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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Getting Help in MAF\n",
+    "\n",
+    "This notebook is a collection of snippets of how to get help on the various bits of the **MAF** ecosystem. It shows some of the **MAF** provided help functions. It also uses the `help` function. The `help` function used below is a Python standard library function. It can be used on any module, class or function. Using `help` should give clarity to the parameters used in associated functions. It will also list functions associated with modules and classes. The notebook also uses the `dir` command which is another Python standard library function. This is useful for getting a list of names from the target object (module/class/function). "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: AstropyDeprecationWarning: Config parameter 'default_cosmology' in section [astropy.cosmology.core] is deprecated. Use science state astropy.cosmology.core.default_cosmology instead. [astropy.utils.state]\n",
+      "WARNING:astropy:AstropyDeprecationWarning: Config parameter 'default_cosmology' in section [astropy.cosmology.core] is deprecated. Use science state astropy.cosmology.core.default_cosmology instead.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Need to import everything before getting help!\n",
+    "import lsst.sims.maf\n",
+    "import lsst.sims.maf.metrics as metrics\n",
+    "import lsst.sims.maf.slicers as slicers\n",
+    "import lsst.sims.maf.stackers as stackers\n",
+    "import lsst.sims.maf.plots as plots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "----  AveSlewFracMetric  ----\n",
+      "None\n",
+      "----  BinaryMetric  ----\n",
+      "Return 1 if there is data. \n",
+      "----  Coaddm5Metric  ----\n",
+      "Calculate the coadded m5 value at this gridpoint.\n",
+      "----  CompletenessMetric  ----\n",
+      "Compute the completeness and joint completeness \n",
+      "----  CountMetric  ----\n",
+      "Count the length of a simData column slice. \n",
+      "----  CountRatioMetric  ----\n",
+      "Count the length of a simData column slice, then divide by 'normVal'. \n",
+      "----  CountSubsetMetric  ----\n",
+      "Count the length of a simData column slice which matches 'subset'. \n",
+      "----  CountUniqueMetric  ----\n",
+      "Return the number of unique values \n",
+      "----  ExgalM5  ----\n",
+      "Calculate co-added five-sigma limiting depth after dust extinction.\n",
+      "----  FftMetric  ----\n",
+      "Calculate a truncated FFT of the exposure times.\n",
+      "----  FilterColorsMetric  ----\n",
+      "Calculate an RGBA value that accounts for the filters used up to time t0.\n",
+      "----  FracAboveMetric  ----\n",
+      "None\n",
+      "----  FracBelowMetric  ----\n",
+      "None\n",
+      "----  FullRangeAngleMetric  ----\n",
+      "Calculate the full range of an angular (radians) simData column slice.\n",
+      "\n",
+      "'FullRangeAngle' differs from 'FullRange' in that it accounts for wraparound at 2pi.\n",
+      "----  FullRangeMetric  ----\n",
+      "Calculate the range of a simData column slice.\n",
+      "----  HourglassMetric  ----\n",
+      "Plot the filters used as a function of time. Must be used with the Hourglass Slicer.\n",
+      "----  IdentityMetric  ----\n",
+      "Return the metric value itself .. this is primarily useful as a summary statistic for UniSlicer metrics.\n",
+      "----  LinkedMetric  ----\n",
+      "Calculate how many other healpixels a given observation is linked to.  This is a fairly crude measure of how well the observations are linked for self-calibration pruposes.  An even better metric would look at the chip level since that's how large calibration patches will be.\n",
+      "\n",
+      "Maybe even better would be to find the common co-added depth of a pixel with all it's neighboring healpixels!  Maybe a complex metric with min and max reduce functions...Do I grab the 4 nearest pixels or 8?\n",
