regression.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at some examples of regression calculations in Python.  I haven't found any direct equivalent to `regress` from Matlab's statistical toolbox.  Similar functionality is available in the Python [statsmodels](http://statsmodels.org) package.  I will give an example of its use below, but we will also see how to calculate the things we need without it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import scipy.stats as ss\n",
    "from scipy import linalg  # numpy linalg plus extras\n",
    "import statsmodels.api as sm\n",
    "\n",
    "from pycurrents.system import Bunch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple regression, straight line"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we will illustrate a single straight-line fit using random data to make partially correlated variables.  We will use a function from scipy.stats, `linregress`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
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       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
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       "    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",
       "            /* 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 * 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.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",
       "\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\", \"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",
       "    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": {
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       "<img 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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ny = 100 \n",
    "b_true = 0.5\n",
    "x1 = np.random.randn(ny) # signal\n",
    "epsilon = np.random.randn(ny) # noise\n",
    "y = b_true * x1 + epsilon\n",
    "\n",
    "fig,(ax0, ax1) = plt.subplots(2)\n",
    "t=np.linspace(0,10,ny)\n",
    "ax0.plot(t,y,t,x1)\n",
    "ax1.plot(y,x1,'o')\n",
    "line=np.linspace(y.min(),y.max(),3)\n",
    "ax1.plot(line,line,'k:')\n",
    "ax1.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "slope: 0.496688691505828  intercept: -0.1819956681573225  r: 0.4729844426585307  p: 6.721494787536857e-07  stderr: 0.09346202273324902\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f9dba9baf10>]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "slope, intercept, r, p, stderr = ss.linregress(x1, y)\n",
    "print(\"slope:\", slope, \" intercept:\", intercept, \n",
    "      \" r:\", r, \" p:\", p, \" stderr:\", stderr)\n",
    "ax1.plot(0,intercept,'r*')\n",
    "liney=line*slope+intercept;\n",
    "ax1.plot(line,liney,'r-')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.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 * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.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",
       "    this.resizeObserverInstance.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'] / 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",
       "            /* 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 * 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.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",
       "\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\", \"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",
       "    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": [
       "<img 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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'slope')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise: put this in a loop and collect the statistical distribution of the slope from many realizations.\n",
    "nreal=1000\n",
    "store_slope=[]\n",
    "# np.vstack?\n",
    "for r in range(nreal):\n",
    "    ny = 100 \n",
    "    b_true = 0.5\n",
    "    x1 = np.random.randn(ny) # signal\n",
    "    epsilon = np.random.randn(ny) # noise\n",
    "    y = b_true * x1 + epsilon\n",
    "    slope, intercept, r, p, stderr = ss.linregress(x1, y)\n",
    "    store_slope=np.hstack((store_slope,slope))\n",
    "fig,ax = plt.subplots()\n",
    "ax.hist(store_slope,20,density=True)\n",
    "ax.set_ylabel('PDF')\n",
    "ax.set_xlabel('slope')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The slope from the fit is reasonably close to its \"true\" value, `b_true`; and the intercept is near zero.\n",
    "\n",
