Coverage for python/lsst/ip/isr/isrMock.py : 22%

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1# This file is part of ip_isr.
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/>.
22import copy
23import numpy as np
24import tempfile
26import lsst.geom
27import lsst.afw.geom as afwGeom
28import lsst.afw.image as afwImage
29import lsst.afw.math as afwMath
30import lsst.afw.cameraGeom.utils as afwUtils
31import lsst.afw.cameraGeom.testUtils as afwTestUtils
32from lsst.meas.algorithms import Defects
33import lsst.pex.config as pexConfig
34import lsst.pipe.base as pipeBase
35from .crosstalk import X_FLIP, Y_FLIP
37__all__ = ["IsrMockConfig", "IsrMock", "RawMock", "TrimmedRawMock", "RawDictMock",
38 "CalibratedRawMock", "MasterMock",
39 "BiasMock", "DarkMock", "FlatMock", "FringeMock", "UntrimmedFringeMock",
40 "BfKernelMock", "DefectMock", "CrosstalkCoeffMock", "TransmissionMock",
41 "DataRefMock"]
44class IsrMockConfig(pexConfig.Config):
45 """Configuration parameters for isrMock.
47 These parameters produce generic fixed position signals from
48 various sources, and combine them in a way that matches how those
49 signals are combined to create real data. The camera used is the
50 test camera defined by the afwUtils code.
51 """
52 # Detector parameters. "Exposure" parameters.
53 isLsstLike = pexConfig.Field(
54 dtype=bool,
55 default=False,
56 doc="If True, products have one raw image per amplifier, otherwise, one raw image per detector.",
57 )
58 plateScale = pexConfig.Field(
59 dtype=float,
60 default=20.0,
61 doc="Plate scale used in constructing mock camera.",
62 )
63 radialDistortion = pexConfig.Field(
64 dtype=float,
65 default=0.925,
66 doc="Radial distortion term used in constructing mock camera.",
67 )
68 isTrimmed = pexConfig.Field(
69 dtype=bool,
70 default=True,
71 doc="If True, amplifiers have been trimmed and mosaicked to remove regions outside the data BBox.",
72 )
73 detectorIndex = pexConfig.Field(
74 dtype=int,
75 default=20,
76 doc="Index for the detector to use. The default value uses a standard 2x4 array of amps.",
77 )
78 rngSeed = pexConfig.Field(
79 dtype=int,
80 default=20000913,
81 doc="Seed for random number generator used to add noise.",
82 )
83 # TODO: DM-18345 Check that mocks scale correctly when gain != 1.0
84 gain = pexConfig.Field(
85 dtype=float,
86 default=1.0,
87 doc="Gain for simulated data in e^-/DN.",
88 )
89 readNoise = pexConfig.Field(
90 dtype=float,
91 default=5.0,
92 doc="Read noise of the detector in e-.",
93 )
94 expTime = pexConfig.Field(
95 dtype=float,
96 default=5.0,
97 doc="Exposure time for simulated data.",
98 )
100 # Signal parameters
101 skyLevel = pexConfig.Field(
102 dtype=float,
103 default=1000.0,
104 doc="Background contribution to be generated from 'the sky' in DN.",
105 )
106 sourceFlux = pexConfig.ListField(
107 dtype=float,
108 default=[45000.0],
109 doc="Peak flux level (in DN) of simulated 'astronomical sources'.",
110 )
111 sourceAmp = pexConfig.ListField(
112 dtype=int,
113 default=[0],
114 doc="Amplifier to place simulated 'astronomical sources'.",
115 )
116 sourceX = pexConfig.ListField(
117 dtype=float,
118 default=[50.0],
119 doc="Peak position (in amplifier coordinates) of simulated 'astronomical sources'.",
120 )
121 sourceY = pexConfig.ListField(
122 dtype=float,
123 default=[25.0],
124 doc="Peak position (in amplifier coordinates) of simulated 'astronomical sources'.",
125 )
126 overscanScale = pexConfig.Field(
127 dtype=float,
128 default=100.0,
129 doc="Amplitude (in DN) of the ramp function to add to overscan data.",
130 )
131 biasLevel = pexConfig.Field(
132 dtype=float,
133 default=8000.0,
134 doc="Background contribution to be generated from the bias offset in DN.",
135 )
136 darkRate = pexConfig.Field(
137 dtype=float,
138 default=5.0,
139 doc="Background level contribution (in e-/s) to be generated from dark current.",
140 )
141 darkTime = pexConfig.Field(
142 dtype=float,
143 default=5.0,
144 doc="Exposure time for the dark current contribution.",
145 )
146 flatDrop = pexConfig.Field(
147 dtype=float,
148 default=0.1,
