问题

我是新手学习Python，尝试读取一个包含对象位置数据的大型文件，涵盖了一段时间序列。类似于：
```python
for a in dum_un.file:
    
    FD = dum_un.select_object("type 1")
    r = FD.positions

每个 r 对应于特定的时间点，列表内的列表对应于该时间点物体的x、y和z位置。整个时间序列中的顺序保持一致。两个物体的示例：

for循环的第一次迭代：r = [[1.11, 2.64, 3.3],[4.0, 5.12, 6.32]]

for循环的第二次迭代：r = [[5.7, 4.44, 1.8],[6.3, 8.9, 4.7]]

我想要能够访问每个对象在整个时间序列内所有x（或y或z）值的列表，例如：

对于对象1，x = [1.11, 5.7]

对于对象2，x = [4.0, 6.3]

<details>
<summary>英文:</summary>

I am new to python and trying to read a large file with position data for objects over a time series. Something like:
~~~python
for a in dum_un.file:
    
    FD = dum_un.select_object(&quot;type 1&quot;)
    r = FD.positions
~~~

Each `r` corresponds to a specific time point, and each list-within-the-list corresponds to the x, y, and z positions of an object at that time point. The ordering is the same throughout the time series. Example for 2 objects:

First iteration of the for loop: `r = [[1.11, 2.64, 3.3],[4.0, 5.12, 6.32]]`

Second iteration of the for loop: `r = [[5.7, 4.44, 1.8],[6.3, 8.9, 4.7]]`

I want to be able to access a list of all x (or y or z) values for each object over the entire time series, e.g., here:

`x = [1.11, 5.7]` for object 1

`x = [4.0, 6.3]` for object 2

</details>


# 答案1
**得分**: 1

这里是一种方法。

解析创建了一个名为`objects`的字典，看起来类似于这样：

```json
{
  "1": {
    "x": [1.11, 5.7],
    "y": [...],
    "z": [...]
  },
  "2": {
    "x": [...],
    "y": [...],
    "z": [...]
  },
  // 其他对象的数据...
}

以下是代码：

# 这个列表表示每次迭代中 `r` 的值
all_r = [
    [[1.11, 2.64, 3.3], [4.0, 5.12, 6.32]],
    [[5.7, 4.44, 1.8], [6.3, 8.9, 4.7]]
]

# 初始化一个字典来收集所有结果
# 每个条目的键将是对象的“ID”
# 例如，`r` 中的第一个项目代表“对象 1”。
objects = dict()

for r in all_r:
    for i, coordinates in enumerate(r):
        # Python 索引从零开始。因此，加一以匹配您的定义
        object_id = str(i + 1)
    
        # 如果对象的字典键不存在，则初始化
        if object_id not in objects.keys():
            objects[object_id] = {
                "x": [],
                "y": [],
                "z": []
            }

        # 将每个坐标添加到相应的X、Y或Z列表中
        objects[object_id]["x"].append(coordinates[0])
        objects[object_id]["y"].append(coordinates[1])
        objects[object_id]["z"].append(coordinates[2])

expected_x_object_1 = [1.11, 5.7]
expected_x_object_2 = [4.0, 6.3]

actual_x_object_1 = objects.get("1", dict()).get("x", None)
actual_x_object_2 = objects.get("2", dict()).get("x", None)

assert expected_x_object_1 == actual_x_object_1
assert expected_x_object_2 == actual_x_object_2

{
  "1": {
    "x": [1.11, 5.7],
    "y": [...],
    "z": [...],
  },
  "2": {
    "x": [...],
    "y": [...],
    "z": [...],
  },
  ...
}

# This list represents the value of `r` in each iteration
all_r = [
    [[1.11, 2.64, 3.3],[4.0, 5.12, 6.32]],
    [[5.7, 4.44, 1.8],[6.3, 8.9, 4.7]]
]

# Initialise a dictionary to collect all the results
# The key for each entry will be the object "ID"
# e.g. the first item in `r` represents "object 1".
objects = dict()

for r in all_r:
    for i, coordinates in enumerate(r):
        # Python indexes start at zero. So increment by one to match your definition
        object_id = str(i + 1)
    
        # Initialise the dictionary key for our object if it doesn't exist already
        if object_id not in objects.keys():
            objects[object_id] = {
                "x": [],
                "y": [],
                "z": [],
            }

        # Add each co-ordinate to their relevant X, Y or Z list
        objects[object_id]["x"].append(coordinates[0])
        objects[object_id]["y"].append(coordinates[1])
        objects[object_id]["z"].append(coordinates[2])

expected_x_object_1 = [1.11, 5.7]
expected_x_object_2 = [4.0, 6.3]

actual_x_object_1 = objects.get("1", dict()).get("x", None)
actual_x_object_2 = objects.get("2", dict()).get("x", None)

assert expected_x_object_1 == actual_x_object_1
assert expected_x_object_2 == actual_x_object_2