def normalize_flux(self, kwargs_options, kwargs_source, kwargs_lens_light, kwargs_ps, norm_factor_source=1, norm_factor_lens_light=1, norm_factor_point_source=1.): """ multiplies the surface brightness amplitudes with a norm_factor aim: mimic different telescopes photon collection area or colours for different imaging bands :param kwargs_source: :param kwargs_lens_light: :param norm_factor: :return: """ lensLightModel = LightModel(kwargs_options.get('lens_light_model_list', ['NONE'])) sourceModel = LightModel(kwargs_options.get('source_light_model_list', ['NONE'])) lensModel = LensModel(lens_model_list=kwargs_options.get('lens_model_list', ['NONE'])) pointSource = PointSource(point_source_type_list=kwargs_options.get('point_source_list', ['NONE']), lensModel=lensModel, fixed_magnification_list=kwargs_options.get('fixed_magnification_list', [False]), additional_images_list=kwargs_options.get('additional_images_list', [False])) kwargs_source_updated = copy.deepcopy(kwargs_source) kwargs_lens_light_updated = copy.deepcopy(kwargs_lens_light) kwargs_ps_updated = copy.deepcopy(kwargs_ps) kwargs_source_updated = sourceModel.re_normalize_flux(kwargs_source_updated, norm_factor_source) kwargs_lens_light_updated = lensLightModel.re_normalize_flux(kwargs_lens_light_updated, norm_factor_lens_light) kwargs_ps_updated = pointSource.re_normalize_flux(kwargs_ps_updated, norm_factor_point_source) return kwargs_source_updated, kwargs_lens_light_updated, kwargs_ps_updated
class TestPointSource_fixed_mag(object): def setup(self): lensModel = LensModel(lens_model_list=['SPEP']) solver = LensEquationSolver(lensModel=lensModel) e1, e2 = param_util.phi_q2_ellipticity(0, 0.7) self.kwargs_lens = [{'theta_E': 1., 'center_x': 0, 'center_y': 0, 'e1': e1, 'e2': e2, 'gamma': 2}] self.sourcePos_x, self.sourcePos_y = 0.01, -0.01 self.x_pos, self.y_pos = solver.image_position_from_source(sourcePos_x=self.sourcePos_x, sourcePos_y=self.sourcePos_y, kwargs_lens=self.kwargs_lens) self.PointSource = PointSource(point_source_type_list=['LENSED_POSITION', 'UNLENSED', 'SOURCE_POSITION'], lensModel=lensModel, fixed_magnification_list=[True]*4, additional_images_list=[False]*4) self.kwargs_ps = [{'ra_image': self.x_pos, 'dec_image': self.y_pos, 'source_amp': 1}, {'ra_image': [1.], 'dec_image': [1.], 'point_amp': [10]}, {'ra_source': self.sourcePos_x, 'dec_source': self.sourcePos_y, 'source_amp': 1.}, {}] def test_image_position(self): x_image_list, y_image_list = self.PointSource.image_position(kwargs_ps=self.kwargs_ps, kwargs_lens=self.kwargs_lens) npt.assert_almost_equal(x_image_list[0][0], self.x_pos[0], decimal=8) npt.assert_almost_equal(x_image_list[1], 1, decimal=8) npt.assert_almost_equal(x_image_list[2][0], self.x_pos[0], decimal=8) def test_source_position(self): x_source_list, y_source_list = self.PointSource.source_position(kwargs_ps=self.kwargs_ps, kwargs_lens=self.kwargs_lens) npt.assert_almost_equal(x_source_list[0], self.sourcePos_x, decimal=8) npt.assert_almost_equal(x_source_list[1], 1, decimal=8) npt.assert_almost_equal(x_source_list[2], self.sourcePos_x, decimal=8) def test_num_basis(self): num_basis = self.PointSource.num_basis(self.kwargs_ps, self.kwargs_lens) assert num_basis == 3 def test_linear_response_set(self): ra_pos, dec_pos, amp, n = self.PointSource.linear_response_set(self.kwargs_ps, kwargs_lens=self.kwargs_lens, with_amp=False, k=None) num_basis = self.PointSource.num_basis(self.kwargs_ps, self.kwargs_lens) assert n == num_basis assert ra_pos[0][0] == self.x_pos[0] assert ra_pos[1][0] == 1 npt.assert_almost_equal(ra_pos[2][0], self.x_pos[0], decimal=8) def test_point_source_list(self): ra_list, dec_list, amp_list = self.PointSource.point_source_list(self.kwargs_ps, self.kwargs_lens) assert ra_list[0] == self.x_pos[0] assert len(ra_list) == 9 def test_check_image_positions(self): bool = self.PointSource.check_image_positions(self.kwargs_ps, self.kwargs_lens, tolerance=0.001) assert bool == True def test_re_normalize_flux(self): norm_factor = 10 kwargs_input = copy.deepcopy(self.kwargs_ps) kwargs_ps = self.PointSource.re_normalize_flux(kwargs_input, norm_factor) npt.assert_almost_equal(kwargs_ps[0]['source_amp'] / self.kwargs_ps[0]['source_amp'], norm_factor, decimal=8) def test_set_amplitudes(self): amp_list = [10, [100], 10] kwargs_out = self.PointSource.set_amplitudes(amp_list, self.kwargs_ps) assert kwargs_out[0]['source_amp'] == 10 * self.kwargs_ps[0]['source_amp'] assert kwargs_out[1]['point_amp'][0] == 10 * self.kwargs_ps[1]['point_amp'][0] assert kwargs_out[2]['source_amp'] == 10 * self.kwargs_ps[2]['source_amp']