Nans in skymodel.ipynb

{
 "cells": [
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "import numpy as np",
   "execution_count": 1,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "import pandas as pd",
   "execution_count": 2,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "import os",
   "execution_count": 3,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "# Change this to point to the OpSim file\nopsimhdf = os.path.join('/Users/rbiswas/data/', 'LSST', 'OpSimData', 'newOpSim.hdf')",
   "execution_count": 4,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "df = pd.read_hdf(opsimhdf)",
   "execution_count": 5,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "from opsimsummary import OpSimOutput",
   "execution_count": 6,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "opsout  = OpSimOutput.fromOpSimDB('/Users/rbiswas/data/LSST/OpSimData/minion_1016_sqlite.db', subset='unique_all')",
   "execution_count": 7,
   "outputs": [
    {
     "output_type": "stream",
     "text": " reading from database sqlite:////Users/rbiswas/data/LSST/OpSimData/minion_1016_sqlite.db\n",
     "name": "stdout"
    },
    {
     "output_type": "stream",
     "text": "/Users/rbiswas/soft/LSST/DarwinX86/miniconda2/4.2.12.lsst1/lib/python2.7/site-packages/pandas/core/indexing.py:476: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n  self.obj[item] = s\n",
     "name": "stderr"
    }
   ]
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "obsHistIDs = df[np.isnan(df.skymags)].index.values",
   "execution_count": 11,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "pointings = opsout.summary.loc[obsHistIDs].query('airmass <=2.5')",
   "execution_count": 31,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "len(pointings)",
   "execution_count": 32,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "205"
     },
     "metadata": {},
     "execution_count": 32
    }
   ]
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "pointings.head()",
   "execution_count": 55,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>sessionID</th>\n      <th>propID</th>\n      <th>fieldID</th>\n      <th>fieldRA</th>\n      <th>fieldDec</th>\n      <th>filter</th>\n      <th>expDate</th>\n      <th>expMJD</th>\n      <th>night</th>\n      <th>visitTime</th>\n      <th>...</th>\n      <th>moonBright</th>\n      <th>darkBright</th>\n      <th>rawSeeing</th>\n      <th>wind</th>\n      <th>humidity</th>\n      <th>slewDist</th>\n      <th>slewTime</th>\n      <th>fiveSigmaDepth</th>\n      <th>ditheredRA</th>\n      <th>ditheredDec</th>\n    </tr>\n    <tr>\n      <th>obsHistID</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>59403</th>\n      <td>1016</td>\n      <td>52</td>\n      <td>1463</td>\n      <td>4.589291</td>\n      <td>-0.459746</td>\n      <td>z</td>\n      <td>6672121</td>\n      <td>59657.223625</td>\n      <td>77</td>\n      <td>34.0</td>\n      <td>...</td>\n      <td>1506.470146</td>\n      <td>145.900806</td>\n      <td>0.796622</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.055968</td>\n      <td>4.411822</td>\n      <td>21.266189</td>\n      <td>4.593551</td>\n      <td>-0.466359</td>\n    </tr>\n    <tr>\n      <th>59680</th>\n      <td>1016</td>\n      <td>52</td>\n      <td>2994</td>\n      <td>5.026549</td>\n      <td>0.130868</td>\n      <td>z</td>\n      <td>6682797</td>\n      <td>59657.347196</td>\n      <td>77</td>\n      <td>34.0</td>\n      <td>...</td>\n      <td>1248.205697</td>\n      <td>146.421190</td>\n      <td>0.835096</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.050956</td>\n      <td>4.346642</td>\n      <td>21.310293</td>\n      <td>5.030400</td>\n      <td>0.124255</td>\n    </tr>\n    <tr>\n      <th>73347</th>\n      <td>1016</td>\n      <td>52</td>\n      <td>775</td>\n      <td>4.258966</td>\n      <td>-0.790248</td>\n      <td>r</td>\n      <td>8216362</td>\n      <td>59675.096793</td>\n      <td>95</td>\n      <td>34.0</td>\n      <td>...</td>\n      <td>1.509612</td>\n      <td>145.894488</td>\n      <td>0.934384</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.048916</td>\n      <td>4.264651</td>\n      <td>23.014633</td>\n      <td>4.277956</td>\n      <td>-0.793554</td>\n    </tr>\n    <tr>\n      <th>78265</th>\n      <td>1016</td>\n      <td>52</td>\n      <td>1101</td>\n      <td>4.337251</td>\n      <td>-0.626596</td>\n      <td>i</td>\n      <td>8649281</td>\n      <td>59680.107423</td>\n      <td>100</td>\n      <td>34.0</td>\n      <td>...