Reputation: 801
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
Upvotes: 12
Views: 37771
Reputation: 377
this will return the mat structure as a dictionary
def _check_keys( dict):
"""
checks if entries in dictionary are mat-objects. If yes
todict is called to change them to nested dictionaries
"""
for key in dict:
if isinstance(dict[key], sio.matlab.mio5_params.mat_struct):
dict[key] = _todict(dict[key])
return dict
def _todict(matobj):
"""
A recursive function which constructs from matobjects nested dictionaries
"""
dict = {}
for strg in matobj._fieldnames:
elem = matobj.__dict__[strg]
if isinstance(elem, sio.matlab.mio5_params.mat_struct):
dict[strg] = _todict(elem)
else:
dict[strg] = elem
return dict
def loadmat(filename):
"""
this function should be called instead of direct scipy.io .loadmat
as it cures the problem of not properly recovering python dictionaries
from mat files. It calls the function check keys to cure all entries
which are still mat-objects
"""
data = sio.loadmat(filename, struct_as_record=False, squeeze_me=True)
return _check_keys(data)
Upvotes: 4
Reputation: 1055
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')
Upvotes: 5
Reputation: 571
(!) 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)
Upvotes: 0
Reputation: 801
Found this tutorial about matlab struct and python
http://docs.scipy.org/doc/scipy/reference/tutorial/io.html
Upvotes: 13