Update notebook, add frequency meter

author: jaseg <git@jaseg.de> 2021-03-25 12:15:38 +0100
committer: jaseg <git@jaseg.de> 2021-03-25 12:15:38 +0100
commit: 2bb9aecfc62cb597155f50b6bf22131ab33cb301 (patch)
tree: ac7d5fd93cf0f22ecf29db69e423e98fdfbe2273 /prototype
parent: 6fc8f236916c10811b8611f46edea4f3be2118b3 (diff)
download: ihsm-2bb9aecfc62cb597155f50b6bf22131ab33cb301.tar.gz
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2 files changed, 2198 insertions, 82 deletions
diff --git a/prototype/fw/freqmeter.py b/prototype/fw/freqmeter.py
index 54c1655..430b73f 100644
--- a/prototype/fw/freqmeter.py
+++ b/prototype/fw/freqmeter.py
@@ -12,11 +12,11 @@ count = lambda le_iter: sum(1 for _ in le_iter)
 
 DEFAULT_SAMPLING_RATE = 1e6 # sps
 
-def sigrok_capture(duration:'seconds'=1, sampling_rate=DEFAULT_SAMPLING_RATE, driver='dreamsourcelab-dslogic', config=None, channel=0):
+def sigrok_capture(duration:'milliseconds', sampling_rate=DEFAULT_SAMPLING_RATE, driver='dreamsourcelab-dslogic', config=None, channel=0):
 
     proc = subprocess.run(['sigrok-cli',
         '--driver', driver,
-        '--time', f'{duration}s',
+        '--time', f'{duration}ms',
         '--config', (f'{config},' if config else '') + f'samplerate={int(sampling_rate/1e3)}k',
         '--channels', str(channel),
         '--output-format', 'csv'], check=True, stdout=subprocess.PIPE)
@@ -54,7 +54,7 @@ def calc_frequency(intervals, sampling_rate=DEFAULT_SAMPLING_RATE):
 
 if __name__ == '__main__':
     while True:
-        capture = sigrok_capture()
+        capture = sigrok_capture(1500)
         intervals = list(debounce(capture))
 
         intervals = intervals[2:-1] # ignore partial first and last intervals
diff --git a/prototype/sensor-analysis/Accelerometer Data Analysis.ipynb b/prototype/sensor-analysis/Accelerometer Data Analysis.ipynb
index 23f31b8..72f13c8 100644
--- a/prototype/sensor-analysis/Accelerometer Data Analysis.ipynb
+++ b/prototype/sensor-analysis/Accelerometer Data Analysis.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 703,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -24,7 +24,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 704,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -33,7 +33,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 705,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -45,7 +45,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 836,
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sampling_rate = 10 # sps, set in firmware\n",
+    "mems_lsb_per_g = 68 # LSBs per 1g for our accelerometer\n",
+    "\n",
+    "g = 9.8066\n",
+    "g_to_ms = lambda x: x * g\n",
+    "ms_to_g = lambda x: x / g\n",
+    "\n",
+    "r_mems = 55e-3 # radius of our sensor from the axis of rotation in m"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
    "metadata": {
     "scrolled": false
    },
@@ -1018,7 +1034,7 @@
     {
      "data": {
       "text/html": [
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\" 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\" width=\"640\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1050,6 +1066,7 @@
     "    filtered = scipy.signal.sosfiltfilt(sos, y / mems_lsb_per_g)\n",
     "    ax.plot(t, filtered, color='darkblue')\n",
     "    \n",
+    "    ax.set_xlabel(r't [mm:ss]')\n",
     "    ax.set_ylabel(r'$a\\; [g]$')\n",
     "    secax_y = ax.secondary_yaxis(\n",
     "        'right', functions=(g_to_ms, ms_to_g))\n",
@@ -1114,7 +1131,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1019,
+   "execution_count": 84,
    "metadata": {
     "scrolled": false
    },
@@ -2090,7 +2107,7 @@
     {
      "data": {
       "text/html": [
-       "<img 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\" 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\" width=\"500\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -2165,22 +2182,14 @@
    "source": [
     "t, y, _1, _2 = load_run(40, plot=False)\n",
     "\n",
-    "sampling_rate = 10 # sps, set in firmware\n",
-    "mems_lsb_per_g = 68 # LSBs per 1g for our accelerometer\n",
-    "\n",
     "ivl_start, ivl_end = 0.5, 1\n",
     "ivl_start, ivl_end = int(ivl_start*60*sampling_rate), int(ivl_end*60*sampling_rate)\n",
     "\n",
-    "fig, ax = plt.subplots()\n",
+    "fig, ax = plt.subplots(figsize=(5, 3))\n",
     "#ax.axvspan(ivl_start/60/sampling_rate, ivl_end/60/sampling_rate, color='orange', alpha=0.5)\n",
     "    \n",
     "plot_measurements(ax, t, y)\n",
     "\n",
-    "g = 9.8066\n",
-    "g_to_ms = lambda x: x * g\n",
-    "ms_to_g = lambda x: x / g\n",
-    "\n",
-    "r_mems = 55e-3 # radius of our sensor from the axis of rotation in m\n",
     "le_data = [(0, 50, 3.12), (1,50,5.55), (2,40, 8.2), (3, 30, 10.2), (4,15, 12.5), (5,10, 15.6),\n",
     "           (6,10, 19.2), (7,11, 11.6), (8,15, 6.49)]\n",
     "avg_include = [True, True, True, True, True, False, True, True, True]\n",
@@ -2191,10 +2200,13 @@
     "    omegan = 2*np.pi*f_actual # angular velocity\n",
     "    acc = omegan**2 * r_mems # m/s^2\n",
     "    acc_theory.append(acc / g)\n",
-    "    ax.axvspan(ts_abs-ivl_w/2, ts_abs+ivl_w/2, zorder=1, color='red', alpha=0.1)\n",
+    "    \n",
     "    \n",
     "    ts_abs = ts_m + ts_s/60\n",
     "    ivl_w = 0.5\n",
+    "    \n",
+    "    #ax.axvspan(ts_abs-ivl_w/2, ts_abs+ivl_w/2, zorder=1, color='red', alpha=0.1)\n",
+    "    \n",
     "    idx = (ts_abs - ivl_w/2 < t) & (t < ts_abs + ivl_w/2)\n",
     "    ivl_avg = (y / mems_lsb_per_g)[idx].mean()\n",
     "    acc_meas.append(ivl_avg)\n",
@@ -2219,7 +2231,7 @@
     "print(f'Found sensor offset: {sensor_offx:.2f} g / {sensor_offx*g:.2f} m/s^2')\n",
     "print()\n",
     "\n",
-    "for theory, meas, interval, (_1, _2, f_actual) in zip(acc_theory, acc_meas, interval_speeds, le_data):\n",
+    "for theory, meas, (_1, _2, f_actual) in zip(acc_theory, acc_meas, le_data):\n",
     "    ax.axhline(theory - sensor_offx, color='orange', alpha=1, zorder=1)\n",
     "    meas += sensor_offx\n",
     "        \n",
@@ -2228,12 +2240,15 @@
     "    print(f'    Measurement: {meas:.2f} g / {meas*g} m/s^2')\n",
     "    print(f'     Rel. Error: {(theory/meas - 1.0) * 100:.2f} %')\n",
     "    print(f'     Abs. Error: {theory-meas:.2f} g / {(theory-meas)*g:.2f} m/s^2')\n",
-    "    print()"
+    "    print()\n",
+    "\n",
+    "fig.tight_layout()\n",
+    "fig.savefig('fig-acc-trace-steps.pdf')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1022,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -3209,10 +3224,10 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x7f3df6c2b3d0>"
+       "<matplotlib.legend.Legend at 0x7f2d6d065190>"
       ]
      },
-     "execution_count": 1022,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3246,7 +3261,1108 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 957,
+   "execution_count": 77,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Loading run #28 with 4918 packets total, 178 distinct over 161.5061011314392s\n",
+      "Packet length: 40\n",
+      "Very approximate lower bound on baudrate: 129032.25806451612 bd\n",
+      "Sequence number range: 611 ... 813\n",
+      "Loading run #37 with 3070 packets total, 144 distinct over 117.43898510932922s\n",
+      "Packet length: 40\n",
+      "Very approximate lower bound on baudrate: 129032.25806451612 bd\n",
+      "Sequence number range: 326 ... 473\n",
+      "Loading run #30 with 2208 packets total, 198 distinct over 166.86816382408142s\n",
+      "Packet length: 40\n",
+      "Very approximate lower bound on baudrate: 129032.25806451612 bd\n",
+      "Sequence number range: 1079 ... 1288\n",
+      "Loading run #31 with 2630 packets total, 157 distinct over 126.19650292396545s\n",
+      "Packet length: 40\n",
+      "Very approximate lower bound on baudrate: 129032.25806451612 bd\n",
+      "Sequence number range: 1316 ... 1474\n",
+      "Loading run #34 with 2714 packets total, 121 distinct over 97.30304408073425s\n",
+      "Packet length: 40\n",
+      "Very approximate lower bound on baudrate: 129032.25806451612 bd\n",
+      "Sequence number range: 165 ... 287\n",
+      "Loading run #38 with 2317 packets total, 122 distinct over 103.3755898475647s\n",
+      "Packet length: 40\n",
+      "Very approximate lower bound on baudrate: 129032.25806451612 bd\n",
+      "Sequence number range: 475 ... 604\n",
+      "Loading run #32 with 2643 packets total, 118 distinct over 98.81923913955688s\n",
+      "Packet length: 40\n",
+      "Very approximate lower bound on baudrate: 129032.25806451612 bd\n",
+      "Sequence number range: 3 ... 1583\n",
+      "Loading run #39 with 1429 packets total, 129 distinct over 104.99669194221497s\n",
+      "Packet length: 40\n",
+      "Very approximate lower bound on baudrate: 129032.25806451612 bd\n",
+      "Sequence number range: 606 ... 737\n",
+      "Loading run #33 with 3178 packets total, 125 distinct over 99.94346904754639s\n",
+      "Packet length: 40\n",
+      "Very approximate lower bound on baudrate: 129032.25806451612 bd\n",
+      "Sequence number range: 35 ... 161\n"
+     ]
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "/* global mpl */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "mpl.get_websocket_type = function () {\n",
+       "    if (typeof WebSocket !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert(\n",
+       "            'Your browser does not have WebSocket support. ' +\n",
+       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "                'Firefox 4 and 5 are also supported but you ' +\n",
+       "                'have to enable WebSockets in about:config.'\n",
+       "        );\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById('mpl-warnings');\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent =\n",
+       "                'This browser does not support binary websocket messages. ' +\n",
+       "                'Performance may be slow.';\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = document.createElement('div');\n",
+       "    this.root.setAttribute('style', 'display: inline-block');\n",
+       "    this._root_extra_style(this.root);\n",
+       "\n",
+       "    parent_element.appendChild(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen = function () {\n",
