Different SLDs for Diffraction Pattern #1341
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| if not _HAS_MPL: | ||
| raise ImportError(msg_mpl) |
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To appease the pre-commit and the linter you want to revert the changes on the conditional imports to the code that is current with the main branch.
| if not _HAS_MPL: | ||
| raise ImportError(msg_mpl) |
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To appease the pre-commit and the linter you want to revert the changes on the conditional imports to the code that is current with the main branch.
| _HAS_MPL = find_spec("matplotlib") is not None | ||
| if _HAS_MPL: | ||
| import matplotlib.cm | ||
| import matplotlib.colors | ||
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| import freud.plot | ||
| else: | ||
| msg_mpl = "Plotting requires matplotlib." | ||
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To appease the pre-commit and the linter you want to revert the changes on the conditional imports to the code that is current with the main branch.
| @@ -13,7 +13,6 @@ | |||
| """ | |||
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| import logging | |||
| from importlib.util import find_spec | |||
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To appease the pre-commit and the linter you want to revert the changes on the conditional imports to the code that is current with the main branch.
| import freud.plot | ||
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There was a problem hiding this comment.
To appease the pre-commit and the linter you want to revert the changes on the conditional imports to the code that is current with the main branch.
| if not _HAS_MPL: | ||
| raise ImportError(msg_mpl) |
There was a problem hiding this comment.
To appease the pre-commit and the linter you want to revert the changes on the conditional imports to the code that is current with the main branch.
| if not _HAS_MPL: | ||
| raise ImportError(msg_mpl) |
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To appease the pre-commit and the linter you want to revert the changes on the conditional imports to the code that is current with the main branch.
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| if vmax is None: | ||
| vmax = 0.7 * self.N_points | ||
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| import freud.plot | ||
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| return freud.plot.diffraction_plot( | ||
| self.diffraction, self.k_values, self.N_points, ax, cmap, vmin, vmax | ||
| ) | ||
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| def _repr_png_(self): | ||
| try: | ||
| import freud.plot | ||
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To appease the pre-commit and the linter you want to revert the changes on the conditional imports to the code that is current with the main branch.
| weights ((:math:`N`,) :class:`numpy.ndarray`, optional): | ||
| SLD weights for each point in the system. If provided, the | ||
| diffraction pattern will be normalized such that the sum of the | ||
| weights is equal to the number of points in the system, resulting in | ||
| :math:`S(0) = N`. If not provided, all points are assumed to | ||
| have a weight of 1. (Default value = :code:`None`). |
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This is the first mention of SLD. Give the full meaning of the acronym when you first mention it.
| @@ -237,3 +237,21 @@ def test_noncubic_system(self, noncubic_box_params): | |||
| dp = freud.diffraction.DiffractionPattern() | |||
| with pytest.raises(ValueError): | |||
| dp.compute((box, points)) | |||
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| def test_weighted_diffraction(self): | |||
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can you also add a test that test that S(0) is N, as you mention in the PR text?
I provided a little modification to the
DiffractionPatternclass, to account for differently strong scattering mixtures.Description
I added weights to the computation of the histogram, to account for the different SLDs. I normalized the weights in a way, that$S(q=0) = N$ still holds.
Motivation and Context
For mixed systems, it is possible, that different parts of the mixture have very different SLDs, resulting in a higher contribution of one part of the mixture to the signal. To have a scattering image, that is close to an experimental one, it is imperative to account for different SLDs.
How Has This Been Tested?
I added new tests, to ensure, that the changes do not change existing behavior, i.e.$S(q = 0) = N$ , otherwise it does not affect the code downstream.
Checklist: