source: sasview/pr_inversion/__init__.py @ 2e51013

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
Last change on this file since 2e51013 was 97d69d9, checked in by Mathieu Doucet <doucetm@…>, 15 years ago

pr_inversion: get rid of unnecessary imports

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[9a11937]1"""
2    P(r) inversion for SANS
3"""
4## \mainpage P(r) inversion for SANS
5#
6# \section intro_sec Introduction
7# This module provides calculations to transform scattering intensity data
8# I(q) into distance distribution function P(r). A description of the
9# technique can be found elsewhere [1-5]. The module is useable as a
10# standalone application but its functionality is meant to be presented
11# to end-users through the user interface developed as part of the SANS
12# flagship application.
13#
14# Procedure: We will follow the procedure of Moore [1].
15#
16# [1] P.B. Moore, J.Appl. Cryst (1980) 13, 168-175.
[896abb3]17#
[9a11937]18# [2] O. Glatter, J.Appl. Cryst (1977) 10, 415-421.
[896abb3]19#
[9a11937]20# [3] D.I. Svergun, J.Appl. Cryst (1991) 24, 485-492.
[896abb3]21#
[9a11937]22# [4] D.I. Svergun, J.Appl. Cryst (1992) 25, 495-503.
[896abb3]23#
[9a11937]24# [5] S. Hansen and J. Skov Pedersen, J.Appl. Cryst (1991) 24, 541-548.
25#
[ffca8f2]26## \subsection class Class Diagram:
27# The following shows a partial class diagram with the main attributes and methods of the invertor.
28#
29# \image html architecture.png
[9a11937]30#
31# \section install_sec Installation
32#
33# \subsection obtain Obtaining the Code
34#
35# The code is available here:
36# \verbatim
37#$ svn co svn://danse.us/sans/pr_inversion
38# \endverbatim
39#
40# \subsection depends External Dependencies
[97d69d9]41# scipy, numpy
[9a11937]42#
43# \subsection build Building the code
44# The standard python package can be built with distutils.
45# \verbatim
46#$ python setup.py build
47#$ python setup.py install
48# \endverbatim
49#
50#
[896abb3]51# \subsection Tutorial
52# To create an inversion object:
53# \verbatim
54#from sans.pr.invertor import Invertor
55#    invertor = Invertor()
56# \endverbatim
57#
58# To set the maximum distance between any two points:
59# \verbatim
60#    invertor.d_max = 160.0
61# \endverbatim
62#
63# To set the regularization constant:
64# \verbatim
65#    invertor.alpha = 0.0007
66# \endverbatim
67#
68# To set the q, I(q) and error on I(q):
69# \verbatim
70#    invertor.x = q_vector
71#    invertor.y = Iq_vector
72#    invertor.err = dIq_vector
73# \endverbatim
74#
75# To perform the inversion. In this example, we choose
76# a P(r) expension wit 10 base functions.
77# \verbatim
78#    c_out, c_cov = invertor.invert(10)
79# \endverbatim
80# The c_out and c_cov are the set of coefficients and the covariance
81# matrix for those coefficients, respectively.
82#
[ffca8f2]83# To get P(r):
84# \verbatim
85#    r = 10.0
86#    pr = invertor.pr(c_out, r)
87# \endverbatim
88# Alternatively, one can get P(r) with the error on P(r):
89# \verbatim
90#    r = 10.0
91#    pr, dpr = invertor.pr_err(c_out, c_cov, r)
92# \endverbatim
93#
94# To get the output I(q) from the set of coefficients found:
95# \verbatim
96#    q = 0.001
97#    iq = invertor.iq(c_out, q)
98# \endverbatim
99#
[9a11937]100# Examples are available as unit tests under sans.pr_inversion.test.
101#
102# \section help_sec Contact Info
103# Code and Documentation produced as part of the DANSE project.
104
105__author__ = 'University of Tennessee'
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