1 | #region License Information
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2 | /*
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3 | * This file is part of SimSharp which is licensed under the MIT license.
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4 | * See the LICENSE file in the project root for more information.
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5 | */
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6 | #endregion
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7 |
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8 | using System;
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9 | using System.Collections.Generic;
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10 | using System.Diagnostics;
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11 | using System.IO;
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12 | using System.Threading;
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13 | using System.Threading.Tasks;
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14 |
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15 | namespace SimSharp {
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16 | /// <summary>
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17 | /// Simulation hold the event queues, schedule and process events.
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18 | /// </summary>
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19 | /// <remarks>
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20 | /// This class is not thread-safe against manipulation of the event queue. If you supply a termination
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21 | /// event that is set outside the simulation thread, please use the <see cref="ThreadSafeSimulation"/> environment.
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22 | ///
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23 | /// For most purposes <see cref="Simulation"/> is however the better and faster choice.
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24 | /// </remarks>
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25 | public class Simulation {
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26 | private const int InitialMaxEvents = 1024;
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27 |
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28 | /// <summary>
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29 | /// Describes the number of seconds that a logical step of 1 in the *D-API takes.
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30 | /// </summary>
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31 | protected double DefaultTimeStepSeconds { get; private set; }
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32 |
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33 | /// <summary>
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34 | /// Calculates the logical date of the simulation by the amount of default steps
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35 | /// that have passed.
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36 | /// </summary>
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37 | public double NowD {
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38 | get { return (Now - StartDate).TotalSeconds / DefaultTimeStepSeconds; }
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39 | }
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40 |
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41 | private DateTime now;
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42 | /// <summary>
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43 | /// The current simulation time as a calendar date.
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44 | /// </summary>
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45 | public virtual DateTime Now { get => now; protected set => now = value; }
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46 |
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47 | /// <summary>
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48 | /// The calendar date when the simulation started. This defaults to 1970-1-1 if
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49 | /// no other date has been specified in the overloaded constructor.
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50 | /// </summary>
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51 | public DateTime StartDate { get; protected set; }
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52 |
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53 | /// <summary>
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54 | /// The random number generator that is to be used in all events in
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55 | /// order to produce reproducible results.
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56 | /// </summary>
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57 | protected IRandom Random { get; set; }
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58 |
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59 | protected EventQueue ScheduleQ;
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60 | public Process ActiveProcess { get; set; }
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61 |
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62 | public TextWriter Logger { get; set; }
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63 | public int ProcessedEvents { get; protected set; }
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64 |
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65 | public Simulation() : this(new DateTime(1970, 1, 1)) { }
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66 | public Simulation(TimeSpan? defaultStep) : this(new DateTime(1970, 1, 1), defaultStep) { }
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67 | public Simulation(int randomSeed, TimeSpan? defaultStep = null) : this(new DateTime(1970, 1, 1), randomSeed, defaultStep) { }
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68 | public Simulation(DateTime initialDateTime, TimeSpan? defaultStep = null) : this(new PcgRandom(), initialDateTime, defaultStep) { }
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69 | public Simulation(DateTime initialDateTime, int randomSeed, TimeSpan? defaultStep = null) : this(new PcgRandom(randomSeed), initialDateTime, defaultStep) { }
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70 | public Simulation(IRandom random, DateTime initialDateTime, TimeSpan? defaultStep = null) {
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71 | DefaultTimeStepSeconds = (defaultStep ?? TimeSpan.FromSeconds(1)).Duration().TotalSeconds;
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72 | StartDate = initialDateTime;
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73 | Now = initialDateTime;
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74 | Random = random;
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75 | ScheduleQ = new EventQueue(InitialMaxEvents);
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76 | Logger = Console.Out;
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77 | }
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78 |
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79 | public double ToDouble(TimeSpan span) {
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80 | return span.TotalSeconds / DefaultTimeStepSeconds;
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81 | }
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82 |
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83 | public TimeSpan ToTimeSpan(double span) {
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84 | return TimeSpan.FromSeconds(DefaultTimeStepSeconds * span);
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85 | }
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86 |
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87 | /// <summary>
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88 | /// Creates a new process from an event generator. The process is automatically
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89 | /// scheduled to be started at the current simulation time.
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90 | /// </summary>
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91 | /// <param name="generator">The generator function that represents the process.</param>
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92 | /// <param name="priority">The priority to rank events at the same time (smaller value = higher priority).</param>
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93 | /// <returns>The scheduled process that was created.</returns>
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94 | public Process Process(IEnumerable<Event> generator, int priority = 0) {
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95 | return new Process(this, generator, priority);
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96 | }
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97 |
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98 | /// <summary>
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99 | /// Creates and returns a new timeout.
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100 | /// </summary>
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101 | /// <param name="delay">The time after which the timeout is fired.</param>
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102 | /// <param name="priority">The priority to rank events at the same time (smaller value = higher priority).</param>
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103 | /// <returns>The scheduled timeout event that was created.</returns>
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104 | public Timeout TimeoutD(double delay, int priority = 0) {
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105 | return Timeout(TimeSpan.FromSeconds(DefaultTimeStepSeconds * delay), priority);
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106 | }
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107 |
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108 | /// <summary>
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109 | /// Creates and returns a new timeout.
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110 | /// </summary>
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111 | /// <param name="delay">The time after which the timeout is fired.</param>
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112 | /// <param name="priority">The priority to rank events at the same time (smaller value = higher priority).</param>
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113 | /// <returns>The scheduled timeout event that was created.</returns>
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114 | public Timeout Timeout(TimeSpan delay, int priority = 0) {
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115 | return new Timeout(this, delay, priority: priority);
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116 | }
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117 |
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118 | public virtual void Reset(int randomSeed) {
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119 | ProcessedEvents = 0;
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120 | Now = StartDate;
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121 | Random = new PcgRandom(randomSeed);
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122 | ScheduleQ = new EventQueue(InitialMaxEvents);
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123 | useSpareNormal = false;
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124 | }
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125 |
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126 | public virtual void ScheduleD(double delay, Event @event) {
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127 | Schedule(TimeSpan.FromSeconds(DefaultTimeStepSeconds * delay), @event);
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128 | }
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129 |
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130 | /// <summary>
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131 | /// Schedules an event to occur at the same simulation time as the call was made.
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132 | /// </summary>
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133 | /// <param name="event">The event that should be scheduled.</param>
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134 | /// <param name="priority">The priority to rank events at the same time (smaller value = higher priority).</param>
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135 | public virtual void Schedule(Event @event, int priority = 0) {
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136 | DoSchedule(Now, @event, priority);
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137 | }
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138 |
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139 | /// <summary>
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140 | /// Schedules an event to occur after a certain (positive) delay.
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141 | /// </summary>
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142 | /// <exception cref="ArgumentException">
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143 | /// Thrown when <paramref name="delay"/> is negative.
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144 | /// </exception>
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145 | /// <param name="delay">The (positive) delay after which the event should be fired.</param>
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146 | /// <param name="event">The event that should be scheduled.</param>
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147 | /// <param name="priority">The priority to rank events at the same time (smaller value = higher priority).</param>
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148 | public virtual void Schedule(TimeSpan delay, Event @event, int priority = 0) {
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149 | if (delay < TimeSpan.Zero)
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150 | throw new ArgumentException("Negative delays are not allowed in Schedule(TimeSpan, Event).");
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151 | var eventTime = Now + delay;
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152 | DoSchedule(eventTime, @event, priority);
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153 | }
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154 |
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155 | protected virtual EventQueueNode DoSchedule(DateTime date, Event @event, int priority = 0) {
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156 | if (ScheduleQ.MaxSize == ScheduleQ.Count) {
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157 | // the capacity has to be adjusted, there are more events in the queue than anticipated
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158 | var oldSchedule = ScheduleQ;
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159 | ScheduleQ = new EventQueue(ScheduleQ.MaxSize * 2);
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160 | foreach (var e in oldSchedule) ScheduleQ.Enqueue(e.PrimaryPriority, e.Event, e.SecondaryPriority);
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161 | }
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162 | return ScheduleQ.Enqueue(date, @event, priority);
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163 | }
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164 |
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165 | public virtual object RunD(double? until = null) {
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166 | if (!until.HasValue) return Run();
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167 | return Run(Now + TimeSpan.FromSeconds(DefaultTimeStepSeconds * until.Value));
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168 | }
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169 |
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170 | public virtual object Run(TimeSpan span) {
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171 | return Run(Now + span);
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172 | }
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173 |
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174 | public virtual object Run(DateTime until) {
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175 | if (until <= Now) throw new InvalidOperationException("Simulation end date must lie in the future.");
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176 | var stopEvent = new Event(this);
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177 | var node = DoSchedule(until, stopEvent);
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178 | // stop event is always the first to execute at the given time
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179 | node.InsertionIndex = -1;
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180 | ScheduleQ.OnNodeUpdated(node);
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181 | return Run(stopEvent);
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182 | }
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183 |
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184 | protected CancellationTokenSource _stop = null;
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185 | /// <summary>
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186 | /// Run until a certain event is processed.
