示例#1
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 def test_key_to_coordinate(self):
     f = opengm.SparseFunction([2, 3, 4], 0)
     c = numpy.ones(3, dtype=numpy.uint64)
     for key, cTrue in enumerate(opengm.shapeWalker(f.shape)):
         f.keyToCoordinate(key, c)
         for ct, cOwn in zip(cTrue, c):
             assert ct == cOwn
示例#2
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 def test_dense_assignment(self):
     f = opengm.SparseFunction()
     fDense = numpy.zeros([3, 4])
     fDense[0, 1] = 1
     fDense[0, 2] = 2
     f.assignDense(fDense, 0)
     assert f.dimension == 2
     assert f.shape[0] == 3
     assert f.shape[1] == 4
     assert f[[0, 0]] == 0
     assert f[[0, 1]] == 1
     assert f[[0, 2]] == 2
     for c in opengm.shapeWalker(f.shape):
         assert f[c] == fDense[c[0], c[1]]
     assert len(f.container) == 2
示例#3
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文件: test.py 项目: vene/opengm
def genericSolverCheck(solverClass, params, gms, semiRings,checkPartial=False,checkMarginals=False,testPythonVisitor=True,testLpInterface=False):
    class PyCallback(object):
        def __init__(self):
            self.inBegin=False
            self.inEnd=False
            self.inVisit=False
        def begin(self,inference):
            self.inBegin=True
        def end(self,inference):
            self.inEnd=True
        def visit(self,inference):
            self.inVisit=True

    for operator, accumulator in semiRings:
        for gmGen in gms:
            gm = gmGen[operator]
            for param in params:

                # start inference
                solver  = solverClass(gm=gm, accumulator=accumulator, parameter=param)
                solver2 = solverClass(gm=gm, accumulator=accumulator, parameter=param)

                if (testLpInterface==True):

                    c=0
                    for vi in range(gm.numberOfVariables):
                        nl = gm.numberOfLabels(vi)
                        for l in range(nl):
                            assert c==solver.lpNodeVariableIndex(vi,l)
                            c+=1
                    cv=c
                    for fi in range(gm.numberOfFactors):
                        if gm[fi].numberOfVariables>1:
                            s = gm[fi].size
                            for l in range(nl):
                                assert solver.lpFactorVariableIndex(fi,s)>0 or cv==0
                            sw = opengm.shapeWalker(gm[fi].shape)

                            for c in sw:
                                assert solver.lpFactorVariableIndex(fi,c)>0 or cv==0

                    solver2.addConstraint(lpVariableIndices=[0,1],coefficients=[1,1],lowerBound=0.0,upperBound=1.0)
                    solver2.addConstraints(lpVariableIndices=[ [0,1],[0,2] ,[1,2]],coefficients=[ [1,1],[2,2],[1,2]],lowerBounds=[0,0,0],upperBounds=[1,1,1])



                solver.infer()
                arg = solver.arg()  # no used?
                value = solver.value()
                bound = solver.bound()

                if testPythonVisitor==True:
                    solver = solverClass(gm=gm, accumulator=accumulator, parameter=param)
                    callback=PyCallback()
                    pvisitor=solver.pythonVisitor(callback,1)
                    solver.infer(pvisitor)

                    assert callback.inBegin == True
                    assert callback.inEnd   == True

                if checkPartial :
                    pOptimal = solver.partialOptimality()

                    assert len(pOptimal)==gm.numberOfVariables
                    #assert len(numpy.where(pOptimal==True)[0]) == gm.numberOfVariables

                if checkMarginals :
                    visRange=numpy.arange(gm.numberOfVariables)
                    marginal = solver.marginals(visRange)
                    assert marginal.shape[0]==gm.numberOfVariables
                    assert marginal.shape[1]==gm.numberOfLabels(0)

                    fis1 = gm.factorSubset(order=1).factorIndices
                    fis2 = gm.factorSubset(order=2).factorIndices

                    assert len(fis1)!=0
                    assert len(fis2)!=0

                    factorMarginal1 = solver.factorMarginals(fis1)
                    assert factorMarginal1.ndim==2
                    assert factorMarginal1.shape[0]==len(fis1)
                    assert factorMarginal1.shape[1]==gm.numberOfLabels(0)

                    factorMarginal2 = solver.factorMarginals(fis2)
                    assert factorMarginal2.ndim==3
                    assert factorMarginal2.shape[0]==len(fis2)
                    assert factorMarginal2.shape[1]==gm.numberOfLabels(0)
                    assert factorMarginal2.shape[2]==gm.numberOfLabels(0)
示例#4
0
def genericSolverCheck(solverClass, params, gms, semiRings,checkPartial=False,checkMarginals=False,testPythonVisitor=True,testLpInterface=False):
    class PyCallback(object):
        def __init__(self):
            self.inBegin=False
            self.inEnd=False
            self.inVisit=False
        def begin(self,inference):
            self.inBegin=True
        def end(self,inference):
            self.inEnd=True
        def visit(self,inference):
            self.inVisit=True

    for operator, accumulator in semiRings:
        for gmGen in gms:
            gm = gmGen[operator]
            for param in params:

