source: sasmodels/sasmodels/models/sphere.py @ 2d81cfe

core_shell_microgelsmagnetic_modelticket-1257-vesicle-productticket_1156ticket_1265_superballticket_822_more_unit_tests
Last change on this file since 2d81cfe was 2d81cfe, checked in by Paul Kienzle <pkienzle@…>, 6 years ago

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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
39A Guinier and G. Fournet, *Small-Angle Scattering of X-Rays*,
40John Wiley and Sons, New York, (1955)
41
42*2013/09/09 and 2014/01/06 - Description reviewed by S King and P Parker.*
[5d4777d]43"""
44
[2d81cfe]45import numpy as np
[3c56da87]46from numpy import inf
[5d4777d]47
48name = "sphere"
[19dcb933]49title = "Spheres with uniform scattering length density"
[5d4777d]50description = """\
[49da079]51P(q)=(scale/V)*[3V(sld-sld_solvent)*(sin(qr)-qr cos(qr))
[eb69cce]52                /(qr)^3]^2 + background
53    r: radius of sphere
[19dcb933]54    V: The volume of the scatter
55    sld: the SLD of the sphere
[49da079]56    sld_solvent: the SLD of the solvent
[5d4777d]57"""
[a5d0d00]58category = "shape:sphere"
[5d4777d]59
[3e428ec]60#             ["name", "units", default, [lower, upper], "type","description"],
[42356c8]61parameters = [["sld", "1e-6/Ang^2", 1, [-inf, inf], "sld",
[3e428ec]62               "Layer scattering length density"],
[42356c8]63              ["sld_solvent", "1e-6/Ang^2", 6, [-inf, inf], "sld",
[3e428ec]64               "Solvent scattering length density"],
65              ["radius", "Ang", 50, [0, inf], "volume",
66               "Sphere radius"],
67             ]
[5d4777d]68
[925ad6e]69source = ["lib/sas_3j1x_x.c", "lib/sphere_form.c"]
[5d4777d]70
71# No volume normalization despite having a volume parameter
72# This should perhaps be volume normalized?
73form_volume = """
[ad90df9]74    return sphere_volume(radius);
[5d4777d]75    """
76
77Iq = """
[49da079]78    return sphere_form(q, radius, sld, sld_solvent);
[5d4777d]79    """
80
81def ER(radius):
[c691551]82    """
[364d8f7]83    Return equivalent radius (ER)
[c691551]84    """
[5d4777d]85    return radius
86
[97d89af]87# VR defaults to 1.0
88
[404ebbd]89def random():
90    radius = 10**np.random.uniform(1.3, 4)
91    pars = dict(
92        radius=radius,
93    )
94    return pars
95
[7e6bea81]96tests = [
97    [{}, 0.2, 0.726362],
98    [{"scale": 1., "background": 0., "sld": 6., "sld_solvent": 1.,
99      "radius": 120., "radius_pd": 0.2, "radius_pd_n":45},
100     0.2, 0.228843],
101    [{"radius": 120., "radius_pd": 0.2, "radius_pd_n":45}, "ER", 120.],
102    [{"radius": 120., "radius_pd": 0.2, "radius_pd_n":45}, "VR", 1.],
103]
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