Coverage for python/lsst/afw/image/_exposureSummaryStats.py: 99%
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1# This file is part of afw.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (https://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 GNU General Public License
20# along with this program. If not, see <https://www.gnu.org/licenses/>.
21from __future__ import annotations
23import dataclasses
24from typing import TYPE_CHECKING
25import yaml
26import warnings
28import numpy as np
30from ..typehandling import Storable, StorableHelperFactory
32if TYPE_CHECKING:
33 from ..table import BaseRecord, Schema
35__all__ = ("ExposureSummaryStats", )
38def _default_corners():
39 return [float("nan")] * 4
42@dataclasses.dataclass
43class ExposureSummaryStats(Storable):
44 _persistence_name = 'ExposureSummaryStats'
46 _factory = StorableHelperFactory(__name__, _persistence_name)
48 version: int = 0
50 psfSigma: float = float('nan')
51 """PSF determinant radius (pixels)."""
53 psfArea: float = float('nan')
54 """PSF effective area (pixels**2)."""
56 psfIxx: float = float('nan')
57 """PSF shape Ixx (pixels**2)."""
59 psfIyy: float = float('nan')
60 """PSF shape Iyy (pixels**2)."""
62 psfIxy: float = float('nan')
63 """PSF shape Ixy (pixels**2)."""
65 ra: float = float('nan')
66 """Bounding box center Right Ascension (degrees)."""
68 dec: float = float('nan')
69 """Bounding box center Declination (degrees)."""
71 pixelScale: float = float('nan')
72 """Measured detector pixel scale (arcsec/pixel)."""
74 zenithDistance: float = float('nan')
75 """Bounding box center zenith distance (degrees)."""
77 expTime: float = float('nan')
78 """Exposure time of the exposure (seconds)."""
80 zeroPoint: float = float('nan')
81 """Mean zeropoint in detector (mag)."""
83 skyBg: float = float('nan')
84 """Average sky background (ADU)."""
86 skyNoise: float = float('nan')
87 """Average sky noise (ADU)."""
89 meanVar: float = float('nan')
90 """Mean variance of the weight plane (ADU**2)."""
92 raCorners: list[float] = dataclasses.field(default_factory=_default_corners)
93 """Right Ascension of bounding box corners (degrees)."""
95 decCorners: list[float] = dataclasses.field(default_factory=_default_corners)
96 """Declination of bounding box corners (degrees)."""
98 psfAdaptiveThresholdValue: float = float('nan')
99 """Threshold value used in the adaptive threshold detection pass for PSF modelling."""
101 psfAdaptiveIncludeThresholdMultiplier: float = float('nan')
102 """Threshold multiplier used in the adaptive threshold detection pass for PSF modelling."""
104 nShapeletsStar: int = 0
105 """Number of sources used in the shapelet decomposition."""
107 shapeletsOnlyIqScore: float = float('nan')
108 """The dimensionless image quality score as determined from the shapelets decomposition
109 that includes power only from the non-atmospheric decomposition coefficients. The
110 score spans the range [0.0, 1.0] with lower values indicating better image quality.
111 """
113 shapeletsIqScore: float = float('nan')
114 """The dimensionless image quality score as determined from the shapelets decomposition
115 that includes power from the median centroid offset between those used in the decomposition
116 and those of the centroid slot in addition to non-atmospheric decomposition coefficients.
117 The score spans the range [0.0, 1.0] with lower values indicating better image quality.
118 """
120 shapeletsCoeffs: list[float] = dataclasses.field(default_factory=list)
121 """List of coefficients from the PSF star shapelet decomposition."""
123 centroidDiffShapeletsVsSlotMedian: float = float('nan')
124 """Median centroid difference (sqrt((slot_x - shapelet_x)**2 + (slot_y - shapelet_y)**2)) for
125 sources used in the shapelet decomposition (pixels).
126 """
128 shapeletsStarEMedian: float = float('nan')
129 """Median ellipticity (sqrt(starE1**2.0 + starE2**2.0)) of the sources used in the
130 shapelet decomposition.
131 """
133 shapeletsStarUnNormalizedEMedian: float = float('nan')
134 """Median un-normalized ellipticity (sqrt((starXX - starYY)**2.0 + (2.0*starXY)**2.0))
135 of the sources used in the shapelet decomposition (pixels**2).
