Python bindings for the Scattering Equation Builder (SEB) library
Project description
Notes for this repository in developing
Release Development Goals
The current development targets are:
- Make setup straightforward for users with a standard Python 3 installation.
- Enable installation with a single command:
pip install pyseb. - Return scattering equations as native SymPy expressions for downstream symbolic and numerical workflows.
- Keep GiNAC workflow as is in the old repository.
Future Development Goals
- Add import/export support for
Worldstructures, so users can save and reload models from files.
Documentation
- Python usage and packaging: docs/python.md
- Symbolic backend architecture: docs/symbolic-backends.md
- Symbolic abstraction design notes: docs/design/symbolic-abstraction.md
Developer note: build options
The canonical build uses CMake + Ninja. The top-level makefile is now only a
thin convenience wrapper around those CMake commands.
1) Build with Makefile shortcuts
Build the portable C++ core:
$ cd /home/tobi/pySEB
$ make core
Build with the optional GiNaC backend:
$ cd /home/tobi/pySEB
$ make ginac
Build the Python extension:
$ cd /home/tobi/pySEB
$ make python
Build and run C++ tests:
$ cd /home/tobi/pySEB
$ make tests
2) Build with CMake + Ninja (recommended)
$ cd /home/tobi/pySEB
$ cmake -S . -B build-core -G Ninja -DCMAKE_BUILD_TYPE=Release -DBUILD_PYTHON=OFF -DSEB_ENABLE_GINAC_BACKEND=OFF
$ cmake --build build-core --target seb seb-symbolic
Build with the optional GiNaC backend:
$ cd /home/tobi/pySEB
$ cmake -S . -B build-ninja-ginac -G Ninja -DCMAKE_BUILD_TYPE=Release -DBUILD_PYTHON=OFF -DSEB_ENABLE_GINAC_BACKEND=ON
$ cmake --build build-ninja-ginac
3) Build and run tests (CTest)
$ cd /home/tobi/pySEB
$ cmake -S . -B build-ninja-ginac -G Ninja -DCMAKE_BUILD_TYPE=Release -DBUILD_PYTHON=OFF -DSEB_ENABLE_GINAC_BACKEND=ON
$ cmake --build build-ninja-ginac
$ cmake -S Tests -B Tests/build-ninja -G Ninja -DCMAKE_BUILD_TYPE=Release -DSEB_BUILD_DIR=/home/tobi/pySEB/build-ninja-ginac
$ cmake --build Tests/build-ninja
$ ctest --test-dir Tests/build-ninja --output-on-failure
4) Install pySEB locally with pip (developer workflow)
Create and use a virtual environment:
$ cd /home/tobi/pySEB
$ python3 -m venv venv
$ source venv/bin/activate
$ python -m pip install -U pip setuptools wheel
Editable install from source (recommended while developing):
$ python -m pip install -e .
Quick smoke test:
python - <<'PY'
import pyseb
w = pyseb.World()
print("pyseb OK", type(w).__name__)
PY
Optional: build and install wheel locally:
$ python -m pip install -U build
$ python -m build
$ python -m pip install dist/pyseb-0.1.0-cp311-cp311-linux_x86_64.whl
5) What must be true before users can run pip install pyseb
This project now has packaging CI for source distributions and desktop Python
wheels, and the Packaging workflow currently builds green wheels for every
target platform. Before a real public pip install pyseb release, the
remaining external release work is:
-
Publish artifacts to PyPI Build and upload both sdist and wheels after the packaging workflow is green. This still needs a tagged release run.
-
Build wheels for supported Python versions and desktop platforms ✅ Supported Python versions are currently 3.9, 3.10, 3.11, and 3.12. Wheels build and repair successfully for Linux x86_64 (manylinux), Windows AMD64, macOS x86_64 (Intel, macOS 14+), and macOS arm64 (Apple Silicon, macOS 15+). iPhone/iPad iOS wheels are not part of the first release.
