diff --git a/module2/exo1/Projet_info.ipynb b/module2/exo1/Projet_info.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..ae2a3d2396571f564053fdc97534ea9da63964fe --- /dev/null +++ b/module2/exo1/Projet_info.ipynb @@ -0,0 +1,1000 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# __Premier pas en $FFTW$__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pour pouvoir utiliser $FFTW$, il est nécéssaire d'installer le module à l'aide de l'outil $pip$. La commande à utiliser (dans le terminal)\n", + "est la suivante :\n", + "\n", + "$$pip \\quad install \\quad pyFFTW$$\n", + "\n", + "Il nous suffit ensuite d'importer le module." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from numpy import *\n", + "import pyfftw\n", + "from IPython.display import display, Markdown, Math\n", + "from matplotlib.pyplot import *" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__FFT à 1 dimension__" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "TYPE = \"complex128\"\n", + "N = 128\n", + "a = pyfftw.empty_aligned(N, dtype=TYPE) \n", + "b = pyfftw.empty_aligned(N, dtype=TYPE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$pyfftw.empty\\_aligned(N, dtype=TYPE)$ renvoie un tableau de taille $N$ de nombres aléatoires. Ces nombres sont aléatoires et devront donc être précisés plus tard." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "On dit maintenant au programme que la bonne transformée de Fourier sera stockée dans $b$ et cette transformation sera appellée $fft\\_object$. " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "fft_object = pyfftw.FFTW(a, b)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "On crée à présent la transformée de Fourier inverse qui prendra les données de $b$, \n", + "fera la transformée inverse et stockera les nouvelles données dans $c$." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "c = pyfftw.empty_aligned(N, dtype=TYPE)\n", + "\n", + "ifft_object = pyfftw.FFTW(b, c, direction='FFTW_BACKWARD')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "On rempli maintenant la liste $a$ avec les données qui nous interessent. \n", + "Pour tester le programme, nous prendrons dans un premier temps des valeurs aléatoires." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "ar, ai = random.randn(2, N)\n", + "a[:] = ar + 1j*ai*0 #partie imaginaire à 0" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "On appelle à présent les transformations générales définies plus haut pour les \n", + "appliquer dans le cas particulier des données aléatoires de $a$ qui \n", + "viennent d\\'être implémentées." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "ffta=fft_object()\n", + "ifft_ = ifft_object() " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Vérifions à présent que les transformées inverses correspondent bien \n", + "aux données de bases dans la limite de l'erreur $rtol$." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True\n", + "True\n" + ] + } + ], + "source": [ + "print( allclose(ifft_,c, rtol=1.e-15) )\n", + "print( allclose(a,c, rtol=1.e-13) )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "La première commande est en réalité triviale en sachant que $ifft\\_$ et $c$ sont le même objet. On peut le prouver grace à la commande suivante :" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ifft_ is c" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pour que cela soit plus visuel, traçons les données de $a$ à coté de celles de $c$ puis celles de $b$ à coté de celles de $ffta$ :" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "T=[i for i in range(len(a))]\n", + "\n", + "fig = figure(1, figsize=(9, 4))\n", + "\n", + "subplot(121)\n", + "\n", + "plot(T,a.real)\n", + "title('Données de a',family='serif',size=20)\n", + "grid(True,linestyle='--')\n", + "\n", + "\n", + "subplot(122)\n", + "\n", + "plot(T,c.real)\n", + "title('Données de c',family='serif',size=20)\n", + "grid(True,linestyle='--')\n", + "show()\n", + "\n", + "\n", + "fig = figure(1, figsize=(9, 4))\n", + "subplot(121)\n", + "\n", + "plot(T,b.real)\n", + "\n", + "title('Données de b',family='serif',size=20)\n", + "grid(True,linestyle='--')\n", + "subplot(122)\n", + "\n", + "plot(T,ffta.real)\n", + "title('Données de ffta',family='serif',size=20)\n", + "grid(True,linestyle='--')\n", + "show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# __Débruitage d'un signal 1D avec $FFTW$__" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "x=linspace(0,6*pi,N)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "for k in range(len(a)) :\n", + " a[k]=sin(x[k])+sin(2*x[k])+0.1*ar[k] +1j*0" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "b=fft_object()\n", + "ifft_ = ifft_object() " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True\n", + "True\n" + ] + } + ], + "source": [ + "print( np.allclose(ifft_,c, rtol=1.e-15) )\n", + "print( np.allclose(a,c, rtol=1.e-13) )" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = figure(1, figsize=(9, 4))\n", + "\n", + "n=a.size\n", + "freq=fft.fftfreq(n,6*pi/N)\n", + "\n", + "subplot(121)\n", + "\n", + "plot(x,a.real)\n", + "title('Données de a',family='serif',size=20)\n", + "grid(True,linestyle='--')\n", + "\n", + "\n", + "subplot(122)\n", + "\n", + "plot(x,c.real)\n", + "title('Données de c',family='serif',size=20)\n", + "grid(True,linestyle='--')\n", + "show()\n", + "\n", + "\n", + "fig = figure(1, figsize=(9, 4))\n", + "subplot(121)\n", + "\n", + "plot(freq,b.real)\n", + "\n", + "plot(freq,b.imag)\n", + "title('Données de b',family='serif',size=20)\n", + "grid(True,linestyle='--')\n", + "subplot(122)\n", + "\n", + "plot(freq,ffta.real)\n", + "plot(freq,ffta.imag)\n", + "title('Données de ffta',family='serif',size=20)\n", + "grid(True,linestyle='--')\n", + "show()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "moyb=0\n", + "ini=0\n", + "for k in range(len(b)):\n", + " ini+=b[k].real\n", + "moyb=ini/len(b)\n", + "ecty=std(b.real)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-0.092306339822423" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "moyb" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.5704264545401647" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ecty" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "pic=[]\n", + "for k in range(len(b)):\n", + " if abs(b[k].real)>(moyb+2*ecty):\n", + " pic.append(b[k])\n", + " else :\n", + " pic.append(0+1j*0)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "b=pic" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "c= ifft_object(b) " + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot(x,c.real,label='Signal débruité',c='r')\n", + "plot(x,sin(x)+sin(2*x),label='Signal sans bruit',c='b')\n", + "grid(True, linestyle='--')\n", + "title('Comparaison entre le signal \\n sans bruit et le signal débruité', family='serif', size=20)\n", + "\n", + "xlabel('$x$',size=15)\n", + "ylabel('$y$',size=15)\n", + "xlim((0,6*pi))\n", + "ylim((-2,2.8))\n", + "\n", + "legend()\n", + "savefig('comparaison_signal_1D_bruiT_DbruiT.pdf')\n", + "show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# __Débruitage d'un signal 2D__" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "N = 64\n", + "k1 = 2*np.pi \n", + "TYPE = \"complex128\"\n", + "x,y = np.linspace( -np.pi, +np.pi, N, dtype=TYPE), np.linspace( -np.pi, np.pi,N, dtype=TYPE)\n", + "\n", + "X,Y = np.meshgrid( x, y )\n", + "\n", + "a2 = pyfftw.empty_aligned((N, N), dtype=TYPE)\n", + "\n", + "\n", + "b2 = pyfftw.empty_aligned((N,N), dtype=TYPE)\n", + "\n", + "c2 = pyfftw.empty_aligned((N,N ), dtype=TYPE)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "fft_object_2d = pyfftw.FFTW(a2, b2, axes=(0,1))\n", + "\n", + "ifft_object_2d = pyfftw.FFTW(b2, c2, axes=(0,1), direction=\"FFTW_BACKWARD\")" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "ar = random.randn(N, N)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "a2[:] = np.sin( k1*X ) + np.cos( k1/2*Y ) +ar*0.5\n", + "if( TYPE == \"complex128\"):\n", + " a2[:] += 1j*X*0" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "fft_2d = fft_object_2d() " + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "moyb2=zeros((N,2))\n", + "ecty2=zeros((N,2))\n", + "\n", + "\n", + "for k in range(len(b2[0])):\n", + " moyb2[k][0]=mean(b2[k].real)\n", + " ecty2[k][0]=std(b2[k].real)\n", + " moyb2[k][1]=mean(b2[k].imag)\n", + " ecty2[k][1]=std(b2[k].imag)\n", + "\n", + "\n", + "pic2=zeros((len(b2[0]),len(b2[1])),dtype=TYPE)\n", + "for k in range(len(b2[0])):\n", + " for l in range(len(b2[1])):\n", + " if abs(b2[k][l].real)>(moyb2[k][0]+4*ecty2[k][0]):\n", + " pic2[k][l]=b2[k][l].real\n", + " if abs(b2[k][l].imag)>(moyb2[k][1]+4*ecty2[k][1]):\n", + " pic2[k][l]+=1j*b2[k][l].imag\n", + "\n", + " \n", + "b2=pic2" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "c2 = ifft_object_2d(b2) " + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "n2=a2.size\n", + "freq2=fft.fftfreq(n2,2*pi/N)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "figures,ax = subplots(figsize=(4,4) )\n", + "bounds=(freq2.max(),freq2.min(),freq2.max(),freq2.min())\n", + "stretch = ( -np.pi, np.pi, -np.pi, +np.pi )\n", + "wavek = ( -N/(2*np.pi), N/(2*np.pi), -N/(2*np.pi), +N/(2*np.pi) )\n", + "im=ax.imshow( a2.real, extent=stretch )\n", + "\n", + "ax.set_title('Signal 2D bruité',family='serif',size=20)\n", + "ax.set_xlabel('$x$',size=15)\n", + "ax.set_ylabel('$y$',size=15)\n", + "\n", + "colorbar(im,ax=ax)\n", + "\n", + "savefig('signal_2D_bruite.pdf')\n", + "show() " + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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970gaHX4GldQADQZrQudknak/S3jJfcBd2pJQP1kdCoT+pwpwR6/ujaTttAMazAL6KcKM65hrdYrQF/aGLM/WqQw7BlWl2uFnUEkN0GBwoYj8iohMisg+wtawP0z4B/NuyVkP9eN4FME1/Laq1np4byvNDuhv53RAg1lAVxMamndF7mk2QFcCf6KqD3RZn21DM5xJsoASZ8r/RXAXvk2Y33It8OuEt/gqqvpOwsTDZeBvCC7IDYRgdgDPzGY4v1JELpcQa/yG7Nrnmtc6rFPTLerEperm3vXS5rlfYA0QwLtU9XTknqa7pYRQTjsYod7hZ1BJa8H6SLYU4hXAFap6sL+1SWw3rnrckP7FJ/Z1dO8jH3J4INeCpVGwRGIbM8jWTSckFyyR2KaEiYi9ccFE5H0iclREogMBInKNiJwSkW9knzf34hmSBdQHsn6Y/+FO3S0i96jq5f2pUWI7osCK9syGeD/wDuCDG9zzd6r6gl4VCMkC6gvN1fAtn8v7Xa/E9kIR6hQ6+uTmpfoF4OTZr/VaUgOUSGxjGiodfXrEU0XkmyLySRF5TC8yHDgXLJtC/wVgmFC/P1fVGzZKUx4e1+HxPQDUy3Zes2Wa4gb6Ci7mabFqF6RiF3SlPTCqlE0qHbZC6sPWhjeyW7xVLG6RQNFlW1i2C7IcLmjd3ez2IpMhK68xYvWoD4V71C9H9XX2ZbtnLVSyC1WbduNHQ6VoGTaftTFs52IaQ1znbjQG0zlPY4jrnKcxxHXO0xjiOudqDFGdYxoDzC0ePq6q+9tLaqfZB9Qh+0TEzym7UVVv7DQxYYrFZao6LyLXEbY2ubKL9FEGrgEizHH5sexBy8AXReSTqvrl9RIMj+/hsc/9NQDmL7IvdiVbYeX/KEeP2h/JroM2iXb4riOrx7UHHgwHbquD0v7zV4+rD79w9fjUQ0dWj5fOC38M9SErr7xgx+OHLb9dd82tHhcOhLly9Rmb5iLDw3b9IRevHi9euXf1+PRDwte3vDv+Rzg86571XpsfOPb9YGnrvfevnmtUKqvHxV22oWDjirCtz9zDbblaTGOI65yrMUR1ztMY4jrnaQxxnfM0hrjOeRpDXOeYxgCf+fq/v6etkHUR6p33AR0/k2F4P+dKVW8Wkf8uIvtU9fhm84QBbIA0vCKaq8PL2SdNVkokWggzobemF0VELgCOZFueXE3ovjlxpvkOXAMEkG218DXg4cA7VfUrGycALba7I83jhpuL3vDXC+6NVrQvctXdarh2r+RcsFLcLG8ex86F8vx590sz74LdLK48Ss5cL0rb8ZqXoHskf2/D1Xk1v7LzparOfFlTdiFSLtHjmM65GkNU5zyN1zvO1RjiOudo3Jp3U+dcjSGuc0TjblEVquv5310iIn8KXENw1Q4RZtCXQzn6bsKukr8sIjXC1i4v0R7MYh7IBijbXuEJIjIN3CQiV6nqmvkJIvIa4DUAQ2Mb7cOVSOxcGj2aiKiqL825/g7CMH1PGehRMFWdJWzl2RbPSFVvVNUnq+qTyyPjbWkTiZ1O6ITuzTB8vxg4C0hE9gMrqjqb7XPzHOB3N0qjYqMVDdcx2RhqWojOTHbX/eiKDtuFwmjW6elcAx0ZcunciJAvr9xaLtRXfKepq8ewSV8aGV5bLiDueO2IUPuz+GfyQ1G+vLVlh/wKI1ZGwflP4s43n3VN+qjGENM5V2OI6pyncWvZTZ3zNG4tu6lznsatx02d8zSGuM4xjbunq07ogWTgGiDgQuADWT9QAfgzVf3rPtcpkRg4trIT+mwxcA1QttXoE3Nv9GkKUMv2BKy7F2t9JLylfD9dbdTeUrVxN79k0hIWFyealbHr43a9Nmbp6j6/0XC/fzNL3V0fc/UYN+nLE6HyhZrbSsdZC7VxO14ZtbJrI806xPsCvRY1l64+Ht7OxQmrkLgOWx23DRab9ay5PRdjGkNc51yNIapznsYQ1zlPY4jrnKdxqEe7znkaQ1znmMbdovSuE7pfDFwDlEgkOqeRXLBEItEPmp3Q25kd0QBpAaqTwQRfmbDO1Hp23HAdwStLZrJWJ5ypvct1Ulbag1SsTJutvTxp6VbcAFwtK099x6wbJV1x5VV3WT2GpoI57o1p3ylanbJjP/O4NqHZT7+0wB3W3bNOOg2y/IoLllnBd7JPmXuwMllsTx/RGOI6d6MxmM55GkNc5zyNIa5znsbhuF3nPI0hrnNM425RhHrv1nn1hR3RACUS5yqpEzqRSPQFVdIw/CCgRVjZlc3LmDIzuTQepr3XV5w5v2wm6/K0na/MmcksjWzUwi0tWN7tXSJxx84NmArllcqWsFZ06ZZc2S6P8p7gmpTdlPzGkJnly9P+2Jv54VmLU/GV5bWGq6dzRyq7w3Gx4uanLDsXZNKOK5lGTX0hrjHEdc7VGKI652kMcZ3zNIa4znkaQ1znPI0hrnNM425RhJU0CpZIJPpF6oROJBJ9QenpZmN9YUc0QFqE6u5gjo/uXlo9PzUejitVM3dna/bGWF6wkZ/ygn+T+Dn3gcpul86tfa3vNrN8enoRgJEhO3d62O1lU7XRkMqcN9HD17Bm462y/WFV9riRnWm36dXusNHVnul5YpwUGz6qLtioSyV71sKKG6mp2p/CyrhzY/aE4+puc0ViGkNc5240BtM5T2OI65ynMcR1ztMY4jrnaQxxnWMab4ZkASUSib6gpImIiUSibwx21NNO2BkNUKlBYW/Y+vPi3adWT184Fo7nV2wE5C7nM88vulELN0FRC9lbxQ2++O04l/eaOzKx11yCy6bDVp+7hswtOTK0a/X4gBtpWp53E+Oq2Upu5xr4ldUV2yGU2l5zOy7YE3bJvGyXbTFacJW+p2j1fGDJbS26GNwfqVt5xWVLtzLh3b9wvqkvxDWGuM65GkNU5zyNIa5znsYQ1zlPY4jrnKcxxHWOadwtISxPGgVLJBJ9QFWSCzYIlEt1zs/eVI+ass3OLx0JG4PPuyXLNffG+M6ivbGXl+xtqdJu1q7pmNxrHZOXTs+uHl81FTY+nyrZG3vPkB0vrNhb8f5Fk77ZebtmHxq37423Bsb32Fv/YVNhS95HTxxePVcUt8F7wdLNVexZm1aJX0ZQ8Msoxt3ygz1h5fhFzhKIaQxxnbvRGEznPI0hrnOexhDXOU9jiOucpzHEdY5pvBnSRMREItEXwn5AqQ8okUj0hbQj4kAwXKxzxa7gClw1bjGYLi8fA2CuYab/otvf8+i0zRk5suB8nogstWkzk/e7+SCP2HV09fhxY/cCMF1wrkHRAoOdnLLlBzNuzshSJZjojbJfIuA223JzUS6esk7fpkvw+DELJVVcJ4LRcbf6/M75bMW56zQu+E5at+J8ZHeIY9XUF+IaQ1znbjQG0zlPY4jrnKcxxHXO0xjydY5pDHGdYxp3S+qETiQSfWMnzITe3vZbInGO06DQ0ScPEXmfiBwVkdvWuS4i8kcicpeIfEtEntSL+u8IC2ioUOPysTBa8YghG6F5aDmM3Mw2LETvsZHJ1eMfTOxbPZ7ZZaZ7td7+VilPmol+wYTld+WohRt+RDm4CntcjOIRF4z+0Nie1eODEzbx5FC2UVet6IPVmYk/OWkm+kMmbC7KD40E9+CR5Xh03Iqay3Ng3J71/okQFvi0d0uqLmjguLmbeyeDa9PUF+IaQ1znbjQG0zlPY4jrnKcxxHXO0xjiOudpDHGdYxp3S9iOo2cW0PsJcb8+uM71HyfEgr8S+BHgXdnPM2LgLCARuVREPicid4jI7SLya/2uUyIxqDRUOvrkoapfAE5ucMsLgQ9q4MvAtIhceKb1H0QLqAa8QVW/LiKTwNdE5DOq+p1+VyyRGCRCH1DHNsQ+EbnV/X6jqt7YRXEXA/e53w9l5w7Hb++MgWuAVPUw2UOp6pyI3EF40HUboLLUOT9zBS4qmel+fjGY3SPi3KeyjXDsHbZRlLERu2dltF2W0VG7vnfYTOYLSpbfRaVgVk8VzNxfURvNOd+VPT1ik92OjoTRk2XnlhTcZluTI7YMYv+QPd8FpTBB7/xi/Gs8VrTy9g9ZPaZGg7ux4AL01Yvm8pVHzD1o1vN852rFNIa4zt1oDKZznsYQ1zlPY4jrnKcxxHXO0xjiOsc07pYwCtZxA3RcVZ+8qYICMTNqZ8aGbyIilxNihH2lvzVJJAaRLV2KcQi41P1+CfDAOvd2zMD1ATURkQngL4DXq+rpyPXXiMitInLr/Mn4lqSJxE6ngXT06QEfB16ejYY9BTiVeStnxEBaQCJSJjQ+H1LVv4zdk/mvNwJcdtWkDmejIGVnFQ5LOftp5u6IWGNVdut4CgUXG73pjjgDs+iuDxVcfgVzK8rZF90sF6Asy+7YyvN5FItZvPCCW2/mjsuubF/nkey5yuLWGrl3yoh/bjca13wW/8yNgv2RNuvj6zns0sc0DsftOudqDFGd8zRuLbupc57GENc5T+OQd7vOeRqHMtp1jmncLb0cBRORPwWuIfQVHQJuAMqhHH03cDNwHXAXsAi8qhflDlwDJCICvBe4Q1Xf1u/6JBKDTK9cMFV9ac51BV7Xk8IcA9cAAU8Hfh74toh8Izv3W6p683oJGhRWV2LPqT3SfCN0BM417I12uuG2SK27SBBuxXKjGd3BvV2qNct3oWadn3N1m+4/p+GtVm5YB+Rcw/JdbFi6xZqLRb4S7lG3XayfJlNxZfulJHPZsyw24luynlabdzPnVqo386u78tRFtKituDpn9fQr3WMah/q065yrMUR1ztMY4jrnaQxxnfM0Dnm365ynMcR1jmncLTthJvTANUCq+kXiPe6JRMKhQC0tRk0kEv0ibUg2AFQbRe5dDlPw7xuZXj1fJEypn3VB8A5VbXr+4UXbLnVxwcxnWWiXZWnIzOQjS7ac456qTb+/tByWK8wVrOP5vprVp1lHgOOLFk1hJYscIQvOTRiyP6xTblX3/UuW38GxUPZ0IT6P5KCrm093ejE8a8OtThe3Gt6PKZ7I6unrHtMY4jp3ozGYznkaQ1znPI1D2e0652kMcZ3zNIa4zjGNu6bDWc6DzI5ogBKJc5G0IVkikegryQIaACr1Mt87fR4A55UvWz0/OxxM29m6uQa3z1+0enz/KVux3JhxAfRm2v3qFbXrh8fMrbh9zNbjTRTDqMx00ZYfHKqaS3Dn3PmrxydPmdldnAlfQ2khviFZpWDm/N0Tlt+3Ry5pq6fn9sWLV48PnrZ0izPB3SjPuHktzgWrLVs9To6Een5v/LzVczGNIa5zNxqD6ZynMcR1ztMY4jqfLY0hrnNM425RoNZIfUCJRKIPpGH4RCLRV1If0ACwXC9y8EQwf8dKNm3/wdFgxs/VzLz+7oy5EvPHzPQdOWZm8rAN7KxScBPHFsqW7rvDZvIXJdvcqmRuwoMVF5jwhI3A6VGr0+jxYEaX3Tw3H5gQN/Hv6Kjl962hYP4vNeIT2X5w2kZoDh83V6h8PIzKjBxzyy9MtjVxy5dKYWLfwRFzL2IaQ1znbjQG0zlPY4jrnKcxrKNzjsYQ1zlPY4jrHNO4azT1ASUSiT4RYsOnBiiRSPSJ1AANALpSYOloGIG5s2gu1tGxMJltacXM4RMnbGOqoaP2+KNHzLQfPdm+z1Jx2b5oLZkrcWzYzPXbsj+G0bJNM5tdMjdg4ai5FWNHzSUYezCUNzRv65y8C+Zjiy8Mmbl+Tym4RYsrPtyNcWzWnpWjlm70SMh77IiVV6zaM1fH3dqlLIb74rCNcMU0hrjO3WgMpnOexhDXOU9jiOucpzHEdc7TGOI6xzTuFkWop1GwRCLRL1In9AAgNWEke9POF+0NuDQR3kh1F/GhdMw6EkeP2pc3fsTtAXPMpvg3KVYtXaPsVjoP2/njBGugOOTesG7JwfBRe6t7a2D8wWxfn9PWudsYcrHFXednfcSeZXEovPUfrMXfgjpr6dZYA9kbefywlVdYtucvT9qbXovhuDHsVsBHNIa4zt1oDKZznsYQ1zlPY4jrnKcxxHXO0xjiOsc07hZNndCJRKKfaGqAEolEf0gTEQeCQg2Gs4hGdecqNKe7F1fsSxqacZ2Yx81MHj1ic0pKR9u2oEbq1hG6Mmqm9orvTGy6K24ZRXnRrg83WqMAACAASURBVA+fcB2TJ9xWng+GCBCFUxYJQkfMtNeilV0d965CcB+qbhMu//c47JY7jJxwHcBHQ+ft0IMW/UEq5iYU3ersxlDoZF2Z8C5Ru8YQ17kbjcF0ztM41K1d5zyNIa5znsYQ1zlPY4jrHNO4WxRSJ3QikegTGvqBtjOpAUoktjFpFGwAkDoMnQ6vAj/FXTLztOBdA2f5D5+yUZnSjK2s5oQFo1u9XnTLCHabib582vJujp5416C04Mt2c1FmzT0ozAQTXWcsyB0umF15zMobPm1fWXUu1KlRcn+E7rBsln9L2dkI1EkrT5fMPSo0XMSGyeEsvT1/TGOI69yNxmA652kMcZ3zNIa4znkaQ1znXI0hqnNM425Rtn8n9EA6kCLyPhE5KiK39bsuicTg0llc+E46qkXkWhG5U0TuEpE3Rq5fIyKnROQb2efNvXiCQbWA3g+8A/hgn+uRSAw0vegDEpEi8E7guYQIqF8VkY+rams49L9T1ReceYnGQDZAqvqFLCxzhwmguBy+iaLbWKuRTet38eJW7wMoVlywuiUzmeuLzlVYvXfCHbugc24VuR1L9HppTdnmHmgllN1w5Yr7yyos2QOUKi6P5ebPuAu2tmxX52Z+zu3yZReGzSVo1nONbhGNIa5zNxqH+yfa0sU1hpjOeRpDXOc8jcNxu865GkNU55jG3aIKjd6Mgl0N3KWqBwBE5CPAC4HWBqjnDKQLlkgkOqMLF2xfM5R59nmNy+Zi4D73+6HsXCtPFZFvisgnReQxvaj/QFpAnZAJ+BqAobHdfa5NItEfunDBjqvqk9e5Fuskas3568BlqjovItcBfwVc2XHp67BtGyAfG35876XalHBNf5u0/Gw5XnuvG9mRyPchcTcn+tV1UJ7GypNC+7mWsteEgYo8X/T5W8prHkvBl+EyLvh7Oy8jdtyVxv6ePI07KC+qMcR1ztO45TiuS7vGobhI2TGNN0GPRsEOAZe63y8BHlhbjp52xzeLyH8XkX2qevxMCk4uWCKxTVEE1c4+OXwVuFJErhCRIeAlwMf9DSJygWSttYhcTWg7TrTl1CUDaQGJyJ8C1xD81kPADar63nUTFKA2EkR24bmpjwYrUm0qx+p9ALVxN8dj3KIYyKStuG6i7npt1NLVXX7N8vzOneKCvNdG/b0mfXks5F1YsY5LcYEQ626OSs0tUaiNNn/G7XBfN//cjYmQX2nclgMU3DwnGbNnrY+X29LHNIa4zt1oDKZznsYQ1zlPY4jrnKdxOG7XOU9jiOsc03gz9GIitKrWROR64BagCLxPVW8Xkddm198N/DTwyyJSA5aAl6ie+RjcQDZAqvrSftchkRh4FLTRm4mIqnozcHPLuXe743cQpsb0lIFsgBKJRGds95nQO6IBahShOhW+iJVdZhXWJsIygILbKMsH4Fuecssr9rpAcnWL8d1kZY9tSbo8bflVd7l7djVdMJsP0nCuTWnRlb3buQdzwR0puG1IGyNmli/vsTkjy1OWRzUrr7bLyvP4ZRI+3fLukF/BxW2XinMJdo26e0M9qi59TGOI69yNxmA652kMcZ3zNIa4znkaQ1znPI0hrnNM482QFqMmEom+sBPWgqUGKJHYrihnNoY/AOyIBkiLUNmbuSN7bYSjPB7mydddUMFlt6lUyW0WVlpye0UXMnPdmbeVvWYmL+1zZvdeZ5bvDfP2y2VzS1bcfsYVF1WhPO828loO5vjQmNv0q2zXl/bb+cpe5x7sDVP4S9Nr1ifY9aKVXVxy7shiOC7U3fIStye033xsMXvWpr4Q1xjiOudqDFGd8zSGuM55GkNc5zyNIa5znsYQ1zmm8WbQuPe9bdgRDVAicW7S0RyfgSY1QInEdiZ1QvcfLSvV/cFUnt5ngb/3jIeVx5WaPeaDYvG7K8s2o664vM7GU817dzuX6Dw3+e48cwnO2xdmq08Mmal+YsxGz2bcvtJLS+YqSD2U7fc+9oEJl86z48p+