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187 | /// </summary>
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188 | /// <remarks>
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189 | /// This simulation environment is not thread-safe, thus triggering this event outside the environment
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190 | /// leads to potential race conditions. Please use the <see cref="ThreadSafeSimulation"/> environment in case you
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191 | /// require this functionality. Note that the performance of <see cref="ThreadSafeSimulation"/> is lower due to locking.
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192 | ///
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193 | /// For real-time based termination, you can also call <see cref="StopAsync"/> which sets a flag indicating the simulation
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194 | /// to stop before processing the next event.
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195 | /// </remarks>
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196 | /// <param name="stopEvent">The event that stops the simulation.</param>
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197 | /// <returns></returns>
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198 | public virtual object Run(Event stopEvent = null) {
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199 | _stop = new CancellationTokenSource();
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200 | if (stopEvent != null) {
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201 | if (stopEvent.IsProcessed) {
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202 | return stopEvent.Value;
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203 | }
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204 | stopEvent.AddCallback(StopSimulation);
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205 | }
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206 | OnRunStarted();
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207 | try {
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208 | var stop = ScheduleQ.Count == 0 || _stop.IsCancellationRequested;
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209 | while (!stop) {
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210 | Step();
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211 | stop = ScheduleQ.Count == 0 || _stop.IsCancellationRequested;
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212 | }
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213 | } catch (StopSimulationException e) { OnRunFinished(); return e.Value; }
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214 | OnRunFinished();
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215 | if (stopEvent == null) return null;
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216 | if (!_stop.IsCancellationRequested && !stopEvent.IsTriggered) throw new InvalidOperationException("No scheduled events left but \"until\" event was not triggered.");
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217 | return stopEvent.Value;
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218 | }
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219 |
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220 | public virtual void StopAsync() {
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221 | _stop?.Cancel();
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222 | }
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223 |
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224 | public event EventHandler RunStarted;
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225 | protected void OnRunStarted() {
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226 | RunStarted?.Invoke(this, EventArgs.Empty);
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227 | }
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228 |
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229 | public event EventHandler RunFinished;
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230 | protected void OnRunFinished() {
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231 | RunFinished?.Invoke(this, EventArgs.Empty);
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232 | }
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233 |
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234 | /// <summary>
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235 | /// Performs a single step of the simulation, i.e. process a single event
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236 | /// </summary>
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237 | /// <remarks>
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238 | /// This method is not thread-safe
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239 | /// </remarks>
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240 | public virtual void Step() {
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241 | Event evt;
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242 | var next = ScheduleQ.Dequeue();
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243 | Now = next.PrimaryPriority;
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244 | evt = next.Event;
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245 | evt.Process();
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246 | ProcessedEvents++;
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247 | }
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248 |
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249 | /// <summary>
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250 | /// Peeks at the time of the next event in terms of the defined step
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251 | /// </summary>
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252 | /// <remarks>
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253 | /// This method is not thread-safe
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254 | /// </remarks>
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255 | public virtual double PeekD() {
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256 | if (ScheduleQ.Count == 0) return double.MaxValue;
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257 | return (Peek() - StartDate).TotalSeconds / DefaultTimeStepSeconds;
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258 | }
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259 |
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260 | /// <summary>
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261 | /// Peeks at the time of the next event
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262 | /// </summary>
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263 | /// <remarks>
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264 | /// This method is not thread-safe
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265 | /// </remarks>
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266 | public virtual DateTime Peek() {
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267 | return ScheduleQ.Count > 0 ? ScheduleQ.First.PrimaryPriority : DateTime.MaxValue;
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268 | }
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269 |
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270 | protected virtual void StopSimulation(Event @event) {
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271 | throw new StopSimulationException(@event.Value);
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272 | }
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273 |
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274 | public virtual void Log(string message, params object[] args) {
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275 | if (Logger != null)
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276 | Logger.WriteLine(message, args);
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277 | }
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278 |
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279 | #region Random number distributions
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280 | public double RandUniform(IRandom random, double a, double b) {
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281 | return a + (b - a) * random.NextDouble();
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282 | }
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283 | public double RandUniform(double a, double b) {
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284 | return RandUniform(Random, a, b);
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285 | }
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286 |
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287 | public TimeSpan RandUniform(IRandom random, TimeSpan a, TimeSpan b) {
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288 | return TimeSpan.FromSeconds(RandUniform(random, a.TotalSeconds, b.TotalSeconds));
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289 | }
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290 | public TimeSpan RandUniform(TimeSpan a, TimeSpan b) {
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291 | return RandUniform(Random, a, b);
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292 | }
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293 | public double RandTriangular(IRandom random, double low, double high) {
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294 | var u = random.NextDouble();
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295 | if (u > 0.5)
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296 | return high + (low - high) * Math.Sqrt(((1.0 - u) / 2));
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297 | return low + (high - low) * Math.Sqrt(u / 2);
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298 | }
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299 | public double RandTriangular(double low, double high) {
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300 | return RandTriangular(Random, low, high);
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301 | }
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302 |
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303 | public TimeSpan RandTriangular(IRandom random, TimeSpan low, TimeSpan high) {
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304 | return TimeSpan.FromSeconds(RandTriangular(random, low.TotalSeconds, high.TotalSeconds));
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305 | }
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306 | public TimeSpan RandTriangular(TimeSpan low, TimeSpan high) {
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307 | return RandTriangular(Random, low, high);
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308 | }
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309 |
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310 | public double RandTriangular(IRandom random, double low, double high, double mode) {
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311 | var u = random.NextDouble();
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312 | var c = (mode - low) / (high - low);
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313 | if (u > c)
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314 | return high + (low - high) * Math.Sqrt(((1.0 - u) * (1.0 - c)));
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315 | return low + (high - low) * Math.Sqrt(u * c);
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316 | }
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317 | public double RandTriangular(double low, double high, double mode) {
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318 | return RandTriangular(Random, low, high, mode);
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319 | }
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320 |
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321 | public TimeSpan RandTriangular(IRandom random, TimeSpan low, TimeSpan high, TimeSpan mode) {
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322 | return TimeSpan.FromSeconds(RandTriangular(random, low.TotalSeconds, high.TotalSeconds, mode.TotalSeconds));
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323 | }
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324 | public TimeSpan RandTriangular(TimeSpan low, TimeSpan high, TimeSpan mode) {
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325 | return RandTriangular(Random, low, high, mode);
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326 | }
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327 |
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328 | /// <summary>
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329 | /// Returns a number that is exponentially distributed given a certain mean.
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330 | /// </summary>
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331 | /// <remarks>
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332 | /// Unlike in other APIs here the mean should be given and not the lambda parameter.
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333 | /// </remarks>
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334 | /// <param name="random">The random number generator to use.</param>
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335 | /// <param name="mean">The mean(!) of the distribution is 1 / lambda.</param>
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336 | /// <returns>A number that is exponentially distributed</returns>
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337 | public double RandExponential(IRandom random, double mean) {
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338 | return -Math.Log(1 - random.NextDouble()) * mean;
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339 | }
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340 | /// <summary>
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341 | /// Returns a number that is exponentially distributed given a certain mean.
