1 files changed, 142 insertions, 142 deletions

diff --git a/source/ProbabDistrib.cpp b/source/ProbabDistrib.cpp
index 98c18b8e1..5fa17c276 100644
--- a/source/ProbabDistrib.cpp
+++ b/source/ProbabDistrib.cpp
@@ -1,142 +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;

-}

-

-

-

-

+
+// 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;
+}
+
+
+
+