diff --git a/Polynomial Regression.ipynb b/Polynomial Regression.ipynb index 7059613..3f0e255 100644 --- a/Polynomial Regression.ipynb +++ b/Polynomial Regression.ipynb @@ -4,22 +4,17 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Algorytm najszybszego spadku dla regresji wielomianowej. \n", - "Zakładamy, że dysponujemy zbiorem składającym się z dwóch cech (x i y). Modelujemy zależność y od x za pomocą funkcji wielomianowej. Celem projektu jest implementacja metody najszybszego spadku dla tego problemu. Zakładamy kwadratową funkcję straty. Implementacja powinna umożliwiać podanie stopnia wielomianu, który ma być użyty do modelowania. Implementacja powinna zwracać wektor oszacowanych parametrów oraz pokazywać wizualnie zmiany wartości funkcji straty wraz z postępem uczenia." + "# Algorytm najszybszego spadku dla regresji wielomianowej. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Inches for Height and Pound for Weight" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Import i preprocessing danych" + "Skład grupy:\n", + "- Nowak Ania,\n", + "- Łaźna Patrycja,\n", + "- Bregier Damian" ] }, { @@ -35,12 +30,41 @@ "np.set_printoptions(suppress=True)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 0. Podstawowe informacje o zbiorze danych" + ] + }, + { + "attachments": { + "image.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ze względu na specyfikę wytycznych projektu zakładającego wykorzystanie jedynie dwóch cech: x i y oraz modelowanie zależności y od x za pomocą funkcji wielomianowej dobrany został przez nas odpowiedni dataset. Obejmuje on jedynie trzy kolumny, czyli: płeć, wzrost w calach oraz wagę w funtach, z czego ze względu na specyfikę projektu wykorzystywane są jedynie wzrost oraz waga. Każdy z parametrów zawiera po 10 tysięcy unikalnych wartości.\n", + "\n", + "![image.png](attachment:image.