在看CNN识别花卉的代码时,遇到的np.array和np.transpose不是太懂,print结果再参考numpy官网: 原来np.array的作用就是将数组升维,np.transpose就是改变索引,二维时不需指定改变索引的方式(交换索引,即交换x、y坐标的值),这里就相当于转置。
以下是一个使用Numpy进行矩阵乘法并将结果向量转置为列向量的示例代码: importnumpyasnp# 创建两个矩阵matrix1=np.array([[1,2,3],[4,5,6],[7,8,9]])matrix2=np.array([[1],[2],[3]])# 两个矩阵进行乘法result=np.dot(matrix1,matrix2)# 将结果向量转置为列向量transpose_result=np.transpose(r...
We can use the transpose() function to get the transpose of an array. import numpy as np arr1 = np.array([[1, 2, 3], [4, 5, 6]]) print(f'Original Array:\n{arr1}') arr1_transpose = arr1.transpose() print(f'Transposed Array:\n{arr1_transpose}') Output: Original Array:...
转到源码中可以看到这句话:Returns a view of the array with axes transposed. 也就是该函数的作用是将数组按指定的轴来进行转置并返回结果。 先来看看二维数组: 二维数组比较直观,效果就是矩阵的转置 再来看看三维数组: 先创建一个三维数组: 其中, reshape 函数中的参数 (2,2,3) 可以看作对应的轴:(x,y...
import numpy as np # Create a NumPy array matrix = np.array([ [1, 2, 3], [4, 5, 6], [7, 8, 9] ]) # Transpose using .T or transpose() transposed_matrix = matrix.T # Alternatively: transposed_matrix = np.transpose(matrix) print(transposed_matrix) Output: text [[1 4 7]...
1. Quick Examples of transpose() Function If you are in a hurry, below are some quick examples of how to use the numpy.transpose() function. # Quick examples of transpose() function import numpy as np # Create a 2-D numpy array arr = np.array([[12, 14,17],[13, 16, 24],[29...
转到源码中可以看到这句话:Returns a view of the array with axes transposed. 也就是该函数的作用是将数组按指定的轴来进行转置并返回结果。 先来看看二维数组: 二维数组比较直观,效果就是矩阵的转置 再来看看三维数组: 先创建一个三维数组: 其中, reshape 函数中的参数 (2,2,3) 可以看作对应的轴:(x,y...
x=np.array([2,3,3])print("Matrix x:")print(x)x_transpose=np.transpose(x)print("\nTranspose of Matrix x:")print(x_transpose) 输出: Matrix x:[2 3 3]Transpose of Matrix x:[2 3 3] 它显示一维数组在通过np.transpose()方法后没有变化。
Returns an array with axes transposed. For a 1-D array, this returns an unchanged view of the original array, as a transposed vector is simply the same vector. To convert a 1-D array into a 2-D column vector, an additional dimension must be added, e.g.,np.atleast2d(a).Tachieves...
Transpose a 1D NumPy Array First, convert the 1D vector into a 2D vector so that you can transpose it. It can be done by slicing it withnp.newaxisduring the creation of the array. And, then by using the.Tmethod, you can transpose it. ...