{"nbformat_minor": 0, "worksheets": [{"cells": [{"source": ["Convex Region-Based Image Segmentation\n", "======================================\n", "\n*Important:* Please read the [installation page](http://gpeyre.github.io/numerical-tours/installation_matlab/) for details about how to install the toolboxes.\n", "$\\newcommand{\\dotp}[2]{\\langle #1, #2 \\rangle}$\n", "$\\newcommand{\\enscond}[2]{\\lbrace #1, #2 \\rbrace}$\n", "$\\newcommand{\\pd}[2]{ \\frac{ \\partial #1}{\\partial #2} }$\n", "$\\newcommand{\\umin}[1]{\\underset{#1}{\\min}\\;}$\n", "$\\newcommand{\\umax}[1]{\\underset{#1}{\\max}\\;}$\n", "$\\newcommand{\\umin}[1]{\\underset{#1}{\\min}\\;}$\n", "$\\newcommand{\\uargmin}[1]{\\underset{#1}{argmin}\\;}$\n", "$\\newcommand{\\norm}[1]{\\|#1\\|}$\n", "$\\newcommand{\\abs}[1]{\\left|#1\\right|}$\n", "$\\newcommand{\\choice}[1]{ \\left\\{ \\begin{array}{l} #1 \\end{array} \\right. }$\n", "$\\newcommand{\\pa}[1]{\\left(#1\\right)}$\n", "$\\newcommand{\\diag}[1]{{diag}\\left( #1 \\right)}$\n", "$\\newcommand{\\qandq}{\\quad\\text{and}\\quad}$\n", "$\\newcommand{\\qwhereq}{\\quad\\text{where}\\quad}$\n", "$\\newcommand{\\qifq}{ \\quad \\text{if} \\quad }$\n", "$\\newcommand{\\qarrq}{ \\quad \\Longrightarrow \\quad }$\n", "$\\newcommand{\\ZZ}{\\mathbb{Z}}$\n", "$\\newcommand{\\CC}{\\mathbb{C}}$\n", "$\\newcommand{\\RR}{\\mathbb{R}}$\n", "$\\newcommand{\\EE}{\\mathbb{E}}$\n", "$\\newcommand{\\Zz}{\\mathcal{Z}}$\n", "$\\newcommand{\\Ww}{\\mathcal{W}}$\n", "$\\newcommand{\\Vv}{\\mathcal{V}}$\n", "$\\newcommand{\\Nn}{\\mathcal{N}}$\n", "$\\newcommand{\\NN}{\\mathcal{N}}$\n", "$\\newcommand{\\Hh}{\\mathcal{H}}$\n", "$\\newcommand{\\Bb}{\\mathcal{B}}$\n", "$\\newcommand{\\Ee}{\\mathcal{E}}$\n", "$\\newcommand{\\Cc}{\\mathcal{C}}$\n", "$\\newcommand{\\Gg}{\\mathcal{G}}$\n", "$\\newcommand{\\Ss}{\\mathcal{S}}$\n", "$\\newcommand{\\Pp}{\\mathcal{P}}$\n", "$\\newcommand{\\Ff}{\\mathcal{F}}$\n", "$\\newcommand{\\Xx}{\\mathcal{X}}$\n", "$\\newcommand{\\Mm}{\\mathcal{M}}$\n", "$\\newcommand{\\Ii}{\\mathcal{I}}$\n", "$\\newcommand{\\Dd}{\\mathcal{D}}$\n", "$\\newcommand{\\Ll}{\\mathcal{L}}$\n", "$\\newcommand{\\Tt}{\\mathcal{T}}$\n", "$\\newcommand{\\si}{\\sigma}$\n", "$\\newcommand{\\al}{\\alpha}$\n", "$\\newcommand{\\la}{\\lambda}$\n", "$\\newcommand{\\ga}{\\gamma}$\n", "$\\newcommand{\\Ga}{\\Gamma}$\n", "$\\newcommand{\\La}{\\Lambda}$\n", "$\\newcommand{\\si}{\\sigma}$\n", "$\\newcommand{\\Si}{\\Sigma}$\n", "$\\newcommand{\\be}{\\beta}$\n", "$\\newcommand{\\de}{\\delta}$\n", "$\\newcommand{\\De}{\\Delta}$\n", "$\\newcommand{\\phi}{\\varphi}$\n", "$\\newcommand{\\th}{\\theta}$\n", "$\\newcommand{\\om}{\\omega}$\n", "$\\newcommand{\\Om}{\\Omega}$\n"], "metadata": {}, "cell_type": "markdown"}, {"source": ["This numerical tour explores a convex relaxation of the piecewise\n", "constant Mumford-Shah. This relaxation is exact, and leads to a global\n", "solution to the segmentation problem. It can be solved using proximal\n", "splitting scheme, and we propose to use here the Douglas-Rachford\n", "algorithm. Of independent interest is the introduction of auxiliary\n", "gradient variables that enables the use of purely primal splitting\n", "schemes.