def test_init_diagonal():
subs, vals, shape = setup_diagonal()
T = sptensor(subs, vals, shape)
assert_equal(len(shape), T.ndim)
assert_true((array(shape) == T.shape).all())
T = sptensor(subs, vals)
assert_equal(len(subs), len(T.shape))
assert_true((shape == array(T.shape)).all())
def test_init_diagonal():
subs, vals, shape = setup_diagonal()
T = sptensor(subs, vals, shape)
assert_equal(len(shape), T.ndim)
assert_true((array(shape) == T.shape).all())
T = sptensor(subs, vals)
assert_equal(len(subs), len(T.shape))
assert_true((shape == array(T.shape)).all())
def test_init_diagonal():
subs, vals, shape = setup_diagonal()
T = sptensor(subs, vals, shape)
assert len(shape) == T.ndim
assert (array(shape) == T.shape).all()
T = sptensor(subs, vals)
assert len(subs) == len(T.shape)
assert (shape == array(T.shape)).all()
def test_init_diagonal():
subs, vals, shape = setup_diagonal()
T = sptensor(subs, vals, shape)
assert len(shape) == T.ndim
assert (array(shape) == T.shape).all()
T = sptensor(subs, vals)
assert len(subs) == len(T.shape)
assert (shape == array(T.shape)).all()
def test_init():
"""
Creation of new sptensor objects
"""
T = sptensor(subs, vals, shape)
assert_equal(len(shape), T.ndim)
assert_true((array(shape) == T.shape).all())
T = sptensor(subs, vals)
tshape = array(subs).max(axis=1) + 1
assert_equal(len(subs), len(T.shape))
assert_true((tshape == array(T.shape)).all())
def test_init():
"""
Creation of new sptensor objects
"""
T = sptensor(subs, vals, shape)
assert_equal(len(shape), T.ndim)
assert_true((array(shape) == T.shape).all())
T = sptensor(subs, vals)
tshape = array(subs).max(axis=1) + 1
assert_equal(len(subs), len(T.shape))
assert_true((tshape == array(T.shape)).all())
def test_init(subs, vals, shape):
"""
Creation of new sptensor objects
"""
T = sptensor(subs, vals, shape)
assert len(shape) == T.ndim
assert (array(shape) == T.shape).all()
T = sptensor(subs, vals)
tshape = array(subs).max(axis=1) + 1
assert len(subs) == len(T.shape)
assert (tshape == array(T.shape)).all()
def test_init(subs, vals, shape):
"""
Creation of new sptensor objects
"""
T = sptensor(subs, vals, shape)
assert len(shape) == T.ndim
assert (array(shape) == T.shape).all()
T = sptensor(subs, vals)
tshape = array(subs).max(axis=1) + 1
assert len(subs) == len(T.shape)
assert (tshape == array(T.shape)).all()
def test_sp_uttkrp():
# Test case by Andre Panisson, sparse ttv
# see issue #3
S = sptensor(subs, vals, shape)
U = []
for shp in shape:
U.append(np.zeros((shp, 5)))
SU = S.uttkrp(U, mode=0)
assert_equal(SU.shape, (25, 5))
def test_sp_uttkrp():
# Test case by Andre Panisson, sparse ttv
# see issue #3
S = sptensor(subs, vals, shape)
U = []
for shp in shape:
U.append(np.zeros((shp, 5)))
SU = S.uttkrp(U, mode=0)
assert_equal(SU.shape, (25, 5))
def test_add():
subs = (array([0, 1, 0]), array([2, 0, 2]), array([0, 1, 2]))
vals = array([1, 2, 3])