    "Exercise: put this in a loop and collect the statistical distribution of the slope from many realizations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Linear regression with just a mean and a slope is so simple that we can easily do it in a vectorized way, so that we can do it efficiently for large numbers of series at once.  Let's make a function to do it for something like regressing SST at many locations on the SOI.  We will illustrate again with fake data.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is the function.  Note that it is designed to work with y being 1-D or higher, and with any location of the time axis.  (We don't need scipy.stats for this, just numpy.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "def regress_many(x, y, axis=0):\n",
    "    \"\"\"\n",
    "    Regress y on x.\n",
    "\n",
    "    x is a 1-D array or masked array with n points.\n",
    "    y is at least 1-D, with n points along the dimension\n",
    "    specified by axis.\n",
    "\n",
    "    Returns (b1, r), where b1 is the slope and r is the correlation\n",
    "    coefficient.\n",
    "    \"\"\"\n",
    "    # Allow masked arrays and ordinary arrays, and remove the means.\n",
    "    x = np.asanyarray(x)\n",
    "    x -= x.mean()\n",
    "    y = np.asanyarray(y)\n",
    "    y -= y.mean(axis=axis, keepdims=True)\n",
    "    \n",
    "    # Black magic to accomodate any dimensionality of y:\n",
    "    bc = tuple([slice(None) if i == axis else np.newaxis \n",
    "               for i in range(y.ndim)])\n",
    "    \n",
    "    # Note that we need only sums of squares and products.\n",
    "    Sxx = (x**2).sum()\n",
    "    Syy = (y**2).sum(axis=axis)\n",
    "    Sxy = (x[bc] * y).sum(axis=axis)\n",
    "    \n",
    "    r = Sxy / np.ma.sqrt(Sxx * Syy)\n",
    "    b1 = Sxy / Sxx\n",
    "    \n",
    "    return b1, r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's test the new function. First, verify that it gives the same result as `linregress` on the simple 1-D example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.465326007261699\n",
      "0.38232455163579815\n"
     ]
    }
   ],
   "source": [
    "b1, r = regress_many(x1, y)\n",
    "print(b1)\n",
    "print(r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, make some 2-D data, simulating a common calculation in oceanography and meteorology: looking at the correlation between a scalar time series, such as the Southern Oscillation Index, and a time series of maps, such as a satellite-based estimate of sea-surface temperature.  In this simulation we are not trying to make anything look like the SOI or SST, but we are making simple arrays with the corresponding dimensions, so we could later plug in an actual SOI time series and set of SST maps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fake data for testing\n",
    "npts = 100\n",
    "nlon = 121\n",
    "nlat = 81\n",
    "lon = np.linspace(140, 260, nlon)\n",
    "lat = np.linspace(-40, 40, nlat)\n",
    "\n",
    "# Very unrealistic: uncorrelated random points\n",
    "SOI = np.random.randn(npts)\n",
    "\n",
    "# Very unrealistic: partial correlation, as in the earlier example\n",
    "# Here is the noise part:\n",
    "SST = np.random.randn(npts, nlon, nlat)\n",
    "# Now let's give the correlated part some spatial structure:\n",
    "amp = 1 + (lon[:, np.newaxis] - 140) / 120  + lat / 40\n",
    "SST += amp * SOI[:, np.newaxis, np.newaxis]\n",
    "# The correlation now ramps up from SW to NE.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(121, 81) (121, 81)\n",
      "-0.22413311078407452 1.497848928098117 3.2067993558065755\n",
      "-0.20348749104172814 0.7583132566086026 0.9592735133996557\n"
     ]
    }
   ],
   "source": [
    "b1, r = regress_many(SOI, SST)\n",
    "\n",
    "print(b1.shape, r.shape)\n",
    "print(b1.min(), b1.mean(), b1.max())\n",
    "print(r.min(), r.mean(), r.max())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we will use filled contours to plot the slope and the correlation coefficient."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "\n",
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       "    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",
       "            /* 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 * 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.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",
       "\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\", \"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",
       "    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=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'correlation coefficient')"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=2, sharex=True)\n",
    "ax = axs[0]\n",
    "slopelevs = np.arange(0, 3.01, 0.2)\n",
    "# Notice that because the arrays here have dimensions nlon, nlat,\n",
    "# we have to transpose them so that they will be contoured with\n",
    "# the right orientation.\n",
    "cmap1 = plt.get_cmap('Blues')\n",
    "cs1 = ax.contourf(lon, lat, b1.T, levels=slopelevs, \n",
    "                  cmap=cmap1, extend='both')\n",
    "cbar1 = fig.colorbar(cs1, ax=ax)\n",
