Coverage for python/lsst/meas/extensions/gaap/_gaap.py: 23%
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1# This file is part of meas_extensions_gaap
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (http://www.lsst.org/).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the LSST License Statement and
20# the GNU General Public License along with this program. If not,
21# see <http://www.lsstcorp.org/LegalNotices/>.
23from __future__ import annotations
25__all__ = ("SingleFrameGaapFluxPlugin", "SingleFrameGaapFluxConfig",
26 "ForcedGaapFluxPlugin", "ForcedGaapFluxConfig")
28from typing import Generator, Optional, Union
29from functools import partial
30import itertools
31import logging
32import lsst.afw.detection as afwDetection
33import lsst.afw.image as afwImage
34import lsst.afw.geom as afwGeom
35import lsst.afw.table as afwTable
36import lsst.geom
37import lsst.meas.base as measBase
38from lsst.meas.base.fluxUtilities import FluxResultKey
39import lsst.pex.config as pexConfig
40from lsst.pex.exceptions import InvalidParameterError
41import scipy.signal
42from ._gaussianizePsf import GaussianizePsfTask
44PLUGIN_NAME = "ext_gaap_GaapFlux"
47class GaapConvolutionError(measBase.exceptions.MeasurementError):
48 """Collection of any unexpected errors in GAaP during PSF Gaussianization.
50 The PSF Gaussianization procedure using `modelPsfMatchTask` may throw
51 exceptions for certain target PSFs. Such errors are caught until all
52 measurements are at least attempted. The complete traceback information
53 is lost, but unique error messages are preserved.
55 Parameters
56 ----------
57 errors : `dict` [`str`, `Exception`]
58 The values are exceptions raised, while the keys are the loop variables
59 (in `str` format) where the exceptions were raised.
60 """
61 def __init__(self, errors: dict[str, Exception]):
62 self.errorDict = errors
63 message = "Problematic scaling factors = "
64 message += ", ".join(errors)
65 message += " Errors: "
66 message += " | ".join(set(msg.__repr__() for msg in errors.values())) # msg.cpp.what() misses type
67 super().__init__(message, 1) # the second argument does not matter.
70class BaseGaapFluxConfig(measBase.BaseMeasurementPluginConfig):
71 """Configuration parameters for Gaussian Aperture and PSF (GAaP) plugin.
72 """
73 def _greaterThanOrEqualToUnity(x: float) -> bool: # noqa: N805
74 """Returns True if the input ``x`` is greater than 1.0, else False.
75 """
76 return x >= 1
78 def _isOdd(x: int) -> bool: # noqa: N805
79 """Returns True if the input ``x`` is positive and odd, else False.
80 """
81 return (x%2 == 1) & (x > 0)
83 sigmas = pexConfig.ListField(
84 dtype=float,
85 default=[0.7, 1.0],
86 doc="List of sigmas (in arcseconds) of circular Gaussian apertures to apply on "
87 "pre-seeing galaxy images. These should be somewhat larger than the PSF "
88 "(determined by ``scalingFactors``) to avoid measurement failures."
89 )
91 scalingFactors = pexConfig.ListField(
92 dtype=float,
93 default=[1.15],
94 itemCheck=_greaterThanOrEqualToUnity,
95 doc="List of factors with which the seeing should be scaled to obtain the "
96 "sigma values of the target Gaussian PSF. The factor should not be less "
97 "than unity to avoid the PSF matching task to go into deconvolution mode "
98 "and should ideally be slightly greater than unity. The runtime of the "
99 "plugin scales linearly with the number of elements in the list."
100 )
102 _modelPsfMatch = pexConfig.ConfigurableField(
103 target=GaussianizePsfTask,
104 doc="PSF Gaussianization Task"
105 )
107 _modelPsfDimension = pexConfig.Field(
108 dtype=int,
109 default=65,
110 check=_isOdd,
111 doc="The dimensions (width and height) of the target PSF image in pixels. Must be odd."
112 )
114 doPsfPhotometry = pexConfig.Field(
115 dtype=bool,
116 default=False,
117 doc="Perform PSF photometry after PSF-Gaussianization to validate Gaussianization accuracy? "
118 "This does not produce consistent color estimates. If setting it to `True`, it must be done so "
119 "prior to registering the plugin for aperture correction if ``registerForApCorr`` is also `True`."
120 )
122 doOptimalPhotometry = pexConfig.Field(
123 dtype=bool,
124 default=True,
125 doc="Perform optimal photometry with near maximal SNR using an adaptive elliptical aperture? "
126 "This requires a shape algorithm to have been run previously."
127 )
129 registerForApCorr = pexConfig.Field(
130 dtype=bool,
131 default=True,
132 doc="Register measurements for aperture correction? "
133 "The aperture correction registration is done when the plugin is instatiated and not "
134 "during import because the column names are derived from the configuration rather than being "
135 "static. Sometimes you want to turn this off, e.g., when you use aperture corrections derived "
136 "from somewhere else through a 'proxy' mechanism."
137 )
139 # scaleByFwm is the only config field of modelPsfMatch Task that we allow
140 # the user to set without explicitly setting the modelPsfMatch config.
141 # It is intended to abstract away the underlying implementation.
142 @property
143 def scaleByFwhm(self) -> bool:
144 """Config parameter of the PSF Matching task.
145 Scale kernelSize, alardGaussians by input Fwhm?
146 """
147 return self._modelPsfMatch.kernel.active.scaleByFwhm
149 @scaleByFwhm.setter
150 def scaleByFwhm(self, value: bool) -> None:
151 self._modelPsfMatch.kernel.active.scaleByFwhm = value
153 @property
154 def gaussianizationMethod(self) -> str:
155 """Type of convolution to use for PSF-Gaussianization."""
156 return self._modelPsfMatch.convolutionMethod
158 @gaussianizationMethod.setter
159 def gaussianizationMethod(self, value: str) -> None:
160 self._modelPsfMatch.convolutionMethod = value
162 @property
163 def _sigmas(self) -> list:
164 """List of values set in ``sigmas`` along with special apertures such
165 as "PsfFlux" and "Optimal" if applicable.
166 """
167 return self.sigmas.list() + ["PsfFlux"]*self.doPsfPhotometry + ["Optimal"]*self.doOptimalPhotometry
169 def setDefaults(self) -> None:
170 # Docstring inherited
171 # TODO: DM-27482 might change these values.
172 self._modelPsfMatch.kernel.active.alardNGauss = 1
173 self._modelPsfMatch.kernel.active.alardDegGaussDeconv = 1
174 self._modelPsfMatch.kernel.active.alardDegGauss = [4]
175 self._modelPsfMatch.kernel.active.alardGaussBeta = 1.0
176 self._modelPsfMatch.kernel.active.spatialKernelOrder = 0
177 self.scaleByFwhm = True
179 def validate(self):
180 super().validate()
181 self._modelPsfMatch.validate()
182 assert self._modelPsfMatch.kernel.active.alardNGauss == 1
184 @staticmethod
185 def _getGaapResultName(scalingFactor: float, sigma: Union[float, str], name: Optional[str] = None) -> str:
186 """Return the base name for GAaP fields
188 For example, for a scaling factor of 1.15 for seeing and sigma of the
189 effective Gaussian aperture of 0.7 arcsec, the returned value would be
190 "ext_gaap_GaapFlux_1_15x_0_7".
192 Notes
193 -----
194 Being a static method, this does not check if measurements correspond
195 to the input arguments. Instead, users should use
196 `getAllGaapResultNames` to obtain the full list of base names.
198 This is not a config-y thing, but is placed here to make the fieldnames
199 from GAaP measurements available outside the plugin.
201 Parameters
202 ----------
203 scalingFactor : `float`
204 The factor by which the trace radius of the PSF must be scaled.
205 sigma : `float` or `str`
206 Sigma of the effective Gaussian aperture (PSF-convolved explicit
207 aperture) or "PsfFlux" for PSF photometry post PSF-Gaussianization.
208 name : `str`, optional
209 The exact registered name of the GAaP plugin, typically either
210 "ext_gaap_GaapFlux" or "undeblended_ext_gaap_GaapFlux". If ``name``
211 is None, then only the middle part (1_15x_0_7 in the example)
212 without the leading underscore is returned.
214 Returns
215 -------
216 baseName : `str`
217 Base name for GAaP field.
218 """
219 suffix = "_".join((str(scalingFactor).replace(".", "_")+"x", str(sigma).replace(".", "_")))
220 if name is None:
221 return suffix
222 return "_".join((name, suffix))
224 def getAllGaapResultNames(self, name: Optional[str] = PLUGIN_NAME) -> Generator[str]:
225 """Generate the base names for all of the GAaP fields.
227 For example, if the plugin is configured with `scalingFactors` = [1.15]
228 and `sigmas` = [0.7, 1.0] the returned expression would yield
229 ("ext_gaap_GaapFlux_1_15x_0_7", "ext_gaap_GaapFlux_1_15x_1_0") when
230 called with ``name`` = "ext_gaap_GaapFlux". It will also generate
231 "ext_gaap_GaapFlux_1_15x_PsfFlux" if `doPsfPhotometry` is True.
