Coverage for tests/ingestIndexTestBase.py : 97%

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1# This file is part of meas_algorithms.
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/>.
22__all__ = ["IngestIndexCatalogTestBase", "make_coord", "makeIngestIndexConfig"]
24import math
25import os.path
26import shutil
27import string
28import tempfile
30import numpy as np
31import astropy
32import astropy.units as u
34import lsst.daf.persistence as dafPersist
35from lsst.meas.algorithms import IndexerRegistry
36from lsst.meas.algorithms import IngestIndexedReferenceTask
37import lsst.utils
40def make_coord(ra, dec):
41 """Make an ICRS coord given its RA, Dec in degrees."""
42 return lsst.geom.SpherePoint(ra, dec, lsst.geom.degrees)
45def makeIngestIndexConfig(withMagErr=False, withRaDecErr=False, withPm=False, withPmErr=False,
46 withParallax=False):
47 """Make a config for IngestIndexedReferenceTask
49 This is primarily intended to simplify tests of config validation,
50 so fields that are not validated are not set.
51 However, it can calso be used to reduce boilerplate in other tests.
52 """
53 config = IngestIndexedReferenceTask.ConfigClass()
54 config.pm_scale = 1000.0
55 config.parallax_scale = 1e3
56 config.ra_name = 'ra_icrs'
57 config.dec_name = 'dec_icrs'
58 config.mag_column_list = ['a', 'b']
60 if withMagErr:
61 config.mag_err_column_map = {'a': 'a_err', 'b': 'b_err'}
63 if withRaDecErr:
64 config.ra_err_name = "ra_err"
65 config.dec_err_name = "dec_err"
66 config.coord_err_unit = "arcsecond"
68 if withPm:
69 config.pm_ra_name = "pm_ra"
70 config.pm_dec_name = "pm_dec"
72 if withPmErr:
73 config.pm_ra_err_name = "pm_ra_err"
74 config.pm_dec_err_name = "pm_dec_err"
76 if withParallax:
77 config.parallax_name = "parallax"
78 config.parallax_err_name = "parallax_err"
80 if withPm or withParallax:
81 config.epoch_name = "unixtime"
82 config.epoch_format = "unix"
83 config.epoch_scale = "utc"
85 return config
88class IngestIndexCatalogTestBase:
89 """Base class for tests involving IngestIndexedReferenceTask
90 """
91 @classmethod
92 def makeSkyCatalog(cls, outPath, size=1000, idStart=1, seed=123):
93 """Make an on-sky catalog, and save it to a text file.
95 Parameters
96 ----------
97 outPath : `str` or None
98 The directory to write the catalog to.
99 Specify None to not write any output.
100 size : `int`, (optional)
101 Number of items to add to the catalog.
102 idStart : `int`, (optional)
103 First id number to put in the catalog.
104 seed : `float`, (optional)
105 Random seed for ``np.random``.
107 Returns
108 -------
109 refCatPath : `str`
110 Path to the created on-sky catalog.
111 refCatOtherDelimiterPath : `str`
112 Path to the created on-sky catalog with a different delimiter.
113 refCatData : `np.ndarray`
114 The data contained in the on-sky catalog files.
115 """
116 np.random.seed(seed)
117 ident = np.arange(idStart, size + idStart, dtype=int)
118 ra = np.random.random(size)*360.
119 dec = np.degrees(np.arccos(2.*np.random.random(size) - 1.))
120 dec -= 90.
121 ra_err = np.ones(size)*0.1 # arcsec
122 dec_err = np.ones(size)*0.1 # arcsec
123 a_mag = 16. + np.random.random(size)*4.
124 a_mag_err = 0.01 + np.random.random(size)*0.2
125 b_mag = 17. + np.random.random(size)*5.
