2015-09-18-hpd-cryomech-performance.ipynb

{
 "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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import netCDF4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "nc = netCDF4.Dataset('/artemis/adc/cooldown_logs/2015-01-13_13-40-50.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "va = nc.groups['cryomech'].variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'min_temp_helium',\n",
       " u'batt_ok',\n",
       " u'min_pressure_high',\n",
       " u'avg_pressure_high',\n",
       " u'max_temp_oil',\n",
       " u'comp_minutes',\n",
       " u'max_pressure_low',\n",
       " u'pressure_high',\n",
       " u'min_pressure_low',\n",
       " u'avg_pressure_delta',\n",
       " u'comp_on',\n",
       " u'max_temp_water_in',\n",
       " u'max_temp_helium',\n",
       " u'temp_water_out',\n",
       " u'min_temp_water_out',\n",
       " u'temp_oil',\n",
       " u'max_pressure_high',\n",
       " u'pressure_error',\n",
       " u'temp_water_in',\n",
       " u'min_temp_oil',\n",
       " u'batt_low',\n",
       " u'pressure_high_deriv',\n",
       " u'pressure_low',\n",
       " u'min_temp_water_in',\n",
       " u'error_code',\n",
       " u'cpu_temp',\n",
       " u'avg_pressure_low',\n",
       " u'max_temp_water_out',\n",
       " u'temp_helium',\n",
       " u'time',\n",
       " u'temp_error',\n",
       " u'motor_current']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "va.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def nc_to_df(fn):\n",
    "    try:\n",
    "        nc = netCDF4.Dataset(fn)\n",
    "        cryo = nc.groups['cryomech'].variables\n",
    "        data_dict = {}\n",
    "        for key in ['time','temp_oil','temp_water_in','temp_water_out','motor_current','cpu_temp']:\n",
    "            data_dict[key] = cryo[key][::60]\n",
    "        df = pd.DataFrame(data_dict)\n",
    "        print fn,df.shape\n",
    "    except Exception, e:\n",
    "        print fn,e\n",
    "        df = None\n",
    "    finally:\n",
    "        nc.close()\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = nc_to_df('/artemis/adc/cooldown_logs/2015-01-15_12-58-41.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(87, 6)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import joblib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pp = joblib.Parallel(n_jobs=20,verbose=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45\n"
     ]
    }
   ],
   "source": [
    "ncfiles=glob.glob('/artemis/adc/cooldown_logs/2015*.nc')\n",
    "ncfiles.sort()\n",
    "print len(ncfiles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dfs = pp(joblib.delayed(nc_to_df)(x) for x in ncfiles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "t = va['time'][::60]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fe68468fa90>]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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kNcbgl6TGGPyS1BiDX5IaY/BLUmMMfklqzJz/AteoXHUV+AGdc5PYZytNhj4n8XL+v2n5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\nmYtieYQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe6846f8650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(np.diff(t),'.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "h20in = nc.groups['cryomech'].variables['temp_water_in'][::60]\n",
    "h20out = nc.groups['cryomech'].variables['temp_water_out'][::60]\n",
    "oil = va['temp_oil'][::60]\n",
    "current = va['motor_current'][::60]\n",