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Wczytywanie i preprocessing danych" + ] + }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ + "# Stopień wielomianu - zgodnie z wytycznymi domyślna wartość to dwa\n", "degree = 2\n", "X_plot = np.linspace(0, 1, 1000)\n", "initial_theta = np.matrix([0] * (degree + 1)).reshape(degree + 1, 1)" @@ -52,7 +76,9 @@ "metadata": {}, "outputs": [], "source": [ + "# Wybór dwóch kolumn - dotyczących wzrostu i wagi\n", "data = pd.read_csv('weight-height.csv')[[\"Height\", \"Weight\"]]\n", + "# Czyszczenie tabeli i wartości pustych\n", "data = data.dropna()\n", "data_matrix = np.matrix(data)\n", "\n", @@ -73,7 +99,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Metody do regresji wielomianowej" + "## 2. Metody do regresji wielomianowej" ] }, { @@ -84,13 +110,16 @@ }, "outputs": [], "source": [ + "# Implementacja wzrosu na regresję wielomianową\n", "def polynomial_regression(theta, x):\n", " return sum(theta * np.power(x, i) for i, theta in enumerate(theta.tolist()))\n", "\n", + "# Implementacja wzoru na RMSE, czyli pierwiastek z błędu średniokwadratowego\n", "def mean_squared_error(theta, X, Y):\n", " J = 1.0 / (2.0 * m) * ((X * theta - Y).T * (X * theta - Y))\n", " return J.item()\n", "\n", + "# Wzór na gradient prosty\n", "def classic_gradient(theta, X, Y):\n", " return 1.0 / len(Y) * (X.T * (X * theta - Y)) \n", "\n", @@ -162,7 +191,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Metody do wykresów" + "## 3. Reprezentacja graficzna regresji wielomianowej" ] }, { @@ -174,7 +203,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -202,7 +231,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Wyniki za pomocą gotowej biblioteki" + "## 4. Regresja wielomianowa z wykorzystaniem gotowej biblioteki" ] }, { @@ -241,7 +270,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -250,13 +279,13 @@ "2" ] }, - "execution_count": 8, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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8Dhc9Cd/4INXfa5u29Rn9bfi8eX5fo03zNnx6waf/Pa6cXOmIljJh8JIkZeZ3L9/Bx7+9kclPwTZzU+2d9eGy3eE3O8CStQhcTUKTL16uzGnRtAU3f++L88cc0VJWmmTdgCSpDFVVwZ13svMBP+au36fQNbM9nHwQbHU6jNpp7UJX6+atGXv4WOLFkTu/fyfd23cnEOjevjtjDh1jyFLJCDE2jD2mKioq4sSJE7NuQ5KUj6oqqKyE4cPhjbSZ4owNYPh3Yez2sGwtrsMEApHo5tQqSSGESTHGipXrXmqUJNW/Zctg7Fi49FJ4661U23JLzt3xE67t9SFVTVf91hVLOQDOy1KDZ/CSJNWfpUvhtttS4Jo5M9V694YLL4Sjj+abr99Ni4cGUFXrDkNIk+EXLVv0pYBl0FJDZ/CSJBXekiUwZgyMGAHvvJNqW28NF10ERx0FTdMQ14og5UiWyoVzvCRJhfP553DLLXD55fBubqn5bbaBn/8cfvCD/wYuqbFzjpckqf4sWgSjR8MVV8Cc3FLz3/hGClyHHw5NvIleAoOXJCkfn30GN94II0fCB7mVT3fYIQWuQw4xcEkrMXhJktbewoUwahRceSXMm5dqFRVw8cVw0EEQQrb9SSXK4CVJWnMLFsANN8BVV8FHH6XazjunwHXggQYuaTUMXpKk1fv4Y7juuvTfJ5+k2q67psC1334GLmkNZRa8QggHAtcBTYFbY4yXZdWLJGkV5s2Da66BX/0qXV4E2HPPtCzE//yPgUtaS5kErxBCU+DXwH7AbOCFEMKDMcapWfQjSVrJf/6TLieOGpUm0APsu28KXHvskW1vUgOW1YjXTsD0GONbACGEccChgMFLkrL03ntpSYjRo2Hx4lTr2zetNP+d72Tbm9QIZBW8OgPv1DqeDeycUS+SpFmz0qKnv/lNWnUe4NBDU+Cq+NIakJLWUVbBq65JAV9aQj+EMAAYANCtW7f67kmSys+MGWlbn9tuSxtZhwBHHJEC1/bbZ92d1OhktbLdbKBrreMuwHsrvyjGODrGWBFjrNh4442L1pwkNXpvvAEnngi9eqUtfqqr4Zhj4LXX4N57DV1SPclqxOsFoFcIoSfwLtAPOCajXiSpfEydCsOHw7hxsHx52juxf3+44ALo3Tvr7qRGL5PgFWOsCiGcBvyFtJzEmBjjlCx6kaSy8OqrcMklcN99ECM0awY//jEMHQpbbJF1d1LZyGwdrxjjn4A/ZfX1JaksTJoEv/wlPPBAOm7RAk46Cc4/H7p3z7Y3qQy5cr0kNUbjx6fA9afcv29btYKf/QzOPRc6d862N6mMGbwkqTF5+ukUuB57LB23bg0DB8LZZ8Nmm2XbmySDlyQ1eDHC3/+eAtc//pFq7drBoEFw5pnQsWOm7UmqYfCSpIYqRvjrX+EXv4Bnn021DTaAwYPh9NOhQ4dM25P0ZQYvSWpoYoSHH04jXC+8kGodOsBZZ8Fpp0H79tn2J2mVDF6S1FAsXw5//GNaFuKll1Jt443ThPlTToG2bTNtT9LqGbwkqdRVV6f1ty65JK0sD9CpE5x3HgwYkCbQS2oQDF6SVKqqquCuu9JK89OmpVqXLjBkSFqLq1WrbPuTtNYMXpJUapYtgzvugEsvhTffTLUePdIq8/37Q8uWmbYnad0ZvCSpVCxZArfdBiNGwMyZqbbVVjBsGBx7LDRvnml7kvJn8JKkrC1eDLfeCldcAbNnp9rXv54C11FHpX0VJTUK/m2WpKx89hncfDOMHAnvv59q220HF14IP/gBNG2abX+SCs7gJUnFtnAhjBoFV10Fc+em2re+BRddBIccAk2aZNufpHpj8JKkYvnkE/jVr+Daa+Gjj1Jt551T4OrbF0LIsjtJRWDwkqT69tFHKWxdfz3Mn59qu++eAtd++xm4pDJi8JKk+jJ3Llx9NdxwA3z6aartvTf8/Oew554GLqkMGbwkqdDmzIErr4SbboJFi1LtgAPSCNduu2Xbm6RMGbwkqVBmz05LQtxyC3z+eaodfHAKXDvtlG1vkkqCwUuS8jVzJlx2GYwZA0uXptrhh6dlIb71rWx7k1RSDF6StK7efDNt6zN2bNpXMYS04OmwYWk9LklaicFLktbWtGlp4+rf/Q6qq9O6W8cdBxdckFacl6RVMHhJ0pp67bUUuO6+G2JMW/mceGIKXFttlXV3khoAg5ckrc5LL8Ell8Af/pCOmzdPgWvIEOjZM9veJDUoBi9JWpXx41PgeuSRdNyyJfz0p3DeedC1a7a9SWqQDF6StLInn0yB6/HH03Hr1nDyyXDOOdCpU7a9SWrQDF6SBGnO1mOPpcD19NOp1q4dDBoEZ5wBG2+caXuSGgeDl6TyFiM8/HAKXBMmpNqGG6awNWhQeixJBWLwklSeli+H3/8+3aX4yiuptvHGcPbZMHBgGu2SpAIzeEkqL1VVMG5cWvj09ddTrVOnNGF+wIA0n0uS6onBS1J5WLoU7rgDRoxIK84DdOuWloQ48URo1Srb/iSVBYOXpMbt88/THoqXXw6zZqXaVlulRU+POy6tySVJRWLwktQ4ffYZjB4NI0fCnDmp1qdP2kfxhz9Mq