索罗增长模型.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 索罗增长模型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$k_{t+1} = \\frac{szk_t^{\\alpha} + (1-\\delta)k_t}{1+n}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Solow:\n",
    "    #default parameter\n",
    "    def __init__(self, n = 0.05,\n",
    "                       s = 0.25, # saving rate\n",
    "                       delta = 0.1, # depreciation rate\n",
    "                       alpha = 0.3, #capital's share of income\n",
    "                       z = 2.0, # productivity parameter\n",
    "                       k = 1.0 # current per capita captital stock\n",
    "                    ):\n",
    "                 self.n = n;\n",
    "                 self.s = s;\n",
    "                 self.z = z;\n",
    "                 self.alpha = alpha;\n",
    "                 self.delta = delta;\n",
    "                 \n",
    "                 self.k = k;\n",
    "                 \n",
    "    def growth_formula(self):\n",
    "                 n = self.n;\n",
    "                 z = self.z;\n",
    "                 s = self.s;\n",
    "                 alpha = self.alpha;\n",
    "                 delta = self.delta;\n",
    "                # the right_hand_side of the equation\n",
    "                 next_capital_stock = (s*z*(self.k ** alpha) + (1-delta) * self.k)/(1+n);\n",
    "                 return next_capital_stock;\n",
    "                 \n",
    "                \n",
    "    def update(self):\n",
    "                 self.k = self.growth_formula();\n",
    "                 ## no return here ,just an inner update\n",
    "    def steady_state(self):\n",
    "                 n = self.n;\n",
    "                 z = self.z;\n",
    "                 s = self.s;\n",
    "                 alpha = self.alpha;\n",
    "                 delta = self.delta;\n",
    "                 ss = ((s*z) / (n+delta)) ** (1/(1-alpha));\n",
    "                 return ss;\n",
    "    def generate_sequence_of_CapitalStock(self, length_of_time):\n",
    "                 # create an empty list\n",
    "                 sequence = [];\n",
    "                 for i in range(length_of_time):\n",
    "                     sequence.append(self.k);\n",
    "                     self.update();\n",
    "                 return sequence;\n",
    "                    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "        this.context.mozBackingStorePixelRatio ||\n",
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       "\n",
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       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
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       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
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       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
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       "    this.message = status_bar;\n",
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       "\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",
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       "\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",
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       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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 / fig.ratio,\n",
       "        fig.canvas.height / fig.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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "                img\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 * this.ratio;\n",
       "    var y = canvas_pos.y * this.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.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"pgf\", \"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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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 / this.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 (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\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": {
      "text/html": [
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width=\"648\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "eco_body1 = Solow(k = 2.0);\n",
    "eco_body2 = Solow();\n",
    "\n",
    "# sixty unit time_length\n",
    "T = 60;\n",
    "\n",
    "figure_size = (9,6);\n",
    "fig, ax = plt.subplots(figsize = figure_size);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# x = np.linspace(0, 2, 100)\n",
    "# # Note that even in the OO-style, we use `.pyplot.figure` to create the figure.\n",
    "# fig, ax = plt.subplots() # Create a figure and an axes.\n",
    "# ax.plot(x, x, label='linear') # Plot some data on the axes.\n",
    "# ax.plot(x, x**2, label='quadratic') # Plot more data on the axes...\n",
    "# ax.plot(x, x**3, label='cubic') # ... and some more.\n",
    "# ax.set_xlabel('x label') # Add an x-label to the axes.\n",
    "# ax.set_ylabel('y label') # Add a y-label to the axes.\n",
    "# ax.set_title(\"Simple Plot\") # Add a title to the axes.\n",
    "# ax.legend() # Add a legend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.5843115041821845"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## steady-state\n",
    "ss = eco_body1.steady_state();\n",
    "ss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax.plot([ss]*T, 'k-', label = 'steady_state');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "for eco_body in eco_body1,eco_body2:\n",
    "    label = f'capital series —— initial state is {eco_body.k}'\n",
    "    ax.plot(eco_body.generate_sequence_of_CapitalStock(T), 'o-',lw = 2,alpha = 0.6, label = label);\n",
    "    \n",
    "ax.set_xlabel('$t$', fontsize = 15);\n",
    "ax.set_ylabel(\"$k_t$\", fontsize = 15);\n",
    "\n",
    "ax.legend();\n",
    "\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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