-
Keep test suite green C++ tests are release-gated by the
Packagingworkflow's CTest job. -
Keep Python API and docs/examples aligned
docs/python.md,pyseb/examples/python/sympy_example.py, and the Python smoke tests use the currentWorld.Add(...)/World.Link(...)calling style. -
Release securely Configure PyPI trusted publishing (register this GitHub repository/workflow as a trusted publisher on the PyPI project settings) before uploading artifacts from CI. The
release.ymlpublish job already requestsid-token: writeand usespypa/gh-action-pypi-publish, so no code change is needed once the PyPI-side trust relationship is configured.
Unsupported platforms can still install from source if Python 3.9+, CMake, a C++ compiler, pybind11, GSL, and platform-specific build tools are available.
Current Codebase Challenges
-
Test stability needs to stay visible
The current C++ suite is passing, but reliability should remain release-gated by the CTest and Python smoke-test workflows. -
Build workflows are fragmented
Multiple parallel build paths (Make, CMake, Ninja, Python packaging) increase maintenance overhead and developer confusion. -
Architecture is partially modularized, but build boundaries still need care
Symbolic backend logic lives inseb-symbolic, and Python bindings are optional withBUILD_PYTHON. The active source layout is split intoseb/for the C++ scattering core,seb-symbolic/for symbolic expressions/backends, andpyseb/for Python bindings, package code, examples, and Python tests.- Keep new symbolic engines as backend-specific implementations registered through
SymbolicFactory. - Keep
pySEBas a thin binding/package layer over the stablesebandseb-symbolictargets.
- Keep new symbolic engines as backend-specific implementations registered through
-
Adding new sub-units has become harder
The implementation and validation path for new sub-units is more complex than before, which slows development. -
Documentation drift exists
Several Markdown docs are outdated or inconsistent with current build steps and API behavior. -
Technical debt
Some inheritance paths are currently messy. For example,GiNaCSymbolic.hppcontains a temporary compatibility inheritance used as a quick fix:// Backward compatibility for legacy code paths that still construct GiNaCSymbolic. class GiNaCSymbolic : public GiNaCFactory { };
Current C++ test status in this development branch: 8/8 passing with ctest --test-dir Tests/build-ninja --output-on-failure.
Scattering Equation Builder - SEB
SEB is a C++ library where one can build a structure by linking sub-units such as polymers or geometric shapes together and then ask SEB to analytically derive a symbolic expression for the small angle scattering of the structure.
Introduction
SEB is a C++ library that allows you to build structures from sub-units such as spheres, polymers, rods, etc., and obtain their scattering properties symbolically. SEB provides functions that enable you to attach sub-units together at specific points called reference points, and compute the form factor of a composite structure, $F$, the radius of gyration, $R^2_g$, and other scattering properties relevant for structures in solution.
Workflow
To give you a quick overview of how SEB works, imagine a structure that you want to build from the available sub-units. You can use SEB to write a short C++ program that defines the structure by creating and linking sub-units together, and generate the form factor as a symbolic equation. You can then plot the equation by substituting the symbols with numerical values. A typical work flow of SEB is shown in the following picture:
- Here we imagine a star-polymer structure one can build from the given sub-units.
- Using the SEB library, we write a small C++ program to build the structure by attaching GaussianPolymer sub-units to a central point.
- End the code with calling
cout << getFormFactor("PolymerStar") << endlto analytically calculate a symbolic expression for the form factor. - Graph the equation by substituting the symbols in the equation for specific values.
Supported Subunits
Overview of supported sub-units (SEB V1.0): a) a solid cylinder (SolidCylinder: center, hull, ends, surface), b) a solid sphere (SolidSphere: center, surface), c) a solid spherical shell (SolidSphericalShell: center, surfacei, surfaceo, surface), d) a thin spherical shell (ThinSphericalShell: center, surface), e) a thin disk (ThinDisk: center, surface, rim), f) a linear polymer (GaussianPolymer: end1, end2, middle, contour), g) a polymer loop (GaussianLoop: contour), h) a thin circle (ThinCircle: center, contour), i) a thin rod (ThinRod: end1, end2, middle, contour), j) an invisible point (Point: point). For each sub-unit type, the parenthesis shows its SEB name and reference points by which it can be linked to other sub-units.
