# 4.8. Array Shape¶

• Any shape operation changes only ndarray.shape and ndarray.strides and does not touch data

## 4.8.1. Get shape¶

import numpy as np

a = np.array([1, 2, 3])

a.shape     # (3,)

import numpy as np

a = np.array([[1, 2, 3],
[4, 5, 6]])

a.shape     # (2, 3)

import numpy as np

a = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])

a.shape     # (3, 3)

import numpy as np

a = np.array([[[ 1,  2,  3],
[ 4,  5,  6],
[ 5,  6,  7]],
[[11, 22, 33],
[44, 55, 66],
[77, 88, 99]]])

a.shape         # (2, 3, 3)


## 4.8.2. Reshape¶

• Returns new array

• Does not modify inplace

• a.reshape(1, 2) is equivalent to a.reshape((1, 2))

import numpy as np

a = np.array([1, 2, 3])

a.reshape(1, 3)
# array([[1, 2, 3]])

a.reshape(3, 1)
# array([[1],
#        [2],
#        [3]])

import numpy as np

a = np.array([[1, 2, 3],
[4, 5, 6]])

a.reshape(3, 2)
# array([[1, 2],
#        [3, 4],
#        [5, 6]])

a.reshape(1, 6)
# array([[1, 2, 3, 4, 5, 6]])

a.reshape(6, 1)
# array([[1],
#        [2],
#        [3],
#        [4],
#        [5],
#        [6]])

a.reshape(5, 2)
# ValueError: cannot reshape array of size 6 into shape (5,2)

import numpy as np

a = np.array([1, 2, 3, 4, 5, 6, 7, 8])

a.reshape(2, 4)
# array([[1, 2, 3, 4],
#        [5, 6, 7, 8]])

a.reshape(2, 4, 1)
# array([[[1],
#         [2],
#         [3],
#         [4]],
#        [[5],
#         [6],
#         [7],
#         [8]]])

a.reshape(2, 2, 2)
# array([[[1, 2],
#         [3, 4]],
#        [[5, 6],
#         [7, 8]]])

a.reshape(1, 2, 4)
# array([[[1, 2, 3, 4],
#         [5, 6, 7, 8]]])

a.reshape(4, 2, 1)
#array([[[1],
#        [2]],
#       [[3],
#        [4]],
#       [[5],
#        [6]],
#       [[7],
#        [8]]])

a.reshape(1, 8, 1)
# array([[[1],
#         [2],
#         [3],
#         [4],
#         [5],
#         [6],
#         [7],
#         [8]]])

a.reshape(2, 3, 1)
# ValueError: cannot reshape array of size 8 into shape (2,3,1)


## 4.8.3. Flatten¶

• Returns new array (makes memory copy - expensive)

• Does not modify inplace

import numpy as np

a = np.array([1, 2, 3])

a.flatten()
# array([1, 2, 3])

import numpy as np

a = np.array([[1, 2, 3],
[4, 5, 6]])

a.flatten()
# array([1, 2, 3, 4, 5, 6])

import numpy as np

a = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])

a.flatten()
# array([1, 2, 3, 4, 5, 6, 7, 8, 9])


## 4.8.4. Ravel¶

• Ravel is the same as Flatten but returns a reference (or view) of the array if possible (i.e. memory is contiguous)

• Otherwise returns new array (makes memory copy)

import numpy as np

a = np.array([1, 2, 3])

a.ravel()
# array([1, 2, 3])

import numpy as np

a = np.array([[1, 2, 3],
[4, 5, 6]])

a.ravel()
# array([1, 2, 3, 4, 5, 6])

import numpy as np

a = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])

a.ravel()
# array([1, 2, 3, 4, 5, 6, 7, 8, 9])


## 4.8.5. Assignments¶

### 4.8.5.1. Numpy Shape¶

English
1. Use data from "Input" section (see below)

2. Given a: ndarray (see below)

3. Flatten using method .ravel()

4. Print a

5. Change shape back to 3x3

6. Print a

Polish
1. Użyj danych z sekcji "Input" (patrz poniżej)

2. Dany a: ndarray (patrz sekcja input)

3. Spłaszcz używając metody .ravel()

4. Wypisz a

5. Zmień kształt na powrót na 3x3

6. Wypisz a

Input
a = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])