Cloning a column in 3d numpy array

Question

Let's say I have a 3D array representing tic-tac-toe games (and their respective historical states):

[ 
  [[0,0,0,1,1,0,0,0,1]], #<<--game 1
  [[1,0,0,1,0,0,1,0,1]], #<<--game 2
  [[1,0,0,1,0,0,1,0,1]]  #<<--game 3
]

I would like to pre-pend a clone of these states, but then keep the historical records growing out to the right where they will act as an unadultered historical record

So the next iteration would look like this:

[ 
  [[0,0,0,1,1,0,0,0,1], [0,0,0,1,1,0,0,0,1]], #<<--game 1
  [[1,0,0,1,0,0,1,0,1], [1,0,0,1,0,0,1,0,1]], #<<--game 2
  [[1,0,0,1,0,0,1,0,1], [1,0,0,1,0,0,1,0,1]]  #<<--game 3
]

I will then edit these new columns. At a later time, I will copy it again.

So, I always want to copy this leftmost column (pass by value) - but I don't know how to perform this operation.

Poe Dator · Accepted Answer · 2019-11-27 19:39:36Z

1

You can use concatenate:

# initial array
a = np.array([ 
  [[0,0,0,1,1,0,0,0,1], [0,1,0,1,1,0,0,0,1]], #<<--game 1
  [[1,0,0,1,0,0,1,0,1], [1,1,0,1,0,0,1,0,1]], #<<--game 2
  [[1,0,0,1,0,0,1,0,1], [1,1,0,1,0,0,1,0,1]]  #<<--game 3
])

#subset of this array (column 0)
b = a[:,0,:]

# reshape to add dimension 
b = b.reshape ([-1,1,9])

print(a.shape, b.shape)  # ((3, 2, 9), (3, 1, 9))

# concatenate:
c = np.concatenate ((a,b), axis = 1)

print (c)

array([[[0, 0, 0, 1, 1, 0, 0, 0, 1],
        [0, 1, 0, 1, 1, 0, 0, 0, 1],
        [0, 0, 0, 1, 1, 0, 0, 0, 1]], # leftmost column copied

       [[1, 0, 0, 1, 0, 0, 1, 0, 1],
        [1, 1, 0, 1, 0, 0, 1, 0, 1],
        [1, 0, 0, 1, 0, 0, 1, 0, 1]], # leftmost column copied

       [[1, 0, 0, 1, 0, 0, 1, 0, 1],
        [1, 1, 0, 1, 0, 0, 1, 0, 1],
        [1, 0, 0, 1, 0, 0, 1, 0, 1]]]) # leftmost column copied

answered Nov 27, 2019 at 19:39

Poe Dator

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2 Comments

birdmw Over a year ago

works perfectly - except I switched a and b in the concatenate.

Ruzihm Over a year ago

@birdmw Please see here

Ruzihm · Accepted Answer · 2019-11-27 20:03:39Z

0

You can do this using hstack and slicing:

import numpy as np
start= np.asarray([[[0,0,0,1,1,0,0,0,1]],[[1,0,0,1,0,0,1,0,1]],[[1,0,0,1,0,0,1,0,1]]])
print(start)

print("duplicating...")
finish = np.hstack((start,start[:,:1,:]))

print(finish)

print("modifying...")
finish[0,1,2]=2

print(finish)

[[[0 0 0 1 1 0 0 0 1]]

 [[1 0 0 1 0 0 1 0 1]]

 [[1 0 0 1 0 0 1 0 1]]]
duplicating...
[[[0 0 0 1 1 0 0 0 1]
  [0 0 0 1 1 0 0 0 1]]

 [[1 0 0 1 0 0 1 0 1]
  [1 0 0 1 0 0 1 0 1]]

 [[1 0 0 1 0 0 1 0 1]
  [1 0 0 1 0 0 1 0 1]]]
modifying...
[[[0 0 0 1 1 0 0 0 1]
  [0 0 2 1 1 0 0 0 1]]

 [[1 0 0 1 0 0 1 0 1]
  [1 0 0 1 0 0 1 0 1]]

 [[1 0 0 1 0 0 1 0 1]
  [1 0 0 1 0 0 1 0 1]]]

edited Nov 27, 2019 at 20:03

answered Nov 27, 2019 at 19:33

Ruzihm

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