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"%plot --format svg"
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"# Gauss Elimination\n",
"### Solving sets of equations with matrix operations\n",
"\n",
"The number of dimensions of a matrix indicate the degrees of freedom of the system you are solving. \n",
"\n",
"If you have a set of known output, $y_{1},~y_{2},~...y_{N}$ and a set of equations that\n",
"relate unknown inputs, $x_{1},~x_{2},~...x_{N}$, then these can be written in a vector\n",
"matrix format as:\n",
"\n",
"$y=Ax$\n",
"\n",
"Consider a problem with 2 DOF:\n",
"\n",
"$x_{1}+3x_{2}=1$\n",
"\n",
"$2x_{1}+x_{2}=1$\n",
"\n",
"$\\left[ \\begin{array}{cc}\n",
"1 & 3 \\\\\n",
"2 & 1 \\end{array} \\right]\n",
"\\left[\\begin{array}{c} \n",
"x_{1} \\\\ \n",
"x_{2} \\end{array}\\right]=\n",
"\\left[\\begin{array}{c} \n",
"1 \\\\\n",
"1\\end{array}\\right]$\n",
"\n",
"The solution for $x_{1}$ and $x_{2}$ is the intersection of two lines:"
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"x21=[-2:2];\n",
"x11=1-3*x21;\n",
"x21=[-2:2];\n",
"x22=1-2*x21;\n",
"plot(x11,x21,x21,x22)"
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"ans =\n",
"\n",
" 0.40000\n",
" 0.20000\n",
"\n"
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"A=[1,3;2,1]; y=[1;1];\n",
"A\\y % matlab's Ax=y solution for x"
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"For a $3\\times3$ matrix, the solution is the intersection of the 3 planes.\n",
"\n",
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"\n",
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"N=25;\n",
"x11=linspace(-2,2,N);\n",
"x12=linspace(-2,2,N);\n",
"[X11,X12]=meshgrid(x11,x12);\n",
"X13=1-10*X11-2*X12;\n",
"\n",
"x21=linspace(-2,2,N);\n",
"x22=linspace(-2,2,N);\n",
"[X21,X22]=meshgrid(x21,x22);\n",
"X23=1-2*X11-X22;\n",
"\n",
"x31=linspace(-2,2,N);\n",
"x32=linspace(-2,2,N);\n",
"[X31,X32]=meshgrid(x31,x32);\n",
"X33=1/10*(1-X31-2*X32);\n",
"\n",
"mesh(X11,X12,X13);\n",
"hold on;\n",
"mesh(X21,X22,X23)\n",
"mesh(X31,X32,X33)\n",
"x=[10,2, 1;2,1, 1; 1, 2, 10]\\[1;1;1];\n",
"plot3(x(1),x(2),x(3),'o')\n",
"xlabel('x1')\n",
"ylabel('x2')\n",
"zlabel('x3')\n",
"view(10,45)"
]
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"cell_type": "markdown",
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"After 3 DOF problems, the solutions are described as *hyperplane* intersections. Which are even harder to visualize"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Gauss elimination\n",
"### Solving sets of equations systematically\n",
"\n",
"$\\left[ \\begin{array}{ccc|c}\n",
" & A & & y \\\\\n",
"10 & 2 & 1 & 1\\\\\n",
"2 & 1 & 1 & 1 \\\\\n",
"1 & 2 & 10 & 1\\end{array} \n",
"\\right] $\n",
"\n",
"Ay(2,:)-Ay(1,:)/5 = ([2 1 1 1]-1/5[10 2 1 1])\n",
"\n",
"$\\left[ \\begin{array}{ccc|c}\n",
" & A & & y \\\\\n",
"10 & 2 & 1 & 1\\\\\n",
"0 & 3/5 & 4/5 & 4/5 \\\\\n",
