Coverage for python/lsst/meas/extensions/gaap/_gaap.py: 27%
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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
38import lsst.pex.config as pexConfig
39from lsst.pex.exceptions import InvalidParameterError
40import scipy.signal
41from ._gaussianizePsf import GaussianizePsfTask
43PLUGIN_NAME = "ext_gaap_GaapFlux"
46class GaapConvolutionError(measBase.MeasurementError):
47 """Raised when there is an error in GAaP convolution.
48 """
51class NoPixelError(measBase.MeasurementError):
52 """Raised when the footprint has no pixels.
53 """
56class BaseGaapFluxConfig(measBase.BaseMeasurementPluginConfig):
57 """Configuration parameters for Gaussian Aperture and PSF (GAaP) plugin.
58 """
59 def _greaterThanOrEqualToUnity(x: float) -> bool: # noqa: N805
60 """Returns True if the input ``x`` is greater than 1.0, else False.
61 """
62 return x >= 1
64 def _isOdd(x: int) -> bool: # noqa: N805
65 """Returns True if the input ``x`` is positive and odd, else False.
66 """
67 return (x%2 == 1) & (x > 0)
69 sigmas = pexConfig.ListField(
70 dtype=float,
71 default=[0.7, 1.0],
72 doc="List of sigmas (in arcseconds) of circular Gaussian apertures to apply on "
73 "pre-seeing galaxy images. These should be somewhat larger than the PSF "
74 "(determined by ``scalingFactors``) to avoid measurement failures."
75 )
77 scalingFactors = pexConfig.ListField(
78 dtype=float,
79 default=[1.15],
80 itemCheck=_greaterThanOrEqualToUnity,
81 doc="List of factors with which the seeing should be scaled to obtain the "
82 "sigma values of the target Gaussian PSF. The factor should not be less "
83 "than unity to avoid the PSF matching task to go into deconvolution mode "
84 "and should ideally be slightly greater than unity. The runtime of the "
85 "plugin scales linearly with the number of elements in the list."
86 )
88 _modelPsfMatch = pexConfig.ConfigurableField(
89 target=GaussianizePsfTask,
90 doc="PSF Gaussianization Task"
91 )
93 _modelPsfDimension = pexConfig.Field(
94 dtype=int,
95 default=65,
96 check=_isOdd,
97 doc="The dimensions (width and height) of the target PSF image in pixels. Must be odd."
98 )
100 doPsfPhotometry = pexConfig.Field(
101 dtype=bool,
102 default=False,
103 doc="Perform PSF photometry after PSF-Gaussianization to validate Gaussianization accuracy? "
104 "This does not produce consistent color estimates. If setting it to `True`, it must be done so "
105 "prior to registering the plugin for aperture correction if ``registerForApCorr`` is also `True`."
106 )
108 doOptimalPhotometry = pexConfig.Field(
109 dtype=bool,
110 default=True,
111 doc="Perform optimal photometry with near maximal SNR using an adaptive elliptical aperture? "
112 "This requires a shape algorithm to have been run previously."
113 )
115 registerForApCorr = pexConfig.Field(
116 dtype=bool,
117 default=True,
118 doc="Register measurements for aperture correction? "
119 "The aperture correction registration is done when the plugin is instatiated and not "
120 "during import because the column names are derived from the configuration rather than being "
121 "static. Sometimes you want to turn this off, e.g., when you use aperture corrections derived "
122 "from somewhere else through a 'proxy' mechanism."
123 )
125 # scaleByFwm is the only config field of modelPsfMatch Task that we allow
126 # the user to set without explicitly setting the modelPsfMatch config.
127 # It is intended to abstract away the underlying implementation.
128 @property
129 def scaleByFwhm(self) -> bool:
130 """Config parameter of the PSF Matching task.
131 Scale kernelSize, alardGaussians by input Fwhm?
132 """
133 return self._modelPsfMatch.kernel.active.scaleByFwhm
135 @scaleByFwhm.setter
136 def scaleByFwhm(self, value: bool) -> None:
137 self._modelPsfMatch.kernel.active.scaleByFwhm = value
139 @property
140 def gaussianizationMethod(self) -> str:
141 """Type of convolution to use for PSF-Gaussianization."""
142 return self._modelPsfMatch.convolutionMethod
144 @gaussianizationMethod.setter
145 def gaussianizationMethod(self, value: str) -> None:
146 self._modelPsfMatch.convolutionMethod = value
148 @property
149 def _sigmas(self) -> list:
150 """List of values set in ``sigmas`` along with special apertures such
151 as "PsfFlux" and "Optimal" if applicable.
