example_fastapi.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "903ef1da-7471-41b5-8a50-41f1a87c8d3e",
   "metadata": {},
   "source": [
    "# Interactive Example\n",
    "\n",
    "## 1. Run PhaseNet in terminal or use QuakeFlow API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, sys\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import obspy\n",
    "import requests\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4e5f57e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# PHASENET_API_URL = \"http://127.0.0.1:8000\"\n",
    "PHASENET_API_URL = \"http://34.221.45.133\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Prepare seismic waveforms\n",
    "\n",
    "Find more details in obspy's tutorials: \n",
    "\n",
    "[FDSN web service client for ObsPy](https://docs.obspy.org/packages/obspy.clients.fdsn.html#module-obspy.clients.fdsn)\n",
    "\n",
    "[Mass Downloader for FDSN Compliant Web Services](https://docs.obspy.org/packages/autogen/obspy.clients.fdsn.mass_downloader.html#module-obspy.clients.fdsn.mass_downloader)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x750 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import obspy\n",
    "stream = obspy.read()\n",
    "stream.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dfe6a3a0-d5ab-43de-9b61-a14f4104e715",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Extract 3-component data\n",
    "stream = stream.sort()\n",
    "assert(len(stream) == 3)\n",
    "data = []\n",
    "for trace in stream:\n",
    "    data.append(trace.data)\n",
    "data = np.array(data).T\n",
    "assert(data.shape[-1] == 3)\n",
    "\n",
    "data_id = stream[0].get_id()[:-1]\n",
    "timestamp = stream[0].stats.starttime.datetime.strftime(\"%Y-%m-%dT%H:%M:%S.%f\")[:-3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Predict P/S-phase picks using PhaseNet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[5], line 5\u001b[0m\n\u001b[1;32m      1\u001b[0m req \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mid\u001b[39m\u001b[38;5;124m\"\u001b[39m: [[data_id]],\n\u001b[1;32m      2\u001b[0m        \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtimestamp\u001b[39m\u001b[38;5;124m\"\u001b[39m: [timestamp],\n\u001b[1;32m      3\u001b[0m        \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvec\u001b[39m\u001b[38;5;124m\"\u001b[39m: [data\u001b[38;5;241m.\u001b[39mtolist()]}\n\u001b[0;32m----> 5\u001b[0m resp \u001b[38;5;241m=\u001b[39m \u001b[43mrequests\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpost\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mPHASENET_API_URL\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m/predict\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjson\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreq\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28mprint\u001b[39m(resp)\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mPicks\u001b[39m\u001b[38;5;124m'\u001b[39m, resp\u001b[38;5;241m.\u001b[39mjson())\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/requests/api.py:115\u001b[0m, in \u001b[0;36mpost\u001b[0;34m(url, data, json, **kwargs)\u001b[0m\n\u001b[1;32m    103\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpost\u001b[39m(url, data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, json\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m    104\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Sends a POST request.\u001b[39;00m\n\u001b[1;32m    105\u001b[0m \n\u001b[1;32m    106\u001b[0m \u001b[38;5;124;03m    :param url: URL for the new :class:`Request` object.\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    112\u001b[0m \u001b[38;5;124;03m    :rtype: requests.Response\u001b[39;00m\n\u001b[1;32m    113\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 115\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpost\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjson\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjson\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/requests/api.py:59\u001b[0m, in \u001b[0;36mrequest\u001b[0;34m(method, url, **kwargs)\u001b[0m\n\u001b[1;32m     55\u001b[0m \u001b[38;5;66;03m# By using the 'with' statement we are sure the session is closed, thus we\u001b[39;00m\n\u001b[1;32m     56\u001b[0m \u001b[38;5;66;03m# avoid leaving sockets open which can trigger a ResourceWarning in some\u001b[39;00m\n\u001b[1;32m     57\u001b[0m \u001b[38;5;66;03m# cases, and look like a memory leak in others.\u001b[39;00m\n\u001b[1;32m     58\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m sessions\u001b[38;5;241m.\u001b[39mSession() \u001b[38;5;28;01mas\u001b[39;00m session:\n\u001b[0;32m---> 59\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43msession\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/requests/sessions.py:589\u001b[0m, in \u001b[0;36mSession.request\u001b[0;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001b[0m\n\u001b[1;32m    584\u001b[0m send_kwargs \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m    585\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtimeout\u001b[39m\u001b[38;5;124m\"\u001b[39m: timeout,\n\u001b[1;32m    586\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mallow_redirects\u001b[39m\u001b[38;5;124m\"\u001b[39m: allow_redirects,\n\u001b[1;32m    587\u001b[0m }\n\u001b[1;32m    588\u001b[0m send_kwargs\u001b[38;5;241m.\u001b[39mupdate(settings)\n\u001b[0;32m--> 589\u001b[0m resp \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprep\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43msend_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    591\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m resp\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/requests/sessions.py:703\u001b[0m, in \u001b[0;36mSession.send\u001b[0;34m(self, request, **kwargs)\u001b[0m\n\u001b[1;32m    700\u001b[0m start \u001b[38;5;241m=\u001b[39m preferred_clock()\n\u001b[1;32m    702\u001b[0m \u001b[38;5;66;03m# Send the request\u001b[39;00m\n\u001b[0;32m--> 703\u001b[0m r \u001b[38;5;241m=\u001b[39m \u001b[43madapter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    705\u001b[0m \u001b[38;5;66;03m# Total elapsed time of the request (approximately)\u001b[39;00m\n\u001b[1;32m    706\u001b[0m elapsed \u001b[38;5;241m=\u001b[39m preferred_clock() \u001b[38;5;241m-\u001b[39m start\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/requests/adapters.py:486\u001b[0m, in \u001b[0;36mHTTPAdapter.send\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m    483\u001b[0m     timeout \u001b[38;5;241m=\u001b[39m TimeoutSauce(connect\u001b[38;5;241m=\u001b[39mtimeout, read\u001b[38;5;241m=\u001b[39mtimeout)\n\u001b[1;32m    485\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 486\u001b[0m     resp \u001b[38;5;241m=\u001b[39m \u001b[43mconn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43murlopen\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    487\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    488\u001b[0m \u001b[43m        \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    489\u001b[0m \u001b[43m        \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    490\u001b[0m \u001b[43m        \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    491\u001b[0m \u001b[43m        \u001b[49m\u001b[43mredirect\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    492\u001b[0m \u001b[43m        \u001b[49m\u001b[43massert_same_host\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    493\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpreload_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    494\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdecode_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    495\u001b[0m \u001b[43m        \u001b[49m\u001b[43mretries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmax_retries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    496\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    497\u001b[0m \u001b[43m        \u001b[49m\u001b[43mchunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    498\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    500\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (ProtocolError, \u001b[38;5;167;01mOSError\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[1;32m    501\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mConnectionError\u001b[39;00m(err, request\u001b[38;5;241m=\u001b[39mrequest)\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/urllib3/connectionpool.py:791\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)\u001b[0m\n\u001b[1;32m    788\u001b[0m response_conn \u001b[38;5;241m=\u001b[39m conn \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m release_conn \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    790\u001b[0m \u001b[38;5;66;03m# Make the request on the HTTPConnection object\u001b[39;00m\n\u001b[0;32m--> 791\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    792\u001b[0m \u001b[43m    \u001b[49m\u001b[43mconn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    793\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    794\u001b[0m \u001b[43m    \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    795\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    796\u001b[0m \u001b[43m    \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    797\u001b[0m \u001b[43m    \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    798\u001b[0m \u001b[43m    \u001b[49m\u001b[43mchunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    799\u001b[0m \u001b[43m    \u001b[49m\u001b[43mretries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    800\u001b[0m \u001b[43m    \u001b[49m\u001b[43mresponse_conn\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mresponse_conn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    801\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpreload_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpreload_content\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    802\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdecode_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdecode_content\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    803\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mresponse_kw\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    804\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    806\u001b[0m \u001b[38;5;66;03m# Everything went great!\u001b[39;00m\n\u001b[1;32m    807\u001b[0m clean_exit \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/urllib3/connectionpool.py:497\u001b[0m, in \u001b[0;36mHTTPConnectionPool._make_request\u001b[0;34m(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)\u001b[0m\n\u001b[1;32m    494\u001b[0m \u001b[38;5;66;03m# conn.request() calls http.client.*.request, not the method in\u001b[39;00m\n\u001b[1;32m    495\u001b[0m \u001b[38;5;66;03m# urllib3.request. It also calls makefile (recv) on the socket.\u001b[39;00m\n\u001b[1;32m    496\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 497\u001b[0m     \u001b[43mconn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    498\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    499\u001b[0m \u001b[43m        \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    500\u001b[0m \u001b[43m        \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    501\u001b[0m \u001b[43m        \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    502\u001b[0m \u001b[43m        \u001b[49m\u001b[43mchunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    503\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpreload_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpreload_content\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    504\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdecode_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdecode_content\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    505\u001b[0m \u001b[43m        \u001b[49m\u001b[43menforce_content_length\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43menforce_content_length\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    506\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    508\u001b[0m \u001b[38;5;66;03m# We are swallowing BrokenPipeError (errno.EPIPE) since the server is\u001b[39;00m\n\u001b[1;32m    509\u001b[0m \u001b[38;5;66;03m# legitimately able to close the connection after sending a valid response.\u001b[39;00m\n\u001b[1;32m    510\u001b[0m \u001b[38;5;66;03m# With this behaviour, the received response is still readable.\u001b[39;00m\n\u001b[1;32m    511\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBrokenPipeError\u001b[39;00m:\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/urllib3/connection.py:395\u001b[0m, in \u001b[0;36mHTTPConnection.request\u001b[0;34m(self, method, url, body, headers, chunked, preload_content, decode_content, enforce_content_length)\u001b[0m\n\u001b[1;32m    393\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m header, value \u001b[38;5;129;01min\u001b[39;00m headers\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m    394\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mputheader(header, value)\n\u001b[0;32m--> 395\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mendheaders\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    397\u001b[0m \u001b[38;5;66;03m# If we're given a body we start sending that in chunks.