18.06-PS9.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Removing Homework (unregistered)\n",
      "INFO: Cloning Homework from https://github.com/shashi/Homework.jl.git\n",
      "INFO: Computing changes...\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<script charset=\"utf-8\">(function ($, undefined) {\n",
       "\n",
       "    function createElem(tag, attr, content) {\n",
       "\t// TODO: remove jQuery dependency\n",
       "\tvar el = $(\"<\" + tag + \"/>\").attr(attr);\n",
       "\tif (content) {\n",
       "\t    el.append(content);\n",
       "\t}\n",
       "\treturn el[0];\n",
       "    }\n",
       "\n",
       "    // A widget must expose an id field which identifies it to the backend,\n",
       "    // an elem attribute which is will be added to the DOM, and\n",
       "    // a getState() method which returns the value to be sent to the backend\n",
       "    // a sendUpdate() method which sends its current value to the backend\n",
       "    var Widget = {\n",
       "\tid: undefined,\n",
       "\telem: undefined,\n",
       "\tlabel: undefined,\n",
       "\tgetState: function () {\n",
       "\t    return this.elem.value;\n",
       "\t},\n",
       "\tsendUpdate: undefined\n",
       "    };\n",
       "\n",
       "    var Slider = function (typ, id, init) {\n",
       "\tvar attr = { type:  \"range\",\n",
       "\t\t     value: init.value,\n",
       "\t\t     min:   init.min,\n",
       "\t\t     max:   init.max,\n",
       "\t\t     step:  init.step },\n",
       "\t    elem = createElem(\"input\", attr),\n",
       "\t    self = this;\n",
       "\n",
       "\telem.onchange = function () {\n",
       "\t    self.sendUpdate();\n",
       "\t}\n",
       "\n",
       "\tthis.id = id;\n",
       "\tthis.elem = elem;\n",
       "\tthis.label = init.label;\n",
       "\n",
       "\tInputWidgets.commInitializer(this); // Initialize communication\n",
       "    }\n",
       "    Slider.prototype = Widget;\n",
       "\n",
       "    var Checkbox = function (typ, id, init) {\n",
       "\tvar attr = { type: \"checkbox\",\n",
       "\t\t     checked: init.value },\n",
       "\t    elem = createElem(\"input\", attr),\n",
       "\t    self = this;\n",
       "\n",
       "\tthis.getState = function () {\n",
       "\t    return elem.checked;\n",
       "\t}\n",
       "\telem.onchange = function () {\n",
       "\t    self.sendUpdate();\n",
       "\t}\n",
       "\n",
       "\tthis.id = id;\n",
       "\tthis.elem = elem;\n",
       "\tthis.label = init.label;\n",
       "\n",
       "\tInputWidgets.commInitializer(this);\n",
       "    }\n",
       "    Checkbox.prototype = Widget;\n",
       "\n",
       "    var Button = function (typ, id, init) {\n",
       "\tvar attr = { type:    \"button\",\n",
       "\t\t     value:   init.label },\n",
       "\t    elem = createElem(\"input\", attr),\n",
       "\t    self = this;\n",
       "\tthis.getState = function () {\n",
       "\t    return null;\n",
       "\t}\n",
       "\telem.onclick = function () {\n",
       "\t    self.sendUpdate();\n",
       "\t}\n",
       "\n",
       "\tthis.id = id;\n",
       "\tthis.elem = elem;\n",
       "\tthis.label = init.label;\n",
       "\n",
       "\tInputWidgets.commInitializer(this);\n",
       "    }\n",
       "    Button.prototype = Widget;\n",
       "\n",
       "    var Text = function (typ, id, init) {\n",
       "\tvar attr = { type:  \"text\",\n",
       "\t\t     placeholder: init.label,\n",
       "\t\t     value: init.value },\n",
       "\t    elem = createElem(\"input\", attr),\n",
       "\t    self = this;\n",
       "\tthis.getState = function () {\n",
       "\t    return elem.value;\n",
       "\t}\n",
       "\telem.onkeyup = function () {\n",
       "\t    self.sendUpdate();\n",
       "\t}\n",
       "\n",
       "\tthis.id = id;\n",
       "\tthis.elem = elem;\n",
       "\tthis.label = init.label;\n",
       "\n",
       "\tInputWidgets.commInitializer(this);\n",
       "    }\n",
       "    Text.prototype = Widget;\n",
       "\n",
       "    var Textarea = function (typ, id, init) {\n",
       "\tvar attr = { placeholder: init.label },\n",
       "\t    elem = createElem(\"textarea\", attr, init.value),\n",
       "\t    self = this;\n",
       "\tthis.getState = function () {\n",
       "\t    return elem.value;\n",
       "\t}\n",
       "\telem.onchange = function () {\n",
       "\t    self.sendUpdate();\n",
       "\t}\n",
       "\n",
       "\tthis.id = id;\n",
       "\tthis.elem = elem;\n",
       "\tthis.label = init.label;\n",
       "\n",
       "\tInputWidgets.commInitializer(this);\n",
       "    }\n",
       "    Textarea.prototype = Widget;\n",
       "\n",
       "    // RadioButtons\n",
       "    // Dropdown\n",
       "    // HTML\n",
       "    // Latex\n",
       "\n",
       "    var InputWidgets = {\n",
       "\tSlider: Slider,\n",
       "\tCheckbox: Checkbox,\n",
       "\tButton: Button,\n",
       "\tText: Text,\n",
       "\tTextarea: Textarea,\n",
       "\tdebug: false,\n",
       "\tlog: function () {\n",
       "\t    if (InputWidgets.debug) {\n",
       "\t\tconsole.log.apply(console, arguments);\n",
       "\t    }\n",
       "\t},\n",
       "\t// a central way to initalize communication\n",
       "\t// for widgets.\n",
       "\tcommInitializer: function (widget) {\n",
       "\t    widget.sendUpdate = function () {};\n",
       "\t}\n",
       "    };\n",
       "\n",
       "    window.InputWidgets = InputWidgets;\n",
       "\n",