\n", "\n", "\n", "Special thanks to Jalal Fadili for telling me about the \"auxiliary variable\"\n", "trick (i.e. adding the variable $u=\\nabla f$),\n", "that allows one to solve TV regularization without the need to use\n", "primal-dual schemes."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 2, "cell_type": "code", "language": "python", "metadata": {}, "input": ["addpath('toolbox_signal')\n", "addpath('toolbox_general')\n", "addpath('solutions/segmentation_4_convex_segmentation')"]}, {"source": ["Binary Segmentation \n", "--------------------\n", "We consider some input image $I(x) \\in \\RR^d$ ($d=1$ for grayscale\n", "image and $d=3$ for color images).\n", "Given weights $w_0$ and $w_1$ computed from $I$, where\n", "$N$ is the number of pixel, the goal is to find a region $\\Om$ that\n", "minimize\n", "$$ \\umin{\\Om} \\int_\\Om w_0(x) d x + \\int_{\\Om^c} w_1(x) d x + \\la \\abs{\\partial \\Om}, $$\n", "where $\\abs{\\partial \\Om}$ is the perimeter of $\\Om$.\n", "\n", "\n", "To perform region based piecewise-constant segmentation, we assume we\n", "know the target values $c_0, c_1 \\in \\RR^d$ for the inside/outside of\n", "the segmented domain, and use quadratic weigths\n", "$$ \\text{for } i=0,1, \\quad w_i(x) = \\norm{I(x)-c_i}^2. $$\n", "We use these weights in all the remaining part of this tour.\n", "\n", "\n", "In the special case $\\la=0$, no regularization is performed, and the\n", "optimal set\n", "$$ is obtained by a simple thresholding\n", "$$ \\Om = \\enscond{x}{ w_0(x) \\leq w_1(x). } $$\n", "\n", "\n", "We load the image $I$."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 3, "cell_type": "code", "language": "python", "metadata": {}, "input": ["name = 'hibiscus';\n", "n = 256;\n", "I = rescale( load_image(name,n) );"]}, {"source": ["Display it."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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Whp2Zq4YWY0lSG/LEUNrP76p0OXjXXLtk9gdZ8LGwBLBPFCsjQ3FACan6DR12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\nfK7MI8JTmax3swhetDTRoy+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4gXlWHcDXX9Kt6BwwpNAZ4fEA8GS79K2ESeu5A8c81H5j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Xc//qF5tQYku6COFMm89Bn4H8nbDcAHE79k/LIBvDdj1bYMoVe5QI8cruRSfw6SXZN/dCE1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\nNjY2Nl4k/y+LbUxDHjQLOgAAAABJRU5ErkJggg==\n", "output_type": "display_data"}], "prompt_number": 4, "cell_type": "code", "language": "python", "metadata": {}, "input": ["clf;\n", "imageplot(I);"]}, {"source": ["Take as target colors red and green."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 5, "cell_type": "code", "language": "python", "metadata": {}, "input": ["c0 = [1;0;0];\n", "c1 = [0;1;0];"]}, {"source": ["__Exercise 1__\n", "\n", "Compute $w_0$ and $w_1$. Compute and display the segmentation when\n", "$\\la=0$."