From 5291970420560f232edaef99ef8149a4ccaffd64 Mon Sep 17 00:00:00 2001
From: jaseg <git@jaseg.net>
Date: Mon, 20 Jan 2020 11:52:25 +0100
Subject: Initial commit

---
 .gitignore      |    3 +
 Makefile        |   41 ++
 main.py.example |  125 ++++
 viz.ipynb       | 1719 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 4 files changed, 1888 insertions(+)
 create mode 100644 .gitignore
 create mode 100644 Makefile
 create mode 100644 main.py.example
 create mode 100644 viz.ipynb

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..705b185
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,3 @@
+*.mpy
+main.py
+.ipynb_checkpoints
diff --git a/Makefile b/Makefile
new file mode 100644
index 0000000..dd83a4b
--- /dev/null
+++ b/Makefile
@@ -0,0 +1,41 @@
+ESPTOOL = esptool.py
+# TOOL can be 'mpfshell' or 'ampy'
+TOOL = mpfshell
+FIRMWARE = esp32-idf3-20191220-v1.12.bin
+PORT = /dev/serial/by-id/usb-Silicon_Labs_CP2102_USB_to_UART_Bridge_Controller_0001-if00-port0
+SHELL = /bin/sh
+MPY := $(patsubst %.py,%.mpy,$(wildcard *.py))
+
+
+.PHONY: erase flash all install clean repl help sanitize
+
+all: $(MPY)
+
+%.mpy: %.py  ## Compile all python files
+	mpy-cross -march=xtensa -o $@ $<
+
+install: $(MPY)  ## Copy all compiled python files to the ESP32
+	if [ "${TOOL}" = "mpfshell" ]; then ${TOOL} -n -c "open ${PORT:/dev/%=%}; mput ${MPY}"; fi
+	if [ "${TOOL}" = "ampy" ]; then ${TOOL} -p ${PORT} put *.mpy; fi
+
+sanitize: main.py.example
+
+%.py.example: %.py
+	sed -n '/#### CONFIG ####/,/#### END ####/{/^#/p;d};p' $< > $@
+
+clean:  ## Delete all compiled python files
+	rm -f *.mpy
+
+erase:  ## Erase the flash of the ESP32
+	${ESPTOOL} --chip esp32 --port ${PORT} erase_flash
+
+flash:  ## Download micropython firmware and flash to ESP32
+	curl -sSLO https://micropython.org/resources/firmware/${FIRMWARE}
+	${ESPTOOL} --chip esp32 --port ${PORT} --baud 460800 write_flash -z 0x1000 ${FIRMWARE}
+
+repl: ## Start repl shell
+	if [ "${TOOL}" = "mpfshell" ]; then ${TOOL} -n -o ${BOARD} -c repl; fi
+	if [ "${TOOL}" != "mpfshell" ]; then screen /dev/${BOARD} ; fi
+
+help:  ## Show this help
+	grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
diff --git a/main.py.example b/main.py.example
new file mode 100644
index 0000000..3d2d0ad
--- /dev/null
+++ b/main.py.example
@@ -0,0 +1,125 @@
+
+from machine import Pin, ADC, Timer
+import network
+import time
+import ujson
+from uhashlib import sha256
+import binascii
+import math
+import urequests
+
+
+######################################################## CONFIG ########################################################
+# Wifi settings:
+# WIFI_ESSID = 'Your wifi ESSID (name)'
+# WIFI_PSK = 'Your wifi key'
+#
+# Notification settings:
+# NOTIFICATION_URL = 'https://automation.jaseg.de/notify/klingel'
+# NOTIFICATION_SECRET = b'Your notification proxy secret for this endpoint'
+#
+# NOTIFICATION_COOLDOWN = 60 # how long to wait after sending a notification before sending the next, in seconds
+#
+# Detection settings
+# MEAN_LEN = 8 # Window length for DC offset determination in seconds (1024ms to be exact)
+# RMS_THRESHOLD = 1000  # Threshold for rms detection threshold over 1s window in ADC counts
+######################################################### END ##########################################################
+
+
+def wifi_connect():
+    iface = network.WLAN(network.STA_IF)
+    if not iface.isconnected():
+        print('Connecting to wifi... ')
+        iface.active(True)
+        iface.connect(WIFI_ESSID, WIFI_PSK)
+        for i in range(20):
+            if iface.isconnected():
+                print('Wifi connected. IP config: ', iface.ifconfig())
+                break
+            time.sleep(0.5)
+        else:
+            print("Couldn't connect to wifi.")
