Coverage for tests/test_SdssShape.py: 21%
164 statements
« prev ^ index » next coverage.py v6.5.0, created at 2023-04-07 01:31 -0700
« prev ^ index » next coverage.py v6.5.0, created at 2023-04-07 01:31 -0700
1# This file is part of meas_base.
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 unittest
24import numpy as np
26import lsst.geom
27import lsst.afw.geom
28import lsst.afw.table
29import lsst.meas.base
30import lsst.meas.base.tests
31import lsst.utils.tests
34class SdssShapeTestCase(lsst.meas.base.tests.AlgorithmTestCase, lsst.utils.tests.TestCase):
36 def setUp(self):
37 self.bbox = lsst.geom.Box2I(lsst.geom.Point2I(-20, -30),
38 lsst.geom.Extent2I(240, 160))
39 self.dataset = lsst.meas.base.tests.TestDataset(self.bbox)
40 # first source is a point
41 self.dataset.addSource(100000.0, lsst.geom.Point2D(50.1, 49.8))
42 # second source is extended
43 self.dataset.addSource(100000.0, lsst.geom.Point2D(149.9, 50.3),
44 lsst.afw.geom.Quadrupole(8, 9, 3))
45 self.config = self.makeSingleFrameMeasurementConfig("base_SdssShape")
47 def tearDown(self):
48 del self.bbox
49 del self.dataset
50 del self.config
52 def makeAlgorithm(self, ctrl=None):
53 """Construct an algorithm and return both it and its schema.
54 """
55 if ctrl is None:
56 ctrl = lsst.meas.base.SdssShapeControl()
57 schema = lsst.meas.base.tests.TestDataset.makeMinimalSchema()
58 algorithm = lsst.meas.base.SdssShapeAlgorithm(ctrl, "base_SdssShape", schema)
59 return algorithm, schema
61 def assertFinite(self, value):
62 self.assertTrue(np.isfinite(value), msg="%s is not finite" % (value,))
64 def _runMeasurementTask(self):
65 task = self.makeSingleFrameMeasurementTask("base_SdssShape", config=self.config)
66 exposure, catalog = self.dataset.realize(10.0, task.schema, randomSeed=0)
67 task.run(catalog, exposure)
68 return exposure, catalog
70 def _checkShape(self, result, record):
71 self.assertFloatsAlmostEqual(result.x, record.get("truth_x"), rtol=1E-2)
72 self.assertFloatsAlmostEqual(result.y, record.get("truth_y"), rtol=1E-2)
73 self.assertFloatsAlmostEqual(result.xx, record.get("truth_xx"), rtol=1E-2)
74 self.assertFloatsAlmostEqual(result.yy, record.get("truth_yy"), rtol=1E-2)
75 self.assertFloatsAlmostEqual(result.xy, record.get("truth_xy"), rtol=1E-1, atol=2E-1)
76 self.assertFinite(result.xxErr)
77 self.assertFinite(result.yyErr)
78 self.assertFinite(result.xyErr)
79 self.assertFinite(result.instFlux_xx_Cov)
80 self.assertFinite(result.instFlux_yy_Cov)
81 self.assertFinite(result.instFlux_xy_Cov)
82 self.assertFinite(result.xx_yy_Cov)
83 self.assertFinite(result.xx_xy_Cov)
84 self.assertFinite(result.yy_xy_Cov)
85 self.assertFalse(result.getFlag(lsst.meas.base.SdssShapeAlgorithm.FAILURE.number))
86 self.assertFalse(result.getFlag(lsst.meas.base.SdssShapeAlgorithm.UNWEIGHTED_BAD.number))
87 self.assertFalse(result.getFlag(lsst.meas.base.SdssShapeAlgorithm.UNWEIGHTED.number))
88 self.assertFalse(result.getFlag(lsst.meas.base.SdssShapeAlgorithm.SHIFT.number))
89 self.assertFalse(result.getFlag(lsst.meas.base.SdssShapeAlgorithm.MAXITER.number))
91 def _checkPsfShape(self, result, psfResult, psfTruth):
92 self.assertFloatsAlmostEqual(psfResult.getIxx(), psfTruth.getIxx(), rtol=1E-4)
93 self.assertFloatsAlmostEqual(psfResult.getIyy(), psfTruth.getIyy(), rtol=1E-4)
94 self.assertFloatsAlmostEqual(psfResult.getIxy(), psfTruth.getIxy(), rtol=1E-4)
95 self.assertFalse(result.getFlag(lsst.meas.base.SdssShapeAlgorithm.PSF_SHAPE_BAD.number))
97 def testMeasureGoodPsf(self):
98 """Test that we measure shapes and record the PSF shape correctly
100 Note: Given that the PSF model here is constant over the entire image, this test
101 would not catch an error in the potition at which base_SdssShape_psf is computed.