+      "----  LongGapAGNMetric  ----\n",
+      "max delta-t and average of the top-10 longest gaps.\n",
+      "    \n",
+      "----  MaxMetric  ----\n",
+      "Calculate the maximum of a simData column slice.\n",
+      "----  MaxPercentMetric  ----\n",
+      "Return the percent of the data which has the maximum value.\n",
+      "----  MaxStateChangesWithinMetric  ----\n",
+      "Compute the maximum number of changes of state that occur within a given timespan.\n",
+      "(useful for calculating time between filter changes in particular).\n",
+      "'timespan' should be in minutes.\n",
+      "----  MeanAngleMetric  ----\n",
+      "Calculate the mean of an angular (radians) simData column slice.\n",
+      "\n",
+      "'MeanAngle' differs from 'Mean' in that it accounts for wraparound at 2pi.\n",
+      "----  MeanMetric  ----\n",
+      "Calculate the mean of a simData column slice.\n",
+      "----  MedianAbsMetric  ----\n",
+      "Calculate the median of the absolute value of a simData column slice.\n",
+      "----  MedianMetric  ----\n",
+      "Calculate the median of a simData column slice.\n",
+      "----  MinMetric  ----\n",
+      "Calculate the minimum of a simData column slice.\n",
+      "----  MinTimeBetweenStatesMetric  ----\n",
+      "Compute the minimum time between changes of state in a column value.\n",
+      "(useful for calculating fastest time between filter changes in particular).\n",
+      "Returns delta time in minutes!\n",
+      "----  NChangesMetric  ----\n",
+      "Compute the number of times a column value changes.\n",
+      "(useful for filter changes in particular).\n",
+      "----  NRevisitsMetric  ----\n",
+      "Calculate the number of (consecutive) visits with time differences less than dT.\n",
+      "----  NStateChangesFasterThanMetric  ----\n",
+      "Compute the number of changes of state that happen faster than 'cutoff'.\n",
+      "(useful for calculating time between filter changes in particular).\n",
+      "'cutoff' should be in minutes.\n",
+      "----  NormalizeMetric  ----\n",
+      "Return a metric values divided by 'normVal'. Useful for turning summary statistics into fractions.\n",
+      "----  NoutliersNsigmaMetric  ----\n",
+      "Calculate the # of visits less than nSigma below the mean (nSigma<0) or\n",
+      "more than nSigma above the mean of 'col'.\n",
+      "----  OpenShutterFractionMetric  ----\n",
+      "Compute the fraction of time the shutter is open compared to the total time spent observing.\n",
+      "----  ParallaxMetric  ----\n",
+      "Calculate the uncertainty in a parallax measures given a serries of observations.\n",
+      "    \n",
+      "----  PassMetric  ----\n",
+      "Just pass the entire array through\n",
+      "----  PercentileMetric  ----\n",
+      "None\n",
+      "----  ProperMotionMetric  ----\n",
+      "Calculate the uncertainty in the returned proper motion.  Assuming Gaussian errors.\n",
+      "    \n",
+      "----  RadiusObsMetric  ----\n",
+      "find the radius in the focal plane. \n",
+      "----  RapidRevisitMetric  ----\n",
+      "Calculate uniformity of time between consecutive visits on short timescales (for RAV1).\n",
+      "----  RmsAngleMetric  ----\n",
+      "Calculate the standard deviation of an angular (radians) simData column slice.\n",
+      "\n",
+      "'RmsAngle' differs from 'Rms' in that it accounts for wraparound at 2pi.\n",
+      "----  RmsMetric  ----\n",
+      "Calculate the standard deviation of a simData column slice.\n",
+      "----  RobustRmsMetric  ----\n",
+      "Use the inter-quartile range of the data to estimate the RMS.  Robust since this calculation\n",
+      "does not include outliers in the distribution\n",
+      "----  SlewContributionMetric  ----\n",
+      "None\n",
+      "----  SumMetric  ----\n",
+      "Calculate the sum of a simData column slice.\n",
+      "----  SupernovaMetric  ----\n",
+      "Measure how many time series meet a given time and filter distribution requirement.\n",
