def test_diag(nps_app_inst):
import nums.numpy as nps
assert nps_app_inst is not None
ba: BlockArray = nps.array([1.0, 2.0, 3.0])
np_arr = ba.get()
# Make a diag matrix.
ba = nps.diag(ba)
np_arr = np.diag(np_arr)
assert np.allclose(ba.get(), np_arr)
# Take diag of diag matrix.
ba = nps.diag(ba)
np_arr = np.diag(np_arr)
assert np.allclose(ba.get(), np_arr)
# Tests all combinations of sizes and block sizes in the range 1 to 4
for i in range(1, 4):
for j in range(1, 4):
for k in range(1, i + 1):
for l in range(1, j + 1):
ba: BlockArray = nps.array(np.full((i, j), 1))
ba = ba.reshape(block_shape=(k, l))
np_arr = ba.get()
ba = nps.diag(ba)
np_arr = np.diag(np_arr)
assert np.allclose(ba.get(), np_arr)
def test_trace(nps_app_inst):
import nums.numpy as nps
assert nps_app_inst is not None
a: BlockArray = nps.array([1.0, 2.0, 3.0, 4.0])
# Construct diagonal matrix with nums and numpy.
a_diag = nps.diag(a)
a_diag_np = np.diag(a.get())
# Apply trace to diagonal matrices.
a_diag_trace = nps.trace(a_diag).get()
a_diag_np_trace = np.trace(a_diag_np)
assert np.allclose(a_diag_trace, a_diag_np_trace)
# Test pre-defined diagonal matrices.
b: BlockArray = nps.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]])
b_diag_trace = nps.trace(b).get()
b_diag_np_trace = np.trace(b.get())
assert np.allclose(b_diag_trace, b_diag_np_trace)
# Test that trace raises on arrays with 3+ axes.
mat: BlockArray = nps.zeros((2, 3, 2))
with pytest.raises(ValueError):
nps.trace(mat)
# Test that trace raises when called with non-zero offset.
mat: BlockArray = nps.array([1.0, 2.0, 3.0, 4.0])
mat_diag = nps.diag(mat)
with pytest.raises(NotImplementedError):
nps.trace(mat_diag, offset=2)
# Test data type of trace.
mat_diag = nps.diag(nps.array([1.01, 2.02, 3.03, 4.04]))
mat_diag_np = np.diag(np.array([1.01, 2.02, 3.03, 4.04]))
mat_diag_trace = nps.trace(mat_diag, dtype=int).get()
mat_diag_np_trace = np.trace(mat_diag_np, dtype=int)
assert np.allclose(mat_diag_trace, mat_diag_np_trace)
assert mat_diag_trace.dtype == int
# Test trace on non-square matrices
ba: BlockArray = nps.array(np.full((10, 12), 1))
ba = ba.reshape(block_shape=(3, 4))
np_arr = ba.get()
ba = nps.trace(ba)
np_arr = np.trace(np_arr)
assert np.allclose(ba.get(), np_arr)
def test_diag(nps_app_inst):
import nums.numpy as nps
assert nps_app_inst is not None
ba: BlockArray = nps.array([1.0, 2.0, 3.0])
np_arr = ba.get()
# Make a diag matrix.
ba = nps.diag(ba)
np_arr = np.diag(np_arr)
assert np.allclose(ba.get(), np_arr)
# Take diag of diag matrix.
ba = nps.diag(ba)
np_arr = np.diag(np_arr)
assert np.allclose(ba.get(), np_arr)