figure-cv.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Figures: cross-validation results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "import numpy as np\n",
    "import pylab as plt\n",
    "import seaborn as sns\n",
    "import pickle\n",
    "import matplotlib\n",
    "\n",
    "import sparseRRR\n",
    "\n",
    "def sns_styleset():\n",
    "    sns.set_context('paper')\n",
    "    sns.set_style('ticks')\n",
    "    matplotlib.rcParams['axes.linewidth']    = .5\n",
    "    matplotlib.rcParams['xtick.major.width'] = .5\n",
    "    matplotlib.rcParams['ytick.major.width'] = .5\n",
    "    matplotlib.rcParams['xtick.major.size'] = 2\n",
    "    matplotlib.rcParams['ytick.major.size'] = 2\n",
    "    matplotlib.rcParams['xtick.minor.size'] = 1\n",
    "    matplotlib.rcParams['ytick.minor.size'] = 1\n",
    "    matplotlib.rcParams['font.size']       = 6\n",
    "    matplotlib.rcParams['axes.titlesize']  = 7\n",
    "    matplotlib.rcParams['axes.labelsize']  = 6\n",
    "    matplotlib.rcParams['legend.fontsize'] = 6\n",
    "    matplotlib.rcParams['xtick.labelsize'] = 6\n",
    "    matplotlib.rcParams['ytick.labelsize'] = 6\n",
    "    matplotlib.rcParams['figure.dpi'] = 120     # only affects the notebook\n",
    "\n",
    "sns_styleset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "scala2020cv   = pickle.load(open('pickles/cvresults-scala2020.pickle', 'rb'))\n",
    "scala2019cv   = pickle.load(open('pickles/cvresults-scala2019.pickle', 'rb'))\n",
    "cadwell2016cv = pickle.load(open('pickles/cvresults-cadwell2016.pickle', 'rb'))\n",
    "gouwens2020cv = pickle.load(open('pickles/cvresults-gouwens2020.pickle', 'rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
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       "\n",
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       "            continue;\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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       "\n",
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       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
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       "\n",
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       "\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",
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       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
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       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
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       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
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       "    x0 = Math.floor(x0) + 0.5;\n",
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       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / mpl.ratio,\n",
       "        fig.canvas.height / mpl.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / mpl.ratio;\n",
       "    fig.root.removeEventListener('remove', this._remove_fig_handler);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / mpl.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function () {\n",
       "    this.close_ws(this, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "    el.addEventListener('remove', this._remove_fig_handler);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "fig = plt.figure(figsize=(8, 4))\n",
    "\n",
    "ylims = [.25, .16, .5, .3]\n",
    "highlight = [1, 1, 3, 3]\n",
    "alphas = [.25, .5, .75, 1]\n",
    "alphaused = [.5, .5, 1, 1]\n",
    "titles = ['Cadwell et al. 2016', 'Scala et al. 2019', 'Scala et al. 2020', 'Gouwens et al. 2020']\n",
    "\n",
    "for datasetnum, cvresults in enumerate([cadwell2016cv, scala2019cv, scala2020cv, gouwens2020cv]):\n",
    "\n",
    "    plt.subplot(2,4,datasetnum+1)\n",
    "    colA = np.array([76, 114, 176]) / 256\n",
    "    colB = np.array([196, 78, 82])  / 256\n",
    "    for alphaid in range(4):\n",
    "        # suppressing \"mean of empty slice\" warnings\n",
    "        with warnings.catch_warnings():\n",
    "            warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n",
