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Load script utilitiesΒΆ
Load script for recovering python dictionaries from mat files
import scipy
import scipy.io as spio
import numpy as np
def loadmat(filename):
'''
this function should be called instead of direct spio.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
'''
def _check_keys(d):
'''
checks if entries in dictionary are mat-objects. If yes
todict is called to change them to nested dictionaries
'''
for key in d:
if isinstance(d[key], spio.matlab.mio5_params.mat_struct):
d[key] = _todict(d[key])
return d
def _todict(matobj):
'''
A recursive function which constructs from matobjects nested dictionaries
'''
d = {}
for strg in matobj._fieldnames:
elem = matobj.__dict__[strg]
if isinstance(elem, spio.matlab.mio5_params.mat_struct):
d[strg] = _todict(elem)
elif isinstance(elem, np.ndarray):
d[strg] = _tolist(elem)
else:
d[strg] = elem
return d
def _tolist(ndarray):
'''
A recursive function which constructs lists from cellarrays
(which are loaded as numpy ndarrays), recursing into the elements
if they contain matobjects.
'''
elem_list = []
for sub_elem in ndarray:
if isinstance(sub_elem, spio.matlab.mio5_params.mat_struct):
elem_list.append(_todict(sub_elem))
elif isinstance(sub_elem, np.ndarray):
elem_list.append(_tolist(sub_elem))
else:
elem_list.append(sub_elem)
return elem_list
data = scipy.io.loadmat(filename, struct_as_record=False, squeeze_me=True)
return _check_keys(data)
#train = loadmat('multi1')
#print(train)
Total running time of the script: ( 0 minutes 0.000 seconds)