{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "Analýza Gaussovy křivky\n", "-----------------\n", "nalezení středu rozdělení (předpoklad normálnosti) s odhadem nejistot\n", "\n", "předpokládáme profil histogramu BEZ POZADÍ \n", "$$D \\exp(-(x-\\mu)^2/(2\\sigma^2)),$$ po zlogaritmování dostáváme polynom 2. řádu\n", "\n", "$$\\log D -\\mu^2/(2\\sigma^2) + x \\mu/\\sigma^2 - x^2 /(2\\sigma^2)$$" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "pro nafitování polynomem $\\sum_{i=0}^2 p_i x^i$ dostaneme pro parametry gausovky\n", "\n", "$$\\sigma^2=-\\frac{1}{2 p_2} \\\\\n", "\\mu=-\\frac{p_1}{2 p_2} \\\\\n", "\\log D = p_0 + \\frac{p_1^2}{4 p_2}$$\n", "\n", "Problémem polynomu v zákl. tvaru jsou silné korelace mezi parametry $p_i$. \n", "Otázka korelace je řešena ortogonalizací polynomů, viz ." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "#### nalezení ortonormálních polynomů \n", "\n", "ortogonalizace na intervalu <-1,1>\n", "\n", "$$\\int_{-1}^1{g_i(x) g_j(x) d x} = \\delta_{ij}$$\n", "(6 rovnic) \n", "dá renorm. Legendrovy polynomy\n", "\n", "$$g_0=\\sqrt{1/2} \\\\\n", "g_1=\\sqrt{3/2}x \\\\\n", "g_2=\\sqrt{5/8} (3x^2-1)$$\n", "\n", "Pozn.: někdy uváděná dodatečná normaliz. podmínka\n", "$$\\int_{-1}^1{g_i(x) d x} = 0$$ vyplyne z předchozího pro $j>0$, pokud $g_0=\\rm{const}$ ." ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "collapsed": false, "slideshow": { "slide_type": "skip" } }, "outputs": [], "source": [ "%matplotlib inline\n", "from matplotlib.pyplot import *\n", "import matplotlib\n", "matplotlib.rcParams['figure.figsize'] = [10, 5]\n", "import numpy as np\n", "a,b=[2,4.]\n", "y=np.r_[a:b:41j]\n", "x=2*y/(b-a) - (a+b)/(b-a)\n", "def mat_Leg(x):\n", " g_0=np.sqrt(1/2.)*ones(x.shape)\n", " g_1=np.sqrt(3/2.)*x\n", " g_2=np.sqrt(5/8.)*(3*x**2-1)\n", " return r_[[g_0,g_1,g_2]]" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "aplikace na lib. interval $(a,b)$ lze provést transformací $y=(a+b)/2 + x (b-a)/2$, resp. dosazením $x=2y/(b-a) - (a+b)/(b-a) = y c - d$:\n", "$$h_1 = \\sqrt{3/2} (yc-d)\\\\\n", "h_2 = \\sqrt{5/8} (3c y^2 - 6cd y +3d^2-1) $$" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "Najdeme-li (téměř) nekorelované koeficienty $k_i$ pro polynomy $h_i(x)$, koeficienty pro počáteč. polynomy $x^i$ dostaneme maticovými operacemi, kdy zavedeme\n", "\n", "$$g_i(x)=\\sum_j G_{ij} x^j$$ kde\n", "\n", "$$G_{ij}=\\left( \\begin{array}{ccc} \\sqrt{1/2} & 0 & 0 \\\\\n", "0 & \\sqrt{3/2} & 0 \\\\\n", "-\\sqrt{5/8} & 0 & \\sqrt{45/8}\\end{array}\\right)$$\n", "\n", "$$h_i(y)=\\sum_j G_{ij} (cy-d)^j = \\sum_j H_{ij} y^j= \\sum_j \\sum_k T_{ik} G_{kj} y^j$$." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Prvky matice $T_{ij}$ vycházejí z kombin. čísel, potom model logaritmu fitované gausovky vychází\n", "$f(y) = \\sum_i k_i h_i(y)= \\sum_i k_i \\sum_j \\sum_k T_{ik} G_{kj} y^j$, tedy koeficienty $p_j$ dostaneme jako \n", "$$p_j= \\sum_k \\sum_i k_i T_{ik} G_{kj}$$." ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# v maticovem zapisu je to jednodussi\n", "matG=np.sqrt(np.r_[[[0.5,0,0],[0,1.5,0],[5/8.,0,45/8.]]])\n", "matG[2][0]*=-1\n", "mat_poly2=lambda x:np.r_[[x**i for i in range(3)]] #obyčejné mocniny\n", "mat_Leg2=lambda x:np.dot(matG,mat_poly2(x)) #Legendrovy polynomy - alternativa k mat_Leg\n", "[plot(y,a) for a in mat_Leg2(x)]\n", "title(\"prvni tri Legendrovy polynomy\")\n", "grid()" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([[ 1., 0., 0.],\n", " [-3., 1., 0.],\n", " [ 9., -6., 1.]])" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from numpy.random import normal\n", "from numpy import r_,array,ones\n", "# transformacni matice polynomu pri presunu intervalu\n", "def mat_trans(c,d,n=2):\n", " rep=[[1]+[0]*n]\n", " from scipy.special import comb\n", " clin=c**r_[:n+1]\n", " dlin=d**r_[n:-1:-1]\n", " for i in range(1,n+1):\n", " #lin=[factorial(i)/factorial(j)/factorial(i-j)*(c**j)*(d**(i-j)) for j in range(i)]\n", " lin=comb(ones(i+1)*i,r_[:i+1])*clin[:i+1]*dlin[-i-1:]\n", " rep.append(list(lin)+[0]*(n-i))\n", " return array(rep)\n", "a,b=2,4\n", "F=mat_trans(2/(b-a),-(b+a)/(b-a),2)\n", "F\n" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Simulace - normálně rozděl. data a rekonstrukce\n", "\n", "funkce `pokus` vrací rekonstruované parametry, kovarianční matici, střední hodnotu a směrod. odchylku, ev. i hodnoty histogramu" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# generovani normalne rozdel. nahodnych cisel\n", "from numpy import histogram,dot,log,exp,polyfit,polyval,sqrt\n", "from numpy.linalg import inv\n", "def pokus(dsize=500,a=2,b=4,step=0.05,full=0):\n", " data=normal((a+b)/2.,(b-a)/4.,size=dsize) # interval pokryje -2sigma - +2sigma\n", " z=r_[(a-step/2):(b+step/2):step]\n", " x=2*z/(b-a) - (a+b)/(b-a)\n", " A=mat_Leg2((x[1:]+x[:-1])/2)\n", " #print A.shape\n", " v,z=histogram(data,z)\n", " H=dot(A,A.transpose())\n", " D=inv(H)\n", " res=dot(D,dot(A,log(v)))\n", " if