Changeset ab60822 in sasmodels for sasmodels/models
- Timestamp:
- Sep 11, 2017 3:07:15 AM (7 years ago)
- Branches:
- master, core_shell_microgels, costrafo411, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
- Children:
- 3a45c2c, dd6885e
- Parents:
- c63a7c8 (diff), 30b60d2 (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent. - git-author:
- Wojciech Potrzebowski <Wojciech.Potrzebowski@…> (09/11/17 03:07:15)
- git-committer:
- GitHub <noreply@…> (09/11/17 03:07:15)
- Location:
- sasmodels/models
- Files:
-
- 12 edited
Legend:
- Unmodified
- Added
- Removed
-
sasmodels/models/binary_hard_sphere.py
r8f04da4 r30b60d2 23 23 :nowrap: 24 24 25 \begin{align }25 \begin{align*} 26 26 x &= \frac{(\phi_2 / \phi)\alpha^3}{(1-(\phi_2/\phi) + (\phi_2/\phi) 27 27 \alpha^3)} \\ 28 28 \phi &= \phi_1 + \phi_2 = \text{total volume fraction} \\ 29 29 \alpha &= R_1/R_2 = \text{size ratio} 30 \end{align }30 \end{align*} 31 31 32 32 The 2D scattering intensity is the same as 1D, regardless of the orientation of -
sasmodels/models/core_shell_bicelle.py
ra151caa r30b60d2 41 41 42 42 I(Q,\alpha) = \frac{\text{scale}}{V_t} \cdot 43 F(Q,\alpha)^2 .sin(\alpha) + \text{background}43 F(Q,\alpha)^2 \cdot sin(\alpha) + \text{background} 44 44 45 45 where 46 46 47 47 .. math:: 48 :nowrap: 48 49 49 \begin{align }50 \begin{align*} 50 51 F(Q,\alpha) = &\bigg[ 51 52 (\rho_c - \rho_f) V_c \frac{2J_1(QRsin \alpha)}{QRsin\alpha}\frac{sin(QLcos\alpha/2)}{Q(L/2)cos\alpha} \\ … … 53 54 &+(\rho_r - \rho_s) V_t \frac{2J_1(Q(R+t_r)sin\alpha)}{Q(R+t_r)sin\alpha}\frac{sin(Q(L/2+t_f)cos\alpha)}{Q(L/2+t_f)cos\alpha} 54 55 \bigg] 55 \end{align }56 \end{align*} 56 57 57 58 where $V_t$ is the total volume of the bicelle, $V_c$ the volume of the core, -
sasmodels/models/core_shell_bicelle_elliptical.py
r8f04da4 r30b60d2 42 42 43 43 I(Q,\alpha,\psi) = \frac{\text{scale}}{V_t} \cdot 44 F(Q,\alpha, \psi)^2 .sin(\alpha) + \text{background}44 F(Q,\alpha, \psi)^2 \cdot sin(\alpha) + \text{background} 45 45 46 where a numerical integration of $F(Q,\alpha, \psi)^2 .sin(\alpha)$ is carried out over \alpha and \psi for:46 where a numerical integration of $F(Q,\alpha, \psi)^2 \cdot sin(\alpha)$ is carried out over \alpha and \psi for: 47 47 48 48 .. math:: 49 :nowrap: 49 50 50 \begin{align}51 \begin{align*} 51 52 F(Q,\alpha,\psi) = &\bigg[ 52 53 (\rho_c - \rho_f) V_c \frac{2J_1(QR'sin \alpha)}{QR'sin\alpha}\frac{sin(QLcos\alpha/2)}{Q(L/2)cos\alpha} \\ … … 54 55 &+(\rho_r - \rho_s) V_t \frac{2J_1(Q(R'+t_r)sin\alpha)}{Q(R'+t_r)sin\alpha}\frac{sin(Q(L/2+t_f)cos\alpha)}{Q(L/2+t_f)cos\alpha} 55 56 \bigg] 56 \end{align }57 \end{align*} 57 58 58 59 where -
sasmodels/models/core_shell_ellipsoid.py
r9f6823b r30b60d2 44 44 45 45 .. math:: 46 \begin{align} 46 :nowrap: 47 48 \begin{align*} 47 49 F(q,\alpha) = &f(q,radius\_equat\_core,radius\_equat\_core.x\_core,\alpha) \\ 48 50 &+ f(q,radius\_equat\_core + thick\_shell,radius\_equat\_core.x\_core + thick\_shell.x\_polar\_shell,\alpha) 49 \end{align }51 \end{align*} 50 52 51 53 where -