+       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+       "        fig.send_message('send_image_mode', {});\n",
+       "        if (fig.ratio !== 1) {\n",
+       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+       "        }\n",
+       "        fig.send_message('refresh', {});\n",
+       "    };\n",
+       "\n",
+       "    this.imageObj.onload = function () {\n",
+       "        if (fig.image_mode === 'full') {\n",
+       "            // Full images could contain transparency (where diff images\n",
+       "            // almost always do), so we need to clear the canvas so that\n",
+       "            // there is no ghosting.\n",
+       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "        }\n",
+       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "    };\n",
+       "\n",
+       "    this.imageObj.onunload = function () {\n",
+       "        fig.ws.close();\n",
+       "    };\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function () {\n",
+       "    var titlebar = document.createElement('div');\n",
+       "    titlebar.classList =\n",
+       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+       "    var titletext = document.createElement('div');\n",
+       "    titletext.classList = 'ui-dialog-title';\n",
+       "    titletext.setAttribute(\n",
+       "        'style',\n",
+       "        'width: 100%; text-align: center; padding: 3px;'\n",
+       "    );\n",
+       "    titlebar.appendChild(titletext);\n",
+       "    this.root.appendChild(titlebar);\n",
+       "    this.header = titletext;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function () {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+       "    canvas_div.setAttribute(\n",
+       "        'style',\n",
+       "        'border: 1px solid #ddd;' +\n",
+       "            'box-sizing: content-box;' +\n",
+       "            'clear: both;' +\n",
+       "            'min-height: 1px;' +\n",
+       "            'min-width: 1px;' +\n",
+       "            'outline: 0;' +\n",
+       "            'overflow: hidden;' +\n",
+       "            'position: relative;' +\n",
+       "            'resize: both;'\n",
+       "    );\n",
+       "\n",
+       "    function on_keyboard_event_closure(name) {\n",
+       "        return function (event) {\n",
+       "            return fig.key_event(event, name);\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.addEventListener(\n",
+       "        'keydown',\n",
+       "        on_keyboard_event_closure('key_press')\n",
+       "    );\n",
+       "    canvas_div.addEventListener(\n",
+       "        'keyup',\n",
+       "        on_keyboard_event_closure('key_release')\n",
+       "    );\n",
+       "\n",
+       "    this._canvas_extra_style(canvas_div);\n",
+       "    this.root.appendChild(canvas_div);\n",
+       "\n",
+       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
+       "    canvas.classList.add('mpl-canvas');\n",
+       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+       "\n",
+       "    this.context = canvas.getContext('2d');\n",
+       "\n",
+       "    var backingStore =\n",
+       "        this.context.backingStorePixelRatio ||\n",
+       "        this.context.webkitBackingStorePixelRatio ||\n",
+       "        this.context.mozBackingStorePixelRatio ||\n",
+       "        this.context.msBackingStorePixelRatio ||\n",
+       "        this.context.oBackingStorePixelRatio ||\n",
+       "        this.context.backingStorePixelRatio ||\n",
+       "        1;\n",
+       "\n",
+       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+       "        'canvas'\n",
+       "    ));\n",
+       "    rubberband_canvas.setAttribute(\n",
+       "        'style',\n",
+       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+       "    );\n",
+       "\n",
+       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+       "    if (this.ResizeObserver === undefined) {\n",
+       "        if (window.ResizeObserver !== undefined) {\n",
+       "            this.ResizeObserver = window.ResizeObserver;\n",
+       "        } else {\n",
+       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+       "            this.ResizeObserver = obs.ResizeObserver;\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+       "        var nentries = entries.length;\n",
+       "        for (var i = 0; i < nentries; i++) {\n",
+       "            var entry = entries[i];\n",
+       "            var width, height;\n",
+       "            if (entry.contentBoxSize) {\n",
+       "                if (entry.contentBoxSize instanceof Array) {\n",
+       "                    // Chrome 84 implements new version of spec.\n",
+       "                    width = entry.contentBoxSize[0].inlineSize;\n",
+       "                    height = entry.contentBoxSize[0].blockSize;\n",
+       "                } else {\n",
+       "                    // Firefox implements old version of spec.\n",
+       "                    width = entry.contentBoxSize.inlineSize;\n",
+       "                    height = entry.contentBoxSize.blockSize;\n",
+       "                }\n",
+       "            } else {\n",
+       "                // Chrome <84 implements even older version of spec.\n",
+       "                width = entry.contentRect.width;\n",
+       "                height = entry.contentRect.height;\n",
+       "            }\n",
+       "\n",
+       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
+       "            // the canvas container.\n",
+       "            if (entry.devicePixelContentBoxSize) {\n",
+       "                // Chrome 84 implements new version of spec.\n",
+       "                canvas.setAttribute(\n",
+       "                    'width',\n",
+       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
+       "                );\n",
+       "                canvas.setAttribute(\n",
+       "                    'height',\n",
+       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
+       "                );\n",
+       "            } else {\n",
+       "                canvas.setAttribute('width', width * fig.ratio);\n",
+       "                canvas.setAttribute('height', height * fig.ratio);\n",
+       "            }\n",
+       "            canvas.setAttribute(\n",
+       "                'style',\n",
+       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
+       "            );\n",
+       "\n",
+       "            rubberband_canvas.setAttribute('width', width);\n",
+       "            rubberband_canvas.setAttribute('height', height);\n",
+       "\n",
+       "            // And update the size in Python. We ignore the initial 0/0 size\n",
+       "            // that occurs as the element is placed into the DOM, which should\n",
+       "            // otherwise not happen due to the minimum size styling.\n",
+       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+       "                fig.request_resize(width, height);\n",
+       "            }\n",
+       "        }\n",
+       "    });\n",
+       "    this.resizeObserverInstance.observe(canvas_div);\n",
+       "\n",
+       "    function on_mouse_event_closure(name) {\n",
+       "        return function (event) {\n",
+       "            return fig.mouse_event(event, name);\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    rubberband_canvas.addEventListener(\n",
+       "        'mousedown',\n",
+       "        on_mouse_event_closure('button_press')\n",
+       "    );\n",
+       "    rubberband_canvas.addEventListener(\n",
+       "        'mouseup',\n",
+       "        on_mouse_event_closure('button_release')\n",
+       "    );\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband_canvas.addEventListener(\n",
+       "        'mousemove',\n",
+       "        on_mouse_event_closure('motion_notify')\n",
+       "    );\n",
+       "\n",
+       "    rubberband_canvas.addEventListener(\n",
+       "        'mouseenter',\n",
+       "        on_mouse_event_closure('figure_enter')\n",
+       "    );\n",
+       "    rubberband_canvas.addEventListener(\n",
+       "        'mouseleave',\n",
+       "        on_mouse_event_closure('figure_leave')\n",
+       "    );\n",
+       "\n",
+       "    canvas_div.addEventListener('wheel', function (event) {\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        on_mouse_event_closure('scroll')(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.appendChild(canvas);\n",
+       "    canvas_div.appendChild(rubberband_canvas);\n",
+       "\n",
+       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+       "    this.rubberband_context.strokeStyle = '#000000';\n",
+       "\n",
+       "    this._resize_canvas = function (width, height, forward) {\n",
+       "        if (forward) {\n",
+       "            canvas_div.style.width = width + 'px';\n",
+       "            canvas_div.style.height = height + 'px';\n",
+       "        }\n",
+       "    };\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+       "        event.preventDefault();\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus() {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function () {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var toolbar = document.createElement('div');\n",
+       "    toolbar.classList = 'mpl-toolbar';\n",
+       "    this.root.appendChild(toolbar);\n",
+       "\n",
+       "    function on_click_closure(name) {\n",
+       "        return function (_event) {\n",
+       "            return fig.toolbar_button_onclick(name);\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    function on_mouseover_closure(tooltip) {\n",
+       "        return function (event) {\n",
+       "            if (!event.currentTarget.disabled) {\n",
+       "                return fig.toolbar_button_onmouseover(tooltip);\n",
+       "            }\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    fig.buttons = {};\n",
+       "    var buttonGroup = document.createElement('div');\n",
+       "    buttonGroup.classList = 'mpl-button-group';\n",
+       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            /* Instead of a spacer, we start a new button group. */\n",