Example structures
| --- | --- |
|---|---|
Structures and form factors. Top left image) linear chains of different types of sub-units, Top right image) dendrimers of different types of sub-units, bottom left image) Rods and polymers attached to different surfaces on geometric bodies, and bottom right image) chain of 5 di-block copolymer stars and its form factor for three different contrasts. See the SEB paper for details and the PaperFigs folder for the code to generate these.
SEB Articles
The theory behind SEB can be found in the journal articles: Carsten Svaneborg, Jan Skov Pedersen, J. Chem. Phys. 136, 104105 (2012) "A formalism for scattering of complex composite structures. I. Applications to branched structures of asymmetric sub-units" and Carsten Svaneborg, Jan Skov Pedersen, J. Chem. Phys. 136, 154907 (2012) "A formalism for scattering of complex composite structures. II. Distributed reference points"
The reference for the SEB library itself is Tobias W. J. Jarrett and Carsten Svaneborg "A computational tool for symbolic derivation of the small angle scattering from complex composite structures", Journal of Applied Crystallography 57, 587 (2024). See below for Bibtex citations for these papers.
SEB's wiki
If you need API information or want more examples than below on how to use SEB please see the wiki (still under construction).
Installing
SEB has only been compiled on linux systems and has not been extensively tested on mac OS or Windows. If you are using Windows, we recommend using the Windows Subsystem for Linux (WSL), search for it in the search bar. Before downloading the source code make sure you have installed
- A working C++11 compliant compiler.
- A standard development environment with make and git.
- The GiNaC symbolic manipulation library for C++. GiNaC depends on the CLN library.
- The GNU scientific Library
SEB on Linux (Ubuntu)
Install dependencies
Ubuntu:
sudo apt update
sudo apt install libcln-dev libgsl-dev libginac-dev
Cloning the GIT code
You can clone the source code in the terminal using
git clone https://github.com/Tobionecenobi/SEB.git
this will create a SEB folder in the current working directory and download the source code into this folder.
Installing SEB on Windows (using WSL)
Windows Subsystem for Linux (WSL) allows you to install a virtual machine running e.g. Ubuntu. In that case you can use the Linux installation guide above.
Installing SEB on Windows (using MSYS2)
See the guide Lau Blom Grøndahl You may experience that the C++ compiler and make are not included by default.
Installing SEB on Mac (using brew)
Thanks to Andreas Haar Larsen / Caolan Browne for help here.
In a terminal do:
brew install cln
brew install gsl
brew install ginac
Clone SEB from github:
git clone https://github.com/Tobionecenobi/SEB.git
This creates a sub-folder SEB in which you find the source code. Before you can compile SEB you need to find the location of the GiNaC include files.
find /opt/homebrew -name ginac.h
If Homebrew installed GiNaC in a non-standard prefix, pass that prefix to CMake when configuring the optional GiNaC backend:
cmake -S . -B build-ninja-ginac -G Ninja -DSEB_ENABLE_GINAC_BACKEND=ON -DCMAKE_PREFIX_PATH=/opt/homebrew
cmake --build build-ninja-ginac
Nb. your exact Homebrew prefix might be different from the one above. Then you are ready to compile SEB.
Optional: Manual compilation of GSL/CLN/GINAC
This will install the GNU scientific library and GiNaC package along with their dependencies.
[!TIP] If you have problems installing GiNaC: If you have trouble installing GiNaC you can try to build GiNaC from scratch. To do this see following guide in SEB's wiki.
[!TIP] Another tip for installing GiNaC is to:
1) clone the cln library
git clone git://www.ginac.de/cln.gitand read the INSTALL* files.2) clone the GiNaC library
git clone git://www.ginac.de/ginac.gitand again read the INSTALL* files.There are guides for installing using cmake or installing on windows for both libraries.
