Clase 09 - Mapas Auto-Organizables.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mapas Auto-Organizables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Julián D. Arias Londoño\n",
    "\n",
    "Profesor Asociado  \n",
    "Departamento de Ingeniería de Sistemas  \n",
    "Universidad de Antioquia, Medellín, Colombia  \n",
    "julian.ariasl@udea.edu.co"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Los Mapas Auto-Organizables (En inglés: Self-Organizing Maps - SOM), son un tipo de red neuronal que permiten resolver problemas no supervisados. Los SOM están basados un concepto conocido como <i>aprendizaje competitivo</i>; en el cual las neuronas de la capa de salida compiten entre ellas por estar activadas o \"despedidas\". Sólo una neurona de salida puede estar activada en un determinado tiempo. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En un SOM las neuronas estan ubicadas en los nodos de una cuadrícula, la cual usualmente tiene una o dos dimensiones. Durante el entrenamiento, las neuronas se van ajustando selectivamente a diferentes patrones de entrada (estímulos), en un proceso de aprendizaje competitivo. La ubicación de las neuronas activadas (winning neurons), van formando un mapa topográfico que se relaciona con los patrones de entrada, en el cual la ubicación espacial de las neuronas en la cuadrícula es un indicador de características estadísticas intrínsecas contenidas en los datos de entrada [1]."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "![alt text](Images/scheme2.png \"Neuronas\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Existen principalmente dos tipos de mapas:\n",
    "<ul>\n",
    "<li>Modelo de Willshaw-von der Malsburg</li>\n",
    "<li>Modelo de Kohonen (figura anterior)</li>\n",
    "</ul>\n",
    "\n",
    "El modelo de Kohonen ha sido mucho más ampliamente utilizado ya que el modelo de Willshaw-von der Malsburg está diseñado para modelar problemas en los que el número de entradas es igual al número de salidas. Por otro lado, el modelo de Kohonen captura los elementos esenciales de los mapas corticales, a partir de los cuales se inspiraron este tipo de RNA."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El entrenamiento de la red responsable de la conformación de los mapas tiene tres fases principales (cuatro si consideramos la inicialización de los pesos de la red, para lo cual usamos un generador de números aleatorios):\n",
    "\n",
    "<ul>\n",
    "<li><b>Competición</b>: Dada una muestra $\\bf{x}$, en esta etapa se debe determinar la neurona ganadora.</li>\n",
    "<li><b>Cooperación</b>: Teniendo en cuenta la neurona ganadora, se define la vecindad de las neuronas excitadas, lo que permite generar el mapa topográfico.</li>\n",
    "<li><b>Adaptación sináptica</b>: Es el paso de adaptación, en el que se reajustan los pesos de la red, para favorecer las neuronas actividas</li>\n",
    "</ul>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Proceso de Competición"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para mantener la notación utilizada en la gráfica, supongamos que $m$ es la dimensión del espacio de entrada, es decir el número de características. Cada muestra estará entonces representada por un vector ${\\bf{x}}=[x_1,x_2,...,x_m]^T$. El vector de pesos sinápticos de cada neurona en la red tiene la misma dimensión del espacio de entrada. Para la neurona $j$, el vector estará dado por ${\\bf{w}}=[w_{j1},w_{j2},...,w_{jm}]^T$, para $j=1,2,...,K$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para encontrar la neurona que mejor \"combina\" con un determinado vector de entrada $\\bf{x}$, podemos evaluar los productos internos ${\\bf{w}}_j^T{\\bf{x}}$ y encontrar la neurona $j$ para la cual dicho producto es mayor. El producto es mayor cuando el ángulo entre los vectores es 0, es decir que encontrar la neurona con mayor producto interno ${\\bf{w}}_j^T{\\bf{x}}$, es matemáticamente equivalente a encontrar la neurona $j$ para la cual la distancia entre los vectores ${\\bf{w}}_j$ y ${\\bf{x}}$ sea mínima."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La neurona ganadora será entonces aquella que cumpla la condición:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$i({\\bf{x}})=\\arg \\min_j ||{\\bf{x}} - {\\bf{w}} _j||, \\;\\; j \\in \\mathcal{A}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "donde $\\mathcal{A}$ denota la cuadrícula de neuronas (el conjunto de neuronas)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Proceso cooperativo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La neurona ganadora estará ubicada en el centro de una <b>vencidad topológica </b> de neuronas cooperantes, intentado emular las vecindades neurobológicas observadas en el cerebro humano. La vecindad topológica estará definida por la cercanía