) / maxBins;
203        var histData = samples.GroupBy(x => x <= min ? 0 : (int)Math.Floor(Math.Min((x - min + interval) / interval, maxBins)))
204                           .Select(x => new { Key = x.Key, Value = x.Count() })
205                           .OrderBy(x => x.Key);
206        sb.AppendLine();
207        sb.AppendLine("Histogram");
208        sb.AppendLine("<=              count      %     cum%   ");
209        sb.AppendLine("--------------- ---------- ----- ------");
210        var cumul = 0.0;
211        var totStars = 0;
212        var last = -1;
213        foreach (var kvp in histData) {
214          while (kvp.Key > last + 1) {
215            last++;
216            var tmp = "|".PadLeft(totStars + 1);
217            sb.AppendLine(string.Format("{0,15} {1,10} {2,5:F1} {3,5:F1} {4}{5}", Formatter.Format15(min + last * interval), 0, 0, cumul * 100, "", tmp));
218          }
219          var prob = kvp.Value / (double)Count;
220          cumul += prob;
221          var probstars = (int)Math.Round(100 * prob / 2);
222          var cumulstars = (int)Math.Round(100 * cumul / 2);
223          var numstars = probstars;
224          if (probstars + totStars < cumulstars) numstars++;
225          var stars = string.Join("", Enumerable.Repeat("*", numstars));
226          totStars += numstars;
227          var cumulbar = "|".PadLeft(totStars + 1 - numstars);
228          sb.AppendLine(string.Format("{0,15} {1,10} {2,5:F1} {3,5:F1} {4}{5}",
229            (kvp.Key == maxBins && min + kvp.Key * interval < Max) ? "inf" : Formatter.Format15(min + kvp.Key * interval),
230            kvp.Value, prob * 100, cumul * 100, stars, cumulbar));
231          last = kvp.Key;
232        }
233      }
234      return sb.ToString();
235    }
236  }
237}
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