85LUpH5k0dS47JgAfz613D11TBvXqp985tw4YVw+OFpX0VJyojBS1Lj8NFHcP31cN118MknqbbzznDRRdC3L4SQaXuSBAYvSQ3dBx/ANdekUa6FC1Ntjz1S4NpnHwOXpJKS15h7CGFkCOFfIYRXQwj3hxA2qPXc0BDC9BDCtBDCAbXq3w4hTM49d30I/lSUtA7eew/OPBN69IDLLkuha//903Y/Tz4J++5r6JJUcvKd7PAYsG2M8RvAv4GhACGEPkA/YBvgQGBUCKFp7j03AgOAXrn/DsyzB0nlZObMtMBpz55w7bWweDF873tpQ+u//CWNdklSicoreMUY/xpjrModjge65B4fCoyLMS6JMc4ApgM7hRA6AevHGJ+LMUZgLHBYPj1IKhPTp8NJJ6WlIG68EZYtgyOOgJdeggcfTPO5JKnEFXKO14+Bu3OPO5OC2Aqzc7Vluccr1+sUQhhAGh2jW7duBWxVUoMxdWpaZf6uu9I2P02awLHHpnW4+vTJujtJWiurDV4hhMeBzep4aliM8YHca4YBVUDlirfV8fr4FfU6xRhHA6MBKioqVvk6SY3Qyy+njav/8Ie0kXWzZnDCCTB0aBr1kqQGaLXBK8a471c9H0LoDxwM7JO7fAhpJKtrrZd1Ad7L1bvUUZekZMKEFLgeeigdt2gBP/lJ2kuxe/dse5OkPOV7V+OBwPnAITHGRbWeehDoF0JoGULoSZpEPyHGOAdYGELYJXc34/HAA/n0IKmRePrpdFfizjun0LXeeumuxRkz0lIRhi5JjUC+c7xuAFoCj+VWhRgfYzw5xjglhHAPMJV0CfLUGGN17j2nALcB6wGP5v6TVI5ihMcfTyNcTz2Vam3bwmmnpdC1ySbZ9idJBZZX8IoxrnKiRYxxODC8jvpEYNt8vq6kBi5GeOSRFLiefz7VNtgAzjgDBg2CDh2y7E6S6o0r10sqnuXL4f77U+B6+eVU69gRzj47rc21/vqZtidJ9c3gJan+VVXB3XenZSGmTk21Tp3g3HNhwABo0ybb/iSpSAxekurPsmVwxx0wYkRaABWga1cYMgR+/GNo1Srb/iSpyAxekgrv88/ht79NeyjOmpVqW26Z1uD60Y/SEhGSVIYMXpIKZ9EiGD0aRo5Mm1gDfP3rMGwYHHVUWgRVksqYPwUl5W/BAhg1Cq6+GubOTbXtt4cLL4Tvfz9t8yNJMnhJysPHH8P118N116XHADvuCBddBAcfDKGuXcIkqXwZvCStvblz4Zpr4IYbYOHCVNt99xS49tvPwCVJq2DwkrTm5syBK6+Em25K87kA9t03Ba499si2N0lqAAxeklZv1iy44gq49VZYsiTVDjoozeHaZZdse5OkBsTgJWnVpk9PS0LcfntaBBXSZPkLL4Qddsi2N0lqgAxekr5sypS0yvy4cWmbnyZN4Jhj4IILYJttsu5Okhosg5ekGpMmwfDhaT9FSOtu9e+fVprv3Tvb3iSpETB4SYJnnkmB689/TsctW8JPfpL2UuzePdveJKkRMXhJ5SpGePzxFLiefDLV2rSBU06Bs85Km1hLkgrK4CWVmxjhoYdS4JowIdXat4fTT4fBg2GjjbLtT5IaMYOXVC6qq+G++1Lgmjw51Tp2TKNbAwem8CVJqlcGL6mxW7YMKithxAj4979TbfPN0/ytn/40XV6UJBWFwUtqrD7/HH77W7j8cpg5M9V69Eh3KJ5wQppAL0kqKoOX1Nh8+incfDNcdVXa4gdg661h6FA4+mho3jzb/iSpjBm8pMbik0/SptXXXgsffphq228Pw4al1eabNs2yO0kSBi+p4Zs7N4WtG26ABQtSbZdd0rY+fftCCJm2J0mqYfCSGqr33oMrr0yXFRctSrW9906Ba++9DVySVIIMXlJD8/bbacL8mDGwdGmq9e2bLinuumumrUmSvprBS2oopk1LS0LceWdakysEOOKItHH1Djtk3Z0kaQ0YvKRS98oradHT++5Lq843bQo/+lG6S/HrX8+6O0nSWjB4SaVq/PgUuB5+OB03bw4nngjnnw9bbJFtb5KkdWLwkkpJjGnD6ksugSeeSLX11oMBA+Ccc6BLl2z7kyTlxeAllYIY4dFH0wjXs8+mWrt2cOqpcOaZsMkm2fYnSSoIg5eUpeXL4f77