Update formatting and RST links

doc/lsst.ip.diffim/tasks/lsst.ip.diffim.DecorrelateALKernalSpatialTask.rst

@@ -1,8 +1,8 @@
 .. lsst-task-topic:: lsst.ip.diffim.DecorrelateALKernelSpatialTask
 
-##########################
+##############################
 DecorrelateALKernelSpatialTask
-##########################
+##############################
 
 Pipe-task that removes the neighboring-pixel covariance in an
 image difference that are added when the template image is
@@ -11,21 +11,21 @@ convolved with the Alard-Lupton PSF matching kernel.
 .. _lsst.ip.diffim.DecorrelateALKernelSpatialTask-description:
 
 Description
-==================
-
-This task is a simple wrapper around @ref DecorrelateALKernelTask,
-which takes a `spatiallyVarying` parameter in its `run` method. If
-it is `False`, then it simply calls the `run` method of @ref
-DecorrelateALKernelTask. If it is True, then it uses the @ref
-ImageMapReduceTask framework to break the exposures into
-subExposures on a grid, and performs the `run` method of @ref
-DecorrelateALKernelTask on each subExposure. This enables it to
+===========
+
+This task is a simple wrapper around `~lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelTask`,
+which takes a ``spatiallyVarying`` parameter in its ``run`` method. If
+it is ``False``, then it simply calls the ``run`` method of
+`~lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelTask`. If it is True, then it uses the
+`~lsst.ip.diffim.imageDecorrelation.ImageMapReduceTask` framework to break the exposures into
+subExposures on a grid, and performs the ``run`` method of
+`~lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelTask` on each subExposure. This enables it to
 account for spatially-varying PSFs and noise in the exposures when
 performing the decorrelation.
 
 This task has no standalone example, however it is applied as a
-subtask of pipe.tasks.imageDifference.ImageDifferenceTask.
-There is also an example of its use in `tests/testImageDecorrelation.py`.
+subtask of `~pipe.tasks.imageDifference.ImageDifferenceTask`.
+There is also an example of its use in ``tests/testImageDecorrelation.py``.
 
 .. _lsst.ip.diffim.DecorrelateALKernelSpatialTask-api:
 

doc/lsst.ip.diffim/tasks/lsst.ip.diffim.DecorrelateALKernelTask.rst

@@ -1,8 +1,8 @@
 .. lsst-task-topic:: lsst.ip.diffim.DecorrelateALKernelTask
 
-##########################
+#######################
 DecorrelateALKernelTask
-##########################
+#######################
 
 Pipe-task that removes the neighboring-pixel covariance in an
 image difference that are added when the template image is
@@ -11,11 +11,10 @@ convolved with the Alard-Lupton PSF matching kernel.
 .. _lsst.ip.diffim.DecorrelateALKernelTask-description:
 
 Description
-==================
+===========
 
-The image differencing pipeline task @link
-ip.diffim.psfMatch.PsfMatchTask PSFMatchTask@endlink and @link
-ip.diffim.psfMatch.PsfMatchConfigAL PSFMatchConfigAL@endlink uses
+The image differencing pipeline task `~ip.diffim.psfMatch.PsfMatchTask` and
+`~ip.diffim.psfMatch.PsfMatchConfigAL` uses
 the Alard and Lupton (1998) method for matching the PSFs of the
 template and science exposures prior to subtraction. The
 Alard-Lupton method identifies a matching kernel, which is then
@@ -32,7 +31,7 @@ convolving the image difference with it. This process is described
 in detail in [DMTN-021](http://dmtn-021.lsst.io).
 
 This task has no standalone example, however it is applied as a
-subtask of pipe.tasks.imageDifference.ImageDifferenceTask.
+subtask of `~pipe.tasks.imageDifference.ImageDifferenceTask`.
 
 .. _lsst.ip.diffim.DecorrelateALKernelTask-api:
 

doc/lsst.ip.diffim/tasks/lsst.ip.diffim.DiaCatalogSourceSelectorTask.rst

@@ -1,15 +1,15 @@
 .. lsst-task-topic:: lsst.ip.diffim.DiaCatalogSourceSelectorTask
 
-##########################
+############################
 DiaCatalogSourceSelectorTask
-##########################
+############################
 
 A task that selects sources for Kernel candidates.
 
 .. _lsst.ip.diffim.DiaCatalogSourceSelectorTask-description:
 
 Description
-==================
+===========
 
 A naive star selector based on second moments. Use with caution.
 
