Changeset c5cfb20 in sasview for src/sas/sasgui/perspectives/fitting/media

Timestamp:

Sep 18, 2017 2:19:13 PM (7 years ago)

Author:

Paul Kienzle <pkienzle@…>

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:

1e6d9340

Parents:

1659f54 (diff), cfd27dd (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.

Message:

Merge branch 'master' into ticket-639-katex

Location:

src/sas/sasgui/perspectives/fitting/media

Files:

• combine_batch_grid.png (added)
• combine_batch_page.png (added)
• combine_batch_plot.png (added)
• fitting_help.rst (modified) (4 diffs)
• plugin.rst (modified) (1 diff)
• M_angles_pic.bmp (deleted)
• M_angles_pic.png (added)
• batch_button_area.bmp (deleted)
• batch_button_area.png (added)
• cat_fig0.bmp (deleted)
• cat_fig0.png (added)
• cat_fig1.bmp (deleted)
• cat_fig1.png (added)
• cat_fig2.bmp (deleted)
• cat_fig2.png (added)
• dm_eq.gif (deleted)
• dm_eq.png (added)
• edit_menu.bmp (deleted)
• edit_menu.png (added)
• file_menu.bmp (deleted)
• file_menu.png (added)
• m0x_eq.gif (deleted)
• m0x_eq.png (added)
• m0y_eq.gif (deleted)
• m0y_eq.png (added)
• m0z_eq.gif (deleted)
• m0z_eq.png (added)
• mag_help.rst (modified) (5 diffs)
• mag_vector.bmp (deleted)
• mag_vector.png (added)
• mqx.gif (deleted)
• mqx.png (added)
• mqy.gif (deleted)
• mqy.png (added)
• mxp.gif (deleted)
• mxp.png (added)
• myp.gif (deleted)
• myp.png (added)
• mzp.gif (deleted)
• mzp.png (added)
• new_model.bmp (deleted)
• new_model.png (added)
• pd_help.rst (modified) (11 diffs)
• plot_button.bmp (deleted)
• plot_button.png (added)
• residuals_help.rst (modified) (3 diffs)
• restore_batch_window.bmp (deleted)
• restore_batch_window.png (added)
• sld1.gif (deleted)
• sld1.png (added)
• sld2.gif (deleted)
• sld2.png (added)
• sm_help.rst (modified) (12 diffs)
• sm_image002.gif (deleted)
• sm_image002.png (added)
• sm_image003.gif (deleted)
• sm_image003.png (added)
• sm_image004.gif (deleted)
• sm_image004.png (added)
• sm_image005.gif (deleted)
• sm_image005.png (added)
• sm_image006.gif (deleted)
• sm_image006.png (added)
• sm_image007.gif (deleted)
• sm_image007.png (added)
• sm_image008.gif (deleted)
• sm_image008.png (added)
• sm_image009.gif (deleted)
• sm_image009.png (added)
• sm_image010.gif (deleted)
• sm_image010.png (added)
• sm_image011.gif (deleted)
• sm_image011.png (added)
• sm_image012.gif (deleted)
• sm_image012.png (added)
• sm_image013.gif (deleted)
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• sm_image016.gif (deleted)
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• sm_image017.png (added)
• sm_image018.gif (deleted)
• sm_image018.png (added)
• sm_image019.gif (deleted)
• sm_image019.png (added)
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• sm_image027.gif (deleted)
• sm_image027.png (added)
• sm_image028.gif (deleted)
• sm_image028.png (added)
• sum_model.bmp (deleted)
• sum_model.png (added)
• view_button.bmp (deleted)
• view_button.png (added)
• view_data_model.bmp (deleted)
• view_data_model.png (added)

src/sas/sasgui/perspectives/fitting/media/fitting_help.rst

@@ -195 +195 @@
 the :ref:`Advanced_Plugin_Editor` .
 
