{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Gaussian Process Regression\n", "\n", "In this notebook, we implement Gaussian Process regression described in chapter 6 of the book PRML. \n", "\n", "In short, Gaussian Process regression is essentially a Bayesian regression method, with the prior for the function to be estimated being Gaussian Process." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import numpy as np\n", "from scipy.linalg import eigh\n", "from scipy.optimize import minimize\n", "from matplotlib import pyplot as plt\n", "\n", "%matplotlib inline\n", "plt.rcParams['axes.labelsize'] = 14\n", "plt.rcParams['xtick.labelsize'] = 12\n", "plt.rcParams['ytick.labelsize'] = 12" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 1 Setting \n", "\n", "* Let $N \\in \\mathbb{N}$ be the number of data points. \n", "* Let $d \\in \\mathbb{N}$ be the dimension of input data.\n", "* Denote input data by $x_0, x_1, \\dots , x_{N-1} \\in \\mathbb{R}^d$, and output (label) data by $t_0, t_1, \\dots, t_{N-1} \\in \\mathbb{R}$. Also, let $t := (t_0, \\dots, t_{N-1})^T \\in \\mathbb{R}^N$." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2 Theory \n", "\n", "## 2.1 Gaussian Processes\n", "\n", "In the Gaussian process regression, we use Gaussian processes as a prior for the function to be estimated. \n", "In this section, we take a look at properties of Gaussian processes themselves.\n", "\n", "\n", "### 2.1.1 Definition\n", "\n", "A gaussian process is defined as a random variable over real-valued functions defined on a set $X$ (which will be taken to be $\\mathbb{R}^d$ in this notebook), with the property that, \n", "there exist $\\mu : X \\rightarrow \\mathbb{R}$ and $k: X \\times X \\rightarrow \\mathbb{R}$ such that, \n", "for an arbitrary $N \\in \\mathbb{N}$ and arbitrary $x_0, x_1, \\dots, x_{N-1} \\in X$, \n", "the value of the function $y : X \\rightarrow \\mathbb{R}$ \n", "generated from the Gaussian process on the points $x_0, x_1, \\dots, x_{N-1} \\in X$ has the joint probability density \n", "$$\n", "\\begin{align}\n", " p\\left(y(x_0), y(x_1), \\dots, y(x_{N-1}) \\middle| \\mu,k \\right) \n", " = \\mathcal{N}\\left((y(x_0), y(x_1), \\dots, y(x_{N-1}) )^T \\middle| M, K \\right), \n", "\\end{align}\n", "$$\n", "where\n", "$$\n", "\\begin{align}\n", " \\mathcal{N} &: \\mbox{ probability density of Gaussian distribution} \\\\\n", " M &:= \\left(\\mu(x_0), \\mu(x_1), \\dots, \\mu(x_{N-1}) \\right)^T \\ \\ \\in \\mathbb{R}^N \\\\\n", " K &:= \\left( K_{i,j} \\right)_{i,j = 0, \\dots, N-1}, \\ \\ K_{i,j} = k(x_i, x_j), \n", " \\mbox{ with $K$ being positive definite}\n", "\\end{align}\n", "$$\n", "\n", "We call the function $k$ a kernel function. \n", "\n", "Note : The definition given above is by no means mathematically rigorous, but practically sufficient, because we only care about finite input data points, i.e., finite $N$.\n", "\n", "\n", "### 2.1.2 Mean and Variance\n", "\n", "From the definition above, if follows that\n", "\n", "$$\n", "\\begin{align}\n", " & \\mathbb{E}[y(x_n)] = M_n \\\\\n", " & \\mathbb{E}\\left[\\left(y(x_n)-M_n \\right) \\left( y(x_m) - M_m\\right) \\right] = K_{n,m}\n", "\\end{align}\n", "$$\n", "\n", "In applications, we usually take $\\mu$ to be 0, which we assume henceforth." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.2 GP regression\n", "\n", "### 2.2.1 Likelihood\n", "\n", "For input data $x_n$, we assume that the output $t_n$ follows the following probability distribution\n", "$$\n", "\\begin{align}\n", " p\\left(t_n \\middle| y(x_n) \\right) = \\mathcal{N}\\left(t_n \\middle| y(x_n), \\beta^{-1} \\right), \n", "\\end{align}\n", "$$\n", "i.e., $t_n$ is given by $y(x_n)$ plus Gaussian noise. \n", "By assuming the noises are independent, we have\n", "$$\n", "\\begin{align}\n", " p \\left( t\\middle| y \\right) = \\mathcal{N} \\left( t \\middle| y, \\beta^{-1} I_N \\right) , \n", "\\end{align}\n", "$$\n", "where $y := (y(x_0), y(x_1), \\dots, y(x_{N-1}))^T$ and $I_N$ is the $N$ dimensional indentity matrix. \n", "\n", "### 2.2.2 Predictive distribution\n", "\n", "Given \n", "$$\n", "\\begin{align}\n", " \\mbox{prior : } p(y) &= \\mathcal{N}\\left(y \\middle| M,K \\right) \\\\\n", " \\mbox{likelihood : } p(t|y) &= \\mathcal{N}\\left(t \\middle| y, \\beta^{-1} I_N \\right), \n", "\\end{align}\n", "$$\n", "we can calculate the predictive distribution. \n", "\n", "Let us make the situation clearer: we are given with $N$ training data points $(x_0, t_0), (x_1, t_1), \\dots, (x_{N-1},t_{N-1})$ and want to know the distribution over the output $\\tau$ with respect to the next input $\\xi$. \n", "By denoting \n", "$$\n", "\\begin{align}\n", " t &:= (t_0, t_1, \\dots, t_{N-1})^T \\\\\n", " t' &:= (t_0, t_1, \\dots, t_{N-1}, \\tau)^T\n", "\\end{align}\n", "$$\n", "we can write the probability we want as $p(\\tau| t )$ (Because the input data $x_0, x_1, \\dots, x_{N-1}, \\xi$ are fixed, we omit them from our formula). \n", "\n", "For that aim, we first calculate the joint distribution $p(t')$ and then compute the conditional distribution from the joint distribution. \n", "The joint distribution $p(t')$ is given by (from PRML (6.61), (6.64), which can be derived from (2.115))\n", "$$\n", "\\begin{align}\n", " p(t') &= \\mathcal{N}(t'| 0, C'), \\\\\n", " C_{N+1} &= \n", " \\begin{pmatrix}\n", " C & \\kappa \\\\\n", " \\kappa^T & k(\\xi, \\xi) + \\beta^{-1}\n", " \\end{pmatrix}, \\\\\n", " \\kappa &\\in \\mathbb{R}^{N}, \\ \\ \\kappa_n = k(\\xi, x_n) \\\\\n", " C &:= K + \\beta^{-1} I_{N}\n", "\\end{align}\n", "$$\n", "By taking the conditional distribution, we have (PRML (6.67), (6.68), which can be derived from PRML(2.81), (2.82))\n", "$$\n", "\\begin{align}\n", " p(\\tau | t ) &= \\mathcal{N} (\\tau | m(\\xi), \\sigma^2(\\xi)), \\\\\n", " m(\\xi) &:= \\kappa^T C^{-1} t, \\\\\n", " \\sigma^2(\\xi) &:= k(\\xi, \\xi) + \\beta^{-1} - \\kappa^T C^{-1} \\kappa\n", "\\end{align}\n", "$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.3 Optimizing hyperparameters\n", "\n", "So far, we have assumed that the kernel function and the noise parameter $\\beta$ are fixed. However, finding appropriate $\\beta$ by hand is sometimes cumbersome. Moreover, it often happens that the kernel function itself is parametrized. In such cases, we would be better of if we can automatically determine the best hyperparameters from our data. \n", "\n", "In this section, we describe how this can be done. Specifically, we choose the set of hyperparameters which maximizes the marginal likelihood. \n", "\n", "Note that, by the word hyperparameters, here we mean $\\beta$ and kernel parameters collectively. \n", "Although not written explicitly in the textbook, we also perform the optimization over $\\beta$ simultaneously.