@@ -39,7 +39,10 @@ Configuration fields
 Debugging
 =========
 
-DiaCatalogSourceSelectorTask has a debug dictionary with the following keys:
+The ``pipetask`` command line interface supports a ``--debug`` flag to import
+``debug.py`` from your PYTHONPATH; see :ref:`lsstDebug` for more about ``debug.py``
+files.
+The available variables in DiaCatalogSourceSelectorTask include:
 
 display : `bool`
     if True display debug information

doc/lsst.ip.diffim/tasks/lsst.ip.diffim.DipoleMeasurementTask.rst

@@ -1,18 +1,18 @@
 .. lsst-task-topic:: lsst.ip.diffim.DipoleMeasurementTask
 
-##########################
+#####################
 DipoleMeasurementTask
-##########################
+#####################
 
 DipoleMeasurementTask measures sources on images to identify likely dipoles.
 This task is purely a configuration wrapper around `~lsst.meas.base.SingleFrameMeasurementTask`, with helpers to performe dipole-specific measurements.
 
 .. _lsst.ip.diffim.DipoleMeasurementTask-description:
 
 Description
-==================
+===========
 
-These plugins enabled by default allow the user to test the hypothesis that the
+The plugins used by this task by default allow the user to test the hypothesis that the
 Source is a dipole. This includes a set of measurements derived from
 intermediate base classes DipoleCentroidAlgorithm and DipoleFluxAlgorithm.
 Their respective algorithm control classes are defined in

doc/lsst.ip.diffim/tasks/lsst.ip.diffim.GetCoaddAsTemplateTask.rst

@@ -1,8 +1,8 @@
 .. lsst-task-topic:: lsst.ip.diffim.GetCoaddAsTemplateTask
 
-##########################
+######################
 GetCoaddAsTemplateTask
-##########################
+######################
 
 From the given skymap, the closest tract is selected; multiple tracts are
 not supported. The assembled template inherits the WCS of the selected

doc/lsst.ip.diffim/tasks/lsst.ip.diffim.ImagePsfMatchTask.rst

@@ -1,15 +1,15 @@
 .. lsst-task-topic:: lsst.ip.diffim.ImagePsfMatchTask
 
-##########################
+#################
 ImagePsfMatchTask
-##########################
+#################
 
 ImagePsfMatchTask creates a PSF-matching kernel for two images.
 
 .. _lsst.ip.diffim.ImagePsfMatchTask-description:
 
 Description
-==================
+===========
 
 Build a Psf-matching kernel using two input images, either as MaskedImages
 (in which case they need to be astrometrically aligned) or Exposures (in which
@@ -19,16 +19,16 @@ not, the Task will perform a coarse source detection and selection for this
 purpose. Sources are vetted for signal-to-noise and masked pixels (in both the
 template and science image), and substamps around each acceptable source are
 extracted and used to create an instance of KernelCandidate. Each
-KernelCandidate is then placed within a lsst.afw.math.SpatialCellSet, which is
-used by an ensemble of lsst.afw.math.CandidateVisitor instances to build the
+KernelCandidate is then placed within a `~lsst.afw.math.SpatialCellSet`, which is
+used by an ensemble of `~lsst.afw.math.CandidateVisitor` instances to build the
 Psf-matching kernel. These visitors include, in the order that they are
-called: BuildSingleKernelVisitor, KernelSumVisitor, BuildSpatialKernelVisitor,
-and AssessSpatialKernelVisitor.
+called: ``BuildSingleKernelVisitor``, ``KernelSumVisitor``, ``BuildSpatialKernelVisitor``,
+and ``AssessSpatialKernelVisitor``.
 
 Upon initialization, the kernel configuration is defined by
-self.config.kernel.active. The task creates an lsst.afw.math.Warper from the
-subConfig self.config.kernel.active.warpingConfig. A schema for the selection
-and measurement of candidate lsst.ip.diffim.KernelCandidates is defined, and
+``self.config.kernel.active``. The task creates an `~lsst.afw.math.Warper` from the
+subConfig ``self.config.kernel.active.warpingConfig``. A schema for the selection
+and measurement of candidate `~lsst.ip.diffim.KernelCandidates` is defined, and
 used to initize subTasks selectDetection (for candidate detection) and
 selectMeasurement(for candidate measurement).
 
@@ -39,20 +39,20 @@ Sigma clipping of KernelCandidates is performed as follows:
 * AssessSpatialKernelVisitor, using the substamp diffim ressiduals from the spatial kernel fit, if PsfMatchConfig.spatialKernelClipping is True
 
