def test_broadcast():
a = np.array([[1, 2, 0, 0], [0, 3, 0, 0], [4, 5, 6, 0], [8, 0, 9, 0]])
b = np.broadcast_to(a, (3, 4, 4))
x = BCOO.from_numpy(a, block_shape=(2, 2))
y = x.broadcast_to((3, 4, 4), (3, 2, 2))
assert_eq(b, y)
a = np.random.random((6, 5, 1, 4, 1))
a[a > 0.3] = 0.0
b = np.broadcast_to(a, (4, 6, 5, 3, 4, 4))
x = BCOO.from_numpy(a, block_shape=(3, 5, 1, 2, 1))
y = x.broadcast_to((4, 6, 5, 3, 4, 4), (2, 3, 5, 3, 2, 1))
assert_eq(b, y)
def test_from_numpy():
#a = np.random.random((6,5,4,1))
#a = np.zeros((6,5,4,1))
a = np.array([[1, 2, 0, 0], [0, 3, 0, 0], [4, 5, 6, 0], [8, 0, 9, 0]])
#x = BCOO.from_numpy(a, block_shape = (2,5,2,1))
x = BCOO.from_numpy(a, block_shape=(2, 2))
assert_eq(a, x)
def test_to_coo():
a = np.random.random((6, 5, 4, 1))
a[a > 0.3] = 0.0
#a = np.zeros((6,5,4,1))
x = BCOO.from_numpy(a, block_shape=(2, 5, 2, 1))
from sparse import COO
y = COO.from_numpy(a)
z = x.to_coo()
assert_eq(y, z)
def test_transpose(axes):
#x = sparse.brandom((2, 3, 4), ,density=.25)
#x = sparse.brandom((4, 6, 8), (2, 3, 4), 0.5, format='bcoo')
#x = sparse.brandom((4, 4), (2, 2), 1.0, format='bcoo')
a = np.array([[1, -1, 0, 0], [1, -1, 0, 0], [2, 3, 6, 7], [4, 5, 8, 9]])
x = BCOO.from_numpy(a, block_shape=(2, 2))
y = x.todense()
xx = x.transpose(axes)
yy = y.transpose(axes)
assert_eq(xx, yy)
def test_add_zero():
# the result is zero
data_x = np.arange(3, 6).repeat(4).reshape(3, 2, 2).astype(np.double)
coords_x = np.array([[1, 1, 0], [0, 1, 1]])
x = BCOO(coords_x, data=data_x, shape=(4, 4), block_shape=(2, 2))
x_d = x.todense()
y = -x
y_d = y.todense()
z = x + y
z_d = x_d + y_d
assert_eq(z, z_d)
# all add numbers are zero
a = np.zeros((6, 5, 4, 1), dtype=np.complex)
x = BCOO.from_numpy(a, block_shape=(2, 5, 2, 1))
x_d = x.todense()
y = BCOO.from_numpy(a, block_shape=(2, 5, 2, 1))
y_d = y.todense()
z = x + y
z_d = x_d + y_d
assert_eq(z, z_d)
def test_block_reshape():
a = np.array([[1, -1, 0, 0], [1, -1, 0, 0], [2, 3, 6, 7], [4, 5, 8, 9]])
x = BCOO.from_numpy(a, block_shape=(2, 2))
y = x.todense()
outer_shape_new = (1, 4)
block_shape_new = (2, 2) # unchanged
z = x.block_reshape(outer_shape_new, block_shape_new)
print("original matrix (2,2)")
print(y)
print("block reshaped matrix (1,4)")
print(z.todense())
def test_sizeof():
import sys
x = np.eye(100)
y = BCOO.from_numpy(x, block_shape=(5, 5))
nb = sys.getsizeof(y)
assert 400 < nb < x.nbytes / 10
def test_from_numpy():
#a = np.random.random((6,5,4,1))
a = np.zeros((6, 5, 4, 1))
x = BCOO.from_numpy(a, block_shape=(2, 5, 2, 1))
assert_eq(a, x)