                # start inference
                solver  = solverClass(gm=gm, accumulator=accumulator, parameter=param)
                solver2 = solverClass(gm=gm, accumulator=accumulator, parameter=param)

                if (testLpInterface==True):

                    c=0
                    for vi in range(gm.numberOfVariables):
                        nl = gm.numberOfLabels(vi)
                        for l in range(nl):
                            assert c==solver.lpNodeVariableIndex(vi,l)
                            c+=1
                    cv=c
                    for fi in range(gm.numberOfFactors):
                        if gm[fi].numberOfVariables>1:
                            s = gm[fi].size
                            for l in range(nl):
                                assert solver.lpFactorVariableIndex(fi,s)>0 or cv==0
                            sw = opengm.shapeWalker(gm[fi].shape)

                            for c in sw:
                                assert solver.lpFactorVariableIndex(fi,c)>0 or cv==0

                    solver2.addConstraint(lpVariableIndices=[0,1],coefficients=[1,1],lowerBound=0.0,upperBound=1.0)
                    solver2.addConstraints(lpVariableIndices=[ [0,1],[0,2] ,[1,2]],coefficients=[ [1,1],[2,2],[1,2]],lowerBounds=[0,0,0],upperBounds=[1,1,1])



                solver.infer()
                arg = solver.arg()  # no used?
                value = solver.value()
                bound = solver.bound()

                if testPythonVisitor==True:
                    solver = solverClass(gm=gm, accumulator=accumulator, parameter=param)
                    callback=PyCallback()
                    pvisitor=solver.pythonVisitor(callback,1)
                    solver.infer(pvisitor)

                    assert callback.inBegin == True
                    assert callback.inEnd   == True

                if checkPartial :
                    pOptimal = solver.partialOptimality()

                    assert len(pOptimal)==gm.numberOfVariables
                    #assert len(numpy.where(pOptimal==True)[0]) == gm.numberOfVariables

                if checkMarginals :
                    visRange=numpy.arange(gm.numberOfVariables)
                    marginal = solver.marginals(visRange)
                    assert marginal.shape[0]==gm.numberOfVariables
                    assert marginal.shape[1]==gm.numberOfLabels(0)

                    fis1 = gm.factorSubset(order=1).factorIndices
                    fis2 = gm.factorSubset(order=2).factorIndices

                    assert len(fis1)!=0
                    assert len(fis2)!=0

                    factorMarginal1 = solver.factorMarginals(fis1)
                    assert factorMarginal1.ndim==2
                    assert factorMarginal1.shape[0]==len(fis1)
                    assert factorMarginal1.shape[1]==gm.numberOfLabels(0)

                    factorMarginal2 = solver.factorMarginals(fis2)
                    assert factorMarginal2.ndim==3
                    assert factorMarginal2.shape[0]==len(fis2)
                    assert factorMarginal2.shape[1]==gm.numberOfLabels(0)
                    assert factorMarginal2.shape[2]==gm.numberOfLabels(0)
import opengm
import numpy

# some graphical model
# -with 3 variables with 4 labels.
# -with 2 random 2-order functions
# -connected to 2 factors
gm = opengm.gm([4] * 3)
f = numpy.random.rand(4, 4).astype(numpy.float32)
gm.addFactor(gm.addFunction(f), [0, 1])
f = numpy.random.rand(4, 4).astype(numpy.float32)
gm.addFactor(gm.addFunction(f), [1, 2])

# iterate over all factors of the graphical model
for factor in gm.factors():
    # iterate over all labelings with a "shape walker"
    for coord in opengm.shapeWalker(f.shape):
        print " f[", coord, "]=", factor[coord]
def myFunc( labels):
    p=1.0
    s=0
    for l in labels:
        p*=l
        s+=l
    return p+s


pf=opengm.PythonFunction(myFunc,[2,2])

print pf.shape
print pf[0,0]
print pf[1,1]
for c in opengm.shapeWalker(pf.shape):
    print c," ",pf[c]



unaries=numpy.random.rand(5 , 5,2)
potts=opengm.PottsFunction([2,2],0.0,0.1)
gm=opengm.grid2d2Order(unaries=unaries,regularizer=potts)


viewFunction=opengm.modelViewFunction(gm[0])
for c in opengm.shapeWalker(viewFunction.shape):
    print c," ",viewFunction[c]

viewFunction=opengm.modelViewFunction(gm[25])
print viewFunction.shape