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342 | /// </summary>
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343 | /// <remarks>
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344 | /// Unlike in other APIs here the mean should be given and not the lambda parameter.
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345 | /// </remarks>
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346 | /// <param name="mean">The mean(!) of the distribution is 1 / lambda.</param>
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347 | /// <returns>A number that is exponentially distributed</returns>
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348 | public double RandExponential(double mean) {
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349 | return RandExponential(Random, mean);
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350 | }
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351 |
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352 | /// <summary>
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353 | /// Returns a timespan that is exponentially distributed given a certain mean.
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354 | /// </summary>
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355 | /// <remarks>
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356 | /// Unlike in other APIs here the mean should be given and not the lambda parameter.
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357 | /// </remarks>
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358 | /// <param name="random">The random number generator to use.</param>
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359 | /// <param name="mean">The mean(!) of the distribution is 1 / lambda.</param>
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360 | /// <returns>A number that is exponentially distributed</returns>
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361 | public TimeSpan RandExponential(IRandom random, TimeSpan mean) {
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362 | return TimeSpan.FromSeconds(RandExponential(random, mean.TotalSeconds));
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363 | }
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364 | /// <summary>
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365 | /// Returns a timespan that is exponentially distributed given a certain mean.
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366 | /// </summary>
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367 | /// <remarks>
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368 | /// Unlike in other APIs here the mean should be given and not the lambda parameter.
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369 | /// </remarks>
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370 | /// <param name="mean">The mean(!) of the distribution is 1 / lambda.</param>
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371 | /// <returns>A number that is exponentially distributed</returns>
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372 | public TimeSpan RandExponential(TimeSpan mean) {
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373 | return RandExponential(Random, mean);
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374 | }
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375 |
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376 | private bool useSpareNormal = false;
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377 | private double spareNormal = double.NaN;
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378 |
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379 | /// <summary>
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380 | /// Uses the Marsaglia polar method to generate a random variable
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381 | /// from two uniform random distributed values.
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382 | /// </summary>
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383 | /// <remarks>
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384 | /// Unlike <see cref="RandNormal(double, double)"/> this method does not
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385 | /// make use of a spare random variable. It discards the spare and thus
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386 | /// requires twice the number of calls to the underlying IRandom instance.
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387 | /// </remarks>
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388 | /// <param name="random">The random number generator to use.</param>
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389 | /// <param name="mu">The mean of the normal distribution.</param>
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390 | /// <param name="sigma">The standard deviation of the normal distribution.</param>
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391 | /// <returns>A number that is normal distributed.</returns>
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392 | public virtual double RandNormal(IRandom random, double mu, double sigma) {
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393 | return MarsagliaPolar(random, mu, sigma, out _); // do not reuse the spare normal in this case, because it could be from a different RNG
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394 | }
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395 | /// <summary>
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396 | /// Uses the Marsaglia polar method to generate a random variable
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397 | /// from two uniform random distributed values.
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398 | /// </summary>
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399 | /// <remarks>
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400 | /// A spare random variable is generated from the second uniformly
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401 | /// distributed value. Thus, the two calls to the uniform random number
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402 | /// generator will be made only every second call.
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403 | /// </remarks>
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404 | /// <param name="mu">The mean of the normal distribution.</param>
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405 | /// <param name="sigma">The standard deviation of the normal distribution.</param>
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406 | /// <returns>A number that is normal distributed.</returns>
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407 | public virtual double RandNormal(double mu, double sigma) {
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408 | if (useSpareNormal) {
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409 | useSpareNormal = false;
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410 | return spareNormal * sigma + mu;
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411 | } else {
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412 | useSpareNormal = true;
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413 | return MarsagliaPolar(Random, mu, sigma, out spareNormal);
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414 | }
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415 | }
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416 | private double MarsagliaPolar(IRandom random, double mu, double sigma, out double spare) {
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417 | double u, v, s;
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418 | do {
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419 | u = random.NextDouble() * 2 - 1;
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420 | v = random.NextDouble() * 2 - 1;
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421 | s = u * u + v * v;
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422 | } while (s > 1 || s == 0);
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423 | var mul = Math.Sqrt(-2.0 * Math.Log(s) / s);
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424 | spare = v * mul;
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425 | return mu + sigma * u * mul;
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426 | }
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427 |
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428 | /// <summary>
|
---|
429 | /// Uses the Marsaglia polar method to generate a random variable
|
---|
430 | /// from two uniform random distributed values.
|
---|
431 | /// </summary>
|
---|
432 | /// <remarks>
|
---|
433 | /// A spare random variable is generated from the second uniformly
|
---|
434 | /// distributed value. Thus, the two calls to the uniform random number
|
---|
435 | /// generator will be made only every second call.
|
---|
436 | /// </remarks>
|
---|
437 | /// <param name="random">The random number generator to use.</param>
|
---|
438 | /// <param name="mu">The mean of the normal distribution.</param>
|
---|
439 | /// <param name="sigma">The standard deviation of the normal distribution.</param>
|
---|
440 | /// <returns>A number that is normal distributed.</returns>
|
---|
441 | public TimeSpan RandNormal(IRandom random, TimeSpan mu, TimeSpan sigma) {
|
---|
442 | return TimeSpan.FromSeconds(RandNormal(random, mu.TotalSeconds, sigma.TotalSeconds));
|
---|
443 | }
|
---|
444 | /// <summary>
|
---|
445 | /// Uses the Marsaglia polar method to generate a random variable
|
---|
446 | /// from two uniform random distributed values.
|
---|
447 | /// </summary>
|
---|
448 | /// <remarks>
|
---|
449 | /// A spare random variable is generated from the second uniformly
|
---|
450 | /// distributed value. Thus, the two calls to the uniform random number
|
---|
451 | /// generator will be made only every second call.