152 """
153 return self.sigmas.list() + ["PsfFlux"]*self.doPsfPhotometry + ["Optimal"]*self.doOptimalPhotometry
155 def setDefaults(self) -> None:
156 # Docstring inherited
157 self._modelPsfMatch.kernel.active.alardNGauss = 1
158 self._modelPsfMatch.kernel.active.alardDegGaussDeconv = 1
159 self._modelPsfMatch.kernel.active.alardDegGauss = [4]
160 self._modelPsfMatch.kernel.active.alardGaussBeta = 1.0
161 self._modelPsfMatch.kernel.active.spatialKernelOrder = 0
162 self.scaleByFwhm = True
164 def validate(self):
165 super().validate()
166 self._modelPsfMatch.validate()
167 assert self._modelPsfMatch.kernel.active.alardNGauss == 1
169 @staticmethod
170 def _getGaapResultName(scalingFactor: float, sigma: Union[float, str], name: Optional[str] = None) -> str:
171 """Return the base name for GAaP fields
173 For example, for a scaling factor of 1.15 for seeing and sigma of the
174 effective Gaussian aperture of 0.7 arcsec, the returned value would be
175 "ext_gaap_GaapFlux_1_15x_0_7".
177 Notes
178 -----
179 Being a static method, this does not check if measurements correspond
180 to the input arguments. Instead, users should use
181 `getAllGaapResultNames` to obtain the full list of base names.
183 This is not a config-y thing, but is placed here to make the fieldnames
184 from GAaP measurements available outside the plugin.
186 Parameters
187 ----------
188 scalingFactor : `float`
189 The factor by which the trace radius of the PSF must be scaled.
190 sigma : `float` or `str`
191 Sigma of the effective Gaussian aperture (PSF-convolved explicit
192 aperture) or "PsfFlux" for PSF photometry post PSF-Gaussianization.
193 name : `str`, optional
194 The exact registered name of the GAaP plugin, typically either
195 "ext_gaap_GaapFlux" or "undeblended_ext_gaap_GaapFlux". If ``name``
196 is None, then only the middle part (1_15x_0_7 in the example)
197 without the leading underscore is returned.
199 Returns
200 -------
201 baseName : `str`
202 Base name for GAaP field.
203 """
204 suffix = "_".join((str(scalingFactor).replace(".", "_")+"x", str(sigma).replace(".", "_")))
205 if name is None:
206 return suffix
207 return "_".join((name, suffix))
209 def getAllGaapResultNames(self, name: Optional[str] = PLUGIN_NAME) -> Generator[str]:
210 """Generate the base names for all of the GAaP fields.
212 For example, if the plugin is configured with `scalingFactors` = [1.15]
213 and `sigmas` = [0.7, 1.0] the returned expression would yield
214 ("ext_gaap_GaapFlux_1_15x_0_7", "ext_gaap_GaapFlux_1_15x_1_0") when
215 called with ``name`` = "ext_gaap_GaapFlux". It will also generate
216 "ext_gaap_GaapFlux_1_15x_PsfFlux" if `doPsfPhotometry` is True.
218 Parameters
219 ----------
220 name : `str`, optional
221 The exact registered name of the GAaP plugin, typically either
222 "ext_gaap_GaapFlux" or "undeblended_ext_gaap_GaapFlux". If ``name``
223 is None, then only the middle parts (("1_15x_0_7", "1_15x_1_0"),
224 for example) without the leading underscores are returned.
226 Returns
227 -------
228 baseNames : `generator`
229 A generator expression yielding all the base names.
230 """
231 scalingFactors = self.scalingFactors
232 sigmas = self._sigmas
233 baseNames = (self._getGaapResultName(scalingFactor, sigma, name)
234 for scalingFactor, sigma in itertools.product(scalingFactors, sigmas))
235 return baseNames
238class BaseGaapFluxMixin:
239 """Mixin base class for Gaussian-Aperture and PSF (GAaP) photometry
240 algorithm.
242 This class does almost all the heavy-lifting for its two derived classes,
243 SingleFrameGaapFluxPlugin and ForcedGaapFluxPlugin which simply adapt it to
244 the slightly different interfaces for single-frame and forced measurement.
245 This class implements the GAaP algorithm and is intended for code reuse
246 by the two concrete derived classes by including this mixin class.
248 Parameters
249 ----------
250 config : `BaseGaapFluxConfig`
251 Plugin configuration.
252 name : `str`
253 Plugin name, for registering.
254 schema : `lsst.afw.table.Schema`
255 The schema for the measurement output catalog. New fields will be added
256 to hold measurements produced by this plugin.
257 logName : `str`, optional
258 Name to use when logging errors. This is typically provided by the
259 measurement framework.
