在尝试附加时我收到一个属性错误
while trying to append I receive an attributeerror
我坚持以下。附加时我似乎做错了什么。我收到错误消息：'float' 对象没有属性 'append'。
我现在明白我要附加一个浮点值，这是不可能的。但是，例如，我如何才能在 TheorBlockNeighborsOne 中的第一个索引的每个列表中获得 Data_BM_Sorted_List 的索引 [0] 的值，以及在第二个位置的每个列表中，从 Data_BM_Sorted_List 和在第三个位置，索引 2 处 Data_BM_Sorted_List 的值。然后对于每个 i.
TheorBlockNeighborsOne[i] = Data_BM_Sorted_List[i][0]
TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][1]+Horizontal_Block_Dimensions))
TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][2]))
Horizontal_Block_Dimensions = int(raw_input())
Horizontal_Block_Dimensions 的原始输入是 100
Data_BM_Sorted_List = [[336350.0, 7089650.0, -7.0, 0.1665, 1.5, 1], [336350.0, 7089650.0, -5.0, 0.1542, 1.5, 1], [336350.0, 7089650.0, -3.0, 0.2259, 1.5, 1], [336350.0, 7089650.0, -1.0, 0.2753, 1.5, 1], [336350.0, 7089650.0, 1.0, 0.2236, 1.5, 1], [336450.0, 7089550.0, -7.0, 0.1791, 1.5, 2], [336450.0, 7089550.0, -5.0, 0.1707, 1.5, 2], [336450.0, 7089550.0, -3.0, 0.2248, 1.5, 2], [336450.0, 7089550.0, -1.0, 0.2791, 1.5, 2], [336450.0, 7089550.0, 1.0, 0.3098, 1.5, 2], [336450.0, 7089650.0, -5.0, 0.1488, 1.5, 3], [336450.0, 7089650.0, -3.0, 0.1961, 1.5, 3], [336450.0, 7089650.0, -1.0, 0.2499, 1.5, 3], [336450.0, 7089650.0, 1.0, 0.2939, 1.5, 3], [336550.0, 7089350.0, -7.0, 0.1774, 1.5, 4], [336550.0, 7089350.0, -5.0, 0.2551, 1.5, 4], [336550.0, 7089350.0, -3.0, 0.3489, 1.5, 4], [336550.0, 7089350.0, -1.0, 0.3707, 1.5, 4], [336550.0, 7089350.0, 1.0, 0.3037, 1.5, 4], [336550.0, 7089450.0, -5.0, 0.1719, 1.5, 5], [336550.0, 7089450.0, -3.0, 0.3121, 1.5, 5], [336550.0, 7089450.0, -1.0, 0.3491, 1.5, 5], [336550.0, 7089450.0, 1.0, 0.326, 1.5, 5], [336550.0, 7089550.0, -7.0, 0.1494, 1.5, 6], [336550.0, 7089550.0, -5.0, 0.1598, 1.5, 6], [336550.0, 7089550.0, -3.0, 0.2061, 1.5, 6], [336550.0, 7089550.0, -1.0, 0.2554, 1.5, 6], [336550.0, 7089550.0, 1.0, 0.3218, 1.5, 6], [336550.0, 7089650.0, -5.0, 0.1334, 1.5, 7], [336550.0, 7089650.0, -3.0, 0.1711, 1.5, 7], [336550.0, 7089650.0, -1.0, 0.193, 1.5, 7], [336550.0, 7089650.0, 1.0, 0.2498, 1.5, 7], [336650.0, 7089150.0, -9.0, 0.165, 1.5, 8], [336650.0, 7089150.0, -7.0, 0.1791, 1.5, 8], [336650.0, 7089150.0, -5.0, 0.2482, 1.5, 8], [336650.0, 7089150.0, -3.0, 0.3541, 1.5, 8]]
TheorBlockNeighborsOne = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsTwo = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsThree = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsFour = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsFive = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsSix = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsSeven = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsEight = [[]]*len(Data_BM_Sorted_List)
# BlockNeighborsX = [[X,Y,Z]]
for i in range(0,len(TheorBlockNeighborsOne)):
TheorBlockNeighborsOne[i] = Data_BM_Sorted_List[i][0]
TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][1]+Horizontal_Block_Dimensions))
TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][2]))