+
+
+buf = [0] * 1024
+capture = None
+mean = 0
+rms = 0
+sample_tim = Timer(-1)
+
+def start_sampling():
+    global sample_tim
+    buf_pos = 0
+    buf_sum = 0
+    mean_acc = []
+
+    adc = ADC(Pin(34))
+    adc.atten(ADC.ATTN_11DB)
+
+    def sample_cb(tim):
+        global buf, mean, rms, capture
+        nonlocal adc, buf_pos, buf_sum, mean_acc
+
+        val = adc.read()
+        buf[buf_pos] = val
+        buf_sum += val
+
+        buf_pos += 1
+        if buf_pos == len(buf):
+            buf_pos = 0
+            mean_acc = [buf_sum/len(buf)] + mean_acc[:MEAN_LEN-1]
+            mean = sum(mean_acc)/len(mean_acc)
+            buf_sum = 0
+
+            rms = math.sqrt( sum( (x-mean)**2 for x in buf )/len(buf) )
+            capture = list(buf) # Make a copy
+
+    sample_tim.init(period=1, mode=Timer.PERIODIC, callback=sample_cb) # period in ms
+
+def uhmac(key, data):
+    blocksize = 64
+    key += bytes(64 - len(key))
+    tx = lambda s, x: bytes( b ^ x for b in s )
+    outer = sha256(tx(key, 0x5C))
+    inner = sha256(tx(key, 0x36))
+    inner.update(data)
+    outer.update(inner.digest())
+    return outer.digest()
+
+def usign(secret, payload=None, seq=None):
+    payload = {'time': int(time.time()), 'd': payload}
+    if seq is not None:
+        payload['seq'] = seq
+
+    payload = ujson.dumps(payload).encode()
+    auth = binascii.hexlify(uhmac(secret, payload))
+
+    return ujson.dumps({'payload': payload, 'auth': auth})
+
+def notify(**kwargs):
+    data = usign(NOTIFICATION_SECRET, kwargs)
+    print(time.time(), 'Notifying', NOTIFICATION_URL)
+    urequests.post(NOTIFICATION_URL, data=data, headers={'Content-Type': 'application/json'})
+
+def klingel_notify(rms, capture):
+    notify(rms=rms, capture=capture)
+
+def loop():
+    global rms, capture
+    while True:
+        if rms > RMS_THRESHOLD:
+            wifi_connect()
+            old_capture = capture
+            rms = 0
+            while rms == 0:
+                time.sleep(0.1)
+            rms = 0
+            klingel_notify(rms, [old_capture, capture])
+            time.sleep(NOTIFICATION_COOLDOWN)
+
+        time.sleep(0.1)
+
+wifi_connect()
+start_sampling()
+loop()
+
diff --git a/viz.ipynb b/viz.ipynb
new file mode 100644
index 0000000..18c464a
--- /dev/null
+++ b/viz.ipynb
@@ -0,0 +1,1719 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import statistics\n",
+    "import math\n",
+    "import numpy as np\n",
+    "\n",
+    "from matplotlib import pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# led off\n",