s7mH9y0BcMG023PYxU4/MmRuTqXq3YBmOWV3zm3CNeHK3h+Oq/vN7YppDHGdu9EYTOc8jSGuc57GENc5T2OI65yvMcR0jmncNZo6oROJRD9JFlAikegfyQLqO4VSg4nzQqiVH9p3dPX8xSNh3+HTbkGP/7rur5hZvrQm8mn7qETVzZtb2W8jIxc4l+CqPQ8CsKtkZvvhEXP5bnOT1uaX3eS0WqhHbcytY3LrnJb32WtOnDty+b4Qi+gRu+yZPaOl/avH36+6UZ7VSYdWnt9kbMWWLlE5L7gjTX0hrjHEde5GYzCd8zSGuM55GkNc5zyNIa5zvsYQ0zmm8aZIo2CJRKIvpHlAg8FQqc5lu2cAeOIu29jtsqGwVclsfSya7nTF5gTNuw5SLba/nVemXazvvdbx+sjd9lb84cmDAEwX7fp9w3tWjxdrZgHcvuim/ldDR23dreT2K71X3FyUi/ZahIXHToctWx475jezM0aL1nF82nUG35/NV1lW6xz1W4vWxtx2sPuCNdDUF+IaQ1znbjQG0zlPY4jrnKcxxHXO0xjiOudpDHGdYxpvhrQUI5FI9I/UACUSib6RXLD+M1JY4eGTxwC4atTM5MtLwW2YdcsvFt3xfbusZ/muBTOfV9T5PxnipuFfOGWdoo8ct07Rx46EsqcLZlJ7N+HopHWKPjht80eOZOZ6o+xcFBd0b2TaoipcNmmu0GPG7gfgccP3t9W3lcNTVvbMQuggXVxxW5O6TmgdsyUO+6ZC53NTX4hrDHGdu9EYTOc8jSGuc57GENc5T2PI1zmmMcR1jmkMcPeGJbQjyQJKJBJ9QQV6tCFZv0gNUCKxnUkWUP8ZKtR5yHCYr3FpyealXJZN959qmBt0/5Dto33hmJn5D4yb+TzX3FjL+ddjY+aCnT9qU/L9KNClpVDOnoKX1erTrCPAntELV49PjofRoxXMLZGyjbpNjdt8l4tHLb/Ly6Hsy0pmzntOu4AFF47Ys+4aC+5GZdzNy3GbdJXHbWRn79hCW91jGkNc51yNIapznsYQ1zlPY4jrnKcxxHXO0xjiOsc03hSpAUokEn1jmzdAuRuRiMjfisiTtqIyrsxrReROEblLRN64lWUnEtuG5kTETj4DSicW0CHgKyLyYeC3VDV/yOUMEJEi8E7guVnZXxWRj6vqunGqizSYykZBpgs2oWyi0FydbObwdMFM+PGiuVXDzrxeKLfPbx8um8m8q+zyc6NcU4ViVu6IO2crxyeLZuZPlG0EZ2golF2rWrklt9nWqCt7wgUrnyxUsvLc/sNu2v90weo55coey/IrujL8qurykGk4Vqpm6e054xpDTOduNAbTOU/jUHa7znkaQ1znPI1Dee0652kMcZ1jGm8G6dFSDBG5FvhDQlieP1bVt7Zcl+z6dcAi8EpV/fqZlptrAanqzwFPBx4GfE9EfkdExnOSnQlXA3ep6gFVrQIfAV54FstLJM5p3Ev/x4FHAy8VkUe33PbjhFDMVxJCor+rF2V31Aekqv8IPENE/iXwn4FfFJF/Rwhg1msv9GLAz3k/BPzIhvUD6llbWne1qWf7Vdado9xwbW7DWQsN/xSRJ/IWQt0dV100vkYmRd3tk+lfUHUX87fh8mg0h1Jdub48f+zrXM+OG2tKsTJWdL1nzeaiNHxHcLzsRpZH3eUb0zjc065zNxr7svM0bi27sXouR+OWspvl5WkczrfrnKcxxHWOabwZejQPaPWlDyAizZe+9zpeCHww+3//sohMi8iFqnr4TAru6slV9aPAo4A/Av4b8E8i8pwzqUCEmMPaJrOIvEZEbhWRW+dnViJJEolzgM77gPY1/1+yz2tcLrGX/sUtJXVyT9d0PAqWxYx+AvDPgEcCp4HHAbeIyM3Ar6pqtxM5YxwCLnW/XwI80HqTqt4I3Ahw2VWT23wsIJHYBEo3o2DHVfXJ61zr5KXfkWHQLbkNkIi8i9DoPJawt+QpQjD7DwBfAY4BbwK+JSI/q6qfPMM6fRW4UkSuAO4HXgK8bKMENS1yfCVMuz/mlgNMNkKn4Cln+x+t2fT82apNl69UbcVyo7lq25nJSyM2l2OmanNKTrqIB8caYblCHeuMPOY29jlZt66zU67saraPjLrV4jXnMswtu7JX2ss+Wbe5TZ4T9d2rx8dXrJ7zy0GjetUtSXBbiFZLpsXcynCW3nSLaQxxnXM1hqjOeRpDXOc8jSGuc57G4bhd5zyNIa5zTONN0ZtXbycv/Y4Mg27pxAJ6KvBlQifVl1X1jsg9Pyki/4Xgml15JhVS1ZqIXA/cQuiRf5+q3n4meSYSO5UejYJ18tL/OHB91j/0I8CpM+3/gQ4aIFV9Qod5/TnwhjOrzmqZNwM39yKvRGJH0wMLaL2Xvoi8Nrv+bsL/43XAXYRh+Fedecm9nQn9TcJQ3ZZT1SL3VMKGVAeGz3NXwkZWfqOsu5ft+mEXs3tp3s3xmM9k8QHzSmaiP7hg6e6etC05LyiFjaxmizb35+DKvtXje5bs+Pi8uQr1uWCOFxacqe62LJ0bMVfi0KKtLv/BWHiWyYK5Ip4DVXtWn+7UfDZ/Zt6+/uJyfJTv+Hio5z27bGO1mMYQ1zlXY4jqnKcxxHXO0xjiOudpDHGdczWGqM4xjbtFtHer4WMv/azhaR4r8LrelGb0rAFS1WXg073KL5FIdMAAz3LuhLQWLJHYzmzz8d8d0QAt10scmAum9/6hS1bPn24Es3q+bubwnfPnrx4/OOuiJsyYizU0E4mK4YLLHR230Y47xi9YPZ4ohmn5fkr+/VUbJfn+aXMlTp0yd6U0E76G8oKP1mB/WdWSuS73TFh+t49uPA3jjoWLVo/vPW3pVmaDHv45fVSM2oobgRsJ9Twwaa5NTGOI69yNxmA652kMcZ3zNIa4zmdLY4jrHNN4M6QNyRKJRH/Q3q0F6xepAUoktjPJAuo/1VqJ+06EEYjRkpnMJ8fC6MLpFTOHvz9jJnrlhLkPo8fNTB5u7kflvlypudjwbsTkB6N7V49L2etoeshcgwcWLTDhvSfNRJfj5o6MnMxWSM+5dU4uNjxiozYzY841GQluznLdvsaCs8kPzFndjp+wiYRDJ0J+IydcwLxlS7dSceuUysElum/MRnhiGkNc51yNIapznsYQ1zlPY1hH5xyNIa5znsYQ1zmm8aZIDVAikegXqQ9oANCasHw8vDHvLtt8ldksPO7Sir1hTpywt9vQcfeWOm7f5OjJ9m+1UHNvrGFLd3LE3nrfz27xe8vMLplV4K2BMWcNjB4N5Q3Nu5Xl3gLyK9HdkpD7h4JVUq27ZQ2OY7P2rGusgeMh77GjVl6x6jq9F90K71I4Xhy1usc0hrjO3WgMpnOexhDXOU9jWE/njTWGuM55GkNc55jG5yI7ogFKJM5JUid0IpHoK8kF6z9Sk9VOv/mydYo2oxHUXQdyYT0z+ZjbAvV4+xaZBRdzvDbiVlOP2vkT2fakRbfdaG3RJF7PHRk7GrbnLJ82l8K7ICrm2tTGfGd4cDuO+A2vXKdAY8bmtvgO4NFjoX5jR6y8wrI9f2mXW7VeLmXlWn1iGkNc5240BtM5T2OI65ynMcR1ztMY4jrnaQxxnWMab4rUACUSiX4gpE7oRCLRT1ID1H+kDsMzzdETe6TmdHdxsbn9tPgRNxLjXYLyUVtlvUrDTP/quJnltXFzMSrlzH0YcqMebuV1s44AoyfNHRk5FpYXFE5Z9Acd8Sa6jQKtTLglE5mr4APtecqzbt7NjIs1fyKUPXTMAuJJxUVxcCNb9ZHgblV3uX2ZIxpDXOeuNIZVnfM0hrjOeRpDXOc8jSGuc57GENc5pnHX9HA1fL/YEQ1QInHOkkbBEolEv0gW0AAgdRg6Hb4Jb66ThXMpuKAZZQs5ztCcC1A3aya6zIQY3z7iUKnoXKk95h4tu82maqOZGzhk95YW4ksAhmZtVKYwm5nos1a5wrBbOT7mjve4GO7zwfz3m5d5yvNW9tBpe9ah2eAKFWbMDdIlW9ZQaLh7p4az9FZGTGOI65ynMcR1ztMY4jrnagxRnfM0hrjOeRpDXOeYxpsiNUCJRKIvdBcVYyAZqDngIvIzInK7iDREZL0QIolEIqO5LWveZ1AZNAvoNuDFwHu6SSQNKFWCyoWqX3lM5Jwz95fMDJZFiwfeWLBRktXrFbterLjRl4rl19zvV5xL4UKjUzIPhGLFRklksZKV69yEhl0vLFomJTd60tybq1jx68Zouw5Qcs9dXAq+ki660aAlN0rkVmcXl2pZuW5P5YjG7edDed1oDKZznsYQ1zlP41B2u855Gofjdp3zNIa4zjGNN0NaitFDmiF/RLb3PreJxJYxwNZNJwxUA9QL1pibkQ27117X+HGj/bUiLujeuiZt7Pw68dCjefhyG+sUEsvD37pe273ec8fKXi9da7mw7qboVrfONQbTuSuN/fk8jVvLjum8Xh55Oudp3Fp2LF03bFEfkIjsAT4KXA4cBH5WVWci9x0E5oA6UNsgEusqW94HJCKfFZHbIp8XdpnPamz42vJCfoJEYochXXzOkDcCf6OqVwJ/k/2+Hs9S1Sd00vhAHywgVX1Oj/JZjQ0/vvfSbW6IJhKbZGv+8l8IXJMdfwD4PPAbvch4Z7hgBdtYqu52t2wMZ9+OewX4jb7qI84AdPNuZCyLUqBmLqvbpKo+5DaTGvLzUtb+BGi4TmgXJp66W+1ezsoWt+mXjNjckMZw2aVz9R9ulmd/hd4j8nXzz91cSlFyK73XuCK+7GxV+hrdYhpDVOdcjSGqc57GbcfVZrmuDhGNIa5znsahvHad8zSGdXSOaLwZtmiE6/xmGGZVPSwi561znwKfFhEF3pMZCRsyUA2QiLwIeDuwH/iEiHxDVZ/f52olEoNL56Ng+0TkVvf7jb6BEJHPAhe0J+NNXdTm6ar6QNZAfUZEvquqX9gowUA1QKp6E3BTv+uRSGwLupvjc3yjfpmNukZE5IiIXJhZPxfi43GvzeOB7OdREbkJuBrYPg3QZmkUoDqZBXybtG+kNh5eD+JM4+KSHVcn3PKCaTPLS1VbGR27Xt1l6fyttYlQnndL1PXzr0y6sqdcoLzdYTW0N8S9y1edcsdupfbKRPNnfNimUPP1dOmmg/lfXLDKi3NR6lO2Oru6q9SWPqYxxHXuRmN/T57GENc5T2OI65yncThu1zlPY4jrHNN4U2yNC/Zx4BXAW7OfH2u9QUTGgYKqzmXHzwN+Jy/jgZoJnUgkumOLZkK/FXiuiHwfeG72OyJykYjcnN1zPvBFEfkm8I/AJ1T1U3kZ7wgLKJE4Z9kCC0hVTwDPjpx/ALguOz4APL7bvHdEA6QlaIZgX5m26ffFyTAdvl51ZrLb27niVjoPLdj5YQnxzP2bo7LPpdvj8pu2m+q7w5T64rDVoeb2+11etpGWpTnLo7QURoTKQ3av3xO6ss/SVfY6F2N3Vs60TfsXV+mqWJ1Li5bf0lwop7BibkChYiM1K26/4qW9xaws7HpEY4jrnKcxxHXO0xjiOudpDHGdczWGqM55GkNc55jGm2GQ13l1wo5ogBKJcxIlbUiWSCT6Q9qUfkDQEizvD6by2H5bljE9HjZ/qqzYY57ERiQqFTOfi8tuz+NS+wZRld0uVIuFl6e2z8zy3fvCRlejQ3bulJv0tlB3IzEVq1Mxq9+Q23/YT2pbPM/OL+91o1z7wsrxfdPx/ZVPFG0Ip7JsLlZxKeQn6p7fR0Yd988a6tHUF+IaQ1znbjQG0zlPY4jrnKcxxHXO0xjiOudpDHGdYxpvitQAJRKJfiHrLXrdJuyIBkhKDcr7wpv4YftOrJ6/cPQUAHMr9mbyscWPL1vc70LVdUyW2zsF3a0s77eO0N377Y38yL1hftZk2TaJOTJqna131u2tV6m4jslsLsnKeNwCquxznbDn2dqOh+ybBeBhu4631RfgQHnv6vE9NTuuLDetDyvPW0ArPgrF/tDJ0NQX4hpDXOduNAbTOU9jiOucpzHEdc7TGOI652sMMZ1jGnfNDtgRcUc0QInEuUrakCyRSPSN1Ak9AAyVajxkX9gf6XFT96+ev2L4GACn6mPRdAuug7SybJ2JWspMZvflVqftVTPs3JFH7D22evzEqXsB2FO0Ttp7h51ZXje5v7fk5p2sBHN9TcSHsusUdh3A+1wn7FW7D4ef44faHw4YL1kH6kLVnvVYM169i2jhtzpdGbeyG/uDO3LFPtt/KqYxxHXO1RiiOudpDHGd8zSGuM55GkNc51yNIapzTONNkRqgRCLRFwZ8w/lOSA1QIrGdSQ1Q/xku1rhyVzDTnzh2z+r5y8th1GK2YXNxKg0zy48s2ZyguxfNfF6OxVqfNjP5gmkz0R818eDq8ZNGD4ZbC+Y+7C3Z3JGZFXNRjrnV2ScrwUT3gfbUbX5VnrbRnsumTq4eN12CJ4yYW+IpuNfj0Wl71tMLYbSq6lymmoto0Rgzd2R6OkR0aOoLcY0hrnNXGsOqznkaQ1znPI0hrnOexhDXOU9jiOsc07hb0kTERCLRV2S94AXbhNQAJRLblTQPaDAYlhqXjYTJcQ8rm6twWSmYubMNmyz34LC5DBeOXbh6fGTCzOeFlfZtksYmbLTjgnGLa37FsE2Me2gplDNdsPRlsfIOjNgEvjvHzl89Pj0RTPSamyQpZRt1m5ow9+CSMZsY99ChUPZD3YQ8z4IesfJGbLfNgxN7ADjqRokaVTdSM25LHPZNhJGmy1zdYxpDXOduNAbTOU9jiOucpzHEdc7TGOI652kMcZ1jGm+GNA8okUj0j2QBJRKJfpE6oXuIiPwe8BNAFfgB8CpVnd04FRSlwe5SMGOnCmba7ioEs7sg5j7tLdqo1C5nUg+XLd3SUPsIzXDZ1iZNleOjXE2XYHfRzP05tetTRRvtmByysoeGs43TnFtSdC7Y+JCNwE2VrOzpLL+pgtW34NYd7S1YebvLdjyaPWtpyG3ohTE0ZL+Nl0LZTX1Dee0aQ1znbjQO94Sy8zSGuM55GkNc5zyNIa5znsYQ1zmmcdco60dg3SYM2p7QnwGuUtXHAd8DfrPP9UkkBhppdPYZVAbKAlLVT7tfvwz8dKdpG1mkuJjWDfeWqK8TqFYjMc79OX/cULea2h9nDnndBdqrrxcifJ28V8+tc28eDaeAf1Zfz2Z5a8rNqY+vw3p/z3k6x/JtPd88ztM4nN9Y5zyNwXTuRmMwnfM0bis7pv0m2QnzgAbNAvK8Gvjkehd9bPj5mZX1bkskdi6qnX8GlC1vgETksyJyW+TzQnfPmwju8ofWy0dVb1TVJ6vqkyd2l9e7LZHY0WxFWB4R+RkRuV1EGiKybnBDEblWRO4UkbtE5I2d5L3lLthGERgBROQVwAuAZ6t21nTXtMjJWlhpfaJhq54nG6Ezcc7NFj1RsxXZJ6vWiVmpurkalXZZ/PVTbuOtk3WXX6M5P2bJnbOOy+M1mwfjN++qZht1qVsuUG+Yib7gyj5RtfKO1SeznzbXyG/zdaJuoSxmavaszVXbdTf3R5fdhl0uksepaqjnSadbTGOI69yNxv6efI0hpnOexhDXOU/jcNyuc57GENc5pvGm2Brj5jbgxcB71rtBRIrAOwlxww4BXxWRj6vqdzbKeKD6gETkWuA3gGeq6uYWyCQS5woKsl4nYy+LUb0DQGTDfqurgbuy+GCIyEeAFwIbNkCD1gf0DmCSENj+GyLy7n5XKJEYaLTDz9nnYuA+9/uh7NyGDJQFpKoP30y6qha5pxKmvh8YPm/1fEODyXy6YSbu3ct2/cEF26+5Mm9uRWG+fb/iSslMap/u7kkL33BBtkxg1s01Oriyb/X4noptTnZ83lZq1+eC+V+c9yu27d0wN2KrzA8t2h7LB7KlBpMFm+9SdGNUB6rnRdOdms/0mHdRI5b9aI4dnxgfy+puSwtiGkNc5240BtM5T2OI65ynMcR1ztMY4jrnagxRnWMab4Yu+nf2icit7vcbVfXG1XxEPgtc0J6MN6lqWyz4WFUi53JrN1ANUCKR6JLOR7iOq+q6Hch5fbMdcAi41P1+CfBAXqJBc8ESiUQXbMUoWId8FbhSRK4QkSHgJcDH8xLtCAtouV7iwFwwwfcPXbJ6/nS2QdZ83czhO+fNpD5yykY4ZNZM9KHZ9na5il0/Om6jJHdOWH4TxWCir9mruGouwQ9Omzt26pSZ3aXZ8DWU550b5DYkq5bNdblvYmr1+I5spXnBTXX1Lth3Fi+yepy20ZqV2aCHf841e0Kv2PH8SKjngUmre0xjiOvcjcZgOudpDHGd8zSGuM55GkNc5zyNIa5zTOOu2aL+HRF5EfB2YD/wCRH5hqo+X0QuAv5YVa9T1ZqIXA/cQhgkfJ+q3p6X945ogBKJcxFhy0bBbgJuipx/ALjO/X4zcHM3eacGKJHYxqTIqANAtVbi0MkwAjFZto782dFg2p6umXl916yZ6JWTZiaPnDQzedgi0KwiDRfL28V7/8GY5TdUCCucd7lQLQ9WzAU5NGumvZywUbXhk8EcL7vQ442yG1Qo2KjNzJhzTUbDCEx9nXVFTbcU4MRJS1eeCfmNnLB0Bbcg27tji0PBJTo0biM8MY0hrnM3GoPpnKcxxHXO0xjW0TlHY4jrnKcxxHWOadw1aUfERCLRPwZ7nVcn7IgGSGtC5UR4Y949ZJ2+p6rh3OKKm2Y/495SJ+3x3U6ejJxsX+8tLuZ4fcTebifc2/L7xTBfZcztBTOzaG/yxRNmLYw6a2DkePgjGpp3K71dbHgt2HFtzN7q94+Et329Ee/Q9R3AetKsk+HsjdwsF1piwy+5TtpyZpGM2XPENIa4zt1oDKZznsYQ1zlPY4jrnKcxxHXO07i17NXY8BGNN8N2Xw2/IxqgROKcJVlAiUSiL2zRWrCzyY5ogKQulGeDyX5qxKbfN1dW11bcauST8Y7J0RPmd83JtgAACP1JREFUEowcb99fSFxAw9qYmcy1cRcPvBTM8XLZtuBcXrR0JeeODFvsO8ZOhPvLpy1dfdhtblW0dLXx9s7ww+t0QldnzSXwHcAjJ8If7ehx69AtLtvzl/xq8eFwXJu0czGNIa5zNxqD6ZynMcR1ztMY4jrnaQxxnfM0hrjOMY03xfZuf3ZGA5RInKukYfhEItE/UgPUf6QOQ7PZKuMRcwkqzQh0LgrC8Kyfi2Jf3shJM5OHToTp/uu9XaoT5hKsTFp+y1mkh/qQuRqyYBIPnXIjIzN2z/CJLErFKdtgS4fd5l1D5gZUd1l+KxPBdK+KuQF+TXLplCvbxRYZnaln5dqyhkLFXKKC2yBrZSyLIz/lRwEjGkNU5zyNIa5znsYQ1zlPY4jrnKcxxHXO0ziU3a5zTOOuUdbfoHubsCMaoETiXERQpLG9W6DUACUS25nkgvUfqUM5CyW+MuEmlGl4vELVTcOfs+OhOXt7lGdtWn9xZq6tjKGymeLDp0225Tk3mpFNnvObiZUWfXmW3/ApM9FLM8ElKJyyNQLeBRsec2b+bucS7Mom0ZXioyhrnvW0m4h3KrhCxRlbTS4VW4tRdkO7w7tCPSqn3Z7REY0hrnM3GoPpnKcxxHXO0xjiOudpDHGd8zSGuM4xjbsmuWCJRKKfpFGwRCLRP1ID1DtE5D8QdtJvAEeBV2Z7jmycrgHlxfBFlBb8Gqrws+hcg5KLtVFecBtMzdlIhc5lJroLM1MYHnLpbNSitFh0x9lInFn+a+pTWlB3bDcV5kOl9NRpSzhqZRTnbX1TedFGYkrZeqL6sBuJcodF8zpW9QEozQU3QObMNdBFu1ncuqjywliW3v5UYhpDXOdcjSGqc57GENc5T2OI65ynMcR1ztMY4jrHNO6e7b8YddC2ZP09VX2cqj4B+Gvgzf2uUCIxsCghJnUnnwFloCwgVXWvJsbpdKK5QnE53Orfwo1sz5W1e924lckVe0P6TtjGwmKzPu7eCXfs3uouP+uEXWefnarPzzopdSlYBo2l+NyYwpLNYfFLJopZkDv/zJ6i9flScuma+Xmrp7FoFkJh2EWvWMo6rL1uEY0hrnOexhDXOV9jiOmcpzHEdc7TOOTdrnOexhDXOabxZkh9QD1GRP4j8HLgFPCsPlcnkRhstnkDNHCx4VX1Tap6KSEu/PUb5PMaEblVRG6tVRbWuy2R2Lkoof+sk8+AMnCx4R0fBj4B3LBOPjcCNwJM7LlUC5mlL65jUjLL1gUzWHO9UHNfzIqZwY1qZKV2zXVo1p2p7aznZh00cq71Xqm5SmXl6YrruCy6d4Mve8XqLFn9pRZ3wfzzibfys/y0auVpzd3g67HSaHuOmMYQ17krjV3d8jQOdW4/n6cxrKNzjsbhuF3nPI1hHZ0jGndP6oTuKSJypfv1J4Hv9qsuicS2QLWzzxkgIj8jIreLSENE1g1uKCIHReTbWVj1W9e7zzNofUBvFZEfIgzD3wO8ts/1SSQGFwXqWzIV+jbgxcB7Orj3WaouXncOA9UAqepPbSbdwsyh41/+6L+5p9f1WcOhdY4D+4CORe8IN7+EO9c5PlvMRI6/fhaeMcahlp9nm6bOQdfwjP3SOHBZ55ko6NlvgFT1DgCRuKt/JgxUA7RZVHV//l1nDxG5daO42zuB9IwDymD1ASnwaRFR4D1ZP+2G7IgGKJE4J2mOgnXGvpZ+mRt9AyEinwUuaE/Gm1T1Yx2W8XRVfUBEzgM+IyLfVdUvbJQgNUCJxHamcwvo+EbWXRej0xtUJSybUtWjInITcDWwYQM0UKNg25hcU3MHkJ5x4FBoNDr7nGVEZFxEJpvHwPMIndcbkhqgHtCJr7vdSc84gChb0gCJyItE5BDwVOATInJLdv4iEbk5u+184Isi8k3gH4FPqOqn8vJOLlgisZ3Zgk5oVb0JuCly/gHguuz4APD4bvNOFlCPEJHfE5Hvisi3ROQmEZnud516hYhcKyJ3ishdIvLGften14jIpSLyORG5I5tw92v9rlPHbMFExLNJaoB6x2eAq1T1ccD3gN/sc316gogUgXcCPw48GnipiDy6v7XqOTXgDar6KOApwOu2xzN2uA5sgNeCpQaoR6jqp1VXVyd9Gbikn/XpIVcDd6nqAVWtAh8hbBq3Y1DVw6r69ex4DrgDuLi/teoABdVGR59BJfUBnR1eDXy035XoERcD97nfDwE/0qe6nHVE5HLgicBX+luTDtmapRhnjdQAdUEnk7VE5E0Ek/5DW1m3s0hs/v3g2vRngIhMAH8BvL5lc7zBRHVLhtjPJqkB6oK8yVoi8grgBcCzVQe45687DgGXut8vAXL36d5uiEiZ0Ph8SFX/st/16Zht/meWGqAeISLXAr8BPFNVF/Pu30Z8FbhSRK4A7gdeArysv1XqLRJWWb4XuENV39bv+nSDbnMLKHVC9453AJOENTDfEJF397tCvSDrWL8euIXQOftnqnp7f2vVc54O/DzwY9l39w0Rua7flcqnwyH4AbaSkgXUI1T14f2uw9lCVW8Gbs69cZuiql8k3tc12ChrYxNtQ1IDlEhsUxTQAZ7j0wmpAUoktiu6NRuSnU1SA5RIbGO2uwUkO2e0OJE4txCRTxG2ke2E46p67dmsz2ZIDVAikegbaRg+kUj0jdQAJRKJvpEaoEQi0TdSA5RYFxF5poioiPy4O3eFiBwVkT/qZ90SO4PUCZ3YEBH5X8CIqj5NRKaAvwfuBl6oqtt7Gm6i76QGKLEhIvLPCaFVng+8gbD5+DNUdb6vFUvsCFIDlMhFRD4DPA2YBX5EVbcqcHJih5P6gBKdcBcwBtyQGp9EL0kWUGJDROQ1wNsJW3FUVPUpfa5SYgeRGqDEuojIc4FPAL9IiPTxD8B1qvrJvlYssWNIDVAiiog8BvgS8A5V/e3s3GeAKVW9uq+VS+wYUgOUaENEziNEhbgV+Nnm/tYi8qPA3wIvUNVP9LGKiR1CaoASiUTfSKNgiUSib6QGKJFI9I3UACUSib6RGqBEItE3UgOUSCT6RmqAEolE30gNUCKR6BupAUokEn0jNUCJRKJv/G9mINGorHlQAAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "figures,ax = subplots(figsize=(4,4) )\n", + "bounds=(freq2.max(),freq2.min(),freq2.max(),freq2.min())\n", + "stretch = ( -np.pi, np.pi, -np.pi, +np.pi )\n", + "wavek = ( -N/(2*np.pi), N/(2*np.pi), -N/(2*np.pi), +N/(2*np.pi) )\n", + "im=ax.imshow(c2.real, extent=stretch)\n", + "\n", + "ax.set_title('Signal 2D débruité \\n par $FFTW$',family='serif',size=20)\n", + "ax.set_xlabel('$x$',size=15)\n", + "ax.set_ylabel('$y$',size=15)\n", + "\n", + "colorbar(im,ax=ax)\n", + "\n", + "savefig('signal_2D_debruite.pdf')\n", + "show() " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__Résolution de l'équation de Poisson__\n", + "\n", + "L'équation de Poisson prend la forme générale :\n", + "\n", + "$$\n", + "\\Delta \\phi = f(x,y)\n", + "$$\n", + "\n", + "où $f(x,y)$ est une fonction à préciser et $\\Delta$ est le laplacien. Cette équation prend donc à 2 dimensions la forme suivante :\n", + "$$\\bigg(\\frac{\\partial^2}{\\partial x^2}+\\frac{\\partial^2}{\\partial y^2}\\bigg)\\phi = f(x,y)$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pour résoudre cette équation, nous allons dans un premier temps décomposer $\\phi$ en série de Fourier :\n", + "$$\\phi(x,y)=\\sum_{i =1}^{\\infty} \\sum_{j =1}^{\\infty} \\phi_{ij}\\sin(i\\pi x)\\sin(j\\pi y)$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Supposons à présent que nous souhaitons résoudre l'équation de Poisson sur un réseau 2D de $N_x\\times N_y$ points. Dans cette hypothèse, l'équation différentielle prend la forme :\n", + "$$\\phi_{i,j}=\\bigg(\\frac{\\phi_{i+1,j}+\\phi_{i-1,j}}{\\Delta x²}+\\frac{\\phi_{i,j+1}+\\phi_{i,j-1}}{\\Delta y²}-f_{i,j}\\bigg)\\times \\frac{1}{2}\\bigg(\\frac{1}{\\Delta x^2}+\\frac{1}{\\Delta y^2}\\bigg)^{-1}$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "En effet, en réécrivant les différentielles de l'équation de Poisson comme des différences finies, nous arrivons effectivement à cette expression pour $\\phi_{i,j}$." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Dans cette formule, $\\Delta x^2$ et $\\Delta y^2$ représentent le pas du réseau respectivement selon $x$ et $y$." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "https://hmf.enseeiht.fr/travaux/projnum/book/export/html/2329" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__Nouvelle méthode plus simple__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "D'une part nous avons besoin de connaître la tranformée de Fourier de la \n", + "différentielle d'une fonction (en ayant bien sûr supposé que celle-ci existe).\n", + "Cette transformée s'exprime comme :\n", + "\n", + "$$\\mathcal{F}\\bigg(\\frac{\\partial u}{\\partial x_k}\\bigg)=i \\xi_k \\hat{u}(\\xi) $$\n", + "\n", + "En supposant que cette relation peut être appliquée 2 fois, nous arrivons à :\n", + "\n", + "$$\\mathcal{F}\\bigg(\\frac{\\partial^2 u}{\\partial x_k^2}\\bigg)= |\\xi_k|^2 \\hat{u}(\\xi) $$\n", + "\n", + "Et ainsi l'équation de Poisson $\\Delta u =f$ prend la forme très simple dans l'espace de Fourier :\n", + "\n", + "$$\\hat{u}(\\xi)=\\frac{1}{|\\xi|²}\\hat{f}(\\xi)$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Définissons la fonction $f$ pour laquelle on souhaite résoudre l'équation de Poisson. Nous prendrons dans un premier \n", + "temps $f(x,y)=1$ car nous connaissons la solution de l'équation de Poisson pour cette fonction." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "def f(x,y):\n", + " return cos(2*x)+sin(y) + 1j*0\n", + "\n", + "def solu(x,y):\n", + " return y*(1-y)*x*x*x" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "N = 64\n", + "TYPE = \"complex128\"\n", + "x,y = linspace( 0, 1, N, dtype=TYPE), linspace( 0, 1,N, dtype=TYPE)\n", + "\n", + "X,Y = meshgrid( x, y )\n", + "\n", + "delx=abs((x.real.max()-x.real.min())/N)\n", + "dely=abs((y.real.max()-y.real.min())/N)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "ap = pyfftw.empty_aligned( (N,N) , dtype=TYPE)\n", + "\n", + "bp = pyfftw.empty_aligned( (N,N) , dtype=TYPE)\n", + "\n", + "bbp = pyfftw.empty_aligned( (N,N) , dtype=TYPE)\n", + "\n", + "cp = pyfftw.empty_aligned( (N,N) , dtype=TYPE)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "fft_object_2dp = pyfftw.FFTW(ap, bp, axes=(0,1))\n", + "\n", + "ifft_object_2dp = pyfftw.FFTW(bbp, cp, axes=(0,1), direction=\"FFTW_BACKWARD\")" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "sol=zeros((N,N))\n", + "\n", + "for k in range(N):\n", + " for l in range(N):\n", + " ap[k][l]=f(X[k][l].real,Y[k][l].real)\n", + " sol[k][l]=solu(X[k][l].real,Y[k][l].real)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "bp=fft_object_2dp()" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "np=ap.size\n", + "freqp=fft.fftfreq(np,(x.max()-x.min())/N)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0. +0.j, 0.015625+0.j, 0.03125 +0.j, ..., -0.046875+0.j,\n", + " -0.03125 +0.j, -0.015625+0.j])" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "freqp" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "for k in range(N):\n", + " for l in range(N):\n", + " if ((k==0 and l==0)):\n", + " bbp[k][l]=bp[k][l]\n", + " else :\n", + " bbp[k][l]=bp[k][l]/(k**2+l**2)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "cp=ifft_object_2dp()" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "figures,ax = subplots( 1,3)\n", + "bounds=(freqp.max(),freqp.min(),freqp.max(),freqp.min())\n", + "stretch = (0, 1, 0, 1 )\n", + "ax[0].imshow( ap.real, extent=stretch ), \\\n", + "ax[1].imshow( sol,extent=(0,1,0,1)), \\\n", + "ax[2].imshow(cp.real, extent=stretch)\n", + "\n", + "pos2=ax[2].imshow(cp.real, extent=stretch)\n", + "\n", + "cax = axes([1, 0, 0.1,1])\n", + "colorbar(pos2,cax=cax)\n", + "\n", + "show() " + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from mpl_toolkits import mplot3d\n", + "fig = figure(figsize=(8,6))\n", + "ax3d = axes(projection=\"3d\")\n", + "\n", + "\n", + "ax3d.plot_surface(X.real , Y.real , cp.real,color='blue')\n", + "ax3d.plot_surface(X.real , Y.real , sol.real,color='red')\n", + "\n", + "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": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module2/exo1/Untitled.ipynb b/module2/exo1/Untitled.