+      "----  TableFractionMetric  ----\n",
+      "Count the completeness (for many fields) and summarize how many fields have given completeness levels\n",
+      "(within a series of bins). Works with completenessMetric only.\n",
+      "\n",
+      "This metric is meant to be used as a summary statistic on something like the completeness metric.\n",
+      "The output is DIFFERENT FROM SSTAR and is:\n",
+      "    element   matching values\n",
+      "    0         0 == P\n",
+      "    1         0 < P < .1\n",
+      "    2         .1 <= P < .2\n",
+      "    3         .2 <= P < .3\n",
+      "    ...\n",
+      "    10        .9 <= P < 1\n",
+      "    11        1 == P\n",
+      "    12        1 < P\n",
+      "    Note the 1st and last elements do NOT obey the numpy histogram conventions.\n",
+      "----  TeffMetric  ----\n",
+      "Effective time equivalent for a given set of visits.\n",
+      "----  TemplateExistsMetric  ----\n",
+      "Calculate the fraction of images with a previous template image of desired quality.\n",
+      "----  TgapsMetric  ----\n",
+      "Histogram up all the time gaps \n",
+      "----  TotalPowerMetric  ----\n",
+      "Calculate the total power in the angular power spectrum between lmin/lmax.\n",
+      "----  TransientMetric  ----\n",
+      "Calculate what fraction of the transients would be detected. Best paired with a spatial slicer.\n",
+      "We are assuming simple light curves with no color evolution.\n",
+      "----  UniformityMetric  ----\n",
+      "Calculate how uniformly the observations are spaced in time.  Returns a value between -1 and 1.\n",
+      "A value of zero means the observations are perfectly uniform.\n",
+      "----  VisitGroupsMetric  ----\n",
+      "Count the number of visits per night within deltaTmin and deltaTmax.\n",
+      "----  ZeropointMetric  ----\n",
+      "Return a metric values with the addition of 'zp'. Useful for altering the zeropoint for summary statistics.\n",
+      "----  fOArea  ----\n",
+      "Metric to calculate the FO Area; works with FO slicer only.\n",
+      "----  fONv  ----\n",
+      "Metric to calculate the FO_Nv; works with FO slicer only.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Show the list of metrics with a little bit of documentation\n",
+    "metrics.BaseMetric.list(doc=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on class MaxMetric in module lsst.sims.maf.metrics.simpleMetrics:\n",
+      "\n",
+      "class MaxMetric(lsst.sims.maf.metrics.baseMetric.BaseMetric)\n",
+      " |  Calculate the maximum of a simData column slice.\n",
+      " |  \n",
+      " |  Method resolution order:\n",
+      " |      MaxMetric\n",
+      " |      lsst.sims.maf.metrics.baseMetric.BaseMetric\n",
+      " |      __builtin__.object\n",
+      " |  \n",
+      " |  Methods defined here:\n",
+      " |  \n",
+      " |  run(self, dataSlice, slicePoint=None)\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Methods inherited from lsst.sims.maf.metrics.baseMetric.BaseMetric:\n",
+      " |  \n",
+      " |  __init__(self, col=None, metricName=None, maps=None, units=None, metricDtype=None, badval=-666)\n",
+      " |      Instantiate metric.\n",
+      " |      \n",
+      " |      'col' is a kwarg for purposes of the MAF driver; when actually using a metric, it must be set to\n",
+      " |      the names of the data columns that the metric will operate on. This can be a single string or a list.\n",
+      " |      \n",
+      " |      'maps' is a list of any maps that the metric will need, accessed via slicePoint that is passed from the slicer.\n",
+      " |      \n",
+      " |      After inheriting from this base metric :\n",
+      " |        * every metric object will have metricDtype (the type of data it calculates) set according to:\n",
+      " |             -- kwarg (metricDtype='float', 'int', etc)\n",
+      " |             -- 'float' (assumes float if not specified in kwarg)\n",
