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哟哟哟12345611
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我是想计算一个由A的特征向量组成的矩阵T,由T组成的对角矩阵,我使用for循环但是他一直报错,麻烦各位大佬帮我看看![[泪]](/static/emoticons/u6cea.png)
fem[lbk]\[lbk]CurlyEpsilon[rbk]1_, \[lbk]CurlyEpsilon[rbk]2_, \[lbk]CurlyEpsilon[rbk]3_, \\[lbk]CurlyEpsilon[rbk]4_, \[lbk]CurlyEpsilon[rbk]5_, \[lbk]CurlyEpsilon[rbk]6_, \\[lbk]CurlyEpsilon[rbk]7_, t_[rbk] :=Module[lbk]{A, \[lbk]CapitalLambda[rbk], T, T1, TT, TT1, SICO, C\[lbk]CapitalLambda[rbk], S\[lbk]CapitalLambda[rbk]}, A = {{0, \[lbk]CurlyEpsilon[rbk]1, \[lbk]CurlyEpsilon[rbk]2, \[lbk]CurlyEpsilon[rbk]3, 0, 0}, {\[lbk]CurlyEpsilon[rbk]1, 0, 0, 0, 0, \[lbk]CurlyEpsilon[rbk]7}, {\[lbk]CurlyEpsilon[rbk]2, 0, 0, 0, \[lbk]CurlyEpsilon[rbk]4, \[lbk]CurlyEpsilon[rbk]5}, {\[lbk]CurlyEpsilon[rbk]3, 0, 0, 0, \[lbk]CurlyEpsilon[rbk]6, 0}, {0, 0, \[lbk]CurlyEpsilon[rbk]4, \[lbk]CurlyEpsilon[rbk]6, 0, 0}, {0, \[lbk]CurlyEpsilon[rbk]7, \[lbk]CurlyEpsilon[rbk]5, 0, 0, 0}}; T = Eigenvectors[lbk]A[rbk]; T1 = Transpose[lbk]T[rbk]; \[lbk]CapitalLambda[rbk] = Eigenvalues[lbk]A[rbk]; SICO = ConstantArray[lbk]0, {12, 12}[rbk]; C\[lbk]CapitalLambda[rbk] = Cosh[lbk]\[lbk]CapitalLambda[rbk]*t[rbk]; S\[lbk]CapitalLambda[rbk] = Sinh[lbk]\[lbk]CapitalLambda[rbk]*t[rbk]; For[lbk]i = 1, i <= 6, i++, SICO[lbk][lbk]i, i[rbk][rbk] = C\[lbk]CapitalLambda[rbk][lbk][lbk]i[rbk][rbk][rbk]; For[lbk]i = 7, i <= 12, i++, SICO[lbk][lbk]i, i[rbk][rbk] = C\[lbk]CapitalLambda[rbk][lbk][lbk]i - 6[rbk][rbk][rbk]; For[lbk]i = 1, i <= 6, i++, SICO[lbk][lbk]i, i + 6[rbk][rbk] = S\[lbk]CapitalLambda[rbk][lbk][lbk]i[rbk][rbk][rbk]; For[lbk]i = 7, i <= 12, i++, SICO[lbk][lbk]i, i - 6[rbk][rbk] = S\[lbk]CapitalLambda[rbk][lbk][lbk]i - 6[rbk][rbk][rbk]; TT = ConstantArray[lbk]0, {12, 12}[rbk]; TT1 = ConstantArray[lbk]0, {12, 12}[rbk]; For[lbk]i = 1, i <= 6, i++, For[lbk]j = 1, j <= 6, j++, TT[lbk][lbk]i, j[rbk][rbk] = T[lbk][lbk]i, j[rbk][rbk];[rbk][rbk]; For[lbk]i = 7, i <= 12, i++, For[lbk]j = 7, j <= 12, j++, TT[lbk][lbk]i, j[rbk][rbk] = T[lbk][lbk]i - 6, j - 6[rbk][rbk];[rbk][rbk]; For[lbk]i = 1, i <= 6, i++, For[lbk]j = 1, j <= 6, j++, TT1[lbk][lbk]i, j[rbk][rbk] = T1[lbk][lbk]i, j[rbk][rbk];[rbk][rbk]; For[lbk]i = 7, i <= 12, i++; For[lbk]j = 7, j <= 12, j++, TT1[lbk][lbk]i, j[rbk][rbk] = T1[lbk][lbk]i - 6, j - 6[rbk][rbk];[rbk][rbk]; XYT = TT.SICO.TT1; {TT1}[rbk]{X} = fem[lbk]\[lbk]CurlyEpsilon[rbk]1, \[lbk]CurlyEpsilon[rbk]2, \[lbk]CurlyEpsilon[rbk]1, \\[lbk]CurlyEpsilon[rbk]1, \[lbk]CurlyEpsilon[rbk]1, \[lbk]CurlyEpsilon[rbk]6, \\[lbk]CurlyEpsilon[rbk]6, t[rbk]