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..31a59cba404841485984c1555dbb8fbfc359a7bf --- /dev/null +++ b/module2/exo1/Untitled.ipynb @@ -0,0 +1,216 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from numpy import *\n", + "\n", + "from IPython.display import display, Markdown, Math\n", + "from matplotlib.pyplot import *\n", + "import matplotlib.pyplot as plt\n" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Paramètres de la gaussienne\n", + "A = 1.0 # Amplitude\n", + " # Moyenne, le maximum est à x = 0\n", + "sigma = 20*10**(-6) # Écart-type, contrôle la largeur de la cloche\n", + "i=complex(0,1)\n", + "\n", + "# Créer un ensemble de valeurs x\n", + "x = linspace(-0.015, 0.015, 10001) # Vous pouvez ajuster la plage en fonction de vos besoins\n", + "z = linspace(0,0.001,1000)\n", + "\n", + "k=2*pi/(600*10**(-9))\n", + "nx=len(x)\n", + "nz=len(z)\n", + "dx=0.03/nx\n", + "dz=1/nz\n", + "# Calculer les valeurs de la gaussienne pour chaque x\n", + "E0 = A * exp(-(x )**2 / (2 * sigma**2))\n", + "\n", + "# Tracer la gaussienne\n", + "plt.plot(x, E0)\n", + "plt.title('Gaussienne avec un maximum à x=0')\n", + "plt.xlim(-0.001,0.001)\n", + "plt.xlabel('x')\n", + "plt.ylabel('E(x,z=0)')\n", + "plt.grid(True)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 139, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "10471975.511965975" + ] + }, + "execution_count": 139, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nu" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [], + "source": [ + "fourier_transform = np.fft.fftshift(np.fft.fft(E0))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "metadata": {}, + "outputs": [], + "source": [ + "nux=np.fft.fftshift(np.fft.fftfreq(nx,dx))\n", + "kx=2*pi*nux" + ] + }, + { + "cell_type": "code", + "execution_count": 142, + "metadata": {}, + "outputs": [], + "source": [ + "kz=np.sqrt(k**2-kx**2)" + ] + }, + { + "cell_type": "code", + "execution_count": 143, + "metadata": {}, + "outputs": [], + "source": [ + "Ez=fourier_transform*exp(i*kz*0.001)" + ] + }, + { + "cell_type": "code", + "execution_count": 144, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 5.04403150e-14-3.00439272e-14j, -5.02186263e-14+3.00862303e-14j,\n", + " 4.97677360e-14-3.01329564e-14j, ...,\n", + " -4.98190361e-14+3.00564478e-14j, 5.02454587e-14-3.00361688e-14j,\n", + " -5.04469045e-14+3.00266971e-14j])" + ] + }, + "execution_count": 144, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "inverse_transform = np.fft.ifft(Ez)\n", + "inverse_transform" + ] + }, + { + "cell_type": "code", + "execution_count": 145, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x,inverse_transform)\n", + "plt.plot(x, E0)\n", + "plt.title('Gaussienne avec un maximum à x=0')\n", + "plt.xlim(-0.001,0.001)\n", + "plt.xlabel('x')\n", + "plt.ylabel('E(x,z=zmax)')\n", + "plt.grid(True)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "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": "3.6.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module2/exo1/module2-exo2.ipynb b/module2/exo1/module2-exo2.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..75aef0d24393bb28289e7dca96d9c9c191dc90cb --- /dev/null +++ b/module2/exo1/module2-exo2.ipynb @@ -0,0 +1,174 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "# Données fournies\n", + "donnees = [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,\n", + " 12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2,\n", + " 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0,\n", + " 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6,\n", + " 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0,\n", + " 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4,\n", + " 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "14.113000000000001" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calcul de la moyenne\n", + "moyenne = np.mean(donnees)\n", + "moyenne" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.334094455301447" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calcul de l'écart-type (4.42/4.31)\n", + "ecart_type = np.std(donnees, ddof=1)\n", + "ecart_type" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2.8" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calcul du minimum\n", + "minimum = np.min(donnees)\n", + "minimum" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "14.5" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calcul de la médiane\n", + "median = np.median(donnees)\n", + "median" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "23.4" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calcul du maximum\n", + "maximum = np.max(donnees)\n", + "maximum " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(14.113000000000001, 4.334094455301447, 2.8, 14.5, 23.4)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Affichage des résultats\n", + "moyenne, ecart_type, minimum, median, maximum" + ] + } + ], + "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": "3.6.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module2/exo1/toy_notebook_fr.ipynb b/module2/exo1/module2_exo1.ipynb similarity index 95% rename from module2/exo1/toy_notebook_fr.ipynb rename to module2/exo1/module2_exo1.ipynb index 7592f4df88c557733c056fc04ab30965ff3e5b17..89cfcb7b0746fd8cf21a904de49711f60cfc717b 100644 --- a/module2/exo1/toy_notebook_fr.ipynb +++ b/module2/exo1/module2_exo1.ipynb @@ -73,7 +73,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -116,7 +116,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -125,7 +125,7 @@ "3.122" ] }, - "execution_count": 17, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -134,6 +134,131 @@ "4*np.mean(accept)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 1.4 Écrire le lien \"aiguilles de Buffon\" vers wikipedia" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "## [Aiguilles de Buffon](https://fr.wikipedia.org/wiki/Aiguilles_de_Buffon) c'est la syntaxe pour avoir le resultats suivant :" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Aiguilles de Buffon](https://fr.wikipedia.org/wiki/Aiguilles_de_Buffon)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 1.5 Écrire le code de la méthode de Buffon pour Python et pour R" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2.9873039581777445\n" + ] + } + ], + "source": [ + "import random\n", + "\n", + "def buffon_needle(num_needles):\n", + " count_crossed = 0\n", + " for _ in range(num_needles):\n", + " # Générez une longueur aléatoire de l'aiguille\n", + " needle_length = random.uniform(0, 1)\n", + " # Générez une position aléatoire pour le centre de l'aiguille\n", + " needle_center = random.uniform(0, 1 / (2 * needle_length))\n", + " # Vérifiez si l'aiguille croise une ligne\n", + " if needle_center < needle_length / 2 or needle_center > 1 - (needle_length / 2):\n", + " count_crossed += 1\n", + "\n", + " # Estimez pi en utilisant la formule de Buffon\n", + " pi_estimate = (2 * num_needles) / count_crossed if count_crossed > 0 else 0\n", + " return pi_estimate\n", + "\n", + "# Nombre d'aiguilles à lancer\n", + "num_needles = 100000\n", + "pi_estimate = buffon_needle(num_needles)\n", + "print(pi_estimate)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 1.5 ECRIRE DANS LE LANGUAGE R" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "%reload_ext rpy2.ipython" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[1] 3.003138\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%%R\n", + "\n", + "buffon_needle <- function(num_needles) {\n", + " count_crossed <- 0\n", + " for (i in 1:num_needles) {\n", + " # Générez une longueur aléatoire de l'aiguille\n", + " needle_length <- runif(1, 0, 1)\n", + " # Générez une position aléatoire pour le centre de l'aiguille\n", + " needle_center <- runif(1, 0, 1 / (2 * needle_length))\n", + " # Vérifiez si l'aiguille croise une ligne\n", + " if (needle_center < needle_length / 2 || needle_center > 1 - (needle_length / 2)) {\n", + " count_crossed <- count_crossed + 1\n", + " }\n", + " }\n", + "\n", + " # Estimez pi en utilisant la formule de Buffon\n", + " pi_estimate <- (2 * num_needles) / count_crossed\n", + " return(pi_estimate)\n", + "}\n", + "\n", + "# Nombre d'aiguilles à lancer\n", + "num_needles <- 100000\n", + "pi_estimate <- buffon_needle(num_needles)\n", + "pi_estimate" + ] + }, { "cell_type": "code", "execution_count": null, diff --git a/module2/exo1/module2_exo3.ipynb b/module2/exo1/module2_exo3.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..7fec51502cbc3200b3d0ffc6bbba1fe85e197f3d --- /dev/null +++ b/module2/exo1/module2_exo3.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module2/exo1/module3-exo1.ipynb b/module2/exo1/module3-exo1.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..e30a601b59a892c1ad2bf3e46785c0b0a1f1369e --- /dev/null +++ b/module2/exo1/module3-exo1.ipynb @@ -0,0 +1,3400 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import isoweek" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "data_file = \"syndrome-grippal.csv\"\n", + "\n", + "import os\n", + "import urllib.request\n", + "if not os.path.exists(data_file):\n", + " urllib.request.urlretrieve(data_url, data_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + 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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020233938211270891.093333.0124107.0141.0FRFrance
120233836356755525.071609.09684.0108.0FRFrance
220233734908542079.056091.07463.085.0FRFrance
320233633824732237.044257.05849.067.0FRFrance
420233533169526013.037377.04839.057.0FRFrance
520233432666321057.032269.04032.048.0FRFrance
620233331914413161.025127.02920.038.0FRFrance
720233231464110285.018997.02215.029.0FRFrance
820233131528610705.019867.02316.030.0FRFrance
92023303132058647.017763.02013.027.0FRFrance
102023293111227113.015131.01711.023.0FRFrance
11202328391795703.012655.0149.019.0FRFrance
12202327389995763.012235.0149.019.0FRFrance
13202326390235934.012112.0149.019.0FRFrance
142023253100906739.013441.01510.020.0FRFrance
152023243113087639.014977.01711.023.0FRFrance
1620232331430010661.017939.02217.027.0FRFrance
1720232231830313822.022784.02821.035.0FRFrance
1820232131646012188.020732.02519.031.0FRFrance
1920232031616211963.020361.02418.030.0FRFrance
2020231931690112577.021225.02518.032.0FRFrance
2120231831992915402.024456.03023.037.0FRFrance
2220231732700721779.032235.04133.049.0FRFrance
2320231632787522767.032983.04234.050.0FRFrance
2420231533745530993.043917.05646.066.0FRFrance
2520231434806040671.055449.07261.083.0FRFrance
2620231336485956800.072918.09886.0110.0FRFrance
2720231237275064499.081001.010997.0121.0FRFrance
2820231137463866420.082856.0112100.0124.0FRFrance
2920231037636868243.084493.0115103.0127.0FRFrance
.................................
200119852132609619621.032571.04735.059.0FRFrance
200219852032789620885.034907.05138.064.0FRFrance
200319851934315432821.053487.07859.097.0FRFrance
200419851834055529935.051175.07455.093.0FRFrance
200519851733405324366.043740.06244.080.0FRFrance
200619851635036236451.064273.09166.0116.0FRFrance
200719851536388145538.082224.011683.0149.0FRFrance
20081985143134545114400.0154690.0244207.0281.0FRFrance
20091985133197206176080.0218332.0357319.0395.0FRFrance
20101985123245240223304.0267176.0445405.0485.0FRFrance
20111985113276205252399.0300011.0501458.0544.0FRFrance
20121985103353231326279.0380183.0640591.0689.0FRFrance
20131985093369895341109.0398681.0670618.0722.0FRFrance
20141985083389886359529.0420243.0707652.0762.0FRFrance
20151985073471852432599.0511105.0855784.0926.0FRFrance
20161985063565825518011.0613639.01026939.01113.0FRFrance
20171985053637302592795.0681809.011551074.01236.0FRFrance
20181985043424937390794.0459080.0770708.0832.0FRFrance
20191985033213901174689.0253113.0388317.0459.0FRFrance
202019850239758680949.0114223.0177147.0207.0FRFrance
202119850138548965918.0105060.0155120.0190.0FRFrance
202219845238483060602.0109058.0154110.0198.0FRFrance
2023198451310172680242.0123210.0185146.0224.0FRFrance
20241984503123680101401.0145959.0225184.0266.0FRFrance
2025198449310107381684.0120462.0184149.0219.0FRFrance
202619844837862060634.096606.0143110.0176.0FRFrance
202719844737202954274.089784.013199.0163.0FRFrance
202819844638733067686.0106974.0159123.0195.0FRFrance
20291984453135223101414.0169032.0246184.0308.0FRFrance
203019844436842220056.0116788.012537.0213.0FRFrance
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2031 rows × 10 columns

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20732.0 25 19.0 \n", + "19 202320 3 16162 11963.0 20361.0 24 18.0 \n", + "20 202319 3 16901 12577.0 21225.0 25 18.0 \n", + "21 202318 3 19929 15402.0 24456.0 30 23.0 \n", + "22 202317 3 27007 21779.0 32235.0 41 33.0 \n", + "23 202316 3 27875 22767.0 32983.0 42 34.0 \n", + "24 202315 3 37455 30993.0 43917.0 56 46.0 \n", + "25 202314 3 48060 40671.0 55449.0 72 61.0 \n", + "26 202313 3 64859 56800.0 72918.0 98 86.0 \n", + "27 202312 3 72750 64499.0 81001.0 109 97.0 \n", + "28 202311 3 74638 66420.0 82856.0 112 100.0 \n", + "29 202310 3 76368 68243.0 84493.0 115 103.0 \n", + "... ... ... ... ... ... ... ... \n", + "2001 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "2002 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "2003 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "2004 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "2005 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "2006 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "2007 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "2008 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "2009 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "2010 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "2011 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "2012 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "2013 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "2014 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "2015 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "2016 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "2017 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "2018 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "2019 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "2020 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "2021 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "2022 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "2023 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "2024 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "2025 198449 3 101073 81684.0 120462.0 184 149.0 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110.0 FR France \n", + "27 121.0 FR France \n", + "28 124.0 FR France \n", + "29 127.0 FR France \n", + "... ... ... ... \n", + "2001 59.0 FR France \n", + "2002 64.0 FR France \n", + "2003 97.0 FR France \n", + "2004 93.0 FR France \n", + "2005 80.0 FR France \n", + "2006 116.0 FR France \n", + "2007 149.0 FR France \n", + "2008 281.0 FR France \n", + "2009 395.0 FR France \n", + "2010 485.0 FR France \n", + "2011 544.0 FR France \n", + "2012 689.0 FR France \n", + "2013 722.0 FR France \n", + "2014 762.0 FR France \n", + "2015 926.0 FR France \n", + "2016 1113.0 FR France \n", + "2017 1236.0 FR France \n", + "2018 832.0 FR France \n", + "2019 459.0 FR France \n", + "2020 207.0 FR France \n", + "2021 190.0 FR France \n", + "2022 198.0 FR France \n", + "2023 224.0 FR France \n", + "2024 266.0 FR France \n", + "2025 219.0 FR France \n", + "2026 176.0 FR France \n", + "2027 163.0 FR France \n", + "2028 195.0 FR France \n", + "2029 308.0 FR France \n", + "2030 213.0 FR France \n", + "\n", 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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020233938211270891.093333.0124107.0141.0FRFrance
120233836356755525.071609.09684.0108.0FRFrance
220233734908542079.056091.07463.085.0FRFrance
320233633824732237.044257.05849.067.0FRFrance
420233533169526013.037377.04839.057.0FRFrance
520233432666321057.032269.04032.048.0FRFrance
620233331914413161.025127.02920.038.0FRFrance
720233231464110285.018997.02215.029.0FRFrance
820233131528610705.019867.02316.030.0FRFrance
92023303132058647.017763.02013.027.0FRFrance
102023293111227113.015131.01711.023.0FRFrance
11202328391795703.012655.0149.019.0FRFrance
12202327389995763.012235.0149.019.0FRFrance
13202326390235934.012112.0149.019.0FRFrance
142023253100906739.013441.01510.020.0FRFrance
152023243113087639.014977.01711.023.0FRFrance
1620232331430010661.017939.02217.027.0FRFrance
1720232231830313822.022784.02821.035.0FRFrance
1820232131646012188.020732.02519.031.0FRFrance
1920232031616211963.020361.02418.030.0FRFrance
2020231931690112577.021225.02518.032.0FRFrance
2120231831992915402.024456.03023.037.0FRFrance
2220231732700721779.032235.04133.049.0FRFrance
2320231632787522767.032983.04234.050.0FRFrance
2420231533745530993.043917.05646.066.0FRFrance
2520231434806040671.055449.07261.083.0FRFrance
2620231336485956800.072918.09886.0110.0FRFrance
2720231237275064499.081001.010997.0121.0FRFrance
2820231137463866420.082856.0112100.0124.0FRFrance
2920231037636868243.084493.0115103.0127.0FRFrance
.................................
