本文整理汇总了Python中sympy.tensor.array.dense_ndim_array.MutableDenseNDimArray.rank方法的典型用法代码示例。如果您正苦于以下问题：Python MutableDenseNDimArray.rank方法的具体用法？Python MutableDenseNDimArray.rank怎么用？Python MutableDenseNDimArray.rank使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sympy.tensor.array.dense_ndim_array.MutableDenseNDimArray的用法示例。
在下文中一共展示了MutableDenseNDimArray.rank方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_reshape
# 需要导入模块: from sympy.tensor.array.dense_ndim_array import MutableDenseNDimArray [as 别名]
# 或者: from sympy.tensor.array.dense_ndim_array.MutableDenseNDimArray import rank [as 别名]
def test_reshape():
array = MutableDenseNDimArray(range(50), 50)
assert array.shape == (50,)
assert array.rank() == 1
array = array.reshape(5, 5, 2)
assert array.shape == (5, 5, 2)
assert array.rank() == 3
assert len(array) == 50示例2: test_ndim_array_initiation
# 需要导入模块: from sympy.tensor.array.dense_ndim_array import MutableDenseNDimArray [as 别名]
# 或者: from sympy.tensor.array.dense_ndim_array.MutableDenseNDimArray import rank [as 别名]
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