To reverse an array in Python using NumPy, various methods such as np.flip(), array slicing, and np.ndarray.flatten() can be employed. np.flip() reverses elements along a specified axis, array slicing offers a simple syntax for reversing, while flipud() and fliplr() flip arrays vertically...
System.arraycopy(keyBytes, 0, keyBytes16, 0, 16); SecretKeySpec secretKeySpec = new SecretKeySpec(keyBytes16, "AES"); Cipher cipher = Cipher.getInstance("AES/ECB/PKCS5Padding"); cipher.init(1, secretKeySpec); byte[] encryptedBytes = c...
Explanation:In the above code -array_nums = np.arange(20).reshape(4,5): This code creates a 1-dimensional NumPy array containing numbers from 0 to 19 and then reshapes it into a 2-dimensional array with 4 rows and 5 columns.array_nums[:] = array_nums[3::-1]: This code reverses ...
[:new_length] # 转换为 numpy 数组 array = np.array(dword_202020) # 计算每个矩阵的起始索引 matrices = [array[i:i + matrix_size].reshape(n, n) for i in range(0, len(array), matrix_size)] # 打印矩阵 for idx, mat in enumerate(matrices): print(f"Matrix {idx + 1}:\n{mat}\n...
转念一想,可以考虑为解32元一次方程,使用math库的solve函数可以解多元一次方程,32个方程的系数作为一个array,32个方程的结果作为一个array 得到如下解密代码,得到flag:FAKE{th15_15_n07_7h3_r341_f14g!} import numpyasnp s=[13,0,0,0,144,0,0,0,129,0,0,0,36,0,0,0,58,0,0,0,38,0,0,0...
System.arraycopy(keyBytes, 0, keyBytes16, 0, 16); SecretKeySpec secretKeySpec = new SecretKeySpec(keyBytes16, "AES"); Cipher cipher = Cipher.getInstance("AES/ECB/PKCS5Padding"); cipher.init(1, secretKeySpec); byte[] encryptedBytes = cipher.doFinal(data.getBytes("UTF-8")); ...
这段时间做时序优化，感觉心有余而力不足了，可能要触及手动布局布线了，打开 Device 布局图才开始有...
public static void main(String[] args) { // Creating an array to be sorted in descending // order Integer[] arr = { 30, 20, 40, 10 }; // Collections.sort method is sorting the // elements of arr[] in descending order // later on Arrays.sort() is applied to sort array Arrays...
matrix[i][j]=0foriinrange(NUM):forjinrange(len(strings[i])):ifj>=NUM:breakmatrix[i][j]=ord(strings[i][j])if__name__=='__main__': gen_matrix() verify=numpy.array(verify) matrix=numpy.array(matrix) a=numpy.linalg.solve(matrix,verify)printa ...
from alumette import Tensor import numpy as np a = Tensor(np.random.random((5, 2)), requires_grad=True) # From Numpy nd-array b = Tensor([[0.1], [-1.5]], requires_grad=True) # Automatic nd-array creation from list c = Tensor(np.random.random((5, 1)), requires_grad=True) ...