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compute mu #278
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**Added:** | ||
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* function to compute x-ray attenuation coefficient (mu) using XrayDB | ||
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**Changed:** | ||
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* <news item> | ||
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**Deprecated:** | ||
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* <news item> | ||
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**Removed:** | ||
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* <news item> | ||
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**Fixed:** | ||
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* <news item> | ||
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**Security:** | ||
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* <news item> |
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numpy | ||
xraydb |
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numpy | ||
xraydb |
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from copy import copy | ||
from pathlib import Path | ||
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from xraydb import material_mu | ||
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def _stringify(obj): | ||
""" | ||
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@@ -131,3 +133,32 @@ def get_package_info(package_names, metadata=None): | |
pkg_info.update({package: importlib.metadata.version(package)}) | ||
metadata["package_info"] = pkg_info | ||
return metadata | ||
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def compute_mu_using_xraydb(sample_composition, energy, density=None, packing_fraction=1): | ||
"""Compute the attenuation coefficient (mu) using the XrayDB database. | ||
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Computes mu based on the sample composition and energy. | ||
If density is not provided, a standard reference density (e.g., 0.987 g/cm^3 for H2O) is used. | ||
User can provide either a measured density or an estimated packing fraction (with a standard density). | ||
It is recommended to specify the density, especially for materials like ZrO2, where it can vary. | ||
Reference: https://xraypy.github.io/XrayDB/python.html#xraydb.material_mu. | ||
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Parameters | ||
---------- | ||
sample_composition : str | ||
The chemical formula or the name of the material. | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. not the name, just chemical formula. |
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energy : float | ||
The energy in eV. | ||
density : float, optional, Default is None | ||
The mass density of the packed powder/sample in gr/cm^3. If None, a standard density from XrayDB is used. | ||
packing_fraction : float, optional, Default is 1 | ||
The fraction of sample in the capillary (between 0 and 1). | ||
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Returns | ||
------- | ||
mu : float | ||
The attenuation coefficient mu in mm^{-1}. | ||
""" | ||
mu = material_mu(sample_composition, energy, density=density, kind="total") * packing_fraction / 10 | ||
return mu |
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import pytest | ||
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from diffpy.utils.tools import get_package_info, get_user_info | ||
from diffpy.utils.tools import compute_mu_using_xraydb, get_package_info, get_user_info | ||
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# def _setup_dirs(monkeypatch, user_filesystem): | ||
# home_dir, cwd_dir = user_filesystem.home_dir, user_filesystem.cwd_dir | ||
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) | ||
actual_metadata = get_package_info(inputs[0], metadata=inputs[1]) | ||
assert actual_metadata == expected | ||
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@pytest.mark.parametrize( | ||
"inputs, expected_mu", | ||
[ | ||
# Test whether the function returns the correct mu | ||
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( # C1: No density or packing fraction provided, expect to compute mu based on standard density | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. do we want to allow this? what is "standard density"? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Just density I think - density under the standard conditions. So user can specify either a measured density or packing fraction. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. The reason I'm not putting a strict "and/or" for density and packing fraction is that xraydb does not know the density to some materials like ZrO2. In this case user needs to put a density and a packing fraction, or they can put their measured density. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I see, so density is in the database? that is unexpected. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. how does xraydb compute the density? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I see, it has a database of some standard materials. So we will need tests for cases where the material can be found and cases where it can't. How many different materials are in that database? The examples show just a few satandard materials (Kapton, quartz, etc.). Is it an extensive database or just a few x-ray standards? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. How will you compute it for the cases where it is not in the db? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. They have densities for some materials (for example, this returns sample name and density: https://xraypy.github.io/XrayDB/python.html#xraydb.get_materials). |
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{ | ||
"sample_composition": "H2O", | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. water is probably not a good "illustrative" choice. Maybe use quartz instead? |
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"energy": 10000, | ||
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"density": None, | ||
"packing_fraction": 1, | ||
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}, | ||
0.5330, | ||
), | ||
( # C2: Packing fraction (=0.5) provided only, expect to return half of mu based on standard density | ||
{ | ||
"sample_composition": "H2O", | ||
"energy": 10000, | ||
"density": None, | ||
"packing_fraction": 0.5, | ||
}, | ||
0.2665, | ||
), | ||
( # C3: Density provided only, expect to compute mu based on density | ||
# 1. Standard density provided, expect to return the same mu as C1 | ||
{ | ||
"sample_composition": "H2O", | ||
"energy": 10000, | ||
"density": 0.997, | ||
"packing_fraction": 1, | ||
}, | ||
0.5330, | ||
), | ||
( # 2. Lower density for H2O (half of standard), expect to return half of mu based on standard density | ||
{ | ||
"sample_composition": "H2O", | ||
"energy": 10000, | ||
"density": 0.4985, | ||
"packing_fraction": 1, | ||
}, | ||
0.2665, | ||
), | ||
( # C4: Both standard density and packing fraction are provided, expect to compute the same mu as C2 | ||
{ | ||
"sample_composition": "H2O", | ||
"energy": 10000, | ||
"density": 0.997, | ||
"packing_fraction": 0.5, | ||
}, | ||
0.2665, | ||
), | ||
], | ||
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) | ||
def test_compute_mu_using_xraydb(inputs, expected_mu): | ||
actual_mu = compute_mu_using_xraydb( | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. here you put
which will unpack the input dict. You may have to handle the required args differently, but you can then have |
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inputs["sample_composition"], | ||
inputs["energy"], | ||
density=inputs["density"], | ||
packing_fraction=inputs["packing_fraction"], | ||
) | ||
assert actual_mu == pytest.approx(expected_mu, rel=0.01, abs=0.1) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. this seems a bit too loose? |
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added packing fraction. does this make sense or should we use None instead? I think if we set the default to 1 the code can be more concise
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I think setting to None is clearer here. The logic from the perspective of the user is that we either have a packing fraction or we don't. If it is None, you can set it to 1 in the code.
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Also, didn't we discuss to change the name to
sample_mass_density
?