    "            n = np.nanmean(cvresults[0][2], axis=(0,1))\n",
    "            c = np.nanmean(cvresults[0][0], axis=(0,1))\n",
    "            cr = np.nanmean(cvresults[0][1], axis=(0,1))\n",
    "        \n",
    "        if alphaid == highlight[datasetnum]:\n",
    "            lw = 1.25\n",
    "        else:\n",
    "            lw = .75\n",
    "        col = (colA * alphaid/3 + colB * (3-alphaid)/3)\n",
    "        plt.plot(n[:,alphaid], cr[:,alphaid], linewidth=lw, color=col, \n",
    "                 label=r'$\\alpha={:.2f}$'.format(alphas[alphaid]))\n",
    "        plt.plot(n[:,alphaid], c[:,alphaid], '--', linewidth=lw, color=col)\n",
    "\n",
    "    if datasetnum==0:\n",
    "        plt.legend()\n",
    "        plt.text(4, .18, 'Relaxed', fontsize=6)\n",
    "        plt.text(17, .03, 'Naive', fontsize=6)\n",
    "        plt.ylabel(r'Cross-validated $R^2$')\n",
    "    plt.xscale('log')\n",
    "    plt.xlabel('Number of genes')#, labelpad=-3)\n",
    "    plt.title(titles[datasetnum] + ', rank=2')\n",
    "    plt.ylim([0, ylims[datasetnum]])\n",
    "    plt.xlim([3, 300])\n",
    "    #if datasetnum==3:\n",
    "    #    plt.xlim([3,1100])\n",
    "    plt.plot([20,20], [0,ylims[datasetnum]], color=[.7,.7,.7], linewidth=.5, zorder=0)\n",
    "    \n",
    "\n",
    "    plt.subplot(2,4,datasetnum+5)\n",
    "    colA = np.array([76, 114, 176]) / 256\n",
    "    colB = np.array([196, 78, 82])  / 256\n",
    "    maxRank = len(cvresults[1])\n",
    "    for rank in range(1,maxRank+1):\n",
    "        # suppressing \"mean of empty slice\" warnings\n",
    "        with warnings.catch_warnings():\n",
    "            warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n",
    "            n = np.nanmean(cvresults[1][rank][2], axis=(0,1))\n",
    "            c = np.nanmean(cvresults[1][rank][0], axis=(0,1))\n",
    "            cr = np.nanmean(cvresults[1][rank][1], axis=(0,1))\n",
    "    \n",
    "        if rank==2:\n",
    "            lw = 1.25\n",
    "        else:\n",
    "            lw = .75\n",
    "        col = (colA * (rank-1)/(maxRank-1) + colB * (maxRank-rank)/(maxRank-1))\n",
    "        if rank==1 or rank==maxRank:\n",
    "            plt.plot(n, cr, color=col, linewidth=lw, label='rank {}'.format(rank))\n",
    "        else:\n",
    "            plt.plot(n, cr, color=col, linewidth=lw)    \n",
    "        plt.plot(n, c, '--', color=col, linewidth=lw)\n",
    "\n",
    "    if datasetnum==0:\n",
    "        plt.legend(loc='lower right')\n",
    "        plt.text(4, .18, 'Relaxed', fontsize=6)\n",
    "        plt.text(20, .03, 'Naive', fontsize=6)\n",
    "        plt.ylabel(r'Cross-validated $R^2$')\n",
    "    plt.xscale('log')\n",
    "    plt.xlabel('Number of genes')#, labelpad=-3)\n",
    "    plt.title(titles[datasetnum] + r', $\\alpha={}$'.format(alphaused[datasetnum]))\n",
    "    plt.ylim([0, ylims[datasetnum]])\n",
    "    plt.xlim([3, 300])\n",
    "    #if datasetnum==3:\n",
    "    #    plt.ylim([0, 0.4])\n",
    "    #    plt.xlim([3,1100])\n",
    "    plt.plot([20,20], [0,ylims[datasetnum]], color=[.7,.7,.7], linewidth=.5, zorder=0)\n",
    "\n",
    "sns.despine()\n",
    "plt.tight_layout()\n",
    "\n",
    "fig.text(.025, .97, 'a', fontsize=8, fontweight='bold')\n",
    "fig.text(.265, .97, 'b', fontsize=8, fontweight='bold')\n",
    "fig.text(.515, .97, 'c', fontsize=8, fontweight='bold')\n",
    "fig.text(.75, .97, 'd', fontsize=8, fontweight='bold')\n",
    "fig.text(.025, .47, 'e', fontsize=8, fontweight='bold')\n",
    "fig.text(.265, .47, 'f', fontsize=8, fontweight='bold')\n",
    "fig.text(.515, .47, 'g', fontsize=8, fontweight='bold')\n",
    "fig.text(.75, .47, 'h', fontsize=8, fontweight='bold')\n",
    "\n",
    "plt.savefig('figures/cv.png', dpi=200)\n",
    "plt.savefig('figures/cv.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cadwell et al. 2016  -- naive std: 0.05, relaxed std: 0.12\n",
      "Scala et al. 2019    -- naive std: 0.04, relaxed std: 0.07\n",
      "Scala et al. 2020    -- naive std: 0.01, relaxed std: 0.01\n",
      "Gouwens et al. 2020  -- naive std: 0.01, relaxed std: 0.01\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "alphaid = [1,1,3,3]\n",