+    "data_led_off = [1753, 1763, 1738, 1696, 1653, 1666, 1773, 1616, 1725, 1616, 1583, 1663, 1605, 1654, 1616, 1606, 1664, 1575, 1647, 1647, 1598, 1682, 1630, 1673, 1699, 1702, 1686, 1753, 1635, 1715, 1810, 1636, 1715, 1638, 1712, 1559, 1619, 1683, 1692, 1636, 1639, 1647, 1691, 1759, 1787, 1702, 1783, 1728, 1647, 1795, 1681, 1616, 1622, 1561, 1627, 1583, 1663, 1655, 1757, 1639, 1698, 1616, 1627, 1615, 1663, 1628, 1669, 1758, 1651, 1651, 1754, 1590, 1615, 1647, 1660, 1625, 1626, 1648, 1729, 1776, 1584, 1712, 1705, 1689, 1667, 1685, 1517, 1648, 1730, 1715, 1632, 1669, 1745, 1664, 1727, 1720, 1678, 1679, 1599, 1723, 1739, 1635, 1611, 1655, 1715, 1658, 1694, 1616, 1779, 1691, 1535, 1762, 1600, 1642, 1648, 1664, 1657, 1678, 1574, 1587, 1695, 1612, 1666, 1571, 1715, 1765, 1697, 1670, 1520, 1683, 1657, 1600, 1646, 1670, 1665, 1643, 1694, 1653, 1612, 1641, 1607, 1607, 1616, 1591, 1598, 1667, 1603, 1618, 1596, 1639, 1654, 1636, 1692, 1730, 1726, 1655, 1706, 1579, 1600, 1591, 1575, 1707, 1591, 1698, 1655, 1649, 1718, 1702, 1622, 1707, 1685, 1655, 1741, 1575, 1622, 1662, 1672, 1687, 1625, 1664, 1586, 1647, 1619, 1626, 1665, 1667, 1745, 1618, 1556, 1715, 1744, 1723, 1599, 1644, 1685, 1711, 1591, 1698, 1619, 1790, 1707, 1671, 1578, 1664, 1725, 1645, 1649, 1633, 1613, 1632, 1639, 1663, 1681, 1711, 1625, 1694, 1695, 1668, 1675, 1810, 1609, 1741, 1701, 1819, 1719, 1659, 1695, 1729, 1667, 1685, 1680, 1731, 1602, 1616, 1687, 1685, 1657, 1627, 1661, 1717, 1709, 1585, 1648, 1622, 1657, 1630, 1692, 1662, 1685, 1648, 1623, 1698, 1621, 1700, 1594, 1602, 1677, 1701, 1755, 1733, 1650, 1665, 1667, 1707, 1651, 1602, 1673, 1794, 1693, 1616, 1647, 1569, 1675, 1776, 1654, 1618, 1628, 1651, 1525, 1569, 1631, 1697, 1588, 1617, 1608, 1803, 1606, 1683, 1667, 1712, 1619, 1686, 1681, 1658, 1589, 1659, 1686, 1523, 1712, 1587, 1717, 1651, 1653, 1647, 1667, 1605, 1687, 1694, 1751, 1694, 1643, 1706, 1611, 1679, 1616, 1717, 1776, 1667, 1707, 1703, 1600, 1587, 1653, 1685, 1706, 1750, 1719, 1665, 1697, 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+    "# led on, sensor over thinkpad keyboard space bar\n",
+    "data_keyboard = [1501, 1693, 1715, 1811, 1750, 0, 1250, 1790, 1661, 1943, 1690, 1645, 4095, 2615, 0, 31, 4095, 1531, 2494, 1650, 4095, 0, 3280, 595, 1519, 2001, 1555, 0, 1129, 3077, 1557, 0, 1746, 2062, 1801, 1680, 1410, 2133, 3280, 0, 0, 0, 1370, 4095, 0, 4095, 2800, 2190, 0, 4095, 4095, 1595, 4095, 1458, 1563, 1794, 1557, 3906, 1547, 1571, 1745, 0, 2667, 0, 1472, 0, 1142, 1511, 1454, 0, 3919, 195, 1680, 1989, 1827, 1853, 4066, 1562, 1648, 1601, 3861, 1425, 1489, 1610, 3978, 2918, 1680, 1722, 0, 2000, 1345, 1495, 1549, 0, 1992, 0, 1520, 1607, 1526, 1639, 1663, 1648, 1637, 1523, 1488, 109, 845, 1717, 1620, 0, 925, 0, 1722, 1703, 1743, 1631, 4095, 0, 1566, 1760, 1559, 1600, 1522, 1510, 1669, 13, 1443, 1696, 1578, 1825, 1649, 1725, 1646, 2478, 1543, 1689, 1534, 1659, 1779, 1797, 1748, 2065, 1526, 1552, 1829, 1381, 1735, 1102, 0, 1427, 1778, 1519, 1338, 1602, 1635, 1303, 1613, 1823, 1650, 4095, 1542, 1157, 1611, 1231, 1572, 0, 1670, 1521, 1680, 1721, 1739, 1385, 1618, 1526, 1606, 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1390, 