+      " |             -- 'object' (if reduce functions are present and value not set in kwarg)\n",
+      " |        * every metric object will have the data columns it requires added to the column registry\n",
+      " |          (so the driver can know which columns to pull from the database)\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data descriptors inherited from lsst.sims.maf.metrics.baseMetric.BaseMetric:\n",
+      " |  \n",
+      " |  __dict__\n",
+      " |      dictionary for instance variables (if defined)\n",
+      " |  \n",
+      " |  __weakref__\n",
+      " |      list of weak references to the object (if defined)\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data and other attributes inherited from lsst.sims.maf.metrics.baseMetric.BaseMetric:\n",
+      " |  \n",
+      " |  __metaclass__ = <class 'lsst.sims.maf.metrics.baseMetric.MetricRegistr...\n",
+      " |      Meta class for metrics, to build a registry of metric classes.\n",
+      " |  \n",
+      " |  colInfo = <lsst.sims.maf.utils.getColInfo.ColInfo object>\n",
+      " |  \n",
+      " |  colRegistry = <lsst.sims.maf.metrics.baseMetric.ColRegistry object>\n",
+      " |  \n",
+      " |  registry = {'AveSlewFracMetric': <class 'lsst.sims.maf.metrics.slewMet...\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Show the help of a given metric\n",
+    "help(metrics.MaxMetric)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on CountMetric in module lsst.sims.maf.metrics.simpleMetrics object:\n",
+      "\n",
+      "class CountMetric(lsst.sims.maf.metrics.baseMetric.BaseMetric)\n",
+      " |  Count the length of a simData column slice.\n",
+      " |  \n",
+      " |  Method resolution order:\n",
+      " |      CountMetric\n",
+      " |      lsst.sims.maf.metrics.baseMetric.BaseMetric\n",
+      " |      __builtin__.object\n",
+      " |  \n",
+      " |  Methods defined here:\n",
+      " |  \n",
+      " |  __init__(self, col=None, **kwargs)\n",
+      " |  \n",
+      " |  run(self, dataSlice, slicePoint=None)\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data descriptors inherited from lsst.sims.maf.metrics.baseMetric.BaseMetric:\n",
+      " |  \n",
+      " |  __dict__\n",
+      " |      dictionary for instance variables (if defined)\n",
+      " |  \n",
+      " |  __weakref__\n",
+      " |      list of weak references to the object (if defined)\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data and other attributes inherited from lsst.sims.maf.metrics.baseMetric.BaseMetric:\n",
+      " |  \n",
+      " |  __metaclass__ = <class 'lsst.sims.maf.metrics.baseMetric.MetricRegistr...\n",
+      " |      Meta class for metrics, to build a registry of metric classes.\n",
+      " |  \n",
+      " |  colInfo = <lsst.sims.maf.utils.getColInfo.ColInfo object>\n",
+      " |  \n",
+      " |  colRegistry = <lsst.sims.maf.metrics.baseMetric.ColRegistry object>\n",
+      " |  \n",
+      " |  registry = {'AveSlewFracMetric': <class 'lsst.sims.maf.metrics.slewMet...\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# If you have an object, help works on it too!\n",
+    "metric = metrics.CountMetric('expMJD')\n",
+    "help(metric)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "----  HealpixSDSSSlicer  ----\n",
+      "For use with SDSS stripe 82 square images \n",
+      "----  HealpixSlicer  ----\n",
+      "Healpix spatial slicer.\n",
+      "----  HourglassSlicer  ----\n",
+      "Slicer to make the filter hourglass plots \n",
+      "----  MovieSlicer  ----\n",
+      "movie Slicer.\n",
+      "----  NDSlicer  ----\n",
+      "Nd slicer (N dimensions)\n",
+      "----  OneDSlicer  ----\n",
+      "oneD Slicer.\n",
+      "----  OpsimFieldSlicer  ----\n",
+      "Index-based slicer, matched ID's between simData and fieldData.\n",
+      "\n",
+      "Slicer uses fieldData RA and Dec values to do sky map plotting, but could be used more\n",
+      "generally for any kind of data slicing where the match is based on a simple ID value.\n",
+      "\n",
