{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style='background-image: url(\"share/baku.jpg\") ; padding: 0px ; background-size: cover ; border-radius: 15px ; height: 250px; background-position: 0% 80%'>\n",
    "    <div style=\"float: right ; margin: 50px ; padding: 20px ; background: rgba(255 , 255 , 255 , 0.9) ; width: 50% ; height: 150px\">\n",
    "        <div style=\"position: relative ; top: 50% ; transform: translatey(-50%)\">\n",
    "            <div style=\"font-size: xx-large ; font-weight: 900 ; color: rgba(0 , 0 , 0 , 0.9) ; line-height: 100%\">ObsPy Tutorial</div>\n",
    "            <div style=\"font-size: large ; padding-top: 20px ; color: rgba(0 , 0 , 0 , 0.7)\">Handling Time</div>\n",
    "        </div>\n",
    "    </div>\n",
    "</div>\n",
    "image: User:Abbaszade656 / Wikimedia Commons / <a href=\"http://creativecommons.org/licenses/by-sa/4.0/\">CC-BY-SA-4.0</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Workshop for the \"Training in Network Management Systems and Analytical Tools for Seismic\"\n",
    "### Baku, October 2018\n",
    "\n",
    "\n",
    "Seismo-Live: http://seismo-live.org\n",
    "\n",
    "##### Authors:\n",
    "* Lion Krischer ([@krischer](https://github.com/krischer))\n",
    "* Tobias Megies ([@megies](https://github.com/megies))\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](images/obspy_logo_full_524x179px.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a bit dry but not very difficult and important to know. It is used **everywhere** in ObsPy!\n",
    "\n",
    "\n",
    "* All absolute time values are consistently handled with this class.\n",
    "* Based on a nanosecond precision POSIX integer timestamp for accuracy.\n",
    "* Timezone can be specified at initialization (if necessary).\n",
    "* In Coordinated Universal Time (UTC) so no need to deal with timezones, daylight savings, ...\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "plt.rcParams['figure.figsize'] = 12, 8"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Features of **`UTCDateTime`**\n",
    "\n",
    "#### Initialization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2014-08-24T10:20:44.000000Z\n",
      "2014-08-24T10:20:44.000000Z\n",
      "2014-08-24T10:20:44.000000Z\n",
      "2014-08-24T10:20:44.000000Z\n"
     ]
    }
   ],
   "source": [
    "from obspy import UTCDateTime\n",
    "\n",
    "print(UTCDateTime(\"2014-08-24T10:20:44.0\"))        # mostly time strings defined by ISO standard\n",
    "print(UTCDateTime(\"2014-08-24T01:20:44.0-09:00\"))  # non-UTC timezone input\n",
    "print(UTCDateTime(2014, 8, 24, 10, 20, 44))        # year, month, day, hour, min, sec, musec\n",
    "print(UTCDateTime(1408875644.0))                   # timestamp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019-11-04T08:59:32.256536Z\n"
     ]
    }
   ],
   "source": [
    "# Current time can be initialized by leaving out any arguments\n",
