def test_constructor(self):
functions = []
functions.append(opengm.SparseFunction([2, 3, 4], 1))
functions.append(opengm.SparseFunction((2, 3, 4), 1))
for f in functions:
assert(f.defaultValue == 1)
assert(f.dimension == 3)
assert(f.shape[0] == 2)
assert(f.shape[1] == 3)
assert(f.shape[2] == 4)
assert(len(f.shape) == 3)
assert(f.size == 2 * 3 * 4)
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
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
#---------------------------------------------------------------
# Numpy Ndarray
# (is stored in a different multi array function within opengm)
#---------------------------------------------------------------
f = numpy.random.rand(2, 2, 3, 4)
fid = gm.addFunction(f)
gm.addFactor(fid, [0, 1, 2, 4])
print "\nexplicit function: \n", f
#---------------------------------------------------------------
# Sparse Function
#---------------------------------------------------------------
# fill sparse function "by hand"
f = opengm.SparseFunction(shape=[3, 4, 4], defaultValue=1)
# fill diagonale with zeros
for d in xrange(4):
f[[d, d, d]] = 0
print "\nsparse function: \n", f
fid = gm.addFunction(f)
functionIds.append(fid)
gm.addFactor(fid, [3, 4, 5])
# fill sparse function from dense function
f = opengm.SparseFunction()
f.assignDense(numpy.identity(4), defaultValue=0)
fid = gm.addFunction(f)
functionIds.append(fid)
gm.addFactor(fid, [4, 5])
print "\nsparse function: \n", f