I saved a cell array as a .mat file in Matlab as follows:
test = {'hello'; 'world!'};
save('data.mat', 'test', '-v7.3')
How can I import it as the list of strings in Python with H5py?
I tried
f = h5py.File('data.mat', 'r')
print f.get('test')
print f.get('test')[0]
This prints out:
<HDF5 dataset "test": shape (1, 2), type "|O8">
[<HDF5 object reference> <HDF5 object reference>]
How can I dereference it to get the list of strings ['hello', 'world!'] in Python?
Writing in Matlab:
test = {'Hello', 'world!'; 'Good', 'morning'; 'See', 'you!'};
save('data.mat', 'test', '-v7.3') % v7.3 so that it is readable by h5py
Reading in Python (works for any number or rows or columns, but assumes that each cell is a string):
import h5py
import numpy as np
data = []
with h5py.File("data.mat") as f:
for column in f['test']:
row_data = []
for row_number in range(len(column)):
row_data.append(''.join(map(unichr, f[column[row_number]][:])))
data.append(row_data)
print data
print np.transpose(data)
Output:
[[u'Hello', u'Good', u'See'], [u'world!', u'morning', u'you!']]
[[u'Hello' u'world!']
[u'Good' u'morning']
[u'See' u'you!']]
This answer should be seen as an addition to Franck Dernoncourt's answer, which totally suffices for all cell arrays that contain 'flat' data (for mat files of version 7.3 and probably above).
I encountered a case where I had nested data (e.g. 1 row of cell arrays inside a named cell array). I managed to get my hands on the data by doing the following:
# assumption:
# idx_of_interest specifies the index of the cell array we are interested in
# (at the second level)
with h5py.File(file_name) as f:
data_of_interest_reference = f['cell_array_name'][idx_of_interest, 0]
data_of_interest = f[data_of_interest_reference]
Reason this works for nested data: If you look at the type of the dataset you want to retrieve at a deeper level, it says 'h5py.h5r.Reference'. In order to actually retrieve the data the reference points to, you need to provide that reference to the file object.
I know this is an old question. But I found a package to scratch that itch:
It can be installed by pip and works nicely on python 3.6 for both pre and post 7.3 matlab files. For older files it calls scipy.io.loadmat according to the docs.