física entre las neuronas de la cuadrícula, definiendo un umbral de vecindad para las neuronas cooperantes. Para emular, biologicamente, de mejor manera el comportamiento de las neuronas en la corteza cerebral, la vecindad no se define de manera rígida, sino que por el contrario se usa una función que permita definir el \"nivel de cooperación\" de cualquier neurona en relación con la neurona ganadora, a partir de la distancia existente entre ambas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La vecindad topológica centrada en la neurona ganadora $i$ y cualquier otra neurona exitada $j$, se define como:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$h_{j,i({\\bf{x}})}=\\exp\\left(-\\frac{d_{j,i}^2}{2\\sigma^2}\\right), \\;\\; j\\in \\mathcal{A}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El parámetro $\\sigma$ se conoce como el ancho efectivo de la vecindad topológica. La distancia $d_{j,i}^2$, corresponde a la distancia en la cuadrícula de las neuronas $i$ y $j$. Si la cuadrícula tiene una sola dimensión, la distancia será igual al entero $|j-i|$; en el caso de una cuadrícula de dos dimensiones, la distancia $d_{j,i}^2 = ||{\\bf{r}}_j - {\\bf{r}}_i||^2$, donde el vector ${\\bf{r}}_j$ está compuesto por las coordenadas de la neurona $j$ en la cuadrícula."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Un aspecto importante de los SOM, es que el tamaño de la vecindad topológica se va reduciendo con el tiempo (iteraciones). La manera usual de implementar dicha reducción, es usar la siguiente expresión:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\\sigma(t)=\\sigma_0\\exp\\left(-\\frac{t}{\\tau_1}\\right)\\;\\; t=0,1,2,...$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "donde $\\sigma_0$ es el valor de inicialización del tamaño de vecindad y $\\tau_1$ es un tiempo definido por el diseñador. Si se usa la expresión anterior, la vecindad topológica estará dada por:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$h_{j,i({\\bf{x}})}(t)=\\exp\\left(-\\frac{d_{j,i}^2}{2\\sigma^2(t)}\\right), \\;\\; t=0,1,2,...$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Proceso de Adaptación"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Esta es la última parte del proceso, en la cual se implementa el \"auto-organizamiento\" de la red. Para esto, el vector de pesos sináptico ${\\bf{w}}_j$ de la neurona $j$, debe cambiar con relación al vector de entrada $\\bf{x}$. Como el objetivo es que cada uno de los pesos de las neuronas se muevan en la dirección del vector entrada, siempre y cuando la neurona a actualizar esté en la región de vecindad de la neurona ganadora, la función de actualización en la iteración $t+1$ tiene la forma:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$${\\bf{w}}_j(t+1)={\\bf{w}}_j(t)+\\eta(t)h_{j,i({\\bf{x}})}(t)({\\bf{x}}(t)-{\\bf{w}}_j(t))$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En este caso la tasa de aprendizaje se asume variable, y está dada por:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\\eta(t) = \\eta_0\\exp\\left(-\\frac{t}{\\tau_2}\\right) \\;\\; t=0,1,2,...$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "donde $\\tau_2$ es otra constante de tiempo del algoritmo SOM. Valores típicos son $\\eta_0 = 0.1$ y $\\tau_2 = 1000$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Veamos un ejemplo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Se debe instalar la siguiente libreria\n",
    "!pip install git+https://github.com/sevamoo/SOMPY.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#from mvpa2.suite import *\n",
    "import numpy as np\n",
    "colors = np.array(\n",
    "         [[0., 0., 0.],\n",
    "          [0., 0., 1.],\n",
    "          [0., 0., 0.5],\n",
    "          [0.125, 0.529, 1.0],\n",
    "          [0.33, 0.4, 0.67],\n",
    "          [0.6, 0.5, 1.0],\n",
    "          [0., 1., 0.],\n",
    "          [1., 0., 0.],\n",
    "          [0., 1., 1.],\n",
    "          [1., 0., 1.],\n",
    "          [1., 1., 0.],\n",
    "          [1., 1., 1.],\n",
    "          [.33, .33, .33],\n",
    "          [.5, .5, .5],\n",
    "          [.66, .66, .66]])\n",
    "\n",
    "# store the names of the colors for visualization later on\n",
    "color_names = \\\n",
    "        ['black', 'blue', 'darkblue', 'skyblue',\n",
    "         'greyblue', 'lilac', 'green', 'red',\n",
    "         'cyan', 'violet', 'yellow', 'white',\n",
    "         'darkgrey', 'mediumgrey', 'lightgrey']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sompy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "sm = sompy.SOMFactory().build(colors, [20, 30], normalization = 'var', initialization='random', neighborhood = 'gaussian', component_names=['R','G','B'])\n",