Compiling
Assuming you git cloned into the folder SEB, then
cd SEB
make
will compile the SEB library (into build/libseb.a), along with all the examples (in Examples), code for generating figures in the SEB paper (in PaperFigs). Assuming everything went well, then Examples and PaperFigs will be full of executables which you can run to see how SEB works. These targets can be recompiled individually by calling make with "seb", "examples", "paperFigs", or "work" as an argument. The last argument compiles user own code in the work folder, which is empty when you clone the repo.
Running an example
cd Examples
./Micelle (or Micelle.exe on windows).
This example calculates the scattering from 100 Gaussian polymers added to the surface of a solid sphere, in particular, the form factor, the form factor amplitude relative to the center, and the phase factor between two free polymer ends. The output of the program is
Form factor= \frac{9900 \frac{ \sin( R_{sphere} q)^{2} {(-1+\exp(- R_{g_{poly}}^{2} q^{2}))}^{2} \beta_{poly}^{2}}{ R_{sphere}^{2} R_{g_{poly}}^{4} q^{6}}+200 \frac{ \beta_{poly}^{2} {(-1+ R_{g_{poly}}^{2} q^{2}+\exp(- R_{g_{poly}}^{2} q^{2}))}}{ R_{g_{poly}}^{4} q^{4}}-600 \frac{ \beta_{sphere} \sin( R_{sphere} q) {(-1+\exp(- R_{g_{poly}}^{2} q^{2}))} \beta_{poly} {(\sin( R_{sphere} q)- R_{sphere} \cos( R_{sphere} q) q)}}{ R_{sphere}^{4} R_{g_{poly}}^{2} q^{6}}+9 \frac{ \beta_{sphere}^{2} {(\sin( R_{sphere} q)- R_{sphere} \cos( R_{sphere} q) q)}^{2}}{ R_{sphere}^{6} q^{6}}}{\beta_{sphere}^{2}+10000 \beta_{poly}^{2}+200 \beta_{sphere} \beta_{poly}}
Form factor amplitude relative to centre= -\frac{100 \frac{ \sin( R_{sphere} q) {(-1+\exp(- R_{g_{poly}}^{2} q^{2}))} \beta_{poly}}{ R_{sphere} R_{g_{poly}}^{2} q^{3}}-3 \frac{ \beta_{sphere} {(\sin( R_{sphere} q)- R_{sphere} \cos( R_{sphere} q) q)}}{ R_{sphere}^{3} q^{3}}}{\beta_{sphere}+100 \beta_{poly}}
Phase factor tip-to-tip= \frac{ \sin( R_{sphere} q)^{2} \exp(-2 R_{g_{poly}}^{2} q^{2})}{ R_{sphere}^{2} q^{2}}
Here R_{sphere} is the radius of the sphere, \beta_{sphere} the excess scattering length of the sphere, R_{poly} is the radius of gyration of the polymer, and \beta_{poly} is its excess scattering length. All scattering expressions are normalized so they converge to unity in the q->0 limit.