    "pressure_low = va['pressure_low'][::60]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fe68bb1e410>]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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zqSBXZSXIN24c9F7JVfFMvnfv7B4HUbYEHuT37QOaNAl6r+Sqpk2BiROB/v2z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\nHp/KTQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe68bb9e490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot(h20in)\n",
    "plot(h20out-h20in)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fe68b9376d0>]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tmiIREVFUIknXEBFR/ZSxK15FpK+IrBKRz0Xk3kxtp74QkfYi8r6ILBeRz0Rk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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe68b9b8350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(oil-h20out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fe68b861c50>]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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u7u66LFu0Rr9hReQ2ADtU9c7ca40u+/HHgR/8wJ6J6mnDBuDYY4G+PuDtt4Ex\nY5rdIqJ0RASqWpO0pOISjYi0i8jI3HAHgLMArCg2D+uh1CjM4ImqK9GMBfBjsf+eFgD/pqpP1aRV\nRERUtYoDvKq+C2BGufMxm6JG4GGSRDyTlTzGwyQp63ixMfISM3giXmyMPMYMnrKOJRryEjN4IpZo\nyGPM4CnrmMGTl5jBE7EGTx5jBk9ZxxINEZGnWKIhL/FSBUTM4ImIvMUMnrzEnaxE3MlKHuNOVso6\nlmjIS8zgiViiIY8xg6esYwZPXmIGT8QaPHmMGTxlHUs05CVm8EQs0ZDHmMFT1jGDJy8xkSBiDZ48\nxksVUNaxRENE5CmWaMhLvNgYETN4IiJvMYMnL/EwSSLuZCWP8TBJyjqWaMhLzOCJWKIhjzGDp6xj\nBk9eYgZPxAyePMYMnrKOO1nJS8zgiViiIY8xg6esY4mGiMhTLNGQl9ylCtwwURaxRENE5CmWaMhL\nzOCJqgjwIjJPRN4QkbdE5Kb081W6RqLyMKGgrKsowIvIUADfBTAPwFEAForItFLzZfUfrru7u9lN\nGDAa1ReDIZHg30WAfVEflWbwJwFYparvqWo/gP8D4DO1a5Zf+McbaGRfDPSEgn8XAfZFfVQa4CcA\nWB16vSY3rqTBkFnR4Odq8Px7oyxrqXC+VLnRBRfkv16zBpg+vcI1EpXBBfihQ5vdEqLmEa3gd6yI\nnAJgqarOy72+GcA+Vf270DQD/AcyEdHApKo1+e1ZaYBvAfAmgDkA1gF4HsBCVX29Fo0iIqLqVVSi\nUdU9IvJVAE8CGApgGYM7EdHAUlEGT0REA19dzmSt9CSowUpEJorIsyLyqoi8IiLX5saPEZGnRWSl\niDwlIqND89yc6583ROSs5rW+9kRkqIgsF5HHcq8z2Q8AICKjReRhEXldRF4TkZOz2B+57XpVRFaI\nyP8WkWFZ6QcRuUdENorIitC4srddRGbm+u8tEfmfqVauqjV9wEo2qwAcBqAVwEsAptV6PQPpAWAc\ngBm54RGw/RPTAHwTwI258TcBuCM3fFSuX1pz/bQKwJBmb0cN++MGAP8G4Ce515nsh9w23gfgi7nh\nFgCjstYfuW15B8Cw3OuHAFyRlX4AcAaA4wCsCI0rZ9tdpeV5ACflhn8KYF6pddcjg8/cSVCqukFV\nX8oN7wDwOuy8gAth/+DIPc/PDX8GwIOq2q+q78E+xJMa2ug6EZFDAZwL4IcA3JEAmesHABCRUQDO\nUNV7ANudU1QMAAACeElEQVR3papbkb3+2AagH0B77gCNdtjBGZnoB1X9FYCeyOhytv1kERkPYKSq\nPp+b7v7QPInqEeArPgnKByJyGOzb+r8AjFXVjbm3NgIYmxs+BNYvjk999G0A/wPAvtC4LPYDABwO\n4H0RuVdE/q+I3C0iHchYf6jqFgB3Avh/sMD+oao+jYz1Q0S52x4dvxYp+qQeAT6ze21FZASAfwfw\nNVXdHn5P7XdVsb4Z9P0mIucD2KSqyxFk73my0A8hLQCOB/A9VT0ewEcAloQnyEJ/iMgRAK6DlRwO\nATBCRC4PT5OFfkiSYtsrVo8AvxbAxNDricj/5vGSiLTCgvsDqvpobvRGERmXe388gE258dE+OjQ3\nbrD7FIALReRdAA8CmC0iDyB7/eCsAbBGVV/IvX4YFvA3ZKw/TgDwG1XdrKp7ADwC4FRkrx/Cyvmf\nWJMbf2hkfMk+qUeA/z2AI0XkMBHZD8BlAH5Sh/UMGCIiAJYBeE1V7wq99RPYziTknh8Njf+siOwn\nIocDOBK2A2VQU9VbVHWiqh4O4LMAnlHVzyFj/eCo6gYAq0Vkcm7UXACvAngM2eqPNwCcIiJtuf+V\nuQBeQ/b6Iays/4nc39K23FFYAuBzoXmS1Wmv8TmwI0lWAbi52Xux6/0AcDqs5vwSgOW5xzwAYwD8\nAsBKAE8BGB2a55Zc/7wB4Oxmb0Md+uSPERxFk+V+OBbACwBehmWuo7LYHwBuhH25rYDtVGzNSj/A\nfs2uA9AH2z/5hUq2HcDMXP+tAvC/0qybJzoREXmKN90mIvIUAzwRkacY4ImIPMUAT0TkKQZ4IiJP\nMcATEXmKAZ6IyFMM8EREnvr/Uc3+A08v3WsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe68b9610d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(current)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fe68b80aad0>]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KqK7O5zFn4LS1eRFraQFuvNEfP2GCvZdvftMKndNO8/suuSTeVRK6Wdw7isaz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\nCCE54/8D+pgUEuXU7b8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe68b90b5d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(pressure_low)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}