</td>\n      <td>346.365422</td>\n      <td>146.547389</td>\n      <td>0.469753</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.048077</td>\n      <td>4.261755</td>\n      <td>22.548176</td>\n      <td>4.299545</td>\n      <td>-0.626596</td>\n    </tr>\n    <tr>\n      <th>75197</th>\n      <td>1016</td>\n      <td>52</td>\n      <td>425</td>\n      <td>4.126475</td>\n      <td>-1.000363</td>\n      <td>r</td>\n      <td>8385217</td>\n      <td>59677.051125</td>\n      <td>97</td>\n      <td>34.0</td>\n      <td>...</td>\n      <td>115.505241</td>\n      <td>146.110759</td>\n      <td>0.910600</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.049572</td>\n      <td>4.317404</td>\n      <td>22.848148</td>\n      <td>4.165360</td>\n      <td>-1.003669</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 46 columns</p>\n</div>",
      "text/plain": "           sessionID  propID  fieldID   fieldRA  fieldDec filter  expDate  \\\nobsHistID                                                                   \n59403           1016      52     1463  4.589291 -0.459746      z  6672121   \n59680           1016      52     2994  5.026549  0.130868      z  6682797   \n73347           1016      52      775  4.258966 -0.790248      r  8216362   \n78265           1016      52     1101  4.337251 -0.626596      i  8649281   \n75197           1016      52      425  4.126475 -1.000363      r  8385217   \n\n                 expMJD  night  visitTime     ...        moonBright  \\\nobsHistID                                     ...                     \n59403      59657.223625     77       34.0     ...       1506.470146   \n59680      59657.347196     77       34.0     ...       1248.205697   \n73347      59675.096793     95       34.0     ...          1.509612   \n78265      59680.107423    100       34.0     ...        346.365422   \n75197      59677.051125     97       34.0     ...        115.505241   \n\n           darkBright  rawSeeing  wind  humidity  slewDist  slewTime  \\\nobsHistID                                                              \n59403      145.900806   0.796622   0.0       0.0  0.055968  4.411822   \n59680      146.421190   0.835096   0.0       0.0  0.050956  4.346642   \n73347      145.894488   0.934384   0.0       0.0  0.048916  4.264651   \n78265      146.547389   0.469753   0.0       0.0  0.048077  4.261755   \n75197      146.110759   0.910600   0.0       0.0  0.049572  4.317404   \n\n           fiveSigmaDepth  ditheredRA  ditheredDec  \nobsHistID                                           \n59403           21.266189    4.593551    -0.466359  \n59680           21.310293    5.030400     0.124255  \n73347           23.014633    4.277956    -0.793554  \n78265           22.548176    4.299545    -0.626596  \n75197           22.848148    4.165360    -1.003669  \n\n[5 rows x 46 columns]"
     },
     "metadata": {},
     "execution_count": 55
    }
   ]
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "%matplotlib inline\nimport matplotlib.pyplot as plt",
   "execution_count": 59,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "fig, ax = plt.subplots()\npointings.airmass.hist(histtype='step', lw=1)\nax.set_xlabel('airmass')\nax.set_ylabel('visits')",
   "execution_count": 60,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<matplotlib.text.Text at 0x175f47d10>"
     },
     "metadata": {},
     "execution_count": 60
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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0aBGzZ8+uG+vp6aFSqbB69eq68Y6ODqZNm5areerUqaXM0au39rLn6M2SQg7I9scFF1yQ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\nakpEREQkCv8fGRSPV1dC8IIAAAAASUVORK5CYII=\n",
      "text/plain": "<matplotlib.figure.Figure at 0x154161290>"
     },
     "metadata": {}
    }
   ]
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "from lsst.sims.photUtils import BandpassDict",
   "execution_count": 14,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "hwbpDict, TotbpDict = BandpassDict.loadBandpassesFromFiles()",
   "execution_count": 15,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "from lsst.sims.skybrightness import SkyModel",
   "execution_count": 37,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "skymodel = SkyModel(preciseAltAz=True)",
   "execution_count": 38,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "pointings[['fieldRA', 'fieldDec', 'filter', 'expMJD']].head()",
