summaryrefslogtreecommitdiffstats
path: root/src/ProbabDistrib.cpp
diff options
context:
space:
mode:
authorMattes D <github@xoft.cz>2013-11-27 09:23:17 +0100
committerMattes D <github@xoft.cz>2013-11-27 09:23:17 +0100
commit49760db89d94ede5d123d927141a6cd60dbaaf07 (patch)
tree6c6cf99e4cf3128311a93cd187947b502f3732a0 /src/ProbabDistrib.cpp
parentcWorld::SpawnExperienceOrb() now returns the entity ID of the spawned orb. (diff)
parentFixed VC2008 compilation, normalized include paths. (diff)
downloadcuberite-49760db89d94ede5d123d927141a6cd60dbaaf07.tar
cuberite-49760db89d94ede5d123d927141a6cd60dbaaf07.tar.gz
cuberite-49760db89d94ede5d123d927141a6cd60dbaaf07.tar.bz2
cuberite-49760db89d94ede5d123d927141a6cd60dbaaf07.tar.lz
cuberite-49760db89d94ede5d123d927141a6cd60dbaaf07.tar.xz
cuberite-49760db89d94ede5d123d927141a6cd60dbaaf07.tar.zst
cuberite-49760db89d94ede5d123d927141a6cd60dbaaf07.zip
Diffstat (limited to 'src/ProbabDistrib.cpp')
-rw-r--r--src/ProbabDistrib.cpp142
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;
+}
+
+
+
+