+       "            if (buttonGroup.hasChildNodes()) {\n",
+       "                toolbar.appendChild(buttonGroup);\n",
+       "            }\n",
+       "            buttonGroup = document.createElement('div');\n",
+       "            buttonGroup.classList = 'mpl-button-group';\n",
+       "            continue;\n",
+       "        }\n",
+       "\n",
+       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
+       "        button.classList = 'mpl-widget';\n",
+       "        button.setAttribute('role', 'button');\n",
+       "        button.setAttribute('aria-disabled', 'false');\n",
+       "        button.addEventListener('click', on_click_closure(method_name));\n",
+       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+       "\n",
+       "        var icon_img = document.createElement('img');\n",
+       "        icon_img.src = '_images/' + image + '.png';\n",
+       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+       "        icon_img.alt = tooltip;\n",
+       "        button.appendChild(icon_img);\n",
+       "\n",
+       "        buttonGroup.appendChild(button);\n",
+       "    }\n",
+       "\n",
+       "    if (buttonGroup.hasChildNodes()) {\n",
+       "        toolbar.appendChild(buttonGroup);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker = document.createElement('select');\n",
+       "    fmt_picker.classList = 'mpl-widget';\n",
+       "    toolbar.appendChild(fmt_picker);\n",
+       "    this.format_dropdown = fmt_picker;\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = document.createElement('option');\n",
+       "        option.selected = fmt === mpl.default_extension;\n",
+       "        option.innerHTML = fmt;\n",
+       "        fmt_picker.appendChild(option);\n",
+       "    }\n",
+       "\n",
+       "    var status_bar = document.createElement('span');\n",
+       "    status_bar.classList = 'mpl-message';\n",
+       "    toolbar.appendChild(status_bar);\n",
+       "    this.message = status_bar;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function (type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function () {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+       "        fig.send_message('refresh', {});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+       "    var x0 = msg['x0'] / fig.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+       "    var x1 = msg['x1'] / fig.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0,\n",
+       "        0,\n",
+       "        fig.canvas.width / fig.ratio,\n",
+       "        fig.canvas.height / fig.ratio\n",
+       "    );\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch (cursor) {\n",
+       "        case 0:\n",
+       "            cursor = 'pointer';\n",
+       "            break;\n",
+       "        case 1:\n",
+       "            cursor = 'default';\n",
+       "            break;\n",
+       "        case 2:\n",
+       "            cursor = 'crosshair';\n",
+       "            break;\n",
+       "        case 3:\n",
+       "            cursor = 'move';\n",
+       "            break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+       "    for (var key in msg) {\n",
+       "        if (!(key in fig.buttons)) {\n",
+       "            continue;\n",
+       "        }\n",
+       "        fig.buttons[key].disabled = !msg[key];\n",
+       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+       "    if (msg['mode'] === 'PAN') {\n",
+       "        fig.buttons['Pan'].classList.add('active');\n",
+       "        fig.buttons['Zoom'].classList.remove('active');\n",
+       "    } else if (msg['mode'] === 'ZOOM') {\n",
+       "        fig.buttons['Pan'].classList.remove('active');\n",
+       "        fig.buttons['Zoom'].classList.add('active');\n",
+       "    } else {\n",
+       "        fig.buttons['Pan'].classList.remove('active');\n",
+       "        fig.buttons['Zoom'].classList.remove('active');\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function () {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message('ack', {});\n",
+       "};\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = 'image/png';\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src\n",
+       "                );\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data\n",
+       "            );\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        } else if (\n",
+       "            typeof evt.data === 'string' &&\n",
+       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+       "        ) {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig['handle_' + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\n",
+       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
+       "                msg\n",
+       "            );\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\n",
+       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+       "                    e,\n",
+       "                    e.stack,\n",
+       "                    msg\n",
+       "                );\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "};\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function (e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e) {\n",
+       "        e = window.event;\n",
+       "    }\n",
+       "    if (e.target) {\n",
+       "        targ = e.target;\n",
+       "    } else if (e.srcElement) {\n",
+       "        targ = e.srcElement;\n",
+       "    }\n",
+       "    if (targ.nodeType === 3) {\n",
+       "        // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "    }\n",
+       "\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    var boundingRect = targ.getBoundingClientRect();\n",
+       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+       "\n",
+       "    return { x: x, y: y };\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys(original) {\n",
+       "    return Object.keys(original).reduce(function (obj, key) {\n",
+       "        if (typeof original[key] !== 'object') {\n",
+       "            obj[key] = original[key];\n",
+       "        }\n",
+       "        return obj;\n",
+       "    }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event);\n",
+       "\n",
+       "    if (name === 'button_press') {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * this.ratio;\n",
+       "    var y = canvas_pos.y * this.ratio;\n",
+       "\n",
+       "    this.send_message(name, {\n",
+       "        x: x,\n",
+       "        y: y,\n",
+       "        button: event.button,\n",
+       "        step: event.step,\n",
+       "        guiEvent: simpleKeys(event),\n",
+       "    });\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function (event, name) {\n",
+       "    // Prevent repeat events\n",
+       "    if (name === 'key_press') {\n",
+       "        if (event.which === this._key) {\n",
+       "            return;\n",
+       "        } else {\n",
+       "            this._key = event.which;\n",
+       "        }\n",
+       "    }\n",
+       "    if (name === 'key_release') {\n",
+       "        this._key = null;\n",
+       "    }\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which !== 17) {\n",
+       "        value += 'ctrl+';\n",
+       "    }\n",
+       "    if (event.altKey && event.which !== 18) {\n",
+       "        value += 'alt+';\n",
+       "    }\n",
+       "    if (event.shiftKey && event.which !== 16) {\n",
+       "        value += 'shift+';\n",
+       "    }\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+       "    return false;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+       "    if (name === 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message('toolbar_button', { name: name });\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "\n",
+       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+       "// prettier-ignore\n",
+       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";/* global mpl */\n",
+       "\n",
+       "var comm_websocket_adapter = function (comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function () {\n",
+       "        comm.close();\n",
+       "    };\n",
+       "    ws.send = function (m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function (msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data']);\n",
+       "    });\n",
+       "    return ws;\n",
+       "};\n",
+       "\n",
+       "mpl.mpl_figure_comm = function (comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = document.getElementById(id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm);\n",
+       "\n",
+       "    function ondownload(figure, _format) {\n",
+       "        window.open(figure.canvas.toDataURL());\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element;\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error('Failed to find cell for figure', id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "    fig.cell_info[0].output_area.element.on(\n",
+       "        'cleared',\n",
+       "        { fig: fig },\n",
+       "        fig._remove_fig_handler\n",
+       "    );\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+       "    var width = fig.canvas.width / fig.ratio;\n",
+       "    fig.cell_info[0].output_area.element.off(\n",
+       "        'cleared',\n",
+       "        fig._remove_fig_handler\n",
+       "    );\n",
+       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable();\n",
+       "    fig.parent_element.innerHTML =\n",
+       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "    fig.close_ws(fig, msg);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width / this.ratio;\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] =\n",
+       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function () {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message('ack', {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () {\n",
+       "        fig.push_to_output();\n",
+       "    }, 1000);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function () {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var toolbar = document.createElement('div');\n",
