{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Zadanie 4.6" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "ename": "NameError", "evalue": "name 'matrix' is not defined", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", "Cell \u001b[1;32mIn[1], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m A\u001b[38;5;241m=\u001b[39m\u001b[43mmatrix\u001b[49m(QQ,\u001b[38;5;241m5\u001b[39m,\u001b[38;5;241m3\u001b[39m,[\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m4\u001b[39m, \u001b[38;5;241m6\u001b[39m, \u001b[38;5;241m8\u001b[39m, \u001b[38;5;241m10\u001b[39m, \u001b[38;5;241m12\u001b[39m, \u001b[38;5;241m14\u001b[39m, \u001b[38;5;241m16\u001b[39m, \u001b[38;5;241m18\u001b[39m, \u001b[38;5;241m20\u001b[39m, \u001b[38;5;241m22\u001b[39m, \u001b[38;5;241m24\u001b[39m, \u001b[38;5;241m26\u001b[39m, \u001b[38;5;241m28\u001b[39m, \u001b[38;5;241m31\u001b[39m])\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mA =\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(A, \u001b[38;5;124m'\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n", "\u001b[1;31mNameError\u001b[0m: name 'matrix' is not defined" ] } ], "source": [ "A=matrix(QQ,5,3,[2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 31])\n", "print('A =')\n", "print(A, '\\n')\n", "\n", "print('b =')\n", "b=vector(QQ,[-1,0,1,0,1])\n", "print(b, '\\n')\n", "\n", "print('A^T * A =')\n", "print(A.transpose()*A, '\\n')\n", "print('Macierz A^T*A jest kwadratowa, więc rozwiązanie istnieje\\n')\n", "\n", "u=(A.transpose()*A)^(-1)*A.transpose()*b\n", "print('u = (A^T * A)^-1 * A^T * b =')\n", "print(u, '\\n')\n", "\n", "\n", "print('b - A * u = ')\n", "print(b - A * u, '\\n')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "

Zadanie 6

\n", "\n", "Rozwiąż układ równań $Ax=b$ metodą przybliżoną, gdzie\n", "\n", "$$A=\\left(\\begin{array}{rrr}\n", "2 & 4 & 6 \\\\\n", "8 & 10 & 12 \\\\\n", "14 & 16 & 18 \\\\\n", "20 & 22 & 24 \\\\\n", "26 & 28 & 31\n", "\\end{array}\\right)$$\n", "\n", "oraz $b=(-1,0,1,0,1)$." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Zadanie 4.7\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "

Zadanie 7

\n", "\n", "Przybliż funkcją $f(t)=a+be^{t}$ zbiór punktów $(1,1)$, $(2,3)$, $(4,5)$ metodą z zadania 6.\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "zbior punktów = [(1, 1), (2, 3), (4, 5)]\n" ] }, { "ename": "NameError", "evalue": "name 'matrix' is not defined", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", "Cell \u001b[1;32mIn[2], line 3\u001b[0m\n\u001b[0;32m 1\u001b[0m zbior\u001b[38;5;241m=\u001b[39m[(\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m1\u001b[39m),(\u001b[38;5;241m2\u001b[39m,\u001b[38;5;241m3\u001b[39m),(\u001b[38;5;241m4\u001b[39m,\u001b[38;5;241m5\u001b[39m)]\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mzbior punktów = \u001b[39m\u001b[38;5;124m'\u001b[39m, zbior)\n\u001b[1;32m----> 3\u001b[0m m\u001b[38;5;241m=\u001b[39m\u001b[43mmatrix\u001b[49m(\u001b[38;5;241m3\u001b[39m,\u001b[38;5;241m2\u001b[39m,[\u001b[38;5;241m1\u001b[39m,exp(\u001b[38;5;241m1.0\u001b[39m),\u001b[38;5;241m1\u001b[39m,exp(\u001b[38;5;241m2.0\u001b[39m),\u001b[38;5;241m1\u001b[39m,exp(\u001b[38;5;241m4.0\u001b[39m)])\n\u001b[0;32m 5\u001b[0m a,b,t\u001b[38;5;241m=\u001b[39mvar(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124ma,b,t\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 7\u001b[0m m\u001b[38;5;241m*\u001b[39mvector([a,b])\u001b[38;5;241m-\u001b[39mvector([\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m3\u001b[39m,\u001b[38;5;241m5\u001b[39m])\n", "\u001b[1;31mNameError\u001b[0m: name 'matrix' is not defined" ] } ], "source": [ "zbior=[(1,1),(2,3),(4,5)]\n", "print('zbior punktów = ', zbior)\n", "m=matrix(3,2,[1,exp(1.0),1,exp(2.0),1,exp(4.0)])\n", "\n", "a,b,t=var('a,b,t')\n", "\n", "m*vector([a,b])-vector([1,3,5])\n", "\n", "print('\\n (m^T * m)^-1 * m^T * vector =')\n", "z = (m.transpose()*m)^(-1)*m.transpose()*vector([1,3,5])\n", "print(z)\n", "\n", "plot(z[0] +z[1]*exp(t),(t,0,4))+sum([point(x) for x in zbior])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Zadanie 4.9" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "

Zadanie 9

\n", "\n", "Znajdź bazę ortonormalnych wektorów własnych dla macierzy\n", "\n", "$$\\left(\\begin{array}{rrr}\n", "1 & 1 & 0 \\\\\n", "1 & 2 & 2 \\\\\n", "0 & 2 & 3\n", "\\end{array}\\right)$$" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "ename": "NameError", "evalue": "name 'matrix' is not defined", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", "Cell \u001b[1;32mIn[3], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m m\u001b[38;5;241m=\u001b[39m\u001b[43mmatrix\u001b[49m(\u001b[38;5;241m3\u001b[39m,\u001b[38;5;241m3\u001b[39m,[\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m0\u001b[39m,\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m2\u001b[39m,\u001b[38;5;241m2\u001b[39m,\u001b[38;5;241m0\u001b[39m,\u001b[38;5;241m2\u001b[39m,\u001b[38;5;241m3\u001b[39m])\n\u001b[0;32m 3\u001b[0m \u001b[38;5;66;03m#wartosci wlasne\u001b[39;00m\n\u001b[0;32m 4\u001b[0m eigenvalues \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mm\u001b[38;5;241m.\u001b[39meigvals(matrix)\n", "\u001b[1;31mNameError\u001b[0m: name 'matrix' is not defined" ] } ], "source": [ "m=matrix(3,3,[1,1,0,1,2,2,0,2,3])\n", "\n", "#wartosci wlasne\n", "eigenvalues = np.m.eigvals(matrix)\n", "\n", "eigen=m.right_eigenvectors()\n", "e1=eigen[0][1][0]\n", "e2=eigen[1][1][0]\n", "print(e1.dot_product(e2))\n", "e3=eigen[2][1][0]\n", "print(e3.dot_product(e1))\n", "print(e2.dot_product(e3))\n", "\n", "#znormalizuj wektor wlasny\n", "\n", "#czy wektory wlasne sa ortogonalne?\n", "\n", "#postac ortonormalna i normalizacja" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.9" } }, "nbformat": 4, "nbformat_minor": 2 }