{
"cells": [
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"import statistics\n",
"import math\n",
"import itertools\n",
"\n",
"import numpy as np\n",
"from matplotlib import pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib notebook"
]
},
{
"cell_type": "code",
"execution_count": 92,
"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, 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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, 1633, 1459, 1503, 1609, 1589, 2453, 1819, 1616, 1698, 1142, 0, 914, 1595, 1806, 2593, 1223, 1595, 1749, 1505, 1744, 1547, 1647, 607, 1519, 1651, 1600, 1831, 1776, 1242, 1584, 0, 1571, 1579, 1509, 2032, 1423, 368, 3691, 0, 1232, 1663, 0, 1683, 1649, 1648, 1862, 1219, 1439, 1664, 1547, 1535, 1456, 1387, 1676, 2340, 1485, 1493, 1706, 1532, 1840, 1553, 1522, 0, 1293, 1486, 1561, 1535, 1431, 1872, 2165, 1648, 1619, 1611, 1613, 1682, 1449, 1838, 1808, 1815, 1682, 1433, 1745, 1614, 1587, 0, 1524, 455, 1283, 4095, 1546, 1491, 1437, 1423, 1670, 0, 1601, 1713, 1758, 1472, 1727, 1702, 1870, 1707, 1603, 1399, 1715, 1678, 1605, 1666, 2448, 1761, 1388, 1743, 1363, 957, 139, 1579, 1589, 1535, 1441, 1781, 1694, 1643, 1834, 1680, 1770, 2299, 1501, 1594, 1648, 1582, 1088, 1679, 2130, 287, 1837, 949, 1388, 1375, 1567, 1743, 1665, 0, 1386, 1555, 1674, 1810, 1821, 1698, 1930, 462, 262, 1520, 1903, 1532, 1600, 1610, 1456, 2449, 1808, 1840, 1583, 1671, 1565, 1581, 2141, 437, 1829, 1902, 1520, 1973, 1787, 1553, 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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, 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"\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, 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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",
"data_upstairs = [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",
"data_downstairs = [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, 1598, 1731, 1632, 1647, 1552, 1671, 1692, 1619, 1535, 1614, 1616, 1616, 1611, 1650, 1597, 1648, 1671, 1600, 1563, 1735, 1677, 1619, 1674, 1783, 1648, 1660, 1570, 1655, 1575, 1666, 1648, 1613, 1651, 1771, 1552, 1631, 1584, 1683, 1683, 1725, 1593, 1638, 1643, 1495, 1644, 1562, 1674, 1667, 1700, 1625, 1648, 1642, 1648, 1675, 1628, 1572, 1678, 1691, 1651, 1675, 1611, 1663, 1611, 1676, 1562, 1679, 1607, 1638, 1718, 1664, 1600, 1600, 1669, 1657, 1589, 1670, 1680, 1716, 1711, 1675, 1591, 1570, 1690, 1612, 1680, 1625, 1671, 1718, 1665, 1692, 1557, 1607, 1753, 1635, 1699, 1665, 1675, 1665, 1561, 1637, 1744, 1648, 1900, 1922, 1707, 1641, 1699, 1514, 1781, 1729, 1623, 1643, 1643, 1680, 1786, 1649, 1599, 1695, 1617, 1705, 1734, 1575, 1658, 1530, 1683, 1679, 1520, 1678, 1653, 1586, 1616, 1744, 1638, 1647, 1654, 1614, 1665, 1665, 1653, 1591, 1669, 1654, 1698, 1576, 1623, 1726, 1633, 1699, 1675, 1610, 1711, 1645, 1616, 1713, 1696, 1666, 1624, 1606, 1806, 1516, 1515, 1805, 1611, 1518, 1598, 1921, 1556, 1484, 1711, 1438, 1409, 1623, 1675, 1590, 1486, 1691, 1618, 1520, 1695, 1607, 1646, 1554, 1567, 1510, 1603, 1451, 1747, 1584, 1473, 1589, 1658, 1552, 1474, 1627, 1659, 1557, 4095, 1246, 1578, 1669, 1467, 1411, 1469, 1562, 1616, 1387, 1313, 1573, 1500, 1535, 1488, 1518, 1367, 1569, 1606, 1507, 1565, 1535, 1520, 1486, 1519, 1454, 1494, 1437, 1527, 1527, 1498, 1458, 1535, 1554, 1518, 1511, 1569, 1457, 1584, 1440, 1548, 1553, 1549, 1524, 1526, 1586, 1483, 1519, 1471, 1644, 1504, 1463, 1553, 1521, 1515, 1504, 1526, 1520, 1531, 1558, 1547, 1574, 1616, 1664, 1661, 1593, 1446, 1479, 1458, 1553, 1485, 1569, 1420, 1558, 1493, 1607, 1609, 1623, 1517, 1533, 1552, 1475, 1562, 1510, 1679, 1511, 1550, 1594, 1562, 1584, 1504, 1582, 1456, 1551, 1415, 1473, 1495, 1519, 1574, 1520, 1565, 1435, 1558, 1556, 1533, 1466, 1498, 1523, 1531, 1535, 1557, 1488, 1565, 1463, 1521, 1491, 1471, 1533, 1563, 1534, 1549, 1584, 1552, 1471, 1549, 1571, 1589, 1535, 1531, 1392, 1535, 1558, 1605, 1598, 1555, 1495, 1632, 1555, 1587, 1570, 1455, 1579, 1529, 1485, 1425, 1552, 1505, 1439, 1531, 1510, 1478, 1471, 1577, 1493, 1535, 1552, 1472, 1488, 1600, 1525, 1565, 1489, 1509, 1487, 1517, 1563, 1459, 1599, 1445, 1590, 1552, 1494, 1530, 1566, 1524, 1545, 1345, 1513, 1534, 1518, 1634, 1523, 1454, 1628, 1517, 1505, 1478, 1651, 1616, 1555, 1381, 1581, 1513, 1681, 1481, 1527, 1640, 1492, 1590, 1530, 1488, 1558, 1472, 1526, 1553, 1569, 1515, 1565, 1491, 1535, 1567, 1597, 1584, 1651, 1841, 1554, 1520, 1520, 1511, 1600, 1619, 0, 4095, 0, 4095, 4095, 0, 4095, 0, 4095, 0, 4095, 4095, 0, 4095, 0, 4095, 0, 4095, 0, 0, 4095, 0, 4095, 0, 4095, 0, 415, 4095, 0, 4095, 0, 4095, 0, 4095, 4095, 0, 4095, 0, 4095, 0, 4095, 3795, 0, 4095, 0, 4095, 0, 4095, 0, 0, 4095, 0, 4095, 0, 4095, 0, 4095, 4095, 0, 4095, 0, 4095, 0, 4095, 4095, 0, 4095, 0, 4095, 0, 4095, 0, 0, 4095, 0, 4095, 0, 4095, 0, 3203, 4095, 0, 4095, 0, 4095, 0, 4095, 4095, 0, 4095, 0, 4095, 0, 4095, 4095, 0, 4095, 0, 4095, 0, 4095, 0, 0, 4095, 0, 4095, 0, 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"# False trigger from jigsaw/drill\n",