126 b_mag_err = 0.02 + np.random.random(size)*0.3
127 is_photometric = np.random.randint(2, size=size)
128 is_resolved = np.random.randint(2, size=size)
129 is_variable = np.random.randint(2, size=size)
130 extra_col1 = np.random.normal(size=size)
131 extra_col2 = np.random.normal(1000., 100., size=size)
132 # compute proper motion and PM error in arcseconds/year
133 # and let the ingest task scale them to radians
134 pm_amt_arcsec = cls.properMotionAmt.asArcseconds()
135 pm_dir_rad = cls.properMotionDir.asRadians()
136 pm_ra = np.ones(size)*pm_amt_arcsec*math.cos(pm_dir_rad)
137 pm_dec = np.ones(size)*pm_amt_arcsec*math.sin(pm_dir_rad)
138 pm_ra_err = np.ones(size)*cls.properMotionErr.asArcseconds()*abs(math.cos(pm_dir_rad))
139 pm_dec_err = np.ones(size)*cls.properMotionErr.asArcseconds()*abs(math.sin(pm_dir_rad))
140 parallax = np.ones(size)*0.1 # arcseconds
141 parallax_error = np.ones(size)*0.003 # arcseconds
142 unixtime = np.ones(size)*cls.epoch.unix
144 def get_word(word_len):
145 return "".join(np.random.choice([s for s in string.ascii_letters], word_len))
146 extra_col3 = np.array([get_word(num) for num in np.random.randint(11, size=size)])
148 dtype = np.dtype([('id', float), ('ra_icrs', float), ('dec_icrs', float),
149 ('ra_err', float), ('dec_err', float), ('a', float),
150 ('a_err', float), ('b', float), ('b_err', float), ('is_phot', int),
151 ('is_res', int), ('is_var', int), ('val1', float), ('val2', float),
152 ('val3', '|S11'), ('pm_ra', float), ('pm_dec', float), ('pm_ra_err', float),
153 ('pm_dec_err', float), ('parallax', float), ('parallax_error', float),
154 ('unixtime', float)])
156 arr = np.array(list(zip(ident, ra, dec, ra_err, dec_err, a_mag, a_mag_err, b_mag, b_mag_err,
157 is_photometric, is_resolved, is_variable, extra_col1, extra_col2, extra_col3,
158 pm_ra, pm_dec, pm_ra_err, pm_dec_err, parallax, parallax_error, unixtime)),
159 dtype=dtype)
160 if outPath is not None:
161 # write the data with full precision; this is not realistic for
162 # real catalogs, but simplifies tests based on round tripped data
163 saveKwargs = dict(
164 header="id,ra_icrs,dec_icrs,ra_err,dec_err,"
165 "a,a_err,b,b_err,is_phot,is_res,is_var,val1,val2,val3,"
166 "pm_ra,pm_dec,pm_ra_err,pm_dec_err,parallax,parallax_err,unixtime",
167 fmt=["%i", "%.15g", "%.15g", "%.15g", "%.15g",
168 "%.15g", "%.15g", "%.15g", "%.15g", "%i", "%i", "%i", "%.15g", "%.15g", "%s",
169 "%.15g", "%.15g", "%.15g", "%.15g", "%.15g", "%.15g", "%.15g"]
170 )
172 np.savetxt(outPath+"/ref.txt", arr, delimiter=",", **saveKwargs)
173 np.savetxt(outPath+"/ref_test_delim.txt", arr, delimiter="|", **saveKwargs)
174 return outPath+"/ref.txt", outPath+"/ref_test_delim.txt", arr
175 else:
176 return arr
178 @classmethod
179 def tearDownClass(cls):
180 try:
181 shutil.rmtree(cls.outPath)
182 except Exception:
183 print("WARNING: failed to remove temporary dir %r" % (cls.outPath,))
184 del cls.outPath
185 del cls.skyCatalogFile
186 del cls.skyCatalogFileDelim
187 del cls.skyCatalog
188 del cls.testRas
189 del cls.testDecs
190 del cls.searchRadius
191 del cls.compCats
192 del cls.testButler
194 @classmethod
195 def setUpClass(cls):
196 cls.obs_test_dir = lsst.utils.getPackageDir('obs_test')
197 cls.input_dir = os.path.join(cls.obs_test_dir, "data", "input")
199 cls.outPath = tempfile.mkdtemp()
200 cls.testCatPath = os.path.join(os.path.dirname(os.path.realpath(__file__)), "data",
201 "testHtmIndex.fits")
202 # arbitrary, but reasonable, amount of proper motion (angle/year)
203 # and direction of proper motion
204 cls.properMotionAmt = 3.0*lsst.geom.arcseconds
205 cls.properMotionDir = 45*lsst.geom.degrees
206 cls.properMotionErr = 1e-3*lsst.geom.arcseconds
207 cls.epoch = astropy.time.Time(58206.861330339219, scale="tai", format="mjd")
208 cls.skyCatalogFile, cls.skyCatalogFileDelim, cls.skyCatalog = cls.makeSkyCatalog(cls.outPath)
209 cls.testRas = [210., 14.5, 93., 180., 286., 0.]
210 cls.testDecs = [-90., -51., -30.1, 0., 27.3, 62., 90.]
