1 files changed, 142 insertions, 0 deletions

diff --git a/src/ProbabDistrib.cpp b/src/ProbabDistrib.cpp
new file mode 100644
index 000000000..5fa17c276
--- /dev/null
+++ b/src/ProbabDistrib.cpp
@@ -0,0 +1,142 @@
+
+// ProbabDistrib.cpp
+
+// Implements the cProbabDistrib class representing a discrete probability distribution curve and random generator
+
+#include "Globals.h"
+#include "ProbabDistrib.h"
+#include "MersenneTwister.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)
+	{
+		int 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;
+	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;
+}
+
+
+
+