       "})(jQuery, undefined);\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div id=\"interact-js-shim\">\n",
       "    <script charset=\"utf-8\">\n",
       "(function (IPython, $, _, MathJax, Widgets) {\n",
       "    $.event.special.destroyed = {\n",
       "\tremove: function(o) {\n",
       "\t    if (o.handler) {\n",
       "\t\to.handler.apply(this, arguments)\n",
       "\t    }\n",
       "\t}\n",
       "    }\n",
       "\n",
       "    var OutputArea = IPython.version >= \"4.0.0\" ? require(\"notebook/js/outputarea\").OutputArea : IPython.OutputArea;\n",
       "\n",
       "    var redrawValue = function (container, type, val) {\n",
       "\tvar selector = $(\"<div/>\");\n",
       "\tvar oa = new OutputArea(_.extend(selector, {\n",
       "\t    selector: selector,\n",
       "\t    prompt_area: true,\n",
       "\t    events: IPython.events,\n",
       "\t    keyboard_manager: IPython.keyboard_manager\n",
       "\t})); // Hack to work with IPython 2.1.0\n",
       "\n",
       "\tswitch (type) {\n",
       "\tcase \"image/png\":\n",
       "            var _src = 'data:' + type + ';base64,' + val;\n",
       "\t    $(container).find(\"img\").attr('src', _src);\n",
       "\t    break;\n",
       "\tdefault:\n",
       "\t    var toinsert = OutputArea.append_map[type].apply(\n",
       "\t\toa, [val, {}, selector]\n",
       "\t    );\n",
       "\t    $(container).empty().append(toinsert.contents());\n",
       "\t    selector.remove();\n",
       "\t}\n",
       "\tif (type === \"text/latex\" && MathJax) {\n",
       "\t    MathJax.Hub.Queue([\"Typeset\", MathJax.Hub, toinsert.get(0)]);\n",
       "\t}\n",
       "    }\n",
       "\n",
       "\n",
       "    $(document).ready(function() {\n",
       "\tWidgets.debug = false; // log messages etc in console.\n",
       "\tfunction initComm(evt, data) {\n",
       "\t    var comm_manager = data.kernel.comm_manager;\n",
       "        //_.extend(comm_manager.targets, require(\"widgets/js/widget\"))\n",
       "\t    comm_manager.register_target(\"Signal\", function (comm) {\n",
       "            comm.on_msg(function (msg) {\n",
       "                //Widgets.log(\"message received\", msg);\n",
       "                var val = msg.content.data.value;\n",
       "                $(\".signal-\" + comm.comm_id).each(function() {\n",
       "                var type = $(this).data(\"type\");\n",
       "                if (val[type]) {\n",
       "                    redrawValue(this, type, val[type], type);\n",
       "                }\n",
       "                });\n",
       "                delete val;\n",
       "                delete msg.content.data.value;\n",
       "            });\n",
       "\t    });\n",
       "\n",
       "\t    // coordingate with Comm and redraw Signals\n",
       "\t    // XXX: Test using Reactive here to improve performance\n",
       "\t    $([IPython.events]).on(\n",
       "\t\t'output_appended.OutputArea', function (event, type, value, md, toinsert) {\n",
       "\t\t    if (md && md.reactive) {\n",
       "                // console.log(md.comm_id);\n",
       "                toinsert.addClass(\"signal-\" + md.comm_id);\n",
       "                toinsert.data(\"type\", type);\n",
       "                // Signal back indicating the mimetype required\n",
       "                var comm_manager = IPython.notebook.kernel.comm_manager;\n",
       "                var comm = comm_manager.comms[md.comm_id];\n",
       "                comm.then(function (c) {\n",
       "                    c.send({action: \"subscribe_mime\",\n",
       "                       mime: type});\n",
       "                    toinsert.bind(\"destroyed\", function() {\n",
       "                        c.send({action: \"unsubscribe_mime\",\n",
       "                               mime: type});\n",
       "                    });\n",
       "                })\n",
       "\t\t    }\n",
       "\t    });\n",
       "\t}\n",
       "\n",
       "\ttry {\n",
       "\t    // try to initialize right away. otherwise, wait on the status_started event.\n",
       "\t    initComm(undefined, IPython.notebook);\n",
       "\t} catch (e) {\n",
       "\t    $([IPython.events]).on('kernel_created.Kernel kernel_created.Session', initComm);\n",
       "\t}\n",
       "    });\n",
       "})(IPython, jQuery, _, MathJax, InputWidgets);\n",
       "</script>\n",
       "    <script>\n",
       "        window.interactLoadedFlag = true\n",
       "       $(\"#interact-js-shim\").bind(\"destroyed\", function () {\n",
       "           if (window.interactLoadedFlag) {\n",
       "               console.warn(\"JavaScript required by Interact will be removed if you remove this cell or run using Interact more than once.\")\n",
       "           }\n",
       "       })\n",
       "       $([IPython.events]).on(\"kernel_starting.Kernel kernel_restarting.Kernel\", function () { window.interactLoadedFlag = false })\n",
       "   </script>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: No packages to install, update or remove\n",
      "WARNING: This version of the GnuTLS library (3.2.11) is deprecated\n",
      "and contains known security vulnerabilities. Please upgrade to a\n",
      "more recent version.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<script>(function ($) {\n",
       "        // hijack IPython's methods of all CodeCells with the required metadata\n",
       "    if (!window.Homework) {\n",
       "        var get_text = IPython.CodeCell.prototype.get_text\n",