TheorBlockNeighborsTwo[i] = Data_BM_Sorted_List[i][0] + Horizontal_Block_Dimensions
TheorBlockNeighborsTwo[i].append(Data_BM_Sorted_List[i][1])
TheorBlockNeighborsTwo[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsThree[i] = Data_BM_Sorted_List[i][0]
TheorBlockNeighborsThree[i].append(Data_BM_Sorted_List[i][1] - Horizontal_Block_Dimensions)
TheorBlockNeighborsThree[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsFour[i] = Data_BM_Sorted_List[i][0] - Horizontal_Block_Dimensions
TheorBlockNeighborsFour[i].append(Data_BM_Sorted_List[i][1])
TheorBlockNeighborsFour[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsFive[i] = Data_BM_Sorted_List[i][0] - Horizontal_Block_Dimensions
TheorBlockNeighborsFive[i].append(Data_BM_Sorted_List[i][1] + Horizontal_Block_Dimensions)
TheorBlockNeighborsFive[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsSix[i] = Data_BM_Sorted_List[i][0] + Horizontal_Block_Dimensions
TheorBlockNeighborsSix[i].append(Data_BM_Sorted_List[i][1] + Horizontal_Block_Dimensions)
TheorBlockNeighborsSix[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsSeven[i] = Data_BM_Sorted_List[i][0] + Horizontal_Block_Dimensions
TheorBlockNeighborsSeven[i].append(Data_BM_Sorted_List[i][1] - Horizontal_Block_Dimensions)
TheorBlockNeighborsSeven[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsEight[i] = Data_BM_Sorted_List[i][0] - Horizontal_Block_Dimensions
TheorBlockNeighborsEight[i].append(Data_BM_Sorted_List[i][1] - Horizontal_Block_Dimensions)
TheorBlockNeighborsEight[i].append(Data_BM_Sorted_List[i][2])
print TheorBlockNeighborsOne
我得到的错误：
AttributeError Traceback (most recent call last)
<ipython-input-46-a2f61fb09e5b> in <module>()
12 for i in range(0,len(TheorBlockNeighborsOne)):
13 TheorBlockNeighborsOne[i] = Data_BM_Sorted_List[i][0]
---> 14 TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][1]+Horizontal_Block_Dimensions))
15 TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][2]))
16 TheorBlockNeighborsTwo[i] = Data_BM_Sorted_List[i][0] + Horizontal_Block_Dimensions
AttributeError: 'float' object has no attribute 'append'
您为列表索引分配了一个浮点数，然后尝试对该浮点数调用 .append()：
TheorBlockNeighborsOne[i] = Data_BM_Sorted_List[i][0]
TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][1]+Horizontal_Block_Dimensions))
此处，Data_BM_Sorted_List[i] 是 Data_BM_Sorted_List 中的嵌套列表之一，[0] 是该列表中的第一个值，它始终是 float:
Data_BM_Sorted_List = [[336350.0, 7089650.0, -7.0, 0.1665, 1.5, 1], [336350.0, 7089650.0, -5.0, 0.1542, 1.5, 1], [336350.0, 7089650.0, -3.0, 0.2259, 1.5, 1], [336350.0, 7089650.0, -1.0, 0.2753, 1.5, 1], [336350.0, 7089650.0, 1.0, 0.2236, 1.5, 1], [336450.0, 7089550.0, -7.0, 0.1791, 1.5, 2], [336450.0, 7089550.0, -5.0, 0.1707, 1.5, 2], [336450.0, 7089550.0, -3.0, 0.2248, 1.5, 2], [336450.0, 7089550.0, -1.0, 0.2791, 1.5, 2], [336450.0, 7089550.0, 1.0, 0.3098, 1.5, 2], [336450.0, 7089650.0, -5.0, 0.1488, 1.5, 3], [336450.0, 7089650.0, -3.0, 0.1961, 1.5, 3], [336450.0, 