\n", "\n", "### 2.3.1 Marginal likelihood\n", "\n", "Let us denote parameters by $\\theta$. \n", "We can express our marginal likelihood $p(t|\\beta, \\theta)$ as\n", "$$\n", "\\begin{align}\n", " & p(\\boldsymbol{t}|\\theta, \\beta) = \\mathcal{N}(\\boldsymbol{t} | 0, C) \\\\\n", " & C = K + \\beta^{-1} I_N\n", "\\end{align}\n", "$$\n", "\n", "Thus, the log marginal likelihood is given by\n", "$$\n", "\\begin{align}\n", " \\log p(t|\\beta, \\theta) = -\\frac{1}{2} \\log ({\\rm det} C) \n", " -\\frac{1}{2} t^T C^{-1} t -\\frac{N}{2} \\log (2\\pi)\n", "\\end{align}\n", "$$\n", "\n", "We regard it as a function of $\\theta$ and $\\beta$, and maximize this function. \n", "\n", "### 2.3.2 Gradient\n", "\n", "To perform the optimization, we also use the gradient, which is given by \n", "$$\n", "\\begin{align}\n", " \\frac{\\partial}{\\partial \\theta_i} \\log p(t|\\beta, \\theta) \n", " = -\\frac{1}{2} \\mathrm{Tr} \\left(C^{-1} \\frac{\\partial C}{\\partial \\theta_i} \\right) + \\frac{1}{2} t^T C^{-1} \\frac{\\partial C}{\\partial \\theta_i} C^{-1} t\n", "\\end{align}\n", "$$\n", "\n", "The gradient with respect to $\\beta$ has the same expression." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 3 From math to code\n", "\n", "We first define a class representing kernel function, and then move to write down a class performing GP regression." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3.1 Kernel\n", "\n", "### 3.1.1 Outline\n", "\n", "Following the API for kernel functions used in scikit-learn (see https://scikit-learn.org/stable/modules/gaussian_process.html#kernels-for-gaussian-processes ), we define our `MyKernel` object as follows: \n", "\n", "The attributes and methods of `MyKernel` (or any kernel that we can use for our `GPRegression` class) is as follows \n", "* `theta` attribute, which is assumed to be 1-D array stores kernel parameters.\n", "* `bounds` attribute, which is assumed to be 2-D list, stores bounds for parameters. It is assumed that i-th element has the form `bounds[i] = [a_i, b_i]`, where `a_i` and `b_i` respectively stand for the lower and upper bounds for i-th parameter.\n", "* `__call__` method : given (n_x, d) array `X` and (n_y, d) array `Y`, `MyKernel(X,Y)` returns a (n_x, n_y) array with `MyKernel(X,Y)[i_x, i_y] = K(X[i_x], Y[i_y])`, i.e., the kernel matrix. The `__call__` method also takes a parameter `eval_gradient`. If it is `True`, the method returns, in addition to the kernel matrix itself, the derivative of the kernel matrix w.r.t. each parameter.\n", "* `diag` method calculates diagonal elements of kernel matrix. It happens that we only need the diagonal elements of the kernel matrix. In such cases, although we can first compute the matrix and then extracting the diagonal, direct calculation of the diagonal is much faster.\n", "\n", "### 3.1.2 Concrete kernel function\n", "\n", "As our concrete kernel function, we use the kernel given by equation (6.63) in the book, \n", "$$\n", "\\begin{align}\n", " k_{\\theta}(x, y) = \\theta_0 \\exp\\left( -\\frac{\\theta_1}{2} \\| x - y \\|^2 \\right) + \\theta_2 + \\theta_3 x^T y\n", "\\end{align}\n", "$$\n", "with non-negative hyper parameters $\\theta_0, \\theta_1, \\theta_2, \\theta_3$\n", "(Note that the at least one of $\\theta_0, \\theta_2, \\theta_3$ has to be positive for $K$ to be positive definite.).\n", "\n", "\n", "The derivative of the kernel function with respect to kernel parameters are given as follows:\n", "$$\n", "\\begin{align}\n", " \\frac{\\partial}{\\partial \\theta_0} k_{\\theta}(x,y) &= \\exp\\left( -\\frac{\\theta_1}{2} \\| x - y \\|^2 \\right) \\\\\n", " \\frac{\\partial}{\\partial \\theta_1} k_{\\theta}(x,y) &= -\\frac{\\theta_0}{2} \\| x - y \\|^2 \\exp\\left( -\\frac{\\theta_1}{2} \\| x - y \\|^2\\right) \\\\\n", " \\frac{\\partial}{\\partial \\theta_2} k_{\\theta}(x,y) &= 1 \\\\\n", " \\frac{\\partial}{\\partial \\theta_3} k_{\\theta}(x,y) &= x^T y\n", "\\end{align}\n", "$$\n", "\n", "### 3.1.3 Code" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "class MyKernel:\n", " \n", " def __init__(self, theta, bounds=None):\n", " self.theta = theta\n", " self.bounds = bounds\n", " \n", " def __call__(self, X, Y, eval_gradient=False):\n", " '''\n", " This method calcualtes the kernel matrix for input points.\n", " \n", " Parameters\n", " ----------\n", " X, Y : 2-D numpy array\n", " numpy array representing input points. X[n, i] (resp. Y[n, i]) represents the i-th element of n-th point in X (resp Y).\n", " eval_gradientt : bool\n", " If True, the gradient of the kernel matrix w.r.t. to parameters are also returned.\n", " \n", " Returns\n", " ----------\n", " K : 2-D numpy array, shape = (len(X), len(Y))\n", " numpy array representing the kernel matrix. K[i, j] stands for k(X[i], Y[j])\n", " gradK : 3-D numpy array, shape = (len(self.theta), len(X), len(Y)), optional\n", " numpy array representing the gradient of kernel matrix. gradK[l, m, n] = derivative of K[m, n] w.r.t. self.theta[l]\n", " Returned only if return_std is True.\n", " '''\n", " \n", " tmp = np.reshape(np.sum(X**2,axis=1), (len(X), 1)) + np.sum(Y**2, axis=1) -2 * (X @ Y.T)\n", " K = self.theta[0]*np.exp(-self.theta[1]/2*tmp) + self.theta[2] + self.theta[3]*(X @ Y.T)\n", " \n", " if not(eval_gradient):\n", " return K\n", " else:\n", " gradK = np.zeros((len(self.theta), len(X), len(Y)))\n", " gradK[0] = np.exp(-self.theta[1]/2*tmp)\n", " gradK[1] = -self.theta[0]/2*tmp*np.exp(-self.theta[1]/2*tmp)\n", " gradK[2] = np.ones((len(X), len(Y)))\n", " gradK[3] = X @ Y.T\n", " return K, gradK\n", " \n", " def diag(self, X):\n", " '''\n", " This method calculates the diagonal elements of the kernel matrix.\n", " \n", " Parameters\n", " ----------\n", " X : 2-D numpy array\n", " numpy array representing input points. X[n, i] represents the i-th element of n-th point in X.\n", " \n", " Returns\n", " ----------\n", " diagK : 1-D numpy array\n", " numpy array representing the diagonal elements of the kernel matrix. diagK[n] = K[n, n]\n", " '''\n", " diagK = self.theta[0] + self.theta[2] + self.theta[3]*np.sum(X**2, axis=1) \n", " return diagK" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3.2 GP regression\n", "\n", "\n", "### 3.2.1 Outline \n", "\n", "We let our `GPRegression` class has the following properties:\n", "\n", "* `kernel` : an object representing kernel function, assumed to have `theta` and `bounds` attribute, and `__call__` and `diag` method. \n", "* `beta` : noise parameter\n", "* `X_train` : training input, which will be used for the prediction\n", "* `t_train` : training label, which will be used for the prediction\n", "* `Cinv` : $C^{-1}$. We calculate it in fitting procedure, because it will be frequently used for prediction.\n", "\n", "We define the following methods:\n", "\n", "* `fit` : The method performing fitting, where `Cinv` is calculated from training data and kernel. If `optimize_hparams` is `True`, it will optimize hyperparameters before the calculation of `Cinv`.