如何从 Python 中创建具有 Matlab 数据结构中的多维数组的 Matlab 文件？

Question

我正在尝试从 Python 创建一个 Matlab 文件 (*.mat)，其中包含一个 Matlab 数据结构，如下所示：

s.key1 where key1 is an array of values
s.key2 where key2 is an array of 1D arrays 
s.key3 where key3 is an array of 2D arrays 

如果我使用 savemat 和字典，Matlab 输出是元胞数组而不是 Matlab 数据结构。

我尝试过使用

np.core.records.fromarrays(data_list, names=q_keys)

但这似乎不适用于二维数组的键。我有 2D 和 3D 数组，它们需要在 Matlab 结构中才能与现有文件格式兼容。有没有办法在 Python 中做到这一点？

谢谢

Answer 1

这是任务的尝试：

In [292]: dt = np.dtype([('key1',int),('key2',int, (3,)),('key3',object)])
In [293]: arr = np.zeros((5,), dt)
In [294]: arr
Out[294]: 
array([(0, [0, 0, 0], 0), (0, [0, 0, 0], 0), (0, [0, 0, 0], 0),
       (0, [0, 0, 0], 0), (0, [0, 0, 0], 0)],
      dtype=[('key1', '<i8'), ('key2', '<i8', (3,)), ('key3', 'O')])
In [295]: arr['key1']=np.arange(5)
In [296]: arr['key2']=np.arange(15).reshape(5,3)
In [302]: arr['key3']=[1,np.arange(5),np.ones((2,3),int),'astring',[['a','b']]]
In [303]: io.savemat('test.mat', {'astruct':arr})

八度：

>> load test.mat
>> format compact
>> astruct
astruct =

  1x5 struct array containing the fields:

    key1
    key2
    key3
>> astruc.key1
error: 'astruc' undefined near line 1 column 1
>> astruct.key1
ans = 0
ans = 1
ans = 2
ans = 3
ans = 4
>> astruct.key2
ans =
  0  1  2
ans =
  3  4  5
ans =
  6  7  8
ans =
   9  10  11
ans =
  12  13  14
>> astruct.key3
ans = 1
ans =
  0  1  2  3  4
ans =
  1  1  1
  1  1  1
ans = astring
ans = ab

回到ipython:

In [304]: d = io.loadmat('test.mat')
In [305]: d
Out[305]: 
{'__header__': b'MATLAB 5.0 MAT-file Platform: posix, Created on: Wed Jun  6 15:36:23 2018',
 '__version__': '1.0',
 '__globals__': [],
 'astruct': array([[(array([[0]]), array([[0, 1, 2]]), array([[1]])),
         (array([[1]]), array([[3, 4, 5]]), array([[0, 1, 2, 3, 4]])),
         (array([[2]]), array([[6, 7, 8]]), array([[1, 1, 1],
        [1, 1, 1]])),
         (array([[3]]), array([[ 9, 10, 11]]), array(['astring'], dtype='<U7')),
         (array([[4]]), array([[12, 13, 14]]), array([['a', 'b']], dtype='<U1'))]],
       dtype=[('key1', 'O'), ('key2', 'O'), ('key3', 'O')])}

因此，虽然创建了一个具有 int 和 int(3) 等 dtype 的 numpy 结构化数组，但加载的数组具有所有字段的 object dtype。 loadmat 大量使用对象 dtype 数组来处理 MATLAB 单元和结构的一般性。 loadmat 有各种加载参数，我们可以玩弄。

这只是基于之前加载 MATLAB 文件的经验的猜测。如果这不是您想要的，我建议在 MATLAB 中构建示例数据，保存它，然后加载以查看 loadmat 是如何构建它的。您可能需要来回多次才能解决错误。

Answer 2

根据 hpaulj 提供的方向，我开发了以下函数，该函数从对象列表创建结构。

    def listobj2struct(list_in):
    """Converts a list of objects to a structured array.

    Parameters
    ----------
    list_in: list
        List of objects

    Returns
    -------
    struct: np.array
        Structured array
    """

    # Create data type for each variable in object
    keys = list(vars(list_in[0]).keys())
    data_type = []
    for key in keys:
        data_type.append((key, list))

    # Create structured array based on data type and length of list
    dt = np.dtype(data_type)
    struct = np.zeros((len(list_in),), dt)

    # Populate the structure with data from the objects
    for n, item in enumerate(list_in):
        new_dict = vars(item)
        for key in new_dict:
            struct[key][n] = new_dict[key]

    return struct

为了完成从复杂的对象嵌套创建 Matlab 文件所需的工作，我还编写了以下函数。也许这会帮助其他面临类似任务的人。可能有更好的方法，但这对我有用。

    def obj2dict(obj):
    """Converts object variables to dictionaries. Works recursively to all levels of objects.

    Parameters
    ----------
    obj: object
        Object of some class

    Returns
    -------
    obj_dict: dict
        Dictionary of all object variables
    """

    obj_dict = vars(obj)
    for key in obj_dict:
        # Clean out NoneTypes
        if obj_dict[key] is None:
            obj_dict[key] = []
        # If variable is another object convert to dictionary recursively
        elif str(type(obj_dict[key]))[8:13] == 'Class':
            obj_dict[key]=obj2dict(obj_dict[key])

    return obj_dict


def listobj2dict(list_in):
    """Converts list of objects to list of dictionaries. Works recursively to all levels of objects.

    Parameters
    ----------
    obj: object
        Object of some class

    Returns
    -------
    new_list: list
        List of dictionaries
    """
    new_list = []
    for obj in list_in:
        new_list.append(obj2dict(obj))
    return new_list


def listdict2struct(list_in):
    """Converts a list of dictionaries to a structured array.

    Parameters
    ----------
    list_in: list
        List of dictionaries

    Returns
    -------
    struct: np.array
        Structured array
    """

    # Create data type for each variable in object
    keys = list(list_in[0].keys())
    data_type = []
    for key in keys:
        data_type.append((key, list))

    # Create structured array based on data type and length of list
    dt = np.dtype(data_type)
    struct = np.zeros((len(list_in),), dt)

    # Populate the structure with data from the objects
    for n, item in enumerate(list_in):
        new_dict = item
        for key in new_dict:
            struct[key][n] = new_dict[key]

    return struct