CODEWITHSUNDEEP
pythonnumpy
rnt_42
rnt_42

Reputation: 106

Load many files into one array - Python

So, I have to load many .mat files with some features to plot it.

Each array to be plotted is loaded into a dictionary:

import numpy as np
import scipy.io as io


dict1 = io.loadmat('file1.MAT')
dict2 = io.loadmat('file2.MAT')  # type = dict
dict3 = io.loadmat('file3.MAT')
...

so I have to take the dictionarie's element I need, to plot after:

array1 = dict1['data']
array2 = dict2['data']
array3 = dict3['data']
...

After this, I can plot the data. It works, but looks dumb to me (If I have 100 vectors, it will take some time...). Is there a better way to make this task?

Upvotes: 0

Views: 328

Answers (1)

aghast
aghast

Reputation: 15300

Given that you are talking about dealing with many matrices, you should manage them as a collection. First, let's define your set of files. It could be a tuple, or a list:

Matrix_files = [ 'fileA.MAT', 'file1.MAT', 'no pattern to these names.MAT' ]

If they happen to have a pattern, you might try generating the names:

Matrix_files = [ 'file{}.MAT'.format(num) for num in range(1,4) ]

If they share a common location, you might consider using one of the various directory scanning approaches (opendir or glob, to name two).

Once you have a list of filenames, you can read the dictionaries in:

def read_matrix(filespec):
    from scipy.io import loadmat
    md = loadmat(filespec)
    # process md
    return md

With that, you can either get all the data, or get some of the data:

All_data = [read_matrix(f) for f in Matrix_files]

Some_data = [read_matrix(f)['data'] for f in Matrix_files]

If you only care about the data, you could skip the function definition:

from scipy.io import loadmat
Just_data = [loadmat(f)['data'] for f in Matrix_files]

Upvotes: 4

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