2024年02月20日 03点02分
1
fem[lbk]\[lbk]CurlyEpsilon[rbk]1_, \[lbk]CurlyEpsilon[rbk]2_, \[lbk]CurlyEpsilon[rbk]3_, \\[lbk]CurlyEpsilon[rbk]4_, \[lbk]CurlyEpsilon[rbk]5_, \[lbk]CurlyEpsilon[rbk]6_, \\[lbk]CurlyEpsilon[rbk]7_, t_[rbk] :=Module[lbk]{A, \[lbk]CapitalLambda[rbk], T, T1, TT, TT1, SICO, C\[lbk]CapitalLambda[rbk], S\[lbk]CapitalLambda[rbk]}, A = {{0, \[lbk]CurlyEpsilon[rbk]1, \[lbk]CurlyEpsilon[rbk]2, \[lbk]CurlyEpsilon[rbk]3, 0, 0}, {\[lbk]CurlyEpsilon[rbk]1, 0, 0, 0, 0, \[lbk]CurlyEpsilon[rbk]7}, {\[lbk]CurlyEpsilon[rbk]2, 0, 0, 0, \[lbk]CurlyEpsilon[rbk]4, \[lbk]CurlyEpsilon[rbk]5}, {\[lbk]CurlyEpsilon[rbk]3, 0, 0, 0, \[lbk]CurlyEpsilon[rbk]6, 0}, {0, 0, \[lbk]CurlyEpsilon[rbk]4, \[lbk]CurlyEpsilon[rbk]6, 0, 0}, {0, \[lbk]CurlyEpsilon[rbk]7, \[lbk]CurlyEpsilon[rbk]5, 0, 0, 0}}; T = Eigenvectors[lbk]A[rbk]; T1 = Transpose[lbk]T[rbk]; \[lbk]CapitalLambda[rbk] = Eigenvalues[lbk]A[rbk]; SICO = ConstantArray[lbk]0, {12, 12}[rbk]; C\[lbk]CapitalLambda[rbk] = Cosh[lbk]\[lbk]CapitalLambda[rbk]*t[rbk]; S\[lbk]CapitalLambda[rbk] = Sinh[lbk]\[lbk]CapitalLambda[rbk]*t[rbk]; For[lbk]i = 1, i <= 6, i++, SICO[lbk][lbk]i, i[rbk][rbk] = C\[lbk]CapitalLambda[rbk][lbk][lbk]i[rbk][rbk][rbk]; For[lbk]i = 7, i <= 12, i++, SICO[lbk][lbk]i, i[rbk][rbk] = C\[lbk]CapitalLambda[rbk][lbk][lbk]i - 6[rbk][rbk][rbk]; For[lbk]i = 1, i <= 6, i++, SICO[lbk][lbk]i, i + 6[rbk][rbk] = S\[lbk]CapitalLambda[rbk][lbk][lbk]i[rbk][rbk][rbk]; For[lbk]i = 7, i <= 12, i++, SICO[lbk][lbk]i, i - 6[rbk][rbk] = S\[lbk]CapitalLambda[rbk][lbk][lbk]i - 6[rbk][rbk][rbk]; TT = ConstantArray[lbk]0, {12, 12}[rbk]; TT1 = ConstantArray[lbk]0, {12, 12}[rbk]; For[lbk]i = 1, i <= 6, i++, For[lbk]j = 1, j <= 6, j++, TT[lbk][lbk]i, j[rbk][rbk] = T[lbk][lbk]i, j[rbk][rbk];[rbk][rbk]; For[lbk]i = 7, i <= 12, i++, For[lbk]j = 7, j <= 12, j++, TT[lbk][lbk]i, j[rbk][rbk] = T[lbk][lbk]i - 6, j - 6[rbk][rbk];[rbk][rbk]; For[lbk]i = 1, i <= 6, i++, For[lbk]j = 1, j <= 6, j++, TT1[lbk][lbk]i, j[rbk][rbk] = T1[lbk][lbk]i, j[rbk][rbk];[rbk][rbk]; For[lbk]i = 7, i <= 12, i++; For[lbk]j = 7, j <= 12, j++, TT1[lbk][lbk]i, j[rbk][rbk] = T1[lbk][lbk]i - 6, j - 6[rbk][rbk];[rbk][rbk]; XYT = TT.SICO.TT1; {TT1}[rbk]{X} = fem[lbk]\[lbk]CurlyEpsilon[rbk]1, \[lbk]CurlyEpsilon[rbk]2, \[lbk]CurlyEpsilon[rbk]1, \\[lbk]CurlyEpsilon[rbk]1, \[lbk]CurlyEpsilon[rbk]1, \[lbk]CurlyEpsilon[rbk]6, \\[lbk]CurlyEpsilon[rbk]6, t[rbk]