+       "    toolbar.classList = 'btn-toolbar';\n",
+       "    this.root.appendChild(toolbar);\n",
+       "\n",
+       "    function on_click_closure(name) {\n",
+       "        return function (_event) {\n",
+       "            return fig.toolbar_button_onclick(name);\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    function on_mouseover_closure(tooltip) {\n",
+       "        return function (event) {\n",
+       "            if (!event.currentTarget.disabled) {\n",
+       "                return fig.toolbar_button_onmouseover(tooltip);\n",
+       "            }\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    fig.buttons = {};\n",
+       "    var buttonGroup = document.createElement('div');\n",
+       "    buttonGroup.classList = 'btn-group';\n",
+       "    var button;\n",
+       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            /* Instead of a spacer, we start a new button group. */\n",
+       "            if (buttonGroup.hasChildNodes()) {\n",
+       "                toolbar.appendChild(buttonGroup);\n",
+       "            }\n",
+       "            buttonGroup = document.createElement('div');\n",
+       "            buttonGroup.classList = 'btn-group';\n",
+       "            continue;\n",
+       "        }\n",
+       "\n",
+       "        button = fig.buttons[name] = document.createElement('button');\n",
+       "        button.classList = 'btn btn-default';\n",
+       "        button.href = '#';\n",
+       "        button.title = name;\n",
+       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+       "        button.addEventListener('click', on_click_closure(method_name));\n",
+       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+       "        buttonGroup.appendChild(button);\n",
+       "    }\n",
+       "\n",
+       "    if (buttonGroup.hasChildNodes()) {\n",
+       "        toolbar.appendChild(buttonGroup);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = document.createElement('span');\n",
+       "    status_bar.classList = 'mpl-message pull-right';\n",
+       "    toolbar.appendChild(status_bar);\n",
+       "    this.message = status_bar;\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = document.createElement('div');\n",
+       "    buttongrp.classList = 'btn-group inline pull-right';\n",
+       "    button = document.createElement('button');\n",
+       "    button.classList = 'btn btn-mini btn-primary';\n",
+       "    button.href = '#';\n",
+       "    button.title = 'Stop Interaction';\n",
+       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+       "    button.addEventListener('click', function (_evt) {\n",
+       "        fig.handle_close(fig, {});\n",
+       "    });\n",
+       "    button.addEventListener(\n",
+       "        'mouseover',\n",
+       "        on_mouseover_closure('Stop Interaction')\n",
+       "    );\n",
+       "    buttongrp.appendChild(button);\n",
+       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+       "    var fig = event.data.fig;\n",
+       "    if (event.target !== this) {\n",
+       "        // Ignore bubbled events from children.\n",
+       "        return;\n",
+       "    }\n",
+       "    fig.close_ws(fig, {});\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function (el) {\n",
+       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.setAttribute('tabindex', 0);\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    } else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager) {\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "    }\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which === 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "};\n",
+       "\n",
+       "mpl.find_output_cell = function (html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i = 0; i < ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code') {\n",
+       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] === html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel !== null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target(\n",
+       "        'matplotlib',\n",
+       "        mpl.mpl_figure_comm\n",
+       "    );\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\" width=\"500\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "run_spans = {\n",
+    "    28: (4.35, 70, 120),\n",
+    "#    29: (3.10, 70, 120), Data is missing initial quiet period\n",
+    "    30: (7.04, 40, 120),\n",
+    "    31: (7.57, 30, 100),\n",
+    "    32: (10.4, 40, 90),\n",
+    "    33: (16.1, 40, 75),\n",
+    "    34: (8.62, 20, 80),\n",
+    "    37: (6.67, 20, 90),\n",
+    "    38: (9.43, 20, 80),\n",
+    "    39: (13.1, 20, 85),\n",
+    "}\n",
+    "\n",
+    "def plot_acceleration(runs, figsize=None, save=None):\n",
+    "    acc_theory, acc_meas, acc_meas_err_tot, acc_meas_err_x, acc_meas_err_y, freqs = [], [], [], [], [], []\n",
+    "    for run_id, (freq_meas, t_start, t_end) in sorted(run_spans.items(), key=lambda x: x[1][0]):\n",
+    "        freqs.append(freq_meas)\n",
+    "        omegan = 2*np.pi*freq_meas# angular velocity\n",
+    "        acc = omegan**2 * r_mems # m/s^2\n",
+    "        acc_theory.append(acc / g)\n",
+    "        \n",
+    "        t, y, packet_delay, packet_times = load_run(run_id, plot=False)\n",
+    "        data_slice = y[(t > t_start/60) & (t < t_end/60)] / mems_lsb_per_g\n",
+    "        silence_slice = y[t < 10/60] / mems_lsb_per_g\n",
+    "        acc_meas.append(data_slice.mean() - silence_slice.mean())\n",
+    "        \n",
+    "        freq_meas_delta = 0.5 # Hz estimated\n",
+    "        delta_due_to_f = 2*4*(np.pi**2)*freq_meas*r_mems*freq_meas_delta / g\n",
+    "        #\n",
+    "        # Absolute offset errors are corrected by subtracting the silence period at the beginning. Sensor noise\n",
+    "        # is measured directly from the data and includes mechanical noise due to device vibrations. We have to\n",
+    "        # account for sensitivity error (incorrect scaling of all measurements) and nonlinearity error\n",
+    "        # (per-measurement scale error) here.\n",
+    "        #\n",
+    "        # We can safely ignore sensor temperature drift.\n",
+    "        #\n",
+    "        mems_nonl_err = 0.01\n",
+    "        mems_sens_err = 0.05\n",
+    "        mems_position_tol = 2e-3 # m\n",
+    "        mems_position_err = omegan**2 * mems_position_tol / g\n",
+    "        data_err_sq = data_slice.std()**2 + mems_nonl_err**2 + mems_sens_err**2 + mems_position_err**2\n",
+    "        err = np.sqrt(delta_due_to_f**2 + data_err_sq)\n",
+    "        #print(f'{delta_due_to_f=} {data_slice.std()=} {err=}')\n",
+    "        \n",
+    "        acc_meas_err_tot.append(err)\n",
+    "        acc_meas_err_x.append(freq_meas_delta)\n",
+    "        acc_meas_err_y.append(np.sqrt(data_err_sq))\n",
+    "\n",
+    "    acc_meas = np.array(acc_meas)\n",
+    "    acc_meas_std = np.array(acc_meas_err_tot)\n",
+    "    \n",
+    "    fig, ax = plt.subplots(figsize=figsize)\n",
+    "    #ax.plot(freqs, acc_theory, label='Theory')\n",
+    "    \n",
+    "    tfreqs = np.linspace(0, 17, 1000)\n",
+    "    ax.plot(tfreqs, (2*np.pi*tfreqs)**2 * r_mems / g, label='Theory')\n",
+    "    \n",
+    "    ax.fill_between(freqs, acc_meas-acc_meas_err_tot, acc_meas+acc_meas_err_tot, color='orange', alpha=0.2, zorder=1)\n",
+    "    ax.errorbar(freqs, acc_meas, xerr=acc_meas_err_x, yerr=acc_meas_err_y, marker='.', label='Measurements', zorder=1)\n",
+    "\n",
+    "    ax.grid()\n",
+    "    ax.set_xlabel('$f\\;[Hz]$')\n",
+    "    ax2 = ax.twiny()\n",
+    "    x1, x2 = ax.get_xlim()\n",
+    "    ax2.set_xlim((x1*60, x2*60))\n",
+    "    ax2.set_xlabel('$f\\;[rpm]$')\n",
+    "    ax.set_ylabel('$a\\;[g]$')\n",
+    "    ax3 = ax.twinx()\n",
+    "    y1, y2 = ax.get_ylim()\n",
+    "    ax3.set_ylim(y1*g, y2*g)\n",
+    "    ax3.set_ylabel('$a\\;[ms^-1]$')\n",
+    "\n",
+    "    ax.legend()\n",
+    "    fig.tight_layout()\n",
+    "    if save:\n",
+    "        fig.savefig(save)\n",
+    "    \n",
+    "plot_acceleration(run_spans, figsize=(5, 3), save='fig-acc-theory-meas.pdf')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
    "metadata": {
     "scrolled": false
    },
@@ -4250,7 +5366,7 @@
        "4.3273542600896855"
       ]
      },
-     "execution_count": 957,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4296,7 +5412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 958,
+   "execution_count": 13,
    "metadata": {
     "scrolled": false
    },
@@ -5294,7 +6410,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 959,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -6270,10 +7386,10 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7f3e0e5af160>]"
+       "[<matplotlib.lines.Line2D at 0x7f2d6fc88040>]"
       ]
      },
-     "execution_count": 959,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -6287,7 +7403,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1000,
+   "execution_count": 15,
    "metadata": {
     "scrolled": false
    },
@@ -7488,7 +8604,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 995,
+   "execution_count": 89,
    "metadata": {},
    "outputs": [
     {
@@ -8452,7 +9568,1027 @@
     {
      "data": {
       "text/html": [
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\" 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\" width=\"500\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " ===== Run 34: =====\n",
+      "Loading run #34 with 2714 packets total, 121 distinct over 97.30304408073425s\n",
+      "Packet length: 40\n",
+      "Very approximate lower bound on baudrate: 129032.25806451612 bd\n",
+      "Sequence number range: 165 ... 287\n",
+      "interval: 0.11474772130686393\n",
+      "scores: [-0.030846569646590577, -0.017939041958299002, 0.007585993694854823, 0.013487796252691883, 0.01286325763359304, 0.012345763316803614, 0.011619541945226932, 0.010974011837158768, 0.010396432266781988]\n",
+      "argmin: 1\n",
+      "min score -0.030846569646590577 -0.09545980709610284\n",
+      "Average speed of rotation: 8.71 Hz / 523 rpm\n",
+      "\n",
+      "    f_meas = 8.62 Hz; f_est = 8.71 Hz\n",
+      "    Δabs = 0.09 Hz; Δrel = +1.1 %\n"
