95 lines
2.3 KiB
Markdown
95 lines
2.3 KiB
Markdown
|
# Numpy: Dealing with Matlab files
|
|||
|
|
{:.no_toc}
|
|||
|
|
|
|||
|
|
<nav markdown="1" class="toc-class">
|
|||
|
|
* TOC
|
|||
|
|
{:toc}
|
|||
|
|
</nav>
|
|||
|
|
|
|||
|
|
## The goal
|
|||
|
|
We want to read and write Matlab files under Python.
|
|||
|
|
|
|||
|
|
Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
|
|||
|
|
|
|||
|
|
Reminder: Learning Python as Matlab user
|
|||
|
|
Please read [NumPy for MATLAB users](https://numpy.org/doc/stable/user/numpy-for-matlab-users.html)
|
|||
|
|
|
|||
|
|
## Mat files under Python
|
|||
|
|
|
|||
|
|
### MATLAB <= 7.2 format mat files
|
|||
|
|
|
|||
|
|
This is a job for [scipy.io](https://docs.scipy.org/doc/scipy/reference/io.html#module-scipy.io)
|
|||
|
|
|
|||
|
|
| | |
|
|||
|
|
| ------------- |-------------|
|
|||
|
|
|[loadmat](https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.loadmat.html#scipy.io.loadmat)(file_name[, mdict, appendmat])| Load MATLAB file. |
|
|||
|
|
|[savemat](https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.savemat.html#scipy.io.savemat)(file_name, mdict[, appendmat, …])| Save a dictionary of names and arrays into a MATLAB-style .mat file. |
|
|||
|
|
|[whosmat](https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.whosmat.html#scipy.io.whosmat)(file_name[, appendmat])| List variables inside a MATLAB file. |
|
|||
|
|
|
|||
|
|
#### Read
|
|||
|
|
Under Matlab we create a test file
|
|||
|
|
|
|||
|
|
```matlab
|
|||
|
|
>> A = rand(10,100);
|
|||
|
|
>> save -v7 Test_1.mat A
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
Under Python we look into the file for information:
|
|||
|
|
```python
|
|||
|
|
import scipy.io as sio
|
|||
|
|
|
|||
|
|
Info = sio.whosmat("Test_1.mat")
|
|||
|
|
print(Info) # --> [('A', (10, 100), 'double')]
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
And we can read the data:
|
|||
|
|
|
|||
|
|
```python
|
|||
|
|
import numpy as np
|
|||
|
|
import scipy.io as sio
|
|||
|
|
|
|||
|
|
mat_data = sio.loadmat("Test_1.mat")
|
|||
|
|
|
|||
|
|
print(
|
|||
|
|
mat_data.keys()
|
|||
|
|
) # -> dict_keys(['__header__', '__version__', '__globals__', 'A'])
|
|||
|
|
|
|||
|
|
a = mat_data["A"]
|
|||
|
|
print(type(a)) # --> <class 'numpy.ndarray'>
|
|||
|
|
print(a.dtype) # --> float64
|
|||
|
|
print(a.shape) # --> (10, 100)
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
#### Write
|
|||
|
|
|
|||
|
|
Under Python we generate a .mat file:
|
|||
|
|
|
|||
|
|
```python
|
|||
|
|
import numpy as np
|
|||
|
|
import scipy.io as sio
|
|||
|
|
|
|||
|
|
myrng = np.random.default_rng()
|
|||
|
|
|
|||
|
|
A: np.ndarray = myrng.random((10, 100), dtype=np.float64)
|
|||
|
|
B: str = "Hellp world!"
|
|||
|
|
mdic = {"A": A, "ImportantMessage": B}
|
|||
|
|
sio.savemat("Test_2.mat", mdic)
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
And read it in under Matlab:
|
|||
|
|
|
|||
|
|
```matlab
|
|||
|
|
>> load Test_2.mat
|
|||
|
|
>> whos
|
|||
|
|
Name Size Bytes Class Attributes
|
|||
|
|
|
|||
|
|
A 10x100 8000 double
|
|||
|
|
ImportantMessage 1x12 24 char
|
|||
|
|
|
|||
|
|
>> ImportantMessage
|
|||
|
|
|
|||
|
|
ImportantMessage =
|
|||
|
|
|
|||
|
|
'Hellp world!'
|
|||
|
|
```
|