87 lines
1.6 KiB
Plaintext
87 lines
1.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"Zadanie 4.6"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from sympy import symbols, Matrix\n",
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"from numpy.linalg import eig\n",
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"\n",
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"A=np.matrix(QQ,5,3,[2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 31])\n",
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"print(A.transpose()*A)\n",
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"print((A.transpose()*A)^(-1))\n",
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"mm=(A.transpose()*A)^(-1)\n",
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"mm=(A.transpose()*A)^(-1)*A.transpose()\n",
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"print(mm)\n",
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"\n",
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"b1=np.vector([-1,0,1,0,1])\n",
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"mm1=mm*b1\n",
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"print(mm1)\n",
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"print((b1-A*mm1))\n",
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"b2=np.vector([1,1,1,1,1])\n",
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"mm2=mm*b2\n",
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"print(mm2)\n",
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"print((b2-A*mm2))\n",
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"\n",
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"b2 in (m.transpose()).image()"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Zadanie 4.7"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Zadanie 4.9"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python",
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"version": "3.10.9"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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