def test_diff():
md = MutableDenseNDimArray([[x, y], [x*z, x*y*z]])
assert md.diff(x) == MutableDenseNDimArray([[1, 0], [z, y*z]])
sd = MutableSparseNDimArray(md)
assert sd == MutableSparseNDimArray([x, y, x*z, x*y*z], (2, 2))
assert sd.diff(x) == MutableSparseNDimArray([[1, 0], [z, y*z]])
def test_ndim_array_converting():
dense_array = MutableDenseNDimArray([1, 2, 3, 4], (2, 2))
alist = dense_array.tolist()
assert alist == [[1, 2], [3, 4]]
matrix = dense_array.tomatrix()
assert isinstance(matrix, Matrix)
for i, ai in enumerate(dense_array):
assert ai == matrix[i]
assert matrix.shape == dense_array.shape
assert MutableDenseNDimArray(matrix) == dense_array
assert MutableDenseNDimArray(matrix.as_immutable()) == dense_array
assert MutableDenseNDimArray(matrix.as_mutable()) == dense_array
sparse_array = MutableSparseNDimArray([1, 2, 3, 4], (2, 2))
alist = sparse_array.tolist()
assert alist == [[1, 2], [3, 4]]
matrix = sparse_array.tomatrix()
assert isinstance(matrix, SparseMatrix)
pytest.raises(ValueError,
lambda: MutableSparseNDimArray([1]*6, (2, 2, 2)).tomatrix())
for i, ai in enumerate(sparse_array):
assert ai == matrix[i]
assert matrix.shape == sparse_array.shape
assert MutableSparseNDimArray(matrix) == sparse_array
assert MutableSparseNDimArray(matrix.as_immutable()) == sparse_array
assert MutableSparseNDimArray(matrix.as_mutable()) == sparse_array
def test_slices():
md = MutableDenseNDimArray(range(10, 34), (2, 3, 4))
assert md[:] == md._array
assert md[:, :, 0].tomatrix() == Matrix([[10, 14, 18], [22, 26, 30]])
assert md[0, 1:2, :].tomatrix() == Matrix([[14, 15, 16, 17]])
assert md[0, 1:3, :].tomatrix() == Matrix([[14, 15, 16, 17], [18, 19, 20, 21]])
assert md[:, :, :] == md
sd = MutableSparseNDimArray(range(10, 34), (2, 3, 4))
assert sd == MutableSparseNDimArray(md)
assert sd[:] == md._array
assert sd[:] == list(sd)
assert sd[:, :, 0].tomatrix() == Matrix([[10, 14, 18], [22, 26, 30]])
assert sd[0, 1:2, :].tomatrix() == Matrix([[14, 15, 16, 17]])
assert sd[0, 1:3, :].tomatrix() == Matrix([[14, 15, 16, 17], [18, 19, 20, 21]])
assert sd[:, :, :] == sd
def test_calculation():
a = MutableDenseNDimArray([1]*9, (3, 3))
b = MutableDenseNDimArray([9]*9, (3, 3))
c = a + b
for i in c:
assert i == 10
assert c == MutableDenseNDimArray([10]*9, (3, 3))
assert c == MutableSparseNDimArray([10]*9, (3, 3))
c = b - a
for i in c:
assert i == 8
assert c == MutableDenseNDimArray([8]*9, (3, 3))
assert c == MutableSparseNDimArray([8]*9, (3, 3))
pytest.raises(TypeError, lambda: c + 1)
def test_calculation():
a = MutableDenseNDimArray([1] * 9, (3, 3))
b = MutableDenseNDimArray([9] * 9, (3, 3))
c = a + b
for i in c:
assert i == 10
assert c == MutableDenseNDimArray([10] * 9, (3, 3))
assert c == MutableSparseNDimArray([10] * 9, (3, 3))
c = b - a
for i in c:
assert i == 8
assert c == MutableDenseNDimArray([8] * 9, (3, 3))
assert c == MutableSparseNDimArray([8] * 9, (3, 3))
assert c.__rtruediv__(1) == NotImplemented
def test_sparse():
sparse_array = MutableSparseNDimArray([0, 0, 0, 1], (2, 2))
