python add multiple arrays together

Question

I have multiple 5x5 arrays which are contained within one large array - the overarching shape is: 5 x 5 x 29. I want to sum every 5 x 5 array to produce one single array, instead of 29 single arrays.

I know that you can do something along the lines of:

new_data = data1[:,:,0] + data1[:,:,1] + ... + data1[:,:,29]

However, this gets very cumbersome for large arrays. Is there an easier way to do this?

This is the very thing loops were designed for.

Scott Hunter
– Scott Hunter

2019-07-31 19:17:15 +00:00
Commented Jul 31, 2019 at 19:17 — Scott Hunter
– Scott Hunter, Commented Jul 31, 2019 at 19:17

iz_ · Accepted Answer · 2019-07-31 19:21:01Z

6

Assuming you are using NumPy, you should be able to do this with:

In [13]: data1 = np.arange(100).reshape(5, 5, 4) # For example

In [14]: data1[:,:,0] + data1[:,:,1] + data1[:,:,2] + data1[:,:,3] # Bad way
Out[14]:
array([[  6,  22,  38,  54,  70],
       [ 86, 102, 118, 134, 150],
       [166, 182, 198, 214, 230],
       [246, 262, 278, 294, 310],
       [326, 342, 358, 374, 390]])

In [15]: data1.sum(axis=2) # Good way
Out[15]:
array([[  6,  22,  38,  54,  70],
       [ 86, 102, 118, 134, 150],
       [166, 182, 198, 214, 230],
       [246, 262, 278, 294, 310],
       [326, 342, 358, 374, 390]])

answered Jul 31, 2019 at 19:21

iz_

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4 Comments

WX_M Over a year ago

What about for floating point numbers? This only seems to be adding integers.

iz_ Over a year ago

@M.Simpson I'm not sure what you mean. This should work regardless of data type. Could you give an example?

WX_M Over a year ago

a = [[ 1.5 1.5 1.5] [1.5 1.5 1.5] [1.5 1.5 1.5]] b = [[ 1.5 1.5 1.5] [1.5 1.5 1.5] [1.5 1.5 1.5]] both = np.zeros([3,3,2]) both[:,:,0] = a both[:,:,1] = b print both.sum(axis=3) [[ 2 2 2] [2 2 2] [2 2 2]] Which works fine. However, a = [[ 1 1 1] [1 1 1] [1 1 1]] b = [[ 1 1 1] [1 1 1] [1 1 1]] both = np.zeros([3,3,2]) both[:,:,0] = a both[:,:,1] = b print both.sum(axis=3) [[ 2 2 2] [2 2 2] [2 2 2]] When it should be 3's instead of 2's

iz_ Over a year ago

@M.Simpson Sorry, it is a little hard to read. Could you update your question or use something like Pastebin instead?

Steven Barnard · Accepted Answer · 2019-07-31 19:23:22Z

1

If you are saying you have a list of arrays, then use a for loop.

for i in range(29):
    new_data+= data1[:,:,i]

If you are saying you have a tensor or some ND array you should review and research numpy's ND array docs.

answered Jul 31, 2019 at 19:23

Steven Barnard

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1 Comment

iz_ Over a year ago

What is the definition of new_data?

iz_ · Accepted Answer · 2019-07-31 19:37:11Z

1

You can use a for loop. Like this:

import numpy as np

new_data = np.zeros((5, 5))
for i in range(29):
    new_data += data1[:,:,i]

edited Jul 31, 2019 at 19:37

iz_

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answered Jul 31, 2019 at 19:20

Axiumin_

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8 Comments

iz_ Over a year ago

This likely won't work because new_data is a Python list, and += will just append.

iz_ Over a year ago

No, you are still appending to the list. In fact, now you are making unnecessary copies of the list. Anyway, OP is using arrays. Lists and arrays don't mix well.

iz_ Over a year ago

What is the definition of new_data?

Axiumin_ Over a year ago

They likely already have a definition for the array of new_data.

iz_ Over a year ago

I am not so sure that is true. It looks like a new variable to me. Anyway, you could make it a 5x5 array of zeroes with np.zeros :)

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