Add classificationHEADmaster

2 files changed, 901 insertions, 4 deletions

diff --git a/main.py.example b/main.py.example
index b468d5d..562d4b6 100644
--- a/main.py.example
+++ b/main.py.example
@@ -108,6 +108,46 @@ def notify(scope, **kwargs):
     urequests.post(NOTIFICATION_URL, data=data, headers={'Content-Type': 'application/json'})
 
 
+def classify(trace, mean):
+    runs = []
+    cur_sign, cur_run = 1, 0
+    for x in trace[len(trace)//2:]:
+        x -= mean
+        if x > 0 and cur_sign < 0:
+            runs.append(cur_run)
+            cur_sign = 1
+            cur_run = 0
+        elif x < 0 and cur_sign >= 0:
+            runs.append(cur_run)
+            cur_sign = -1
+            cur_run = 0
+        else:
+            cur_run += 1
+    
+    run_means = []
+    for start in range(0, len(runs), 8):
+        k = 32
+        run_means.append(sum(runs[start:start+k])/k)
+        
+    bin_low, bin_high = 0, 0
+    for e in run_means:
+        if 0.05 < e < 0.25:
+            bin_low += 1
+        elif 0.30 < e < 0.50:
+            bin_high += 1
+    total = len(run_means)
+    
+    bin_low /= total
+    bin_high /= total
+    
+    if 0.3 < bin_low < 0.7 and 0.3 < bin_high < 0.7:
+        return 'downstairs'
+    elif bin_low < 0.3 and bin_high > 0.7:
+        return 'upstairs'
+    else:
+        return 'none'
+        
+
 def format_exc(limit=None, chain=True):
     return "".join(repr(i) for i in sys.exc_info())
 
@@ -124,11 +164,15 @@ def loop():
             now = unix_time()
             if (now - last_notification) > NOTIFICATION_COOLDOWN and rms > RMS_THRESHOLD:
                     old_capture = capture
+                    classification = classify(capture, mean)
                     rms = 0
                     while rms == 0:
                         time.sleep(0.1)
                     rms = 0
-                    notify('default', rms=rms, capture=[old_capture, capture])
+                    if classification in ('downstairs', 'upstairs'):
+                        notify('default', classification=classification, rms=rms, capture=[old_capture, capture])
+                    else:
+                        notify('info', info_msg='Unclassified capture', rms=rms, capture=[old_capture, capture])
                     last_notification = now
 
             if (now - last_heartbeat) > HEARTBEAT_INTERVAL:
diff --git a/viz.ipynb b/viz.ipynb
index 04a185d..ebbba6f 100644
--- a/viz.ipynb
+++ b/viz.ipynb
@@ -1699,7 +1699,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 103,
+   "execution_count": 125,
    "metadata": {
     "scrolled": false
    },
@@ -2487,7 +2487,7 @@
     {
      "data": {
       "text/html": [
-       "<img src=\"data:image/png;base64,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\" width=\"640\">"
+       "<img src=\"data:image/png;base64,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\" width=\"900\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -2498,7 +2498,7 @@
     }
    ],
    "source": [
-    "fig, axs = plt.subplots(2)\n",
+    "fig, axs = plt.subplots(2, figsize=(9,6))\n",
     "\n",
     "for ax, capture in zip(axs.flatten(), [data_downstairs[0] + data_downstairs[1], data_upstairs]):\n",
     "    cap = np.array(capture)\n",
@@ -2524,6 +2524,859 @@
     "            elif all(0.25 < x < 0.4 for x in h_len):\n",
     "                ax.axvspan(idx, idx + p*q, color='pink')"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\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('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",
+       "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 = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            if (mpl.ratio != 1) {\n",
+       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+       "            }\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        fig.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\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",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\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",
+       "\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",
+       "\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]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\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",
+       "    {\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.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",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\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",
+       "    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",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\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",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\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,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\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.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\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).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\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) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('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",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\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",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\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('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img src=\"data:image/png;base64,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\" width=\"900\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axs = plt.subplots(2, figsize=(9,6))\n",
+    "\n",
+    "for ax, capture in zip(axs.flatten(), [data_downstairs[0] + data_downstairs[1], data_upstairs]):\n",
+    "    cap = np.array(capture)\n",
+    "    cap -= np.mean(cap).astype(int)\n",
+    "    \n",
+    "    runs = []\n",
+    "    cur_sign, cur_run = 1, 0\n",
+    "    for x in cap[len(cap)//2:]:\n",
+    "        if x > 0 and cur_sign < 0:\n",
+    "            runs.append(cur_run)\n",
+    "            cur_sign = 1\n",
+    "            cur_run = 0\n",
+    "        elif x < 0 and cur_sign >= 0:\n",
+    "            runs.append(cur_run)\n",
+    "            cur_sign = -1\n",
+    "            cur_run = 0\n",
+    "        else:\n",
+    "            cur_run += 1\n",
+    "    \n",
+    "    run_means = []\n",
+    "    for start in range(0, len(runs), 8):\n",
+    "        k = 32\n",
+    "        run_means.append(sum(runs[start:start+k])/k)\n",
+    "        \n",
+    "    bin_low, bin_high = 0, 0\n",
+    "    for e in run_means:\n",
+    "        if 0.05 < e < 0.25:\n",
+    "            bin_low += 1\n",
+    "        elif 0.30 < e < 0.50:\n",
+    "            bin_high += 1\n",
+    "    total = len(run_means)\n",
+    "    \n",
+    "    bin_low /= total\n",
+    "    bin_high /= total\n",
+    "    \n",
+    "    if 0.3 < bin_low < 0.7 and 0.3 < bin_high < 0.7:\n",
+    "        res = 'downstairs'\n",
+    "    elif bin_low < 0.3 and bin_high > 0.7:\n",
+    "        res = 'upstairs'\n",
+    "    else:\n",
+    "        res = 'none'\n",
+    "        \n",
+    "    ax.text(0.98, 0.25, f'bin[l,h]: {bin_low:.3f} {bin_high:.3f}',\n",
+    "            transform=ax.transAxes, color='white', bbox=bbox, ha='right')\n",
+    "        \n",
+    "    ax.text(0.98, 0.1, f'res: {res}',\n",
+    "            transform=ax.transAxes, color='white', bbox=bbox, ha='right')\n",
+    "    \n",
+    "    ax.plot(run_means)"
+   ]
   }
  ],
  "metadata": {