source: sasmodels/sasmodels/models/sphere.py @ c1e44e5

Last change on this file since c1e44e5 was c1e44e5, checked in by Paul Kienzle <pkienzle@…>, 5 years ago

Add local link to source files. Refs #1263.

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[5d4777d]1r"""
[40a87fa]2For information about polarised and magnetic scattering, see
[9a4811a]3the :ref:`magnetism` documentation.
[19dcb933]4
5Definition
6----------
7
8The 1D scattering intensity is calculated in the following way (Guinier, 1955)
9
10.. math::
11
[eb69cce]12    I(q) = \frac{\text{scale}}{V} \cdot \left[
13        3V(\Delta\rho) \cdot \frac{\sin(qr) - qr\cos(qr))}{(qr)^3}
[19dcb933]14        \right]^2 + \text{background}
15
16where *scale* is a volume fraction, $V$ is the volume of the scatterer,
[7e6bea81]17$r$ is the radius of the sphere and *background* is the background level.
[49da079]18*sld* and *sld_solvent* are the scattering length densities (SLDs) of the
[7e6bea81]19scatterer and the solvent respectively, whose difference is $\Delta\rho$.
[19dcb933]20
21Note that if your data is in absolute scale, the *scale* should represent
22the volume fraction (which is unitless) if you have a good fit. If not,
23it should represent the volume fraction times a factor (by which your data
24might need to be rescaled).
25
26The 2D scattering intensity is the same as above, regardless of the
27orientation of $\vec q$.
28
29Validation
30----------
31
32Validation of our code was done by comparing the output of the 1D model
33to the output of the software provided by the NIST (Kline, 2006).
34
35
[eb69cce]36References
37----------
[19dcb933]38
[0507e09]39.. [#] A Guinier and G. Fournet, *Small-Angle Scattering of X-Rays*, John Wiley and Sons, New York, (1955)
[19dcb933]40
[0507e09]41Authorship and Verification
42----------------------------
43
[c1e44e5]44* **Author:**
45* **Last Modified by:**
[ef07e95]46* **Last Reviewed by:** S King and P Parker **Date:** 2013/09/09 and 2014/01/06
[5d4777d]47"""
48
[2d81cfe]49import numpy as np
[3c56da87]50from numpy import inf
[5d4777d]51
52name = "sphere"
[19dcb933]53title = "Spheres with uniform scattering length density"
[5d4777d]54description = """\
[49da079]55P(q)=(scale/V)*[3V(sld-sld_solvent)*(sin(qr)-qr cos(qr))
[eb69cce]56                /(qr)^3]^2 + background
57    r: radius of sphere
[19dcb933]58    V: The volume of the scatter
59    sld: the SLD of the sphere
[49da079]60    sld_solvent: the SLD of the solvent
[5d4777d]61"""
[a5d0d00]62category = "shape:sphere"
[5d4777d]63
[3e428ec]64#             ["name", "units", default, [lower, upper], "type","description"],
[42356c8]65parameters = [["sld", "1e-6/Ang^2", 1, [-inf, inf], "sld",
[3e428ec]66               "Layer scattering length density"],
[42356c8]67              ["sld_solvent", "1e-6/Ang^2", 6, [-inf, inf], "sld",
[3e428ec]68               "Solvent scattering length density"],
69              ["radius", "Ang", 50, [0, inf], "volume",
70               "Sphere radius"],
71             ]
[5d4777d]72
[b297ba9]73source = ["lib/sas_3j1x_x.c", "sphere.c"]
[71b751d]74have_Fq = True
[d277229]75effective_radius_type = ["radius"]
[c036ddb]76
[404ebbd]77def random():
[b297ba9]78    """Return a random parameter set for the model."""
[404ebbd]79    radius = 10**np.random.uniform(1.3, 4)
80    pars = dict(
81        radius=radius,
82    )
83    return pars
84
[7e6bea81]85tests = [
86    [{}, 0.2, 0.726362],
87    [{"scale": 1., "background": 0., "sld": 6., "sld_solvent": 1.,
88      "radius": 120., "radius_pd": 0.2, "radius_pd_n":45},
89     0.2, 0.228843],
[304c775]90    [{"radius": 120., "radius_pd": 0.2, "radius_pd_n":45},
91     0.1, None, None, 120., None, 1.0],
[81751c2]92    [{"@S": "hardsphere"}, 0.1, None],
[7e6bea81]93]
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