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]
},
{
"cell_type": "code",
"execution_count": 28,
"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 = $('');\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",
" '');\n",
" var titletext = $(\n",
" '');\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 = $('');\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 = $('');\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 = $('');\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 = $('')\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 = $('');\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 = $('');\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 = $('');\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 = $('');\n",
"\n",
" var fmt_picker = $('');\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",
" '', {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 = $('');\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(\"\");\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('![](\"')
');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '';\n",
"}\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 = $('')\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 = $('');\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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('');\n",
" var 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= 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"
],
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\")
"
],
"text/plain": [
""
]
},
"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[0], '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": 25,
"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 = $('');\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",
" '');\n",
" var titletext = $(\n",
" '');\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 = $('');\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 = $('');\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 = $('');\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 = $('')\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 = $('');\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 = $('');\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 = $('');\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 = $('');\n",
"\n",
" var fmt_picker = $('');\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",
" '', {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 = $('');\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(\"\");\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('');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '';\n",
"}\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 = $('')\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 = $('');\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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('');\n",
" var 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= 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"
],
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\")
"
],
"text/plain": [
""
]
},
"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",
" )"
]
},
"execution_count": 25,
"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)"
]
},
{
"cell_type": "code",
"execution_count": 125,
"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 = $('');\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",
" '');\n",
" var titletext = $(\n",
" '');\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 = $('');\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 = $('');\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 = $('');\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 = $('')\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 = $('');\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 = $('');\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 = $('');\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 = $('');\n",
"\n",
" var fmt_picker = $('');\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",
" '', {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 = $('');\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(\"\");\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('');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '';\n",