\n", "* `predict` : The method performing prediction. If `return_std` is `True`, it will return predictive standard deviation.\n", "\n", "For hyperparameter optimization, we define our cost function `cost_and_grad` separately from `GPRegression` class." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.2.2 Fitting with fixed hyperparameters\n", "\n", "First, let us consider the case with fixed hyperparameters.\n", "\n", "For this case, we just need to calculate $C^{-1}$ (`Cinv`) by \n", "$$\n", "\\begin{align}\n", " & C = K + \\beta^{-1} I_N \\\\\n", " & K := \\left( K_{i,j} \\right)_{i,j = 0, \\dots, N-1}, \\ \\ K_{i,j} = k(x_i, x_j), \n", "\\end{align}\n", "$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.2.3 Prediction\n", "\n", "In the previous section, we gave predictive distribution\n", "$$\n", "\\begin{align}\n", " p(\\tau | t ) &= \\mathcal{N} (\\tau | m(\\xi), \\sigma^2(\\xi)), \\\\\n", " m(\\xi) &:= \\kappa^T C^{-1} t, \\\\\n", " \\sigma^2(\\xi) &:= k(\\xi, \\xi) + \\beta^{-1} - \\kappa^T C^{-1} \\kappa \\\\\n", " \\kappa &\\in \\mathbb{R}^N, \\ \\ \\kappa_n := k(\\xi, x_n)\n", "\\end{align}\n", "$$\n", "for one input $\\xi$. \n", "\n", "In real application, it is desirable to be able to calculate $m(\\xi_i), \\sigma(\\xi_i)$ for multiple input $\\xi_i$ with $i=0, \\dots, N_{test}-1$ (Note that the result tells nothing about joint distribution of $\\tau_0, \\dots, \\tau_{N_{test}-1}$.). Here we derive formula for that aim.\n", "\n", "Let us define some arrays as follows:\n", "\n", "* `mean` : ($N_{test}$, ) array, with `mean[i]` = $m(\\xi_i)$\n", "* `std` : ($N_{test}$, ) array, with `std[i]` = $\\sigma(\\xi_i)$\n", "* `kappa` : ($N_{test}, N$) array, with `kappa[i, j]` = $k(\\xi_i, x_j)$\n", "\n", "Then, we have \n", "\n", "* `mean`[i] = $\\sum_{j, k}$ `kappa[i, j]` $\\left( C^{-1} \\right)_{j, k} t_k$ \n", "* (`std[i]`)**2 = $k(\\xi_i, \\xi_i) + \\beta^{-1} - \\sum_{j, k}$ `kappa[i, j]` $\\left(C^{(-1)} \\right)_{j,k} $ `kappa[i, k]`\n", "\n", "This formula is used in coding `predict` method." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.2.4 Hyperparameter optimization \n", "\n", "As was stated, the log marginal likelihood, which we want to maximize, and its derivative are given by\n", "$$\n", "\\begin{align}\n", " \\log p(t|\\beta, \\theta) &= -\\frac{1}{2} \\log ({\\rm det} C) \n", " -\\frac{1}{2} t^T C^{-1} t -\\frac{N}{2} \\log (2\\pi) \\\\\n", " \\frac{\\partial}{\\partial \\theta_i} \\log p(t|\\beta, \\theta) \n", " &= -\\frac{1}{2} \\mathrm{Tr} \\left(C^{-1} \\frac{\\partial C}{\\partial \\theta_i} \\right) + \\frac{1}{2} t^T C^{-1} \\frac{\\partial C}{\\partial \\theta_i} C^{-1} t \\\\\n", " C &= K + \\beta^{-1} I_N\n", "\\end{align}\n", "$$\n", "\n", "Here we give a function that calculates these quantities. Note that, because we want to use `scipy.optimize.minimize` later, we let the function invert the sign. \n", "\n", "In addition, in calculating $\\log (\\mathrm{det}C)$, we do not calculate determinant directly to avoid underflow. Concretely, we first calculate eigenvalues $\\lambda_i$ ($i = 0, \\dots, N-1$)by `scipy.linalg.eigh`, and then use the relation\n", "$$\n", "\\begin{align}\n", " \\log(\\mathrm{det}C) \n", " = \\log \\left( \\prod_{i=0}^{N-1} \\lambda_i \\right)\n", " = \\sum_{i=0}^{N-1} \\log \\lambda_i\n", "\\end{align}\n", "$$" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def cost_and_grad(beta, theta, kernel, X, t, return_grad=False):\n", " '''\n", " The method calculates cost function (negative of log marginal likelihood) and its gradient\n", " \n", " Parameters\n", " ----------\n", " beta : float\n", " noise parameter (precision)\n", " theta : 1-D numpy array\n", " 1-D numpy array representing kernel parameteres\n", " kernel : kernel object\n", " An object representing kernel function\n", " X : 2-D numpy array\n", " Array representing input data, with X[n, i] being the i-th element of n-th point in X.\n", " t : 1-D numpy array\n", " Array representing label data.\n", " return_grad : bool\n", " If True, the function also returns the gradient of the cost function.\n", " \n", " Returns\n", " ----------\n", " val : float\n", " The value of the cost function\n", " grad : 1-D numpy array, optional\n", " Array representing the gradient of the cost function. Returned only if return_grad is True.\n", " '''\n", " kernel.theta = theta\n", " K, gradK = kernel(X, X, eval_gradient=True)\n", " C = K + 1.0/beta*np.identity(len(K))\n", " Cinv = np.linalg.inv(C)\n", " val = np.sum(np.log(eigh(C)[0])) + 0.5 * t @ Cinv @ t + 0.5*len(X)*np.log(2*np.pi)\n", " if not(return_grad):\n", " return val\n", " else:\n", " grad = np.zeros(len(theta)+1)\n", " grad[0] = -0.5*np.trace(Cinv)/(beta**2) + 0.5/(beta**2) * (t @ Cinv @ Cinv @ t)\n", " for cnt in range(len(theta)):\n", " grad[cnt+1] = 0.5 * np.trace(Cinv @ gradK[cnt]) - 0.5 * t @ Cinv @ gradK[cnt] @ Cinv @ t\n", " return val, grad" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.2.5 Code for GPRegression" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "class GPRegression:\n", " \n", " def __init__(self, kernel, beta):\n", " self.kernel = kernel\n", " self.beta = beta\n", " \n", " def fit(self, X, t, optimize_hparams=False):\n", " '''\n", " Parameters\n", " ----------\n", " X : 2-D numpy array\n", " Array representing training input data, with X[n, i] being the i-th element of n-th point in X.\n", " t : 1-D numpy array\n", " Array representing training label data.\n", " optimize_hparams : bool\n", " If True, optimization of hyperparameters (noise parameter and kernel parameters) is performed.\n", " '''\n", " self.X_train = X\n", " self.t_train = t\n", " if optimize_hparams:\n", " theta_old = np.copy(self.kernel.theta)\n", " bounds_full = np.concatenate(( [[0, None]], self.kernel.bounds ), axis=0)\n", " result = minimize(x0=np.append([self.beta], [self.kernel.theta]),\n", " fun=lambda x : cost_and_grad(beta=x[0], theta=x[1:], kernel=self.kernel, X=self.X_train, t=self.t_train, return_grad=True), \n", " jac=True,\n", " bounds=bounds_full)\n", " if not(result.success):\n", " print(result.message)\n", " self.kernel.theta = theta_old\n", " else:\n", " print(result.message)\n", " self.beta = result.x[0]\n", " self.kernel.theta = result.x[1:]\n", " self.Cinv = np.linalg.inv( self.kernel(self.X_train, self.X_train) + 1.0/self.beta*np.identity(len(self.X_train)) )\n", " \n", " \n", " def predict(self, X, return_std=False):\n", " ''' \n", " Parameters\n", " ----------\n", " X : 2-D numpy array\n", " Array representing test input data, with X[n, i] being the i-th element of n-th point in X.\n", " return_std : bool\n", " If True, predictive standard deviation is also returned.\n", " \n", " Returns\n", " ----------\n", " mean : 1-D numpy array\n", " Array representing predictive mean.