Coverage for python/lsst/ip/diffim/getTemplate.py : 13%

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1#
2# LSST Data Management System
3# Copyright 2016 LSST Corporation.
4#
5# This product includes software developed by the
6# LSST Project (http://www.lsst.org/).
7#
8# This program is free software: you can redistribute it and/or modify
9# it under the terms of the GNU General Public License as published by
10# the Free Software Foundation, either version 3 of the License, or
11# (at your option) any later version.
12#
13# This program is distributed in the hope that it will be useful,
14# but WITHOUT ANY WARRANTY; without even the implied warranty of
15# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
16# GNU General Public License for more details.
17#
18# You should have received a copy of the LSST License Statement and
19# the GNU General Public License along with this program. If not,
20# see <http://www.lsstcorp.org/LegalNotices/>.
21#
23import numpy as np
25import lsst.afw.image as afwImage
26import lsst.geom as geom
27import lsst.pex.config as pexConfig
28import lsst.pipe.base as pipeBase
29from lsst.ip.diffim.dcrModel import DcrModel
31__all__ = ["GetCoaddAsTemplateTask", "GetCoaddAsTemplateConfig",
32 "GetCalexpAsTemplateTask", "GetCalexpAsTemplateConfig"]
35class GetCoaddAsTemplateConfig(pexConfig.Config):
36 templateBorderSize = pexConfig.Field(
37 dtype=int,
38 default=10,
39 doc="Number of pixels to grow the requested template image to account for warping"
40 )
41 coaddName = pexConfig.Field(
42 doc="coadd name: typically one of 'deep', 'goodSeeing', or 'dcr'",
43 dtype=str,
44 default="deep",
45 )
46 numSubfilters = pexConfig.Field(
47 doc="Number of subfilters in the DcrCoadd, used only if ``coaddName``='dcr'",
48 dtype=int,
49 default=3,
50 )
51 warpType = pexConfig.Field(
52 doc="Warp type of the coadd template: one of 'direct' or 'psfMatched'",
53 dtype=str,
54 default="direct",
55 )
58class GetCoaddAsTemplateTask(pipeBase.Task):
59 """Subtask to retrieve coadd for use as an image difference template.
61 This is the default getTemplate Task to be run as a subtask by
62 ``pipe.tasks.ImageDifferenceTask``. The main methods are ``run()`` and
63 ``runGen3()``.
65 Notes
66 -----
67 From the given skymap, the closest tract is selected; multiple tracts are
68 not supported. The assembled template inherits the WCS of the selected
69 skymap tract and the resolution of the template exposures. Overlapping box
70 regions of the input template patches are pixel by pixel copied into the
71 assembled template image. There is no warping or pixel resampling.
73 Pixels with no overlap of any available input patches are set to ``nan`` value
74 and ``NO_DATA`` flagged.
75 """
77 ConfigClass = GetCoaddAsTemplateConfig
78 _DefaultName = "GetCoaddAsTemplateTask"
80 def runDataRef(self, exposure, sensorRef, templateIdList=None):
81 """Gen2 task entry point. Retrieve and mosaic a template coadd exposure
82 that overlaps the science exposure.
84 Parameters
85 ----------
86 exposure: `lsst.afw.image.Exposure`
87 an exposure for which to generate an overlapping template
88 sensorRef : TYPE
89 a Butler data reference that can be used to obtain coadd data
90 templateIdList : TYPE, optional
91 list of data ids, unused here, in the case of coadd template
93 Returns
94 -------
95 result : `lsst.pipe.base.Struct`
96 - ``exposure`` : `lsst.afw.image.ExposureF`
97 a template coadd exposure assembled out of patches
98 - ``sources`` : None for this subtask
99 """
100 skyMap = sensorRef.get(datasetType=self.config.coaddName + "Coadd_skyMap")
101 tractInfo, patchList, skyCorners = self.getOverlapPatchList(exposure, skyMap)
103 availableCoaddRefs = dict()
104 for patchInfo in patchList:
105 patchNumber = tractInfo.getSequentialPatchIndex(patchInfo)
106 patchArgDict = dict(
107 datasetType=self.getCoaddDatasetName() + "_sub",
108 bbox=patchInfo.getOuterBBox(),
109 tract=tractInfo.getId(),
110 patch="%s,%s" % (patchInfo.getIndex()[0], patchInfo.getIndex()[1]),
111 numSubfilters=self.config.numSubfilters,
112 )
114 if sensorRef.datasetExists(**patchArgDict):
115 self.log.info("Reading patch %s" % patchArgDict)
116 availableCoaddRefs[patchNumber] = patchArgDict
118 templateExposure = self.run(
119 tractInfo, patchList, skyCorners, availableCoaddRefs,
120 sensorRef=sensorRef, visitInfo=exposure.getInfo().getVisitInfo()
121 )
122 return pipeBase.Struct(exposure=templateExposure, sources=None)
124 def runQuantum(self, exposure, butlerQC, skyMapRef, coaddExposureRefs):
125 """Gen3 task entry point. Retrieve and mosaic a template coadd exposure
126 that overlaps the science exposure.
