- Timestamp:
- Sep 29, 2017 9:11:13 AM (7 years ago)
- Branches:
- master, core_shell_microgels, costrafo411, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
- Children:
- b76191e
- Parents:
- 4aa5dce
- Location:
- doc/guide
- Files:
-
- 3 edited
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doc/guide/magnetism/magnetism.rst
r59485a4 r1f058ea 77 77 =========== ================================================================ 78 78 M0_sld = $D_M M_0$ 79 Up_theta = $\theta_ {up}$79 Up_theta = $\theta_\mathrm{up}$ 80 80 M_theta = $\theta_M$ 81 81 M_phi = $\phi_M$ -
doc/guide/pd/polydispersity.rst
rf8a2baa r1f058ea 95 95 \exp\left(-\frac{(x - \bar x)^2}{2\sigma^2}\right) 96 96 97 where $\bar x$ is the mean of the distribution and *Norm* is a normalization factor98 which is determined during the numerical calculation.97 where $\bar x$ is the mean of the distribution and *Norm* is a normalization 98 factor which is determined during the numerical calculation. 99 99 100 100 The polydispersity is … … 122 122 during the numerical calculation. 123 123 124 The median value for the distribution will be the value given for the respective125 size parameter, for example, *radius=60*.124 The median value for the distribution will be the value given for the 125 respective size parameter, for example, *radius=60*. 126 126 127 127 The polydispersity is given by $\sigma$ … … 208 208 209 209 Many commercial Dynamic Light Scattering (DLS) instruments produce a size 210 polydispersity parameter, sometimes even given the symbol $p$ This210 polydispersity parameter, sometimes even given the symbol $p$\ ! This 211 211 parameter is defined as the relative standard deviation coefficient of 212 212 variation of the size distribution and is NOT the same as the polydispersity -
doc/guide/resolution.rst
r30b60d2 r1f058ea 17 17 resolution contribution into a model calculation/simulation (which by definition 18 18 will be exact) to make it more representative of what has been measured 19 experimentally - a process called *smearing*. sasmodels does the latter.19 experimentally - a process called *smearing*. Sasmodels does the latter. 20 20 21 21 Both smearing and desmearing rely on functions to describe the resolution 22 effect. sasmodels provides three smearing algorithms:22 effect. Sasmodels provides three smearing algorithms: 23 23 24 24 * *Slit Smearing* … … 99 99 100 100 For discrete $q$ values, at the $q$ values of the data points and at the $q$ 101 values extended up to $q_N = q_i + \Delta q_ v$ the smeared101 values extended up to $q_N = q_i + \Delta q_u$ the smeared 102 102 intensity can be approximately calculated as 103 103
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