U+B66aVU69ABBg+GQYNgww2z7U+SVFAGLykLVVUwbly6S3Hq1FTbdNN0OfFnP0ujXZKkRsfgJRXTkiUwdixcdhm89Vaqde2aJsz/+MdpPpckqdEyeEnFsGgR3HorXHEFvPtuqm21VVoS4rjjoEWLbPuTJBWFwUuqTwsWwI03wlVXpT0VAbbdNi16euSR0My/gpJUTpoU4kNCCOeEEGIIoWOt2tAQwvQQwrQQwgG16t8OIUzOPXd9CG4op0boo4/g4ouhe3cYMiSFroqKNJH+lVfg6KMNXZJUhvL+yR9C6ArsB8yqVesD9AO2ATYHHg8h9I4xVgM3AgOA8cCfgAOBR/PtQyoJ778PV1+dRrk+/TTVvvvdtI/i/vu7cbUklblCjHhdA5wHxFq1Q4FxMcYlMcYZwHRgpxBCJ2D9GONzMcYIjAUOK0APUrZmzUrLP/TsCSNHptC1//5pMdSnnoIDDjB0SZLyG/EKIRwCvBtjfGWlK4adSSNaK8zO1ZblHq9clxqm6dPTHYpjx8KyZal26KFphGvHHbPtTZJUclYbvEIIjwOb1fHUMOACYP+63lZHLX5FfVVfewDpsiTdunVbXatS8UyZApdemtbiWr4cmjSBfv3SpPnttsu6O0lSiVpt8Iox7ltXPYSwHdATWDHa1QV4MYSwE2kkq2utl3cB3svVu9RRX9XXHg2MBqioqFhlQJOKZtKktMr8/fen42bN4IQT0gT6Xr0ybU2SVPrWeY5XjHFyjHGTGGOPGGMPUqj6VozxfeBBoF8IoWUIoSfQC5gQY5wDLAwh7JK7m/F44IH8vw2pnj3zDBx4YM2diS1bpn0Up0+H3/zG0CVJWiP1cj97jHFKCOEeYCpQBZyau6MR4BTgNmA90t2M3tGo0hQjPP44XHJJmiAP0KYNnHwynH02dOqUbX+SpAanYMErN+pV+3g4MLyO100Eti3U15UKbvlyePjhFLheeCHV2reH009Pm1dvtFG2/UmSGixXcJRWqKqCe+9Nk+Zfey3VOnaEs86CgQNT+JIkKQ8GL2nJErjjjrQsxJtvplrnznDOOfDTn6bLi5IkFYDBS+Xrs8/SxtUjR9ZsXL3FFukOxeOPTxPoJUkqIIOXys8nn8CoUXDNNTBvXqpts01ag+uHP3QPRUlSvfE3jMrH3Llw7bVwww2wYEGq7bhjWmX+e99Li6BKklSPDF5q/GbPhiuvhNGjYfHiVNt77zTCtc8+7qEoSSoag5car+nT4fLL4fbba/ZRPPjgFLi+851se5MklSWDlxqfyZPTkhD33JPW5AoBjjoKhg6F7bfPujtJUhkzeKnxeP75tI/iQw+l4xX7KJ5/PvTunWlrkiSBwUsNXYzw97+nwPW3v6Vaq1Zp/a1zzoFu3bLtT5KkWgxeaphiTNv6DB+eRroA2rVLG1efeSZsskm2/UmSVAeDlxqW6uqabX0mT061jTaCM86A006DDTbIsjtJkr6SwUsNw9KlNdv6TJ+eaptvni4nDhjgtj6SpAbB4KXStmhRzbY+s2en2hZbpAnz/fu7rY8kqUExeKk0zZ9fs63P3Lmpts02aUmIo45yWx9JUoPkby+Vlrlz4brr0rY+8+enWkVF2tbnkEPc1keS1KAZvFQaZs+Gq65K2/osWpRqe+2VVpnfd1+39ZEkNQoGL2Vr+nS44gq47baabX0OOigFrl13zbQ1SZIKzeClbLz2GowYAePG1Wzr88Mfpjlc3/xm1t1JklQvDF4qrgkT0hpcDzyQjps1S3cnDhnitj6SpEbP4KX6FyP84x8pcD3+eKq1agU/+Qmce67b+kiSyobBS/UnRnjkkRS4nnsu1dq1g4ED07Y+m26abX+SJBWZwUuFV10N992XAterr6Zahw412/psuGGm7UmSlBWDlwpn6VK48860rc8bb6Rap0412/q0bZttf5IkZczgpfwtXlyzrc8776Raz55pW58TTnBbH0mScgxeWncLFtRs6/PBB6nWp09aEqJfP7f1kSRpJf5m1NqbNy9t6/OrX7mtjyRJa8HgpTX37rtpW5+bb67Z1mfPPVPgclsfSZJWy+Cl1XvzzZptfZYuTbW+fdO2PrvtlmlrkiQ1JAYvrdprr6U7FO+6q2ZbnyOPTIHLbX0kSVprBi992QsvpDW4/