|
---|
452 | /// </remarks>
|
---|
453 | /// <param name="mu">The mean of the normal distribution.</param>
|
---|
454 | /// <param name="sigma">The standard deviation of the normal distribution.</param>
|
---|
455 | /// <returns>A number that is normal distributed.</returns>
|
---|
456 | public TimeSpan RandNormal(TimeSpan mu, TimeSpan sigma) {
|
---|
457 | return RandNormal(Random, mu, sigma);
|
---|
458 | }
|
---|
459 |
|
---|
460 | public double RandNormalPositive(IRandom random, double mu, double sigma) {
|
---|
461 | double val;
|
---|
462 | do {
|
---|
463 | val = RandNormal(random, mu, sigma);
|
---|
464 | } while (val <= 0);
|
---|
465 | return val;
|
---|
466 | }
|
---|
467 | public double RandNormalPositive(double mu, double sigma) {
|
---|
468 | return RandNormalPositive(Random, mu, sigma);
|
---|
469 | }
|
---|
470 |
|
---|
471 | public TimeSpan RandNormalPositive(IRandom random, TimeSpan mu, TimeSpan sigma) {
|
---|
472 | return TimeSpan.FromSeconds(RandNormalPositive(random, mu.TotalSeconds, sigma.TotalSeconds));
|
---|
473 | }
|
---|
474 | public TimeSpan RandNormalPositive(TimeSpan mu, TimeSpan sigma) {
|
---|
475 | return RandNormalPositive(Random, mu, sigma);
|
---|
476 | }
|
---|
477 |
|
---|
478 | public double RandNormalNegative(IRandom random, double mu, double sigma) {
|
---|
479 | double val;
|
---|
480 | do {
|
---|
481 | val = RandNormal(random, mu, sigma);
|
---|
482 | } while (val >= 0);
|
---|
483 | return val;
|
---|
484 | }
|
---|
485 | public double RandNormalNegative(double mu, double sigma) {
|
---|
486 | return RandNormalNegative(Random, mu, sigma);
|
---|
487 | }
|
---|
488 |
|
---|
489 | public TimeSpan RandNormalNegative(IRandom random, TimeSpan mu, TimeSpan sigma) {
|
---|
490 | return TimeSpan.FromSeconds(RandNormalNegative(random, mu.TotalSeconds, sigma.TotalSeconds));
|
---|
491 | }
|
---|
492 | public TimeSpan RandNormalNegative(TimeSpan mu, TimeSpan sigma) {
|
---|
493 | return RandNormalNegative(Random, mu, sigma);
|
---|
494 | }
|
---|
495 |
|
---|
496 | /// <summary>
|
---|
497 | /// Returns values from a log-normal distribution with the mean
|
---|
498 | /// exp(mu + sigma^2 / 2)
|
---|
499 | /// and the standard deviation
|
---|
500 | /// sqrt([exp(sigma^2)-1] * exp(2 * mu + sigma^2))
|
---|
501 | /// </summary>
|
---|
502 | /// <param name="random">The random number generator to use.</param>
|
---|
503 | /// <param name="mu">The mu parameter of the log-normal distribution (not the mean).</param>
|
---|
504 | /// <param name="sigma">The sigma parameter of the log-normal distribution (not the standard deviation).</param>
|
---|
505 | /// <returns>A log-normal distributed random value.</returns>
|
---|
506 | public double RandLogNormal(IRandom random, double mu, double sigma) {
|
---|
507 | return Math.Exp(RandNormal(random, mu, sigma));
|
---|
508 | }
|
---|
509 | /// <summary>
|
---|
510 | /// Returns values from a log-normal distribution with the mean
|
---|
511 | /// exp(mu + sigma^2 / 2)
|
---|
512 | /// and the standard deviation
|
---|
513 | /// sqrt([exp(sigma^2)-1] * exp(2 * mu + sigma^2))
|
---|
514 | /// </summary>
|
---|
515 | /// <param name="mu">The mu parameter of the log-normal distribution (not the mean).</param>
|
---|
516 | /// <param name="sigma">The sigma parameter of the log-normal distribution (not the standard deviation).</param>
|
---|
517 | /// <returns>A log-normal distributed random value.</returns>
|
---|
518 | public double RandLogNormal(double mu, double sigma) {
|
---|
519 | return RandLogNormal(Random, mu, sigma);
|
---|
520 | }
|
---|
521 |
|
---|
522 | /// <summary>
|
---|
523 | /// Returns values from a log-normal distribution with
|
---|
524 | /// the mean <paramref name="mean"/> and standard deviation <paramref name="stdev"/>.
|
---|
525 | /// </summary>
|
---|
526 | /// <param name="random">The random number generator to use.</param>
|
---|
527 | /// <param name="mean">The distribution mean.</param>
|
---|
528 | /// <param name="stdev">The distribution standard deviation.</param>
|
---|
529 | /// <returns>A log-normal distributed random value.</returns>
|
---|
530 | public double RandLogNormal2(IRandom random, double mean, double stdev) {
|
---|
531 | if (stdev == 0) return mean;
|
---|
532 | var sigma = Math.Sqrt(Math.Log(stdev * stdev / (mean * mean) + 1));
|
---|
533 | var mu = Math.Log(mean) - 0.5 * sigma * sigma;
|
---|
534 | return Math.Exp(RandNormal(random, mu, sigma));
|
---|
535 | }
|
---|
536 | /// <summary>
|
---|
537 | /// Returns values from a log-normal distribution with
|
---|
538 | /// the mean <paramref name="mean"/> and standard deviation <paramref name="stdev"/>.
|
---|
539 | /// </summary>
|
---|
540 | /// <param name="mean">The distribution mean.</param>
|
---|
541 | /// <param name="stdev">The distribution standard deviation.</param>
|
---|
542 | /// <returns>A log-normal distributed random value.</returns>
|
---|
543 | public double RandLogNormal2(double mean, double stdev) {
|
---|
544 | return RandLogNormal2(Random, mean, stdev);
|
---|
545 | }
|
---|
546 |
|
---|
547 | /// <summary>
|
---|
548 | /// Returns a timespan value from a log-normal distribution with the mean
|
---|
549 | /// exp(mu + sigma^2 / 2)
|
---|
550 | /// and the standard deviation
|
---|
551 | /// sqrt([exp(sigma^2)-1] * exp(2 * mu + sigma^2))
|
---|
552 | /// </summary>
|
---|
553 | /// <param name="random">The random number generator to use.</param>
|
---|
554 | /// <param name="mu">The mu parameter of the log-normal distribution (not the mean).</param>
|
---|
555 | /// <param name="sigma">The sigma parameter of the log-normal distribution (not the standard deviation).</param>
|
---|
556 | /// <returns>A log-normal distributed random timespan.</returns>
|
---|
557 | public TimeSpan RandLogNormal(IRandom random, TimeSpan mu, TimeSpan sigma) {
|
---|
558 | return TimeSpan.FromSeconds(RandLogNormal(random, mu.TotalSeconds, sigma.TotalSeconds));
|
---|
559 | }
|
---|
560 | /// <summary>
|
---|
561 | /// Returns a timespan value from a log-normal distribution with the mean
|
---|
562 | /// exp(mu + sigma^2 / 2)
|
---|
563 | /// and the standard deviation
|
---|
564 | /// sqrt([exp(sigma^2)-1] * exp(2 * mu + sigma^2))
|
---|
565 | /// </summary>
|
---|
566 | /// <param name="mu">The mu parameter of the log-normal distribution (not the mean).</param>
|
---|
567 | /// <param name="sigma">The sigma parameter of the log-normal distribution (not the standard deviation).</param>
|
---|
568 | /// <returns>A log-normal distributed random timespan.</returns>
|
---|
569 | public TimeSpan RandLogNormal(TimeSpan mu, TimeSpan sigma) {
|
---|
570 | return RandLogNormal(Random, mu, sigma);
|
---|
571 | }
|
---|
572 |
|
---|
573 | /// <summary>
|
---|
574 | /// Returns a timespan value from a log-normal distribution with
|
---|
575 | /// the mean <paramref name="mean"/> and standard deviation <paramref name="stdev"/>.
|
---|
576 | /// </summary>
|
---|
577 | /// <param name="random">The random number generator to use.</param>
|
---|
578 | /// <param name="mean">The distribution mean.</param>
|
---|
579 | /// <param name="stdev">The distribution standard deviation.</param>
|
---|
580 | /// <returns>A log-normal distributed random timespan.</returns>
|
---|
581 | public TimeSpan RandLogNormal2(IRandom random, TimeSpan mean, TimeSpan stdev) {
|
---|
582 | return TimeSpan.FromSeconds(RandLogNormal2(random, mean.TotalSeconds, stdev.TotalSeconds));
|
---|
583 | }
|
---|
584 | /// <summary>
|
---|
585 | /// Returns a timespan value from a log-normal distribution with
|
---|
586 | /// the mean <paramref name="mean"/> and standard deviation <paramref name="stdev"/>.
