Coverage for tests/test_match_tract_catalog.py: 96%
67 statements
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23import unittest
24import lsst.utils.tests
26from lsst.meas.astrom import ConvertCatalogCoordinatesConfig
27from lsst.pipe.tasks.match_tract_catalog import MatchTractCatalogConfig, MatchTractCatalogTask
28from lsst.pipe.tasks.match_tract_catalog_probabilistic import MatchTractCatalogProbabilisticTask
29from lsst.skymap.discreteSkyMap import DiscreteSkyMap
31from astropy.table import Table
32import numpy as np
35def _error_format(column):
36 return f'{column}Err'
39class MatchTractCatalogTaskTestCase(lsst.utils.tests.TestCase):
40 """Test matching with some arbitrary mock data.
42 This test is largely copied from diff_matched_tract_catalog, which
43 implemented outputting a matched catalog separately from this task.
44 """
45 def setUp(self):
46 # test wrapping from 0 to 360
47 ra_cen = 0.
48 ra = ra_cen + np.array([-5.1, -2.2, 0., 3.1, -3.2, 2.01, -4.1])/60
49 dec_cen = -30.
50 dec = dec_cen + np.array([-4.15, 1.15, 0, 2.15, -7.15, -3.05, 5.7])/60
51 mag_g = np.array([23., 24., 25., 25.5, 26., 24.7, 23.3])
52 mag_r = mag_g + [0.5, -0.2, -0.8, -0.5, -1.5, 0.8, -0.4]
54 coord_format = ConvertCatalogCoordinatesConfig
55 zeropoint = coord_format.mag_zeropoint_ref.default
56 fluxes = tuple(10**(-0.4*(mag - zeropoint)) for mag in (mag_g, mag_r))
57 # Percent error in measurement
58 err_flux = np.array((0.02, 0.015, -0.035, 0.02, -0.04, 0.06, 0.01))
59 # Absolute error
60 eps_coord = np.array((2.3, 0.6, -1.7, 3.6, -2.4, 55.0, -40.8))
61 err_coord = np.full_like(eps_coord, 0.02)
62 eps_coord *= err_coord
63 flags = np.ones_like(eps_coord, dtype=bool)
65 bands = ['g', 'r']
67 columns_flux = [f'flux_{band}' for band in bands]
68 columns_flux_err = [_error_format(column) for column in columns_flux]
70 column_ra_ref = coord_format.column_ref_coord1.default
71 column_dec_ref = coord_format.column_ref_coord2.default
72 column_ra_target = coord_format.column_target_coord1.default
73 column_dec_target = coord_format.column_target_coord2.default
75 column_ra_target_err, column_dec_target_err = [
76 _error_format(col) for col in (column_ra_target, column_dec_target)
77 ]
79 data_ref = {
80 column_ra_ref: ra[::-1],
81 column_dec_ref: dec[::-1],
82 columns_flux[0]: fluxes[0][::-1],
83 columns_flux[1]: fluxes[1][::-1],
84 }
85 self.catalog_ref = Table(data=data_ref)
87 data_target = {
88 column_ra_target: ra + eps_coord,
89 column_dec_target: dec + eps_coord,
90 column_ra_target_err: err_coord,
91 column_dec_target_err: err_coord,
92 columns_flux[0]: fluxes[0]*(1 + err_flux),
93 columns_flux[1]: fluxes[1]*(1 + err_flux),
94 columns_flux_err[0]: np.sqrt(fluxes[0]),
95 columns_flux_err[1]: np.sqrt(fluxes[1]),
96 "detect_isPrimary": flags,
97 "merge_peak_sky": ~flags,
98 }
99 self.catalog_target = Table(data=data_target)
101 config = MatchTractCatalogConfig(
102 coord_unit="deg",
103 output_matched_catalog=True,
104 refcat_sharding_type="none",
105 target_sharding_type="none",
106 )
107 mtc = config.match_tract_catalog
108 mtc.retarget(MatchTractCatalogProbabilisticTask)
109 mtc.columns_ref_flux = [columns_flux[0], columns_flux[0]]
110 mtc.columns_ref_meas = [column_ra_ref, column_dec_ref, columns_flux[0], columns_flux[0]]
111 mtc.columns_target_meas = [
112 column_ra_target, column_dec_target, columns_flux[0], columns_flux[0],
113 ]
114 mtc.columns_target_err = [
115 column_ra_target_err, column_dec_target_err, columns_flux_err[0], columns_flux_err[0],
116 ]
117 config.validate()
118 self.config = config
119 self.skymap = DiscreteSkyMap(
120 DiscreteSkyMap.ConfigClass(raList=[ra_cen], decList=[dec_cen], radiusList=[1.])
121 )
122 self.wcs = self.skymap[0].wcs
124 def test_MatchTractCatalogTask(self):
125 # These tables will have columns added to them in run
126 columns_ref, columns_target = (list(x.columns) for x in (self.catalog_ref, self.catalog_target))
127 task = MatchTractCatalogTask(None, config=self.config)
128 task._add_tract_column_to_catalogs(self.catalog_ref, self.catalog_target, self.skymap)
129 result = task.run(
130 catalog_ref=self.catalog_ref,
131 catalog_target=self.catalog_target,
132 wcs=self.wcs,
133 )
134 columns_result = list(result.cat_output_matched.columns)
135 columns_expect = list(columns_target) + [
136 "tract", "patch", "match_candidate", "match_distance", "match_distanceErr",
137 ]
138 prefix = task.diff_matched_catalog.config.column_matched_prefix_ref
139 columns_expect.extend((f"{prefix}{col}" for col in columns_ref))
140 columns_expect.extend((
141 f"{prefix}{col}" for col in ("tract", "patch", "flux_total", "match_candidate")
142 ))
143 self.assertListEqual(columns_expect, columns_result)
146class MemoryTester(lsst.utils.tests.MemoryTestCase):
147 pass
150def setup_module(module):
151 lsst.utils.tests.init()
154if __name__ == "__main__": 154 ↛ 155line 154 didn't jump to line 155 because the condition on line 154 was never true
155 lsst.utils.tests.init()
156 unittest.main()