vjHdNysGRx/fNrW52tfy7Q1SZIaMoOXkhXb+owYAY89lmotW9Zs69O9e6btSZLUGBi8yt3y5fDwwylwjR+fam3b1mzrs9lm2fYnSVIjYvAqV1VVcPfdaQ7Xa6+l2kYbweDBbusjSVI9yXvBpRDCoBDCtBDClBDCFbXqQ0MI03PPHVCr/u0QwuTcc9eH4BoERfX553DTTdC7Nxx3XApdnTunRVBnzoSLLjJ0SZJUT/Ia8Qoh7A0cCnwjxrgkhLBJrt4H6AdsA2wOPB5C6B1jrAZuBAYA44E/AQcCj+bTh9bAwoUpcF19Nbz/fqr16pUmzB93HLRokW1/kiSVgXwvNZ4CXBZjXAIQY8ztG8OhwLhcfUYIYTqwUwjhbWD9GONzACGEscBhGLzqz4cfwvXXp1XmP/441b75zbStzw9+AE2bZtqeJEnlJN/g1Rv4bghhOPA5cE6M8QWgM2lEa4XZudqy3OOV6yq02bPTKvOjR9esMv/d76bAdeCBrjIvSVIGVhu8QgiPA3Xd2jYs9/4NgV2AHYF7QghbAHX9Vo9fUV/V1x5AuixJt27dVteqAN54Ay6/HMaOhWXLUq1v3xS4dt89294kSSpzqw1eMcZ9V/VcCOEU4A8xxghMCCEsBzqSRrK61nppF+C9XL1LHfVVfe3RwGiAioqKVQY0AS+/nO5QvPfemlXmjzoqzeFylXlJkkpCvnc1/hH4H4AQQm+gBTAPeBDoF0JoGULoCfQCJsQY5wALQwi75O5mPB54IM8eytszz8BBB8EOO6TlIZo2TYueTpsG48YZuiRJKiH5zvEaA4wJIbwGLAX650a/poQQ7gGmAlXAqbk7GiFNyL8NWI80qd6J9WsrRvjzn9Oip08/nWqtW8OAAXD22dCly1e/X5IkZSKknFT6Kioq4sSJE7NuI1vV1fD736fA9fLLqbbBBnD66TBoEHTsmGV3kiQpJ4QwKcZYsXLdlesbgqVL4Y470qT5N95Itc02g7POgpNPhnbtsu1PkiStEYNXKfvsM7jllrQsxOzcKhw9e8J558EJJ0CrVpm2J0mS1o7BqxR9/DHccANcd11aABVg223THYpHHQXN/J9NkqSGyN/gpeT999OeiaNGwaefptrOO8MFF8DBB0OTvLfWlCRJGTJ4lYIZM2DkSBgzBpYsSbX99kuLnu61l6vMS5LUSBi8sjRlSlr09K670h2LAIcfngLXjjtm25skSSo4g1cWnn8+LQnxQG7t2KZN4fjj4fzzoU+fbHuTJEn1xuBVLDHCE0+kwPW3v6Vaq1ZplflzzoHu3bPtT5Ik1TuDV31bvhwefBAuvRReeCHV1l8fBg6EM86ATTfNtD1JklQ8Bq/6smxZmrt1+eUwdWqqbbxxClsDB6YV5yVJUlkxeBXa4sXp7sSRI2HmzFTr2hXOPRdOOintqShJksqSwatQFiyAG2+Eq6+GDz5Ita99LS16eswx0KJFtv1JkqTMGbzyNXduWmH+hhtg/vxU+/a305IQhx2W7liUJEnC4LXuZs1Keyjecku6vAiw555plfn99nPRU0mS9CUGr7U1bVqaMH/HHVBVlWoHH5xGuHbdNdveJElSSTN4rakXX0xrcP3+92lNriZN0tytIUNgu+2y7k6SJDUABq+vEiM8/XRag+svf0m1Fi3ghBPgvPNgyy0zbU+SJDUsBq+6xAiPPJJGuJ59NtXatIGTT4azzoLNN8+2P0mS1CAZvGqrqoJ7700bV7/6aqp16ACnnw6DBqXHkiRJ68jgBbBkCYwdmybNv/lmqm2+OZx9NgwYAG3bZtufJElqFAxeAJ99Bmeemf7ccks4/3w4/nho2TLrziRJUiNi8IJ0CXHEiLSX4hFHQDNPiyRJKjwTxgqDBmXdgSRJauSaZN2AJElSuTB4SZIkFYnBS5IkqUgMXpIkSUVi8JIkSSoSg5ckSVKRGLwkSZKKxOAlSZJUJAYvSZKkIjF4SZIkFUmIMWbdwxoJIcwFZmbdR5F0BOZl3UQJ8XzU8Fx8keejhufiizwfX+T5qFGsc9E9xrjxysUGE7zKSQhhYoyxIus+SoXno4bn4os8HzU8F1/k+fgiz0eNrM+FlxolSZKKxOAlSZJUJAav0jQ66wZKjOejhufiizwfNTwXX+T5+CLPR41Mz4VzvCRJkorEES9JkqQiMXiVmBDCOSGEGELoWKs2NIQwPYQwLYRwQJb9FUsIYWQI4V8hhFdDCPeHEDao9VzZnQ+AEMKBue95eghhSNb9FFMIoWsI4e8hhNdDCFNCCINz9Q4hhMdCCG/k/tww616LJYTQNITwUgjh4dxxOZ+LDUII9+V+ZrweQvhOmZ+PM3N/T14LIdwVQmhVTucjhDAmhPBBCOG1WrVVfv/F/p1i8CohIYSuwH7ArFq1PkA/YBvgQGBUCKFpNh0W1WPAtjHGbwD/BoZC+Z6P3Pf4a+B/gT7A0blzUS6qgLNjjF8HdgFOzX3/Q4AnYoy9gCdyx+ViMPB6reNyPhfXAX+OMW4NbE86L2V5PkIInYHTgYoY47ZAU9LPzHI6H7eRfj/UVuf3n8XvFINXabkGOA+oPfHuUGBcjHFJjHEGMB3YKYvmiinG+NcYY1XucDzQJfe4LM8H6XucHmN8K8a4FBhHOhdlIcY4J8b4Yu7xQtIv1s6kc3B77mW3A4dl0mCRhRC6AAcBt9Yql+u5WB/YA/gNQIxxaYzxE8r0fOQ0A9YLITQDWgPvUUbnI8b4FPDRSuVVff9F/51i8CoRIYRDgHdjjK+s9FRn4J1ax7NztXLyY+DR3ONyPR/l+n1/SQihB7AD8DywaYxxDqRwBmySYWvFdC3pH2nLa9XK9VxsAcwFfpu79HprCKENZXo+YozvAleSrpzMAebHGP9KmZ6PWlb1/Rf9Z2uz+vxwfVEI4XFgszqeGgZcAOxf19vqqDWKW1G/6nzEGB/IvWYY6TJT5Yq31fH6RnE+VqNcv+8vCCG0BX4PnBFjXBBCXaelcQshHAx8EGOcFELYK+N2SkEz4FvAoBjj8yGE62jcl9G+Um7u0qFAT+AT4N4QwnGZNlXaiv6z1eBVRDHGfeuqhxC2I/0leSX3i6QL8GIIYSdS+u5a6+VdSMPGDd6qzscKIYT+wMHAPrFm3ZNGez5Wo1y/7/8KITQnha7KGOMfcuX/hBA6xRjnhBA6AR9k12HR7AYcEkLoC7QC1g8h3El5ngtIfzdmxxifzx3fRwpe5Xo+9gVmxBjnAoQQ/gDsSvmejxVW9f0X/WerlxpLQIxxcoxxkxhjjxhjD9L/Eb4VY3wfeBDoF0JoGULoCfQCJmTYblGEEA4EzgcOiTEuqvVUWZ4P4AWgVwihZwihBWky6IMZ91Q0If2L5DfA6zHGq2s99SDQP/e4P/BAsXsrthjj0Bhjl9zPin7A32KMx1GG5wIg93PynRDC13KlfYCplOn5IF1i3CWE0Dr392Yf0pzIcj0fK6zq+y/67xRHvEpcjHFKCOEe0g+SKuDUGGN1xm0Vww1AS+Cx3Cjg+BjjyeV6PmKMVSGE04C/kO5SGhNjnJJxW8W0G/AjYHII4eVc7QLgMuCeEMJJpF84R2bTXkko53MxCKjM/aPkLeBE0sBC2Z2P3OXW+4AXST8jXyKt1N6WMjkfIYS7gL2AjiGE2cDFrOLvRxa/U1y5XpIkqUi81ChJklQkBi9JkqQiMXhJkiQVicFLkiSpSAxekiRJRWLwkiRJKhKDlyRJUpEYvCRJkork/wMkZUDZ1j60IgAAAABJRU5ErkJggg==\n", + "image/png": 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\n", 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" ] @@ -275,8 +304,17 @@ "chart = fig.add_subplot()\n", "chart.plot(data[\"Height\"], Y ,\"go\")\n", "chart.plot(X_plot_2, Y_plot_2, color=\"red\", lw=2, label=f\"degree {degree}\")\n", + "plt.ylim([0,250])\n", + "plt.xlim([40,80])\n", "degree" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -295,7 +333,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.5" + "version": "3.8.8" } }, "nbformat": 4,