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 math 

25import shutil 

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 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 

193 @classmethod 

194 def setUpClass(cls): 

195 cls.outPath = tempfile.mkdtemp() 

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

197 # and direction of proper motion 

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

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

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

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

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

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

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

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

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

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

208 

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

210 # Match on disk comparison file 

211 config.depth = cls.depth 

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

213 for ra in cls.testRas: 

214 for dec in cls.testDecs: 

215 tupl = (ra, dec) 

216 cent = make_coord(*tupl) 

217 cls.compCats[tupl] = [] 

218 for rec in cls.skyCatalog: 

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

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

221 

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

223 

224 def setUp(self): 

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

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

227 

228 @staticmethod 

229 def makeTemporaryRepo(rootPath, depth): 

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

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

232 

233 Parameters 

234 ---------- 

235 rootPath : `str` 

236 Root path for butler. 

237 depth : `int` 

238 HTM pixel depth to be used in this test. 

239 

240 Returns 

241 ------- 

242 butler : `lsst.daf.butler.Butler` 

243 The newly created and instantiated butler. 

244 """ 

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

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

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

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

249 

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

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

252 and check that fields are correct in it. 

253 

254 Parameters 

255 ---------- 

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

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

258 ``skyCatalog``. 

259 skyCatalog : `np.ndarray` 

260 The original data to compare with. 

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

262 The Config that was used to generate the refcat. 

263 """ 

264 for row in skyCatalog: 

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

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

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

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

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

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

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

272 rtol=1e-14, msg=msg) 

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

274 rtol=1e-14, msg=msg) 

275 if config.coord_err_unit is not None: 

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

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

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

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

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

281 rtol=1e-7, msg=msg) 

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

283 rtol=1e-7, msg=msg) 

284 

285 if config.parallax_name is not None: 

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

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