|
---|
587 | /// </summary>
|
---|
588 | /// <param name="mean">The distribution mean.</param>
|
---|
589 | /// <param name="stdev">The distribution standard deviation.</param>
|
---|
590 | /// <returns>A log-normal distributed random timespan.</returns>
|
---|
591 | public TimeSpan RandLogNormal2(TimeSpan mean, TimeSpan stdev) {
|
---|
592 | return RandLogNormal2(Random, mean, stdev);
|
---|
593 | }
|
---|
594 |
|
---|
595 | public double RandCauchy(IRandom random, double x0, double gamma) {
|
---|
596 | return x0 + gamma * Math.Tan(Math.PI * (random.NextDouble() - 0.5));
|
---|
597 | }
|
---|
598 | public double RandCauchy(double x0, double gamma) {
|
---|
599 | return RandCauchy(Random, x0, gamma);
|
---|
600 | }
|
---|
601 |
|
---|
602 | public TimeSpan RandCauchy(IRandom random, TimeSpan x0, TimeSpan gamma) {
|
---|
603 | return TimeSpan.FromSeconds(RandCauchy(random, x0.TotalSeconds, gamma.TotalSeconds));
|
---|
604 | }
|
---|
605 | public TimeSpan RandCauchy(TimeSpan x0, TimeSpan gamma) {
|
---|
606 | return RandCauchy(Random, x0, gamma);
|
---|
607 | }
|
---|
608 |
|
---|
609 | public double RandWeibull(IRandom random, double alpha, double beta) {
|
---|
610 | return alpha * Math.Pow(-Math.Log(1 - random.NextDouble()), 1 / beta);
|
---|
611 | }
|
---|
612 | public double RandWeibull(double alpha, double beta) {
|
---|
613 | return RandWeibull(Random, alpha, beta);
|
---|
614 | }
|
---|
615 |
|
---|
616 | public TimeSpan RandWeibull(IRandom random, TimeSpan alpha, TimeSpan beta) {
|
---|
617 | return TimeSpan.FromSeconds(RandWeibull(random, alpha.TotalSeconds, beta.TotalSeconds));
|
---|
618 | }
|
---|
619 | public TimeSpan RandWeibull(TimeSpan alpha, TimeSpan beta) {
|
---|
620 | return RandWeibull(Random, alpha, beta);
|
---|
621 | }
|
---|
622 |
|
---|
623 |
|
---|
624 | /// <summary>
|
---|
625 | /// Generates a random sample from a given source
|
---|
626 | /// </summary>
|
---|
627 | /// <typeparam name="T">The type of the element in parameter source</typeparam>
|
---|
628 | /// <exception cref="ArgumentException">
|
---|
629 | /// Thrown when <paramref name="source"/> and <paramref name="weights"/> have different size.
|
---|
630 | /// or when <paramref name="weights"/> contains an invalid or negative value.
|
---|
631 | /// or when <paramref name="weights"/> sum equals zero or an invalid value.
|
---|
632 | /// </exception>
|
---|
633 | /// <param name="random">The random number generator to use.</param>
|
---|
634 | /// <param name="source">a random sample is generated from its elements.</param>
|
---|
635 | /// <param name="weights">The weight associated with each entry in source.</param>
|
---|
636 | /// <returns>The generated random samples</returns>
|
---|
637 | public T RandChoice<T>(IRandom random, IList<T> source, IList<double> weights) {
|
---|
638 | if (source.Count != weights.Count) {
|
---|
639 | throw new ArgumentException("source and weights must have same size");
|
---|
640 | }
|
---|
641 |
|
---|
642 | double totalW = 0;
|
---|
643 | foreach (var w in weights) {
|
---|
644 | if (w < 0) {
|
---|
645 | throw new ArgumentException("weight values must be non-negative", nameof(weights));
|
---|
646 | }
|
---|
647 | totalW += w;
|
---|
648 | }
|
---|
649 |
|
---|
650 | if (double.IsNaN(totalW) || double.IsInfinity(totalW))
|
---|
651 | throw new ArgumentException("Not a valid weight", nameof(weights));
|
---|
652 | if (totalW == 0)
|
---|
653 | throw new ArgumentException("total weight must be greater than 0", nameof(weights));
|
---|
654 |
|
---|
655 | var rnd = random.NextDouble();
|
---|
656 | double aggWeight = 0;
|
---|
657 | int idx = 0;
|
---|
658 | foreach (var w in weights) {
|
---|
659 | if (w > 0) {
|
---|
660 | aggWeight += (w / totalW);
|
---|
661 | if (rnd <= aggWeight) {
|
---|
662 | break;
|
---|
663 | }
|
---|
664 | }
|
---|
665 | idx++;
|
---|
666 | }
|
---|
667 | return source[idx];
|
---|
668 | }
|
---|
669 | /// <summary>
|
---|
670 | /// Generates a random sample from a given source
|
---|
671 | /// </summary>
|
---|
672 | /// <typeparam name="T">The type of the element in parameter source</typeparam>
|
---|
673 | /// <exception cref="ArgumentException">
|
---|
674 | /// Thrown when <paramref name="source"/> and <paramref name="weights"/> have different size.
|
---|
675 | /// or when <paramref name="weights"/> contains an invalid or negative value.
|
---|
676 | /// or when <paramref name="weights"/> sum equals zero
|
---|
677 | /// </exception>
|
---|
678 | /// <param name="source">a random sample is generated from its elements.</param>
|
---|
679 | /// <param name="weights">The weight associated with each entry in source.</param>
|
---|
680 | /// <returns>The generated random samples</returns>
|
---|
681 | public T RandChoice<T>(IList<T> source, IList<double> weights) {
|
---|
682 | return RandChoice(Random, source, weights);
|
---|
683 | }
|
---|
684 |
|
---|
685 | #endregion
|
---|
686 |
|
---|
687 | #region Random timeouts
|
---|
688 | public Timeout TimeoutUniformD(IRandom random, double a, double b) {
|
---|
689 | return new Timeout(this, ToTimeSpan(RandUniform(random, a, b)));
|
---|
690 | }
|
---|
691 | public Timeout TimeoutUniformD(double a, double b) {
|
---|
692 | return TimeoutUniformD(Random, a, b);
|
---|
693 | }
|
---|
694 |
|
---|
695 | public Timeout TimeoutUniform(IRandom random, TimeSpan a, TimeSpan b) {
|
---|
696 | return new Timeout(this, RandUniform(random, a, b));
|
---|
697 | }
|
---|
698 | public Timeout TimeoutUniform(TimeSpan a, TimeSpan b) {
|
---|
699 | return TimeoutUniform(Random, a, b);
|
---|
700 | }
|
---|
701 |
|
---|
702 | public Timeout TimeoutTriangularD(IRandom random, double low, double high) {
|
---|
703 | return new Timeout(this, ToTimeSpan(RandTriangular(random, low, high)));
|
---|
704 | }
|
---|
705 | public Timeout TimeoutTriangularD(double low, double high) {
|
---|
706 | return TimeoutTriangularD(Random, low, high);
|
---|
707 | }
|
---|
708 |
|
---|
709 | public Timeout TimeoutTriangular(IRandom random, TimeSpan low, TimeSpan high) {
|
---|
710 | return new Timeout(this, RandTriangular(random, low, high));
|
---|
711 | }
|
---|
712 | public Timeout TimeoutTriangular(TimeSpan low, TimeSpan high) {
|
---|
713 | return TimeoutTriangular(Random, low, high);
|
---|
714 | }
|
---|
715 |
|
---|
716 | public Timeout TimeoutTriangularD(IRandom random, double low, double high, double mode) {
|
---|
717 | return new Timeout(this, ToTimeSpan(RandTriangular(random, low, high, mode)));
|
---|
718 | }
|
---|
719 | public Timeout TimeoutTriangularD(double low, double high, double mode) {
|
---|
720 | return TimeoutTriangularD(Random, low, high, mode);
|
---|
721 | }
|
---|
722 |
|
---|
723 | public Timeout TimeoutTriangular(IRandom random, TimeSpan low, TimeSpan high, TimeSpan mode) {
|
---|
724 | return new Timeout(this, RandTriangular(random, low, high, mode));
|
---|
725 | }
|
---|
726 | public Timeout TimeoutTriangular(TimeSpan low, TimeSpan high, TimeSpan mode) {
|
---|
727 | return TimeoutTriangular(Random, low, high, mode);
|
---|
728 | }
|
---|
729 |
|
---|
730 | public Timeout TimeoutExponentialD(IRandom random, double mean) {
|
---|
731 | return new Timeout(this, ToTimeSpan(RandExponential(random, mean)));
|
---|
732 | }
|
---|
733 | public Timeout TimeoutExponentialD(double mean) {
|
---|
734 | return TimeoutExponentialD(Random, mean);
|
---|
735 | }
|
---|
736 |
|
---|
737 | public Timeout TimeoutExponential(IRandom random, TimeSpan mean) {
|
---|
738 | return new Timeout(this, RandExponential(random, mean));
|
---|
739 | }
|
---|
740 | public Timeout TimeoutExponential(TimeSpan mean) {
|
---|
741 | return TimeoutExponential(Random, mean);
|
---|
