# Changeset 1f058ea in sasmodels

Ignore:
Timestamp:
Sep 29, 2017 9:11:13 AM (4 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
Message:

resolve minor differences between the updated docs sasview and the corresponding docs in sasmodels

Location:
doc/guide
Files:
3 edited

### Legend:

Unmodified
 r59485a4 ===========   ================================================================ M0_sld        = $D_M M_0$ Up_theta      = $\theta_{up}$ Up_theta      = $\theta_\mathrm{up}$ M_theta       = $\theta_M$ M_phi         = $\phi_M$
 rf8a2baa \exp\left(-\frac{(x - \bar x)^2}{2\sigma^2}\right) where $\bar x$ is the mean of the distribution and *Norm* is a normalization factor which is determined during the numerical calculation. where $\bar x$ is the mean of the distribution and *Norm* is a normalization factor which is determined during the numerical calculation. The polydispersity is during the numerical calculation. The median value for the distribution will be the value given for the respective size parameter, for example, *radius=60*. The median value for the distribution will be the value given for the respective size parameter, for example, *radius=60*. The polydispersity is given by $\sigma$ Many commercial Dynamic Light Scattering (DLS) instruments produce a size polydispersity parameter, sometimes even given the symbol $p$ This polydispersity parameter, sometimes even given the symbol $p$\ ! This parameter is defined as the relative standard deviation coefficient of variation of the size distribution and is NOT the same as the polydispersity
 r30b60d2 resolution contribution into a model calculation/simulation (which by definition will be exact) to make it more representative of what has been measured experimentally - a process called *smearing*. sasmodels does the latter. experimentally - a process called *smearing*. Sasmodels does the latter. Both smearing and desmearing rely on functions to describe the resolution effect. sasmodels provides three smearing algorithms: effect. Sasmodels provides three smearing algorithms: *  *Slit Smearing* For discrete $q$ values, at the $q$ values of the data points and at the $q$ values extended up to $q_N = q_i + \Delta q_v$ the smeared values extended up to $q_N = q_i + \Delta q_u$ the smeared intensity can be approximately calculated as