Fixed documentation for baseSlicer.

Author: rhiannonlynne

python/lsst/sims/maf/slicers/baseSlicer.py

@@ -48,11 +48,6 @@ class BaseSlicer(object):
     saving/restoring metric data should be present (although slicer does not need to be able to
     slice data again and generally will not be able to).
 
-    The sliceMetric has a 'memo-ize' functionality that can save previous indexes & return
-    metric data value calculated for same set of previous indexes, if desired.
-    CacheSize = 0 effectively turns this off, otherwise cacheSize should be set by the slicer.
-    (Most useful for healpix slicer, where many healpixels may have same set of LSST visits).
-
     Parameters
     ----------
     verbose: boolean, optional
@@ -102,6 +97,13 @@ def setupSlicer(self, simData, maps=None):
 
         Set up internal parameters necessary for slicer to slice data and generates indexes on simData.
         Also sets _sliceSimData for a particular slicer.
+
+        Parameters
+        -----------
+        simData : np.recarray
+            The simulated data to be sliced.
+        maps : list of lsst.sims.maf.maps objects, optional.
+            Maps to apply at each slicePoint, to add to the slicePoint metadata. Default None.
         """
         # Typically args will be simData, but opsimFieldSlicer also uses fieldData.
         raise NotImplementedError()
@@ -169,8 +171,12 @@ def writeData(self, outfilename, metricValues, metricName='',
         """
         Save metric values along with the information required to re-build the slicer.
 
-        outfilename: the output file
-        metricValues: the metric values to save to disk
+        Parameters
+        -----------
+        outfilename : str
+            The output file name.
+        metricValues : np.ma.MaskedArray or np.ndarray
+            The metric values to save to disk.
         """
         header = {}
         header['metricName']=metricName
@@ -210,14 +216,29 @@ def outputJSON(self, metricValues, metricName='',
         """
         Send metric data to JSON streaming API, along with a little bit of metadata.
 
-        Output is
-        header dictionary with 'metricName/metadata/simDataName/slicerName' and plot labels from plotDict (if provided).
-        then data for plot:
-        if oneDSlicer, it's [ [bin_left_edge, value], [bin_left_edge, value]..].
-        if a spatial slicer, it's [ [lon, lat, value], [lon, lat, value] ..].
-
-        This method will only work for non-complex metrics (i.e. metrics where the metric value is a float or int),
+        This method will only work for metrics where the metricDtype is float or int,
         as JSON will not interpret more complex data properly. These values can't be plotted anyway though.
+
+        Parameters
+        -----------
+        metricValues : np.ma.MaskedArray or np.ndarray
+            The metric values.
+        metricName : str, optional
+            The name of the metric. Default ''.
+        simDataName : str, optional
+            The name of the simulated data source. Default ''.
+        metadata : str, optional
+            The metadata about this metric. Default ''.
+        plotDict : dict, optional.
+            The plotDict for this metric bundle. Default None.
+
+        Returns
+        --------
+        StringIO
+            StringIO object containing a header dictionary with metricName/metadata/simDataName/slicerName,
+            and plot labels from plotDict, and metric values/data for plot.
+            if oneDSlicer, the data is [ [bin_left_edge, value], [bin_left_edge, value]..].
+            if a spatial slicer, the data is [ [lon, lat, value], [lon, lat, value] ..].
         """
         # Bail if this is not a good data type for JSON.
         if not (metricValues.dtype == 'float') or (metricValues.dtype == 'int'):
@@ -309,7 +330,16 @@ def readData(self, infilename):
         """
         Read metric data from disk, along with the info to rebuild the slicer (minus new slicing capability).
 
-        infilename: the filename containing the metric data.
+        Parameters
+        -----------
+        infilename: str
+            The filename containing the metric data.
+
+        Returns
+        -------
+        np.ma.MaskedArray, lsst.sims.maf.slicer, dict
+            MetricValues stored in data file, the slicer basis for those metric values, and a dictionary
+            containing header information (runName, metadata, etc.).
         """
         import lsst.sims.maf.slicers as slicers
         restored = np.load(infilename)