# source:sasmodels/sasmodels/models/stacked_disks.py@0507e09

core_shell_microgelsmagnetic_modelticket-1257-vesicle-productticket_1156ticket_1265_superballticket_822_more_unit_tests
Last change on this file since 0507e09 was 0507e09, checked in by smk78, 17 months ago

• Property mode set to 100644
File size: 11.0 KB
Line
1r"""
2Definition
3----------
4
5This model provides the form factor, $P(q)$, for stacked discs (tactoids)
6with a core/layer structure which is constructed itself as $P(q) S(Q)$
7multiplying a $P(q)$ for individual core/layer disks by a structure factor
8$S(q)$ proposed by Kratky and Porod in 1949\ [#CIT1949]_ assuming the next
9neighbor distance (d-spacing) in the stack of parallel discs obeys a Gaussian
10distribution. As such the normalization of this "composite" form factor is
11relative to the individual disk volume, not the volume of the stack of disks.
12This model is appropriate for example for non non exfoliated clay particles
13such as Laponite.
14
15.. figure:: img/stacked_disks_geometry.png
16
17   Geometry of a single core/layer disk
18
19The scattered intensity $I(q)$ is calculated as
20
21.. math::
22
23    I(q) = N\int_{0}^{\pi /2}\left[ \Delta \rho_t
24    \left( V_t f_t(q,\alpha) - V_c f_c(q,\alpha)\right) + \Delta
25    \rho_c V_c f_c(q,\alpha)\right]^2 S(q,\alpha)\sin{\alpha}\ d\alpha
26    + \text{background}
27
28where the contrast
29
30.. math::
31
32    \Delta \rho_i = \rho_i - \rho_\text{solvent}
33
34and $N$ is the number of individual (single) discs per unit volume, $\alpha$
35is the angle between the axis of the disc and $q$, and $V_t$ and $V_c$ are the
36total volume and the core volume of a single disc, respectively, and
37
38.. math::
39
40    f_t(q,\alpha) =
41    \left(\frac{\sin(q(d+h)\cos{\alpha})}{q(d+h)\cos{\alpha}}\right)
42    \left(\frac{2J_1(qR\sin{\alpha})}{qR\sin{\alpha}} \right)
43
44    f_c(q,\alpha) =
45    \left(\frac{\sin(qh)\cos{\alpha})}{qh\cos{\alpha}}\right)
46    \left(\frac{2J_1(qR\sin{\alpha})}{qR\sin{\alpha}}\right)
47
48where $d$ = thickness of the layer (*thick_layer*),
49$2h$ = core thickness (*thick_core*), and $R$ = radius of the disc (*radius*).
50
51.. math::
52
53    S(q,\alpha) = 1 + \frac{1}{2}\sum_{k=1}^n(n-k)\cos{(kDq\cos{\alpha})}
54    \exp\left[ -k(q)^2(D\cos{\alpha}~\sigma_d)^2/2\right]
55
56where $n$ is the total number of the disc stacked (*n_stacking*),
57$D = 2(d+h)$ is the next neighbor center-to-center distance (d-spacing),
58and $\sigma_d$ = the Gaussian standard deviation of the d-spacing (*sigma_d*).
59Note that $D\cos(\alpha)$ is the component of $D$ parallel to $q$ and the last
60term in the equation above is effectively a Debye-Waller factor term.
61
62.. note::
63
64    1. Each assembly in the stack is layer/core/layer, so the spacing of the
65    cores is core plus two layers. The 2nd virial coefficient of the cylinder
66    is calculated based on the *radius* and *length*
67    = *n_stacking* * (*thick_core* + 2 * *thick_layer*)
68    values, and used as the effective radius for $S(Q)$ when $P(Q) * S(Q)$
69    is applied.
70
71    2. the resolution smearing calculation uses 76 Gaussian quadrature points
72    to properly smear the model since the function is HIGHLY oscillatory,
73    especially around the q-values that correspond to the repeat distance of
74    the layers.
75
762d scattering from oriented stacks is calculated in the same way as for
77cylinders, for further details of the calculation and angular dispersions
78see :ref:orientation.
79
80.. figure:: img/cylinder_angle_definition.png
81
82    Angles $\theta$ and $\phi$ orient the stack of discs relative
83    to the beam line coordinates, where the beam is along the $z$ axis.
84    Rotation $\theta$, initially in the $xz$ plane, is carried out first,
85    then rotation $\phi$ about the $z$ axis. Orientation distributions are
86    described as rotations about two perpendicular axes $\delta_1$ and
87    $\delta_2$ in the frame of the cylinder itself, which when
88    $\theta = \phi = 0$ are parallel to the $Y$ and $X$ axes.