    "ax.set_title('slope')\n",
    "\n",
    "ax = axs[1]\n",
    "rlevs = np.arange(0, 1.01, 0.05)\n",
    "cmap2 = plt.get_cmap('Reds')\n",
    "cs2 = ax.contourf(lon, lat, r.T, levels=rlevs, cmap=cmap2,\n",
    "                   extend='min')\n",
    "cbar2 = fig.colorbar(cs2, ax=ax)\n",
    "ax.set_title('correlation coefficient')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.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 * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.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",
       "    this.resizeObserverInstance.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'] / 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",
       "            /* 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 * 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.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",
       "\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\", \"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",
       "    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": {
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       "<img 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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f9db9062dc0>,\n",
       " <matplotlib.lines.Line2D at 0x7f9db9062df0>]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# KD plot the data at one location as a timeseries \n",
    "fig,ax = plt.subplots()\n",
    "t=np.linspace(0,1,npts)\n",
    "ax.plot(t,SST[:,1,1],t,SOI)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What happens if we let the \"SST\" be a uniform multiple of \"SOI\", but with the added noise component ramped up from SW to NE?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.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 * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.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",
       "    this.resizeObserverInstance.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'] / 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",
       "            /* 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 * 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.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",
       "\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\", \"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",
       "    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": {
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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'correlation coefficient')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SST = SOI[:, np.newaxis, np.newaxis] # uniform multiple\n",
    "SST = SST + 2 * amp * np.random.randn(npts, nlon, nlat) # plus noise ramp\n",
    "\n",
    "b1, r = regress_many(SOI, SST)\n",
    "\n",
    "fig, axs = plt.subplots(nrows=2, sharex=True)\n",
    "ax = axs[0]\n",
    "slopelevs = np.arange(0, 3.01, 0.2)\n",
    "\n",
    "cmap1 = plt.get_cmap('Blues')\n",
    "cs1 = ax.contourf(lon, lat, b1.T, levels=slopelevs, \n",
    "                  cmap=cmap1, extend='both')\n",
    "cbar1 = fig.colorbar(cs1, ax=ax)\n",
    "ax.set_title('slope')\n",
    "\n",
    "ax = axs[1]\n",
    "rlevs = np.arange(0, 1.01, 0.05)\n",
    "cmap2 = plt.get_cmap('Reds')\n",
    "cs2 = ax.contourf(lon, lat, r.T, levels=rlevs, cmap=cmap2,\n",
    "                   extend='min')\n",
    "cbar2 = fig.colorbar(cs2, ax=ax)\n",
    "ax.set_title('correlation coefficient')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multiple linear regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The basic MLR calculation is easily done, as will be illustrated here.  The following model could be considered as a starting point for fitting a diurnal cycle, or an annual cycle, for example.\n",
    "\n",
    "We will first make a fake data set with a deterministic part and a random part.  The deterministic part consists of a mean and a sinusoid (which has a sine part and a cosine part).  We could add a zero-mean trend; that is left as an exercise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.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 * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.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",
       "    this.resizeObserverInstance.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'] / 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",
       "            /* 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 * 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.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",
       "\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\", \"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",
       "    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": {