128 Parameters
129 ----------
130 exposure : `lsst.afw.image.Exposure`
131 The science exposure to define the sky region of the template coadd.
132 butlerQC : `lsst.pipe.base.ButlerQuantumContext`
133 Butler like object that supports getting data by DatasetRef.
134 skyMapRef : `lsst.daf.butler.DatasetRef`
135 Reference to SkyMap object that corresponds to the template coadd.
136 coaddExposureRefs : iterable of `lsst.daf.butler.DeferredDatasetRef`
137 Iterable of references to the available template coadd patches.
139 Returns
140 -------
141 result : `lsst.pipe.base.Struct`
142 - ``exposure`` : `lsst.afw.image.ExposureF`
143 a template coadd exposure assembled out of patches
144 - ``sources`` : `None` for this subtask
145 """
146 skyMap = butlerQC.get(skyMapRef)
147 tractInfo, patchList, skyCorners = self.getOverlapPatchList(exposure, skyMap)
148 patchNumFilter = frozenset(tractInfo.getSequentialPatchIndex(p) for p in patchList)
150 availableCoaddRefs = dict()
151 for coaddRef in coaddExposureRefs:
152 dataId = coaddRef.datasetRef.dataId
153 if dataId['tract'] == tractInfo.getId() and dataId['patch'] in patchNumFilter:
154 if self.config.coaddName == 'dcr':
155 self.log.info("Using template input tract=%s, patch=%s, subfilter=%s" %
156 (tractInfo.getId(), dataId['patch'], dataId['subfilter']))
157 if dataId['patch'] in availableCoaddRefs:
158 availableCoaddRefs[dataId['patch']].append(butlerQC.get(coaddRef))
159 else:
160 availableCoaddRefs[dataId['patch']] = [butlerQC.get(coaddRef), ]
161 else:
162 self.log.info("Using template input tract=%s, patch=%s" %
163 (tractInfo.getId(), dataId['patch']))
164 availableCoaddRefs[dataId['patch']] = butlerQC.get(coaddRef)
166 templateExposure = self.run(tractInfo, patchList, skyCorners, availableCoaddRefs,
167 visitInfo=exposure.getInfo().getVisitInfo())
168 return pipeBase.Struct(exposure=templateExposure, sources=None)
170 def getOverlapPatchList(self, exposure, skyMap):
171 """Select the relevant tract and its patches that overlap with the science exposure.
173 Parameters
174 ----------
175 exposure : `lsst.afw.image.Exposure`
176 The science exposure to define the sky region of the template coadd.
178 skyMap : `lsst.skymap.BaseSkyMap`
179 SkyMap object that corresponds to the template coadd.
181 Returns
182 -------
183 result : `tuple` of
184 - ``tractInfo`` : `lsst.skymap.TractInfo`
185 The selected tract.
186 - ``patchList`` : `list` of `lsst.skymap.PatchInfo`
187 List of all overlap patches of the selected tract.
188 - ``skyCorners`` : `list` of `lsst.geom.SpherePoint`
189 Corners of the exposure in the sky in the order given by `lsst.geom.Box2D.getCorners`.
190 """
191 expWcs = exposure.getWcs()
192 expBoxD = geom.Box2D(exposure.getBBox())
193 expBoxD.grow(self.config.templateBorderSize)
194 ctrSkyPos = expWcs.pixelToSky(expBoxD.getCenter())
195 tractInfo = skyMap.findTract(ctrSkyPos)
196 self.log.info("Using skyMap tract %s" % (tractInfo.getId(),))
197 skyCorners = [expWcs.pixelToSky(pixPos) for pixPos in expBoxD.getCorners()]
198 patchList = tractInfo.findPatchList(skyCorners)
200 if not patchList:
201 raise RuntimeError("No suitable tract found")
203 self.log.info("Assembling %s coadd patches" % (len(patchList),))
204 self.log.info("exposure dimensions=%s" % exposure.getDimensions())
206 return (tractInfo, patchList, skyCorners)
208 def run(self, tractInfo, patchList, skyCorners, availableCoaddRefs,
209 sensorRef=None, visitInfo=None):
210 """Gen2 and gen3 shared code: determination of exposure dimensions and
211 copying of pixels from overlapping patch regions.