    "\n",
    "for datasetnum, cvresults in enumerate([cadwell2016cv, scala2019cv, scala2020cv, gouwens2020cv]):\n",
    "    # suppressing \"mean of empty slice\" warnings\n",
    "    with warnings.catch_warnings():\n",
    "        warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n",
    "        n  = np.nanmean(cvresults[0][2], axis=(0,1))[:,alphaid[datasetnum]]\n",
    "        c  = np.nanstd (cvresults[0][0], axis=(0,1))[:,alphaid[datasetnum]]\n",
    "        cr = np.nanstd (cvresults[0][1], axis=(0,1))[:,alphaid[datasetnum]]\n",
    "        \n",
    "        c = c[np.nanargmin(np.abs(n-20))]\n",
    "        cr = cr[np.nanargmin(np.abs(n-20))]\n",
    "        \n",
    "        print('{:20} -- naive std: {:.2f}, relaxed std: {:.2f}'.format(titles[datasetnum], c, cr))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preprocessing variants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "scala2020cv   = pickle.load(open('pickles/cvresults-scala2020-variants.pickle', 'rb'))\n",
    "scala2019cv   = pickle.load(open('pickles/cvresults-scala2019-variants.pickle', 'rb'))\n",
    "cadwell2016cv = pickle.load(open('pickles/cvresults-cadwell2016-variants.pickle', 'rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "/* 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",
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       "\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",
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       "\n",
       "    this.context = undefined;\n",
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       "    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",
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       "    this._init_toolbar(this);\n",
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       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
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       "        if (mpl.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
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       "            // Full images could contain transparency (where diff images\n",
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       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
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       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
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       "        for (var i = 0; i < nentries; i++) {\n",
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       "                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",
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       "                canvas.setAttribute('width', width * mpl.ratio);\n",
       "                canvas.setAttribute('height', height * mpl.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
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       "        };\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",
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       "    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",
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       "\n",
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       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / mpl.ratio,\n",
       "        fig.canvas.height / mpl.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / mpl.ratio;\n",
       "    fig.root.removeEventListener('remove', this._remove_fig_handler);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / mpl.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function () {\n",
       "    this.close_ws(this, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "    el.addEventListener('remove', this._remove_fig_handler);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"875.4166666666667\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "fig = plt.figure(figsize=(7.3, 2))\n",
    "\n",
    "ylims = [.25, .16, .5]\n",
    "highlight = [1, 1, 3]\n",
    "alphas = [.25, .5, .75, 1]\n",
    "alphaused = [.5, .5, 1]\n",
    "titles = ['Cadwell et al. 2016', 'Scala et al. 2019', 'Scala et al. 2020']\n",
    "\n",
