Python (and C) organizes the data arrays in row major order. ![]() I was having the same issues, until I found this wikipedia article: row- and column-major order So, is there a way to fix this?Īnd maybe you know the correct way of operating with multidimensional arrays in Matlab -> python, like should I get the same SVD for arrays like arange(1, 13).reshape(3, 4) and in Matlab 1:12 -> reshape(_, ) or what is the correct way to work with that? Maybe I can swap axes somehow in python to get the same results as in Matlab? Or change the order of axes in reshape(x1, x2, x3.) in Python? In Matlab for A = 1:27 reshaped to and then to it seems that I get another array: 1 4 7 10 13 16 19 22 25Īnd SVD in Matlab and Python gives different results. If I perform A.reshape(3, 9, order='F') I get For example, if A is an array from 1 to 27 in python array(, But when I work with 3D data I noticed that it does not work. ![]() I'm a little bit confused since it seems that it's enough to use order='F' in python reshape(). A point here that shapes and indexes are really important since it works with tensors. I have a code in Matlab which I need to translate in Python.
0 Comments
Leave a Reply. |