213 Parameters
214 ----------
215 skyMap : `lsst.skymap.BaseSkyMap`
216 SkyMap object that corresponds to the template coadd.
217 tractInfo : `lsst.skymap.TractInfo`
218 The selected tract.
219 patchList : iterable of `lsst.skymap.patchInfo.PatchInfo`
220 Patches to consider for making the template exposure.
221 skyCorners : list of `lsst.geom.SpherePoint`
222 Sky corner coordinates to be covered by the template exposure.
223 availableCoaddRefs : `dict` of `int` : `lsst.daf.butler.DeferredDatasetHandle` (Gen3)
224 `dict` (Gen2)
225 Dictionary of spatially relevant retrieved coadd patches,
226 indexed by their sequential patch number. In Gen3 mode, .get() is called,
227 in Gen2 mode, sensorRef.get(**coaddef) is called to retrieve the coadd.
228 sensorRef : `lsst.daf.persistence.ButlerDataRef`, Gen2 only
229 TODO DM-22952 Butler data reference to get coadd data.
230 Must be `None` for Gen3.
231 visitInfo : `lsst.afw.image.VisitInfo`, Gen2 only
232 TODO DM-22952 VisitInfo to make dcr model.
234 Returns
235 -------
236 templateExposure: `lsst.afw.image.ExposureF`
237 The created template exposure.
238 """
239 coaddWcs = tractInfo.getWcs()
241 # compute coadd bbox
242 coaddBBox = geom.Box2D()
243 for skyPos in skyCorners:
244 coaddBBox.include(coaddWcs.skyToPixel(skyPos))
245 coaddBBox = geom.Box2I(coaddBBox)
246 self.log.info("coadd dimensions=%s" % coaddBBox.getDimensions())
248 coaddExposure = afwImage.ExposureF(coaddBBox, coaddWcs)
249 coaddExposure.maskedImage.set(np.nan, afwImage.Mask.getPlaneBitMask("NO_DATA"), np.nan)
250 nPatchesFound = 0
251 coaddFilter = None
252 coaddPsf = None
253 coaddPhotoCalib = None
254 for patchInfo in patchList:
255 patchNumber = tractInfo.getSequentialPatchIndex(patchInfo)
256 patchSubBBox = patchInfo.getOuterBBox()
257 patchSubBBox.clip(coaddBBox)
258 patchArgDict = dict(
259 datasetType=self.getCoaddDatasetName() + "_sub",
260 bbox=patchSubBBox,
261 tract=tractInfo.getId(),
262 patch="%s,%s" % (patchInfo.getIndex()[0], patchInfo.getIndex()[1]),
263 numSubfilters=self.config.numSubfilters,
264 )
265 if patchSubBBox.isEmpty():
266 self.log.info(f"skip tract={patchArgDict['tract']}, "
267 f"patch={patchNumber}; no overlapping pixels")
268 continue
269 if patchNumber not in availableCoaddRefs:
270 self.log.warn(f"{patchArgDict['datasetType']}, "
271 f"tract={patchArgDict['tract']}, patch={patchNumber} does not exist")
272 continue
274 if self.config.coaddName == 'dcr':
275 if sensorRef and not sensorRef.datasetExists(subfilter=0, **patchArgDict):
276 self.log.warn("%(datasetType)s, tract=%(tract)s, patch=%(patch)s,"
277 " numSubfilters=%(numSubfilters)s, subfilter=0 does not exist"
278 % patchArgDict)
279 continue
280 patchInnerBBox = patchInfo.getInnerBBox()
281 patchInnerBBox.clip(coaddBBox)
282 if np.min(patchInnerBBox.getDimensions()) <= 2*self.config.templateBorderSize:
283 self.log.info("skip tract=%(tract)s, patch=%(patch)s; too few pixels." % patchArgDict)
284 continue
285 self.log.info("Constructing DCR-matched template for patch %s" % patchArgDict)
287 if sensorRef:
288 dcrModel = DcrModel.fromDataRef(sensorRef, **patchArgDict)
289 else:
290 dcrModel = DcrModel.fromQuantum(availableCoaddRefs[patchNumber])
291 # The edge pixels of the DcrCoadd may contain artifacts due to missing data.
292 # Each patch has significant overlap, and the contaminated edge pixels in
293 # a new patch will overwrite good pixels in the overlap region from
294 # previous patches.
295 # Shrink the BBox to remove the contaminated pixels,
296 # but make sure it is only the overlap region that is reduced.
297 dcrBBox = geom.Box2I(patchSubBBox)
298 dcrBBox.grow(-self.config.templateBorderSize)
299 dcrBBox.include(patchInnerBBox)
300 coaddPatch = dcrModel.buildMatchedExposure(bbox=dcrBBox,
301 wcs=coaddWcs,
302 visitInfo=visitInfo)
303 else:
304 if sensorRef is None:
305 # Gen3
306 coaddPatch = availableCoaddRefs[patchNumber].get()
307 else:
308 # Gen2
309 coaddPatch = sensorRef.get(**availableCoaddRefs[patchNumber])
310 nPatchesFound += 1
312 # Gen2 get() seems to clip based on bbox kwarg but we removed bbox
313 # calculation from caller code. Gen3 also does not do this.
