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"name": ""
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"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Visualizing information geometry with multidimensional scaling"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*License:* [*BSD*](http://opensource.org/licenses/BSD-3-Clause)\n",
"*(C) 2014, Kyle Cranmer.*\n",
" *Feel free to use, distribute, and modify with the above attribution.*"
]
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Introduction"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"When I was a graduate student I went to a conference in Germany about neural networks. I didn't know anyone at the conference, and during lunch I joined a Japanese man sitting by himself. We started to chat, and he introduced himself as \n",
"[Shun'ichi Amari](http://en.wikipedia.org/wiki/Shun%27ichi_Amari). I asked him what he did, and he started to tell me about the fascinating subject of [Information Geometry](http://en.wikipedia.org/wiki/Information_geometry). I had recently studied differential geometry, so I was facinated.\n",
"\n",
"The basic idea is that if you have a parametrized probability model like $G(x|\\mu,\\sigma)$ one can use ideas from information theory and statistics to define a distance measure (a metric) on the parameter space $(\\mu,\\sigma)$ that has some nice properties. For example, the distance is invariant to reparametrization of the statistical model (e.g. do I parametrize the distribution in terms of standard devaition $\\sigma$ or the variance $\\sigma^2$). This last property wouldn't hold if we simply used the Euclidean distance for the parameters $\\sqrt{\\Delta_1^2 + \\Delta_2^2}$.\n",
"\n",
"To me this was very important, because there is some arbitrariness to how we parametrize theories of particle physics, and it's not satisfying when the results depend on that arbitrary choice."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The starting point for informaiton geometry is that one defines the [Fisher information metric](http://en.wikipedia.org/wiki/Fisher_information_metric)\n",
"\n",
"\\begin{equation}\n",
"g_{ij}(\\vec\\alpha) = E\\left[ -\\partial_i \\partial_j \\ln L(\\vec\\alpha) \\left | \\vec\\alpha\\right .\\right]\n",
"\\end{equation}\n",
"\n",
"This tells you about the geometry of the space locally around the point $\\vec\\alpha$.\n",
"\n",
"In the case of the Gaussian distribution, the Fisher information metric defines a surface of constant negative curvature. The sphere is the surface of constant positive curvature, so some call this surface of constant negative curvature the [pseudo-sphere](http://mathworld.wolfram.com/Pseudosphere.html). Here's an image of the pseudo-sphere from [B Jessup](http://www.mathstat.uottawa.ca/~bjessup/) \n",
"\n",
"\n",
"\n",
"(I can't resist telling the story that the first time I was asked to give a talk at the Institute for Advanced Study, I found myself sitting at lunch next to [Juan Maldacena](http://en.wikipedia.org/wiki/Juan_Mart%C3%ADn_Maldacena). Juan is the author of [the most cited paper in particle physics](http://blog.inspirehep.net/2011/06/topcited-hep-paper-of-all-time.html), which is about -- you guessed it -- a space of constant negative curvature. There I am, a lowly experimental physicist sitting next to one of the greats. He asks me what I'm going to talk about. Despite my better judgement, I tell him that I was going to mention these ideas of information geometry and I tell him the Gaussian example because I thought he'd enjoy that. He looked interested, and asked me \"what does the boundary correspond to?\" I wasn't sure, but with a little thought I think I could have answered him. Unfortunately, I was so frazled by the fact I had just put myself in that situation that I couldn't think very clearly. Live and learn.)"