233 Parameters
234 ----------
235 name : `str`, optional
236 The exact registered name of the GAaP plugin, typically either
237 "ext_gaap_GaapFlux" or "undeblended_ext_gaap_GaapFlux". If ``name``
238 is None, then only the middle parts (("1_15x_0_7", "1_15x_1_0"),
239 for example) without the leading underscores are returned.
241 Returns
242 -------
243 baseNames : `generator`
244 A generator expression yielding all the base names.
245 """
246 scalingFactors = self.scalingFactors
247 sigmas = self._sigmas
248 baseNames = (self._getGaapResultName(scalingFactor, sigma, name)
249 for scalingFactor, sigma in itertools.product(scalingFactors, sigmas))
250 return baseNames
253class BaseGaapFluxMixin:
254 """Mixin base class for Gaussian-Aperture and PSF (GAaP) photometry
255 algorithm.
257 This class does almost all the heavy-lifting for its two derived classes,
258 SingleFrameGaapFluxPlugin and ForcedGaapFluxPlugin which simply adapt it to
259 the slightly different interfaces for single-frame and forced measurement.
260 This class implements the GAaP algorithm and is intended for code reuse
261 by the two concrete derived classes by including this mixin class.
263 Parameters
264 ----------
265 config : `BaseGaapFluxConfig`
266 Plugin configuration.
267 name : `str`
268 Plugin name, for registering.
269 schema : `lsst.afw.table.Schema`
270 The schema for the measurement output catalog. New fields will be added
271 to hold measurements produced by this plugin.
272 logName : `str`, optional
273 Name to use when logging errors. This is typically provided by the
274 measurement framework.
276 Raises
277 ------
278 GaapConvolutionError
279 Raised if the PSF Gaussianization fails for one or more target PSFs.
280 lsst.meas.base.FatalAlgorithmError
281 Raised if the Exposure does not contain a PSF model.
282 """
284 ConfigClass = BaseGaapFluxConfig
285 hasLogName = True
287 def __init__(self, config: BaseGaapFluxConfig, name, schema, logName=None) -> None:
288 # Flag definitions for each variant of GAaP measurement
289 flagDefs = measBase.FlagDefinitionList()
290 for scalingFactor, sigma in itertools.product(config.scalingFactors, config.sigmas):
291 baseName = self.ConfigClass._getGaapResultName(scalingFactor, sigma, name)
292 doc = f"GAaP Flux with {sigma} aperture after multiplying the seeing by {scalingFactor}"
293 FluxResultKey.addFields(schema, name=baseName, doc=doc)
295 # Remove the prefix_ since FlagHandler prepends it
296 middleName = self.ConfigClass._getGaapResultName(scalingFactor, sigma)
297 flagDefs.add(schema.join(middleName, "flag_bigPsf"), "The Gaussianized PSF is "
298 "bigger than the aperture")
299 flagDefs.add(schema.join(middleName, "flag"), "Generic failure flag for this set of config "
300 "parameters. ")
302 # PSF photometry
303 if config.doPsfPhotometry:
304 for scalingFactor in config.scalingFactors:
305 baseName = self.ConfigClass._getGaapResultName(scalingFactor, "PsfFlux", name)
306 doc = f"GAaP Flux with PSF aperture after multiplying the seeing by {scalingFactor}"
307 FluxResultKey.addFields(schema, name=baseName, doc=doc)
309 # Remove the prefix_ since FlagHandler prepends it
310 middleName = self.ConfigClass._getGaapResultName(scalingFactor, "PsfFlux")
311 flagDefs.add(schema.join(middleName, "flag"), "Generic failure flag for this set of config "
312 "parameters. ")
314 if config.doOptimalPhotometry:
315 # Add fields to hold the optimal aperture shape
316 # OptimalPhotometry case will fetch the aperture shape from here.
317 self.optimalShapeKey = afwTable.QuadrupoleKey.addFields(schema, schema.join(name, "OptimalShape"),
318 doc="Pre-seeing aperture used for "
319 "optimal GAaP photometry")
320 for scalingFactor in config.scalingFactors:
321 baseName = self.ConfigClass._getGaapResultName(scalingFactor, "Optimal", name)
322 docstring = f"GAaP Flux with optimal aperture after multiplying the seeing by {scalingFactor}"
323 FluxResultKey.addFields(schema, name=baseName, doc=docstring)
325 # Remove the prefix_ since FlagHandler prepends it
326 middleName = self.ConfigClass._getGaapResultName(scalingFactor, "Optimal")
327 flagDefs.add(schema.join(middleName, "flag_bigPsf"), "The Gaussianized PSF is "
328 "bigger than the aperture")
329 flagDefs.add(schema.join(middleName, "flag"), "Generic failure flag for this set of config "
330 "parameters. ")
332 if config.registerForApCorr:
333 for baseName in config.getAllGaapResultNames(name):
334 measBase.addApCorrName(baseName)
336 for scalingFactor in config.scalingFactors:
337 flagName = self.ConfigClass._getGaapResultName(scalingFactor, "flag_gaussianization")
338 flagDefs.add(flagName, "PSF Gaussianization failed when trying to scale by this factor.")