    "legends = ['Default', 'Without standardization', 'Without gene selection',\n",
    "           'Without either', 'Preprocessing inside CV']\n",
    "\n",
    "for datasetnum, cvresults in enumerate([cadwell2016cv, scala2019cv, scala2020cv]):\n",
    "    plt.subplot(1,3,datasetnum+1)\n",
    "    for mode in range(5):\n",
    "        # suppressing \"mean of empty slice\" warnings\n",
    "        with warnings.catch_warnings():\n",
    "            warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n",
    "            n = np.nanmean(cvresults[mode][2], axis=(0,1))\n",
    "            c = np.nanmean(cvresults[mode][0], axis=(0,1))\n",
    "            cr = np.nanmean(cvresults[mode][1], axis=(0,1))\n",
    "        \n",
    "        color = next(plt.gca()._get_lines.prop_cycler)['color']\n",
    "        plt.plot(n, cr, linewidth=.75, color=color, label=legends[mode], zorder=10-mode)\n",
    "        plt.plot(n, c, '--', linewidth=.75, color=color, zorder=10-mode)\n",
    "\n",
    "    if datasetnum==0:\n",
    "        plt.text(4, .18, 'Relaxed', fontsize=6)\n",
    "        plt.text(25, .03, 'Naive', fontsize=6)\n",
    "        plt.ylabel(r'Cross-validated $R^2$')\n",
    "    if datasetnum==2:\n",
    "        plt.legend()\n",
    "    plt.xscale('log')\n",
    "    plt.xlabel('Number of genes', labelpad=-3)\n",
    "    plt.title(titles[datasetnum])\n",
    "    plt.ylim([0, ylims[datasetnum]])\n",
    "    plt.xlim([3, 300])\n",
    "    plt.plot([20,20], [0,ylims[datasetnum]], color=[.7,.7,.7], linewidth=.5, zorder=0)\n",
    "    \n",
    "sns.despine()\n",
    "plt.tight_layout()\n",
    "\n",
    "fig.text(.01, .92, 'a', fontsize=8, fontweight='bold')\n",
    "fig.text(.33, .92, 'b', fontsize=8, fontweight='bold')\n",
    "fig.text(.66, .92, 'c', fontsize=8, fontweight='bold')\n",
    "\n",
    "plt.savefig('figures/preprocessing.png', dpi=200)\n",
    "plt.savefig('figures/preprocessing.pdf')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison to Witten et al."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "scala2020cv   = pickle.load(open('pickles/cvresults-scala2020.pickle', 'rb'))\n",
    "scala2019cv   = pickle.load(open('pickles/cvresults-scala2019.pickle', 'rb'))\n",
    "cadwell2016cv = pickle.load(open('pickles/cvresults-cadwell2016.pickle', 'rb'))\n",
    "gouwens2020cv = pickle.load(open('pickles/cvresults-gouwens2020.pickle', 'rb'))\n",
    "\n",
    "scala2020cv_w   = pickle.load(open('pickles/cvresults-scala2020-witten.pickle', 'rb'))\n",
    "scala2019cv_w   = pickle.load(open('pickles/cvresults-scala2019-witten.pickle', 'rb'))\n",
    "cadwell2016cv_w = pickle.load(open('pickles/cvresults-cadwell2016-witten.pickle', 'rb'))\n",
    "gouwens2020cv_w = pickle.load(open('pickles/cvresults-gouwens2020-witten.pickle', 'rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (mpl.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    var resizeObserver = new ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * mpl.ratio);\n",
       "                canvas.setAttribute('height', height * mpl.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / mpl.ratio,\n",
       "        fig.canvas.height / mpl.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / mpl.ratio;\n",
       "    fig.root.removeEventListener('remove', this._remove_fig_handler);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / mpl.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function () {\n",
       "    this.close_ws(this, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "    el.addEventListener('remove', this._remove_fig_handler);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"875.4166666666667\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "fig = plt.figure(figsize=(7.3, 2))\n",
    "\n",
    "highlight = [1, 1, 3, 1]     # ?\n",
    "alphas = [.25, .5, .75, 1] # ? \n",
    "alphaused = [.5, .5, 1, 1]\n",
    "alphaids=[0,1,2,3]\n",
    "titles = ['Cadwell et al. 2016', 'Scala et al. 2019', 'Scala et al. 2020', 'Gouwens et al. 2020']\n",
    "\n",
    "for datasetnum, cvresults in enumerate([cadwell2016cv, scala2019cv, scala2020cv, gouwens2020cv]):\n",