136 """
138 refCatSourceDensity: float = float('nan')
139 """Source density for the detector region as computed from the loaded reference catalog
140 (number per degrees**2).
141 """
143 astromOffsetMean: float = float('nan')
144 """Astrometry match offset mean."""
146 astromOffsetStd: float = float('nan')
147 """Astrometry match offset stddev."""
149 nPsfStar: int = 0
150 """Number of stars used for psf model."""
152 psfStarDeltaE1Median: float = float('nan')
153 """Psf stars median E1 residual (starE1 - psfE1)."""
155 psfStarDeltaE2Median: float = float('nan')
156 """Psf stars median E2 residual (starE2 - psfE2)."""
158 psfStarDeltaE1Scatter: float = float('nan')
159 """Psf stars MAD E1 scatter (starE1 - psfE1)."""
161 psfStarDeltaE2Scatter: float = float('nan')
162 """Psf stars MAD E2 scatter (starE2 - psfE2)."""
164 psfStarDeltaSizeMedian: float = float('nan')
165 """Psf stars median size residual (starSize - psfSize)."""
167 psfStarDeltaSizeScatter: float = float('nan')
168 """Psf stars MAD size scatter (starSize - psfSize)."""
170 psfStarScaledDeltaSizeScatter: float = float('nan')
171 """Psf stars MAD size scatter scaled by psfSize**2."""
173 psfTraceRadiusDelta: float = float('nan')
174 """Delta (max - min) of the model psf trace radius values evaluated on a
175 grid of unmasked pixels (pixels).
176 """
178 psfApFluxDelta: float = float('nan')
179 """Delta (max - min) of the model psf aperture flux (with aperture radius of
180 max(2, 3*psfSigma)) values evaluated on a grid of unmasked pixels.
181 """
183 psfApCorrSigmaScaledDelta: float = float('nan')
184 """Delta (max - min) of the psf flux aperture correction factors scaled (divided)
185 by the psfSigma evaluated on a grid of unmasked pixels.
186 """
188 maxDistToNearestPsf: float = float('nan')
189 """Maximum distance of an unmasked pixel to its nearest model psf star
190 (pixels).
191 """
193 starEMedian: float = float('nan')
194 """Median ellipticity (sqrt(starE1**2.0 + starE2**2.0)) of the stars used
195 in the PSF model.
196 """
198 starUnNormalizedEMedian: float = float('nan')
199 """Median un-normalized ellipticity (sqrt((starXX - starYY)**2.0 + (2.0*starXY)**2.0))
200 of the stars used in the PSF model (pixel**2).
201 """
203 starComa1Median: float = float('nan')
204 """Coma-like higher-order moment combination: median M30 + M12
205 of the stars used in the PSF model.
206 """
208 starComa2Median: float = float('nan')
209 """Coma-like higher-order moment combination: median M21 + M03
210 of the stars used in the PSF model.
211 """
213 starTrefoil1Median: float = float('nan')
214 """Trefoil-like higher-order moment combination: median M30 - 3*M12
215 of the stars used in the PSF model.
216 """
218 starTrefoil2Median: float = float('nan')
219 """Trefoil-like higher-order moment combination: median 3*M21 - M03
220 of the stars used in the PSF model.
221 """
223 starKurtosisMedian: float = float('nan')
224 """Kurtosis-like higher-order moment combination: median M40 + 2*M22 + M04
225 of the stars used in the PSF model.
226 """
228 starE41Median: float = float('nan')
229 """Fourth-order ellipticity-like higher-order moment combination: median M40 - M04
230 of the stars used in the PSF model.
231 """
233 starE42Median: float = float('nan')
234 """Fourth-order ellipticity-like higher-order moment combination: median 2*(M31 + M13)
235 of the stars used in the PSF model.
236 """
238 effTime: float = float('nan')
239 """Effective exposure time calculated from psfSigma, skyBg, and
240 zeroPoint (seconds).
241 """
243 effTimePsfSigmaScale: float = float('nan')
244 """PSF scaling of the effective exposure time."""
246 effTimeSkyBgScale: float = float('nan')
247 """Sky background scaling of the effective exposure time."""
249 effTimeZeroPointScale: float = float('nan')
250 """Zeropoint scaling of the effective exposure time."""