       "        IPython.CodeCell.prototype.get_text = function () {\n",
       "            if (this.metadata && typeof(this.metadata.question) !== \"undefined\") {\n",
       "                var fn = (Homework.mode() == \"create\") ? \"new_question\" : \"attempt_prompt\";\n",
       "                return 'Homework.' + fn + '(' + [\n",
       "                                         JSON.stringify(JSON.stringify(this.metadata)),\n",
       "                                         \"begin \\n\" + get_text.call(this) +\"\\n end\"\n",
       "                                       ].join(\", \") + \")\"\n",
       "            } else {\n",
       "                console.log(\"vs\", get_text.call(this))\n",
       "                return get_text.call(this)\n",
       "            }\n",
       "        }\n",
       "\n",
       "        var cell_to_json = IPython.CodeCell.prototype.toJSON\n",
       "        IPython.CodeCell.prototype.toJSON = function () {\n",
       "            if (this.metadata && typeof(this.metadata.question) !== \"undefined\") {\n",
       "                data = cell_to_json.call(this)\n",
       "                data.source = get_text.call(this)\n",
       "                return data\n",
       "            } else {\n",
       "                return cell_to_json.call(this)\n",
       "            }\n",
       "        }\n",
       "\n",
       "        var rename_keys = IPython.OutputArea.prototype.rename_keys;\n",
       "        IPython.OutputArea.prototype.rename_keys = function (data, key_map) {\n",
       "            data = rename_keys(data, key_map)\n",
       "\n",
       "            if (data.metadata && data.metadata.reactive) {\n",
       "                var cls = \".signal-\" + data.metadata.comm_id\n",
       "                data.html = $(cls).eq(0).html()\n",
       "            }\n",
       "            return data\n",
       "        }\n",
       "\n",
       "        var delete_cell = IPython.Notebook.prototype.delete_cell\n",
       "        IPython.Notebook.prototype.delete_cell = function (index) {\n",
       "            var i = this.index_or_selected(index);\n",
       "            var cell = this.get_selected_cell();\n",
       "            if (cell.metadata && typeof(cell.metadata.question) !== \"undefined\") {\n",
       "                alert(\"Cannot delete this cell. You need to code the answer to Question \" + \n",
       "                        cell.metadata.question + \" here.\")\n",
       "            } else {\n",
       "                // go on and delete\n",
       "                delete_cell.call(this, i)\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "\n",
       "\n",
       "    function get_question(q) {\n",
       "        var i = 0\n",
       "        var cell = IPython.notebook.get_cell(i)\n",
       "        while(cell !== null) {\n",
       "            if (cell.metadata && cell.metadata.question === q) {\n",
       "                return cell\n",
       "            }\n",
       "            cell = IPython.notebook.get_cell(i)\n",
       "            i+=1\n",
       "        }\n",
       "        return null\n",
       "    }\n",
       "\n",
       "    function mount_message(cell) {\n",
       "        if (!cell) { return }\n",
       "        var meta = cell.metadata,\n",
       "            msg = meta.msg || \"<span class='icon-terminal'></span> &nbsp; Code your answer above, hit &lt;Shift+Enter&gt;, then Submit. <span style='float: right'>\",\n",
       "            score = meta.score || 0,\n",
       "            max_score = meta.max_score || 0,\n",
       "            attempts = meta.attempts || 0,\n",
       "            max_attempts = meta.max_attempts || 0\n",
       "\n",
       "        msg += \"<span style='position:absolute; top: 0.5em; right:0.5em' class='label label-info'> Score: \"\n",
       "        if (Homework.mode() === \"answering\") {\n",
       "            msg += \"<b>\" + score + \"</b> / <b>\" + max_score + \"</b>\"\n",
       "        } else if (Homework.mode() === \"create\") {\n",
       "            msg += \"<b>\" + max_score + \"</b>\"\n",
       "        }\n",
       "\n",
       "        msg += \" &middot; Attempts: \"\n",
       "        if (Homework.mode() === \"answering\") {\n",
       "            msg += \"<b>\" + attempts + \"</b>\"\n",
       "            if (max_attempts != 0) {\n",
       "                msg += \" / <b>\" + max_attempts + \"</b>\"\n",
       "            }\n",
       "        } else if (Homework.mode() === \"create\") {\n",
       "            msg += \"<b>\" + max_attempts + \"</b>\"\n",
       "        }\n",
       "        msg += \"</span>\"\n",
       "\n",
       "        var level = meta.alert || \"info\"\n",
       "\n",
       "        msg = \"<div class='hw-msg alert alert-\" + level + \"' id='hw-msg-\" + meta.question +\n",
       "               \"' style='padding: 0.5em; margin: 0; position:relative; border-radius: 0'>\" +\n",
       "               msg + \"</div>\"\n",
       "\n",
       "        $(cell.element).find(\".hw-msg\").remove()\n",
       "        $(cell.element).find(\".input_area\").eq(0).append(msg)\n",
       "        if (cell.metadata.finished) { $(cell.element).find(\".widget-area\").hide() }\n",
       "    }\n",
       "\n",
       "    function set_meta(question, extension) {\n",
       "        console.log(\"set meta\", question, extension)\n",
       "        var cell = get_question(question)\n",
       "        for (var key in extension) {\n",
       "            if (extension.hasOwnProperty(key)) {\n",