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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'fake data with sinusoid and noise')"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ny = 100\n",
    "# frequency in cycles per time unit:\n",
    "freq = 1\n",
    "\n",
    "t = np.linspace(0, 2.4, ny, endpoint=False)\n",
    "\n",
    "xc = np.cos(2 * np.pi * freq * t)\n",
    "xs = np.sin(2 * np.pi * freq * t)\n",
    "\n",
    "ys = 0.5      # amp of sine component\n",
    "yc = 1.2      # amp of cosine component\n",
    "y0 = 0.2      # mean\n",
    "yrand = 1.5   # amp of Gaussian noise\n",
    "\n",
    "np.random.seed(0)  # make the \"random\" numbers repeatable\n",
    "y = y0 + yc * xc + ys * xs + yrand * np.random.randn(ny)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(t, y, '.')\n",
    "ax.set_title('fake data with sinusoid and noise')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now make the model.  Note that we know the frequency of the sinusoid; only its amplitude and phase, or equivalently its cosine and sine coefficients, need to be determined by the fit.  If we did not know the frequency, we could not use linear regression at all; it would be a fundamentally nonlinear problem.  (Also, note that it is linear in the sine and cosine coefficients, but *not* in amplitude and phase; that's why we solve for the former, from which we can calculate the latter.)\n",
    "\n",
    "Each column in the $X$ array is the time series of one component of the model.  Here we have 3 components; the first one is all ones, so its coefficient will be the mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.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 * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.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",
       "    this.resizeObserverInstance.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'] / 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",
       "            /* 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 * 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.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",
       "\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\", \"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",
       "    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": {
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       "<img 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\" 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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'components of the model')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nparams = 3  # parameters in the model\n",
    "xmod = np.ones((ny, nparams), dtype=float)\n",
    "xmod[:,1] = xc\n",
    "xmod[:,2] = xs\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(t, xmod)  # plots columns of xmod versus t\n",
    "ax.set_ylim(-1.2, 1.2)\n",
    "ax.legend(['mean', 'cosine', 'sine'])\n",
    "ax.set_title('components of the model')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we find the least-squares solution of $Y = X b $ , the fit based on that solution, and the residuals from the fit:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b is:  [0.25006954 1.40301451 0.756066  ]\n"
     ]
    },
    {
     "data": {
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       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
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       "    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",
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       "            canvas_div.style.width = width + 'px';\n",
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       "};\n",
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       "    toolbar.classList = 'mpl-toolbar';\n",
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       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
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       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
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       "\n",
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       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            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",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
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       "        button.appendChild(icon_img);\n",
       "\n",
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       "\n",
       "    for (var ind in mpl.extensions) {\n",
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       "        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",
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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",