+      "Note that this slicer uses the fieldID of the opsim fields to generate spatial matches,\n",
+      "thus this slicer is not suitable for use in evaluating dithering or high resolution metrics\n",
+      "(use the healpix slicer instead for those use-cases). \n",
+      "----  UniSlicer  ----\n",
+      "UniSlicer.\n",
+      "----  UserPointsSlicer  ----\n",
+      "Use spatial slicer on a user provided point \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Show the list of slicers with a little bit of documentation\n",
+    "slicers.BaseSlicer.list(doc=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on class OpsimFieldSlicer in module lsst.sims.maf.slicers.opsimFieldSlicer:\n",
+      "\n",
+      "class OpsimFieldSlicer(lsst.sims.maf.slicers.baseSpatialSlicer.BaseSpatialSlicer)\n",
+      " |  Index-based slicer, matched ID's between simData and fieldData.\n",
+      " |  \n",
+      " |  Slicer uses fieldData RA and Dec values to do sky map plotting, but could be used more\n",
+      " |  generally for any kind of data slicing where the match is based on a simple ID value.\n",
+      " |  \n",
+      " |  Note that this slicer uses the fieldID of the opsim fields to generate spatial matches,\n",
+      " |  thus this slicer is not suitable for use in evaluating dithering or high resolution metrics\n",
+      " |  (use the healpix slicer instead for those use-cases).\n",
+      " |  \n",
+      " |  Method resolution order:\n",
+      " |      OpsimFieldSlicer\n",
+      " |      lsst.sims.maf.slicers.baseSpatialSlicer.BaseSpatialSlicer\n",
+      " |      lsst.sims.maf.slicers.baseSlicer.BaseSlicer\n",
+      " |      __builtin__.object\n",
+      " |  \n",
+      " |  Methods defined here:\n",
+      " |  \n",
+      " |  __eq__(self, otherSlicer)\n",
+      " |      Evaluate if two grids are equivalent.\n",
+      " |  \n",
+      " |  __init__(self, verbose=True, simDataFieldIDColName='fieldID', simDataFieldRaColName='fieldRA', simDataFieldDecColName='fieldDec', fieldIDColName='fieldID', fieldRaColName='fieldRA', fieldDecColName='fieldDec', badval=-666)\n",
+      " |      Instantiate opsim field slicer (an index-based slicer that can do spatial plots).\n",
+      " |      \n",
+      " |      simDataFieldIDColName = the column name in simData for the field ID\n",
+      " |      simDataFieldRaColName = the column name in simData for the field RA\n",
+      " |      simDataFieldDecColName = the column name in simData for the field Dec\n",
+      " |      fieldIDcolName = the column name in the fieldData for the field ID (to match with simData)\n",
+      " |      fieldRaColName = the column name in the fieldData for the field RA (for plotting only)\n",
+      " |      fieldDecColName = the column name in the fieldData for the field Dec (for plotting only).\n",
+      " |  \n",
+      " |  setupSlicer(self, simData, fieldData, maps=None)\n",
+      " |      Set up opsim field slicer object.\n",
+      " |      \n",
+      " |      simData = numpy rec array with simulation pointing history,\n",
+      " |      fieldData = numpy rec array with the field information (ID, RA, Dec),\n",
+      " |      Values for the column names are set during 'init'.\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Methods inherited from lsst.sims.maf.slicers.baseSlicer.BaseSlicer:\n",
+      " |  \n",
+      " |  __getitem__(self, islice)\n",
+      " |  \n",
+      " |  __iter__(self)\n",
+      " |      Iterate over the slices.\n",
+      " |  \n",
+      " |  __len__(self)\n",
+      " |      Return nslice, the number of slicePoints in the slicer.\n",
+      " |  \n",
+      " |  __ne__(self, otherSlicer)\n",
+      " |      Evaluate if two slicers are not equivalent.\n",
+      " |  \n",
+      " |  getSlicePoints(self)\n",
+      " |      Return the slicePoint metadata, for all slice points.\n",
+      " |  \n",
+      " |  next(self)\n",
+      " |      Returns results of self._sliceSimData when iterating over slicer.\n",
+      " |      \n",