assert len(sparse_array) == 2 * 2
# dictionary where all data is, only non-zero entries are actually stored:
assert len(sparse_array._sparse_array) == 1
assert list(sparse_array) == [0, 0, 0, 1]
assert sparse_array == MutableSparseNDimArray({(1, 1): 1}, (2, 2))
for i, j in zip(sparse_array, [0, 0, 0, 1]):
assert i == j
sparse_array[0, 0] = 123
assert len(sparse_array._sparse_array) == 2
assert sparse_array[0, 0] == 123
# when element in sparse array become zero it will disappear from
# dictionary
sparse_array[0, 0] = 0
assert len(sparse_array._sparse_array) == 1
sparse_array[1, 1] = 0
assert len(sparse_array._sparse_array) == 0
assert sparse_array[0, 0] == 0
def test_ndim_array_initiation():
arr_with_one_element = MutableDenseNDimArray([23])
assert len(arr_with_one_element) == 1
assert arr_with_one_element[0] == 23
assert arr_with_one_element.rank() == 1
pytest.raises(ValueError, lambda: arr_with_one_element[1])
arr_with_symbol_element = MutableDenseNDimArray([Symbol('x')])
assert len(arr_with_symbol_element) == 1
assert arr_with_symbol_element[0] == Symbol('x')
assert arr_with_symbol_element.rank() == 1
number5 = 5
vector = MutableDenseNDimArray.zeros(number5)
assert len(vector) == number5
assert vector.shape == (number5,)
assert vector.rank() == 1
pytest.raises(ValueError, lambda: arr_with_one_element[5])
vector = MutableSparseNDimArray.zeros(number5)
assert len(vector) == number5
assert vector.shape == (number5,)
assert not vector._sparse_array
assert vector.rank() == 1
n_dim_array = MutableDenseNDimArray(range(3**4), (3, 3, 3, 3,))
assert len(n_dim_array) == 3 * 3 * 3 * 3
assert n_dim_array.shape == (3, 3, 3, 3)
assert n_dim_array.rank() == 4
pytest.raises(ValueError, lambda: n_dim_array[0, 0, 0, 3])
pytest.raises(ValueError, lambda: n_dim_array[3, 0, 0, 0])
pytest.raises(ValueError, lambda: n_dim_array[3**4])
array_shape = (3, 3, 3, 3)
sparse_array = MutableSparseNDimArray.zeros(*array_shape)
assert len(sparse_array._sparse_array) == 0
assert len(sparse_array) == 3 * 3 * 3 * 3
assert n_dim_array.shape == array_shape
assert n_dim_array.rank() == 4
one_dim_array = MutableDenseNDimArray([2, 3, 1])
assert len(one_dim_array) == 3
assert one_dim_array.shape == (3,)
assert one_dim_array.rank() == 1
assert one_dim_array.tolist() == [2, 3, 1]
shape = (3, 3)
array_with_many_args = MutableSparseNDimArray.zeros(*shape)
assert len(array_with_many_args) == 3 * 3
assert array_with_many_args.shape == shape
assert array_with_many_args[0, 0] == 0
assert array_with_many_args.rank() == 2
pytest.raises(TypeError, lambda: MutableDenseNDimArray(1))
pytest.raises(TypeError, lambda: MutableDenseNDimArray([1, 2], shape=(1.2, 3)))
pytest.raises(ValueError, lambda: MutableDenseNDimArray([[1, 2], [3]]))
b = MutableDenseNDimArray([1, 2, 3, 4], shape=(2, 2))
c = MutableDenseNDimArray(b)
assert c.shape == (2, 2)
a2 = MutableDenseNDimArray([[2, 3], [4, 5]])
pytest.raises(ValueError, lambda: a2[10])
pytest.raises(ValueError, lambda: a2[1, 1, 1])
pytest.raises(ValueError, lambda: a2[3, 3])