Hi, With some further work, I found that the file produced by SciPy isn't actually correct. Matlab can read it but at some point in the array the rest of the data is just zeros. I'm surprised that SciPy doesn't throw an error when writing data that is too big... Are there any good alternatives to .mat files? (Preferably something that Matlab could read too.) PyTables? The data consists of one large array (around 9GB), one list containing a few smaller arrays, and a few other arrays and scalars. Thanks, Michal

Hi,

...

Hi,

On Mon, Aug 19, 2013 at 7:44 AM, Michal Romaniuk <michal.romaniuk06@imperial.ac.uk> wrote:

...

Hi,

I'm saving a large batch of data using savemat and although I get no errors, the files produced are not readable for either matlab or scipy. Is there a limit on file size?

Ah - yes there is - the individual matrices in the mat file cannot be larger than 4GB. Is it possible you hit this limit?

Sorry, I only realized this when Richard Llewellyn pointed this out a couple of weeks ago on the list:

http://scipy-user.10969.n7.nabble.com/SciPy-User-scipy-io-loadmat-throws-Typ...

The current scipy code has an error message for matrices that are too large.

Cheers,

Matthew

Well, I managed to work around the problem to some extent by setting do_compression=True. Now Matlab can read those files (so they must be valid to some extent) but SciPy can't (even though they were written with SciPy).

I get this error:

PATH/lib/python2.6/site-packages/scipy/io/matlab/mio.pyc in loadmat(file_name, mdict, appendmat, **kwargs) 173 variable_names = kwargs.pop('variable_names', None) 174 MR = mat_reader_factory(file_name, appendmat, **kwargs) --> 175 matfile_dict = MR.get_variables(variable_names) 176 if mdict is not None: 177 mdict.update(matfile_dict)

PATH/lib/python2.6/site-packages/scipy/io/matlab/mio5.pyc in get_variables(self, variable_names) 290 continue 291 try: --> 292 res = self.read_var_array(hdr, process) 293 except MatReadError, err: 294 warnings.warn(

PATH/lib/python2.6/site-packages/scipy/io/matlab/mio5.pyc in read_var_array(self, header, process) 253 `process`. 254 ''' --> 255 return self._matrix_reader.array_from_header(header, process) 256 257 def get_variables(self, variable_names=None):

PATH/lib/python2.6/site-packages/scipy/io/matlab/mio5_utils.so in scipy.io.matlab.mio5_utils.VarReader5.array_from_header (scipy/io/matlab/mio5_utils.c:5401)()

PATH/lib/python2.6/site-packages/scipy/io/matlab/mio5_utils.so in scipy.io.matlab.mio5_utils.VarReader5.array_from_header (scipy/io/matlab/mio5_utils.c:4849)()

PATH/lib/python2.6/site-packages/scipy/io/matlab/mio5_utils.so in scipy.io.matlab.mio5_utils.VarReader5.read_real_complex (scipy/io/matlab/mio5_utils.c:5602)()

ValueError: total size of new array must be unchanged

The size of the main array is about 9 GB before compression, but the compressed files are less than 500 MB and closer to 400 MB. There are some other arrays in the file too but they are much smaller.

Any ideas on how I could get SciPy to read this data back? Right now I can only think of storing the data in single precision format...

Thanks, Michal