def test_nnz_sparsity(sqlmatrix, r, c, nset):
M = matrix.SqlMatrix(r, c)
pos = [(i, j) for i in range(r) for j in range(c)][:nset]
for i, j in pos:
M.set(i, j, i * j - i + j + 0.5)
assert M.nnz == len(pos)
assert M.sparsity == 1.0 - len(pos) / (r * c)
Ilist, Jlist = M.nonzero()
assert set(zip(Ilist, Jlist)) == set(pos)
M.destroy()
def test_scale(sqlmatrix, random, r, c, scalar):
A = numpy.matrix(numpy.random.normal(size=(r, c)))
A2 = matrix.SqlMatrix.from_dense(A)
RES = matrix.SqlMatrix(r, c)
resptr = A2.scale(scalar, RES)
assert _is_close(A * scalar, RES.to_dense()) #The result is correct
assert _is_close(A, A2.to_dense()) #The input is unchanged
assert resptr._table == RES._table #The returned matrix is correct
A2.destroy()
RES.destroy()
def test_pow(sqlmatrix, random, n, exp):
A = 10.0 * numpy.matrix(numpy.random.normal(size=(n, n)))
A2 = matrix.SqlMatrix.from_dense(A)
R = matrix.SqlMatrix(n, n)
resptr = A2.pow(exp, R)
assert _is_close(A**exp, R.to_dense()) #The result is correct
assert _is_close(A, A2.to_dense()) #The input is unchanged
assert resptr._table == R._table #The returned matrix is correct
A2.destroy()
R.destroy()
def test_matmul_square(sqlmatrix, random, n):
A = 10.0 * numpy.matrix(numpy.random.normal(size=(n, n)))
B = matrix.SqlMatrix.from_dense(A)
C = matrix.SqlMatrix(n, n)
resptr = B.matmul(B, C)
assert _is_close(A**2, C.to_dense()) #The result is correct
assert _is_close(A, B.to_dense()) #The input is unchanged
assert resptr._table == C._table #The returned matrix is correct
B.destroy()
C.destroy()
def test_hadamard_product(sqlmatrix, random, r, c):
left = 10.0 * numpy.matrix(numpy.random.normal(size=(r, c)))
right = 10.0 * numpy.matrix(numpy.random.normal(size=(r, c)))
sqlleft = matrix.SqlMatrix.from_dense(left)
sqlright = matrix.SqlMatrix.from_dense(right)
sqlresult = matrix.SqlMatrix(r, c)
resptr = sqlleft.hadamard_product(sqlright, sqlresult)
assert _is_close(numpy.multiply(left, right),
sqlresult.to_dense()) #The result is correct
assert _is_close(left, sqlleft.to_dense()) #The input is unchanged
assert _is_close(right, sqlright.to_dense()) #The input is unchanged
assert resptr._table == sqlresult._table #The returned matrix is correct
sqlleft.destroy()
sqlright.destroy()
sqlresult.destroy()
def test_get_set(sqlmatrix, random, n):
M = matrix.SqlMatrix(n, n)
for i, j in [(0.5, 0), (0, 0.5), (0.5, 0.5), (-12.2, 18.9)]:
with pytest.raises(TypeError):
M.get(i, j)
with pytest.raises(TypeError):
M.set(i, j, 3.14)
for i, j in [(-1, 0), (n, 0), (0, -1), (0, n), (-1, -1), (-1, n), (n, -1),
(n, n)]:
with pytest.raises(IndexError):
M.get(i, j)
with pytest.raises(IndexError):
M.set(i, j, 3.14)
for i, j in zip(numpy.random.randint(n, size=n),
numpy.random.randint(n, size=n)):
v = numpy.random.normal()
M.set(i, j, v)
assert M.get(i, j) == v
M.destroy()