LaTeX produce the following rendering of the form factor expression: $$\frac{9900 \frac{ \sin( R_{sphere} q)^{2} {(-1+\exp(- R_{g_{poly}}^{2} q^{2}))}^{2} \beta_{poly}^{2}}{ R_{sphere}^{2} R_{g_{poly}}^{4} q^{6}}+200 \frac{ \beta_{poly}^{2} {(-1+ R_{g_{poly}}^{2} q^{2}+\exp(- R_{g_{poly}}^{2} q^{2}))}}{ R_{g_{poly}}^{4} q^{4}}-600 \frac{ \beta_{sphere} \sin( R_{sphere} q) {(-1+\exp(- R_{g_{poly}}^{2} q^{2}))} \beta_{poly} {(\sin( R_{sphere} q)- R_{sphere} \cos( R_{sphere} q) q)}}{ R_{sphere}^{4} R_{g_{poly}}^{2} q^{6}}+9 \frac{ \beta_{sphere}^{2} {(\sin( R_{sphere} q)- R_{sphere} \cos( R_{sphere} q) q)}^{2}}{ R_{sphere}^{6} q^{6}}}{\beta_{sphere}^{2}+10000 \beta_{poly}^{2}+200 \beta_{sphere} \beta_{poly}} $$
This looks pretty horrific because GiNaC does not attempt to simplify expressions, but it has the advantage that we can immediately provide a physical interpretation of all the terms. The terms in the numerator describe 1) the polymer-to-polymer interference contribution, 2) the single polymer Debye form factor, 3) the polymer-to-core interference contribution, 4) the Rayleigh form factor of the core. The numerator is the total excess scattering length squared hence its just $\left(100 \beta_{poly}+\beta_{sphere}\right)^2$.
The example folder has numerous other examples, most of which produce symbolic expressions. These can become very long. The code to generate all the figures from the SEB paper is located in PaperFigs. We have uploaded png plots of the figures with illustrations of the structures. For each curve, there is a corresponding C++ file that generates that structure and its scattering curve.
Validation
To ensure that all the sub-unit scattering expressions implemented in SEB are correct. We have validated the code and theory as follows.
Sampling Scattering Profiles for Complex Geometries
For more complex geometries, we have sampled the scattering profiles directly. We generate random points on the surface and internally in the geometry. Based on these points we have used the Debye formula to calculate the scattering form factors between pairs of scatterers inside the geometry, form factor amplitudes between internal points and reference points, and finally the phase factors between all pairs of reference points. Here reference points in the example of a solid spherical shell would be the centre, the internal surface, the external surface and the total surface. This gives a relatively large number of synthetic scattering files for each geometry. (Code+data in Mathematica/Sampled)
Analytical Derivation and Comparison with Synthetic Data
We have used Wolfram Mathematica to derive analytic expressions for the sub-units (Code in Mathematica/*.nb). Where relevant these expressions have been compared the synthetic data to ensure that all expressions derived by Mathematica match the sampled data within the statistical accuracy of our sampling. At this stage we can trust that theoretical expressions match the synthetic scattering data.
Implementation in SEB
To implement sub-units in SEB, we have exported the Mathematica expressions to C++ either manually or using CForm[expression]. The resulting expresions are in sub-unit header files in the seb/Subunits folder, where each header file is a specific sub-unit geometry. We also generate Guinier expansions of all scattering expressions to obtain size expressions for $\langle Rg^2 \rangle$ for the form factor, and $\sigma\langle R^2 \rangle$ for form factor amplitudes and phase factors. The size expressions are also exported to the C++ code. The SubUnit->ValidateDefinedTerms() method checks that all scattering terms and size terms are defined for the reference points combinations for a sub-unit.
Validation of Mathematical Correctness
Finally, to ensure that the scattering terms not only exist but are also mathematically correct, we have taken the following steps:
- Generation of Theoretical Scattering Data: Using Mathematica, we have created tabulated theory scattering curves for each scattering expression. This data, devoid of statistical sampling errors, can be found in the Examples/Validate subfolders.
- Numerical Evaluation and Comparison: Each scattering expression has been numerically evaluated at the same q-values as those used in the Mathematica-generated curves. We then compared the results from these numerical evaluations with the theoretical data. To ensure precision, we've set a tolerance level of $10^{-4}$ for the systematic error on the evaluation of the special functions. Scattering expressions showing deviations larger than this tolerance are flagged for review and potential correction.
By following these steps, we aim to guarantee that our mathematical formulations in SEB are not only theoretically sound but also practically applicable and accurate.