full==3: return res,D,data.mean(),data.std(),v,z\n", " if full==2: return res,D,data.mean(),data.std()\n", " if full==1: return res,D\n", " return res" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([[1. , 0.08693164, 0.01120797],\n", " [0.08693164, 1. , 0.19104018],\n", " [0.01120797, 0.19104018, 1. ]])" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from numpy import corrcoef\n", "res,D,mu,st,v,z=pokus(dsize=500,full=3,step=0.1)\n", "polres,polcov=polyfit((z[:-1]+z[1:])/2.,log(v),2,cov=True) # alternativne normalni polynomialni fit\n", "err=np.sqrt(D.diagonal())\n", "R=D/err[:,np.newaxis]/err[np.newaxis,:]\n", "R #korelacni matice ortogonaliz. polynomu" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([[ 1. , -0.99514148, 0.98339914],\n", " [-0.99514148, 1. , -0.99622942],\n", " [ 0.98339914, -0.99622942, 1. ]])" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "polerr=np.sqrt(polcov[::-1,::-1].diagonal())\n", "polcorr=polcov[::-1,::-1]/polerr[:,np.newaxis]/polerr[np.newaxis,:]\n", "polcorr\n", "#polerr/polres[::-1]" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "0.2316147791773176" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rsid=((np.polyval(polres,(z[:-1]+z[1:])/2.)-log(v))**2).sum()\n", "sig=np.sqrt(rsid/(len(z)-1-3))\n", "sig" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([ 0.01727503, -2.71395582, -0.08797732])" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "err/res*sig" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### aplikace Legendrovych polynomu" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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A+ecnv69TRCQZ9tvPL8Wtbo/EUqCQqHzxhV9LX90dIpLOcnJg5ky/kJYkhgKF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\nYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from scipy import stats\n", "xs=r_[2:4:0.1]\n", "y=stats.norm(3,1).pdf(xs)+stats.norm(0,0.01).rvs(size=len(xs))\n", "plot(xs,y)\n", "A=mat_Leg2(2*xs/(b-a) - (a+b)/(b-a))\n", "D=inv(A.dot(A.T))\n", "#ted analyzu 500x zopakujeme\n", "rall=array([A.dot(log(stats.norm(3,1).pdf(xs)+stats.norm(0,0.01).rvs(size=len(xs)))) for i in range(500)])" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(-0.086801991223572864, 0.2190241521981868, -0.24733020472468203)" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "corrcoef(rall[:,0],rall[:,1])[1,0],corrcoef(rall[:,0],rall[:,2])[1,0],corrcoef(rall[:,1],rall[:,2])[1,0]" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([ 0.09349273, 0.10337155, 0.10909491])" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rall.std(0) #smerod. odchylka jednotlivych parametru" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5,1,'Legendr. polynomy vyssich radu')" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from numpy.polynomial import legendre as pc\n", "\n", "x=np.r_[-1:1:0.01]\n", "[plot(x,pc.Legendre([0]*i+[1])(x)) for i in range(2,7)]\n", "legend(range(2,7))\n", "title(\"Legendr. polynomy vyssich radu\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### rekapitulace" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "fit Legend. polynomy (po transformaci): [-16.78698427 13.65041352 -2.27028983]\n", "fit mocninami: [-16.78698427 13.65041352 -2.27028983]\n", "korelační matice.. \n", " [[1. 0.08693164 0.01120797]\n", " [0.08693164 1. 0.19104018]\n", " [0.01120797 0.19104018 1. ]]\n", "korelační matice..(po transformaci) \n", " [[1. 0.98560734 0.95097407]\n", " [0.98560734 1. 0.98734087]\n", " [0.95097407 0.98734087 1. ]]\n" ] }, { "data": { "text/plain": [ "array([[ 1. , -0.99514148, 0.98339914],\n", " [-0.99514148, 1. , -0.99622942],\n", " [ 0.98339914, -0.99622942, 1. ]])" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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iZTZf2kfFHV3ZfeUYCwq/TYfstZyOJB4mb1B2Vhf7kEaZH+D1w2PoePBTYmys07FEUi2VKREvsvT8Jh7a2QOLZU2xD6mlXTRyh0L8g5lesDu9wpox6tRSWu4bTKyNczqWSKqkMiXiJcacXEqd3e9RME0Y64oPomy6gk5HEg/nZ/zol6c1Q/O0Y8bZtbTd/zFxKlQi/6ID0EU8nLWWt49OpN+xadTMeC/TCnYno386p2OJF3k9rCGX7VV6RXxDsF8go8Jf1jF4ItdQmRLxYNZaXj38JSNOLOT5bDX4NPwFAo1e1pL0euZsxuX4GPocm0KwCWJEvo66DJGIi951RTyUtZaeEeMZcWIhXXI0YlCeZ/XhJsmqd66nuGyvMvD4LNL4BTIkz3P6NyeCypSIx+p/bDoDjs/khey1VKQkRRhj+DB3Wy7Hx/BR5FyCTSD9crfWvz3xeSpTIh7o48i5/O/oBFpnfYxP872gDzNJMcYYPs7bnsv2Kh8cn0FavyDeztXC6VgijlKZEvEwo08u5fXDY2icuRJj87+qA4ElxRlj+DxfJ67Ex/DO0UmkMYF0y9nE6VgijlGZEvEgk09/T4eDn1I7YzkmF3iTAOPvdCTxUX7GjzH5X+GKjaF7xNcE+wXxao76TscScYTKlIiHmHt2Ha33f8Qj6Uszs1APgvwCnY4kPs7f+DO+wOtciY+h8+FRBPsF6oz74pO0f0DEAyw9v4nm+wZSPl0R5hV+i7R+aZyOJAJAoAlgSsGu1M1YnhcOfs7Xp1Y4HUkkxalMiaRyqy9updGefpQIzsfiIr3JoBNySioT5BfIjEI9qJahDM8dGM6U0z84HUkkRalMiaRiv0Ttou7uPoQHhbK0yHtkCUjvdCSRGwr2C2Ju4f/xUPoSPL1/KLO3zXY6kkiKUZkSSaU2X9pHzd3vkj0gIyuK9iVHYGanI4n8p3R+aVhQ+G3uDynKkzOeZOHOhU5HEkkRKlMiqdDOy0eovvsd0vmlYUXR98kTlM3pSCKJksE/HYsLv0uZsDI0mdaEZXuWOR1JJNmpTImkMvvP7qfarrexwPKi71MwTU6nI4nclswB6fn26W8pnr04Dac05Pv93zsdSSRZqUyJpCIRFyJ4fPzjXIyPZmmR97grOK/TkUTuSLZ02VjWehkFMheg3uR6/HToJ6