def get_subgraph_nedges(self, rows, cols):
"""
Pulls out an arbitrary i.e. non-contiguous submatrix out of
a sparse.coo_matrix.
Returns
------
tuples of org_row_id, org_col_id, value
"""
matr = self.sm.tocoo()
gr = -1 * st.ones(matr.shape[0], dtype=int)
gc = -1 * st.ones(matr.shape[1], dtype=int)
lr = len(rows)
lc = len(cols)
ar = st.arange(0, lr, 1)
ac = st.arange(0, lc, 1)
gr[rows[ar]] = ar
gc[cols[ac]] = ac
mrow = matr.row
mcol = matr.col
newelem = (gr[mrow] > -1) & (gc[mcol] > -1)
subvalues = matr.data[newelem]
if self.weighted:
nedges = len(subvalues)
else:
nedges = subvalues.sum()
return nedges
def test_arange_shape(self):
# Arange with no parameters.
Assert.raises_exception(ValueError, spartan.arange)
# Arange with shape and stop
# Assert.raises_exception(ValueError, spartan.arange, (0, ), stop=0)
# Arange with shape
Assert.all_eq(spartan.arange((10,)).glom(), np.arange(10))
Assert.all_eq(spartan.arange((3, 5)).glom(), np.arange(15).reshape((3, 5)))
# Arange with shape, start
Assert.all_eq(spartan.arange((10,), -1).glom(), np.arange(-1, 9))
Assert.all_eq(spartan.arange((10,), 1).glom(), np.arange(1, 11))
Assert.all_eq(spartan.arange((3, 5), -1).glom(), np.arange(-1, 14).reshape((3, 5)))
# Arange with shape, step
Assert.all_eq(spartan.arange((10,), step=2).glom(), np.arange(0, 20, 2))
Assert.all_eq(spartan.arange((3, 5), step=2).glom(), np.arange(0, 30, 2).reshape((3, 5)))
# Arange with shape, start, step
Assert.all_eq(spartan.arange((10,), -1, step=2).glom(), np.arange(-1, 19, 2))
Assert.all_eq(spartan.arange((10,), 1, step=2).glom(), np.arange(1, 21, 2))
Assert.all_eq(spartan.arange((3, 5), 1, step=2).glom(), np.arange(1, 31, 2).reshape((3, 5)))
def get_sub_graph(self, rows, cols):
cootensor = self.graph_tensor
gr = -1 * st.ones(cootensor.shape[0], dtype=int)
gc = -1 * st.ones(cootensor.shape[1], dtype=int)
lr = len(rows)
lc = len(cols)
ar = st.arange(0, lr, 1)
ac = st.arange(0, lc, 1)
gr[rows[ar]] = ar
gc[cols[ac]] = ac
mrow = cootensor.coords[0]
mcol = cootensor.coords[1]
newelem = (gr[mrow] > -1) & (gc[mcol] > -1)
newrows = mrow[newelem]
newcols = mcol[newelem]
subcoords = st.stack(
(gr[newrows], gc[newcols], *cootensor.coords[2:, newelem]), axis=0)
subvalues = cootensor.data[newelem]
subtensor = st.STensor((subcoords, subvalues),
shape=(lr, lc, *cootensor.shape[2:]))
return st.Graph(subtensor, self.weighted, self.bipartite, self.modet)
def test_arange_stop(self):
# Arange with stop.
Assert.all_eq(spartan.arange(stop=10).glom(), np.arange(10))
# Arange with start, stop
Assert.all_eq(spartan.arange(None, -1, 10).glom(), np.arange(-1, 10))
Assert.all_eq(spartan.arange(None, 1, 10).glom(), np.arange(1, 10))
# Arange with start, stop, step
Assert.all_eq(spartan.arange(None, -1, 19, 2).glom(), np.arange(-1, 19, 2))
Assert.all_eq(spartan.arange(None, 1, 21, 2).glom(), np.arange(1, 21, 2))
def test_arange_stop(self):