+     ]
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(5, 3))\n",
+    "run_id = 34\n",
+    "freq_meas, t_start, t_end = run_spans[run_id]\n",
+    "\n",
+    "print()\n",
+    "print(f' ===== Run {run_id}: =====')\n",
+    "t, y, packet_delay, packet_times = load_run(run_id, plot=False)\n",
+    "freq_est = estimate_freq_delay(packet_delay, packet_times, (t_start, t_end), ax=ax)\n",
+    "#ax.set_title(f'Run {run_id} @ $f_{{meas}} = {freq_meas:02.2f} Hz$ / $f_{{est}} = {freq_est:02.2f} Hz$')\n",
+    "print()\n",
+    "print(f'    f_meas = {freq_meas:02.2f} Hz; f_est = {freq_est:02.2f} Hz')\n",
+    "delta_abs = freq_est - freq_meas\n",
+    "delta_rel = freq_est/freq_meas-1\n",
+    "deltas.append((delta_abs, delta_rel))\n",
+    "print(f'    Δabs = {delta_abs:02.2f} Hz; Δrel = {delta_rel*100:+.1f} %')\n",
+    "\n",
+    "ax.set_ylabel(r'$\\Delta t\\;[s]$')\n",
+    "ax.set_xlabel(r'Cumulative packets')\n",
+    "\n",
+    "fig.tight_layout()\n",
+    "fig.savefig('fig-comms-delays.pdf')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "/* global mpl */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "mpl.get_websocket_type = function () {\n",
+       "    if (typeof WebSocket !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert(\n",
+       "            'Your browser does not have WebSocket support. ' +\n",
+       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "                'Firefox 4 and 5 are also supported but you ' +\n",
+       "                'have to enable WebSockets in about:config.'\n",
+       "        );\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById('mpl-warnings');\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent =\n",
+       "                'This browser does not support binary websocket messages. ' +\n",
+       "                'Performance may be slow.';\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = document.createElement('div');\n",
+       "    this.root.setAttribute('style', 'display: inline-block');\n",
+       "    this._root_extra_style(this.root);\n",
+       "\n",
+       "    parent_element.appendChild(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen = function () {\n",
+       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+       "        fig.send_message('send_image_mode', {});\n",
+       "        if (fig.ratio !== 1) {\n",
+       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+       "        }\n",
+       "        fig.send_message('refresh', {});\n",
+       "    };\n",
+       "\n",
+       "    this.imageObj.onload = function () {\n",
+       "        if (fig.image_mode === 'full') {\n",
+       "            // Full images could contain transparency (where diff images\n",
+       "            // almost always do), so we need to clear the canvas so that\n",
+       "            // there is no ghosting.\n",
+       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "        }\n",
+       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "    };\n",
+       "\n",
+       "    this.imageObj.onunload = function () {\n",
+       "        fig.ws.close();\n",
+       "    };\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function () {\n",
+       "    var titlebar = document.createElement('div');\n",
+       "    titlebar.classList =\n",
+       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+       "    var titletext = document.createElement('div');\n",
+       "    titletext.classList = 'ui-dialog-title';\n",
+       "    titletext.setAttribute(\n",
+       "        'style',\n",
+       "        'width: 100%; text-align: center; padding: 3px;'\n",
+       "    );\n",
+       "    titlebar.appendChild(titletext);\n",
+       "    this.root.appendChild(titlebar);\n",
+       "    this.header = titletext;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function () {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+       "    canvas_div.setAttribute(\n",
+       "        'style',\n",
+       "        'border: 1px solid #ddd;' +\n",
+       "            'box-sizing: content-box;' +\n",
+       "            'clear: both;' +\n",
+       "            'min-height: 1px;' +\n",
+       "            'min-width: 1px;' +\n",
+       "            'outline: 0;' +\n",
+       "            'overflow: hidden;' +\n",
+       "            'position: relative;' +\n",
+       "            'resize: both;'\n",
+       "    );\n",
+       "\n",
+       "    function on_keyboard_event_closure(name) {\n",
+       "        return function (event) {\n",
+       "            return fig.key_event(event, name);\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.addEventListener(\n",
+       "        'keydown',\n",
+       "        on_keyboard_event_closure('key_press')\n",
+       "    );\n",
+       "    canvas_div.addEventListener(\n",
+       "        'keyup',\n",
+       "        on_keyboard_event_closure('key_release')\n",
+       "    );\n",
+       "\n",
+       "    this._canvas_extra_style(canvas_div);\n",
+       "    this.root.appendChild(canvas_div);\n",
+       "\n",
+       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
+       "    canvas.classList.add('mpl-canvas');\n",
+       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+       "\n",
+       "    this.context = canvas.getContext('2d');\n",
+       "\n",
+       "    var backingStore =\n",
+       "        this.context.backingStorePixelRatio ||\n",
+       "        this.context.webkitBackingStorePixelRatio ||\n",
+       "        this.context.mozBackingStorePixelRatio ||\n",
+       "        this.context.msBackingStorePixelRatio ||\n",
+       "        this.context.oBackingStorePixelRatio ||\n",
+       "        this.context.backingStorePixelRatio ||\n",
+       "        1;\n",
+       "\n",
+       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+       "        'canvas'\n",
+       "    ));\n",
+       "    rubberband_canvas.setAttribute(\n",
+       "        'style',\n",
+       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+       "    );\n",
+       "\n",
+       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+       "    if (this.ResizeObserver === undefined) {\n",
+       "        if (window.ResizeObserver !== undefined) {\n",
+       "            this.ResizeObserver = window.ResizeObserver;\n",
+       "        } else {\n",
+       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+       "            this.ResizeObserver = obs.ResizeObserver;\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+       "        var nentries = entries.length;\n",
+       "        for (var i = 0; i < nentries; i++) {\n",
+       "            var entry = entries[i];\n",
+       "            var width, height;\n",
+       "            if (entry.contentBoxSize) {\n",
+       "                if (entry.contentBoxSize instanceof Array) {\n",
+       "                    // Chrome 84 implements new version of spec.\n",
+       "                    width = entry.contentBoxSize[0].inlineSize;\n",
+       "                    height = entry.contentBoxSize[0].blockSize;\n",
+       "                } else {\n",
+       "                    // Firefox implements old version of spec.\n",
+       "                    width = entry.contentBoxSize.inlineSize;\n",
+       "                    height = entry.contentBoxSize.blockSize;\n",
+       "                }\n",
+       "            } else {\n",
+       "                // Chrome <84 implements even older version of spec.\n",
+       "                width = entry.contentRect.width;\n",
+       "                height = entry.contentRect.height;\n",
+       "            }\n",
+       "\n",
+       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
+       "            // the canvas container.\n",
+       "            if (entry.devicePixelContentBoxSize) {\n",
+       "                // Chrome 84 implements new version of spec.\n",
+       "                canvas.setAttribute(\n",
+       "                    'width',\n",
+       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
+       "                );\n",
+       "                canvas.setAttribute(\n",
+       "                    'height',\n",
+       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
+       "                );\n",
+       "            } else {\n",
+       "                canvas.setAttribute('width', width * fig.ratio);\n",
+       "                canvas.setAttribute('height', height * fig.ratio);\n",
+       "            }\n",
+       "            canvas.setAttribute(\n",
+       "                'style',\n",
+       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
+       "            );\n",
+       "\n",
+       "            rubberband_canvas.setAttribute('width', width);\n",
+       "            rubberband_canvas.setAttribute('height', height);\n",
+       "\n",
+       "            // And update the size in Python. We ignore the initial 0/0 size\n",
+       "            // that occurs as the element is placed into the DOM, which should\n",
+       "            // otherwise not happen due to the minimum size styling.\n",
+       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+       "                fig.request_resize(width, height);\n",
+       "            }\n",
+       "        }\n",
+       "    });\n",
+       "    this.resizeObserverInstance.observe(canvas_div);\n",
+       "\n",
+       "    function on_mouse_event_closure(name) {\n",
+       "        return function (event) {\n",
+       "            return fig.mouse_event(event, name);\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    rubberband_canvas.addEventListener(\n",
+       "        'mousedown',\n",
+       "        on_mouse_event_closure('button_press')\n",
+       "    );\n",
+       "    rubberband_canvas.addEventListener(\n",
+       "        'mouseup',\n",
+       "        on_mouse_event_closure('button_release')\n",
+       "    );\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband_canvas.addEventListener(\n",
+       "        'mousemove',\n",
+       "        on_mouse_event_closure('motion_notify')\n",
+       "    );\n",
+       "\n",
+       "    rubberband_canvas.addEventListener(\n",
+       "        'mouseenter',\n",
