Numpy. section6 : ndarray의 인덱싱과 슬라이싱. Lec24. 텐서 ndarray의 인덱싱과 슬라이싱

[1] Indexing and slicing 3rd Order Tensor ndarrays

• 하나 인덱싱할때에는 바깥쪽부터 인덱싱한다.

a = np.arange(3*3*3).reshape((3,3,3))
print(f"ndarray: \n{a}\n")

print("a[0] : \n", a[0])

print("a[1] : \n", a[1])

print("a[2] : \n", a[2])

print("a[0, 0] : \n", a[0, 0])
print("a[0, 1] : \n", a[0, 1])
print("a[0, 2] : \n", a[0, 2])

print("a[1, 0] : \n", a[1, 0])
print("a[1, 1] : \n", a[1, 1])
print("a[1, 2] : \n", a[1, 2])

print("a[2, 0] : \n", a[2, 0])
print("a[2, 1] : \n", a[2, 1])
print("a[2, 2] : \n", a[2, 2])

print("a[0, :2, :2] : \n", a[0, :2, :2])

print("a[1, :2, :] : \n", a[1, :2, :])

print("a[2, -2:, -2:] : \n", a[2, -2:, -2:])

a = np.arange(3*3*3).reshape((3,3,3))
print(f"ndarray: \n{a}\n")
print("a[:, :2, :] : \n", a[:, :2, :])

a = np.arange(3*3*3).reshape((3,3,3))
print(f"ndarray: \n{a}\n")
print("a[:, :, 0] : \n", a[:, :, 0])

print("a[1:, -2:, -2:] : \n", a[1:, -2:, -2:])

[2] 전체코드

import numpy as np

a = np.arange(3*3*3).reshape((3,3,3))
print(f"ndarray: \n{a}\n")

print("a[0] : \n", a[0])

print("a[1] : \n", a[1])

print("a[2] : \n", a[2])

#
print("a[0, 0] : \n", a[0, 0])
print("a[0, 1] : \n", a[0, 1])
print("a[0, 2] : \n", a[0, 2])

print("a[1, 0] : \n", a[1, 0])
print("a[1, 1] : \n", a[1, 1])
print("a[1, 2] : \n", a[1, 2])

print("a[2, 0] : \n", a[2, 0])
print("a[2, 1] : \n", a[2, 1])
print("a[2, 2] : \n", a[2, 2])

# 

print("a[0, :2, :2] : \n", a[0, :2, :2])

print("a[1, :2, :] : \n", a[1, :2, :])

print("a[2, -2:, -2:] : \n", a[2, -2:, -2:])

#

images = np.random.normal(size = (32, 100, 200))
print("image set: ", images.shape)

image0 = images[0, :, :]
print(image0.shape)

image0 = images[0, ...]
print(image0.shape)

col0 = images[:, :, 0]
print(col0.shape)

col0 = images[..., 0]
print(col0.shape, '\n')

image0_col0 = images[0, :, 0]
print(image0_col0.shape)


#

a = np.arange(3*3*3).reshape((3,3,3))
print(f"ndarray: \n{a}\n")
print("a[:, :2, :] : \n", a[:, :2, :])

#

a = np.arange(3*3*3).reshape((3,3,3))
print(f"ndarray: \n{a}\n")
print("a[:, :, 0] : \n", a[:, :, 0])

#

print("a[1:, -2:, -2:] : \n", a[1:, -2:, -2:])

#

image = np.random.normal(size = (3, 500, 300))

image_r = image[0]
image_g = image[1]
image_b = image[2]

print(image_r.shape, image_g.shape, image_b.shape)

# 튜플 언펙킹 사용

image = np.random.normal(size = (3, 500, 300))

image_r, image_g, image_b = image
print(image_r.shape, image_g.shape, image_b.shape)

#

image = np.random.normal(size = (3, 500, 300))

top_left = image[:, :100, :100]
top_right = image[:, :100, -100:]
bottom_left = image[:, -100:, :100]
bottom_right = image[:, -100:, -100:]

print(top_left.shape, top_right.shape)
print(bottom_left.shape, bottom_right.shape)