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 6, "cell_type": "code", "language": "python", "metadata": {}, "input": ["exo1()"]}, {"collapsed": false, "outputs": [], "prompt_number": 7, "cell_type": "code", "language": "python", "metadata": {}, "input": ["%% Insert your code here."]}, {"source": ["Define $w=w_0-w_1$."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 8, "cell_type": "code", "language": "python", "metadata": {}, "input": ["w = w0-w1;"]}, {"source": ["Convex Discrete Formulation\n", "---------------------------\n", "If one represents $\\Om$ using its indicator function $f$\n", "$$ f(x) = \\chi_\\Om(x) = \\choice{\n", " 1 \\qifq x \\in \\Om. \\\\\n", " 0 \\quad \\text{otherwise},\n", " } $$\n", "this problem is re-casted equivalently\n", "$$ \\umin{ f(x) \\in \\{0,1\\} } \\dotp{f}{w} + \\la \\norm{f}_{\\text{TV}}, $$\n", "where $w=w_0-w_1$ and $\\norm{f}_{\\text{TV}}$ is the total variation\n", "pseudo-norm, that is equal to $\\abs{\\partial \\Om}$ for binary indicator $f=\\chi_\\Om$.\n", "Here the inner product is the canonical one $\\dotp{f}{w}=\\int f w$.\n", "\n", "\n", "The variational problem is discretized on a grid of $N=n \\times n$ pixels, and we define the\n", "total variation pseudo-norm, for $f \\in \\RR^N$, as\n", "$$ \\norm{f}_{\\text{TV}} = \\norm{\\nabla f}_1\n", " \\qwhereq \\norm{u}_1 = \\sum_{i=1}^N \\norm{u_i}, $$\n", "when $u=(u_i)_{i=1}^N \\in \\RR^{N \\times 2}, u_i \\in \\RR^2 $ is a vector\n", "field.\n", "\n", "\n", "We use a finite difference gradient operator\n", "$$ (\\nabla f)_i = (f_{i+\\de_1}-f_i, f_{i+\\de_2}-f_i) \\in \\RR^2, $$\n", "(we assume the pixels are indexed on a 2-D grid)\n", "where $\\de_1=(1,0)$ and $\\de_2=(0,1)$.\n", "We use periodic boundary conditions for simplicity."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 9, "cell_type": "code", "language": "python", "metadata": {}, "input": ["options.bound = 'per';\n", "Grad = @(x)grad(x,options);\n", "Div = @(x)div(x,options);"]}, {"source": ["The inner product in the objective is discretized using the canonical\n", "inner product in $\\RR^N$\n", "$$ \\dotp{f}{w} = \\sum_{i=1}^N f_i w_i . $$\n", "\n", "\n", "To obtain a convex program, one replaces the binary constraint $f_i \\in \\{0,1\\}$\n", "by a box constraint $ f_i \\in [0,1] $. This defines the folowing finite\n", "dimensional convex problem\n", "$$ \\umin{ f \\in [0,1]^N } \\dotp{f}{w} + \\la \\norm{\\nabla f}_{1}. $$\n", "\n", "\n", "One can prove that this relaxation is exact, meaning that the minimizer $f$,\n", "when it is unique, is binary, $f \\in \\{0,1\\}^N$. It means that $\\Om$ such that $f=\\chi_\\Om$\n", "actually solves the original segmentation problem. See for instance:\n", "\n", "\n", "Tony F. Chan, Selim Esedoglu, and Mila Nikolova.\n", "_Algorithms for finding global minimizers of image segmentation and denoising models_\n", "SIAM J. Appl. Math., 66(5):1632-1648, 2006.\n", "\n", "\n", "It is possible to generalize this convexification method to the\n", "segmentation problem with more than 2 partitions. See for instance:\n", "\n", "\n", "Antonin Chambolle, Daniel Cremers, Thomas Pock,\n", "_A convex approach to minimal partitions,_\n", "Preprint hal-00630947, 2011.