261 Raises
262 ------
263 GaapConvolutionError
264 Raised if the PSF Gaussianization fails for one or more target PSFs.
265 lsst.meas.base.FatalAlgorithmError
266 Raised if the Exposure does not contain a PSF model.
267 """
269 ConfigClass = BaseGaapFluxConfig
270 hasLogName = True
272 def __init__(self, config: BaseGaapFluxConfig, name, schema, logName=None) -> None:
273 # Flag definitions for each variant of GAaP measurement
274 flagDefs = measBase.FlagDefinitionList()
275 for scalingFactor, sigma in itertools.product(config.scalingFactors, config.sigmas):
276 baseName = self.ConfigClass._getGaapResultName(scalingFactor, sigma, name)
277 doc = f"GAaP Flux with {sigma} aperture after multiplying the seeing by {scalingFactor}"
278 measBase.FluxResultKey.addFields(schema, name=baseName, doc=doc)
280 # Remove the prefix_ since FlagHandler prepends it
281 middleName = self.ConfigClass._getGaapResultName(scalingFactor, sigma)
282 flagDefs.add(schema.join(middleName, "flag_bigPsf"), "The Gaussianized PSF is "
283 "bigger than the aperture")
284 flagDefs.add(schema.join(middleName, "flag"), "Generic failure flag for this set of config "
285 "parameters. ")
287 # PSF photometry
288 if config.doPsfPhotometry:
289 for scalingFactor in config.scalingFactors:
290 baseName = self.ConfigClass._getGaapResultName(scalingFactor, "PsfFlux", name)
291 doc = f"GAaP Flux with PSF aperture after multiplying the seeing by {scalingFactor}"
292 measBase.FluxResultKey.addFields(schema, name=baseName, doc=doc)
294 # Remove the prefix_ since FlagHandler prepends it
295 middleName = self.ConfigClass._getGaapResultName(scalingFactor, "PsfFlux")
296 flagDefs.add(schema.join(middleName, "flag"), "Generic failure flag for this set of config "
297 "parameters. ")
299 if config.doOptimalPhotometry:
300 # Add fields to hold the optimal aperture shape
301 # OptimalPhotometry case will fetch the aperture shape from here.
302 self.optimalShapeKey = afwTable.QuadrupoleKey.addFields(schema, schema.join(name, "OptimalShape"),
303 doc="Pre-seeing aperture used for "
304 "optimal GAaP photometry")
305 for scalingFactor in config.scalingFactors:
306 baseName = self.ConfigClass._getGaapResultName(scalingFactor, "Optimal", name)
307 docstring = f"GAaP Flux with optimal aperture after multiplying the seeing by {scalingFactor}"
308 measBase.FluxResultKey.addFields(schema, name=baseName, doc=docstring)
310 # Remove the prefix_ since FlagHandler prepends it
311 middleName = self.ConfigClass._getGaapResultName(scalingFactor, "Optimal")
312 flagDefs.add(schema.join(middleName, "flag_bigPsf"), "The Gaussianized PSF is "
313 "bigger than the aperture")
314 flagDefs.add(schema.join(middleName, "flag"), "Generic failure flag for this set of config "
315 "parameters. ")
317 if config.registerForApCorr:
318 for baseName in config.getAllGaapResultNames(name):
319 measBase.addApCorrName(baseName)
321 for scalingFactor in config.scalingFactors:
322 flagName = self.ConfigClass._getGaapResultName(scalingFactor, "flag_gaussianization")
323 flagDefs.add(flagName, "PSF Gaussianization failed when trying to scale by this factor.")
325 self.log = logging.getLogger(logName)
326 self.flagHandler = measBase.FlagHandler.addFields(schema, name, flagDefs)
327 self.EdgeFlagKey = schema.addField(schema.join(name, "flag_edge"), type="Flag",
328 doc="Source is too close to the edge")
329 self.NoPixelKey = schema.addField(schema.join(name, "flag_no_pixel"), type="Flag",
330 doc="No pixels in the footprint")
331 self._failKey = schema.addField(name + '_flag', type="Flag", doc="Set for any fatal failure")
333 self.psfMatchTask = config._modelPsfMatch.target(config=config._modelPsfMatch)
335 @staticmethod
336 def _computeKernelAcf(kernel: lsst.afw.math.Kernel) -> lsst.afw.image.Image: # noqa: F821
337 """Compute the auto-correlation function of ``kernel``.