1711, 1458, 1614, 2027, 1734, 1595, 0, 1408, 2438, 1824, 1762, 1811, 1605, 2519, 368, 1679, 1639, 1835, 1535, 1740, 1712, 1535, 1797, 2142, 1558, 1413, 1746, 1549, 1778, 1748, 2015, 784, 1901, 1547, 1638, 2023, 1584, 1935, 1280, 1414, 976, 1680, 1591, 1854, 1817, 1770, 1680, 1683, 1547, 1446, 1600, 1474, 1306, 1398, 1744, 1754, 1648, 1744, 1871, 1351, 1774, 1661, 0, 1775, 1669, 1616, 1776, 1759, 1808, 1644, 1909, 4095, 1327, 1427, 1659, 1655, 1718, 2031, 1646, 1736, 1600, 1794, 1819, 1918, 1720, 1477, 0, 1535, 1610, 1675, 509, 1743, 1766, 1563, 981, 1643, 3815, 1520, 4095, 1392, 2287, 1745, 7, 1730, 1699, 2704, 1792, 1725, 2311, 2409, 0, 1410, 1653, 1669, 1723, 1644, 1711, 1584, 779, 1730, 1707, 1664, 1829, 1631, 1763, 2711, 0, 0, 912, 2202, 1680, 1398, 1904, 1530, 0, 1583, 1770, 1804, 1556, 1469, 1661, 4095, 1490, 1723, 1450, 4095, 1614, 1714, 859, 1717, 1722, 1762, 567, 1669, 1569, 1550, 1622, 1648, 2486, 1776, 1765, 1727, 1410, 1630, 1683, 1723, 1151, 1458, 1587, 1675, 1520, 0, 4095, 834, 1662, 1483, 1696, 1915, 1581, 1654, 1779, 1469, 1721, 1958, 1697, 1749, 1887, 1494, 465, 1551, 0, 1671, 1920, 1600, 1472, 1493, 1686, 1862, 0, 1451, 1672, 1763, 1811, 1899, 1667, 2339, 48, 1591, 2069, 1790, 1653, 1843, 1455, 1580, 0, 1382, 1610, 1791, 1877, 1596, 1738, 1712, 0, 1508, 0, 1023, 1808, 1553, 1700, 1729, 38, 1561, 1891, 1491, 1667, 1581, 1601, 1852, 731, 1610, 1881, 970, 1929, 1566, 1703, 1386, 1166, 1589, 4095, 1557, 1783, 1488, 1821, 1710, 1764, 2257, 2331, 1419, 1654, 1759, 1667, 1630, 1721, 1779, 1841, 1443, 1702, 1645, 1443, 1350, 0, 4081, 592, 1566, 1602, 694, 1792, 1744, 1475, 1606, 1040, 0, 4095, 1666, 1677, 1877, 1840, 1449, 4095, 1663, 2025, 1670, 1830, 1638, 0, 1473, 1723, 1738, 1729, 1406, 1751, 2875, 0, 1745, 1705, 1619, 1927, 1389, 1648, 2331, 1067, 1375, 1511, 1290, 1838, 1617, 1776, 1721, 0, 1471, 1415, 0, 1557, 89, 1680, 283, 779, 1470, 1501, 1784, 1683, 1759, 1595, 1664, 1335, 1813, 1876, 1868, 1667, 1665, 1951, 1654, 0, 1666, 1557, 1758, 1575, 1559, 1734, 1643, 1391, 1813, 1763, 1616, 1499, 1776, 1424, 1648, 1523, 1767, 1795, 1531, 1392, 1630, 1399, 1678, 1089, 1439, 1445, 1825, 1681, 0, 0, 779, 2320, 791, 1535, 2352, 1789, 1600, 1863, 1584, 1699, 1617, 1520, 1648, 1795, 0, 0, 1686, 1670, 1565, 1751, 1578, 1702, 1761, 1616, 2557, 848, 832, 1467, 1754, 1649, 1769, 2103, 1646, 22, 1596, 1585, 1839, 1643, 1894, 1587, 0, 0, 1488, 1402, 1559, 1622, 1450, 1882, 1475, 0, 1551, 1666, 1008, 1889, 1555, 583, 1942, 254, 1575, 1901, 1513, 1831, 1913, 1645, 1681, 961, 1520, 1890, 1487, 1647, 1940, 1535, 1810, 180, 1552, 1692, 1360, 1727, 1620, 1670, 1733, 1099, 1546, 1424, 1717, 1581, 1392, 1741, 2000, 1782, 1718, 1754, 1471, 1754, 1607, 1386, 1542, 1530, 1523, 1955, 1433, 1718, 1559, 1691, 1419, 49, 1410, 1563, 1870, 1833, 1333, 1616, 1661, 1711, 1599, 1631, 1950, 1782, 1635, 1855, 1911, 1744, 1418, 1648, 1456, 1488, 4095, 1735, 1737, 1040, 1727, 1551]\n",
