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/*
Copyright (C) 2000,2001 Franz Josef Och (RWTH Aachen - Lehrstuhl fuer Informatik VI)
This file is part of GIZA++ ( extension of GIZA ).
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 2
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, write to the Free Software
Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307,
USA.
*/
#include "transpair_model5.h"
#include "Parameter.h"
int m5scorefound=0,m5scorenotfound=0;
GLOBAL_PARAMETER(float,d5modelsmooth_factor,"model5SmoothFactor","smooting parameter for distortion probabilities in Model 5 (linear interpolation with constant)",PARLEV_SMOOTH,0.1);
float d5modelsmooth_countoffset=0.0;
LogProb transpair_model5::_scoreOfMove(const alignment&a, WordIndex new_i, WordIndex j,double)const
{
if( doModel4Scoring )
return transpair_model4::_scoreOfMove(a,new_i,j);
alignment b(a);
b.set(j, new_i);
LogProb a_prob=prob_of_target_and_alignment_given_source(a);
LogProb b_prob=prob_of_target_and_alignment_given_source(b);
if( a_prob )
return b_prob/a_prob;
else if( b_prob )
return 1e20;
else
return 1.0;
}
LogProb transpair_model5::_scoreOfSwap(const alignment&a, WordIndex j1, WordIndex j2,double thisValue)const
{
if( doModel4Scoring )
return transpair_model4::_scoreOfSwap(a,j1,j2,thisValue);
alignment b(a);
b.set(j1, a(j2));
b.set(j2, a(j1));
LogProb a_prob=prob_of_target_and_alignment_given_source(a);
LogProb b_prob=prob_of_target_and_alignment_given_source(b);
assert(a_prob);
assert(b_prob);
if( a_prob )
return b_prob/a_prob;
else if( b_prob )
return 1e20;
else
return 1.0;
}
//increasing efficiency: no copy of alignment (calc. everything incrementally)
LogProb transpair_model5::scoreOfMove(const alignment&a, WordIndex new_i, WordIndex j,double thisValue)const
{
if( doModel4Scoring )
return transpair_model4::scoreOfMove(a,new_i,j,thisValue);
alignment b(a);
b.set(j,new_i);
LogProb change;
const WordIndex old_i=a(j);
WordIndex f0=a.fert(0);
if (old_i == new_i)
change=1.0;
else if (old_i == 0)
change=((double)p0*p0/p1) *
((f0*(m-f0+1.0)) / ((m-2*f0+1)*(m-2*f0+2.0))) *
((PROB)(1.0)) *
(get_fertility(new_i, a.fert(new_i)+1) / get_fertility(new_i, a.fert(new_i)))*
(t(new_i, j)/t(old_i, j))*
1.0;
else if (new_i == 0)
change=(double(p1) / (p0*p0)) *
(double((m-2*f0)*(m-2*f0-1))/((1+f0)*(m-f0))) *
(1.0) *
(get_fertility(old_i, a.fert(old_i)-1) /get_fertility(old_i, a.fert(old_i)))*
(t(new_i, j) /t(old_i, j)) *
(1.0);
else
change=(1.0) *
(get_fertility(old_i,a.fert(old_i)-1) / get_fertility(old_i,a.fert(old_i))) *
(get_fertility(new_i,a.fert(new_i)+1) /get_fertility(new_i,a.fert(new_i))) *
(t(new_i,j)/t(old_i,j)) *
(1.0);
LogProb a_prob=thisValue;
if( a_prob<0.0 )
a_prob=prob_of_target_and_alignment_given_source(a,2);
massert(a_prob==prob_of_target_and_alignment_given_source(a,2));
LogProb b_prob=prob_of_target_and_alignment_given_source(b,2);
change*=b_prob/a_prob;
return change;
}
LogProb transpair_model5::scoreOfSwap(const alignment&a, WordIndex j1, WordIndex j2,double thisValue)const
{
if( doModel4Scoring )
return transpair_model4::scoreOfSwap(a,j1,j2,thisValue);
alignment b(a);
b.set(j1,a(j2));
b.set(j2,a(j1));
LogProb change=transpair_model3::scoreOfSwap(a,j1,j2,-1.0,0);
LogProb a_prob=thisValue;
if( a_prob<0.0 )
a_prob=prob_of_target_and_alignment_given_source(a,2);
massert(a_prob==prob_of_target_and_alignment_given_source(a,2));
LogProb b_prob=prob_of_target_and_alignment_given_source(b,2);
change*=b_prob/a_prob;
return change;
}
LogProb transpair_model5::prob_of_target_and_alignment_given_source(const alignment&al, short distortionType,bool verb)const
{
if( doModel4Scoring )
return transpair_model4::prob_of_target_and_alignment_given_source(al,distortionType);
LogProb total = 1.0 ;
static const LogProb almostZero = 1E-299 ;
double x2;
if( distortionType&1 ) {
total *= pow(double(1-p1), m-2.0 * al.fert(0)) * pow(double(p1), double(al.fert(0)));
if( verb) cerr << "IBM-5: (1-p1)^(m-2 f0)*p1^f0: " << total << endl;
for (WordIndex i = 1 ; i <= al.fert(0) ; i++)
total *= double(m - al.fert(0) - i + 1) / i ; // IBM-5 is not deficient!