339 Parameters
340 ----------
341 kernel : `~lsst.afw.math.Kernel`
342 The kernel for which auto-correlation function is to be computed.
344 Returns
345 -------
346 acfImage : `~lsst.afw.image.Image`
347 The two-dimensional auto-correlation function of ``kernel``.
348 """
349 kernelImage = afwImage.ImageD(kernel.getDimensions())
350 kernel.computeImage(kernelImage, False)
351 acfArray = scipy.signal.correlate2d(kernelImage.array, kernelImage.array, boundary='fill')
352 acfImage = afwImage.ImageD(acfArray)
353 return acfImage
355 @staticmethod
356 def _getFluxErrScaling(kernelAcf: lsst.afw.image.Image, # noqa: F821
357 aperShape: lsst.afw.geom.Quadrupole) -> float: # noqa: F821
358 """Calculate the value by which the standard error has to be scaled due
359 to noise correlations.
361 This calculates the correction to apply to the naively computed
362 `instFluxErr` to account for correlations in the pixel noise introduced
363 in the PSF-Gaussianization step.
364 This method performs the integral in Eq. A17 of Kuijken et al. (2015).
366 The returned value equals
367 :math:`\\int\\mathrm{d}x C^G(x) \\exp(-x^T Q^{-1}x/4)`
368 where :math: `Q` is ``aperShape`` and :math: `C^G(x)` is ``kernelAcf``.
370 Parameters
371 ----------
372 kernelAcf : `~lsst.afw.image.Image`
373 The auto-correlation function (ACF) of the PSF matching kernel.
374 aperShape : `~lsst.afw.geom.Quadrupole`
375 The shape parameter of the Gaussian function which was used to
376 measure GAaP flux.
378 Returns
379 -------
380 fluxErrScaling : `float`
381 The factor by which the standard error on GAaP flux must be scaled.
382 """
383 aperShapeX2 = aperShape.convolve(aperShape)
384 corrFlux = measBase.SdssShapeAlgorithm.computeFixedMomentsFlux(kernelAcf, aperShapeX2,
385 kernelAcf.getBBox().getCenter())
386 fluxErrScaling = (0.5*corrFlux.instFlux)**0.5
387 return fluxErrScaling
389 def _gaussianize(self, exposure: afwImage.Exposure, modelPsf: afwDetection.GaussianPsf,
390 measRecord: lsst.afw.table.SourceRecord) -> lsst.pipe.base.Struct: # noqa: F821
391 """Modify the ``exposure`` so that its PSF is a Gaussian.
393 Compute the convolution kernel to make the PSF same as ``modelPsf``
394 and return the Gaussianized exposure in a struct.
396 Parameters
397 ----------
398 exposure : `~lsst.afw.image.Exposure`
399 Original (full) exposure containing all the sources.
400 modelPsf : `~lsst.afw.detection.GaussianPsf`
401 Target PSF to which to match.
402 measRecord : `~lsst.afw.tabe.SourceRecord`
403 Record for the source to be measured.
405 Returns
406 -------
407 result : `~lsst.pipe.base.Struct`
408 ``result`` is the Struct returned by `modelPsfMatch` task. Notably,
409 it contains a ``psfMatchedExposure``, which is the exposure
410 containing the source, convolved to the target seeing and
411 ``psfMatchingKernel``, the kernel that ``exposure`` was convolved
412 by to obtain ``psfMatchedExposure``. Typically, the bounding box of
413 ``psfMatchedExposure`` is larger than that of the footprint.
414 """
415 footprint = measRecord.getFootprint()
416 bbox = footprint.getBBox()
418 # The kernelSize is guaranteed to be odd, say 2N+1 pixels (N=10 by
419 # default). The flux inside the footprint is smeared by N pixels on
420 # either side, which is region of interest. So grow the bounding box
421 # initially by N pixels on either side.
422 pixToGrow = self.config._modelPsfMatch.kernel.active.kernelSize//2
423 bbox.grow(pixToGrow)
425 # The bounding box may become too big and go out of bounds for sources
426 # near the edge. Clip the subExposure to the exposure's bounding box.
427 # Set the flag_edge marking that the bbox of the footprint could not
428 # be grown fully but do not set it as a failure.
429 if not exposure.getBBox().contains(bbox):
430 bbox.clip(exposure.getBBox())
431 measRecord.setFlag(self.EdgeFlagKey, True)
433 subExposure = exposure[bbox]
435 # The size parameter of the basis has to be set dynamically.
436 result = self.psfMatchTask.run(exposure=subExposure, center=measRecord.getCentroid(),
437 targetPsfModel=modelPsf,
438 basisSigmaGauss=[modelPsf.getSigma()])
439 # TODO: DM-27407 will re-Gaussianize the exposure to make the PSF even
440 # more Gaussian-like
442 # Do not let the variance plane be rescaled since we handle it
443 # carefully later using _getFluxScaling method
444 result.psfMatchedExposure.variance.array = subExposure.variance.array
445 return result
447 def _measureFlux(self, measRecord: lsst.afw.table.SourceRecord,
448 exposure: afwImage.Exposure, kernelAcf: afwImage.Image,
449 center: lsst.geom.Point2D, aperShape: afwGeom.Quadrupole,
450 baseName: str, fluxScaling: Optional[float] = None) -> None:
451 """Measure the flux and populate the record.