       "                cell.metadata[key] = extension[key]\n",
       "            }\n",
       "        }\n",
       "        mount_message(cell)\n",
       "    }\n",
       "\n",
       "    function get_question_cells() {\n",
       "        var cell = IPython.notebook.get_cell(0),\n",
       "            i = 0,\n",
       "            cells = []\n",
       "        while(cell !== null) {\n",
       "            if (cell.metadata && typeof(cell.metadata.question) !== \"undefined\") {\n",
       "                var q = cell.metadata.question\n",
       "                cells.push(cell)\n",
       "            }\n",
       "            i+=1\n",
       "            cell = IPython.notebook.get_cell(i)\n",
       "        }\n",
       "        return cells\n",
       "    }\n",
       "\n",
       "    function hw_create(host, course, s, f) {\n",
       "        if(!s) {\n",
       "            s = function(result){\n",
       "                if(result.code == 0) {\n",
       "                    IPython.dialog.modal({\n",
       "                        title: 'Problemset created',\n",
       "                        body: \"The problem set was created. Now run <code>Homework.clear_answers()</code> to get the notebook ready for distribution.\"\n",
       "                    })\n",
       "                }\n",
       "                else {\n",
       "                    IPython.dialog.modal({\n",
       "                        title: 'Problemset NOT created',\n",
       "                        body: \"Non-zero result code. There was a problem saving the problem set!\"\n",
       "                    })\n",
       "                }\n",
       "            };\n",
       "        };\n",
       "        if(!f) {\n",
       "            f = function() {\n",
       "                    IPython.dialog.modal({\n",
       "                        title: 'Failure',\n",
       "                        body: \"Failed to create problem set. Are you sure you have permission to edit the course? Unexpected server error.\"\n",
       "                    })\n",
       "            };\n",
       "        };\n",
       "        console.log({\n",
       "            'mode': 'create',\n",
       "            'params': JSON.stringify(course)\n",
       "        })\n",
       "        $.ajax({\n",
       "            url: host + '/jboxplugin/hw/',\n",
       "            method: 'POST',\n",
       "            data: {\n",
       "                'mode': 'create',\n",
       "                'params': JSON.stringify(course)\n",
       "            },\n",
       "            success: s,\n",
       "            failure: f\n",
       "        })\n",
       "    }\n",
       "\n",
       "    function create_problemset(config) {\n",
       "        config = config || IPython.notebook.metadata.homework\n",
       "\n",
       "        var cells = get_question_cells()\n",
       "\n",
       "        if (!config.host) { config.host == \"\" }\n",
       "        var questions = []\n",
       "        for (var i=0, l=cells.length; i < l; i++) {\n",
       "            questions.push({\n",
       "                id:    String(cells[i].metadata.question),\n",
       "                score: cells[i].metadata.max_score,\n",
       "                attempts: cells[i].metadata.max_attempts,\n",
       "                ans:   cells[i].metadata.answer,\n",
       "                explanation: cells[i].metadata.explanation || \"\"\n",
       "            })\n",
       "        }\n",
       "\n",
       "        var course = {\n",
       "             admins: config.admins || [],\n",
       "             id: config.course,\n",
       "             problemsets: [{\n",
       "                 id: config.problemset,\n",
       "                 questions: questions\n",
       "             }]\n",
       "        }\n",
       "\n",
       "        console.log(course)\n",
       "\n",
       "        try {\n",
       "            hw_create(config.host || \"\", course)\n",
       "        } catch (e) {\n",
       "            alert(\"An error occured. Problem set not saved!\")\n",
       "        }\n",
       "   }\n",
       "\n",
       "   function clear_admin_metadata() {\n",
       "       var cells = get_question_cells()\n",
       "       for (var i=0, l=cells.length; i < l; i++) {\n",
       "           var cell = cells[i]\n",
       "           delete cell.metadata.answer\n",
       "           delete cell.metadata.msg\n",
       "           cell.metadata.finished && delete cell.metadata.finished\n",
       "           delete cell.metadata.alert\n",
       "       }\n",
       "       IPython.notebook.metadata.homework.mode = \"answering\"\n",
       "       Homework.refresh_messages()\n",
       "   }\n",
       "\n",
       "   function clear_answers() {\n",
       "       var cells = get_question_cells()\n",
       "       for (var i=0, l=cells.length; i < l; i++) {\n",
       "           var cell = cells[i]\n",
       "           cell.clear_input()\n",
       "           cell.clear_output()\n",
       "       }\n",
       "       IPython.notebook.metadata.homework.mode = \"answering\"\n",
       "       Homework.refresh_messages()\n",
       "   }\n",
       "\n",
       "    function refresh_messages(q) {\n",
       "        _.map(q ? [get_question(q)] : get_question_cells(), mount_message)\n",
       "    }\n",
       "\n",
       "    $([IPython.events]).on('notebook_loaded.Notebook', refresh_messages)\n",
       "    $([IPython.events]).on('select.Cell', refresh_messages)\n",