742 | }
|
---|
743 |
|
---|
744 | public Timeout TimeoutNormalPositiveD(IRandom random, double mu, double sigma) {
|
---|
745 | return new Timeout(this, ToTimeSpan(RandNormalPositive(random, mu, sigma)));
|
---|
746 | }
|
---|
747 | public Timeout TimeoutNormalPositiveD(double mu, double sigma) {
|
---|
748 | return TimeoutNormalPositiveD(Random, mu, sigma);
|
---|
749 | }
|
---|
750 |
|
---|
751 | public Timeout TimeoutNormalPositive(IRandom random, TimeSpan mu, TimeSpan sigma) {
|
---|
752 | return new Timeout(this, RandNormalPositive(random, mu, sigma));
|
---|
753 | }
|
---|
754 | public Timeout TimeoutNormalPositive(TimeSpan mu, TimeSpan sigma) {
|
---|
755 | return TimeoutNormalPositive(Random, mu, sigma);
|
---|
756 | }
|
---|
757 |
|
---|
758 | public Timeout TimeoutLogNormalD(IRandom random, double mu, double sigma) {
|
---|
759 | return new Timeout(this, ToTimeSpan(RandLogNormal(random, mu, sigma)));
|
---|
760 | }
|
---|
761 | public Timeout TimeoutLogNormalD(double mu, double sigma) {
|
---|
762 | return TimeoutLogNormalD(Random, mu, sigma);
|
---|
763 | }
|
---|
764 |
|
---|
765 | public Timeout TimeoutLogNormal2D(IRandom random, double mean, double stdev) {
|
---|
766 | return new Timeout(this, ToTimeSpan(RandLogNormal2(random, mean, stdev)));
|
---|
767 | }
|
---|
768 | public Timeout TimeoutLogNormal2D(double mean, double stdev) {
|
---|
769 | return TimeoutLogNormal2D(Random, mean, stdev);
|
---|
770 | }
|
---|
771 |
|
---|
772 | public Timeout TimeoutLogNormal(IRandom random, TimeSpan mu, TimeSpan sigma) {
|
---|
773 | return new Timeout(this, RandLogNormal(random, mu, sigma));
|
---|
774 | }
|
---|
775 | public Timeout TimeoutLogNormal(TimeSpan mu, TimeSpan sigma) {
|
---|
776 | return TimeoutLogNormal(Random, mu, sigma);
|
---|
777 | }
|
---|
778 |
|
---|
779 | public Timeout TimeoutLogNormal2(IRandom random, TimeSpan mean, TimeSpan stdev) {
|
---|
780 | return new Timeout(this, RandLogNormal2(random, mean, stdev));
|
---|
781 | }
|
---|
782 | public Timeout TimeoutLogNormal2(TimeSpan mean, TimeSpan stdev) {
|
---|
783 | return TimeoutLogNormal2(Random, mean, stdev);
|
---|
784 | }
|
---|
785 | #endregion
|
---|
786 | }
|
---|
787 |
|
---|
788 | /// <summary>
|
---|
789 | /// Provides a simulation environment that is thread-safe against manipulations of the event queue.
|
---|
790 | /// Its performance is somewhat lower than the non-thread-safe environment (cf. <see cref="Simulation"/>)
|
---|
791 | /// due to the locking involved.
|
---|
792 | /// </summary>
|
---|
793 | /// <remarks>
|
---|
794 | /// Please carefully consider if you must really schedule the stop event in a separate thread. You can also
|
---|
795 | /// call <see cref="Simulation.StopAsync"/> to request termination after the current event has been processed.
|
---|
796 | ///
|
---|
797 | /// The simulation will still run in only one thread and execute all events sequentially.
|
---|
798 | /// </remarks>
|
---|
799 | public class ThreadSafeSimulation : Simulation {
|
---|
800 | protected object _locker;
|
---|
801 |
|
---|
802 | public ThreadSafeSimulation() : this(new DateTime(1970, 1, 1)) { }
|
---|
803 | public ThreadSafeSimulation(TimeSpan? defaultStep) : this(new DateTime(1970, 1, 1), defaultStep) { }
|
---|
804 | public ThreadSafeSimulation(DateTime initialDateTime, TimeSpan? defaultStep = null) : this(new PcgRandom(), initialDateTime, defaultStep) { }
|
---|
805 | public ThreadSafeSimulation(int randomSeed, TimeSpan? defaultStep = null) : this(new DateTime(1970, 1, 1), randomSeed, defaultStep) { }
|
---|
806 | public ThreadSafeSimulation(DateTime initialDateTime, int randomSeed, TimeSpan? defaultStep = null) : this(new PcgRandom(randomSeed), initialDateTime, defaultStep) { }
|
---|
807 | public ThreadSafeSimulation(IRandom random, DateTime initialDateTime, TimeSpan? defaultStep = null) : base(random, initialDateTime, defaultStep) {
|
---|
808 | _locker = new object();
|
---|
809 | }
|
---|
810 |
|
---|
811 |
|
---|
812 | /// <summary>
|
---|
813 | /// Schedules an event to occur at the same simulation time as the call was made.
|
---|
814 | /// </summary>
|
---|
815 | /// <remarks>
|
---|
816 | /// This method is thread-safe against manipulations of the event queue
|
---|
817 | /// </remarks>
|
---|
818 | /// <param name="event">The event that should be scheduled.</param>
|
---|
819 | /// <param name="priority">The priority to rank events at the same time (smaller value = higher priority).</param>
|
---|
820 | public override void Schedule(Event @event, int priority = 0) {
|
---|
821 | lock (_locker) {
|
---|
822 | DoSchedule(Now, @event, priority);
|
---|
823 | }
|
---|
824 | }
|
---|
825 |
|
---|
826 | /// <summary>
|
---|
827 | /// Schedules an event to occur after a certain (positive) delay.
|
---|
828 | /// </summary>
|
---|
829 | /// <remarks>
|
---|
830 | /// This method is thread-safe against manipulations of the event queue
|
---|
831 | /// </remarks>
|
---|
832 | /// <exception cref="ArgumentException">
|
---|
833 | /// Thrown when <paramref name="delay"/> is negative.
|
---|
834 | /// </exception>
|
---|
835 | /// <param name="delay">The (positive) delay after which the event should be fired.</param>
|
---|
836 | /// <param name="event">The event that should be scheduled.</param>
|
---|
837 | /// <param name="priority">The priority to rank events at the same time (smaller value = higher priority).</param>
|
---|
838 | public override void Schedule(TimeSpan delay, Event @event, int priority = 0) {
|
---|
839 | if (delay < TimeSpan.Zero)
|
---|
840 | throw new ArgumentException("Negative delays are not allowed in Schedule(TimeSpan, Event).");
|
---|
841 | lock (_locker) {
|
---|
842 | var eventTime = Now + delay;
|
---|
843 | DoSchedule(eventTime, @event, priority);
|
---|
844 | }
|
---|
845 | }
|
---|
846 |
|
---|
847 | /// <summary>
|
---|
848 | /// Run until a certain event is processed.
|
---|
849 | /// </summary>
|
---|
850 | /// <remarks>
|
---|
851 | /// This method is thread-safe against manipulations of the event queue
|
---|
852 | /// </remarks>
|
---|
853 | /// <param name="stopEvent">The event that stops the simulation.</param>
|
---|
854 | /// <returns></returns>
|
---|
855 | public override object Run(Event stopEvent = null) {
|
---|
856 | _stop = new CancellationTokenSource();
|
---|
857 | if (stopEvent != null) {
|
---|
858 | if (stopEvent.IsProcessed) {
|
---|
859 | return stopEvent.Value;
|
---|
860 | }
|
---|
861 | stopEvent.AddCallback(StopSimulation);
|
---|
862 | }
|
---|
863 | OnRunStarted();
|
---|
864 | try {
|
---|
865 | var stop = false;
|
---|
866 | lock (_locker) {
|
---|
867 | stop = ScheduleQ.Count == 0 || _stop.IsCancellationRequested;
|
---|
868 | }
|
---|
869 | while (!stop) {
|
---|
870 | Step();
|
---|
871 | lock (_locker) {
|
---|
872 | stop = ScheduleQ.Count == 0 || _stop.IsCancellationRequested;
|
---|
873 | }
|
---|
874 | }
|
---|
875 | } catch (StopSimulationException e) { OnRunFinished(); return e.Value; }
|
---|
876 | OnRunFinished();
|
---|
877 | if (stopEvent == null) return null;
|
---|
878 | if (!_stop.IsCancellationRequested && !stopEvent.IsTriggered) throw new InvalidOperationException("No scheduled events left but \"until\" event was not triggered.");
|
---|
879 | return stopEvent.Value;
|
---|
880 | }
|
---|
881 |
|
---|
882 | public Task<object> RunAsync(TimeSpan duration) {
|
---|
883 | return Task.Run(() => Run(duration));
|
---|
884 | }
|
---|
885 |
|
---|
886 | public Task<object> RunAsync(DateTime until) {
|
---|
887 | return Task.Run(() => Run(until));
|
---|
888 | }
|
---|
889 |
|
---|
890 | /// <summary>
|
---|
891 | /// Run until a certain event is processed, but does not block.