89
90
91Our model is derived from the form factor calculations implemented in a
92c-library provided by the NIST Center for Neutron Research\ [#CIT_Kline]_
93
94References
95----------
96
97.. [#CIT1949] O Kratky and G Porod, *J. Colloid Science*, 4, (1949) 35
98.. [#CIT_Kline] S R Kline, *J Appl. Cryst.*, 39 (2006) 895
99.. [#] J S Higgins and H C Benoit, *Polymers and Neutron Scattering*,
100   Clarendon, Oxford, 1994
101.. [#] A Guinier and G Fournet, *Small-Angle Scattering of X-Rays*,
102   John Wiley and Sons, New York, 1955
103
104Source
105------
106
107stacked_disks.py <https://github.com/SasView/sasmodels/blob/master/sasmodels/models/stacked_disks.py>_
108
109stacked_disks.c <https://github.com/SasView/sasmodels/blob/master/sasmodels/models/stacked_disks.c>_
110
111Authorship and Verification
112----------------------------
113
114* **Author:** NIST IGOR/DANSE **Date:** pre 2010
115* **Last Modified by:** Paul Butler and Paul Kienzle **Date:** November 26, 2016
116* **Last Reviewed by:** Paul Butler and Paul Kienzle **Date:** November 26, 2016
117* **Source added by :** Steve King **Date:** March 25, 2019
118"""
119
120import numpy as np
121from numpy import inf, sin, cos, pi
122
123name = "stacked_disks"
124title = "Form factor for a stacked set of non exfoliated core/shell disks"
125description = """\
126    One layer of disk consists of a core, a top layer, and a bottom layer.
128    thick_core = thickness of the core
129    thick_layer = thickness of a layer
130    sld_core = the SLD of the core
131    sld_layer = the SLD of the layers
132    n_stacking = the number of the disks
133    sigma_d =  Gaussian STD of d-spacing
134    sld_solvent = the SLD of the solvent
135    """
136category = "shape:cylinder"
137
139#   ["name", "units", default, [lower, upper], "type","description"],
140parameters = [
141    ["thick_core",  "Ang",        10.0, [0, inf],    "volume",      "Thickness of the core disk"],
142    ["thick_layer", "Ang",        10.0, [0, inf],    "volume",      "Thickness of layer each side of core"],
143    ["radius",      "Ang",        15.0, [0, inf],    "volume",      "Radius of the stacked disk"],
144    ["n_stacking",  "",            1.0, [1, inf],    "volume",      "Number of stacked layer/core/layer disks"],
145    ["sigma_d",     "Ang",         0,   [0, inf],    "",            "Sigma of nearest neighbor spacing"],
146    ["sld_core",    "1e-6/Ang^2",  4,   [-inf, inf], "sld",         "Core scattering length density"],
147    ["sld_layer",   "1e-6/Ang^2",  0.0, [-inf, inf], "sld",         "Layer scattering length density"],
148    ["sld_solvent", "1e-6/Ang^2",  5.0, [-inf, inf], "sld",         "Solvent scattering length density"],
149    ["theta",       "degrees",     0,   [-360, 360], "orientation", "Orientation of the stacked disk axis w/respect incoming beam"],
150    ["phi",         "degrees",     0,   [-360, 360], "orientation", "Rotation about beam"],
151    ]
153
154source = ["lib/polevl.c", "lib/sas_J1.c", "lib/gauss76.c", "stacked_disks.c"]
155
156def random():
157    """Return a random parameter set for the model."""
159    total_stack = 10**np.random.uniform(1, 4.7)
160    n_stacking = int(10**np.random.uniform(0, np.log10(total_stack)-1) + 0.5)
161    d = total_stack/n_stacking
162    thick_core = np.random.uniform(0, d-2)  # at least 1 A for each layer
163    thick_layer = (d - thick_core)/2
164    # Let polydispersity peak around 15%; 95% < 0.4; max=100%
165    sigma_d = d * np.random.beta(1.5, 7)
166    pars = dict(
167        thick_core=thick_core,
168        thick_layer=thick_layer,
170        n_stacking=n_stacking,
171        sigma_d=sigma_d,
172    )
173    return pars
174
175demo = dict(background=0.001,
176            scale=0.01,
177            thick_core=10.0,
178            thick_layer=10.0,
180            n_stacking=1,
181            sigma_d=0,
182            sld_core=4,
183            sld_layer=0.0,
184            sld_solvent=5.0,
185            theta=90,
186            phi=0)
187# After redefinition of spherical coordinates -
188# tests had in old coords theta=0, phi=0; new coords theta=90, phi=0
189q = 0.1
190# april 6 2017, rkh added a 2d unit test, assume correct!
