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# superball model
# Note: model title and parameter table are inserted automatically
r"""
Definition
----------
.. figure:: img/superball_realSpace.png
Superball visualisation for varied values of the parameter p.
This model calculates the scattering of a superball, which represents a cube
with rounded edges. It can be used to describe nanoparticles that deviate from
the perfect cube shape as it is often observed experimentally
[#WetterskogSuperball]_. The shape is described by
.. math::
x^{2p} + y^{2p} + z^{2p} \leq \biggl( \frac{a}{2} \biggr)^{2p}
with $a$ the cube edge length of the superball and $p$ a parameter that
describes the roundness of the edges. In the limiting cases $p=1$ the superball
corresponds to a sphere with radius $R = a/2$ and for $p = \infty$ to a cube
with edge length $a$. The exponent $p$ is related to $a$ and the face diagonal
$d$ via
.. math::
p = \frac{1}{1 + 2 \mathrm{log}_2 (a/d)}.
.. figure:: img/superball_geometry2d.png
Cross-sectional view of a superball showing the principal axis length $a$,
the face-diagonal $d$ and the superball radius $R$.
The oriented form factor is determined by solving
.. math::
p_o(\vec{q}) =& \int_{V} \mathrm{d} \vec{r} e^{i \vec{q} \cdot \vec{r}}\\
=& \frac{a^3}{8} \int_{-1}^{1} \mathrm{d} x \int_{-\gamma}^{\gamma}
\mathrm{d} y \int_{-\zeta}^{\zeta} \mathrm{d} z
e^{i a (q_x x + q_y y + q_z z) / 2}\\
=& \frac{a^2}{2 q_z} \int_{-1}^{1} \mathrm{d} x \int_{-\gamma}^{\gamma}
\mathrm{d} y e^{i a(q_x x + q_y y)/2}
\sin(q_z a \zeta / 2),
with
.. math::
\gamma =& \sqrt[2p]{1-x^{2p}}, \\
\zeta =& \sqrt[2p]{1-x^{2p} -y^{2p}}.
The integral can be transformed to
.. math::
p_o(\vec{q}) = \frac{2 a^2}{q_z} \int_{0}^{1} \mathrm{d} x \, \cos
\biggl(\frac{a q_x x}{2} \biggr) \int_{0}^{\gamma} \mathrm{d} y \,
\cos \biggl( \frac{a q_y y}{2} \biggr) \sin
\biggl( \frac{a q_z \zeta}{2} \biggr),
which can be solved numerically.
The orientational average is then obtained by calculating
.. math::
P(q) = \int_0^{\tfrac{\pi}{2}} \mathrm{d} \varphi \int_0^{\tfrac{\pi}{2}}
\mathrm{d} \theta \, \sin (\theta) | p_o(\vec{q}) |^2
with
.. math::
\vec{q} &= q \begin{pmatrix} \cos (\varphi) \sin (\theta)\\
\sin (\varphi) \sin(\theta)\\
\cos (\theta)\end{pmatrix}
The implemented orientationally averaged superball model is then fully given by
[#DresenSuperball]_
.. math::
I(q) = \mathrm{scale} (\Delta \rho)^2 P(q) + \mathrm{background}.
FITTING NOTES
~~~~~~~~~~~~~
Validation
----------
The code is validated by reproducing the spherical form factor implemented
in SasView for $p = 1$ and the parallelepiped form factor with $a = b = c$ for
$p = 1000$. The form factors match in the first order oscillation with a
precision in the order of $10^{-4}$. The agreement worsens for higher order
oscillations and beyond the third order oscillations a higher order Gauss
quadrature rule needs to be used to keep the agreement below $10^{-3}$.
This is however avoided in this implementation to keep the computation time
fast.