S = sptensor(subs, vals, shape=[3, 3, 3])
D = np.arange(27).reshape(3, 3, 3)
T = S - D
for i in range(3):
for j in range(3):
for k in range(3):
assert_equal(S[i, j, k] - D[i, j, k], T[i, j, k])
def test_add():
subs = (array([0, 1, 0]), array([2, 0, 2]), array([0, 1, 2]))
vals = array([1, 2, 3])
S = sptensor(subs, vals, shape=[3, 3, 3])
D = np.arange(27).reshape(3, 3, 3)
T = S - D
for i in range(3):
for j in range(3):
for k in range(3):
assert_equal(S[i, j, k] - D[i, j, k], T[i, j, k])
def test_getitem():
subs = (
array([0, 1, 0, 5, 7, 8]),
array([2, 0, 4, 5, 3, 9]),
array([0, 1, 2, 2, 1, 0])
)
vals = array([1, 2, 3, 4, 5, 6])
S = sptensor(subs, vals, shape=[10, 10, 3])
assert_equal(0, S[1, 1, 1])
assert_equal(0, S[1, 2, 3])
for i in range(len(vals)):
assert_equal(vals[i], S[subs[0][i], subs[1][i], subs[2][i]])
def test_fold(subs, vals, shape):
T = sptensor(subs, vals, shape)
for i in range(len(shape)):
X = T.unfold([i]).fold()
assert shape == tuple(T.shape)
assert len(shape) == len(T.subs)
assert len(subs) == len(T.subs)
assert X == T
for j in range(len(subs)):
subs[j].sort()
T.subs[j].sort()
assert (subs[j] == T.subs[j]).all()
def test_getitem():
subs = (array([0, 1, 0, 5, 7, 8]), array([2, 0, 4, 5, 3, 9]), array([0, 1, 2, 2, 1, 0]))
vals = array([1, 2, 3, 4, 5, 6])
S = sptensor(subs, vals, shape=[10, 10, 3])
assert_equal(0, S[1, 1, 1])
assert_equal(0, S[1, 2, 3])
assert_equal(1, S[0, 2, 0])
assert_equal(2, S[1, 0, 1])
assert_equal(3, S[0, 4, 2])
assert_equal(4, S[5, 5, 2])
assert_equal(5, S[7, 3, 1])
assert_equal(6, S[8, 9, 0])
def test_ttv_sparse_result():
# Test case by Andre Panisson to check return type of sptensor.ttv
subs = (array([0, 1, 0, 5, 7, 8]), array([2, 0, 4, 5, 3, 9]), array([0, 1, 2, 2, 1, 0]))
vals = array([1, 1, 1, 1, 1, 1])
S = sptensor(subs, vals, shape=[10, 10, 3])
sttv = S.ttv((zeros(10), zeros(10)), modes=[0, 1])
assert_equal(type(sttv), sptensor)
# sparse tensor should return only nonzero vals
assert_true((allclose(np.array([]), sttv.vals)))
assert_true((allclose(np.array([]), sttv.subs)))
assert_equal(sttv.shape, (3,))
def test_fold():
T = sptensor(subs, vals, shape)
for i in range(len(shape)):
X = T.unfold([i]).fold()
assert_equal(shape, tuple(T.shape))
assert_equal(len(shape), len(T.subs))
assert_equal(len(subs), len(T.subs))
assert_equal(X, T)
for j in range(len(subs)):
subs[j].sort()
T.subs[j].sort()
assert_true((subs[j] == T.subs[j]).all())
def test_fold():
T = sptensor(subs, vals, shape)
for i in range(len(shape)):
X = T.unfold([i]).fold()
assert_equal(shape, tuple(T.shape))
assert_equal(len(shape), len(T.subs))
assert_equal(len(subs), len(T.subs))
assert_equal(X, T)
for j in range(len(subs)):
subs[j].sort()
T.subs[j].sort()
assert_true((subs[j] == T.subs[j]).all())
def test_fold(subs, vals, shape):
T = sptensor(subs, vals, shape)
for i in range(len(shape)):
X = T.unfold([i]).fold()
