Coverage for tests/test_fit_phot_model.py : 93%

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# LSST Data Management System # Copyright 2017 AURA/LSST. # # This product includes software developed by the # LSST Project (http://www.lsst.org/). # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the LSST License Statement and # the GNU General Public License along with this program. If not, # see <https://www.lsstcorp.org/LegalNotices/>.
"""Testing photometric error model fitting performance and failure modes."""
# Set seed for repeatibility self.mag, self.sigmaSys, self.gamma, self.m5)
# Resample mag # Set seed for repeatibility. # We explicityly reset it here to a known value # in case `photErrModel` called np.random
"""Does a simple fit to a small, perfect, data set work?"""
fit_results['sigmaSys'].value, self.sigmaSys, atol=1e-7) fit_results['gamma'].value, self.gamma, atol=1e-7) fit_results['m5'].value, self.m5, atol=1e-7)
"""Does a simple fit to a small, perfect, data set work?"""
# Different absolute tolerances because we expect some variation in the # fit results to the hnoisy data and that variation is different # for different parameters fit_results['sigmaSys'].value, self.sigmaSys, atol=1e-2) fit_results['gamma'].value, self.gamma, atol=2e-2) fit_results['m5'].value, self.m5, atol=0.2)
"""Does a failed fit recover and return NaN?"""
lsst.utils.tests.init() unittest.main() |