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@PavelEprines
Created February 6, 2019 19:49
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{
"cells": [
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"def L(xnew, xk, yk): # считаем многочлен Лагранжа\n",
" sum = 0\n",
" for k in range(len(xk)):\n",
" basis = 1\n",
" for i in range(len(xk)):\n",
" if k == i:\n",
" continue\n",
" basis *= (xnew - xk[i]) / (xk[k] - xk[i])\n",
" sum += yk[k]*basis\n",
" return sum"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2.0"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x1 = [0, 1] # проверка работы на элементарном случае\n",
"y1 = [0, 1]\n",
"L(2, x1, y1)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt #проверяем \n",
"plt.plot([1, 2], [8, 9], 'o-')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"def func(x): # заводим функцию\n",
" return 1/(1+x**2)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"x2 = [] #\n",
"y2 = []\n",
"for i in range(-100, 100):\n",
" y2.append(func(i/100))\n",
" x2.append(i/100)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x2, y2, 'o-') # график без интреполяции\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"x3 = [-0.5, 0, 0.5] #\n",
"y3 = []\n",
"for i in x3:\n",
" y3.append(func(i))\n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
"x4 = [] #\n",
"y4 = []\n",
"for i in range(-100, 100):\n",
" w = i / 100\n",
" q = L(w, x3, y3)\n",
" y4.append(q) "
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD8CAYAAACMwORRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAHf9JREFUeJzt3X+QXfV53/H3h0UywnYsMNsUrxCSPUKNCIZNdzBTz8Q4SZGgtbSxXSyNmULqROM02MUmTGBgAKtm3Ji4TDpVx1U81HGcIGSabNatMvIPYDLtGJelkiCCCtZyDbuiYW0jMg4ySOLpH/dcc9i9P87ePffec879vGY0uvfcs3cfnV09+93n+5zvVxGBmZlVy2n9DsDMzPLn5G5mVkFO7mZmFeTkbmZWQU7uZmYV5ORuZlZBTu5mZhXk5G5mVkFO7mZmFXR6vz7xOeecE2vWrOnXpzczK6XHHnvshxEx3O68viX3NWvWMDU11a9Pb2ZWSpJ+kOU8l2XMzCrIyd3MrIKc3M3MKsjJ3cysgpzczcwqqG23jKR7gX8OvBARv9jgdQF/CFwFvAxcFxH/O+9AzbphYv8sd04e4tjxEy3PO03