examples: add an IPython notebook showcase

This is a small example on how to use the artiq functionality in an IPython notebook. This can be expanded and provides a much more powerful shell than the one integrated in the GUI. Potentially, some shared functionality between this and artiq_client could be factored out.
m-labs · Jan 31, 2016 · f14fed5 · f14fed5 · sbourdeauducq · Jan 31, 2016
1 parent 6889149
commit f14fed5
Showing 2 changed files with 342 additions and 0 deletions.
diff --git a/.gitignore b/.gitignore
@@ -6,6 +6,7 @@ __pycache__/
 *.bin
 *.elf
 *.fbi
+.ipynb_checkpoints
 /doc/manual/_build
 /build
 /dist

diff --git a/examples/artiq_ipython_notebook.ipynb b/examples/artiq_ipython_notebook.ipynb
@@ -0,0 +1,341 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Populating the interactive namespace from numpy and matplotlib\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pylab inline\n",
+    "\n",
+    "import os\n",
+    "import logging\n",
+    "import time\n",
+    "import asyncio\n",
+    "import datetime\n",
+    "import glob\n",
+    "\n",
+    "import numpy as np\n",
+    "np.set_printoptions(precision=3)\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn\n",
+    "seaborn.set_style(\"whitegrid\")\n",
+    "import pandas as pd\n",
+    "import h5py\n",
+    "\n",
+    "from artiq.protocols.pc_rpc import (Client, AsyncioClient,\n",
+    "                                    BestEffortClient, AutoTarget)\n",
+    "from artiq.master.databases import DeviceDB\n",
+    "from artiq.master.worker_db import DeviceManager"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# let's assume artiq_master and artiq_ctlmgr are already running\n",
+    "# move to a location where we have our artiq setup\n",
+    "os.chdir(os.path.expanduser(\"~/work/nist/artiq/run\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# you can directly use the artiq controller infrastructure\n",
+    "# and access any artiq device\n",
+    "\n",
+    "# you can have artiq prepare that for you:\n",
+    "\n",
+    "ddb = DeviceDB(\"device_db.pyon\")\n",
+    "devmgr = DeviceManager(ddb)\n",
+    "lda = devmgr.get(\"lda\")\n",
+    "lda.set_attenuation(42)\n",
+    "assert lda.get_attenuation() == 42\n",
+    "\n",
+    "# ... or you can wire it up yourself if you know where it is\n",
+    "assert ddb.get(\"lda\")[\"host\"] == \"::1\"\n",
+    "assert ddb.get(\"lda\")[\"port\"] == 3253\n",
+    "\n",
+    "# synchronous\n",
+    "lda = Client(\"::1\", 3253)\n",
+    "assert lda.get_attenuation() == 42\n",
+    "\n",
+    "# asyncio\n",
+    "lda = AsyncioClient()\n",
+    "async def test_lda():\n",
