-
Notifications
You must be signed in to change notification settings - Fork 3
/
modelset.h
182 lines (144 loc) · 5.9 KB
/
modelset.h
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
/*
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) 2012 BUI Quang Minh <email>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef MODELSET_H
#define MODELSET_H
#include "gtrmodel.h"
/**
* a set of substitution models, used eg for site-specific state frequency model or
* partition model with joint branch lengths
*/
class ModelSet : public GTRModel, public vector<GTRModel*>
{
public:
ModelSet(const char *model_name, PhyloTree *tree);
/**
* @return TRUE if this is a site-specific model, FALSE otherwise
*/
virtual bool isSiteSpecificModel() { return true; }
/**
* get the size of transition matrix, default is num_states*num_states.
* can be changed for e.g. site-specific model
*/
virtual int getTransMatrixSize() { return num_states * num_states * size(); }
/**
compute the transition probability matrix.
@param time time between two events
@param trans_matrix (OUT) the transition matrix between all pairs of states.
Assume trans_matrix has size of num_states * num_states.
*/
virtual void computeTransMatrix(double time, double *trans_matrix);
/**
* wrapper for computing transition matrix times state frequency vector
* @param time time between two events
* @param trans_matrix (OUT) the transition matrix between all pairs of states.
* Assume trans_matrix has size of num_states * num_states.
*/
virtual void computeTransMatrixFreq(double time, double *trans_matrix);
/**
compute the transition probability matrix.and the derivative 1 and 2
@param time time between two events
@param trans_matrix (OUT) the transition matrix between all pairs of states.
Assume trans_matrix has size of num_states * num_states.
@param trans_derv1 (OUT) the 1st derivative matrix between all pairs of states.
@param trans_derv2 (OUT) the 2nd derivative matrix between all pairs of states.
*/
virtual void computeTransDerv(double time, double *trans_matrix,
double *trans_derv1, double *trans_derv2);
/**
compute the transition probability matrix.and the derivative 1 and 2 times state frequency vector
@param time time between two events
@param trans_matrix (OUT) the transition matrix between all pairs of states.
Assume trans_matrix has size of num_states * num_states.
@param trans_derv1 (OUT) the 1st derivative matrix between all pairs of states.
@param trans_derv2 (OUT) the 2nd derivative matrix between all pairs of states.
*/
virtual void computeTransDervFreq(double time, double rate_val, double *trans_matrix,
double *trans_derv1, double *trans_derv2);
/**
To AVOID 'hides overloaded virtual functions
compute the transition probability between two states
@param time time between two events
@param state1 first state
@param state2 second state
*/
virtual double computeTrans(double time, int state1, int state2) { return 0; }
/**
To AVOID 'hides overloaded virtual functions
compute the transition probability between two states
@param time time between two events
@param state1 first state
@param state2 second state
@param derv1 (OUT) 1st derivative
@param derv2 (OUT) 2nd derivative
*/
virtual double computeTrans(double time, int state1, int state2, double &derv1, double &derv2) { return 0; }
/**
compute the transition probability between two states at a specific site
One should override this function when defining new model.
The default is the Juke-Cantor model, valid for all kind of data (DNA, AA, Codon, etc)
@param time time between two events
@param model_id model ID
@param state1 first state
@param state2 second state
*/
virtual double computeTrans(double time, int model_id, int state1, int state2);
/**
compute the transition probability and its 1st and 2nd derivatives between two states at a specific site
One should override this function when defining new model.
The default is the Juke-Cantor model, valid for all kind of data (DNA, AA, Codon, etc)
@param time time between two events
@param model_id model ID
@param state1 first state
@param state2 second state
@param derv1 (OUT) 1st derivative
@param derv2 (OUT) 2nd derivative
*/
virtual double computeTrans(double time, int model_id, int state1, int state2, double &derv1, double &derv2);
/**
* @return pattern ID to model ID map, useful for e.g., partition model
* @param ptn pattern ID of the alignment
*/
virtual int getPtnModelID(int ptn);
/**
return the number of dimensions
*/
virtual int getNDim();
/**
write information
@param out output stream
*/
virtual void writeInfo(ostream &out);
/**
decompose the rate matrix into eigenvalues and eigenvectors
*/
virtual void decomposeRateMatrix();
~ModelSet();
/** map from pattern ID to model ID */
IntVector pattern_model_map;
protected:
/**
this function is served for the multi-dimension optimization. It should pack the model parameters
into a vector that is index from 1 (NOTE: not from 0)
@param variables (OUT) vector of variables, indexed from 1
*/
virtual void setVariables(double *variables);
/**
this function is served for the multi-dimension optimization. It should assign the model parameters
from a vector of variables that is index from 1 (NOTE: not from 0)
@param variables vector of variables, indexed from 1
*/
virtual void getVariables(double *variables);
};
#endif // MODELSET_H