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