cjiSQblSmRVOJE1Amqf1Od41HHWVzkXe5JV8jpSCJuyRGSgxVtVpAzfU5qTazFhogNTkcSSRYqUyKpwNnLZ6k5oSZ7z+xl/lPzqRhyl9ORRJJErgy5WNlmJVnTZqXGNzX4/djvTkcSSXIqUyIOu3j1InUm1mFL5BZmNZ/FowUedTqSSJLKlykfK9usJCQohOrfVOfPE386HUkkSd2yTBljgo0x640xvxtjthpj3nPNL2iM+dkYs8sYM9UYE5T8cUW8S3RMNA0mN2D9kfVMaTqF2kVrOx1JJFkUzFKQFW1W4O/nT7Xx1dh1apfTkUSSTGK2TF0BqlprywL3ALWMMRWBAcBH1tqiwBmgXfLFFPE+V+Ou0mx6M1btX8W4huNoXKKx05FEklWxbMVY0WYFsfGxVB1flX1n9jkdSSRJ3LJM2QQXXTcDXT8WqArMcM3/GmiULAlFvFBcfBxPz3qahbsW8nndz2ldtrXTkURSRMnQkixvvZyoq1FUG1+NQ+cOOR1JxG2JOmbKGONvjPkNiASWAXuAs9baWNcih4E8N3lsB2PMBmPMhhMnTiRFZhGPFm/jaT+/PdP/nM7g6oN5ofwLTkcSSVFlc5ZlaeulnIo+RbXx1Th64ajTkUTckqgyZa2Ns9beA+QFKgAlbrTYTR77pbW2vLW2fGho6J0nFfEC1lpeXfwqX/32Fb0f6U2XB7s4HUnEEeVzl2dxq8VEXIig2vhqREZFOh1J5I7d1rf5rLVnge+AikBmY0yA6668QETSRhPxLtZaeizvwae/fMqbld7knUfecTqSiKMezPcgC1suZP/Z/VT/pjqno087HUnkjiTm23yhxpjMrum0wOPANmAV0NS1WFtgbnKFFPEG/Vb3Y+DagbxQ7gUGVh+IMcbpSCKOe6TAI8xtMZcdJ3dQe2Jtoq5GOR1J5LYlZstULmCVMWYz8AuwzFq7AOgOvGGM2Q1kA8YkX0wRz/bRTx/x9qq3aV2mNZ/W/VRFSuQa1QtXZ2rTqWyI2EDzGc2JiYtxOpLIbUnMt/k2W2vvtdaWsdaWttb2cc3fa62tYK0tYq1tZq29kvxxRTzPlxu/5I2lb9C4RGPGNhyLn9G5ckWu1/CuhnxW5zMW7VpExwUdsfaGh+GKpEoBt15ERO7UpD8m8cKCF6hdpDaTm0wmwE8vOZGb6Vi+IxEXIujzQx9yZ8hN36p9nY4kkih6ZxdJJsv2LKPtnLZUyV+Fmc1nEuSviwSI3ErvR3sTcSGCfqv7kSdDHjrd38npSCK3pDIlkgx+Pforjac1pkT2EsxrMY+0gWmdjiTiEYwxfF7vc45HHeelRS8Rlj5MVweQVE8Hb4gksb1n9lJnYh2yps3K4laLyRScyelIIh4lwC+AKU2n8EDeB2g5syWrD6x2OpLIf1KZEklCJ6JOUGtCLa7GXWVJqyXkyXjDCwOIyC2kC0zH/KfmUyBzARpMacDWyK1ORxK5Ke3mE0kiUVejqDe5HofOH2J56+WUCL3RhQJEfMT8+W7/iezAkpxvUmlHN2qNfpSfig8kb1D2fy5Uv77bzyPiLm2ZEkkCsfGxPDnjSTZEbGBS40lUDq/sdCQRr1AgTRhLivTmfNwlau3uzZnYi05HEvkXlSkRN1lreWHBCyzctZARtUfwRIknnI4k4lXKpivI7MI92XklgoZ7+3I5/qrTkUT+QWVKxE29v+vNmE1jeKvKW/oat0gyqZqhLOPzv8bqi3/Sav8Q4myc05FE/qYyJeKGLzZ8QZ8f+vDsPc/y/mPvOx1HxKu1yPowH+Vtx6yzP9H58CidJV1SDR2ALnKH5m6fy4uLXqR2kdp8Ue8LXW9PJAW8lqMhR66eZnDkbPIEZqMnDZyOJKItUyJ3Yu2htbSY2YJyucoxvdl0Av0DnY4k4jMG5GlLqyyP0CviG7767Sun44hoy5TI7dp+cjv1J9cnb8a8LGi5gJCgEKcjifgUP+PH2PyvEhl7jvbz2hMWEkbtorWdjiU+TFumRG5DxIUIak2oRYBfAEtaLSFHSA6nI4n4pCC/QGYW6kGZsDI0nd6U9UfWOx1JfJjKlEginbt8jjoT63Dy0kkWtlxI4ayFnY4k4tMy+KdjUatFhIWEUXdSXXad2uV0JPFRKlMiiXAl9gqNpzVm64mtzGw+k/K5yzsdSUSAnOlz8u3T3wJQc0JNjl085nAi8UUqUyK3EG/jeWbuM6zct5IxDcZQs0hNpyOJyDWKZivKwpYLOR51nLqT6nLhygWnI4mPUZkSuYWuS7syZcsUPqj2AW3KtnE6jojcQIU8FZjebDq/H/udJtOacDVOZ0mXlKMyJfIfhv40lKHrhvLy/S/TvXJ3p+OIyH+oU7QOoxuMZtneZTw39znibbzTkcRH6NQIIjcxZcsUuiztQpMSTfi41sc6KaeIB3jmnmeIuBDBWyvfIneG3AysPtDpSOIDVKZEbmDlvpW0md2GKuFVmNB4Av5+/k5HEpFE6vlQT46cP8KgtYPIkyEPnSt2djqSeDmVKZHr/H7sdxpNaUSxbMWY22IuwQHB/3/n/PnOBRORRDHGMKz2MI5FHeP1b18nZ/qcPFn6SadjiRfTMVMi19h/dj+1J9YmY5qMLG61mCxpszgdSUTugL+fPxMbT+Sh8IdoM6cNq/atcjqSeDGVKRGXU5dOUWtCLaJjo1ny9BLyZcrndCQRcUNwQDBzW8ylaNaiNJraiN+P/e50JPFSKlMiQHRMNPUn12f/2f3MbTGX0jlKOx1JRJJAlrRZWNxqMRnTZKT2xNrsP7vf6UjihVSmxOfFxsfy1MynWHd4HRMbT+Th/A87HUlEklC+TPlY0moJ0bHR1JpQi5OXTjodSbyMypT4NGstLy96mbk75jKs9jCalGzidCQRSQalcpRiXot5HDh3gLqT6nLx6kWnI4kXUZkSn9b3h758sfELelTuwcsVXnY6jogkoyr5qzC16VQ2RmzUWdIlSalMic8a8+sY3vnuHVqXaU3/av2djiMiKaBB8QaMqj+KpXuW0nZOW50lXZKEzjMlPmnejnl0XNCRGoVrMKbBGJ3dXMSHPHvvs5y4dILuy7uTPW12htUepvcAcYvKlPic7/d/T/Ppzbkv133MaDaDQP9ApyOJSArr+mBXIqMiGfLTEMLSh/G/h//ndCTxYCpT4lM2Hd1EgykNKJSlEItaLSJDmgxORxIRBxhjGFh9ICcuneDtVW8Tmi6UjuU7Oh1LPJTKlPiMXad2UWtiLTIHZ2Zp66VkT5fd6Ugi4iA/48fo+qM5dekUnRZ2Ilu6bDQt2dTpWOKBdAC6+IQj549Q/ZvqxNt4lj69lLwZ8zodSURSgUD/QKY1m0alfJVoNasVK/etdDqSeCCVKfF6p6NPU3NCTU5Fn2JJqyUUz17c6UgikoqkC0zHgqcWUCxbMRpOacjGiI1ORxIPozIlXi3qahR1J9Vl1+ldzGsxj3K5yzkdSURSoSxps7Ck1RKypc1G7Ym12XVql9ORxIOoTInXuhp3lSbTmrD+yHqmNJnCYwUfczqSiKRieTLmYWnrpVgsNSbUIOJChNORxEOoTIlXiouPo83sNny751tG1R/FEyWecDqSiHiAYtmKsbjVYk5eOknNCTU5E33G6UjiAVSmxOtYa3l18atM3TqVgY8P5Ll7n3M6koh4kPK5yzPnyTnsPLWT+pPrcynmktORJJVTmRKv0/u73ny24TO6PdiNrpW7Oh1HRDxQtULVmPDEBNYeWsuTM54kJi7G6UiSiqlMiVcZ9vMw+vzQh3b3tuPDxz90Oo6IeLBmpZrxaZ1PWbBzAc/Pfx5rrdORJJXSSTvFa0zcPJHOSzrzxF1PMLLeSF1rS0Tc1un+Tpy4dIJ3v3uXHCE5GFh9oNORJBVSmRKvsHDnQp6Z3ZbH0t/NpOBWBCxc7HQkEfESbz/8NpFRkQxaO4jQdKE6fED+RWVKPN6ag2toOr0pZdMVZE7htwj2C3I6koh4EWMMw2oP4+Slk3Rb3o3QkFCeuecZp2NJKnLLY6aMMfmMMauMMduMMVuNMZ1d87MaY5YZY3a5fmdJ/rgi/7T5+GbqTapHeKZwFhd+l4z+6ZyOJCJeyM/4Mf6J8VQvVJ3289ozf8d8pyNJKpKYA9BjgS7W2hJAReAlY0xJoAewwlpbFFjhui2SYvac3kPNCTXJkCYDy1ovIzQwk9ORRMSLBfkHMbP5TO7LdR/NZzRnzcE1TkeSVOKWZcpae9Ra+6tr+gKwDcgDNAS+di32NdAouUKKXO/ohaPUmFCDmLgYlj69lPBM4U5HEhEfkCFNBha2XEj+TPmpN6kem49vdjqSpALmdr7qaYwpAPwAlAYOWmszX3PfGWvtv3b1GWM6AB0AwsPDyx04cMDNyOLrzkSf4ZGvHmHvmb2sbLuSCnkqJNwxX5vdRSQZ1K//r1kHzh6g8tjKxNt4fnzuRwpmKehAMEluxpiN1tryt1ou0eeZMsakB2YCr1lrzyf2cdbaL6215a215UNDQxP7MJEbuhRzifqT67P95HbmtJjz/0VKRCQF5c+cn2+f/pbLsZepMaEGxy8edzqSOChRZcoYE0hCkZporZ3lmn3cGJPLdX8uIDJ5IookiImLodn0Zqw9tJZJTSbxeKHHnY4kIj6sVI5SLGy5kCPnj1B7Ym3OX0n0dgbxMon5Np8BxgDbrLVDr7lrHtDWNd0WmJv08UQSxNt4np37LIt2LWJkvZE0LdnU6UgiIlTKV4mZzWfyR+QfNJrSiMuxl52OJA5IzJapykBroKox5jfXTx3gQ6C6MWYXUN11WyTJWWt5bclrTPxjIv2r9qdDuQ5ORxIR+VvtorX5quFXrNq/ilazWhEXH+d0JElhtzxpp7V2DXCz63JUS9o4Iv/W94e+DF8/nDcqvkGPh3QGDhFJfVqVacXJSyd57dvXeHHhi7qklY/RGdAlVfvsl89457vo6H9KAAAYdElEQVR3aFu2LYNqDNKbk4ikWp0rdiYyKpL+a/qTMU1GBlYfqPcsH6EyJanWlC1TeHnRyzQo3oDRDUbjZxL95VMREUf0rdqXc1fOMfinwcTbeAbXGKxC5QNUpiRVWrJ7Ca1nt6ZK/ipMaTKFAD/9UxWR1M8Yw/Daw/EzfgxdN5Q4G8dHNT9SofJy+oSSVGfNwTU0mdaE0jlKM6/FPNIGpnU6kohIohlj+KTWJ/gbfz7++WPibTyf1PpEhcqLqUxJqvLd/u+oN6keeTPmZUmrJWQK1vX2RMTzGGMYWnPo31uo4m08w2sPV6HyUipTkmos27OMhlMaUjBLQVa0WUFY+jCnI4mI3DFjDINrDMbfz59BawcRb+MZUWfEjY//TKnLYd3g0jjiPpUpSRUW7VpE46mNuSv7XSxrvYzQEF16SEQ8nzGGAY8PwM/4MeDHAcTFx/F5vc/1hRovozIljpuzfQ7NpzenTFgZlrZeSta0WZ2OJCKSZIwxfFDtA/yNP/3X9CfexvNF/S9UqLyIypQ4atrWabSc2ZL789zP4laLyRyc2elIIiJJzhhD36p98TN+9F3dl3gbz6gGo1SovITKlDhmwuYJtJ3TlgfzPciilovIkCaD05FERJKNMYY+j/XB38+f975/jzgbx5gGY/D383c6mrhJZUocMXbTWNrPa8+jBR5l/lPzCQkKcTqSiEiyM8bQ+9HeGAy9v+9NvI1nXMNxqE55NpUpSXEjN4yk08JO1Cxck9lPztZ5pETE57z76Lv4+/nz9qq3ibfxfBXQlACjSuWpVKYkRQ37eRidl3SmXrF6TG82neCAYKcjiYg44n8P/w8/48dbK98iPsshxhd4XYXKQ6lMSYoZ9OMgui3vRuMSjZncZDJB/kFORxIRcVSvKr3wN/70WNGDeCwTCryhQuWBVKYkRbz//fu88907tCjdgvGNxhPoH+h0JBGRVKH7Q93x376DrkfGEW/jmViwC4FGH8+eRGtLkpW1lndWvUPf1X1pnfUxxgU+if+iJU7HEhFJVd4MewI/DF2OjCV+n2VywTdVqDyITnAhycZaS/fl3em7ui/tslVnXP5X8dfmaxGRG3ojrBEf5W3HzLNreXLvQK7GxzgdSRJJZUqShbWW1799nUFrB/Fi+Rf5MvwlFSkRkVt4LUdDhuXtwOxz62i+T4XKU6hMSZKLt/G8uPBFPvn5E16v+PrNL+wpIiL/8kqOeozI15G5536myd4PuaJClerpE06SVFx8HO3ntWfkxpH0qNyDITWGYIxxOpaIiEd5KbQun+V7gQXnf6Hx3g+4HH/V6UjyH1SmJMnExsfSdk5bxv02jncfeZf+1fqrSImI3KFOoXX4IvxFFp3fwBN7+6tQpWL6qoCvmz8/Sf5MjI2l1b4hTD/7I/1yP02vC+VgwYIk+dsiIr6qQ/Za+OHH8wdH0HBPP+YU7kVavzROx5LraMuUuO1KfAzN9w5k+tkfGZznWXrlbO50JBERr9E+ew3GhL/Csgu/0XBPPy7FX3E6klxHZUrccjn+Ko33fsCcc+sYnrcDXcKecDqSiIjXeS57dcbmf5XlF36nwZ6+KlSpjMqU3LFL8VdosKcvi89v5IvwF3k5Rz2nI4mIeK1nslXjq/ydWXlhM/V29yEq7rLTkcRFZUruyMW4aOru7sPyC78zNv+rdMhey+lIIiJer022qnxT4HW+v7iVmrvf5WTseacjCToAXe7A+bhL1Nn9HuuidjChwBu0zPqI05FERJJPEn1RJ6m0yvooQSaA1vs/osL2Liwo/DYl04Y7HcunacuU3JYzsRepvusdfo7ayZSCXVWkREQc0CzLQ3xfrD/R8VeptKMbi89tdDqST1OZkkTbd+UYj+zsyabovcwo1J2mWSo7HUlExGc9EFKc9XcNplCaMOrteZ+PI+dirXU6lk9SmZJEWXVhM/dv78KhmJMsLPw2DTNXdDqSiIjPyxcUyppiA2iYqQKvHx5Dx4Of6np+DlCZkv9kreXTEwupvusdcgRmZn3xIVTPeK/TsURExCXEP5gZhXrQK6wZo04tpebu3pzSgekpSmVKbupqfAwdD37Ky4e+oHbGcqwrPoiiwbmdjiUiItfxM370y9Oab/K/ztqobTyw4022Xz7sdCyfoTIlN3Q85gxVd/2PUaeW0iusGXMK9yKjfzqnY4mIyH94OttjfFe0Pxfioqm4oytLz29yOpJPUJmSf9l4aTflt3fh10t7mFKgK/3ytMbf+DsdS0REEqFS+rtYX3wI+YNCqbP7PUZE6jqpyU1lSv5h8unveWhHDwzwY/EBPJm1itORRETkNuVPk4Mfiw2gbqbyvHL4S146OJIYG+t0LK+lMiUAxNk4ehz5mpb7h3B/SBE23DWUe9MVdjqWiIjcofT+aZlVqCfdwhrz2clF1N79HmeizzgdyyupTAnn4qJosKcfA47PpGP2Wiwv8j45AjM7HUtERNzkb/wZkOcZxuXvzA8Xt1JxTEV2ntrpdCyvozLl43ZcPswD299k6flNfJ6vEyPDXyTIL9DpWCIikoSeyVaNlUX7cjr6NA+MfoAVe1c4HcmrqEz5sMW7FvPAjq6cirvAiqLv80JobacjiYhIMnkofUnWt19Pngx5qDmhJiM3jHQ6ktdQmfJB1loG/jiQupPqUiAoBxuKD+XhDKWdjiUiIsmsYJaCrG23lppFatJpYSdeXfwqsfE6MN1dKlM+JjommqdnP0335d1pVqoZPxYbQP40OZyOJSIiKSRjmozMazGPNyq+wfD1w6k7qS5nL591OpZHU5nyIYfOHaLKuCpM/mMy/ar2Y0qTKYT4BzsdS0REUpi/nz9Dag5hdP3RrNy3kkpjKrH79G6nY3kslSkf8ePBH7l/1P3sPLWTuS3m0qtKL4wxTscSEREHtbuvHctbLycyKpIHRj/Ad/u/czqSR1KZ8gGjfx3NY18/RoY0GVjXfh31i9d3OpKIiKQSjxR4hPXt1xMWEkb1b6oz+tfRTkfyOLcsU8aYscaYSGPMlmvmZTXGLDPG7HL9zpK8MeVOxMTF8MqiV3h+/vM8VvAx1rdfT8nQkk7HEhGRVKZw1sL81O4nqhWsxvPzn+eNb98gLj7O6VgeIzFbpr4Cal03rwewwlpbFFjhui2pyMlLJ6k5oSYjfhlBl0pdWNhyIVnSqvOKiMiNZQrOxIKWC+j8QGc+WvcRDaY04PyV807H8gi3LFPW2h+A09fNbgh87Zr+GmiUxLnEDZuPb+b+Ufez9tBavm70NYNrDCbAL8DpWCIiksoF+AXwca2PGVl3JEv3LKXSmEpsPr7Z6Vip3p1+woZZa48CWGuPGmNu+t16Y0wHoANAeHj4HT6dj5o//7YfMvPMWtoc+IhM/iH8UKQfFQ5mgYO3/3dERMR3dSzfkaLZivLUzKco92U5/lflf/Ss0pMg/yCno6VKyX4AurX2S2tteWtt+dDQ0OR+Op8VZ+N4N2ISTfd9yN3B+dlQfAgVQoo5HUtERDxU1YJV+fPFP2leqjm9v+9NhVEV2HR0k9OxUqU7LVPHjTG5AFy/I5Muktyu3y/to9KObvQ5NoVnslbju2L9yR2UzelYIiLi4bKly8bExhOZ22Iux6OOU2F0Bd5Z9Q5X4646HS1VudMyNQ9o65puC8xNmjhyO6Ljr9DryHjKb3+D/VcjmVzgTcbmf5VgP22GFRGRpNOgeAO2vriVlne35P0f3qfcl+XYELHB6VipRmJOjTAZ+Akobow5bIxpB3wIVDfG7AKqu25LCvr+whbKbuvMB8dn0CrrI2wr+Sktsj6sE3GKiEiyyJo2K183+poFTy3gdPRpKo6uSK8VvbgSe8XpaI4z1toUe7Ly5cvbDRu8pMnewcHhSeFs7EW6HfmKUaeWUjAojC/CX6R6xnsdySIiIh6mftKctPns5bN0+bYLY38bS8nQkoxrOI4KeSok3JkSn49JNI5bMcZstNaWv9VyOgO6B5l1Zi0lt73MmFPLeTPHE/xRYriKlIiIpLjMwZkZ03AMi1st5vyV81QaU4nuy7pzOfay09EcoTLlASKunqLxnv402fchYQGZWH/XYAblfVYXKRYREUfVKlKLLZ220O7edgxcO5B7Rt7DTxe3Ox0rxalMpWLxNp4vTy6hxJ8vsfj8r3yYuy3r7xpCuXRFnI4mIiICJJw5/cv6X7L06aVEx0ZTeWd3uhwew6V43zmWSmUqldpx+TCP7XqLjgc/o1y6wvxRYhjdczYh0OhM5iIikvpUL1ydLZ220DF7TYZGzuWebZ1Zc/FPp2OlCJWpVCbGxtL/2DTKbuvM5uj9jAl/hRVF+1IkOLfT0URERP5ThjQZ+Dz8RVYUfZ9YG8fDO3vy2qFRRMV597FU2syRiqyP2kn7A8P54/IBmmWuzLB8HcgZqIsTi4hIEkmhb6JXzVCWzSWG0TNiPJ+cmM/8c78wNv+rPJKhdIo8f0rTlqlU4GJcNK8fHk2lHd04FXeBOYV6Ma1QdxUpERHxWOn90zI8X0e+K9ofY+DRXb14+dBILsZFOx0tyalMOezb879SetsrfBw5j47Za/JnyU9pmLmi07FERESSxCMZSvP7XcPoHFqfz04s5u5tr7Dywu9Ox0pSKlMOORl7njb7P6LW7t6kNUGsLvYhn4V3IpN/iNPRREREklSIfzAf53ueH4p9QKAJoNqut+l08DMuxF1yOlqSUJlKYdZaJp7+jhJ/vsiUM6t5O+eTbCrxMQ+lL+l0NBERkWT1UPqS/FbiE7rkaMQXJ7+l9LZXWHZ+k9Ox3KYylYIOXImkzp73eHr/UAoH5eTXuz6iT+5WujCxiIj4jHR+aRic9zl+LDaAtCaIGrvfpc/RKU7Hcou+zZcC4mwcI04s5K2ICQAMy9uBF0Nr42/8HU4mIiLijErp72JTiY/pfXQyj2W42+k4blGZSkZX42OYcPo7Bhyfxc4rR6iTsTyfh3ciPCjU6WgiIiKOS+uXhgF5nnE6httUppLBpfgrjD65lEHHZ3M45iT3pC3IzII9eCJzJYwxTscTERGRJKQylYTOxF7k0xML+eTEfE7Gnufh9KUYFf4SNTPepxIlIiLipVSmksCxmDN8FDmXz08s5kJ8NHUzlqdnzqZU1jf0REREvJ7KlBv2XTnGoOOzGXtqOTE2juZZKtMjrCll0xV0OpqIiIikEJWpO7A1cisf7h/K5NM/4Gf8eCZrVbqFNdbFiEVERHyQytRt+Pnwz3yw5gPm7phLOr80dM5RnzdyNCJPUDano4mIiIhDVKZuwVrLin0r+GDNB6zct5IswVl495F3eeVMUbIFZHQ6noiIiDhMZeom4m0883bMo//q/vwS8Qu50udicPXBdCjXgQxpMsD8+U5HFBERkVRAZeo6MXExTN4ymQE/DuDPE39SKEshvqj3BW3KtiE4INjpeCIiIpLKqEy5RMdEM3bTWAatHcSBcwe4O8fdTGo8iWalmhHgp/9MIiIicmM+3xLOXT7H5xs+56N1HxEZFUmlvJUYUWcEdYvW1Yk2RURE5JZ8ukxdjbtKyc9KEnEhgpqFa9LzoZ48nP9hlSgRERFJNJ8uU0H+QfSv2p/SOUpTLnc5p+OIiIiIB/LpMgXQ9p62TkcQERERD+bndAARERERT6YyJSIiIuIGlSkRERERN6hMiYiIiLjB+w5A12VeREREJAVpy5SIiIiIG1SmRERERNygMiUiIiLiBpUpERERETeoTImIiIi4QWVKRERExA0qUyIiIiJuUJkSERERcYPKlIiIiIgbVKZERERE3KAyJSIiIuIGt8qUMaaWMWaHMWa3MaZHUoUSERER8RR3XKaMMf7Ap0BtoCTwlDGmZFIFExEREfEE7myZqgDsttbutdZeBaYADZMmloiIiIhncKdM5QEOXXP7sGueiIiIiM8IcOOx5gbz7L8WMqYD0MF186IxZocbz5lcsgMnnQ7hEF8eO/j2+H157ODb49fYfZcvj/9Oxp4/MQu5U6YOA/muuZ0XiLh+IWvtl8CXbjxPsjPGbLDWlnc6hxN8eezg2+P35bGDb49fY/fNsYNvjz85x+7Obr5fgKLGmILGmCCgBTAvaWKJiIiIeIY73jJlrY01xrwMfAv4A2OttVuTLJmIiIiIB3BnNx/W2kXAoiTK4qRUvRsymfny2MG3x+/LYwffHr/G7rt8efzJNnZj7b+OGRcRERGRRNLlZERERETcoDIlIiIi4gavLlPGmHzGmFXGmG3GmK3GmM43WMYYY4a5ri+42Rhz3zX3tTXG7HL9tE3Z9O5J5Nhbuca82Riz1hhT9pr79htj/jDG/GaM2ZCy6d2TyLE/aow55xrfb8aYd665z6OvOZnI8Xe9ZuxbjDFxxpisrvs8ed0HG2PWG2N+d439vRssk8YYM9W1fn82xhS45r6ervk7jDE1UzJ7Ukjk+N8wxvzpet2vMMbkv+a+uGv+XXjUt7MTOfZnjDEnrhlj+2vu8+T3+8SM/aNrxr3TGHP2mvs8dr1fyxjjb4zZZIxZcIP7kvd1b6312h8gF3CfazoDsBMoed0ydYDFJJyEtCLws2t+VmCv63cW13QWp8eUxGN/8K8xkXCNxZ+vuW8/kN3pcSTj2B8FFtzgsf7AHqAQEAT8fv1jU/tPYsZ/3fL1gZVesu4NkN41HQj8DFS8bpkXgZGu6RbAVNd0Sdf6TgMUdP078Hd6TMkw/seAdK7pTn+N33X7otNjSOaxPwOMuMFjPf39/pZjv275V0j4Br7Hr/frxvUGMOkm7+3J+rr36i1T1tqj1tpfXdMXgG38+5I3DYHxNsE6ILMxJhdQE1hmrT1trT0DLANqpWB8tyRm7Nbata6xAawj4cSrHi+R6/1mPP6ak3cw/qeAySmRLbm5XscXXTcDXT/Xf8umIfC1a3oGUM0YY1zzp1hrr1hr9wG7Sfj34DESM35r7Spr7SXXTW963Sdm3d+Mp7/f3+7YveY1/xdjTF6gLjD6Josk6+veq8vUtVyb9O4lobFf62bXGPSaaw/+x9iv1Y6ELXR/scBSY8xGk3BJII90i7FXcm0WX2yMKeWa5zXrHW697o0x6Uj40Jh5zWyPXveuTf2/AZEkfEDe9DVvrY0FzgHZ8JJ1n4jxX+v6132wMWaDMWadMaZRsgZNBokcexPXLs4Zxpi/ruLh8es+sevdtVu3ILDymtkevd5dPga6AfE3uT9ZX/c+UaaMMelJ+LB4zVp7/vq7b/AQ+x/zPcotxv7XMo+R8Kba/ZrZla2195Gw++8lY8zDyR42id1i7L8C+a21ZYHhwJy/HnaDP+Vx6x0St+5J2MX3o7X29DXzPHrdW2vjrLX3kLDFpYIxpvR1i3j1az4R4wfAGPM0UB4YdM3scJtwuY2WwMfGmMLJHjgJJWLs84EC1toywHL+f0uFx6/7xK53EnZxzbDWxl0zz6PXuzGmHhBprd34X4vdYF6Sve69vkwZYwJJ+ECZaK2ddYNFbnaNwURdezA1S8TYMcaUIWGzaENr7am/5ltrI1y/I4HZeNjujluN3Vp7/q/N4jbh5LOBxpjseMF6h8Ste5cWXLe539PX/V+stWeB7/j37pq/17ExJgDIBJzGS9b9X/5j/BhjHgfeAhpYa69c85i/1v1e12PvTYmsSe1mY7fWnrpmvKOAcq5pr1n3/7XeXf7rNe+p670y0MAYs5+EQzOqGmMmXLdM8r7ub/cgK0/6IaFxjgc+/o9l6vLPA9DXu+ZnBfaRcDBiFtd0VqfHlMRjDydh//CD180PATJcM70WqOX0mJJ47Dn5/5PWVgAOuh4XQMLBpwX5/wPQSzk9pqQev2u5v95MQrxo3YcCmV3TaYHVQL3rlnmJfx6IOs01XYp/Hoi6F887AD0x47+XhINsi143PwuQxjWdHdiFB335IpFjz3XN9BPAOte0p7/f33LsrvuKk/AFE+Mt6/0GY3yUGx+Anqyve7cuJ+MBKgOtgT9c+5IBepFQIrDWjiThcjh1SCgVl4BnXfedNsa8T8IFnQH62H/uCkntEjP2d0jYZ/xZwnF4xNqETb1hwGzXvABgkrV2ScrGd0tixt4U6GSMiQWigRY24ZXlDdecTMz4IeHDZKm1Nuqax3r6us8FfG2M8Sdhy/s0a+0CY0wfYIO1dh4wBvjGGLObhDLZAsBau9UYMw34E4gFXrL/3BXiCRIz/kFAemC6az0ftNY2AEoAXxhj4l2P/dBa+6cjo7gziRn7q8aYBiSs39MkfLvPG97vEzN2SDjwfIrrve4vnr7ebyolX/e6nIyIiIiIG7z+mCkRERGR5KQyJSIiIuIGlSkRERERN6hMiYiIiLhBZUpERETEDSpTIiIiIm5QmRIRERFxw/8B3imn6a6h2NwAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "zz=(z[:-1]+z[1:])/2.\n", "bar(zz,v,0.1,color='r',alpha=0.3)\n", "a,b=2,4\n", "#xx=2*zz/(b-a) - (a+b)/(b-a)\n", "F=mat_trans(2/(b-a),-(b+a)/(b-a),2)#.transpose()\n", "#m1=mat_poly2(xx)\n", "polym2=mat_poly2(zz)\n", "T=matG.dot(F)\n", "A=T.dot(polym2)\n", "newres=res.dot(T)\n", "### transformace zpet do prostoru obyc. polynomu\n", "newD=inv(T.dot(inv(D).dot(T.T)))\n", "newsig=sqrt(newD.diagonal())\n", "newrho=newD/(newsig.reshape(3,1)*newsig.reshape(1,3))\n", "D2=inv(dot(polym2,polym2.transpose()))\n", "sig2=sqrt(D2.diagonal())\n", "rho2=D2/(sig2.reshape(3,1)*sig2.reshape(1,3))\n", "#plot(zz,exp(dot(res,A)),'r',hold=1)\n", "plot(zz,exp(dot(newres,polym2)),'g')\n", "print(\"fit Legend. polynomy (po transformaci):\",newres)\n", "print(\"fit mocninami:\",polres[::-1])\n", "sig=sqrt(D.diagonal())\n", "print(\"korelační matice.. \\n\",D/(sig.reshape(3,1)*sig.reshape(1,3)))\n", "print(\"korelační matice..(po transformaci) \\n\",newrho)\n", "rho2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "původně nekorelované parametry jsou opět provázány..." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### opakování simulace - rozdělení rekonstruovaných parametrů" ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\ipykernel_launcher.py:13: RuntimeWarning: divide by zero encountered in log\n", " del sys.path[0]\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "if True: #případně vypneme, pokud chceme ušetřit čas\n", " rep=[pokus(full=2,step=0.1) for i in range(200)]\n", " mux,sigx=array([r[2:] for r in rep]).transpose() #prumer a stredni hodnota\n", " pask1=array([r[0] for r in rep]).transpose() #parametry z histogramu\n", " plot(pask1[0],pask1[1],'.')