252 magLim: float = float('nan')
253 """Magnitude limit at fixed SNR (default SNR=5) calculated from psfSigma, skyBg,
254 zeroPoint, and readNoise.
255 """
257 psfTE1e1: float = float('nan')
258 """Per-exposure TE1e1 ~ <de1 de1> of PSF residual ellipticity, averaged over
259 theta [0,1] arcmin via treecorr KK correlation. Dimensionless; used to form the
260 full-survey TE1 metric.
261 """
263 psfTE1e2: float = float('nan')
264 """Per-exposure TE1e2 ~ <de2 de2> of PSF residual ellipticity, averaged over
265 theta [0,1] arcmin via treecorr KK correlation. Dimensionless; used to form the
266 full-survey TE1 metric.
267 """
269 psfTE1ex: float = float('nan')
270 """Per-exposure TE1ex ~ <de1 de2> of PSF residual ellipticity, averaged over
271 theta [0,1] arcmin via treecorr KK correlation. Dimensionless; used to form the
272 full-survey TE1 metric.
273 """
275 psfTE2e1: float = float('nan')
276 """Per-exposure TE2e1 ~ <de1 de1> of PSF residual ellipticity, averaged over
277 theta [5,100] arcmin via treecorr KK correlation. Dimensionless; used to form the
278 full-survey TE2 metric.
279 """
281 psfTE2e2: float = float('nan')
282 """Per-exposure TE2e2 ~ <de2 de2> of PSF residual ellipticity, averaged over
283 theta [5,100] arcmin via treecorr KK correlation. Dimensionless; used to form the
284 full-survey TE2 metric.
285 """
287 psfTE2ex: float = float('nan')
288 """Per-exposure TE2ex ~ <de1 de2> of PSF residual ellipticity, averaged over
289 theta [5,100] arcmin via treecorr KK correlation. Dimensionless; used to form the
290 full-survey TE2 metric.
291 """
293 psfTE3e1: float = float('nan')
294 """Per-exposure median-over-CCDs of TE3e1 ~ <de1 de1> of PSF residual
295 ellipticity, where each CCD uses theta within [0,5] arcmin bins. Dimensionless;
296 downstream pipelines take the 85th percentile over
297 images to evaluate TE3.
298 """
300 psfTE3e2: float = float('nan')
301 """Per-exposure median-over-CCDs of TE3e2 ~ <de2 de2> of PSF residual
302 ellipticity, where each CCD uses theta within [0,5] arcmin bins. Dimensionless;
303 downstream pipelines take the 85th percentile over
304 images to evaluate TE3.
305 """
307 psfTE3ex: float = float('nan')
308 """Per-exposure median-over-CCDs of TE3ex ~ <de1 de2> of PSF residual
309 ellipticity, where each CCD uses theta within [0,5] arcmin bins. Dimensionless;
310 downstream pipelines take the 85th percentile over
311 images to evaluate TE3.
312 """
314 psfTE4e1: float = float('nan')
315 """Per-exposure median-over-CCDs of TE4e1 ~ <de1 de1> of PSF residual
316 ellipticity, where each CCD uses theta within [5,20] arcmin bins. Dimensionless;
317 downstream pipelines take the 85th percentile over
318 images to evaluate TE4.
319 """
321 psfTE4e2: float = float('nan')
322 """Per-exposure median-over-CCDs of TE4e2 ~ <de2 de2> of PSF residual
323 ellipticity, where each CCD uses theta within [5,20] arcmin bins. Dimensionless;
324 downstream pipelines take the 85th percentile over
325 images to evaluate TE4.
326 """
328 psfTE4ex: float = float('nan')
329 """Per-exposure median-over-CCDs of TE4ex ~ <de1 de2> of PSF residual
330 ellipticity, where each CCD uses theta within [5,20] arcmin bins. Dimensionless;
331 downstream pipelines take the 85th percentile over
332 images to evaluate TE4.
333 """
335 def __post_init__(self):
336 Storable.__init__(self)
338 def isPersistable(self):
339 return True
341 def _getPersistenceName(self):
342 return self._persistence_name
344 def _getPythonModule(self):
345 return __name__
347 def _write(self):
348 return yaml.dump(dataclasses.asdict(self), encoding='utf-8')
350 @staticmethod
351 def _read(bytes):
352 yamlDict = yaml.load(bytes, Loader=yaml.SafeLoader)
354 # Special list of fields to forward to new names.