Checking Guinier Expansions
To check the Guinier expansions e.g. of a form factor amplitude, we predict the scattering from the Guinier expansion $A_{\text{Guinier}}(q)= 1- q^2 \sigma \langle R^2\rangle/6$, where an size expression for $\sigma \langle R^2 \rangle$ is hard-coded for each reference point. Where the second term is $<0.01$ we compare $A_\text{Guinier}(q)$ to the scattering data generated by Mathematica. These should also match within the accuracy of a tolerance, that again we choose as $10^{-4}$. Size expressions with larger deviations are flagged as bugs that needs to be fixed.
Additional Checks with GiNaC
For some of the sub-unit expressions but not all, we can also use GiNaC to expand the scattering terms directly as a Taylor series around $q=0$. That automatically generates the size expressions. In that case we perform a term-by-term comparison with the 1,0, $2 \langle Rg^2 \rangle$ for form factors or 1, 0, $\sigma\langle R^2 \rangle$ for form factor amplitudes and phase factors to check that the expressions match. This does not work for special functions, where GiNaC does not know the Series expansions. The comparison also fails for expressions that are sufficiently complicated so even though $A==B$ GiNaC is not able to simplify $A-B$ to zero and hence prove their identity.
Symbolic Expression Abstraction Layer
SEB now includes a symbolic expression abstraction layer with a portable C++ backend, optional GiNaC support in C++, and SymPy conversion in Python. See docs/symbolic-backends.md for the backend model.
Using GiNaC in C++
GiNaC is an optional C++ symbolic backend. To explicitly initialize it in a GiNaC-enabled build:
#include "SEB.hpp"
#include "GiNaCSymbolic.hpp"
int main() {
// Initialize the SymbolicFactory with GiNaC
SymbolicFactory::setInstance(new GiNaCSymbolic());
// Use SEB as normal
World w("World");
// ...
}
Using SymPy in Python
The Python bindings (pySEB) use SymPy for symbolic computations. You can use pySEB with SymPy as follows:
import pyseb
import sympy
# Create a world
world = pyseb.World("World")
# Add a diblock copolymer
world.Add("diblock", "diblock")
# Get the form factor expression
form_factor = world.FormFactor("diblock")
# Print the expression
print(form_factor)
# Convert to LaTeX
latex_expr = sympy.latex(form_factor.expr)
print(latex_expr)
Using SEB in your own C++ Code
To use SEB you can either 1) develop code in the repository work/ folder or 2) develop code anywhere on your computer. Option 1 allows you to reuse the SEB compilation infrastructure and no installation of SEB is required. Option 2 requires the user to manually compile the code specifying where SEB header files and library is located.
Example source code
To derive the scattering for a diblock copolymer created by linking two Gaussian polymer models end-to-end, we do
#include "SEB.hpp"
int main()
{
// Define world
World w;
// Add a single polymer, named 'poly1'
GraphID g = w.Add("GaussianPolymer", "poly1");
// Add a second polymer, named 'poly2'. Poly2's end1 is linked to poly1's end2 forming a diblock copolymer
w.Link("GaussianPolymer", "poly2.end1", "poly1.end2");
// Wrap the g structure naming it "diblockcopolymer"
GraphID g2 = w.Add(g, "diblockcopolymer");
// Request the symbolic expression for the form factor of this structure
ex formFactor=w.FormFactor("diblockcopolymer");
// Print out form factor expression
cout << formFactor << endl;
// Request LaTeX formatted output
cout << latex;
// Print out LaTeX expression for form factor
cout << formFactor << endl;
}
The output is
