Gaussian Elimination Written by Michael K. May, S.J., revised by Russell Blyth restart: with(LinearAlgebra): with(plots): with(plottools): Warning, the name changecoords has been redefined Warning, the assigned name arrow now has a global binding
<Text-field style="Heading 1" layout="Heading 1">Outline</Text-field> The basic objectives are: 1) Converting between systems of equations and matrices 2) Using Maple commands for elementary row operations 3) Using more general Maple commands on matrices.
<Text-field style="Heading 1" layout="Heading 1">Part 1: Converting between systems and matrices</Text-field> The text points out that the Gaussian elimination method we used on systems of equations can be performed in shorthand by working on the matrix of coefficients of the system. In Maple the command for converting from a system of equations to a matrix is GenerateMatrix. To convert back from a matrix to a system of equations, the command is GenerateEquations. Each of these commands has two forms, one for the matrix of coefficients, and one for the augmented matrix. These commands are part of the LinearAlgebra package. To convert from a system of equations to a matrix we first need a list of equations, and an ordered list of variables. eq1 := x + y + 2*z + w = 1; eq2 := 3*x - 4*y + z + w = 2; eq3 := 4*x - 3*y + 3*z + 2*w = 3; eqlist := [eq1, eq2, eq3]; varlist := [x, y, z, w]; 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If we want the matrix of coefficients, the command GenerateMatrix has three parameters: the list of equations, the list of variables, and the name `augmented`. It produces the augmented matrix. If we forget the augmented option, the command returns an ordered pair composed by the coefficient matrix and the vector of constants. M1 := GenerateMatrix(eqlist, varlist, `augmented`); (M2,b) := GenerateMatrix(eqlist, varlist); M2 := GenerateMatrix(eqlist, varlist)[1]; 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To convert back from a matrix to a system of equations we use the GenerateEquations command. To produce a system with the constants set to zero (that is, a homogeneous system) we use two parameters: the matrix of coefficients and the variable list. For a nonhomogeneous system, we either use a third parameter, a vector of constants, or we use the augmented matrix. homsys := GenerateEquations(M2,varlist); nonhomsys := GenerateEquations(M2,varlist,b); nonhomsys2 := GenerateEquations(M1,varlist); 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 Matrix(<< -2 | 3 | 0 >, < 3 | 5 | 7 >>); 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M= 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
<Text-field style="Heading 2" layout="Heading 2">Exercises</Text-field> 1) Use Maple to convert the system{x-y+2z-2w=1, 2x+y+3w=4, 2x+3y+2z=6} to an augmented matrix. 2) Use Maple to convert the augmented matrix 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 to a system of equations in x, y, z, and w. 3) Use the command N1 := RandomMatrix(3, 5); to generate a random 3 by 5 matrix named N1. Convert it to a system of equations in x, y, z, and w.
<Text-field style="Heading 1" layout="Heading 1">Part 2: Elementary row operations</Text-field> Once we have a system of equations converted to an augmented matrix, the next task is to use elementary row operations to perform Gaussian elimination on the matrix. The linalg package of Maple has a command corresponding to each type of elementary row operation. The command RowOperation(M, [r1, r2], scal); is used to add scal times row r2 of matrix M to row r1. The command RowOperation(M, r1, scal); is used to multiply row r1 of M by scal. The command RowOperation(M, [r1, r2]); is used to switch rows r1 and r2 of the matrix M. We use these operations to reduce the matrix M2 above to row echelon form. print(M1); 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 M3a := RowOperation(M1,[2,1],-3); 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 M3b := RowOperation(M3a,[3,1],-4); 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 M3c := RowOperation(M3b,[3,2],-1); NiQtSSVtcm93RzYjL0krbW9kdWxlbmFtZUc2IkksVHlwZXNldHRpbmdHSShfc3lzbGliR0YoNiUtSSNtaUdGJTY5USRNM2NGKC8lJ2ZhbWlseUdRMFRpbWVzfk5ld35Sb21hbkYoLyUlc2l6ZUdRIzEyRigvJSVib2xkR1EmZmFsc2VGKC8lJ2l0YWxpY0dRJXRydWVGKC8lKnVuZGVybGluZUdGOC8lKnN1YnNjcmlwdEdGOC8lLHN1cGVyc2NyaXB0R0Y4LyUrZm9yZWdyb3VuZEdRKlswLDAsMjU1XUYoLyUrYmFja2dyb3VuZEdRLlsyNTUsMjU1LDI1NV1GKC8lJ29wYXF1ZUdGOC8lK2V4ZWN1dGFibGVHRjgvJSlyZWFkb25seUdGOy8lKWNvbXBvc2VkR0Y4LyUqY29udmVydGVkR0Y4LyUraW1zZWxlY3RlZEdGOC8lLHBsYWNlaG9sZGVyR0Y4LyUwZm9udF9zdHlsZV9uYW1lR1EqMkR+T3V0cHV0RigvJSptYXRoY29sb3JHRkQvJS9tYXRoYmFja2dyb3VuZEdGRy8lK2ZvbnRmYW1pbHlHRjIvJSxtYXRodmFyaWFudEdRJ2l0YWxpY0YoLyUpbWF0aHNpemVHRjUtSSNtb0dGJTYzUSM6PUYoLyUlZm9ybUdRJmluZml4RigvJSZmZW5jZUdGOC8lKnNlcGFyYXRvckdGOC8lJ2xzcGFjZUdRL3RoaWNrbWF0aHNwYWNlRigvJSdyc3BhY2VHRltwLyUpc3RyZXRjaHlHRjgvJSpzeW1tZXRyaWNHRjgvJShtYXhzaXplR1EpaW5maW5pdHlGKC8lKG1pbnNpemVHUSIxRigvJShsYXJnZW9wR0Y4LyUubW92YWJsZWxpbWl0c0dGOC8lJ2FjY2VudEdGOC8lMGZvbnRfc3R5bGVfbmFtZUdGWC8lJXNpemVHRjUvJStmb3JlZ3JvdW5kR0ZELyUrYmFja2dyb3VuZEdGRy1GJDYlLUZfbzYzUSJbRigvRmNvUSdwcmVmaXhGKC9GZm9GO0Znby9Gam9RLnRoaW5tYXRoc3BhY2VGKC9GXXBGX3IvRl9wRjtGYHBGYnBGZXBGaHBGanBGXHFGXnFGYHFGYnFGZHEtRiQ2Iy1JJ210YWJsZUdGJTYlLUkkbXRyR0YlNictSSRtdGRHRiU2Iy1JI21uR0YlNjlGZ3BGMEYzRjYvRjpGOEY8Rj5GQEZCRkVGSEZKRkxGTkZQRlJGVEZWRllGZW5GZ24vRmpuUSdub3JtYWxGKEZcb0Zqci1GW3M2Iy1GXnM2OVEiMkYoRjBGM0Y2RmBzRjxGPkZARkJGRUZIRkpGTEZORlBGUkZURlZGWUZlbkZnbkZhc0Zcb0ZqckZqci1GaHI2Jy1GW3M2Iy1GXnM2OVEiMEYoRjBGM0Y2RmBzRjxGPkZARkJGRUZIRkpGTEZORlBGUkZURlZGWUZlbkZnbkZhc0Zcby1GW3M2Iy1GXnM2OVEpJm1pbnVzOzdGKEYwRjNGNkZgc0Y8Rj5GQEZCRkVGSEZKRkxGTkZQRlJGVEZWRllGZW5GZ25GYXNGXG8tRltzNiMtRl5zNjlRKSZtaW51czs1RihGMEYzRjZGYHNGPEY+RkBGQkZFRkhGSkZMRk5GUEZSRlRGVkZZRmVuRmduRmFzRlxvLUZbczYjLUZeczY5USkmbWludXM7MkYoRjBGM0Y2RmBzRjxGPkZARkJGRUZIRkpGTEZORlBGUkZURlZGWUZlbkZnbkZhc0Zcby1GW3M2Iy1GXnM2OVEpJm1pbnVzOzFGKEYwRjNGNkZgc0Y8Rj5GQEZCRkVGSEZKRkxGTkZQRlJGVEZWRllGZW5GZ25GYXNGXG8tRmhyNidGanNGanNGanNGanNGanMtRl9vNjNRIl1GKC9GY29RKHBvc3RmaXhGKEZdckZnb0Zeci9GXXBRMnZlcnl0aGlubWF0aHNwYWNlRihGYXJGYHBGYnBGZXBGaHBGanBGXHFGXnFGYHFGYnFGZHE3Iy1fRilJLG1wcmludHNsYXNoR0YoNiQ3Iz5JJE0zY0dGKC1JJ1JUQUJMRUdGKDYlIigrMk4pLUknTUFUUklYR0YoNiM3JTcnIiIiRl13IiIjRl13Rl13NyciIiEhIighIiYhIiMhIiI3J0Zgd0Zgd0Zgd0Zgd0Zgd0knTWF0cml4RzYkJSpwcm90ZWN0ZWRHRio3Iy1GZnc2Iy9JJCVpZEdGKEZndg== This completes Gaussian elimination on the system. If instead we want to perform Gauss-Jordan elimination, we continue on to the reduced row echelon form. M3d := RowOperation(M3c,2,-1/7); 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 M3e := RowOperation(M3d,[1,2],-1); 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
<Text-field style="Heading 2" layout="Heading 2">Exercises:</Text-field> 4) Use elementary row operations on the matrix N1 from exercise 3 to obtain a row equivalent matrix in echelon form. 5) Use more row operations to reduce N1 to a row equivalent matrix in reduced echelon form.
<Text-field style="Heading 1" layout="Heading 1">Part 3: Some more powerful linear algebra commands</Text-field> Gaussian elimination and Gauss Jordan elimination are standard techniques in linear algebra. Rather than use row operations one by one, they can be performed with the GaussianElimination and ReducedRowEchelonForm commands. GaussianElimination(M1); ReducedRowEchelonForm(M1); 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 Sometimes we do not need the reduced matrix, but only the number of nonzero rows in the reduced matrix. This is found using the Rank command. The transpose of a matrix is given by the Transpose command. Rank(M1); Transpose(M1); 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 We started this section by converting systems of equations into matrix form. The command LinearSolve(MatrixCoefficients, ConstantVector); finds the solution to a system which has MatrixCoefficients as the matrix of coefficients, and ConstantVector the vector of constants. gensol := LinearSolve(M2, b); 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 The _t0i are Maple-provided parameters in the solution vectors. We can find a translation vector by setting the parameters to zero. transvec := eval(gensol,{_t[2]=0, _t[3]=0}); 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Spanning vectors are obtained by setting each parameter to 1 in turn and subtracting off the translation vectors. svec1 := eval(gensol,{_t[2]=1, _t[3]=0}); spanvec1 := svec1- transvec; svec2 := eval(gensol,{_t[2]=0, _t[3]=1}); spanvec2 := svec2 - transvec; 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<Text-field style="Heading 2" layout="Heading 2">Exercise:</Text-field> 6) Find the general solution to the system of equations you generated in Exercise 3 above.