Load MATLAB .mat 7.3 into Python native data types (via h5/hd5/hdf5/h5py)
Load MATLAB 7.3 .mat files into Python.
Starting with MATLAB 7.3, .mat
files have been changed to store as custom hdf5
files.
This means they cannot be loaded by scipy.io.loadmat
any longer and raise.
NotImplementedError: Please use HDF reader for matlab v7.3 files
This library loads MATLAB 7.3 HDF5 files into a Python dictionary.
import mat73
data_dict = mat73.loadmat('data.mat')
As easy as that!
By enabling use_attrdict=True
you can even access sub-entries of structs
as attributes, just like in MATLAB:
data_dict = mat73.loadmat('data.mat', use_attrdict=True)
struct = data_dict['structure'] # assuming a structure was saved in the .mat
struct[0].var1 == struct[0]['var1'] # it's the same!
You can also specifiy to only load a specific variable or variable tree, useful to reduce loading times
data_dict = mat73.loadmat('data.mat', only_include='structure')
struct = data_dict['structure'] # now only structure is loaded and nothing else
data_dict = mat73.loadmat('data.mat', only_include=['var/subvar/subsubvar', 'tree1/'])
tree1 = data_dict['tree1'] # the entire tree has been loaded, so tree1 is a dict with all subvars of tree1
subsubvar = data_dict['var']['subvar']['subsubvar'] # this subvar has been loaded
To install, run:
pip install mat73
Alternatively for most recent version:
pip install git+https://github.com/skjerns/mat7.3
The following MATLAB datatypes can be loaded
MATLAB | Python |
---|---|
logical | np.bool_ |
single | np.float32 |
double | np.float64 |
int8/16/32/64 | np.int8/16/32/64 |
uint8/16/32/64 | np.uint8/16/32/64 |
complex | np.complex128 |
char | str |
struct | list of dicts |
cell | list of lists |
canonical empty | [] |
missing | None |
sparse | scipy.sparse.csc |
Other (ie Datetime, ...) | Not supported |
scipy.io.loadmat
datetime
, duriation
, etc) are not supported. If someone tells me how to convert them, I'll implement that