 The actual solving for the kernel (and differential background model) happens
-in lsst.ip.diffim.PsfMatchTask._solve.  This involves a loop over the
+in ``lsst.ip.diffim.PsfMatchTask._solve``.  This involves a loop over the
 SpatialCellSet that first builds the per-candidate matching kernel for the
 requested number of KernelCandidates per cell
-(PsfMatchConfig.nStarPerCell).  The quality of this initial per-candidate
+(``PsfMatchConfig.nStarPerCell``).  The quality of this initial per-candidate
 difference image is examined, using moments of the pixel residuals in the
 difference image normalized by the square root of the variance(i.e. sigma);
 ideally this should follow a normal (0, 1) distribution, but the rejection
-thresholds are set by the config (PsfMatchConfig.candidateResidualMeanMax and
-PsfMatchConfig.candidateResidualStdMax). All candidates that pass this initial
+thresholds are set by the config (``PsfMatchConfig.candidateResidualMeanMax`` and
+``PsfMatchConfig.candidateResidualStdMax``). All candidates that pass this initial
 build are then examined en masse to find the mean/stdev of the kernel sums
 across all candidates. Objects that are significantly above or below the mean,
 typically due to variability or sources that are saturated in one image but
 not the other, are also rejected.This threshold is defined by
-PsfMatchConfig.maxKsumSigma. Finally, a spatial model is built using all
+``PsfMatchConfig.maxKsumSigma``. Finally, a spatial model is built using all
 currently-acceptable candidates, and the spatial model used to derive a second
 set of (spatial) residuals which are again used to reject bad candidates,
 using the same thresholds as above.
@@ -69,11 +69,11 @@ may be used to invoke the Psf-matching.  These are
 `~lsst.ip.diffim.imagePsfMatch.ImagePsfMatchTask.matchExposures`, and
 `~lsst.ip.diffim.imagePsfMatch.ImagePsfMatchTask.subtractExposures`.
 
-The methods that operate on lsst.afw.image.MaskedImage require that the images
+The methods that operate on `~lsst.afw.image.MaskedImage` require that the images
 already be astrometrically aligned, and are the same shape.  The methods that
-operate on lsst.afw.image.Exposure allow for the input images to be
+operate on `~lsst.afw.image.Exposure` allow for the input images to be
 misregistered and potentially be different sizes; by default a
-lsst.afw.math.LanczosWarpingKernel is used to perform the astrometric
+`~lsst.afw.math.LanczosWarpingKernel` is used to perform the astrometric
 alignment.  The methods that "match" images return a Psf-matched image, while
 the methods that "subtract" images return a Psf-matched and template
 subtracted image.
@@ -106,9 +106,9 @@ Configuration fields
 Debugging
 =========
 
-The ``pipetask`` command line interface supports a flag ``--debug`` to import
-ref:  supports a flag `--debug`` to import debug.py from your PYTHONPATH;
-see :ref:`lsstDebug` for more about debug.py files.
+The ``pipetask`` command line interface supports a ``--debug`` flag to import
+``debug.py`` from your PYTHONPATH; see :ref:`lsstDebug` for more about ``debug.py``
+files.
 The available variables in ImagePsfMatchTask include:
 
 display : `bool`

doc/lsst.ip.diffim/tasks/lsst.ip.diffim.ModelPsfMatchTask.rst

@@ -1,8 +1,8 @@
 .. lsst-task-topic:: lsst.ip.diffim.ModelPsfMatchTask
 
-##########################
+#################
 ModelPsfMatchTask
-##########################
+#################
 
 ImagePsfMatchTask creates a PSF-matching kernel for two models.
 
@@ -22,7 +22,7 @@ a 21x21 matrix).  When the Psf-matching kernel is being solved for, the
 Psf "image" is convolved with each kernel basis function, leading to a loss of
 information around the borders. This pixel loss will be problematic for the
 numerical stability of the kernel solution if the size of the convolution
-kernel(set by ModelPsfMatchConfig.kernelSize) is much bigger than: psfSize//2.
+kernel(set by ``ModelPsfMatchConfig.kernelSize``) is much bigger than: psfSize//2.
 Thus the sizes of Psf-model matching kernels are typically smaller than their
 image-matching counterparts.  If the size of the kernel is too small, the
 convolved stars will look "boxy"; if the kernel is too large, the kernel
@@ -33,7 +33,7 @@ The primary use case for this Task is in matching an Exposure to a
 constant-across-the-sky Psf model for the purposes of image coaddition. It is
 important to note that in the code, the "template" Psf is the Psf that the
 science image gets matched to.  In this sense the order of template and
-science image are reversed, compared to ImagePsfMatchTask, which operates on
+science image are reversed, compared to ``ImagePsfMatchTask``, which operates on
 the template image.
 
 .. _lsst.ip.diffim.ModelPsfMatchTask-api:
@@ -62,9 +62,9 @@ Configuration fields
 Debugging
 =========
 
-The ``pipetask`` command line interface supports a flag ``--debug`` to import
-ref:  supports a flag ``--debug`` to import debug.py from your PYTHONPATH;
-see :ref:`lsstDebug` for more about debug.py files.
+The ``pipetask`` command line interface supports a ``--debug`` flag to import
+``debug.py`` from your PYTHONPATH; see :ref:`lsstDebug` for more about ``debug.py``
+files.
 The available variables in ModelsPsfMatchTask include:
 
 display : `bool`