+      " |      Results of self._sliceSimData should be dictionary of\n",
+      " |         {'idxs' - the data indexes relevant for this slice of the slicer,\n",
+      " |         'slicePoint' - the metadata for the slicePoint .. always includes ['sid'] key for ID of slicePoint.}\n",
+      " |  \n",
+      " |  outputJSON(self, metricValues, metricName='', simDataName='', metadata='', plotDict=None)\n",
+      " |      Send metric data to JSON streaming API, along with a little bit of metadata.\n",
+      " |      \n",
+      " |      Output is\n",
+      " |         header dictionary with 'metricName/metadata/simDataName/slicerName' and plot labels from plotDict (if provided).\n",
+      " |         then data for plot:\n",
+      " |           if oneDSlicer, it's [ [bin_left_edge, value], [bin_left_edge, value]..].\n",
+      " |           if a spatial slicer, it's [ [lon, lat, value], [lon, lat, value] ..].\n",
+      " |      This method will only work for non-complex metrics (i.e. metrics where the metric value is a float or int),\n",
+      " |      as JSON will not interpret more complex data properly. These values can't be plotted anyway though.\n",
+      " |  \n",
+      " |  readData(self, infilename)\n",
+      " |      Read metric data from disk, along with the info to rebuild the slicer (minus new slicing capability).\n",
+      " |      \n",
+      " |      infilename: the filename containing the metric data.\n",
+      " |  \n",
+      " |  writeData(self, outfilename, metricValues, metricName='', simDataName='', sqlconstraint='', metadata='', plotDict=None, displayDict=None)\n",
+      " |      Save metric values along with the information required to re-build the slicer.\n",
+      " |      \n",
+      " |      outfilename: the output file\n",
+      " |      metricValues: the metric values to save to disk\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data descriptors inherited from lsst.sims.maf.slicers.baseSlicer.BaseSlicer:\n",
+      " |  \n",
+      " |  __dict__\n",
+      " |      dictionary for instance variables (if defined)\n",
+      " |  \n",
+      " |  __weakref__\n",
+      " |      list of weak references to the object (if defined)\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data and other attributes inherited from lsst.sims.maf.slicers.baseSlicer.BaseSlicer:\n",
+      " |  \n",
+      " |  __metaclass__ = <class 'lsst.sims.maf.slicers.baseSlicer.SlicerRegistr...\n",
+      " |      Meta class for slicers, to build a registry of slicer classes.\n",
+      " |  \n",
+      " |  registry = {'HealpixSDSSSlicer': <class 'lsst.sims.maf.slicers.healpix...\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Show help of a given slicer\n",
+    "help(slicers.OpsimFieldSlicer)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "----  EclipticStacker  ----\n",
+      "\n",
+      "    Stack on the ecliptic coordinates of each pointing.  Optionally\n",
+      "    subtract off the sun's ecliptic longitude and wrap.\n",
+      "    \n",
+      " Columns added to SimData:  eclipLat,eclipLon\n",
+      " Default columns required:  expMJD,fieldRA,fieldDec\n",
+      "----  FilterColorStacker  ----\n",
+      "\n",
+      "    Translate filters ('u', 'g', 'r' ..) into RGB tuples.\n",
+      "    \n",
+      " Columns added to SimData:  rRGB,gRGB,bRGB\n",
+      " Default columns required:  filter\n",
+      "----  GalacticStacker  ----\n",
+      "\n",
+      "    Stack on the galactic coordinates of each pointing.\n",
+      "    \n",
+      " Columns added to SimData:  gall,galb\n",
+      " Default columns required:  fieldRA,fieldDec\n",
+      "----  HourAngleStacker  ----\n",
+      "\n",
+      "    Add the Hour Angle for each observation.\n",
+      "    \n",
+      " Columns added to SimData:  HA\n",
+      " Default columns required:  lst,fieldRA\n",
+      "----  NEODistStacker  ----\n",
+      "\n",
+      "    For each observation, find the max distance to a ~144 km NEO,\n",
+      "    also stack on the x,y position of the object.\n",