453 Parameters
454 ----------
455 measRecord : `~lsst.afw.table.SourceRecord`
456 Catalog record for the source being measured.
457 exposure : `~lsst.afw.image.Exposure`
458 Subexposure containing the deblended source being measured.
459 The PSF attached to it should nominally be an
460 `lsst.afw.Detection.GaussianPsf` object, but not enforced.
461 kernelAcf : `~lsst.afw.image.Image`
462 An image representating the auto-correlation function of the
463 PSF-matching kernel.
464 center : `~lsst.geom.Point2D`
465 The centroid position of the source being measured.
466 aperShape : `~lsst.afw.geom.Quadrupole`
467 The shape parameter of the post-seeing Gaussian aperture.
468 It should be a valid quadrupole if ``fluxScaling`` is specified.
469 baseName : `str`
470 The base name of the GAaP field.
471 fluxScaling : `float`, optional
472 The multiplication factor by which the measured flux has to be
473 scaled. If `None` or unspecified, the pre-factor in Eq. A16
474 of Kuijken et al. (2015) is computed and applied.
475 """
476 if fluxScaling is None:
477 # Calculate the pre-factor in Eq. A16 of Kuijken et al. (2015)
478 # to scale the flux. Include an extra factor of 0.5 to undo
479 # the normalization factor of 2 in `computeFixedMomentsFlux`.
480 try:
481 aperShape.normalize()
482 # Calculate the pre-seeing aperture.
483 preseeingShape = aperShape.convolve(exposure.getPsf().computeShape(center))
484 fluxScaling = 0.5*preseeingShape.getArea()/aperShape.getArea()
485 except (InvalidParameterError, ZeroDivisionError):
486 self._setFlag(measRecord, baseName, "bigPsf")
487 return
489 # Calculate the integral in Eq. A17 of Kuijken et al. (2015)
490 # ``fluxErrScaling`` contains the factors not captured by
491 # ``fluxScaling`` and `instFluxErr`. It is 1 theoretically
492 # if ``kernelAcf`` is a Dirac-delta function.
493 fluxErrScaling = self._getFluxErrScaling(kernelAcf, aperShape)
495 fluxResult = measBase.SdssShapeAlgorithm.computeFixedMomentsFlux(exposure.getMaskedImage(),
496 aperShape, center)
498 # Scale the quantities in fluxResult and copy result to record
499 fluxResult.instFlux *= fluxScaling
500 fluxResult.instFluxErr *= fluxScaling*fluxErrScaling
501 fluxResultKey = measBase.FluxResultKey(measRecord.schema[baseName])
502 fluxResultKey.set(measRecord, fluxResult)
504 def _gaussianizeAndMeasure(self, measRecord: lsst.afw.table.SourceRecord,
505 exposure: afwImage.Exposure,
506 center: lsst.geom.Point2D) -> None:
507 """Measure the properties of a source on a single image.
509 The image may be from a single epoch, or it may be a coadd.
511 Parameters
512 ----------
513 measRecord : `~lsst.afw.table.SourceRecord`
514 Record describing the object being measured. Previously-measured
515 quantities may be retrieved from here, and it will be updated
516 in-place with the outputs of this plugin.
517 exposure : `~lsst.afw.image.ExposureF`
518 The pixel data to be measured, together with the associated PSF,
519 WCS, etc. All other sources in the image should have been replaced
520 by noise according to deblender outputs.
521 center : `~lsst.geom.Point2D`
522 Centroid location of the source being measured.
524 Raises
525 ------
526 GaapConvolutionError
527 Raised if the PSF Gaussianization fails for any of the target PSFs.
528 lsst.meas.base.FatalAlgorithmError
529 Raised if the Exposure does not contain a PSF model.
530 NoPixelError
531 Raised if the footprint has no pixels.
533 Notes
534 -----
535 This method is the entry point to the mixin from the concrete derived
536 classes.
537 """
538 # First make sure we have a PSF.
539 if (psf := exposure.getPsf()) is None:
540 raise measBase.FatalAlgorithmError("No PSF in exposure")
542 # Raise errors if the plugin would fail for this record for all
543 # scaling factors and sigmas.
544 if measRecord.getFootprint().getArea() == 0:
545 self._setFlag(measRecord, self.name, "no_pixel")
546 self._setScalingAndSigmaFlags(measRecord, self.config.scalingFactors)
547 raise NoPixelError("No good pixels in footprint", 1)
549 psfSigma = psf.computeShape(center).getTraceRadius()
550 if not (psfSigma > 0): # This captures NaN and negative values.