340 self.log = logging.getLogger(logName)
341 self.flagHandler = measBase.FlagHandler.addFields(schema, name, flagDefs)
342 self.EdgeFlagKey = schema.addField(schema.join(name, "flag_edge"), type="Flag",
343 doc="Source is too close to the edge")
344 self._failKey = schema.addField(name + '_flag', type="Flag", doc="Set for any fatal failure")
346 self.psfMatchTask = config._modelPsfMatch.target(config=config._modelPsfMatch)
348 @staticmethod
349 def _computeKernelAcf(kernel: lsst.afw.math.Kernel) -> lsst.afw.image.Image: # noqa: F821
350 """Compute the auto-correlation function of ``kernel``.
352 Parameters
353 ----------
354 kernel : `~lsst.afw.math.Kernel`
355 The kernel for which auto-correlation function is to be computed.
357 Returns
358 -------
359 acfImage : `~lsst.afw.image.Image`
360 The two-dimensional auto-correlation function of ``kernel``.
361 """
362 kernelImage = afwImage.ImageD(kernel.getDimensions())
363 kernel.computeImage(kernelImage, False)
364 acfArray = scipy.signal.correlate2d(kernelImage.array, kernelImage.array, boundary='fill')
365 acfImage = afwImage.ImageD(acfArray)
366 return acfImage
368 @staticmethod
369 def _getFluxErrScaling(kernelAcf: lsst.afw.image.Image, # noqa: F821
370 aperShape: lsst.afw.geom.Quadrupole) -> float: # noqa: F821
371 """Calculate the value by which the standard error has to be scaled due
372 to noise correlations.
374 This calculates the correction to apply to the naively computed
375 `instFluxErr` to account for correlations in the pixel noise introduced
376 in the PSF-Gaussianization step.
377 This method performs the integral in Eq. A17 of Kuijken et al. (2015).
379 The returned value equals
380 :math:`\\int\\mathrm{d}x C^G(x) \\exp(-x^T Q^{-1}x/4)`
381 where :math: `Q` is ``aperShape`` and :math: `C^G(x)` is ``kernelAcf``.
383 Parameters
384 ----------
385 kernelAcf : `~lsst.afw.image.Image`
386 The auto-correlation function (ACF) of the PSF matching kernel.
387 aperShape : `~lsst.afw.geom.Quadrupole`
388 The shape parameter of the Gaussian function which was used to
389 measure GAaP flux.
391 Returns
392 -------
393 fluxErrScaling : `float`
394 The factor by which the standard error on GAaP flux must be scaled.
395 """
396 aperShapeX2 = aperShape.convolve(aperShape)
397 corrFlux = measBase.SdssShapeAlgorithm.computeFixedMomentsFlux(kernelAcf, aperShapeX2,
398 kernelAcf.getBBox().getCenter())
399 fluxErrScaling = (0.5*corrFlux.instFlux)**0.5
400 return fluxErrScaling
402 def _gaussianize(self, exposure: afwImage.Exposure, modelPsf: afwDetection.GaussianPsf,
403 measRecord: lsst.afw.table.SourceRecord) -> lsst.pipe.base.Struct: # noqa: F821
404 """Modify the ``exposure`` so that its PSF is a Gaussian.
406 Compute the convolution kernel to make the PSF same as ``modelPsf``
407 and return the Gaussianized exposure in a struct.
409 Parameters
410 ----------
411 exposure : `~lsst.afw.image.Exposure`
412 Original (full) exposure containing all the sources.
413 modelPsf : `~lsst.afw.detection.GaussianPsf`
414 Target PSF to which to match.
415 measRecord : `~lsst.afw.tabe.SourceRecord`
416 Record for the source to be measured.
418 Returns
419 -------
420 result : `~lsst.pipe.base.Struct`
421 ``result`` is the Struct returned by `modelPsfMatch` task. Notably,
422 it contains a ``psfMatchedExposure``, which is the exposure
423 containing the source, convolved to the target seeing and
424 ``psfMatchingKernel``, the kernel that ``exposure`` was convolved
425 by to obtain ``psfMatchedExposure``. Typically, the bounding box of
426 ``psfMatchedExposure`` is larger than that of the footprint.
