使用另一个 2d 数组对 numpy 2d 数组进行切片

Question

我有一个 (4,5) 形状的二维数组和另一个 (4,2) 形状的二维数组。第二个数组包含我需要从第一个数组中过滤掉的开始和结束索引，即我想使用第二个数组对第一个数组进行切片。

np.random.seed(0)
a = np.random.randint(0,999,(4,5))
a
array([[684, 559, 629, 192, 835],
       [763, 707, 359,   9, 723],
       [277, 754, 804, 599,  70],
       [472, 600, 396, 314, 705]])

idx = np.array([[2,4],
                [0,3],
                [2,3],
                [1,3]
               ])

预期输出 - 可以是以下两种格式之一。用零填充的唯一原因是不支持可变长度二维数组。

[[629, 192, 835, 0, 0],
 [763, 707, 359, 9, 0],
 [804, 599, 0, 0, 0],
 [600, 396, 314, 0, 0]
]

[[0, 0, 629, 192, 835],
 [763, 707, 359, 9, 0],
 [0, 0, 804, 599, 0],
 [0, 600, 396, 314, 0]
]

Answer 1

import numpy as np

# Input arrays
np.random.seed(0)
a = np.random.randint(0, 999, (4, 5))
idx = np.array([[2, 4],
                [0, 3],
                [2, 3],
                [1, 3]])

# Prepare the output array with zeros
output_padded_start = np.zeros_like(a)
output_padded_end = np.zeros_like(a)

# Slice and place the values
for i in range(a.shape[0]):
    start, end = idx[i]
    sliced_values = a[i, start:end + 1]
    output_padded_start[i, :len(sliced_values)] = sliced_values  # Padding with zeros at the end
    output_padded_end[i, -len(sliced_values):] = sliced_values  # Padding with zeros at the start


print("Padded at the end:")
print(output_padded_start)
print("\nPadded at the start:")
print(output_padded_end)


# Output
Padded at the end:
[[629 192 835   0   0]
 [763 707 359   9   0]
 [804 599   0   0   0]
 [600 396 314   0   0]]

Padded at the start:
[[  0   0 629 192 835]
 [763 707 359   9   0]
 [  0   0 804 599   0]
 [  0 600 396 314   0]]