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#cython: language_level=3
'''
Created on 6 Nov. 2009
@author: coissac
'''
cdef class NWS(DynamicProgramming):
def __init__(self,match=4,mismatch=-6,opengap=-8,extgap=-2):
DynamicProgramming.__init__(self,opengap,extgap)
self._match=match
self._mismatch=mismatch
cdef double matchScore(self,int h, int v):
cdef double score
score = iupacPartialMatch(self.hSeq.sequence[h-1],self.vSeq.sequence[v-1])
return score * self._match + (1-score) * self._mismatch
cdef double doAlignment(self) except? 0:
cdef int i # vertical index
cdef int j # horizontal index
cdef int idx
cdef int jump
cdef int delta
cdef double score
cdef double scoremax
cdef int path
if self.needToCompute:
self.allocate()
self.reset()
for j in range(1,self._hlen()+1):
idx = self.index(j,0)
self.matrix.matrix[idx].score = self._opengap + (self._extgap * (j-1))
self.matrix.matrix[idx].path = j
for i in range(1,self._vlen()+1):
idx = self.index(0,i)
self.matrix.matrix[idx].score = self._opengap + (self._extgap * (i-1))
self.matrix.matrix[idx].path = -i
for i in range(1,self._vlen()+1):
for j in range(1,self._hlen()+1):
# 1 - came from diagonal
idx = self.index(j-1,i-1)
# print "computing cell : %d,%d --> %d/%d" % (j,i,self.index(j,i),self.matrix.msize),
scoremax = self.matrix.matrix[idx].score + \
self.matchScore(j,i)
path = 0
# print "so=%f sd=%f sm=%f" % (self.matrix.matrix[idx].score,self.matchScore(j,i),scoremax),
# 2 - open horizontal gap
idx = self.index(j-1,i)
score = self.matrix.matrix[idx].score + \
self._opengap
if score > scoremax :
scoremax = score
path = +1
# 3 - open vertical gap
idx = self.index(j,i-1)
score = self.matrix.matrix[idx].score + \
self._opengap
if score > scoremax :
scoremax = score
path = -1
# 4 - extend horizontal gap
jump = self.matrix.bestHJump[i]
if jump >= 0:
idx = self.index(jump,i)
delta = j-jump
score = self.matrix.matrix[idx].score + \
self._extgap * delta
if score > scoremax :
scoremax = score
path = delta+1
# 5 - extend vertical gap
jump = self.matrix.bestVJump[j]
if jump >= 0:
idx = self.index(j,jump)
delta = i-jump
score = self.matrix.matrix[idx].score + \
self._extgap * delta
if score > scoremax :
scoremax = score
path = -delta-1
idx = self.index(j,i)
self.matrix.matrix[idx].score = scoremax
self.matrix.matrix[idx].path = path
if path == -1:
self.matrix.bestVJump[j]=i
elif path == +1 :
self.matrix.bestHJump[i]=j
self.sequenceChanged=False
self.scoreChanged=False
idx = self.index(self._hlen(),self._vlen())
return self.matrix.matrix[idx].score
cdef void backtrack(self):
#cdef list path=[]
cdef int i
cdef int j
cdef int p
self.doAlignment()
i=self._vlen()
j=self._hlen()
self.path=allocatePath(i,j,self.path)
while (i or j):
p=self.matrix.matrix[self.index(j,i)].path
self.path.path[self.path.length]=p
self.path.length+=1
#path.append(p)
if p==0:
i-=1
j-=1
elif p < 0:
i+=p
else:
j-=p
#path.reverse()
#reversePath(self.path)
self.path.hStart=0
self.path.vStart=0
#return 0,0,path
property match:
def __get__(self):
return self._match
def __set__(self,match):
self._match=match
self.scoreChanged=True
property mismatch:
def __get__(self):
return self._mismatch
def __set__(self,mismatch):
self._mismatch=mismatch
self.scoreChanged=True
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