200119852132609619621.032571.04735.059.0FRFrance
200219852032789620885.034907.05138.064.0FRFrance
200319851934315432821.053487.07859.097.0FRFrance
200419851834055529935.051175.07455.093.0FRFrance
200519851733405324366.043740.06244.080.0FRFrance
200619851635036236451.064273.09166.0116.0FRFrance
200719851536388145538.082224.011683.0149.0FRFrance
20081985143134545114400.0154690.0244207.0281.0FRFrance
20091985133197206176080.0218332.0357319.0395.0FRFrance
20101985123245240223304.0267176.0445405.0485.0FRFrance
20111985113276205252399.0300011.0501458.0544.0FRFrance
20121985103353231326279.0380183.0640591.0689.0FRFrance
20131985093369895341109.0398681.0670618.0722.0FRFrance
20141985083389886359529.0420243.0707652.0762.0FRFrance
20151985073471852432599.0511105.0855784.0926.0FRFrance
20161985063565825518011.0613639.01026939.01113.0FRFrance
20171985053637302592795.0681809.011551074.01236.0FRFrance
20181985043424937390794.0459080.0770708.0832.0FRFrance
20191985033213901174689.0253113.0388317.0459.0FRFrance
202019850239758680949.0114223.0177147.0207.0FRFrance
202119850138548965918.0105060.0155120.0190.0FRFrance
202219845238483060602.0109058.0154110.0198.0FRFrance
2023198451310172680242.0123210.0185146.0224.0FRFrance
20241984503123680101401.0145959.0225184.0266.0FRFrance
2025198449310107381684.0120462.0184149.0219.0FRFrance
202619844837862060634.096606.0143110.0176.0FRFrance
202719844737202954274.089784.013199.0163.0FRFrance
202819844638733067686.0106974.0159123.0195.0FRFrance
20291984453135223101414.0169032.0246184.0308.0FRFrance
203019844436842220056.0116788.012537.0213.0FRFrance
\n", + "

2030 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202339 3 82112 70891.0 93333.0 124 107.0 \n", + "1 202338 3 63567 55525.0 71609.0 96 84.0 \n", + "2 202337 3 49085 42079.0 56091.0 74 63.0 \n", + "3 202336 3 38247 32237.0 44257.0 58 49.0 \n", + "4 202335 3 31695 26013.0 37377.0 48 39.0 \n", + "5 202334 3 26663 21057.0 32269.0 40 32.0 \n", + "6 202333 3 19144 13161.0 25127.0 29 20.0 \n", + "7 202332 3 14641 10285.0 18997.0 22 15.0 \n", + "8 202331 3 15286 10705.0 19867.0 23 16.0 \n", + "9 202330 3 13205 8647.0 17763.0 20 13.0 \n", + "10 202329 3 11122 7113.0 15131.0 17 11.0 \n", + "11 202328 3 9179 5703.0 12655.0 14 9.0 \n", + "12 202327 3 8999 5763.0 12235.0 14 9.0 \n", + "13 202326 3 9023 5934.0 12112.0 14 9.0 \n", + "14 202325 3 10090 6739.0 13441.0 15 10.0 \n", + "15 202324 3 11308 7639.0 14977.0 17 11.0 \n", + "16 202323 3 14300 10661.0 17939.0 22 17.0 \n", + "17 202322 3 18303 13822.0 22784.0 28 21.0 \n", + "18 202321 3 16460 12188.0 20732.0 25 19.0 \n", + "19 202320 3 16162 11963.0 20361.0 24 18.0 \n", + "20 202319 3 16901 12577.0 21225.0 25 18.0 \n", + "21 202318 3 19929 15402.0 24456.0 30 23.0 \n", + "22 202317 3 27007 21779.0 32235.0 41 33.0 \n", + "23 202316 3 27875 22767.0 32983.0 42 34.0 \n", + "24 202315 3 37455 30993.0 43917.0 56 46.0 \n", + "25 202314 3 48060 40671.0 55449.0 72 61.0 \n", + "26 202313 3 64859 56800.0 72918.0 98 86.0 \n", + "27 202312 3 72750 64499.0 81001.0 109 97.0 \n", + "28 202311 3 74638 66420.0 82856.0 112 100.0 \n", + "29 202310 3 76368 68243.0 84493.0 115 103.0 \n", + "... ... ... ... ... ... ... ... \n", + "2001 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "2002 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "2003 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "2004 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "2005 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "2006 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "2007 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "2008 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "2009 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "2010 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "2011 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "2012 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "2013 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "2014 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "2015 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "2016 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "2017 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "2018 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "2019 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "2020 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "2021 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "2022 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "2023 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "2024 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "2025 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "2026 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "2027 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "2028 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "2029 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "2030 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 141.0 FR France \n", + "1 108.0 FR France \n", + "2 85.0 FR France \n", + "3 67.0 FR France \n", + "4 57.0 FR France \n", + "5 48.0 FR France \n", + "6 38.0 FR France \n", + "7 29.0 FR France \n", + "8 30.0 FR France \n", + "9 27.0 FR France \n", + "10 23.0 FR France \n", + "11 19.0 FR France \n", + "12 19.0 FR France \n", + "13 19.0 FR France \n", + "14 20.0 FR France \n", + "15 23.0 FR France \n", + "16 27.0 FR France \n", + "17 35.0 FR France \n", + "18 31.0 FR France \n", + "19 30.0 FR France \n", + "20 32.0 FR France \n", + "21 37.0 FR France \n", + "22 49.0 FR France \n", + "23 50.0 FR France \n", + "24 66.0 FR France \n", + "25 83.0 FR France \n", + "26 110.0 FR France \n", + "27 121.0 FR France \n", + "28 124.0 FR France \n", + "29 127.0 FR France \n", + "... ... ... ... \n", + "2001 59.0 FR France \n", + "2002 64.0 FR France \n", + "2003 97.0 FR France \n", + "2004 93.0 FR France \n", + "2005 80.0 FR France \n", + "2006 116.0 FR France \n", + "2007 149.0 FR France \n", + "2008 281.0 FR France \n", + "2009 395.0 FR France \n", + "2010 485.0 FR France \n", + "2011 544.0 FR France \n", + "2012 689.0 FR France \n", + "2013 722.0 FR France \n", + "2014 762.0 FR France \n", + "2015 926.0 FR France \n", + "2016 1113.0 FR France \n", + "2017 1236.0 FR France \n", + "2018 832.0 FR France \n", + "2019 459.0 FR France \n", + "2020 207.0 FR France \n", + "2021 190.0 FR France \n", + "2022 198.0 FR France \n", + "2023 224.0 FR France \n", + "2024 266.0 FR France \n", + "2025 219.0 FR France \n", + "2026 176.0 FR France \n", + "2027 163.0 FR France \n", + "2028 195.0 FR France \n", + "2029 308.0 FR France \n", + "2030 213.0 FR France \n", + "\n", + "[2030 rows x 10 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = raw_data.dropna().copy()\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def convert_week(year_and_week_int):\n", + " year_and_week_str = str(year_and_week_int)\n", + " year = int(year_and_week_str[:4])\n", + " week = int(year_and_week_str[4:])\n", + " w = isoweek.Week(year, week)\n", + " return pd.Period(w.day(0), 'W')\n", + "\n", + "data['period'] = [convert_week(yw) for yw in data['week']]" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
period
1984-10-29/1984-11-0419844436842220056.0116788.012537.0213.0FRFrance
1984-11-05/1984-11-111984453135223101414.0169032.0246184.0308.0FRFrance
1984-11-12/1984-11-1819844638733067686.0106974.0159123.0195.0FRFrance
1984-11-19/1984-11-2519844737202954274.089784.013199.0163.0FRFrance
1984-11-26/1984-12-0219844837862060634.096606.0143110.0176.0FRFrance
1984-12-03/1984-12-09198449310107381684.0120462.0184149.0219.0FRFrance
1984-12-10/1984-12-161984503123680101401.0145959.0225184.0266.0FRFrance
1984-12-17/1984-12-23198451310172680242.0123210.0185146.0224.0FRFrance
1984-12-24/1984-12-3019845238483060602.0109058.0154110.0198.0FRFrance
1984-12-31/1985-01-0619850138548965918.0105060.0155120.0190.0FRFrance
1985-01-07/1985-01-1319850239758680949.0114223.0177147.0207.0FRFrance
1985-01-14/1985-01-201985033213901174689.0253113.0388317.0459.0FRFrance
1985-01-21/1985-01-271985043424937390794.0459080.0770708.0832.0FRFrance
1985-01-28/1985-02-031985053637302592795.0681809.011551074.01236.0FRFrance
1985-02-04/1985-02-101985063565825518011.0613639.01026939.01113.0FRFrance
1985-02-11/1985-02-171985073471852432599.0511105.0855784.0926.0FRFrance
1985-02-18/1985-02-241985083389886359529.0420243.0707652.0762.0FRFrance
1985-02-25/1985-03-031985093369895341109.0398681.0670618.0722.0FRFrance
1985-03-04/1985-03-101985103353231326279.0380183.0640591.0689.0FRFrance
1985-03-11/1985-03-171985113276205252399.0300011.0501458.0544.0FRFrance
1985-03-18/1985-03-241985123245240223304.0267176.0445405.0485.0FRFrance
1985-03-25/1985-03-311985133197206176080.0218332.0357319.0395.0FRFrance
1985-04-01/1985-04-071985143134545114400.0154690.0244207.0281.0FRFrance
1985-04-08/1985-04-1419851536388145538.082224.011683.0149.0FRFrance
1985-04-15/1985-04-2119851635036236451.064273.09166.0116.0FRFrance
1985-04-22/1985-04-2819851733405324366.043740.06244.080.0FRFrance
1985-04-29/1985-05-0519851834055529935.051175.07455.093.0FRFrance
1985-05-06/1985-05-1219851934315432821.053487.07859.097.0FRFrance
1985-05-13/1985-05-1919852032789620885.034907.05138.064.0FRFrance
1985-05-20/1985-05-2619852132609619621.032571.04735.059.0FRFrance
.................................
2023-03-06/2023-03-1220231037636868243.084493.0115103.0127.0FRFrance
2023-03-13/2023-03-1920231137463866420.082856.0112100.0124.0FRFrance
2023-03-20/2023-03-2620231237275064499.081001.010997.0121.0FRFrance
2023-03-27/2023-04-0220231336485956800.072918.09886.0110.0FRFrance
2023-04-03/2023-04-0920231434806040671.055449.07261.083.0FRFrance
2023-04-10/2023-04-1620231533745530993.043917.05646.066.0FRFrance
2023-04-17/2023-04-2320231632787522767.032983.04234.050.0FRFrance
2023-04-24/2023-04-3020231732700721779.032235.04133.049.0FRFrance
2023-05-01/2023-05-0720231831992915402.024456.03023.037.0FRFrance
2023-05-08/2023-05-1420231931690112577.021225.02518.032.0FRFrance
2023-05-15/2023-05-2120232031616211963.020361.02418.030.0FRFrance
2023-05-22/2023-05-2820232131646012188.020732.02519.031.0FRFrance
2023-05-29/2023-06-0420232231830313822.022784.02821.035.0FRFrance
2023-06-05/2023-06-1120232331430010661.017939.02217.027.0FRFrance
2023-06-12/2023-06-182023243113087639.014977.01711.023.0FRFrance
2023-06-19/2023-06-252023253100906739.013441.01510.020.0FRFrance
2023-06-26/2023-07-02202326390235934.012112.0149.019.0FRFrance
2023-07-03/2023-07-09202327389995763.012235.0149.019.0FRFrance
2023-07-10/2023-07-16202328391795703.012655.0149.019.0FRFrance
2023-07-17/2023-07-232023293111227113.015131.01711.023.0FRFrance
2023-07-24/2023-07-302023303132058647.017763.02013.027.0FRFrance
2023-07-31/2023-08-0620233131528610705.019867.02316.030.0FRFrance
2023-08-07/2023-08-1320233231464110285.018997.02215.029.0FRFrance
2023-08-14/2023-08-2020233331914413161.025127.02920.038.0FRFrance
2023-08-21/2023-08-2720233432666321057.032269.04032.048.0FRFrance
2023-08-28/2023-09-0320233533169526013.037377.04839.057.0FRFrance
2023-09-04/2023-09-1020233633824732237.044257.05849.067.0FRFrance
2023-09-11/2023-09-1720233734908542079.056091.07463.085.0FRFrance
2023-09-18/2023-09-2420233836356755525.071609.09684.0108.0FRFrance
2023-09-25/2023-10-0120233938211270891.093333.0124107.0141.0FRFrance
\n", + "

2030 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 \\\n", + "period \n", + "1984-10-29/1984-11-04 198444 3 68422 20056.0 116788.0 125 \n", + "1984-11-05/1984-11-11 198445 3 135223 101414.0 169032.0 246 \n", + "1984-11-12/1984-11-18 198446 3 87330 67686.0 106974.0 159 \n", + "1984-11-19/1984-11-25 198447 3 72029 54274.0 89784.0 131 \n", + "1984-11-26/1984-12-02 198448 3 78620 60634.0 96606.0 143 \n", + "1984-12-03/1984-12-09 198449 3 101073 81684.0 120462.0 184 \n", + "1984-12-10/1984-12-16 198450 3 123680 101401.0 145959.0 225 \n", + "1984-12-17/1984-12-23 198451 3 101726 80242.0 123210.0 185 \n", + "1984-12-24/1984-12-30 198452 3 84830 60602.0 109058.0 154 \n", + "1984-12-31/1985-01-06 198501 3 85489 65918.0 105060.0 155 \n", + "1985-01-07/1985-01-13 198502 3 97586 80949.0 114223.0 177 \n", + "1985-01-14/1985-01-20 198503 3 213901 174689.0 253113.0 388 \n", + "1985-01-21/1985-01-27 198504 3 424937 390794.0 459080.0 770 \n", + "1985-01-28/1985-02-03 198505 3 637302 592795.0 681809.0 1155 \n", + "1985-02-04/1985-02-10 198506 3 565825 518011.0 613639.0 1026 \n", + "1985-02-11/1985-02-17 198507 3 471852 432599.0 511105.0 855 \n", + "1985-02-18/1985-02-24 198508 3 389886 359529.0 420243.0 707 \n", + "1985-02-25/1985-03-03 198509 3 369895 341109.0 398681.0 670 \n", + "1985-03-04/1985-03-10 198510 3 353231 326279.0 380183.0 640 \n", + "1985-03-11/1985-03-17 198511 3 276205 252399.0 300011.0 501 \n", + "1985-03-18/1985-03-24 198512 3 245240 223304.0 267176.0 445 \n", + "1985-03-25/1985-03-31 198513 3 197206 176080.0 218332.0 357 \n", + "1985-04-01/1985-04-07 198514 3 134545 114400.0 154690.0 244 \n", + "1985-04-08/1985-04-14 198515 3 63881 45538.0 82224.0 116 \n", + "1985-04-15/1985-04-21 198516 3 50362 36451.0 64273.0 91 \n", + "1985-04-22/1985-04-28 198517 3 34053 24366.0 43740.0 62 \n", + "1985-04-29/1985-05-05 198518 3 40555 29935.0 51175.0 74 \n", + "1985-05-06/1985-05-12 198519 3 43154 32821.0 53487.0 78 \n", + "1985-05-13/1985-05-19 198520 3 27896 20885.0 34907.0 51 \n", + "1985-05-20/1985-05-26 198521 3 26096 19621.0 32571.0 47 \n", + "... ... ... ... ... ... ... \n", + "2023-03-06/2023-03-12 202310 3 76368 68243.0 84493.0 115 \n", + "2023-03-13/2023-03-19 202311 3 74638 66420.0 82856.0 112 \n", + "2023-03-20/2023-03-26 202312 3 72750 64499.0 81001.0 109 \n", + "2023-03-27/2023-04-02 202313 3 64859 56800.0 72918.0 98 \n", + "2023-04-03/2023-04-09 202314 3 48060 40671.0 55449.0 72 \n", + "2023-04-10/2023-04-16 202315 3 37455 30993.0 43917.0 56 \n", + "2023-04-17/2023-04-23 202316 3 27875 22767.0 32983.0 42 \n", + "2023-04-24/2023-04-30 202317 3 27007 21779.0 32235.0 41 \n", + "2023-05-01/2023-05-07 202318 3 19929 15402.0 24456.0 30 \n", + "2023-05-08/2023-05-14 202319 3 16901 12577.0 21225.0 25 \n", + "2023-05-15/2023-05-21 202320 3 16162 11963.0 20361.0 24 \n", + "2023-05-22/2023-05-28 202321 3 16460 12188.0 20732.0 25 \n", + "2023-05-29/2023-06-04 202322 3 18303 13822.0 22784.0 28 \n", + "2023-06-05/2023-06-11 202323 3 14300 10661.0 17939.0 22 \n", + "2023-06-12/2023-06-18 202324 3 11308 7639.0 14977.0 17 \n", + "2023-06-19/2023-06-25 202325 3 10090 6739.0 13441.0 15 \n", + "2023-06-26/2023-07-02 202326 3 9023 5934.0 12112.0 14 \n", + "2023-07-03/2023-07-09 202327 3 8999 5763.0 12235.0 14 \n", + "2023-07-10/2023-07-16 202328 3 9179 5703.0 12655.0 14 \n", + "2023-07-17/2023-07-23 202329 3 11122 7113.0 15131.0 17 \n", + "2023-07-24/2023-07-30 202330 3 13205 8647.0 17763.0 20 \n", + "2023-07-31/2023-08-06 202331 3 15286 10705.0 19867.0 23 \n", + "2023-08-07/2023-08-13 202332 3 14641 10285.0 18997.0 22 \n", + "2023-08-14/2023-08-20 202333 3 19144 13161.0 25127.0 29 \n", + "2023-08-21/2023-08-27 202334 3 26663 21057.0 32269.0 40 \n", + "2023-08-28/2023-09-03 202335 3 31695 26013.0 37377.0 48 \n", + "2023-09-04/2023-09-10 202336 3 38247 32237.0 44257.0 58 \n", + "2023-09-11/2023-09-17 202337 3 49085 42079.0 56091.0 74 \n", + "2023-09-18/2023-09-24 202338 3 63567 55525.0 71609.0 96 \n", + "2023-09-25/2023-10-01 202339 3 82112 70891.0 93333.0 124 \n", + "\n", + " inc100_low inc100_up geo_insee geo_name \n", + "period \n", + "1984-10-29/1984-11-04 37.0 213.0 FR France \n", + "1984-11-05/1984-11-11 184.0 308.0 FR France \n", + "1984-11-12/1984-11-18 123.0 195.0 FR France \n", + "1984-11-19/1984-11-25 99.0 163.0 FR France \n", + "1984-11-26/1984-12-02 110.0 176.0 FR France \n", + "1984-12-03/1984-12-09 149.0 219.0 FR France \n", + "1984-12-10/1984-12-16 184.0 266.0 FR France \n", + "1984-12-17/1984-12-23 146.0 224.0 FR France \n", + "1984-12-24/1984-12-30 110.0 198.0 FR France \n", + "1984-12-31/1985-01-06 120.0 190.0 FR France \n", + "1985-01-07/1985-01-13 147.0 207.0 FR France \n", + "1985-01-14/1985-01-20 317.0 459.0 FR France \n", + "1985-01-21/1985-01-27 708.0 832.0 FR France \n", + "1985-01-28/1985-02-03 1074.0 1236.0 FR France \n", + "1985-02-04/1985-02-10 939.0 1113.0 FR France \n", + "1985-02-11/1985-02-17 784.0 926.0 FR France \n", + "1985-02-18/1985-02-24 652.0 762.0 FR France \n", + "1985-02-25/1985-03-03 618.0 722.0 FR France \n", + "1985-03-04/1985-03-10 591.0 689.0 FR France \n", + "1985-03-11/1985-03-17 458.0 544.0 FR France \n", + "1985-03-18/1985-03-24 405.0 485.0 FR France \n", + "1985-03-25/1985-03-31 319.0 395.0 FR France \n", + "1985-04-01/1985-04-07 207.0 281.0 FR France \n", + "1985-04-08/1985-04-14 83.0 149.0 FR France \n", + "1985-04-15/1985-04-21 66.0 116.0 FR France \n", + "1985-04-22/1985-04-28 44.0 80.0 FR France \n", + "1985-04-29/1985-05-05 55.0 93.0 FR France \n", + "1985-05-06/1985-05-12 59.0 97.0 FR France \n", + "1985-05-13/1985-05-19 38.0 64.0 FR France \n", + "1985-05-20/1985-05-26 35.0 59.0 FR France \n", + "... ... ... ... ... \n", + "2023-03-06/2023-03-12 103.0 127.0 FR France \n", + "2023-03-13/2023-03-19 100.0 124.0 FR France \n", + "2023-03-20/2023-03-26 97.0 121.0 FR France \n", + "2023-03-27/2023-04-02 86.0 110.0 FR France \n", + "2023-04-03/2023-04-09 61.0 83.0 FR France \n", + "2023-04-10/2023-04-16 46.0 66.0 FR France \n", + "2023-04-17/2023-04-23 34.0 50.0 FR France \n", + "2023-04-24/2023-04-30 33.0 49.0 FR France \n", + "2023-05-01/2023-05-07 23.0 37.0 FR France \n", + "2023-05-08/2023-05-14 18.0 32.0 FR France \n", + "2023-05-15/2023-05-21 18.0 30.0 FR France \n", + "2023-05-22/2023-05-28 19.0 31.0 FR France \n", + "2023-05-29/2023-06-04 21.0 35.0 FR France \n", + "2023-06-05/2023-06-11 17.0 27.0 FR France \n", + "2023-06-12/2023-06-18 11.0 23.0 FR France \n", + "2023-06-19/2023-06-25 10.0 20.0 FR France \n", + "2023-06-26/2023-07-02 9.0 19.0 FR France \n", + "2023-07-03/2023-07-09 9.0 19.0 FR France \n", + "2023-07-10/2023-07-16 9.0 19.0 FR France \n", + "2023-07-17/2023-07-23 11.0 23.0 FR France \n", + "2023-07-24/2023-07-30 13.0 27.0 FR France \n", + "2023-07-31/2023-08-06 16.0 30.0 FR France \n", + "2023-08-07/2023-08-13 15.0 29.0 FR France \n", + "2023-08-14/2023-08-20 20.0 38.0 FR France \n", + "2023-08-21/2023-08-27 32.0 48.0 FR France \n", + "2023-08-28/2023-09-03 39.0 57.0 FR France \n", + "2023-09-04/2023-09-10 49.0 67.0 FR France \n", + "2023-09-11/2023-09-17 63.0 85.0 FR France \n", + "2023-09-18/2023-09-24 84.0 108.0 FR France \n", + "2023-09-25/2023-10-01 107.0 141.0 FR France \n", + "\n", + "[2030 rows x 10 columns]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_data = data.set_index('period').sort_index()\n", + "sorted_data " + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n" + ] + } + ], + "source": [ + "periods = sorted_data.index\n", + "for p1, p2 in zip(periods[:-1], periods[1:]):\n", + " delta = p2.to_timestamp() - p1.end_time\n", + " if delta > pd.Timedelta('1s'):\n", + " print(p1, p2)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "Empty 'DataFrame': no numeric data to plot", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msorted_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'inc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)\u001b[0m\n\u001b[1;32m 2501\u001b[0m \u001b[0mcolormap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolormap\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2502\u001b[0m \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2503\u001b[0;31m **kwds)\n\u001b[0m\u001b[1;32m 2504\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplot_series\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2505\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36mplot_series\u001b[0;34m(data, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)\u001b[0m\n\u001b[1;32m 1925\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1926\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1927\u001b[0;31m **kwds)\n\u001b[0m\u001b[1;32m 1928\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1929\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m_plot\u001b[0;34m(data, x, y, subplots, ax, kind, **kwds)\u001b[0m\n\u001b[1;32m 1727\u001b[0m \u001b[0mplot_obj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mklass\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubplots\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1728\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1729\u001b[0;31m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1730\u001b[0m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1731\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36mgenerate\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 248\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mgenerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 249\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_args_adjust\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 250\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compute_plot_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 251\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setup_subplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 252\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_plot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m_compute_plot_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 363\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_empty\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 364\u001b[0m raise TypeError('Empty {0!r}: no numeric data to '\n\u001b[0;32m--> 365\u001b[0;31m 'plot'.format(numeric_data.__class__.__name__))\n\u001b[0m\u001b[1;32m 366\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 367\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumeric_data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mTypeError\u001b[0m: Empty 'DataFrame': no numeric data to plot" + ] + } + ], + "source": [ + "sorted_data['inc'].plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'68422'" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_data['inc'][0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "tout la colonne \"inc\" est representer par des chaines de caractère a cause d'un trait dans une ligne de la semaine 19 de l'année 1989 trouver dans par la cellule \"5\" \n", + "apres \"sorted_data['inc'][0]\" j'ai plus ce probléme de l'année 1989 \n", + "du coup maintenant je vais convertire mes chaines de caractère en entier ." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_data['inc'] = sorted_data['inc'].astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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FMVAaTD7gh9dzZwOlwbQ0qQbDNAZ898QgX483e0XgcIvEKoUdDeZLaPRLpe7xZKJ5NRim/rCAiUGuTqOD1QdTR2ewor4bbTYfqr+CNJjCuXWA94VjKgALmBjkaqzBuE7+kPPYRFZ7Vm7dj+4DpWtH6prmG3yZSbNeF6YxYAETgyizznpQ1zdalp2/9m2vhEnxoh89jXO/Xbp/RykIQdqwus/iNrOnbxiPrAvbjsYM6y9MJWABE4NaazAK24BYqS3zy6Hcwboeba9UnX0xItTc6LuARpTbvk/8/DlcevMyDGdz4ScfQrAvsnFgARMDm1njmdd24+4X36htYzR4GUwxQVud1LPNyncetBOLGijjanebdg/KckrPW2+/3tfuXYPP/uaFWHkbNAbnsKTcN1oeltjMGh//2RIAwEWnTKtlc1zq6mhv0K1iBjP22Xs9Z7rKBBVkbi27dWXYuZRWXK9Zyy+f3gQA+OHHS8/LGkzjwBpMDOplIrPSAPtalb9VTHUaf3AkQMBUpcZoKBNZoIAps4GVeBFdg93pkWi0x/NwhgVMDOo1QwrdTbk2zTDXXQUNphL9PBggYOoZrBFFgynXyR8lkCAsr4mRbB4buvviNaoGcMh848ACJgZ1WwdjeXCiDFbNSCV+TqAPpo7dpTSYYB9MmXUgXEsKw5T1X+94Ee/9zpMYqMH2O3EWNR9ij0FTwwImBg1nIlMcYutgKvFzGvVSRdkqplIajIix1ibIffPHl3YAALI16NzdA8Ml5znUJlrNDAuYGNRrcVzYc1PPB6vsmk0CpgK/p5o+jnJQUWS12HaoLA0m4MrWou1xms7ypXFgARODepnIbDTCy6vKXgdjGMgq8XOCmlVPW33BfGU/p1JO/jgCJso9VYsJTZw6WINpHFjAxKB+Cy3N6VG3kqkm1ai7EgNFsAmq7OJjk5BPXpSV/HEpRKrFzxtELfovTh0sXhoHFjAxqNcMyVZrFHt+tamKD6YCPydQg6lrFFmElfwVqquc3xmUsyYaTBwnf4Pv73Y4wQImBo3q5K+vZaBcE1l1qOpCxnKI4IMpOPnjtVTpINUy6dZCwMTywbAO0zCwgIlBmICp1szYvhdZdeuNQvkajMEHU4Gf06hOfrcNQcdE+DmBuJpt3AKC+6gWE614PpgqNISJBQuYGITd9PW6wQ+156oSM9HgAbxMravqS+TL9MHI/3HMTFFeB1MLAR1HwPBWMY0DC5gYhM3cqmU6sPtgGmA35Srkr4wPpnoaTLV9ROo2i78OJv59UQgcqV4QQhTiTNZYg2kcWMDEIFyDqe0d3ggr+ZtxoWW55VdrfYl7TrlhymUEf7gaTJ1NZHGuEmswjUPZAoaIkkS0goj+KL+PJ6LFRLRe/h+nnXslEW0goleI6AIt/XQiWiWPXU9y6kVErUR0u0xfQkSztTwLZR3riWhhub+jFMKeq6rd32H1VqnaKJS92aUhf0XClAMuVvlrd8qnFlFa5QnCoHJjFxsZDlNubiqhwXwewDrt+xUAHhFCzAHwiPwOIpoLYAGAEwFcCOAGIkrKPD8GcBmAOfLvQpl+KYB9QohjAHwXwHWyrPEArgJwBoD5AK7SBVm1qbmJzH03h3UhjHO8iTWYapUZdKnKHSArvceX7Zy4wrug2cbPGwQvtGTCKEvAENF0AB8A8HMt+SIAN8vPNwP4kJZ+mxBiWAixEcAGAPOJaAqALiHEs8IZIW/x5VFl3QXgXKndXABgsRBirxBiH4DFKAilqhPmNK34zC5iec3sgzE7YcotNGydSblO/rKyyzKq174ob80sh9qsgyk9D8uXxqFcDeZ7AP4dgH4bHCGE2AEA8v9kmT4NwFbtvG0ybZr87E/35BFCZAH0ApgQUFZNCFtXUDUnf7ACg6v/uLaOrxKovLmp2lFkZb8krUrhv/5zYjv55f9y1sGYrqvr26nBgkbWYJqb2AKGiD4IoFsIsTxqFkOaCEiPm8dbKdFlRLSMiJb19PREamgYoetg6rSSeO/ACA4GvMGx2ajkOhhT2G35kW9N4uSPs5tygI2slkElzbjZ5Qtb9tX11emNRDkazNkA/pKINgG4DcB7iOhXAHZJsxfk/255/jYAM7T80wFsl+nTDemePESUAjAGwN6AsooQQtwohJgnhJg3adKkeL/UR72iyMLClJuZekSRlXudqrWAsVB+uT0Q/30wha1sDMcivI2zUsRbB1OFhpTAX93wDD5/24v1bUSDEFvACCGuFEJMF0LMhuO8f1QI8bcA7gGgoroWArhbfr4HwAIZGXYUHGf+89KM1kdEZ0r/yiW+PKqsj8o6BIAHAZxPROOkc/98mVYTgl4SBVTRyW8zkTWAfCk7TNm0m3IFN7s0qrxlm8gqYMKrYhh1lDpsuLspB5xTmyiyGAKG48gahlQVyvwmgDuI6FIAWwBcDABCiDVEdAeAtQCyAC4XQih7zmcA3ASgHcD98g8AfgHgViLaAEdzWSDL2ktE1wBYKs+7Wgixtwq/xUh4FFmNGmKAIsX/eHny1R4cNbETM8Z3xK63Gg7zSvSjcE1kxf1SVw0mUvki8rkmwtbB9A9nkc3lMbajxVqGUYOR/2uzVUxt8jDVoSICRgjxOIDH5ec9AM61nHctgGsN6csAnGRIH4IUUIZjiwAsitvmcggbmKq2F1nIK5Pjcsmi55FOEtZf+/7YZVQlTLkSTv4gDaF8J0zZBP7GCjn5bffrGdc+jIGRHDZ98wOllVvDsPg4dfBCy8aBV/LHoJE1mLhkcvUN2TVmr4iT3/lfDRNZ1dfBVMjUY7sfB0bCA0JMbVBaMmswTBgsYGIwnA12wtQ8TLkBnDBlKwOm3ZTLLBOI9s57W/1hVKJ9gXuRubdZvJqqpmlUYJfmqLAG09ywgInBwZFs4PF67UVWT8rfmThaWunl2sOU9esUb6ZcTgMjhCmXUTpQGU0j2MTYmBoMi5fGgQVMDMJMC9V67qIUW68ImmrUWonfUjCRmZz8+uf6hMMGR2mVVwGVoWkEVV3tF5l521F6HbzQsnFgAVMCLUmnu4ZCFjNWzTZteXAawEJWFSrRje5gY1po6dFgamuKqeVK/njmP3uecgRXqVRaODK1hQVMKQS85lZPa+Zt8+NXXGZ2o4mschpM2LFYK8ZLz1JcRmAh1XXyB9bsCje7kz/Oi8xKhbeKaW5YwJSCvG+zhgcrV6Y9v4Tqi0glEqHnVJtqbNdf7c0kvU7+0suu1jb4hfKjn2uinBX3QTnKec9MqTTjSn6mAAuYElCDoMkEpqfVOoolnaq/jaxRH+oAC5nPyV8vH4y9kEr1aTm/LdhHFK89cdpR7TxMdWABUwLqxjUJmHIjkkqp309a12Dq9HSVH6YcLa1UAje7LNPJX946mPC8ldIQ4pn/Anww8n9t1sFU1n/E1BYWMDEwmshq4IOxDkr1V2CqstCy2lFkXgFTetmVMeEFHHPPiVdRJUxZQZtdNmqYMi+0bBxYwJSAum9ND6y+JXrcB1oIgV0HhuI3DOVrEnEpfy+y8nwwi57aiJuf2VSUXtWFlmX85ChZyx3AlYCJo2kUTGT2vLUIU2Ynf3PDAqYE1ANv0mCymoSJe3/fsWwrzvjvR7BqW6+5flu74lXn5K2jGSaMUgaKq/+4Flfds6YoPepCy0qbkSpBFD9IEG60V4WbWc6rmEul1oK/kvCOAixgSkLdLjnDvl3eKLJ4N9aS150NoV/Z1RcrP1D6w9Uoz4DZRFY+UcOU482UYzRIUsu9yOL0pBocje2MsAXNJYuex/+7e3XJ9fqJZ7psjJu6Fj6qRocFTAm4Tv5QE1m88pMJtbWHea8z23PjeaBKFTClnV61cqq3VYzz37zZZXmBGWUttIxQhroNyu2Hqq3kDyj4yVd7cMuzm0uvuIR2WPNEOGdDdz+O/8r92Lp3sPQKIsLyhQVMLIxhyhE0mJVb96NvKGMtN5V0Hl2TCS6IRjCRVWfv+0o4+ZWJLHirmHhbksRuVqT6ynXyF+qKkcf3X6ewviZ2kyITS7OM0LA7l23FUCaPe18yvgjXyobufrzv+39G76D9OXbb0SCaVD1hARMR/SE3CYB8yDqYbC6Pi370NP7+pqVFxxQFDcZ8Y1p9MB4FprSbulKDRDUepVoutIzXD+U3MDCKrEJO/mq9VqBRV/LrOcIiL0st/vpH1mPdjgN4/NXu0HNZwLCAiYwnpDU0TLk4vxJKSzfts9ahVuRnfT6esD2lyrHVR827dNPewAi3ssOUTSay8ooEEPw+mHIXWlZ7fK2YcllW3cW5K7WS/96V27GnfzhiO6ITZeIQ582vQGm/nU1kLGAio98rWYOPxGMiC1mIaUNpMP7yw3J6NJgqOfkv/smzuOB7TwaUU6YZx1hmWUUCCN7sstzw7sqs5A86VpkRqtI7Elciimx3/zD++bcr8OlblsVuh5UIps+4G8QWJnvh57IGwwImMvqNmjP44PMhGkyUiBIlYKq9vsJzfgkZ9gfYnavh5C93nYpTRrRjNnPPA6t34Et3rrTkr66JrNy9yKLUYa87QMDI0TnKOpiBYfO7k5SW/sa+gyHtCK0iME/FQ7Qp+jMqgt9LeFjAAiYi+v1kivLKhQyGlsCwilCeQKrULLkixVjLDBoogk130XwwttP+6Vcv4M7l20LbVyqRBqggT3spdcUoQE2ITPdtKa8B2NDdb0x337YZkr/crWJs+eO+yiBqu4HaLERtdFjARES/V8K3iinObzKrWeuK0AZr3hJv6kaxExt3U9bSgjTAM/77EXu5VfXBVECDCdrsslLb9ceY3Kj+DmpDFCd/uYNsudF9capfsWUfHnvZ7MQvLF6N4oNpkIerjqTq3YBmIWxWFLZVTJQHzWbfddMtD3t5L76K8KBEGEji+TCCNQivBhPXRObkM4UpV6L8uEQRHrWK8BNCFPWPK2AMmd0taKL4ISw/QvV3WLeX+ypr23VVvy+ZKJ5jf/iGZwAAm775gaJjicLDWFI7DldYg4mBP8oL8GooYQKo0gjL51Lz2ogiHKu9pUfcVdFuFFnIVjHlDmRxCSwipPxMLo+7lm8LnQCY78dg7VBdc3PR0Te7tK3pKtRZettDiTBxUOnJEkfAUqLIWL6wgIlM2Gw3bNYUyVTg2ndtmkp420oliiOyWlteeARjiAZT6uJThavBGI/ZWmNqi8GEV2UfTJiT/5dPb8S/3bkSd1l8RIXKipOyISbdfICJLGwTTc8OCTYNJuKEq1zBb8uuAnUSJYaTqfMjTcwaxf5cR1jAxMDsgzF/VkQxMxEqEEVWYt4oppoog3tYvb2DGcz7+mIs31xYB+QxkYX4YOIu6qvUQsuwdwCVqsGJEOGhl2mbLfcPORFa23vNkViFcOLSJ0TZIBOZm89YbaSJQWSfZJmasW0CpQJ1kgmvgAm7jqWtg6mtgNnQ3Y+Lf/IM+i2Re/WABUxE9Hsl7I2WYcdthE2mbCXoA3GpjuEoz4Bpc8+gNphYvmUvdveP4AePrtfyBLdD77K4zuKCiczkgwm31StMA6WeUqr8K8UHYxukO1odF6otFLhQVzFeDcYugKIKaB39WtmuW919MBbNNqPd6+ZJTQlhyjVWYK574GUs3bQPT63fXduKA2ABE5GwiKaKmMisdYccL+NGjjLLijLbDCsm7IVf5jIrocHYj3nXwQSXY+qnKAJq6aa9eGD1Tnu7AhqojtgmJyk5+86ETACM92PEdVumY+4sPsSBD9gnJ0rLD7uq5W4VY3fyq+Pe9IxmfjAJ9kQJYco1DxyR9SVKs/pVFY4ii0i5GkxZ+zYpc4rNJGH9ErnoQKJoX1Gr9ZgvwvweehvKjSILaUssDSZC/ot/8iyA4oikKL9GDRi2/i8szA3pxwABAoSYyAzlhb1nxvOshERxhbW93F2ubfmVicz/23UBY+oXdx1MhPux1j4Y1aRS/UrVhDWYiHgGuxi7KZcWpmw+t1TnfxSi5K2EDwaGmZ9H2Bjyhwn1KLjvNTEcK+WFY6aZeFnrLYTnn/mUkDITEXc1NpvItBfkBfgMgwRvmPDwf/aUH6S5leHbcvKYy/LWb27HSDZMg4luIqu1j78Qkl/beoNgARMR71YxwRpKpX0w4fZ6YfgUjXJnYlGdnmFVN6rYAAAgAElEQVT3vPk3hg9UYdgGEn9aWB+bNZjoAqoob4QrFXZOIhFt0V/YzhImQeHKU5PgR7D2kQt5VoDgSUspmqWJKFvFFASoN31E02BMbQ8KnPBT6xefqdpYg2lCwsw14SayEuoS5u/lOBYPDGVw57KtxedHaE/QYFCY0UV7mGyDcrU0mCBnsogwEBXODdZgSh0I8xGuaT7k9yciCnfT4bB1W8qEZBJyBf+FRTuIoMEUdgowtU23BhizBxJl4pB1BYz3uMd0aBIwJWgwtd4qxm1u48iX+AKGiGYQ0WNEtI6I1hDR52X6eCJaTETr5f9xWp4riWgDEb1CRBdo6acT0Sp57HqSV5GIWonodpm+hIhma3kWyjrWE9HCuL8jKvq9YlpoWQknvxum7K+7hLbZuPL3q/Clu17Cqm29Jee1vWET0DWY4DKMUVy6hlLhAdxfhllABF8zHVP7RAmao3+wivTCMe2UjCH2PalMZDECFEJ3nlADsKHsgm/IXF82goAJEvxhwi8MPYfVB2OpX2+7aWJVUphyjTe7LDj5G0fClKPBZAF8UQhxAoAzAVxORHMBXAHgESHEHACPyO+QxxYAOBHAhQBuIKKkLOvHAC4DMEf+XSjTLwWwTwhxDIDvArhOljUewFUAzgAwH8BVuiCrCiGDnfehKs5eiomsdHOL/tmceWevsyHkUDbnSY8WRWY/J6rJIMzJbl7IGNynUQh6t3w+pH7buYU8+vHg/BnLKxii7kVmEjCFLVvK02DMQQD29hUG5/I1GBN6VJztp/3XH1bhlKsfMh6LEn1430s7jMfDgh9KeY+M7Z54cM1OLNu0N3I5USk4+StedGxiCxghxA4hxAvycx+AdQCmAbgIwM3ytJsBfEh+vgjAbUKIYSHERgAbAMwnoikAuoQQzwrnzrjFl0eVdReAc6V2cwGAxUKIvUKIfQAWoyCUqoJ+s4Rvdhk8W7Zh23NMhDzQ0WbDwlOHmx6aM5pwjGrKsA3KxgG8xDYY6zPUFbV+z7khUWRhOyL4td5SzZ0mrdltmzUoxH7cE0ocEHYftMrfKjz0skMCAWxvf/XX5efXS7ZYXx8RZnrV8Rev93O5GoztlH+8dTk+KqMLK0kj7n1WER+MNF2dCmAJgCOEEDsARwgBmCxPmwZAdwJsk2nT5Gd/uiePECILoBfAhICyTG27jIiWEdGynp6eeD8QPrU7zjqYEgZp20Nlu39ECef4tedIO+IGOWTdeqPd3N5NQ4PriKohTB3TBgAY1Vocde8OhiEaUqz9vEowsfkHq0K/2fPo7TNpMK6WYbvmAWWHLbQMWslfCJywlB0ySAO188GUavoM88Eo7cC29khEEK7VQoRcl3pQtoAholEAfgfgC0KIA0GnGtJEQHrcPN5EIW4UQswTQsybNGlSQPOCUTdqgmxOfv2zYTCKJGDMg6Gyqdpu2NJmw3b92SYkokT8hAlQ09F8yCCnC6OgNkzucgSMyTSQD2hflGgjhVEAWj6byPoFRBQbvnbKiEHAuPeLbUIC4TlPR89jFCIBGkZBuzHX6xngI2g5fsLWouiE7REX/tu9x3XToemeU7sv6+HMOpXwG8bFvd4NJGHKEjBElIYjXH4thPi9TN4lzV6Q/9WLFbYBmKFlnw5gu0yfbkj35CGiFIAxAPYGlFU11M2SSibMayLCwpRLGFBs/oZyts23aTDeh9GcN1iDUYNNcLtMbfe+pM1QdoiGUzgvaLbtJIYtlAwLCa6aBhOQJ8xEFjbQq2SzjyW47UEaRmGVf7B2AtgnBkH3sv5bw+74YcNAH2b6HBjJGs8FwqNB1X0ylMkVHfPnqVaYcj4v8PnbVnj29QOCJ1P1opwoMgLwCwDrhBDf0Q7dA2Ch/LwQwN1a+gIZGXYUHGf+89KM1kdEZ8oyL/HlUWV9FMCj0k/zIIDziWicdO6fL9Oqh7xm6QRZ1g1Ee2ADq7D4WtQ3uwYT4aa2+GC8viWzZAuy/4fWKwnbXqccE1nBZGMqoyB8/INaKQstjZevhNmq38QVSevUKjBqMAFmLG85xUTdO8/cp7Ae85dnEySu4DEc9gYglNavxUUW51ebhAIGH0yYL1UeP2gRMKX49eKy/2AGd7+4HZ++ean3gBIwDeSLKWermLMBfBLAKiJ6Uab9J4BvAriDiC4FsAXAxQAghFhDRHcAWAsnAu1yIYS6Sp8BcBOAdgD3yz/AEWC3EtEGOJrLAlnWXiK6BoDq4auFEJUPy9BQN0sqmTDeXN4H1pQ/igYjisoCCg+ZTbOJcjsVNBgypgP2sEr/rEwvI2ywccswaBlhobJhAsh/ntEhrWsBeYEWzY5Wkq0+RECGXd6ia4ri/iguP7j+XEjfB12b0L3IArTC4HfFeAe4MA3GdHQoE91EZp6YhGgww9E0GLPW6PzXhZS37uC2VRJ/8e5z0EAaTGwBI4R4CnaD/rmWPNcCuNaQvgzASYb0IUgBZTi2CMCiqO0tF3Xx0knCwHDwYGN+oKPUIc/15Xcne1btRPsYrMAUtU14BoM8gCT86DPKXF4glTQJGHO9CtNsO9REZshvLDtgIA0SUmGDrO1ct30R+l3hdwpHmmSGanjmCUlAMS76wG+6r2wmMiGEtkbGop3oOxLbtByLtg54zU9h18XkbA/TfIN2TI5qOnx994CxPWGWjEqg/HlFz7KhDfWGV/JHRF2yVCIRGqYcd6uYsBmI3Zkbjs0BqH/t7hsOrdcWPRNnoWKYkz8sNFwR5IPRk/wmwLDBxFtHcVppPhiziSzwnfchAixox2Mnj30Qz4cI17wl76Pau+qjOPlt5tWg56EUDcZk1vU42kPWpPmbEeY/Uv0xOGLWYErRauOSsZhGw4I+6gELmIioBzKdIs93RehWMRHuNpM2ECXssZRV4cVtK3z/9M3LjHn1B61owWDA4K5TmBGbB2XjQ2HRdmxlB/lgTHWU4pA1r+QvEDoQ+jWYwLPVOcHXPmzBo1tOiAZj6nvVXn9efRJi08o9z0IEP40fjwYTMliWu6uG/3hYv6i8Nh+MCDH7VgKbBhOkydcLFjARUdcsLcMU/bObqKp1EOocm+koUhSZ5RSb+U3/unmPRe0PsEurb2E3tWlrkDATVZRwV/0843qOgDUZYSY6W1sKeaLnL4oiK6gwVsLs+cJyTd3j8n+Qj8U5bh+k/cd0m7h1s0vPIG2WQkFRanpkWJhpOexFcGbNz76LQS5kmxpV3cERSxRZRLNmOajAhqKiXA2m7CoqBguYiKjZpPI/FDkHQ26sUpz8NtNR0EAyobMltHxT2/SvqaT5dvDsz2SJhgp3xhan2TQ1f9lOfnv5QX6gTMDuuGFmItu5pvaFCpgYT73H1BMwabG13RXqpu1eQrZjKay0D2pfFAET0rbQaxbcb6Z+DXsRXJCPKBswmQK0KDKLgAkzkUV59UUYykxdtGhaPQdsIms+1DVLWTQYdVHtCzGjCJjic/Vc1igyoe3yapkS2xzC+vlpyyZG+kOesfyOyE5+T55g4RnVx+F9qL3n6eG9xVqnuQwT4Qs1g/PbnPxBuSJv52LzzQnvf52w7VxsZseEdo/Yote9ky2bBmPOC4S/k0XH5BO0PT+m40FRZEGa3WAmF7gI1Za/Ev4RU2g2UHiW2cnfhOhRZIDJng95PGFeVBjB3q/Sbc7doBeRRd1AtTiKrPA5nbJoMNpDnPEtbIu6ejhnGFHDTWT6ufayvQO995g+WBX5zQIEEwDcu7KwdtfsIoomAIFiZ3QUjTZ0sFMm1RChHxQlZivbFqY8tj0dmM9ftt1PY38dwLDMRBQ+IIcF1IT5YPztC9vmRt+ex7QXmuc9O4b8NuFQCq4GY6mbnfxNxta9g3hMRs8oM1KRgHEFUCJ0HUzYFuaeGTnC8wmhvSvccm+59npf2/S6Jo5qNeb1RtbENZEFz/bMwtNer60cfztGAgaMMBPZw+t2Wcv15wl7pP11F/b6suf0LlgsPq4O2/om6G2eYRMekz+w92AGl926XGtTFAET4oMxFKEmMR3pZOhg6Q86AcJDsIOOhy0S1c9/cn3x3oZhCy2jLFoOI+sKYPOatkYSMOUstDxseO93nnAdj6mEWYPJ5wUS5Az0YetgckIYOz5nmIF4/BABg1HYNuKu+lzkbC58PuvoCca8nigyq5M/sHqjPyBsthfVBCUCzhvRXk/gH+zCVm2HbhsSIiD1Aco/sAQJTFObgqLIwkLHYy20lIm6Bth9YMj93JJKRApTtkaRBdwvyqzZ3hIuYEwDduhvi+qDMWkw2vmmdxyFCW5/lFoyxt76Ng0m6rqoWsIaTAT0qJYgJ38yQUgmKDC8EbDfAGoAtDkKrbZ2aO+SsfwGm6ahfw3b+RawbzsfVYOxCUyjCUo/N2A8tglkwDv4FmkwIQ7ZMHu6V7AV5w8KjshZwoA954TMplWaTVgVTGTBZQeZmXSTTmuqsAi3NZmwTir0e8SqrQcMgkqotbckQ30wpt+eDVhICQTfdznfomI/eQF0tDj9YFrNH35PaP7MmOYyk9am181hyk2McvKbNRgpYEJms7aHzvQaV+9aCEujRPiri23qs9cEZ9mLTMtTvCdW+ECp16ufFjaAlxqmrNfjtld3GPs6MMxWH7Yi3fNGy5BB3B8ckTX0h5+oTn71Mjlb/UEair8ef5ref/p93Zo2+xqjtBsI/v0j2TwSBLQkE6EOa7MGo4caF+cJ+u2he5EJgU75WgjTWpgw7U1vr2l/uSi4flD/xrUWK0U9