551 center = measRecord.getCentroid()
552 self.log.debug("Invalid PSF sigma; cannot solve for PSF matching kernel in GAaP for (%f, %f): %s",
553 center.getX(), center.getY(), "GAaP Convolution Error")
554 self._setScalingAndSigmaFlags(
555 measRecord,
556 self.config.scalingFactors,
557 specificFlag="flag_gaussianization",
558 )
559 raise GaapConvolutionError("Failed to solve for PSF matching kernel", 1)
560 else:
561 errorCollection = dict()
563 wcs = exposure.getWcs()
565 for scalingFactor in self.config.scalingFactors:
566 targetSigma = scalingFactor*psfSigma
567 # If this target PSF is bound to fail for all apertures,
568 # set the flags and move on without PSF Gaussianization.
569 if self._isAllFailure(measRecord, scalingFactor, targetSigma):
570 continue
572 stampSize = self.config._modelPsfDimension
573 targetPsf = afwDetection.GaussianPsf(stampSize, stampSize, targetSigma)
574 try:
575 result = self._gaussianize(exposure, targetPsf, measRecord)
576 except Exception as error:
577 errorCollection[str(scalingFactor)] = error
578 continue
580 convolved = result.psfMatchedExposure
581 kernelAcf = self._computeKernelAcf(result.psfMatchingKernel)
583 measureFlux = partial(self._measureFlux, measRecord, convolved, kernelAcf, center)
584 # Computing shape is inexpensive and position-independent for a
585 # GaussianPsf
586 psfShape = targetPsf.computeShape(center)
588 if self.config.doPsfPhotometry:
589 baseName = self.ConfigClass._getGaapResultName(scalingFactor, "PsfFlux", self.name)
590 aperShape = psfShape
591 measureFlux(aperShape, baseName, fluxScaling=1)
593 if self.config.doOptimalPhotometry:
594 baseName = self.ConfigClass._getGaapResultName(scalingFactor, "Optimal", self.name)
595 optimalShape = measRecord.get(self.optimalShapeKey)
596 aperShape = afwGeom.Quadrupole(optimalShape.getParameterVector()
597 - psfShape.getParameterVector())
598 measureFlux(aperShape, baseName)
600 # Iterate over pre-defined circular apertures
601 for sigma in self.config.sigmas:
602 baseName = self.ConfigClass._getGaapResultName(scalingFactor, sigma, self.name)
603 if sigma <= targetSigma * wcs.getPixelScale(center).asArcseconds():
604 # Raise when the aperture is invalid
605 self._setFlag(measRecord, baseName, "bigPsf")
606 continue
608 intrinsicShape = afwGeom.Quadrupole(sigma**2, sigma**2, 0.0) # in sky coordinates
609 intrinsicShape.transformInPlace(wcs.linearizeSkyToPixel(center,
610 lsst.geom.arcseconds).getLinear())
611 aperShape = afwGeom.Quadrupole(intrinsicShape.getParameterVector()
612 - psfShape.getParameterVector())
613 measureFlux(aperShape, baseName)
615 # Raise GaapConvolutionError before exiting the plugin
616 # if the collection of errors is not empty
617 if errorCollection:
618 message = "Problematic scaling factors = "
619 message += ", ".join(errorCollection)
620 message += " Errors: "
621 message += " | ".join(set(msg.__repr__() for msg in errorCollection.values()))
622 center = measRecord.getCentroid()
623 self.log.debug("Failed to solve for PSF matching kernel in GAaP for (%f, %f): %s",
624 center.getX(), center.getY(), message)
625 self._setScalingAndSigmaFlags(
626 measRecord,
627 errorCollection.keys(),
628 specificFlag="flag_gaussianization",
629 )
630 raise GaapConvolutionError("Failed to solve for PSF matching kernel", 1)
632 @staticmethod
633 def _setFlag(measRecord, baseName, flagName=None):
634 """Set the GAaP flag determined by ``baseName`` and ``flagName``.
636 A convenience method to set {baseName}_flag_{flagName} to True.
637 This also automatically sets the generic {baseName}_flag to True.
638 To set the general plugin flag indicating measurement failure,
639 use _failKey directly.
641 Parameters
642 ----------
643 measRecord : `~lsst.afw.table.SourceRecord`
644 Record describing the source being measured.
645 baseName : `str`
646 The base name of the GAaP field for which the flag must be set.
647 flagName : `str`, optional
648 The name of the specific flag to set along with the general flag.
649 If unspecified, only the general flag corresponding to ``baseName``
650 is set. For now, the only value that can be specified is "bigPsf".
