Coverage for tests/test_coadds.py: 20%
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1# This file is part of cell_coadds.
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5# (https://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
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22import unittest
23from collections.abc import Iterable, Mapping
24from itertools import product
26import numpy as np
27from frozendict import frozendict
29import lsst.cell_coadds.test_utils as test_utils
30import lsst.geom as geom
31import lsst.meas.base.tests
32import lsst.utils.tests
33from lsst.afw.geom import Quadrupole
34from lsst.afw.image import ExposureF, ImageF
35from lsst.cell_coadds import (
36 CellCoaddFitsReader,
37 CellIdentifiers,
38 CoaddUnits,
39 CommonComponents,
40 ExplodedCoadd,
41 MultipleCellCoadd,
42 ObservationIdentifiers,
43 OwnedImagePlanes,
44 PatchIdentifiers,
45 SingleCellCoadd,
46 StitchedCoadd,
47 UniformGrid,
48)
49from lsst.meas.algorithms import SingleGaussianPsf
50from lsst.skymap import Index2D
53class BaseMultipleCellCoaddTestCase(lsst.utils.tests.TestCase):
54 """A base class that provides a common set of methods."""
56 psf_size: int
57 psf_sigmas: Mapping[Index2D, float]
58 border_size: int
59 inner_size: int
60 outer_size: int
61 test_positions: Iterable[tuple[geom.Point2D, Index2D]]
62 exposures: Mapping[Index2D, ExposureF]
63 multiple_cell_coadd: MultipleCellCoadd
65 @classmethod
66 def setUpClass(cls) -> None:
67 """Set up a multiple cell coadd with 2x2 cells."""
68 np.random.seed(42)
69 data_id = test_utils.generate_data_id()
70 common = CommonComponents(
71 units=CoaddUnits.nJy, # units here are arbitrary.
72 wcs=test_utils.generate_wcs(),
73 band=data_id["band"],
74 identifiers=PatchIdentifiers.from_data_id(data_id),
75 )
77 cls.nx, cls.ny = 3, 2
78 cls.psf_sigmas = {
79 Index2D(x=0, y=0): 1.2,
80 Index2D(x=0, y=1): 0.7,
81 Index2D(x=1, y=0): 0.9,
82 Index2D(x=1, y=1): 1.1,
83 Index2D(x=2, y=0): 1.3,
84 Index2D(x=2, y=1): 0.8,
85 }
87 cls.border_size = 5
88 # In practice, we expect this to be squares.
89 # To check for any possible x, y swap, we use different values.
90 cls.psf_size_x, cls.psf_size_y = 21, 23
91 cls.inner_size_x, cls.inner_size_y = 17, 15
92 cls.outer_size_x = cls.inner_size_x + 2 * cls.border_size
93 cls.outer_size_y = cls.inner_size_y + 2 * cls.border_size
94 # The origin should not be at (0, 0) for robust testing.
95 cls.x0, cls.y0 = 5, 2
96 cls.n_noise_realizations = 2
98 patch_outer_bbox = geom.Box2I(
99 geom.Point2I(cls.x0, cls.y0), geom.Extent2I(cls.nx * cls.inner_size_x, cls.ny * cls.inner_size_y)
100 )
101 patch_outer_bbox.grow(cls.border_size)
103 # Add one star and one galaxy per quadrant.
104 # The mapping of positions to cell indices assume inner_size = (17, 15)
105 # and border_size = 5. If that is changed, these values need an update.