       "            /* 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 * 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.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",
       "\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\", \"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",
       "    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": [
       "<img 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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'residuals')"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = linalg.lstsq(xmod, y)[0] # ignore other outputs\n",
    "yfit = np.dot(xmod, b)\n",
    "# yfit = xmod @ b  # New matrix-multiplication operator...\n",
    "yresid = y - yfit\n",
    "\n",
    "print(\"b is: \", b)\n",
    "\n",
    "fig, axs = plt.subplots(nrows=2, sharex=True)\n",
    "axs[0].plot(t, y, 'b.', t, yfit, 'g-')\n",
    "axs[0].legend(['y', 'yfit'], loc='best')\n",
    "axs[0].set_title('fit')\n",
    "\n",
    "axs[1].plot(t, yresid, 'r.')\n",
    "axs[1].set_title('residuals')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also calculate the uncertainties in the parameters.  This will depend on the variance-covariance matrix of the model.  In this context, \"variance\" and \"covariance\" is really referring just to sums of products; the means are not removed, and there is no normalization by the number of points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[100.           4.79499138  11.67978251]\n",
      " [  4.79499138  48.60799289   1.37462363]\n",
      " [ 11.67978251   1.37462363  51.39200711]]\n"
     ]
    }
   ],
   "source": [
    "# dot() does matrix multiplication\n",
    "# vcv_mod = np.dot(xmod.T, xmod)\n",
    "vcv_mod = xmod.T @ xmod\n",
    "print(vcv_mod)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that the matrix is symmetric, and that the off-diagonal elements are substantial; this means that the columns in our model are not independent.  This is typically the case, and doesn't hurt, so long as the correlations are fairly small.  When columns are highly correlated, however, it means that the coefficients will be poorly determined and highly uncertain.\n",
    "\n",
    "The variance-covariance matrix for the estimated parameters is \n",
    "$$V(b) = (X'X)^{-1}\\sigma^2$$\n",
    "where $\\sigma^2$ is the variance of $\\epsilon$, *assuming* the $\\epsilon$ distribution is *uniform* and **independent**; that is, the variance-covariance matrix of $\\epsilon$ is $\\sigma^2$ on the diagonal and zero off the diagonal.  We estimate $\\sigma^2$ from the residuals, compensating for the 3 DOF removed by this model with its 3 components.  The numpy `var()` function has a kwarg for this.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimated variance of epsilon: 2.3010524259519842\n",
      "\n",
      "VCV matrix for the coefficients, b:\n",
      "[[ 0.02373887 -0.00219083 -0.0053365 ]\n",
      " [-0.00219083  0.047577   -0.00077467]\n",
      " [-0.0053365  -0.00077467  0.04600806]]\n",
      "\n",
      "Estimated std dev of epsilon:\n",
      "1.5169220236887537\n",
      "versus true value:\n",
      "1.5\n"
     ]
    }
   ],
   "source": [
    "epsvar = np.var(yresid, ddof=nparams)\n",
    "bvar = linalg.inv(vcv_mod) * epsvar\n",
    "print('Estimated variance of epsilon:', epsvar)\n",
    "print('\\nVCV matrix for the coefficients, b:')\n",
    "print(bvar)\n",
    "print('\\nEstimated std dev of epsilon:')\n",
    "print(np.sqrt(epsvar))\n",
    "print('versus true value:')\n",
    "print(yrand)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our estimated variance of $\\epsilon$ is very close to the value we used to generate it.\n",
    "\n",
    "The standard deviations of the parameter estimates are just the square roots of the diagonal entries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.15407422 0.21812152 0.21449489]\n"
     ]
    }
   ],
   "source": [
    "bstd = np.sqrt(np.diag(bvar))\n",
    "print(bstd)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The off-diagonal elements of bvar show how errors in one parameter are coupled with errors in another.  For example, the correlation coefficients between the sine and cosine parameters, and the sine and mean, are:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.016557818231182554\n",
      "-0.1614764604308733\n"
     ]
    }
   ],
   "source": [
    "print(bvar[1, 2] / (bstd[1] * bstd[2]))\n",
    "print(bvar[0, 2] / (bstd[0] * bstd[2]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that the sine and cosine components are nearly orthogonal, but a positive error in the sine coefficient will tend to occur together with a negative error in the mean.\n",
    "\n",