|
---|
892 | /// </summary>
|
---|
893 | /// <param name="stopEvent">The event that stops the simulation.</param>
|
---|
894 | /// <returns></returns>
|
---|
895 | public Task<object> RunAsync(Event stopEvent = null) {
|
---|
896 | return Task.Run(() => Run(stopEvent));
|
---|
897 | }
|
---|
898 |
|
---|
899 | /// <summary>
|
---|
900 | /// Performs a single step of the simulation, i.e. process a single event
|
---|
901 | /// </summary>
|
---|
902 | /// <remarks>
|
---|
903 | /// This method is thread-safe against manipulations of the event queue
|
---|
904 | /// </remarks>
|
---|
905 | public override void Step() {
|
---|
906 | Event evt;
|
---|
907 | lock (_locker) {
|
---|
908 | var next = ScheduleQ.Dequeue();
|
---|
909 | Now = next.PrimaryPriority;
|
---|
910 | evt = next.Event;
|
---|
911 | }
|
---|
912 | evt.Process();
|
---|
913 | ProcessedEvents++;
|
---|
914 | }
|
---|
915 |
|
---|
916 | /// <summary>
|
---|
917 | /// Peeks at the time of the next event in terms of the defined step
|
---|
918 | /// </summary>
|
---|
919 | /// <remarks>
|
---|
920 | /// This method is thread-safe against manipulations of the event queue
|
---|
921 | /// </remarks>
|
---|
922 | public override double PeekD() {
|
---|
923 | lock (_locker) {
|
---|
924 | if (ScheduleQ.Count == 0) return double.MaxValue;
|
---|
925 | return (Peek() - StartDate).TotalSeconds / DefaultTimeStepSeconds;
|
---|
926 | }
|
---|
927 | }
|
---|
928 |
|
---|
929 | /// <summary>
|
---|
930 | /// Peeks at the time of the next event
|
---|
931 | /// </summary>
|
---|
932 | /// <remarks>
|
---|
933 | /// This method is thread-safe against manipulations of the event queue
|
---|
934 | /// </remarks>
|
---|
935 | public override DateTime Peek() {
|
---|
936 | lock (_locker) {
|
---|
937 | return ScheduleQ.Count > 0 ? ScheduleQ.First.PrimaryPriority : DateTime.MaxValue;
|
---|
938 | }
|
---|
939 | }
|
---|
940 | }
|
---|
941 |
|
---|
942 | /// <summary>
|
---|
943 | /// Provides a simulation environment where delays in simulation time may result in a similar
|
---|
944 | /// delay in wall-clock time. The environment is not an actual realtime simulation environment
|
---|
945 | /// in that there is no guarantee that 3 seconds in model time are also exactly 3 seconds in
|
---|
946 | /// observed wall-clock time. This simulation environment is a bit slower, as the overhead of
|
---|
947 | /// the simulation kernel (event creation, queuing, processing, etc.) is not accounted for.
|
---|
948 | ///
|
---|
949 | /// However, it features a switch between virtual and realtime, thus allowing it to be used
|
---|
950 | /// in contexts where realtime is only necessary sometimes (e.g. during interaction with
|
---|
951 | /// long-running co-processes). Such use cases may arise in simulation control problems.
|
---|
952 | /// </summary>
|
---|
953 | public class PseudoRealtimeSimulation : ThreadSafeSimulation {
|
---|
954 | public const double DefaultRealtimeScale = 1;
|
---|
955 |
|
---|
956 | /// <summary>
|
---|
957 | /// The scale at which the simulation runs in comparison to realtime. A value smaller
|
---|
958 | /// than 1 results in longer-than-realtime delays, while a value larger than 1 results
|
---|
959 | /// in shorter-than-realtime delays. A value of exactly 1 is realtime.
|
---|
960 | /// </summary>
|
---|
961 | public double? RealtimeScale { get; protected set; } = DefaultRealtimeScale;
|
---|
962 | /// <summary>
|
---|
963 | /// Whether a non-null <see cref="RealtimeScale"/> has been set.
|
---|
964 | /// </summary>
|
---|
965 | public bool IsRunningInRealtime => RealtimeScale.HasValue;
|
---|
966 |
|
---|
967 | private object _timeLocker = new object();
|
---|
968 | /// <summary>
|
---|
969 | /// The current model time. Note that, while in realtime, this may continuously change.
|
---|
970 | /// </summary>
|
---|
971 | public override DateTime Now {
|
---|
972 | get { lock (_timeLocker) { return base.Now + _rtDelayTime.Elapsed; } }
|
---|
973 | protected set => base.Now = value;
|
---|
974 | }
|
---|
975 |
|
---|
976 | protected CancellationTokenSource _rtDelayCtrl = null;
|
---|
977 | protected Stopwatch _rtDelayTime = new Stopwatch();
|
---|
978 |
|
---|
979 |
|
---|
980 | public PseudoRealtimeSimulation() : this(new DateTime(1970, 1, 1)) { }
|
---|
981 | public PseudoRealtimeSimulation(TimeSpan? defaultStep) : this(new DateTime(1970, 1, 1), defaultStep) { }
|
---|
982 | public PseudoRealtimeSimulation(DateTime initialDateTime, TimeSpan? defaultStep = null) : this(new PcgRandom(), initialDateTime, defaultStep) { }
|
---|
983 | public PseudoRealtimeSimulation(int randomSeed, TimeSpan? defaultStep = null) : this(new DateTime(1970, 1, 1), randomSeed, defaultStep) { }
|
---|
984 | public PseudoRealtimeSimulation(DateTime initialDateTime, int randomSeed, TimeSpan? defaultStep = null) : this(new PcgRandom(randomSeed), initialDateTime, defaultStep) { }
|
---|
985 | public PseudoRealtimeSimulation(IRandom random, DateTime initialDateTime, TimeSpan? defaultStep = null) : base(random, initialDateTime, defaultStep) { }
|
---|
986 |
|
---|
987 | protected override EventQueueNode DoSchedule(DateTime date, Event @event, int priority = 0) {
|
---|
988 | if (ScheduleQ.Count > 0 && date < ScheduleQ.First.PrimaryPriority) _rtDelayCtrl?.Cancel();
|
---|
989 | return base.DoSchedule(date, @event, priority);
|
---|
990 | }
|
---|
991 |
|
---|
992 | public override void Step() {
|
---|
993 | var delay = TimeSpan.Zero;
|
---|
994 | double? rtScale = null;
|
---|
995 | lock (_locker) {
|
---|
996 | if (IsRunningInRealtime) {
|
---|
997 | rtScale = RealtimeScale;
|
---|
998 | var next = ScheduleQ.First.PrimaryPriority;
|
---|
999 | delay = next - base.Now;
|
---|
1000 | if (rtScale.Value != 1.0) delay = TimeSpan.FromMilliseconds(delay.TotalMilliseconds / rtScale.Value);
|
---|
1001 | _rtDelayCtrl = CancellationTokenSource.CreateLinkedTokenSource(_stop.Token);
|
---|
1002 | }
|
---|
1003 | }
|
---|
1004 |
|
---|
1005 | if (delay > TimeSpan.Zero) {
|
---|
1006 | _rtDelayTime.Start();
|
---|
1007 | Task.Delay(delay, _rtDelayCtrl.Token).ContinueWith(_ => { }).Wait();
|
---|
1008 | _rtDelayTime.Stop();
|
---|
1009 | var observed = _rtDelayTime.Elapsed;
|
---|
1010 |
|
---|
1011 | lock (_locker) {
|
---|
1012 | if (rtScale.Value != 1.0) observed = TimeSpan.FromMilliseconds(observed.TotalMilliseconds / rtScale.Value);
|
---|
1013 | if (_rtDelayCtrl.IsCancellationRequested && observed < delay) {
|
---|
1014 | lock (_timeLocker) {
|
---|
1015 | Now = base.Now + observed;
|
---|
1016 | _rtDelayTime.Reset();
|
---|
1017 | }
|
---|
1018 | return; // next event is not processed, step is not actually completed
|
---|
1019 | }
|
---|
1020 | }
|
---|
1021 | }
|
---|
1022 |
|
---|
1023 | Event evt;
|
---|
1024 | lock (_locker) {
|
---|
1025 | var next = ScheduleQ.Dequeue();
|
---|
1026 | lock (_timeLocker) {
|
---|
1027 | _rtDelayTime.Reset();
|
---|
1028 | Now = next.PrimaryPriority;
|
---|
1029 | }
|
---|
1030 | evt = next.Event;
|
---|
1031 | }
|
---|
1032 | evt.Process();
|
---|
1033 | ProcessedEvents++;
|
---|
1034 | }
|
---|
1035 |
|
---|
1036 | /// <summary>
|
---|
1037 | /// Switches the simulation to virtual time mode, i.e., running as fast as possible.