106 sources = (
107 # flux, centroid, shape
108 (1000.0, geom.Point2D(cls.x0 + 6.3, cls.y0 + 7.2), None),
109 (2500.0, geom.Point2D(cls.x0 + 16.8, cls.y0 + 18.3), None),
110 (1500.0, geom.Point2D(cls.x0 + 21.2, cls.y0 + 5.1), None),
111 (3200.0, geom.Point2D(cls.x0 + 16.1, cls.y0 + 23.9), None),
112 (1800.0, geom.Point2D(cls.x0 + 44.7, cls.y0 + 8.9), None),
113 (2100.0, geom.Point2D(cls.x0 + 34.1, cls.y0 + 19.2), None),
114 (900.0, geom.Point2D(cls.x0 + 9.1, cls.y0 + 13.9), Quadrupole(2.5, 1.5, 0.8)),
115 (1250.0, geom.Point2D(cls.x0 + 19.3, cls.y0 + 11.2), Quadrupole(1.5, 2.5, 0.75)),
116 (2100.0, geom.Point2D(cls.x0 + 5.1, cls.y0 + 21.2), Quadrupole(1.7, 1.9, 0.05)),
117 (2800.0, geom.Point2D(cls.x0 + 24.1, cls.y0 + 19.2), Quadrupole(1.9, 1.7, 0.1)),
118 (2350.0, geom.Point2D(cls.x0 + 40.3, cls.y0 + 13.9), Quadrupole(1.8, 1.8, -0.4)),
119 (4999.0, geom.Point2D(cls.x0 + 45.8, cls.y0 + 22.0), Quadrupole(1.6, 1.2, 0.2)),
120 )
122 # The test points are chosen to cover various corner cases assuming
123 # inner_size = (17, 15) and border_size = 5. If that is changed, the
124 # test points should be updated to not fall outside the coadd and still
125 # cover the description in the inline comments. This is checked below.
126 test_points = (
127 geom.Point2D(cls.x0 + 5, cls.y0 + 4), # inner point in lower left
128 geom.Point2D(cls.x0 + 6, cls.y0 + 24), # inner point in upper left
129 geom.Point2D(cls.x0 + 25.2, cls.y0 + 7.8), # inner point in lower middle
130 geom.Point2D(cls.x0 + 23, cls.y0 + 22), # inner point in upper middle
131 geom.Point2D(cls.x0 + 39, cls.y0 + 9.4), # inner point in lower right
132 geom.Point2D(cls.x0 + 44, cls.y0 + 24), # inner point in upper right
133 # Some points that lie on the border
134 geom.Point2D(cls.x0 + 33, cls.y0 + 24), # inner point in upper right
135 geom.Point2D(cls.x0 + 46, cls.y0 + 0), # inner point in lower right
136 geom.Point2D(cls.x0 + 19, cls.y0 + 16), # inner point in upper middle
137 geom.Point2D(cls.x0 + 17, cls.y0 + 8), # inner point in lower middle
138 geom.Point2D(cls.x0 + 0, cls.y0 + 29), # inner point in upper left
139 geom.Point2D(cls.x0 + 0, cls.y0 + 0), # inner point in lower left
140 )
141 # A list of (point, cell_index) pairs.
142 cls.test_positions = [
143 (
144 point,
145 Index2D(
146 x=int((point.getX() - cls.x0) // cls.inner_size_x),
147 y=int((point.getY() - cls.y0) // cls.inner_size_y),
148 ),
149 )
150 for point in test_points
151 ]
153 schema = lsst.meas.base.tests.TestDataset.makeMinimalSchema()
155 single_cell_coadds = []
156 cls.exposures = dict.fromkeys(cls.psf_sigmas.keys())
158 for x in range(cls.nx):
159 for y in range(cls.ny):
160 identifiers = CellIdentifiers(
161 cell=Index2D(x=x, y=y),
162 skymap=common.identifiers.skymap,
163 tract=common.identifiers.tract,
164 patch=common.identifiers.patch,
165 band=common.identifiers.band,
166 )
168 outer_bbox = geom.Box2I(
169 geom.Point2I(cls.x0 + x * cls.inner_size_x, cls.y0 + y * cls.inner_size_y),
170 geom.Extent2I(cls.inner_size_x, cls.inner_size_y),
171 )
172 outer_bbox.grow(cls.border_size)
174 dataset = lsst.meas.base.tests.TestDataset(
175 patch_outer_bbox, psfSigma=cls.psf_sigmas[identifiers.cell]
176 )
178 for inst_flux, position, shape in sources:
179 dataset.addSource(inst_flux, position, shape)
181 # Create a spatially varying variance plane.
182 variance = ImageF(
183 # np.random.uniform returns an array with x-y flipped.
