source: sasmodels/README.rst @ 19dcb933

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Last change on this file since 19dcb933 was 19dcb933, checked in by Paul Kienzle <pkienzle@…>, 10 years ago

build docs for models

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1Sasmodels
2=========
3
4Theory models for small angle scattering.
5
6The models provided are usable directly in the bumps fitting package and
7in the sasview analysis package.  If OpenCL is available, the models will
8run much faster.  If not, then precompiled versions will be included with
9the distributed package.  New models can be added if OpenCL or a C compiler
10is available.
11
12cylinder.c + cylinder.py is the cylinder model with renamed variables and
13sld scaled by 1e6 so the numbers are nicer.  The model name is "cylinder"
14
15cylinder_clone.c + cylinder_clone.py is the cylinder model using the
16same interface as the sasview, including calling the model CylinderModel,
17so that it can be used as a drop-in replacement for the sasview cylinder
18model.
19
20lamellar.py is an example of a single file model with embedded C code.
21
22Note: may want to rename form_volume to calc_volume and Iq/Iqxy to
23calc_Iq/calc_Iqxy in model interface. Similarly ER/VR go to calc_ER/calc_VR.
24
25Note: It is possible to translate python code automatically to opencl, using
26something like numba, clyther, shedskin or pypy, so maybe the kernel functions
27could be implemented without any C syntax.
28
29Note: angular dispersion in theta is probably not calculated correctly, but
30is left this way for compatibility with sasview.
31
32Magnetism hasn't been implemented yet.  We may want a separate Imagnetic
33calculator with the extra parameters and calculations.   We should
34return all desired spin states together so we can share the work of
35computing the form factors for the different magnetic contrasts.  This
36will mean extending the data handler to support multiple cross sections
37in the same data set.
38
39Need to implement an example kernel directly in python.  Polydispersity
40loops should be generated automatically as they are for the OpenCL models.
41The kernels should be vectorized across Q.  These will need vectorized
42versions of numerical quadrature if we want to get reasonable performance.
43
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