7089650.0, -1.0, 0.2499, 1.5, 3], [336450.0, 7089650.0, 1.0, 0.2939, 1.5, 3], [336550.0, 7089350.0, -7.0, 0.1774, 1.5, 4], [336550.0, 7089350.0, -5.0, 0.2551, 1.5, 4], [336550.0, 7089350.0, -3.0, 0.3489, 1.5, 4], [336550.0, 7089350.0, -1.0, 0.3707, 1.5, 4], [336550.0, 7089350.0, 1.0, 0.3037, 1.5, 4], [336550.0, 7089450.0, -5.0, 0.1719, 1.5, 5], [336550.0, 7089450.0, -3.0, 0.3121, 1.5, 5], [336550.0, 7089450.0, -1.0, 0.3491, 1.5, 5], [336550.0, 7089450.0, 1.0, 0.326, 1.5, 5], [336550.0, 7089550.0, -7.0, 0.1494, 1.5, 6], [336550.0, 7089550.0, -5.0, 0.1598, 1.5, 6], [336550.0, 7089550.0, -3.0, 0.2061, 1.5, 6], [336550.0, 7089550.0, -1.0, 0.2554, 1.5, 6], [336550.0, 7089550.0, 1.0, 0.3218, 1.5, 6], [336550.0, 7089650.0, -5.0, 0.1334, 1.5, 7], [336550.0, 7089650.0, -3.0, 0.1711, 1.5, 7], [336550.0, 7089650.0, -1.0, 0.193, 1.5, 7], [336550.0, 7089650.0, 1.0, 0.2498, 1.5, 7], [336650.0, 7089150.0, -9.0, 0.165, 1.5, 8], [336650.0, 7089150.0, -7.0, 0.1791, 1.5, 8], [336650.0, 7089150.0, -5.0, 0.2482, 1.5, 8], [336650.0, 7089150.0, -3.0, 0.3541, 1.5, 8]]
请注意，您创建矩阵的方法存在缺陷，您正在陷入List of lists changes reflected across sublists unexpectedly中描述的列表乘法陷阱；列表的乘法不会创建新对象；而只有 references 内容重复。所以 TheorBlockNeighborsOne[0] 将成为与 TheorBlockNeighborsOne[1] 等完全相同的列表对象。在一个索引处向该嵌套列表附加一个值，您将看到在所有其他引用中重复相同的值.
如果你想让那个浮点值成为每个列表的一部分，你需要附加它太；赋值替换列表对象。
接下来，您的代码会重复多次。与其创建 8 个命名列表，不如使用字典或列表来包含它们。你可以这样做：
theor_block_neighbors = [
[[] for _ in range(len(Data_BM_Sorted_List))]
for _ in range(8)]
这将创建一个包含 8 个矩阵的列表，然后您可以在循环中对其进行寻址。
我坚持以下。附加时我似乎做错了什么。我收到错误消息：'float' 对象没有属性 'append'。 我现在明白我要附加一个浮点值，这是不可能的。但是，例如，我如何才能在 TheorBlockNeighborsOne 中的第一个索引的每个列表中获得 Data_BM_Sorted_List 的索引 [0] 的值，以及在第二个位置的每个列表中，从 Data_BM_Sorted_List 和在第三个位置，索引 2 处 Data_BM_Sorted_List 的值。然后对于每个 i.
TheorBlockNeighborsOne[i] = Data_BM_Sorted_List[i][0]
TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][1]+Horizontal_Block_Dimensions))
TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][2]))
Horizontal_Block_Dimensions = int(raw_input())
Horizontal_Block_Dimensions 的原始输入是 100
Data_BM_Sorted_List = [[336350.0, 7089650.0, -7.0, 0.1665, 1.5, 1], [336350.0, 7089650.0, -5.0, 0.1542, 1.5, 1], [336350.0, 7089650.0, -3.0, 0.2259, 1.5, 1], [336350.0, 7089650.0, -1.0, 0.2753, 1.5, 1], [336350.0, 7089650.0, 1.0, 0.2236, 1.5, 1], [336450.0, 7089550.0, -7.0, 0.1791, 1.5, 2], [336450.0, 7089550.0, -5.0, 0.1707, 1.5, 2], [336450.0, 7089550.0, -3.0, 0.2248, 1.5, 2], [336450.0, 7089550.0, -1.0, 0.2791, 1.5, 2], [336450.0, 7089550.0, 1.0, 0.3098, 1.5, 2], [336450.0, 7089650.0, -5.0, 0.1488, 1.5, 3], [336450.0, 7089650.0, -3.0, 0.1961, 1.5, 3], [336450.0, 7089650.0, -1.0, 0.2499, 1.5, 3], [336450.0, 7089650.0, 1.0, 0.2939, 1.5, 3], [336550.0, 7089350.0, -7.0, 0.1774, 1.5, 4], [336550.0, 7089350.0, -5.0, 0.2551, 1.5, 4], [336550.0, 7089350.0, -3.0, 0.3489, 1.5, 4], [336550.0, 7089350.0, -1.0, 0.3707, 1.5, 4], [336550.0, 7089350.0, 1.0, 0.3037, 1.5, 4], [336550.0, 7089450.0, -5.0, 0.1719, 1.5, 