+       "        on_mouse_event_closure('figure_enter')\n",
+       "    );\n",
+       "    rubberband_canvas.addEventListener(\n",
+       "        'mouseleave',\n",
+       "        on_mouse_event_closure('figure_leave')\n",
+       "    );\n",
+       "\n",
+       "    canvas_div.addEventListener('wheel', function (event) {\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        on_mouse_event_closure('scroll')(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.appendChild(canvas);\n",
+       "    canvas_div.appendChild(rubberband_canvas);\n",
+       "\n",
+       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+       "    this.rubberband_context.strokeStyle = '#000000';\n",
+       "\n",
+       "    this._resize_canvas = function (width, height, forward) {\n",
+       "        if (forward) {\n",
+       "            canvas_div.style.width = width + 'px';\n",
+       "            canvas_div.style.height = height + 'px';\n",
+       "        }\n",
+       "    };\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+       "        event.preventDefault();\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus() {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function () {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var toolbar = document.createElement('div');\n",
+       "    toolbar.classList = 'mpl-toolbar';\n",
+       "    this.root.appendChild(toolbar);\n",
+       "\n",
+       "    function on_click_closure(name) {\n",
+       "        return function (_event) {\n",
+       "            return fig.toolbar_button_onclick(name);\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    function on_mouseover_closure(tooltip) {\n",
+       "        return function (event) {\n",
+       "            if (!event.currentTarget.disabled) {\n",
+       "                return fig.toolbar_button_onmouseover(tooltip);\n",
+       "            }\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    fig.buttons = {};\n",
+       "    var buttonGroup = document.createElement('div');\n",
+       "    buttonGroup.classList = 'mpl-button-group';\n",
+       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            /* Instead of a spacer, we start a new button group. */\n",
+       "            if (buttonGroup.hasChildNodes()) {\n",
+       "                toolbar.appendChild(buttonGroup);\n",
+       "            }\n",
+       "            buttonGroup = document.createElement('div');\n",
+       "            buttonGroup.classList = 'mpl-button-group';\n",
+       "            continue;\n",
+       "        }\n",
+       "\n",
+       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
+       "        button.classList = 'mpl-widget';\n",
+       "        button.setAttribute('role', 'button');\n",
+       "        button.setAttribute('aria-disabled', 'false');\n",
+       "        button.addEventListener('click', on_click_closure(method_name));\n",
+       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+       "\n",
+       "        var icon_img = document.createElement('img');\n",
+       "        icon_img.src = '_images/' + image + '.png';\n",
+       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+       "        icon_img.alt = tooltip;\n",
+       "        button.appendChild(icon_img);\n",
+       "\n",
+       "        buttonGroup.appendChild(button);\n",
+       "    }\n",
+       "\n",
+       "    if (buttonGroup.hasChildNodes()) {\n",
+       "        toolbar.appendChild(buttonGroup);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker = document.createElement('select');\n",
+       "    fmt_picker.classList = 'mpl-widget';\n",
+       "    toolbar.appendChild(fmt_picker);\n",
+       "    this.format_dropdown = fmt_picker;\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = document.createElement('option');\n",
+       "        option.selected = fmt === mpl.default_extension;\n",
+       "        option.innerHTML = fmt;\n",
+       "        fmt_picker.appendChild(option);\n",
+       "    }\n",
+       "\n",
+       "    var status_bar = document.createElement('span');\n",
+       "    status_bar.classList = 'mpl-message';\n",
+       "    toolbar.appendChild(status_bar);\n",
+       "    this.message = status_bar;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function (type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function () {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+       "        fig.send_message('refresh', {});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+       "    var x0 = msg['x0'] / fig.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+       "    var x1 = msg['x1'] / fig.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0,\n",
+       "        0,\n",
+       "        fig.canvas.width / fig.ratio,\n",
+       "        fig.canvas.height / fig.ratio\n",
+       "    );\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch (cursor) {\n",
+       "        case 0:\n",
+       "            cursor = 'pointer';\n",
+       "            break;\n",
+       "        case 1:\n",
+       "            cursor = 'default';\n",
+       "            break;\n",
+       "        case 2:\n",
+       "            cursor = 'crosshair';\n",
+       "            break;\n",
+       "        case 3:\n",
+       "            cursor = 'move';\n",
+       "            break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+       "    for (var key in msg) {\n",
+       "        if (!(key in fig.buttons)) {\n",
+       "            continue;\n",
+       "        }\n",
+       "        fig.buttons[key].disabled = !msg[key];\n",
+       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+       "    if (msg['mode'] === 'PAN') {\n",
+       "        fig.buttons['Pan'].classList.add('active');\n",
+       "        fig.buttons['Zoom'].classList.remove('active');\n",
+       "    } else if (msg['mode'] === 'ZOOM') {\n",
+       "        fig.buttons['Pan'].classList.remove('active');\n",
+       "        fig.buttons['Zoom'].classList.add('active');\n",
+       "    } else {\n",
+       "        fig.buttons['Pan'].classList.remove('active');\n",
+       "        fig.buttons['Zoom'].classList.remove('active');\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function () {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message('ack', {});\n",
+       "};\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = 'image/png';\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src\n",
+       "                );\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data\n",
+       "            );\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        } else if (\n",
+       "            typeof evt.data === 'string' &&\n",
+       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+       "        ) {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig['handle_' + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\n",
+       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
+       "                msg\n",
+       "            );\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\n",
+       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+       "                    e,\n",
+       "                    e.stack,\n",
+       "                    msg\n",
+       "                );\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "};\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function (e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e) {\n",
+       "        e = window.event;\n",
+       "    }\n",
+       "    if (e.target) {\n",
+       "        targ = e.target;\n",
+       "    } else if (e.srcElement) {\n",
+       "        targ = e.srcElement;\n",
+       "    }\n",
+       "    if (targ.nodeType === 3) {\n",
+       "        // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "    }\n",
+       "\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    var boundingRect = targ.getBoundingClientRect();\n",
+       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+       "\n",
+       "    return { x: x, y: y };\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys(original) {\n",
+       "    return Object.keys(original).reduce(function (obj, key) {\n",
+       "        if (typeof original[key] !== 'object') {\n",
+       "            obj[key] = original[key];\n",
+       "        }\n",
+       "        return obj;\n",
+       "    }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event);\n",
+       "\n",
+       "    if (name === 'button_press') {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * this.ratio;\n",
+       "    var y = canvas_pos.y * this.ratio;\n",
+       "\n",
+       "    this.send_message(name, {\n",
+       "        x: x,\n",
+       "        y: y,\n",
+       "        button: event.button,\n",
+       "        step: event.step,\n",
+       "        guiEvent: simpleKeys(event),\n",
+       "    });\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function (event, name) {\n",
+       "    // Prevent repeat events\n",
+       "    if (name === 'key_press') {\n",
+       "        if (event.which === this._key) {\n",
+       "            return;\n",
+       "        } else {\n",
+       "            this._key = event.which;\n",
+       "        }\n",
+       "    }\n",
+       "    if (name === 'key_release') {\n",
+       "        this._key = null;\n",
+       "    }\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which !== 17) {\n",
+       "        value += 'ctrl+';\n",
+       "    }\n",
+       "    if (event.altKey && event.which !== 18) {\n",
+       "        value += 'alt+';\n",
+       "    }\n",
+       "    if (event.shiftKey && event.which !== 16) {\n",
+       "        value += 'shift+';\n",
+       "    }\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+       "    return false;\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+       "    if (name === 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message('toolbar_button', { name: name });\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "\n",
+       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+       "// prettier-ignore\n",
+       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";/* global mpl */\n",
+       "\n",