References
----------
.. [#WetterskogSuperball] E. Wetterskog, A. Klapper, S. Disch, E. Josten, R. P. Hermann, U. Rücker, T. Brückel, L. Bergström and G. Salazar-Alvarez, *Nanoscale*, 8 (2016) 15571
.. [#DresenSuperball] D. Dresen, A. Qdemat, S. Ulusoy, F. Mees, D. Zakutna, E. Wetterskog, E. Kentzinger, G. Salazar-Alvarez, S. Disch, *J. Phys. Chem. C* (2021), doi: 10.1021/acs.jpcc.1c06082
Source
------
`superball.py <https://github.com/SasView/sasmodels/blob/master/sasmodels/models/superball.py>`_
`superball.c <https://github.com/SasView/sasmodels/blob/master/sasmodels/models/superball.c>`_
Authorship and Verification
----------------------------
* **Author:** Dominique Dresen **Date:** March 27, 2019
* **Last Modified by:** Dominique Dresen **Date:** March 27, 2019
* **Last Reviewed by:** Dirk Honecker **Date:** November 05, 2021
* **Source added by :** Dominique Dresen **Date:** March 27, 2019"""
import numpy as np
from numpy import inf
# saved in utf-8 encoding for the German umlaut (üö)
name = "superball"
title = "Superball with uniform scattering length density."
description = """
I(q)= scale*V*(sld - sld_solvent)^2*P(q)+background
P(q) = (2/pi) * double integral from 0 to pi/2 of ...
AP^2(q)*sin(theta)*dtheta*dphi
AP = integral from -1 to 1 integral from -g to g of ...
cos(R qx x) cos(R qy y]) sin(R qz Ze)
g = (1 - x^(2p))^(1/(2p))
Ze = (1 - x^(2p) - y^(2p))^(1/(2p))
"""
category = "shape:sphere"
# ["name", "units", default, [lower, upper], "type","description"],
parameters = [["sld", "1e-6/Ang^2", 4, [-inf, inf], "sld",
"Superball scattering length density"],
["sld_solvent", "1e-6/Ang^2", 1, [-inf, inf], "sld",
"Solvent scattering length density"],
["length_a", "Ang", 50, [0, inf], "volume",
"Cube edge length of the superball"],
["exponent_p", "", 2.5, [0, inf], "volume",
"Exponent describing the roundness of the superball"],
["theta", "degrees", 0, [-360, 360], "orientation",
"c axis to beam angle"],
["phi", "degrees", 0, [-360, 360], "orientation",
"rotation about beam"],
["psi", "degrees", 0, [-360, 360], "orientation",
"rotation about c axis"],
]
# lib/gauss76.c
# lib/gauss20.c
source = ["lib/gauss20.c", "lib/sas_gamma.c", "superball.c"]
have_Fq = True
radius_effective_modes = [
"radius of gyration",
"equivalent volume sphere",
"half length_a",
]
def random():
"""Return a random parameter set for the model."""
length = np.random.uniform(10, 500)
exponent = np.random.uniform(1.5, 5)
pars = dict(
length_a=length,
exponent_p=exponent)
return pars
# parameters for demo
demo = dict(scale=1, background=0,
sld=6.3, sld_solvent=1.0,
length_a=100, exponent_p=2.5,
theta=45, phi=30, psi=15,
length_a_pd=0.1, length_a_pd_n=10,
theta_pd=10, theta_pd_n=1,
phi_pd=10, phi_pd_n=1,
psi_pd=10, psi_pd_n=1)
tests = [
[{}, 0.2, 0.76833],
[{"length_a": 100., "exponent_p": 1, "sld": 6., "sld_solvent": 1.},
0.2, 0.7263],
[{"length_a": 100., "exponent_p": 1000, "sld": 6., "sld_solvent": 1.},
0.2, 0.2714],
[{"length_a": 100., "exponent_p": 2.5, "sld": 6., "sld_solvent": 1.},
0.2, 0.2810],
[{"length_a": 100., "exponent_p": 2.5, "sld": 6., "sld_solvent": 1.,
"length_a_pd": 0.1, "length_a_pd_n": 10},
0.2, 0.49551865],
]
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