651 """
652 if flagName is not None:
653 specificFlagKey = measRecord.schema.join(baseName, f"flag_{flagName}")
654 measRecord.set(specificFlagKey, True)
655 genericFlagKey = measRecord.schema.join(baseName, "flag")
656 measRecord.set(genericFlagKey, True)
658 def _setScalingAndSigmaFlags(self, measRecord, scalingFactors, specificFlag=None):
659 """Set a full suite of flags for scalingFactors/sigmas.
661 Parameters
662 ----------
663 measRecord : `~lsst.afw.table.SourceRecord`
664 Record describing the source being measured.
665 scalingFactors : `list` [`float`]
666 List of scaling factors.
667 specificFlag : `str`, optional
668 Specific type of flag to set if needed.
669 """
670 for scalingFactor in scalingFactors:
671 if specificFlag is not None:
672 flagName = self.ConfigClass._getGaapResultName(scalingFactor, specificFlag,
673 self.name)
674 measRecord.set(flagName, True)
675 for sigma in self.config._sigmas:
676 baseName = self.ConfigClass._getGaapResultName(scalingFactor, sigma, self.name)
677 self._setFlag(measRecord, baseName)
679 def _isAllFailure(self, measRecord, scalingFactor, targetSigma) -> bool:
680 """Check if all measurements would result in failure.
682 If all of the pre-seeing apertures are smaller than size of the
683 target PSF for the given ``scalingFactor``, then set the
684 `flag_bigPsf` for all fields corresponding to ``scalingFactor``
685 and move on instead of spending computational effort in
686 Gaussianizing the exposure.
688 Parameters
689 ----------
690 measRecord : `~lsst.afw.table.SourceRecord`
691 Record describing the source being measured.
692 scalingFactor : `float`
693 The multiplicative factor by which the seeing is scaled.
694 targetSigma : `float`
695 Sigma (in pixels) of the target circular Gaussian PSF.
697 Returns
698 -------
699 allFailure : `bool`
700 A boolean value indicating whether all measurements would fail.
702 Notes
703 ----
704 If doPsfPhotometry is set to True, then this will always return False.
705 """
706 if self.config.doPsfPhotometry:
707 return False
709 allFailure = targetSigma >= max(self.config.sigmas)
710 # If measurements would fail on all circular apertures, and if
711 # optimal elliptical aperture is used, check if that would also fail.
712 if self.config.doOptimalPhotometry and allFailure:
713 optimalShape = measRecord.get(self.optimalShapeKey)
714 aperShape = afwGeom.Quadrupole(optimalShape.getParameterVector()
715 - [targetSigma**2, targetSigma**2, 0.0])
716 allFailure = (aperShape.getIxx() <= 0) or (aperShape.getIyy() <= 0) or (aperShape.getArea() <= 0)
718 # Set all failure flags if allFailure is True.
719 if allFailure:
720 if self.config.doOptimalPhotometry:
721 baseName = self.ConfigClass._getGaapResultName(scalingFactor, "Optimal", self.name)
722 self._setFlag(measRecord, baseName, "bigPsf")
723 for sigma in self.config.sigmas:
724 baseName = self.ConfigClass._getGaapResultName(scalingFactor, sigma, self.name)
725 self._setFlag(measRecord, baseName, "bigPsf")
727 return allFailure
729 def fail(self, measRecord, error=None):
730 """Record a measurement failure.
732 This default implementation simply records the failure in the source
733 record and is inherited by the SingleFrameGaapFluxPlugin and
734 ForcedGaapFluxPlugin.
736 Parameters
737 ----------
738 measRecord : `lsst.afw.table.SourceRecord`
739 Catalog record for the source being measured.
740 error : `Exception`
741 Error causing failure, or `None`.
742 """
743 # We only need to set the failKey if no error was specified which
744 # signifies that the flagging was already handled.
745 if error is None:
746 measRecord.set(self._failKey, True)
749class SingleFrameGaapFluxConfig(BaseGaapFluxConfig,
750 measBase.SingleFramePluginConfig):
751 """Config for SingleFrameGaapFluxPlugin."""
754@measBase.register(PLUGIN_NAME)
755class SingleFrameGaapFluxPlugin(BaseGaapFluxMixin, measBase.SingleFramePlugin):
756 """Gaussian Aperture and PSF photometry algorithm in single-frame mode.
758 Parameters
759 ----------
760 config : `GaapFluxConfig`
761 Plugin configuration.
762 name : `str`
763 Plugin name, for registering.
764 schema : `lsst.afw.table.Schema`
765 The schema for the measurement output catalog. New fields will be added
766 to hold measurements produced by this plugin.
