Coverage for tests / test_fit_coadd.py: 36%
105 statements
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1# This file is part of meas_extensions_multiprofit.
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 os
24from astropy.table import Table
25from lsst.afw.image import ExposureF
26from lsst.afw.table import SourceCatalog
27from lsst.daf.butler.formatters.parquet import arrow_to_astropy
28import lsst.gauss2d.fit as g2f
29import lsst.meas.extensions.multiprofit.fit_coadd_multiband as fitCMB
30import lsst.meas.extensions.multiprofit.fit_coadd_psf as fitCP
31from lsst.multiprofit.componentconfig import (
32 CentroidConfig,
33 GaussianComponentConfig,
34 ParameterConfig,
35 SersicComponentConfig,
36 SersicIndexParameterConfig,
37)
38from lsst.multiprofit.fitting.fit_psf import CatalogPsfFitterConfig
39from lsst.multiprofit.modelconfig import ModelConfig
40from lsst.multiprofit.sourceconfig import ComponentGroupConfig, SourceConfig
41from lsst.pipe.tasks.fit_coadd_psf import CatalogExposurePsf
42import numpy as np
43import pytest
45ROOT = os.environ.get("TESTDATA_CI_IMSIM_MINI_DIR", None)
46has_files = (ROOT is not None) and os.path.isdir(ROOT)
48filename_cat = os.path.join(ROOT, "data", "deepCoadd_meas_0_24_r_2k_ci_imsim.fits") if has_files else None
49filename_exp = os.path.join(ROOT, "data", "deepCoadd_calexp_0_24_r_2k_ci_imsim.fits") if has_files else None
51band = "r"
52channel = g2f.Channel.get(band)
53dataId = {"band": band}
54do_exp_fixedcen = False
55include_ps = False
56n_test = 5
59@pytest.fixture(scope="module")
60def catalog():
61 if not has_files:
62 return None
63 catalog = SourceCatalog.readFits(filename_cat)
64 good = (catalog["detect_isPrimary"] == 1) & (catalog["merge_peak_sky"] == 0)
65 good[np.where(good)[0][n_test:]] = False
66 return catalog[good]
69@pytest.fixture(scope="module")
70def exposure():
71 if not has_files:
72 return None
73 return ExposureF.readFits(filename_exp)
76@pytest.fixture(scope="module")
77def psf_fit_config():
78 return fitCP.MultiProFitPsfConfig()
81@pytest.fixture(scope="module")
82def psf_fit_results(catalog, exposure, psf_fit_config):
83 if not has_files:
84 return None
85 catexp = CatalogExposurePsf(dataId=dataId, catalog=catalog, exposure=exposure)
86 task = fitCP.MultiProFitPsfTask(config=psf_fit_config)
87 results = task.run(catexp).output
88 return arrow_to_astropy(results)
91@pytest.fixture(scope="module")
92def source_fit_exp_fixedcen_config():
93 config = fitCMB.MultiProFitSourceConfig(
94 bands_fit=(band,),
95 config_model=ModelConfig(
96 sources={
97 "": SourceConfig(
98 component_groups={
99 "": ComponentGroupConfig(
100 centroids={
101 "default": CentroidConfig(
102 x=ParameterConfig(fixed=True),
103 y=ParameterConfig(fixed=True),
104 )
105 },
106 components_sersic={
107 "exp": SersicComponentConfig(
108 sersic_index=SersicIndexParameterConfig(value_initial=1.0, fixed=True),
109 )
110 },
111 ),
112 }
113 ),
114 },
115 ),
116 )
117 config.validate()
118 return config
121@pytest.fixture(scope="module")
122def source_fit_ser_config():
123 config = fitCMB.MultiProFitSourceConfig(
124 bands_fit=(band,),
125 config_model=ModelConfig(
126 sources={
127 "": SourceConfig(
128 component_groups={
129 "": ComponentGroupConfig(
130 components_gauss=(
131 {
132 "ps": GaussianComponentConfig(
133 size_x=ParameterConfig(value_initial=0.0, fixed=True),
134 size_y=ParameterConfig(value_initial=0.0, fixed=True),
