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题解 | 使用行阶梯形求矩阵的像(image)

import numpy as np def matrix_image(A): mat = np.array(A, dtype=np.float64).copy() row, col = mat.shape pivot_cols = [] cur_...

2026-01-17

0 9

题解 | 高斯消元法求解线性方程组

import numpy as np def gaussian_elimination(A, b): n=len(b) aug_matrix = np.hstack([A.astype(float),b.reshape(n,1).astype(float)]) for co...

2026-01-17

0 10

题解 | Gauss-Seidel法求解线性方程组

import numpy as np def gauss_seidel(A, b, n, x_ini=None): x = x_ini or np.zeros_like(b) dim = len(b) for _ in range(n): for i in ...

2026-01-17

0 11

题解 | 二维平移矩阵实现

import numpy as np def translate_object(points, tx, ty): pts=np.array(points,dtype=np.float64) pts+=np.array([tx,ty]) return pts.tolist() ...

2026-01-17

0 8

题解 | 计算相关矩阵

import numpy as np def calculate_correlation_matrix(X, Y=None): # Your code here m,p=X.shape x_mean=np.mean(X,axis=0) x_centered=X-x_mea...

2026-01-16

0 11

题解 | 使用Jacobi方法求解线性方程组

import numpy as np def solve_jacobi(A, b, n) : # 补全代码 a=np.array(A,dtype=np.float64) b=np.array(b,dtype=np.float64) size=len(b) x=...

2026-01-16

0 11

题解 | 计算矩阵的积

import numpy as np def matrixmul(a,b): # 补全代码 mata=np.array(matrixa) matb=np.array(matrixb) if mata.shape[1]!=matb.shape[0]: r...

2026-01-16

0 9

题解 | 计算矩阵的逆

import numpy as np def inverse_2x2(matrix) : # 补全代码 mat=np.array(matrix,dtype=np.float64) if np.isclose(np.linalg.det(mat),0): ret...

2026-01-16

0 8

题解 | 矩阵变换

import numpy as np def transform_matrix(A,T,S): # 补全代码 an=np.array(A,dtype=np.float64) tn=np.array(T,dtype=np.float64) sn=np.array(S,d...

2026-01-16

0 12

题解 | 计算矩阵的特征值

from typing import List, Union import numpy as np def calculate_eigenvalues(matrix: List[List[Union[int, float]]]) -> List[float]: mat=np.array...

2026-01-16

0 11