\n", " xlabel(\"param. 0\")\n", " ylabel(\"param. 1\")" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\ipykernel_launcher.py:1: RuntimeWarning: invalid value encountered in greater\n", " \"\"\"Entry point for launching an IPython kernel.\n" ] }, { "data": { "text/plain": [ "198" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sel=(pask1[0]>0)*(pask1[1]+10>0)*(pask1[2]+10>0)\n", "pask1=pask1[:,sel]\n", "sum(sel)" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Text(0,0.5,'sigma')" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot(mux,sigx,'.')\n", "xlabel('mu')\n", "ylabel('sigma')" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "-0.06950556442590902" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "corrcoef(mux,sigx)[0,1]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "korelace mezi odhadem střední hodnoty a rozptylu na úrovni 8%" ] }, { "cell_type": "code", "execution_count": 62, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "korelace 1,2: 0.045105565873923156\n", "korelace 0,2: 0.9171578199385589\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot(pask1[0],pask1[2],'.')\n", "xlabel(\"param.0\")\n", "ylabel(\"param.2\")\n", "print(\"korelace 1,2:\",corrcoef(pask1[2],pask1[1])[0,1])\n", "print(\"korelace 0,2:\",corrcoef(pask1[0],pask1[2])[0,1])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### testovací otázka - proč je parametr 0 korelován s 2 ?\n", "(hint: vzorce v úvodu) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### přepočet na parametry norm. rozdělení" ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Text(0,0.5,'est. sigma')" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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cup2PzD3MsePJ6TPBNZdun3aRRD0nx/SXqUmZqrW6cJv0GdQtGwZrmXm4+PNx4OerLY6kadu9cxu3XPdCD1oaWtMyVat14TbtM6hbNgzWIuKVwDuAncX6AWTdZoNKKk8dsziqr6ZNNlitC3ffHQcb9RnULcN0g/4y8Crg3mzLjUSlktSt22Sa5albXUxL1fVQ9uuX8XpNnGwweELSxM+g7hjmOmt3AC/LzOXJFGk0XmdNk1a3bpNplqdudTEtVddD2ZdVKbO8bQjW2/AZ1BxlX2ftXwMfj4g/Ap5YWZiZvzRi+aRWqFvXzzTLU7e6mJaq66Hsy6qUWd42dJ234TOonbYMsc7/CTwGPAU4s++fNJb5w4vsu+Mg84cXp12Ukax0m8wEteg2mWZ56lYX01J1PYx6WZW1vmvuN6kZhukGnRs2TTdNdoM2S1u6zerWbbJSnm1P3criY0cnWq661cW0VFkP84cXec1Nf/bkZVVuue6FQ92RYr3vWpf2W5c+66iso8kpuxv0DyLiisz8xJjlkp7Ulm6zaXWbrPWDuvJ31YHwau+/2bpo60GhyjYxymVVNvqutbXrb7B9teUEsUrWUX0NE6y9BfjXEfEEcAwv3aESOPNqdBv9oFYdCJfxg172wPaP3r1A0rugb9MOLpsNWjcbXHXxu7Za+2rLCWKVrKP6GuaiuI5PU+mafKuaadvoB7Xqg/N67z9s4FHWQWFlduTKoPuPzD08VNdgXUwik9HF79pq7auLQetmWUf1NcxFcS9dZfHfAIczc6n8Iqkr2tr9UrX+H9SZLcEjf/0484cXT+qOrPLgvNYP+mYCjzIOCvOHF/nlP/jCk4EawLHjyW13LzQmMJlUJqNr37XV2lcXg9bNso7qa5gJBgeAS4F7i0UvAD4LnAW8uS5j2ZxgoC6ZP7zIbXcv8JH5BZaOT+e6aoM/6PvuOMgvfuJBlhNmAn7yiufylpd+x6ZeYzPv/7r3HeCJY8snzYg8bQts2bJlKnUyipXPsRJU1L28TdLWMZFqj7InGHwZeGNm3l+8+POAn6Z3C6qPAmsGaxFxJfBuejeCf19mvnPg+TcA/w74SrHoVzPzfcVzrwfeXiz/PzLz5mE+kNQFu3du48ChIywdn874ktUyNZvNlo2T7VnJSCW96w+9YPu38vxzv5UAbvn0X5TSvTqJA72ZjOp0LZuodhsmWPvOlUANIDMfiIhLMvNQRKy5UUTMAPuAlwMLwF0RsT8zHxhY9Tcz8/qBbZ8B/CwwS+9SQvPFts28IJdUgbqNL5lk4DH42W/8R89/csbfbXcvjN29OskZcQYVkjYyTLD2YET8GnBr8fiHgC9ExBn0Zoeu5TLgYGYeAoiIW4GrgcFgbTWvAD6ZmY8W234SuBK4ZYhtpU6oY1ZmUoHHWp+9jDqp+4w4u/ek7hkmWHsD8C+BH6d32Y7/BvwUvUDtpetsdy7wcN/jBeDyVda7JiJeDHwB+InMfHiNbc8d3DAirgOuA9ixY8cQH0U6WdMPfHXOylRdt2t99nHrpG4Zy35tvw5W07+PUlWGuXTH48AvFv8G/Y91Nl2tj3RwNsPvALdk5hMR8WbgZuD7htyWzLwJuAl6EwzWKYt0irYf+DZS9ZX2m1q342Tnqg426p71G0eT24xUtTWDtYj4z5n5gxFxL6sHSt+9wWsvAOf1Pd4OPDLwGkf6Hr4X+IW+bV8ysO2dG7yftCltPvBtpOoDY9PrdpTs3CSCjTpn/cbV9DYjVWm9zNqPFf+/csTXvgu4MCIuoDfb81rgtf0rRMSzM/OrxcOrgM8Xf98O/NuIWPmmXgHcMGI5NEFN6sZo84FvI1UfGLtYt5MINuo4TrEsXWwz0rDWDNb6gqi/Ah7PzOWIeA7wncDvbfTCmbkUEdfTC7xmgPdn5v0RsReYy8z9wFsj4ipgCXiU3vg4MvPRiHgHvYAPYO/KZAPVV9O6Mdp84NtI1QfGLtbtpIKNaY5TrPJkrIttRhrWMBfFnQe+F9gGHADmgMcy83XVF294XhR3+jZ7UVRNV5OyoE3R5jpt2smYVHdlXxQ3MvOxiHgj8CuZ+a6I+Mx4RVQb1bUbo80H0HHUeSZpkwy2r0nU6TTadN3HlPk9V5sNFaxFxAuB1wFv3MR26pjNdmNM4sfVbED5PCieMI32Na02XdeTMfB7rvYbJuj6MXqD+3+rGHO2C7ij2mKpqYbNLEzqx7Xu2YCmGdxvN77y+Sw+drSzgds02te02nSdx5T5PVfbDXOdtT8G/rjv8SHgrVUWSu03qR/XOmcDmqh/vx09tsyNH7uP5cxWZTM2kzmcRvua5Huu1sVbx33s91xtZ3empmIzP67jdLvVORvQRP37LSJYzmxVNmOzGd9ptK9JvWeTuhab/D13WIGGYbCmqRj2x7WMA8ZmsgH+cJ5qsE5W9tu2p25l7+/eX3nAPUmjZHzHzTaNUjeTyHA1rWuxrlm/9TQpINZ0Gaxpaob5cZ3kAcMfzlOtVScr9fLcZ505kYB7UibdnVbnurFrsXpNC4g1PSMFaxHxysz83bILIw2a5AHDH85TrVYnK8uHvVRFk+p10t1pda6bUeuiKVnUOjAg1rBGzax9D2CwpspN8uDpD+epButk21O3bjoT1LR6nWR3Wtl1U3agtNm6qHOmsI6aPNZOkzXMHQzOyMwnNlo2bd7BQGUwK3Cq/jo5cOjISHepsF7XVlbd1CFQ8i4m0vDKvoPBnwGXDrFMarxpD1KedlCz2vsP1skomaBp12udlVU3dehSLTNTOO3vglQnawZrEfEs4FzgWyLiEiCKp54OPHUCZZM6ZdqZkZX3f+LYMjNbgr1XX8RrL99x0jpd7rape/BQh+7mzczyXm+dtb4Ldd8HUlXWy6y9AngDsB34RU4Ea98E/vdqiyV1z7QzIwcOHeGJY8sksLSc3Pix+3jus848pQxdzJJNO5AeRl0C6Y3axzB1udbElrrvA6kqawZrmXkzcHNEXJOZt02wTFInrZYZmWQmYc+us5jZEiwt98axLmfWanbiNE07kB7WqIF0Fe1srdccpi5X+y40ZR9IVRhmzNr2iHg6vYzae+mNVXtbZn6i0pJJHTOYGYHJZhJ279zG3qsvOukWUnWfuTkpdehirEoVWcP1XnOYulwrS9jWfSBtZJhg7Z9n5rsj4hXAM4EfAT4AGKxJJevPjOy74+DEMwmvvXzHUBe67Zq6dDFWoYqM1XqvOWxdDmYJ27wPpI0ME6ytjFX7AeADmfnZiIj1NpDqZJQunjoMZJ5WNqcJY9KmsX+aUC+jqGIG57anbl3zNce9128b94G0kWGus/YBerNCLwD+PjAD3JmZu6sv3vC8zppWM0oXT50Gk9chaKybOu2ftiijnQ3ulxtf+XwWHzt60mu676QTyr7O2huBi4FDmflYRJxFrytUDdK0g35Z5R2li6dOA5nbkkkos/3Vaf+0RRntbHC/LD529JQL4rrvpNEME6wl8DzglcBe4GnAU6oslMrVpLPZ+cOL3Hb3Ah+ZX2Dp+PjlHaWLp82DyQdNIogvu/11af80yTD7xX2nJqhjcmOYYO3/BpaB76MXrH0TuI3e/UHVAE05m+2/KOtK5/y45R1lUHJXBjJPKogvu/01af/U8Ue/KsPslybtO3VTXZMbwwRrl2fmpRHxGYDMXIyIrRWXSyVqytnsykF9JVALKKW8o3TxtKX7cT2TCuKraH9N2D91/dGv0jD7pQn7Tt1V1+TGMMHasYiYodcdSkScQy/TpoZoytls/0F9ZkvwT2bP41WXbq9teZtuUkF8U9pf2er6oy9pbXVNbgwzG/R1wA/RuxjuzcCrgbdn5oerL97wnA3aDqN2G3Wpu6lM1lt1VjJrKz/6XcisSW0wqd/FzcwG3TBYK17wO4GX0euZ+sPM/Px4RSyfwVp3dbG7SdOzmR9yg2FJayn70h1k5p8Dfz5WqaSKjNrd5IFUm7XZEwPHZ0kqw1DBmlRno4wx6D/obolg79UX8drLd0ygtGqyNo5D86RFqj+DNTXeKAPY+w+6y5nc+LH7eO6zzvRgtUldO9CXNfi4LvXmEAKpGQzW1Aqb7W7as+sstkSwXIzZXF5Ou083qYsH+jJmttap3uqQKfT7NBrrrVsM1tRJu3duY+/VF3Hjx+5jeTnZevrmu0+nfaCdtjoc6NdT1cFs3HFo49Rb2Z9p2pcp6Nr3qaz917V6k8Fa63i2NbzXXr6D5z7rzJG7T+sYoIxrM+1n2gf69dT5YDZqvVXxmaZ9Dby2f5/6lbn/ulRv6jFYa5E6H6DqapTu07oGKOMaZaZjXS92W+eD2aj1VtVnmuaM1TZ/nwaVuf+6VG/qqTRYi4grgXcDM8D7MvOda6z3auDDwPdk5lxEnA98HniwWOVAZr65yrK2QZ0PUE01mGkqK0CpYwZ0lPZT10tT1P1gNkq91f0zrWW9tl7ngL9sZe6/LtWbeioL1opbVO0DXg4sAHdFxP7MfGBgvTOBtwKfGniJhzLz4qrK10ZN/TGvq7UyTeMGKHXNgLap/bTxYNbEzzRMW69rwF+2svdfV+pNPVVm1i4DDmbmIYCIuBW4GnhgYL13AO8CfqrCsnRCE3/M66yqTOW0M6BrZTra1n7aeDBr2meadluvm6btP9VHlcHaucDDfY8XgMv7V4iIS4DzMvN3I2IwWLsgIj4DfIPevUj/ZPANIuI64DqAHTu8oCn4Y1CmqjJN08xgbZTpsP2oTG3K1krTVGWwFqsse/JGpBGxBfj3wBtWWe+rwI7MPBIRu4HfjojnZ+Y3TnqxzJuAm6B3b9CyCi5BdZmmaWawzHRoktqWra1SHcexqj6qDNYWgPP6Hm8HHul7fCZwEXBnRAA8C9gfEVdl5hzwBEBmzkfEQ8BzAO/UromqKtM0rQxWFzIdHvTqxWztxuo6jlX1UWWwdhdwYURcAHwFuBZ47cqTmfk3wNkrjyPiTuCnitmg5wCPZubxiNgFXAgcqrCsUie0PdPhQU9NZMZbG6ksWMvMpYi4Hrid3qU73p+Z90fEXmAuM/evs/mLgb0RsQQcB96cmY9WVVapCdbLGG0mm9TmTEf/Qe+oBz01RBcy3hpPpddZy8yPAx8fWHbjGuu+pO/v24DbqiybVCcbBVvrZYzMJp2w7albWS5Gry5n77FUd23PeGt83sGg5Ry/U3/DBFvrdZPYhXLC4mNHCXozmbYUj4fld0XT1OaMt8ZnsNZiZlyaYZhga71ukq50oQwTTO3ZdRZnnF6P+25KUlkM1lrMjEszDBNsrddN0oUulGGDqWHqYrWgz++K1Cxdy4QbrLVYVzIuTTdssLVeN0nbu1A2E0ytVxdrBX1Vfle6dlCRqtbFTLjBWot1IePSFm0PtsZVVjC1XtD3qku3E8X/Ze2LLh5UpKp1MRNusNZyBgHTZ2ZlfGWdeKwW9A0GVK+6dHtp5W7aQcW2qiboYq+RwZrUp+yDlZmVelkt6Nt3x8HKAqomHVRsq2qKLvYaGaxJhSoOVk3LrIyq6oxMmftmMNtcZUA1jYPKqPuiK21V7dC1XiODNalQxcGqSZmVUU0iI1NlIFF1QDV4UKkysB1nX3ShrUpNZbCmVXVx7EoVB6supOsnkZGpOpCY1Fl61YHtOPuiC21VaiqDNZ2iq2NXqjpYtT1dP4mMTFsCif5g6oljy3z07oWxP0v/idW4+6LtbVVqKoM1naLLY1emcbBqehZzUoFU3QOJYe+wcNrMFo4uLZPAh+ceHutSIaudWNUpqG1625bqwmBNp3DsyuS0JYtZ90Cqapu5w8Krd2/nlk/9BQkcX86xToZWO7F6y0u/oxb7oi1tW6qDLdMugOpnJVPyk1c8d+wf2PnDi+y74yDzhxdLLGF7rHaw7Wf9NcNG+7HfNZdu54zTtzATjH0ytHJiVcZrlW0zdSJpfWbWtKoyMiWeWW9svSym9dccm8lGl9ltXOexfGbopfIYrLVAXceFdHns27DWO9haf82x2aCpzG7junZB1zmQlJrGYK3h6px98cx6OGsdbK2/Zqlr0DRN1olUDoO1hqtz9sUz6/FYf9Lm1bWnoa6sr2YwWGu4umdfPLMej/UnDa/OPQ11ZH01h8Faw5l9kaSejXoazCLdeaQIAAAOy0lEQVSdrM49MzqZwVoLmH2RJGdXb1bde2Z0gsGaJKkVnF29OfbMNIfBmiSpNZxdvTn2zDSDwZo0IY6XOZn1oUkyi6QmM1iTJsDxMiezPjQNZpHUVN4bVJoA75N4MutDkoZnsCZNQJ1vuD0N/fUxsyV45K8f92b1krSGyMxpl6EUs7OzOTc3N+1itJJji8phPZ5s/vAit929wEfmF1g6bneopG6JiPnMnB1mXcesaV1dG1tUZUDleJmT7d65jQOHjrB03MspSNJ6DNa0ri5dm6hrgWkdeDkFSdqYwZrW1aWDaZcC07rwcgqStDGDNa2rSwfTLgWmdWL3sCStr9IJBhFxJfBuYAZ4X2a+c431Xg18GPiezJwrlt0AvBE4Drw1M29f772cYKAyOAlAkjQJtZhgEBEzwD7g5cACcFdE7M/MBwbWOxN4K/CpvmXPA64Fng98G/AHEfGczDxeVXklMMsjSaqfKq+zdhlwMDMPZeZR4Fbg6lXWewfwLuD/61t2NXBrZj6RmV8CDhavJ0mS1ClVBmvnAg/3PV4olj0pIi4BzsvM393stsX210XEXETMff3rXy+n1JIkSTVSZbAWqyx7coBcRGwB/j3wv2522ycXZN6UmbOZOXvOOeeMXFCpDuYPL7LvjoNeyV8jsf1I7VXlbNAF4Ly+x9uBR/oenwlcBNwZEQDPAvZHxFVDbCu1itd40zhsP1K7VZlZuwu4MCIuiIit9CYM7F95MjP/JjPPzszzM/N84ABwVTEbdD9wbUScEREXABcCn66wrNJUeWNzjcP2I7VbZZm1zFyKiOuB2+lduuP9mXl/ROwF5jJz/zrb3h8R/xl4AFgC3uJMULWZ13jTOGw/Urt5I3epJrzGm8Zh+5GapRbXWZO0OV7jTeOw/UjtVeWYNUmSJI3JYE2SJKnGDNYkSZJqzGBNmjAvXipJ2gwnGEgT5MVLJUmbZWZNmiAvXipJ2iyDNWmCVi5eOhN48VJJ0lDsBpUmaPfObXzwTXs6dfFSL9YqSeMxWJMmrEsXL3WMniSNz25QSZVxjJ4kjc9gTVJlHKMnSeOzG1RSZbo4Rk+SymawJqlSXRqjJ0lVsBtUkiSpxgzWJEmSasxgTZIkqcYM1iRJkmrMYE2SJKnGDNYkSZJqzGBNUi3NH15k3x0HmT+8OO2iSNJUeZ21inkTa2nzvKeoJJ1gsFYhDzjSaFa7p6jfHUldZTdohbyJtTQa7ykqSSeYWavQygHn2NKyBxxtWpe70L2nqCSdEJk57TKUYnZ2Nufm5qZdjFN0+YCr0dmFLkntFhHzmTk7zLpm1irmTaw1CsdsSZJWOGZNqiHHbEmSVphZk2rIMVuSpBUGa1JN2YUuSQK7QSVJkmrNYE2SJKnGKg3WIuLKiHgwIg5GxNtWef7NEXFvRNwTEf8tIp5XLD8/Ih4vlt8TEe+pspySJEl1VdmYtYiYAfYBLwcWgLsiYn9mPtC32ocy8z3F+lcBvwRcWTz3UGZeXFX5JEmSmqDKzNplwMHMPJSZR4Fbgav7V8jMb/Q9fBrQjiv0SpIklaTKYO1c4OG+xwvFspNExFsi4iHgXcBb+566ICI+ExF/FBHfW2E5JUmSaqvKYC1WWXZK5iwz92XmtwP/G/D2YvFXgR2ZeQnwk8CHIuLpp7xBxHURMRcRc1//+tdLLLqkupk/vMi+Ow4yf3hx2kWRpImq8jprC8B5fY+3A4+ss/6twK8BZOYTwBPF3/NF5u05wEk3/8zMm4CboHdv0NJKLqlWvFeqpC6rMrN2F3BhRFwQEVuBa4H9/StExIV9D/8h8MVi+TnFBAUiYhdwIXCowrJKqrHV7pUqSV1RWWYtM5ci4nrgdmAGeH9m3h8Re4G5zNwPXB8R/wA4BiwCry82fzGwNyKWgOPAmzPz0arKKqneVu6Vemxp2XulSuqcyGxH7+Hs7GzOzc1tvKKkRpo/vOi9UiW1RkTMZ+bsMOt6b1BJjeC9UiV1lbebkiRJqjGDNUmSpBozWJMkSaoxgzVJkqQaM1iTJEmqMYM1SZKkGjNYkyRJqjGDNUmSpBozWJMkSaqx1txuKiK+Dhyu8C3OBv6qwtdvC+tpONbTcKyn4VhPw7GehmM9DW+cutqZmecMs2JrgrWqRcTcsPfw6jLraTjW03Csp+FYT8OxnoZjPQ1vUnVlN6gkSVKNGaxJkiTVmMHa8G6adgEawnoajvU0HOtpONbTcKyn4VhPw5tIXTlmTZIkqcbMrEmSJNWYwZokSVKNdS5Yi4jzIuKOiPh8RNwfET+2yjrbIuK3IuJzEfHpiLhoo20j4uci4isRcU/x7wcm+bnKNk49Fc99OSLuLepirm/5MyLikxHxxeL/bZP6TFUYsz09t6+93BMR34iIHy+ea1V7AoiIpxSf/7NFXf38KuucERG/GREHI+JTEXF+33M3FMsfjIhX9C2/slh2MCLeNplPU51x6ikiXh4R88V3bz4ivq9vmzuLelppU8+c3Kcq35j1dH5EPN5XF+/p22Z3UX8HI+L/ioiY3Kcq35j19LqB36jliLi4eK6L7enFEXF3RCxFxKsHnnt9cVz7YkS8vm95Oe0pMzv1D3g2cGnx95nAF4DnDazz74CfLf7+TuAPN9oW+Dngp6b9+epQT8XjLwNnr/K67wLeVvz9NuAXpv1Zp1lPfevMAP8vvYsktq49FZ8pgL9T/H068Clgz8A6/xJ4T/H3tcBvFn8/D/gscAZwAfBQUWczxd+7gK3FOs+b1GeqYT1dAnxb8fdFwFf6trkTmJ3256tJPZ0P3LfG634aeGHx+r8HfP+0P+u06mlgnRcAhzrens4Hvhv4j8Cr+5Y/AzhU/L+t+Htbme2pc5m1zPxqZt5d/P1N4PPAuQOrPQ/4w2KdPwfOj4i/N+S2rTBOPW3w0lcDNxd/3wz849IKPQUl1tPLgIcys8q7cExV9vyP4uHpxb/BGU797eMjwMuKM9GrgVsz84nM/BJwELis+HcwMw9l5lHg1mLdxhqnnjLzM5n5SLH8fuApEXFG5YWegjHb06oi4tnA0zPzz7J3pP2PNP83qqx6eg1wS2UFnbJh6ikzv5yZnwOWBzZ/BfDJzHw0MxeBTwJXltmeOhes9StSvZfQi6D7fRZ4VbHOZcBOYPsQ214fva6u90fDu/f6jVhPCXyi6Iq5rm+bv5eZX4VeoAM0OnXeb5z2RO9sdvCHsHXtKSJmIuIe4Gv0ftwG6+pc4GGAzFwC/gY4q395YaFYttbyRhujnvpdA3wmM5/oW/aBosvq3zS9ew/GrqcLIuIzEfFHEfG9fesv9G1vezrhhzj1N6pr7Wkt6/0+ldKeOhusRcTfAW4DfjwzvzHw9DuBbcVO+1fAZ4ClDbb9NeDbgYuBrwK/WO0nmIwx6ulFmXkp8P3AWyLixZMq8zSM2Z62AlcBH+7bppXtKTOPZ+bF9ILVy6JvnGNhtR/8HGF5o41RT70nI54P/ALwL/qef11mvgD43uLfPyu31JM3Rj19FdiRmZcAPwl8KCKevs76jVZCe7oceCwz7+t7vovtaS2V/z51MliLiNPpHVg/mJkfHXw+M7+RmT9S7LQfBs4BvrTetpn5l8WOXgbeS697ptHGqaeVrpjM/BrwW5yoj78sUsMrXQ5fq/yDVGyceip8P3B3Zv5l3zata0/9MvOv6Y15uXLgqQXgPICIOA34VuDR/uWF7cAj6yxvhRHqiYjYTu8798OZ+VDfa32l+P+bwIdoUZvabD0V3elHim3n6Y17fE6xfn/Wu/PtqXBK5r+j7Wkt6/0+ldKeOhesFana/wB8PjN/aY11/m6R7QB4E/DHmfmN9bZdCUAK/wvQfwbSOGPW09Mi4sxinacBV3CiPvYDKzNlXg98rKrPMAnj1FPfKqeMBWlbewKIiHMi4u8Wf38L8A+APx9Yrb99vBr4r8VYj/3AtdGbtXYBcCG9gbt3ARdGxAVFHV9brNtY49RTsd1/AW7IzD/te83TIuLs4u/TgVfS8DY1Zj2dExEzxba76LWnQ8XQjG9GxJ7iu/3DNP83apzvHRGxBfgn9MaDrrxmV9vTWm4HrojezP9t9I55t5fanrIGszAm+Q/4n+mlIT8H3FP8+wHgzcCbi3VeCHyx2FEf5cSsjlW3LZ77T8C9xXP7gWdP+7NOsZ520Run9Vl6g5x/pu91z6I32P6Lxf/PmPZnnVY9Fc89FTgCfOvA67aqPRWf6bvpdQF/jt4P+43F8r3AVcXfT6HXHXyQXjC2q2/7n6GXAXmQvhlVRX1/oXjuZyb1eepYT8Dbgb/ta4v30BsX+jRgvnjN+4F3AzPT/qxTrKdrinr4LHA38I/6Xne2eL2HgF+luNNPU/+V8L17CXBg4DW72p6+h1627G+L3+37+7b/50X9HQR+pOz25O2mJEmSaqxz3aCSJElNYrAmSZJUYwZrkiRJNWawJkmSVGMGa5IkSTVmsCZJQES8ISK+bdrlkKRBBmuS1PMGwGBNUu0YrElqrYj4pxHx6eJm079e3Kh5JiJ+IyLui4h7I+InIuLV9C5e+cFi3W9Z5zV/LiJujohPRMSXI+JVEfGu4rV+v7iiO8VzK1d5n42IOyfyoSW1jsGapFaKiO8Cfgh4Ufbuy3oceB1wMXBuZl6UvRtRfyAzPwLM0bs59cWZ+fgGL//twD8Ergb+H+CO4rUeL5ZLUmlOm3YBJKkiLwN2A3f1bsvHtwBfA34H2BURv0LvPpqfGOG1fy8zj0XEvcAM8PvF8nuB88cstySdxGBNUlsFcHNm3nDKExF/H3gF8BbgB+nd128zngDIzOWIOJYn7tu3zInf1SVO9F48ZZOvL0lPshtUUlv9IfDqiHgmQEQ8IyJ2FuPItmTmbcC/AS4t1v8mcGaJ7/9lepk96N04XJJGYrAmqZUy8wHg7cAnIuJzwCeBZwPnAndGxD3AbwArmbffAN6zMsEgIvZGxFVjFOHngXdHxJ/QGy8nSSOJE9l7SZIk1Y2ZNUmSpBozWJMkSaoxgzVJkqQaM1iTJEmqMYM1SZKkGjNYkyRJqjGDNUmSpBr7/wFVkUfbsPZ3UQAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pask2=dot(pask1.transpose(),T).transpose()\n", "estmu=-pask2[1]/2./pask2[2]\n", "estsigma=-1/pask2[2]\n", "plot(estmu,estsigma,'.')\n", "xlabel('est. mu')\n", "ylabel('est. sigma')" ] }, { "cell_type": "code", "execution_count": 59, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(-33.41713154465355, 4.293518519088544)" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "estamp=pask2[0]+pask2[1]**2/4/pask2[2]\n", "plot(estmu,estamp,'.')\n", "estamp.mean(),estamp.std()" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "korelace urcenych parametru: 0.00034128037287813897\n" ] }, { "data": { "text/plain": [ "((0.023331361105216716, 0.03305238767076496),\n", " (0.0164531770902861, 0.05591150621188542))" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print(\"korelace urcenych parametru:\",corrcoef(estmu,estsigma)[0,1])\n", "(mux.std(),estmu.std()),(sigx.std(),estsigma.std())" ] }, { "cell_type": "code", "execution_count": 61, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([-34686.15855586, 10824.42376684, 237.17082451])" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "r_[1,1e4,1e2].dot(T)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "0.707*p1 - 3.67*p2 + 20.5*p3\n", "1.22*p2 - 14.23*p3\n", "2.37*p3" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([[ 0.70710678, 0. , 0. ],\n", " [ -3.67423461, 1.22474487, 0. ],\n", " [ 20.55480479, -14.23024947, 2.37170825]])" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "T" ] } ], "metadata": { "anaconda-cloud": {}, "desrip": "pracovni verze", "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": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 2 }