355 forwardFieldDict = {"decl": "dec"}
357 # For forwards compatibility, filter out any fields that are
358 # not defined in the dataclass.
359 droppedFields = []
360 for _field in list(yamlDict.keys()):
361 if _field not in ExposureSummaryStats.__dataclass_fields__:
362 if _field in forwardFieldDict and forwardFieldDict[_field] not in yamlDict:
363 yamlDict[forwardFieldDict[_field]] = yamlDict[_field]
364 else:
365 droppedFields.append(_field)
366 yamlDict.pop(_field)
367 if len(droppedFields) > 0:
368 droppedFieldString = ", ".join([str(f) for f in droppedFields])
369 plural = "s" if len(droppedFields) != 1 else ""
370 them = "them" if len(droppedFields) > 1 else "it"
371 warnings.warn(
372 f"Summary field{plural} [{droppedFieldString}] not recognized by this software version;"
373 f" ignoring {them}.",
374 FutureWarning,
375 stacklevel=2,
376 )
377 return ExposureSummaryStats(**yamlDict)
379 @classmethod
380 def update_schema(cls, schema: Schema) -> None:
381 """Update an schema to includes for all summary statistic fields.
383 Parameters
384 -------
385 schema : `lsst.afw.table.Schema`
386 Schema to add which fields will be added.
387 """
388 schema.addField(
389 "psfSigma",
390 type="F",
391 doc="PSF model second-moments determinant radius (center of chip) (pixel)",
392 units="pixel",
393 )
394 schema.addField(
395 "psfArea",
396 type="F",
397 doc="PSF model effective area (center of chip) (pixel**2)",
398 units='pixel**2',
399 )
400 schema.addField(
401 "psfIxx",
402 type="F",
403 doc="PSF model Ixx (center of chip) (pixel**2)",
404 units='pixel**2',
405 )
406 schema.addField(
407 "psfIyy",
408 type="F",
409 doc="PSF model Iyy (center of chip) (pixel**2)",
410 units='pixel**2',
411 )
412 schema.addField(
413 "psfIxy",
414 type="F",
415 doc="PSF model Ixy (center of chip) (pixel**2)",
416 units='pixel**2',
417 )
418 schema.addField(
419 "raCorners",
420 type="ArrayD",
421 size=4,
422 doc="Right Ascension of bounding box corners (degrees)",
423 units="degree",
424 )
425 schema.addField(
426 "decCorners",
427 type="ArrayD",
428 size=4,
429 doc="Declination of bounding box corners (degrees)",
430 units="degree",
431 )
432 schema.addField(
433 "ra",
434 type="D",
435 doc="Right Ascension of bounding box center (degrees)",
436 units="degree",
437 )
438 schema.addField(
439 "dec",
440 type="D",
441 doc="Declination of bounding box center (degrees)",
442 units="degree",
443 )
444 schema.addField(
445 "zenithDistance",
446 type="F",
447 doc="Zenith distance of bounding box center (degrees)",
448 units="degree",
449 )
450 schema.addField(
451 "pixelScale",
452 type="F",
453 doc="Measured detector pixel scale (arcsec/pixel)",
454 units="arcsec/pixel",
455 )
456 schema.addField(
457 "expTime",
458 type="F",
459 doc="Exposure time of the exposure (seconds)",
460 units="second",
461 )
462 schema.addField(
463 "zeroPoint",
464 type="F",
465 doc="Mean zeropoint in detector (mag)",
466 units="mag",
467 )
468 schema.addField(
469 "skyBg",
470 type="F",
471 doc="Average sky background (ADU)",
472 units="adu",
473 )
474 schema.addField(
475 "skyNoise",
476 type="F",
477 doc="Average sky noise (ADU)",
478 units="adu",
479 )
480 schema.addField(
481 "meanVar",
482 type="F",
483 doc="Mean variance of the weight plane (ADU**2)",
484 units="adu**2"
485 )
486 schema.addField(
487 "psfAdaptiveThresholdValue",
488 type="F",
489 doc="Threshold value used in the adaptive threshold detection pass for PSF modelling.",