YQFTIjYn//LN+zCczTsr/Y3v7tAHS3PZrt3bMiO3azDhN1QhgCBAg7GuutYH6Xg+GPXg6hYBjw/EZILS2xBQvicYoMhElkeLzW8WoPn4jxt9ICEmPu8WO/ZdBGyEr61y/u/uHwl0KJvuj7BwXFWed02KV5uxXfMwMxOg/R7D4Uwuj5ZUAqmEeedyb13l+mB8x0Kc/Pm8QKfUYEw7KocFjngma5Yt/8NQZfhNZCa/Wb1hAVMiymbqv4bL5NbZqSSFri623QDKnGMLnw2K2nHbZWm3TYPRy7SFIOvtsW07HzZemhyTYbbyoFX4tvP8fZ/J5dEuB4QgE1lotFGIhhUWzeT3k6jBf/v+g0X5CvnNdZnS+oeLzTVBjnT995i2vFd9pZtx9P5rTSXsYcohEwdP20xRZNk80skEEgmKF6bssQCY6rabwbIhbc8LgdZUEgkyC5iwNTh63ZfetLToeBRspjX1WyoRSFApWMCUiGsiswz2LcmEcaAOisQqnKNW6JofkKBw1FBnoTCX4S0/uF2A/eYO02BGDI7JsNXkXh9MkAZTELD+vh3O5l2beeBgYig+zJbvFc7BM2mbee7+1TuLKzaUHxaZOOATMEKIwEi1nFbgcNZg6lFOfl3AaL+hJZWwmmNVu5IBAiJI+I3k8mhNJZBKkPWe9JfjSQsxbaqf1JIsDlTIWgSqnjeRILSnk8bFlnoWU9N1gbhyW2/xCREoLLT0PvOqvZVYzFkpWMCUSMpiItOP+9eKAL7B1PLMqBvDulVMgG8nNEzZUob+1RaNFBhFJuyDmKcMw/5JepawRWvBAsZuuszk8mhPKw3GtxYlxAS1b3DEU4efMDOT19xij2CzEbanl37cr4WEmf/0+vXNJf312RY9tqYDTGTyd5sG8EJZeU89Ohlp1nT8mcV58577sbjt3jdiFudXQiudpOKgkDCzrRBIJoC2dDL8tR0h1ywuBWuAN11dqzi7RlQLFjAlojQY24Pj7LZcfIFtzlIdkw/GtjBRodqh2mUzkqnzit/cGz6Ie6PI/AstZfkh97RpdhUWyaQn7T9YvKitcJ5AWvpZ/AP9iGYiC/LBmLptvLb9Tljghumh1u8Dvzkl2s4OupAwDMRanX57fph2pgskoy/BYCLz+GCSiQCNWgqYVMJqrtE30/QP5CO5PNIBGoxNqyr8HrvvCyj0TcogAD3mM4vZNEFkFTClXLNTZ44tOh4FmxVBXdMbHn8NW/cOxiq70rCAKZGudieCxBbvnk6SURPwPKghmoLNN2DKph6CRIiJTBVTtNmlpY2mdgHFfhpbuX7UAJi3zPDCfDDb9tkfGCFgdeSPBJjIVGi5U39xA47saiu0L8TsaYoI0o/v01Z96+arIPJCWH8X4NUmgwSMyc+hC5VgASMK4dCyvl9degYSCbvfzbOrRYi/EbAHZiQSZn/miEfoFR/XB/5hg3bm7oxuEJKhTn7hRGy2tySNZXstDkWH3fpaUonYTn7bOhjd1PnCln1oBFjAlMi4DmdW6+5JNJLFUVf+yT2eSsbXYNQAr2cPczqqotQ+lWEBJDnfQBhlzYL+IBVHkQnPfxuqT/SBJcwhqpK62lI4cND8/g3V7paU2iPO275MLo+2tFnA5PPCXThrm+UrM4QxjDnMRKYLmIGCuS2qmSSbE1bTH+AdaEdyXiGhXyfTpRkcybm/3W9eE0J4zI7Kv5RzB2ZCgihgN2Xn/NaU+d1JgD/CzntOIYrMvKZMN0GbfF8HMzm0pRPG3+bU7ZTZli5uX6iTP+8sqG6PYCIz3TPq/u9oScZeB6P6zvtmWeEZY/RnNpPLY8iyd1q1YQFTIkdP6gRQEAL6zPTsYyZYNRiPgLE8dGpvI+8rZ3V7sn0WnQzZjEwpOP62qfwpy2wRAA5mCoN70bvl3bYFVu+W7R1YCseD1pmM7WhB35DdRJbLC1eI+AeITE64GoxpMFEagqn+4WzO9d+EbXVjmlR4NZgR7dyIAkb7XcbBSh9QfAOp/t00sBzM5DC2Iw0iYNg3UKrmqbrVvau015QUMGEm1ZaU3Yym34emtrekEtY1ZeEmshzGtre4n23ta0sXD/LZXGFSYdZgHK23LZ2wOPmDBZS6TzrSyYpqMNm88DyDA9oL0R5YvRPHf+UBbOjuj1VfObCAKYFPnDGzYG6RN5J+E1144pFIJ83rYG5+drP72ThY5QU2ytew2rYYCRrkEiFhyuq435Sjbvi2dNK6QnhgOOf+7iLhKbztsKHqtQla0zik0sa0p3HA8g50wJnFtqaKfTDPbdwDAHhwza6i+lSbVdCGaRB2ItCKTaKKoOAHf1v2DRQEZFQNxqt9mY/rbdW57v6X3c+m6oZGcmhvSaI1lcBQkXnN+d7uEzBKM0kmHPOV7WeofmkJ8NPoz4hfCIzIMGWbBqPfQyYtYEgKT1PZevvaTQImL9x7yWYWpYg+GGNgiNJgWlPWoJowCuubCviF1dfuXet+Vu1U91ItYQFTAscdOdpdMa9ufP0ma00lkUoUazDrdhzwfDc9NH9Y8UbhuB7+6omIMQkm53+YBqOO+h8o1ZbWgNnm4EgOY+Quun7hWdjvKrB698GKYyIb057GAYuTP58XEMKJatJ/DwD0+F4BbXpJXMrVYIrLHsnm3YHKOJjoEwGjM9lJa0kmsKtvSEsvNtWZGMnm0Zq2a1j6YOgfYJ5+bbf72eSDOZhxtLPWVLJoEFY/pd03qVDXMJUg6557eluDNBi9DwZ9moAKU07afDAh1oCDmoAxmshyBQHqf1azOeFuiWN+ZbLzrLWni/sN8N7fpv5RebraUsa2hSGEcM3FevmmstT9rzQtdT1rCQuYCLzz2EkAgL89Y1aRU1i/ybbtG0QqmSgaxPf0j3i+mx6KV3f1uZ9tjsZIGoxloFc3oM0Z3GZ42BSDI1l0tamB1ufjkPmj+mA8DtqI5oRxnXYTmdK62gw+mLHSX3bNh05y6itaTV/YvNTU/mde2+NeX/8gqPK77cjaNZyjJ3Vi855Btyy/kLZtGZLJ5d3BzjRYjWTzGN2Wcj/r/M28Ge5n0xg/OOIImLZ0ojjCTRRm+HrZrjk1SUgGmsic/+mk/Rz9GfGbmjK5Qpiy2XRpDp3Wy1O+UlMI9oirRYRoMLYoMhmmbBIwYcJvSDriR7elPRuxRuXHT7yGRU9vdNrqMTM6ZSm/GQDs6HUW8arJUQcLmMbkG3/1ZjzxpXchkSA3HFjZv/Ub+JK3zUY6Wby4TNlD//W8YwEAX713jed4Li/w0ydfB+CY2fRoEP0BMA5yalFbyAvHVDuDNRjzQDc4ksP4zhYkE4QtvvBH2/vB/YzIAbgUE5kSeOM70ugfzgZGcrk+GO2hUwPA5NGtRcdUmwubl3rLVQ/ntn0HkU6SZaV8sLNZtW36uA4Aheun0t8k/XmmaCTA+f3KWW3bCkbti+UXMMoBPHFUi3HS4TjCk2hLJ4vX0OS8faoCCFwfTIKkKdgmYKTmlrLvJaYPzrqPT/0WtVWMyQRmez4KZTv9kk6ScRGpilJLJxPFGky+oDXazKIJqcGYtFqv76vosPscdrWnY5nIbnp6k/vZFKZ+3Ufe4qbtkYElg/LebUuxgGlIpo1tx6wJzmDQ2epcpAE5WOg32cRRrUYfjJqhKSf+8s3eEML/ffAV93NrOuGdocmbcOKoVvMLjuRdnDb4IHTUg1b8QEkBk05a8w6OZDGmPY3p49o9A21ecyyGr4MpFnBhm0nmNA0mL7yOS0XGHQyLBwU1iI2Wg7DptysNwT+Y6K8/6GxNuQ+pp+6wKDKZ1iW1jEHZftXno2S7TIOg0968OyjYwpSVj8ivBQ3JSCrHpGs21XS0JNFmMJEVazBCtqHgg2lJJaztdlfKp+zb7euTpYMjPo1O+mBa0wmjBtI/XMhr6nev+a84fyaXRzpJzq4bBg3GXVNl8f+0ppJobzGv5Nf7xHRPqzxdbalYm112a2ZfvX1qzGhNJfH9BacAKOzucGAoi9GtqdClDNWABUyJqBmjungvbd0PAPjlp94KAHLW5b2xeqX/4OxjnPetTBzV4jn+0Bpnu5ATp3ahNZXwzGjVjXP8kaOx88AQ9vR7/QpqYHed3Ea7sXAHEf9sVQnDoJDSPf0jGD+qpcjuHLbzrLce5YMxO2jXbj+A2VfchyWv79GOO3kmyAWPfQZHf5EGY3joxsn8gz4BNZzJudfTFuAAOBMDPUhDMTCcdU2mppn0zgOOFqTMWGpwUffOGGnGsdniB0dy7oTGHPKaxyh53B8JpgZZIrPwf2lbL1pTjonMb/ZUfapMKsqso/tgWgPWcQxnc6HnHMzk3IWs/uuSyTlh56NbU0bNUd8m32Yia29xfptJCKowaCfis/h5SCekec4oYHJoTSWsTn7PG1RNGoxsT1d7Grm8KGtlfy4vXNPu0k17ATjP8VtnjwdQ6Ke+oSy6tDeR1hIWMCWiZp1rtjv7CH178asAgEnybZCjWpM44PMX7B0YARFwzrGTcPqscXjTpFHusTuWbcXrMnpM2dz1h+Kvf/osAGD+Uc5Ns2mP10Sl3rqoBIxpoLvge0+6g7VpxgbINQGGvCPZPPYMjGDy6Fa0t3gFjHd/teAHRQ0imVzhoVBtIQIeWuv8jj+t2lEoU7ZZ+VJMAka12TTTV4OuGsgGhr0Dwkgu7+6Ma9ok04/uJwOAR1/udu8Hk7njX25fCQCYKbXfbXJjyx45SZg2tt1pp2EQXrO9F1v2DroDrDEIQTeRGbTm9nTSqGk8J4X4A2t2YuW2Xjz5ao/HB6Wu8SRpWlQDlbrGyQQVado6/cNZjG5LGc1vgHPNVmzZ7wpa/0A9MJJFWzqB0W2OadTvH+sfznjK0snnhWP+SyWsGozSkNLJRNG2Tk7gB1n3URuRwqmzxfFZ+gWobmUwCTfVnsJ9Ey9UWaHa+F9/WA3AMUuOkhOaPlfAZNxJTq1hAVMi6oH+2Z834uWdheiwuVO6ADj29r6hrGeX3NuXboUQziLMCZ0tnpvw3+96yf2cIGfWpx7K13oKceuzJjh2fN3Z3T+cxZf/r3BjAbaBsVCO/7iaVY9uSxsfKDWoHtHVVmRO0Wf9ppcvKYQQeGVnYXB2Q5bloDxJe1Vzm+aIzOad94KoCDaTo189sB2tKuKpWPvrkLPZYg3GWeVPVNwvfy93um1NJfC+k44E4A3W2Lh7ANv2HUTvwQxSCcLeAa9mqTN1TJtsv1P/blnObMM1VfzkCccnt3a7c4/5B9Jt+wbxes+A63vzD3QHMzm0tSTR1ZYuEsym98foA7EyRR4hdzJQa3jUvdLRkkRL0uzkBpx7obM1hXbLWpHXepwJlbo++jm9BzPYP5jBzPEdGNWWQi4vioSEx0Tmu2c3Sx/htHHtUggW179l7yAmd7UinUp4XqkNOBOFVMIJYjAGGGScCDe/JUPR3TeMlmQC7emk8ZlQpks3+k+FHAuB3yzZ4lo7TJh+S1bbaQFwrk2nNJv2uSayjBukU2tYwJRIhxZLrmaoQCGKS+0vpAbmdTsOYKf2qtlxHS2eRXc6RN6Zof7gHXfkaADebdn1V9ja/Ax+NX/vgLduJewmjW41zjafeNV57/i7jpvk2J11DUary6+16fz8zxtdn5XeRjWoq5ky4HVEZnJOGLFS7/115PMC//E7R0ArIWTywbSlkxhlMLcMZ3NoTSeR9pk1c3mB9XJR2v9efDI++55jiurXr83xU0Z7hLi/Har9araswkePl5MSf5QhUBA608d1oCWZ8AyqAHC1XOewWmrSfgEzlHE2+exqSxf1m5qMvPeEI9w0Xfgq/8gJU7qQTJA7OVD919mawozx7RgYybnBEDr9w1mMak05JlXDoKgmX5e+/ShPfQDQI8O5j+hqc2f5fgGsvo/tSBeFh6v2zBjfISdExff0vsEMjuxqQ4th143hbM5dbmAyXw1nHQGj2ua/p7oPDGHS6FaMbjOb937+59cxlMm710BdtzXbD+A//7AK/6FNOP08vLa7KO287z6B7z78qvud5EsPR7Wm3H7aP5hhE1mzoDvK1E2i+85mjHdmpVv3OTe6MnEpxnamsX8wAyFE0WwlmXCcdLm8QDaXd2/Qmz71VncGos+KdIefbZ1Kt28tyJ/XF9ZH9A1l3Jtz0qhW9B7MePKv3Lof//vgKxjbkcaUMe3SB1PsQ2lNJazrVDbvGcC1f1rnScpSxQEAABmhSURBVFMDrfrvETBpXcDkkU6Qq977Z+Kv7x7As9Lco36/bioakNuhpBKEjpaUZ7a5eO0u9PQNozXp2OL1360PaGmZF/AOwrqgnTW+E5v3DHjappfhXhs5mF3zR0c4qCiy3f3F2s/jrziC/S9OnopRbSmPWWgkm3cnBn89b4Y0gxU7+dvTSbmGyO/jcM694n3H438/+hb52wq/Z7+cAE3uasW4jjT2H8xgKJPDd6Q5OJ1MuBr7C5v3F7XdNZFZHOGfktqh0gz1vuzpc+qeNKq1cN19A/UrO/swcVSL4zf0TaiU8J48us2owYxk81i34wAS5NwXfhOZ8t8kDAJGCCHNTWnXDOUPPOnuG8bkrlaMaksVtbv3YMY1dapAAiVgNkvTt+leUNy3antR2rZ9B/GDRzcAcMahk6Y512VsRxr7BkYghMDWvYOYPq7dWm41YQETgy9dcBwAGPexmjSqFS3JhLs5oxoUv/LBuQAcDWYkl8fvX3ijSJtQJjLAmSmpAXFcR4t7Q3s0GE14qBnKPl+k2VbDJpHqoftvbeCfKAd5vU0X/ehpAAUtZ+PuAWzo7ne1IqWVTBnThoGRnNE8t3DR8+7nf7/wOPe3AY7DM5kgV6UHvIP4gYMZjGlPuwONfzW/3hfKn6EE3dMbduPOZdswrrMFRITO1pTb3v2DI/iHW5bhwFAWrelE0dol3YSp+2muf8R5kJ99bQ8+8uNnADgh7LMmdGDbvoMeIaUmD++YM9E1NfnNMUqwKmGi+LtfFvrsn845GqNaU67/aDibw9nXPYrnpVP3X957LNrTyaIQdhWG3NWewv6D3vtMlTWqNaUJT32QV4N0KyaNbsOG7v6iyEflF7v8Ny/AT580kbWlHB+MbSHpEV1tSJBXG1T+qYmjWwtagnbdM7k87l+9EydNG1MUUDOUybnO7kmjW9HVli6axN36nBOs8dDaXdJE5r1nB0ec6DqT72pgJIe8cDa8tZnIdh0YwhGj2xz/ke9+7dEW26otitR999vntwBw+nX55n34ix88hbuWb3PPPziSwzOv7cFZR09wIyb93H35292oyKlj27HqjV7sHRjBwEjOnfjWGhYwMXj3cZMBFMKNVXQY4Gg408a1uwNOMkH4y5OnuuaAcXKF8RfvXOnOZI+a6MxkE0Ru5E5337A7gI5qS7mD8B5NAOgmMhU58m93rnRNIi9t24+Lf+JoUE9+6d34r/efAKAg9PQHe6J0hO/WzDXKR3DKDMfst1buSKDa8PQGRxtSTmz/ynmgEJRwZFcbjp5YmLH3Hszgt89vRUc66Tq/gcJMDnCE5ZiOFld7W7pxr3tsJJvHP9yyzP1+xtETQATctXwbBkey+MTPl2B3/7AbgdbZknQHA10wkexz3QSlvxpg7fYDbhTaxt0DWLFlHz72s+fc4+ccOwnHTB6FrGZWA4CfPPEaAOAz57ypMJhIwTplTBs+evp0dzB4YM1Ot+/29A97BI4SjuqavbB5v3vukV1tSCQIM8d3YJOmQS1c9DyWb96HtnQS08Z2oLtv2L3WmVwe//mHVU6ftCZd35U+E1flTxzVilNmjMFr3f3uoKZWyKv/fu5YuhWr3ujF+M4Wd+W4rl3N+/rD7udpY9vR0ZJyhdvqN3rxud+ucH7bmDajGeobf3K2wBnf0YLxnS2e3/2DR9fjV885A3VXWwoTOluK/GbfechZEqDMh5mccCc1QgjsG8xgVGsKnS3FQlsJq662wqRHF2Aj2TzWd/djclcrutpSRa+YWLfDMTXeffnZrvVjKONYKp6Sz9LD63bhIz9+Bqve6MW/3VkwwX/h9hXYP+hMuF666gLcftmZRX0/ZWxh9+/5s8fjtZ4B12IxkwVM6RDRhUT0ChFtIKIralXvnCNGeb7/7JJ5nu/jOtK476UdeK1nALm8wNveVBBAaj0NAKyQW2p/8C1TADgq7jnHOsLroTU73UFlVGvKDYf98eOv4f/dvRpDmRx6pENx+Zffi5NnFN4t0X3AGSB++/xWN23G+HZMHO0MlA/Ityiq8v/3o29xNZhdmtBKJgjTx7Xj158+AwDw1b9wtDA1WKkAgzNkhNuf1xcGxnU7DuCoK+8DALxl+hg8e+V73Jn8fat24IbHN2DvwAj6hrP4xoffjJTcQFBfyOmPkLtn5XbXfv+1e9e4A+Hdl5+NMe1pCOG8JXDBjQUBoAZCXYPRB44nX+3B+M4WPPLyLvzw0fXI5PKuiQgAPvueY5BOJlzt68M3PAOdqWPbcerMcQCA933/z3hq/W789U+fdft+7tQupFOFt20ODGexo3fIXfypuPL3ju39DU3YqonHaM2e3qOZUP7ylKkAnJ0C1D52QgjXb3ZEVyumjWuHEIXrqgZoAOhsSbk+RX2y8aIMvW9LJzF9XAf2DIzgR485AvPGT86TZbdh9oQOzJnsfRb+XfrEDhzMuuto1AD+0rb9rglo/uzxzpshNb/e9Y+sd8vpaku7Wvknfr4Ev3hqI4YyOXcV+9uOmYizj5mIlVv3u6as379Q2G6JiDC+s8WjkV9601L3HrjtsjMxQS4XUELoew+vx+7+Ybx5+hi0+0yq3QeG8P7v/9m5Hm1pTB3jaMw7tICJVW84/rCjJ3Zi+rh2bPMtSl71Ri9akgnMndrlahQbdw8ULT3QURF0aj+9VJLQkkoYNZIJ2vuL1Bj1hdtfBAA2kZUKESUB/AjA+wDMBfAxIppbi7rTyQT+/O/vdr93tHhDANUs/ILvPQkAmDK2cHFPOLLL/azMWafNcgaoebPHY+aEDiQI+Mb9L7sDuH+2eMuzm3H8Vx7A7154AxNHtWCCjML63LlzAACPrNuF1W/0ugPlx+bPABHh7GMmAnAEw2s9/ejpH8Y75kzExfNmuO8+ueoeZ5eBvqEMXusZwIdOmeaaAya756zGhu5CVNg/vONojO1I48n1u9E/nMVQJocVW/a7K5mvfN8JIHI0O8ARkvpan7lTu7Dhv9+PD586Det39WEok3O1k3U7DoCIXO1HLUpdua1g+/c/PC9pr6JV2uao1hT2Dzo2aV3z6R3MYM32A9g/mMG3HnoVl968zJ2VXvvhkzBaak+nSyFiQhcWf/uLJXhe07TGdrSgJZkAkbMKWwn3qfKemCIjzB5e142Lf/IM1mwvRCb+PynQp4xtw5KNe7FvYAS98pqeMmMsLnvn0e5vUxFtr2ih1B+bP9M1w/1p9Q4MZ3P4/QrH7HL+3COQSJA7iG/ZO4i+oQweXLMTD68rOJNnywnRoy87aRO0NVzvf/MUrO/uR0/fMB57pdsTOdndN+TuPL5E9ocSXABwy6XzAUBqj1lkc3lXI1boL3y75o9r8cU7CjP6j5w2DbMmdCCbF3hp234IIdzB/ssfOEG2tRUHMzn0DWXQezDjLgf45/ccg5NnjHXXo+3uH0Yml8f3pYB755xJaE8n8PC6bjdQ5NbnNrv3xZFj2jCuU5qkpQDL5PL4FzmYn3fikZg1oRN7BkZca8KG7n7c+OTrEHAWch57xCgQOVqbshoc65u4As5kbPYV97nfr5RWiKljiwWGvn3/hdK/pdCXRtSS+gRHV4b5ADYIIV4HACK6DcBFANYG5qoQQTbN2y47E+d990n3+ynTC9rFmI40rrnoRHzl7sJ2Me+cMwkPfuGdrtP3fSdNwX3aehBlSlnxlfNw6jWL3fTd/cPu7B4AvnDuHFz/yHp8Q+6k+6ZJnTht5lj894ffDMBxfE4Z04YdvUM499tPAAA+fsZM9/d88C1T8MeXvDf02zTzn3rgH3ulB49JM87vPvM2tKQSmDKmHfe9tAP3vVRoNwB8929OxplHj3frP3XmWKzYsh/3rdqBmeM78KQmqM85dhJ++/xWHP+VB9y03/yDoz398OOn4f3X/xl/WPGGZ2PQoyd2ugK2zbfy+4cfPxUffIszy580uhWb9wx63t0DAP/1gROweO0uPCIH0Cdf7cGTUgN430lT3POUNqGYNLoVv5GanW2Pp9VfuwCAE54uBLC9dwhflGYP1SdPfOndOPbL9wMAlm7ah6WbHK121VfPd4WbmsDo1/53n3mbq9Uqre/krz2EBW8t7EF24tQu16z5Pw+8gv95wBHO08a240apdR93hBOdeOXvV+HK369y835Rbmt0hmwn4GiSR2v98J7jJ+OGx1/DW68tmL0UV/3FXJwywxHK/9+vvX6at71pghvM0dGSwr0rt+PelQUH9sZvvB+AY6LTUc/Ejz5+GojInVjoWuWM8e349DuOdj8DwJu/+hDOPd6ZaHzhvXNw+budqMAju4rzp6TJ8dwTjsALW/ZjwY3PoSWV8EwaTps51h3Mv/XQq1jf3Y89/SPYsncQEzpbMG1su2tevuruNXjHnIm4Sj7v75ITno6WFN48bQx++NgG/PAxx7f3jb96Mx5e140Fb52B/uEsPnD9U/jsb1a49T75pXe7vkYAeOJL7wKB8N7vPIHzTixEBALOmHH35Wfji3euxL+df5xrkqs1TavBAJgGYKv2fZtMqxkvX3Mh1l59QVH6nCNGY+FZswA4s5IxPg3kk2fNdjfQvP2yM5FMEI47crS7s+93/uZk91y17QPgrEjf+I33u3uaAcDVF53ofvZvBfFazwBOnzXOM7N54PPv9JjsdBOHCl7QmT+7MMCcZpjFv2X6GADAZ+VD6+fDp0731H/FhccDcOz858/1PhRnHT3R8/1TZ8/G297kpM2d2oW/OHmq5/hn330MHvniOe73b198imeTRz0M9xzZ3zqbvvkBLJg/Ez9fOA9/97bZRcfHaddtks+k9a/nHYs5cnAmInxeao+Kay460fUhAMV9O0WaWFpSCfz602d4JgoTR7W6wgUoRFvpJLVrrff9bUudR+Llay4EERlnrvpOEokEucJOP/7P8vdMHNWK333mLJw2cyyWfvm9nms5b/b4ot8NAK98/UKcPms8kgnCp86e7Tn2kdOmu7teAMA753iv+U8/ebpbRzJBngEVcAb3D0iT8klTx3iOpRKEO//xbe53de8AcCcQl73zaDeC69gjRuHtx3jrX/7l85BIEBbK++HFrftd4XLGUePxwlfO8/QBANz94nY8tWE3Tp4xFrf/o+MbUdaCP6x4A/96x0r0DWfxsfkz8JO/Pd3N94E3FyYwM8d34KRpY/AfFx6PWRM6ceLUMe51veSsWXjiS+/CzAneSe2sCZ2YOaEDT13xbnz74pPh5+QZY/Hwv55TpM3UEqrHW84qARFdDOACIcSn5fdPApgvhPhn33mXAbgMAGbOnHn65s3FW35Ug0wujz+88AbOPHpC0Y0BOOHEOVHYC6tUlry+B7MmdOLIMW2e9O4DQ7h96VZs2TuIfYMj+NbFJ7sRPzr3vbQDyQThvLlHeAarbC7vvJUzl3dj6v3s6R/G4EgO08e1ex62TC6Pa+9bh529Q/jwadPwnuMnuw+zzis7+/Dn9T345Fmzin7//sER3LlsG17fPYAr3ne8G+ILOFFCr/cM4OkNuzG5qxUXnWKeTzz2cjeOnzLaHcQVw9kccnmBF7fu9ww+Op/77Qps3juIn33ydNckqBBC4KG1u/DA6p345kfeXNT24WwOD6/tRu/BDP7mrTM8fSeE876fl3f2IZsX+EufsFSsfqMXsyZ0eASM+u1rth/AMxt2Y+HZs40L5/7zD6vwmyVbcNOn3urOlAEn0mndjgP42r1rkUgQfrDgVM89KYTA7Uu3YnAkh+OOHI2Tpo4pmhTZEELg+Y17Mb6zBYue3oTPnXuMp9/zeYG9gyP4/QvbcPqs8Th9lneSMpzNuS/CGt/ZUnTNtu4dxNZ9g9i8ZxBt6QQuOnmaZyKVywtHcxjVgn0DIx4fp17Gw+t2obMlhb/WNDxFT98wHlyzE+ccO8ljmbhr+Tas2LIPc6d24Z1zJmFyV6vnmr+x/yBueGwDzj1hMgZHcnjvCUd4wuzXbO/Fw2u70d03hLlTu/DX82Z4noeRbB5/fGk7Zk3oxKwJHUUam+q/euwh5oeIlgsh5oWf6cvXxALmLABfFUJcIL9fCQBCiG/Y8sybN08sW7bMdphhGIYxEFfANLOJbCmAOUR0FBG1AFgA4J46t4lhGIaRNK2TXwiRJaLPAngQQBLAIiHEmpBsDMMwTI1oWgEDAEKIPwH4U+iJDMMwTM1pZhMZwzAM08CwgGEYhmGqAgsYhmEYpiqwgGEYhmGqAgsYhmEYpio07ULLOBBRH4CdAHotp4wJOAYAMwFsCTgelr/ax4Pax22L17aw/I3ctrDj3G/VOd7IbQs7bmvbcUKI0QFlmhFCHDZ/AJYBuDHguPWYPN4Tcjwsf7WPW9vHbavOdW3kttWg7Ydlv1XgtzXsOGJrG4BlQWXa/g5HE9m9MY8BQPH7YUvLX+3jQe3jttkp57o2ctvCjnO/Ved4I7ct7HhY20ricDORLRMx9tOpVP5q08jt47bFg9sWD25bPGxti9vmw02DubHO+atNI7eP2xYPbls8uG3xsLUtVpsPKw2GYRiGqR2HmwbDMAzD1IjDXsAQ0SIi6iai1VrayUT0LBGtIqJ7iahLpqeJ6GaZvk69g0Yee5yIXiGiF+XfZFN9VWxbCxH9UqavJKJ3aXlOl+kbiOh68r+Sr75tq0a/zSCix+Q1WkNEn5fp44loMRGtl//HaXmulP3zChFdoKVXtO8q3LaK9l2pbSOiCfL8fiL6oa+suvZbSNvq3W/nEdFy2T/Lieg9Wln17regtpXeb3FCzw6lPwDvBHAagNVa2lIA58jPfw/gGvn54wBuk587AGwCMFt+fxzAvDq27XIAv5SfJwNYDiAhvz8P4CwABOB+AO9roLZVo9+mADhNfh4N4FUAcwH8D4ArZPoVAK6Tn+cCWAmgFcBRAF4DkKxG31W4bRXtuxht6wTwdgD/BOCHvrLq3W9Bbat3v50KYKr8fBKANxqo34LaVnK/HfYajBDiSQB7fcnHAXhSfl4M4CPqdACdRJQC0A5gBMCBBmnbXACPyHzdcMIN5xHRFABdQohnhXOX3ALgQ43QtnLbENC2HUKIF+TnPgDrAEwDcBGAm+VpN6PQDxfBmTgMCyE2AtgAYH41+q5SbSunDZVqmxBiQAjxFIAhvZxG6Ddb26pBjLatEEJsl+lrALQRUWuD9JuxbXHrP+wFjIXVAP5Sfr4YgHqR910ABgDsgLPa9VtCCH2Q/aVUHb9Srmobo20rAVxERCkiOgrA6fLYNADbtPzbZFojtE1RtX4jotlwZmVLABwhhNgBOA8eHG0KcPpjq5ZN9VFV+67Mtimq0ncR22ajEfotjEbpt48AWCGEGEbj9ZveNkVJ/cYCxszfA7iciJbDUStHZPp8ADkAU+GYK75IREfLY58QQrwZwDvk3ydr3LZFcG7IZQC+B+AZAFk4qrafaoUOlto2oIr9RkSjAPwOwBeEEEGapq2PqtZ3FWgbUKW+K6Ft1iIMabXutyAaot+I6EQA1wH4R5VkOK0u/WZoGxCj31jAGBBCvCyEOF8IcTqA38KxewOOD+YBIURGmnqehjT1CCHekP/7APwG1TNjGNsmhMgKIf5FCHGKEOIiAGMBrIczsE/XipgOYLu/3Dq1rWr9RkRpOA/Ur4UQv5fJu6QZQplxumX6Nng1KtVHVem7CrWtKn1XYttsNEK/WWmEfiOi6QD+AOASIYQaXxqi3yxti9VvLGAMqOgIIkoA+DKAn8hDWwC8hxw6AZwJ4GVp+pko86QBfBCOuahmbSOiDtkmENF5ALJCiLVS/e0jojOlSnsJgLsboW3V6jf5O38BYJ0Q4jvaoXsALJSfF6LQD/cAWCDt4EcBmAPg+Wr0XaXaVo2+i9E2Iw3Sb7Zy6t5vRDQWwH0ArhRCPK1OboR+s7Utdr/5vf6H2x+cmfYOABk4M4hLAXweTrTFqwC+icKC1FEA7oTj/FoL4EsyvRNOZNRL8tj3ISN9ati22QBegePEexjALK2cefJmeA3AD1Weeretiv32djimhZcAvCj/3g9gApxgg/Xy/3gtz3/J/nkFWuROpfuuUm2rRt/FbNsmOMEe/fI+mNtA/VbUtkboNziTrwHt3BcBTG6EfrO1LW6/8Up+hmEYpiqwiYxhGIapCixgGIZhmKrAAoZhGIapCixgGIZhmKrAAoZhGIapCixgGKZBIKJ/IqJLSjh/Nmm7WTNMo5GqdwMYhnEWsgkhfhJ+JsM0DyxgGKZCyM0EH4CzmeCpcBacXgLgBADfgbNQdzeAvxNC7CCix+Hsy3Y2gHuIaDSAfiHEt4joFDg7IXTAWXT390KIfUR0Opy93QYBPFW7X8cwpcMmMoapLMcBuFEI8RY4r3K4HMAPAHxUOHu0LQJwrXb+WCHEOUKIb/vKuQXAf8hyVgG4Sqb/EsDnhBBnVfNHMEwlYA2GYSrLVlHYw+lXAP4TzoubFsvdzZNwtthR3O4vgIjGwBE8T8ikmwHcaUi/FcD7Kv8TGKYysIBhmMri33upD8CaAI1joISyyVA+wzQsbCJjmMoyk4iUMPkYgOcATFJpRJSW79qwIoToBbCPiN4hkz4J4AkhxH4AvUT0dpn+ico3n2EqB2swDFNZ1gFYSEQ/hbNT7Q8APAjgemniSsF56dqakHIWAvgJEXUAeB3Ap2T6pwAsIqJBWS7DNCy8mzLDVAgZRfZHIcRJdW4KwzQEbCJjGIZhqgJrMAzDMExVYA2GYRiGqQosYBiGYZiqwAKGYRiGqQosYBiGYZiqwAKGYRiGqQosYBiGYZiq8P8DgAwrMoKZD4YAAAAASUVORK5CYII=\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sorted_data['inc'][-200:].plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", + " for y in range(1985,\n", + " sorted_data.index[-1].year)]" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "year = []\n", + "yearly_incidence = []\n", + "for week1, week2 in zip(first_august_week[:-1],\n", + " first_august_week[1:]):\n", + " one_year = sorted_data['inc'][week1:week2-1]\n", + " assert abs(len(one_year)-52) < 2\n", + " yearly_incidence.append(one_year.sum())\n", + " year.append(week2.year)\n", + "yearly_incidence = pd.Series(data=yearly_incidence, index=year)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
0202339713901182662204FRFrance
1202338716702783062315FRFrance
2202337711222232021213FRFrance
32023367726101442102FRFrance
42023357961961826102FRFrance
52023347116892327204FRFrance
62023337330811845432528FRFrance
72023327799611201487212222FRFrance
82023317331813985238528FRFrance
920233075821326983739513FRFrance
10202329713558829718819201228FRFrance
11202328767004043935710614FRFrance
12202327772534599990711715FRFrance
1320232679192622312161141018FRFrance
14202325711498825714739171222FRFrance
15202324711115796814262171222FRFrance
1620232371256361341899219929FRFrance
17202322712184812516243181224FRFrance
18202321711349759815100171123FRFrance
192023207900046151338514721FRFrance
202023197934460911259714919FRFrance
21202318710671729114051161121FRFrance
222023177918461621220614919FRFrance
23202316711387801414760171222FRFrance
24202315714040761320467211131FRFrance
252023147152471103219462231729FRFrance
26202313713322970016944201525FRFrance
27202312710374721813530161121FRFrance
2820231174919288069587410FRFrance
2920231074854273169777410FRFrance
.................................
