如何在Matlab数据结构中使用多维数组从Python创建Matlab文件？
我正在尝试从Python创建一个Matlab文件（*.mat），该文件包含如下所示的Matlab数据结构：如何在Matlab数据结构中使用多维数组从Python创建Matlab文件？,python,matlab,numpy,Python,Matlab,Numpy,我正在尝试从Python创建一个Matlab文件（*.mat），该文件包含如下所示的Matlab数据结构： 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输出是一个单元数组，而不是Matlab数据结构 我试过使用 np.core.records
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
np.core.records.fromarrays(data_list, names=q_keys)
谢谢这是一个尝试：
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})
ipythonIn [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')])}
：d=io.loadmat（'test.mat'））
In[305]：d
Out[305]：
{“头文件”：b'MATLAB 5.0 MAT文件平台：posix，创建日期：Wed Jun 6 15:36:23 2018'，
“\uuuuu版本：”1.0“，
“\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu，
'astruct'：数组（[[（数组（[[0]]）、数组（[[0,1,2]]）、数组（[[1]]），
（数组（[[1]]），数组（[[3,4,5]]），数组（[[0,1,2,3,4]]），
（数组（[[2]]）、数组（[[6,7,8]]）、数组（[[1,1,1]]，
[1, 1, 1]])),
（array（[[3]]）、array（[[9,10,11]]）、array（['astring']）、dtype='根据hpaulj提供的指导，我开发了以下函数，该函数从对象列表创建了一个结构
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中创建Matlab文件所需的工作，我还编写了以下函数。也许这将帮助其他面临类似任务的人。可能有更好的方法，但这对我很有用
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
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