Turn polar input into .mat files (can be read using hdf5)?

[jellepoland]

You can add dicts inside .mat, which will point towards each 4D polar.
Stick with 7.3 version

from scipy.io import savemat
import numpy as np

def save_multiple_arrays_to_mat(arrays, filename='combined_data.mat'):
    """
    Save multiple numpy arrays to a single .mat file
    
    Parameters:
    arrays : list of numpy.ndarray
        List containing all the arrays to save
    filename : str
        The name of the output .mat file
    """
    # Create a dictionary to store all arrays
    data_dict = {}
    
    # Add each array to the dictionary with a unique key
    for i, array in enumerate(arrays):
        data_dict[f'array_{i+1}'] = array
    
    # Save the dictionary to a .mat file
    savemat(filename, data_dict)
    print(f"Successfully saved {len(arrays)} arrays to {filename}")

# Example usage:
# Create 30 sample arrays (4 columns × 40 rows each)
sample_arrays = [np.random.rand(40, 4) for _ in range(30)]

# Save all arrays to a single .mat file
save_multiple_arrays_to_mat(sample_arrays, 'multiple_arrays.mat')

If your arrays have specific names or meanings, you can customize the keys in the dictionary:

# If you have meaningful names for your arrays
array_names = [f'airfoil_{i+1}' for i in range(30)]  # Or any custom names

data_dict = {}
for name, array in zip(array_names, arrays):
    data_dict[name] = array

savemat('named_arrays.mat', data_dict)

You can also organize them into a cell array structure similar to how MATLAB might handle it:

# For a MATLAB-like cell array structure
data_dict = {'all_arrays': np.array(arrays, dtype=object)}
savemat('matlab_cell_arrays.mat', data_dict)