    "I think that at this point, treating the standard deviations of the parameters as Gaussian with the standard deviation estimated above is good enough; then you can just use two standard deviations, or whatever you like.  But technically we should use the t distribution, so let's try it. (Recall that the t distribution is similar to the Gaussian, but it has heavier tails to take into account the fact that don't know the true standard deviation, but must instead estimate it from the data.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.05572514  0.97010368  0.33035302]\n",
      "[0.25006954 1.40301451 0.756066  ]\n",
      "[0.55586422 1.83592535 1.18177898]\n"
     ]
    }
   ],
   "source": [
    "b_t = ss.t(ny - nparams, loc=b, scale=bstd)\n",
    "b_lo = b_t.ppf(0.025)\n",
    "b_hi = b_t.ppf(0.975)\n",
    "print(b_lo)\n",
    "print(b)\n",
    "print(b_hi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Doing this manually was not so hard, but let's try out a fancy function from statsmodels, a higher-powered statistical package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                      y   R-squared:                       0.360\n",
      "Model:                            OLS   Adj. R-squared:                  0.347\n",
      "Method:                 Least Squares   F-statistic:                     27.28\n",
      "Date:                Mon, 28 Dec 2020   Prob (F-statistic):           3.98e-10\n",
      "Time:                        17:14:57   Log-Likelihood:                -182.04\n",
      "No. Observations:                 100   AIC:                             370.1\n",
      "Df Residuals:                      97   BIC:                             377.9\n",
      "Df Model:                           2                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "const          0.2501      0.154      1.623      0.108      -0.056       0.556\n",
      "x1             1.4030      0.218      6.432      0.000       0.970       1.836\n",
      "x2             0.7561      0.214      3.525      0.001       0.330       1.182\n",
      "==============================================================================\n",
      "Omnibus:                        0.503   Durbin-Watson:                   1.872\n",
      "Prob(Omnibus):                  0.777   Jarque-Bera (JB):                0.633\n",
      "Skew:                           0.010   Prob(JB):                        0.729\n",
      "Kurtosis:                       2.611   Cond. No.                         1.47\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "model = sm.OLS(y, xmod)\n",
    "results = model.fit()\n",
    "print(results.summary())  # makes a formatted table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's more than we wanted to know!  Let's isolate the bits we care about.  The documentation is sparse, so we have to do a little exploration.  Let's see what's available."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['HC0_se', 'HC1_se', 'HC2_se', 'HC3_se', '_HCCM', '__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', '_abat_diagonal', '_cache', '_data_attr', '_data_in_cache', '_get_robustcov_results', '_is_nested', '_use_t', '_wexog_singular_values', 'aic', 'bic', 'bse', 'centered_tss', 'compare_f_test', 'compare_lm_test', 'compare_lr_test', 'condition_number', 'conf_int', 'conf_int_el', 'cov_HC0', 'cov_HC1', 'cov_HC2', 'cov_HC3', 'cov_kwds', 'cov_params', 'cov_type', 'df_model', 'df_resid', 'diagn', 'eigenvals', 'el_test', 'ess', 'f_pvalue', 'f_test', 'fittedvalues', 'fvalue', 'get_influence', 'get_prediction', 'get_robustcov_results', 'initialize', 'k_constant', 'llf', 'load', 'model', 'mse_model', 'mse_resid', 'mse_total', 'nobs', 'normalized_cov_params', 'outlier_test', 'params', 'predict', 'pvalues', 'remove_data', 'resid', 'resid_pearson', 'rsquared', 'rsquared_adj', 'save', 'scale', 'ssr', 'summary', 'summary2', 't_test', 't_test_pairwise', 'tvalues', 'uncentered_tss', 'use_t', 'wald_test', 'wald_test_terms', 'wresid']\n"
     ]
    }
   ],
   "source": [
    "print(dir(results))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It turns out we need an attribute, `params`, and a method, `conf_int`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters (b):\n",
      "[0.25006954 1.40301451 0.756066  ]\n",
      "\n",
      "Confidence intervals:\n",
      "[[-0.05572514  0.97010368  0.33035302]\n",
      " [ 0.55586422  1.83592535  1.18177898]]\n"
     ]
    }
   ],
   "source": [
    "print('Parameters (b):')\n",
    "print(results.params)\n",
    "print('\\nConfidence intervals:')\n",
    "print(results.conf_int(alpha=0.05).T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A function for MLR"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's make a function that efficiently calculates the MLR parameters and their confidence intervals for a time series as a function of depth--that is, for a 2-D array.  The key to doing this efficiently is noticing that only the last steps involve the depth dimension.  We won't need to use a loop at all; everything will be vectorized.  We will use functions to calculate $(X'X)^{-1}$, which we need for the confidence limits, and $(X'X)^{-1}X'$, which is known as the pseudoinverse of $X$.  If our time series, $Y$, is arranged with ntimes rows and ndepths columns, then matrix-multiplying this times the pseudoinverse gives us the parameters, $b$, with one column for each depth."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mlr(y, x, alpha=0.05):\n",