sasmodels/models/fractal_core_shell.py
r8f04da4 r64eecf7 31 31 $\rho_{solv}$ are the scattering length densities of the core, shell, and 32 32 solvent respectively, $r_c$ and $r_s$ are the radius of the core and the radius 33 of the whole particle respectively, $D_f$ is the fractal dimension, and |xi|the33 of the whole particle respectively, $D_f$ is the fractal dimension, and $\xi$ the 34 34 correlation length. 35 35 -
sasmodels/models/hollow_rectangular_prism.py
r8f04da4 r30b60d2 31 31 :nowrap: 32 32 33 \begin{align }33 \begin{align*} 34 34 A_{P\Delta}(q) & = A B C 35 35 \left[\frac{\sin \bigl( q \frac{C}{2} \cos\theta \bigr)} … … 47 47 \left[ \frac{\sin \bigl[ q \bigl(\frac{B}{2}-\Delta\bigr) \sin\theta \cos\phi \bigr]} 48 48 {q \bigl(\frac{B}{2}-\Delta\bigr) \sin\theta \cos\phi} \right] 49 \end{align }49 \end{align*} 50 50 51 51 where $A$, $B$ and $C$ are the external sides of the parallelepiped fulfilling -
sasmodels/models/multilayer_vesicle.py
r142a8e2 r64eecf7 33 33 .. math:: 34 34 35 r_i &= r_c + (i-1)(t_s + t_w) &&\text{ solvent radius before shell } i \\36 R_i &= r_i + t_s &&\text{ shell radius for shell } i35 r_i &= r_c + (i-1)(t_s + t_w) \text{ solvent radius before shell } i \\ 36 R_i &= r_i + t_s \text{ shell radius for shell } i 37 37 38 38 $\phi$ is the volume fraction of particles, $V(r)$ is the volume of a sphere -
sasmodels/models/parallelepiped.py
r8f04da4 r30b60d2 20 20 Parallelepiped with the corresponding definition of sides. 21 21 22 .. note:: 23 24 The three dimensions of the parallelepiped (strictly here a cuboid) may be given in 25 $any$ size order. To avoid multiple fit solutions, especially 26 with Monte-Carlo fit methods, it may be advisable to restrict their ranges. There may 27 be a number of closely similar "best fits", so some trial and error, or fixing of some 28 dimensions at expected values, may help. 22 The three dimensions of the parallelepiped (strictly here a cuboid) may be 23 given in *any* size order. To avoid multiple fit solutions, especially 24 with Monte-Carlo fit methods, it may be advisable to restrict their ranges. 25 There may be a number of closely similar "best fits", so some trial and 26 error, or fixing of some dimensions at expected values, may help. 29 27 30 28 The 1D scattering intensity $I(q)$ is calculated as: -
sasmodels/models/rpa.py
r4f9e288 r30b60d2 30 30 These case numbers are different from those in the NIST SANS package! 31 31 32 The models are based on the papers by Akcasu et al. [#Akcasu]_and by33 Hammouda [#Hammouda]_assuming the polymer follows Gaussian statistics such32 The models are based on the papers by Akcasu *et al.