\n", " std : 1-D numpy array, optional\n", " Array reprensenting predictive standard deviation, returned only if return_std is True.\n", " '''\n", " kappa = self.kernel(X, self.X_train)\n", " mean = kappa @ (self.Cinv @ self.t_train)\n", " if not(return_std):\n", " return mean\n", " else:\n", " std = np.sqrt( self.kernel.diag(X) + 1.0/self.beta - np.diag( kappa @ self.Cinv @ (kappa.T) ) )\n", " return mean, std" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 4 Experiment\n", "\n", "Having defined all the classes and functions we need, finally we proceed to experiment. \n", "In the example, we consider one dimensional i.e., $d=1$ case.\n", "\n", "## 4.1 Gaussian Process and kernel functions\n", "\n", "Before performing Gaussian process regression, let us take a look at how parameters in kernel affect functions sampled from Gaussian processes." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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y8gt4/qfdVPHzZEK/xmbHcSgNQivx/I2NWXMonrmbT5odRwhzxO6zzrSM86q1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8iT+ew87lMRRkVNw4Vanh/B/p/PTBSUpyqhjzdIiUhGgCd2UiQv2nEiLzcgnDHumC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4Zp9IcPjFipbPRT1RigvKH1e6M6kj0OcpNc9E920z/Zw5DUGLISXF06MOrMumJbrGmaHfgn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\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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "X = np.linspace(-1,1,101)\n", "X = np.reshape(X, (len(X),-1))\n", "Thts = np.array([[1.0, 4.0, 0.0, 0.0],\n", " [9.0, 4.0, 0.0, 0.0],\n", " [1.0, 64.0, 0.0,0.0],\n", " [1.0,0.25, 0.0, 0.0],\n", " [1.0, 4.0, 10.0, 0.0],\n", " [1.0, 4.0, 0.0, 5.0]\n", " ])\n", "\n", "num = 5\n", "cnt = 0\n", "fig = plt.figure(figsize=(18,10))\n", "while cnt < len(Thts):\n", " theta = Thts[cnt]\n", " kernel = MyKernel(theta)\n", " Kmat = kernel(X, X)\n", " yy = np.random.multivariate_normal(np.zeros(len(X)), Kmat, num)\n", " ax = fig.add_subplot(2,3,cnt+1)\n", " for y in yy:\n", " ax.plot(X, y)\n", " ax.set_title(f\"theta=({theta[0]}, {theta[1]}, {theta[2]}, {theta[3]})\")\n", " cnt += 1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It can be seen that $\\theta_1$ determines the scale of change(smaller $\\theta_1$ means more oscillation)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4.2 Data\n", "\n", "We use the following toy data for our regression task." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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NA8YxFQZBs/gVKNgOI/87+KMFZTIug5P7uuOgS0t9p5FYsnGae6/1BRGRmnUV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\npgRuu6JIWPS+HBa9BBv/7bYwSs2tnQQ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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def truef(x):\n", " return np.sin(2*x) + 0.2*np.sin(x) + 0.1*x\n", "\n", "N = 50\n", "X = np.random.uniform(-3, 3, N)\n", "ep = 0.3*np.random.randn(N)\n", "t = truef(X) + ep\n", "\n", "Xcont = np.linspace(np.min(X),np.max(X),200) # for plotting\n", "\n", "plt.figure(figsize=(8,6))\n", "plt.plot(X, t,'.', label='training data')\n", "plt.plot(Xcont, truef(Xcont), label='ground truth')\n", "plt.xlabel(r'$x$')\n", "plt.ylabel(r'$t$')\n", "plt.legend()\n", "plt.show()\n", "\n", "X = np.reshape(X,(len(X),1))\n", "Xtest = np.reshape(Xcont,(len(Xcont),1))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4.3 Regression (with fixed hyperparameters)\n", "\n", "First, let us perform Gaussian process regression with given hyperparameters. \n", "We try several hyperparameters and see how they affect the result." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def plot_result(pred_mean, pred_std, ax=None):\n", " if ax is None:\n", " fig = plt.figure(figsize=(8,6))\n", " ax = fig.add_subplot(111)\n", " ax.plot(X, t,'.',label='training data')\n", " ax.plot(Xcont, pred_mean, label='predictive mean')\n", " ax.plot(Xcont, truef(Xcont), ':', label='ground truth')\n", " ax.fill_between(Xcont, pred_mean + pred_std, pred_mean - pred_std, alpha=0.2)\n", " ax.set_xlabel(r'$x$')\n", " ax.set_ylabel(r'$t$')\n", " ax.legend()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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CKdVqfww3AEWB8veA+Un6bnLMft8PiFtzGShb5hVUGS7ErU+grAiXAGkzbt3i\nv4FjAuUL/HEEt7vj+t9FKfv9/xc4xjW4cOv8QPkXcJEiFbhwtTuA3oHyiTijvxq3TObLcf1fhDO+\nt+McGCP9/sO9nDVx5/8wX74Pzlte4+fgZc1cxwU0ncNtuq622aZqephO0sMJ2sfLOdbrjlIv27PA\n3oHyJnrYt4/Xh2MC5yS+bGmgbVJ9l4ZeORX3dLUGl9Dz6LjjujvB2At8meB07ye4+8AHwFmBtg/4\n46/C6fJvx/V9Ks5RUYlz5PySnfOzWV0KvOyPdwcuEd3pgbKv4eZ0Ne7+80d2/eHQ3H0tqVyBufKu\nP64VJMl1ZFvP3jBdnBW62O9r7v89aMNdhrP9avx1+h3QN1B3EO6BVjVO750RKLsLly8pqGvfSzJm\nk+vl9xXhnNNHJqifyq7vh3O2VAbmVzDv3HCcQ+dzSWRJaosD04GVuKUt/wamB8oEl0ulzG/Xs9MR\nfzhON8d+I7xIwHmBcxaF487XM4HyG3A2eBVuueQusjd3zbvSFjthRhdHRI7FJRYanWlZDMMweiKm\nhw3DMDKP6WLD6FlYDo0uioj0EpHjRCRPRIbjniA9kWm5DMMwegqmhw3DMDKP6WLD6NlYhEYXxb/l\n4kVc7oNaXOjbd1R1R/ybPAIcq0ne+GAYhmG0DNPDhmEYmcd0sWH0bMyhYRiGYRiGYRiGYRhGl8OW\nnBiGYRiGYRiGYRiG0eXIy7QAmWDIkCE6ZsyYTIthGIbRhJUrV25T1aGZlqOzMF1sGEY2ki26WEQK\nca8rnot7O8R/gR+q6jNJ6n8X92rHXsBjwEWqWt/cGKaHDcPIRlqih3ukQ2PMmDGsWLEi02IYhmE0\nQUTWZ1qGzsR0sWEY2UgW6eI83CskD8e94vI44GERmayq64IVReRo4Pu4VxBvwiXF/InflxTTw4Zh\nZCMt0cO25MQwDMMwDMMwsgxVrVbVRaq6TlWjqvoXYC0wM0H1s4HFqvqeqm4Hfgos6ERxDcMwMoI5\nNAzDMAzDMAwjyxGRYcA+wHsJiicCbwe+vw0ME5HBCfpZKCIrRGRFSUlJxwhrGIbRSWSdQ0NECkVk\nsYisF5FKEXlTRI5tpv53RWSLiFSIyJ1+vaFhGIZhGIZhdAtEJB9YAtyjqqsSVCkGKgLfY5/7xldU\n1dtVdZaqzho6NOOpQgzDMNpENubQ6PD1gokIhUJs3LiRurq6tklvZAVFRUWMGDGC/Pz8TItiGIZh\ndBPMVuhedBVbQURygHuBBuCSJNWqgH6B77HPlS0dz+Z596KrzHPDaC1Z59BQ1WpgUWDXX0Qktl5w\nXVz1xvWCACLyU5z3usUOjY2XpWZWAAAgAElEQVQbN9K3b1/GjBmDiLRGdCNLUFVKS0vZuHEjY8eO\nzbQ4hmEYRjfBbIXuQ1exFcRNtMXAMOA4VQ0lqfoeMBV42H+fCmxV1dKWjmnzvPvQVea5YbSFrFty\nEk9nrResq6tj8ODBpri7ASLC4MGD7cmCYRiG0a6YrdB96EK2wh+ACcCJqlrbTL0/AueKyH4iMhC4\nCri7NQPaPO8+dKF5bhitJqsdGp29XtAUd/fBrqVhGIbREdj9pfuQ7ddSREYDFwDTgC0iUuW3+SIy\nyn8eBaCqzwLXAy8A6/12TRvGbvsBGFmBXUuju5N1S05idPZ6QcMwDMMwDMPIFlR1PdDcr9HiuPq/\nBn7doUIZhmFkGVkZoRG3XvCraawXjNHq9YKZpry8nFtuuaVVbY877jjKy8ubrfPjH/+Y559/vlX9\nN8fdd9/NJZck8zc5li5dyquvvtruYxuGYRhGT8JsBaMnYPPcMIyWkJUODTKwXjDTNKe8I5FIs22f\nfvppBgwY0Gyda6+9lrlz57ZavrZgyjsz1IUilFbVs6Wijq076iivaSAS1UyLZRiG0WNQVcLRKKFI\nlIZwlHAkimrr9bDZCkZPwOa5kQhVpay6gajZskYcWefQyOR6wZaycv12bn7hv6xcv73NfX3/+9/n\n448/Ztq0aVxxxRUsXbqUI444gjPOOIPJkycD8KUvfYmZM2cyceJEbr/99sa2Y8aMYdu2baxbt44J\nEyZw/vnnM3HiRI466ihqa50/aMGCBTz66KON9a+55hpmzJjB5MmTWbXKpScpKSnhi1/8IjNmzOCC\nCy5g9OjRbNu2bRdZ77rrLvbZZx8OP/xwXnnllcb9Tz31FAceeCDTp09n7ty5bN26lXXr1nHrrbfy\nm9/8hmnTpvHyyy8nrGe0H7UNEdZuq2b11io2lddRUlnPZzvq2VBWywebd7C5otYcG4ZhGB1MKBKl\nLhTljTVl3PzCf1mxroyGSJS6UIRQuHWODbMVjGzFbGKb5x3N2m3VfLq9lrWl1ebUMJqiqj1umzlz\npsbz/vvv77KvOVasK9N9r3pax37/L7rvVU/rinVlLWofz9q1a3XixImN31944QXt3bu3rlmzpnFf\naWmpqqrW1NToxIkTddu2baqqOnr0aC0pKdG1a9dqbm6uvvnmm6qqesopp+i9996rqqpnn322PvLI\nI431b7rpJlVVvfnmm/Xcc89VVdVvfvObet1