Numpy 1

RP-FIZ

12. 12. 2023

Vir slik:

Alammar, J (2018). The Illustrated Transformer [Blog post]. Retrieved from https://jalammar.github.io/illustrated-transformer/

import numpy as np

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

# [1 2 3]

podatki = np.linspace(0, 10, 5)
print(podatki)

# [ 0.   2.5  5.   7.5 10. ]

podatki = np.linspace(0, 10, 8)
print(podatki)

# [ 0.          1.42857143  2.85714286  4.28571429  5.71428571  7.14285714
#   8.57142857 10.        ]

podatki = np.arange(0, 10, 1)
print(podatki)

# [0 1 2 3 4 5 6 7 8 9]

podatki = np.arange(0, 10, 0.2)
print(podatki)

# [0.  0.2 0.4 0.6 0.8 1.  1.2 1.4 1.6 1.8 2.  2.2 2.4 2.6 2.8 3.  3.2 3.4
#  3.6 3.8 4.  4.2 4.4 4.6 4.8 5.  5.2 5.4 5.6 5.8 6.  6.2 6.4 6.6 6.8 7.
#  7.2 7.4 7.6 7.8 8.  8.2 8.4 8.6 8.8 9.  9.2 9.4 9.6 9.8]

import numpy as np

data = np.array([1, 2])
ones = np.ones(2)

rezultat = data + ones

data = np.array([[1, 2], [3, 4], [5, 6]])
print(data.shape)

# (3, 2)

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

# [[1 2]
#  [3 4]
#  [5 6]]