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]
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
# test for large scale sparse array
a = MutableSparseNDimArray.zeros(100000, 200000)
b = MutableSparseNDimArray.zeros(100000, 200000)
assert a == b
a[1, 1] = 1
b[1, 1] = 2
assert a != b
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
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
raises(ValueError, lambda: arr_with_one_element[5])
vector = MutableSparseNDimArray.zeros(number5)
assert len(vector) == number5
assert vector.shape == (number5,)
assert 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
raises(ValueError, lambda: n_dim_array[0, 0, 0, 3])
raises(ValueError, lambda: n_dim_array[3, 0, 0, 0])
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
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 sparse_array.tolist() == [[0, 0], [0, 1]]
for i, j in zip(sparse_array, [[0, 0], [0, 1]]):
assert i == MutableSparseNDimArray(j)
sparse_array[0, 0] = 123
assert len(sparse_array._sparse_array) == 2
assert sparse_array[0, 0] == 123
assert sparse_array / 0 == MutableSparseNDimArray(
[[S.ComplexInfinity, S.NaN], [S.NaN, S.ComplexInfinity]], (2, 2))
# 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
# test for large scale sparse array
# equality test
a = MutableSparseNDimArray.zeros(100000, 200000)
b = MutableSparseNDimArray.zeros(100000, 200000)
assert a == b
a[1, 1] = 1
b[1, 1] = 2
assert a != b
# __mul__ and __rmul__
assert a * 3 == MutableSparseNDimArray({200001: 3}, (100000, 200000))
assert 3 * a == MutableSparseNDimArray({200001: 3}, (100000, 200000))
assert a * 0 == MutableSparseNDimArray({}, (100000, 200000))
assert 0 * a == MutableSparseNDimArray({}, (100000, 200000))
# __div__
assert a / 3 == MutableSparseNDimArray({200001: Rational(1, 3)},
(100000, 200000))
# __neg__
assert -a == MutableSparseNDimArray({200001: -1}, (100000, 200000))
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
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
raises(ValueError, lambda: arr_with_one_element[5])
vector = MutableSparseNDimArray.zeros(number5)
assert len(vector) == number5
assert vector.shape == (number5, )
assert 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
raises(ValueError, lambda: n_dim_array[0, 0, 0, 3])
raises(ValueError, lambda: n_dim_array[3, 0, 0, 0])
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
shape = (long(3), long(3))
array_with_long_shape = MutableSparseNDimArray.zeros(*shape)
assert len(array_with_long_shape) == 3 * 3
assert array_with_long_shape.shape == shape
assert array_with_long_shape[long(0), long(0)] == 0
assert array_with_long_shape.rank() == 2
vector_with_long_shape = MutableDenseNDimArray(range(5), long(5))
assert len(vector_with_long_shape) == 5
assert vector_with_long_shape.shape == (long(5), )
assert vector_with_long_shape.rank() == 1
raises(ValueError, lambda: vector_with_long_shape[long(5)])
from sympy.abc import x
for ArrayType in [MutableDenseNDimArray, MutableSparseNDimArray]:
rank_zero_array = ArrayType(x)
assert len(rank_zero_array) == 1
assert rank_zero_array.shape == ()
assert rank_zero_array.rank() == 0
assert rank_zero_array[()] == x
raises(ValueError, lambda: rank_zero_array[0])