2*(beta_poly1^2+beta_poly2^2+2*beta_poly2*beta_poly1)^(-1)*(beta_poly2^2*Rg_poly2^(-4)*q^(-4)*(-1+exp(-Rg_poly2^2*q^2)+Rg_poly2^2*q^2)+q^(-4)*(-1+q^2*Rg_poly1^2+exp(-q^2*Rg_poly1^2))*Rg_poly1^(-4)*beta_poly1^2+beta_poly2*Rg_poly2^(-2)*q^(-4)*Rg_poly1^(-2)*(-1+exp(-Rg_poly2^2*q^2))*beta_poly1*(-1+exp(-q^2*Rg_poly1^2)))
2 \frac{\frac{ \beta_{poly2}^{2} {(-1+\exp(- R_{g_{poly2}}^{2} q^{2})+ R_{g_{poly2}}^{2} q^{2})}}{ R_{g_{poly2}}^{4} q^{4}}+\frac{ {(-1+ q^{2} R_{g_{poly1}}^{2}+\exp(- q^{2} R_{g_{poly1}}^{2}))} \beta_{poly1}^{2}}{ q^{4} R_{g_{poly1}}^{4}}+\frac{ \beta_{poly2} {(-1+\exp(- R_{g_{poly2}}^{2} q^{2}))} \beta_{poly1} {(-1+\exp(- q^{2} R_{g_{poly1}}^{2}))}}{ R_{g_{poly2}}^{2} q^{4} R_{g_{poly1}}^{2}}}{\beta_{poly1}^{2}+\beta_{poly2}^{2}+2 \beta_{poly2} \beta_{poly1}}
where the top line is the symbolic expression in the default format, and the bottom expression is formatted according to LaTeX. Rendinger the equation in LaTeX we get the following
Again we can interpret the physical origin of the three terms in this expression. The terms in the numerator are 1) the Debye form factor of poly2, 2) the Debye form factor of poly1, and 3) the interference contribution between scatterers on poly1 and scatterers on poly2. The numerator is the total excess scattering length squared which is given by $(\beta_{poly1}+\beta_{poly2})^2$.
Compiling
To compile the code depends on where your code is located
work folder
make work
Running this command in the repository root will compile and link user C++ code in the work/ folder using the SEB compile infrastructure. The resulting executable is placed in work/.
Elsewhere
Assuming your code is in code.cpp then you can compile and link your code manually with
c++ -O2 -c -IFOLDER/pySEB/seb -IFOLDER/pySEB/seb-symbolic code.cpp
c++ code.o -lseb -lseb-symbolic -lgsl -lgslcblas -lm -lginac -LFOLDER/pySEB/build-ninja-ginac -o myexecutable
where the user manually has to specify the location of the header files and libraries, where you should modify FOLDER to fit your local environment. Note its important the object file is specified before the libraries when compiling.
Contributing
SEB is Open Source and we wellcome contributions from users. Each time a new sub-unit or even just a new reference point is added to SEB the library of structures that can be generated by SEB grows exponentially. For adding code for new sub-units, please provide the code along with validation code following our protocol above or better. Ideally we would also like to include the mathematical derivation of the scattering expressions within SEB for future documentation.
Bibtex
@article{svaneborg2012formalism1,
title={A formalism for scattering of complex composite structures. {I}. {A}pplications to branched structures of asymmetric sub-units},
author={Svaneborg, Carsten and Pedersen, Jan Skov},
journal={J. Chem. Phys.},
volume={136},
number={10},
pages={104105},
year={2012},
publisher={AIP Publishing},
doi={10.1063/1.3682778},
url={http://doi.org/10.1063/1.3682778}
}
@article{svaneborg2012formalism2,
title={A formalism for scattering of complex composite structures. {II}. {D}istributed reference points},
author={Svaneborg, Carsten and Pedersen, Jan Skov},
journal={J. Chem. Phys.},
volume={136},
pages={154907},
year={2012},
publisher={AIP Publishing},
doi={10.1063/1.3701737},
url={http://doi.org/10.1063/1.3701737}
}
@article{Jarrett2024SEB,
title={{S}{E}{B}: a computational tool for symbolic derivation of the small-angle scattering from complex composite structures},
author={Jarrett, Tobias William Jensen and Svaneborg, Carsten}
journal={J. Appl. Crystallogr.},
volume={57},
pages={587},
year={2024},
publisher={IUCL},
doi={10.1107/S1600576724001729},
url={http://doi.org/10.1107/S1600576724001729}
}
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