+       "var comm_websocket_adapter = function (comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function () {\n",
+       "        comm.close();\n",
+       "    };\n",
+       "    ws.send = function (m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function (msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data']);\n",
+       "    });\n",
+       "    return ws;\n",
+       "};\n",
+       "\n",
+       "mpl.mpl_figure_comm = function (comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = document.getElementById(id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm);\n",
+       "\n",
+       "    function ondownload(figure, _format) {\n",
+       "        window.open(figure.canvas.toDataURL());\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element;\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error('Failed to find cell for figure', id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "    fig.cell_info[0].output_area.element.on(\n",
+       "        'cleared',\n",
+       "        { fig: fig },\n",
+       "        fig._remove_fig_handler\n",
+       "    );\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+       "    var width = fig.canvas.width / fig.ratio;\n",
+       "    fig.cell_info[0].output_area.element.off(\n",
+       "        'cleared',\n",
+       "        fig._remove_fig_handler\n",
+       "    );\n",
+       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable();\n",
+       "    fig.parent_element.innerHTML =\n",
+       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "    fig.close_ws(fig, msg);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width / this.ratio;\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] =\n",
+       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function () {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message('ack', {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () {\n",
+       "        fig.push_to_output();\n",
+       "    }, 1000);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function () {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var toolbar = document.createElement('div');\n",
+       "    toolbar.classList = 'btn-toolbar';\n",
+       "    this.root.appendChild(toolbar);\n",
+       "\n",
+       "    function on_click_closure(name) {\n",
+       "        return function (_event) {\n",
+       "            return fig.toolbar_button_onclick(name);\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    function on_mouseover_closure(tooltip) {\n",
+       "        return function (event) {\n",
+       "            if (!event.currentTarget.disabled) {\n",
+       "                return fig.toolbar_button_onmouseover(tooltip);\n",
+       "            }\n",
+       "        };\n",
+       "    }\n",
+       "\n",
+       "    fig.buttons = {};\n",
+       "    var buttonGroup = document.createElement('div');\n",
+       "    buttonGroup.classList = 'btn-group';\n",
+       "    var button;\n",
+       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            /* Instead of a spacer, we start a new button group. */\n",
+       "            if (buttonGroup.hasChildNodes()) {\n",
+       "                toolbar.appendChild(buttonGroup);\n",
+       "            }\n",
+       "            buttonGroup = document.createElement('div');\n",
+       "            buttonGroup.classList = 'btn-group';\n",
+       "            continue;\n",
+       "        }\n",
+       "\n",
+       "        button = fig.buttons[name] = document.createElement('button');\n",
+       "        button.classList = 'btn btn-default';\n",
+       "        button.href = '#';\n",
+       "        button.title = name;\n",
+       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+       "        button.addEventListener('click', on_click_closure(method_name));\n",
+       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+       "        buttonGroup.appendChild(button);\n",
+       "    }\n",
+       "\n",
+       "    if (buttonGroup.hasChildNodes()) {\n",
+       "        toolbar.appendChild(buttonGroup);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = document.createElement('span');\n",
+       "    status_bar.classList = 'mpl-message pull-right';\n",
+       "    toolbar.appendChild(status_bar);\n",
+       "    this.message = status_bar;\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = document.createElement('div');\n",
+       "    buttongrp.classList = 'btn-group inline pull-right';\n",
+       "    button = document.createElement('button');\n",
+       "    button.classList = 'btn btn-mini btn-primary';\n",
+       "    button.href = '#';\n",
+       "    button.title = 'Stop Interaction';\n",
+       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+       "    button.addEventListener('click', function (_evt) {\n",
+       "        fig.handle_close(fig, {});\n",
+       "    });\n",
+       "    button.addEventListener(\n",
+       "        'mouseover',\n",
+       "        on_mouseover_closure('Stop Interaction')\n",
+       "    );\n",
+       "    buttongrp.appendChild(button);\n",
+       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+       "    var fig = event.data.fig;\n",
+       "    if (event.target !== this) {\n",
+       "        // Ignore bubbled events from children.\n",
+       "        return;\n",
+       "    }\n",
+       "    fig.close_ws(fig, {});\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function (el) {\n",
+       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.setAttribute('tabindex', 0);\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    } else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager) {\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "    }\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which === 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "};\n",
+       "\n",
+       "mpl.find_output_cell = function (html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i = 0; i < ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code') {\n",
+       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] === html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel !== null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target(\n",
+       "        'matplotlib',\n",
+       "        mpl.mpl_figure_comm\n",
+       "    );\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" width=\"640\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -8467,7 +10603,7 @@
        "Text(0.5, 0, '$f\\\\;[Hz]$')"
       ]
      },
-     "execution_count": 995,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -8480,7 +10616,7 @@
     "\n",
     "#ax = ax.twinx()\n",
     "ax.grid()\n",
-    "ax.plot(freqs[:-1], [ delta_rel*100 for _delta_abs, delta_rel in deltas[:-1] ])#, color='orange')\n",
+    "ax.plot(freqs, [ delta_rel*100 for _delta_abs, delta_rel in deltas[:-1] ])#, color='orange')\n",
     "ax.set_ylabel('$\\Delta_{rel}\\;[\\%]$')\n",
     "\n",
     "ax.set_xlabel('$f\\;[Hz]$')"
@@ -8488,7 +10624,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 718,
+   "execution_count": 19,
    "metadata": {
     "scrolled": false
    },
@@ -9467,20 +11603,23 @@
    "source": [
     "fig, ax = plt.subplots()\n",
     "ax.grid()\n",
-    "ax.magnitude_spectrum(reassembled_values[ivl_start:ivl_end]/mems_lsb_per_g, Fs=10);"
+    "ax.magnitude_spectrum(y[ivl_start:ivl_end]/mems_lsb_per_g, Fs=10);"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 719,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Centrifugal acceleration at 4.31 Hz: 40.42 m/s^2 / 4.12 g\n",
-      "Centrifugal acceleration at 15.73 Hz: 537.19 m/s^2 / 54.78 g\n"
+     "ename": "NameError",
+     "evalue": "name 'largest_peak_f' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-20-312a4bb81e5c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mr_mems\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m55e-3\u001b[0m \u001b[0;31m# radius of our sensor from the axis of rotation in m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlargest_peak_f\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0momega\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpi\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mf\u001b[0m \u001b[0;31m# angular velocity\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mcentrifugal_acceleration\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0momega\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mr_mems\u001b[0m \u001b[0;31m# m/s^2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'largest_peak_f' is not defined"
      ]
     }
    ],
@@ -9500,45 +11639,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 720,
+   "execution_count": null,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Centrifugal acceleration at 0.10 Hz: 0.02 m/s^2 / 0.00 g\n",
-      "Centrifugal acceleration at 0.20 Hz: 0.09 m/s^2 / 0.01 g\n",
-      "Centrifugal acceleration at 0.50 Hz: 0.54 m/s^2 / 0.06 g\n",
-      "Centrifugal acceleration at 1.00 Hz: 2.17 m/s^2 / 0.22 g\n",
-      "Centrifugal acceleration at 1.50 Hz: 4.89 m/s^2 / 0.50 g\n",
-      "Centrifugal acceleration at 2.00 Hz: 8.69 m/s^2 / 0.89 g\n",
-      "Centrifugal acceleration at 2.50 Hz: 13.57 m/s^2 / 1.38 g\n",
-      "Centrifugal acceleration at 3.00 Hz: 19.54 m/s^2 / 1.99 g\n",
-      "Centrifugal acceleration at 3.50 Hz: 26.60 m/s^2 / 2.71 g\n",
-      "Centrifugal acceleration at 4.00 Hz: 34.74 m/s^2 / 3.54 g\n",
-      "Centrifugal acceleration at 4.50 Hz: 43.97 m/s^2 / 4.48 g\n",
-      "Centrifugal acceleration at 5.00 Hz: 54.28 m/s^2 / 5.54 g\n",
-      "Centrifugal acceleration at 6.00 Hz: 78.17 m/s^2 / 7.97 g\n",
-      "Centrifugal acceleration at 7.00 Hz: 106.39 m/s^2 / 10.85 g\n",
-      "Centrifugal acceleration at 8.00 Hz: 138.96 m/s^2 / 14.17 g\n",
-      "Centrifugal acceleration at 9.00 Hz: 175.88 m/s^2 / 17.93 g\n",
-      "Centrifugal acceleration at 10.00 Hz: 217.13 m/s^2 / 22.14 g\n",
-      "Centrifugal acceleration at 11.00 Hz: 262.73 m/s^2 / 26.79 g\n",
-      "Centrifugal acceleration at 12.00 Hz: 312.67 m/s^2 / 31.88 g\n",
-      "Centrifugal acceleration at 13.00 Hz: 366.95 m/s^2 / 37.42 g\n",
-      "Centrifugal acceleration at 14.00 Hz: 425.58 m/s^2 / 43.40 g\n",