   "execution_count": 42,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>fieldRA</th>\n      <th>fieldDec</th>\n      <th>filter</th>\n      <th>expMJD</th>\n    </tr>\n    <tr>\n      <th>obsHistID</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>59403</th>\n      <td>4.589291</td>\n      <td>-0.459746</td>\n      <td>z</td>\n      <td>59657.223625</td>\n    </tr>\n    <tr>\n      <th>59680</th>\n      <td>5.026549</td>\n      <td>0.130868</td>\n      <td>z</td>\n      <td>59657.347196</td>\n    </tr>\n    <tr>\n      <th>73347</th>\n      <td>4.258966</td>\n      <td>-0.790248</td>\n      <td>r</td>\n      <td>59675.096793</td>\n    </tr>\n    <tr>\n      <th>78265</th>\n      <td>4.337251</td>\n      <td>-0.626596</td>\n      <td>i</td>\n      <td>59680.107423</td>\n    </tr>\n    <tr>\n      <th>75197</th>\n      <td>4.126475</td>\n      <td>-1.000363</td>\n      <td>r</td>\n      <td>59677.051125</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "            fieldRA  fieldDec filter        expMJD\nobsHistID                                         \n59403      4.589291 -0.459746      z  59657.223625\n59680      5.026549  0.130868      z  59657.347196\n73347      4.258966 -0.790248      r  59675.096793\n78265      4.337251 -0.626596      i  59680.107423\n75197      4.126475 -1.000363      r  59677.051125"
     },
     "metadata": {},
     "execution_count": 42
    }
   ]
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "skymodel.setRaDecMjd(4.589291, -0.459746, 59657.223625)",
   "execution_count": 52,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "skymodel.returnMags(hwbpDict)",
   "execution_count": 53,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "{'g': array([ nan]),\n 'i': array([ nan]),\n 'r': array([ nan]),\n 'u': array([ nan]),\n 'y': array([ nan]),\n 'z': array([ nan])}"
     },
     "metadata": {},
     "execution_count": 53
    }
   ]
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "skymodel.returnWaveSpec()",
   "execution_count": 54,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "(array([  300. ,   300.1,   300.2, ...,  1999.8,  1999.9,  2000. ]),\n array([[ nan,  nan,  nan, ...,  nan,  nan,  nan]]))"
     },
     "metadata": {},
     "execution_count": 54
    }
   ]
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "# How it usually works for me for pointings other than these 205 ",
   "execution_count": null,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "skymodel.setRaDecMjd(0.925, -0.4789, 59580.14)",
   "execution_count": 49,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "skymodel.returnWaveSpec()",
   "execution_count": 50,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "(array([  300. ,   300.1,   300.2, ...,  1999.8,  1999.9,  2000. ]),\n array([[  6.68041555e-19,   4.60766642e-18,   4.72274672e-18, ...,\n           6.23963220e-16,   2.16958882e-16,   8.11758447e-17]]))"
     },
     "metadata": {},
     "execution_count": 50
    }
   ]
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "skymodel.returnMags(bandpasses=hwbpDict)",
   "execution_count": 51,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "{'g': array([ 22.25374335]),\n 'i': array([ 20.31395037]),\n 'r': array([ 21.260975]),\n 'u': array([ 22.77388112]),\n 'y': array([ 18.50654798]),\n 'z': array([ 19.34471914])}"
     },
     "metadata": {},
     "execution_count": 51
    }
   ]
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# scratch"
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "## How I am trying to calculate this",
   "execution_count": null,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "import obscond",
   "execution_count": null,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "skycalc = obscond.SkyCalculations(photparams=\"LSST\", hwBandpassDict=hwbpDict)",
   "execution_count": 16,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "skycalc.skymag('r', 0.925, -0.4789, 59580.14)",
   "execution_count": 33,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "21.260974999286908"
     },
     "metadata": {},
     "execution_count": 33
    }
   ]
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "x  = skycalc.calculatePointings(pointings)",
   "execution_count": 34,
   "outputs": []
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "x.dropna()",
   "execution_count": 36,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>filtSkyBrightness</th>\n      <th>fiveSigmaDepth</th>\n    </tr>\n    <tr>\n      <th>obsHistID</th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n  </tbody>\n</table>\n</div>",
      "text/plain": "Empty DataFrame\nColumns: [filtSkyBrightness, fiveSigmaDepth]\nIndex: []"
     },
     "metadata": {},
     "execution_count": 36
    }
   ]
  }
 ],
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