\n", "\n", "\n", "To solve this problem using primal proximal splitting scheme, we\n", "introduce an auxiliary variable $u=\\nabla f$, and write the\n", "optimization problem as\n", "$$ \\umin{z=(f,u) \\in \\Zz = \\RR^N \\times \\RR^{N \\times 2} } F(z) + G(z)\n", " \\qwhereq \\choice{\n", " F(f,u) = \\dotp{f}{w} + \\iota_{[0,1]^N}(f) + \\la \\norm{u}_1, \\\\\n", " G(f,u) = \\iota_{\\Cc}(f,u),\n", " } $$\n", "where here we included the constraints using indicator functions\n", " $$ \\iota_{A}(z) = \\choice{\n", " 0 \\qifq z \\in A, \\\\\n", " +\\infty \\quad \\text{otherwise}. } $$\n", "The constraint linking $f$ to $u$ is\n", " $$ \\Cc = \\enscond{z = (f,u) \\in \\Zz}{ u=\\nabla f }. $$\n", "\n", "\n", "Douglas-Rachford Algorithm\n", "--------------------------\n", "To minimize the segmentation energy, we will make use of proximal\n", "splitting scheme. These scheme are adapted to solve structured non-smooth\n", "optimization problem.\n", "\n", "\n", "They basically replace the traditional gradient-descent step (that is not\n", "available because neither $F$ nor $G$ are smooth functionals) by\n", "proximal mappings, defined as\n", "$$ \\text{Prox}_{\\gamma F}(z) = \\uargmin{y} \\frac{1}{2}\\norm{z-y}^2 + \\ga F(y) $$\n", "(the same definition applies also for $G$).\n", "\n", "\n", "The Douglas-Rachford (DR) algorithm is an iterative scheme to minimize\n", "functionals of the form\n", "$$ \\umin{z} F(z) + G(z) $$\n", "where $F$ and $G$ are convex functions for which one is able to\n", "comptue the proximal mappings $ \\text{Prox}_{\\gamma F} $ and\n", "$ \\text{Prox}_{\\gamma G} $.\n", "\n", "\n", "The important point is that $F$ and $G$ do not need to be smooth.\n", "One onely needs then to be \"proximable\".\n", "\n", "\n", "A DR iteration reads\n", "$$ \\tilde z_{k+1} = \\pa{1-\\frac{\\mu}{2}} \\tilde z_k +\n", " \\frac{\\mu}{2} \\text{rPox}_{\\gamma G}( \\text{rProx}_{\\gamma F}(\\tilde z_k) )\n", " \\qandq z_{k+1} = \\text{Prox}_{\\gamma F}(\\tilde z_{k+1},) $$\n", "\n", "\n", "\n", "We have use the following shortcuts:\n", "$$ \\text{rProx}_{\\gamma F}(z) = 2\\text{Prox}_{\\gamma F}(z)-z $$\n", "\n", "\n", "It is of course possible to inter-change the roles of $F$ and $G$,\n", "which defines another set of iterations.\n", "\n", "\n", "One can show that for any value of $\\gamma>0$, any $ 0 < \\mu < 2 $,\n", "and any $\\tilde z_0$, $z_k \\rightarrow z^\\star$\n", "which is a minimizer of $F+G$.\n", "\n", "\n", "Please note that it is actually $z_k$ that converges, and not $\\tilde\n", "z_k$.\n", "\n", "\n", "To learn more about this algorithm, you can read:\n", "\n", "\n", "_Proximal Splitting Methods in Signal Processing_, Patrick L. Combettes\n", "and Jean-Christophe Pesquet, in: Fixed-Point Algorithms for Inverse\n", "Problems in Science and Engineering, New York: Springer-Verlag, 2010.