116mq6jPPPKOAlpSUNJFz06ZNOnLkSP3ss8+0vr5e\nDznkEP3mN7+pqqplZWUajUZVVfWOO+7Qyy67TFVVr7nmGr3hhhsa+0hWr71p6TXtDmypqNV3NpSn\n3FZt3qE19eFMi2vEAazQLNCRnbUl0sWGkc2kc1+JRqNa1xDW6vqQvrK6RPf9kbcVfvS0vrK6RKvr\nQ1pdH9LahrBG/L0wXcxWaH8SXdOepIvNJu6587wrUVUXamLHbqus69Dx6kJhLa2q13CkZTraaD9a\nooezNilotvPamlIawlGiCqFwlNfWlDJz9MB2HeOAAw5o8s7om266iSeeeAKADRs2sHr1agYPbvqG\n2rFjxzJt2jQAZs6cybp16xL2/ZWvfKWxzuOPPw7AsmXLGvs/5phjGDhw1+N5/fXXmTNnDrE3xZx2\n2ml89NFHgHtv+WmnncbmzZtpaGhI+r7rdOsZ6aOqbCirpaI2WbqZpjSEo3xcUsXowb3pW5TfwdIZ\nhmH0DFSV+nCUqLqnh2/4qIyouoiNN9aVMW2UC4ePqtIQjlKQl0NOG95CYLaCkWnMJrZ53tGUVNY3\n+b6tqoFBfQo65A0uVfVh1m2rRtWNO25oH/Jzs25RgxHArk4rOWjcYArycsgVyM/L4aBxg1M3aiF9\n+vRp/Lx06VKef/55li9fzttvv8306dMTvlO6sLCw8XNubi7hcDhh37F6wTqq6YVvJVMe3/rWt7jk\nkkt49913ue2225K+8zrdekZ6qCrrS2vSdmbsbAfrS2uork88R4yejYgUishiEVkvIpUi8qaIHNtM\n/e+KyBYRqRCRO0WkMFldw+iOxDszAA4YM4iCXG8r5OZwwJhBTdrEnBrp3n8TYbaCkWnMJt4Vm+ft\nRygSpbKu6bVrCEfZUdf+9mtdKNLozIiNs6XCrkm2Yw6NVjJz9ECWnHcQlx21L0vOO6jNnui+fftS\nWZn8bbMVFRUMHDiQ3r17s2rVKl577bU2jZeIQw89lIcffhiA5557ju3bd10HeeCBB7J06VJKS0sJ\nhUI88sgjTWQcPnw4APfcc0/j/vhjS1bPaB0bt9fuoujTJebUqA83n2TL6JHkARuAw4H+wNXAwyIy\nJr6iiBwNfB84EhgDjAN+0klyGkZW4CIxmv4ImjZqAHcu2J9vHbk3dy7YvzE6I0hUlVAkmtYYZisY\n2YjZxDbPO5KqJDZuWXVDu44TiboHhPG+rPKaEFX28C+rMYdGG5g5eiDfPOJz7RJWN3jwYGbPns2k\nSZO44oordik/5phjCIfDTJkyhauvvpqDDjqozWPGc8011/Dcc88xY8YMnnnmGfbYYw/69u3bpM4e\ne+zBokWLOPjgg5k7dy4zZsxoLFu0aBGnnHIKhx12GEOGDGncf+KJJ/LEE080JkBKVs9oOZ9V1lFe\n07LIjHgiUWVDWY0lWDKaoKrVqrpIVdepalRV/wKsBWYmqH42sFhV31PV7cBPgQWdKK5hZJRQJJo0\n2fK0UQNY+PlxCZ0ZMcJRJZyGU8NsBSNbMZvY5nlHkeyhXVVduN0eyNWHI6wpqaIhnFgPxy95MbIL\naUuYY1dl1qxZumLFiib7PvjgAyZMmJAhibKD+vp6cnNzycvLY/ny5Vx00UW89dZbmRar1XT3a1pV\nH2ZtSXW79Te4uIA9B/Rqt/6MliMiK1V1VqblSISIDMO9SWqaqq6KK3sbuE5VH/LfhwAlwBBVLY2r\nuxBYCDBq1KiZ69ev7wzxDaNdSHRfiUaV+nCEtlpTAhTm57Ypn0Zn0BNshWzWxe2N2cSJ6QnzvCug\nqry/eQfRJP7e3foVMqxfUav6bghHKa9toKouTE1DZJfIjHj22b2YwrzcVo1ltJyW6GFLCmo08skn\nn3DqqacSjUYpKCjgjjvuyLRIRhLCkSgbymratc/Sqgb698qnT6GpBaMpIpIPLAHuiXdmeIqBisD3\n2Oe+QBOHhqreDtwOzpBuf2kNo/NQVRoi0TY7MwAUF+mR7Qaz2QpGT8DmeXZQ0xBJ6swAZ7sOLS4k\nJ6dljuCK2hAbt9c023c8ZdUN7NHfHvxlI/bLxWhk77335s0338y0GEYabCqvIxxp/9+Cn5bXsvdu\nxR2SNdromohIDnAv0ABckqRaFdAv8D32OfkiaMPoBoSjukvejLYQiSqRaJTcnOxdEWy2gtETsHme\nHaRKXB+JKqXVDQztm34e8qr6MBvKds2VkYqy6gZ271dkNnIWkr13TMMwElJRE2rxG03SpT4UZVtV\n+yZZMrou4u7ai4FhwFdVNdnEew+YGvg+Fdgav9zEMLoTUU0v70VLCUW0TW89MQzD6C5UN6TOkVFS\nWZ80h1E89eEInyRI/JkO0SjsqLXkoNmIOTQMowsRiSqbKmo7dIytO+rSzrhvdHv+AEwATlTV5ibe\nH4FzRWQ/ERkIXAXc3QnyGUbGCLXTUpN4oqppG+eGYRjdFVWlpiG1AyES1WYTegbrrS+taZN+3V5j\nD/2yEXNoGEYXYuuOjllqEkQVPrNszj0eERkNXABMA7aISJXf5ovIKP95FICqPgtcD7yASxy6Hrgm\nU7IbRkfjloZ0nC4ORy1KwzDA5QxrCEfs/6EHUh+Opp3joi4U5cMtlXy0tZL1pdV8tqOOulAkUO7e\nYlIfatsDu6r6sD30y0Ish4ZhdBHqQpF2f+d2MrZXNzCkuCDrk9MZHYeqrse9eCEZxXH1fw38ukOF\nMowsoaMN2liURl6urdU2ei6q2hgJJaLk2/9DjyJV/oxE1Iei1Iei7KgNs3VHPQV5OeSIc460h09M\n1eXSaO2bVYyOwSI0ujHFxe73xqZNmzj55JObrXvjjTdSU7PzrRnHHXcc5eXlHSqf0TI2V9S1izJO\nB1X4bIdFaRiGYcQTiUbbNRFoMjorSsNsBSNbiUS1cVlXOBJt0/+DzfOuR00a+TNS0RCOUhdqH2dG\njNKqBosYyjLModHFiERa/s+955578uijjzZbJ155P/300wwYMKDFYxkdw466EFV1nZuIqKI2RH24\n7TcTwzCM7kSog5f9xWhLLg2zFYzuQDgw/xV2+X+wed69aQ+HRkcQiSrbazomOb/ROsyhkSWsW7eO\n8ePHc/bZZzNlyhROPvnkRmU6ZswYrr32Wg499FAeeeQRPv74Y4455hhmzpzJYYcdxqpVqwBYu3Yt\nBx98MPvvvz9XX311k74nTZoEOOV/+eWXM3nyZKZMmcLvfvc7brrpJjZt2sQRRxzBEUcc0Tjmtm3b\nuPLKK7nlllsa+1q0aBG/+tWvALjhhhvYf//9mTJlCtdck3i5fHFxMVdeeSUzZ85k7ty5vPHGG8yZ\nM4dx48bx5z//uVGmK664orGv2267DYCqqiqOPPJIZsyYweTJk3nyyScbj2fChAmcf/75TJw4kaOO\nOora2o5NlJlJVJWtFXUZGNdljjYMwzAcUW3f17SmIhz3A85sBbMVegKxeX7uNxZwwMzpzD/9NGpq\naoiq2jzvIfPc5U7J3lwVm8prqfUOl0hUW7U8xmg/LIdGIp75Pmx5t3373H0yHPuLZqt8+OGHLF68\nmNmzZ/ONb3yDW265hcsvvxyAoqIili1bBsCRRx7Jrbfeyt57783rr7/OxRdfzD//+U++853vcNFF\nF/H1r3+dm2++OeEYt99+O2vXruXNN98kLy+PsrIyBg0axK9//WteeOEFhgwZ0qT+6aefzqWXXsrF\nF18MwMMPP8yzzz7Lc889x+rVq3njjTdQVebNm8dLL73E5z//+Sbtq6urmTNnDr/85S/58pe/zFVX\nXcXf//533n//fc4++2zmzZvH4sWL6d+/P//617+or69n9uzZHHXUUYwcOZInnniCfv36sW3bNg46\n6CDmzZsHwOrVq3nggQe44447OPXUU3nsscc488wzW35dugDlNSHq2pjEqC1jD+sXJT/XfJ+GYRjB\nJ8T5f/8hOVv/0679R4dNIvTF63Z+91EauTk7cweYrWC2QqeSQZv45ltv4+BDZnPhwvO4/dZb+e5l\n3wNsnveEeV4Tys7ojBiqsHZbNQV50rikZWCffEYM7J1p0Xok5tDIIkaOHMns2bMBOPPMM7npppsa\njZTTTjsNcB7aV199lVNOOaWxXX29e4r+yiuv8NhjjwFw1llnceWVV+4yxvPPP8+FF15IXp679IMG\nDWpWpunTp/PZZ5+xadMmSkpKGDhwIKNGjeKmm27iueeeY/r06Y1yrV69ehflXVBQwDHHHAPA5MmT\nKSwsJD8/n8mTJ7Nu3ToAnnvuOd55553GEMCKigpWr17NiBEj+OEPf8hLL71ETk4On376KVu3bgVg\n7NixTJs2DYCZM2c29tXdUNWMvnHEkh8ZhmE4qurDnZbHKEg4GiU3Z2eCZrMVzFboCYwcOZKDD3Hz\n/PSvzecPN/+eSy+7DLB53hPmeW2WLjcJEokqtQ07bwrbq0MMKY5QlG8J9Tsbc2gkIoXXuKMQkaTf\n+/TpA0A0GmXAgAG89dZbafURj6qmrBPPySefzKOPPsqWLVs4/fTTG/v5wQ9+wAUXXNBs2/z8/Mbx\ncnJyKCwsbPwcDocb+/rd737H0Ucf3aTt3XffTUlJCStXriQ/P58xY8ZQV+eWXsT6AcjNze0W4XWJ\nKKtuyHjIXWlVA0OLC8nJsezihmH0XOKX4AUjKTqSaNQtc8nx91KzFXqWrSAilwALgMnAA6q6IEm9\nBcBiIHiQJ6jq0jYJkCGbGJvnTdp293keT1ddwlFW3cCeA3plWoweh8WRZxGffPIJy5cvB+CBBx7g\n0EMP3aVOv379GDt2LI888gjgFN/bb78NwOzZs3nwwQcBWLJkScIxjjrqKG699dZGxVlWVgZA3759\nqaysTNjm9NNP58EHH+TRRx9tzAx99NFHc+edd1JVVQXAp59+ymeffdaq4z766KP5wx/+QCjkEux8\n9NFHVFdXU1FRwW677UZ+fj4vvPAC69evb1X/XRVVpaQq8zksIlGlvNaSHxmG0XOpbYh0emLmGPHJ\nEM1W6HG2wibgZ8CdadRdrqrFgW1px4rWMagqGz75hNdfc/P8kYcfbIzWCAZJ2TzvnqgqtVm+5CQZ\n5TUhewNKBjCHRhYxYcIE7rnnHqZMmUJZWRkXXXRRwnpLlixh8eLFTJ06lYkTJzYmBvrtb3/LzTff\nzP77709FRUXCtueddx6jRo1iypQpTJ06lfvvvx+AhQsXcuyxxzYmQAoyceJEKisrGT58OHvssQfg\nbgJnnHEGBx98MJMnT+bkk09OqvxTcd5557HffvsxY8YMJk2axAUXXEA4HGb+/PmsWLGCWbNmsWTJ\nEsaPH9+q/rsqZdUNhMLZoRRLs8CxYhiGkSm2ZVgHhiM7X+FqtkLPshVU9XFV/RNQmmlZOouowvjx\nE1hy770cMHM628u2c36S6Aeb592P+nCUaPbmA22WSFSp6qLRJV0Z6YlepFmzZumKFSua7Pvggw+Y\nMGFChiRyWYpPOOEE/vOf9k0w1pPJ9DVtC6rKh1srs8ahATBuaB/6FNoqtY5ERFaq6qxMy9FZJNLF\nhpFthCJRPtxSiSpEt29k7333zYgcBXk5bPzkE7MV2plEtkI26mIR+RkwIsWSk5txS07KgHuB/1XV\nXX5dichCYCHAqFGjZsY/7c+0/bT64zWcNG8eK95MvJSkKD+3cQmWkR6ZvqYtoay6gU+3d91lM7v1\nK7Tcc+1AS/SwRWgYRhZSXhPKKmcGuBuMYRhGT6OsuiEjyUDjiUSyQAgjm3kJmATsBnwV+BpwRaKK\nqnq7qs5S1VlDhw7tRBHTI9XD1mjU/he6M101f0aMri5/VyQrHRoicomIrBCRehG5u5l6C0QkIiJV\ngW1O50nafowZM8aeuBhA9uTOiKeiNkQ40kVjAA3DMFpBNKqUVmWHMzeiyqjRo81WMBKiqmtUda2q\nRlX1XeBa4ORMy9UaRo0ekzQ6A9ySFKP70lXzZ8SoaYhYHo1OJlvjx2MJkI4GUqWKXa6qu2bEMowu\nyo7aMPWh7HMcqEJ5bYghxYWpKxuGYXQDKmpDTRJyZppIVMnJtVB7Iy0U6HKTRVVTR2jYj8VuSzgS\nzUobuCWoQl0oSq8Ce31rZ5GVERo9MQGSYcQoqarLtAhJ2W7LTgzD6EGUVmdXtFw2OVeMzkFE8kSk\nCMgFckWkSER2eSApIseKyDD/eTxwNfBk50rbdlSbvskkcZ3UTg+ja1LTxaMzYlQ32LKTziQrHRot\nZLqIbBORj0Tk6kRKHlwCJL+MZUVJSUlny2gYaVFVH6a2IXs903WhKLUN3eNmYxiG0Rw1Ddmnj6Oq\n5tToeVyFS/T5feBM//kqERnll1qP8vWOBN4RkWrgaeBx4LpMCNwW0om+UMiKvDZG+1NT3z1sTLOV\nO5dsXXKSLrEESOuBicBDQBj43/iKqno7cDu4zPqdKKNhpE1JZXY9DUzE9poGehWkWglmGIbRtcmW\n3BnxRKJKbk6XW0lgtBJVXQQsSlJcHKh3OXB5J4jUoaTrr4uqktP1VtQYKegukQ1dPQ9IV6NLR2h0\npwRI2cDSpUs54YQTdtn/1ltv8fTTT7eqz+uu2/lwYN26dUyaNKnV8nV36kIRquqyX5GX14Qs1NMw\njG5NOBKlojaUaTESEolmNtzebAWjI0k3P0ZH59Gwed75RKPabSIb6kNRextPJ9KlHRoJ6JIJkFpC\nONz5P3ibU96p5Akqb6N5ukJ0BjhjekcXcLwYhmG0lu01oawNaVeUSArhzFYwuirpOuuiavO8u1Eb\nimSt3m0NdeHu4ZzpCmTlkhOfByOPQAIkIKyq4bh6xwL/VtWtgQRIj3S6wO3ET3/6U5YsWcLIkSMZ\nMmQIM2fO5PLLL2fOnDkccsghvPLKK8ybN4+TTz6Zb3zjG5SUlDB06FDuuusuRo0axYIFCzjhhBM4\n+WQXpFJcXExVVRVLly5l0aJFDBkyhP/85z/MnDmT++67DxHh2Wef5dJLL2XIkCHMmDFjF5kaGhr4\n8Y9/TG1tLcuWLeMHP/gBH3zwAZs2bWLdunUMGTKEo446ihUrVvD73/8egBNOOIHLL7+cZ599ltra\nWqZNm8bEiRP5+c9/TiQS4fzzz+fVV19l+PDhPPnkk/TqZcsXQln8NDARFTUh+vfKz7QYhmEYHUJZ\nFidA/sV1P+ehBx9glNkKRjcjqtqYEPQX1/2chx54gOEjRjB4yBCmT5/BpZddxjFfPJIDDzqY15a/\nyknz5nHKKafYPO8mZHK5yarNO3j30womD+/P+D36tUufdaEovQvapSsjBdkaoZHxBEjnPHsOf/rv\nnwAIRUOc8+w5PPXxUwDUhms559lzeHbtswBUNlRyzrPn8Pz65wHYXredc549h6UblgKwrXZbyvFW\nrFjBY489xptvvsnjjz/OihUrmpSXl5fz4osv8r3vfY9LLrmEr3/967zzzjvMnz+fb3/72yn7f/PN\nN7nxxht5//33WbNmDa+88gp1dXWcf/75PPXUU7z88sts2bJll3YFBQVce+21nHbaabz11lucdtpp\nAKxcuZInn3yS+++/P+mYv/jFL+jVqxdvvfUWS5YsAWD16tV885vf5L333mPAgAE89thjKWXvCZRW\nNXQpr/SOuux6laFhGEZ7UVkXoiGcXjLQi/5xHn9Z82cAwtEQF/3jPJ5Z+1cA6sK1XPSP8/j7+r8B\nUNVQyUX/OI8XNvwDgPL67Vz0j/N4+dMXAShNw1b498oV/OmJx1n++r947LHHzFYwOoWW2MQ76ndw\n9jMLeHrNc0RVW2QTx0L0Y/P81Tf+xQMPP8KbK1c2qVdRXs7fnv8n373M5nl3ojpDCUFXbd7Bj578\nD/e9vp4fPfkfVm3e0S79Wh6NziMrHRqqukhVJW5bpKqfqGqxqn7i612uqsNUtY+qjlPVH6tq13nM\nHWDZsmWcdNJJ9OrVi759+3LiiSc2KY8pTYDly5dzxhlnAHDWWWexbNmylP0fcMABjBgxgpycHKZN\nm8a6detYtWoVY8eOZe+990ZEOPPMM9OWd968ea3yIo8dO5Zp06YBMHPmTNatW9fiProb0ahm9dPA\nRKjSpSJKjJYjIpf4N0PVi8jdzdRbICIR72yObXM6T1LDaF+2V2evbnv1lVc44cR5FPXqRe8+xWYr\nGFlHyDsDVbXxc7rEHpPE5nnMJj72+OOb1PvqKacCLqLD5nn3IBpVquszE6Hx7qcVhCNRt4wpEuXd\nTyvapd86c2h0Glm55CQbuOuYuxo/5+fkN/neK69Xk+99C/o2+T6waGCT70N6DUk5Xqo1g3369Ela\nJuLShuTl5RGN7ryRNDTs/JFcWFjY+Dk3N7dxnV+sbUsJyhMcF6Curi5pu3g5amtrWzV+d2J7TUOX\njHaoqA0xqI/F0nVjNgE/A44GUllqy1X10I4XyTA6llAkyo669B0afzjy/zV+zsvJb/K9KK9Xk+/F\nBX2bfB9QOLDJ98EttBUS3TfMVjA6gnRt4mhU6ZVf3DivI6r0ze+ftk0ci9BIbRP3dv0n+B+wed41\nqW4IZyxSefLw/uTl5hCORMnLzWHy8P7t0m93SXDaFcjKCI2eyKGHHspTTz1FXV0dVVVV/PWvf01a\n95BDDuHBBx8EYMmSJRx6qPsdMWbMGFb6sLwnn3ySUKh5o2z8+PGsXbuWjz/+GIAHHnggYb2+fftS\nWVmZtJ8xY8bw1ltvEY1G2bBhA2+88UZjWX5+fko5ejqlXSw6I0ZVXZhQpGVPX4yug6o+rqp/Akoz\nLYthdBbba7J7+d8hs2fz9F//Ql1dHTsqK81WMLKKcHRXmyDcggc2sarBeV5VVcUzzzxNbUOEulDT\n/lW12Xm+YsUKVNXmeRegKkPRGQDj9+jHz0+axJkHjubnJ01qtxwaqlBviUE7BXNoZAn7778/8+bN\nY+rUqXzlK19h1qxZ9O+f2EN40003cddddzFlyhTuvfdefvvb3wJw/vnn8+KLL3LAAQfw+uuvN/uk\nBqCoqIjbb7+d448/nkMPPZTRo0cnrHfEEUfw/vvvM23aNB566KFdymfPns3YsWOZPHkyl19+eZNE\nSgsXLmTKlCnMnz8/3VPRo6isC1Ef6rpOgR227MRwTBeRbSLykYhc7RM7J0REFvqlLCtKSko6U0bD\nSEk2LzcBmDlrf44/4UQOmjWT0089hRkzZ5qtYGQFqpowYiKqmtbrK11CUFcvOM9PO+Vk9p04jZyi\n3nxaXkvQZ6LAb268MeE8P+cb57L0xRfZ/4ADWL78NZvnWU5Vht+eN36Pfpwya2S7OTNi1DV0XRu/\nKyGZfJd5ppg1a5bGJ9L64IMPmDBhQoYkclRWVtK7TzHVNdUcMWcOt956G7Nmzmh1CFxPJxuuaSrW\nbqvOmBJvj4zOvQtz2WtocTtL1nMRkZWqOivTcgQRkZ8BI1R1QZLycTi7cj0wEXgIuFdV/zdV34l0\nsWFkisq6EOu21TRbJ7p9I3vvu28nSZSYqqoqiouLqamp4egjv8Add9ye8I0MRnokshWyURd3FO1l\nE4cjURqSRG3m5QgFebktah+b55tKKjjp2Ln8+Jc3st/kqQzqU8jAPjvfspaXk0NBXk6zfQHk5+SQ\nn9dzn+Nms03cEI7y4ZbkUS9tYWPVGl7Z+ncOGfZFRhaPIxINIyLkSPPzsb3YrV8hw/oVdcpY3Y2W\n6GHLoZFhVJVw1Hm1zz1/Ias+eJ/6unrOOOssJk6ZSm0oQo4IuTluyzHnRrehLhTJqDPjR0/+p3G9\nYGtD7GrqI4QiUfJzewobiMMAACAASURBVK6R0NNR1TWBr++KyLXAFUBKh4ZhZBPZHp0R45KLL2q0\nFeafdRbTp0/PtEiGQbSZB6SRqKKqzT6giw/iiM3z2to6jvvq6ew3eSqI0Kug6Q/RSDSKqjT2HVVN\nuBw2FI1CBLNXOolIVImqpnW+25pkPviAbp/di1m25W+M6bsPo4r3Iqxhnlp/PzOHuKVI75b9izs/\n/D/+Z+oNjCge16Zx08HyaHQO5tDIEKpKKKJOEft9d//x3oR1o6pEI0o4Ark5OeTnikVtdAMymTsj\nUUbn1kZpVNSGGFJcmLqi0VNQwBSU0aVoaTLQTBJvK0SiSl6u/csZmaW5lFpK6nka7xAJzvO6UJTa\nhgi9CnIpym/6A1lxeTryc8Ul/wzvtKvjiTk6zKnRsdSFIqzdVg3A6MG96V3Q/M/NitrW28PxD+h+\ncPxw7vr415w46gxGFe/F6OK9ufeIpY2/m/oVDGRs330Z1nsE4F63nZeT39wQbaLOcmh0CvYfHaCz\nlt+EI1HqQhHC0eRKNxFOaUepC0UTJl4ydpLtS6kiUWV7Bh0asYzOOUKbMzrb61u7JyKSJyJFQC6Q\nKyJFiXJjiMixIjLMfx4PXA082bnSGkbbaEky0Gy7v3TFt2RlC9l2LbOJlpybaHRn/otkRJrpT1Wb\njfAoys9hYJ/8XZwZMcKRKA3hCPXhaLP9gHNq9LSE5p09z0sq6wlHlHBEWV9a06yOqgtFqG1DnonY\nAzrN20Y4EmXt1hx+Ous2vjT2bMC9uSb4EHhcv/F8d8p15OcU0BCp58crLuAv6+9v9firNu/gkRUb\nWLV5R8LyUFgJ97D5lgnMoeEpKiqitLS0Q//po6rUhyI0RFrmyIhHcR7ohnDUbsYJUFVKS0spKsre\nNWtl1ZnNpN+eGZ1jy06MbsdVQC3wfeBM//kqERklIlUiMsrXOxJ4R0SqgaeBx4HrMiGwYbSWtJeb\n5OZTvr0sq+69UdWskqer0BVshUzRUpu4OWdFjGg0+TxN5YRIRSxKI91+QpEooXDPsFs6e56HI9Em\nD7rCEWVTefLX0bY1Wnny8P4U9P2QPnv9ioJ+HzB5eH9GFI8jR1L/xI0SZWSfcYxs5dKTWHTIfa+v\n50dP/iepU6Ouh8y1TGJLTjwjRoxg48aNdFTW/ajP/pyuzo55kPNzc5oNjcsRtwzFVqA0paioiBEj\nRmRajISoKmVZ8KrW8Xv0a7dszjtqQwy2ZSfdClVdBCxKUlwcqHc5cHkniGQYHUJVfZiGNA1OKR7M\ntrJStpVsa8EIikRDSNSFHmtOHtrOIc55OUJOjhkCLSWbbYVM0lKbOLaENRWxfHC7tI9GyUTgcTJ5\nuhudOc/LEkS7ldeE6FvUwIDeBU3214UibY5WHr9HP6458kv8aW0NJ33hpBbZtUW5vbho4lWN3zdU\nrWF4nzFpOUMg/eXbtQ0RigvtJ3dHYmfXk5+fz9ixYzuk77LqBjaV1yKa3sLyliZsLCzMZezgPmbM\ndBEqW2A8t5ZPtq1k6KbljN/yJoUVHyPhWiIF/akdMpkdY4+lcsQcyGm/f/8ddWFzaBjdhvpwhHDE\nBVDnCBTk5pBna667LWVV6RvUkpOH9BuWVt38yg0MfftmBqz5C7kNTZ/chXoPo3TCWZROOpdofvOv\nk0yH4l55jB7c9n4MA1pmE6sq72/eAWmYNQX5OewzrG+r27c3CvQqymNYvyJ6FeQ2Lg0wfd96kiW7\n37i9lqL8XIryXVLXaNRFbrQlOGdd5Ufs2Xs0k4YPZtLwb7W+I+DT6vX86I1zOWWv8zlx9BlptYkt\n3479Xku2fLsuZHk0OhpzaHQwW3fU8dmO+ha1aWnCxpr6COtKqxljTo0uQWkLjOdkxL9ytTpUSVl9\nCaMKd2e3t27ivPI/85XKKqaG+1M7eD8eyqnmyAYY88nfGbT6Eer7j2PzQT+mcuQX2uGIoLo+3KjQ\nDaOrEYkqFbUhdtSGqKoPJzSw8vOE4sI8BvQusCct3YhwRyQDjYbZ7a3fM/St34HkUDHuBHaMmktD\nv3GgYYrKVjFgzZ/ZfeX/MejDB9n4+V9RvefBbRqysi5MNKpmAxidTl0o/eiK+lCUqvpwEx1aWR/O\nSHRG4/h1YSrrqprsG9a/kN362lKklqKq1CR5q4cq/PezKnbrV0hBbg7bqurblDujKrSDn//7O8wc\neigX7vejVvcTY8/eozhj74s5dPej024TW74dtMcTkeycGO2HWWUdhKqycXst5TUtN5TS9fgFqa6P\n8Gl5LSMH9W6NuEYn0R6vao2P4PnZvIks2fg9csI1PPTJegqqNnDtuC/Q+6AFfLTH4Wyq2cAtr59F\n+YSLOe6Ld9Fv/XPsvuIGxvxtAdv2W8CWA69CcwtSD9wMqs4oGNinbf0YRmcSikQpqaxPK6dNKKxs\nD4fYXh2iMD+H3foW7hI+a3Q9EoVHt4Xcuu2Men4hxVtep3yvk9h8wI8I99m9SZ26IZMp3+cUem95\ngxEv/w9jn5nPp4dex/Z9T2/1uDEd3L93x2XrN4xE/H/2zjs8jurqw+9s00parXqvlnvFNsbGlNAx\nvYZQAiGEUAMEki+0EEooaUASIEAInQChBgymhI7BgLEB27hbVu9te5+53x+LhGSrbJmVV/a8z+Pn\nwbN37pw1s7ece87vuPzRrWna7F4m5lv6hRqjiZAaK9rtfsxGPVaz9nuKBm9QHnE8FSL8bzsaOx7a\nDYXFaOXSmTdSll4Vo7WDkSSJo8pP+85OgTNow2rKHvW+SNK3AyEFWRF7RHrTrkJzaCQARRE09npw\neGPbuEbq8dsRmyeIyeCj0Kp5lZMVNbQzvo/gkQnJ8G2LgwvNM6la+yAY86g57gVKihb1ty9Jr+Cv\ni58jJyUPdAbW5k2h7pinmbHuUfK//RcpjlrqD38IYUiN6PnDTTR2b1BzaGiMC4QQdLr8dDj8MW1m\n/UGFxh4vXa4ApVmppJr06hupMSZELAYaAQZ3K9VvnInR1UzjQX/FNvnUEdt7ihay7cSl5L5xIWXL\nr6bV7sO88KcxP9/hC2oODY0xxx2lQ8MbUOhyBcjPSKHb5ccZ5yFPouhxBTSHRpRE69waikjS7l1B\nBxajlXl58UW2Dcc/N95BrXMLty54CJNenXRqb1DT0Ugk2r+sysiKoL7bjdsfX3hRrIKNHQ4/qSbN\nq5yMyIqg1xO/Q2N2aSYGQxBDyaMI90xOCaxh7jd/xVlyANsOvR/ZnLXTPfmp4RNCRSj8Y/0tpOrT\nuGXRP/FnT6F0+dVU/e9n1C15YtRIjZEmGpdfC3nWSH58QZnGHg++YPwxzt6ATE1nOIRWC08efzh9\nQdX0jAyedqqXnYHB20nt0U/jKVoY0X0buuHmtku4X+figDU3scKUS9bc42OyweELIoQYVKJQQyOR\nCCFwB6LfxLbZfXS5/EldctjpC+udmQxaKm2keOLc+8Doafcbe7/hL2t+w2/2+jPTs+fF/byhWFx4\nGBOt0zHq1Duk04RBE4v2K1WRkKxQ2xW/MyNeGns8CRed1IgemyegSp7otGIrtx4/l8rMYi4rszN3\nw5+wVx1N/ZLHhnRmDEQn6bh85s1cNON6JEmid+rpNB10F5aWTyld/htGO64eaqLpQ4hwLqyGRrLS\n4w6wrcOlijOjj74Q2roud1IvzjV2Rq3oDF3QTdXb52HwtFN31JMROzMgPKZ6ZT0XBa5io6hkwdfX\nYnLUxWSHoqhzQqqhESnugBzzuiYkR175b1dh8yZfOkwyo4ZWRF/avU5iyLT7gtQSFhcezgTrtLif\nNRx75e7LEWWnqOoc9mo6GglFc2ioRPA7Z0YyvLCKAo29Hq0ufZIRb61tCEdYBJUAM0qyebDiUC7d\n9AyO8sNoOPQ+RIRhcRUZkyj9Lufwg+bXqK04mLa9/4/sbf8ld/2jI9472kTj8KosrqehoQJCCJpt\nXpp7o1dU39Tq4IVVjcPWl+/D6QtR0+nCH9r1c4DG6ATVEgMVgrIPr8Tcs4HGw+7HU7ggqtv7xtSA\nlMIVyq/Q6XSUv38ZKLE5JhxJGr6vETuSJF0mSdIqSZL8kiQ9PkrbqyRJapMkyS5J0qOSJCW0/JhT\nbUHdJCNezbM9iaCsqOLU70u7P3tR5ZDpJrnmAi6Yfg1mfWRp0vHwbc8qbl19GX7ZF3dfnqD2LiUS\nLfZFBXzBcJWRYCh5HAgev9yfo6ix63H5Q/hVOBV+ufYx1nR/zu8rL6b8w1/izZ9Lw2EPgC76FKNe\nfxdPbb2HNm8j2XMvJ63zG4pW3oGncAHe/L2GvGc0fRct5Fkj2VAUQX2PJ6aFabQltP1Bhe2dbibk\npfeXptNITnojEIKNhLy1D5JZ/zYtMVaNGjymzqHNa6Dy/UvJX/MAnfOiL0Po8AYpzUr8Ql9jTGkB\nbgOWAMP+z5UkaQlwLXDod/f8F7jlu2sJIVn1L9TCE5C1NU2EeFUsTTpU2n2Pr5MXax/hR9UXkJWS\nq9qzRkIvGXCFnNj83RSmlcbVVzAkCMoKRq0aYELQ/lXjxO0Psb0zuZwZfbQ7fFrt4yRBLRXvSssk\nJlsmM+XDK5FNmdQf8RDCEFvufnZKHrcs+CenT7wIJImmH9xNKDWPso9+hSQPr0I9rdjKaQvKh9zY\nKUo4BFVDIxkIyQrbu9wxn7KNlGI1/DMF2zvd2tibxAgh6FFBz6h946cUfPlnGouX0D3z/EGfbbF/\nyyu1T/T/vcvXRo+vc8h+Bo6pjurjsFUfT8HXf8Nk3x61TSFZ4IlB00AjeRFCvCyEeAXoHqXpucAj\nQoj1Qohe4Fbgp4myyxeUVTmoSWaEQNUUxd2ZRM95W+zr+KL9AwLK6FVSYiGldwsTlp1BzoYn+tOv\np2fP5Q8LH4vbmdGHVr41cWgOjTiweQLUJnHetBDQbPPuajP2eAKh0UObIw1r36fgIK7raCfF2UjD\nofcSSiuMy7ZySzU6SY8n5GJboJ3mA/6I2baVgq/viblPLe1EIxkIqZAGOFqK1XDIiqC2y62lnyQp\nDl8o7kOILU2dVH7yGzpEJic2ns6mNiftnub+VM+NvV/zwvaHkb9LHXmt/hl+/flZ+OTR5+TWfW9C\n6M2UfHbTqLpGQxFrhTWNcc9MYM2Av68BCiVJ2uk4W5KkC79LY1nV2Tm0o200Op2J2VgmG7GInu6J\nJNq5tW/hodx7wMsUpJao3ndq5xomLj2JtPYvKV3xO0pW3ND/mU7SEVQCfNz6Ztyp/MkgS7C7ojk0\nYkAIQYvNS2NP9PnYY43HL9OrgnaDRuz0ekYObe4La//3F/X89tVvh3RqPLrpTla0vUtmzVJytr5A\nx9zL8QwozRov9317C3etvQ5b6QH0TjqFvLUPxnQ6CKiTl66hEQd9zox4T9ZGy+Ud2QZBXZeHkKyd\n7iUbapTPzv/qb0yWmrgu+HNsspn36j/lV5+dyequTwA4suxUHj/kPfQ6w3d/P4XLZt7Un/f9duNL\nOINDR/yE0gpon38VGU0fkdH43pBtRnKCa2PwHosFGPhS9f13xo4NhRAPCSEWCCEW5OfnR/0gTyCE\nzbNnvGfaJjQyEhWhIYSg1dMAQJohvf+6JPtJa1+F3jta4NLo5H8T1qHb8qOP6ZrxU3I3PkVqxzf9\nn3/W/h4PbridTbY1I/QyOlr0XOLQHBpR4guGy/R1q5RCMBa02n1JG0WyuyOEGHXxPFpYu1/20eCq\nocO2ntJPrsNdsDcd836pqp1nTLyIK2ffikFnpG3hbxF6M8Wf/z6mvoIhoYXba+wy1HJm9DFSitVo\nBEIK9T2aQHMy4Q/JcQv9pXau4cCOp3lBOZiPxVwMeh2HVOzLaRN/zpTMWeE2hrRBJf9K06vYO/8A\nIKxf9PTW+3in8eVhn9E981z81iqKvvwTKIPH09Gc4P6goo3BeyYuYOBA1fffTrUftLtrZwxEi9AY\nHSEE/gRVV1zb8wW//uws1nR/8d3DFHK/fYSpzy5m4munMOPpeRSu/EPM/RvcbVgb3qVn6ukELaW0\nL7iakDmXopV39EfI7V94BDfu/Q+mZ8+N67v0abJoqI/m0IgQWRG02r1s63DhDYyvEzdZEXQ441fo\n1YgeuzdISB558BotrD1Fb+bG+ffxi/qvQcg0HvJ30Kmr51uRMYlJmTMB8Jmz6Jj3S6yN75PevDym\n/rS0E41dgawI6rrVc2aogccva6l/SUTc0RlKiNLlVxNKK8B52C+pnvUcvztuAjNKsjmp6idYTdmj\ndpGdksdtCx/mhKqzw12KId5XnZH2vf8Pc+9msmpeGfRRJNoue9KGU6Of9cBARe+9gHYhRPxH2LsY\nva8HSd41B4nBkNAOBUfBH1ISFrE+0TqDMyZexMzs+RhdzUxYdjoln9+CL2caDYfcR++kUyhY+wDZ\nm56Nqf+czf9BEjI9U88EQDFZaJ9/JZa2z0lv+RQAvc7AtKzwT2vI8TpCNE2WxJGUDo1kLFHV7fLT\n5VRHFX1X0O0KaPncu4BISrWOFNa+2bYWb8hDVsO75DS+T8f8XxHMqEiYve80vczVn59D67QzCKQX\nU7j67thyuLXFtMYYE47MSE6Hc687qKX+JQGKMnrE3GjkbP4PqT0baVl8E+YshYC+kbys6B1WFZaJ\nGHRGnEE7N6+6mK+7VuzUxl59HN7cmRR8c++gKI1ItF20tJPdB0mSDJIkmQE9oJckySxJ0lCnGk8C\n50uSNEOSpGzgBuDxMTRVdXQBJ+XvXcr0p+dT9tGvdpkd2vp5ZBKpn2ExWjmh6hxy695i8stLSO1e\nT+MP7qLu6KexTzyBph/cibP0QIo/vwVdYGQduqHI3L4UV8n+BK2V/dd6p5xOMDWf/HX/HNT2k7b/\nce0X5xIYQTh/NLS0k8SQlA4Nvi9R9ehIjQaUqDoMqAKqCZeo0tgBIaDdvmcIOCULvqCMxx/ZJDhU\nWLtP9nLnmmt4dMMfKP7sRrw50+madV6izAWgLH0CU7Lm4Jegc+5lpHesxtL8cdT9eAMyQU07QGOM\nCPYLgCbvO9ds82ppALsYmzeIEscrogs4KFx9J66iRTiqjmF27j78dfFzlFmqY+5TQsKoMyEYwnEs\n6ejc61JS7NuxNrzTfzkSbRePX9b0W3YfbgC8hNe7Z3/33zdIklQhSZJLkqQKACHEW8CfgQ+A+u/+\n3LRrTFaHnI1PkVX7Ou6iRWRtXxpz1Gi8aKfqI+NLgMNHCMGTW/5OjX0DxStupOL9X+DPmsTWk9/E\nNuU06CulqzPQts816EMesre8GNUzDJ5OzLZtOMsOGvxsg5numeeR0fQR5u71/ddzU/IpTC3FE3IB\nYHQ2oPPbonqmVukkMSSlQyNZS1SNd+zeoCZuNIZEEp0xEmZ9KtfMvZMLXEFM7lZa9r8DdEaVrBua\n6dnzuHjG9ViMVnqnnE7AUkrh6rtiitLQQp41xgJfUP6uTGpyLziFgKZer5Y/uwvpdsXn1C/4+h7w\n9XJlUSGru8KhyCZ9fEGhFqOVG+bfy/y8/QF2ej/sVUfjz6ggf80Dg8bhSLRdtEi53QMhxM1CCGmH\nPzcLIRqEEBYhRMOAtncLIQqFEFYhxHlCiDE/yYq0atuoCIWczc/iKtqXuiVP4LdWUvL5LTGtR+JF\ni9AYmUREaHT52lnR9g62dfeQt+FxumadT81xLwyKpOjDlzcHd8He5G54AqJICUlv+xwAd9G+O33W\nPf0cZGMGhavu7L82PXsev97rj+QKiYr3Lmbacwcw+emF6D76Y8TP9GoHGwkhKR0aUTCmJap2B9oc\nmpbGWCArQpUQ85kihfkbn6Nn6pl4CvdWwbLIaPc281bLa3TMvYK0zm/IaPog6j40HQ2NRNPt8rOt\nw0UgQWJkauMNyHTGuanWiA23PzSq02ukjZjJXkvu+sdonHwyXcKPPdCjmm3SdyeNn7e/xx1fX0lI\nGTB26gx0zb6ItM6vSWtbGVW/Ti3tRGOMiaRqW6Skt6wgxVFPz7SzEAYzXbMvwty7hRTbFhUtjoxk\nd5jvahLh8MlPLeJfE67ix5veoHv6ObQuunHEQ73uGeeS4qglvfWLiJ+R3vo5sjEdb96snT5TUjLp\nmHsZ1sb3BkUG6X09ZLxxOhvbPuZ+5WTeD85m5tb7sa15PaJn+oOKpsmSAMa7Q2PMSlTtLrh8Idx+\n7dQm0dhGKdU6Gg9v/DP/rX2copV/QDGk0rbgavWMi4CPWpbxn5oH2V55CIGMcgpi0NJw+UMo2qCt\noTI2T4AOp48t7U5abL5xp2vU4fBrqSe7gNEqk422EStc9ReEzohvn+u4ee8HOKTkeNVt1El6QkoQ\nT8g96HrvlNMImXPJX/tAVP05fdoYrDG2RCJYGynZ214mlJKJo+ooABwVhwNgrX9npNsSgjZmD08i\nKpwEZD9CDlK98o+IjHJaF/3u+xSTYXBUHomiTxmUnjca6a2f4SlcOKzQfvfM8whklFP2ybWY7HWY\n7HVMfO0U/mCycVVROXcGT+Hy4OVsU0qYueY2pFBkh8aajob6jHeHxpiVqNqdaNeiNBJOPOkmilAI\nKH5kew3Whnfo3OtS5NSdgo4SyvGVZ/O3xc+RnVpE55yLSetaS1r7l1H1IQQ4NeeZhso09nhpt/sT\nKkKWSISAFq3qyZgSlJVRRTJH2oil9GzCWLeMOyfthyvFil5n6I+qUJOFBQfzu73vw2rKGnRdGMx0\nzTwPa+P7pPRsirg/IcClLZw1xpBIBGsjJb31c9wl+yMMZgBC6UV48uaQ0fCeWuZGTEjWKp0MR0BW\nv8LJw5v+zJ8/O4eU3s20Lryh/x0YCWFMw128HxkN70R0AKf3dmG2bcNVvHO6SX+fBjMNh/wDXdDN\n5JcOY+oLP0Dv6+W0WTdw7sS/YdAbkSUDt4nzyAm07FSRaji09H/1Ge8Ojd22RFUicftlzTuYQFz+\nUFybLZ2k49IZN3B1/TcE04romnW+itZFRqohjcyUHAA6q09ANlnJXf9Y1P1oIc/jl2SsNrW74PbL\n2D3ab2Os6HGPHjE30kas8Ku/8mFGNs8Gamh01STUVp2kwxfy8Njmu3EEevuv90z/CYo+hdwNT0bV\nn5b6pzGWRCJYGwlGZxMmVxPuokWDrjsrDiet4yv03q4R71dNx2MAWpTG0KgdnQEwPWsuBzpt+DMn\n9kfoRIKj8nBSHPWk2LaN2ja99Tv9jOLFI7bzFsyl5vhX6JnxE9r2/j+2nfQaeVUnsn/V9P53/djj\nz8CfWU3W1pcjslPT0VCfpHRo7MklqsaKDoeWx50oekYJbR4JR8BGt6+dzO2vkd65hrYFv0EYUlW0\nLjoe2vhH7tx4Kz1TzySz7i2Mrpao7teEQcc1WrWpBNLq8GrpAGOAoohR001g+I2YuetbMuveZMHE\nn/C3/Z5ncubOudZq0+3v4MOW1/m2Z3X/Ndmchb36OLJqXkEXdI9w92AcXm0M1hhbIhGsHY30trAO\nwo4ODUfFYUgIMpqGr76mpo7HQMaLVtNYk4hoySWWWVzUvIHegdVMIqAvLSkjgrQTywj6GTsSyKyi\ndd+b6Jx3BcGMivA12c9y2wPkl6xlWkkmvZNOwdL2OUZn46j9aZVO1CcpHRrswSWqxgqnL6R5mxNA\nJKHNI/Fa/dP86rMzSfnqTrzZ07BNOkVF66KnyjKZydaZdE4/BxDkbHgiqvtDstCigcYpWrWpxBIM\nCbo0gdCEY/cGIw4VH2ojlv/V3TSmZtI163xyzYWJMnMQpelV3LP/S+xXdPig6z3Tfow+6CKz5tWI\n+5IVbQzWGH+kt32BbLLiy5466LovZwayydpfnWIo1NTxGEgiIhF2B9QUBPXJXr5o/wDrlucRki7q\nNXAovRhvzgwyGj8ctW1YP2OfYfUzRsOoM9HqacQWCC+RbJNOBiBr239Ht1MWBLWy2qqSlA6NPbZE\n1RjT6dQW02rTG0Fo80gcWXYql2UdRKG9jo69fw06vXrGxWJP+amcUn0esrUCR+USsjY+zSsrt0b1\nrmtRGrs9EVebAq3i1EA6nH5C2qImoXS7Y5/nzF3r+LjnM04syqbG36aiVaOTacoGoMm1nYAc/g6e\ngr3xZU8lZ9MzUfWlRWlojDfS21biLtxn5zWQTo+7aNGIlSzU1PEYiFa6dWjUrACzsuND/v7t72hs\negNXyf6E0oui7sNZdhDp7avQBVzDtgnrZ2wdUT9jNCRJ4ob593BS1U8ACGaU4y7YG2v9/yK6X4vS\nUJekdGiMJxIV2jYW2L1BLYRORYQQ9HjiK9Wan5LHj7e+hzd3Jo7KI1WyLD6EEGzs/Zo38w7FFHTg\nXf1MVO+6lsO92xNxtSnQKk4NRIiwU0MjMbj9IbyB2Oe4/DUPsCio56SKs6jMmKyiZZHR4W3hupXn\n8