View Operations¶

These operations return views that share memory with the original array.

Slicing¶

Array slices return views by default.

1. Basic Slice¶

import numpy as np

def main():
    x = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
    print(f"{x = }")

    y = x[1:4]  # returns view
    y[0] = -1
    print(f"{x = }")

if __name__ == "__main__":
    main()

Output:

x = array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
x = array([ 0, -1,  2,  3,  4,  5,  6,  7,  8,  9])

2. Mutation Propagates¶

Modifying the slice modifies the original array.

Method reshape¶

The reshape method returns a view when possible.

1. reshape View¶

import numpy as np

def main():
    x = np.arange(6)
    print(f"{x = }")

    y = x.reshape((3, 2))  # returns view
    y[0, 0] = 6
    print(f"{x = }")

if __name__ == "__main__":
    main()

Output:

x = array([0, 1, 2, 3, 4, 5])
x = array([6, 1, 2, 3, 4, 5])

2. Same Memory¶

The reshaped array shares the underlying data buffer.

Function np.reshape¶

The np.reshape function also returns a view.

1. np.reshape View¶

import numpy as np

def main():
    x = np.arange(6)
    print(f"{x = }")

    y = np.reshape(x, (3, 2))  # returns view
    y[0, 0] = 6
    print(f"{x = }")

if __name__ == "__main__":
    main()

Output:

x = array([0, 1, 2, 3, 4, 5])
x = array([6, 1, 2, 3, 4, 5])

2. Equivalent Behavior¶

Method and function behave identically.

Attribute T¶

The transpose attribute .T returns a view.

1. Transpose View¶

import numpy as np

def main():
    x = np.array([[1, 2], [3, 4]])
    print(f"{x = }")

    y = x.T  # returns view
    y[0, 0] = 6
    print(f"{x = }")

if __name__ == "__main__":
    main()

Output:

x = array([[1, 2],
           [3, 4]])
x = array([[6, 2],
           [3, 4]])

2. Shared Data¶

Transposed array shares memory with original.

Function np.transpose¶

The np.transpose function returns a view.

1. np.transpose View¶

import numpy as np

def main():
    x = np.array([[1, 2], [3, 4]])
    print(f"{x = }")

    y = np.transpose(x)  # returns view
    y[0, 0] = 6
    print(f"{x = }")

if __name__ == "__main__":
    main()

Output:

x = array([[1, 2],
           [3, 4]])
x = array([[6, 2],
           [3, 4]])

2. Same as .T¶

Function and attribute produce equivalent views.

View Summary¶

Common operations returning views.

1. List of Operations¶

Slicing: arr[1:4]
Reshape: arr.reshape(shape)
Transpose: arr.T
Ravel: arr.ravel()
Squeeze: np.squeeze(arr)
Expand dims: arr[np.newaxis]

2. General Rule¶

Operations that reinterpret existing data return views.