+    "\n",
+    "# ring upstairs, thr=250\n",
+    "#capture = [1792, 1890, 2014, 1888, 1770, 1862, 1888, 1857, 1817, 1967, 1714, 1665, 1739, 1714, 1674, 1666, 1651, 1730, 1587, 1681, 1690, 1631, 1729, 1727, 1663, 1663, 1744, 1639, 1729, 1658, 1674, 1710, 1654, 1763, 1651, 1696, 1693, 1662, 1773, 1655, 1646, 1661, 1744, 1667, 1611, 1655, 1680, 1695, 1642, 1716, 1707, 1610, 1594, 1600, 1650, 1605, 1710, 1737, 1621, 1669, 1669, 1771, 1687, 1663, 1629, 1678, 1607, 1675, 1693, 1721, 1551, 1728, 1590, 1650, 1607, 1715, 1771, 1631, 1703, 1626, 1634, 1664, 1691, 1654, 1640, 1691, 1527, 1647, 1740, 1659, 1713, 1630, 1682, 1643, 1613, 1622, 1599, 1555, 1601, 1680, 1613, 1693, 1655, 1635, 1651, 1683, 1673, 1533, 1745, 1684, 1689, 1673, 1647, 1680, 1725, 1663, 1687, 1710, 1711, 1639, 1703, 1677, 1642, 1687, 1617, 1681, 1715, 1651, 1664, 1600, 1584, 1619, 1623, 1715, 1565, 1654, 1594, 1751, 1760, 1646, 1691, 1714, 1726, 1682, 1614, 1659, 1689, 1625, 1627, 1776, 1694, 1699, 1766, 1616, 1680, 1651, 1669, 1747, 1695, 1675, 1567, 1681, 1680, 1648, 1818, 1664, 1658, 1648, 1707, 1678, 1645, 1680, 1687, 1744, 1617, 1677, 1627, 1639, 1680, 1674, 1664, 1680, 1743, 1616, 1675, 1697, 1615, 1779, 1680, 1746, 1662, 1664, 1621, 1552, 1751, 1674, 1745, 1680, 1673, 1633, 1729, 1667, 1666, 1653, 1649, 1707, 1606, 1669, 1747, 1683, 1674, 1685, 1579, 1585, 1669, 1713, 1657, 1651, 1680, 1559, 1680, 1621, 1535, 1649, 1644, 1713, 1651, 1658, 1671, 1648, 1707, 1682, 1641, 1678, 1647, 1735, 1643, 1747, 1745, 1808, 1568, 1655, 1671, 1622, 1581, 1595, 1695, 1686, 1687, 1597, 1749, 1616, 1747, 1638, 1786, 1750, 1680, 1668, 1679, 1617, 1854, 1610, 1702, 1674, 1614, 1661, 1589, 1682, 1595, 1552, 1692, 1711, 1660, 1600, 1663, 1654, 1745, 1601, 1715, 1767, 1643, 1630, 1574, 1598, 1664, 1671, 1643, 1707, 1718, 1591, 1716, 1710, 1704, 1582, 1584, 1664, 1707, 1739, 1709, 1589, 1582, 1651, 1621, 1705, 1717, 1626, 1643, 1734, 1682, 1641, 1680, 1754, 1590, 1709, 1685, 1667, 1647, 1709, 1667, 1744, 1590, 1712, 1722, 1628, 1678, 1646, 1693, 1635, 1662, 1728, 1701, 1626, 1717, 1603, 1529, 1606, 1700, 1733, 1604, 1575, 1654, 1726, 1697, 1595, 1634, 1638, 1667, 1663, 1616, 1709, 1693, 1580, 1725, 1826, 1671, 1653, 1632, 1719, 1698, 1654, 1658, 1693, 1600, 1595, 1649, 1603, 1679, 1637, 1673, 1737, 1648, 1555, 1775, 1685, 1707, 1663, 1686, 1594, 1754, 1805, 1730, 1590, 1745, 1689, 1622, 1638, 1655, 1680, 1583, 1663, 1672, 1679, 1677, 1687, 1601, 1550, 1650, 1647, 1703, 1715, 1712, 1633, 1661, 1673, 1675, 1642, 1616, 1613, 1616, 1667, 1650, 1744, 1668, 1664, 1680, 1655, 1675, 1586, 1584, 1683, 1631, 1631, 1646, 1619, 1635, 1641, 1651, 1621, 1712, 1601, 1661, 1584, 1662, 1719, 1617, 1681, 1793, 1754, 1691, 1728, 1626, 1754, 1681, 1571, 1676, 1712, 1639, 1648, 1727, 1651, 1691, 1617, 1754, 1607, 1712, 1682, 1706, 