143 lines
2.8 KiB
C++
143 lines
2.8 KiB
C++
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// ProbabDistrib.cpp
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// Implements the cProbabDistrib class representing a discrete probability distribution curve and random generator
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#include "Globals.h"
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#include "ProbabDistrib.h"
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#include "FastRandom.h"
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cProbabDistrib::cProbabDistrib(int a_MaxValue) :
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m_MaxValue(a_MaxValue),
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m_Sum(-1)
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{
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}
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void cProbabDistrib::SetPoints(const cProbabDistrib::cPoints & a_Points)
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{
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ASSERT(!a_Points.empty());
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m_Sum = 0;
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m_Cumulative.clear();
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m_Cumulative.reserve(a_Points.size() + 1);
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int ProbSum = 0;
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int LastProb = 0;
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int LastValue = -1;
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if (a_Points[0].m_Value != 0)
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{
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m_Cumulative.push_back(cPoint(0, 0)); // Always push in the [0, 0] point for easier search algorithm bounds
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LastValue = 0;
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}
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for (cPoints::const_iterator itr = a_Points.begin(), end = a_Points.end(); itr != end; ++itr)
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{
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if (itr->m_Value == LastValue)
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{
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continue;
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}
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// Add the current trapezoid to the sum:
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ProbSum += (LastProb + itr->m_Probability) * (itr->m_Value - LastValue) / 2;
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LastProb = itr->m_Probability;
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LastValue = itr->m_Value;
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m_Cumulative.push_back(cPoint(itr->m_Value, ProbSum));
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} // for itr - a_Points[]
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if (LastValue != m_MaxValue)
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{
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m_Cumulative.push_back(cPoint(m_MaxValue, 0)); // Always push in the last point for easier search algorithm bounds
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}
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m_Sum = ProbSum;
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}
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bool cProbabDistrib::SetDefString(const AString & a_DefString)
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{
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AStringVector Points = StringSplitAndTrim(a_DefString, ";");
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if (Points.empty())
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{
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return false;
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}
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cPoints Pts;
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for (AStringVector::const_iterator itr = Points.begin(), end = Points.end(); itr != end; ++itr)
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{
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AStringVector Split = StringSplitAndTrim(*itr, ",");
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if (Split.size() != 2)
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{
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// Bad format
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return false;
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}
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int Value = atoi(Split[0].c_str());
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int Prob = atoi(Split[1].c_str());
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if (
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((Value == 0) && (Split[0] != "0")) ||
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((Prob == 0) && (Split[1] != "0"))
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)
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{
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// Number parse error
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return false;
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}
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Pts.push_back(cPoint(Value, Prob));
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} // for itr - Points[]
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SetPoints(Pts);
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return true;
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}
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int cProbabDistrib::Random(MTRand & a_Rand) const
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{
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int v = a_Rand.randInt(m_Sum);
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return MapValue(v);
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}
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int cProbabDistrib::MapValue(int a_OrigValue) const
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{
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ASSERT(a_OrigValue >= 0);
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ASSERT(a_OrigValue < m_Sum);
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// Binary search through m_Cumulative for placement:
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size_t Lo = 0;
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size_t Hi = m_Cumulative.size() - 1;
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while (Hi - Lo > 1)
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{
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size_t Mid = (Lo + Hi) / 2;
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int MidProbab = m_Cumulative[Mid].m_Probability;
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if (MidProbab < a_OrigValue)
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{
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Lo = Mid;
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}
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else
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{
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Hi = Mid;
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}
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}
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ASSERT(Hi - Lo == 1);
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// Linearly interpolate between Lo and Hi:
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int ProbDif = m_Cumulative[Hi].m_Probability - m_Cumulative[Lo].m_Probability;
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int ValueDif = m_Cumulative[Hi].m_Value - m_Cumulative[Lo].m_Value;
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return m_Cumulative[Lo].m_Value + (a_OrigValue - m_Cumulative[Lo].m_Probability) * ValueDif / ProbDif;
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}
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