       "\n",
       "    setTimeout(refresh_messages, 100)\n",
       "    setTimeout(refresh_messages, 200)\n",
       "    setTimeout(refresh_messages, 400)\n",
       "    setTimeout(refresh_messages, 500)\n",
       "    setTimeout(refresh_messages, 1000)\n",
       "    setTimeout(refresh_messages, 2000)\n",
       "    setTimeout(refresh_messages, 4000)\n",
       "\n",
       "    $([IPython.events]).on('status_started.Kernel', function (data) {\n",
       "        var k = data.kernel || IPython.notebook.kernel\n",
       "        k.comm_manager.register_target(\"HomeworkData\", function (comm) {})\n",
       "    })\n",
       "    IPython.notebook && IPython.notebook.kernel &&\n",
       "        IPython.notebook.kernel.comm_manager.register_target(\"HomeworkData\", function (comm) {})\n",
       "\n",
       "    window.Homework = {\n",
       "        config: {},\n",
       "        metadata: function (field) {\n",
       "            return IPython.notebook.metadata.homework[field]\n",
       "        },\n",
       "        mode: function () {\n",
       "            return Homework.metadata(\"mode\") || \"answering\"\n",
       "        },\n",
       "        set_meta: set_meta,\n",
       "        mount_message: mount_message,\n",
       "        clear_answers: clear_answers,\n",
       "        clear_admin_metadata: clear_admin_metadata,\n",
       "        get_question: get_question,\n",
       "        get_question_cells: get_question_cells,\n",
       "        refresh_messages: refresh_messages,\n",
       "        create_problemset: create_problemset\n",
       "    }\n",
       "\n",
       "})(jQuery)\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<script>IPython.notebook.kernel.comm_manager.comms[\"eb98aebc-14b8-406a-9325-a27021dd7928\"].then(\n",
       "    function (comm) {\n",
       "        comm.send({\n",
       "            cookie: document.cookie,\n",
       "            host: IPython.notebook.metadata.homework.host,\n",
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       "            mode: IPython.notebook.metadata.homework.mode,\n",
       "            problemset: IPython.notebook.metadata.homework.problemset\n",
       "        })\n",
       "    }\n",
       ")</script>"
      ],
      "text/plain": [
       "Html(\"<script>IPython.notebook.kernel.comm_manager.comms[\\\"eb98aebc-14b8-406a-9325-a27021dd7928\\\"].then(\\n    function (comm) {\\n        comm.send({\\n            cookie: document.cookie,\\n            host: IPython.notebook.metadata.homework.host,\\n            course: IPython.notebook.metadata.homework.course,\\n            mode: IPython.notebook.metadata.homework.mode,\\n            problemset: IPython.notebook.metadata.homework.problemset\\n        })\\n    }\\n)</script>\")"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<iframe src=\"https://docs.google.com/forms/d/1uPqGeJChe0FFOsuUkdeLVbgPo9LzQEbRnS0xIzE-VGo/viewform?embedded=true\" width=\"720\" height=\"570\" frameborder=\"0\" marginheight=\"0\" marginwidth=\"0\">Loading...</iframe>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Pkg.rm(\"Homework\")\n",
    "Pkg.clone(\"https://github.com/shashi/Homework.jl.git\")\n",
    "using Homework\n",
    "\n",
    "\n",
    "Homework.show_mit_form()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Linear Transformations\n",
    "\n",
    "1a (2 pts) Which transformations with input v=(v$_1$,v$_2$) are linear? <br> <br>\n",
    "\n",
    "1. T(v)=(v$_2$,v$_1$) <br>\n",
    "2. T(v)=(v$_1$,v$_1$) <br>\n",
    "3. T(v)=(0,v$_1$) <br>\n",
    "4. T(v)=(0,1) <br> \n",
    "5. T(v)=v$_1$-v$_2$ <br>\n",
    "6. T(v)= v$_1$v$_2$\n",
    "\n",
    "Format: If 1,2,and 6 are linear write [1,2,6] etc.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 2,
    "question": "1a"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1b (1 pt) Which transformations satisfy T(v+w)=T(v)+T(w). The input is v=(v$_1$,v$_2$,v$_3$). <br> <br>\n",
    "\n",
    "1. T(v)=v/$\\|v\\|$ <br>\n",
    "2. T(v)=v$_1$+v$_2$+v$_3$ <br>\n",
    "3. T(v)=(v$_1$,2v$_2$,3v$_3$) <br>\n",
    "4. T(v) = largest component of v\n",
    "\n",
    "Format: If 1 and 4 work write [1,4] etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 2,
    "question": "1b"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1c (1 pt.) Which transformations satisfy T(cv)=cT(v). The input is v=(v$_1$,v$_2$,v$_3$)\n",
    "\n",
    "\n",
    "1. T(v)=v/$\\|v\\|$ <br>\n",
    "2. T(v)=v$_1$+v$_2$+v$_3$ <br>\n",
    "3. T(v)=(v$_1$,2v$_2$,3v$_3$) <br>\n",
    "4. T(v) = largest component of v\n",
    "\n",
    "Format: If 1 and 4 work write [1,4] etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 2,
    "question": "1c"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Transpose as a Linear Transformation\n",
    "\n",
    "(2 pts.) The transformation T that transposes every matrix is definitely linear. Which of these extra properties are true? \n",
    "\n",
    "1. T$^2$ = the identity transformation.<br>\n",
    "2. The kernel of T is the zero matrix. <br>\n",
    "2. Every matrix is in the range of T. <br>\n",
    "4. T(M) = −M is impossible\n",
    "\n",
    "Format: If 1 and 4 are true write [1,4] etc.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 2,
    "question": "2"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Derivative as a Linear Transformation\n",
    "\n",
    "(2 pts.) The transformation S takes the second derivative. Let 1,x,x$^2$,x$^3$ be an ordered basis for degree 3 polynomials in x. Find the 4 by 4 matrix B for S with respect to this ordered basis.\n",