767 metadata : `lsst.daf.base.PropertySet`
768 Plugin metadata that will be attached to the output catalog.
769 logName : `str`, optional
770 Name to use when logging errors. This will be provided by the
771 measurement framework.
773 Notes
774 -----
775 This plugin must be run in forced mode to produce consistent colors across
776 the different bandpasses.
777 """
778 ConfigClass = SingleFrameGaapFluxConfig
780 def __init__(self, config, name, schema, metadata, logName=None):
781 BaseGaapFluxMixin.__init__(self, config, name, schema, logName=logName)
782 measBase.SingleFramePlugin.__init__(self, config, name, schema, metadata, logName=logName)
784 @classmethod
785 def getExecutionOrder(cls) -> float:
786 # Docstring inherited
787 return cls.FLUX_ORDER
789 def measure(self, measRecord, exposure):
790 # Docstring inherited.
791 center = measRecord.getCentroid()
792 if self.config.doOptimalPhotometry:
793 # The adaptive shape is set to post-seeing aperture.
794 # Convolve with the PSF shape to obtain pre-seeing aperture.
795 # Refer to pg. 30-31 of Kuijken et al. (2015) for this heuristic.
796 # psfShape = measRecord.getPsfShape() # TODO: DM-30229
797 psfShape = afwTable.QuadrupoleKey(measRecord.schema["slot_PsfShape"]).get(measRecord)
798 optimalShape = measRecord.getShape().convolve(psfShape)
799 # Record the aperture used for optimal photometry
800 measRecord.set(self.optimalShapeKey, optimalShape)
801 self._gaussianizeAndMeasure(measRecord, exposure, center)
804class ForcedGaapFluxConfig(BaseGaapFluxConfig, measBase.ForcedPluginConfig):
805 """Config for ForcedGaapFluxPlugin."""
808@measBase.register(PLUGIN_NAME)
809class ForcedGaapFluxPlugin(BaseGaapFluxMixin, measBase.ForcedPlugin):
810 """Gaussian Aperture and PSF (GAaP) photometry plugin in forced mode.
812 This is the GAaP plugin to run for consistent colors across the bandpasses.
814 Parameters
815 ----------
816 config : `GaapFluxConfig`
817 Plugin configuration.
818 name : `str`
819 Plugin name, for registering.
820 schemaMapper : `lsst.afw.table.SchemaMapper`
821 A mapping from reference catalog fields to output catalog fields.
822 Output fields will be added to the output schema.
823 for the measurement output catalog. New fields will be added
824 to hold measurements produced by this plugin.
825 metadata : `lsst.daf.base.PropertySet`
826 Plugin metadata that will be attached to the output catalog.
827 logName : `str`, optional
828 Name to use when logging errors. This will be provided by the
829 measurement framework.
830 """
831 ConfigClass = ForcedGaapFluxConfig
833 def __init__(self, config, name, schemaMapper, metadata, logName=None):
834 schema = schemaMapper.editOutputSchema()
835 BaseGaapFluxMixin.__init__(self, config, name, schema, logName=logName)
836 measBase.ForcedPlugin.__init__(self, config, name, schemaMapper, metadata, logName=logName)
838 @classmethod
839 def getExecutionOrder(cls) -> float:
840 # Docstring inherited.
841 return cls.FLUX_ORDER
843 def measure(self, measRecord, exposure, refRecord, refWcs):
844 # Docstring inherited.
845 wcs = exposure.getWcs()
846 center = wcs.skyToPixel(refWcs.pixelToSky(refRecord.getCentroid()))
847 if self.config.doOptimalPhotometry:
848 # The adaptive shape is set to post-seeing aperture.
849 # Convolve it with the PSF shape to obtain pre-seeing aperture.
850 # Refer to pg. 30-31 of Kuijken et al. (2015) for this heuristic.
851 # psfShape = refRecord.getPsfShape() # TODO: DM-30229
852 psfShape = afwTable.QuadrupoleKey(refRecord.schema["slot_PsfShape"]).get(refRecord)
853 optimalShape = refRecord.getShape().convolve(psfShape)
854 if not (wcs == refWcs):
855 measFromSky = wcs.linearizeSkyToPixel(measRecord.getCentroid(), lsst.geom.radians)
856 skyFromRef = refWcs.linearizePixelToSky(refRecord.getCentroid(), lsst.geom.radians)
857 measFromRef = measFromSky*skyFromRef
858 optimalShape.transformInPlace(measFromRef.getLinear())
859 # Record the intrinsic aperture used for optimal photometry.
860 measRecord.set(self.optimalShapeKey, optimalShape)
861 self._gaussianizeAndMeasure(measRecord, exposure, center)