Numpy的FancyIndexing fancyIndexing的图片示例 fancyIndexing的代码示例1 fancyIndexing的代码示例2 fancyIndexing的代码示例3 Numpy的FancyIndexing FancyIndexing可以翻译为‘神奇索引’。神奇索引主要用于numpy数组中的任意元素的索引,具有强大的灵活性。 fancyIndexing的图片示例 np.reshape图示 np的神奇索引 np.array图示 ...
#Fancy Indexing x = np.arange(16) np.random.shuffle(x) print(x) #打印所有的元素 print(x[2])#获取某个元素的值 print(x[1:3])#切片 print(x[3:9:2])#指定间距切片 index = [2,4,7,9] #索引数组 print(x[index])#获取索引数组中的元素的值 ind = np.array([[0,2],[1,4]]) #...
We specified different ranges for thexvalues andyvalues. These ranges were used to index the Lena array. Fancy indexing is done based on an internal NumPy iterator object. The following three steps are performed: The iterator object is created. ...
Fancy indexing is indexing that does not involve integers or slices, which is conventional indexing. In this tutorial, we will practice fancy indexing to set the diagonal values of the Lena photo to 0. This will draw black lines along the diagonals, crossing through them. The following is the...
fancy indexing:传递索引数组来一次返回多个数组元素。 索引为一维数组 代码语言:javascript 代码运行次数:0 运行 AI代码解释 importnumpyasnpif__name__=='__main__':x=np.array([51,92,14,71,60,20,82,86,74,74])ind=[3,4,5]print(x[ind]) ...
Fancy Indexing 首先创建一个向量。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 importnumpyasnp x=np.arange(16) 我们可以对向量进行和Python列表一样的索引和切片操作。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 x[3]# 索引第4个元素 ...
Now it's time for fancy indexing, in which we pass an array of indices to an array in order to access or modify multiple array elements at the same time.Let's try it out:Python Копирај rand = np.random.RandomState(42) arr = rand.randint(100, size=10) print(arr) ...
Write a NumPy program that creates a 3D NumPy array and uses fancy indexing to select elements from specific rows and columns.Sample Solution:Python Code:import numpy as np # Create a 3D NumPy array of shape (3, 4, 5) array_3d = np.random.randint(0, 100, size=(3, 4, 5)) # ...
File"lib/python3.10/site-packages/numpy/_core/arrayprint.py", line 1692,in_array_str_implementationreturnarray2string(a, max_line_width, precision, suppress_small,'',"") File"lib/python3.10/site-packages/numpy/_core/arrayprint.py", line 776,inarray2stringreturn_array2string(a, options, se...
Python platform: Linux-6.5.0-1023-aws-x86_64-with-glibc2.35 Is CUDA available: True CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA A10G Nvidia driver version: 555.42.06 ...