149 doc="Fractional flux drop due to flat from center to edge of detector along x-axis.",
150 )
151 fringeScale = pexConfig.ListField(
152 dtype=float,
153 default=[200.0],
154 doc="Peak fluxes for the components of the fringe ripple in DN.",
155 )
156 fringeX0 = pexConfig.ListField(
157 dtype=float,
158 default=[-100],
159 doc="Center position for the fringe ripples.",
160 )
161 fringeY0 = pexConfig.ListField(
162 dtype=float,
163 default=[-0],
164 doc="Center position for the fringe ripples.",
165 )
167 # Inclusion parameters
168 doAddSky = pexConfig.Field(
169 dtype=bool,
170 default=True,
171 doc="Apply 'sky' signal to output image.",
172 )
173 doAddSource = pexConfig.Field(
174 dtype=bool,
175 default=True,
176 doc="Add simulated source to output image.",
177 )
178 doAddCrosstalk = pexConfig.Field(
179 dtype=bool,
180 default=False,
181 doc="Apply simulated crosstalk to output image. This cannot be corrected by ISR, "
182 "as detector.hasCrosstalk()==False.",
183 )
184 doAddOverscan = pexConfig.Field(
185 dtype=bool,
186 default=True,
187 doc="If untrimmed, add overscan ramp to overscan and data regions.",
188 )
189 doAddBias = pexConfig.Field(
190 dtype=bool,
191 default=True,
192 doc="Add bias signal to data.",
193 )
194 doAddDark = pexConfig.Field(
195 dtype=bool,
196 default=True,
197 doc="Add dark signal to data.",
198 )
199 doAddFlat = pexConfig.Field(
200 dtype=bool,
201 default=True,
202 doc="Add flat signal to data.",
203 )
204 doAddFringe = pexConfig.Field(
205 dtype=bool,
206 default=True,
207 doc="Add fringe signal to data.",
208 )
210 # Datasets to create and return instead of generating an image.
211 doTransmissionCurve = pexConfig.Field(
212 dtype=bool,
213 default=False,
214 doc="Return a simulated transmission curve.",
215 )
216 doDefects = pexConfig.Field(
217 dtype=bool,
218 default=False,
219 doc="Return a simulated defect list.",
220 )
221 doBrighterFatter = pexConfig.Field(
222 dtype=bool,
223 default=False,
224 doc="Return a simulated brighter-fatter kernel.",
225 )
226 doCrosstalkCoeffs = pexConfig.Field(
227 dtype=bool,
228 default=False,
229 doc="Return the matrix of crosstalk coefficients.",
230 )
231 doDataRef = pexConfig.Field(
232 dtype=bool,
233 default=False,
234 doc="Return a simulated gen2 butler dataRef.",
235 )
236 doGenerateImage = pexConfig.Field(
237 dtype=bool,
238 default=False,
239 doc="Return the generated output image if True.",
240 )
241 doGenerateData = pexConfig.Field(
242 dtype=bool,
243 default=False,
244 doc="Return a non-image data structure if True.",
245 )
246 doGenerateAmpDict = pexConfig.Field(
247 dtype=bool,
248 default=False,
249 doc="Return a dict of exposure amplifiers instead of an afwImage.Exposure.",
250 )
253class IsrMock(pipeBase.Task):
254 """Class to generate consistent mock images for ISR testing.
256 ISR testing currently relies on one-off fake images that do not
257 accurately mimic the full set of detector effects. This class
258 uses the test camera/detector/amplifier structure defined in
259 `lsst.afw.cameraGeom.testUtils` to avoid making the test data
260 dependent on any of the actual obs package formats.
261 """
262 ConfigClass = IsrMockConfig
263 _DefaultName = "isrMock"
265 def __init__(self, **kwargs):
266 super().__init__(**kwargs)
267 self.rng = np.random.RandomState(self.config.rngSeed)
268 self.crosstalkCoeffs = np.array([[0.0, 0.0, 0.0, 0.0, 0.0, -1e-3, 0.0, 0.0],
269 [1e-2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
270 [1e-2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
271 [1e-2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
272 [1e-2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
273 [1e-2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
274 [1e-2, 0.0, 0.0, 2.2e-2, 0.0, 0.0, 0.0, 0.0],
275 [1e-2, 5e-3, 5e-4, 3e-3, 4e-2, 5e-3, 5e-3, 0.0]])
277 self.bfKernel = np.array([[1., 4., 7., 4., 1.],
278 [4., 16., 26., 16., 4.],
279 [7., 26., 41., 26., 7.],
280 [4., 16., 26., 16., 4.],
281 [1., 4., 7., 4., 1.]]) / 273.0
283 def run(self):
284 """Generate a mock ISR product, and return it.