16831991267176081130423912312042FRFrance
16841991257161691070021638281838FRFrance
16851991247161711007122271281739FRFrance
1686199123711947767116223211329FRFrance
1687199122715452995320951271737FRFrance
1688199121714903897520831261636FRFrance
16891991207190531274225364342345FRFrance
16901991197167391124622232291939FRFrance
16911991187213851388228888382551FRFrance
1692199117713462887718047241632FRFrance
16931991167148571006819646261834FRFrance
1694199115713975978118169251832FRFrance
1695199114712265768416846221430FRFrance
169619911379567604113093171123FRFrance
1697199112710864733114397191325FRFrance
16981991117155741118419964271935FRFrance
16991991107166431137221914292038FRFrance
1700199109713741878018702241533FRFrance
1701199108713289881317765231531FRFrance
1702199107712337807716597221529FRFrance
1703199106710877701314741191226FRFrance
1704199105710442654414340181125FRFrance
17051991047791345631126314820FRFrance
17061991037153871048420290271836FRFrance
17071991027162771104621508292038FRFrance
17081991017155651027120859271836FRFrance
17091990527193751329525455342345FRFrance
17101990517190801380724353342543FRFrance
1711199050711079666015498201228FRFrance
17121990497114302610205FRFrance
\n", + "

1713 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202339 7 1390 118 2662 2 0 \n", + "1 202338 7 1670 278 3062 3 1 \n", + "2 202337 7 1122 223 2021 2 1 \n", + "3 202336 7 726 10 1442 1 0 \n", + "4 202335 7 961 96 1826 1 0 \n", + "5 202334 7 1168 9 2327 2 0 \n", + "6 202333 7 3308 1184 5432 5 2 \n", + "7 202332 7 7996 1120 14872 12 2 \n", + "8 202331 7 3318 1398 5238 5 2 \n", + "9 202330 7 5821 3269 8373 9 5 \n", + "10 202329 7 13558 8297 18819 20 12 \n", + "11 202328 7 6700 4043 9357 10 6 \n", + "12 202327 7 7253 4599 9907 11 7 \n", + "13 202326 7 9192 6223 12161 14 10 \n", + "14 202325 7 11498 8257 14739 17 12 \n", + "15 202324 7 11115 7968 14262 17 12 \n", + "16 202323 7 12563 6134 18992 19 9 \n", + "17 202322 7 12184 8125 16243 18 12 \n", + "18 202321 7 11349 7598 15100 17 11 \n", + "19 202320 7 9000 4615 13385 14 7 \n", + "20 202319 7 9344 6091 12597 14 9 \n", + "21 202318 7 10671 7291 14051 16 11 \n", + "22 202317 7 9184 6162 12206 14 9 \n", + "23 202316 7 11387 8014 14760 17 12 \n", + "24 202315 7 14040 7613 20467 21 11 \n", + "25 202314 7 15247 11032 19462 23 17 \n", + "26 202313 7 13322 9700 16944 20 15 \n", + "27 202312 7 10374 7218 13530 16 11 \n", + "28 202311 7 4919 2880 6958 7 4 \n", + "29 202310 7 4854 2731 6977 7 4 \n", + "... ... ... ... ... ... ... ... \n", + "1683 199126 7 17608 11304 23912 31 20 \n", + "1684 199125 7 16169 10700 21638 28 18 \n", + "1685 199124 7 16171 10071 22271 28 17 \n", + "1686 199123 7 11947 7671 16223 21 13 \n", + "1687 199122 7 15452 9953 20951 27 17 \n", + "1688 199121 7 14903 8975 20831 26 16 \n", + "1689 199120 7 19053 12742 25364 34 23 \n", + "1690 199119 7 16739 11246 22232 29 19 \n", + "1691 199118 7 21385 13882 28888 38 25 \n", + "1692 199117 7 13462 8877 18047 24 16 \n", + "1693 199116 7 14857 10068 19646 26 18 \n", + "1694 199115 7 13975 9781 18169 25 18 \n", + "1695 199114 7 12265 7684 16846 22 14 \n", + "1696 199113 7 9567 6041 13093 17 11 \n", + "1697 199112 7 10864 7331 14397 19 13 \n", + "1698 199111 7 15574 11184 19964 27 19 \n", + "1699 199110 7 16643 11372 21914 29 20 \n", + "1700 199109 7 13741 8780 18702 24 15 \n", + "1701 199108 7 13289 8813 17765 23 15 \n", + "1702 199107 7 12337 8077 16597 22 15 \n", + "1703 199106 7 10877 7013 14741 19 12 \n", + "1704 199105 7 10442 6544 14340 18 11 \n", + "1705 199104 7 7913 4563 11263 14 8 \n", + "1706 199103 7 15387 10484 20290 27 18 \n", + "1707 199102 7 16277 11046 21508 29 20 \n", + "1708 199101 7 15565 10271 20859 27 18 \n", + "1709 199052 7 19375 13295 25455 34 23 \n", + "1710 199051 7 19080 13807 24353 34 25 \n", + "1711 199050 7 11079 6660 15498 20 12 \n", + "1712 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 4 FR France \n", + "1 5 FR France \n", + "2 3 FR France \n", + "3 2 FR France \n", + "4 2 FR France \n", + "5 4 FR France \n", + "6 8 FR France \n", + "7 22 FR France \n", + "8 8 FR France \n", + "9 13 FR France \n", + "10 28 FR France \n", + "11 14 FR France \n", + "12 15 FR France \n", + "13 18 FR France \n", + "14 22 FR France \n", + "15 22 FR France \n", + "16 29 FR France \n", + "17 24 FR France \n", + "18 23 FR France \n", + "19 21 FR France \n", + "20 19 FR France \n", + "21 21 FR France \n", + "22 19 FR France \n", + "23 22 FR France \n", + "24 31 FR France \n", + "25 29 FR France \n", + "26 25 FR France \n", + "27 21 FR France \n", + "28 10 FR France \n", + "29 10 FR France \n", + "... ... ... ... \n", + "1683 42 FR France \n", + "1684 38 FR France \n", + "1685 39 FR France \n", + "1686 29 FR France \n", + "1687 37 FR France \n", + "1688 36 FR France \n", + "1689 45 FR France \n", + "1690 39 FR France \n", + "1691 51 FR France \n", + "1692 32 FR France \n", + "1693 34 FR France \n", + "1694 32 FR France \n", + "1695 30 FR France \n", + "1696 23 FR France \n", + "1697 25 FR France \n", + "1698 35 FR France \n", + "1699 38 FR France \n", + "1700 33 FR France \n", + "1701 31 FR France \n", + "1702 29 FR France \n", + "1703 26 FR France \n", + "1704 25 FR France \n", + "1705 20 FR France \n", + "1706 36 FR France \n", + "1707 38 FR France \n", + "1708 36 FR France \n", + "1709 45 FR France \n", + "1710 43 FR France \n", + "1711 28 FR France \n", + "1712 5 FR France \n", + "\n", + "[1713 rows x 10 columns]" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = raw_data.dropna().copy()\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + " def convert_week(year_and_week_int):\n", + " year_and_week_str = str(year_and_week_int)\n", + " year = int(year_and_week_str[:4])\n", + " week = int(year_and_week_str[4:])\n", + " w = isoweek.Week(year, week)\n", + " return pd.Period(w.day(0), 'W')\n", + "\n", + "data['period'] = [convert_week(yw) for yw in data['week']]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + " sorted_data = data.set_index('period').sort_index()\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "periods = sorted_data.index\n", + "for p1, p2 in zip(periods[:-1], periods[1:]):\n", + " delta = p2.to_timestamp() - p1.end_time\n", + " if delta > pd.Timedelta('1s'):\n", + " print(p1, p2)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sorted_data['inc'][-200:].plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + " first_august_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", + " for y in range(1991,\n", + " sorted_data.index[-1].year)]" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "year = []\n", + "yearly_incidence = []\n", + "for week1, week2 in zip(first_august_week[:-1],\n", + " first_august_week[1:]):\n", + " one_year = sorted_data['inc'][week1:week2-1]\n", + " assert abs(len(one_year)-52) < 2\n", + " yearly_incidence.append(one_year.sum())\n", + " year.append(week2.year)\n", + "yearly_incidence = pd.Series(data=yearly_incidence, index=year)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" yearly_incidence.sort_values()" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+++ b/module2/exo1/module3-exo2.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module2/exo1/syndrome-grippal.csv b/module2/exo1/syndrome-grippal.csv new file mode 100644 index 0000000000000000000000000000000000000000..642b077cec2d298d69a73e5643b8aa5dc5d9b21d --- /dev/null +++ b/module2/exo1/syndrome-grippal.csv @@ -0,0 +1,2033 @@ +# @source="réseau Sentinelles, INSERM, Sorbonne Université, https://www.sentiweb.fr", @meta={"period":[198444,202339],"geo":["PAY",1],"geo_ref":"insee","indicator":"3","type":"all","conf_int":true,"compact":false,"age_group":false}, @date=2023-10-04T13:08:27+02:00, bundle=1696417706 +week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name +202339,3,82112,70891,93333,124,107,141,FR,France +202338,3,63567,55525,71609,96,84,108,FR,France +202337,3,49085,42079,56091,74,63,85,FR,France +202336,3,38247,32237,44257,58,49,67,FR,France +202335,3,31695,26013,37377,48,39,57,FR,France +202334,3,26663,21057,32269,40,32,48,FR,France +202333,3,19144,13161,25127,29,20,38,FR,France +202332,3,14641,10285,18997,22,15,29,FR,France +202331,3,15286,10705,19867,23,16,30,FR,France +202330,3,13205,8647,17763,20,13,27,FR,France +202329,3,11122,7113,15131,17,11,23,FR,France +202328,3,9179,5703,12655,14,9,19,FR,France +202327,3,8999,5763,12235,14,9,19,FR,France +202326,3,9023,5934,12112,14,9,19,FR,France +202325,3,10090,6739,13441,15,10,20,FR,France +202324,3,11308,7639,14977,17,11,23,FR,France +202323,3,14300,10661,17939,22,17,27,FR,France +202322,3,18303,13822,22784,28,21,35,FR,France +202321,3,16460,12188,20732,25,19,31,FR,France +202320,3,16162,11963,20361,24,18,30,FR,France +202319,3,16901,12577,21225,25,18,32,FR,France +202318,3,19929,15402,24456,30,23,37,FR,France +202317,3,27007,21779,32235,41,33,49,FR,France +202316,3,27875,22767,32983,42,34,50,FR,France +202315,3,37455,30993,43917,56,46,66,FR,France 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+198447,3,72029,54274,89784,131,99,163,FR,France +198446,3,87330,67686,106974,159,123,195,FR,France +198445,3,135223,101414,169032,246,184,308,FR,France +198444,3,68422,20056,116788,125,37,213,FR,France diff --git a/module2/exo2/module2-exo2.ipynb b/module2/exo2/module2-exo2.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..75aef0d24393bb28289e7dca96d9c9c191dc90cb --- /dev/null +++ b/module2/exo2/module2-exo2.ipynb @@ -0,0 +1,174 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "# Données fournies\n", + "donnees = [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,\n", + " 12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2,\n", + " 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0,\n", + " 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6,\n", + " 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0,\n", + " 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4,\n", + " 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "14.113000000000001" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calcul de la moyenne\n", + "moyenne = np.mean(donnees)\n", + "moyenne" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.334094455301447" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calcul de l'écart-type (4.42/4.31)\n", + "ecart_type = np.std(donnees, ddof=1)\n", + "ecart_type" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2.8" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calcul du minimum\n", + "minimum = np.min(donnees)\n", + "minimum" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "14.5" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calcul de la médiane\n", + "median = np.median(donnees)\n", + "median" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "23.4" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calcul du maximum\n", + "maximum = np.max(donnees)\n", + "maximum " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(14.113000000000001, 4.334094455301447, 2.8, 14.5, 23.4)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Affichage des résultats\n", + "moyenne, ecart_type, minimum, median, maximum" + ] + } + ], + "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": "3.6.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module3/exo1/Untitled.ipynb b/module3/exo1/Untitled.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..7fec51502cbc3200b3d0ffc6bbba1fe85e197f3d --- /dev/null +++ b/module3/exo1/Untitled.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb index 59d72b5b58a3ae26346460dd39e62a39c55243d7..778b67773d5f6bc3ec490134bdc0bbf7136573f2 100644 --- a/module3/exo1/analyse-syndrome-grippal.ipynb +++ b/module3/exo1/analyse-syndrome-grippal.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -28,10 +28,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" @@ -61,9 +59,976 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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20131985093369895341109.0398681.0670618.0722.0FRFrance
20141985083389886359529.0420243.0707652.0762.0FRFrance
20151985073471852432599.0511105.0855784.0926.0FRFrance
20161985063565825518011.0613639.01026939.01113.0FRFrance
20171985053637302592795.0681809.011551074.01236.0FRFrance
20181985043424937390794.0459080.0770708.0832.0FRFrance
20191985033213901174689.0253113.0388317.0459.0FRFrance
202019850239758680949.0114223.0177147.0207.0FRFrance
202119850138548965918.0105060.0155120.0190.0FRFrance
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20732.0 25 19.0 \n", + "19 202320 3 16162 11963.0 20361.0 24 18.0 \n", + "20 202319 3 16901 12577.0 21225.0 25 18.0 \n", + "21 202318 3 19929 15402.0 24456.0 30 23.0 \n", + "22 202317 3 27007 21779.0 32235.0 41 33.0 \n", + "23 202316 3 27875 22767.0 32983.0 42 34.0 \n", + "24 202315 3 37455 30993.0 43917.0 56 46.0 \n", + "25 202314 3 48060 40671.0 55449.0 72 61.0 \n", + "26 202313 3 64859 56800.0 72918.0 98 86.0 \n", + "27 202312 3 72750 64499.0 81001.0 109 97.0 \n", + "28 202311 3 74638 66420.0 82856.0 112 100.0 \n", + "29 202310 3 76368 68243.0 84493.0 115 103.0 \n", + "... ... ... ... ... ... ... ... \n", + "2001 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "2002 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "2003 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "2004 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "2005 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "2006 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "2007 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "2008 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "2009 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "2010 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "2011 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "2012 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "2013 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "2014 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "2015 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "2016 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "2017 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "2018 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "2019 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "2020 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "2021 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "2022 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "2023 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "2024 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "2025 198449 3 101073 81684.0 120462.0 184 149.0 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110.0 FR France \n", + "27 121.0 FR France \n", + "28 124.0 FR France \n", + "29 127.0 FR France \n", + "... ... ... ... \n", + "2001 59.0 FR France \n", + "2002 64.0 FR France \n", + "2003 97.0 FR France \n", + "2004 93.0 FR France \n", + "2005 80.0 FR France \n", + "2006 116.0 FR France \n", + "2007 149.0 FR France \n", + "2008 281.0 FR France \n", + "2009 395.0 FR France \n", + "2010 485.0 FR France \n", + "2011 544.0 FR France \n", + "2012 689.0 FR France \n", + "2013 722.0 FR France \n", + "2014 762.0 FR France \n", + "2015 926.0 FR France \n", + "2016 1113.0 FR France \n", + "2017 1236.0 FR France \n", + "2018 832.0 FR France \n", + "2019 459.0 FR France \n", + "2020 207.0 FR France \n", + "2021 190.0 FR France \n", + "2022 198.0 FR France \n", + "2023 224.0 FR France \n", + "2024 266.0 FR France \n", + "2025 219.0 FR France \n", + "2026 176.0 FR France \n", + "2027 163.0 FR France \n", + "2028 195.0 FR France \n", + "2029 308.0 FR France \n", + "2030 213.0 FR France \n", + "\n", + "[2031 rows x 10 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" @@ -78,9 +1043,73 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020233938211270891.093333.0124107.0141.0FRFrance
120233836356755525.071609.09684.0108.0FRFrance
220233734908542079.056091.07463.085.0FRFrance
320233633824732237.044257.05849.067.0FRFrance
420233533169526013.037377.04839.057.0FRFrance
520233432666321057.032269.04032.048.0FRFrance
620233331914413161.025127.02920.038.0FRFrance
720233231464110285.018997.02215.029.0FRFrance
820233131528610705.019867.02316.030.0FRFrance
92023303132058647.017763.02013.027.0FRFrance
102023293111227113.015131.01711.023.0FRFrance
11202328391795703.012655.0149.019.0FRFrance
12202327389995763.012235.0149.019.0FRFrance
13202326390235934.012112.0149.019.0FRFrance
142023253100906739.013441.01510.020.0FRFrance
152023243113087639.014977.01711.023.0FRFrance
1620232331430010661.017939.02217.027.0FRFrance
1720232231830313822.022784.02821.035.0FRFrance
1820232131646012188.020732.02519.031.0FRFrance
1920232031616211963.020361.02418.030.0FRFrance
2020231931690112577.021225.02518.032.0FRFrance
2120231831992915402.024456.03023.037.0FRFrance
2220231732700721779.032235.04133.049.0FRFrance
2320231632787522767.032983.04234.050.0FRFrance
2420231533745530993.043917.05646.066.0FRFrance
2520231434806040671.055449.07261.083.0FRFrance
2620231336485956800.072918.09886.0110.0FRFrance
2720231237275064499.081001.010997.0121.0FRFrance
2820231137463866420.082856.0112100.0124.0FRFrance
2920231037636868243.084493.0115103.0127.0FRFrance
.................................
200119852132609619621.032571.04735.059.0FRFrance
200219852032789620885.034907.05138.064.0FRFrance
200319851934315432821.053487.07859.097.0FRFrance
200419851834055529935.051175.07455.093.0FRFrance
200519851733405324366.043740.06244.080.0FRFrance
200619851635036236451.064273.09166.0116.0FRFrance
200719851536388145538.082224.011683.0149.0FRFrance
20081985143134545114400.0154690.0244207.0281.0FRFrance
20091985133197206176080.0218332.0357319.0395.0FRFrance
20101985123245240223304.0267176.0445405.0485.0FRFrance
20111985113276205252399.0300011.0501458.0544.0FRFrance
20121985103353231326279.0380183.0640591.0689.0FRFrance
20131985093369895341109.0398681.0670618.0722.0FRFrance
20141985083389886359529.0420243.0707652.0762.0FRFrance
20151985073471852432599.0511105.0855784.0926.0FRFrance
20161985063565825518011.0613639.01026939.01113.0FRFrance
20171985053637302592795.0681809.011551074.01236.0FRFrance
20181985043424937390794.0459080.0770708.0832.0FRFrance
20191985033213901174689.0253113.0388317.0459.0FRFrance
202019850239758680949.0114223.0177147.0207.0FRFrance
202119850138548965918.0105060.0155120.0190.0FRFrance
202219845238483060602.0109058.0154110.0198.0FRFrance
2023198451310172680242.0123210.0185146.0224.0FRFrance
20241984503123680101401.0145959.0225184.0266.0FRFrance
2025198449310107381684.0120462.0184149.0219.0FRFrance
202619844837862060634.096606.0143110.0176.0FRFrance
202719844737202954274.089784.013199.0163.0FRFrance
202819844638733067686.0106974.0159123.0195.0FRFrance
20291984453135223101414.0169032.0246184.0308.0FRFrance
203019844436842220056.0116788.012537.0213.0FRFrance
\n", + "

2030 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202339 3 82112 70891.0 93333.0 124 107.0 \n", + "1 202338 3 63567 55525.0 71609.0 96 84.0 \n", + "2 202337 3 49085 42079.0 56091.0 74 63.0 \n", + "3 202336 3 38247 32237.0 44257.0 58 49.0 \n", + "4 202335 3 31695 26013.0 37377.0 48 39.0 \n", + "5 202334 3 26663 21057.0 32269.0 40 32.0 \n", + "6 202333 3 19144 13161.0 25127.0 29 20.0 \n", + "7 202332 3 14641 10285.0 18997.0 22 15.0 \n", + "8 202331 3 15286 10705.0 19867.0 23 16.0 \n", + "9 202330 3 13205 8647.0 17763.0 20 13.0 \n", + "10 202329 3 11122 7113.0 15131.0 17 11.0 \n", + "11 202328 3 9179 5703.0 12655.0 14 9.0 \n", + "12 202327 3 8999 5763.0 12235.0 14 9.0 \n", + "13 202326 3 9023 5934.0 12112.0 14 9.0 \n", + "14 202325 3 10090 6739.0 13441.0 15 10.0 \n", + "15 202324 3 11308 7639.0 14977.0 17 11.0 \n", + "16 202323 3 14300 10661.0 17939.0 22 17.0 \n", + "17 202322 3 18303 13822.0 22784.0 28 21.0 \n", + "18 202321 3 16460 12188.0 20732.0 25 19.0 \n", + "19 202320 3 16162 11963.0 20361.0 24 18.0 \n", + "20 202319 3 16901 12577.0 21225.0 25 18.0 \n", + "21 202318 3 19929 15402.0 24456.0 30 23.0 \n", + "22 202317 3 27007 21779.0 32235.0 41 33.0 \n", + "23 202316 3 27875 22767.0 32983.0 42 34.0 \n", + "24 202315 3 37455 30993.0 43917.0 56 46.0 \n", + "25 202314 3 48060 40671.0 55449.0 72 61.0 \n", + "26 202313 3 64859 56800.0 72918.0 98 86.0 \n", + "27 202312 3 72750 64499.0 81001.0 109 97.0 \n", + "28 202311 3 74638 66420.0 82856.0 112 100.0 \n", + "29 202310 3 76368 68243.0 84493.0 115 103.0 \n", + "... ... ... ... ... ... ... ... \n", + "2001 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "2002 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "2003 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "2004 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "2005 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "2006 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "2007 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "2008 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "2009 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "2010 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "2011 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "2012 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "2013 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "2014 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "2015 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "2016 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "2017 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "2018 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "2019 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "2020 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "2021 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "2022 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "2023 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "2024 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "2025 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "2026 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "2027 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "2028 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "2029 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "2030 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 141.0 FR France \n", + "1 108.0 FR France \n", + "2 85.0 FR France \n", + "3 67.0 FR France \n", + "4 57.0 FR France \n", + "5 48.0 FR France \n", + "6 38.0 FR France \n", + "7 29.0 FR France \n", + "8 30.0 FR France \n", + "9 27.0 FR France \n", + "10 23.0 FR France \n", + "11 19.0 FR France \n", + "12 19.0 FR France \n", + "13 19.0 FR France \n", + "14 20.0 FR France \n", + "15 23.0 FR France \n", + "16 27.0 FR France \n", + "17 35.0 FR France \n", + "18 31.0 FR France \n", + "19 30.0 FR France \n", + "20 32.0 FR France \n", + "21 37.0 FR France \n", + "22 49.0 FR France \n", + "23 50.0 FR France \n", + "24 66.0 FR France \n", + "25 83.0 FR France \n", + "26 110.0 FR France \n", + "27 121.0 FR France \n", + "28 124.0 FR France \n", + "29 127.0 FR France \n", + "... ... ... ... \n", + "2001 59.0 FR France \n", + "2002 64.0 FR France \n", + "2003 97.0 FR France \n", + "2004 93.0 FR France \n", + "2005 80.0 FR France \n", + "2006 116.0 FR France \n", + "2007 149.0 FR France \n", + "2008 281.0 FR France \n", + "2009 395.0 FR France \n", + "2010 485.0 FR France \n", + "2011 544.0 FR France \n", + "2012 689.0 FR France \n", + "2013 722.0 FR France \n", + "2014 762.0 FR France \n", + "2015 926.0 FR France \n", + "2016 1113.0 FR France \n", + "2017 1236.0 FR France \n", + "2018 832.0 FR France \n", + "2019 459.0 FR France \n", + "2020 207.0 FR France \n", + "2021 190.0 FR France \n", + "2022 198.0 FR France \n", + "2023 224.0 FR France \n", + "2024 266.0 FR France \n", + "2025 219.0 FR France \n", + "2026 176.0 FR France \n", + "2027 163.0 FR France \n", + "2028 195.0 FR France \n", + "2029 308.0 FR France \n", + "2030 213.0 FR France \n", + "\n", + "[2030 rows x 10 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -122,7 +2118,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -152,10 +2148,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" @@ -179,9 +2173,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n" + ] + } + ], "source": [ "periods = sorted_data.index\n", "for p1, p2 in zip(periods[:-1], periods[1:]):\n", @@ -199,9 +2201,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "TypeError", + "evalue": "Empty 'DataFrame': no numeric data to plot", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msorted_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'inc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)\u001b[0m\n\u001b[1;32m 2501\u001b[0m \u001b[0mcolormap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolormap\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2502\u001b[0m \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2503\u001b[0;31m **kwds)\n\u001b[0m\u001b[1;32m 2504\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplot_series\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2505\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36mplot_series\u001b[0;34m(data, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)\u001b[0m\n\u001b[1;32m 1925\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1926\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1927\u001b[0;31m **kwds)\n\u001b[0m\u001b[1;32m 1928\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1929\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m_plot\u001b[0;34m(data, x, y, subplots, ax, kind, **kwds)\u001b[0m\n\u001b[1;32m 1727\u001b[0m \u001b[0mplot_obj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mklass\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubplots\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1728\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1729\u001b[0;31m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1730\u001b[0m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1731\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36mgenerate\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 248\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mgenerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 249\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_args_adjust\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 250\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compute_plot_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 251\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setup_subplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 252\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_plot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m_compute_plot_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 363\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_empty\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 364\u001b[0m raise TypeError('Empty {0!r}: no numeric data to '\n\u001b[0;32m--> 365\u001b[0;31m 'plot'.format(numeric_data.__class__.__name__))\n\u001b[0m\u001b[1;32m 366\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 367\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumeric_data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mTypeError\u001b[0m: Empty 'DataFrame': no numeric data to plot" + ] + } + ], "source": [ "sorted_data['inc'].plot()" ] @@ -215,9 +2234,93 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'68422'" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_data['inc'][0]" + ] + }, + { + "cell_type": "code", + "execution_count": 17, "metadata": {}, "outputs": [], + "source": [ + "sorted_data['inc'] = sorted_data['inc'].astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
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4182691\n", + "1986 5115251\n", + "1990 5235827\n", + "1989 5466192\n", + "dtype: int64" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -331,9 +2503,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.hist(xrot=20)" ] @@ -364,7 +2559,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.1" + "version": "3.6.4" } }, "nbformat": 4, diff --git a/module3/exo2/co2_mm_mlo.txt b/module3/exo2/co2_mm_mlo.txt new file mode 100644 index 0000000000000000000000000000000000000000..bd409a50a962339fb01e1dcf6a7a4702224e25ff --- /dev/null +++ b/module3/exo2/co2_mm_mlo.txt @@ -0,0 +1,109 @@ +# -------------------------------------------------------------------- +# USE OF NOAA GML DATA +# +# These data are made freely available to the public and the scientific +# community in the belief that their wide dissemination will lead to +# greater understanding and new scientific insights. To ensure that GML +# receives fair credit for their work please include relevant citation +# text in publications. We encourage users to contact the data providers, +# who can provide detailed information about the measurements and +# scientific insight. In cases where the data are central to a +# publication, coauthorship for data providers may be appropriate. +# +# +# +# Contact Xin Lan (xin.lan@noaa.gov) +# +# File Creation Thu Oct 5 035533 2023 +# +# +# -------------------------------------------------------------------- +# +# +# See gml.noaa.govccggtrends for additional details. +# +# Data from March 1958 through April 1974 have been obtained by C. David Keeling +# of the Scripps Institution of Oceanography (SIO) and were obtained from the +# Scripps website (scrippsco2.ucsd.edu). +# +# The estimated uncertainty in the annual mean is the standard deviation +# of the differences of annual mean values determined independently by +# NOAAESRL and the Scripps Institution of Oceanography. +# +# NOTE In general, the data presented for the last year are subject to change, +# depending on recalibration of the reference gas mixtures used, and other quality +# control procedures. Occasionally, earlier years may also be changed for the same +# reasons. Usually these changes are minor. +# +# CO2 expressed as a mole fraction in dry air, micromolmol, abbreviated as ppm +# +# NOTE Due to the eruption of the Mauna Loa Volcano, measurements from Mauna Loa Observatory +# were suspended as of Nov. 29, 2022 and resumed in July 2023. +# Observations starting from December 2022 to July 4, 2023 are from a site at the +# Maunakea Observatories, approximately 21 miles north of the Mauna Loa Observatory. +# +# year mean unc + 1959 315.98 0.12 + 1960 316.91 0.12 + 1961 317.64 0.12 + 1962 318.45 0.12 + 1963 318.99 0.12 + 1964 319.62 0.12 + 1965 320.04 0.12 + 1966 321.37 0.12 + 1967 322.18 0.12 + 1968 323.05 0.12 + 1969 324.62 0.12 + 1970 325.68 0.12 + 1971 326.32 0.12 + 1972 327.46 0.12 + 1973 329.68 0.12 + 1974 330.19 0.12 + 1975 331.13 0.12 + 1976 332.03 0.12 + 1977 333.84 0.12 + 1978 335.41 0.12 + 1979 336.84 0.12 + 1980 338.76 0.12 + 1981 340.12 0.12 + 1982 341.48 0.12 + 1983 343.15 0.12 + 1984 344.87 0.12 + 1985 346.35 0.12 + 1986 347.61 0.12 + 1987 349.31 0.12 + 1988 351.69 0.12 + 1989 353.20 0.12 + 1990 354.45 0.12 + 1991 355.70 0.12 + 1992 356.54 0.12 + 1993 357.21 0.12 + 1994 358.96 0.12 + 1995 360.97 0.12 + 1996 362.74 0.12 + 1997 363.88 0.12 + 1998 366.84 0.12 + 1999 368.54 0.12 + 2000 369.71 0.12 + 2001 371.32 0.12 + 2002 373.45 0.12 + 2003 375.98 0.12 + 2004 377.70 0.12 + 2005 379.98 0.12 + 2006 382.09 0.12 + 2007 384.02 0.12 + 2008 385.83 0.12 + 2009 387.64 0.12 + 2010 390.10 0.12 + 2011 391.85 0.12 + 2012 394.06 0.12 + 2013 396.74 0.12 + 2014 398.81 0.12 + 2015 401.01 0.12 + 2016 404.41 0.12 + 2017 406.76 0.12 + 2018 408.72 0.12 + 2019 411.65 0.12 + 2020 414.21 0.12 + 2021 416.41 0.12 + 2022 418.53 0.12 \ No newline at end of file diff --git a/module3/exo2/module3-exo2.ipynb b/module3/exo2/module3-exo2.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..5f4f1571e27ce3dd388d48e447a5b9b0b8b1dfaf --- /dev/null +++ b/module3/exo2/module3-exo2.ipynb @@ -0,0 +1,2380 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import isoweek" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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32023367726101442102FRFrance
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52023347116892327204FRFrance
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920233075821326983739513FRFrance
10202329713558829718819201228FRFrance
11202328767004043935710614FRFrance
12202327772534599990711715FRFrance
1320232679192622312161141018FRFrance
14202325711498825714739171222FRFrance
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192023207900046151338514721FRFrance
202023197934460911259714919FRFrance
21202318710671729114051161121FRFrance
222023177918461621220614919FRFrance
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24202315714040761320467211131FRFrance
252023147152471103219462231729FRFrance
26202313713322970016944201525FRFrance
27202312710374721813530161121FRFrance
2820231174919288069587410FRFrance
2920231074854273169777410FRFrance
.................................