    "sm.train(n_job=4, verbose=False, train_len_factor=0.5, train_rough_len=2, train_finetune_len=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 1152x192 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sompy.visualization.mapview import View2D\n",
    "view2D  = View2D(50,50,\"rand data\",text_size=10)\n",
    "view2D.show(sm, col_sz=4, which_dim=\"all\", denormalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20, 30, 3)"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "codebook = sm._normalizer.denormalize_by(sm.data_raw, sm.codebook.matrix)\n",
    "mp = codebook.reshape(sm.codebook.mapsize[0],sm.codebook.mapsize[1],codebook.shape[1])\n",
    "mp.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Definiendo un SOM con una cuadrícula de 20x40 neuronas de salida y 400 iteraciones."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "#som = SimpleSOMMapper((20, 30), 400, learning_rate=0.05)\n",
    "#som.train(colors)\n",
    "Neurons = np.arange(sm.codebook.matrix.shape[0]).reshape(sm.codebook.mapsize[0],sm.codebook.mapsize[1])\n",
    "plt.figure(figsize=(15,8))\n",
    "plt.imshow(mp, origin='lower')\n",
    "mapped = sm.project_data(colors)\n",
    "\n",
    "plt.title('Color SOM')\n",
    "# SOM's kshape is (rows x columns), while matplotlib wants (X x Y)\n",
    "for i,j in enumerate(mapped):\n",
    "    m = np.asarray(np.where(Neurons == j)).flatten()\n",
    "    plt.text(m[1], m[0], color_names[i], ha='center', va='center',\n",
    "           bbox=dict(facecolor='white', alpha=0.5, lw=0))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Veamos un ejemplo donde un algoritmo de clustering convencional tendría problemas y el SOM no"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fb06168e9d0>]"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "dlen = 700\n",
    "tetha = np.random.uniform(low=0,high=2*np.pi,size=dlen)[:,np.newaxis]\n",
    "X1 = 3*np.cos(tetha)+ .22*np.random.rand(dlen,1)\n",
    "Y1 = 3*np.sin(tetha)+ .22*np.random.rand(dlen,1)\n",
    "Data1 = np.concatenate((X1,Y1),axis=1)\n",
    "X2 = 1*np.cos(tetha)+ .22*np.random.rand(dlen,1)\n",
    "Y2 = 1*np.sin(tetha)+ .22*np.random.rand(dlen,1)\n",
    "Data2 = np.concatenate((X2,Y2),axis=1)\n",
    "X3 = 5*np.cos(tetha)+ .22*np.random.rand(dlen,1)\n",
    "Y3 = 5*np.sin(tetha)+ .22*np.random.rand(dlen,1)\n",
    "Data3 = np.concatenate((X3,Y3),axis=1)\n",
    "X4 = 8*np.cos(tetha)+ .22*np.random.rand(dlen,1)\n",
    "Y4 = 8*np.sin(tetha)+ .22*np.random.rand(dlen,1)\n",
    "Data4 = np.concatenate((X4,Y4),axis=1)\n",
    "Data2 = np.concatenate((Data1,Data2,Data3,Data4),axis=0)\n",
    "fig = plt.figure()\n",
    "fig.set_size_inches(7,7)\n",
    "plt.plot(Data2[:,0],Data2[:,1],'ob',alpha=0.2, markersize=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2800, 2)"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "mapsize = [50,50]\n",
    "som = sompy.SOMFactory.build(Data2, mapsize, mask=None, mapshape='planar', lattice='rect', normalization='var', initialization='pca', neighborhood='gaussian', training='batch', name='sompy')  # this will use the default parameters, but i can change the initialization and neighborhood methods\n",
    "som.train(n_job=1, verbose=False, train_finetune_len=200)  # verbose='debug' will print more, and verbose=None wont print anything"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1188x264 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "v = sompy.mapview.View2DPacked(50, 50, 'test',text_size=8)  \n",
    "# could be done in a one-liner: sompy.mapview.View2DPacked(300, 300, 'test').show(som)\n",
    "v.show(som, what='codebook', which_dim=[0,1], cmap=None, col_sz=6) #which_dim='all' default\n",
    "# v.save('2d_packed_test')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/SOMPY-1.1-py3.7.egg/sompy/visualization/mapview.py:163: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x1800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#In this case, K-means simply fails as expected\n",
    "\n",
    "v = sompy.mapview.View2DPacked(2, 2, 'test',text_size=8)  \n",
    "#first you can do clustering. Currently only K-means on top of the trained som\n",
    "cl = som.cluster(n_clusters=4)\n",
    "v.show(som, what='cluster')\n",
    "# v.save('kmeans_test')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#But Umatrix finds the clusters easily\n",
    "u = sompy.umatrix.UMatrixView(50, 50, 'umatrix', show_axis=True, text_size=8, show_text=True)\n",
    "#This is the Umat value\n",
    "UMAT  = u.build_u_matrix(som, distance=1, row_normalized=False)\n",
    "UMAT = u.show(som, distance2=1, row_normalized=False, show_data=True, contooor=False, blob=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[1] Simon Haykin, Neural Networks and Learning Machines, 3ra Edición, Prentice Hall, USA, 2009."
   ]
  }
 ],
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