Coverage for tests/ingestIndexTestBase.py: 15%

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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/>. 

21 

22__all__ = ["ConvertReferenceCatalogTestBase", "make_coord", "makeConvertConfig"] 

23 

24import logging 

25import math 

26import string 

27import tempfile 

28 

29import numpy as np 

30import astropy 

31import astropy.units as u 

32 

33import lsst.daf.butler 

34from lsst.meas.algorithms import IndexerRegistry 

35from lsst.meas.algorithms import ConvertReferenceCatalogConfig 

36import lsst.utils 

37 

38 

39def make_coord(ra, dec): 

40 """Make an ICRS coord given its RA, Dec in degrees.""" 

41 return lsst.geom.SpherePoint(ra, dec, lsst.geom.degrees) 

42 

43 

44def makeConvertConfig(withMagErr=False, withRaDecErr=False, withPm=False, withPmErr=False, 

45 withParallax=False): 

46 """Make a config for ConvertReferenceCatalogTask 

47 

48 This is primarily intended to simplify tests of config validation, 

49 so fields that are not validated are not set. 

50 However, it can calso be used to reduce boilerplate in other tests. 

51 """ 

52 config = ConvertReferenceCatalogConfig() 

53 config.dataset_config.ref_dataset_name = "testRefCat" 

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'] 

59 

60 if withMagErr: 

61 config.mag_err_column_map = {'a': 'a_err', 'b': 'b_err'} 

62 

63 if withRaDecErr: 

64 config.ra_err_name = "ra_err" 

65 config.dec_err_name = "dec_err" 

66 config.coord_err_unit = "arcsecond" 

67 

68 if withPm: 

69 config.pm_ra_name = "pm_ra" 

70 config.pm_dec_name = "pm_dec" 

71 

72 if withPmErr: 

73 config.pm_ra_err_name = "pm_ra_err" 

74 config.pm_dec_err_name = "pm_dec_err" 

75 

76 if withParallax: 

77 config.parallax_name = "parallax" 

78 config.parallax_err_name = "parallax_err" 

79 

80 if withPm or withParallax: 

81 config.epoch_name = "unixtime" 

82 config.epoch_format = "unix" 

83 config.epoch_scale = "utc" 

84 

85 return config 

86 

87 

88class ConvertReferenceCatalogTestBase: 

89 """Base class for tests involving ConvertReferenceCatalogTask 

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. 

94 

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``. 

106 

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 

143 

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)]) 

147 

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)]) 

155 

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 ) 

171 

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 

177 

178 @classmethod 

179 def tearDownClass(cls): 

180 cls.outDir.cleanup() 

181 del cls.outPath 

182 del cls.skyCatalogFile 

183 del cls.skyCatalogFileDelim 

184 del cls.skyCatalog 

185 del cls.testRas 

186 del cls.testDecs 

187 del cls.searchRadius 

188 del cls.compCats 

189 

190 @classmethod 

191 def setUpClass(cls): 

192 cls.outDir = tempfile.TemporaryDirectory() 

193 cls.outPath = cls.outDir.name 

194 # arbitrary, but reasonable, amount of proper motion (angle/year) 

195 # and direction of proper motion 

196 cls.properMotionAmt = 3.0*lsst.geom.arcseconds 

197 cls.properMotionDir = 45*lsst.geom.degrees 

198 cls.properMotionErr = 1e-3*lsst.geom.arcseconds 

199 cls.epoch = astropy.time.Time(58206.861330339219, scale="tai", format="mjd") 

200 cls.skyCatalogFile, cls.skyCatalogFileDelim, cls.skyCatalog = cls.makeSkyCatalog(cls.outPath) 

201 cls.testRas = [210., 14.5, 93., 180., 286., 0.] 

202 cls.testDecs = [-90., -51., -30.1, 0., 27.3, 62., 90.] 

203 cls.searchRadius = 3. * lsst.geom.degrees 

204 cls.compCats = {} # dict of center coord: list of IDs of stars within cls.searchRadius of center 

205 cls.depth = 4 # gives a mean area of 20 deg^2 per pixel, roughly matching a 3 deg search radius 

206 

207 config = IndexerRegistry['HTM'].ConfigClass() 

208 # Match on disk comparison file 

209 config.depth = cls.depth 

210 cls.indexer = IndexerRegistry['HTM'](config) 

211 for ra in cls.testRas: 

212 for dec in cls.testDecs: 

213 tupl = (ra, dec) 

214 cent = make_coord(*tupl) 