427 """
428 footprint = measRecord.getFootprint()
429 bbox = footprint.getBBox()
431 # The kernelSize is guaranteed to be odd, say 2N+1 pixels (N=10 by
432 # default). The flux inside the footprint is smeared by N pixels on
433 # either side, which is region of interest. So grow the bounding box
434 # initially by N pixels on either side.
435 pixToGrow = self.config._modelPsfMatch.kernel.active.kernelSize//2
436 bbox.grow(pixToGrow)
438 # The bounding box may become too big and go out of bounds for sources
439 # near the edge. Clip the subExposure to the exposure's bounding box.
440 # Set the flag_edge marking that the bbox of the footprint could not
441 # be grown fully but do not set it as a failure.
442 if not exposure.getBBox().contains(bbox):
443 bbox.clip(exposure.getBBox())
444 measRecord.setFlag(self.EdgeFlagKey, True)
446 subExposure = exposure[bbox]
448 # The size parameter of the basis has to be set dynamically.
449 result = self.psfMatchTask.run(exposure=subExposure, center=measRecord.getCentroid(),
450 targetPsfModel=modelPsf,
451 basisSigmaGauss=[modelPsf.getSigma()])
452 # TODO: DM-27407 will re-Gaussianize the exposure to make the PSF even
453 # more Gaussian-like
455 # Do not let the variance plane be rescaled since we handle it
456 # carefully later using _getFluxScaling method
457 result.psfMatchedExposure.variance.array = subExposure.variance.array
458 return result
460 def _measureFlux(self, measRecord: lsst.afw.table.SourceRecord,
461 exposure: afwImage.Exposure, kernelAcf: afwImage.Image,
462 center: lsst.geom.Point2D, aperShape: afwGeom.Quadrupole,
463 baseName: str, fluxScaling: Optional[float] = None) -> None:
464 """Measure the flux and populate the record.
466 Parameters
467 ----------
468 measRecord : `~lsst.afw.table.SourceRecord`
469 Catalog record for the source being measured.
470 exposure : `~lsst.afw.image.Exposure`
471 Subexposure containing the deblended source being measured.
472 The PSF attached to it should nominally be an
473 `lsst.afw.Detection.GaussianPsf` object, but not enforced.
474 kernelAcf : `~lsst.afw.image.Image`
475 An image representating the auto-correlation function of the
476 PSF-matching kernel.
477 center : `~lsst.geom.Point2D`
478 The centroid position of the source being measured.
479 aperShape : `~lsst.afw.geom.Quadrupole`
480 The shape parameter of the post-seeing Gaussian aperture.
481 It should be a valid quadrupole if ``fluxScaling`` is specified.
482 baseName : `str`
483 The base name of the GAaP field.
484 fluxScaling : `float`, optional
485 The multiplication factor by which the measured flux has to be
486 scaled. If `None` or unspecified, the pre-factor in Eq. A16
487 of Kuijken et al. (2015) is computed and applied.
488 """
489 if fluxScaling is None:
490 # Calculate the pre-factor in Eq. A16 of Kuijken et al. (2015)
491 # to scale the flux. Include an extra factor of 0.5 to undo
492 # the normalization factor of 2 in `computeFixedMomentsFlux`.
493 try:
494 aperShape.normalize()
495 # Calculate the pre-seeing aperture.
496 preseeingShape = aperShape.convolve(exposure.getPsf().computeShape(center))
497 fluxScaling = 0.5*preseeingShape.getArea()/aperShape.getArea()
498 except (InvalidParameterError, ZeroDivisionError):
499 self._setFlag(measRecord, baseName, "bigPsf")
500 return
502 # Calculate the integral in Eq. A17 of Kuijken et al. (2015)
503 # ``fluxErrScaling`` contains the factors not captured by
504 # ``fluxScaling`` and `instFluxErr`. It is 1 theoretically
505 # if ``kernelAcf`` is a Dirac-delta function.
506 fluxErrScaling = self._getFluxErrScaling(kernelAcf, aperShape)
508 fluxResult = measBase.SdssShapeAlgorithm.computeFixedMomentsFlux(exposure.getMaskedImage(),
509 aperShape, center)
511 # Scale the quantities in fluxResult and copy result to record
512 fluxResult.instFlux *= fluxScaling
513 fluxResult.instFluxErr *= fluxScaling*fluxErrScaling
514 fluxResultKey = FluxResultKey(measRecord.schema[baseName])
515 fluxResultKey.set(measRecord, fluxResult)
517 def _gaussianizeAndMeasure(self, measRecord: lsst.afw.table.SourceRecord,
518 exposure: afwImage.Exposure,
519 center: lsst.geom.Point2D) -> None:
520 """Measure the properties of a source on a single image.
