def test_ndim_array_converting():
dense_array = ImmutableDenseNDimArray([1, 2, 3, 4], (2, 2))
alist = dense_array.tolist()
alist == [[1, 2], [3, 4]]
matrix = dense_array.tomatrix()
assert (isinstance(matrix, Matrix))
for i in range(len(dense_array)):
assert dense_array[dense_array._get_tuple_index(i)] == matrix[i]
assert matrix.shape == dense_array.shape
assert ImmutableDenseNDimArray(matrix) == dense_array
assert ImmutableDenseNDimArray(matrix.as_immutable()) == dense_array
assert ImmutableDenseNDimArray(matrix.as_mutable()) == dense_array
sparse_array = ImmutableSparseNDimArray([1, 2, 3, 4], (2, 2))
alist = sparse_array.tolist()
assert alist == [[1, 2], [3, 4]]
matrix = sparse_array.tomatrix()
assert (isinstance(matrix, SparseMatrix))
for i in range(len(sparse_array)):
assert sparse_array[sparse_array._get_tuple_index(i)] == matrix[i]
assert matrix.shape == sparse_array.shape
assert ImmutableSparseNDimArray(matrix) == sparse_array
assert ImmutableSparseNDimArray(matrix.as_immutable()) == sparse_array
assert ImmutableSparseNDimArray(matrix.as_mutable()) == sparse_array
def test_ndim_array_converting():
dense_array = ImmutableDenseNDimArray([1, 2, 3, 4], (2, 2))
alist = dense_array.tolist()
alist == [[1, 2], [3, 4]]
matrix = dense_array.tomatrix()
assert (isinstance(matrix, Matrix))
for i in range(len(dense_array)):
assert dense_array[i] == matrix[i]
assert matrix.shape == dense_array.shape
assert ImmutableDenseNDimArray(matrix) == dense_array
assert ImmutableDenseNDimArray(matrix.as_immutable()) == dense_array
assert ImmutableDenseNDimArray(matrix.as_mutable()) == dense_array
sparse_array = ImmutableSparseNDimArray([1, 2, 3, 4], (2, 2))
alist = sparse_array.tolist()
assert alist == [[1, 2], [3, 4]]
matrix = sparse_array.tomatrix()
assert(isinstance(matrix, SparseMatrix))
for i in range(len(sparse_array)):
assert sparse_array[i] == matrix[i]
assert matrix.shape == sparse_array.shape
assert ImmutableSparseNDimArray(matrix) == sparse_array
assert ImmutableSparseNDimArray(matrix.as_immutable()) == sparse_array
assert ImmutableSparseNDimArray(matrix.as_mutable()) == sparse_array
def test_sparse():
sparse_array = ImmutableSparseNDimArray([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 sparse_array.tolist() == [[0, 0], [0, 1]]
for i, j in zip(sparse_array, [[0, 0], [0, 1]]):
assert i == ImmutableSparseNDimArray(j)
def sparse_assignment():
sparse_array[0, 0] = 123
assert len(sparse_array._sparse_array) == 1
raises(TypeError, sparse_assignment)
assert len(sparse_array._sparse_array) == 1
assert sparse_array[0, 0] == 0
assert sparse_array / 0 == ImmutableSparseNDimArray(
[[S.NaN, S.NaN], [S.NaN, S.ComplexInfinity]], (2, 2))
# test for large scale sparse array
# equality test
assert ImmutableSparseNDimArray.zeros(
100000, 200000) == ImmutableSparseNDimArray.zeros(100000, 200000)
# __mul__ and __rmul__
a = ImmutableSparseNDimArray({200001: 1}, (100000, 200000))
assert a * 3 == ImmutableSparseNDimArray({200001: 3}, (100000, 200000))
assert 3 * a == ImmutableSparseNDimArray({200001: 3}, (100000, 200000))
assert a * 0 == ImmutableSparseNDimArray({}, (100000, 200000))
assert 0 * a == ImmutableSparseNDimArray({}, (100000, 200000))
# __div__
assert a / 3 == ImmutableSparseNDimArray({200001: Rational(1, 3)},
(100000, 200000))
# __neg__
assert -a == ImmutableSparseNDimArray({200001: -1}, (100000, 200000))
def test_ndim_array_converting():
dense_array = ImmutableDenseNDimArray([1, 2, 3, 4], (2, 2))
alist = dense_array.tolist()
alist == [[1, 2], [3, 4]]
matrix = dense_array.tomatrix()
assert (isinstance(matrix, Matrix))
for i in range(len(dense_array)):
assert dense_array[i] == matrix[i]
assert matrix.shape == dense_array.shape
sparse_array = ImmutableSparseNDimArray([1, 2, 3, 4], (2, 2))
alist = sparse_array.tolist()
assert alist == [[1, 2], [3, 4]]
matrix = sparse_array.tomatrix()
assert (isinstance(matrix, SparseMatrix))
for i in range(len(sparse_array)):
assert sparse_array[i] == matrix[i]
assert matrix.shape == sparse_array.shape