    "    \"\"\"\n",
    "    Multiple linear regression.\n",
    "    \n",
    "        y: 1-D or 2-D array, independent variable.\n",
    "            (ntimes,) or (ntimes, nrealizations)\n",
    "        x: 2-D array, model; (ntimes, nparams)\n",
    "    \n",
    "    returns a Bunch with attributes:\n",
    "    \n",
    "        y: the input dependent variable\n",
    "        x: the input model\n",
    "        alpha: the input confidence level\n",
    "        b: (nparams,) or (nparams, nrealizations)\n",
    "        b_std: standard error of b\n",
    "        b_lo: lower confidence limits\n",
    "        b_hi: upper confidence limits\n",
    "        fit: same shape as y\n",
    "        residuals: same shape as y\n",
    "        \n",
    "    The input arrays must be ndarrays with no nan or inf values; \n",
    "    masked arrays are not supported.\n",
    "\n",
    "    \"\"\"\n",
    "    ntimes, nparams = x.shape\n",
    "    if y.shape[0] != ntimes:\n",
    "        raise ValueError(\"Shape mismatch: x is %s, y is %s\" %\n",
    "                         x.shape, y.shape)\n",
    "    pinv = linalg.pinv2(x)\n",
    "    b = np.dot(pinv, y)\n",
    "    fit = np.dot(x, b)\n",
    "    residuals = y - fit\n",
    "    \n",
    "    eps_std = np.std(residuals, axis=0, ddof=nparams, keepdims=True)\n",
    "    inv_vcv = linalg.inv(np.dot(x.T, x))\n",
    "    b_std = (np.sqrt(np.diag(inv_vcv)) * eps_std.T).T\n",
    "    b_t = ss.t(ntimes - nparams, loc=b, scale=b_std)\n",
    "    b_lo = b_t.ppf(alpha/2)\n",
    "    b_hi = b_t.ppf(1 - alpha/2)\n",
    "    out = Bunch(x=x, y=y, b=b, b_std=b_std, b_lo=b_lo,\n",
    "                b_hi=b_hi, fit=fit, residuals=residuals)\n",
    "    return out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test it first with the same time series we used above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.05572514  0.97010368  0.33035302]\n",
      "[0.25006954 1.40301451 0.756066  ]\n",
      "[0.55586422 1.83592535 1.18177898]\n"
     ]
    }
   ],
   "source": [
    "test1 = mlr(y, xmod)\n",
    "print(test1.b_lo)\n",
    "print(test1.b)\n",
    "print(test1.b_hi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now try a minimal test with a 2-D array by making two columns of y:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.25006954 0.25006954]\n",
      " [1.40301451 1.40301451]\n",
      " [0.756066   0.756066  ]]\n",
      "shapes:\n",
      "           b :       (3, 2)\n",
      "        b_hi :       (3, 2)\n",
      "        b_lo :       (3, 2)\n",
      "       b_std :       (3, 2)\n",
      "         fit :     (100, 2)\n",
      "   residuals :     (100, 2)\n",
      "           x :     (100, 3)\n",
      "           y :     (100, 2)\n"
     ]
    }
   ],
   "source": [
    "y2 = np.column_stack((y, y))\n",
    "test2 = mlr(y2, xmod)\n",
    "print(test2.b)\n",
    "attributes = sorted(list(test2.keys()))\n",
    "print(\"shapes:\")\n",
    "for a in attributes:\n",
    "    print(\"%12s : %12s\" % (a, test2[a].shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Last, test with a larger array.  To keep things simple, only the random component will vary from one column to the next.  This also lets us do an empirical test of the estimated parameter error bars."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_test_array(ntimes=100, ncolumns=1000,\n",
    "                    y0=0.2, yc=1.2, ys=0.5, yrand=1,\n",
    "                    seed=0):\n",
    "\n",
    "    # frequency in cycles per time unit:\n",
    "    freq = 1\n",
    "\n",
    "    t = np.linspace(0, 10, ntimes)\n",
    "\n",
    "    xc = np.cos(2 * np.pi * freq * t)\n",
    "    xs = np.sin(2 * np.pi * freq * t)\n",
    "\n",
    "    xmod = np.ones((ntimes, 3), float)\n",
    "    xmod[:, 1] = xc\n",
    "    xmod[:, 2] = xs\n",
    "    \n",
    "    np.random.seed(seed)  # make the \"random\" numbers repeatable\n",
    "    y = y0 + yc * xc + ys * xs\n",
    "    y = y[:, np.newaxis] + yrand * np.random.randn(ntimes, ncolumns)\n",
    "    return y, xmod\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "yy, xmod = make_test_array(yrand=4, ntimes=10000, seed=20)\n",
    "bigtest = mlr(yy, xmod)\n",
    "print(bigtest.b.mean(axis=-1))\n",
    "print(bigtest.b.std(axis=-1))\n",
