def sparseAlignSimple(self, stateMachine, points, size):
p = points["points"][:]
gp = points["gapPoints"][:]
blp = points["blGaps"][:]
trp = points["trGaps"][:]
print "points ", p
print "gapPoints ", gp
print "blPoints ", blp
print "trPoints ", trp
pPA = {}
for i in p:
pPA[i] = Maths.NEG_INFINITY
def makeMatrix(values):
matrix = [ [False]*size for i in xrange(0, size) ]
for i in values:
matrix[i[0]][i[1]] = True
return matrix
fMatrix = [ [ [Maths.NEG_INFINITY]*stateMachine.stateNo() for j in xrange(0, size) ] for i in xrange(0, size) ]
bMatrix = [ [ [Maths.NEG_INFINITY]*stateMachine.stateNo() for j in xrange(0, size) ] for i in xrange(0, size) ]
def fn3(i):
if i == MATCH:
return 0
return Maths.NEG_INFINITY
startStates = [ fn3(i) for i in stateMachine.getStateTypes() ]
fMatrix[0][0] = startStates[:] #[0]*stateMachine.stateNo()
bMatrix[size-1][size-1] = startStates[:]#[0]*stateMachine.stateNo()
#fMatrix[0][0] = [0]*stateMachine.stateNo()
#bMatrix[size-1][size-1] = [0]*stateMachine.stateNo()
def bTransition(s, sI, s2, sI2, i, j, t, de, *args):
s2[i] = Maths.logAdd(s2[i], s[j] + t + de)
print "doing backwards "
fn = stateMachine.getFns(bTransition)
computeMatrixR(bMatrix, makeMatrix(gp),
makeMatrix(p),
makeMatrix(blp),
makeMatrix(trp),
fn[(MATCH, GAP)],
fn[(GAP, GAP)],
fn[(GAP, MATCH)],
fn[(MATCH, MATCH)])
stateNo = stateMachine.stateNo()
total = SparseAlign.logSum([ bMatrix[0][0][i] + startStates[i] for i in range(0, stateNo)])
#total = bMatrix[0][0][0]#SparseAlign.logSum(bMatrix[0][0])
stateNo = stateMachine.stateNo()
print "doing forwards "
def fTransition(s, sI, s2, sI2, i, j, t, de, x2, y2, x1, y1):
l = s[i] + t + de
s2[j] = Maths.logAdd(s2[j], l)
l += bMatrix[x1][y1][j] - total
#print x1, x2, "boo"
if x2 >= x1:
raise IndexError()
for k in xrange(0, x1-x2):
pPA[(x1-k, y1-k)] = Maths.logAdd(pPA[(x1-k, y1-k)], l)
fn = stateMachine.getFns(fTransition)
def fTransition2(s, sI, s2, sI2, i, j, t, de, x2, y2, x1, y1):
l = s[i] + t + de
s2[j] = Maths.logAdd(s2[j], l)
fn2 = stateMachine.getFns(fTransition2)
print "gp", gp
computeMatrix(fMatrix, makeMatrix(gp),
makeMatrix(p),
makeMatrix(blp),
makeMatrix(trp),
fn2[(MATCH, GAP)],
fn2[(GAP, GAP)],
fn[(GAP, MATCH)],
fn[(MATCH, MATCH)])
print "fmatrix ", fMatrix
print "bmatrix ", bMatrix
print fMatrix[0][0], "cro", SparseAlign.logSum(bMatrix[0][0])
return (SparseAlign.logSum([ fMatrix[size-1][size-1][i] + startStates[i] for i in range(0, stateNo)]),
SparseAlign.logSum([ bMatrix[0][0][i] + startStates[i] for i in range(0, stateNo)]) , pPA)