215 cls.compCats[tupl] = [] 

216 for rec in cls.skyCatalog: 

217 if make_coord(rec['ra_icrs'], rec['dec_icrs']).separation(cent) < cls.searchRadius: 

218 cls.compCats[tupl].append(rec['id']) 

219 

220 cls.testRepoPath = cls.outPath+"/test_repo" 

221 

222 def setUp(self): 

223 self.repoPath = tempfile.TemporaryDirectory() # cleaned up automatically when test ends 

224 self.butler = self.makeTemporaryRepo(self.repoPath.name, self.depth) 

225 self.logger = logging.getLogger('lsst.ReferenceObjectLoader') 

226 

227 def tearDown(self): 

228 self.repoPath.cleanup() 

229 

230 @staticmethod 

231 def makeTemporaryRepo(rootPath, depth): 

232 """Create a temporary butler repository, configured to support a given 

233 htm pixel depth, to use for a single test. 

234 

235 Parameters 

236 ---------- 

237 rootPath : `str` 

238 Root path for butler. 

239 depth : `int` 

240 HTM pixel depth to be used in this test. 

241 

242 Returns 

243 ------- 

244 butler : `lsst.daf.butler.Butler` 

245 The newly created and instantiated butler. 

246 """ 

247 dimensionConfig = lsst.daf.butler.DimensionConfig() 

248 dimensionConfig['skypix']['common'] = f'htm{depth}' 

249 lsst.daf.butler.Butler.makeRepo(rootPath, dimensionConfig=dimensionConfig) 

250 return lsst.daf.butler.Butler(rootPath, writeable=True) 

251 

252 def checkAllRowsInRefcat(self, refObjLoader, skyCatalog, config): 

253 """Check that every item in ``skyCatalog`` is in the ingested catalog, 

254 and check that fields are correct in it. 

255 

256 Parameters 

257 ---------- 

258 refObjLoader : `lsst.meas.algorithms.LoadIndexedReferenceObjectsTask` 

259 A reference object loader to use to search for rows from 

260 ``skyCatalog``. 

261 skyCatalog : `np.ndarray` 

262 The original data to compare with. 

263 config : `lsst.meas.algorithms.LoadIndexedReferenceObjectsConfig` 

264 The Config that was used to generate the refcat. 

265 """ 

266 for row in skyCatalog: 

267 center = lsst.geom.SpherePoint(row['ra_icrs'], row['dec_icrs'], lsst.geom.degrees) 

268 with self.assertLogs(self.logger.name, level="INFO") as cm: 

269 cat = refObjLoader.loadSkyCircle(center, 2*lsst.geom.arcseconds, filterName='a').refCat 

270 self.assertIn("Loading reference objects from testRefCat in region", cm.output[0]) 

271 self.assertGreater(len(cat), 0, "No objects found in loaded catalog.") 

272 msg = f"input row not found in loaded catalog:\nrow:\n{row}\n{row.dtype}\n\ncatalog:\n{cat[0]}" 

273 self.assertEqual(row['id'], cat[0]['id'], msg) 

274 # coordinates won't match perfectly due to rounding in radian/degree conversions 

275 self.assertFloatsAlmostEqual(row['ra_icrs'], cat[0]['coord_ra'].asDegrees(), 

276 rtol=1e-14, msg=msg) 

277 self.assertFloatsAlmostEqual(row['dec_icrs'], cat[0]['coord_dec'].asDegrees(), 

278 rtol=1e-14, msg=msg) 

279 if config.coord_err_unit is not None: 

280 # coordinate errors are not lsst.geom.Angle, so we have to use the 

281 # `units` field to convert them, and they are float32, so the tolerance is wider. 

282 raErr = cat[0]['coord_raErr']*u.Unit(cat.schema['coord_raErr'].asField().getUnits()) 

283 decErr = cat[0]['coord_decErr']*u.Unit(cat.schema['coord_decErr'].asField().getUnits()) 

284 self.assertFloatsAlmostEqual(row['ra_err'], raErr.to_value(config.coord_err_unit), 

285 rtol=1e-7, msg=msg) 

286 self.assertFloatsAlmostEqual(row['dec_err'], decErr.to_value(config.coord_err_unit), 

287 rtol=1e-7, msg=msg) 

288 

289 if config.parallax_name is not None: 

290 self.assertFloatsAlmostEqual(row['parallax'], cat[0]['parallax'].asArcseconds()) 

291 self.assertFloatsAlmostEqual(row['parallax_error'], cat[0]['parallaxErr'].asArcseconds())