source: sasmodels/sasmodels/models/sphere.py @ c036ddb

core_shell_microgelsmagnetic_modelticket-1257-vesicle-productticket_1156ticket_1265_superballticket_822_more_unit_tests
Last change on this file since c036ddb was c036ddb, checked in by Paul Kienzle <pkienzle@…>, 14 months ago

refactor so Iq is not needed if Fq is defined

  • Property mode set to 100644
File size: 3.2 KB
Line 
1r"""
2For information about polarised and magnetic scattering, see
3the :ref:`magnetism` documentation.
4
5Definition
6----------
7
8The 1D scattering intensity is calculated in the following way (Guinier, 1955)
9
10.. math::
11
12    I(q) = \frac{\text{scale}}{V} \cdot \left[
13        3V(\Delta\rho) \cdot \frac{\sin(qr) - qr\cos(qr))}{(qr)^3}
14        \right]^2 + \text{background}
15
16where *scale* is a volume fraction, $V$ is the volume of the scatterer,
17$r$ is the radius of the sphere and *background* is the background level.
18*sld* and *sld_solvent* are the scattering length densities (SLDs) of the
19scatterer and the solvent respectively, whose difference is $\Delta\rho$.
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
36References
37----------
38
39A Guinier and G. Fournet, *Small-Angle Scattering of X-Rays*,
40John Wiley and Sons, New York, (1955)
41
42* **Last Reviewed by:** S King and P Parker **Date:** 2013/09/09 and 2014/01/06
43"""
44
45import numpy as np
46from numpy import inf
47
48name = "sphere"
49title = "Spheres with uniform scattering length density"
50description = """\
51P(q)=(scale/V)*[3V(sld-sld_solvent)*(sin(qr)-qr cos(qr))
52                /(qr)^3]^2 + background
53    r: radius of sphere
54    V: The volume of the scatter
55    sld: the SLD of the sphere
56    sld_solvent: the SLD of the solvent
57"""
58category = "shape:sphere"
59
60#             ["name", "units", default, [lower, upper], "type","description"],
61parameters = [["sld", "1e-6/Ang^2", 1, [-inf, inf], "sld",
62               "Layer scattering length density"],
63              ["sld_solvent", "1e-6/Ang^2", 6, [-inf, inf], "sld",
64               "Solvent scattering length density"],
65              ["radius", "Ang", 50, [0, inf], "volume",
66               "Sphere radius"],
67             ]
68
69source = ["lib/sas_3j1x_x.c", "lib/sphere_form.c"]
70
71c_code = """
72static double form_volume(double radius)
73{
74    return sphere_volume(radius);
75}
76
77static void Fq(double q, double *F1,double *F2, double sld, double solvent_sld, double radius)
78{
79    const double fq = sas_3j1x_x(q*radius);
80    const double contrast = (sld - solvent_sld);
81    const double form = 1e-2 * contrast * sphere_volume(radius) * fq;
82    *F1 = form;
83    *F2 = form*form;
84}
85"""
86
87# TODO: figure this out by inspection
88have_Fq = True
89
90def ER(radius):
91    """
92    Return equivalent radius (ER)
93    """
94    return radius
95
96# VR defaults to 1.0
97
98def random():
99    radius = 10**np.random.uniform(1.3, 4)
100    pars = dict(
101        radius=radius,
102    )
103    return pars
104
105tests = [
106    [{}, 0.2, 0.726362],
107    [{"scale": 1., "background": 0., "sld": 6., "sld_solvent": 1.,
108      "radius": 120., "radius_pd": 0.2, "radius_pd_n":45},
109     0.2, 0.228843],
110    [{"radius": 120., "radius_pd": 0.2, "radius_pd_n":45}, "ER", 120.],
111    [{"radius": 120., "radius_pd": 0.2, "radius_pd_n":45}, "VR", 1.],
112]
Note: See TracBrowser for help on using the repository browser.