Changeset d78b5cb in sasview
- Timestamp:
- Jul 19, 2017 5:40:46 AM (7 years ago)
- Branches:
- master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, magnetic_scatt, release-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload
- Children:
- 9b90bf8
- Parents:
- c728295
- File:
-
- 1 edited
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src/sas/sasgui/perspectives/corfunc/media/corfunc_help.rst
r1404cce rd78b5cb 10 10 11 11 This performs a correlation function analysis of one-dimensional 12 SAXS/SANS data, or generates a model-independent volume fraction 12 SAXS/SANS data, or generates a model-independent volume fraction 13 13 profile from the SANS from an adsorbed polymer/surfactant layer. 14 14 15 A correlation function may be interpreted in terms of an imaginary rod moving 16 through the structure of the material. Î\ :sub:`1D`\ (R) is the probability that 17 a rod of length R moving through the material has equal electron/neutron scattering 18 length density at either end. Hence a frequently occurring spacing within a structure 15 A correlation function may be interpreted in terms of an imaginary rod moving 16 through the structure of the material. Î\ :sub:`1D`\ (R) is the probability that 17 a rod of length R moving through the material has equal electron/neutron scattering 18 length density at either end. Hence a frequently occurring spacing within a structure 19 19 manifests itself as a peak. 20 20 … … 30 30 * Fourier / Hilbert Transform of the smoothed data to give the correlation 31 31 function / volume fraction profile, respectively 32 * (Optional) Interpretation of the 1D correlation function based on an ideal 32 * (Optional) Interpretation of the 1D correlation function based on an ideal 33 33 lamellar morphology 34 34 … … 74 74 :align: center 75 75 76 76 77 77 Smoothing 78 78 --------- 79 79 80 The extrapolated data set consists of the Guinier back-extrapolation from Q~0 80 The extrapolated data set consists of the Guinier back-extrapolation from Q~0 81 81 up to the lowest Q value in the original data, then the original scattering data, and the Porod tail-fit beyond this. The joins between the original data and the Guinier/Porod fits are smoothed using the algorithm below to avoid the formation of ripples in the transformed data. 82 82 … … 93 93 h_i = \frac{1}{1 + \frac{(x_i-b)^2}{(x_i-a)^2}} 94 94 95 95 96 96 Transform 97 97 --------- … … 102 102 If "Fourier" is selected for the transform type, the analysis will perform a 103 103 discrete cosine transform on the extrapolated data in order to calculate the 104 correlation function 104 1D correlation function: 105 105 106 106 .. math:: … … 115 115 \left(n + \frac{1}{2} \right) k \right] } \text{ for } k = 0, 1, \ldots, 116 116 N-1, N 117 118 The 3D correlation function is also calculated: 119 120 .. math:: 121 \Gamma _{3D}(R) = \frac{1}{Q^{*}} \int_{0}^{\infty}I(q) q^{2} 122 \frac{sin(qR)}{qR} dq 117 123 118 124 Hilbert … … 165 171 .. figure:: profile1.png 166 172 :align: center 167 173 168 174 .. figure:: profile2.png 169 175 :align: center 170 176 171 177 172 178 References … … 191 197 ----- 192 198 Upon sending data for correlation function analysis, it will be plotted (minus 193 the background value), along with a *red* bar indicating the *upper end of the 199 the background value), along with a *red* bar indicating the *upper end of the 194 200 low-Q range* (used for back-extrapolation), and 2 *purple* bars indicating the range to be used for forward-extrapolation. These bars may be moved my clicking and 195 201 dragging, or by entering appropriate values in the Q range input boxes. … … 221 227 :align: center 222 228 223 229 224 230 .. note:: 225 231 This help document was last changed by Steve King, 08Oct2016
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