def sparseAlignReal(self, stateMachine, points):
p = points["points"][:]
gp = points["gapPoints"][:]
blp = points["blGaps"][:]
trp = points["trGaps"][:]
pPA = {}
for i in p:
pPA[i] = 0
def join(one, two):
def f(*args):
two(*args)
one(*args)
return f
total = [0]
def totalGetter(t):
total[0] = t
pP.total(t)
#totalFn, startDiagonal, endDiagonal, interval
rescale = SparseAlign.Rescale(1, stateMachine.stateNo())
stateMachine.mapEmissions(rescale.rescaleFn)
pPoints = p[:]
pPoints.sort()
pPoint = pPoints[len(pPoints)-1]
bTransition = SparseAlign.BTransitionAndTotalReCalculator(totalGetter, 0, pPoint[0] + pPoint[1], r.randrange(1, 2 + 1.5*(pPoint[0] + pPoint[1])), stateMachine.stateNo())
pP = SparseAlign.PosteriorProbs(pPA, stateMachine.stateNo())
fn = stateMachine.getFns(join(pP.bTransition, bTransition.bTransition))
fn_2 = stateMachine.getFns(bTransition.bTransition)
fn2 = stateMachine.getFns(SparseAlign.fTransition(stateMachine.stateNo()))
x1 = [0]
y1 = [0]
x2 = [0]
y2 = [0]
def diagBuilder(i, j):
x2[0] = i
y2[0] = j
def diagStart(i, j):
x1[0] = i
y1[0] = j
x2[0] = i
y2[0] = j
def diagEnd():
pass
def dFW(diagFn):
def f(s1, sI, s2, sI2, ):
return diagFn(s1, sI, s2, sI2, x2[0]-1, y2[0]-1, x1[0], y1[0])
return f
def fn3(i):
if i == MATCH:
return 0
return Maths.NEG_INFINITY
startStates = [ fn3(i) for i in stateMachine.getStateTypes() ]
SparseAlign.sparseAlign(startStates[:],#*stateMachine.stateNo(),
p, blp, trp,
startStates[:],#[0]*stateMachine.stateNo(),
stateMachine.stateNo(),
fn2[(MATCH, GAP)],
fn2[(GAP, GAP)],
diagStart,
diagBuilder,
diagEnd,
dFW(fn2[(GAP, MATCH)]),
dFW(fn2[(MATCH, MATCH)]),
fn_2[(MATCH, GAP)],
fn_2[(GAP, GAP)],
join(diagStart, pP.diagStart),
join(diagBuilder, pP.diagBuilder),
join(diagEnd, pP.diagEnd),
dFW(fn[(GAP, MATCH)]),
dFW(fn[(MATCH, MATCH)]),
totalGetter,
rescale, 1000000)
return (total[0], total[0], pPA)