1637, 1609, 1666, 1664, 1637, 1626, 1669, 1705, 1715, 1675, 1717, 1663, 1531, 1733, 1679, 1722, 1648, 1578, 1603, 1803, 1737, 1651, 1642, 1627, 1680, 1725, 1745, 1620, 1657, 1699, 1685, 1505, 1638, 1742, 1670, 1730, 1676, 1691, 1639, 1637, 1619, 1679, 1771, 1646, 1648, 1744, 1775, 1581, 1651, 1618, 1666, 1665, 1692, 1675, 1680, 1597, 1683, 1711, 1639, 1697, 1655, 1723, 1675, 1594, 1631, 1627, 1664, 1729, 1679, 1706, 1637, 1616, 1712, 1759, 1646, 1694, 1653, 1633, 1710, 1725, 1575, 1621, 1613, 1582, 1590, 1699, 1744, 1680, 1760, 1681, 1704, 1579, 1717, 1712, 1604, 1663, 1665, 1663, 1707, 1641, 1616, 1648, 1635, 1562, 1958, 1669, 1721, 1645, 1743, 1648, 1605, 2006, 1644, 1663, 1701, 1583, 1677, 1659, 1744, 1709, 1728, 1635, 1686, 1570, 1610, 1729, 1667, 1638, 1619, 1664, 1702, 1686, 1643, 1628, 1680, 1603, 1615, 1594, 1600, 1577, 1522, 1727, 1664, 1680, 1611, 1716, 1642, 1629, 1665, 1630, 1678, 1655, 1594, 1552, 1648, 1665, 1675, 1741, 1635, 1649, 1680, 1667, 1584, 1629, 1584, 1597, 1680, 1692, 1655, 1584, 1691, 1614, 1753, 1722, 1637, 1594, 1673, 1649, 1628, 1645, 1786, 1648, 1744, 1591, 1660, 1577, 1666, 1706, 1728, 1709, 1639, 1666, 1673, 1682, 1662, 1649, 1729, 1677, 1638, 1651, 1803, 1731, 1719, 1666, 1648, 1643, 1655, 1725, 1697, 1734, 1614, 1655, 1647, 1731, 1786, 1618, 1706, 1716, 1552, 1648, 1616, 1645, 1755, 1616, 1696, 1723, 1683, 1635, 1683, 1794, 1600, 1692, 1741, 1712, 1690, 1648, 1609, 1663, 1727, 1646, 1725, 1696, 1686, 1617, 1649, 1682, 1680, 1719, 1575, 1659, 1638, 1712, 1593, 1779, 1680, 1722, 1607, 1680, 1699, 1759, 1645, 1661, 1661, 1616, 1668, 1616, 1750, 1761, 1680, 1743, 1697, 1613, 1629, 1682, 1669, 1581, 1643, 1617, 1627, 1712, 1702, 1778, 1630, 1662, 1621, 1680, 1648, 1674, 1514, 1615, 1557, 1639, 1623, 1703, 1664, 1680, 1552, 1696, 1659, 1579, 1617, 1689, 1675, 1531, 1655, 1600, 1728, 1587, 1648, 1575, 1671, 1669, 1602, 1649, 1685, 1639, 1643, 1728, 1682, 1655, 1641, 1600, 1679, 1671, 1503, 1750, 1709, 1721, 1614, 1606, 1709, 1682, 1659, 1785, 1653, 1595, 1547, 1712, 1600, 1578, 1666, 1714, 1670, 1683, 1667, 1631, 1651, 1746, 1658, 1611, 1618, 1669, 1713, 1739, 1681, 1690, 1763, 1674, 1621, 1631, 1593, 1616, 1681, 1637, 1619, 1685, 1589, 1637, 1562, 1674, 1716, 1661, 1626, 1733, 1603, 1634, 1674, 1573, 1649, 1574, 1554, 1645, 1616, 1642, 1659, 1761, 1623, 1743, 1637, 1709, 1618, 1719, 1597, 1704, 1744, 1679, 1697, 1644, 1711, 1638, 1675, 1698, 1739, 1597, 1651, 1674, 1728, 1651, 1743, 1771, 1706, 1893, 1667, 1641, 1662, 1815, 1721, 1665, 1747, 1611, 1677, 1661, 1694, 1709, 1751, 1730, 1680, 1776, 1600, 1739, 1696, 1677, 1581, 1766, 1638, 1761, 1773, 1553, 1562, 1605, 1664, 1725, 1600, 1525, 1631, 1605, 1683, 1738, 1634, 1636, 1675, 1552, 1664, 1707, 1745, 1654, 1727, 1666, 1627, 1734, 1613, 1759, 1731, 1584, 1719, 1687, 1681, 1661, 1686, 1575, 1662, 1703, 1738, 1646, 1552, 1664, 