Jelaskan >>> c dari NumPy

array([ 1.        ,  1.33333333,  1.66666667,  4.        ])

array([ 1,  4,  9, 36])

>>> a = np.linspace(-np.pi, np.pi, 100)

>>> from numpy.random import rand

>>> from numpy.linalg import solve, inv

>>> a = np.array([[1, 2, 3], [3, 4, 6.7], [5, 9.0, 5]])

array([[ 1. ,  3. ,  5. ],

[ 2. ,  4. ,  9. ],

[ 3. ,  6.7,  5. ]])

[ 1.04519774, -0.56497175,  0.1299435 ],

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

>>> solve(a, b)  # menyelesaikan persamaan ax = b

>>> c = rand(3, 3) * 20  # buat matriks nilai acak 3x3 dalam [0,1] dengan skala 20

[  9.24410671,   5.5240412 ,  10.6468792 ],

>>> np.dot(a, c)  # matrix multiplication

array([[  53.61964114,   38.8741616 ,   71.53462537],

[ 118.4935668 ,   86.14012835,  158.40440712],

[ 155.04043289,  104.3499231 ,  195.26228855]])

>>> a @ c # Starting with Python 3.5 and NumPy 1.10

array([[  53.61964114,   38.8741616 ,   71.53462537],

[ 118.4935668 ,   86.14012835,  158.40440712],

[ 155.04043289,  104.3499231 ,  195.26228855]])

>>> M = np.zeros(shape=(2, 3, 5, 7, 11))

>>> T = np.transpose(M, (4, 2, 1, 3, 0))

(11, 5, 3, 7, 2)

>>> import numpy as np

>>> r = np.reshape(np.arange(256*256)%256,(256,256))  # array 256x256 piksel dengan gradien horizontalfrom 0 to 255 for the red color channel

>>> g = np.zeros_like(r)  # array dengan ukuran dan tipe yang sama dengan r tetapi diisi dengan 0 untuk kanal warna hijau

>>> b = r.T # transposed r will give a vertical gradient for the blue color channel

>>> cv2.imwrite('gradients.png', np.dstack([b,g,r]))  # Gambar OpenCV ditafsirkan sebagai BGR, array tumpuk kedalaman akan ditulis ke file PNG RGB 8bit yang dinamai 'gradients.png'