    "    cvresults_ws = [cadwell2016cv_w, scala2019cv_w, scala2020cv_w, gouwens2020cv_w][datasetnum]\n",
    "\n",
    "    plt.subplot(1,4,datasetnum+1)\n",
    "    colA = np.array([76, 114, 176]) / 256\n",
    "    colB = np.array([196, 78, 82])  / 256\n",
    "    alphaid = alphaids[datasetnum]\n",
    "    \n",
    "#     for alphaid in range(4):\n",
    "    # suppressing \"mean of empty slice\" warnings\n",
    "    with warnings.catch_warnings():\n",
    "        warnings.simplefilter('ignore', category=RuntimeWarning)\n",
    "        n = np.nanmean(cvresults[0][2], axis=(0,1))\n",
    "        c = np.nanmean(cvresults[0][4], axis=(0,1))\n",
    "        \n",
    "#         if alphaid == highlight[datasetnum]:\n",
    "#             lw = 1.25\n",
    "#         else:\n",
    "#             lw = .75\n",
    "#     col = (colA * alphaid/3 + colB * (3-alphaid)/3)\n",
    "    col = next(plt.gca()._get_lines.prop_cycler)['color']\n",
    "    plt.plot(n[:,alphaid], c[:,alphaid,0], linewidth=.75, color=col, label='sRRR 1', zorder=10)\n",
    "#              label=r'$\\alpha={:.2f}$'.format(alphas[alphaid]))\n",
    "    plt.plot(n[:,alphaid], c[:,alphaid,1], '--', linewidth=.75, color=col, label='sRRR 2', zorder=10)\n",
    "        \n",
    "    with warnings.catch_warnings():\n",
    "        warnings.simplefilter('ignore', category=RuntimeWarning)\n",
    "            \n",
    "        col = next(plt.gca()._get_lines.prop_cycler)['color']\n",
    "\n",
    "        x = np.nanmean(cvresults_ws[1][:,:,:,0], axis=(0,1))\n",
    "        y = np.nanmean(cvresults_ws[0][:,:,:,0], axis=(0,1))\n",
    "        plt.plot(x, y, color=col, linewidth=.75, label='Witten et al. 1')\n",
    "        \n",
    "        x = np.nanmean(cvresults_ws[1][:,:,:,1], axis=(0,1))\n",
    "        y = np.nanmean(cvresults_ws[0][:,:,:,1], axis=(0,1))\n",
    "        plt.plot(x, y, '--', color=col, linewidth=.75, label='Witten et al. 2')\n",
    "        \n",
    "    if datasetnum==0:\n",
    "#         plt.text(4, .8, 'Component 1', fontsize=6)\n",
    "#         plt.text(40,.15, 'Component 2', fontsize=6)\n",
    "        plt.ylabel('Cross-validated correlation')\n",
    "    if datasetnum==3:\n",
    "        plt.legend(loc='lower right')        \n",
    "    plt.xscale('log')\n",
    "    plt.xlabel('Number of genes') #, labelpad=-3)\n",
    "    plt.title(titles[datasetnum])\n",
    "    plt.ylim([0, 1])\n",
    "    plt.xlim([3, 300])\n",
    "    if datasetnum==3:\n",
    "        plt.xlim([3,700])\n",
    "    plt.plot([20,20], [0,1], color=[.7,.7,.7], linewidth=.5, zorder=0)\n",
    "    \n",
    "sns.despine()\n",
    "plt.tight_layout()\n",
    "\n",
    "\n",
    "fig.text(.025, .92, 'a', fontsize=8, fontweight='bold')\n",
    "fig.text(.265, .92, 'b', fontsize=8, fontweight='bold')\n",
    "fig.text(.506, .92, 'c', fontsize=8, fontweight='bold')\n",
    "fig.text(.75, .92, 'd', fontsize=8, fontweight='bold')\n",
    "\n",
    "plt.savefig('figures/corr.png', dpi=200)\n",
    "plt.savefig('figures/corr.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cadwell et al. 2016  -- corr1: 0.69, corr2: 0.35\n",
      "Scala et al. 2019    -- corr1: 0.65, corr2: 0.54\n",
      "Scala et al. 2020    -- corr1: 0.91, corr2: 0.77\n",
      "Gouwens et al. 2020  -- corr1: 0.92, corr2: 0.83\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "alphaid = [1,1,3,3]\n",
    "\n",
    "for datasetnum, cvresults in enumerate([cadwell2016cv, scala2019cv, scala2020cv, gouwens2020cv]):\n",
    "    # suppressing \"mean of empty slice\" warnings\n",
    "    with warnings.catch_warnings():\n",
    "        warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n",
    "        n  = np.nanmean(cvresults[0][2], axis=(0,1))[:,alphaid[datasetnum]]\n",
    "        c1 = np.nanmean(cvresults[0][4], axis=(0,1))[:,alphaid,0]\n",
    "        c2 = np.nanmean(cvresults[0][4], axis=(0,1))[:,alphaid,1]\n",
    "        \n",
    "        c1 = c1[np.nanargmin(np.abs(n-20))]\n",
    "        c2 = c2[np.nanargmin(np.abs(n-20))]\n",
    "        \n",
    "        print('{:20} -- corr1: {:.2f}, corr2: {:.2f}'.format(titles[datasetnum], c1[0], c2[0]))"
   ]
  }
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