184 np.random.uniform(
185 0.8,
186 1.2,
187 (
188 cls.ny * cls.inner_size_y + 2 * cls.border_size,
189 cls.nx * cls.inner_size_x + 2 * cls.border_size,
190 ),
191 ).astype(np.float32),
192 xy0=outer_bbox.getMin(),
193 )
194 noise_realizations = [
195 ImageF(
196 np.random.normal(
197 0.0,
198 1.0,
199 (
200 cls.ny * cls.inner_size_y + 2 * cls.border_size,
201 cls.nx * cls.inner_size_x + 2 * cls.border_size,
202 ),
203 ).astype(np.float32)
204 * variance.array,
205 xy0=outer_bbox.getMin(),
206 )
207 for _ in range(cls.n_noise_realizations)
208 ]
209 mask_fraction = ImageF(
210 np.random.uniform(
211 0.0,
212 1.0,
213 (
214 cls.ny * cls.inner_size_y + 2 * cls.border_size,
215 cls.nx * cls.inner_size_x + 2 * cls.border_size,
216 ),
217 ).astype(np.float32),
218 xy0=outer_bbox.getMin(),
219 )
220 exposure, _ = dataset.realize(variance.getArray() ** 0.5, schema, randomSeed=123456789)
221 cls.exposures[identifiers.cell] = exposure
222 exposure = exposure[outer_bbox]
223 image_plane = OwnedImagePlanes(
224 image=exposure.image,
225 variance=exposure.variance,
226 mask=exposure.mask,
227 noise_realizations=noise_realizations,
228 mask_fractions=mask_fraction,
229 )
230 aperture_correction_map = frozendict(
231 base_GaussianFlux_instFlux=0.9 * (x + 1),
232 base_GaussianFlux_instFluxErr=0.01 * (y + 1),
233 base_PsfFlux_instFlux=0.8 * (y + 2),
234 base_PsfFlux_instFluxErr=0.02 * (x + 2),
235 )
237 single_cell_coadds.append(
238 SingleCellCoadd(
239 outer=image_plane,
240 psf=SingleGaussianPsf(
241 cls.psf_size_x, cls.psf_size_y, cls.psf_sigmas[Index2D(x=x, y=y)]
242 ).computeKernelImage(outer_bbox.getCenter()),
243 inner_bbox=geom.Box2I(
244 geom.Point2I(cls.x0 + x * cls.inner_size_x, cls.y0 + y * cls.inner_size_y),
245 geom.Extent2I(cls.inner_size_x, cls.inner_size_y),
246 ),
247 inputs=(
248 ObservationIdentifiers(
249 instrument="dummy",
250 physical_filter="dummy-I",
251 visit=12345,
252 detector=67,
253 day_obs=20000101,
254 ),
255 ),
256 common=common,
257 identifiers=identifiers,
258 aperture_correction_map=aperture_correction_map,
259 )
260 )
262 grid_bbox = geom.Box2I(
263 geom.Point2I(cls.x0, cls.y0), geom.Extent2I(cls.nx * cls.inner_size_x, cls.ny * cls.inner_size_y)
264 )
265 grid = UniformGrid.from_bbox_shape(grid_bbox, Index2D(x=cls.nx, y=cls.ny), padding=cls.border_size)
267 for test_point, test_index in cls.test_positions:
268 assert test_index == grid.index(
269 geom.Point2I(test_point)
270 ), f"Test point {test_point} is not in cell {test_index}."
272 cls.multiple_cell_coadd = MultipleCellCoadd(
273 single_cell_coadds,
274 grid=grid,
275 outer_cell_size=geom.Extent2I(cls.outer_size_x, cls.outer_size_y),
276 inner_bbox=None,
277 common=common,
278 psf_image_size=geom.Extent2I(cls.psf_size_x, cls.psf_size_y),
279 )
281 @classmethod
282 def tearDownClass(cls) -> None: # noqa: D102
283 # Docstring inherited
284 del cls.multiple_cell_coadd
285 del cls.exposures
286 super().tearDownClass()
288 def assertMultipleCellCoaddsEqual(self, mcc1: MultipleCellCoadd, mcc2: MultipleCellCoadd) -> None:
289 """Check the equality of two instances of `MultipleCellCoadd`.