286 Returns
287 -------
288 image : `lsst.afw.image.Exposure`
289 Simulated ISR image with signals added.
290 dataProduct :
291 Simulated ISR data products.
292 None :
293 Returned if no valid configuration was found.
295 Raises
296 ------
297 RuntimeError
298 Raised if both doGenerateImage and doGenerateData are specified.
299 """
300 if self.config.doGenerateImage and self.config.doGenerateData:
301 raise RuntimeError("Only one of doGenerateImage and doGenerateData may be specified.")
302 elif self.config.doGenerateImage:
303 return self.makeImage()
304 elif self.config.doGenerateData:
305 return self.makeData()
306 else:
307 return None
309 def makeData(self):
310 """Generate simulated ISR data.
312 Currently, only the class defined crosstalk coefficient
313 matrix, brighter-fatter kernel, a constant unity transmission
314 curve, or a simple single-entry defect list can be generated.
316 Returns
317 -------
318 dataProduct :
319 Simulated ISR data product.
320 """
321 if sum(map(bool, [self.config.doBrighterFatter,
322 self.config.doDefects,
323 self.config.doTransmissionCurve,
324 self.config.doCrosstalkCoeffs])) != 1:
325 raise RuntimeError("Only one data product can be generated at a time.")
326 elif self.config.doBrighterFatter is True:
327 return self.makeBfKernel()
328 elif self.config.doDefects is True:
329 return self.makeDefectList()
330 elif self.config.doTransmissionCurve is True:
331 return self.makeTransmissionCurve()
332 elif self.config.doCrosstalkCoeffs is True:
333 return self.crosstalkCoeffs
334 else:
335 return None
337 def makeBfKernel(self):
338 """Generate a simple Gaussian brighter-fatter kernel.
340 Returns
341 -------
342 kernel : `numpy.ndarray`
343 Simulated brighter-fatter kernel.
344 """
345 return self.bfKernel
347 def makeDefectList(self):
348 """Generate a simple single-entry defect list.
350 Returns
351 -------
352 defectList : `lsst.meas.algorithms.Defects`
353 Simulated defect list
354 """
355 return Defects([lsst.geom.Box2I(lsst.geom.Point2I(0, 0),
356 lsst.geom.Extent2I(40, 50))])
358 def makeCrosstalkCoeff(self):
359 """Generate the simulated crosstalk coefficients.
361 Returns
362 -------
363 coeffs : `numpy.ndarray`
364 Simulated crosstalk coefficients.
365 """
367 return self.crosstalkCoeffs
369 def makeTransmissionCurve(self):
370 """Generate a simulated flat transmission curve.
372 Returns
373 -------
374 transmission : `lsst.afw.image.TransmissionCurve`
375 Simulated transmission curve.
376 """
378 return afwImage.TransmissionCurve.makeIdentity()
380 def makeImage(self):
381 """Generate a simulated ISR image.
383 Returns
384 -------
385 exposure : `lsst.afw.image.Exposure` or `dict`
386 Simulated ISR image data.
388 Notes
389 -----
390 This method currently constructs a "raw" data image by:
391 * Generating a simulated sky with noise
392 * Adding a single Gaussian "star"
393 * Adding the fringe signal
394 * Multiplying the frame by the simulated flat
395 * Adding dark current (and noise)
396 * Adding a bias offset (and noise)
397 * Adding an overscan gradient parallel to the pixel y-axis
398 * Simulating crosstalk by adding a scaled version of each
399 amplifier to each other amplifier.
401 The exposure with image data constructed this way is in one of
402 three formats.
403 * A single image, with overscan and prescan regions retained
404 * A single image, with overscan and prescan regions trimmed
405 * A `dict`, containing the amplifer data indexed by the
406 amplifier name.
408 The nonlinearity, CTE, and brighter fatter are currently not
409 implemented.
411 Note that this method generates an image in the reverse
412 direction as the ISR processing, as the output image here has
413 had a series of instrument effects added to an idealized
414 exposure.