+      "    \n",
+      " Columns added to SimData:  MaxGeoDist,NEOHelioX,NEOHelioY\n",
+      " Default columns required:  solarElong,filter,fiveSigmaDepth,sunAz,azimuth\n",
+      "----  NightlyRandomDitherStacker  ----\n",
+      "\n",
+      "    Randomly dither the RA and Dec pointings up to maxDither degrees from center, one dither offset per night.\n",
+      "    \n",
+      " Columns added to SimData:  nightlyRandomRADither,nightlyRandomDecDither\n",
+      " Default columns required:  fieldRA,fieldDec,night\n",
+      "----  NightlySequentialHexDitherStacker  ----\n",
+      "\n",
+      "    Use offsets from the hexagonal grid of 'hexdither', but visit each vertex sequentially.\n",
+      "    Sequential offset for each night of visits.\n",
+      "    \n",
+      " Columns added to SimData:  nightlySequentialHexRADither,nightlySequentialHexDecDither\n",
+      " Default columns required:  fieldRA,fieldDec,night\n",
+      "----  NightlySpiralDitherStacker  ----\n",
+      "\n",
+      "    Offset along an equidistant spiral with numPoints, out to a maximum radius of maxDither.\n",
+      "    Sequential offset for each night of visits to a field.\n",
+      "    \n",
+      " Columns added to SimData:  nightlySpiralRADither,nightlySpiralDecDither\n",
+      " Default columns required:  fieldRA,fieldDec,fieldID,night\n",
+      "----  NormAirmassStacker  ----\n",
+      "\n",
+      "    Calculate the normalized airmass for each opsim pointing.\n",
+      "    \n",
+      " Columns added to SimData:  normairmass\n",
+      " Default columns required:  airmass,fieldDec\n",
+      "----  ParallaxFactorStacker  ----\n",
+      "\n",
+      "    Calculate the parallax factors for each opsim pointing.  Output parallax factor in arcseconds.\n",
+      "    \n",
+      " Columns added to SimData:  ra_pi_amp,dec_pi_amp\n",
+      " Default columns required:  fieldRA,fieldDec,expMJD\n",
+      "----  RandomDitherStacker  ----\n",
+      "\n",
+      "    Randomly dither the RA and Dec pointings up to maxDither degrees from center, different offset per visit.\n",
+      "    \n",
+      " Columns added to SimData:  randomRADither,randomDecDither\n",
+      " Default columns required:  fieldRA,fieldDec\n",
+      "----  SdssRADecStacker  ----\n",
+      "convert the p1,p2,p3... columns to radians and wrap them \n",
+      " Columns added to SimData:  RA1,Dec1,RA2,Dec2,RA3,Dec3,RA4,Dec4\n",
+      " Default columns required:  p1,p2,p3,p4,p5,p6,p7,p8\n",
+      "----  SequentialHexDitherStacker  ----\n",
+      "\n",
+      "    Use offsets from the hexagonal grid of 'hexdither', but visit each vertex sequentially.\n",
+      "    Sequential offset for each visit.\n",
+      "    \n",
+      " Columns added to SimData:  sequentialHexRADither,sequentialHexDecDither\n",
+      " Default columns required:  fieldRA,fieldDec\n",
+      "----  SpiralDitherStacker  ----\n",
+      "\n",
+      "    Offset along an equidistant spiral with numPoints, out to a maximum radius of maxDither.\n",
+      "    Sequential offset for each individual visit to a field.\n",
+      "    \n",
+      " Columns added to SimData:  spiralRADither,spiralDecDither\n",
+      " Default columns required:  fieldRA,fieldDec,fieldID\n",
+      "----  ZenithDistStacker  ----\n",
+      "\n",
+      "    Calculate the zenith distance for each pointing.\n",
+      "    \n",
+      " Columns added to SimData:  zenithDistance\n",
+      " Default columns required:  altitude\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Show the list of stackers with a bit of documentation\n",
+    "stackers.BaseStacker.list(doc=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on class ParallaxFactorStacker in module lsst.sims.maf.stackers.generalStackers:\n",
+      "\n",
+      "class ParallaxFactorStacker(lsst.sims.maf.stackers.baseStacker.BaseStacker)\n",
+      " |  Calculate the parallax factors for each opsim pointing.  Output parallax factor in arcseconds.\n",
+      " |  \n",