211 cls.searchRadius = 3. * lsst.geom.degrees
212 cls.compCats = {} # dict of center coord: list of IDs of stars within cls.searchRadius of center
213 cls.depth = 4 # gives a mean area of 20 deg^2 per pixel, roughly matching a 3 deg search radius
215 config = IndexerRegistry['HTM'].ConfigClass()
216 # Match on disk comparison file
217 config.depth = cls.depth
218 cls.indexer = IndexerRegistry['HTM'](config)
219 for ra in cls.testRas:
220 for dec in cls.testDecs:
221 tupl = (ra, dec)
222 cent = make_coord(*tupl)
223 cls.compCats[tupl] = []
224 for rec in cls.skyCatalog:
225 if make_coord(rec['ra_icrs'], rec['dec_icrs']).separation(cent) < cls.searchRadius:
226 cls.compCats[tupl].append(rec['id'])
228 cls.testRepoPath = cls.outPath+"/test_repo"
229 config = makeIngestIndexConfig(withMagErr=True, withRaDecErr=True, withPm=True, withPmErr=True,
230 withParallax=True)
231 # To match on disk test data
232 config.dataset_config.indexer.active.depth = cls.depth
233 config.id_name = 'id'
234 config.pm_scale = 1000.0 # arcsec/yr --> mas/yr
235 config.parallax_scale = 1e3 # arcsec -> milliarcsec
236 # np.savetxt prepends '# ' to the header lines, so use a reader that understands that
237 config.file_reader.format = 'ascii.commented_header'
238 # run the intest once to create a butler repo we can compare to
239 IngestIndexedReferenceTask.parseAndRun(args=[cls.input_dir, "--output", cls.testRepoPath,
240 cls.skyCatalogFile], config=config)
241 cls.defaultDatasetName = config.dataset_config.ref_dataset_name
242 cls.testDatasetName = 'diff_ref_name'
243 cls.testButler = dafPersist.Butler(cls.testRepoPath)
244 os.symlink(os.path.join(cls.testRepoPath, 'ref_cats', cls.defaultDatasetName),
245 os.path.join(cls.testRepoPath, 'ref_cats', cls.testDatasetName))
247 def checkAllRowsInRefcat(self, refObjLoader, skyCatalog, config):
248 """Check that every item in ``skyCatalog`` is in the ingested catalog,
249 and check that fields are correct in it.
251 Parameters
252 ----------
253 refObjLoader : `lsst.meas.algorithms.LoadIndexedReferenceObjectsTask`
254 A reference object loader to use to search for rows from
255 ``skyCatalog``.
256 skyCatalog : `np.ndarray`
257 The original data to compare with.
258 config : `lsst.meas.algorithms.LoadIndexedReferenceObjectsConfig`
259 The Config that was used to generate the refcat.
260 """
261 for row in skyCatalog:
262 center = lsst.geom.SpherePoint(row['ra_icrs'], row['dec_icrs'], lsst.geom.degrees)
263 cat = refObjLoader.loadSkyCircle(center, 2*lsst.geom.arcseconds, filterName='a').refCat
264 self.assertGreater(len(cat), 0, "No objects found in loaded catalog.")
265 msg = f"input row not found in loaded catalog:\nrow:\n{row}\n{row.dtype}\n\ncatalog:\n{cat[0]}"
266 self.assertEqual(row['id'], cat[0]['id'], msg)
267 # coordinates won't match perfectly due to rounding in radian/degree conversions
268 self.assertFloatsAlmostEqual(row['ra_icrs'], cat[0]['coord_ra'].asDegrees(),
269 rtol=1e-14, msg=msg)
270 self.assertFloatsAlmostEqual(row['dec_icrs'], cat[0]['coord_dec'].asDegrees(),
271 rtol=1e-14, msg=msg)
272 if config.coord_err_unit is not None:
273 # coordinate errors are not lsst.geom.Angle, so we have to use the
274 # `units` field to convert them, and they are float32, so the tolerance is wider.
275 raErr = cat[0]['coord_raErr']*u.Unit(cat.schema['coord_raErr'].asField().getUnits())
276 decErr = cat[0]['coord_decErr']*u.Unit(cat.schema['coord_decErr'].asField().getUnits())
277 self.assertFloatsAlmostEqual(row['ra_err'], raErr.to_value(config.coord_err_unit),
278 rtol=1e-7, msg=msg)
279 self.assertFloatsAlmostEqual(row['dec_err'], decErr.to_value(config.coord_err_unit),
280 rtol=1e-7, msg=msg)
282 if config.parallax_name is not None: 282 ↛ 283line 282 didn't jump to line 283, because the condition on line 282 was never true
283 self.assertFloatsAlmostEqual(row['parallax'], cat[0]['parallax'].asArcseconds())
284 self.assertFloatsAlmostEqual(row['parallax_error'], cat[0]['parallaxErr'].asArcseconds())