    "\n",
    "Format: [[1 2 3 4],[1 2 3 4],[1 2 3 4],[1 2 3 4]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 5,
    "question": "3"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Fibonacci Matrix SVD\n",
    "\n",
    "Let the SVD of $A=\\left[\\begin{matrix}1 & 1\\\\1 & 0\\end{matrix}\\right]$\n",
    "be $A=U\\Sigma V^T$ where the first row of $U$ is positive.\n",
    "\n",
    "Enter U, $\\Sigma$ and $V$ numerically, we will check a few decimal places.\n",
    "\n",
    "(If you want to use Julia, try -svd(A)[1], diagm(svd(A)[2]), -svd(A)[3] to\n",
    "match the format of MITx)\n",
    "\n",
    "4a.(.5 pts) U="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 1,
    "question": "4a"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4b.(1 pt) $\\Sigma$="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 1,
    "question": "4b"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4c. (.5 pts) V="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 1,
    "question": "4c"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Constructing a matrix of rank one\n",
    "\n",
    "5a (1 pt.) What is the matrix A with rank one that has Av=12u for v=$\\frac{1}{2}$(1,1,1,1) and u=$\\frac{1}{3}$(2,2,1)?\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 2,
    "question": "5a"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5b. (1 pt.)  What is the (non-zero) singular value of $A$?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 2,
    "question": "5b"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Singular Value Decomposition of a Symmetric Matrix\n",
    "\n",
    "6a. (2 pts.)\n",
    "Suppose A is a 2 by 2 symmetric matrix with unit eigenvectors u$_1$ and u$_2$ and corresponding eigenvalues λ$_1$=3 and λ$_2$=−2. What are possible singular value decompositions for A?\n",
    "\n",
    "1. U=(u$_1$,u$_2$), $\\Sigma=\\left[\\begin{matrix}3 & 0\\\\0 & -2\\end{matrix}\\right]$,  V=(u$_1$,u$_2$) <br>\n",
    "2. U=(u$_1$,-u$_2$), $\\Sigma=\\left[\\begin{matrix}3 & 0\\\\0 & 2\\end{matrix}\\right]$,  V=(u$_1$,u$_2$) <br>\n",
    "3. U=(u$_1$,u$_2$), $\\Sigma=\\left[\\begin{matrix}3 & 0\\\\0 & 2\\end{matrix}\\right]$,  V=(u$_1$,u$_2$) <br>\n",
    "4. U=(u$_1$,u$_2$), $\\Sigma=\\left[\\begin{matrix}3 & 0\\\\0 & 2\\end{matrix}\\right]$,  V=(u$_1$,-u$_2$) <br>\n",
    "\n",
    "Format: If 1 and 4 work write [1,4] etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 2,
    "question": "6a"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 7. Linear Fitting of Data\n",
    "\n",
    "\n",
    "Suppose you have the following 3 dimensional points:\n",
    "\n",
    "{⟨0,2,1⟩,⟨0,4,3⟩,⟨1,4,5⟩,⟨1,8,6⟩,⟨1,8,10⟩,⟨4,8,14⟩,⟨5,9,13⟩} <br> <br>\n",
    "We'd like to find the best fit plane that will fit these data points. There are many ways that we can attempt this.\n",
    "\n",
    "We can use least squares approximation\n",
    "\n",
    "$\\begin{bmatrix} x_1 &  y_1 &  1 \\\\ x_2 &  y_2 &  1\\\\ x_3 &  y_3 &  1 \\\\ \\vdots &  \\vdots &  \\vdots \\end{bmatrix} \\begin{bmatrix} A\\\\ B \\\\ C \\end{bmatrix} = \\begin{bmatrix} z_1 \\\\ z_2 \\\\ z_3 \\\\ \\vdots \\end{bmatrix}\n",
    "$\n",
    "\n",
    "to find the best fit plane of the form z=Ax+By+C.\n",
    "However, you might ask yourself why is the z-coordinate on the right, and x and y on the left?\n",
    "Why should z be different?  This strategy \n",
    "assumes that the x and y coordinates are correct, and the error is all in the z-direction, perpendicular to the xy-plane.\n",
    "\n",
    "We could instead assume the error is along the x or the y direction and use least square approximation to find the best fit plane of the form x=Ay+Bz+C or y=Ax+Bz+C. However, each of these methods makes a pretty strong assumption about in which direction the error or noise in the data occurs.\n",
    "\n",
    "Another method is to make an assumption that the data is mostly correct, and lies on some plane, and that the error is small in comparison. A priori, we make no assumption about the direction of this error. This method is called principal component analysis and applies SVD. Let's see how.\n",
    "\n",
    "PRINCIPAL COMPONENT ANALYSIS\n",
    "\n",
    "We will explain this method in the context of the problem we are using. Let A be the matrix whose rows are the data of 3 dimensional points above. However, a more general method is described below. First, find the mean data point μ=[μ$_x$ μ$_y$ μ$_z$]. We use this mean to create a matrix M with zero mean by taking the rows of A and subtracting μ from each row.\n",
    "\n",
    "Once we find the plane P that the data in M lie on, the data from A lie on P+μ.\n",
    "\n",
    "Question: Which plane do the data in M come from? The answer is to use SVD. If we look at svd(M), we get M=USV$^T$. S has 3 nonzero singular values if our data is not already on a plane. However, one singular value will be smaller than the other two. The matrix V=[v$_1$ v$_2$ v$_3$] consists of orthogonal vectors. The conjecture is that the data come from the plane spanned by v$_1$ and v$_2$, and that the error occurs in the direction of v$_3$. Because v$_3$ corresponds to the smallest singular value, this minimizes the magnitude of the error in this data.\n",
    "\n",
    "GENERAL PRINCIPAL COMPONENT ANALYSIS\n",
    "\n",
    "Suppose your data is a collection of m-dimensional vectors: D=[d$_1$, …, $d_n$]. But we suppose that this data should fit some k-dimensional subspace. It doesn't because there is error, noise that is perpendicular to this k-dimensional subspace. The question posed is: what subspace did this data most likely come from? And what dimension is that subspace?\n",