490 units="",
491 )
492 schema.addField(
493 "psfAdaptiveIncludeThresholdMultiplier",
494 type="F",
495 doc="Threshold multiplier used in the adaptive threshold detection pass for PSF modelling.",
496 units="",
497 )
498 schema.addField(
499 "nShapeletsStar",
500 type="I",
501 doc="Number of sources used in the shapelet decomposition.",
502 units="count",
503 )
504 schema.addField(
505 "shapeletsOnlyIqScore",
506 type="F",
507 doc="The dimensionless image quality score as determined from the shapelets "
508 "decomposition that includes power only from the non-atmospheric decomposition "
509 "coefficients. The score spans the range [0.0, 1.0] with lower values indicating "
510 "better image quality.",
511 units="",
512 )
513 schema.addField(
514 "shapeletsIqScore",
515 type="F",
516 doc="The dimensionless image quality score as determined from the shapelets "
517 "decomposition that includes power from the median centroid offset between those "
518 "used in the decomposition and those of the centroid slot in addition to "
519 "non-atmospheric decomposition coefficients. The score spans the range [0.0, 1.0] "
520 "with lower values indicating better image quality.",
521 units="",
522 )
523 schema.addField(
524 "shapeletsCoeffs",
525 type="ArrayD",
526 size=0, # dynamic size
527 doc="List of coefficients from the PSF star shapelet decomposition.",
528 units="",
529 )
530 schema.addField(
531 "centroidDiffShapeletsVsSlotMedian",
532 type="F",
533 doc="Median centroid difference (sqrt((slot_x - shapelet_x)**2 + (slot_y - shapelet_y)**2)) "
534 "for sources used in the shapelet decomposition.",
535 units="pixel",
536 )
537 schema.addField(
538 "shapeletsStarEMedian",
539 type="F",
540 doc="Median ellipticity (sqrt(starE1**2.0 + starE2**2.0)) of the stars used in the "
541 "shapelet decomposition.",
542 units="",
543 )
544 schema.addField(
545 "shapeletsStarUnNormalizedEMedian",
546 type="F",
547 doc="Median un-normalized ellipticity (sqrt((starXX - starYY)**2.0 + (2.0*starXY)**2.0)) "
548 "of the stars used in the shapelet decomposition.",
549 units="pixel**2",
550 )
551 schema.addField(
552 "refCatSourceDensity",
553 type="F",
554 doc="Source density for the detector region as computed from the loaded reference catalog "
555 "(number per degrees**2)",
556 units="degree**-2",
557 )
558 schema.addField(
559 "astromOffsetMean",
560 type="F",
561 doc="Mean offset of astrometric calibration matches (arcsec)",
562 units="arcsec",
563 )
564 schema.addField(
565 "astromOffsetStd",
566 type="F",
567 doc="Standard deviation of offsets of astrometric calibration matches (arcsec)",
568 units="arcsec",
569 )
570 schema.addField("nPsfStar", type="I", doc="Number of stars used for PSF model")
571 schema.addField(
572 "psfStarDeltaE1Median",
573 type="F",
574 doc="Median E1 residual (starE1 - psfE1) for psf stars",
575 )
576 schema.addField(
577 "psfStarDeltaE2Median",
578 type="F",
579 doc="Median E2 residual (starE2 - psfE2) for psf stars",
580 )
581 schema.addField(
582 "psfStarDeltaE1Scatter",
583 type="F",
584 doc="Scatter (via MAD) of E1 residual (starE1 - psfE1) for psf stars",
585 )
586 schema.addField(
587 "psfStarDeltaE2Scatter",
588 type="F",
589 doc="Scatter (via MAD) of E2 residual (starE2 - psfE2) for psf stars",
590 )
591 schema.addField(
592 "psfStarDeltaSizeMedian",
593 type="F",
594 doc="Median size residual (starSize - psfSize) for psf stars (pixel)",
