Is it possible to read binary MATLAB .mat files in Python?
I\'ve seen that SciPy has alleged support for reading .mat files, but I\'m unsuccessful with it. I install
Neither scipy.io.savemat
, nor scipy.io.loadmat
work for MATLAB arrays version 7.3. But the good part is that MATLAB version 7.3 files are hdf5 datasets. So they can be read using a number of tools, including NumPy.
For Python, you will need the h5py
extension, which requires HDF5 on your system.
import numpy as np
import h5py
f = h5py.File('somefile.mat','r')
data = f.get('data/variable1')
data = np.array(data) # For converting to a NumPy array
An import is required, import scipy.io
...
import scipy.io
mat = scipy.io.loadmat('file.mat')
Reading the file
import scipy.io
mat = scipy.io.loadmat(file_name)
Inspecting the type of MAT variable
print(type(mat))
#OUTPUT - <class 'dict'>
The keys inside the dictionary are MATLAB variables, and the values are the objects assigned to those variables.
There is also the MATLAB Engine for Python by MathWorks itself. If you have MATLAB, this might be worth considering (I haven't tried it myself but it has a lot more functionality than just reading MATLAB files). However, I don't know if it is allowed to distribute it to other users (it is probably not a problem if those persons have MATLAB. Otherwise, maybe NumPy is the right way to go?).
Also, if you want to do all the basics yourself, MathWorks provides (if the link changes, try to google for matfile_format.pdf
or its title MAT-FILE Format
) a detailed documentation on the structure of the file format. It's not as complicated as I personally thought, but obviously, this is not the easiest way to go. It also depends on how many features of the .mat
-files you want to support.
I've written a "small" (about 700 lines) Python script which can read some basic .mat
-files. I'm neither a Python expert nor a beginner and it took me about two days to write it (using the MathWorks documentation linked above). I've learned a lot of new stuff and it was quite fun (most of the time). As I've written the Python script at work, I'm afraid I cannot publish it... But I can give some advice here:
.mat
-file you want to parse.miCOMPRESSED
, miMATRIX
, mxDOUBLE
, or miINT32
).mat
-files' structure is optimal for saving the data elements in a tree data structure; each node has one class and subnodesThere is a nice package called mat4py which can easily be installed using
pip install mat4py
It is straightforward to use (from the website):
Load data from a MAT-file
The function loadmat
loads all variables stored in the MAT-file into a simple Python data structure, using only Python’s dict
and list
objects. Numeric and cell arrays are converted to row-ordered nested lists. Arrays are squeezed to eliminate arrays with only one element. The resulting data structure is composed of simple types that are compatible with the JSON format.
Example: Load a MAT-file into a Python data structure:
from mat4py import loadmat
data = loadmat('datafile.mat')
The variable data
is a dict
with the variables and values contained in the MAT-file.
Save a Python data structure to a MAT-file
Python data can be saved to a MAT-file, with the function savemat
. Data has to be structured in the same way as for loadmat
, i.e. it should be composed of simple data types, like dict
, list
, str
, int
, and float
.
Example: Save a Python data structure to a MAT-file:
from mat4py import savemat
savemat('datafile.mat', data)
The parameter data
shall be a dict
with the variables.
Having MATLAB 2014b or newer installed, the MATLAB engine for Python could be used:
import matlab.engine
eng = matlab.engine.start_matlab()
content = eng.load("example.mat", nargout=1)