291 Parameters
292 ----------
293 mcc1 : `MultipleCellCoadd`
294 The MultipleCellCoadd created by reading a FITS file.
295 mcc2 : `MultipleCellCoadd`
296 The reference MultipleCellCoadd for comparison.
297 """
298 self.assertEqual(mcc1.band, mcc2.band)
299 self.assertEqual(mcc1.identifiers, mcc2.identifiers)
300 self.assertEqual(mcc1.inner_bbox, mcc2.inner_bbox)
301 self.assertEqual(mcc1.outer_bbox, mcc2.outer_bbox)
302 self.assertEqual(mcc1.outer_cell_size, mcc2.outer_cell_size)
303 self.assertEqual(mcc1.grid, mcc2.grid)
304 self.assertEqual(mcc1.mask_fraction_names, mcc2.mask_fraction_names)
305 self.assertEqual(mcc1.n_noise_realizations, mcc2.n_noise_realizations)
306 self.assertEqual(mcc1.psf_image_size, mcc2.psf_image_size)
307 self.assertEqual(mcc1.units, mcc2.units)
308 self.assertEqual(mcc1.wcs.getFitsMetadata().toString(), mcc2.wcs.getFitsMetadata().toString())
310 # Check that the individual cells are identical.
311 self.assertEqual(mcc1.cells.keys(), mcc2.cells.keys())
312 for idx in mcc1.cells.keys(): # noqa: SIM118
313 self.assertImagesEqual(mcc1.cells[idx].outer.image, mcc2.cells[idx].outer.image)
314 self.assertMasksEqual(mcc1.cells[idx].outer.mask, mcc2.cells[idx].outer.mask)
315 self.assertImagesEqual(mcc1.cells[idx].outer.variance, mcc2.cells[idx].outer.variance)
316 self.assertImagesEqual(mcc1.cells[idx].outer.mask_fractions, mcc2.cells[idx].outer.mask_fractions)
317 self.assertEqual(
318 len(mcc1.cells[idx].outer.noise_realizations), len(mcc2.cells[idx].outer.noise_realizations)
319 )
320 for noise_id in range(len(mcc1.cells[idx].outer.noise_realizations)):
321 with self.subTest(noise_id):
322 self.assertImagesEqual(
323 mcc1.cells[idx].outer.noise_realizations[noise_id],
324 mcc2.cells[idx].outer.noise_realizations[noise_id],
325 )
326 self.assertImagesEqual(mcc1.cells[idx].psf_image, mcc2.cells[idx].psf_image)
327 self.assertEqual(mcc1.cells[idx].inputs, mcc2.cells[idx].inputs)
329 self.assertEqual(mcc1.cells[idx].band, mcc1.band)
330 self.assertEqual(mcc1.cells[idx].common, mcc1.common)
331 self.assertEqual(mcc1.cells[idx].units, mcc2.units)
332 self.assertEqual(mcc1.cells[idx].wcs, mcc1.wcs)
333 self.assertEqual(mcc1.cells[idx].aperture_correction_map, mcc2.cells[idx].aperture_correction_map)
335 # Identifiers differ because of the ``cell`` component.
336 # Check the other attributes within the identifiers.
337 for attr in ("skymap", "tract", "patch", "band"):
338 self.assertEqual(getattr(mcc1.cells[idx].identifiers, attr), getattr(mcc1.identifiers, attr))
341class MultipleCellCoaddTestCase(BaseMultipleCellCoaddTestCase):
342 """Test the construction and interfaces of MultipleCellCoadd."""
344 def test_fits(self):
345 """Test that we can write a coadd to a FITS file and read it."""
346 with lsst.utils.tests.getTempFilePath(".fits") as filename:
347 self.multiple_cell_coadd.write_fits(filename)
348 mcc1 = MultipleCellCoadd.read_fits(filename) # Test the readFits method.
350 # Test the reader class.
351 reader = CellCoaddFitsReader(filename)
352 mcc2 = reader.readAsMultipleCellCoadd()
354 wcs = reader.readWcs()
356 self.assertMultipleCellCoaddsEqual(mcc1, self.multiple_cell_coadd)
357 self.assertMultipleCellCoaddsEqual(mcc2, self.multiple_cell_coadd)
358 # By transititve property of equality, mcc1 == mcc2.