    "\n",
    "Method.\n",
    "\n",
    "* Find the expected value of your data μ=$\\sum_{i=1}^n d_i/n$.\n",
    "\n",
    "* Create a new, zero mean matrix M whose ith row is d$_i$−μ.\n",
    "\n",
    "* Find svd(M)=USV$^T$.\n",
    "\n",
    "* Identify k such that σ$_k$>>σ$_{k+1}$.\n",
    "\n",
    "*  Conjecture that data came from the span of μ and the first k columns of V. These vectors are called the principal components."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7a) (6 pts)\n",
    "\n",
    "\n",
    "This problem is exercise 14.4 in \n",
    "<a href=\"http://cs.nyu.edu/faculty/davise/MathTechniques/index.html\">\n",
    "“Linear Algebra and Probability for Computer Science Applications\", </a> by Ernest Davis.\n",
    "\n",
    "Consider the following set of three dimensional points we introduced earlier.\n",
    "\n",
    "{⟨0,2,1⟩,⟨0,4,3⟩,⟨1,4,5⟩,⟨1,8,6⟩,⟨1,8,10⟩,⟨4,8,14⟩,⟨5,9,13⟩}\n",
    "Find the least squares estimate for z taken as a linear combination of x and y; e.g. z=ax+by+c.\n",
    "\n",
    "Define a matrix A  whose rows are the data above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "alert": "info",
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3-element Array{Int64,1}:\n",
       " 1\n",
       " 3\n",
       " 5"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Complete A (currently with three points) to the seven data points (not graded) \n",
    "A= [ 0 2 1\n",
    "     0 4 3\n",
    "     1 4 5  ]\n",
    "\n",
    "\n",
    "# Also obtain A_ls (least squares)\n",
    "A_ls = [A[:,1:2] ones(size(A,1))]\n",
    "z = A[:,3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let zz be the data predicted by the least squares approximation. (You can use backslash: \"\\\" ) <br>\n",
    "Compute norm(zz-z), the  norm of the difference between zz and the actual data for the z-coordinates "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Fill in the blanks for two points\n",
    "zz = ?? #(Hint: Use A_ls, z, *, and \\ )\n",
    "norm(z-zz)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 6,
    "precision": 3,
    "question": "7a"
   },
   "outputs": [],
   "source": [
    "A_ls =   # Use 2:3 this time\n",
    "x=\n",
    "xx =     # Use x this time\n",
    "norm(x-xx)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7b) ( 6 pts.)\n",
    "\n",
    "\n",
    "Take the same data from before.\n",
    "\n",
    "{⟨0,2,1⟩,⟨0,4,3⟩,⟨1,4,5⟩,⟨1,8,6⟩,⟨1,8,10⟩,⟨4,8,14⟩,⟨5,9,13⟩} <br>\n",
    "This time, find the least squares estimate for x as a linear combination of y and z; e.g. x = A + By + Cz. Do you think the error will be larger or smaller than in part (a)? Compute norm(x-xx)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.097079044348641"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A_ls =   # Use 2:3 this time\n",
    "x=\n",
    "xx =     # Use x this time\n",
    "norm(x-xx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 6,
    "precision": 3,
    "question": "7b"
   },
   "outputs": [],
   "source": [
    "# We can't grade you but try to understand how this works\n",
    "μ = mean(A,1)\n",
    "M = broadcast(-,A,μ) # Make mean 0\n",
    "U,S,V = svd(M)\n",
    "best_fit  = broadcast(+, U[:,1:2]*diagm(S[1:2])*V[:,1:2]', μ) # Make rank 2 and add back mean"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7c) (6 pts.)\n",
    "\n",
    "Looking at the same data one last time.\n",
    "\n",
    "{⟨0,2,1⟩,⟨0,4,3⟩,⟨1,4,5⟩,⟨1,8,6⟩,⟨1,8,10⟩,⟨4,8,14⟩,⟨5,9,13⟩} <br>\n",
    "Find the best-fit plane from a principal component analysis. Use U,S,V = svd(A) to find the 3 singular value decomposition of A. (Julia stores the diagonal of S as a vector which is less wasteful than storing a whole matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7x3 Array{Float64,2}:\n",
       " -0.14732    1.94221   1.08145\n",
       "  0.0728165  4.02856   2.95974\n",
       "  1.1453     4.05699   4.91967\n",
       "  0.449134   7.78393   6.30457\n",
       "  1.96438    8.37827   9.4668 \n",
       "  4.4242     8.16639  13.7655 \n",
       "  4.0915     8.64365  13.5023 "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We can't grade you but try to understand how this works\n",
    "μ = mean(A,1)\n",
    "M = broadcast(-,A,μ) # Make mean 0\n",
    "U,S,V = svd(M)\n",
    "best_fit  = broadcast(+, U[:,1:2]*diagm(S[1:2])*V[:,1:2]', μ) # Make rank 2 and add back mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "max_attempts": 1000,
    "max_score": 6,
    "precision": 3,
    "question": "7c"
   },
   "outputs": [],
   "source": [
    "# For six points create a vector of length three which\n",
    "# has norm(best_fit[:,j]-A[:,j]) for j=1:3\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8. COMPRESSION ALGORITHMS\n",
    "\n",
    "(10 pts.) The following is a classical example of an application of svd, although it is not typically used for image compression .\n",
    "\n",
    "A compression algorithm Φ takes in data D and constructs a representation E=Φ(D) such that:\n",
    "\n",
    "The computer memory required to record E is less than that required by natural encoding of D.\n",
    "\n",
    "There is a decompression algorithm Ψ to reconstruct D from E. If Ψ(E)=D, the algorithms Φ is called lossless compression. If Ψ(E) is approximately D, then Φ is called lossy compression.\n",
    "\n",
    "The singular value decomposition  gives lossy compression algorithms.\n",