Xr9dw4MSaJn2lmkda3F3LUu4n7iiRrU0Bhr9D4bKfbteIoWDPm5u3hfUhy1GNxDOxnV0vHYEW29\nPDRqRnsfUHQkv5v2W/bprsVZdkhMfbjKDkISIdJbVwzbpj+laRT9jNHQSeFtdKc3/C46yw8hrWst\nBs/ohzValLy6aA6NOElUaNtYIER8p1cag3H4QgRDsYVnyEqIp7bcg2PTo6Q46uiYd2VUeYOJxCd7\nuXPNNfzb8S2blHJO138Q1bvuCyraQmD3Rqs2FQc97oD2+0gQ8aT0mBx1ZNa9gW7qWZw8+eL+hetY\nUpBaws+nXcPhZSf1X+uddAqK3kzOpqcj7scfVLTFs8a4IbVrLQCevL2G/NxVHNbV6NuUDoUaOh47\n4g8piPFWJzzBBELqVjjRSXr2czmQAFfpATH14SlcgGxII6Ppo2HbRKOfMRorOz7ilyt+yHbHJpzl\nB4f7bx7+2f12ahEaqqI5NOIkUaFtY0WPO6AJ06lETxylWhvdtbzfvBTX5qeSKjoDwhVPrpl3N2dN\nvIIXxSHspdvOTH1jVO+6dkK4W6NVm4oDIaBT09JQnUBIiSvVwrD2fm7Iy2XDpONVtCp6Dio5But3\n6ScASkomturjALjlcQAAIABJREFUyap5NSpxUC31T2O80OfQGG6z6cuZiWzMIL31s7E0CyHCJUo1\nvsenYhrOy9sf472mV7A0LyeYmo9/B/2USBF6E+7ixVhGcGiE9TMWgM4Yq7n9zMpZwA+rf06euQhf\n7iyC5ryINDy00q3qojk04iRRoW1jhaJAb5xpEhrh3EpXHAvGqozJPFVyHod119M+/6qkic7oY0rm\nLGaX5jP7qAsISQbumvxtVO+6tpgef2jVpsaOXi1KQ3XiiT7Ue7toaVzGexYL3pQhM6fGlG5fO3eu\nuYZ651YAeqf+CH3QjbXurYj70JzKGmNNrPpyqV3r8FurUFKyhm6g0+Mu2mdEHY1EoY3Tg1Er8ksI\nwUbbN2x3bMLS8imukgPiWge7yg4ixdmAyV6302d6bxfm3i2449DPGEiaIZ1TJvwUqykLJB2u8oOx\nNH8Mysj/NrIiNF0WFdEcGiqQiNC2aIlHmLQrjjKjGmF63bEvFhWhgBBM+PZxQtlTcVYcoaJl6rHN\nvp5nuu6kteowqluXIcmRvzdufyjiSgMaSYNWbWqMECK+9AiNwSiKiCtiLm/9YxzgdvHPuQ9Qml6l\nnmExkqJPpcldS7u3GQBP4T4ELOURqen34fHLmgCtxpgRj75catdavHlzRmzjLl6M2V6DwdMer6lR\noVU6GYxaJVslSeK38//OxflHY/B1x5xu0oez7GBg6NSPvlQlV5z6GTuysfcbVrS9i6vkAAx+G+ae\njaPe44tD4ykZ2ZUR/5pDYzcgXmHSQEjBqZ3exIwQ8S2en9zyd/72xc9J6d1M55yLky46ow+TLoUe\nfyebKw7G4Osho+G9iO8VgrgiWDTGHq3a1NjS4w5oG06V6PUEUGL8p5RCXgKbn8JRuQRd7gx1DYsR\ni9HK3YufZWHBwQBsanOxIv1QLM2fRLWhc2hjsMZYoMjw7QscLz4kSzii0tzSe7swuZojcGiET9fH\nOkpDc2gMRo0IAyEEISW8B8luDZfjdZUeGFefgcwq/BkVQ+popLd+gWxIw5s3O65n7MgbDc/xUu2j\nOL9zlFgiSInyBHePMdkfktnS7qSm07XLDi81h8ZugBrCpN1alEbM2L3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Wq1+2ixxZ9CK8kBMhrfx161BHThCLZccyG6YQ6C1dRTiZdEnxO4ixaS27senbkOjJ2qpdkkUmh2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OcCCOTDuJ6b55JNpTBsWuoAzyxLb7OS7zNLLdebrOiXNYzMhQjJLitRm+xsIh3mnBZ5YcmYxQ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\nzMbQZ9GKrfxi/n9YtCJ+bIyH332YS/9+Ke/VvZeR8z+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d5+KWRvuQ5hBOnyq7nUiGJUJ0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/tjLSHLkrWzRVrZep/Hz4NGd+4cpNWZe88953P2zICOCIn6wl5CchCrzoY7fy6tk39M1vpH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+/PJ9xhZc1eQ2NcF8dve/jt39r2tjlF/bemATH+xaxOmdzoYWFDTywuqdkWwhvwe/10Vl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\nwJie4xjZ7cKozuF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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Thts = np.array([[1.0, 4.0, 0.0, 0.0],\n", " [9.0, 4.0, 0.0, 0.0],\n", " [1.0, 64.0, 0.0,0.0],\n", " [1.0,0.25, 0.0, 0.0],\n", " [1.0, 4.0, 10.0, 0.0],\n", " [1.0, 4.0, 0.0, 5.0]\n", " ])\n", "\n", "beta = 3.0\n", "\n", "kernel = MyKernel(theta = np.array([0.0, 0.0, 0.0, 0.0]), bounds=[[0.0, None],[0.0, None],[0.0, None],[0.0, None]])\n", "gpr = GPRegression(kernel=kernel, beta=beta)\n", "\n", "fig = plt.figure(figsize=(18,10))\n", "cnt = 0\n", "while cnt < len(Thts):\n", " theta = Thts[cnt]\n", " kernel.theta = theta\n", " gpr.fit(X, t)\n", " mean, std = gpr.predict(Xtest, return_std=True)\n", " ax = fig.add_subplot(2, 3, cnt+1)\n", " plot_result(mean, std, ax)\n", " ax.set_title(f\"beta={gpr.beta}, theta = ({theta[0]}, {theta[1]}, {theta[2]}, {theta[3]}) \\n log_likelihod : {-cost_and_grad(beta=gpr.beta, theta=gpr.kernel.theta, kernel=gpr.kernel, X=X, t=t, return_grad=False)}\")\n", " cnt += 1\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that the quality of our prediction heavily depends on kernel parameters, especially on $\\theta_1$, which governs the length scale." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4.4 Regression (optimization of hyperparameters)\n", "\n", "Having seen that it is important to choose appropriate hyperparameters, here we let the algorithm it self to choose its favorite hyperparameters." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'\n", "beta = 14.070930995250336\n", "theta=[0.58665406 1.87938774 0. 0. ]\n", "log_likelihod : 31.408184692392034\n" ] }, { "data": { "image/png": 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NLWUiqbnnMCZhcvcNrIv8Z9c/eHrn/W0eq867GJ2zLqijixa7J0xOXEjhLiwD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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "kernel = MyKernel(theta = np.array([2.0, 1.0, 0.01, 0.02]), bounds=[[0.0, None],[0.0, None],[0.0, None],[0.0, None]])\n", "gpr = GPRegression(kernel=kernel, beta=1.0)\n", "gpr.fit(X, t, optimize_hparams=True)\n", "mean, std = gpr.predict(Xtest, return_std=True)\n", "print(f\"beta = {gpr.beta}\")\n", "print(f\"theta={kernel.theta}\")\n", "print(f\"log_likelihod : {-cost_and_grad(beta=gpr.beta, theta=gpr.kernel.theta, kernel=gpr.kernel, X=X, t=t, return_grad=False)}\")\n", "plot_result(mean, std)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that it gives much nicer result, with the value of log marginal likelihood much larger than those for the previoius section." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Appendix scikit-learn\n", "\n", "In this appendix, we see how to use scikit-learn library to perform the above analysis.\n", "\n", "* http://scikit-learn.org/stable/modules/gaussian_process.html\n", "* http://scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessRegressor.html\n", "\n", "For simplicity, here we consider the Gaussian kernel only." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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HrvXAdJ8VYATsfBijxF/WYZhZSYtiqWOUfIUZuPiNv16qmoW533ao6uo6lut/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\nzuF5yylwFhOMBGgNNZHnKOqzr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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from sklearn.gaussian_process import GaussianProcessRegressor\n", "from sklearn.gaussian_process.kernels import RBF, WhiteKernel\n", "\n", "kernel = 1.0 * RBF(length_scale=0.1, length_scale_bounds=(1e-3, 1e2)) \\\n", " + WhiteKernel(noise_level=1, noise_level_bounds=(1e-10, 3e+1))\n", "gp = GaussianProcessRegressor(kernel=kernel,alpha=0.0)\n", "\n", "# fitting \n", "gp.fit(X, t)\n", "\n", "# prediction\n", "y_mean, y_std = gp.predict(Xtest, return_std=True)\n", "\n", "# plotting\n", "fig = plt.figure(figsize=(8,6))\n", "ax = fig.add_subplot(1,1,1)\n", "plot_result(y_mean, y_std, ax)\n", "ax.set_title(f\"Initial: {kernel}\\n\\\n", "Optimum: {gp.kernel_}\\n\\\n", "Log-Marginal-Likelihood: {gp.log_marginal_likelihood(gp.kernel_.theta)}\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "(Currently, I have not figured out where the discrepancy of the value of log marginal likelihood comes from.)" ] } ], "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": "3.6.6" } }, "nbformat": 4, "nbformat_minor": 2 }