def setUp(self):
self.c1 = mls.COONDArray(indices=np.asarray([(9, 5, 4), (7, 6, 5),
(2, 2, 4), (7, 9, 4),
(2, 2, 6)]),
data=np.asarray([3, 4, 5, 3, 1]),
shape=np.asarray([10, 11, 12]))
self.c2 = mls.COONDArray(indices=np.asarray([(9, 5, 4), (2, 2, 4),
(7, 9, 4), (2, 2, 6),
(8, 4, 9)]),
data=np.asarray([3, 5, 3, 1, 2]),
shape=np.asarray([10, 11, 12]))
self.c3 = mls.COONDArray(indices=np.asarray(
[tuple(i - 1 for i in list(ind)) for ind in self.c1.indices]),
data=np.asarray(self.c1.data),
shape=np.asarray(self.c1.shape))
# self.s1 = sps.coo_matrix()
# create dense numpy arrays with a similar shape and all zero values
self.d1 = np.zeros(shape=self.c1.shape)
self.d2 = np.zeros(shape=self.c2.shape)
self.d3 = np.zeros(shape=self.c3.shape)
# assign nnz val to the dense numpy array of each instance.
# d stands for dense
for i in range(len(self.c1.indices)):
self.d1[tuple(self.c1.indices[i])] = self.c1.data[i]
for i in range(len(self.c2.indices)):
self.d2[tuple(self.c2.indices[i])] = self.c2.data[i]
for i in range(len(self.c3.indices)):
self.d3[tuple(self.c3.indices[i])] = self.c3.data[i]
def testCooCreation(self):
# self.assert(mls.issparse(self.c1))
# type assertion only. REQUIRE: parameter assertion as well
s = mls.COONDArray(self.c1)
assert (isinstance(s, mls.COONDArray))
assert (isinstance(s, mls.SparseNDArray))
assert (mls.issparse(s))
assert (s.issparse())