LSST Applications
21.0.0-172-gfb10e10a+18fedfabac,22.0.0+297cba6710,22.0.0+80564b0ff1,22.0.0+8d77f4f51a,22.0.0+a28f4c53b1,22.0.0+dcf3732eb2,22.0.1-1-g7d6de66+2a20fdde0d,22.0.1-1-g8e32f31+297cba6710,22.0.1-1-geca5380+7fa3b7d9b6,22.0.1-12-g44dc1dc+2a20fdde0d,22.0.1-15-g6a90155+515f58c32b,22.0.1-16-g9282f48+790f5f2caa,22.0.1-2-g92698f7+dcf3732eb2,22.0.1-2-ga9b0f51+7fa3b7d9b6,22.0.1-2-gd1925c9+bf4f0e694f,22.0.1-24-g1ad7a390+a9625a72a8,22.0.1-25-g5bf6245+3ad8ecd50b,22.0.1-25-gb120d7b+8b5510f75f,22.0.1-27-g97737f7+2a20fdde0d,22.0.1-32-gf62ce7b1+aa4237961e,22.0.1-4-g0b3f228+2a20fdde0d,22.0.1-4-g243d05b+871c1b8305,22.0.1-4-g3a563be+32dcf1063f,22.0.1-4-g44f2e3d+9e4ab0f4fa,22.0.1-42-gca6935d93+ba5e5ca3eb,22.0.1-5-g15c806e+85460ae5f3,22.0.1-5-g58711c4+611d128589,22.0.1-5-g75bb458+99c117b92f,22.0.1-6-g1c63a23+7fa3b7d9b6,22.0.1-6-g50866e6+84ff5a128b,22.0.1-6-g8d3140d+720564cf76,22.0.1-6-gd805d02+cc5644f571,22.0.1-8-ge5750ce+85460ae5f3,master-g6e05de7fdc+babf819c66,master-g99da0e417a+8d77f4f51a,w.2021.48
LSST Data Management Base Package
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Public Member Functions | |
def | __init__ (self, *args, **kwargs) |
def | run (self, skyInfo, tempExpRefList, imageScalerList, weightList, *args, **kwargs) |
def | buildDifferenceImage (self, skyInfo, tempExpRefList, imageScalerList, weightList) |
def | detectClip (self, exp, tempExpRefList) |
def | detectClipBig (self, clipList, clipFootprints, clipIndices, detectionFootprints, maskClipValue, maskDetValue, coaddBBox) |
Static Public Attributes | |
ConfigClass | |
Assemble a coadded image from a set of coadded temporary exposures, being careful to clip & flag areas with potential artifacts. In ``AssembleCoaddTask``, we compute the coadd as an clipped mean (i.e., we clip outliers). The problem with doing this is that when computing the coadd PSF at a given location, individual visit PSFs from visits with outlier pixels contribute to the coadd PSF and cannot be treated correctly. In this task, we correct for this behavior by creating a new ``badMaskPlane`` 'CLIPPED'. We populate this plane on the input coaddTempExps and the final coadd where i. difference imaging suggests that there is an outlier and ii. this outlier appears on only one or two images. Such regions will not contribute to the final coadd. Furthermore, any routine to determine the coadd PSF can now be cognizant of clipped regions. Note that the algorithm implemented by this task is preliminary and works correctly for HSC data. Parameter modifications and or considerable redesigning of the algorithm is likley required for other surveys. ``SafeClipAssembleCoaddTask`` uses a ``SourceDetectionTask`` "clipDetection" subtask and also sub-classes ``AssembleCoaddTask``. You can retarget the ``SourceDetectionTask`` "clipDetection" subtask if you wish. Notes ----- The `lsst.pipe.base.cmdLineTask.CmdLineTask` interface supports a flag ``-d`` to import ``debug.py`` from your ``PYTHONPATH``; see `baseDebug` for more about ``debug.py`` files. `SafeClipAssembleCoaddTask` has no debug variables of its own. The ``SourceDetectionTask`` "clipDetection" subtasks may support debug variables. See the documetation for `SourceDetectionTask` "clipDetection" for further information. Examples -------- `SafeClipAssembleCoaddTask` assembles a set of warped ``coaddTempExp`` images into a coadded image. The `SafeClipAssembleCoaddTask` is invoked by running assembleCoadd.py *without* the flag '--legacyCoadd'. Usage of ``assembleCoadd.py`` expects a data reference to the tract patch and filter to be coadded (specified using '--id = [KEY=VALUE1[^VALUE2[^VALUE3...] [KEY=VALUE1[^VALUE2[^VALUE3...] ...]]') along with a list of coaddTempExps to attempt to coadd (specified using '--selectId [KEY=VALUE1[^VALUE2[^VALUE3...] [KEY=VALUE1[^VALUE2[^VALUE3...] ...]]'). Only the coaddTempExps that cover the specified tract and patch will be coadded. A list of the available optional arguments can be obtained by calling assembleCoadd.py with the --help command line argument: .. code-block:: none assembleCoadd.py --help To demonstrate usage of the `SafeClipAssembleCoaddTask` in the larger context of multi-band processing, we will generate the HSC-I & -R band coadds from HSC engineering test data provided in the ci_hsc package. To begin, assuming that the lsst stack has been already set up, we must set up the obs_subaru and ci_hsc packages. This defines the environment variable $CI_HSC_DIR and points at the location of the package. The raw HSC data live in the ``$CI_HSC_DIR/raw`` directory. To begin assembling the coadds, we must first - ``processCcd`` process the individual ccds in $CI_HSC_RAW to produce calibrated exposures - ``makeSkyMap`` create a skymap that covers the area of the sky present in the raw exposures - ``makeCoaddTempExp`` warp the individual calibrated exposures to the tangent plane of the coadd</DD> We can perform all of these steps by running .. code-block:: none $CI_HSC_DIR scons warp-903986 warp-904014 warp-903990 warp-904010 warp-903988 This will produce warped coaddTempExps for each visit. To coadd the warped data, we call ``assembleCoadd.py`` as follows: .. code-block:: none assembleCoadd.py $CI_HSC_DIR/DATA --id patch=5,4 tract=0 filter=HSC-I \ --selectId visit=903986 ccd=16 --selectId visit=903986 ccd=22 --selectId visit=903986 ccd=23 \ --selectId visit=903986 ccd=100--selectId visit=904014 ccd=1 --selectId visit=904014 ccd=6 \ --selectId visit=904014 ccd=12 --selectId visit=903990 ccd=18 --selectId visit=903990 ccd=25 \ --selectId visit=904010 ccd=4 --selectId visit=904010 ccd=10 --selectId visit=904010 ccd=100 \ --selectId visit=903988 ccd=16 --selectId visit=903988 ccd=17 --selectId visit=903988 ccd=23 \ --selectId visit=903988 ccd=24 This will process the HSC-I band data. The results are written in ``$CI_HSC_DIR/DATA/deepCoadd-results/HSC-I``. You may also choose to run: .. code-block:: none scons warp-903334 warp-903336 warp-903338 warp-903342 warp-903344 warp-903346 nnn assembleCoadd.py $CI_HSC_DIR/DATA --id patch=5,4 tract=0 filter=HSC-R --selectId visit=903334 ccd=16 \ --selectId visit=903334 ccd=22 --selectId visit=903334 ccd=23 --selectId visit=903334 ccd=100 \ --selectId visit=903336 ccd=17 --selectId visit=903336 ccd=24 --selectId visit=903338 ccd=18 \ --selectId visit=903338 ccd=25 --selectId visit=903342 ccd=4 --selectId visit=903342 ccd=10 \ --selectId visit=903342 ccd=100 --selectId visit=903344 ccd=0 --selectId visit=903344 ccd=5 \ --selectId visit=903344 ccd=11 --selectId visit=903346 ccd=1 --selectId visit=903346 ccd=6 \ --selectId visit=903346 ccd=12 to generate the coadd for the HSC-R band if you are interested in following multiBand Coadd processing as discussed in ``pipeTasks_multiBand``.
Definition at line 1472 of file assembleCoadd.py.
def lsst.pipe.tasks.assembleCoadd.SafeClipAssembleCoaddTask.__init__ | ( | self, | |
* | args, | ||
** | kwargs | ||
) |
Definition at line 1584 of file assembleCoadd.py.