    "\n",
    "Suppose image data is stored in an m by n matrix M, let USV$^T$=svd(M). Choose k<<min(m,n) and\n",
    "rebuild the matrix from the best rank k approximation.\n",
    "\n",
    "(This problem is not really being graded you will get a free ten points, but do play with the code\n",
    "and look at how it works)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100  111k  100  111k    0     0   536k      0 --:--:-- --:--:-- --:--:--  538k\n"
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    },
    {
     "data": {
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",
      "text/plain": [
       "RGB Image with:\n",
       "  data: 313x198 Array{RGB{UfixedBase{Uint8,8}},2}\n",
       "  properties:\n",
       "    IMcs: sRGB\n",
       "    spatialorder:  x y\n",
       "    pixelspacing:  1 1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using Images, Interact, Colors  #Ignore warnings\n",
    "picture = download(\"http://web.mit.edu/jfrench/Public/gstrang.png\")\n",
    "A=imread(picture)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#svd the three component arrays in the image\n",
    "arrays = float(separate(A.data))\n",
    "uR,sR,vR=svd(arrays[:,:,1])\n",
    "uG,sG,vG=svd(arrays[:,:,2])\n",
    "uB,sB,vB=svd(arrays[:,:,3]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "Slider{Int64}([Input{Int64}] 25,\"k\",25,1:50)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "RGB Image with:\n",
       "  data: 198x313 Array{RGB{Float64},2}\n",
       "  properties:"
      ]
     },
     "execution_count": 20,
     "metadata": {
      "comm_id": "d6a36ec2-17fc-4e48-a615-c5e671912f10",
      "reactive": true
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reconstruct a rank k version of the picture\n",
    "@manipulate for k=1:50\n",
    "    Image(map(RGB, uR[:,1:k]*diagm(sR[1:k])*vR[:,1:k]',\n",
    "    uG[:,1:k]*diagm(sG[1:k])*vG[:,1:k]',\n",
    "    uB[:,1:k]*diagm(sB[1:k])*vB[:,1:k]'))'\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
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    {
     "data": {
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       "Options{:ToggleButtons,ASCIIString}([Input{ASCIIString}] score,\"report\",\"score\",\"Score\",OptionDict({\"Score\",\"Incorrect attempts\"},{\"Score\"=>\"score\",\"Incorrect attempts\"=>\"attempts\"}),None[],None[])"
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       "<table class=\"data-frame\"><tr><th></th><th>Names</th><th>total</th><th>1a</th><th>1b</th><th>1c</th><th>2</th><th>3</th><th>4a</th><th>4b</th><th>4c</th><th>5a</th><th>5b</th><th>6a</th><th>7a</th><th>7b</th><th>7c</th></tr><tr><th>1</th><td>MAX</td><td><span style=\"color: black\">40.0</span></td><td><span style=\"color: black\">2.0</span></td><td><span style=\"color: black\">2.0</span></td><td><span style=\"color: black\">2.0</span></td><td><span style=\"color: black\">2.0</span></td><td><span style=\"color: black\">5.0</span></td><td><span style=\"color: black\">1.0</span></td><td><span style=\"color: black\">1.0</span></td><td><span style=\"color: black\">1.0</span></td><td><span style=\"color: black\">2.0</span></td><td><span style=\"color: black\">2.0</span></td><td><span style=\"color: black\">2.0</span></td><td><span style=\"color: black\">6.0</span></td><td><span style=\"color: black\">6.0</span></td><td><span style=\"color: black\">6.0</span></td></tr></table>"
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       "1x16 DataFrame\n",
       "| Row | Names | total                 | 1a                     |\n",
       "|-----|-------|-----------------------|------------------------|\n",
       "| 1   | \"MAX\" | Colored(\"black\",40.0) | Colored(\"black\",\"2.0\") |\n",
       "\n",
       "| Row | 1b                     | 1c                     |\n",
       "|-----|------------------------|------------------------|\n",
       "| 1   | Colored(\"black\",\"2.0\") | Colored(\"black\",\"2.0\") |\n",
       "\n",
       "| Row | 2                      | 3                      |\n",
       "|-----|------------------------|------------------------|\n",
       "| 1   | Colored(\"black\",\"2.0\") | Colored(\"black\",\"5.0\") |\n",
       "\n",
       "| Row | 4a                     | 4b                     |\n",
       "|-----|------------------------|------------------------|\n",
       "| 1   | Colored(\"black\",\"1.0\") | Colored(\"black\",\"1.0\") |\n",
       "\n",
       "| Row | 4c                     | 5a                     |\n",
       "|-----|------------------------|------------------------|\n",
       "| 1   | Colored(\"black\",\"1.0\") | Colored(\"black\",\"2.0\") |\n",
       "\n",
       "| Row | 5b                     | 6a                     |\n",
       "|-----|------------------------|------------------------|\n",
       "| 1   | Colored(\"black\",\"2.0\") | Colored(\"black\",\"2.0\") |\n",
       "\n",
       "| Row | 7a                     | 7b                     |\n",
       "|-----|------------------------|------------------------|\n",
       "| 1   | Colored(\"black\",\"6.0\") | Colored(\"black\",\"6.0\") |\n",
       "\n",
       "| Row | 7c                     |\n",
       "|-----|------------------------|\n",
       "| 1   | Colored(\"black\",\"6.0\") |"
      ]
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   "source": [
    "Homework.progress()"
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   "mode": "answering",
   "problemset": "pset9"
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