135 rho=ParameterConfig(value_initial=0.0, fixed=True),
136 )
137 }
138 if include_ps
139 else {}
140 ),
141 components_sersic={
142 "ser": SersicComponentConfig(
143 sersic_index=SersicIndexParameterConfig(value_initial=1.0),
144 )
145 },
146 ),
147 }
148 ),
149 },
150 ),
151 )
152 config.validate()
153 return config
156@pytest.fixture(scope="module")
157def source_fit_exp_fixedcen_results(
158 catalog,
159 exposure,
160 psf_fit_results,
161 psf_fit_config,
162 source_fit_exp_fixedcen_config,
163) -> Table:
164 if not has_files:
165 return None
166 if not do_exp_fixedcen:
167 return None
168 catexp = fitCMB.CatalogExposurePsfs(
169 dataId=dataId,
170 catalog=catalog,
171 exposure=exposure,
172 table_psf_fits=psf_fit_results,
173 channel=channel,
174 config_fit=source_fit_exp_fixedcen_config,
175 )
176 task = fitCMB.MultiProFitSourceTask(config=source_fit_exp_fixedcen_config)
177 results = task.run(catalog_multi=catalog, catexps=[catexp])
178 return arrow_to_astropy(results.output)
181@pytest.fixture(scope="module")
182def source_fit_ser_results(
183 catalog,
184 exposure,
185 psf_fit_results,
186 psf_fit_config,
187 source_fit_ser_config,
188) -> Table:
189 if not has_files:
190 return None
191 catexp = fitCMB.CatalogExposurePsfs(
192 dataId=dataId,
193 catalog=catalog,
194 exposure=exposure,
195 table_psf_fits=psf_fit_results,
196 channel=channel,
197 config_fit=source_fit_ser_config,
198 )
199 task = fitCMB.MultiProFitSourceTask(config=source_fit_ser_config)
200 results = task.run(catalog_multi=catalog, catexps=[catexp])
201 return arrow_to_astropy(results.output)
204@pytest.fixture(scope="module")
205def source_fit_ser_shapelet_psf_results(
206 catalog,
207 exposure,
208 psf_fit_results,
209 psf_fit_config,
210 source_fit_ser_config,
211) -> Table:
212 if not has_files:
213 return None
214 table_psf = Table(
215 meta=dict(config=CatalogPsfFitterConfig().toDict()),
216 )
217 catexp = fitCMB.CatalogExposurePsfs(
218 dataId=dataId,
219 catalog=catalog,
220 exposure=exposure,
221 table_psf_fits=table_psf,
222 channel=channel,
223 config_fit=source_fit_ser_config,
224 )
225 source_fit_ser_config.action_psf = fitCMB.SourceTablePsfComponentsAction()
226 task = fitCMB.MultiProFitSourceTask(config=source_fit_ser_config)
227 results = task.run(catalog_multi=catalog, catexps=[catexp])
228 return arrow_to_astropy(results.output)
231@pytest.fixture(scope="module")
232def source_fits_all(
233 source_fit_exp_fixedcen_results,
234 source_fit_ser_results,
235 source_fit_ser_shapelet_psf_results,
236):
237 return (
238 source_fit_exp_fixedcen_results,
239 source_fit_ser_results,
240 source_fit_ser_shapelet_psf_results,
241 )
244def test_psf_fits(psf_fit_results):
245 if psf_fit_results is not None:
246 assert len(psf_fit_results) == n_test
247 for column in psf_fit_results.columns:
248 assert column and np.all(np.isfinite(psf_fit_results[column]))
249 # TODO: Determine what checks can be done against previous values
252def test_source_fits(source_fits_all):
253 for results in source_fits_all:
254 if results is not None:
255 assert len(results) == n_test
256 prefix = results.meta["config"]["prefix_column"]
257 good = ~results[f"{prefix}unknown_flag"]
258 assert np.sum(~good) == 0
259 for column in results.columns:
260 if column.startswith(prefix):
261 assert column and (np.sum(~np.isfinite(results[column][good])) == 0)
262 # TODO: Determine what checks can be done against previous values