360 self.assertEqual(self.multiple_cell_coadd.band, self.multiple_cell_coadd.common.band)
361 self.assertEqual(
362 wcs.getFitsMetadata().toString(), self.multiple_cell_coadd.wcs.getFitsMetadata().toString()
363 )
365 def test_visit_count(self):
366 """Test the visit_count method."""
367 # Since we don't simulate coaddition from multiple warps, the cells are
368 # all going to have just a single visit.
369 for cellId, singleCellCoadd in self.multiple_cell_coadd.cells.items():
370 with self.subTest(x=cellId.x, y=cellId.y):
371 self.assertEqual(singleCellCoadd.visit_count, 1)
373 def test_aperture_correction(self):
374 """Test the aperture correction values are what we expect."""
375 for cellId, single_cell_coadd in self.multiple_cell_coadd.cells.items():
376 with self.subTest(x=cellId.x, y=cellId.y):
377 ap_corr_map = single_cell_coadd.aperture_correction_map
378 self.assertIsNotNone(ap_corr_map)
379 self.assertEqual(ap_corr_map["base_GaussianFlux_instFlux"], 0.9 * (cellId.x + 1))
380 self.assertEqual(ap_corr_map["base_GaussianFlux_instFluxErr"], 0.01 * (cellId.y + 1))
381 self.assertEqual(ap_corr_map["base_PsfFlux_instFlux"], 0.8 * (cellId.y + 2))
382 self.assertEqual(ap_corr_map["base_PsfFlux_instFluxErr"], 0.02 * (cellId.x + 2))
385class ExplodedCoaddTestCase(BaseMultipleCellCoaddTestCase):
386 """Test the construction and methods of an ExplodedCoadd instance."""
388 exploded_coadd: ExplodedCoadd
390 @classmethod
391 def setUpClass(cls) -> None: # noqa: D102
392 # Docstring inherited
393 super().setUpClass()
394 cls.exploded_coadd = cls.multiple_cell_coadd.explode()
396 @classmethod
397 def tearDownClass(cls) -> None: # noqa: D102
398 # Docstring inherited
399 del cls.exploded_coadd
400 super().tearDownClass()
402 def test_exploded_psf_image(self):
403 """Show that psf_image sizes are absurd."""
404 self.assertEqual(
405 self.exploded_coadd.psf_image.getBBox().getDimensions(),
406 geom.Extent2I(self.nx * self.psf_size_x, self.ny * self.psf_size_y),
407 )
408 for pad_psfs_with in (-999, -4, 0, 4, 8, 21, 40, 100):
409 exploded_coadd = self.multiple_cell_coadd.explode(pad_psfs_with=pad_psfs_with)
410 self.assertEqual(
411 exploded_coadd.psf_image.getBBox().getDimensions(),
412 geom.Extent2I(self.nx * self.outer_size_x, self.ny * self.outer_size_y),
413 )
415 def test_asMaskedImage(self):
416 """Test the asMaskedImage method for an ExplodedCoadd object."""
417 masked_image = self.exploded_coadd.asMaskedImage()
418 masked_image.setXY0(self.multiple_cell_coadd.outer_bbox.getMin())
419 base_bbox = self.multiple_cell_coadd.cells.first.outer.bbox
420 for cell_x, cell_y in product(range(self.nx), range(self.ny)):
421 bbox = base_bbox.shiftedBy(geom.Extent2I(cell_x * self.outer_size_x, cell_y * self.outer_size_y))
422 with self.subTest(cell_x=cell_x, cell_y=cell_y):
423 self.assertMaskedImagesEqual(
424 masked_image[bbox],
425 self.multiple_cell_coadd.cells[Index2D(cell_x, cell_y)].outer.asMaskedImage(),
426 )
429class StitchedCoaddTestCase(BaseMultipleCellCoaddTestCase):
430 """Test the construction and methods of a StitchedCoadd instance."""
432 stitched_coadd: StitchedCoadd
434 @classmethod
435 def setUpClass(cls) -> None: # noqa: D102
436 # Docstring inherited
437 super().setUpClass()
438 cls.stitched_coadd = cls.multiple_cell_coadd.stitch()
440 @classmethod
441 def tearDownClass(cls) -> None: # noqa: D102
442 # Docstring inherited
443 del cls.stitched_coadd
444 super().tearDownClass()
446 def test_computeBBox(self):
447 """Test the computeBBox method for a StitchedPsf object."""
