CODEWITHSUNDEEP
pythonmatlabmatrix
Wallace and Gromit
Wallace and Gromit

Reputation: 59

Lists in Python vs vectors and matrices in Matlab

Coming from Matlab I am unable to even think of singular datapoints / variables. Anything I deal with is a matrix / array. After one week of searching and insuccesful trial and error I realise, that I ABSOLUTELY do NOT get the concept of dealing with matrices in (plain) Python.

I created

In[]: A = [[1,2,3], [9,8,7], [5,5,5]]
In[]: A
Out[]: [[1, 2, 3], [9, 8, 7], [5, 5, 5]]

Trying to extract the vectors in the matrix along the two dimensions: 

In[]: A[:][1]
Out[]: [9, 8, 7]
In[]: A[1][:]
Out[]: [9, 8, 7]

'surprisingly' gives the same! No way to get a specific column (of course, except with one by one iteration).

Consequently, I am unable to manage merging matrix A with another vector, i.e. extending A with another column. Matlab style approach obviously is odd:

In[]: B = A, [4,6,8]
In[]: B
Out[]: ([[1, 2, 3], [9, 8, 7], [5, 5, 5]], [4, 6, 8])

Results in something nested, not an extension of A. Same for 

B = [A, [4,6,8]]

Ok, more Python-like:

A.append([11,12,13])

This easily adds a row. But is there a similar way to add a column??

(The frustrating thing is that Python doc gives all kinds of fancy examples but apparently these focus on demonstrating 'pythonic' solutions for one-dimensional lists.)

Upvotes: 0

Views: 683

Answers (1)

Nyps
Nyps

Reputation: 886

Coming from MATLAB myself, I understand your point. The problem is that Python lists are not designed to serve as matrices. When indexing a list, you always work on the top level list elements, e.g. A[:][1] returns all the ([:]) three list elements, namely [1, 2, 3], [9, 8, 7] and [5, 5, 5]. Then you select the second ([1]) element from those, i.e. [9, 8, 7]. A[1][:] does the same, just the other way round.

This being said, you can still use nested lists for simple indexing tasks, as A[1][1] gives the expected result (8). However, if you are planing to migrate your whole MATLAB code to Python or work on non-trivial matrix problems, you should definitely consider using NumPy. There is even a NumPy guide for former MATLAB users.

Upvotes: 6

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