]
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"The project"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Almost any 2-d Manifold (surface)](http://en.wikipedia.org/wiki/Whitney_embedding_theorem) can be [embedded](http://en.wikipedia.org/wiki/Embedding#Riemannian_geometry) into 3-d in a way that preserves the metric. In the case of the 2-d surface defined by the $(\\mu,\\sigma)$ of the Gaussian distribution, that embedding into 3-d is the pseudo-sphere I mentioned above. Can we use some numerical algorithms to 'discover' that embedding without ever explicitly figuring out the mapping $(\\mu,\\sigma) \\to \\mathbb{R}^3$?\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Eventually, what I'd like to do is create some general purpose code that allows me to make these embeddings to visualize the surface based on an arbitrary Fisher information metric $g_{ij}(\\vec\\alpha)$. That is going to take some more work, because calculating hte distance between points is a bit involved.\n",
"\n",
"In the case of the Gaussian, all of the difficulties of the differential equations that define the geodesic and the integration to define the distance between points can be done analytically. For a \"FINE\" paper on the subject, look [here](http://arxiv.org/abs/0802.2050), in particular eq. 7. There you will find:\n",
"\\begin{equation}\n",
"D_F(\\mu_1,\\sigma_1;\\mu_2,\\sigma_2)) = \\sqrt{2}\\ln\\left[ \\frac{\n",
"\\left|\n",
"\\left(\\frac{\\mu_1}{\\sqrt{2}},\\sigma_1\\right)\n",
"+\\left(\\frac{\\mu_2}{\\sqrt{2}},-\\sigma_2\\right)\n",
"\\right|\n",
"}{\n",
"\\left|\n",
"\\left(\\frac{\\mu_1}{\\sqrt{2}},\\sigma_1\\right)\n",
"-\\left(\\frac{\\mu_2}{\\sqrt{2}},-\\sigma_2\\right)\n",
"\\right|\n",
"}\\right]\n",
"\\end{equation}\n",
"\n",
"Now that I have those distances, I can use the numerical technique of [Multidimensional scaling](\n",
"http://en.wikipedia.org/wiki/Multidimensional_scaling) (MDS) to find an embedding that preserves those distances. Luckily, [scikit-learn](http://scikit-learn.org/stable/modules/manifold.html) has a nice set of manifold learning algorithms including an MDS implementation. This algorithm only needs to know the distances between pairs of points, and then it will do its best to embed in whatever number of dimensions you ask. Let's see how it does with the Gaussian problem."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"First let's get the basics imports out of the way:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Author: Kyle Cranmer \n",
"# Licence: BSD\n",
"\n",
"print(__doc__)\n",
"import numpy as np\n",
"\n",
"from matplotlib import pyplot as plt\n",
"from matplotlib.collections import LineCollection\n",
"from mpl_toolkits.mplot3d import Axes3D\n",
"\n",
"from sklearn import manifold\n",
"from sklearn.metrics import euclidean_distances\n",
"from sklearn.decomposition import PCA\n",
"\n",
"# Next line to silence pyflakes.\n",
"Axes3D"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Automatically created module for IPython interactive environment\n"
]
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
"mpl_toolkits.mplot3d.axes3d.Axes3D"
]
}
],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now let's make a grid in the $(\\mu,\\sigma)$ plane that is n_samples x n_samples "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#make some random samples in 2d\n",
"n_samples = 20\n",
"seed = np.random.RandomState(seed=3)\n",
"\n",
"#create a set of Gaussians in a grid of mean (-1.5,1.5) and standard devaition (0.2,5)\n",
"gridMuSigma=[]\n",
"for i in np.linspace(-1.5,1.5,n_samples):\n",
" for j in np.linspace(.2,5,n_samples):\n",
" gridMuSigma.append([i,j])\n",
"gridMuSigma=np.array(gridMuSigma)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now let's code up that handy-dandy distance measure (this would be a big numerical project for an arbitrary metric $g_{ij}(\\vec\\alpha)$ -- let's takle that later.)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#use 2-d Gaussian information metric for distances\n",
"# see equation 7 from http://arxiv.org/abs/0802.2050 (\"FINE\" paper)\n",
"def getDistance(x,y):\n",
" #going to define a measure here\n",
" #print 'in getSim', x, y\n",
" aa = x[0]-y[0]\n",
" ab = x[1]+y[1]\n",
" bb = x[1]-y[1]\n",
" num = np.sqrt((aa**2+ab**2))+np.sqrt((aa**2+bb**2))\n",
" den = np.sqrt((aa**2+ab**2))-np.sqrt((aa**2+bb**2))\n",
" ret = np.log(num/den)\n",
" return ret"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now let's loop through all the pairs of points and calculate the distance between them. For some reason this is referred to as \"dissimilarity\" in a lot of MDS literature. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Create the array of \"dissimilarities\" (distances) between points\n",
"tempSim=[]\n",
"for x in gridMuSigma:\n",
" temp = []\n",
" for y in gridMuSigma:\n",
" temp.append(getDistance(x,y))\n",
" tempSim.append(temp)\n",
"distances=np.array(tempSim)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 5