415 """
416 exposure = self.getExposure()
418 for idx, amp in enumerate(exposure.getDetector()):
419 bbox = None
420 if self.config.isTrimmed is True:
421 bbox = amp.getBBox()
422 else:
423 bbox = amp.getRawDataBBox()
425 ampData = exposure.image[bbox]
427 if self.config.doAddSky is True:
428 self.amplifierAddNoise(ampData, self.config.skyLevel, np.sqrt(self.config.skyLevel))
430 if self.config.doAddSource is True:
431 for sourceAmp, sourceFlux, sourceX, sourceY in zip(self.config.sourceAmp,
432 self.config.sourceFlux,
433 self.config.sourceX,
434 self.config.sourceY):
435 if idx == sourceAmp:
436 self.amplifierAddSource(ampData, sourceFlux, sourceX, sourceY)
438 if self.config.doAddFringe is True:
439 self.amplifierAddFringe(amp, ampData, np.array(self.config.fringeScale),
440 x0=np.array(self.config.fringeX0),
441 y0=np.array(self.config.fringeY0))
443 if self.config.doAddFlat is True:
444 if ampData.getArray().sum() == 0.0:
445 self.amplifierAddNoise(ampData, 1.0, 0.0)
446 u0 = exposure.getDimensions().getX()
447 v0 = exposure.getDimensions().getY()
448 self.amplifierMultiplyFlat(amp, ampData, self.config.flatDrop, u0=u0, v0=v0)
450 if self.config.doAddDark is True:
451 self.amplifierAddNoise(ampData,
452 self.config.darkRate * self.config.darkTime / self.config.gain,
453 np.sqrt(self.config.darkRate *
454 self.config.darkTime / self.config.gain))
456 if self.config.doAddCrosstalk is True:
458 for idxS, ampS in enumerate(exposure.getDetector()):
459 for idxT, ampT in enumerate(exposure.getDetector()):
460 ampDataS = exposure.image[ampS.getBBox() if self.config.isTrimmed
461 else ampS.getRawDataBBox()]
462 ampDataT = exposure.image[ampT.getBBox() if self.config.isTrimmed
463 else ampT.getRawDataBBox()]
464 ampDataS = afwMath.flipImage(ampDataS,
465 (X_FLIP[ampS.getReadoutCorner()] ^
466 X_FLIP[ampT.getReadoutCorner()]),
467 (Y_FLIP[ampS.getReadoutCorner()] ^
468 Y_FLIP[ampT.getReadoutCorner()]))
469 self.amplifierAddCT(ampDataS, ampDataT, self.crosstalkCoeffs[idxT][idxS])
471 for amp in exposure.getDetector():
472 bbox = None
473 if self.config.isTrimmed is True:
474 bbox = amp.getBBox()
475 else:
476 bbox = amp.getRawDataBBox()
478 ampData = exposure.image[bbox]
480 if self.config.doAddBias is True:
481 self.amplifierAddNoise(ampData, self.config.biasLevel,
482 self.config.readNoise / self.config.gain)
484 if self.config.doAddOverscan is True:
485 oscanBBox = amp.getRawHorizontalOverscanBBox()
486 oscanData = exposure.image[oscanBBox]
487 self.amplifierAddNoise(oscanData, self.config.biasLevel,
488 self.config.readNoise / self.config.gain)
490 self.amplifierAddYGradient(ampData, -1.0 * self.config.overscanScale,
491 1.0 * self.config.overscanScale)
492 self.amplifierAddYGradient(oscanData, -1.0 * self.config.overscanScale,
493 1.0 * self.config.overscanScale)
495 if self.config.doGenerateAmpDict is True:
496 expDict = dict()
497 for amp in exposure.getDetector():
498 expDict[amp.getName()] = exposure
499 return expDict
500 else:
501 return exposure
503 # afw primatives to construct the image structure
504 def getCamera(self):
505 """Construct a test camera object.
507 Returns
508 -------
509 camera : `lsst.afw.cameraGeom.camera`
510 Test camera.
511 """
512 cameraWrapper = afwTestUtils.CameraWrapper(
513 plateScale=self.config.plateScale,
514 radialDistortion=self.config.radialDistortion,
515 isLsstLike=self.config.isLsstLike,
516 )
517 camera = cameraWrapper.camera
518 return camera
520 def getExposure(self):
521 """Construct a test exposure.
523 The test exposure has a simple WCS set, as well as a list of
524 unlikely header keywords that can be removed during ISR
525 processing to exercise that code.
527 Returns
528 -------
529 exposure : `lsst.afw.exposure.Exposure`
530 Construct exposure containing masked image of the
531 appropriate size.
532 """
533 camera = self.getCamera()
534 detector = camera[self.config.detectorIndex]
535 image = afwUtils.makeImageFromCcd(detector,
536 isTrimmed=self.config.isTrimmed,
537 showAmpGain=False,
538 rcMarkSize=0,
539 binSize=1,
540 imageFactory=afwImage.ImageF)
542 var = afwImage.ImageF(image.getDimensions())
543 mask = afwImage.Mask(image.getDimensions())
544 image.assign(0.0)
546 maskedImage = afwImage.makeMaskedImage(image, mask, var)
547 exposure = afwImage.makeExposure(maskedImage)
548 exposure.setDetector(detector)
549 exposure.setWcs(self.getWcs())
551 visitInfo = afwImage.VisitInfo(exposureTime=self.config.expTime, darkTime=self.config.darkTime)
552 exposure.getInfo().setVisitInfo(visitInfo)
554 metadata = exposure.getMetadata()
555 metadata.add("SHEEP", 7.3, "number of sheep on farm")
556 metadata.add("MONKEYS", 155, "monkeys per tree")
557 metadata.add("VAMPIRES", 4, "How scary are vampires.")