+    "    await lda.connect_rpc(\"::1\", 3253, AutoTarget)\n",
+    "    return await lda.get_attenuation()\n",
+    "assert asyncio.get_event_loop().run_until_complete(test_lda()) == 42\n",
+    "\n",
+    "# best effort\n",
+    "lda = BestEffortClient(\"::1\", 3253, AutoTarget)\n",
+    "assert lda.get_attenuation() == 42"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "current schedule {}\n",
+      "experiments ['__pycache__/', 'flopping_f_simulation.py', 'notebook_test.py', '.git/', 'idle.elf', 'transport.py', 'idle.py', 'speed_benchmark.py', 'test_raise.py']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# let's connect to the master\n",
+    "\n",
+    "schedule, exps, datasets = [\n",
+    "    Client(\"::1\", 3251, \"master_\" + i) for i in\n",
+    "    \"schedule experiment_db dataset_db\".split()]\n",
+    "\n",
+    "print(\"current schedule\", schedule.get_status())\n",
+    "print(\"experiments\", exps.list_directory(\"repository\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "current schedule {131: {'priority': 0, 'status': 'preparing', 'repo_msg': None, 'pipeline': 'main', 'due_date': None, 'flush': False, 'expid': {'file': 'repository/flopping_f_simulation.py', 'arguments': {'noise_amplitude': 0.1, 'F0': 1500}, 'log_level': 30, 'class_name': 'FloppingF'}}}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# we can submit experiments to be run:\n",
+    "\n",
+    "expid = dict(\n",
+    "    file=\"repository/flopping_f_simulation.py\",\n",
+    "    class_name=\"FloppingF\",\n",
+    "    log_level=logging.WARNING,\n",
+    "    arguments=dict(\n",
+    "        F0=1500,\n",
+    "        noise_amplitude=.1,\n",
+    "    ),\n",
+    ")\n",
+    "if not schedule.get_status():\n",
+    "    rid = schedule.submit(pipeline_name=\"main\", expid=expid,\n",
+    "        priority=0, due_date=None, flush=False)\n",
+    "print(\"current schedule\", schedule.get_status())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# wait for experiment to finish\n",
+    "# this can be written nicer by subscribing and reacting to scheduler changes\n",
+    "while rid in schedule.get_status():\n",
+    "    time.sleep(.1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "flopping_f 