314 overlapBox = coaddPatch.getBBox()
315 overlapBox.clip(coaddBBox)
316 coaddExposure.maskedImage.assign(coaddPatch.maskedImage[overlapBox], overlapBox)
318 if coaddFilter is None:
319 coaddFilter = coaddPatch.getFilter()
321 # Retrieve the PSF for this coadd tract, if not already retrieved
322 if coaddPsf is None and coaddPatch.hasPsf():
323 coaddPsf = coaddPatch.getPsf()
325 # Retrieve the calibration for this coadd tract, if not already retrieved
326 if coaddPhotoCalib is None:
327 coaddPhotoCalib = coaddPatch.getPhotoCalib()
329 if coaddPhotoCalib is None:
330 raise RuntimeError("No coadd PhotoCalib found!")
331 if nPatchesFound == 0:
332 raise RuntimeError("No patches found!")
333 if coaddPsf is None:
334 raise RuntimeError("No coadd Psf found!")
336 coaddExposure.setPhotoCalib(coaddPhotoCalib)
337 coaddExposure.setPsf(coaddPsf)
338 coaddExposure.setFilter(coaddFilter)
339 return coaddExposure
341 def getCoaddDatasetName(self):
342 """Return coadd name for given task config
344 Returns
345 -------
346 CoaddDatasetName : `string`
348 TODO: This nearly duplicates a method in CoaddBaseTask (DM-11985)
349 """
350 warpType = self.config.warpType
351 suffix = "" if warpType == "direct" else warpType[0].upper() + warpType[1:]
352 return self.config.coaddName + "Coadd" + suffix
355class GetCalexpAsTemplateConfig(pexConfig.Config):
356 doAddCalexpBackground = pexConfig.Field(
357 dtype=bool,
358 default=True,
359 doc="Add background to calexp before processing it."
360 )
363class GetCalexpAsTemplateTask(pipeBase.Task):
364 """Subtask to retrieve calexp of the same ccd number as the science image SensorRef
365 for use as an image difference template. Only gen2 supported.
367 To be run as a subtask by pipe.tasks.ImageDifferenceTask.
368 Intended for use with simulations and surveys that repeatedly visit the same pointing.
369 This code was originally part of Winter2013ImageDifferenceTask.
370 """
372 ConfigClass = GetCalexpAsTemplateConfig
373 _DefaultName = "GetCalexpAsTemplateTask"
375 def run(self, exposure, sensorRef, templateIdList):
376 """Return a calexp exposure with based on input sensorRef.
378 Construct a dataId based on the sensorRef.dataId combined
379 with the specifications from the first dataId in templateIdList
381 Parameters
382 ----------
383 exposure : `lsst.afw.image.Exposure`
384 exposure (unused)
385 sensorRef : `list` of `lsst.daf.persistence.ButlerDataRef`
386 Data reference of the calexp(s) to subtract from.
387 templateIdList : `list` of `lsst.daf.persistence.ButlerDataRef`
388 Data reference of the template calexp to be subtraced.
389 Can be incomplete, fields are initialized from `sensorRef`.
390 If there are multiple items, only the first one is used.
392 Returns
393 -------
394 result : `struct`
396 return a pipeBase.Struct:
398 - ``exposure`` : a template calexp
399 - ``sources`` : source catalog measured on the template
400 """
402 if len(templateIdList) == 0:
403 raise RuntimeError("No template data reference supplied.")
404 if len(templateIdList) > 1:
405 self.log.warn("Multiple template data references supplied. Using the first one only.")
407 templateId = sensorRef.dataId.copy()
408 templateId.update(templateIdList[0])
410 self.log.info("Fetching calexp (%s) as template." % (templateId))
412 butler = sensorRef.getButler()
413 template = butler.get(datasetType="calexp", dataId=templateId)
414 if self.config.doAddCalexpBackground:
415 templateBg = butler.get(datasetType="calexpBackground", dataId=templateId)
416 mi = template.getMaskedImage()
417 mi += templateBg.getImage()
419 if not template.hasPsf():
420 raise pipeBase.TaskError("Template has no psf")
422 templateSources = butler.get(datasetType="src", dataId=templateId)
423 return pipeBase.Struct(exposure=template,
424 sources=templateSources)
426 def runDataRef(self, *args, **kwargs):
427 return self.run(*args, **kwargs)
429 def runQuantum(self, **kwargs):
430 raise NotImplementedError("Calexp template is not supported with gen3 middleware")