448 stitched_psf = self.stitched_coadd.psf
450 psf_bbox = geom.Box2I(
451 geom.Point2I(-(self.psf_size_x // 2), -(self.psf_size_y // 2)),
452 geom.Extent2I(self.psf_size_x, self.psf_size_y),
453 )
455 for position, _ in self.test_positions:
456 bbox = stitched_psf.computeBBox(position)
457 self.assertEqual(bbox, psf_bbox)
459 def test_computeShape(self):
460 """Test the computeShape method for a StitchedPsf object."""
461 stitched_psf = self.stitched_coadd.psf
462 for position, cell_index in self.test_positions:
463 psf_shape = stitched_psf.computeShape(position) # check we can compute shape
464 self.assertIsNot(psf_shape.getIxx(), np.nan)
465 self.assertIsNot(psf_shape.getIyy(), np.nan)
466 self.assertIsNot(psf_shape.getIxy(), np.nan)
468 # Moments measured from pixellated images are significantly
469 # underestimated for small PSFs.
470 if self.psf_sigmas[cell_index] >= 1.0:
471 self.assertAlmostEqual(psf_shape.getIxx(), self.psf_sigmas[cell_index] ** 2, delta=1e-3)
472 self.assertAlmostEqual(psf_shape.getIyy(), self.psf_sigmas[cell_index] ** 2, delta=1e-3)
473 self.assertAlmostEqual(psf_shape.getIxy(), 0.0)
475 def test_computeKernelImage(self):
476 """Test the computeKernelImage method for a StitchedPsf object."""
477 stitched_psf = self.stitched_coadd.psf
478 psf_bbox = geom.Box2I(
479 geom.Point2I(-(self.psf_size_x // 2), -(self.psf_size_y // 2)),
480 geom.Extent2I(self.psf_size_x, self.psf_size_y),
481 )
483 for position, cell_index in self.test_positions:
484 image1 = stitched_psf.computeKernelImage(position)
485 image2 = SingleGaussianPsf(
486 self.psf_size_x, self.psf_size_y, self.psf_sigmas[cell_index]
487 ).computeKernelImage(position)
488 self.assertImagesEqual(image1, image2)
489 self.assertEqual(image1.getBBox(), psf_bbox)
491 def test_computeImage(self):
492 """Test the computeImage method for a StitchedPsf object."""
493 stitched_psf = self.stitched_coadd.psf
494 psf_extent = geom.Extent2I(self.psf_size_x, self.psf_size_y)
496 for position, cell_index in self.test_positions:
497 image1 = stitched_psf.computeImage(position)
498 image2 = SingleGaussianPsf(
499 self.psf_size_x, self.psf_size_y, self.psf_sigmas[cell_index]
500 ).computeImage(position)
501 self.assertImagesEqual(image1, image2)
502 self.assertEqual(image1.getBBox().getDimensions(), psf_extent)
504 def test_computeImage_computeKernelImage(self):
505 """Test that computeImage called at integer points gives the same
506 result as calling computeKernelImage.
507 """
508 stitched_psf = self.stitched_coadd.psf
509 for position, _cell_index in self.test_positions:
510 pos = geom.Point2D(geom.Point2I(position)) # round to integer
511 image1 = stitched_psf.computeKernelImage(pos)
512 image2 = stitched_psf.computeImage(pos)
513 self.assertImagesEqual(image1, image2)
515 def test_computeApetureFlux(self):
516 """Test the computeApertureFlux method for a StitchedPsf object."""
517 stitched_psf = self.stitched_coadd.psf
518 for position, cell_index in self.test_positions:
519 flux1sigma = stitched_psf.computeApertureFlux(self.psf_sigmas[cell_index], position=position)
520 self.assertAlmostEqual(flux1sigma, 0.39, delta=5e-2)
522 flux3sigma = stitched_psf.computeApertureFlux(
523 3.0 * self.psf_sigmas[cell_index], position=position
524 )
525 self.assertAlmostEqual(flux3sigma, 0.97, delta=2e-2)
527 def test_asExposure(self):
528 """Test the asExposure method for a StitchedCoadd object."""
