To efficiently read MATLAB .mat
files in Python, pymatreader
simplifies the process by returning data as a nested dictionary, akin to scipy.io.loadmat
style.
import pymatreader
# Specify the path to your .mat file
filename = 'path/to/your/file.mat'
# Read the .mat file
data = pymatreader.read_mat(filename)
# Now 'data' contains the structured information from the .mat file
- filename (str): Path and filename of the
.mat
file containing the data. - variable_names (list of strings, optional): Specify to read only data from certain keys or variable names.
- ignore_fields (list of strings, optional): Exclude specific keys or variable names from the structure (works for
.mat
files v7.3). - uint16_codec (str | None, optional): Specify codec (e.g., 'latin1', 'utf-8') for character arrays with non-ASCII characters.
The function returns a dictionary representing the structure of the .mat
file:
- Keys: Variable names.
- Values: Corresponding data.
Consider a .mat
file example.mat
with variables var1
, var2
, and var3
. To load only var2
from this file:
data = pymatreader.read_mat('example.mat', variable_names=['var2'])
This loads only var2
into the data
dictionary.
For additional details, consult the pymatreader documentation.
Alternatively, you can use scipy.io.loadmat
to read .mat
files, which returns a dictionary-like object:
from scipy.io import loadmat
# Load .mat file
mat_data = loadmat('example.mat')
# Access variables
var1 = mat_data['var1']
var2 = mat_data['var2']
This approach loads all variables into a dictionary-like object mat_data
, where each key is a variable name.
This markdown note provides comprehensive guidance for your team on reading MATLAB files in Python using pymatreader
and scipy.io.loadmat
.