| 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. |
| | 40 | * Wojciech - the optimiser might have problems with that if we are not careful. |
| | 41 | * RKH: Would need non-fittable (static) parameters |
| | 42 | * PDB: this is also been needed with constraints |
| | 43 | * AJJ: Also been needed in calculated outputs |
| | 44 | * "There is a ticket for that" |
| | 45 | * Also other static output plots (see SLD profiles, see 3D shape) would be nice .. though off-topic here. |
| | 46 | * Narayan: Make sure that all constrained parameters (fitable or not) are visible and that it is clear that they are constrained. |
| 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 |
| | 54 | * Discussion of !SasFit / !SasView |
| | 55 | * More ways of dealing with structure factors |
| | 56 | * Orientationally dependent structure factors |
| | 57 | * e.g. Beta - Now in !SasView |
| | 58 | * Structure factors that depend on form factor (amplitude) |
| | 59 | * More ways of dealing with polydispersity |
| | 60 | * Beta - Now in !SasView |
| | 61 | * Locally monodisperse |
| | 62 | * Other Models |
| | 63 | * OZ Solver |
| | 64 | * pyPRISM - will be implemented in !SasView by Tyler Martin |
| | 65 | * Probably for most cases nee to just write analytical ones |
| | 66 | * Yun - Most cases will only be good for hard sphere and spherical particles |
| | 67 | * Yun - Continuous distributions in OZ framework is hard |
| | 68 | * Yun - should go for numerical solutions for more complex interaction potentials |
| | 69 | * Yun - for e.g. mixture of latex and gold, need cross terms, so need complex amplitudes |
| 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 | | |
| 75 | | |
| 76 | | |
| 77 | | |
| 78 | | Check SasFit - Joachim may have implemented already. |
| | 74 | * Andrew has had student working on this. It is quite difficult. Key is the use of hypergeometric functions. This might also be good for integration speeds in general (see below). |
| | 75 | * MLZ have been working on it too for a few simple models. |
| | 76 | * They have some proof of concept in Born Again |
| | 77 | * Need to work out API to work with SasView |
| | 78 | * Plan for this ... |
| | 79 | *Aim for next Code Camp to have BornAgain team integrate their code. |
| | 80 | *Check !SasFit - Joachim may have implemented already. |
| 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. |
| | 83 | * How to fit a slice from a 2D data sets (oriented objects, magnetic scattering, etc.) |
| | 84 | * Should we do it? |
| | 85 | * If we are going to provide live access to fast computers |
| | 86 | * If not too hard maybe do anyway .. a number of users with good cases |
| | 87 | * How would we do it? |
| | 88 | * Make special 1D models? |
| | 89 | * Or cut 2D models? |
| | 90 | * Speed … ? |
| | 91 | * Need to look at the speed ...= |
| | 92 | * User interface … ? |
| | 93 | * How to show the slicer options to the user? |
| | 94 | * Narayan / Sylvain to find some example data. |
| | 95 | * Maybe start with simulation and treat as real data to test process |
| | 96 | * AJJ to make some simulated data and share with everyone. |
| 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? |
| | 99 | * Wojciech : Idea is that there is a summer student at ISIS working with Anders |
| | 100 | * Mantid have been testing their optimisers seeing how they perform on different classes of problems. |
| | 101 | *Want to do something similar for !SasView |
| | 102 | * Test !SasView optimisers against their defined problems |
| | 103 | * Identify classes of problems that would be representative for the SANS community |
| | 104 | * AJJ - need to know the answer? |
| | 105 | * AJJ - how is SANS mathematically different from other test cases? |
| | 106 | * RKH - What about things where we have models that have multiple possible simulations? |