+      " |  Method resolution order:\n",
+      " |      ParallaxFactorStacker\n",
+      " |      lsst.sims.maf.stackers.baseStacker.BaseStacker\n",
+      " |      __builtin__.object\n",
+      " |  \n",
+      " |  Methods defined here:\n",
+      " |  \n",
+      " |  __init__(self, raCol='fieldRA', decCol='fieldDec', dateCol='expMJD')\n",
+      " |  \n",
+      " |  run(self, simData)\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Methods inherited from lsst.sims.maf.stackers.baseStacker.BaseStacker:\n",
+      " |  \n",
+      " |  __eq__(self, otherStacker)\n",
+      " |      Evaluate if two stackers are equivalent.\n",
+      " |  \n",
+      " |  __ne__(self, otherStacker)\n",
+      " |      Evaluate if two stackers are not equal.\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data descriptors inherited from lsst.sims.maf.stackers.baseStacker.BaseStacker:\n",
+      " |  \n",
+      " |  __dict__\n",
+      " |      dictionary for instance variables (if defined)\n",
+      " |  \n",
+      " |  __weakref__\n",
+      " |      list of weak references to the object (if defined)\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data and other attributes inherited from lsst.sims.maf.stackers.baseStacker.BaseStacker:\n",
+      " |  \n",
+      " |  __metaclass__ = <class 'lsst.sims.maf.stackers.baseStacker.StackerRegi...\n",
+      " |      Meta class for Stackers, to build a registry of stacker classes.\n",
+      " |  \n",
+      " |  registry = {'EclipticStacker': <class 'lsst.sims.maf.stackers.ecliptic...\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Show help of a given stacker\n",
+    "help(stackers.ParallaxFactorStacker)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['BaseHistogram',\n",
+       " 'BasePlotter',\n",
+       " 'BaseSkyMap',\n",
+       " 'FOPlot',\n",
+       " 'HealpixHistogram',\n",
+       " 'HealpixPowerSpectrum',\n",
+       " 'HealpixSDSSSkyMap',\n",
+       " 'HealpixSkyMap',\n",
+       " 'HourglassPlot',\n",
+       " 'NeoDistancePlotter',\n",
+       " 'OneDBinnedData',\n",
+       " 'OneDSubsetData',\n",
+       " 'OpsimHistogram',\n",
+       " 'PlotHandler',\n",
+       " 'SummaryHistogram',\n",
+       " 'TwoDSubsetData',\n",
+       " '__builtins__',\n",
+       " '__doc__',\n",
+       " '__file__',\n",
+       " '__name__',\n",
+       " '__package__',\n",
+       " '__path__',\n",
+       " 'hourglassPlotters',\n",
+       " 'ndPlotters',\n",
+       " 'neoDistancePlotter',\n",
+       " 'onedPlotters',\n",
+       " 'plotHandler',\n",
+       " 'spatialPlotters',\n",
+       " 'specialPlotters']"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# The plots module doesn't have a nice way of listing its members, so using the dir command to list its members\n",
+    "dir(plots)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on class HealpixSkyMap in module lsst.sims.maf.plots.spatialPlotters:\n",
+      "\n",
+      "class HealpixSkyMap(lsst.sims.maf.plots.plotHandler.BasePlotter)\n",
+      " |  Method resolution order:\n",
+      " |      HealpixSkyMap\n",
+      " |      lsst.sims.maf.plots.plotHandler.BasePlotter\n",
+      " |      __builtin__.object\n",
+      " |  \n",
+      " |  Methods defined here:\n",
+      " |  \n",
+      " |  __call__(self, metricValueIn, slicer, userPlotDict, fignum=None)\n",
+      " |      Generate a sky map of healpix metric values using healpy's mollweide view.\n",
+      " |  \n",
+      " |  __init__(self)\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data descriptors inherited from lsst.sims.maf.plots.plotHandler.BasePlotter:\n",
+      " |  \n",
+      " |  __dict__\n",
+      " |      dictionary for instance variables (if defined)\n",
+      " |  \n",
+      " |  __weakref__\n",
+      " |      list of weak references to the object (if defined)\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Show the help of a given plots class\n",
+    "help(plots.HealpixSkyMap)"
+   ]
+  },
+  {
+   "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
+}