"1 & 2 & 10 & 1\\end{array} \n",
"\\right] $\n",
"\n",
"Ay(3,:)-Ay(1,:)/10 = ([1 2 10 1]-1/10[10 2 1 1])\n",
"\n",
"$\\left[ \\begin{array}{ccc|c}\n",
" & A & & y \\\\\n",
"10 & 2 & 1 & 1\\\\\n",
"0 & 3/5 & 4/5 & 4/5 \\\\\n",
"0 & 1.8 & 9.9 & 0.9\\end{array} \n",
"\\right] $\n",
"\n",
"Ay(3,:)-1.8\\*5/3\\*Ay(2,:) = ([0 1.8 9.9 0.9]-3\\*[0 3/5 4/5 4/5])\n",
"\n",
"$\\left[ \\begin{array}{ccc|c}\n",
" & A & & y \\\\\n",
"10 & 2 & 1 & 1\\\\\n",
"0 & 3/5 & 4/5 & 4/5 \\\\\n",
"0 & 0 & 7.5 & -1.5\\end{array} \n",
"\\right] $\n",
"\n",
"now, $7.5x_{3}=-1.5$ so $x_{3}=-\\frac{1}{5}$\n",
"\n",
"then, $3/5x_{2}+4/5(-1/5)=1$ so $x_{2}=\\frac{8}{5}$\n",
"\n",
"finally, $10x_{1}+2(8/5)+1(-\\frac{1}{5})=1$"
]
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"source": [
"Consider the problem again from the intro to Linear Algebra, 4 masses are connected in series to 4 springs with K=10 N/m. What are the final positions of the masses? \n",
"\n",
"![Springs-masses](../lecture_09/mass_springs.svg)\n",
"\n",
"The masses haves the following amounts, 1, 2, 3, and 4 kg for masses 1-4. Using a FBD for each mass:\n",
"\n",
"$m_{1}g+k(x_{2}-x_{1})-kx_{1}=0$\n",
"\n",
"$m_{2}g+k(x_{3}-x_{2})-k(x_{2}-x_{1})=0$\n",
"\n",
"$m_{3}g+k(x_{4}-x_{3})-k(x_{3}-x_{2})=0$\n",
"\n",
"$m_{4}g-k(x_{4}-x_{3})=0$\n",
"\n",
"in matrix form:\n",
"\n",
"$\\left[ \\begin{array}{cccc}\n",
"2k & -k & 0 & 0 \\\\\n",
"-k & 2k & -k & 0 \\\\\n",
"0 & -k & 2k & -k \\\\\n",
"0 & 0 & -k & k \\end{array} \\right]\n",
"\\left[ \\begin{array}{c}\n",
"x_{1} \\\\\n",
"x_{2} \\\\\n",
"x_{3} \\\\\n",
"x_{4} \\end{array} \\right]=\n",
"\\left[ \\begin{array}{c}\n",
"m_{1}g \\\\\n",
"m_{2}g \\\\\n",
"m_{3}g \\\\\n",
"m_{4}g \\end{array} \\right]$"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"K =\n",
"\n",
" 20 -10 0 0\n",
" -10 20 -10 0\n",
" 0 -10 20 -10\n",
" 0 0 -10 10\n",
"\n",
"y =\n",
"\n",
" 9.8100\n",
" 19.6200\n",
" 29.4300\n",
" 39.2400\n",
"\n"
]
}
],
"source": [
"k=10; % N/m\n",
"m1=1; % kg\n",
"m2=2;\n",
"m3=3;\n",
"m4=4;\n",
"g=9.81; % m/s^2\n",
"K=[2*k -k 0 0; -k 2*k -k 0; 0 -k 2*k -k; 0 0 -k k]\n",
"y=[m1*g;m2*g;m3*g;m4*g]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"K1 =\n",
"\n",
" 20.00000 -10.00000 0.00000 0.00000 9.81000\n",
" 0.00000 15.00000 -10.00000 0.00000 24.52500\n",
" 0.00000 -10.00000 20.00000 -10.00000 29.43000\n",
" 0.00000 0.00000 -10.00000 10.00000 39.24000\n",
"\n"
]
}
],
"source": [
"K1=[K y];\n",
"K1(2,:)=K1(1,:)/2+K1(2,:)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"K2 =\n",
"\n",
" 20.00000 -10.00000 0.00000 0.00000 9.81000\n",
" 0.00000 15.00000 -10.00000 0.00000 24.52500\n",
" 0.00000 0.00000 13.33333 -10.00000 45.78000\n",
" 0.00000 0.00000 -10.00000 10.00000 39.24000\n",
"\n"
]
}
],
"source": [
"K2=K1;\n",
"K2(3,:)=K1(2,:)*2/3+K1(3,:)\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"K2 =\n",
"\n",
" 20.00000 -10.00000 0.00000 0.00000 9.81000\n",
