| 26 | |
| 27 | == Minutes == |
| 28 | |
| 29 | === Reparameterisation of models === |
| 30 | * Use Cases: |
| 31 | * Amounts of water in outer layer vs SLD of layer |
| 32 | * Number of particles / packing e.g. Volumes of heads and tails tied |
| 33 | * Examples of complicated things from Sylvain and Richard e.g. micelles with charge and molecular constraints |
| 34 | * How to implement? |
| 35 | * Make lots of models and use categories to manage. Each parameterization of a model is now its own model |
| 36 | * Provide a "workflow" that uses the contraints system to create on the fly |
| 37 | * Create new infrastructure to add calculated parameters on the fly |
| 38 | * How do we do this? |
| 39 | * Can we make a good interface for the user to do parameter mapping |
| 40 | * Wojciech - the optimiser might have problems with that. |
| 41 | * Non-fittable parameters |
| 42 | * Involved with a constraint |
| 43 | * Calculated outputs |
| 44 | * See SLD profiles, see 3D shape |
| 45 | * Narayan: Make sure that it is clear that constrained parameters are visible and clear that they are constrained. |
| 46 | * PDB: Actually should be easy to provide an on the fly reparameterization: Use a GUI tool like the Add Model Editor to provide parameters, any constraints and their relationship to the existing parameters. Then "create the code" by editing the model file: adding the conversion math at the beginning of the function. Essentially the infrastructure and a first order proof of concept already. |
| 47 | * Start with a simple test, then maybe talk to Paul Kienzle |
| 48 | * Think about GUI |
| 49 | |
| 50 | === Include more complex structure factors === |
| 51 | * Discussion of the implementation of F(Q) |
| 52 | * We don’t have complex amplitudes |
| 53 | * Use case : Janus particles - but can cheat it with end capped cylinder |
| 54 | * Beta |
| 55 | * Locally monodisperse |
| 56 | * More ways of dealing with structure factors |
| 57 | *pyPRISM - will be implemented in SasView by Tyler Martin |
| 58 | * Discussion of SasFit / SasView |
| 59 | * Models |
| 60 | * OZ Solver |
| 61 | * More ways of dealing with polydispersity |
| 62 | * Orientation dependent Structure factors that depend on form factor (amplitude) |
| 63 | Write analytical ones |
| 64 | Yun - only good for hard sphere and spherical particles |
| 65 | Yun - Continuous distributions in OZ framework is hard |
| 66 | Yun - should go for numerical solutions for more complex interaction potentials |
| 67 | Yun - for e.g. mixture of latex and gold, need cross terms, so need complex amplitudes |
| 68 | * Sylvain - Finish decoupling approximation first? For spherical. |
| 69 | ALL - AGREED last point |
| 70 | |
| 71 | === Include material from Scatter === |
| 72 | Andrew has had student working on it. Difficult. Needs hypergeometric functions. |
| 73 | MLZ have been working on it too - a few simple models. |
| 74 | They have some proof of concept in Born Again |
| 75 | Need to work out API to work with SasView |
| 76 | Plan for this ... |
| 77 | Aim for next Code Camp to have BornAgain team integrate their code. |
| 78 | Check SasFit - Joachim may have implemented already. |
| 79 | |
| 80 | === 1D oriented data ... === |
| 81 | How to fit a slice from a 2D dataset |
| 82 | Do we do it? How? |
| 83 | Make special 1D models? |
| 84 | Or cut 2D models? |
| 85 | Speed … ? Need to look at the speed ...= |
| 86 | User interface … ? |
| 87 | How to show the slicer options to the user? |
| 88 | Narayan / Sylvain to find some example data. |
| 89 | Maybe start with simulation and treat as real data to test process |
| 90 | AJJ to make some simulated data and share with everyone. |
| 91 | |
| 92 | === Project to do benchmarking of optimisers === |
| 93 | * Wojciech : Idea is that there is a summer student at ISIS working with Anders |
| 94 | Mantid have been testing their optimisers seeing how they perform on different classes of problems. Want to do something similar for SasView |
| 95 | * Test SasView optimisers against their defined problems |
| 96 | * Identify classes of problems that would be representative for the SANS community |
| 97 | * AJJ - need to know the answer? |
| 98 | * AJJ - how is SANS mathematically different from other test cases? |
| 99 | * RKH - What about things where we have models that have multiple possible simulations? |
| 100 | |
| 101 | === Computation speed and integration options and approaches === |
| 102 | * Ingo : Suggestion - improve the integrations inside models. |
| 103 | * Get rid of nested integrals |
| 104 | * Use lebchev(?) Integrals? - some unrolled already- but other would require balancing competing requirements? |
| 105 | * How to include with GPU code ? |
| 106 | * Testing already … some models have numerical integration problems. Work underway. |
| 107 | * Richard - will always have convergence issues for large particles. Or at least with particles that have one dimension that is massively larger than the other. |
| 108 | * Hypergeometric functions |
| 109 | * Can we implement them for more models? |
| 110 | * AJJ to find code from Johan. |