559 ccd = exposure.getDetector()
560 newCcd = ccd.rebuild()
561 newCcd.clear()
562 for amp in ccd:
563 newAmp = amp.rebuild()
564 newAmp.setLinearityCoeffs((0., 1., 0., 0.))
565 newAmp.setLinearityType("Polynomial")
566 newAmp.setGain(self.config.gain)
567 newAmp.setSuspectLevel(25000.0)
568 newAmp.setSaturation(32000.0)
569 newCcd.append(newAmp)
570 exposure.setDetector(newCcd.finish())
572 exposure.image.array[:] = np.zeros(exposure.getImage().getDimensions()).transpose()
573 exposure.mask.array[:] = np.zeros(exposure.getMask().getDimensions()).transpose()
574 exposure.variance.array[:] = np.zeros(exposure.getVariance().getDimensions()).transpose()
576 return exposure
578 def getWcs(self):
579 """Construct a dummy WCS object.
581 Taken from the deprecated ip_isr/examples/exampleUtils.py.
583 This is not guaranteed, given the distortion and pixel scale
584 listed in the afwTestUtils camera definition.
586 Returns
587 -------
588 wcs : `lsst.afw.geom.SkyWcs`
589 Test WCS transform.
590 """
591 return afwGeom.makeSkyWcs(crpix=lsst.geom.Point2D(0.0, 100.0),
592 crval=lsst.geom.SpherePoint(45.0, 25.0, lsst.geom.degrees),
593 cdMatrix=afwGeom.makeCdMatrix(scale=1.0*lsst.geom.degrees))
595 def localCoordToExpCoord(self, ampData, x, y):
596 """Convert between a local amplifier coordinate and the full
597 exposure coordinate.
599 Parameters
600 ----------
601 ampData : `lsst.afw.image.ImageF`
602 Amplifier image to use for conversions.
603 x : `int`
604 X-coordinate of the point to transform.
605 y : `int`
606 Y-coordinate of the point to transform.
608 Returns
609 -------
610 u : `int`
611 Transformed x-coordinate.
612 v : `int`
613 Transformed y-coordinate.
615 Notes
616 -----
617 The output is transposed intentionally here, to match the
618 internal transpose between numpy and afw.image coordinates.
619 """
620 u = x + ampData.getBBox().getBeginX()
621 v = y + ampData.getBBox().getBeginY()
623 return (v, u)
625 # Simple data values.
626 def amplifierAddNoise(self, ampData, mean, sigma):
627 """Add Gaussian noise to an amplifier's image data.
629 This method operates in the amplifier coordinate frame.
631 Parameters
632 ----------
633 ampData : `lsst.afw.image.ImageF`
634 Amplifier image to operate on.
635 mean : `float`
636 Mean value of the Gaussian noise.
637 sigma : `float`
638 Sigma of the Gaussian noise.
639 """
640 ampArr = ampData.array
641 ampArr[:] = ampArr[:] + self.rng.normal(mean, sigma,
642 size=ampData.getDimensions()).transpose()
644 def amplifierAddYGradient(self, ampData, start, end):
645 """Add a y-axis linear gradient to an amplifier's image data.
647 This method operates in the amplifier coordinate frame.
649 Parameters
650 ----------
651 ampData : `lsst.afw.image.ImageF`
652 Amplifier image to operate on.
653 start : `float`
654 Start value of the gradient (at y=0).
655 end : `float`
656 End value of the gradient (at y=ymax).
657 """
658 nPixY = ampData.getDimensions().getY()
659 ampArr = ampData.array
660 ampArr[:] = ampArr[:] + (np.interp(range(nPixY), (0, nPixY - 1), (start, end)).reshape(nPixY, 1) +
661 np.zeros(ampData.getDimensions()).transpose())
663 def amplifierAddSource(self, ampData, scale, x0, y0):
664 """Add a single Gaussian source to an amplifier.
666 This method operates in the amplifier coordinate frame.
668 Parameters
669 ----------
670 ampData : `lsst.afw.image.ImageF`
671 Amplifier image to operate on.
672 scale : `float`
673 Peak flux of the source to add.
674 x0 : `float`
675 X-coordinate of the source peak.
676 y0 : `float`
677 Y-coordinate of the source peak.
678 """
679 for x in range(0, ampData.getDimensions().getX()):
680 for y in range(0, ampData.getDimensions().getY()):
681 ampData.array[y][x] = (ampData.array[y][x] +
682 scale * np.exp(-0.5 * ((x - x0)**2 + (y - y0)**2) / 3.0**2))
684 def amplifierAddCT(self, ampDataSource, ampDataTarget, scale):
685 """Add a scaled copy of an amplifier to another, simulating crosstalk.