" 0.00000 15.00000 -10.00000 0.00000 24.52500\n",
" 0.00000 0.00000 13.33333 -10.00000 45.78000\n",
" 0.00000 0.00000 0.00000 2.50000 73.57500\n",
"\n"
]
}
],
"source": [
"K2(4,:)=-K2(3,:)*K2(4,3)/K2(3,3)+K2(4,:)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"x4 = 29.430\n",
"x3 = 25.506\n",
"x2 = 18.639\n",
"x1 = 9.8100\n"
]
}
],
"source": [
"yp=K2(:,5);\n",
"x4=yp(4)/K2(4,4)\n",
"x3=(yp(3)+10*x4)/K2(3,3)\n",
"x2=(yp(2)+10*x3)/K2(2,2)\n",
"x1=(yp(1)+10*x2)/K2(1,1)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ans =\n",
"\n",
" 9.8100\n",
" 18.6390\n",
" 25.5060\n",
" 29.4300\n",
"\n"
]
}
],
"source": [
"K\\y"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Automate Gauss Elimination\n",
"\n",
"We can automate Gauss elimination with a function whose input is A and y:\n",
"\n",
"`x=GaussNaive(A,y)`"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"x =\n",
"\n",
" 9.8100\n",
" 18.6390\n",
" 25.5060\n",
" 29.4300\n",
"\n"
]
}
],
"source": [
"x=GaussNaive(K,y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Problem (Diagonal element is zero)\n",
"\n",
"If a diagonal element is 0 or very small either:\n",
"\n",
"1. no solution found\n",
"2. errors are introduced \n",
"\n",
"Therefore, we would want to pivot before applying Gauss elimination\n",
"\n",
"Consider:\n",
"\n",
"(a) $\\left[ \\begin{array}{cccc}\n",
"0 & 2 & 3 \\\\\n",
"4 & 6 & 7 \\\\\n",
"2 & -3 & 6 \\end{array} \\right]\n",
"\\left[ \\begin{array}{c}\n",
"x_{1} \\\\\n",
"x_{2} \\\\\n",
"x_{3} \\end{array} \\right]=\n",
"\\left[ \\begin{array}{c}\n",
"8 \\\\\n",
"-3 \\\\\n",
"5\\end{array} \\right]$\n",
"\n",
"(b) $\\left[ \\begin{array}{cccc}\n",
"0.0003 & 3.0000 \\\\\n",
"1.0000 & 1.0000 \\end{array} \\right]\n",
"\\left[ \\begin{array}{c}\n",
"x_{1} \\\\\n",
"x_{2} \\end{array} \\right]=\n",
"\\left[ \\begin{array}{c}\n",
"2.0001 \\\\\n",
"1.0000 \\end{array} \\right]$"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"warning: division by zero\n",
"warning: called from\n",
" GaussNaive at line 16 column 12\n",
"warning: division by zero\n",
"warning: division by zero\n",
"ans =\n",
"\n",
" NaN\n",
" NaN\n",
" NaN\n",
"\n",
"ans =\n",
"\n",
" -5.423913\n",
" 0.021739\n",
" 2.652174\n",
"\n"
]
}
],
"source": [
"format short\n",
"Aa=[0,2,3;4,6,7;2,-3,6]; ya=[8;-3;5];\n",
"GaussNaive(Aa,ya)\n",
"Aa\\ya"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"x =\n",
"\n",
" -5.423913\n",
" 0.021739\n",
" 2.652174\n",
"\n",
"Aug =\n",
"\n",
" 4.00000 6.00000 7.00000 -3.00000\n",
" 0.00000 -6.00000 2.50000 6.50000\n",
" 0.00000 0.00000 3.83333 10.16667\n",
"\n",
"npivots = 2\n"
]
}
],
"source": [
"[x,Aug,npivots]=GaussPivot(Aa,ya)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ans =\n",
"\n",
" 0.325665420556713\n",
" 0.666666666666667\n",
"\n",
"ans =\n",
"\n",
" 0.333333333333333\n",
" 0.666666666666667\n",
"\n"
]
}
],
"source": [
"format long\n",