\n", "\n", "\n", "Proximal Operator of $G$\n", "--------------------------\n", "The proximal mapping of $G$ is the orthogonal projection on the convex\n", "set $G$:\n", "$$ (\\tilde f, \\tilde u) = \\text{Prox}_{\\ga G}(f,u) = \\text{Proj}_\\Cc(f,u). $$\n", "\n", "\n", "It can be computed by solving a linear system of equations since\n", "$$ \\tilde u = \\nabla \\tilde f \\qwhereq\n", " \\tilde f = (\\text{Id}_N - \\Delta)^{-1}(f-\\text{div}(u)). $$\n", "Here, by convention, $\\Delta=\\text{div} \\circ \\nabla$ and\n", "$\\text{div}=-\\nabla^*$.\n", "\n", "\n", "Since we use periodic boundary conditions for the gradient operator, it\n", "is possible to solve this linear system in $O(N \\log(N))$ operations\n", "using the FFT algorithm. Note that a similar method can be used with\n", "non-periodic Neumann condition (this requires to extend by symmetry the\n", "image).\n", "\n", "\n", "One indeed has\n", "$$ \\forall \\om=(\\om_1,\\om_2), \\quad\n", " \\hat {\\tilde f}(\\om) = \\frac{\\hat g(\\om)}{K(\\om)} \\qwhereq\n", " K(\\om) = 1+4\\sin\\pa{\\frac{\\pi \\om_1}{n}}^2+4\\sin\\pa{\\frac{\\pi \\om_2}{n}}^2, $$\n", "where $g = f-\\text{div}(u)$ and\n", "where $\\hat g$ is the 2-D discrete Fourier transform of an image $g$.\n", "\n", "\n", "Compute $K(\\om)$."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 10, "cell_type": "code", "language": "python", "metadata": {}, "input": ["[X Y] = meshgrid(0:n-1, 0:n-1);\n", "K = 1 + 4*sin(X*pi/n).^2 + 4*sin(Y*pi/n).^2;"]}, {"source": ["Define Proj$_\\Cc$."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 11, "cell_type": "code", "language": "python", "metadata": {}, "input": ["Replicate = @(z)deal(z, Grad(z));\n", "ProjC = @(f,u)Replicate( real( ifft2( fft2( f - Div(u) ) ./ K ) ) );"]}, {"source": ["One has $\\text{Prox}_{\\ga G} = \\text{Proj}_{\\Cc}$, whatever the value\n", "of $\\ga$."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 12, "cell_type": "code", "language": "python", "metadata": {}, "input": ["ProxG = @(f,u,gamma)ProjC(f,u);"]}, {"source": ["Proximal Operator of $F$\n", "--------------------------\n", "Recall that the function $F(f,u)$ is actully a separable sum of a function\n", "that only depends on $f$ and a function that depends only on $u$:\n", "$$ F(f,u) = F_0(f) + \\la \\norm{u}_1\n", " \\qwhereq F_0(f) = \\dotp{f}{w} + \\iota_{[0,1]^N}(f) $$\n", "The proximal operator of $F$ reads\n", "$$ \\text{Prox}_{\\ga F}(f,u) =\n", " ( \\text{Prox}_{\\ga F_0 }(f),\n", " \\text{Prox}_{\\ga \\la \\norm{\\cdot}_1 }(u) ). $$\n", "\n", "\n", "Define the value of $\\la>0$ (you can change this value)."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 13, "cell_type": "code", "language": "python", "metadata": {}, "input": ["lambda = .1;"]}, {"source": ["The proximal operator of $F_0$ is obtained by using the projection on the box\n", "constraint\n", "$$ \\text{Prox}_{\\ga F_0 }(f) = \\text{Proj}_{[0,1]^N}( f - \\ga w )\n", " \\qwhereq\n", " \\text{Proj}_{[0,1]^N}(g) = \\max(0,\\min(1, g)). $$"], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 14, "cell_type": "code", "language": "python", "metadata": {}, "input": ["ProxF0 = @(f,gamma)max(0, min(1, f-gamma*w) );"]}, {"source": ["The proximal operator of the $ \\ell^1-\\ell^2 $ norm $\\norm{\\cdot}_1$\n", "is a soft thresholding of the amplitude of the vector field:\n", "$$ \\text{Prox}_{\\ga \\norm{\\cdot}_1}(u)_i =\n", " \\max\\pa{ 0, \\frac{\\ga}{\\norm{u_i}} } u_i. $$"], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 15, "cell_type": "code", "language": "python", "metadata": {}, "input": ["amplitude = @(u)repmat( sqrt( sum(u.