Esempio n. 1
0
    def test__gal_data_7x7_image(self, gal_data_7x7, sub_mask_2d_7x7):
        galaxy_fit_data = ag.MaskedGalaxyDataset(galaxy_data=gal_data_7x7,
                                                 mask=sub_mask_2d_7x7,
                                                 use_image=True)

        assert galaxy_fit_data.pixel_scales == (1.0, 1.0)
        assert (galaxy_fit_data.galaxy_data.image.native == np.ones(
            (7, 7))).all()
        assert (galaxy_fit_data.galaxy_data.noise_map.native == 2.0 * np.ones(
            (7, 7))).all()

        assert (galaxy_fit_data.image.slim == np.ones(9)).all()
        assert (galaxy_fit_data.noise_map.slim == 2.0 * np.ones(9)).all()

        assert (galaxy_fit_data.mask == np.array([
            [True, True, True, True, True, True, True],
            [True, True, True, True, True, True, True],
            [True, True, False, False, False, True, True],
            [True, True, False, False, False, True, True],
            [True, True, False, False, False, True, True],
            [True, True, True, True, True, True, True],
            [True, True, True, True, True, True, True],
        ])).all()

        assert (galaxy_fit_data.image.native == np.array([
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0],
            [0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0],
            [0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
        ])).all()

        assert (galaxy_fit_data.noise_map.native == np.array([
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0],
            [0.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0],
            [0.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
        ])).all()

        galaxy = mock.MockGalaxy(value=1, shape=36)

        image = galaxy_fit_data.profile_quantity_from_galaxies(
            galaxies=[galaxy])

        assert (image.binned == np.ones(9)).all()

        galaxy = ag.Galaxy(redshift=0.5, light=ag.lp.SphSersic(intensity=1.0))

        image_gal = galaxy.image_2d_from_grid(grid=galaxy_fit_data.grid)

        image_gd = galaxy_fit_data.profile_quantity_from_galaxies(
            galaxies=[galaxy])

        assert (image_gal == image_gd).all()
Esempio n. 2
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    def test__gal_data_7x7_deflections_x(self, gal_data_7x7, sub_mask_2d_7x7):
        galaxy_fit_data = ag.MaskedGalaxyDataset(galaxy_data=gal_data_7x7,
                                                 mask=sub_mask_2d_7x7,
                                                 use_deflections_x=True)

        assert galaxy_fit_data.pixel_scales == (1.0, 1.0)
        assert (galaxy_fit_data.galaxy_data.image.native == np.ones(
            (7, 7))).all()
        assert (galaxy_fit_data.galaxy_data.noise_map.native == 2.0 * np.ones(
            (7, 7))).all()

        assert (galaxy_fit_data.image.slim == np.ones(9)).all()
        assert (galaxy_fit_data.noise_map.slim == 2.0 * np.ones(9)).all()

        assert (galaxy_fit_data.mask == np.array([
            [True, True, True, True, True, True, True],
            [True, True, True, True, True, True, True],
            [True, True, False, False, False, True, True],
            [True, True, False, False, False, True, True],
            [True, True, False, False, False, True, True],
            [True, True, True, True, True, True, True],
            [True, True, True, True, True, True, True],
        ])).all()

        assert (galaxy_fit_data.image.native == np.array([
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0],
            [0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0],
            [0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
        ])).all()

        assert (galaxy_fit_data.noise_map.native == np.array([
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0],
            [0.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0],
            [0.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
        ])).all()

        galaxy = mock.MockGalaxy(value=1, shape=36)

        deflections_x = galaxy_fit_data.profile_quantity_from_galaxies(
            galaxies=[galaxy])

        assert (deflections_x.binned == np.ones(9)).all()

        galaxy = ag.Galaxy(redshift=0.5,
                           mass=ag.mp.SphIsothermal(einstein_radius=1.0))

        deflections_gal = galaxy.deflections_2d_from_grid(
            grid=galaxy_fit_data.grid)
        deflections_gal = np.asarray([
            np.multiply(
                deflections_gal.mask.sub_fraction,
                deflections_gal[:, 0].reshape(
                    -1, deflections_gal.mask.sub_length).sum(axis=1),
            ),
            np.multiply(
                deflections_gal.mask.sub_fraction,
                deflections_gal[:, 1].reshape(
                    -1, deflections_gal.mask.sub_length).sum(axis=1),
            ),
        ]).T

        deflections_gd = galaxy_fit_data.profile_quantity_from_galaxies(
            galaxies=[galaxy])

        assert (deflections_gal[:, 1] == deflections_gd.binned).all()
Esempio n. 3
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    def test__gal_data_7x7_potential(self, gal_data_7x7, sub_mask_2d_7x7):
        galaxy_fit_data = ag.MaskedGalaxyDataset(galaxy_data=gal_data_7x7,
                                                 mask=sub_mask_2d_7x7,
                                                 use_potential=True)

        assert galaxy_fit_data.pixel_scales == (1.0, 1.0)
        assert (galaxy_fit_data.galaxy_data.image.native == np.ones(
            (7, 7))).all()
        assert (galaxy_fit_data.galaxy_data.noise_map.native == 2.0 * np.ones(
            (7, 7))).all()

        assert (galaxy_fit_data.image.slim == np.ones(9)).all()
        assert (galaxy_fit_data.noise_map.slim == 2.0 * np.ones(9)).all()

        assert (galaxy_fit_data.mask == np.array([
            [True, True, True, True, True, True, True],
            [True, True, True, True, True, True, True],
            [True, True, False, False, False, True, True],
            [True, True, False, False, False, True, True],
            [True, True, False, False, False, True, True],
            [True, True, True, True, True, True, True],
            [True, True, True, True, True, True, True],
        ])).all()

        assert (galaxy_fit_data.image.native == np.array([
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0],
            [0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0],
            [0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
        ])).all()

        assert (galaxy_fit_data.noise_map.native == np.array([
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0],
            [0.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0],
            [0.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
            [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
        ])).all()

        galaxy = mock.MockGalaxy(value=1, shape=36)

        potential = galaxy_fit_data.profile_quantity_from_galaxies(
            galaxies=[galaxy])

        assert (potential.binned == np.ones(9)).all()

        galaxy = ag.Galaxy(redshift=0.5,
                           mass=ag.mp.SphIsothermal(einstein_radius=1.0))

        potential_gal = galaxy.potential_2d_from_grid(
            grid=galaxy_fit_data.grid)

        potential_gd = galaxy_fit_data.profile_quantity_from_galaxies(
            galaxies=[galaxy])

        assert (potential_gal == potential_gd).all()