importnumpyasnp# 创建一个3D数组array_3d=np.arange(24).reshape(2,3,4)print("Original 3D array from numpyarray.com:")print(array_3d)# 重塑为(6, 4)的2D数组array_2d_1=array_3d.reshape(6,4)print("\nReshaped to (6, 4):")print(array_2d_1)# 重塑为(8, 3)的2D数组array_2d_2=ar...
reshape()方法是实现3D到2D转换的关键。它允许我们重新指定数组的形状,只要保持元素总数不变。 3.1 基本用法 importnumpyasnp array_3d=np.arange(24).reshape(2,3,4)array_2d=array_3d.reshape(6,4)print("Original 3D array from numpyarray.com:")print(array_3d)print("\nReshaped 2D array:")print(...
Example 2: Reshape Array Row-Wise import numpy as np originalArray = np.array([0, 1, 2, 3, 4, 5, 6, 7]) # reshape the array to 2D # the last argument 'C' reshapes the array row-wise reshapedArray = np.reshape(originalArray, (2, 4), 'C') ...
array = np.linspace(0,1,256*256) # reshape to 2d mat = np.reshape(array,(256,256)) # Creates PIL image img = Image.fromarray(np.uint8(mat * 255) , 'L') img.show() 做一个干净的渐变 对比 import numpy as np from PIL import Image # gradient between 0 and 1 for 256*256 arra...
Example Try converting 1D array with 8 elements to a 2D array with 3 elements in each dimension (will raise an error): import numpy as nparr = np.array([1, 2, 3, 4, 5, 6, 7, 8]) newarr = arr.reshape(3, 3)print(newarr) Try it Yourself » ...
# Create a 1-dimensional array arr = np.array([1, 2, 3, 4, 5, 6]) # Reshape the array to a 2x3 matrix reshaped_arr = np.reshape(arr, (2, 3)) [[1 2 3] [4 5 6]] numpy.transpose:用于排列数组的维度。它返回一个轴调换后的新数组。
array([1,2,3]) # 数值型数组 array(['w','s','q'],dtype = '<U1') # 字符型数组...
a=np.array ([1,2,3,4,5,6])a1=a.reshape ([2,3])a2=a.reshape ([3,1,2])print("a1 shape:",a1.shape)print(a1)print("a2 shape:",a2.shape)print(a2) 4 矩阵转置 np.transpose() a=np.array ([1,2,3,4,5,6]).reshape ...
假设我们有一个2D数组,并且我们希望根据某些条件选择其中的元素。 代码语言:txt 复制 import numpy as np # 创建一个2D数组 arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # 创建一个布尔数组,表示每个元素是否大于4 bool_arr = arr > 4 print("原始数组:") print(arr) print("布...
array([6, 7, 8]) 1. 2. 3. 花式索引: 可以将需要索引的值的下标放入列表中 ,将列表作为索引值,取出对应下标的值: res = np.array([1,2,3,4,5,6,7,8,9,10]) res[[1,3,6,8]] array([2, 4, 7, 9]) 1. 2. 3. reshape ...