^2, 3) ), [1 1 2]);\n", "ProxL1 = @(u,gamma)max(0,1-gamma./max(1e-9, amplitude(u))) .* u;"]}, {"source": ["Define the proximal operator of $F$."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 16, "cell_type": "code", "language": "python", "metadata": {}, "input": ["ProxF = @(f,u,gamma)deal( ProxF0(f,gamma), ProxL1(u,gamma*lambda) );"]}, {"source": ["Douglas-Rachford for Convex Segmentation\n", "----------------------------------------\n", "Set the value of $\\mu$ and $\\gamma$.\n", "You might consider using your own value to speed up the convergence."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 17, "cell_type": "code", "language": "python", "metadata": {}, "input": ["mu = 1;\n", "gamma = 1;"]}, {"source": ["Number of iterations."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 18, "cell_type": "code", "language": "python", "metadata": {}, "input": ["niter = 800;"]}, {"source": ["__Exercise 2__\n", "\n", "Implement the DR iterative algorithm on |niter| iterations.\n", "Keep track of the evolution of the minimized energy\n", "$$ E(f) = \\dotp{w}{f} + \\la \\norm{\\nabla f}_1 $$\n", "during the iterations.\n", "_Remark:_ to speedup the convergence, you can use a \"clever\"\n", "initialization."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 19, "cell_type": "code", "language": "python", "metadata": {}, "input": ["exo2()"]}, {"collapsed": false, "outputs": [], "prompt_number": 20, "cell_type": "code", "language": "python", "metadata": {}, "input": ["%% Insert your code here."]}, {"source": ["Display the result image $f$ at convergence. Note that $f$ is almost\n", "binary."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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U7dq1mzNnDoC//vWv/v7+Yvn8lStXNljC448/rlbYRFLw9fWNiIgA0KFDB19f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\nBoMhNjZWLCVlDXFkZGTkqFG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"output_type": "display_data"}], "prompt_number": 21, "cell_type": "code", "language": "python", "metadata": {}, "input": ["clf;\n", "imageplot(f);"]}, {"source": ["__Exercise 3__\n", "\n", "Test with different value of the $\\lambda$ parameter."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 24, "cell_type": "code", "language": "python", "metadata": {}, "input": ["exo3()"]}, {"collapsed": false, "outputs": [], "prompt_number": 23, "cell_type": "code", "language": "python", "metadata": {}, "input": ["%% Insert your code here."]}], "metadata": {}}], "nbformat": 3, "metadata": {"kernelspec": {"name": "matlab_kernel", "language": "matlab", "display_name": "Matlab"}, "language_info": {"mimetype": "text/x-matlab", "name": "matlab", "file_extension": ".m", "help_links": [{"url": "https://github.com/calysto/metakernel/blob/master/metakernel/magics/README.md", "text": "MetaKernel Magics"}]}}}