wWsDIyhXctHE946MjPYrQrDNqtxOTpF8GfgJ8pUlyvwr4BLXk/h7gDyPiPe0+8djYWLgV0nolaxJfLCd96zVJj0XEWLvz2o7cI+KvJa1pccoWaok/gEckrZR0bkQ8nzlasxx1K5E38loyNpo9dpwb7j/ADfcfYEjiVIQTvvVVHjcxjQDPpZ7PJMcWJHdJ24HtAKtXr87hU5vV9DKht3Mq+W04nfCd6K3X8kjuanCsYa0nInYBu6BWlsnhc9sAK1JCb8eJ3notj+Q+A5yXer4KOJrD+5otUKaE3owTvfVCHsl9Erhe0m5qE6ovud5ueatCUm9k9thxPnX/AaZ+8GM+O35Rv8OxCsnSCnkfcDlwjqQZ4A5gGUBEfBHYS61TZppaK+RvdCtYGywT+2e5e99hZo8d7+rnOevMZdzxgQtbjp7TsYgmdccOBfDVR57lq488mykWsyzatkJ2i1shrZXbJp7gTx95Npck2s12xXTSr3fJ5MFJ3prJ2grp5G6Fklf5pZ/JMa/fOAR89LLVLtfYGzi5W+ksdbRexNFuHom+iP8u6x8ndyuNpYzWy5T4lpLoPYq3Oid3K4VORutVSHSd/kAr0w8z6w4ndyu0TpNb1frCO7kOVfjhZp1zcrdC6iSZDcpodbG/xQzKdbE3cnK3wlls8hrEEap/+Fk7Tu5WGE5Yi+cfhNaMk7sVgpNU5/xD0Rpxcre+cmLKj39AWpqTu/WNJwbz5x+WVufkbj232ATkEebi+Rpb1uR+Wi+Cseqb2D/LLX/+ROakc9aZy7jnI5c46SzS+OgIB+64gmsuW91wl5z5AvjTR55lYv9st0OzgsljPXczPvP1Qxw/carteR5J5uOz4xcxdv7ZmUbxAdy45yCASzQDxCN3W5KJ/bNc8plv8OLL7UfsHq3nazGj+FMRfOr+A9w28URPYrP+y5TcJW2SdFjStKSbG7x+vqRvS3pc0sOSVuUfqhXNbRNP8Kn7D7QdOQq45rLV7L/9Co8cu+Cz4xdxz0cuYeWKZS3Pq28KMrrjGy7TDIC2yV3SELATuBLYAGyTtGHeaX8AfCUi3g3sAD6Xd6BWLBP7ZzN1xHi03huLGcW/+PIJbvnzJ5zgKy7LyP1SYDoijkTEq8BuYMu8czYA304eP9TgdauQif2z3LjnYNvEvnLFMo/We6w+ih9S6xR//MQp7pw81KOorB+yJPcR4LnU85nkWNpB4EPJ418H3irp7UsPz4qmXoppt53cimVD3Ln5wh5FZWnjoyN84eqL247gjx0/4RJNhWVJ7o2+R+b/z/5d4H2S9gPvA2aBkwveSNouaUrS1Nzc3KKDtf5aTCnmcx+8yCP2PhofHeGjLtEMtCzJfQY4L/V8FXA0fUJEHI2ID0bEKHBrcuyl+W8UEbsiYiwixoaHh5cQtvVallKMJ06LJetEq0s01ZQluT8KrJO0VtJyYCswmT5B0jmS6u91C3BvvmFaP2UpxQxJnjgtoPpE61lntk7wLtFUT9vkHhEngeuBfcBTwJ6IOCRph6TNyWmXA4clPQ38PHBXl+K1HstSihHwhasv9mi9wO74wIWsWDbU8hyXaKrFa8tYU/VSTKsRu+84LY+s69KsXLGMA3dc0aOobLG8towtiUsx1eMSzWBxcrcFXIqpNpdoBoOTu71B1q6Yj1622om9pMZHR/jcBy9yF03FObnbz9SX7XUppvoWU6Lx6L2cnNwNeH3E3mrZXpdiqidLiebGPQed4EvIyd0yjdhdiqmmLCWaUxGuv5eQk7u13WjDpZhqy1KiOX7ilEfwJePkPsCybLSxYtmQSzEDol2Jxht+lIuT+4DKsufpkOQFwAZIvUTTarlg78laHk7uAyrLnqcesQ+e+nLBrUbw9T1ZneCLzcl9AE3sn2275+nKFcuc2AdUlhG8J1mLz8l9wNRbHlvxRhuWZcMP3+RUbE7uAyRLy6M32rC6LBt++Can4jq93wFY77Srs9f3PDWr++z4RYydf3bL1UHrvwl6QFAsTu4Dol2d3aUYa6aetG+4/0DD1+v19/S51n8uywyAdnV2tzxaO+OjI21vcnL9vVgyJXdJmyQdljQt6eYGr6+W9JCk/ZIel3RV/qFaJ7LU2d3yaFm0u8nJ9fdiaZvcJQ0BO4ErgQ3ANkkb5p12G7Xt90ap7bH6n/IO1DqTpc7uxG5ZZGmRdP97cWQZuV8KTEfEkYh4FdgNbJl3TgA/lzx+G3A0vxCtU66zW97qLZLNuP+9OLIk9xHgudTzmeRY2p3ANZJmgL3AJ3KJzjrmOrt1i+vv5ZAluTf6HWx+AXcb8OWIWAVcBfyJpAXvLWm7pClJU3Nzc4uP1jJxnd26zfX34suS3GeA81LPV7Gw7PIxYA9ARHwHOAM4Z/4bRcSuiBiLiLHh4eHOIra2XGe3bnP9vfiyJPdHgXWS1kpaTm3CdHLeOc8Cvwog6ReoJXcPzfvAdXbrFdffi61tco+Ik8D1wD7gKWpdMYck7ZC0OTntRuC3JB0E7gOui2hRE7CucJ3des319+LK1OceEXsj4oKIeFdE3JUcuz0iJpPHT0bEeyPi4oi4JCK+0c2gbSHX2a1fXH8vJt+hWhGus1u/uP5eTF5bpgJcZ7d+8/ozxeORe8m5zm5F4fp7sTi5l5jr7FY0rr8Xh5N7ibnObkXj+ntxuOZeUq6zW1G5/l4MHrmXkOvsVnSuv/efk3vJuM5uZeH6e385uZfM3fsOu85upZCl/n73vsM9jGiwOLmXzOyx401fc53diqbd+jOzx4579N4lTu4lMrF/tuH6y+A6uxVXu/q7FxfrDif3kqhPojaqtAvX2a3YWtXfPbnaHU7uJdBuEjVwS5kVW73+3ownV/Pn5F5w9RF7q0nUkZUrehiRWWfGR0dafq/65qZ8ObkXWJa2xxXLhrhp4/oeRmXWuVbfq97cI19O7gXWru3Rk6hWNllubnJ7ZD4yJXdJmyQdljQt6eYGr98j6UDy52lJx/IPdfC0a3v0JKqVUbubm9wemY+2a8tIGgJ2Av+U2mbZj0qajIgn6+dExKdS538CGO1CrAOl3vbYqCDjEbuVWf379sY9B5uWHL32zNJlGblfCkxHxJGIeBXYDWxpcf42avuoWofc9mhVV7+5ye2R3ZMluY8Az6WezyTHFpB0PrAWeLDJ69slTUmampubW2ysA8FtjzYo3B7ZXVmSe6ObIpu1b2wFHoiIhrOAEbErIsYiYmx4eDhrjAOl3SSq2x6tStq1R3pytXNZkvsMcF7q+SrgaJNzt+KSzJK0m0R126NVTavvaU+udi5Lcn8UWCdpraTl1BL45PyTJK0HzgK+k2+Ig8Nrx9gg8toz3dE2uUfESeB6YB/wFLAnIg5J2iFpc+rUbcDuiBZ33FhTnkS1Qea1Z/KXaZu9iNgL7J137PZ5z+/ML6zB4klUG3TttuarT676/0F2vkO1ADyJaubJ1bw5uReAJ1HNajy5mh8n9z7zJKrZ6zy5mh8n9z7yJKrZQp5czYeTe594EtWsMd+5mg8n9z7xJKpZc55cXTon9z7xJKpZa55cXRon9z7wJKpZe55cXRon9z64e99hT6KaZdBuctXlmeYy3aFq+ZnYP9u0JONJVLM3anfnaqvy5qDzyL2H6h0yzXgS1WyhVpOrApdmmnBy76HPfP1Q0w4ZT6KaNXfTxvVNN5a4cc9BJ/gGnNx7ZGL/LC++fKLp655ENWtufHSk6Q5BpyI8udqAk3uPtJr4GVm5wondrI1WZUtPri7k5N4DrSZRoXU/r5nV3LRxfdPOGfDk6nyZkrukTZIOS5qWdHOTc66W9KSkQ5L+LN8wy6vdJOrKFcs8ajfLoL4swZAa3yXiydU3apvcJQ0BO4ErgQ3ANkkb5p2zDrgFeG9EXAjc0IVYS6nVMgMrlg1x5+YLexyRWXmNj47whasvbjq56tLM67KM3C8FpiPiSES8CuwGtsw757eAnRHxIkBEvJBvmOXV6ldFT6KaLV6ryVUvS/C6LMl9BHgu9XwmOZZ2AXCBpP8p6RFJm/IKsMxaLTPgSVSzzrWaXHXnTE2W5N7sN6C004F1wOXUNsr+kqSVC95I2i5pStLU3NzcYmMtnVbLDHgS1axzrSZX3TlTkyW5zwDnpZ6vAo42OOcvI+JERHwfOEwt2b9BROyKiLGIGBseHu405lLwMgNm3dNuzXd3zmRL7o8C6yStlbQc2ApMzjtnAng/gKRzqJVpjuQZaJl4mQGz7vOyBK21Te4RcRK4HtgHPAXsiYhDknZI2pyctg/4kaQngYeAmyLiR90Kuujadci4JGOWj1bLEgx6aSZTn3tE7I2ICyLiXRFxV3Ls9oiYTB5HRHw6IjZExEURsbubQRedO2TMesOdM835DtWcuUPGrLfcOdOYk3uOJvbPcuOeg+6QMeuhdp0zd04e6nFExeDknpP6JOqpaPxLojtkzLqjXefMseMnBnL07uSek1aTqOAOGbNuatU5A4M5uerknpNWk6jukDHrvlb/xwZxctXJPQetJlGHJHfImPXA+OgIZ525rOnrgza56uSeg1bLDHzh6oud2M165I4PXOhlCRKn9zuAsvMyA2bFUf//dsP9Bxq+PkjLEnjkvgReZsCseLwsQY2T+xJ4mQGzYvKyBE7uHWu3L6onUc36x8sSOLl3JEs5xondrL8GfVkCJ/cOuBxjVnyDvqGHu2U6cNTlGLPCa9c50+r/cRV45N6BlU1ulHA5xqxYWnXOnCZVujTj5L5IE/tn+clPTy44vmxILseYFVCz8sypiErX3jMld0mbJB2WNC3p5gavXydpTtKB5M9v5h9qMdy97zAnXls4D//m5ad71G5WQPVVI4e0sDmyyrX3tsld0hCwE7gS2ABsk7Shwan3R8QlyZ8v5RxnIbRqf3zp+IkeR2NmWY2PjvBak+W4q3rXapaR+6XAdEQciYhXgd3Alu6GVTzt2h/f4btRzQqt2f/Rqt61miW5jwDPpZ7PJMfm+5CkxyU9IOm8XKIrELc/mpXboN21miW5N7seaV8H1kTEu4FvAX/c8I2k7ZKmJE3Nzc0tLtI+892oZuU2aHetZknuM0B6JL4KOJo+ISJ+FBGvJE//CPjHjd4oInZFxFhEjA0PD3cSb19402uzahiku1azJPdHgXWS1kpaDmwFJtMnSDo39XQz8FR+IfZfq/XaXY4xK49Bumu17R2qEXFS0vXAPmAIuDciDknaAUxFxCTwSUmbgZPAj4HruhhzT3m9drPqGKT13jP1uUfE3oi4ICLeFRF3JcduTxI7EXFLRFwYERdHxPsj4v90M+he8XrtZtUzKOu9+w7VFtwhY1ZNg9A54+TegjtkzKppEDpnnNybcIeMWbVVvXPGyb0Jd8iYVVvVO2e8nnsD7pAxq76qd8545D6PO2TMBkeVO2ec3Odxh4zZYKlq54yT+zzeQs9ssLTqnCnzVnxO7vN4Cz2zwVPFrfic3FO8hZ7ZYKriVnxO7ineQs9sMFVxKz4n94S30DMbbFXbis/JHW+hZ2Y1VdqKz8kdtz+aWU2V2iKd3PECYWZWU6UFxQY+uXuBMDNLq8qCYpmSu6RNkg5LmpZ0c4vzPiwpJI3lF2J3eYEwM0uryoJibZO7pCFgJ3AlsAHYJmlDg/PeCnwS+G7eQXZTszvQvECY2WCqt0U2U5a7VrOM3C8FpiPiSES8CuwGtjQ4798Cnwd+mmN8XTWxf5bTGvS1ghcIMxtkrRYUe9uKxnexF02W5D4CPJd6PpMc+xlJo8B5EfHfWr2RpO2SpiRNzc3NLTrYPNXbH0816Gt1h4yZ3bRxPctOWzj4+/tXT5ai7p4luTfrDKq9KJ0G3APc2O6NImJXRIxFxNjw8HD2KLugWfvjkOQOGTNjfHSEt5yxcMuLE6eiFHX3LMl9Bjgv9XwVcDT1/K3ALwIPS/q/wGXAZNEnVZu1P74W4cRuZgAce7nx3ellaIvMktwfBdZJWitpObAVmKy/GBEvRcQ5EbEmItYAjwCbI2KqKxHnoFX7o