+**SasView version 4.2** made it possible to specify whether a plugin created with 
+the *New Plugin Model* dialog is actually a form factor P(Q) or a structure factor 
+S(Q). To do this, simply add one or other of the following lines under the *import* 
+statements.
+
+For a form factor::
+
+     form_factor = True
+         
+or for a structure factor::
+
+     structure_factor = True
+         
+If the plugin is a structure factor it is *also* necessary to add two variables to 
+the parameter list::
+
+     parameters = [ 
+                     ['radius_effective', '', 1, [0.0, numpy.inf], 'volume', ''],
+                     ['volfraction', '', 1, [0.0, 1.0], '', ''],
+                     [...],
+
+and to the declarations of the functions Iq and Iqxy:::
+
+     def Iq(x , radius_effective, volfraction, ...):
+
+     def Iqxy(x, y, radius_effective, volfraction, ...):
+
+Such a plugin should then be available in the S(Q) drop-down box on a FitPage (once 
+a P(Q) model has been selected).
+
 Sum|Multi(p1,p2)
 ^^^^^^^^^^^^^^^^
@@ -206 +236 @@
 or::
 
-     Plugin Model = scale_factor * model_1 /* model_2 + background
+     Plugin Model = scale_factor * (model1 * model2) + background
 
 In the *Easy Sum/Multi Editor* give the new model a function name and brief
 description (to appear under the *Details* button on the *FitPage*). Then select
 two existing models, as p1 and p2, and the required operator, '+' or '*' between
-them. Finally, click the *Apply* button to generate the model and then click *Close*.
-
-Any changes to a plugin model generated in this way only become effective *after* it is re-selected from the model drop-down menu on the FitPage.
+them. Finally, click the *Apply* button to generate and test the model and then click *Close*.
+
+Any changes to a plugin model generated in this way only become effective *after* it is re-selected 
+from the plugin models drop-down menu on the FitPage. If the model is not listed you can force a 
+recompilation of the plugins by selecting *Fitting* > *Plugin Model Operations* > *Load Plugin Models*.
+
+**SasView version 4.2** introduced a much simplified and more extensible structure for plugin models 
+generated through the Easy Sum/Multi Editor. For example, the code for a combination of a sphere model 
+with a power law model now looks like this::
+
+     from sasmodels.core import load_model_info
+     from sasmodels.sasview_model import make_model_from_info
+     
+     model_info = load_model_info('sphere+power_law')
+     model_info.name = 'MyPluginModel'
+     model_info.description = 'sphere + power_law'
+     Model = make_model_from_info(model_info)
+
+To change the models or operators contributing to this plugin it is only necessary to edit the string 
+in the brackets after *load_model_info*, though it would also be a good idea to update the model name 
+and description too!!!
+
+The model specification string can handle multiple models and combinations of operators (+ or *) which 
+are processed according to normal conventions. Thus 'model1+model2*model3' would be valid and would 
+multiply model2 by model3 before adding model1. In this example, parameters in the *FitPage* would be 
+prefixed A (for model2), B (for model3) and C (for model1). Whilst this might appear a little 
+confusing, unless you were creating a plugin model from multiple instances of the same model the parameter 
+assignments ought to be obvious when you load the plugin.
+
+If you need to include another plugin model in the model specification string, just prefix the name of 
+that model with *custom*. For instance::
+
+     sphere+custom.MyPluginModel
+
+To create a P(Q)*\S(Q) model use the @ symbol instead of * like this::
+
+     sphere@hardsphere
+     
+This streamlined approach to building complex plugin models from existing library models, or models 
+available on the *Model Marketplace*, also permits the creation of P(Q)*\S(Q) plugin models, something 
+that was not possible in earlier versions of SasView. 
 
