1029_Simulating BM.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (mpl.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    var resizeObserver = new ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * mpl.ratio);\n",
       "                canvas.setAttribute('height', height * mpl.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / mpl.ratio,\n",
       "        fig.canvas.height / mpl.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    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",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        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, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, 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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / mpl.ratio;\n",
       "    fig.root.removeEventListener('remove', this._remove_fig_handler);\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.innerHTML =\n",
       "        '<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'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function () {\n",
       "    this.close_ws(this, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "    el.addEventListener('remove', this._remove_fig_handler);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Simulating Browinan Motion\n",
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "np.random.seed(0)\n",
    "\n",
    "T = 1\n",
    "N = 100000\n",
    "dt = T/N\n",
    "Z = np.zeros(N+1)\n",
    "t = np.zeros(N+1)\n",
    "\n",
    "Z[0] = 0.0\n",
    "t[0] = 0.0\n",
    "\n",
    "for k in range(N):\n",
    "    dZ = np.random.randn()*np.sqrt(dt)\n",
    "    Z[k+1] = Z[k] + dZ\n",
    "    t[k+1] = t[k] + dt\n",
    "    \n",
    "plt.plot(t,Z)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimated Call Price (95% C.I.) =  16.27627587133836  ±  0.01866985776459475\n",
      "True Call Price =  16.27544888310898\n"
     ]
    }
   ],
   "source": [
    "# BSM_example (Euler_Richardson)\n",
    "\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "\n",
    "# BSM closed-form solution (for call) \n",
    "def bsm_call_value(S0, K, T, r, sigma):\n",
    "    d1= (np.log(S0/K)+(r+0.5*sigma**2)*T)/(sigma*np.sqrt(T))\n",
    "    d2= (np.log(S0/K)+(r-0.5*sigma**2)*T)/(sigma*np.sqrt(T))\n",
    "    call_value = (S0*stats.norm.cdf(d1,0.0,1.0) - K*np.exp(-r*T)*stats.norm.cdf(d2,0.0,1.0))\n",
    "    return call_value\n",
    "\n",
    "# BSMOPM parameter setting\n",
    "S_0= 100.\n",
    "K= 100.\n",
    "T= 1.0\n",
    "r= 0.01\n",
    "sigma= 0.4\n",
    "\n",
    "np.random.seed(0)\n",
    "\n",
    "N = int(1e7)\n",
    "M = 126\n",
    "dt = T/M\n",
    "St_1 = np.ones(N)*S_0\n",
    "St_2 = np.ones(N)*S_0\n",
    "\n",
    "# Euler Discretization Scheme with Richardson Extrapolation\n",
    "temp_Z = np.zeros(N)\n",
    "\n",
    "for k in range(M):\n",
    "    Z = np.random.randn(N)\n",
    "    St_1 = St_1 + r*St_1*dt + sigma*St_1*Z*np.sqrt(dt)\n",
    "    temp_Z = temp_Z + Z\n",
    "    \n",
    "    if(k%2==1):\n",
    "        St_2 = St_2 + r*St_2*2*dt + sigma*St_2*temp_Z*np.sqrt(dt)\n",
    "        temp_Z = np.zeros(N)\n",
    "\n",
    "C_0_1 = np.exp(-r*T)*(St_1-K)*(St_1 > K)\n",
    "C_0_2 = np.exp(-r*T)*(St_2-K)*(St_2 > K)        \n",
    "C_0 = 2*C_0_1 - C_0_2\n",
    "\n",
    "print('Estimated Call Price (95% C.I.) = ',np.mean(C_0),' ± ',1.96*np.std(C_0)/np.sqrt(N))\n",
    "print('True Call Price = ', bsm_call_value(S_0,K,T,r,sigma))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimated Call Price (95% C.I.) =  16.284918758810424  ±  0.018618307083550653\n",
      "True Call Price =  16.27544888310898\n"
     ]
    }
   ],
   "source": [
    "# BSM_example\n",
    "\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "\n",
    "# BSM closed-form solution (for call) \n",
    "def bsm_call_value(S0, K, T, r, sigma):\n",
    "    d1= (np.log(S0/K)+(r+0.5*sigma**2)*T)/(sigma*np.sqrt(T))\n",
    "    d2= (np.log(S0/K)+(r-0.5*sigma**2)*T)/(sigma*np.sqrt(T))\n",
    "    call_value = (S0*stats.norm.cdf(d1,0.0,1.0) - K*np.exp(-r*T)*stats.norm.cdf(d2,0.0,1.0))\n",
    "    return call_value\n",
    "\n",
    "# BSMOPM parameter setting\n",
    "S_0= 100.\n",
    "K= 100.\n",
    "T= 1.0\n",
    "r= 0.01\n",
    "sigma= 0.4\n",
    "\n",
    "np.random.seed(0)\n",
    "\n",
    "N = int(1e7)\n",
    "M = 125\n",
    "dt = T/M\n",
    "St = np.ones(N)*S_0\n",
    "\n",
    "# Euler Discretization Scheme\n",
    "for k in range(M):\n",
    "    Z = np.random.randn(N)\n",
    "    St = St + r*St*dt + sigma*St*Z*np.sqrt(dt)\n",
    "\n",
    "C_0 = np.exp(-r*T)*(St-K)*(St > K)\n",
    "\n",
    "print('Estimated Call Price (95% C.I.) = ',np.mean(C_0),' ± ',1.96*np.std(C_0)/np.sqrt(N))\n",
    "print('True Call Price = ', bsm_call_value(S_0,K,T,r,sigma))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# generating Normal Random Var. validation Example : The Box-Muller Algorithm\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "np.random.seed(0)\n",
    "\n",
    "N = int(1e5)\n",
    "\n",
    "# Uniform Dist. 만들때는 rand (randn은 정규분포))\n",
    "U1 = np.random.rand(N)\n",
    "U2 = np.random.rand(N)\n",
    "\n",
    "X = np.sqrt(-2*np.log(U1))*np.cos(2*np.pi*U2)\n",
    "Y = np.sqrt(-2*np.log(U1))*np.sin(2*np.pi*U2)\n",
    "\n",
    "# 막대기 bean 100개 표시\n",
    "plt.hist(X, 100)\n",
    "plt.show()\n",
    "\n",
    "plt.hist(Y, 100)\n",
    "plt.show()\n",
    "\n",
    "Z1 = np.random.randn(N)\n",
    "Z2 = np.random.normal(size=N, loc=0.5, scale=1.0) # 평균 0.5, 분산 1인 정규분포\n",
    "\n",
    "plt.hist(Z2, 100)\n",
    "plt.hist(Z1, 100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "operands could not be broadcast together with shapes (0,13) (100,) ",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-22-e18440ebd350>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mM\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m     \u001b[0mY\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrandom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrandn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mN\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqrt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdt\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# 분산이 sqrt(dt)인 정규분포 Y\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m     \u001b[0mW\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mW\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     18\u001b[0m     \u001b[0mt\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mdt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (0,13) (100,) "
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}