Feature/shapelets #91
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Jammy2211
requested review from
rhayes777,
Sketos,
caoxiaoyue,
qiuhan96 and
samlange04
rhayes777
approved these changes
Feb 27, 2023
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| lower_limit: -inf | ||
| upper_limit: inf |
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gaussian limits are implicitly infinite
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Like to keep them there so users know they exist (I know this is source code but principle still applies).
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| def __init__( | ||
| self, | ||
| n: int, | ||
| m: int, | ||
| centre: Tuple[float, float] = (0.0, 0.0), | ||
| beta: float = 1.0, | ||
| ): | ||
| """ | ||
| Shapelets where the basis function is defined according to a Exponential (r,theta) grid of coordinates. | ||
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| Shapelets are defined according to: | ||
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| https://arxiv.org/abs/astro-ph/0105178 | ||
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| Shapelets are are described in the context of strong lens modeling in: | ||
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| https://ui.adsabs.harvard.edu/abs/2016MNRAS.457.3066T/abstract | ||
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| Parameters | ||
| ---------- | ||
| n_y | ||
| The order of the shapelets basis function in the y-direction. | ||
| n_x | ||
| The order of the shapelets basis function in the x-direction. | ||
| centre | ||
| The (y,x) arc-second coordinates of the profile (shapelet) centre. | ||
| beta | ||
| The characteristic length scale of the shapelet basis function, defined in arc-seconds. | ||
| """ | ||
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| super().__init__(n=n, m=m, centre=centre, ell_comps=(0.0, 0.0), beta=beta) |
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Not sure if there's any point in this constructor?
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| def __init__( | ||
| self, | ||
| n: int, | ||
| m: int, | ||
| centre: Tuple[float, float] = (0.0, 0.0), | ||
| beta: float = 1.0, | ||
| ): | ||
| """ | ||
| Shapelets where the basis function is defined according to a Polar (r,theta) grid of coordinates. | ||
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| Shapelets are defined according to: | ||
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| https://arxiv.org/abs/astro-ph/0105178 | ||
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| Shapelets are are described in the context of strong lens modeling in: | ||
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| https://ui.adsabs.harvard.edu/abs/2016MNRAS.457.3066T/abstract | ||
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| Parameters | ||
| ---------- | ||
| n_y | ||
| The order of the shapelets basis function in the y-direction. | ||
| n_x | ||
| The order of the shapelets basis function in the x-direction. | ||
| centre | ||
| The (y,x) arc-second coordinates of the profile (shapelet) centre. | ||
| beta | ||
| The characteristic length scale of the shapelet basis function, defined in arc-seconds. | ||
| """ | ||
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| super().__init__(n=n, m=m, centre=centre, ell_comps=(0.0, 0.0), beta=beta) |
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Same with this one. You could just put docs at the class level and not bother with the init
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| def test__image_2d_from(): | ||
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| shapelet = ag.lp_shapelets.ShapeletExponential( | ||
| n=2, m=0, centre=(0.0, 0.0), beta=1.0 | ||
| ) | ||
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| image = shapelet.image_2d_from(grid=np.array([[0.0, 1.0], [0.5, 0.25]])) | ||
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| assert image == pytest.approx(np.array([0.05784, 0.17962]), 1e-4) | ||
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| shapelet = ag.lp_shapelets.ShapeletExponential( | ||
| n=2, m=0, centre=(0.2, 0.4), beta=1.0 | ||
| ) | ||
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| image = shapelet.image_2d_from(grid=np.array([[0.0, 1.0], [0.5, 0.25]])) | ||
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| assert image == pytest.approx(np.array([0.16136, 0.22476]), 1e-4) |
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Could be separated into two separate tests
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| import autogalaxy as ag | ||
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| grid = np.array([[1.0, 1.0], [2.0, 2.0], [3.0, 3.0], [2.0, 4.0]]) |
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Slightly safer to define this as a fixture in case the array is mutated in a test
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Implement Shapelets in their various forms.
Example scripts here:
https://github.com/Jammy2211/autogalaxy_workspace/blob/main/scripts/imaging/modeling/advanced/light_shapelets.py
https://github.com/Jammy2211/autolens_workspace/blob/main/scripts/imaging/modeling/advanced/shapelets.py