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1713 rows × 10 columns

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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202339 7 1390 118 2662 2 0 \n", + "1 202338 7 1670 278 3062 3 1 \n", + "2 202337 7 1122 223 2021 2 1 \n", + "3 202336 7 726 10 1442 1 0 \n", + "4 202335 7 961 96 1826 1 0 \n", + "5 202334 7 1168 9 2327 2 0 \n", + "6 202333 7 3308 1184 5432 5 2 \n", + "7 202332 7 7996 1120 14872 12 2 \n", + "8 202331 7 3318 1398 5238 5 2 \n", + "9 202330 7 5821 3269 8373 9 5 \n", + "10 202329 7 13558 8297 18819 20 12 \n", + "11 202328 7 6700 4043 9357 10 6 \n", + "12 202327 7 7253 4599 9907 11 7 \n", + "13 202326 7 9192 6223 12161 14 10 \n", + "14 202325 7 11498 8257 14739 17 12 \n", + "15 202324 7 11115 7968 14262 17 12 \n", + "16 202323 7 12563 6134 18992 19 9 \n", + "17 202322 7 12184 8125 16243 18 12 \n", + "18 202321 7 11349 7598 15100 17 11 \n", + "19 202320 7 9000 4615 13385 14 7 \n", + "20 202319 7 9344 6091 12597 14 9 \n", + "21 202318 7 10671 7291 14051 16 11 \n", + "22 202317 7 9184 6162 12206 14 9 \n", + "23 202316 7 11387 8014 14760 17 12 \n", + "24 202315 7 14040 7613 20467 21 11 \n", + "25 202314 7 15247 11032 19462 23 17 \n", + "26 202313 7 13322 9700 16944 20 15 \n", + "27 202312 7 10374 7218 13530 16 11 \n", + "28 202311 7 4919 2880 6958 7 4 \n", + "29 202310 7 4854 2731 6977 7 4 \n", + "... ... ... ... ... ... ... ... \n", + "1683 199126 7 17608 11304 23912 31 20 \n", + "1684 199125 7 16169 10700 21638 28 18 \n", + "1685 199124 7 16171 10071 22271 28 17 \n", + "1686 199123 7 11947 7671 16223 21 13 \n", + "1687 199122 7 15452 9953 20951 27 17 \n", + "1688 199121 7 14903 8975 20831 26 16 \n", + "1689 199120 7 19053 12742 25364 34 23 \n", + "1690 199119 7 16739 11246 22232 29 19 \n", + "1691 199118 7 21385 13882 28888 38 25 \n", + "1692 199117 7 13462 8877 18047 24 16 \n", + "1693 199116 7 14857 10068 19646 26 18 \n", + "1694 199115 7 13975 9781 18169 25 18 \n", + "1695 199114 7 12265 7684 16846 22 14 \n", + "1696 199113 7 9567 6041 13093 17 11 \n", + "1697 199112 7 10864 7331 14397 19 13 \n", + "1698 199111 7 15574 11184 19964 27 19 \n", + "1699 199110 7 16643 11372 21914 29 20 \n", + "1700 199109 7 13741 8780 18702 24 15 \n", + "1701 199108 7 13289 8813 17765 23 15 \n", + "1702 199107 7 12337 8077 16597 22 15 \n", + "1703 199106 7 10877 7013 14741 19 12 \n", + "1704 199105 7 10442 6544 14340 18 11 \n", + "1705 199104 7 7913 4563 11263 14 8 \n", + "1706 199103 7 15387 10484 20290 27 18 \n", + "1707 199102 7 16277 11046 21508 29 20 \n", + "1708 199101 7 15565 10271 20859 27 18 \n", + "1709 199052 7 19375 13295 25455 34 23 \n", + "1710 199051 7 19080 13807 24353 34 25 \n", + "1711 199050 7 11079 6660 15498 20 12 \n", + "1712 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 4 FR France \n", + "1 5 FR France \n", + "2 3 FR France \n", + "3 2 FR France \n", + "4 2 FR France \n", + "5 4 FR France \n", + "6 8 FR France \n", + "7 22 FR France \n", + "8 8 FR France \n", + "9 13 FR France \n", + "10 28 FR France \n", + "11 14 FR France \n", + "12 15 FR France \n", + "13 18 FR France \n", + "14 22 FR France \n", + "15 22 FR France \n", + "16 29 FR France \n", + "17 24 FR France \n", + "18 23 FR France \n", + "19 21 FR France \n", + "20 19 FR France \n", + "21 21 FR France \n", + "22 19 FR France \n", + "23 22 FR France \n", + "24 31 FR France \n", + "25 29 FR France \n", + "26 25 FR France \n", + "27 21 FR France \n", + "28 10 FR France \n", + "29 10 FR France \n", + "... ... ... ... \n", + "1683 42 FR France \n", + "1684 38 FR France \n", + "1685 39 FR France \n", + "1686 29 FR France \n", + "1687 37 FR France \n", + "1688 36 FR France \n", + "1689 45 FR France \n", + "1690 39 FR France \n", + "1691 51 FR France \n", + "1692 32 FR France \n", + "1693 34 FR France \n", + "1694 32 FR France \n", + "1695 30 FR France \n", + "1696 23 FR France \n", + "1697 25 FR France \n", + "1698 35 FR France \n", + "1699 38 FR France \n", + "1700 33 FR France \n", + "1701 31 FR France \n", + "1702 29 FR France \n", + "1703 26 FR France \n", + "1704 25 FR France \n", + "1705 20 FR France \n", + "1706 36 FR France \n", + "1707 38 FR France \n", + "1708 36 FR France \n", + "1709 45 FR France \n", + "1710 43 FR France \n", + "1711 28 FR France \n", + "1712 5 FR France \n", + "\n", + "[1713 rows x 10 columns]" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = raw_data.dropna().copy()\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + " def convert_week(year_and_week_int):\n", + " year_and_week_str = str(year_and_week_int)\n", + " year = int(year_and_week_str[:4])\n", + " week = int(year_and_week_str[4:])\n", + " w = isoweek.Week(year, week)\n", + " return pd.Period(w.day(0), 'W')\n", + "\n", + "data['period'] = [convert_week(yw) for yw in data['week']]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + " sorted_data = data.set_index('period').sort_index()\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "periods = sorted_data.index\n", + "for p1, p2 in zip(periods[:-1], periods[1:]):\n", + " delta = p2.to_timestamp() - p1.end_time\n", + " if delta > pd.Timedelta('1s'):\n", + " print(p1, p2)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sorted_data['inc'][-200:].plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + " first_august_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", + " for y in range(1991,\n", + " sorted_data.index[-1].year)]" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "year = []\n", + "yearly_incidence = []\n", + "for week1, week2 in zip(first_august_week[:-1],\n", + " first_august_week[1:]):\n", + " one_year = sorted_data['inc'][week1:week2-1]\n", + " assert abs(len(one_year)-52) < 2\n", + " yearly_incidence.append(one_year.sum())\n", + " year.append(week2.year)\n", + "yearly_incidence = pd.Series(data=yearly_incidence, index=year)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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To ensure that GML +# receives fair credit for their work please include relevant citation +# text in publications. We encourage users to contact the data providers, +# who can provide detailed information about the measurements and +# scientific insight. In cases where the data are central to a +# publication, coauthorship for data providers may be appropriate. +# +# +# +# Contact: Xin Lan (xin.lan@noaa.gov) +# +# File Creation: Thu Oct 5 03:55:33 2023 +# +# +# -------------------------------------------------------------------- +# +# +# See gml.noaa.gov/ccgg/trends/ for additional details. +# +# Data from March 1958 through April 1974 have been obtained by C. David Keeling +# of the Scripps Institution of Oceanography (SIO) and were obtained from the +# Scripps website (scrippsco2.ucsd.edu). +# +# The estimated uncertainty in the annual mean is the standard deviation +# of the differences of annual mean values determined independently by +# NOAA/ESRL and the Scripps Institution of Oceanography. +# +# NOTE: In general, the data presented for the last year are subject to change, +# depending on recalibration of the reference gas mixtures used, and other quality +# control procedures. Occasionally, earlier years may also be changed for the same +# reasons. Usually these changes are minor. +# +# CO2 expressed as a mole fraction in dry air, micromol/mol, abbreviated as ppm +# +# NOTE: Due to the eruption of the Mauna Loa Volcano, measurements from Mauna Loa Observatory +# were suspended as of Nov. 29, 2022 and resumed in July 2023. +# Observations starting from December 2022 to July 4, 2023 are from a site at the +# Maunakea Observatories, approximately 21 miles north of the Mauna Loa Observatory. +year,mean,unc +1959,315.98,0.12 +1960,316.91,0.12 +1961,317.64,0.12 +1962,318.45,0.12 +1963,318.99,0.12 +1964,319.62,0.12 +1965,320.04,0.12 +1966,321.37,0.12 +1967,322.18,0.12 +1968,323.05,0.12 +1969,324.62,0.12 +1970,325.68,0.12 +1971,326.32,0.12 +1972,327.46,0.12 +1973,329.68,0.12 +1974,330.19,0.12 +1975,331.13,0.12 +1976,332.03,0.12 +1977,333.84,0.12 +1978,335.41,0.12 +1979,336.84,0.12 +1980,338.76,0.12 +1981,340.12,0.12 +1982,341.48,0.12 +1983,343.15,0.12 +1984,344.87,0.12 +1985,346.35,0.12 +1986,347.61,0.12 +1987,349.31,0.12 +1988,351.69,0.12 +1989,353.20,0.12 +1990,354.45,0.12 +1991,355.70,0.12 +1992,356.54,0.12 +1993,357.21,0.12 +1994,358.96,0.12 +1995,360.97,0.12 +1996,362.74,0.12 +1997,363.88,0.12 +1998,366.84,0.12 +1999,368.54,0.12 +2000,369.71,0.12 +2001,371.32,0.12 +2002,373.45,0.12 +2003,375.98,0.12 +2004,377.70,0.12 +2005,379.98,0.12 +2006,382.09,0.12 +2007,384.02,0.12 +2008,385.83,0.12 +2009,387.64,0.12 +2010,390.10,0.12 +2011,391.85,0.12 +2012,394.06,0.12 +2013,396.74,0.12 +2014,398.81,0.12 +2015,401.01,0.12 +2016,404.41,0.12 +2017,406.76,0.12 +2018,408.72,0.12 +2019,411.65,0.12 +2020,414.21,0.12 +2021,416.41,0.12 +2022,418.53,0.12 diff --git a/module3/exo3/co2_mm_mlo.txt b/module3/exo3/co2_mm_mlo.txt new file mode 100644 index 0000000000000000000000000000000000000000..4d5fe209e8909ba600cfa21a9e8b14d627b88f54 --- /dev/null +++ b/module3/exo3/co2_mm_mlo.txt @@ -0,0 +1,109 @@ +# -------------------------------------------------------------------- +# USE OF NOAA GML DATA +# +# These data are made freely available to the public and the scientific +# community in the belief that their wide dissemination will lead to +# greater understanding and new scientific insights. To ensure that GML +# receives fair credit for their work please include relevant citation +# text in publications. We encourage users to contact the data providers, +# who can provide detailed information about the measurements and +# scientific insight. In cases where the data are central to a +# publication, coauthorship for data providers may be appropriate. +# +# +# +# Contact Xin Lan (xin.lan@noaa.gov) +# +# File Creation Thu Oct 5 035533 2023 +# +# +# -------------------------------------------------------------------- +# +# +# See gml.noaa.govccggtrends for additional details. +# +# Data from March 1958 through April 1974 have been obtained by C. David Keeling +# of the Scripps Institution of Oceanography (SIO) and were obtained from the +# Scripps website (scrippsco2.ucsd.edu). +# +# The estimated uncertainty in the annual mean is the standard deviation +# of the differences of annual mean values determined independently by +# NOAAESRL and the Scripps Institution of Oceanography. +# +# NOTE In general, the data presented for the last year are subject to change, +# depending on recalibration of the reference gas mixtures used, and other quality +# control procedures. Occasionally, earlier years may also be changed for the same +# reasons. Usually these changes are minor. +# +# CO2 expressed as a mole fraction in dry air, micromolmol, abbreviated as ppm +# +# NOTE Due to the eruption of the Mauna Loa Volcano, measurements from Mauna Loa Observatory +# were suspended as of Nov. 29, 2022 and resumed in July 2023. +# Observations starting from December 2022 to July 4, 2023 are from a site at the +# Maunakea Observatories, approximately 21 miles north of the Mauna Loa Observatory. +# + year mean unc + 1959 315.98 0.12 + 1960 316.91 0.12 + 1961 317.64 0.12 + 1962 318.45 0.12 + 1963 318.99 0.12 + 1964 319.62 0.12 + 1965 320.04 0.12 + 1966 321.37 0.12 + 1967 322.18 0.12 + 1968 323.05 0.12 + 1969 324.62 0.12 + 1970 325.68 0.12 + 1971 326.32 0.12 + 1972 327.46 0.12 + 1973 329.68 0.12 + 1974 330.19 0.12 + 1975 331.13 0.12 + 1976 332.03 0.12 + 1977 333.84 0.12 + 1978 335.41 0.12 + 1979 336.84 0.12 + 1980 338.76 0.12 + 1981 340.12 0.12 + 1982 341.48 0.12 + 1983 343.15 0.12 + 1984 344.87 0.12 + 1985 346.35 0.12 + 1986 347.61 0.12 + 1987 349.31 0.12 + 1988 351.69 0.12 + 1989 353.20 0.12 + 1990 354.45 0.12 + 1991 355.70 0.12 + 1992 356.54 0.12 + 1993 357.21 0.12 + 1994 358.96 0.12 + 1995 360.97 0.12 + 1996 362.74 0.12 + 1997 363.88 0.12 + 1998 366.84 0.12 + 1999 368.54 0.12 + 2000 369.71 0.12 + 2001 371.32 0.12 + 2002 373.45 0.12 + 2003 375.98 0.12 + 2004 377.70 0.12 + 2005 379.98 0.12 + 2006 382.09 0.12 + 2007 384.02 0.12 + 2008 385.83 0.12 + 2009 387.64 0.12 + 2010 390.10 0.12 + 2011 391.85 0.12 + 2012 394.06 0.12 + 2013 396.74 0.12 + 2014 398.81 0.12 + 2015 401.01 0.12 + 2016 404.41 0.12 + 2017 406.76 0.12 + 2018 408.72 0.12 + 2019 411.65 0.12 + 2020 414.21 0.12 + 2021 416.41 0.12 + 2022 418.53 0.12 \ No newline at end of file diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb index 0bbbe371b01e359e381e43239412d77bf53fb1fb..5d045800a061dcc36cd9826e4e9904d2eb2bb4b4 100644 --- a/module3/exo3/exercice.ipynb +++ b/module3/exo3/exercice.ipynb @@ -1,5 +1,215 @@ { - "cells": [], + "cells": [ + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# methode 1 c'est on utilison les donné extre directement du site " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Chargement et traitement des données\n", + "Chargeons les données et préparons-les pour l'analyse. Les données sont stockées dans un fichier texte avec des colonnes séparées par des espaces. Nous allons extraire les années et les concentrations de CO2.\n", + "methode 1 c'est on utilison les donné extre directement du site " + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1959., 1960., 1961., 1962., 1963., 1964., 1965., 1966., 1967.,\n", + " 1968., 1969., 1970., 1971., 1972., 1973., 1974., 1975., 1976.,\n", + " 1977., 1978., 1979., 1980., 1981., 1982., 1983., 1984., 1985.,\n", + " 1986., 1987., 1988., 1989., 1990., 1991., 1992., 1993., 1994.,\n", + " 1995., 1996., 1997., 1998., 1999., 2000., 2001., 2002., 2003.,\n", + " 2004., 2005., 2006., 2007., 2008., 2009., 2010., 2011., 2012.,\n", + " 2013., 2014., 2015., 2016., 2017., 2018., 2019., 2020., 2021.,\n", + " 2022.])" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Charger les données depuis le fichier texte\n", + "data = np.genfromtxt('https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_annmean_mlo.txt', skip_header=43)\n", + "\n", + "# Extraire les années et les concentrations de CO2\n", + "years = data[:, 0]\n", + "co2_concentration = data[:, 1]\n", + "years" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([315.98, 316.91, 317.64, 318.45, 318.99, 319.62, 320.04, 321.37,\n", + " 322.18, 323.05, 324.62, 325.68, 326.32, 327.46, 329.68, 330.19,\n", + " 331.13, 332.03, 333.84, 335.41, 336.84, 338.76, 340.12, 341.48,\n", + " 343.15, 344.87, 346.35, 347.61, 349.31, 351.69, 353.2 , 354.45,\n", + " 355.7 , 356.54, 357.21, 358.96, 360.97, 362.74, 363.88, 366.84,\n", + " 368.54, 369.71, 371.32, 373.45, 375.98, 377.7 , 379.98, 382.09,\n", + " 384.02, 385.83, 387.64, 390.1 , 391.85, 394.06, 396.74, 398.81,\n", + " 401.01, 404.41, 406.76, 408.72, 411.65, 414.21, 416.41, 418.53])" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "co2_concentration" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Methode 2: la en telechargent le document en txt dans l'espace jupyter" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ nan, 1959., 1960., 1961., 1962., 1963., 1964., 1965., 1966.,\n", + " 1967., 1968., 1969., 1970., 1971., 1972., 1973., 1974., 1975.,\n", + " 1976., 1977., 1978., 1979., 1980., 1981., 1982., 1983., 1984.,\n", + " 1985., 1986., 1987., 1988., 1989., 1990., 1991., 1992., 1993.,\n", + " 1994., 1995., 1996., 1997., 1998., 1999., 2000., 2001., 2002.,\n", + " 2003., 2004., 2005., 2006., 2007., 2008., 2009., 2010., 2011.,\n", + " 2012., 2013., 2014., 2015., 2016., 2017., 2018., 2019., 2020.,\n", + " 2021., 2022.])" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Charger les données depuis le fichier texte\n", + "data = np.genfromtxt('co2_mm_mlo.txt', skip_header=43)\n", + "\n", + "# Extraire les années et les concentrations de CO2\n", + "years = data[:, 0]\n", + "co2_concentration = data[:, 1]\n", + "years" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ nan, 315.98, 316.91, 317.64, 318.45, 318.99, 319.62, 320.04,\n", + " 321.37, 322.18, 323.05, 324.62, 325.68, 326.32, 327.46, 329.68,\n", + " 330.19, 331.13, 332.03, 333.84, 335.41, 336.84, 338.76, 340.12,\n", + " 341.48, 343.15, 344.87, 346.35, 347.61, 349.31, 351.69, 353.2 ,\n", + " 354.45, 355.7 , 356.54, 357.21, 358.96, 360.97, 362.74, 363.88,\n", + " 366.84, 368.54, 369.71, 371.32, 373.45, 375.98, 377.7 , 379.98,\n", + " 382.09, 384.02, 385.83, 387.64, 390.1 , 391.85, 394.06, 396.74,\n", + " 398.81, 401.01, 404.41, 406.76, 408.72, 411.65, 414.21, 416.41,\n", + " 418.53])" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "co2_concentration" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Visualisation des données\n", + "Créons un graphique pour visualiser l'évolution de la concentration de CO2 dans l'atmosphère au fil des années." + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Créer un graphique\n", + "plt.figure(figsize=(10, 6))\n", + "plt.plot(years, co2_concentration, label='Concentration de CO2')\n", + "plt.xlabel('Année')\n", + "plt.ylabel('Concentration de CO2 (ppm)')\n", + "plt.title('Évolution de la Concentration de CO2 dans l\\'Atmosphère depuis 195')\n", + "plt.grid(True)\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Conclusion\n", + "L'analyse des données montre clairement l'augmentation de la concentration de CO2 dans l'atmosphère depuis 1959. Cette augmentation continue est une préoccupation majeure en matière de changement climatique. Il est essentiel de prendre des mesures pour réduire ces émissions de CO2 afin de lutter contre le réchauffement climatique.\n", + "\n", + "Ce document computationnel a permis de visualiser de manière informative l'évolution de la concentration de CO2 dans l'atmosphère au fil du temps. Il est crucial de continuer à surveiller ces données pour mieux comprendre l'impact du CO2 sur notre climat." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], "metadata": { "kernelspec": { "display_name": "Python 3", @@ -16,10 +226,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.3" + "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 } - diff --git a/module3/exo3/gml.noaa.gov/webdata/ccgg/trends/co2/co2_annmean_mlo.txt b/module3/exo3/gml.noaa.gov/webdata/ccgg/trends/co2/co2_annmean_mlo.txt new file mode 100644 index 0000000000000000000000000000000000000000..a879a8b094ac78af46455cca52e445141f62df43 --- /dev/null +++ b/module3/exo3/gml.noaa.gov/webdata/ccgg/trends/co2/co2_annmean_mlo.txt @@ -0,0 +1,109 @@ +# -------------------------------------------------------------------- +# USE OF NOAA GML DATA +# +# These data are made freely available to the public and the scientific +# community in the belief that their wide dissemination will lead to +# greater understanding and new scientific insights. To ensure that GML +# receives fair credit for their work please include relevant citation +# text in publications. We encourage users to contact the data providers, +# who can provide detailed information about the measurements and +# scientific insight. In cases where the data are central to a +# publication, coauthorship for data providers may be appropriate. +# +# +# +# Contact: Xin Lan (xin.lan@noaa.gov) +# +# File Creation: Thu Oct 5 03:55:33 2023 +# +# +# -------------------------------------------------------------------- +# +# +# See gml.noaa.gov/ccgg/trends/ for additional details. +# +# Data from March 1958 through April 1974 have been obtained by C. David Keeling +# of the Scripps Institution of Oceanography (SIO) and were obtained from the +# Scripps website (scrippsco2.ucsd.edu). +# +# The estimated uncertainty in the annual mean is the standard deviation +# of the differences of annual mean values determined independently by +# NOAA/ESRL and the Scripps Institution of Oceanography. +# +# NOTE: In general, the data presented for the last year are subject to change, +# depending on recalibration of the reference gas mixtures used, and other quality +# control procedures. Occasionally, earlier years may also be changed for the same +# reasons. Usually these changes are minor. +# +# CO2 expressed as a mole fraction in dry air, micromol/mol, abbreviated as ppm +# +# NOTE: Due to the eruption of the Mauna Loa Volcano, measurements from Mauna Loa Observatory +# were suspended as of Nov. 29, 2022 and resumed in July 2023. +# Observations starting from December 2022 to July 4, 2023 are from a site at the +# Maunakea Observatories, approximately 21 miles north of the Mauna Loa Observatory. +# +# year mean unc + 1959 315.98 0.12 + 1960 316.91 0.12 + 1961 317.64 0.12 + 1962 318.45 0.12 + 1963 318.99 0.12 + 1964 319.62 0.12 + 1965 320.04 0.12 + 1966 321.37 0.12 + 1967 322.18 0.12 + 1968 323.05 0.12 + 1969 324.62 0.12 + 1970 325.68 0.12 + 1971 326.32 0.12 + 1972 327.46 0.12 + 1973 329.68 0.12 + 1974 330.19 0.12 + 1975 331.13 0.12 + 1976 332.03 0.12 + 1977 333.84 0.12 + 1978 335.41 0.12 + 1979 336.84 0.12 + 1980 338.76 0.12 + 1981 340.12 0.12 + 1982 341.48 0.12 + 1983 343.15 0.12 + 1984 344.87 0.12 + 1985 346.35 0.12 + 1986 347.61 0.12 + 1987 349.31 0.12 + 1988 351.69 0.12 + 1989 353.20 0.12 + 1990 354.45 0.12 + 1991 355.70 0.12 + 1992 356.54 0.12 + 1993 357.21 0.12 + 1994 358.96 0.12 + 1995 360.97 0.12 + 1996 362.74 0.12 + 1997 363.88 0.12 + 1998 366.84 0.12 + 1999 368.54 0.12 + 2000 369.71 0.12 + 2001 371.32 0.12 + 2002 373.45 0.12 + 2003 375.98 0.12 + 2004 377.70 0.12 + 2005 379.98 0.12 + 2006 382.09 0.12 + 2007 384.02 0.12 + 2008 385.83 0.12 + 2009 387.64 0.12 + 2010 390.10 0.12 + 2011 391.85 0.12 + 2012 394.06 0.12 + 2013 396.74 0.12 + 2014 398.81 0.12 + 2015 401.01 0.12 + 2016 404.41 0.12 + 2017 406.76 0.12 + 2018 408.72 0.12 + 2019 411.65 0.12 + 2020 414.21 0.12 + 2021 416.41 0.12 + 2022 418.53 0.12