python读取matlab_MATLAB to Python读取

What I am basically trying to do is convert from some MATLAB code to Python:

The MATLAB code:

for time = 100:model_times

for i = 1:5

indat = fread(fid,[48,40],'real*4');

vort(:,:,i,time) = indat';

end

end

fid holds the file path (a DAT file) is being used. vort is a preallocated as: vort = zeros(40,48,5,model_times). model_times is a fixed integer (e.g. 100).

What seems to be happening is that the .dat file data is being read in as a 48x40 matrix, then inserted into the preallocated array vort, at a fixed i and time (the loop counters).

I have attempted this in Python:

for time in range(model_times):

for i in range(5):

vort[:,:,i,time] = np.fromfile(fid,np.float64)

I receive an error that says, "ValueError: operands could not be broadcast together with shapes (40,48) (6048000)". The error occurs on the last line of Python code above. I have also tried adding .reshape((40,48,5,model_times)) to the line with the error, but receive another error that says "ValueError: total size of new array must be unchanged."

So my question is, what is the Python equivalent to MATLAB's "fread", that can handle multidimensional arrays?

On a scale from 1 to 10, with 1 being a total beginner and 10 being a seasoned veteran, I'm about a 4.

解决方案

This should work too. No reason you can't do it all in a single read:

vort = np.fromfile(fid, np.float64).reshape((model_times,5,48,40)).transpose()

You have to be careful to reshape the 1-D array into the native order of the array indices in the file (model_times,5,48,40), then use transpose to reorder the indices to what you want (40,48,5,model_times). If you tried to reshape directly to the latter, you'd get data in the wrong places.