-      "Centrifugal acceleration at 15.00 Hz: 488.55 m/s^2 / 49.82 g\n",
-      "Centrifugal acceleration at 16.00 Hz: 555.86 m/s^2 / 56.68 g\n",
-      "Centrifugal acceleration at 17.00 Hz: 627.51 m/s^2 / 63.99 g\n",
-      "Centrifugal acceleration at 18.00 Hz: 703.51 m/s^2 / 71.74 g\n",
-      "Centrifugal acceleration at 19.00 Hz: 783.84 m/s^2 / 79.93 g\n",
-      "Centrifugal acceleration at 20.00 Hz: 868.53 m/s^2 / 88.57 g\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "for fn in [0.1, 0.2, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0,\n",
     "           11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0]:\n",
@@ -9550,7 +11655,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 721,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -10514,7 +12619,7 @@
     {
      "data": {
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\" 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+       "<img 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AzA1A7AgAxAAkhiAqRmABRmAAJDEAEzNACzIAASAJAZgagZgQQYgACQxAFMzAAsyAAEgiQGYmgFYkAEIAEkMwNQMwIIMQABIYgCmZgAWZAACQBIDMDUDsCADEACSGICpGYAFGYAAkMQATM0ALMgABIAkBmBqBmBBBiAAJDEAUzMACzIAASCJAZiaAViQAQgASQzA1AzAggxAAEhiAKZmABZkAAJAEgMwNQOwIAMQAJIYgKkZgAUZgACQxABMzQAsyAAEgCQGYGoGYEEGIAAkMQBTMwALMgABIIkBmJoBWJABCABJDMDUDMCCDEAASGIApmYAFmQAAkASAzA1A7AgAxAAkhiAqRmABRmAAJDEAEzNACzIAASAJAZgagZgQQYgACQxAFMzAAsyAAEgiQGYmgFYkAEIAEkMwNQMwIIMQABIYgCmZgAWZAACQBIDMDUDsCADEACSGICpGYAFGYAAkMQATM0ALMgABIAkBmBqBmBBBiAAJDEAUzMACzIAASCJAZiaAViQAQgASQzA1AzAggxAAEhiAKZmABZkAAJAEgMwNQOwIAMQAJIYgKkZgAUZgACQxABMzQAsyAAEgCQGYGoGYEEGIAAkMQBTMwALMgABIIkBmJoBWJABCABJDMDUDMCCDEAASGIApmYAFmQAAkASAzA1A7AgAxAAkhiAqTXVANyxY0f09PREZ2dn9PX1xYEDB+b1vEOHDkVbW1v83u/93oJezwAEgCQGYGpNMwB37doVS5cujZ07d0atVovh4eHo7u6OkydPvuPzpqenY9WqVfGnf/qnBiAAvFsYgKk1zQDs7++PwcHBumu9vb0xMjLyjs/75Cc/GV/5yldidHTUAASAdwsDMLWmGIDnz5+Ptra22LNnT931zZs3x/r16y/7vL//+7+PO+64I/73f/93XgPw3LlzMTMzM2tqasoABIAMBmBqTTEAT506FVVVxcTERN317du3x5o1a+Z8zrFjx+J973tfHD16NCJiXgNwdHQ0qqp6GwMQAK4yAzC1phqAk5OTdde3bdsWa9eufdvj33zzzbjjjjviqaeemr3mO4AA8C5iAKbWFANwoT8Cfu2116Kqqmhra5u1ZMmS2WvPPffcvF7X7wEEgCQGYGpNMQAjLr4JZGhoqO7aunXr5nwTyIULF+KFF16oMzQ0FGvXro0XXngh/ud//mder2kAAkASAzC1phmAlz4GZmxsLGq1WmzZsiW6u7vjxIkTERExMjISGzduvOzzvQsYAN5FDMDUmmYARlz8IOiVK1dGR0dH9PX1xfj4+OzfGxgYiA0bNlz2uQYgALyLGICpNdUAbHQGIAAkMQBTMwALMgABIIkBmJoBWJABCABJDMDUDMCCDEAASGIApmYAFmQAAkASAzA1A7AgAxAAkhiAqRmABRmAAJDEAEzNACzIAASAJAZgagZgQQYgACQxAFMzAAsyAAEgiQGYmgFYkAEIAEkMwNQMwIIMQABIYgCmZgAWZAACQBIDMDUDsCADEACSGICpGYAFGYAAkMQATM0ALMgABIAkBmBqBmBBBiAAJDEAUzMACzIAASCJAZiaAViQAQgASQzA1AzAggxAAEhiAKZmABZkAAJAEgMwNQOwIAMQAJIYgKkZgAUZgACQxABMzQAsyAAEgCQGYGoGYEEGIAAkMQBTMwALMgABIIkBmJoBWJABCABJDMDUDMCCDEAASGIApmYAFmQAAkASAzA1A7AgAxAAkhiAqRmABRmAAJDEAEzNACzIAASAJAZgagZgQQYgACQxAFMzAAsyAAEgiQGYmgFYkAEIAEkMwNQMwIIMQABIYgCmZgAWZAACQBIDMDUDsCADEACSGICpGYAFGYAAkMQATM0ALMgABIAkBmBqBmBBBiAAJDEAUzMACzIAASCJAZiaAViQAQgASQzA1AzAggxAAEhiAKZmABZkAAJAEgMwNQOwIAMQAJIYgKkZgAUZgACQxABMzQAsyAAEgCQGYGoGYEEGIAAkMQBTMwALMgABIIkBmJoBWJABCABJDMDUDMCCDEAASGIApmYAFmQAAkASAzA1A7AgAxAAkhiAqRmABRmAAJDEAEzNACzIAASAJAZgagZgQQYgACQxAFMzAAsyAAEgiQGYmgFYkAEIAEkMwNQMwIIMQABIYgCmZgAWZAACQBIDMDUDsCADEACSGICpGYAFGYAAkMQATM0ALMgABIAkBmBqTTUAd+zYET09PdHZ2Rl9fX1x4MCByz529+7dcc8998Rv//Zvx3ve856466674plnnlnQ6xmAAJDEAEytaQbgrl27YunSpbFz586o1WoxPDwc3d3dcfLkyTkfPzw8HF/96lfj3//93+PYsWPxxS9+MZYuXRr/9V//Ne/XNAABIIkBmFrTDMD+/v4YHBysu9bb2xsjIyPz/mfcdttt8dd//dfzfrwBCABJDMDUmmIAnj9/Ptra2mLPnj111zdv3hzr16+f1z/jwoUL8Tu/8zvxt3/7t5d9zLlz52JmZmbW1NSUAQgAGQzA1JpiAJ46dSqqqoqJiYm669u3b481a9bM65/x+OOPx4033hg///nPL/uY0dHRqKrqbQxAALjKDMDUmmoATk5O1l3ftm1brF279tc+/+mnn47rr78+nn322Xd8nO8AAkCDGICpNcUALPkR8K5du6Krqyv+9V//dcGv6/cAAkASAzC1phiAERffBDI0NFR3bd26de/4JpCnn346li1bFnv37r2i1zQAASCJAZha0wzASx8DMzY2FrVaLbZs2RLd3d1x4sSJiIgYGRmJjRs3zj7+6aefjvb29tixY0ecOXNm1vT09Lxf0wAEgCQGYGpNMwAjLn4Q9MqVK6OjoyP6+vpifHx89u8NDAzEhg0bZv96w4YNc76hY2BgYN6vZwACQBIDMLWmGoCNzgAEgCQGYGoGYEEGIAAkMQBTMwALMgABIIkBmJoBWJABCABJDMDUDMCCDEAASGIApmYAFmQAAkASAzA1A7AgAxAAkhiAqRmABRmAAJDEAEzNACzIAASAJAZgagZgQQYgACQxAFMzAAsyAAEgiQGYmgFYkAEIAEkMwNQMwIIMQABIYgCmZgAWZAACQBIDMDUDsCADEACSGICpGYAFGYAAkMQATM0ALMgABIAkBmBqBmBBBiAAJDEAUzMACzIAASCJAZiaAViQAQgASQzA1AzAggxAAEhiAKZmABZkAAJAEgMwNQOwIAMQAJIYgKkZgAUZgACQxABMzQAsyAAEgCQGYGoGYEEGIAAkMQBTMwALMgABIIkBmJoBWJABCABJDMDUDMCCDEAASGIApmYAFmQAAkASAzA1A7AgAxAAkhiAqRmABRmAAJDEAEzNACzIAASAJAZgagZgQQYgACQxAFMzAAsyAAEgiQGYmgFYkAEIAEkMwNQMwIIMQABIYgCmZgAWZAACQBIDMDUDsCADEACSGICpGYAFGYAAkMQATM0ALMgABIAkBmBqBmBBBiAAJDEAUzMACzIAASCJAZiaAViQAQgASQzA1AzAggxAAEhiAKZmABZkAAJAEgMwNQOwIAMQAJIYgKkZgAUZgACQxABMzQAsyAAEgCQGYGoGYEEGIAAkMQBTMwALMgABIIkBmJoBWJABCABJDMDUDMCCDEAASGIApmYAFmQAAkASAzA1A7AgAxAAkhiAqRmABRmAAJDEAEzNACzIAASAJAZgagZgQQYgACQxAFMzAAsyAAEgiQGYmgFYkAEIAEkMwNQMwIIMQABIYgCmZgAWZAACQBIDMDUDsCADEACSGICpGYAFGYAAkMQATK2pBuCOHTuip6cnOjs7o6+vLw4cOPCOj9+/f3/09fVFZ2dn3HLLLfHUU08t6PUMQABIYgCm1jQDcNeuXbF06dLYuXNn1Gq1GB4eju7u7jh58uScj3/55Zfj+uuvj+Hh4ajVarFz585YunRpfO9735v3axqAAJDEAEytaQZgf39/DA4O1l3r7e2NkZGROR+/devW6O3trbu2adOmuOuuu+b9mgYgACQxAFNrigF4/vz5aGtriz179tRd37x5c6xfv37O59x9992xefPmumt79uyJ9vb2eOONN+Z8zrlz52JmZmbWT3/606iqKqampuquXxWvHo2ZZz8VM889HDP7/xIAWstzD1/8dfDVo1f919ipqamoqiqmp6evzhBZhDXFADx16lRUVRUTExN117dv3x5r1qyZ8zmrV6+O7du3112bmJiIqqri9Om5/29jdHQ0qqoCAJrA1NTU1Rkii7CmGoCTk5N117dt2xZr166d8zmrV6+Oxx57rO7aoUOHoqqqOHPmzJzP+dXvAL722mtx/PjxmJ6eTvu/k5TvLuKcnXNTcs7OuZlknvP09HRMTU3FhQsXrs4QWYQ1xQBs1I+AG9nMjN+f0Iicc2Nyzo3JOTcm59yYnHNuTTEAIy6+CWRoaKju2rp1697xTSDr1q2ruzY4OLigN4Fk5gu/MTnnxuScG5NzbkzOuTE559yaZgBe+hiYsbGxqNVqsWXLluju7o4TJ05ERMTIyEhs3Lhx9vGXPgbmkUceiVqtFmNjYwv+GJjMfOE3JufcmJxzY3LOjck5NybnnFvTDMCIix8EvXLlyujo6Ii+vr4YHx+f/XsDAwOxYcOGusfv378/br/99ujo6Iienp4FfxB0ZufOnYvR0dE4d+7ctb6Vps45Nybn3Jicc2Nyzo3JOefWVANQkiRJvz4DUJIkqcUyACVJklosA1CSJKnFMgAlSZJaLAPwGrVjx47o6emJzs7O6OvriwMHDlz2sT/60Y/m/CNsXnrppQbe8eJtIWcdcfGdZ1/60pfi/e9/f3R0dMSqVatibGysQXe7eFvIOQ8MDMz5NX3bbbc18I4XZwv9ev7Od74TH/rQh6Krqytuuumm+OxnPxu/+MUvGnS3i7eFnvPf/d3fRW9vbyxbtizWrFkT//AP/9CgO128jY+Px3333RfLly+Pqqpi7969v/Y5+/fvj76+vujs7IxbbrnlXfXpHYstA/AadOkzC3fu3Bm1Wi2Gh4eju7s7Tp48OefjLw3Ao0ePxpkzZ2a9+eabDb7zxddCzzoi4v77748777wznn322XjllVfi8OHDb/tzplXfQs95enq67mt5amoqbrzxxhgdHW3sjS+yFnrOBw8ejOuuuy6+8Y1vxMsvvxwHDx6MD3zgA/Gxj32swXe+uFroOT/55JPxnve8J3bt2hXHjx+Pf/qnf4obbrgh/uVf/qXBd764+sEPfhBf/vKXY/fu3fMagJc+v3d4eDhqtVrs3LnzXfX5vYstA/Aa1N/fH4ODg3XXent7L/unllwagK+99lojbq+pWuhZ//CHP4z3vve98ctf/rIRt9c0LfScf7W9e/fGkiVLZj+4XXO30HP+2te+FqtWraq79sQTT8SKFSvS7rEZWug5/8Ef/EH81V/9Vd214eHh+MM//MO0e2y25jMAt27dGr29vXXXNm3a9K75E7wWWwZgg7uSP7f40gDs6emJm266Kf7kT/4k/u3f/q0Rt7uou5KzHhoaig9/+MPxhS98IW6++eZYvXp1fP7zn4/XX3+9Ebe8KLuSc/7V7rvvvrj33nszbq9pupJznpiYiI6Ojti3b1+89dZb8eqrr8b69etj06ZNjbjlRdmVnHNfX1985Stfqbs2MjISS5cufVf82fKLofkMwLvvvjs2b95cd23Pnj3R3t7unK8gA7DBnTp1KqqqetuPFLdv3x5r1qyZ8zk/+clP4lvf+lb853/+Z0xOTsbQ0FAsWbKk7k860du7krP+yEc+Ep2dnfHRj340Dh8+HPv27YuVK1fGQw891IhbXpRdyTn//06fPh1tbW3xz//8z1m32BRd6Tl/97vfjRtuuCHa29ujqqq4//77/WL5Dl3JOX/xi1+Mm266KX784x/HW2+9Ff/xH/8R73vf+6Kqqjh9+nQjbnvRN58BuHr16ti+fXvdtYmJCed8hRmADe7Sf1wmJyfrrm/bti3Wrl0773/OfffdF3/2ZylsSCEAAAQsSURBVH92tW+vqbqSs7733ntj2bJlMT09PXtt9+7dsWTJEt8FvEylX9OPPfZY/NZv/VacP38+6xabois55xdffDGWL18ejz/+eDz//PPxzDPPxAc/+MF4+OGHG3HLi7IrOefXX389HnrooWhvb4+2tra4+eabY+vWrVFVVfz85z9vxG0v+uY7AB977LG6a4cOHYqqquLMmTOZt9eUGYAN7mr8uCzi4n+MfvX3Qqi+Kznrz3zmM3HrrbfWXavValFVVRw7diztXhdzJV/Tb731Vvzu7/5ubNmyJfMWm6IrOecHH3wwHnjggbprBw8e9B2Td6jk6/mNN96IqampePPNN2ffGHLhwoXM222a/Ai48RmA16D+/v4YGhqqu7Zu3bp5/4b5iIi/+Iu/iD/+4z++2rfWdC30rL/5zW9GV1dXnD17dvba97///bjuuut8B/AdutKv6Uu/v/WFF17IvL2maaHn/PGPfzw+8YlP1F2bnJyMqqri1KlTafe52Lsa/41ev359fOpTn7rat9a0zfdNIOvWrau7Njg46E0gV5gBeA269BEDY2NjUavVYsuWLdHd3T37DsiRkZHYuHHj7OP/5m/+Jvbu3RvHjh2L//7v/46RkZGoqip27959rf4VFk0LPeuzZ8/GihUr4oEHHogXX3wxxsfHY/Xq1fG5z33uWv0rLIoWes6XevDBB+POO+9s9O0u2hZ6zt/+9rejvb09nnzyyTh+/HgcOnQo7rjjjujv779W/wqLooWe89GjR+Mf//Ef49ixY3H48OH45Cc/GTfeeGO88sor1+jfYHF09uzZOHLkSBw5ciSqqoqvf/3rceTIkdmP2/nVc770MTCPPPJI1Gq1GBsb8zEwBRmA16gdO3bEypUro6OjI/r6+ure0DEwMBAbNmyY/euvfvWrceutt8ayZcviN3/zN+OP/uiPYt++fdfgrhdnCznriIiXXnop7rnnnujq6ooVK1bEo48+6rt/82ih5zw9PR1dXV3xrW99q8F3urhb6Dk/8cQTcdttt0VXV1csX748Pv3pT8fPfvazBt/14msh51yr1eL3f//3o6urK37jN34j/vzP/zx+8pOfXIO7Xlxd7g85GBgYiIi5v573798ft99+e3R0dERPT48Pgi7IAJQkSWqxDEBJkqQWywCUJElqsQxASZKkFssAlCRJarEMQEmSpBbLAJQkSWqxDEBJkqQWywCUJElqsQxASZKkFssAlCRJarEMQEmSpBbLAJQkSWqxDEBJkqQWywCUJElqsQxASZKkFssAlCRJarEMQEmSpBbLAJQkSWqxDEBJkqQWywCUJElqsQxASZKkFssAlCRJarEMQEmSpBbLAJQkSWqxDEBJkqQWywCUJElqsQxASZKkFssAlCRJarEMQEmSpBbLAJQkSWqxDEBJkqQW6/8A+/Ho8QQ9MsMAAAAASUVORK5CYII=\" width=\"640\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -10522,6 +12627,17 @@
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "ename": "NameError",
+     "evalue": "name 'centrifugal_acceleration' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-21-492c806a914e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxvspan\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mivl_start\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;36m60\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0msampling_rate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mivl_end\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;36m60\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0msampling_rate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'orange'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxhline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcentrifugal_acceleration\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'orange'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxhline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcentrifugal_acceleration2\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'orange'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0minterval\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'centrifugal_acceleration' is not defined"
+     ]
     }
    ],
    "source": [
author	jaseg <git@jaseg.de>	2021-03-25 12:15:38 +0100
committer	jaseg <git@jaseg.de>	2021-03-25 12:15:38 +0100
commit	2bb9aecfc62cb597155f50b6bf22131ab33cb301 (patch)
tree	ac7d5fd93cf0f22ecf29db69e423e98fdfbe2273 /prototype
parent	6fc8f236916c10811b8611f46edea4f3be2118b3 (diff)
download	ihsm-2bb9aecfc62cb597155f50b6bf22131ab33cb301.tar.gz ihsm-2bb9aecfc62cb597155f50b6bf22131ab33cb301.tar.bz2 ihsm-2bb9aecfc62cb597155f50b6bf22131ab33cb301.zip