191qx = q*cos(pi/6.0)
192qy = q*sin(pi/6.0)
193# Accuracy tests based on content in test/utest_extra_models.py.
194# Added 2 tests with n_stacked = 5 using SasView 3.1.2 - PDB;
195# for which alas q=0.001 values seem closer to n_stacked=1 not 5,
196# changed assuming my 4.1 code OK, RKH
197tests = [
198    [{'thick_core': 10.0,
199      'thick_layer': 15.0,
201      'n_stacking': 1.0,
202      'sigma_d': 0.0,
203      'sld_core': 4.0,
204      'sld_layer': -0.4,
205      'sld_solvent': 5.0,
206      'theta': 90.0,
207      'phi': 0.0,
208      'scale': 0.01,
209      'background': 0.001,
210     }, 0.001, 5075.12],
211    [{'thick_core': 10.0,
212      'thick_layer': 15.0,
214      'n_stacking': 5,
215      'sigma_d': 0.0,
216      'sld_core': 4.0,
217      'sld_layer': -0.4,
218      'sld_solvent': 5.0,
219      'theta': 90.0,
220      'phi': 0.0,
221      'scale': 0.01,
222      'background': 0.001,
223      # n_stacking=1 not 5 ? slight change in value here 11jan2017,
224      # check other cpu types
225      #}, 0.001, 5065.12793824],
226      #}, 0.001, 5075.11570493],
227     }, 0.001, 25325.635693],
228    [{'thick_core': 10.0,
229      'thick_layer': 15.0,
231      'n_stacking': 5,
232      'sigma_d': 0.0,
233      'sld_core': 4.0,
234      'sld_layer': -0.4,
235      'sld_solvent': 5.0,
236      'theta': 90.0,
237      'phi': 20.0,
238      'scale': 0.01,
239      'background': 0.001,
240     }, (qx, qy), 0.0491167089952],
241    [{'thick_core': 10.0,
242      'thick_layer': 15.0,
244      'n_stacking': 5,
245      'sigma_d': 0.0,
246      'sld_core': 4.0,
247      'sld_layer': -0.4,
248      'sld_solvent': 5.0,
249      'theta': 90.0,
250      'phi': 0.0,
251      'scale': 0.01,
252      'background': 0.001,
253      # n_stacking=1 not 5 ?  slight change in value here 11jan2017,
254      # check other cpu types
255      #}, 0.164, 0.0127673597265],
256      #}, 0.164, 0.01480812968],
257     }, 0.164, 0.0598367986509],
258
259    [{'thick_core': 10.0,
260      'thick_layer': 15.0,
262      'n_stacking': 1.0,
263      'sigma_d': 0.0,
264      'sld_core': 4.0,
265      'sld_layer': -0.4,
266      'sld_solvent': 5.0,
267      'theta': 90.0,
268      'phi': 0.0,
269      'scale': 0.01,
270      'background': 0.001,
271      # second test here was at q=90, changed it to q=5,
272      # note I(q) is then just value of flat background
273     }, [0.001, 5.0], [5075.12, 0.001]],
274
275    [{'thick_core': 10.0,
276      'thick_layer': 15.0,
278      'n_stacking': 1.0,
279      'sigma_d': 0.0,
280      'sld_core': 4.0,
281      'sld_layer': -0.4,
282      'sld_solvent': 5.0,
283      'theta': 90.0,
284      'phi': 0.0,
285      'scale': 0.01,
286      'background': 0.001,
287     }, ([0.4, 0.5]), [0.00105074, 0.00121761]],
288    #[{'thick_core': 10.0,
289    #  'thick_layer': 15.0,
291    #  'n_stacking': 1.0,
292    #  'sigma_d': 0.0,
293    #  'sld_core': 4.0,
294    #  'sld_layer': -0.4,
295    #  'sld_solvent': 5.0,
296    #  'theta': 90.0,
297    #  'phi': 20.0,
298    #  'scale': 0.01,
299    #  'background': 0.001,
300    # 2017-05-18 PAK temporarily suppress output of qx,qy test; j1 is
301    #     not accurate for large qr
302    # }, (qx, qy), 0.0341738733124],
303    # }, (qx, qy), None],
304
305    [{'thick_core': 10.0,
306      'thick_layer': 15.0,