522 The image may be from a single epoch, or it may be a coadd.
524 Parameters
525 ----------
526 measRecord : `~lsst.afw.table.SourceRecord`
527 Record describing the object being measured. Previously-measured
528 quantities may be retrieved from here, and it will be updated
529 in-place with the outputs of this plugin.
530 exposure : `~lsst.afw.image.ExposureF`
531 The pixel data to be measured, together with the associated PSF,
532 WCS, etc. All other sources in the image should have been replaced
533 by noise according to deblender outputs.
534 center : `~lsst.geom.Point2D`
535 Centroid location of the source being measured.
537 Raises
538 ------
539 GaapConvolutionError
540 Raised if the PSF Gaussianization fails for any of the target PSFs.
541 lsst.meas.base.FatalAlgorithmError
542 Raised if the Exposure does not contain a PSF model.
544 Notes
545 -----
546 This method is the entry point to the mixin from the concrete derived
547 classes.
548 """
549 psf = exposure.getPsf()
550 if psf is None:
551 raise measBase.FatalAlgorithmError("No PSF in exposure")
552 wcs = exposure.getWcs()
554 psfSigma = psf.computeShape(center).getTraceRadius()
555 if not (psfSigma > 0): # This captures NaN and negative values.
556 errorCollection = {str(scalingFactor): measBase.MeasurementError("PSF size could not be measured")
557 for scalingFactor in self.config.scalingFactor}
558 raise GaapConvolutionError(errorCollection)
559 else:
560 errorCollection = dict()
562 for scalingFactor in self.config.scalingFactors:
563 targetSigma = scalingFactor*psfSigma
564 # If this target PSF is bound to fail for all apertures,
565 # set the flags and move on without PSF Gaussianization.
566 if self._isAllFailure(measRecord, scalingFactor, targetSigma):
567 continue
569 stampSize = self.config._modelPsfDimension
570 targetPsf = afwDetection.GaussianPsf(stampSize, stampSize, targetSigma)
571 try:
572 result = self._gaussianize(exposure, targetPsf, measRecord)
573 except Exception as error:
574 errorCollection[str(scalingFactor)] = error
575 continue
577 convolved = result.psfMatchedExposure
578 kernelAcf = self._computeKernelAcf(result.psfMatchingKernel)
580 measureFlux = partial(self._measureFlux, measRecord, convolved, kernelAcf, center)
581 # Computing shape is inexpensive and position-independent for a
582 # GaussianPsf
583 psfShape = targetPsf.computeShape(center)
585 if self.config.doPsfPhotometry:
586 baseName = self.ConfigClass._getGaapResultName(scalingFactor, "PsfFlux", self.name)
587 aperShape = psfShape
588 measureFlux(aperShape, baseName, fluxScaling=1)
590 if self.config.doOptimalPhotometry:
591 baseName = self.ConfigClass._getGaapResultName(scalingFactor, "Optimal", self.name)
592 optimalShape = measRecord.get(self.optimalShapeKey)
593 aperShape = afwGeom.Quadrupole(optimalShape.getParameterVector()
594 - psfShape.getParameterVector())
595 measureFlux(aperShape, baseName)
597 # Iterate over pre-defined circular apertures
598 for sigma in self.config.sigmas:
599 baseName = self.ConfigClass._getGaapResultName(scalingFactor, sigma, self.name)
600 if sigma <= targetSigma * wcs.getPixelScale(center).asArcseconds():
601 # Raise when the aperture is invalid
602 self._setFlag(measRecord, baseName, "bigPsf")
603 continue
605 intrinsicShape = afwGeom.Quadrupole(sigma**2, sigma**2, 0.0) # in sky coordinates
606 intrinsicShape.transformInPlace(wcs.linearizeSkyToPixel(center,
607 lsst.geom.arcseconds).getLinear())
608 aperShape = afwGeom.Quadrupole(intrinsicShape.getParameterVector()
609 - psfShape.getParameterVector())
610 measureFlux(aperShape, baseName)
612 # Raise GaapConvolutionError before exiting the plugin
613 # if the collection of errors is not empty
614 if errorCollection:
615 raise GaapConvolutionError(errorCollection)
617 @staticmethod
618 def _setFlag(measRecord, baseName, flagName=None):
619 """Set the GAaP flag determined by ``baseName`` and ``flagName``.
621 A convenience method to set {baseName}_flag_{flagName} to True.
622 This also automatically sets the generic {baseName}_flag to True.
623 To set the general plugin flag indicating measurement failure,
624 use _failKey directly.
