add zeros to missing values of a matrix using Numpy

Question

I am obtaining several values of two matrices L and R of expected dimensions of 2200x88 for each ith iteration of a for loop using Numpy (Python). some of the matrices have fewer elements for example 1200x55, in those cases I have to add zeros to the matrix to reshape it to be of 2200x88 dimension. I have created the following program to solve that problem:

        for line in infile:
        line = line.strip()
        #more code here, l is matrix 1 of the ith iteration, r is matrix 2 of ith iteration 
ls1, ls2=l.shape
rs1, rs2= r.shape
            if ls1 != 2200 | ls2 != 88:
                l.resize((2200, 88), refcheck=False)
            if rs1 != 2200 | rs2 != 88:
                r.resize((2200, 88), refcheck=False)
            var = np.concatenate((l, r), axis=0).reshape(1,387200)

The problem is that when a matrix R or L is detected not to be of dimensions 2200 by 88 I obtain the following error:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Has anyone any recommendations on how to solve this?

Thank you.

I suspect that l[0] != 2200 | l[1] != 88 should be ls1 != 2200 | ls2 != 88 and the same thing goes for the r[0]... line 2 lines below. — jedwards
– jedwards, Commented Mar 5, 2015 at 19:18
yes, my bad! I copied the wrong code. Thank you for spotting it. — user3025898
– user3025898, Commented Mar 5, 2015 at 19:30
You need to clean up the indentation, e.g. the for line. Also are you missing some if statements? — hpaulj
– hpaulj, Commented Mar 6, 2015 at 0:00

jedwards · Accepted Answer · 2015-03-05 19:24:42Z

1

Since l is a matrix, l[0] is a strip of that matrix, an array.

This part:

if l[0] != 2200 | l[1] != 88

is causing your error, since you're trying to "or" two arrays.

So instead of

ls1, ls2=l.shape
rs1, rs2= r.shape
if l[0] != 2200 | l[1] != 88:
    l.resize((2200, 88), refcheck=False)
if r[0] != 2200 | r[1] != 88:
    r.resize((2200, 88), refcheck=False)

Consider:

 if l.shape != (2200, 88):
     l.resize((2200, 88), refcheck=False)
 if r.shape != (2200, 88):
     r.resize((2200, 88), refcheck=False)

answered Mar 5, 2015 at 19:24

jedwards

30.3k3 gold badges69 silver badges94 bronze badges

Sign up to request clarification or add additional context in comments.

4 Comments

user3025898 Over a year ago

I have tried and I get: ValueError: cannot resize this array: it does not own its data

jedwards Over a year ago

Thats a different issue, but consider looking at answers to this question

user3025898 Over a year ago

I think the answer may be to do the following c = b.copy() but do I have to create a separate concatenate function to do that?

jedwards Over a year ago

It's hard to say without knowing more about your code. If you copy both matrices ll,rr = l.copy(),r.copy() then your concatenate line should look like var = np.concatenate((ll, rr), axis=0).reshape(1,387200)

Collectives™ on Stack Overflow

add zeros to missing values of a matrix using Numpy

1 Answer 1

4 Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

4 Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related