ANSA二次开发_Python基础-矩阵
学习Numpy的必备知识矩阵的基本概念importnumpyasnp#定义一个矩阵matrix=np.array([[1,2],[3,4]])#定义一个向量vector=np.array([1,2])print("Matrix:\n",matrix)print("Vector:\n",vector)2.矩阵运算-矩阵点乘F=A*Bprint("Element-wiseMultiplication:\n",F)-矩阵叉乘#G=np.dot(A,B)print("MatrixMultiplication:\n",G)-逆矩阵#逆矩阵I=np.linalg.inv(A)print("InverseMatrix:\n",I)-行列式det=np.linalg.det(A)print("Determinant:",det)-其他运算#定义矩阵A=np.array([[1,2],[3,4]])B=np.array([[5,6],[7,8]])#矩阵加法C=A+Bprint("MatrixAddition:\n",C)#矩阵减法D=A-Bprint("MatrixSubtraction:\n",D)#标量乘法scalar=2E=A*scalarprint("ScalarMultiplication:\n",E)#矩阵转置H=A.Tprint("MatrixTranspose:\n",H)3.特殊矩阵-单位矩阵identity_matrix=np.eye(2)print("IdentityMatrix:\n",identity_matrix)[[1.0.0.0.0.][0.1.0.0.0.][0.0.1.0.0.][0.0.0.1.0.][0.0.0.0.1.]]-对角矩阵diagonal_matrix=np.diag([1,2])print("DiagonalMatrix:\n",diagonal_matrix)[[100][020][003]]-计算矩阵特征值eigenvalues,eigenvectors=np.linalg.eig(A)print(eigenvalues)#[-0.372281325.37228132]print(eigenvectors)#[[-0.82456484-0.41597356]#[0.56576746-0.90937671]]4、矩阵的实际应用案例tcl调用Python实现两组节点最近距离计算JinTian,公众号:TodayCAEertcl调用Python实现两组节点最近距离计算来源:TodayCAEer