+9GNbO6Vvmg6G2RbZN7RJwErgf2AU8BeyLikKQdkjZ3O8BucPujmWVR5rbITHuoRsReYO+8Y7c3OffypYfVXW5/NLMs2u2zWuS2yIG7Q9Xtj2a2GGVtixyo5O72RzPrRBnbIgcqubv90cw6Uca2yIFK7m5/NLNOla0tcmCSu9sfzWwpytYWOTDJ3e2PZrYUZWuLzNQKWQVufzSzpShbW+RAjNzd/mhmeShTW2Tlk7vbH80sT2Vpi6x8cnf7o5nlqSxtkZVP7s3qYG5/NLNONWuLLFLdvfLJfeWZjetgbn80s041yx+nSYUpzVQ6uU/sn+UnP134E3bZkFxrN7OONWuLPBVRmJ73Sif3u/cd5sRrC4+/efnpLsmYWcfqm2gPNejCK0rPe2WT+8T+2abLDbx0vHG9zMwsq/HREV5r0IUHzZc66aVKJvd6+2MzrrebWR6a5RJB30szmZK7pE2SDkualnRzg9c/LukJSQck/Q9JG/IPNbtm7Y/g3nYzy89NG9c3XLMqoO+lmbbJXdIQsBO4EtgAbGuQvP8sIi6KiEuAzwP/PvdIF6FVO5J7280sL+OjIw3XrIL+t0VmGblfCkxHxJGIeBXYDWxJnxARf5d6+mZo+u/tunZLDTixm1memi1H0O+2yCzJfQR4LvV8Jjn2BpJ+R9L3qI3cP9nojSRtlzQlaWpubq6TeFvyUgNm1mtFbYvMktyblZTeeCBiZ0S8C/g94LZGbxQRuyJiLCLGhoeHFxdpBl5qwMx6rahtkVmS+wxwXur5KuBoi/N3A+NLCapTXmrAzPqhVVtkv2rvWZL7o8A6SWslLQe2ApPpEyStSz39Z8Az+YWYnZcaMLN+KdqSBG2Te0ScBK4H9gFPAXsi4pCkHZI2J6ddL+mQpAPAp4FruxZxE7WlBk4uOO6lBsysF4pWe8+0E1NE7AX2zjt2e+rxv8k5rkWrLTWw8NciLzVgZr1QzzM37jm4oKmjXnvvZS6qxB2qXmrAzIqgSEsSlD65e6kBMyuSoixJUPrk7qUGzKxIirIkQemTu5caMLMiKcqSBKVP7s3aH73UgJn1SxGWJCh1cnf7o5kVURHaIkud3N3+aGZFVIQlCUqd3JvVr9z+aGb91u8lCUqb3Fst7ev2RzMrgma56G0rGs8V5qmUyd1L+5pZGdy0cT3LTls4CP37V092ve5eyuTupX3NrAzGR0d4yxkLV3k5cSq6XncvZXL30r5mVhbHXm48B9jtunspk7uX9jWzsujXUsClS+7ubTezMulXz3vpkrt7282sTPrV854puUvaJOmwpGlJNzd4/dOSnpT0uKRvSzo//1Br3NtuZmXTj573tsld0hCwE7gS2ABsk7Rh3mn7gbGIeDfwAPD5vAMF97abWXk1y1Hdyl1ZRu6XAtMRcSQiXqW2AfaW9AkR8VBEvJw8fYTaJtq5cm+7mZVZo9p7N3NXlm32RoDnUs9ngPe0OP9jwF8tJahG3NtuZmVWz1F37zvM0WPHecfKFdy0cX3XcleW5N5s3fmFJ0rXAGPA+5q8vh3YDrB69eqMIda4t93Mym58dKRn+SpLWWYGOC/1fBVwdP5Jkn4NuBXYHBGvNHqjiNgVEWMRMTY8PLyoQHtdrzIzK7Msyf1RYJ2ktZKWA1uByfQJkkaB/0wtsb+Qf5i9r1eZmZVZ27JMRJyUdD2wDxgC7o2IQ5J2AFMRMQncDbwF+Jpq3SzPRsTmPAPtdb3KzKzMFE16L7ttbGwspqam+vK5zczKStJjETHW7rzS3aFqZmbtObmbmVWQk7uZWQU5uZuZVZCTu5lZBfWtW0bSHPCDDj/8HOCHOYaTp6LG5rgWx3EtXlFjq1pc50dE27tA+5bcl0LSVJZWoH4oamyOa3Ec1+IVNbZBjctlGTOzCnJyNzOroLIm9139DqCFosbmuBbHcS1eUWMbyLhKWXM3M7PWyjpyNzOzFgqb3CX9C0mHJL0mqemMcrPNu5Mlir8r6RlJ9yfLFecR19mSvpm87zclndXgnPdLOpD681NJ48lrX5b0/dRrl+QRV9bYkvNOpT7/ZOp4P6/ZJZK+k3zNH5f0kdRruV6zDBu+vyn5908n12NN6rVbkuOHJW1cShwdxNV0I/pmX9MexXWdpLnU5//N1GvXJl/3ZyRd2+O47knF9LSkY6nXunm97pX0gqS/afK6JP2HJO7HJf1S6rX8rldEFPIP8AvAeuBhaptvNzpnCPge8E5gOXAQ2JC8tgfYmjz+IvDbOcX1eeDm5PHNwO+3Of9s4MfAmcnzLwMf7tI1yxQb8JMmx/t2zYALgHXJ43cAzwMr875mrb5nUuf8a+CLyeOtwP3J4w3J+W8C1ibvM9TDuN6f+j767Xpcrb6mPYrrOuA/NvjYs4Ejyd9nJY/P6lVc887/BLXlyrt6vZL3/mXgl4C/afL6VdS2IhVwGfDdblyvwo7cI+KpiDjc5rSGm3dLEvArwAPJeX8MjOcU2pbk/bK+74eBv4rXNxDvpsXG9jP9vmYR8XREPJM8Pgq8ACxuu65s2m74Pi/eB4BfTa7PFmB3RLwSEd8HppP360lc0YON6DuJq4WNwDcj4scR8SLwTWBTn+LaBtyX0+duKSL+mtqArpktwFei5hFgpaRzyfl6FTa5Z9Ro8+4R4O3AsYg4Oe94Hn4+Ip4HSP7+B23O38rCb6q7kl/H7pH0ppziWkxsZ0iakvRIvVxEga6ZpEupjca+lzqc1zVr9j3T8JzkerxE7fpk+dhuxpU2fyP6Rl/TXsb1oeTr84Ck+rachbheSflqLfBg6nC3rlcWzWLP9Xpl2SC7ayR9C/iHDV66NSL+MstbNDgWLY4vOa6s75G8z7nARdR2saq7Bfh/1JLXLuD3gB09jm11RByV9E7gQUlPAH/X4Lx+XbM/Aa6NiNeSw0u6ZvM/RYNj8/+dXfm+amOpG9Ev+JpGxPcafXwX4vo6cF9EvCLp49R+6/mVjB/bzbjqtgIPRMSp1LFuXa8sevL91dfkHhG/tsS3aLZ59w+p/apzejLyaripdydxSfpbSedGxPNJImq1Z+zVwF9ExInUez+fPHxF0n8BfjdrXHnFlpQ9iIgjkh4GRoH/Sp+vmaSfA/47cFvy62r9vZd0zebJsuF7/ZwZSacDb6P2a3amzeK7GFd6I/r3RWoj+iZf0zySVdu4IuJHqad/BPx+6mMvn/exD+cQU6a4UrYCv5M+0MXrlUWz2HO9XmUvyzTcvDtqsxMPUat3A1wLZPlNIIvJ5P2yvO+COl+S3Oo17nGg4Yx6t2KTdFa9rCHpHOC9wJP9vmbJ1+8vqNUivzbvtTyvWdsN3+fF+2HgweT6TAJbVeumWQusA/7XEmJZVFxqshF9s69pD+M6N/V0M/BU8ngfcEUS31nAFbzxt9iuxpXEtp7a5OR3Use6eb2ymAT+ZdI1cxnwUjKAyfd6dWvGeKl/gF+n9pPsFeBvgX3J8XcAe1PnXQU8Te2n7q2p4++k9h9vGvga8Kac4no78G3gmeTvs5PjY8CXUuetAWaB0+Z9/IPAE9QS1FeBt+R4zdrGBvyT5PMfTP7+WBGuGXANcAI4kPpzSTeuWaPvGWplns3J4zOSf/90cj3emfrYW5OPOwxcmfP3fLu4vpX8X6hfn8l2X9MexfU54FDy+R8C/lHqY/9Vch2ngd/oZVzJ8zuBfzfv47p9ve6j1u11gloO+xjwceDjyesCdiZxP0GqGzDP6+U7VM3MKqjsZRkzM2vAyd3MrIKc3M3MKsjJ3cysgpzczcwqyMndzKyCnNzNzCrIyd3MrIL+P2AwjluSBA8BAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x2, y4, 'o-') # график c интерполяцией\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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