687 This method operates in the amplifier coordinate frame.
689 Parameters
690 ----------
691 ampDataSource : `lsst.afw.image.ImageF`
692 Amplifier image to add scaled copy from.
693 ampDataTarget : `lsst.afw.image.ImageF`
694 Amplifier image to add scaled copy to.
695 scale : `float`
696 Flux scale of the copy to add to the target.
698 Notes
699 -----
700 This simulates simple crosstalk between amplifiers.
701 """
702 ampDataTarget.array[:] = (ampDataTarget.array[:] +
703 scale * ampDataSource.array[:])
705 # Functional form data values.
706 def amplifierAddFringe(self, amp, ampData, scale, x0=100, y0=0):
707 """Add a fringe-like ripple pattern to an amplifier's image data.
709 Parameters
710 ----------
711 amp : `~lsst.afw.ampInfo.AmpInfoRecord`
712 Amplifier to operate on. Needed for amp<->exp coordinate transforms.
713 ampData : `lsst.afw.image.ImageF`
714 Amplifier image to operate on.
715 scale : `numpy.array` or `float`
716 Peak intensity scaling for the ripple.
717 x0 : `numpy.array` or `float`, optional
718 Fringe center
719 y0 : `numpy.array` or `float`, optional
720 Fringe center
722 Notes
723 -----
724 This uses an offset sinc function to generate a ripple
725 pattern. True fringes have much finer structure, but this
726 pattern should be visually identifiable. The (x, y)
727 coordinates are in the frame of the amplifier, and (u, v) in
728 the frame of the full trimmed image.
729 """
730 for x in range(0, ampData.getDimensions().getX()):
731 for y in range(0, ampData.getDimensions().getY()):
732 (u, v) = self.localCoordToExpCoord(amp, x, y)
733 ampData.getArray()[y][x] = np.sum((ampData.getArray()[y][x] +
734 scale *
735 np.sinc(((u - x0) / 50)**2 +
736 ((v - y0) / 50)**2)))
738 def amplifierMultiplyFlat(self, amp, ampData, fracDrop, u0=100.0, v0=100.0):
739 """Multiply an amplifier's image data by a flat-like pattern.
741 Parameters
742 ----------
743 amp : `lsst.afw.ampInfo.AmpInfoRecord`
744 Amplifier to operate on. Needed for amp<->exp coordinate transforms.
745 ampData : `lsst.afw.image.ImageF`
746 Amplifier image to operate on.
747 fracDrop : `float`
748 Fractional drop from center to edge of detector along x-axis.
749 u0 : `float`
750 Peak location in detector coordinates.
751 v0 : `float`
752 Peak location in detector coordinates.
754 Notes
755 -----
756 This uses a 2-d Gaussian to simulate an illumination pattern
757 that falls off towards the edge of the detector. The (x, y)
758 coordinates are in the frame of the amplifier, and (u, v) in
759 the frame of the full trimmed image.
760 """
761 if fracDrop >= 1.0:
762 raise RuntimeError("Flat fractional drop cannot be greater than 1.0")
764 sigma = u0 / np.sqrt(-2.0 * np.log(fracDrop))
766 for x in range(0, ampData.getDimensions().getX()):
767 for y in range(0, ampData.getDimensions().getY()):
768 (u, v) = self.localCoordToExpCoord(amp, x, y)
769 f = np.exp(-0.5 * ((u - u0)**2 + (v - v0)**2) / sigma**2)
770 ampData.array[y][x] = (ampData.array[y][x] * f)
773class RawMock(IsrMock):
774 """Generate a raw exposure suitable for ISR.
775 """
776 def __init__(self, **kwargs):
777 super().__init__(**kwargs)
778 self.config.isTrimmed = False
779 self.config.doGenerateImage = True
780 self.config.doGenerateAmpDict = False
781 self.config.doAddOverscan = True
782 self.config.doAddSky = True
783 self.config.doAddSource = True
784 self.config.doAddCrosstalk = False
785 self.config.doAddBias = True
786 self.config.doAddDark = True
789class TrimmedRawMock(RawMock):
790 """Generate a trimmed raw exposure.
791 """
792 def __init__(self, **kwargs):
793 super().__init__(**kwargs)
794 self.config.isTrimmed = True
795 self.config.doAddOverscan = False
798class CalibratedRawMock(RawMock):
799 """Generate a trimmed raw exposure.
800 """
801 def __init__(self, **kwargs):
802 super().__init__(**kwargs)
803 self.config.isTrimmed = True
804 self.config.doGenerateImage = True
805 self.config.doAddOverscan = False
806 self.config.doAddSky = True
807 self.config.doAddSource = True
808 self.config.doAddCrosstalk = False
810 self.config.doAddBias = False
811 self.config.doAddDark = False
812 self.config.doAddFlat = False
813 self.config.doAddFringe = True
815 self.config.biasLevel = 0.0
816 self.config.readNoise = 10.0
819class RawDictMock(RawMock):
820 """Generate a raw exposure dict suitable for ISR.
