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/*
<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/>.
*/
#include "tree/phylotree.h"
#include "ratekategory.h"
RateKategory::RateKategory(int ncat, PhyloTree *tree)
{
ncategory = ncat;
phylo_tree = tree;
rates = new double[ncategory];
name = "+K";
name += convertIntToString(ncategory);
full_name = "KAT";
full_name += " with " + convertIntToString(ncategory) + " categories";
if (ncategory == 1) { rates[0] = 1.0; return; }
int i;
for (i = 0; i < ncategory; i++) do { rates[i] = random_double(); } while (rates[i]<0.1 || rates[i] > 0.9);
//for (i = 0; i < ncategory; i++) rates[i] = 1.0 + i;
double sum = 0.0;
for (i = 0; i < ncategory; i++) sum += rates[i];
for (i = 0; i < ncategory; i++) rates[i] = rates[i]*ncategory/sum;
}
RateKategory::~RateKategory()
{
if (rates) delete [] rates;
rates = NULL;
}
double RateKategory::targetFunk(double x[])
{
getVariables(x);
if (rates[ncategory-1] < 1e-4) return 1.0e+12;
ASSERT(phylo_tree);
phylo_tree->clearAllPartialLH();
return -phylo_tree->computeLikelihood();
}
double RateKategory::optimizeParameters(double gradient_epsilon)
{
int ndim = getNDim();
// return if nothing to be optimized
if (ndim == 0) return 0.0;
if (verbose_mode >= VB_MAX)
cout << "Optimizing " << name << " model parameters..." << endl;
//if (freq_type == FREQ_ESTIMATE) scaleStateFreq(false);
double *variables = new double[ndim+1];
double *upper_bound = new double[ndim+1];
double *lower_bound = new double[ndim+1];
bool *bound_check = new bool[ndim+1];
int i;
double score;
// by BFGS algorithm
setVariables(variables);
for (i = 1; i <= ndim; i++) {
//cout << variables[i] << endl;
lower_bound[i] = 1e-4;
upper_bound[i] = ncategory;
bound_check[i] = false;
}
score = -minimizeMultiDimen(variables, ndim, lower_bound, upper_bound, bound_check, max(gradient_epsilon, 1e-6));
getVariables(variables);
//sort(rates, rates+ncategory);
phylo_tree->clearAllPartialLH();
score = phylo_tree->computeLikelihood();
delete [] bound_check;
delete [] lower_bound;
delete [] upper_bound;
delete [] variables;
return score;
}
int RateKategory::computePatternRates(DoubleVector& pattern_rates, IntVector& pattern_cat)
{
cout << "Computing site rates by empirical Bayes..." << endl;
phylo_tree->computePatternLhCat(WSL_RATECAT);
int npattern = phylo_tree->aln->getNPattern();
pattern_rates.resize(npattern);
pattern_cat.resize(npattern);
double *lh_cat = phylo_tree->_pattern_lh_cat;
for (int i = 0; i < npattern; i++) {
double sum_rate = 0.0, sum_lh = 0.0;
int best = 0;
for (int c = 0; c < ncategory; c++) {
sum_rate += rates[c] * lh_cat[c];
sum_lh += lh_cat[c];
if (lh_cat[c] > lh_cat[best]) best = c;
}
pattern_rates[i] = sum_rate / sum_lh;
pattern_cat[i] = best;
lh_cat += ncategory;
}
return ncategory;
// int npattern = phylo_tree->aln->getNPattern();
// double *ptn_rates = new double[npattern];
// phylo_tree->computeLikelihoodBranchNaive((PhyloNeighbor*)phylo_tree->root->neighbors[0],
// (PhyloNode*)phylo_tree->root, NULL, ptn_rates);
//
// pattern_rates.clear();
// pattern_rates.insert(pattern_rates.begin(), ptn_rates, ptn_rates + npattern);
// pattern_cat.resize(npattern, 0);
// for (int i = 0; i < npattern; i++)
// for (int j = 1; j < ncategory; j++)
// if (fabs(rates[j] - ptn_rates[i]) < fabs(rates[pattern_cat[i]] - ptn_rates[i]))
// pattern_cat[i] = j;
// delete [] ptn_rates;
}
bool RateKategory::getVariables(double* variables)
{
if (ncategory == 1) return false;
bool changed = (rates[0] != 1.0);
rates[0] = 1.0;
changed |= memcmpcpy(rates, variables+1, (ncategory-1) * sizeof(double));
double sum = 0.0;
int i;
for (i = 0; i < ncategory-1; i++)
sum += rates[i];
/*
for (i = 0; i < ncategory; i++)
rates[i] = rates[i]*ncategory/sum;*/
changed |= (rates[ncategory-1] != ncategory - sum);
rates[ncategory-1] = ncategory - sum;
return changed;
}
void RateKategory::setVariables(double* variables)
{
if (ncategory == 1) return;
memcpy(variables+1, rates, (ncategory-1) * sizeof(double));
}
void RateKategory::writeInfo(ostream& out)
{
out << "Rates: ";
for (int i = 0; i < ncategory; i++)
out << " " << rates[i];
out << endl;
out << "BIC: " << -2 * phylo_tree->computeLikelihood() + getNDim() * log(phylo_tree->getAlnNSite()) << endl;
}
void RateKategory::writeParameters(ostream& out)
{
}
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