"Ab=[0.3E-13,3.0000;1.0000,1.0000];yb=[2+0.1e-13;1.0000];\n",
"GaussNaive(Ab,yb)\n",
"Ab\\yb"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"x =\n",
"\n",
" 0.333333333333333\n",
" 0.666666666666667\n",
"\n",
"Aug =\n",
"\n",
" 1.000000000000000 1.000000000000000 1.000000000000000\n",
" 0.000000000000000 2.999999999999970 1.999999999999980\n",
"\n",
"npivots = 1\n",
"ans =\n",
"\n",
" 0.333333333333333\n",
" 0.666666666666667\n",
"\n"
]
}
],
"source": [
"[x,Aug,npivots]=GaussPivot(Ab,yb)\n",
"Ab\\yb\n",
"format short"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ans = -3.0000\n",
"ans = 3.0000\n"
]
}
],
"source": [
"% determinant is (-1)^(number_of_pivots)*diagonal_elements\n",
"det(Ab)\n",
"Aug(1,1)*Aug(2,2)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Spring-Mass System again\n",
"Now, 4 masses are connected in series to 4 springs with $K_{1}$=10 N/m, $K_{2}$=5 N/m, \n",
"$K_{3}$=2 N/m \n",
"and $K_{4}$=1 N/m. What are the final positions of the masses? \n",
"\n",
"![Springs-masses](../lecture_09/mass_springs.svg)\n",
"\n",
"The masses have the following amounts, 1, 2, 3, and 4 kg for masses 1-4. Using a FBD for each mass:\n",
"\n",
"$m_{1}g+k_{2}(x_{2}-x_{1})-k_{1}x_{1}=0$\n",
"\n",
"$m_{2}g+k_{3}(x_{3}-x_{2})-k_{2}(x_{2}-x_{1})=0$\n",
"\n",
"$m_{3}g+k_{4}(x_{4}-x_{3})-k_{3}(x_{3}-x_{2})=0$\n",
"\n",
"$m_{4}g-k_{4}(x_{4}-x_{3})=0$\n",
"\n",
"in matrix form:\n",
"\n",
"$\\left[ \\begin{array}{cccc}\n",
"k_1+k_2 & -k_2 & 0 & 0 \\\\\n",
"-k_2 & k_2+k_3 & -k_3 & 0 \\\\\n",
"0 & -k_3 & k_3+k_4 & -k_4 \\\\\n",
"0 & 0 & -k_4 & k_4 \\end{array} \\right]\n",
"\\left[ \\begin{array}{c}\n",
"x_{1} \\\\\n",
"x_{2} \\\\\n",
"x_{3} \\\\\n",
"x_{4} \\end{array} \\right]=\n",
"\\left[ \\begin{array}{c}\n",
"m_{1}g \\\\\n",
"m_{2}g \\\\\n",
"m_{3}g \\\\\n",
"m_{4}g \\end{array} \\right]$"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"K =\n",
"\n",
" 15 -5 0 0\n",
" -5 7 -2 0\n",
" 0 -2 3 -1\n",
" 0 0 -1 1\n",
"\n",
"y =\n",
"\n",
" 9.8100\n",
" 19.6200\n",
" 29.4300\n",
" 39.2400\n",
"\n"
]
}
],
"source": [
"k1=10; k2=5;k3=2;k4=1; % N/m\n",
"m1=1; % kg\n",
"m2=2;\n",
"m3=3;\n",
"m4=4;\n",
"g=9.81; % m/s^2\n",
"K=[k1+k2 -k2 0 0; -k2, k2+k3, -k3 0; 0 -k3, k3+k4, -k4; 0 0 -k4 k4]\n",
"y=[m1*g;m2*g;m3*g;m4*g]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Tridiagonal matrix\n",
"\n",
"This matrix, K, could be rewritten as 3 vectors e, f and g\n",
"\n",
"$e=\\left[ \\begin{array}{c}\n",
"0 \\\\\n",
"-5 \\\\\n",
"-2 \\\\\n",
"-1 \\end{array} \\right]$\n",
"\n",
"$f=\\left[ \\begin{array}{c}\n",
"15 \\\\\n",
"7 \\\\\n",
"3 \\\\\n",
"1 \\end{array} \\right]$\n",
"\n",
"$g=\\left[ \\begin{array}{c}\n",
"-5 \\\\\n",
"-2 \\\\\n",
"-1 \\\\\n",
"0 \\end{array} \\right]$\n",
"\n",
"Where all other components are 0 and the length of the vectors are n and the first component of e and the last component of g are zero\n",
"\n",
"`e(1)=0` \n",