5], [336550.0, 7089450.0, -3.0, 0.3121, 1.5, 5], [336550.0, 7089450.0, -1.0, 0.3491, 1.5, 5], [336550.0, 7089450.0, 1.0, 0.326, 1.5, 5], [336550.0, 7089550.0, -7.0, 0.1494, 1.5, 6], [336550.0, 7089550.0, -5.0, 0.1598, 1.5, 6], [336550.0, 7089550.0, -3.0, 0.2061, 1.5, 6], [336550.0, 7089550.0, -1.0, 0.2554, 1.5, 6], [336550.0, 7089550.0, 1.0, 0.3218, 1.5, 6], [336550.0, 7089650.0, -5.0, 0.1334, 1.5, 7], [336550.0, 7089650.0, -3.0, 0.1711, 1.5, 7], [336550.0, 7089650.0, -1.0, 0.193, 1.5, 7], [336550.0, 7089650.0, 1.0, 0.2498, 1.5, 7], [336650.0, 7089150.0, -9.0, 0.165, 1.5, 8], [336650.0, 7089150.0, -7.0, 0.1791, 1.5, 8], [336650.0, 7089150.0, -5.0, 0.2482, 1.5, 8], [336650.0, 7089150.0, -3.0, 0.3541, 1.5, 8]]
TheorBlockNeighborsOne = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsTwo = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsThree = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsFour = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsFive = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsSix = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsSeven = [[]]*len(Data_BM_Sorted_List)
TheorBlockNeighborsEight = [[]]*len(Data_BM_Sorted_List)
# BlockNeighborsX = [[X,Y,Z]]
for i in range(0,len(TheorBlockNeighborsOne)):
TheorBlockNeighborsOne[i] = Data_BM_Sorted_List[i][0]
TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][1]+Horizontal_Block_Dimensions))
TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][2]))
TheorBlockNeighborsTwo[i] = Data_BM_Sorted_List[i][0] + Horizontal_Block_Dimensions
TheorBlockNeighborsTwo[i].append(Data_BM_Sorted_List[i][1])
TheorBlockNeighborsTwo[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsThree[i] = Data_BM_Sorted_List[i][0]
TheorBlockNeighborsThree[i].append(Data_BM_Sorted_List[i][1] - Horizontal_Block_Dimensions)
TheorBlockNeighborsThree[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsFour[i] = Data_BM_Sorted_List[i][0] - Horizontal_Block_Dimensions
TheorBlockNeighborsFour[i].append(Data_BM_Sorted_List[i][1])
TheorBlockNeighborsFour[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsFive[i] = Data_BM_Sorted_List[i][0] - Horizontal_Block_Dimensions
TheorBlockNeighborsFive[i].append(Data_BM_Sorted_List[i][1] + Horizontal_Block_Dimensions)
TheorBlockNeighborsFive[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsSix[i] = Data_BM_Sorted_List[i][0] + Horizontal_Block_Dimensions
TheorBlockNeighborsSix[i].append(Data_BM_Sorted_List[i][1] + Horizontal_Block_Dimensions)
TheorBlockNeighborsSix[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsSeven[i] = Data_BM_Sorted_List[i][0] + Horizontal_Block_Dimensions
TheorBlockNeighborsSeven[i].append(Data_BM_Sorted_List[i][1] - Horizontal_Block_Dimensions)
TheorBlockNeighborsSeven[i].append(Data_BM_Sorted_List[i][2])
TheorBlockNeighborsEight[i] = Data_BM_Sorted_List[i][0] - Horizontal_Block_Dimensions
TheorBlockNeighborsEight[i].append(Data_BM_Sorted_List[i][1] - Horizontal_Block_Dimensions)
