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128 lines
4.0 KiB
C++
128 lines
4.0 KiB
C++
#ifndef ___COMPUTE_JUMPS__
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#define ___COMPUTE_JUMPS__
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#include "definitions.h"
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#include "tree.h"
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#include "stochasticProcess.h"
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#include "alphabet.h"
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#include "someUtil.h"
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#include <math.h>
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#include <map>
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#include <vector>
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using namespace std;
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/******************************************************************
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This class compute jumps (events) by Suchard equations along differing branch lengths (according to a
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given tree), with the aim of giving the expectation of the number of jumps
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from state a to state b given that the terminal states at the end of the branch are
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x and y.
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*******************************************************************/
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class computeJumps {
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public:
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computeJumps(const MDOUBLE Lambda1, const MDOUBLE Lambda2, const MDOUBLE r=1, const int maxNumOfChangesPerBranchSum=5);
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virtual ~computeJumps();
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/******************************************************************
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Foreach computeJumps, for gFunc objects are needed:
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inner class gFunc, if startState=0, Lambda1=gain, Lambda2= loss
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if startState=1, Lambda1=loss, Lambda2= gain.
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For both with use +r and -r versions
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*******************************************************************/
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class gFunc {
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public:
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gFunc(const MDOUBLE Lambda1, const MDOUBLE Lambda2 , const MDOUBLE r);
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gFunc(){};
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~gFunc(){};
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MDOUBLE gFunc_dr(MDOUBLE BranchLength);
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MDOUBLE g1Func_dr(MDOUBLE BranchLength);
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MDOUBLE g2Func_dr(MDOUBLE BranchLength);
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MDOUBLE g1Exp(MDOUBLE BranchLength);
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MDOUBLE g2Exp(MDOUBLE BranchLength);
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MDOUBLE gFunc_(MDOUBLE BranchLength);
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//////////////////////////////////////////////////////////////////////////
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MDOUBLE _A_(int k, int i);
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MDOUBLE _B_(int k, int i);
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MDOUBLE _C_(int k, int i);
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MDOUBLE _D_(int k, int i);
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// prob for (2k-1) transitions (gains and losses), given start=0
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MDOUBLE qFunc_2k_1 (MDOUBLE BranchLength, int k=1);
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// prob for (2k) transitions (gains and losses), given start=0
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MDOUBLE qFunc_2k (MDOUBLE BranchLength, int k=0);
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private:
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MDOUBLE _r;
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MDOUBLE _Lambda1;
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MDOUBLE _Lambda2;
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MDOUBLE _Alpha1;
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MDOUBLE _Alpha2;
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MDOUBLE _Alpha1_dr;
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MDOUBLE _Alpha2_dr;
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MDOUBLE _Alpha1_2;
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MDOUBLE _Alpha1_2_dr;
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MDOUBLE _delta;
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MDOUBLE _delta_dr;
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MDOUBLE _g1Part;
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MDOUBLE _g2Part;
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MDOUBLE _g1Part_dr;
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MDOUBLE _g2Part_dr;
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};
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//////////////////////////////////////////////////////////////////////////
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MDOUBLE getExpectation(const MDOUBLE BranchLength, int terminalStart, int terminalEnd, int fromId, int toId);
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MDOUBLE getTotalExpectation(const MDOUBLE BranchLength, int terminalStart, int terminalEnd);
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MDOUBLE gainExp(MDOUBLE BranchLength,MDOUBLE prob01,MDOUBLE prob11);
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MDOUBLE gainExpGiven01(MDOUBLE BranchLength);
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MDOUBLE gainExpGiven00(MDOUBLE BranchLength);
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MDOUBLE gainExpGiven11(MDOUBLE BranchLength);
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MDOUBLE gainExpGiven10(MDOUBLE BranchLength);
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MDOUBLE lossExpGiven01(MDOUBLE BranchLength);
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MDOUBLE lossExpGiven00(MDOUBLE BranchLength);
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MDOUBLE lossExpGiven11(MDOUBLE BranchLength);
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MDOUBLE lossExpGiven10(MDOUBLE BranchLength);
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MDOUBLE getProb(const MDOUBLE BranchLength, int terminalStart, int terminalEnd, int fromId, int toId);
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MDOUBLE gainProbGiven01(MDOUBLE BranchLength);
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MDOUBLE gainProbGiven00(MDOUBLE BranchLength);
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MDOUBLE gainProbGiven11(MDOUBLE BranchLength);
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MDOUBLE gainProbGiven10(MDOUBLE BranchLength);
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MDOUBLE lossProbGiven01(MDOUBLE BranchLength);
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MDOUBLE lossProbGiven00(MDOUBLE BranchLength);
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MDOUBLE lossProbGiven11(MDOUBLE BranchLength);
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MDOUBLE lossProbGiven10(MDOUBLE BranchLength);
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MDOUBLE gFunc_dr(MDOUBLE BranchLength, int startState);
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private:
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MDOUBLE m01(MDOUBLE BranchLength);
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MDOUBLE m00(MDOUBLE BranchLength);
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MDOUBLE m11(MDOUBLE BranchLength);
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MDOUBLE m10(MDOUBLE BranchLength);
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MDOUBLE Pij_t(const int i,const int j, const MDOUBLE d);
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MDOUBLE _Lambda1;
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MDOUBLE _Lambda2;
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int _maxNumOfChangesPerBranchSum;
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gFunc _gFuncStart0;
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gFunc _gFuncStart0MinusR;
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gFunc _gFuncStart1;
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gFunc _gFuncStart1MinusR;
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};
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#endif
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