 .. _Advanced_Plugin_Editor:
@@ -484 +552 @@
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
 
+.. _Batch_Fit_Mode:
+
 Batch Fit Mode
 --------------
@@ -636 +706 @@
 
      Example: radius [2 : 5] , radius [10 : 25]
-
-.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
-
-.. note::  This help document was last changed by Steve King, 10Oct2016
+     
+.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+
+Combined Batch Fit Mode
+-----------------------
+
+The purpose of the Combined Batch Fit is to allow running two or more batch
+fits in sequence without overwriting the output table of results.  This may be
+of interest for example if one is fitting a series of data sets where there is
+a shape change occurring in the series that requires changing the model part
+way through the series; for example a sphere to rod transition.  Indeed the
+regular batch mode does not allow for multiple models and requires all the
+files in the series to be fit with single model and set of parameters.  While
+it is of course possible to just run part of the series as a batch fit using
+model one followed by running another batch fit on the rest of the series with
+model two (and/or model three etc), doing so will overwrite the table of
+outputs from the previous batch fit(s).  This may not be desirable if one is
+interested in comparing the parameters: for example the sphere radius of set
+one and the cylinder radius of set two.
+
+Method
+^^^^^^
+
+In order to use the *Combined Batch Fit*, first load all the data needed as
+described in :ref:`Loading_data`. Next start up two or more *BatchPage* fits
+following the instructions in :ref:`Batch_Fit_Mode` but **DO NOT PRESS FIT**.
+At this point the *Combine Batch Fit* menu item under the *Fitting menu* should
+be active (if there is one or no *BatchPage* the menu item will be greyed out
+and inactive).  Clicking on *Combine Batch Fit* will bring up a new panel,
+similar to the *Const & Simult Fit* panel. In this case there will be a
+checkbox for each *BatchPage* instead of each *FitPage* that should be included
+in the fit.  Once all are selected, click the Fit button on
+the *BatchPage* to run each batch fit in *sequence*
+
+.. image:: combine_batch_page.png
+
+The batch table will then pop up at the end as for the case of the simple Batch
+Fitting with the following caveats:
+
+.. note::
+   The order matters.  The parameters in the table will be taken from the model
+   used in the first *BatchPage* of the list.  Any parameters from the
+   second and later *BatchPage* s that have the same name as a parameter in the
+   first will show up allowing for plotting of that parameter across the
+   models. The other parameters will not be available in the grid.
+.. note::
+   a corralary of the above is that currently models created as a sum|multiply
+   model will not work as desired because the generated model parameters have a
+   p#_ appended to the beginning and thus radius and p1_radius will not be
+   recognized as the same parameter.
+   
+.. image:: combine_batch_grid.png
+
+In the example shown above the data is a time series with a shifting peak.
+The first part of the series was fitted using the *broad_peak* model, while
+the rest of the data were fit using the *gaussian_peak* model. Unfortunately the
+time is not listed in the file but the file name contains the information. As
+described in :ref:`Grid_Window`, a column can be added manually, in this case
+called time, and the peak position plotted against time. 
+
+.. image:: combine_batch_plot.png
+
+Note the discontinuity in the peak position.  This reflects the fact that the
+Gaussian fit is a rather poor model for the data and is not actually
+finding the peak.
+
+.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+
+.. note::  This help document was last changed by Paul Butler, 10 September
+   2017

src/sas/sasgui/perspectives/fitting/media/plugin.rst

@@ -18 +18 @@
 * By writing a model from scratch outside of SasView (only recommended for
   code monkeys!)
+
+**What follows below is quite technical. If you just want a helping hand to get 
+started creating your own models see** :ref:`Adding_your_own_models`.
 
 Overview

src/sas/sasgui/perspectives/fitting/media/mag_help.rst

@@ -4 +4 @@
 .. by S King, ISIS, during SasView CodeCamp-III in Feb 2015.
 
-.. |inlineimage004| image:: sm_image004.gif
-.. |inlineimage005| image:: sm_image005.gif
-.. |inlineimage008| image:: sm_image008.gif
-.. |inlineimage009| image:: sm_image009.gif
-.. |inlineimage010| image:: sm_image010.gif
-.. |inlineimage011| image:: sm_image011.gif
-.. |inlineimage012| image:: sm_image012.gif
-.. |inlineimage018| image:: sm_image018.gif
-.. |inlineimage019| image:: sm_image019.gif
+.. |inlineimage004| image:: sm_image004.png
+.. |inlineimage005| image:: sm_image005.png
+.. |inlineimage008| image:: sm_image008.png
+.. |inlineimage009| image:: sm_image009.png
+.. |inlineimage010| image:: sm_image010.png
+.. |inlineimage011| image:: sm_image011.png
+.. |inlineimage012| image:: sm_image012.png
+.. |inlineimage018| image:: sm_image018.png
+.. |inlineimage019| image:: sm_image019.png
 