* and by 33 Hammouda assuming the polymer follows Gaussian statistics such 34 34 that $R_g^2 = n b^2/6$ where $b$ is the statistical segment length and $n$ is 35 35 the number of statistical segment lengths. A nice tutorial on how these are 36 36 constructed and implemented can be found in chapters 28 and 39 of Boualem 37 Hammouda's 'SANS Toolbox' [#toolbox]_.37 Hammouda's 'SANS Toolbox'. 38 38 39 39 In brief the macroscopic cross sections are derived from the general forms … … 49 49 are calculated with respect to component D).** So the scattering contrast 50 50 for a C/D blend = [SLD(component C) - SLD(component D)]\ :sup:`2`. 51 * Depending on which case is being used, the number of fitting parameters can 51 * Depending on which case is being used, the number of fitting parameters can 52 52 vary. 53 53 … … 57 57 component are obtained from other methods and held fixed while The *scale* 58 58 parameter should be held equal to unity. 59 * The variables are normally the segment lengths (b\ :sub:`a`, b\ :sub:`b`, 60 etc) and $\chi$ parameters (K\ :sub:`ab`, K\ :sub:`ac`, etc). 61 59 * The variables are normally the segment lengths ($b_a$, $b_b$, 60 etc.) and $\chi$ parameters ($K_{ab}$, $K_{ac}$, etc). 62 61 63 62 References 64 63 ---------- 65 64 66 .. [#Akcasu] A Z Akcasu, R Klein and B Hammouda, *Macromolecules*, 26 (1993) 67 4136. 68 .. [#Hammouda] B. Hammouda, *Advances in Polymer Science* 106 (1993) 87. 69 .. [#toolbox] https://www.ncnr.nist.gov/staff/hammouda/the_sans_toolbox.pdf 65 A Z Akcasu, R Klein and B Hammouda, *Macromolecules*, 26 (1993) 4136. 66 67 B. Hammouda, *Advances in Polymer Science* 106 (1993) 87. 68 69 B. Hammouda, *SANS Toolbox* 70 https://www.ncnr.nist.gov/staff/hammouda/the_sans_toolbox.pdf. 70 71 71 72 Authorship and Verification -
sasmodels/models/star_polymer.py
r142a8e2 r30b60d2 7 7 emanating from a common central (in the case of this model) point. It is 8 8 derived as a special case of on the Benoit model for general branched 9 polymers\ [#CITBenoit]_ as also used by Richter ''et. al.''\ [#CITRichter]_9 polymers\ [#CITBenoit]_ as also used by Richter *et al.*\ [#CITRichter]_ 10 10 11 11 For a star with $f$ arms the scattering intensity $I(q)$ is calculated as -
sasmodels/models/surface_fractal.py
r48462b0 r30b60d2 9 9 10 10 .. math:: 11 :nowrap: 11 12 13 \begin{align*} 12 14 I(q) &= \text{scale} \times P(q)S(q) + \text{background} \\ 13 15 P(q) &= F(qR)^2 \\ … … 15 17 S(q) &= \Gamma(5-D_S)\xi^{\,5-D_S}\left[1+(q\xi)^2 \right]^{-(5-D_S)/2} 16 18 \sin\left[-(5-D_S) \tan^{-1}(q\xi) \right] q^{-1} \\ 17 \text{scale} &= \text{scale _factor}\, N V^2(\rho_\text{particle} - \rho_\text{solvent})^2 \\19 \text{scale} &= \text{scale factor}\, N V^1(\rho_\text{particle} - \rho_\text{solvent})^2 \\ 18 20 V &= \frac{4}{3}\pi R^3 21 \end{align*} 19 22 20 23 where $R$ is the radius of the building block, $D_S$ is the **surface** fractal -
sasmodels/models/line.py
r48462b0 rc63a7c8 15 15 16 16 .. math:: 17 17 18 I(q) = \text{scale} (I(qx) \cdot I(qy)) + \text{background} 18 19
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