595 units="pixel",
596 )
597 schema.addField(
598 "psfStarDeltaSizeScatter",
599 type="F",
600 doc="Scatter (via MAD) of size residual (starSize - psfSize) for psf stars (pixel)",
601 units="pixel",
602 )
603 schema.addField(
604 "psfStarScaledDeltaSizeScatter",
605 type="F",
606 doc="Scatter (via MAD) of size residual scaled by median size squared",
607 )
608 schema.addField(
609 "psfTraceRadiusDelta",
610 type="F",
611 doc="Delta (max - min) of the model psf trace radius values evaluated on a grid of "
612 "unmasked pixels (pixel).",
613 units="pixel",
614 )
615 schema.addField(
616 "psfApFluxDelta",
617 type="F",
618 doc="Delta (max - min) of the model psf aperture flux (with aperture radius of "
619 "max(2, 3*psfSigma)) values evaluated on a grid of unmasked pixels.",
620 )
621 schema.addField(
622 "psfApCorrSigmaScaledDelta",
623 type="F",
624 doc="Delta (max - min) of the model psf aperture correction factors scaled (divided) "
625 "by the psfSigma evaluated on a grid of unmasked pixels.",
626 )
627 schema.addField(
628 "maxDistToNearestPsf",
629 type="F",
630 doc="Maximum distance of an unmasked pixel to its nearest model psf star (pixel).",
631 units="pixel",
632 )
633 schema.addField(
634 "starEMedian",
635 type="F",
636 doc="Median ellipticity (sqrt(starE1**2.0 + starE2**2.0)) of the stars used in "
637 "the PSF model.",
638 )
639 schema.addField(
640 "starUnNormalizedEMedian",
641 type="F",
642 doc="Median un-normalized ellipticity (sqrt((starXX - starYY)**2.0 + (2.0*starXY)**2.0)) "
643 "of the stars used in the PSF model.",
644 )
645 schema.addField(
646 "starComa1Median",
647 type="F",
648 doc="Coma-like higher-order moment combination: median M30 + M12 "
649 "of the stars used in the PSF model.",
650 )
651 schema.addField(
652 "starComa2Median",
653 type="F",
654 doc="Coma-like higher-order moment combination: median M21 + M03 "
655 "of the stars used in the PSF model.",
656 )
657 schema.addField(
658 "starTrefoil1Median",
659 type="F",
660 doc="Trefoil-like higher-order moment combination: median M30 - 3*M12 "
661 "of the stars used in the PSF model.",
662 )
663 schema.addField(
664 "starTrefoil2Median",
665 type="F",
666 doc="Trefoil-like higher-order moment combination: median 3*M21 - M03 "
667 "of the stars used in the PSF model.",
668 )
669 schema.addField(
670 "starKurtosisMedian",
671 type="F",
672 doc="Kurtosis-like higher-order moment combination: median M40 + 2*M22 + M04 "
673 "of the stars used in the PSF model.",
674 )
675 schema.addField(
676 "starE41Median",
677 type="F",
678 doc="Fourth-order ellipticity-like higher-order moment combination: median M40 - M04 "
679 "of the stars used in the PSF model.",
680 )
681 schema.addField(
682 "starE42Median",
683 type="F",
684 doc="Fourth-order ellipticity-like higher-order moment combination: median 2*(M31 + M13) "
685 "of the stars used in the PSF model.",
686 )
687 schema.addField(
688 "effTime",
689 type="F",
690 doc="Effective exposure time calculated from psfSigma, skyBg, and "
691 "zeroPoint (seconds).",
692 units="second",
693 )
694 schema.addField(
695 "effTimePsfSigmaScale",
696 type="F",
697 doc="PSF scaling of the effective exposure time."
698 )
699 schema.addField(
700 "effTimeSkyBgScale",
701 type="F",
702 doc="Sky background scaling of the effective exposure time."
703 )
704 schema.addField(
705 "effTimeZeroPointScale",
706 type="F",
707 doc="Zeropoint scaling of the effective exposure time."