"\n",
"`g(end)=0`\n",
"\n",
"No need to pivot and number of calculations reduced enormously.\n",
"\n",
"|method |Number of Floating point operations for n$\\times$n-matrix|\n",
"|----------------|---------|\n",
"| Gauss | n-cubed |\n",
"| Tridiagonal | n |"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ans =\n",
"\n",
" 9.8100 27.4680 61.8030 101.0430\n",
"\n",
"ans =\n",
"\n",
" 9.8100\n",
" 27.4680\n",
" 61.8030\n",
" 101.0430\n",
"\n"
]
}
],
"source": [
"e=[0;-5;-2;-1];\n",
"g=[-5;-2;-1;0];\n",
"f=[15;7;3;1];\n",
"Tridiag(e,f,g,y)\n",
"K\\y\n"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"% tic ... t=toc \n",
"% is Matlab timer used for debugging programs\n",
"t_GE = zeros(1,100);\n",
"t_GE_tridiag = zeros(1,100);\n",
"t_TD = zeros(1,100);\n",
"%for n = 1:200\n",
"for n=1:100\n",
" A = rand(n,n);\n",
" e = rand(n,1); e(1)=0;\n",
" f = rand(n,1);\n",
" g = rand(n,1); g(end)=0;\n",
" Atd=diag(f, 0) - diag(e(2:n), -1) - diag(g(1:n-1), 1);\n",
" b = rand(n,1);\n",
" tic;\n",
" x = GaussPivot(A,b);\n",
" t_GE(n) = toc;\n",
" tic;\n",
" x = A\\b;\n",
" t_GE_tridiag(n) = toc;\n",
" tic;\n",
" x = Tridiag(e,f,g,b);\n",
" t_TD(n) = toc;\n",
"end"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [
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"text/plain": [
"<IPython.core.display.SVG object>"
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},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"n=1:100;\n",
"loglog(n,t_GE,n,t_TD,n,t_GE_tridiag)\n",
"legend('Gauss elim','Matlab \\','TriDiag')\n",
"xlabel('number of elements')\n",
"ylabel('time (s)')"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"x =\n",
"\n",
" 9.8100\n",
" 27.4680\n",
" 61.8030\n",
" 101.0430\n",
"\n",
"Aug =\n",
"\n",
" 15.00000 -5.00000 0.00000 0.00000 9.81000\n",
" 0.00000 5.33333 -2.00000 0.00000 22.89000\n",
" 0.00000 0.00000 2.25000 -1.00000 38.01375\n",
" 0.00000 0.00000 0.00000 0.55556 56.13500\n",
"\n",
"npivots = 0\n"
]
}
],
"source": [
"[x,Aug,npivots]=GaussPivot(K,y)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A =\n",
"\n",
" 15.00000 -5.00000 0.00000 0.00000\n",
" 0.00000 5.33333 -2.00000 0.00000\n",
" 0.00000 0.00000 2.25000 -1.00000\n",
" 0.00000 0.00000 0.00000 0.55556\n",
"\n"
]
}
],
"source": [
"A=Aug(1:4,1:4)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ans = 100.00\n",
"detA = 100.00\n"
]
}
],
"source": [
"det(A)\n",
"detA=A(1,1)*A(2,2)*A(3,3)*A(4,4)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
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"display_name": "Octave",
"language": "octave",
"name": "octave"
},
"language_info": {
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"help_links": [
{
"text": "MetaKernel Magics",
"url": "https://github.com/calysto/metakernel/blob/master/metakernel/magics/README.md"
}
],
"mimetype": "text/x-octave",
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