source: sasview/sansmodels/src/release_notes.txt @ db08737

ESS_GUIESS_GUI_DocsESS_GUI_batch_fittingESS_GUI_bumps_abstractionESS_GUI_iss1116ESS_GUI_iss879ESS_GUI_iss959ESS_GUI_openclESS_GUI_orderingESS_GUI_sync_sascalccostrafo411magnetic_scattrelease-4.1.1release-4.1.2release-4.2.2release_4.0.1ticket-1009ticket-1094-headlessticket-1242-2d-resolutionticket-1243ticket-1249ticket885unittest-saveload
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1Release Notes
2=============
3
4SANS Models version 0.4.3
5
6Package name: sans.models
7
81- What's New in Version 0.4.3
9    - Release date: April 21, 2009
10    - C extension models now use new C++ classes that incorporate dispersity and averaging
11      functionality. See utest_dispersity.py for examples of how to use the new dispersion
12      classes.
13     
14      # Create a model
15      model= CylinderModel()
16     
17      # Create a dispersion model
18      disp = GaussianDispersion()
19     
20          # Set the dispersion for a chosen parameter
21          model.set_dispersion('radius', disp)
22         
23          # Set the parameters of the dispersion model
24      model.dispersion['radius']['width'] = 5.0
25      model.dispersion['radius']['npts'] = 100
26
27
28    Version 0.4.3
29    -P(Q)*S(Q) added for P(Q)=cylinder, sphere, ellipsoid
30    -Array dispersion (user defined) added
31
32    Version 0.4.2
33    -4 Structure factors added
34   
35    Version 0.4.1
36    - Release date: 6/9/2008
37    - Modified non-shape models so that the 2D output is the 1D output for the length of Q
38
39    Version 0.4.0
40        - Release date: 4/15/2008
41        - Added shape-independent models.
42       
43        Version 0.3.2:
44        - Release date: 2/14/2008
45        - Added models to be used in magnetic analysis.
46
47
482- Downloading and Installing
49
50        2.1- System Requirements:
51                - Python version >= 2.4 should be running on the system
52
53        2.2- Installing:
54                - Get the code from svn://danse.us/sans/releases/sansmodels-0.4.3
55                - Execute the following:
56                        python setup.py install
57
583- Known Issues
59
60        3.1- All systems:
61                - Q range validity of I(q) calculations.
62                        Our 1D models of I(q) use the function of the NCNR library
63                        for their IGOR package (Klein, 2006). That library uses a
64                        fast integration technique in some of its models (cylinders
65                        and ellipsoids). Integration is done using 76 points in the
66                        angle between the axis of the object and the q-vector, which
67                        translates in a larger inaccuracy at high q. Integratiing
68                        the 2D model I(q,phi) over all orientations of the object
69                        will not yield the exact same result as the NCNR calculation
70                        for q > 0.3 A-1.
71                - Refactoring needs to be done to update the model base class.
72                  We should get rid of the useless arithmetics and store the parameters
73                  as class objects rather than values. This would eliminate the multitude
74                  of dictionaries needed to store all the various aspects of a parameter
75                  (limits, units, dispersity information). The C++ design it relies
76                  on is much cleaner in that respect, but it still depends on the old
77                  C computation. Those should be incorporated in the C++ classes.
78
79        3.2- Windows:
80                - None
81
82        3.3- Linux:
83                - None
84
854- Troubleshooting
86
87        - None
88
895- Frequently Asked Questions
90
91        - None
92
936- Other Resources
94
95        - See: http://danse.us/trac/sans/wiki/8_2_2_1DModelFitting
96        - See: http://danse.us/trac/sans/wiki/8_2_3_2DModeling
97        - See: http://danse.us/trac/sans/wiki/8_2_6_model_extensions
98        - See: http://danse.us/trac/sans/wiki/8_2_1Nonshape_models
99
100       
101
102       
103
104
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