reading HDF5-format MATLAB file in python with h5py

Question

I am trying to read a HDF5-format MATLAB file in python, using the h5py library. This file is called "Q_visSDF_accurate.mat" and has two keys: "filename" and "sdf". "filename contains a cell array strings. "sdf" is a [6001, 49380] matrix containing floats. I had no problem to extract the variable sdf using the following code:

import h5py
data = h5py.File("Q_visSDF_accurate.mat", 'r')
sdf = data.get("sdf")[:,:]
sdf = sdf.astype(float)

However, I cant read the filename variable. I tried:

filename = data.get("filename")[0]

but the code returns:

array([<HDF5 object reference>, <HDF5 object reference>,
   <HDF5 object reference>, ..., <HDF5 object reference>,
   <HDF5 object reference>, <HDF5 object reference>], dtype=object)

I can I de-reference the containt of the filename variable? Using the hdf5storage package is not a solution, as it works only for python 32 bits and can only read a subset of matlab variables.

Have you tried using hdf5storage? It can read hdf5-based .mat files into a more usable form. — TheBlackCat
– TheBlackCat, Commented Dec 8, 2016 at 1:31
did you manage to solve this? I'm still stuck with your exact problem — raaj
– raaj, Commented Mar 11, 2018 at 5:39

hpaulj · Accepted Answer · 2017-03-29 17:06:50Z

In Octave I created a file with cell and matrix

>> xmat = [1,2,3;4,5,6;7,8,9];
>> xcell = {1,2,3;4,5,6;7,8,9};
>> save -hdf5 testmat.h5 xmat xcell

In ipython with h5py, I find that this file contains 2 groups

In [283]: F = h5py.File('../testmat.h5','r')
In [284]: list(F.keys())
Out[284]: ['xcell', 'xmat']

The matrix group has a type and value dataset:

In [285]: F['xmat']
Out[285]: <HDF5 group "/xmat" (2 members)>
In [286]: list(F['xmat'].keys())
Out[286]: ['type', 'value']
In [287]: F['xmat']['type']
Out[287]: <HDF5 dataset "type": shape (), type "|S7">
In [288]: F['xmat']['value']
Out[288]: <HDF5 dataset "value": shape (3, 3), type "<f8">
In [289]: F['xmat']['value'][:]
Out[289]: 
array([[ 1.,  4.,  7.],
       [ 2.,  5.,  8.],
       [ 3.,  6.,  9.]])

The cell has the same type and value, but value is another group:

In [291]: F['xcell']['type']
Out[291]: <HDF5 dataset "type": shape (), type "|S5">
In [292]: F['xcell']['value']
Out[292]: <HDF5 group "/xcell/value" (10 members)>

In [294]: list(F['xcell']['value'].keys())
Out[294]: ['_0', '_1', '_2', '_3', '_4', '_5', '_6', '_7', '_8', 'dims']
...
In [296]: F['xcell']['value']['dims'][:]
Out[296]: array([3, 3])

I had to use the [...] to fetch the value of a cell, since it is a 0d array:

In [301]: F['xcell']['value']['_0']['value'][...]
Out[301]: array(1.0)

To really replicate the question I should have created string cells values, but I think this illustrates well enough how a cells are stored - as named datasets within a data group.

I'm assuming the Octave h5 storage is compatible with MATLAB's.

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