\u001b[39;00m\n\u001b[1;32m    398\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunks \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/http/client.py:1280\u001b[0m, in \u001b[0;36mHTTPConnection.endheaders\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1278\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   1279\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m CannotSendHeader()\n\u001b[0;32m-> 1280\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_output\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmessage_body\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencode_chunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencode_chunked\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/http/client.py:1040\u001b[0m, in \u001b[0;36mHTTPConnection._send_output\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1038\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\r\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer)\n\u001b[1;32m   1039\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer[:]\n\u001b[0;32m-> 1040\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmsg\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1042\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m message_body \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m   1043\u001b[0m \n\u001b[1;32m   1044\u001b[0m     \u001b[38;5;66;03m# create a consistent interface to message_body\u001b[39;00m\n\u001b[1;32m   1045\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(message_body, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mread\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m   1046\u001b[0m         \u001b[38;5;66;03m# Let file-like take precedence over byte-like.  This\u001b[39;00m\n\u001b[1;32m   1047\u001b[0m         \u001b[38;5;66;03m# is needed to allow the current position of mmap'ed\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m         \u001b[38;5;66;03m# files to be taken into account.\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/http/client.py:980\u001b[0m, in \u001b[0;36mHTTPConnection.send\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    978\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    979\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mauto_open:\n\u001b[0;32m--> 980\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    981\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    982\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m NotConnected()\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/urllib3/connection.py:243\u001b[0m, in \u001b[0;36mHTTPConnection.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    242\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconnect\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 243\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_new_conn\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    244\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tunnel_host:\n\u001b[1;32m    245\u001b[0m         \u001b[38;5;66;03m# If we're tunneling it means we're connected to our proxy.\u001b[39;00m\n\u001b[1;32m    246\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_has_connected_to_proxy \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/urllib3/connection.py:203\u001b[0m, in \u001b[0;36mHTTPConnection._new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Establish a socket connection and set nodelay settings on it.\u001b[39;00m\n\u001b[1;32m    199\u001b[0m \n\u001b[1;32m    200\u001b[0m \u001b[38;5;124;03m:return: New socket connection.\u001b[39;00m\n\u001b[1;32m    201\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    202\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 203\u001b[0m     sock \u001b[38;5;241m=\u001b[39m \u001b[43mconnection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate_connection\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    204\u001b[0m \u001b[43m        \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_dns_host\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mport\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    205\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    206\u001b[0m \u001b[43m        \u001b[49m\u001b[43msource_address\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msource_address\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    207\u001b[0m \u001b[43m        \u001b[49m\u001b[43msocket_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msocket_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    208\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    209\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m socket\u001b[38;5;241m.\u001b[39mgaierror \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    210\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m NameResolutionError(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhost, \u001b[38;5;28mself\u001b[39m, e) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/barbara/lib/python3.9/site-packages/urllib3/util/connection.py:73\u001b[0m, in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m     71\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m source_address:\n\u001b[1;32m     72\u001b[0m     sock\u001b[38;5;241m.\u001b[39mbind(source_address)\n\u001b[0;32m---> 73\u001b[0m \u001b[43msock\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[43msa\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     74\u001b[0m \u001b[38;5;66;03m# Break explicitly a reference cycle\u001b[39;00m\n\u001b[1;32m     75\u001b[0m err \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "req = {\"id\": [[data_id]],\n",
    "       \"timestamp\": [timestamp],\n",
    "       \"vec\": [data.tolist()]}\n",
    "\n",
    "resp = requests.post(f'{PHASENET_API_URL}/predict', json=req)\n",
    "print(resp)\n",
    "print('Picks', resp.json())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Get both picks and prediction (time series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<Response [200]>\n",
      "Picks [{'station_id': 'BW.RJOB..EH', 'phase_time': '2009-08-24T00:20:07.710', 'phase_score': 0.978, 'phase_type': 'P', 'dt': 0.01}, {'station_id': 'BW.RJOB..EH', 'phase_time': '2009-08-24T00:20:08.680', 'phase_score': 0.924, 'phase_type': 'S', 'dt': 0.01}]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "resp = requests.post(f'{PHASENET_API_URL}/predict_prob', json=req)\n",
    "print(resp)\n",
    "picks, preds = resp.json() \n",
    "preds = np.array(preds)\n",
    "print('Picks', picks)\n",
    "\n",
    "plt.figure()\n",
    "plt.subplot(211)\n",
    "plt.plot(data[:,-1], 'k', label=\"Z\")\n",
    "plt.subplot(212)\n",
    "plt.plot(preds[0, :, 0, 1], label=\"P\")\n",
    "plt.plot(preds[0, :, 0, 2], label=\"S\")\n",
    "plt.legend()\n",
    "plt.show();"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "barbara",
   "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": "3.9.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}