1499.996784076909\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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DMFB3xY9LjUGEwhqCkShCYQ1aVMeoYfkYPSIvbcMC/c21DdOuStpyDgQCePLJJ3Hp0iVo\nmoaHHnoI5eXlWLNmDVRVxahRo7Bhw4ZOu7riLwLKrL5Sz6Gwhj99fB7vbv8EZ+tjQyZOuxKbs+Cy\n4bYxRfjyXTehqCB5K/PCJR9+snkvjtZchdtpxeJ7J+CLny1pd7y8/oof63/+F5xr8GLqhCFY+eCN\n3cxVf9mNV//cgvMXfVjz9an47C1Du/13vvybQ/jNtlO4fWwR9p64hLtuLcaqr03p9vEyQdcNfHXN\neygqcOFLd5TixXcO4rPlQ3rUvf3r90/g1d8dxa1jBuJ7//tzN3y4fe032/HWzkZouoF/+J+34QtT\nRrZ7nEBIxUvvHMQHe87BbrPgwdnj8eW7ytrtUr6WYRiovezHx8cu4viZRnxS2xybL9La7SrLEqaM\nH4xZU0eiYvzgpMczq75yvRBZT+o4acvZ5XLh+eefv+HnlZWV3TohUTIOu4I5d5Ri9rQS+IIqnHal\n2xfIYUUePPP3d+EPVTV49XdH8MKb+/HBnnP4+/m3onigB1dbQrjcFETdZT9eee8wmn0RfGXGKHz9\nb8rb7RGxKTK+u2gyvvOTbfjJG3vxk2H5KX1I+LRdh+vxm22nMKzIgycWT8XXn/5PnK5N33yMdLnY\nGEAwHEXpkFzM+VwZdhyow18O12Pr3guY+ZnhXT7e/hOXsOn3RzEwz4HHHpzcbh2PG+7EhkcmYP3P\nP8Lzm/eiyRvGfX81+roPA8dqruLHr1Wj/koAo0fkY+UDFRhWlNo8AEmSEr1HfzM99rOIGpvUWX/V\nj/Kywh71DBClg3izT4haSZKEHFfPu/4ssoR77yzDtFuGYOO/H8TOA3X4h2f/BAO4bpKLLEtYdv8k\nfOlzZZ0er6w4D9/4yi342VsH8KNNe/DM8jtTnmAEAJcag3h+88ewKjJWfW1yolv16OkrCEU0OGzi\nvC3P1MU+MJQW50KWJfzD392Gbz77J2x85wBuHT2wSyF2uSmIH/1yD2RZwqqHpnQ6S3h82QD84Jt3\nYe3GKrzy3hG8s/VkbJasIsOqyDh30QfDMDD/C2Ow8K9v7nHr1ma1YPSIfIwekd+j4xClizhXAaIM\nK8xz4omHpmLX4Xq8+cF/Q7HIKMx3YGCeEwPzHBhfVoibhuWldKzZd5Ri/39fxo4DtfhDVQ3uveum\nlJ5nGAb+z+vV8AZULLt/EsqKY+crG5qLw59cwdl6L8aOvHEMvbfUtIZzydBcAMCQQjcW3zsBL71z\nEC+9cxCPP5R6N/yrvzuCZl8ES+dOxM0lA5I+fuSQXPzwWzPwwpv7UH8lADWqIxTR4A3oGFbkwbL7\nJ2HiqIHd+8OIBMdwpn5navkQTC0f0qNjSJKER+6bhN1HG/Dmn07ii9NKk97+BQCHTl3BoVNXMHn8\nYMy5ozTx89LWkD5d2yJkOJcOyU387EufK8MHe85h58Fa1F5O7bayS41BbNt7ASMGe5L2TFyrqMCJ\ndd+4o+sFJzK5vjnTgSgL8nPsmH1HCS43BfHBnnMpPefdHbH70Od/Ycx1Y6hlxbHwq6ltTn9Be+BM\nfQtcDuW6cXVZlvA/ZoyCYQC/31mT0nF+++EpRHUDc+8enfLiNUT9GcOZqAfumzkaikXGmx+cQDTJ\nIhCXGoP46FA9birOw/jS67t1Rw7JgSwBp+vEmRQWUaO4cMmPkiG5N8zMvnNSMfJz7PivXWcTqzd1\nxB9U8cePzmBArh0zK7o+iYyoP2I4E/VAYZ4Tsz47EvVXAti693ynj/3DRzXQdQP33lV2Q9g5bAqG\nDvSgprYZSe5uzJpzDV7ouoHSobk3/M6qyJg9rRT+oIo/f9z53/3Hj2oQDGv48l038X5ZohQxnIl6\naN5fjYFFlvCrLSc6XKJQ1aL440c18DitmHH7sHYfU1acC39Iw6VuLKeaCWfq22Zqt2f2HSWwyBLe\n23G6ww8Uqqbjtx9+AofNct0YOxF1juFM1EODBrjw+ckjcOGSHzv2X2j3Mdv316LZF8Gsz5Z0eKtU\nPARrBOnajt93XTKk/XAuzHPijolDUVPXgsOfXGn3Mdv2nseV5hC+OK0EnjTcFkfUXzCcidJg/hfG\nQpYlvLHlRLsbN7y3/TQkCfjS50o7PEZZYsa2GJPCEvc4t9OtHffl1lvI3t1x+obfGYaBd/58ErIs\n4SvTR2WmkER9FMOZKA2GDnTj7tuH4Wy9Fx8dqrvudyfOxtZcnjx+MIYUujs8RjwERVkp7Ex9C4oK\nnJ1u5zihbADKinNRdbAOl5uu747/+PhFnKn3YvqtwzBoQM83yyDqTxjORGky/wtjIUnA85v34uXf\nHELD1QAA4L3WVuWX7+x8oZKi/FgQ1tT1fsu52RfG1ZZwh13acZIk4d47b4KuG/hDVQ2A2Pj6x8cv\novL3RwEAc2ey1UzUVVyEhChNRgzOwd/Puw2v/fEofrPtFP7jw1OYNnEodh9pQPFAN24bW9Tp8yVJ\nQllxbKWwUFiDoxf3do5PBivrYDLYte7+zDC88u5h/L6qBmcbvNh34mJin+I7Jg7FqOFcEpOoqxjO\nRGn019NK8PnJI/Dhvgv4zdZT2Hkg1sV9711lKS2+UTo0F4dOXcHZht5dxrMmyWSwazlsCmZ9tgTv\n/Pkkqg7WYehAN7742SGYWj4Y5WWFmS4qUZ/EcCZKM6si4/OTR+CvKobj0KkrOH62EbOnlab03Gsn\nhfVqOKcwGexaC784DqVDczB2ZAGGD8rJZNGI+gWGM1GGSJKEiaMHYuLo1DdniHcj9/aksDP1LVAs\nEoYNSm0bRoddwecnt7/vMhF1HSeEEQlk5JBcyFLv3uus6wbO1HsxfFBOj7diJKLu4TuPSCB2qwXF\nRb27jGf9VT/CkWjKXdpElH4MZyLBlBXnwR/ScLGXlvFMZfERIsoshjORYOKh2FvbRyZmajOciXoN\nw5lIMIlJYb007lzThXuciSgzGM5Egom3WM/We3vl/Ocv+uB2KBiQ6+iV8xMRw5lIOAU5dgCA1x/p\nlfN7/RHkeew37DlNRNnDcCYSjFWxwGa1wBdSe+X8/qDa6WYXRJR5DGciAXmcCvzB7IdzRI0iounw\nMJyJehXDmUhAbqcNvkD2wzn+gYAtZ6LexXAmEpDHaYU/pGZ9IRIfw5lICAxnIgG5nVbouoFQJJrV\n88ZbzuzWJupdDGciAcXDMdtd22w5E4mB4UwkoHg4+rM8Yzsezh6XLavnJaLrMZyJBJQI5yzP2E50\nazvYcibqTQxnIgG1dWtndyESXzB2PnZrE/UuhjORgHqrW9sf1AAAHhfDmag3MZyJBOTupQlhvM+Z\nSAwMZyIBeXppzDnerc1bqYh6F8OZSECJlnPWu7Vj53NxQhhRr2I4EwmoN+9zttsssCq8NBD1JiXZ\nA9555x28/fbbkCQJ4XAYx44dw+bNm7F06VKUlpYCABYsWIA5c+ZkuqxE/UZvdWv7gyq7tIkEkDSc\n586di7lz5wIA1q9fj3nz5uHQoUN4+OGHsXjx4kyXj6hfcjp6a7a2ioJcR1bPSUQ3Srnv6uDBgzh5\n8iTmz5+Pw4cP489//jMefPBBrF69GoFAIJNlJOp3LLIEl0PJare2rhtsORMJIuVw3rhxI771rW8B\nAG699VZ897vfxaZNmzBixAj89Kc/zVgBifqr+M5U2RKKaNAN3kZFJIKk3doA4PV6UVNTgylTpgAA\n7rnnHuTk5AAAZs2ahQ0bNiQ9RnV1dQ+KSaliPWdetupYMjQ0+7Wsna/JH1uAJBzw9vrrqLfP31+w\nnsWVUjjv3r0b06ZNS3y/ZMkSPPXUU5g4cSKqqqpQXl6e9BgVFRXdLyWlpLq6mvWcYdms46K/bEdD\n0xXcdvtnYJGljJ/vdG0zgHqMHD4YFRWTMn6+jvB1nB2s58zryYeflML59OnTGDFiROL7733ve1i/\nfj2sViuKioqwfv36bheAiNoXH/sNhFTkZGGXKG4XSSSOlMJ5yZIl130/fvx4vP766xkpEBHFXLsz\nVVbCuXXymcfJ7SKJehtXGiASVLbX105sF+lM6TM7EWUQw5lIUPEWbLYWImG3NpE4GM5EgnK3tmCz\ntb52W8uZ3dpEvY3hTCSobK+vHd+Rii1not7HcCYSVLa7tdtazgxnot7GcCYSVGK2dta6tbXrzktE\nvYfhTCSottnakayczxeMQJIAp52ztYl6G8OZSFBt20ZqWTmfP6jC7bBCzsJqZETUOYYzkaCy3a3t\nC6rs0iYSBMOZSFAOmwWyLGWtW9sfVOFxMZyJRMBwJhKUJElZ2zZSi+oIRaJwOxjORCJgOBMJzO20\nZuVWKj9XByMSCsOZSGBupzUri5DwHmcisTCciQTmcVoR0XRE1GhGz8N1tYnEwnAmEli2ZmzHw5kT\nwojEwHAmEli21tdOdGtzQhiREBjORALzZLnlzG5tIjEwnIkE5s52y9nF7SKJRMBwJhJYYsw5w7dT\nxRc64X3ORGJgOBMJLFvd2v5QfEcqbnpBJAKGM5HAstWtHW85s1ubSAwMZyKBZatbmyuEEYmF4Uwk\nsOx1a6uwKjLsVktGz0NEqWE4Ewkse93a3C6SSCQMZyKBebLVrR1SOVObSCAMZyKBWRULbFYLfBns\n1jYMA74A93ImEgnDmUhwHqcCfwa7tcORKKK6wW5tIoEwnIkE53ZaE8trZkJ8shm3iyQSB8OZSHAe\npw3+kArDMDJy/PhkM7acicTBcCYSnNtpha4bCIa1jBw/sV0kw5lIGAxnIsHFZ1H7g5kJZz/DmUg4\nDGciwcVnUWdqIRJuF0kkHoYzkeDaFiKJZOT4bS1nrqtNJAqGM5Hg2rq1M91y5o5URKJgOBMJLtPd\n2tz0gkg8DGciwWV6fW1fsHW7SHZrEwkjaT/WO++8g7fffhuSJCEcDuPYsWP45S9/iX/6p3+CLMsY\nM2YM1q5dm42yEvVLngx3a7PlTCSepC3nuXPnorKyEq+++irKy8uxZs0avPDCC1ixYgU2bdoEXdex\nZcuWbJSVqF9yt3ZrZ2p97cSYs4NjzkSiSLlb++DBgzh58iTmz5+Pw4cPY/LkyQCAGTNmoKqqKmMF\nJOrvPBnu1vYHVTjtCiwWjnIRiSLlj8obN27Et771rRt+7na74fV6kz6/urq6ayWjbmE9Z1626zgQ\n1gEAF+ovZeTcV5v9sFrEeu2IVJa+jPUsrpTC2ev1oqamBlOmTAEAyHLbJ2y/34/c3Nykx6ioqOhm\nESlV1dXVrOcM6406juoG8NZvYbW7M3Ju9e33MKjAJcxrh6/j7GA9Z15PPvyk1I+1e/duTJs2LfH9\n+PHjsXv3bgDAtm3b+D+YKIMssgSXQ8lIt3ZUNxAIaZwMRiSYlFrOp0+fxogRIxLfr1q1Ck899RRU\nVcWoUaMwe/bsjBWQiGIzqTNxn3OA20USCSmlcF6yZMl135eWlqKysjIjBSKiG3mcVtRfCaT9uLyN\nikhMnJ5JZAJupxXBsIZoVE/rcbldJJGYGM5EJhBfXzuQ5j2d/QGGM5GIGM5EJhDvdk73KmHxcWyn\ng+FMJBKGM5EJuOyx6SHBNLecQ5HY8Zx2rg5GJBKGM5EJOB2ZCedgOAqgLfyJSAwMZyITcNhi4Rlq\nDdN0CbWGvcNuSetxiahnGM5EJhAPz/S3nOPhzJYzkUgYzkQmkKkx5yDHnImExHAmMgFHpiaEtXaT\nM5yJxMJwJjKBxJhzJEPd2jaOOROJhOFMZALOTHVrh9mtTSQihjORCWQqnOMtcbuN4UwkEoYzkQnE\nwzndt1IFwxrsNgssspTW4xJRzzCciUwgcStVmsecQ2GNXdpEAmI4E5mA05a5FcKc7NImEg7DmcgE\n7DYLJKltRa90CYY1rg5GJCCGM5EJSJIEh01J65izYRgIRditTSQihjORSTjtlrR2a4fVKAyDS3cS\niYjhTGQSTruS1glhidXBOOZMJByGM5FJOOxKWlvOQe5IRSQshjORSTjtCsKRKKK6kZbjhbjpBZGw\nGM5EJhFfXzucpq5tLt1JJC6GM5FJpHsJz7ZNLxjORKJhOBOZRGIJz0h6bqfidpFE4mI4E5lEYgnP\nNLecnZwQRiQchjORSaR7Cc+22dpsOROJhuFMZBJtO1OlJ5w5W5tIXAxnIpNwpHnbSE4IIxIXw5nI\nJOIt3EAV6YmfAAATZklEQVTax5wZzkSiYTgTmUR84lYoTfc5c7Y2kbgYzkQm4Uj3hLAIl+8kEhXD\nmcgknI70TghLdGtzzJlIOAxnIpNI961UobAGSQLsNraciUTDcCYyCUeal+8MhaNw2BRIkpSW4xFR\n+jCciUwi3ct3BiMaVwcjEhTDmcgknBlYvpMztYnElNI7c+PGjfjggw+gqioWLlyICRMmYOnSpSgt\nLQUALFiwAHPmzMlkOYn6PatigWKR0jrmXJjnSMuxiCi9kobzrl27sHfvXmzevBmBQAD/+q//Cl3X\n8fDDD2Px4sVZKCIRxTlsSlpma+u6gVAkytXBiASV9J25fft2jB07FsuXL4ff78djjz2GN998EzU1\nNdiyZQtKSkqwevVquFyubJSXqF9z2JW0tJy5rjaR2CTDMIzOHvDUU0+htrYWL730Es6dO4dly5Zh\n6dKlGDduHCZMmIAXX3wRzc3NWLVqVYfHqK6uTnvBifqjF96rhy+kY9X9xT06jjcYxY/fqUP5SCfm\n31WYptIR0adVVFR063lJPzbn5+dj1KhRUBQFZWVlsNvtuPvuuzFgwAAAwKxZs7Bhw4aMFZBSV11d\nzXrOsN6u44LtW9Hkb+lxGWov+QDUoXhIESoqbk9P4dKkt+u4v2A9Z15PGqZJZ2tXVFTgww8/BAA0\nNDQgGAxi6dKlOHDgAACgqqoK5eXl3S4AEaXOYVOgajq0qN6j4wS46QWR0JK+M2fOnIk9e/Zg3rx5\nMAwD69atQ0FBAdavXw+r1YqioiKsX78+G2Ul6veu3dPZ47J1+zghhjOR0FJ6Z65cufKGn73++utp\nLwwRdc6ZWCUsCk8P5mDGFzJxMJyJhMRFSIhMpC2c1R4dJxiKb3rBFcKIRMRwJjIRR5qW8IxvFxnf\n6YqIxMJwJjKReEu3p/c6x8ecuQgJkZgYzkQmEm/p9jSc4y1njjkTiYnhTGQi8ZZuT5fwjI85uxjO\nREJiOBOZSLr2dOZsbSKxMZyJTMR1za1UPRFMjDlztjaRiBjORCbiaN3TOb5xRXcFuQgJkdAYzkQm\n4kxXtzbDmUhoDGciE4lPCEvHmLMsS7AqvAQQiYjvTCITaVtbu+djzk67AkmS0lEsIkozhjORiaSr\nWzsY1rh0J5HAGM5EJhKfXd3TCWGhiMbbqIgExnAmMhGLRYZNkXvecg5pnAxGJDCGM5HJOB1Kj8I5\nGtUR0XSGM5HAGM5EJuOwKT1avjOxOhg3vSASFsOZyGSc9p61nOPj1Ww5E4mL4UxkMk67gmAkCsMw\nuvX8QCi+IxVnaxOJiuFMZDIOmwW6bkDV9G49ny1nIvExnIlMpqd7OscXMOGYM5G4GM5EJtPTJTy5\n6QWR+BjORCaTWMIz0r0lPNvCmWPORKJiOBOZTGIJz1A3u7Uj8QlhbDkTiYrhTGQy8VnWwW4u4clu\nbSLxMZyJTKZtZ6ruhnOsO9zJCWFEwmI4E5mMs4cTwuKhzvucicTFcCYyGUePW87s1iYSHcOZyGTi\noRrobjhzQhiR8BjORCbT01upQmw5EwmP4UxkMg5bbKy4u93aXCGMSHwMZyKT6enyncGwBsUiw6rw\n7U8kKr47iUymp7O1gxGNq4MRCY7hTGQy6Rhz5ngzkdgYzkQmY7NaIEk969bmTG0isTGciUxGliU4\nbJYehHOUq4MRCS6ld+jGjRvxwQcfQFVVLFy4EFOmTMHjjz8OWZYxZswYrF27NtPlJKJrOO1Kt2Zr\nq5oOLaqzW5tIcElbzrt27cLevXuxefNmVFZWoq6uDs888wxWrFiBTZs2Qdd1bNmyJRtlJaJWDpvS\nrZZz245UnBBGJLKk4bx9+3aMHTsWy5cvx7JlyzBz5kwcOXIEkydPBgDMmDEDVVVVGS8oEbVx2JVE\n0HZFMMzVwYjMIOk7tLGxEbW1tXjppZdw7tw5LFu2DLquJ37vdrvh9XozWkgiup7TriAYjkLXDciy\nlPLzuDoYkTkkfYfm5+dj1KhRUBQFZWVlsNvtaGhoSPze7/cjNzc36Ymqq6t7VlJKCes580So40jI\nDwD4aNce2K2pz+s8fzkMAGhuvCzE39ERkcvWl7CexZU0nCsqKlBZWYnFixejoaEBwWAQ06ZNw65d\nuzB16lRs27YN06ZNS3qiioqKtBSYOlZdXc16zjBR6vj9I3vw37UXMH7CRBTkOlJ+nnLiEoBLKB05\nHBUV4zJXwB4QpY77OtZz5vXkw0/ScJ45cyb27NmDefPmwTAMrFu3DsOGDcOaNWugqipGjRqF2bNn\nd7sARNR18fW1g2ENBV14XnxHKnZrE4ktpXfoypUrb/hZZWVl2gtDRKmJh2tXZ2y3jTlztjaRyLgI\nCZEJdXcJz8RsbS5CQiQ0hjORCTm62XIOtm4XyW5tIrExnIlMyHnNmHNXhDjmTGQKDGciE+runs5t\ni5BwzJlIZAxnIhOKjxl3dX1tjjkTmQPDmciEErO1u7iEZ6h1zNnlYDgTiYzhTGRCiXAOseVM1Bcx\nnIlMqLuztRO7Utk45kwkMoYzkQm5HVYAQKCLLWdfUIXDZoHFwrc+kcj4DiUyIY8rFs6+oNql5/mC\nKjxOayaKRERpxHAmMiGHzQKLLMEbiHTpef5ABB6XLUOlIqJ0YTgTmZAkSchx2eALpN5yjuoG/CEt\n0eomInExnIlMyu20wt+Fbu34Y9mtTSQ+hjORSXlcVngDERiGkdLjfcFYF7jHyW5tItExnIlMKsdl\nQ1Q3Ut6ZKt4Fzm5tIvExnIlMKt49neq4c3xmN8OZSHwMZyKTSoRzMLUZ274Au7WJzILhTGRS8Vui\nutxy5oQwIuExnIlMqm0hklRbzuzWJjILhjORScVbwN4utpxzuAgJkfAYzkQmldPVbu3EmDNbzkSi\nYzgTmZS7qxPCWlvOboYzkfAYzkQmlRhzTrnlzAlhRGbBcCYyqbZbqVIdc47A5VC4XSSRCfBdSmRS\nbbdSpdat7Q1wu0gis2A4E5mU3WqBTZHhTbHl7A9GuAAJkUkwnIlMzOOywp/CmLMW1REMR3mPM5FJ\nMJyJTMzjsqU0W9vPdbWJTIXhTGRiHqcVvqAKXe9820gv19UmMhWGM5GJeZw2GAYQCGudPo7rahOZ\nC8OZyMTa7nXuvGub62oTmQvDmcjEUl2IpG0vZ3ZrE5kBw5nIxOJjyMkmhXFdbSJzYTgTmViOK7VV\nwjjmTGQuDGciE0t120iOOROZC8OZyMRSXcIz3u3NvZyJzEFJ5UH33XcfPB4PAGD48OFYtGgRli5d\nitLSUgDAggULMGfOnIwVkojaF28J+5N1a3NHKiJTSRrOkUjsE/err76a+Nmvf/1rPPzww1i8eHHG\nCkZEyaXcrR1UIUmAy8FwJjKDpOF87NgxBAIBLFmyBNFoFI8++igOHz6MmpoabNmyBSUlJVi9ejVc\nLlc2yktE1+jKbG2XwwpZlrJRLCLqoaRjzg6HA0uWLMHPf/5zrFu3DitXrkR5eTm++93vYtOmTRgx\nYgR++tOfZqOsRPQpXbnPmV3aROaRtOVcWlqKkpKSxH/n5+djxowZGDx4MABg1qxZ2LBhQ9ITVVdX\n97ColArWc+aJVsc2RcLFK82dlqvZF0ZRniJc2TtilnKaHetZXEnD+a233sKJEyewdu1aNDQ0wOfz\nYfny5Vi7di0mTZqEqqoqlJeXJz1RRUVFWgpMHauurmY9Z5iIdZz7uyvQ0fF7TNWi0F47j8GF+cKV\nvT0i1nFfxHrOvJ58+EkazvPmzcMTTzyBhQsXQpZlPPPMM7Db7Vi/fj2sViuKioqwfv36bheAiHom\nx2VFw9VAh7+Pd3m7eY8zkWkkDWer1Ypnn332hp+//vrrGSkQEXWNx2nD6VALolEdFsuN00i4OhiR\n+XAREiKT8yRZwjO+lzMXICEyD4YzkcnFW8QdLUTCljOR+TCciUwuvoSnt4MlPLmuNpH5MJyJTC7e\nIu6oWzu+QEl8wRIiEh/DmcjkcpIsRMKWM5H5MJyJTC6xhGdH3doccyYyHYYzkcm5k8zWjoe2h7O1\niUyD4UxkcjnJwpktZyLTYTgTmVy8W7uz2dqyLMHlSGn7diISAMOZyOSS7UzlC0bgdlghSdwuksgs\nGM5EJudyWCFJnY05q5ypTWQyDGcik7PIElwOa7uztQ3D4F7ORCbEcCbqAzxOa7st57AaharpXFeb\nyGQYzkR9QI6r/XD2c6Y2kSkxnIn6AI/ThnAkClWLXvdz7uVMZE4MZ6I+wN3BjG3e40xkTgxnoj4g\nPqb86a5t7uVMZE4MZ6I+IN4y/vRCJIlNL9hyJjIVhjNRH9DRtpGJbm2OOROZCsOZqA+Ib2px45gz\n93ImMiOGM1Ef0LaEZwfd2mw5E5kKw5moD+iwWzsx5syWM5GZMJyJ+oCOZmsnurXZciYyFYYzUR/Q\n4WztoAqLLMFhs/RGsYiomxjORH1AR9tG+gIReFzcLpLIbBjORH2A065AlqXEWtpxsR2pON5MZDYM\nZ6I+QJIkeJzW67q1DcPgXs5EJsVwJuojPr1tZCgSRVQ3uDoYkQkxnIn6iByXDb6ACsMwALRNDmO3\nNpH5KL1dACJKD4/LCi2qY94T76Egxw6XI/b2zmG3NpHpMJyJ+oi5d4+GLEtobAmh0RvGmXovAOCm\nYXm9XDIi6iqGM1EfcevYItw6tijxva4bCEU0uBxsOROZDcecifooWZYYzEQmxXAmIiISDMOZiIhI\nMAxnIiIiwaQ0Iey+++6Dx+MBAAwfPhyPPPIIHn/8cciyjDFjxmDt2rUZLSQREVF/kjScI5HYQgav\nvvpq4mfLli3DihUrMHnyZKxduxZbtmzBPffck7lSEhER9SNJu7WPHTuGQCCAJUuWYPHixdi/fz+O\nHDmCyZMnAwBmzJiBqqqqjBeUiIiov0jacnY4HFiyZAnmz5+PmpoafOMb30gsDwgAbrcbXq83o4Uk\nIiLqT5KGc2lpKUpKShL/nZ+fjyNHjiR+7/f7kZubm/RE1dXVPSgmpYr1nHms48xjHWcH61lcScP5\nrbfewokTJ7B27Vo0NDTA5/PhzjvvxK5duzB16lRs27YN06ZN6/QYFRUVaSswERFRXycZ1/ZRt0NV\nVTzxxBOora2FLMt47LHHkJ+fjzVr1kBVVYwaNQobNmyAJEnZKjMREVGfljSciYiIKLu4CAkREZFg\nGM5ERESCYTgTEREJhuFMREQkmJTW1u4uwzCwbt06HD9+HDabDd///vcxYsSITJ6yX9A0DU8++SQu\nXLgAVVXxyCOPYPTo0VzvPEOuXLmC+++/H7/4xS9gsVhYz2m2ceNGfPDBB1BVFQsXLsSUKVNYx2mk\naRpWrVqFCxcuQFEUPP3003wdp9n+/fvx7LPPorKyEmfPnm23bn/1q1/hjTfegNVqxSOPPIKZM2d2\nesyMtpy3bNmCSCSCzZs34zvf+Q6eeeaZTJ6u3/jtb3+LgoIC/PKXv8TLL7+Mp59+Gs888wxWrFiB\nTZs2Qdd1bNmypbeL2Sdomoa1a9fC4XAAAOs5zXbt2oW9e/di8+bNqKysRF1dHes4zbZu3Qpd17F5\n82YsX74czz33HOs4jV5++eXErcVA+9eIy5cvo7KyEm+88QZefvll/PjHP048viMZDefq6mpMnz4d\nAHDrrbfi0KFDmTxdvzFnzhx8+9vfBgBEo1FYLBaud54hP/jBD7BgwQIMGjQIhmGwntNs+/btGDt2\nLJYvX45ly5Zh5syZrOM0Ky0tRTQahWEY8Hq9UBSFdZxGJSUleOGFFxLfHz58+Lq63blzJw4cOICK\nigooigKPx4PS0lIcP3680+NmNJx9Ph9ycnIS3yuKAl3XM3nKfsHpdMLlcsHn8+Hb3/42Hn30Ua53\nngFvv/02CgsLceeddybq99rXL+u55xobG3Ho0CH8y7/8C9atW4eVK1eyjtPM7Xbj/PnzmD17Nv7x\nH/8RixYt4vUijWbNmgWLxZL4/tN16/P54Pf7r8tCl8uVtM4zOubs8Xjg9/sT3+u6DlnmHLR0qKur\nwze/+U08+OCDuPfee/GjH/0o8btU1zunzr399tuQJAk7duzA8ePHsWrVKjQ2NiZ+z3ruufz8fIwa\nNQqKoqCsrAx2ux0NDQ2J37OOe+6VV17B9OnT8eijj6KhoQGLFi26rkuVdZxe12ZcvG49Hg98Pt8N\nP+/0OBkrIYDPfOYz2Lp1KwBg3759GDt2bCZP129cvnwZS5YswWOPPYa5c+cCAMaPH4/du3cDALZt\n28b1zNNg06ZNqKysRGVlJW6++Wb88Ic/xPTp01nPaVRRUYEPP/wQANDQ0IBgMIhp06Zh165dAFjH\n6ZCXlwePxwMAyMnJgaZpmDBhAus4QyZMmHDDNWLixImorq5GJBKB1+vFJ598gjFjxnR6nIy2nGfN\nmoUdO3bgq1/9KgBwQliavPTSS2hpacHPfvYzvPDCC5AkCatXr8aGDRsS653Pnj27t4vZJ61atQpP\nPfUU6zlNZs6ciT179mDevHmJuzuGDRt23dr9rOOeeeihh/Dkk0/igQcegKZpWLlyJcrLy1nHGdLe\nNUKSJCxatAgLFy6EYRhYsWIFbDZbp8fh2tpERESC4QAwERGRYBjOREREgmE4ExERCYbhTEREJBiG\nMxERkWAYzkRERIJhOBMREQnm/wMjA6onfM82FQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0d5095f2b0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# now that the experiment has completed, we can get the\n",
+    "# current value of the (live) dataset and plot it\n",
+    "# had we done this earlier, the dataset would have been incomplete\n",