626 Parameters
627 ----------
628 measRecord : `~lsst.afw.table.SourceRecord`
629 Record describing the source being measured.
630 baseName : `str`
631 The base name of the GAaP field for which the flag must be set.
632 flagName : `str`, optional
633 The name of the specific flag to set along with the general flag.
634 If unspecified, only the general flag corresponding to ``baseName``
635 is set. For now, the only value that can be specified is "bigPsf".
636 """
637 if flagName is not None:
638 specificFlagKey = measRecord.schema.join(baseName, f"flag_{flagName}")
639 measRecord.set(specificFlagKey, True)
640 genericFlagKey = measRecord.schema.join(baseName, "flag")
641 measRecord.set(genericFlagKey, True)
643 def _isAllFailure(self, measRecord, scalingFactor, targetSigma) -> bool:
644 """Check if all measurements would result in failure.
646 If all of the pre-seeing apertures are smaller than size of the
647 target PSF for the given ``scalingFactor``, then set the
648 `flag_bigPsf` for all fields corresponding to ``scalingFactor``
649 and move on instead of spending computational effort in
650 Gaussianizing the exposure.
652 Parameters
653 ----------
654 measRecord : `~lsst.afw.table.SourceRecord`
655 Record describing the source being measured.
656 scalingFactor : `float`
657 The multiplicative factor by which the seeing is scaled.
658 targetSigma : `float`
659 Sigma (in pixels) of the target circular Gaussian PSF.
661 Returns
662 -------
663 allFailure : `bool`
664 A boolean value indicating whether all measurements would fail.
666 Notes
667 ----
668 If doPsfPhotometry is set to True, then this will always return False.
669 """
670 if self.config.doPsfPhotometry:
671 return False
673 allFailure = targetSigma >= max(self.config.sigmas)
674 # If measurements would fail on all circular apertures, and if
675 # optimal elliptical aperture is used, check if that would also fail.
676 if self.config.doOptimalPhotometry and allFailure:
677 optimalShape = measRecord.get(self.optimalShapeKey)
678 aperShape = afwGeom.Quadrupole(optimalShape.getParameterVector()
679 - [targetSigma**2, targetSigma**2, 0.0])
680 allFailure = (aperShape.getIxx() <= 0) or (aperShape.getIyy() <= 0) or (aperShape.getArea() <= 0)
682 # Set all failure flags if allFailure is True.
683 if allFailure:
684 if self.config.doOptimalPhotometry:
685 baseName = self.ConfigClass._getGaapResultName(scalingFactor, "Optimal", self.name)
686 self._setFlag(measRecord, baseName, "bigPsf")
687 for sigma in self.config.sigmas:
688 baseName = self.ConfigClass._getGaapResultName(scalingFactor, sigma, self.name)
689 self._setFlag(measRecord, baseName, "bigPsf")
691 return allFailure
693 def fail(self, measRecord, error=None):
694 """Record a measurement failure.
696 This default implementation simply records the failure in the source
697 record and is inherited by the SingleFrameGaapFluxPlugin and
698 ForcedGaapFluxPlugin.
700 Parameters
701 ----------
702 measRecord : `lsst.afw.table.SourceRecord`
703 Catalog record for the source being measured.
704 error : `Exception`
705 Error causing failure, or `None`.
706 """
707 if error is not None:
708 center = measRecord.getCentroid()
709 self.log.error("Failed to solve for PSF matching kernel in GAaP for (%f, %f): %s",
710 center.getX(), center.getY(), error)
711 for scalingFactor in error.errorDict:
712 flagName = self.ConfigClass._getGaapResultName(scalingFactor, "flag_gaussianization",
713 self.name)
714 measRecord.set(flagName, True)
715 for sigma in self.config._sigmas:
716 baseName = self.ConfigClass._getGaapResultName(scalingFactor, sigma, self.name)
717 self._setFlag(measRecord, baseName)
718 else:
719 measRecord.set(self._failKey, True)
722class SingleFrameGaapFluxConfig(BaseGaapFluxConfig,
723 measBase.SingleFramePluginConfig):
724 """Config for SingleFrameGaapFluxPlugin."""
727@measBase.register(PLUGIN_NAME)
728class SingleFrameGaapFluxPlugin(BaseGaapFluxMixin, measBase.SingleFramePlugin):
729 """Gaussian Aperture and PSF photometry algorithm in single-frame mode.
731 Parameters
732 ----------
733 config : `GaapFluxConfig`
734 Plugin configuration.
735 name : `str`
736 Plugin name, for registering.
737 schema : `lsst.afw.table.Schema`
738 The schema for the measurement output catalog. New fields will be added
739 to hold measurements produced by this plugin.