# Arange with stop.
Assert.all_eq(spartan.arange(stop=10).glom(), np.arange(10))
# Arange with start, stop
Assert.all_eq(spartan.arange(-1, 10).glom(), np.arange(-1, 10))
Assert.all_eq(spartan.arange(1, 10).glom(), np.arange(1, 10))
# Arange with start, stop, step
Assert.all_eq(spartan.arange(-1, 19, 2).glom(), np.arange(-1, 19, 2))
Assert.all_eq(spartan.arange(1, 21, 2).glom(), np.arange(1, 21, 2))
def test_distarray(self): A = spartan.arange(40000, dtype=np.int32).reshape(100, 400).evaluate() nA = np.arange(40000).reshape(100, 400) B = A.transpose().evaluate() nB = nA.transpose() C = B.T.evaluate() nC = nB.T D = (C / 100).evaluate() nD = nC / 100 E = D.all() nE = nD.all() Assert.all_eq(E.glom(), nE)
def test_distarray(self):
A = spartan.arange(40000, dtype=np.int32).reshape(100, 400).evaluate()
nA = np.arange(40000).reshape(100, 400)
B = A.transpose().evaluate()
nB = nA.transpose()
C = B.T.evaluate()
nC = nB.T
D = (C / 100).evaluate()
nD = nC / 100
E = D.all()
nE = nD.all()
Assert.all_eq(E.glom(), nE)
def test_logic(self):
# Arange with no parameters.
A = spartan.arange(40000, dtype=np.int32).reshape(100, 400)
nA = np.arange(40000).reshape(100, 400)
B = A.T
nB = nA.T
C = B / 1000
nC = nB / 1000
D = spartan.all(C)
nD = np.all(nC)
E = spartan.any(C)
nE = np.any(nC)
Assert.all_eq(D.glom(), nD)
Assert.all_eq(E.glom(), nE)
def test_logic(self): # Arange with no parameters. A = spartan.arange(40000, dtype=np.int32).reshape(100, 400) nA = np.arange(40000).reshape(100, 400) B = A.T nB = nA.T C = B / 1000 nC = nB / 1000 D = spartan.all(C) nD = np.all(nC) E = spartan.any(C) nE = np.any(nC) Assert.all_eq(D.glom(), nD) Assert.all_eq(E.glom(), nE)
def test_arange_shape(self):
# Arange with no parameters.
Assert.raises_exception(ValueError, spartan.arange)
# Arange with shape and stop
Assert.raises_exception(ValueError, spartan.arange, (0, ), stop=0)
# Arange with shape
Assert.all_eq(spartan.arange((10, )).glom(), np.arange(10))
Assert.all_eq(
spartan.arange((3, 5)).glom(),
np.arange(15).reshape((3, 5)))
# Arange with shape, start
Assert.all_eq(spartan.arange((10, ), -1).glom(), np.arange(-1, 9))
Assert.all_eq(spartan.arange((10, ), 1).glom(), np.arange(1, 11))
Assert.all_eq(
spartan.arange((3, 5), -1).glom(),
np.arange(-1, 14).reshape((3, 5)))
# Arange with shape, step
Assert.all_eq(
spartan.arange((10, ), step=2).glom(), np.arange(0, 20, 2))
Assert.all_eq(
spartan.arange((3, 5), step=2).glom(),
np.arange(0, 30, 2).reshape((3, 5)))
# Arange with shape, start, step
Assert.all_eq(
spartan.arange((10, ), -1, step=2).glom(), np.arange(-1, 19, 2))
Assert.all_eq(
spartan.arange((10, ), 1, step=2).glom(), np.arange(1, 21, 2))
Assert.all_eq(
spartan.arange((3, 5), 1, step=2).glom(),
np.arange(1, 31, 2).reshape((3, 5)))
def test_ravel(self):
x = spartan.arange((TEST_SIZE, TEST_SIZE))
n = np.arange(TEST_SIZE * TEST_SIZE).reshape((TEST_SIZE, TEST_SIZE))
Assert.all_eq(n.ravel(), x.ravel().glom())
def test_mathematics(self): A = spartan.arange(40000, dtype=np.int32).reshape(100, 400) nA = np.arange(40000).reshape(100, 400) B = A.prod() nB = nA.prod() Assert.all_eq(B.glom(), nB)
def test_mathematics(self):
A = spartan.arange(40000, dtype=np.int32).reshape(100, 400)
nA = np.arange(40000).reshape(100, 400)
B = A.prod()
nB = nA.prod()
Assert.all_eq(B.glom(), nB)
def test_ravel(self):
x = spartan.arange((TEST_SIZE, TEST_SIZE))
n = np.arange(TEST_SIZE * TEST_SIZE).reshape((TEST_SIZE, TEST_SIZE))
Assert.all_eq(n.ravel(), x.ravel().glom())