    "print(UTCDateTime())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Attribute Access"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2014\n",
      "236\n",
      "1408875644.0\n",
      "6\n"
     ]
    }
   ],
   "source": [
    "time = UTCDateTime(\"2014-08-24T10:20:44.0\")\n",
    "print(time.year)\n",
    "print(time.julday)\n",
    "print(time.timestamp)\n",
    "print(time.weekday)\n",
    "# try time.<Tab>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Handling time differences\n",
    "\n",
    "* \"**`+`**/**`-`**\" defined to add seconds to an **`UTCDateTime`** object\n",
    "* \"**`-`**\" defined to get time difference of two **`UTCDateTime`** objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2014-08-24T10:20:44.000000Z\n"
     ]
    }
   ],
   "source": [
    "time = UTCDateTime(\"2014-08-24T10:20:44.0\")\n",
    "print(time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2014-08-24T11:20:44.000000Z\n"
     ]
    }
   ],
   "source": [
    "# one hour later\n",
    "print(time + 3600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11194756.0\n"
     ]
    }
   ],
   "source": [
    "# Time differences\n",
    "time2 = UTCDateTime(2015, 1, 1)\n",
    "print(time2 - time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercises\n",
    "\n",
    "Calculate the number of days passed since the 2014 South Napa earthquake (the timestamp used above)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1897.901947792662\n"
     ]
    }
   ],
   "source": [
    "print((UTCDateTime() - UTCDateTime(\"2014-08-24T11:20:44.000000Z\")) / 86400)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make a list of 10 UTCDateTime objects, starting today at 10:00 with a spacing of 90 minutes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2017-09-18T10:00:00.000000Z,\n",
       " 2017-09-18T11:30:00.000000Z,\n",
       " 2017-09-18T13:00:00.000000Z,\n",
       " 2017-09-18T14:30:00.000000Z,\n",
       " 2017-09-18T16:00:00.000000Z,\n",
       " 2017-09-18T17:30:00.000000Z,\n",
       " 2017-09-18T19:00:00.000000Z,\n",
       " 2017-09-18T20:30:00.000000Z,\n",
       " 2017-09-18T22:00:00.000000Z,\n",
       " 2017-09-18T23:30:00.000000Z]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = UTCDateTime(2017, 9, 18, 10)\n",
    "\n",
    "times = []\n",
    "for i in range(10):\n",
    "    t2 = t + i * 90 * 60\n",
    "    times.append(t2)\n",
    "\n",
    "times"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below is a list of strings with origin times of magnitude 8+ earthquakes since 2000 (fetched from IRIS). Assemble a list of interevent times in days. Use matplotlib to display a histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "times = [\"2000-11-16T04:54:56\",\n",
    "         \"2001-06-23T20:33:09\",\n",
    "         \"2003-09-25T19:50:07\",\n",
    "         \"2004-12-23T14:59:00\",\n",
    "         \"2004-12-26T00:58:52\",\n",
    "         \"2005-03-28T16:09:35\",\n",
    "         \"2006-05-03T15:26:39\",\n",
    "         \"2006-06-01T18:57:02\",\n",
    "         \"2006-06-05T00:50:31\",\n",