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And now we can use scikit-learn's MDS implementation to embed these points in 3d and 2d so that the euclidean distance between points in the embedding corresponds to the Fisher information distance we calculated above. So even though we start with a 2d grid, the 2d embeddign will not look the same b/c the grid is not uniformly spaced in terms of the information distance."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#make 3d embedding \n",
"mds = manifold.MDS(n_components=3, metric=True, max_iter=3000, eps=1e-9, random_state=seed,\n",
" dissimilarity=\"precomputed\", n_jobs=1)\n",
"embed3d = mds.fit(distances).embedding_\n",
"\n",
"#make 2d embedding\n",
"mds2 = manifold.MDS(n_components=2, max_iter=3000, eps=1e-9, random_state=seed,\n",
" dissimilarity=\"precomputed\", n_jobs=1)\n",
"embed2d = mds2.fit(distances).embedding_"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 6
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ok, the hard work is done, now let's make some plots. Let's color each point so we can see the correspondence. The colors will mainly stripe along a constant mean (as in all green points will correspond to a mean of ~0)."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Setup plots\n",
"fig = plt.figure(figsize=(5*3,4.5))\n",
"\n",
"# choose a different color for each point\n",
"colors = plt.cm.jet(np.linspace(0, 1, len(gridMuSigma)))\n",
"\n",
"#make original grid plot\n",
"gridsubpl = fig.add_subplot(131)\n",
"gridsubpl.scatter(gridMuSigma[:, 0], gridMuSigma[:, 1], s=20, c=colors)\n",
"gridsubpl.set_xlabel('mean')\n",
"gridsubpl.set_ylabel('standard deviation')\n",
"plt.title('Original grid in mean and std. dev.')\n",
"plt.axis('tight')\n",
"\n",
"# plot 3d embedding\n",
"#since it is a surface of constant negative curvature (hyperbolic geometry)\n",
"#expect it to look like the pseudo-sphere\n",
"#http://mathworld.wolfram.com/Pseudosphere.html\n",
"subpl = fig.add_subplot(132,projection='3d')\n",
"subpl.scatter(embed3d[:, 0], embed3d[:, 1], embed3d[:, 2],s=20, c=colors)\n",
"subpl.view_init(42, 101) #looks good when njobs=-1\n",
"subpl.view_init(-130,-33)#looks good when njobs=1\n",
"\n",
"plt.suptitle('3D Multidim. Scaling Embedding')\n",
"plt.axis('tight')\n",
"\n",
"# plot 2d embedding\n",
"subpl2 = fig.add_subplot(133)\n",
"subpl2.set_autoscaley_on(False)\n",
"subpl2.scatter(embed2d[:, 0], embed2d[:, 1],s=20, c=colors)\n",
"plt.title('2D Multidim. Scaling Embedding')\n",
"plt.axis('tight')\n",
"\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
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b7dx1111kZGQQFhbGqFGjmDRp0uVOq8aoqftHdYNUFEVRFEW5xG699VZWrVpF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\nMbVC5LprW8vevXt9xq9fv16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tXRHHj9h56Z+59Ot/g9fc+/UbwZynDezZI+zeLTzztIF+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acOFovJ51PNyZOn8M5iI66qH+Z/cG0JTaI+5cDerT59b9KyA4dKPwa1BwGg3DqWCT1i+d+b04rY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+4y2hv63SA3rb5RpskUmSZTZOQXwyVpZFIZ3cmTJyUotLok/PKs3CgfSedPJ0jt+tHicDj+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\nGxBiJ0fK0z9A8/UFJMTuR7du3Zp9HIz2RbtfrAUHB8HY+CSAGgAFk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"text": [
""
]
}
],
"prompt_number": 8
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*Wow! Super cool! That looks like the pseudo-sphere!*\n",
"\n",
"Ok, it looks like half of the pseudo-sphere. That makes sense because as the means get furhter apart I'm never going to wrap around and have distributions that seem similar. \n",
"\n",
"The 2d embedding looks cool too -- in fact, this image is Fig 5 of the FINE paper](http://arxiv.org/abs/0802.2050) I mentioned above. I'm not quite sure why those authors never made the 3d embedding, but they do have some nice thoughts about how to approximate the Fisher information distance.\n",
"\n",
"You can see some nice correspondence of the curves of constant $\\mu$ and constant $\\sigma$ between the 2d and 3d embeddings that seem to are reminicent of the [correspondance of the pseudosphere and the 2d Poincar\u00e9 disc](http://web1.kcn.jp/hp28ah77/us20_pseu.htm) model of this same hyperbolic space shown below. The Poincar\u00e9 disc is 2d, but it is not the same kind of distance-preserving embedding, so that visual correspondance is a bit misleading. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So that was a very fun weekend project. I'm impressed with scikit-learn and how well the MDS algorithm discovered the pseudo-sphere. Now to think about how to visualize some more tricky theoretical physics models where I can describe the information metric, but it's not so easy to calculate the distance between random points in that space."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*This post was created entirely in IPython notebook. Download the raw notebook*\n",
"[*here*](https://github.com/cranmer/play/raw/master/manifoldLearning/GaussianInformationGeometryEmbedding.ipynb), *or see a static view on* [*nbviewer*](http://nbviewer.ipython.org/url/github.com/cranmer/play/raw/master/manifoldLearning/GaussianInformationGeometryEmbedding.ipynb)"
]
}
],
"metadata": {}
}
]
}