From b7ce5ad13cff1bb692e5cac14d5eeb68461dd835 Mon Sep 17 00:00:00 2001 From: Steve King Date: Thu, 28 Mar 2019 16:11:47 +0000 Subject: [PATCH] Added section on Fitting Integer Parameters. Closes #882 --- .../fitting/media/fitting_help.rst | 32 +++++++++++++++++++ 1 file changed, 32 insertions(+) diff --git a/src/sas/sasgui/perspectives/fitting/media/fitting_help.rst b/src/sas/sasgui/perspectives/fitting/media/fitting_help.rst index eb3b64750f..a67b932f4e 100644 --- a/src/sas/sasgui/perspectives/fitting/media/fitting_help.rst +++ b/src/sas/sasgui/perspectives/fitting/media/fitting_help.rst @@ -340,6 +340,38 @@ on each optimiser, see the :ref:`Fitting_Documentation`. .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ +Fitting Integer Parameters +-------------------------- + +Most of the parameters in SasView models will naturally take floating point (decimal) +values, but there are some parameters which can only have integer values. Examples +include, but are not limited to, the number of shells in a multilayer vesicle, the +number of beads in a pearl necklace, the number of arms of a star polymer, and so on. +Wherever possible/recognised, the integer nature of a parameter is specified in the +respective model documentation and/or parameter table, so read the documentation +carefully! + +Integer parameters must be fitted with care. + +Start with your best possible guess for the value of the parameter. And using +*a priori* knowledge, fix as many of the other parameters as possible. + +The SasView optimizers treat integer parameters internally as floating point +numbers, but the values presented to the user are truncated or rounded, as +appropriate. + +In most instances integer parameters will probably be greater than zero. A good +policy in such cases is to use a constraint to enforce this. + +Because an integer parameter should, by definition, only move in integer steps, +problems may be encountered if the optimizer step size is too small. Similarly, +be **very careful** about applying polydispersity to integer parameters. + +The Levenberg-Marquardt and Quasi-Newton BFGS (and other derivative-based) +optimizers are probably best avoided for fitting models with integer parameters. + +.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ + Fitting Limits --------------