How to preserve matlab struct when accessing in python?

Question

I have a mat-file that I accessed using

from scipy import io
mat = io.loadmat('example.mat')

From matlab, example.mat contains the following struct

    >> load example.mat
    >> data1

    data1 =

            LAT: [53x1 double]
            LON: [53x1 double]
            TIME: [53x1 double]
            units: {3x1 cell}


    >> data2

    data2 = 

            LAT: [100x1 double]
            LON: [100x1 double]
            TIME: [100x1 double]
            units: {3x1 cell}

In matlab, I can access data as easy as data2.LON, etc.. It's not as trivial in python. It give me several option though like

mat.clear       mat.get         mat.iteritems   mat.keys        mat.setdefault  mat.viewitems   
mat.copy        mat.has_key     mat.iterkeys    mat.pop         mat.update      mat.viewkeys    
mat.fromkeys    mat.items       mat.itervalues  mat.popitem     mat.values      mat.viewvalues    

Is is possible to preserve the same structure in python? If not, how to best access the data? The present python code that I am using is very difficult to work with.

Thanks

Answer 1

Found this tutorial about matlab struct and python

http://docs.scipy.org/doc/scipy/reference/tutorial/io.html

Answer 2

When I need to load data into Python from MATLAB that is stored in an array of structs {strut_1,struct_2} I extract a list of keys and values from the object that I load with scipy.io.loadmat. I can then assemble these into there own variables, or if needed, repackage them into a dictionary. The use of the exec command may not be appropriate in all cases, but if you are just trying to processes data it works well.

# Load the data into Python     
D= sio.loadmat('data.mat')

# build a list of keys and values for each entry in the structure
vals = D['results'][0,0] #<-- set the array you want to access. 
keys = D['results'][0,0].dtype.descr

# Assemble the keys and values into variables with the same name as that used in MATLAB
for i in range(len(keys)):
    key = keys[i][0]
    val = np.squeeze(vals[key][0][0])  # squeeze is used to covert matlat (1,n) arrays into numpy (1,) arrays. 
    exec(key + '=val')

Answer 3

(!) In case of nested structures saved in *.mat files, is necessary to check if the items in the dictionary that io.loadmat outputs are Matlab structures. For example if in Matlab

>> thisStruct

ans =
      var1: [1x1 struct]
      var2: 3.5

>> thisStruct.var1

ans =
      subvar1: [1x100 double]
      subvar2: [32x233 double]

Then use the code by mergen in scipy.io.loadmat nested structures (i.e. dictionaries)