821 """
822 def __init__(self, **kwargs):
823 super().__init__(**kwargs)
824 self.config.doGenerateAmpDict = True
827class MasterMock(IsrMock):
828 """Parent class for those that make master calibrations.
829 """
830 def __init__(self, **kwargs):
831 super().__init__(**kwargs)
832 self.config.isTrimmed = True
833 self.config.doGenerateImage = True
834 self.config.doAddOverscan = False
835 self.config.doAddSky = False
836 self.config.doAddSource = False
837 self.config.doAddCrosstalk = False
839 self.config.doAddBias = False
840 self.config.doAddDark = False
841 self.config.doAddFlat = False
842 self.config.doAddFringe = False
845class BiasMock(MasterMock):
846 """Simulated master bias calibration.
847 """
848 def __init__(self, **kwargs):
849 super().__init__(**kwargs)
850 self.config.doAddBias = True
851 self.config.readNoise = 10.0
854class DarkMock(MasterMock):
855 """Simulated master dark calibration.
856 """
857 def __init__(self, **kwargs):
858 super().__init__(**kwargs)
859 self.config.doAddDark = True
860 self.config.darkTime = 1.0
863class FlatMock(MasterMock):
864 """Simulated master flat calibration.
865 """
866 def __init__(self, **kwargs):
867 super().__init__(**kwargs)
868 self.config.doAddFlat = True
871class FringeMock(MasterMock):
872 """Simulated master fringe calibration.
873 """
874 def __init__(self, **kwargs):
875 super().__init__(**kwargs)
876 self.config.doAddFringe = True
879class UntrimmedFringeMock(FringeMock):
880 """Simulated untrimmed master fringe calibration.
881 """
882 def __init__(self, **kwargs):
883 super().__init__(**kwargs)
884 self.config.isTrimmed = False
887class BfKernelMock(IsrMock):
888 """Simulated brighter-fatter kernel.
889 """
890 def __init__(self, **kwargs):
891 super().__init__(**kwargs)
892 self.config.doGenerateImage = False
893 self.config.doGenerateData = True
894 self.config.doBrighterFatter = True
895 self.config.doDefects = False
896 self.config.doCrosstalkCoeffs = False
897 self.config.doTransmissionCurve = False
900class DefectMock(IsrMock):
901 """Simulated defect list.
902 """
903 def __init__(self, **kwargs):
904 super().__init__(**kwargs)
905 self.config.doGenerateImage = False
906 self.config.doGenerateData = True
907 self.config.doBrighterFatter = False
908 self.config.doDefects = True
909 self.config.doCrosstalkCoeffs = False
910 self.config.doTransmissionCurve = False
913class CrosstalkCoeffMock(IsrMock):
914 """Simulated crosstalk coefficient matrix.
915 """
916 def __init__(self, **kwargs):
917 super().__init__(**kwargs)
918 self.config.doGenerateImage = False
919 self.config.doGenerateData = True
920 self.config.doBrighterFatter = False
921 self.config.doDefects = False
922 self.config.doCrosstalkCoeffs = True
923 self.config.doTransmissionCurve = False
926class TransmissionMock(IsrMock):
927 """Simulated transmission curve.
928 """
929 def __init__(self, **kwargs):
930 super().__init__(**kwargs)
931 self.config.doGenerateImage = False
932 self.config.doGenerateData = True
933 self.config.doBrighterFatter = False
934 self.config.doDefects = False
935 self.config.doCrosstalkCoeffs = False
936 self.config.doTransmissionCurve = True
939class DataRefMock(object):
940 """Simulated gen2 butler data ref.
942 Currently only supports get and put operations, which are most
943 likely to be called for data in ISR processing.
945 """
946 dataId = "isrMock Fake Data"
947 darkval = 2. # e-/sec
948 oscan = 250. # DN
949 gradient = .10
950 exptime = 15.0 # seconds
951 darkexptime = 15.0 # seconds
953 def __init__(self, **kwargs):
954 if 'config' in kwargs.keys():
955 self.config = kwargs['config']
956 else:
957 self.config = None
959 def expectImage(self):
960 if self.config is None:
961 self.config = IsrMockConfig()
962 self.config.doGenerateImage = True
963 self.config.doGenerateData = False
965 def expectData(self):
966 if self.config is None:
967 self.config = IsrMockConfig()
968 self.config.doGenerateImage = False
969 self.config.doGenerateData = True
971 def get(self, dataType, **kwargs):
972 """Return an appropriate data product.