TheorBlockNeighborsEight[i].append(Data_BM_Sorted_List[i][2])
print TheorBlockNeighborsOne
我得到的错误：
AttributeError Traceback (most recent call last)
<ipython-input-46-a2f61fb09e5b> in <module>()
12 for i in range(0,len(TheorBlockNeighborsOne)):
13 TheorBlockNeighborsOne[i] = Data_BM_Sorted_List[i][0]
---> 14 TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][1]+Horizontal_Block_Dimensions))
15 TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][2]))
16 TheorBlockNeighborsTwo[i] = Data_BM_Sorted_List[i][0] + Horizontal_Block_Dimensions
AttributeError: 'float' object has no attribute 'append'
您为列表索引分配了一个浮点数，然后尝试对该浮点数调用 .append()：
TheorBlockNeighborsOne[i] = Data_BM_Sorted_List[i][0]
TheorBlockNeighborsOne[i].append((Data_BM_Sorted_List[i][1]+Horizontal_Block_Dimensions))
此处，Data_BM_Sorted_List[i] 是 Data_BM_Sorted_List 中的嵌套列表之一，[0] 是该列表中的第一个值，它始终是 float:
Data_BM_Sorted_List = [[336350.0, 7089650.0, -7.0, 0.1665, 1.5, 1], [336350.0, 7089650.0, -5.0, 0.1542, 1.5, 1], [336350.0, 7089650.0, -3.0, 0.2259, 1.5, 1], [336350.0, 7089650.0, -1.0, 0.2753, 1.5, 1], [336350.0, 7089650.0, 1.0, 0.2236, 1.5, 1], [336450.0, 7089550.0, -7.0, 0.1791, 1.5, 2], [336450.0, 7089550.0, -5.0, 0.1707, 1.5, 2], [336450.0, 7089550.0, -3.0, 0.2248, 1.5, 2], [336450.0, 7089550.0, -1.0, 0.2791, 1.5, 2], [336450.0, 7089550.0, 1.0, 0.3098, 1.5, 2], [336450.0, 7089650.0, -5.0, 0.1488, 1.5, 3], [336450.0, 7089650.0, -3.0, 0.1961, 1.5, 3], [336450.0, 7089650.0, -1.0, 0.2499, 1.5, 3], [336450.0, 7089650.0, 1.0, 0.2939, 1.5, 3], [336550.0, 7089350.0, -7.0, 0.1774, 1.5, 4], [336550.0, 7089350.0, -5.0, 0.2551, 1.5, 4], [336550.0, 7089350.0, -3.0, 0.3489, 1.5, 4], [336550.0, 7089350.0, -1.0, 0.3707, 1.5, 4], [336550.0, 7089350.0, 1.0, 0.3037, 1.5, 4], [336550.0, 7089450.0, -5.0, 0.1719, 1.5, 5], [336550.0, 7089450.0, -3.0, 0.3121, 1.5, 5], [336550.0, 7089450.0, -1.0, 0.3491, 1.5, 5], [336550.0, 7089450.0, 1.0, 0.326, 1.5, 5], [336550.0, 7089550.0, -7.0, 0.1494, 1.5, 6], [336550.0, 7089550.0, -5.0, 0.1598, 1.5, 6], [336550.0, 7089550.0, -3.0, 0.2061, 1.5, 6], [336550.0, 7089550.0, -1.0, 0.2554, 1.5, 6], [336550.0, 7089550.0, 1.0, 0.3218, 1.5, 6], [336550.0, 7089650.0, -5.0, 0.1334, 1.5, 7], [336550.0, 7089650.0, -3.0, 0.1711, 1.5, 7], [336550.0, 7089650.0, -1.0, 0.193, 1.5, 7], [336550.0, 7089650.0, 1.0, 0.2498, 1.5, 7], [336650.0, 7089150.0, -9.0, 0.165, 1.5, 8], [336650.0, 7089150.0, -7.0, 0.1791, 1.5, 8], [336650.0, 7089150.0, -5.0, 0.2482, 1.5, 8], [336650.0, 7089150.0, -3.0, 0.3541, 1.5, 8]]
请注意，您创建矩阵的方法存在缺陷，您正在陷入List of lists changes reflected across sublists unexpectedly中描述的列表乘法陷阱；列表的乘法不会创建新对象；而只有 references 内容重复。所以 TheorBlockNeighborsOne[0] 将成为与 TheorBlockNeighborsOne[1] 等完全相同的列表对象。在一个索引处向该嵌套列表附加一个值，您将看到在所有其他引用中重复相同的值.
如果你想让那个浮点值成为每个列表的一部分，你需要附加它太；赋值替换列表对象。
接下来，您的代码会重复多次。与其创建 8 个命名列表，不如使用字典或列表来包含它们。你可以这样做：
theor_block_neighbors = [
[[] for _ in range(len(Data_BM_Sorted_List))]
for _ in range(8)]
这将创建一个包含 8 个矩阵的列表，然后您可以在循环中对其进行寻址。