529 exposure = self.stitched_coadd.asExposure()
531 # Check that the bounding box is correct.
532 bbox = exposure.getBBox()
533 self.assertEqual(bbox.getWidth(), self.inner_size_x * self.nx + 2 * self.border_size)
534 self.assertEqual(bbox.getHeight(), self.inner_size_y * self.ny + 2 * self.border_size)
536 for y in range(self.ny):
537 for x in range(self.nx):
538 bbox = geom.Box2I(
539 geom.Point2I(self.x0 + x * self.inner_size_x, self.y0 + y * self.inner_size_y),
540 geom.Extent2I(self.inner_size_x, self.inner_size_y),
541 )
542 index = Index2D(x=x, y=y)
543 self.assertImagesEqual(exposure.image[bbox], self.exposures[index].image[bbox])
544 self.assertImagesEqual(exposure.variance[bbox], self.exposures[index].variance[bbox])
545 self.assertImagesEqual(exposure.mask[bbox], self.exposures[index].mask[bbox])
547 def test_aperture_correction(self):
548 """Test the aperture correction values are what we expect."""
549 ap_corr_map = self.stitched_coadd.ap_corr_map
550 algorithm_names = ap_corr_map.keys()
552 for (position, cellId), algorithm_name in product(self.test_positions, algorithm_names):
553 with self.subTest(x=cellId.x, y=cellId.y, algorithm_name=algorithm_name):
554 field_name = algorithm_name
555 self.assertEqual(
556 ap_corr_map[field_name].evaluate(position),
557 self.multiple_cell_coadd.cells[cellId].aperture_correction_map[field_name],
558 )
560 def test_inputs(self):
561 """Test that the inputs are populated correctly on stitching."""
562 inputs = self.stitched_coadd.ccds
563 for position, cellId in self.test_positions:
564 with self.subTest(x=cellId.x, y=cellId.y):
565 self.assertEqual(
566 inputs.subsetContaining(position),
567 self.multiple_cell_coadd.cells[cellId].inputs,
568 )
569 self.assertEqual(len(self.stitched_coadd.visits), 1)
571 def test_borders(self):
572 """Test that the borders are populated correctly on stitching."""
573 mi = self.stitched_coadd.asMaskedImage()
575 # Check that the borders are not all zero.
576 with self.assertRaises(AssertionError):
577 np.testing.assert_array_equal(mi.image.array[: self.border_size, :], 0)
578 with self.assertRaises(AssertionError):
579 np.testing.assert_array_equal(mi.image.array[-self.border_size :, :], 0)
580 with self.assertRaises(AssertionError):
581 np.testing.assert_array_equal(mi.image.array[:, : self.border_size], 0)
582 with self.assertRaises(AssertionError):
583 np.testing.assert_array_equal(mi.image.array[:, -self.border_size :], 0)
585 def test_fits(self):
586 """Test that we can write an Exposure with StitchedPsf to a FITS file
587 and read it.
588 """
589 write_exposure = self.stitched_coadd.asExposure()
590 with lsst.utils.tests.getTempFilePath(".fits") as filename:
591 write_exposure.writeFits(filename)
592 read_exposure = ExposureF.readFits(filename) # Test the readFits method.
594 # Test that the image planes are identical.
595 self.assertImagesEqual(read_exposure.image, write_exposure.image)
596 self.assertImagesEqual(read_exposure.variance, write_exposure.variance)
597 self.assertImagesEqual(read_exposure.mask, write_exposure.mask)
599 # Test the PSF images in the StitchedPsf.
600 for index in write_exposure.psf.images.indices():
601 self.assertImagesEqual(read_exposure.psf.images[index], write_exposure.psf.images[index])
603 # Test that the WCSs are equal.
604 self.assertEqual(
605 read_exposure.wcs.getFitsMetadata().toString(),
606 write_exposure.wcs.getFitsMetadata().toString(),
607 )
610class TestMemory(lsst.utils.tests.MemoryTestCase):
611 """Check for resource/memory leaks."""
614def setup_module(module): # noqa: D103
615 lsst.utils.tests.init()
618if __name__ == "__main__": 618 ↛ 619line 618 didn't jump to line 619 because the condition on line 618 was never true
619 lsst.utils.tests.init()
620 unittest.main()