"}\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 = $('')\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 = $('');\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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('');\n",
" var 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= 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": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
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\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, axs = plt.subplots(2, figsize=(9,6))\n",
"\n",
"for ax, capture in zip(axs.flatten(), [data_downstairs[0] + data_downstairs[1], data_upstairs]):\n",
" cap = np.array(capture)\n",
" cap -= np.mean(cap).astype(int)\n",
" lens = np.array([ x for g in (list(g) for g_key, g in itertools.groupby(cap, lambda x: 1 if x >= 0 else -1)) for x in range(len(g)) ])\n",
" w = 32\n",
" k = 8\n",
" lens = np.array(list(sum(xs) for xs in zip(*(lens[i::k] for i in range(w))))) / w\n",
" rmss = np.array(list(np.sqrt(np.mean(np.square(xs))) for xs in zip(*(cap[i::k] for i in range(w)))))\n",
" ax.plot(lens)\n",
" ax2 = ax.twinx()\n",
" ax2.plot(rmss, color='red')\n",
" ax2.grid()\n",
"\n",
" both_data = list(zip(lens, rmss))\n",
" p, q = 12, 3\n",
" for idx, data in enumerate(zip(*(both_data[i*p:] for i in range(q)))):\n",
" h_len, h_rms = zip(*data)\n",
" if all(x > 1500 for x in h_rms):\n",
" if all(0.1 < x < 0.25 for x in h_len[::2]) and \\\n",
" all(0.25 < x < 0.4 for x in h_len[1::2]):\n",
" ax.axvspan(idx, idx + p*q, color='lightgreen')\n",
" elif all(0.25 < x < 0.4 for x in h_len):\n",
" ax.axvspan(idx, idx + p*q, color='pink')"
]
},
{
"cell_type": "code",
"execution_count": 127,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('');\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",
" '');\n",
" var titletext = $(\n",
" '');\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 = $('');\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 = $('');\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 = $('');\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 = $('')\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 = $('');\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 = $('');\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 = $('');\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 = $('');\n",
"\n",
" var fmt_picker = $('');\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",
" '', {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 = $('');\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(\"\");\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('');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '';\n",
"}\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 = $('')\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 = $('');\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 = $('');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('');\n",
" var 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= 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"
],
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\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, axs = plt.subplots(2, figsize=(9,6))\n",
"\n",
"for ax, capture in zip(axs.flatten(), [data_downstairs[0] + data_downstairs[1], data_upstairs]):\n",
" cap = np.array(capture)\n",
" cap -= np.mean(cap).astype(int)\n",
" \n",
" runs = []\n",
" cur_sign, cur_run = 1, 0\n",
" for x in cap[len(cap)//2:]:\n",
" if x > 0 and cur_sign < 0:\n",
" runs.append(cur_run)\n",
" cur_sign = 1\n",
" cur_run = 0\n",
" elif x < 0 and cur_sign >= 0:\n",
" runs.append(cur_run)\n",
" cur_sign = -1\n",
" cur_run = 0\n",
" else:\n",
" cur_run += 1\n",
" \n",
" run_means = []\n",
" for start in range(0, len(runs), 8):\n",
" k = 32\n",
" run_means.append(sum(runs[start:start+k])/k)\n",
" \n",
" bin_low, bin_high = 0, 0\n",
" for e in run_means:\n",
" if 0.05 < e < 0.25:\n",
" bin_low += 1\n",
" elif 0.30 < e < 0.50:\n",
" bin_high += 1\n",
" total = len(run_means)\n",
" \n",
" bin_low /= total\n",
" bin_high /= total\n",
" \n",
" if 0.3 < bin_low < 0.7 and 0.3 < bin_high < 0.7:\n",
" res = 'downstairs'\n",
" elif bin_low < 0.3 and bin_high > 0.7:\n",
" res = 'upstairs'\n",
" else:\n",
" res = 'none'\n",
" \n",
" ax.text(0.98, 0.25, f'bin[l,h]: {bin_low:.3f} {bin_high:.3f}',\n",
" transform=ax.transAxes, color='white', bbox=bbox, ha='right')\n",
" \n",
" ax.text(0.98, 0.1, f'res: {res}',\n",
" transform=ax.transAxes, color='white', bbox=bbox, ha='right')\n",
" \n",
" ax.plot(run_means)"
]
}
],
"metadata": {
"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
}