def lsst.pipe.tasks.assembleCoadd.SafeClipAssembleCoaddTask.buildDifferenceImage | ( | self, | |
skyInfo, | |||
tempExpRefList, | |||
imageScalerList, | |||
weightList | |||
) |
Return an exposure that contains the difference between unclipped and clipped coadds. Generate a difference image between clipped and unclipped coadds. Compute the difference image by subtracting an outlier-clipped coadd from an outlier-unclipped coadd. Return the difference image. Parameters ---------- skyInfo : `lsst.pipe.base.Struct` Patch geometry information, from getSkyInfo tempExpRefList : `list` List of data reference to tempExp imageScalerList : `list` List of image scalers weightList : `list` List of weights Returns ------- exp : `lsst.afw.image.Exposure` Difference image of unclipped and clipped coadd wrapped in an Exposure
Definition at line 1647 of file assembleCoadd.py.
def lsst.pipe.tasks.assembleCoadd.SafeClipAssembleCoaddTask.detectClip | ( | self, | |
exp, | |||
tempExpRefList | |||
) |
Detect clipped regions on an exposure and set the mask on the individual tempExp masks. Detect footprints in the difference image after smoothing the difference image with a Gaussian kernal. Identify footprints that overlap with one or two input ``coaddTempExps`` by comparing the computed overlap fraction to thresholds set in the config. A different threshold is applied depending on the number of overlapping visits (restricted to one or two). If the overlap exceeds the thresholds, the footprint is considered "CLIPPED" and is marked as such on the coaddTempExp. Return a struct with the clipped footprints, the indices of the ``coaddTempExps`` that end up overlapping with the clipped footprints, and a list of new masks for the ``coaddTempExps``. Parameters ---------- exp : `lsst.afw.image.Exposure` Exposure to run detection on. tempExpRefList : `list` List of data reference to tempExp. Returns ------- result : `lsst.pipe.base.Struct` Result struct with components: - ``clipFootprints``: list of clipped footprints. - ``clipIndices``: indices for each ``clippedFootprint`` in ``tempExpRefList``. - ``clipSpans``: List of dictionaries containing spanSet lists to clip. Each element contains the new maskplane name ("CLIPPED") as the key and list of ``SpanSets`` as the value. - ``detectionFootprints``: List of DETECTED/DETECTED_NEGATIVE plane compressed into footprints.
Definition at line 1698 of file assembleCoadd.py.
def lsst.pipe.tasks.assembleCoadd.SafeClipAssembleCoaddTask.detectClipBig | ( | self, | |
clipList, | |||
clipFootprints, | |||
clipIndices, | |||
detectionFootprints, | |||
maskClipValue, | |||
maskDetValue, | |||
coaddBBox | |||
) |
Return individual warp footprints for large artifacts and append them to ``clipList`` in place. Identify big footprints composed of many sources in the coadd difference that may have originated in a large diffuse source in the coadd. We do this by indentifying all clipped footprints that overlap significantly with each source in all the coaddTempExps. Parameters ---------- clipList : `list` List of alt mask SpanSets with clipping information. Modified. clipFootprints : `list` List of clipped footprints. clipIndices : `list` List of which entries in tempExpClipList each footprint belongs to. maskClipValue Mask value of clipped pixels. maskDetValue Mask value of detected pixels. coaddBBox : `lsst.geom.Box` BBox of the coadd and warps. Returns ------- bigFootprintsCoadd : `list` List of big footprints
Definition at line 1824 of file assembleCoadd.py.
def lsst.pipe.tasks.assembleCoadd.SafeClipAssembleCoaddTask.run | ( | self, | |
skyInfo, | |||
tempExpRefList, | |||
imageScalerList, | |||
weightList, | |||
* | args, | ||
** | kwargs | ||
) |
Assemble the coadd for a region. Compute the difference of coadds created with and without outlier rejection to identify coadd pixels that have outlier values in some individual visits. Detect clipped regions on the difference image and mark these regions on the one or two individual coaddTempExps where they occur if there is significant overlap between the clipped region and a source. This leaves us with a set of footprints from the difference image that have been identified as having occured on just one or two individual visits. However, these footprints were generated from a difference image. It is conceivable for a large diffuse source to have become broken up into multiple footprints acrosss the coadd difference in this process. Determine the clipped region from all overlapping footprints from the detected sources in each visit - these are big footprints. Combine the small and big clipped footprints and mark them on a new bad mask plane. Generate the coadd using `AssembleCoaddTask.run` without outlier removal. Clipped footprints will no longer make it into the coadd because they are marked in the new bad mask plane. Notes ----- args and kwargs are passed but ignored in order to match the call signature expected by the parent task.
Definition at line 1591 of file assembleCoadd.py.
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static |
Definition at line 1581 of file assembleCoadd.py.