Skip to main content

Load MATLAB .mat 7.3 into Python native data types (via h5/hd5/hdf5/h5py)

Project description

Python package pypi Version

mat 7.3

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

Quickstart

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

Installation

To install, run:

pip install mat73

Alternatively for most recent version:

pip install git+https://github.com/skjerns/mat7.3

Datatypes

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
Other (ie Datetime, ...) Not supported

Short-comings

  • This library will only load mat 7.3 files. For older versions use scipy.io.loadmat
  • Proprietary MATLAB types (e.g datetime, duriation, etc) are not supported. If someone tells me how to convert them, I'll implement that
  • For now, you can't save anything back to the .mat. It's a bit more difficult than expected, so it's not on the roadmap for now
  • See also hdf5storage, which can indeed be used for saving .mat, but has less features for loading

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mat73-0.59.tar.gz (18.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mat73-0.59-py3-none-any.whl (19.0 kB view details)

Uploaded Python 3

File details

Details for the file mat73-0.59.tar.gz.

File metadata

  • Download URL: mat73-0.59.tar.gz
  • Upload date:
  • Size: 18.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.9.12

File hashes

Hashes for mat73-0.59.tar.gz
Algorithm Hash digest
SHA256 e48e8600ebcb378713f39b32685704090f497ddca4dc9305f109e452568d8a26
MD5 0cfd9e44299d81f88bddb73c4fccd64f
BLAKE2b-256 0987a444eab1d9aee2be2cc2c11bfa3cb9e53c1b2851ac746bd407aaec9689aa

See more details on using hashes here.

File details

Details for the file mat73-0.59-py3-none-any.whl.

File metadata

  • Download URL: mat73-0.59-py3-none-any.whl
  • Upload date:
  • Size: 19.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.9.12

File hashes

Hashes for mat73-0.59-py3-none-any.whl
Algorithm Hash digest
SHA256 1856cf8b251c19cca7e1cd8ebb7cb5748e95bf4dddf777b46ec244ffea54c8c7
MD5 7714b785a07eb713a6b6666bc4a68852
BLAKE2b-256 fdb2ff48f85271fccd19613acbe4b134db3c31e43caf53bff287a6f722fbb866

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page