+    "fig, ax = plt.subplots()\n",
+    "d = datasets.get(\"flopping_f_brightness\")\n",
+    "ax.plot(d)\n",
+    "print(\"flopping_f\", datasets.get(\"flopping_freq\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# this is how you would clear all pipelines\n",
+    "for i in schedule.get_status():\n",
+    "    schedule.delete(i)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "available datasets ['artiq_version', 'flopping_f_brightness']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# we can easily find and use the data that was saved as part\n",
+    "# of the experiment\n",
+    "\n",
+    "t = datetime.datetime.now()\n",
+    "f = os.path.join(\n",
+    "    \"results\", t.strftime(\"%Y-%m-%d\"), #t.strftime(\"%H-%M\"),\n",
+    "    \"*\", \"{:09d}-FloppingF.h5\".format(rid))\n",
+    "\n",
+    "# we would usually like to use pandas but our data doe not comply\n",
+    "# with the pandas metadata\n",
+    "#d = pd.HDFStore(glob.glob(f)[0])\n",
+    "\n",
+    "with h5py.File(glob.glob(f)[0]) as f:\n",
+    "    print(\"available datasets\", list(f))\n",
+    "    assert np.allclose(f[\"flopping_f_brightness\"], d)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Overwriting repository/notebook_test.py\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%writefile repository/notebook_test.py\n",
+    "\n",
+    "# we can also write experiments in the notebook ans submit them\n",
+    "# we don't have submit-by-content yet (and there would be questions\n",
+    "# about other modules that would need to be imported) so we just export\n",
+    "# this cell and submit it by filename\n",
+    "\n",
+    "from artiq.experiment import *\n",
+    "\n",
+    "class Hello(EnvExperiment):\n",
+    "    def build(self):\n",
+    "        pass\n",
+    "    \n",
+    "    def run(self):\n",
+    "        print(\"Hello world!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "133\n"
+     ]
+    }
+   ],
+   "source": [
+    "expid = dict(\n",
+    "    file=\"repository/notebook_test.py\",\n",
+    "    class_name=\"Hello\",\n",
+    "    log_level=logging.WARNING,\n",
+    "    arguments=dict(),\n",
+    ")\n",
+    "rid = schedule.submit(pipeline_name=\"misc\", expid=expid,\n",
+    "    priority=1, due_date=None, flush=False)\n",
+    "print(rid)\n",
+    "# on the master you should see the message."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.5.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
-Original file line number
+Diff line change
@@ @@ -6,6 +6,7 @@ __pycache__/ @@
     *.bin
     *.elf
     *.fbi
+    .ipynb_checkpoints
     /doc/manual/_build
     /build
     /dist