102 Such a test requires a spatially varying PSF model such that different locations
103 can be distinguished by their different PSF model shapes. Such a test exists in
104 meas_algorithms (tests/testSdssShapePsf.py), making use of the PcaPsf algorithm
105 to build the spatially varying PSF.
106 """
107 exposure, catalog = self._runMeasurementTask()
108 key = lsst.meas.base.SdssShapeResultKey(catalog.schema["base_SdssShape"])
109 psfTruth = exposure.getPsf().computeShape(catalog[0].getCentroid())
110 for record in catalog:
111 result = record.get(key)
112 self._checkShape(result, record)
113 psfResult = key.getPsfShape(record)
114 self._checkPsfShape(result, psfResult, psfTruth)
116 def testMeasureWithoutPsf(self):
117 """Test that we measure shapes correctly and do not record the PSF shape when not needed."""
118 self.config.plugins["base_SdssShape"].doMeasurePsf = False
119 _, catalog = self._runMeasurementTask()
120 key = lsst.meas.base.SdssShapeResultKey(catalog.schema["base_SdssShape"])
121 for record in catalog:
122 result = record.get(key)
123 self._checkShape(result, record)
124 self.assertNotIn("base_SdssShape_psf_xx", catalog.schema)
125 self.assertNotIn("base_SdssShape_psf_yy", catalog.schema)
126 self.assertNotIn("base_SdssShape_psf_xy", catalog.schema)
127 self.assertNotIn("base_SdssShape_flag_psf", catalog.schema)
129 def testMeasureBadPsf(self):
130 """Test that we measure shapes correctly and set a flag with the PSF is unavailable."""
131 self.config.plugins["base_SdssShape"].doMeasurePsf = True
132 task = self.makeSingleFrameMeasurementTask("base_SdssShape", config=self.config)
133 exposure, catalog = self.dataset.realize(10.0, task.schema, randomSeed=1)
134 exposure.setPsf(None) # Set PSF to None to test no PSF case
135 task.run(catalog, exposure)
136 key = lsst.meas.base.SdssShapeResultKey(catalog.schema["base_SdssShape"])
137 for record in catalog:
138 result = record.get(key)
139 self._checkShape(result, record)
140 self.assertTrue(result.getFlag(lsst.meas.base.SdssShapeAlgorithm.PSF_SHAPE_BAD.number))
142 def testMonteCarlo(self):
143 """Test an ideal simulation, with deterministic noise.
145 Demonstrate that:
147 - We get the right answer, and
148 - The reported uncertainty agrees with a Monte Carlo test of the noise.
149 """
150 algorithm, schema = self.makeAlgorithm()
151 # Results are RNG dependent; we choose a seed that is known to pass.
152 exposure, cat = self.dataset.realize(0.0, schema, randomSeed=3)
153 record = cat[1]
154 instFlux = record["truth_instFlux"]
155 algorithm.measure(record, exposure)
156 for suffix in ["xx", "yy", "xy"]:
157 self.assertFloatsAlmostEqual(record.get("truth_"+suffix),
158 record.get("base_SdssShape_"+suffix), rtol=1E-4)
160 for noise in (0.0001, 0.001,):
161 nSamples = 1000
162 catalog = lsst.afw.table.SourceCatalog(cat.schema)
163 for i in range(nSamples):
164 # By using ``i`` to seed the RNG, we get results which
165 # fall within the tolerances defined below. If we allow this
166 # test to be truly random, passing becomes RNG-dependent.