assert shape == tuple(T.shape)
assert len(shape) == len(T.subs)
assert len(subs) == len(T.subs)
assert X == T
for j in range(len(subs)):
subs[j].sort()
T.subs[j].sort()
assert (subs[j] == T.subs[j]).all()
def test_getitem():
subs = (array([0, 1, 0, 5, 7, 8]), array([2, 0, 4, 5, 3,
9]), array([0, 1, 2, 2, 1, 0]))
vals = array([1, 2, 3, 4, 5, 6])
S = sptensor(subs, vals, shape=[10, 10, 3])
assert_equal(0, S[1, 1, 1])
assert_equal(0, S[1, 2, 3])
assert_equal(1, S[0, 2, 0])
assert_equal(2, S[1, 0, 1])
assert_equal(3, S[0, 4, 2])
assert_equal(4, S[5, 5, 2])
assert_equal(5, S[7, 3, 1])
assert_equal(6, S[8, 9, 0])
def test_getitem():
subs = (array([0, 1, 0, 5, 7, 8]), array([2, 0, 4, 5, 3,
9]), array([0, 1, 2, 2, 1, 0]))
vals = array([1, 2, 3, 4, 5, 6])
S = sptensor(subs, vals, shape=[10, 10, 3])
assert 0 == S[1, 1, 1]
assert 0 == S[1, 2, 3]
assert 1 == S[0, 2, 0]
assert 2 == S[1, 0, 1]
assert 3 == S[0, 4, 2]
assert 4 == S[5, 5, 2]
assert 5 == S[7, 3, 1]
assert 6 == S[8, 9, 0]
def test_ttv_sparse_result():
# Test case by Andre Panisson to check return type of sptensor.ttv
subs = (array([0, 1, 0, 5, 7, 8]), array([2, 0, 4, 5, 3,
9]), array([0, 1, 2, 2, 1, 0]))
vals = array([1, 1, 1, 1, 1, 1])
S = sptensor(subs, vals, shape=[10, 10, 3])
sttv = S.ttv((zeros(10), zeros(10)), modes=[0, 1])
assert_equal(type(sttv), sptensor)
# sparse tensor should return only nonzero vals
assert_true((allclose(np.array([]), sttv.vals)))
assert_true((allclose(np.array([]), sttv.subs)))
assert_equal(sttv.shape, (3, ))
def test_ttv():
# Test case by Andre Panisson to check return type of sptensor.ttv
subs = (
array([0, 1, 0, 5, 7, 8]),
array([2, 0, 4, 5, 3, 9]),
array([0, 1, 2, 2, 1, 0])
)
vals = array([1, 1, 1, 1, 1, 1])
S = sptensor(subs, vals, shape=[10, 10, 3])
sttv = S.ttv((zeros(10), zeros(10)), modes=[0, 1])
assert_equal(type(sttv), sptensor)
assert_true((allclose(zeros(3), sttv.vals)))
assert_true((allclose(np.arange(3), sttv.subs)))
def test_getitem():
subs = (
array([0, 1, 0, 5, 7, 8]),
array([2, 0, 4, 5, 3, 9]),
array([0, 1, 2, 2, 1, 0])
)
vals = array([1, 2, 3, 4, 5, 6])
S = sptensor(subs, vals, shape=[10, 10, 3])
assert 0 == S[1, 1, 1]
assert 0 == S[1, 2, 3]
assert 1 == S[0, 2, 0]
assert 2 == S[1, 0, 1]
assert 3 == S[0, 4, 2]
assert 4 == S[5, 5, 2]
assert 5 == S[7, 3, 1]
assert 6 == S[8, 9, 0]
def test_unfold():
Td = dtensor(zeros(shape, dtype=np.float32))
Td[subs] = vals
for i in range(len(shape)):
rdims = [i]
cdims = setdiff1d(range(len(shape)), rdims)[::-1]
Md = Td.unfold(i)
T = sptensor(subs, vals, shape, accumfun=lambda l: l[-1])
Ms = T.unfold(rdims, cdims)
assert_equal(Md.shape, Ms.shape)
assert_true((allclose(Md, Ms.toarray())))
Ms = T.unfold(rdims)
assert_equal(Md.shape, Ms.shape)
assert_true((allclose(Md, Ms.toarray())))
Md = Md.T
Ms = T.unfold(rdims, cdims, transp=True)
assert_equal(Md.shape, Ms.shape)