|
---|
1038 | /// In this mode, events are processed without delay just like in a <see cref="ThreadSafeSimulation"/>.
|
---|
1039 | /// </summary>
|
---|
1040 | /// <remarks>
|
---|
1041 | /// An ongoing real-time delay is being canceled when this method is called. Usually, this
|
---|
1042 | /// is only the case when this method is called from a thread other than the main simulation thread.
|
---|
1043 | ///
|
---|
1044 | /// If the simulation is already in virtual time mode, this method has no effect.
|
---|
1045 | /// </remarks>
|
---|
1046 | public virtual void SetVirtualtime() {
|
---|
1047 | lock (_locker) {
|
---|
1048 | if (!IsRunningInRealtime) return;
|
---|
1049 | RealtimeScale = null;
|
---|
1050 | _rtDelayCtrl?.Cancel();
|
---|
1051 | }
|
---|
1052 | }
|
---|
1053 |
|
---|
1054 | /// <summary>
|
---|
1055 | /// Switches the simulation to real time mode. The real time factor of
|
---|
1056 | /// this default mode is configurable.
|
---|
1057 | /// </summary>
|
---|
1058 | /// <remarks>
|
---|
1059 | /// If this method is called while running in real-time mode, but given a different
|
---|
1060 | /// <paramref name="realtimeScale"/>, the current delay is canceled and the remaining
|
---|
1061 | /// time is delayed using the new time factor.
|
---|
1062 | ///
|
---|
1063 | /// The default factor is 1, i.e., real time - a timeout of 5 seconds would cause
|
---|
1064 | /// a wall-clock delay of 5 seconds. With a factor of 2, the delay as measured by
|
---|
1065 | /// a wall clock would be 2.5 seconds, whereas a factor of 0.5, a wall-clock delay of
|
---|
1066 | /// 10 seconds would be observed.
|
---|
1067 | /// </remarks>
|
---|
1068 | /// <param name="realtimeScale">A value strictly greater than 0 used to scale real time events.</param>
|
---|
1069 | public virtual void SetRealtime(double realtimeScale = DefaultRealtimeScale) {
|
---|
1070 | lock (_locker) {
|
---|
1071 | if (realtimeScale <= 0.0) throw new ArgumentException("The simulation speed scaling factor must be strictly positive.", nameof(realtimeScale));
|
---|
1072 | if (IsRunningInRealtime && realtimeScale != RealtimeScale) _rtDelayCtrl?.Cancel();
|
---|
1073 | RealtimeScale = realtimeScale;
|
---|
1074 | }
|
---|
1075 | }
|
---|
1076 |
|
---|
1077 | /// <summary>
|
---|
1078 | /// This is only a convenience for mixed real- and virtual time simulations.
|
---|
1079 | /// It creates a new pseudo realtime process which will set the simulation
|
---|
1080 | /// to realtime every time it continues (e.g., if it has been set to virtual time).
|
---|
1081 | /// The process is automatically scheduled to be started at the current simulation time.
|
---|
1082 | /// </summary>
|
---|
1083 | /// <param name="generator">The generator function that represents the process.</param>
|
---|
1084 | /// <param name="priority">The priority to rank events at the same time (smaller value = higher priority).</param>
|
---|
1085 | /// <param name="realtimeScale">A value strictly greater than 0 used to scale real time events (1 = realtime).</param>
|
---|
1086 | /// <returns>The scheduled process that was created.</returns>
|
---|
1087 | public Process PseudoRealtimeProcess(IEnumerable<Event> generator, int priority = 0, double realtimeScale = DefaultRealtimeScale) {
|
---|
1088 | return new PseudoRealtimeProcess(this, generator, priority, realtimeScale);
|
---|
1089 | }
|
---|
1090 | }
|
---|
1091 |
|
---|
1092 | /// <summary>
|
---|
1093 | /// Environments hold the event queues, schedule and process events.
|
---|
1094 | /// </summary>
|
---|
1095 | [Obsolete("Use class Simulation or ThreadSafeSimulation instead. Due to name clashes with System.Environment the class SimSharp.Environment is being outphased.")]
|
---|
1096 | public class Environment : ThreadSafeSimulation {
|
---|
1097 | public Environment()
|
---|
1098 | : base() {
|
---|
1099 | Random = new SystemRandom();
|
---|
1100 | }
|
---|
1101 | public Environment(TimeSpan? defaultStep)
|
---|
1102 | : base(defaultStep) {
|
---|
1103 | Random = new SystemRandom();
|
---|
1104 | }
|
---|
1105 | public Environment(int randomSeed, TimeSpan? defaultStep = null)
|
---|
1106 | : base(randomSeed, defaultStep) {
|
---|
1107 | Random = new SystemRandom(randomSeed);
|
---|
1108 | }
|
---|
1109 | public Environment(DateTime initialDateTime, TimeSpan? defaultStep = null)
|
---|
1110 | : base(initialDateTime, defaultStep) {
|
---|
1111 | Random = new SystemRandom();
|
---|
1112 | }
|
---|
1113 | public Environment(DateTime initialDateTime, int randomSeed, TimeSpan? defaultStep = null)
|
---|
1114 | : base(initialDateTime, randomSeed, defaultStep) {
|
---|
1115 | Random = new SystemRandom(randomSeed);
|
---|
1116 | }
|
---|
1117 |
|
---|
1118 | protected static readonly double NormalMagicConst = 4 * Math.Exp(-0.5) / Math.Sqrt(2.0);
|
---|
1119 | public override double RandNormal(double mu, double sigma) {
|
---|
1120 | return RandNormal(Random, mu, sigma);
|
---|
1121 | }
|
---|
1122 | public override double RandNormal(IRandom random, double mu, double sigma) {
|
---|
1123 | double z, zz, u1, u2;
|
---|
1124 | do {
|
---|
1125 | u1 = random.NextDouble();
|
---|
1126 | u2 = 1 - random.NextDouble();
|
---|
1127 | z = NormalMagicConst * (u1 - 0.5) / u2;
|
---|
1128 | zz = z * z / 4.0;
|
---|
1129 | } while (zz > -Math.Log(u2));
|
---|
1130 | return mu + z * sigma;
|
---|
1131 | }
|
---|
1132 | }
|
---|
1133 | }
|
---|