1712, 1547, 1702, 1631, 1761, 1651, 1743, 1647, 1729, 1590, 1731, 1689, 1600, 1605, 1723, 1680, 1660, 1658, 1567, 1712, 1602, 1606, 1651, 1572, 1641, 1584, 1665, 1531, 1633, 1680, 1574, 1735, 1651, 1712, 1712, 1629, 1348, 1600, 1495, 1655, 1695, 1872, 1936, 1958, 1911, 1741, 1747, 1897, 1518, 1454, 1462, 1883, 1719, 1680, 1713, 1825, 1606, 1610, 1489, 1840, 1625, 1651, 1621, 1781, 1488, 1809, 1392, 1350, 1655, 1759, 1509, 1825, 1654, 1567, 1551, 1629, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095]\n",
+    "# ring upstairs, thr=1000\n",
+    "#capture = [4095, 0, 0, 0, 0, 4095, 4095, 4095, 4095, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 1984, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 1952, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4016, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 3296, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 2606, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 1855, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 3530, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 3184, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 1079, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 3152, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 447, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4032, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 1215, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 0, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095, 4095, 0, 4095]\n",
+    "# ring downstairs, thr=1000\n",
+    "captures = [1787, 1953, 1932, 1936, 1898, 1933, 1911, 1872, 1885, 1895, 1749, 1647, 1615, 1706, 1649, 1627, 1674, 1646, 1602, 1632, 1665, 1732, 1647, 1614, 1619, 1744, 1596, 1761, 1569, 1647, 1729, 1649, 1619, 1648, 1694, 1628, 1669, 1653, 1648, 1651, 1707, 1683, 1535, 1641, 1595, 1735, 1711, 1622, 1683, 1691, 1685, 1794, 1650, 1631, 1663, 1687, 1664, 1671, 1697, 1680, 1683, 1769, 1685, 1727, 1705, 1695, 1712, 1725, 1666, 1680, 1679, 1586, 1648, 1605, 1639, 1655, 1631, 1634, 1557, 1610, 1646, 1712, 1643, 1734, 1511, 1694, 1707, 1757, 1659, 1661, 1600, 1669, 1622, 1666, 1646, 1654, 1655, 1698, 1638, 1717, 1616, 1663, 1673, 1623, 1629, 1585, 1718, 1583, 1675, 1648, 1665, 1627, 1528, 1616, 1583, 1637, 1633, 1620, 1579, 1639, 1658, 1644, 1711, 1710, 1419, 1648, 1806, 1679, 1443, 1668, 1771, 1585, 1559, 1745, 1607, 1673, 1623, 1629, 1399, 1639, 1674, 1600, 1534, 1717, 1462, 1579, 1525, 1748, 1662, 1529, 1535, 1866, 1549, 1472, 1683, 1663, 1591, 1519, 1687, 1728, 1530, 1603, 1687, 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+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "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": [
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\" width=\"900\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axs = plt.subplots(3, figsize=(9, 10))\n",