assert_true((allclose(Md, Ms.toarray())))
def test_unfold():
Td = dtensor(zeros(shape, dtype=np.float32))
Td[subs] = vals
for i in range(len(shape)):
rdims = [i]
cdims = setdiff1d(range(len(shape)), rdims)[::-1]
Md = Td.unfold(i)
T = sptensor(subs, vals, shape, accumfun=lambda l: l[-1])
Ms = T.unfold(rdims, cdims)
assert_equal(Md.shape, Ms.shape)
assert_true((allclose(Md, Ms.toarray())))
Ms = T.unfold(rdims)
assert_equal(Md.shape, Ms.shape)
assert_true((allclose(Md, Ms.toarray())))
Md = Md.T
Ms = T.unfold(rdims, cdims, transp=True)
assert_equal(Md.shape, Ms.shape)
assert_true((allclose(Md, Ms.toarray())))
def dataframeToTensor(dataset,
dimensions_col=['user', 'item', 'action'],
rating_col='rating',
keepZero=False):
dims = dict.fromkeys(dimensions_col)
shape = []
for col in dimensions_col:
dims[col] = max(dataset[col]) + 1
shape.append(dims[col])
if not (keepZero):
dataset = dataset.loc[dataset[rating_col] != 0]
subs = []
for col in dimensions_col:
subs.append(list(dataset[col]))
tensor = sptensor(tuple(subs),
dataset[rating_col].values,
shape=tuple(shape),
dtype=np.float)
return tensor
def test_non2Dsubs():
sptensor(randint(0, 10, 18).reshape(3, 3, 2), ones(10))
def test_non2Dsubs():
with pytest.raises(ValueError):
sptensor(randint(0, 10, 18).reshape(3, 3, 2), ones(10))
def test_nonEqualLength(subs):
with pytest.raises(ValueError):
sptensor(subs, ones(len(subs) + 1))
def test_ttm(T, Y, U):
S = sptensor(T.nonzero(), T.flatten(), T.shape)
Y2 = S.ttm(U, 0)
assert (2, 4, 2) == Y2.shape
assert (Y == Y2).all()
def test_nonEqualLength():
subs, vals, shape = mysetup()
sptensor(subs, ones(len(subs) + 1))
def test_ttm():
S = sptensor(T.nonzero(), T.flatten(), T.shape)
Y2 = S.ttm(U, 0)
assert_equal((2, 4, 2), Y2.shape)
assert_true((Y == Y2).all())
def test_sttm_me():
S = sptensor(T.nonzero(), T.flatten(), T.shape)
S.ttm_me(U, [1], [0], False)
def test_ttm(T, Y, U):
S = sptensor(T.nonzero(), T.flatten(), T.shape)
Y2 = S.ttm(U, 0)
assert (2, 4, 2) == Y2.shape
assert (Y == Y2).all()
def test_non2Dsubs():
sptensor(randint(0, 10, 18).reshape(3, 3, 2), ones(10))
def test_nonEqualLength(subs):
with pytest.raises(ValueError):
sptensor(subs, ones(len(subs) + 1))
def test_non2Dsubs():
with pytest.raises(ValueError):
sptensor(randint(0, 10, 18).reshape(3, 3, 2), ones(10))
def test_nonEqualLength():
sptensor(subs, ones(len(subs) + 1))
def test_nonEqualLength():
sptensor(subs, ones(len(subs) + 1))
def test_sttm_me():
S = sptensor(T.nonzero(), T.flatten(), T.shape)
S.ttm_me(U, [1], [0], False)
def test_sttm_me(T, U):
S = sptensor(T.nonzero(), T.flatten(), T.shape)
S._ttm_me_compute(U, [1], [0], False)
def test_ttm():
S = sptensor(T.nonzero(), T.flatten(), T.shape)
Y2 = S.ttm(U, 0)
assert_equal((2, 4, 2), Y2.shape)
assert_true((Y == Y2).all())
def test_sttm_me(T, U):
S = sptensor(T.nonzero(), T.flatten(), T.shape)
S._ttm_me_compute(U, [1], [0], False)
