GaltonMachine.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Galton Machine\n",
    "\n",
    "In the lectures, we discussed the central limit theorem. A Galton machine is as a simple demonstration of how this works using simulated events. The machine works as follows. \n",
    "\n",
    "There's a board with rows of pins with collection buckets (bins) at the bottom. A marble is dropped into the top of the board and left to fall to the bottom. When the marble encounters a pin it will either get deflected one spot to the left or one to the right. Finally when the marble leaves the board at the bottom, it will land in one of the buckets and the position of the bucket that it lands in is recorded. The figure below shows the setup. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![GaltonMachine](galton_image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code below simulates this process and counts the number of marbles that landed in each position. In this code, we record the \"normalised position\" which is just the position divided by the square root of the number of layers, and we bin that in a histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.animation as animation\n",
    "\n",
    "plt.rcParams.update({'font.size': 14})\n",
    "plt.rcParams['figure.figsize'] = (6, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 50-50 probability to go left or right\n",
    "def galton_step(x):\n",
    " r = numpy.random.uniform(0,1)\n",
    " if r < 0.5: return x-1\n",
    " else: return x+1\n",
    "\n",
    "n_layers = 1000\n",
    "n_trials = 1000\n",
    "\n",
    "finish=[]\n",
    "\n",
    "for i in range(n_trials):\n",
    "  start=0\n",
    "  for j in range(n_layers): start = galton_step(start)\n",
    "  # normalise the position \n",
    "  start /=  numpy.math.sqrt(n_layers)\n",
    "  finish.append(start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "\n",
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       "\n",
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       "\n",
       "\n",
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       "\n",
       "\n",
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       "\n",
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       "\n",
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       "    // Updates the figure title.\n",
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       "\n",
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       "    var cursor = msg['cursor'];\n",
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       "\n",
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       "    fig.message.textContent = msg['message'];\n",
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       "\n",
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       "    // Request the server to send over a new figure.\n",
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       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
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       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
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       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
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       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def update(curr):\n",
    "    if curr==n_trials:\n",
    "        a.event_source.stop()\n",
    "    plt.cla()\n",
    "    bins = numpy.arange(-3,3,0.5)\n",
    "    plt.hist(finish[:curr], bins=bins,density=True,color='green',ec='black')\n",
    "    plt.axis([-3,3,0,1])\n",
    "    plt.xlabel(\"position\")\n",
    "    plt.ylabel(\"density of counters\")\n",
    "    plt.title(\"N layers = %d, N trials = %d\"%(n_layers, n_trials))\n",
    "\n",
    "fig =  plt.figure()\n",
    "a = animation.FuncAnimation(fig,update,interval=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you think about the distribution of \"position\", its simly a sum over $X_i$ where $X_i=-1$ or $X_i=+1$ with 50:50 probability. The distribution of each random variable $X_i$ is identical - a uniform distribution in the set $\\left\\{-1,1\\right\\}$. The normalised position $P_{N}$ is then given by, \n",
    "\n",
    "$$\n",
    "P_{N} = \\frac{1}{\\sqrt{N}} \\sum_{i} X_{i}.\n",
    "$$\n",
    "\n",
    "The mean of each distribution of $X_{i}$ is 0, and the variance is $(-1)^2\\times \\frac{1}{2} + (1)^2\\times \\frac{1}{2}=1$. The quantity we saw in lectures, \n",
    "\n",
    "$$\n",
    "T_{N} = \\frac{\\bar{X}N - \\sum_{i}\\mu_{1}^{i}}{\\sqrt{\\sum_{i}v^i_2}} = \\frac{\\frac{N}{N}\\sum_{i}X_{i} - 0 }{\\sqrt{N}} = P_{N}\n",
    "$$\n",
    "\n",
    "So of course as $N\\rightarrow+\\infty$ we know from the CLT that $P_{N}$ will be distributed as $\\phi(0,1)$\n",
    "\n",
    "Try increasing the number of layers `n_layers`. The larger it is, the more normal it will be."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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