    "         \"2006-11-15T11:14:14\",\n",
    "         \"2007-01-13T04:23:23\",\n",
    "         \"2007-04-01T20:39:56\",\n",
    "         \"2007-08-15T23:40:58\",\n",
    "         \"2007-09-12T11:10:26\",\n",
    "         \"2009-09-29T17:48:11\",\n",
    "         \"2010-02-27T06:34:13\",\n",
    "         \"2011-03-11T05:46:23\",\n",
    "         \"2012-04-11T08:38:37\",\n",
    "         \"2012-04-11T10:43:10\",\n",
    "         \"2013-05-24T05:44:49\",\n",
    "         \"2014-04-01T23:46:47\",\n",
    "         \"2015-09-16T22:54:32\",\n",
    "         \"2017-09-08T04:49:21\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qYybfsX0r8JCkvQqPxZrAqcBWpMudPw78gQLjERGfAz5BisNvgQOByRQSi65p2Rc8JMNi4HBJbwF2AD6dt/tLwM8lbQL8PL8mz5sObAnsAZycY9dNDiNdCFBXcixmAVdJ2hyYSopLcfGIiPWAzwDbSdqK1CCcTkGx6JpkT6FDMkhaIOn2/PfTpC/zeqRtPzMvdibwvvz33sAFkl6UdD/wR1LsukJErA+8h9SarSs1FmsA/wCcBiBpkaQnKDQepJ6MVSKih9Sin09BseimZD/UkAzrjVNdxkVEbAi8DbgJmCJpAaQfBGDdvFi3x+kk4F9JXVp1pcZiY+BR4PSI+HVEnBoRq1JgPCQ9BPwb8GdgAfCkpKspKBbdlOyHuk24mOtKI2I14GLgs5KeWsqiXRuniNgLeETSbSNcpWtjkfUA2wDfk/Q24FlyN8UwujYeEfFaUmt9I6AXWDUi9l/KKl0Xi25K9sUOyRARK5AS/bmSLsmTF0bE6/P81wOP5OndHKd3ANMi4gFSN97OEXEOZcYC0vbNk3RTfn0RKfmXGI9dgfslPSrpJeASYEcKikU3XY1T5JAMETGB1Cd7t6QTG2ZdCnwUOD7//+OG6edFxImkFs4mwM3V1XjsSDoCOAIgInYCviBp/4j4JoXFAkDSwxHxYERsJukPwC7A7/O/0uLxZ2CHiJgMPE+Kxa2ko50iYtE1LftxGJKhU7wDOIDUir0j/3s3aefdLSL+F9gtvybHRKQv/FXApyW9PD5Vr0zJsTgUODci7gS2Br5OgfHIRzcXAbeTLrucSBoeoZhYeLgEM7MCdE3L3szMhudkb2ZWACd7M7MCONmbmRXAyd7MrADddJ19x4qIu0iXbl3Tpvd7APiEpP9qx/str4i4kjSOyJnLXLgwnRybiPg+aWTQr413XaoWEWeQ7sOZL2nDYZaZCbxZ0tLutF2eOqwE/AVYCThB0lfGopy6rk/2OTH2Ar2S+hqm30EaBXAjSQ+MZR0kbdlQ7kzGcAdalogI4BjSHYEPAkdK+s/leU9Je7ZQ/jXAOZJOXdaynSSPO3Q/sEK+p2OoZWbS9Nm2EpuqSfqnKsvLye1k0t2sa5EGFztS0pUNy+xCGr32jaQxnj4maW6eN4F0Hfwn8uKnAV+U1J/nbwicDmxPuonqkGU0iL4x1gl2aSS9CKyWf3jGXCndOPcD+9ZfRMTfAKuMX3XGRx7m9Rzg88AawL+Q7hJcd4hld8qJuaO82oeZLVwPqYHxTuA1wFGAcpImImqkYQyOIv0Y3Eoaa75uBmlUyqnAW4G9gE82zD8f+DWwNvBl4KKIWGfsNufVpetb9tnZwEeA/8ivP0p64Mf/ry8QEe/Jr98EPAmcJmlmw/yPAF8DViONrHgQuSslt+i2AF4A9iG1Kj4q6da87gOk1kgPcCQwISLeB9wnaWpzt0xzCzEiDsh1Ww1oHBKBiJhIGuXxYGBN0pjc/yTpsSHisD7wRENL6icR8Wze5keGWH5EGlvrEfGxvK035hg9AXxK0pURcRzw96Tb1k8CzpB0SERsTvpstiWN0niUJOX3PoN0e/sGpCSxd0T8CjgOCNIh8Bzgc5Kej4i7gX+RdHlevwd4GNhd0u0RsUOO4RbAXOCwevda3o5fATuTkskNwH75iPDavLlPpIMjdpN0Q0MM9mDoz7Y5NgeTbrs/EHgM2B/YlLRvrZTrfmZ+z5WWsp014Azg70gjfN4FvFNS42if9dbwicCH83vMzdv0uxzbeZK+koeXOAf4d+CLpAd2HCnp9Pw+q5D2wQ+Q9rPf5hg8v7SYNpL0LDCzYdLlEXE/6XN/APh/wF2SfpTLnAn0RcTmku4hfW+/JWlenv+tHM/vR8SmpHF/dpf0PHBxRHwWeD/w/ea6DCUPtXJGfp8bSQ95aZz/I9L+uwrwG+CfJd0VEX8LXA6sVz/qi4j3k/bjrSPi7aQjmk1J+/K5kj4/kjq1Uykt+xuBNSLiLbll+CHSjt3oWdIPwpqk8dD/OX9p6w8yOJn0hXk9qVXSPNzpNNLgW2uSxtX4TnMlJF1Ful39QkmrSZq6rIrnsr9HGhKhl9RqWb9hkc+QWjvvzPMfJx0GD+VW4O6ImBYRk/L2vQjcuax6tGh70helBnwDOC0iJkj6MimZHpK3/5A85O7PgPNIw8vuS3pQxJYN77cfKemtDlwHnED64mwNvJn0WXw1L3s+DUdxwLuAvpzo1wN+QkpaawFfICWFxtbffqREvC6wYl4G0rjwAGvmut/QsE4rn+32pHivnbf5AuBv83bsD3wnj2DKMrbzcNJgXesAU0g/NEPdDr97rvumpH3zQ6R+4qG8joF9+yDgu3m0SEjDA29LGjxsLfIw0iOM6ZAiYkquV31Yky1JSRR45cfhvjx9ifn578Z5f8rPdBhq/kicB9xG2m+/RvpxaXQlaYycdUnDLpyb63kLKaa7NSy7P6mRCekBMrMkrUFqWKmFOrVNKS17GGjd/xK4hzRY2iuaWiJ3RsT5pAT6n6TWzGWSrgOIiK+Skmyj6yRdkeefDXy2TfX+AHC5pGvzex9FGgOo7pOk5Flv7cwE/hwRBzT3LUt6OSLOIu3UKwOLgA/mL1U7zZV0Sq7PmaQfyimkFnazvYAH6i1I4PaIuJi03fUk8GNJ/5Pf70VSa+6t9aOXiPh63qYj8v+/jojJkp4jJe/z8vvsD1xR/5yAn0XErcC7GXiAxemS7s3vK9KPeDvd39BavpDU3XBs7r+9OiIWAW+OiN8sYztfIjU8NpD0R9KP6FBeIv1Ibg7cLOnuYZarL3ts3m+uiIhngM0i4mbS4wx3UBoXHuD6XKeRxHQJkUZqPRc4M7faIR25Ptq06JO5/vX5TzbNWy0fvTTPq88f0Rj0EfFG0o/urvmzuDYiLmtcRtIPG5afCTweEa+R9CRpW/cHroz0GMx3AZ/Ki79E+kxr+SjxxpHUqd1KS/bXksazPqt5ZkRsTzr5sxWpRbcS8KM8u5eGBxlIei4imltHjYnsOWDliOgZ7mReC5rLfrap7A2AORHRePj+Mim5DvpBi4hdSS3tnUgtk22BSyNiT0l3RMSXGBjvvCdvwxMNZa85wjq/EoscK0hfxqFsAGzfWE4u++yG140PkViH9JSh2/L7Qhp7fFIu74+5K+e9+cs6jfRAl3pZH4yI9za83wrAfw9Vd9LnOFy9R2thw9/P5zo3T1uNZWwn8E1Sl8jVef5sDfHMZUm/iIjvkE96RsQc0migQz3z4C9N+2t9+2ukxsF9Q6wzkpgOkrsezyY1NhobLs+QziU1WgN4epj5awDPSOrPP0xLW3dZeoHHmxo+c8nDHOcegeOAD5I+m/r3rUb6UTmHdNS8Gqnb7VfKD0UhHSUdC9yTu62OqXczVqmYZC9pbg70u0nBb3YeqetlT0kv5D7lWp63ANisvmDuv1x7lFUZ6lD7WdIXu+51DX8vAN7SUPbkprIfBD5eb/kuw9bAtfVzCcAtEXET6eqIO3KyOD6XsxMwU9JOI3jfVjRv/4PALyXtNtTCQ6zTR0qIWza0MpvVu3ImAr/PLd96WWdLOrj1ao/owRXtHFVwqduZuysOBw7PXV7/HRG3SPr5EMt+G/h2pBPxIp2YP6rFurxA6oL4TdO8lmIaA0NyTwHerTS2fN1dNHSd5C6+NzFwhHcX6eRsfajhqU3zNo6I1Ru6cqYycFS3LAuA10bEqg0J/40MfKb7kR5+sivp/MJrSF2mEyA9CSsibiCdszuA1PVKnve/pGdiTySdl7goItYegyPqpSom2WcHAa/NrePmbV8deCwn+reTPtyr87yLgBsjYkdSv/cxDP0km5FYSBpSdWLDybQ7gOmRrsmeSurCuKqh7Jsi4u9IO/mxDD7X8n3guIj4aP5BWwfYUdKPWdItwJciYuvckn8b6YTTyaPcltFYSHpcXt3lwPGRTkJfkKdtTWqxLdHlIOmvEXEK8O8RcYikR3K/8VaSfpoXu4DUCluLwV/2c0g/cO8C/ovUAt2B9Oziecuo96Ok1tzGwL1L2bbmz3ZUlrWdkZ7KdQ+ptf0U6WhuiSF488nDiaQjuWdJSbuloXpzXX4InJg/p4Wk57HeTusx/R6p8bJrPpHaaA7wzXxy8yek8xN3NnTznAV8PiKuICXhw8kXXUi6N9Ll1EdHxFeAPUkn2d8/wm2cm7ufjomII/P2vZd0/g1SfniR1Dc/mXR+ptlZpCPjDfK2AK90df1U0qMNR7CVD5dcyglaACTd19CqbfYp4NiIeJq0k6lhvbtI44JfQGoBPE26euXFUVSj3jX0l4i4Pf99FKkF8zjph+SVBJXL/nSetiAv0/glmkXaIa/Odb+RdBJwCZJ+STr0vygvezHwdaVncVZlFvCBiHg8Ir6dW2G7kx42M5/UjXICqRttOF8kXaN9Y0Q8RUoyrxx55cPnG0gnEy9smP4gqXV2JCl5P0hq5S7ze5D7/48D/icinoh0BUqzoT7b5bG07dwkv36GtK0nD3UFDKkr4xTSfjOXlKz+bRR1+QLpCpxbSFcRnQBMbCWmEbEB6RzT1sDDEfFM/vdhAEmPkpLzcbm+25P2i7ofAJflevyO9IPwg4b504Ht8rrHAx/I7zlS++UyHwOOZnB371mk+D1EGuN+qH73OeRE39Rq3wO4K3c1zQKmS3qhhXq1hcezH4XcL/cEsInSk+fN7FUkHzXtCyyU9KY2vu99wCc1grvbI11au5B0NPQNSce0qx5DcbIfoXwC6uek7ptvkVoA2yjfvWdmZcvdTycAmy5vN95YKK3PfnnsTbqCYAKp3366E72ZwSs35G0BHNCJiR7csjczK0JRJ2jNzErlZG9mVgAnezOzAjjZm5kVwMnezKwA/wdr3fsEi9vyPAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "inter_event_times = []\n",
    "\n",
    "for i in range(1, len(times)):\n",
    "    dt = UTCDateTime(times[i]) - UTCDateTime(times[i-1])\n",
    "    dt = dt / (3600 * 24)\n",
    "    inter_event_times.append(dt)\n",
    "\n",
    "plt.hist(inter_event_times, bins=range(0, 1000, 100))\n",
    "plt.xlabel(\"Magnitude 8+ interevent times since 2000 [days]\")\n",
    "plt.ylabel(\"count\")\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}