+    "fig.tight_layout()\n",
+    "for ax, (data, title) in zip(axs.flatten(), [\n",
+    "            (data_led_off, 'LED off'),\n",
+    "            (data_keyboard, 'ThinkPad keyboard'),\n",
+    "            (captures[1], 'Capture'),\n",
+    "        ]):\n",
+    "    ax.plot(data)\n",
+    "    ax.set_title(title)\n",
+    "    mean = statistics.mean(data)\n",
+    "    rms = math.sqrt(sum((x-mean)**2 for x in data)/len(data))\n",
+    "    ax.axhline(mean, color='red')\n",
+    "    bbox = {'facecolor': 'black', 'alpha': 0.8, 'pad': 2}\n",
+    "    ax.text(0, mean, f'mean: {mean:.3f}', color='white', bbox=bbox)\n",
+    "    ax.text(0.98, 0.1, f'RMS: {rms:.3f}', transform=ax.transAxes, color='white', bbox=bbox, ha='right')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "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 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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(array([[1.16263635e+05, 1.17516983e+05, 1.14159440e+05, ...,\n",
+       "         1.81110593e+05, 1.98501199e+05, 1.90240084e+05],\n",
+       "        [2.32455272e+05, 2.34962883e+05, 2.28249748e+05, ...,\n",
+       "         3.62114688e+05, 3.96886544e+05, 3.80363971e+05],\n",
+       "        [2.32239396e+05, 2.34749751e+05, 2.28042468e+05, ...,\n",
+       "         3.61795366e+05, 3.96539170e+05, 3.80015573e+05],\n",
+       "        ...,\n",
+       "        [1.31973095e+01, 7.33739226e+00, 1.49770074e+01, ...,\n",
+       "         5.68101887e+02, 1.15431061e+01, 2.16135322e+02],\n",
+       "        [1.32081642e+01, 7.35024163e+00, 1.49773133e+01, ...,\n",
+       "         5.67992560e+02, 1.15598690e+01, 2.16139910e+02],\n",
+       "        [6.60589216e+00, 3.67726423e+00, 7.48870808e+00, ...,\n",
+       "         2.83978052e+02, 5.78274574e+00, 1.08070693e+02]]),\n",
+       " array([0.00000000e+00, 2.44140625e-01, 4.88281250e-01, ...,\n",
+       "        4.99511719e+02, 4.99755859e+02, 5.00000000e+02]),\n",
+       " array([0.032, 0.064, 0.096, 0.128, 0.16 , 0.192, 0.224, 0.256, 0.288,\n",
+       "        0.32 , 0.352, 0.384, 0.416, 0.448, 0.48 , 0.512, 0.544, 0.576,\n",
+       "        0.608, 0.64 , 0.672, 0.704, 0.736, 0.768, 0.8  , 0.832, 0.864,\n",
+       "        0.896, 0.928, 0.96 , 0.992, 1.024, 1.056, 1.088, 1.12 , 1.152,\n",
+       "        1.184, 1.216, 1.248, 1.28 , 1.312, 1.344, 1.376, 1.408, 1.44 ,\n",
+       "        1.472, 1.504, 1.536, 1.568, 1.6  , 1.632, 1.664, 1.696, 1.728,\n",
+       "        1.76 , 1.792, 1.824, 1.856, 1.888, 1.92 , 1.952, 1.984, 2.016]),\n",
+       " <matplotlib.image.AxesImage at 0x73487e104d10>)"
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "ax.specgram(np.array(captures[0] + captures[1]), NFFT=64, noverlap=32, Fs=1000, pad_to=4096)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
-- 
cgit