167 exposure, cat = self.dataset.realize(noise*instFlux, schema, randomSeed=i)
168 record = cat[1]
169 algorithm.measure(record, exposure)
170 catalog.append(record)
172 catalog = catalog.copy(deep=True)
173 for suffix in ["xx", "yy", "xy"]:
174 shapeMean = np.mean(catalog["base_SdssShape_"+suffix])
175 shapeErrMean = np.nanmean(catalog["base_SdssShape_"+suffix+"Err"])
176 shapeInterval68 = 0.5*(np.nanpercentile(catalog["base_SdssShape_"+suffix], 84)
177 - np.nanpercentile(catalog["base_SdssShape_"+suffix], 16))
178 self.assertFloatsAlmostEqual(np.nanstd(catalog["base_SdssShape_"+suffix]),
179 shapeInterval68, rtol=0.03)
180 self.assertFloatsAlmostEqual(shapeErrMean, shapeInterval68, rtol=0.03)
181 self.assertLess(abs(shapeMean - record.get("truth_"+suffix)), 2.0*shapeErrMean/nSamples**0.5)
184class SdssShapeTransformTestCase(lsst.meas.base.tests.FluxTransformTestCase,
185 lsst.meas.base.tests.CentroidTransformTestCase,
186 lsst.meas.base.tests.SingleFramePluginTransformSetupHelper,
187 lsst.utils.tests.TestCase):
189 name = "sdssShape"
190 controlClass = lsst.meas.base.SdssShapeControl
191 algorithmClass = lsst.meas.base.SdssShapeAlgorithm
192 transformClass = lsst.meas.base.SdssShapeTransform
193 flagNames = ("flag", "flag_unweighted", "flag_unweightedBad", "flag_shift", "flag_maxIter")
194 singleFramePlugins = ('base_SdssShape',)
195 forcedPlugins = ('base_SdssShape',)
196 testPsf = True
198 def _setFieldsInRecords(self, records, name):
199 lsst.meas.base.tests.FluxTransformTestCase._setFieldsInRecords(self, records, name)
200 lsst.meas.base.tests.CentroidTransformTestCase._setFieldsInRecords(self, records, name)
201 for record in records:
202 for field in ('xx', 'yy', 'xy', 'xxErr', 'yyErr', 'xyErr', 'psf_xx', 'psf_yy', 'psf_xy'):
203 if record.schema.join(name, field) in record.schema:
204 record[record.schema.join(name, field)] = np.random.random()
206 def _compareFieldsInRecords(self, inSrc, outSrc, name):
207 lsst.meas.base.tests.FluxTransformTestCase._compareFieldsInRecords(self, inSrc, outSrc, name)
208 lsst.meas.base.tests.CentroidTransformTestCase._compareFieldsInRecords(self, inSrc, outSrc, name)
210 inShape = lsst.meas.base.ShapeResultKey(inSrc.schema[name]).get(inSrc)
211 outShape = lsst.meas.base.ShapeResultKey(outSrc.schema[name]).get(outSrc)
213 centroid = lsst.meas.base.CentroidResultKey(inSrc.schema[name]).get(inSrc).getCentroid()
214 xform = self.calexp.getWcs().linearizePixelToSky(centroid, lsst.geom.radians)
216 trInShape = inShape.getShape().transform(xform.getLinear())
217 self.assertEqual(trInShape.getIxx(), outShape.getShape().getIxx())
218 self.assertEqual(trInShape.getIyy(), outShape.getShape().getIyy())
219 self.assertEqual(trInShape.getIxy(), outShape.getShape().getIxy())
221 m = lsst.meas.base.makeShapeTransformMatrix(xform.getLinear())
222 np.testing.assert_array_almost_equal(
223 np.dot(np.dot(m, inShape.getShapeErr()), m.transpose()), outShape.getShapeErr()
224 )
225 if self.testPsf:
226 inPsfShape = lsst.meas.base.ShapeResultKey(
227 inSrc.schema[inSrc.schema.join(name, "psf")]
228 ).get(inSrc)
229 outPsfShape = lsst.meas.base.ShapeResultKey(
230 outSrc.schema[outSrc.schema.join(name, "psf")]
231 ).get(outSrc)
232 trInPsfShape = inPsfShape.getShape().transform(xform.getLinear())
234 self.assertEqual(trInPsfShape.getIxx(), outPsfShape.getShape().getIxx())
235 self.assertEqual(trInPsfShape.getIyy(), outPsfShape.getShape().getIyy())
236 self.assertEqual(trInPsfShape.getIxy(), outPsfShape.getShape().getIxy())
237 else:
238 self.assertNotIn(inSrc.schema.join(name, "psf", "xx"), inSrc.schema)
239 self.assertNotIn(inSrc.schema.join(name, "flag", "psf"), inSrc.schema)
242class PsfSdssShapeTransformTestCase(SdssShapeTransformTestCase, lsst.utils.tests.TestCase):
243 testPsf = False
245 def makeSdssShapeControl(self):
246 ctrl = lsst.meas.base.SdssShapeControl()
247 ctrl.doMeasurePsf = False
248 return ctrl
249 controlClass = makeSdssShapeControl
252class TestMemory(lsst.utils.tests.MemoryTestCase):
253 pass
256def setup_module(module):
257 lsst.utils.tests.init()
260if __name__ == "__main__": 260 ↛ 261line 260 didn't jump to line 261, because the condition on line 260 was never true
261 lsst.utils.tests.init()
262 unittest.main()