    "print(bigtest.b_std.mean(axis=-1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That looks fine.  Notice that the mean of the estimated standard deviations (third line) is close to the actual standard deviation over the ensemble of trials (second line)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots()\n",
    "counts, edges, patches = ax.hist(bigtest.b[0], bins=20, density=True)\n",
    "ax.set_xlabel('constant term in the MLR')\n",
    "ax.set_ylabel('PDF')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mlr function above has one limitation: it can't handle missing data.  If your data set has missing points--that is, for a given column in $Y$, there are times with nan or a masked value--then the corresponding rows in the $X$ array must be deleted before calculating the inverse and the pseudo-inverse.  There are two ways of dealing with this: either interpolate to replace the bad values in $Y$, after which the mlr function can be used on the whole array, or use a loop to cycle through the columns of $Y$, using indexing to remove the bad points and the corresponding rows of $X$, and applying the mlr function with each 1-dimensional cleaned $Y$ and its matching $X$. The results of these two methods will be similar if the data gaps are small and not too numerous, but interpolation will bias the error estimates low.  If large chunks of data are missing, one should use the slower loop strategy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mlr_gappy(y, x, alpha=0.05):\n",
    "    \"\"\"\n",
    "    MLR; handles y as a masked array or with nans.\n",
    "    x must still be an ndarray with all valid values.\n",
    "    See mlr() docstring for details.\n",
    "    \"\"\"\n",
    "    ma_input = np.ma.isMA(y)\n",
    "    ym = np.ma.masked_invalid(y)\n",
    "    # If there are no bad values call mlr directly,\n",
    "    # ensuring y is an ndarray and not a masked array.\n",
    "    if not np.ma.is_masked(ym):\n",
    "        return mlr(ym.filled(), x, alpha=alpha)\n",
    "    \n",
    "    if y.ndim == 1:\n",
    "        igood = ~ym.mask  # True where not masked.\n",
    "        result = mlr(ym[igood].filled(), x[igood], alpha=alpha)\n",
    "        \n",
    "        resid = ym.copy()\n",
    "        resid[igood] = result.residuals\n",
    "        result.residuals = resid\n",
    "        \n",
    "        fit = ym.copy()\n",
    "        fit[igood] = result.fit\n",
    "        result.fit = fit\n",
    "        \n",
    "        if not ma_input:\n",
    "            for key in ('fit', 'residuals'):\n",
    "                result[key] = result[key].filled(np.nan)\n",
    "        \n",
    "        return result\n",
    "\n",
    "    # 2-D case, with time as the first axis\n",
    "    nseries = y.shape[1]\n",
    "    ntimes, nparams = x.shape\n",
    "\n",
    "    bshape = (nparams, nseries)\n",
    "    b = np.empty(bshape)\n",
    "    b_lo = np.empty(bshape)\n",
    "    b_hi = np.empty(bshape)\n",
    "    b_std = np.empty(bshape)\n",
    "    fit = np.nan + np.zeros(y.shape)\n",
    "    residuals = np.nan + np.zeros(y.shape)\n",
    "    \n",
    "    out = Bunch(b=b, b_lo=b_lo, b_hi=b_hi, b_std=b_std, \n",
    "                fit=fit, residuals=residuals)\n",
    "    \n",
    "    for i in range(nseries):\n",
    "        yi = ym[:, i]\n",
    "        igood = ~yi.mask\n",
    "        result = mlr(yi[igood].filled(), x[igood])\n",
    "        for key in ('b', 'b_lo', 'b_hi', 'b_std'):\n",
    "            out[key][:, i] = result[key]\n",
    "        for key in ('fit', 'residuals'):\n",
    "            out[key][igood, i] = result[key]\n",
    "    \n",
    "    if ma_input:\n",
    "        for key in ('fit', 'residuals'):\n",
    "            out[key] = np.ma.masked_invalid(out[key])\n",
    "            \n",
    "    out.x = x\n",
    "    out.y = y\n",
    "    \n",
    "    return out\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test with gappy data.  Because of its need to loop, this function will be slow, so don't try it with a large number of input columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "yy, xmod = make_test_array()\n",
    "# make a Boolean array with 1/3 of its values\n",
    "#   True, randomly distributed.\n",
    "ibad = np.random.randint(3, size=yy.shape) > 1\n",
    "yyb = yy.copy()\n",
    "yyb[ibad] = np.nan\n",
    "bigtest = mlr_gappy(yyb, xmod)\n",
    "print('With gaps:')\n",
    "print(bigtest.b.mean(axis=-1))\n",
    "print(bigtest.b.std(axis=-1))\n",
    "print(bigtest.b_std.mean(axis=-1))\n",
    "\n",
    "bigtestng = mlr(yy, xmod)\n",
    "print('\\nWithout gaps:')\n",
    "print(bigtestng.b.mean(axis=-1))\n",
    "print(bigtestng.b.std(axis=-1))\n",
    "print(bigtestng.b_std.mean(axis=-1))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on this very minimal testing, it appears the function works.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
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