974 Parameters
975 ----------
976 dataType : `str`
977 Type of data product to return.
979 Returns
980 -------
981 mock : IsrMock.run() result
982 The output product.
983 """
984 if "_filename" in dataType:
985 self.expectData()
986 return tempfile.mktemp(), "mock"
987 elif 'transmission_' in dataType:
988 self.expectData()
989 return TransmissionMock(config=self.config).run()
990 elif dataType == 'ccdExposureId':
991 self.expectData()
992 return 20090913
993 elif dataType == 'camera':
994 self.expectData()
995 return IsrMock(config=self.config).getCamera()
996 elif dataType == 'raw':
997 self.expectImage()
998 return RawMock(config=self.config).run()
999 elif dataType == 'bias':
1000 self.expectImage()
1001 return BiasMock(config=self.config).run()
1002 elif dataType == 'dark':
1003 self.expectImage()
1004 return DarkMock(config=self.config).run()
1005 elif dataType == 'flat':
1006 self.expectImage()
1007 return FlatMock(config=self.config).run()
1008 elif dataType == 'fringe':
1009 self.expectImage()
1010 return FringeMock(config=self.config).run()
1011 elif dataType == 'defects':
1012 self.expectData()
1013 return DefectMock(config=self.config).run()
1014 elif dataType == 'bfKernel':
1015 self.expectData()
1016 return BfKernelMock(config=self.config).run()
1017 elif dataType == 'linearizer':
1018 return None
1019 elif dataType == 'crosstalkSources':
1020 return None
1021 else:
1022 raise RuntimeError("ISR DataRefMock cannot return %s.", dataType)
1024 def put(self, exposure, filename):
1025 """Write an exposure to a FITS file.
1027 Parameters
1028 ----------
1029 exposure : `lsst.afw.image.Exposure`
1030 Image data to write out.
1031 filename : `str`
1032 Base name of the output file.
1033 """
1034 exposure.writeFits(filename+".fits")
1037class FringeDataRefMock(object):
1038 """Simulated gen2 butler data ref.
1040 Currently only supports get and put operations, which are most
1041 likely to be called for data in ISR processing.
1043 """
1044 dataId = "isrMock Fake Data"
1045 darkval = 2. # e-/sec
1046 oscan = 250. # DN
1047 gradient = .10
1048 exptime = 15 # seconds
1049 darkexptime = 40. # seconds
1051 def __init__(self, **kwargs):
1052 if 'config' in kwargs.keys():
1053 self.config = kwargs['config']
1054 else:
1055 self.config = IsrMockConfig()
1056 self.config.isTrimmed = True
1057 self.config.doAddFringe = True
1058 self.config.readNoise = 10.0
1060 def get(self, dataType, **kwargs):
1061 """Return an appropriate data product.
1063 Parameters
1064 ----------
1065 dataType : `str`
1066 Type of data product to return.
1068 Returns
1069 -------
1070 mock : IsrMock.run() result
1071 The output product.
1072 """
1073 if "_filename" in dataType:
1074 return tempfile.mktemp(), "mock"
1075 elif 'transmission_' in dataType:
1076 return TransmissionMock(config=self.config).run()
1077 elif dataType == 'ccdExposureId':
1078 return 20090913
1079 elif dataType == 'camera':
1080 return IsrMock(config=self.config).getCamera()
1081 elif dataType == 'raw':
1082 return CalibratedRawMock(config=self.config).run()
1083 elif dataType == 'bias':
1084 return BiasMock(config=self.config).run()
1085 elif dataType == 'dark':
1086 return DarkMock(config=self.config).run()
1087 elif dataType == 'flat':
1088 return FlatMock(config=self.config).run()
1089 elif dataType == 'fringe':
1090 fringes = []
1091 configCopy = copy.deepcopy(self.config)
1092 for scale, x, y in zip(self.config.fringeScale, self.config.fringeX0, self.config.fringeY0):
1093 configCopy.fringeScale = [1.0]
1094 configCopy.fringeX0 = [x]
1095 configCopy.fringeY0 = [y]
1096 fringes.append(FringeMock(config=configCopy).run())
1097 return fringes
1098 elif dataType == 'defects':
1099 return DefectMock(config=self.config).run()
1100 elif dataType == 'bfKernel':
1101 return BfKernelMock(config=self.config).run()
1102 elif dataType == 'linearizer':
1103 return None
1104 elif dataType == 'crosstalkSources':
1105 return None
1106 else:
1107 return None
1109 def put(self, exposure, filename):
1110 """Write an exposure to a FITS file.
1112 Parameters
1113 ----------
1114 exposure : `lsst.afw.image.Exposure`
1115 Image data to write out.
1116 filename : `str`
1117 Base name of the output file.
1118 """
1119 exposure.writeFits(filename+".fits")