708 )
709 schema.addField(
710 "magLim",
711 type="F",
712 doc="Magnitude limit at SNR=5 (M5) calculated from psfSigma, "
713 "skyBg, zeroPoint, and readNoise.",
714 units="mag",
715 )
716 schema.addField(
717 "psfTE1e1",
718 type="F",
719 doc="Per-exposure E1e1 ~ <de1 de1> of PSF residual ellipticity "
720 "over theta within [0,1] arcmin. Dimensionless; contributes to TE1.",
721 )
722 schema.addField(
723 "psfTE1e2",
724 type="F",
725 doc="Per-exposure E1e2 ~ <de2 de2> of PSF residual ellipticity "
726 "over theta within [0,1] arcmin. Dimensionless; contributes to TE1.",
727 )
728 schema.addField(
729 "psfTE1ex",
730 type="F",
731 doc="Per-exposure E1ex ~ <de1 de2> of PSF residual ellipticity "
732 "over theta within [0,1] arcmin. Dimensionless; contributes to TE1.",
733 )
734 schema.addField(
735 "psfTE2e1",
736 type="F",
737 doc="Per-exposure E2e1 ~ <de1 de1> of PSF residual ellipticity "
738 "over theta within [5, 100] arcmin. Dimensionless; contributes to TE2.",
739 )
740 schema.addField(
741 "psfTE2e2",
742 type="F",
743 doc="Per-exposure E2e2 ~ <de2 de2> of PSF residual ellipticity "
744 "over theta within [5, 100] arcmin. Dimensionless; contributes to TE2.",
745 )
746 schema.addField(
747 "psfTE2ex",
748 type="F",
749 doc="Per-exposure E2ex ~ <de1 de2> of PSF residual ellipticity "
750 "over theta within [5, 100] arcmin. Dimensionless; contributes to TE2.",
751 )
752 schema.addField(
753 "psfTE3e1",
754 type="F",
755 doc="Per-exposure median-over-CCDs of TE3e1 ~ <de1 de1> with "
756 "per-CCD theta within [0,5] arcmin. Dimensionless; used for TE3.",
757 )
758 schema.addField(
759 "psfTE3e2",
760 type="F",
761 doc="Per-exposure median-over-CCDs of TE3e2 ~ <de2 de2> with "
762 "per-CCD theta within [0,5] arcmin. Dimensionless; used for TE3.",
763 )
764 schema.addField(
765 "psfTE3ex",
766 type="F",
767 doc="Per-exposure median-over-CCDs of TE3ex ~ <de1 de2> with "
768 "per-CCD theta within [0,5] arcmin. Dimensionless; used for TE3.",
769 )
770 schema.addField(
771 "psfTE4e1",
772 type="F",
773 doc="Per-exposure median-over-CCDs of TE4e1 ~ <de1 de1> with "
774 "per-CCD theta within [5, 20] arcmin. Dimensionless; used for TE4.",
775 )
776 schema.addField(
777 "psfTE4e2",
778 type="F",
779 doc="Per-exposure median-over-CCDs of TE4e2 ~ <de2 de2> with "
780 "per-CCD theta within [5, 20] arcmin. Dimensionless; used for TE4.",
781 )
782 schema.addField(
783 "psfTE4ex",
784 type="F",
785 doc="Per-exposure median-over-CCDs of TE4ex ~ <de1 de2> with "
786 "per-CCD theta within [5, 20] arcmin. Dimensionless; used for TE4.",
787 )
789 def update_record(self, record: BaseRecord) -> None:
790 """Write summary-statistic columns into a record.
792 Parameters
793 ----------
794 record : `lsst.afw.table.BaseRecord`
795 Record to update. This is expected to frequently be an
796 `ExposureRecord` instance (with higher-level code adding other
797 columns and objects), but this method can work with any record
798 type.
799 """
800 for field in dataclasses.fields(self):
801 value = getattr(self, field.name)
802 if field.name == "version":
803 continue
804 elif field.type.startswith("list"):
805 record[field.name] = np.array(value, dtype=record[field.name].dtype)
806 else:
807 record[field.name] = value
809 @classmethod
810 def from_record(cls, record: BaseRecord) -> ExposureSummaryStats:
811 """Read summary-statistic columns from a record into ``self``.
813 Parameters
814 ----------
815 record : `lsst.afw.table.BaseRecord`
816 Record to read from. This is expected to frequently be an
817 `ExposureRecord` instance (with higher-level code adding other
818 columns and objects), but this method can work with any record
819 type, ignoring any attributes or columns it doesn't recognize.
821 Returns
822 -------
823 summary : `ExposureSummaryStats`
824 Summary statistics object created from the given record.
825 """
826 return cls(
827 **{
828 field.name: (
829 record[field.name] if not field.type.startswith("list")
830 else [float(v) for v in record[field.name]]
831 )
832 for field in dataclasses.fields(cls)
833 if field.name != "version"
834 }
835 )