if( verb) cerr << "IBM-5: +NULL:binomial+distortion " << total << endl;
for (WordIndex i = 1 ; i <= l ; i++) {
total *= get_fertility(i, al.fert(i));
if( verb) cerr << "IBM-5: fertility of " << i << " " << get_fertility(i, al.fert(i)) << " -> " << total << endl;
}
for (WordIndex j = 1 ; j <= m ; j++) {
total*= get_t(al(j), j) ;
if( verb) cerr << "IBM-5: t of j:" << j << " i:" << al(j) << ": " << get_t(al(j), j) << " -> " << total << endl;
}
}
if( distortionType&2 ) {
PositionIndex prev_cept=0;
PositionIndex vac_all=m;
Vector<char> vac(m+1,0);
for(WordIndex i=1; i<=l; i++) {
PositionIndex cur_j=al.als_i[i];
PositionIndex prev_j=0;
PositionIndex k=0;
if(cur_j) { // process first word of cept
k++;
// previous position
total*= (x2=d5m.getProb_first(vacancies(vac,cur_j),vacancies(vac,al.get_center(prev_cept)),d5m.fwordclasses->getClass(get_fs(cur_j)),l,m,vac_all-al.fert(i)+k));
vac_all--;
assert(vac[cur_j]==0);
vac[cur_j]=1;
if( verb) cerr << "IBM-5: d=1 of " << cur_j << ": " << x2 << " -> " << total << endl;
prev_j=cur_j;
cur_j=al.als_j[cur_j].next;
}
while(cur_j) { // process following words of cept
k++;
// previous position
int vprev=vacancies(vac,prev_j);
total*= (x2=d5m.getProb_bigger(vacancies(vac,cur_j),vprev,d5m.fwordclasses->getClass(get_fs(cur_j)),l,m,vac_all-vprev/*war weg*/-al.fert(i)+k));
vac_all--;
vac[cur_j]=1;
if( verb) cerr << "IBM-5: d>1 of " << cur_j << ": " << x2 << " -> " << total << endl;
prev_j=cur_j;
cur_j=al.als_j[cur_j].next;
}
assert(k==al.fert(i));
if( k )
prev_cept=i;
}
assert(vac_all==al.fert(0));
}
total = total?total:almostZero;
return total;
}
void transpair_model5::computeScores(const alignment&al,vector<double>&d)const
{
LogProb total1 = 1.0,total2=1.0,total3=1.0,total4=1.0 ;
total1 *= pow(double(1-p1), m-2.0 * al.fert(0)) * pow(double(p1), double(al.fert(0)));
for (WordIndex i = 1 ; i <= al.fert(0) ; i++)
total1 *= double(m - al.fert(0) - i + 1) / i ; // IBM-5 is not deficient!
for (WordIndex i = 1 ; i <= l ; i++)
total2 *= get_fertility(i, al.fert(i));
for (WordIndex j = 1 ; j <= m ; j++)
total3*= get_t(al(j), j) ;
PositionIndex prev_cept=0;
PositionIndex vac_all=m;
Vector<char> vac(m+1,0);
for(WordIndex i=1; i<=l; i++) {
PositionIndex cur_j=al.als_i[i];
PositionIndex prev_j=0;
PositionIndex k=0;
if(cur_j) { // process first word of cept
k++;
total4*=d5m.getProb_first(vacancies(vac,cur_j),vacancies(vac,al.get_center(prev_cept)),d5m.fwordclasses->getClass(get_fs(cur_j)),l,m,vac_all-al.fert(i)+k);
vac_all--;
assert(vac[cur_j]==0);
vac[cur_j]=1;
prev_j=cur_j;
cur_j=al.als_j[cur_j].next;
}
while(cur_j) { // process following words of cept
k++;
int vprev=vacancies(vac,prev_j);
total4*=d5m.getProb_bigger(vacancies(vac,cur_j),vprev,d5m.fwordclasses->getClass(get_fs(cur_j)),l,m,vac_all-vprev/*war weg*/-al.fert(i)+k);
vac_all--;
vac[cur_j]=1;
prev_j=cur_j;
cur_j=al.als_j[cur_j].next;
}
assert(k==al.fert(i));
if( k )
prev_cept=i;
}
assert(vac_all==al.fert(0));
d.push_back(total1);//13
d.push_back(total2);//14
d.push_back(total3);//15
d.push_back(total4);//16
}
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