740 metadata : `lsst.daf.base.PropertySet`
741 Plugin metadata that will be attached to the output catalog.
742 logName : `str`, optional
743 Name to use when logging errors. This will be provided by the
744 measurement framework.
746 Notes
747 -----
748 This plugin must be run in forced mode to produce consistent colors across
749 the different bandpasses.
750 """
751 ConfigClass = SingleFrameGaapFluxConfig
753 def __init__(self, config, name, schema, metadata, logName=None):
754 BaseGaapFluxMixin.__init__(self, config, name, schema, logName=logName)
755 measBase.SingleFramePlugin.__init__(self, config, name, schema, metadata, logName=logName)
757 @classmethod
758 def getExecutionOrder(cls) -> float:
759 # Docstring inherited
760 return cls.FLUX_ORDER
762 def measure(self, measRecord, exposure):
763 # Docstring inherited.
764 center = measRecord.getCentroid()
765 if self.config.doOptimalPhotometry:
766 # The adaptive shape is set to post-seeing aperture.
767 # Convolve with the PSF shape to obtain pre-seeing aperture.
768 # Refer to pg. 30-31 of Kuijken et al. (2015) for this heuristic.
769 # psfShape = measRecord.getPsfShape() # TODO: DM-30229
770 psfShape = afwTable.QuadrupoleKey(measRecord.schema["slot_PsfShape"]).get(measRecord)
771 optimalShape = measRecord.getShape().convolve(psfShape)
772 # Record the aperture used for optimal photometry
773 measRecord.set(self.optimalShapeKey, optimalShape)
774 self._gaussianizeAndMeasure(measRecord, exposure, center)
777class ForcedGaapFluxConfig(BaseGaapFluxConfig, measBase.ForcedPluginConfig):
778 """Config for ForcedGaapFluxPlugin."""
781@measBase.register(PLUGIN_NAME)
782class ForcedGaapFluxPlugin(BaseGaapFluxMixin, measBase.ForcedPlugin):
783 """Gaussian Aperture and PSF (GAaP) photometry plugin in forced mode.
785 This is the GAaP plugin to run for consistent colors across the bandpasses.
787 Parameters
788 ----------
789 config : `GaapFluxConfig`
790 Plugin configuration.
791 name : `str`
792 Plugin name, for registering.
793 schemaMapper : `lsst.afw.table.SchemaMapper`
794 A mapping from reference catalog fields to output catalog fields.
795 Output fields will be added to the output schema.
796 for the measurement output catalog. New fields will be added
797 to hold measurements produced by this plugin.
798 metadata : `lsst.daf.base.PropertySet`
799 Plugin metadata that will be attached to the output catalog.
800 logName : `str`, optional
801 Name to use when logging errors. This will be provided by the
802 measurement framework.
803 """
804 ConfigClass = ForcedGaapFluxConfig
806 def __init__(self, config, name, schemaMapper, metadata, logName=None):
807 schema = schemaMapper.editOutputSchema()
808 BaseGaapFluxMixin.__init__(self, config, name, schema, logName=logName)
809 measBase.ForcedPlugin.__init__(self, config, name, schemaMapper, metadata, logName=logName)
811 @classmethod
812 def getExecutionOrder(cls) -> float:
813 # Docstring inherited.
814 return cls.FLUX_ORDER
816 def measure(self, measRecord, exposure, refRecord, refWcs):
817 # Docstring inherited.
818 wcs = exposure.getWcs()
819 center = wcs.skyToPixel(refWcs.pixelToSky(refRecord.getCentroid()))
820 if self.config.doOptimalPhotometry:
821 # The adaptive shape is set to post-seeing aperture.
822 # Convolve it with the PSF shape to obtain pre-seeing aperture.
823 # Refer to pg. 30-31 of Kuijken et al. (2015) for this heuristic.
824 # psfShape = refRecord.getPsfShape() # TODO: DM-30229
825 psfShape = afwTable.QuadrupoleKey(refRecord.schema["slot_PsfShape"]).get(refRecord)
826 optimalShape = refRecord.getShape().convolve(psfShape)
827 if not (wcs == refWcs):
828 measFromSky = wcs.linearizeSkyToPixel(measRecord.getCentroid(), lsst.geom.radians)
829 skyFromRef = refWcs.linearizePixelToSky(refRecord.getCentroid(), lsst.geom.radians)
830 measFromRef = measFromSky*skyFromRef
831 optimalShape.transformInPlace(measFromRef.getLinear())
832 # Record the intrinsic aperture used for optimal photometry.
833 measRecord.set(self.optimalShapeKey, optimalShape)
834 self._gaussianizeAndMeasure(measRecord, exposure, center)