 
@@ -20 +20 @@
 --------------------------------
 
-Magnetic scattering is implemented in five (2D) models 
+Magnetic scattering is implemented in five (2D) models
 
 *  *sphere*
@@ -28 +28 @@
 *  *parallelepiped*
 
-In general, the scattering length density (SLD, = |beta|) in each region where the
+In general, the scattering length density (SLD, = $\beta$) in each region where the
 SLD is uniform, is a combination of the nuclear and magnetic SLDs and, for polarised
 neutrons, also depends on the spin states of the neutrons.
 
-For magnetic scattering, only the magnetization component, *M*\ :sub:`perp`,
-perpendicular to the scattering vector *Q* contributes to the the magnetic
+For magnetic scattering, only the magnetization component, $M_\perp$,
+perpendicular to the scattering vector $Q$ contributes to the the magnetic
 scattering length.
 
-.. image:: mag_vector.bmp
+.. image:: mag_vector.png
 
 The magnetic scattering length density is then
 
-.. image:: dm_eq.gif
+.. image:: dm_eq.png
 
-where |gamma| = -1.913 is the gyromagnetic ratio, |mu|\ :sub:`B` is the
-Bohr magneton, *r*\ :sub:`0` is the classical radius of electron, and |sigma|
+where $\gamma = -1.913$ is the gyromagnetic ratio, $\mu_B$ is the
+Bohr magneton, $r_0$ is the classical radius of electron, and $\sigma$
 is the Pauli spin.
 
@@ -53 +53 @@
 Spin-flips    (+ -) and (- +)
 
-.. image:: M_angles_pic.bmp
+.. image:: M_angles_pic.png
 
-If the angles of the *Q* vector and the spin-axis (*x'*) to the *x*-axis are |phi|
-and |theta|\ :sub:`up`, respectively, then, depending on the spin state of the
+If the angles of the $Q$ vector and the spin-axis (*x'*) to the *x*-axis are $\phi$
+and $\theta_\text{up}$, respectively, then, depending on the spin state of the
 neutrons, the scattering length densities, including the nuclear scattering
-length density (|beta|\ :sub:`N`) are
+length density ($\beta_N$) are
 
-.. image:: sld1.gif
+.. image:: sld1.png
 
 when there are no spin-flips, and
 
-.. image:: sld2.gif
+.. image:: sld2.png
 
 when there are, and
 
-.. image:: mxp.gif
+.. image:: mxp.png
 
-.. image:: myp.gif
+.. image:: myp.png
 
-.. image:: mzp.gif
+.. image:: mzp.png
 
-.. image:: mqx.gif
+.. image:: mqx.png
 
-.. image:: mqy.gif
+.. image:: mqy.png
 
-Here, *M*\ :sub:`0x`, *M*\ :sub:`0y` and *M*\ :sub:`0z` are the x, y and z components
-of the magnetization vector given in the laboratory xyz frame given by
+Here, $M_{0x}$, $M_{0y}$ and $M_{0z}$ are the $x$, $y$ and $z$ components
+of the magnetization vector given in the laboratory $xyz$ frame given by
 
-.. image:: m0x_eq.gif
+.. image:: m0x_eq.png
 
-.. image:: m0y_eq.gif
+.. image:: m0y_eq.png
 
-.. image:: m0z_eq.gif
+.. image:: m0z_eq.png
 
-and the magnetization angles |theta|\ :sub:`M` and |phi|\ :sub:`M` are defined in
+and the magnetization angles $\theta_M$ and $\phi_M$ are defined in
 the figure above.
 
@@ -93 +93 @@
 
 ===========   ================================================================
- M0_sld        = *D*\ :sub:`M` *M*\ :sub:`0`
- Up_theta      = |theta|\ :sub:`up`
- M_theta       = |theta|\ :sub:`M`
- M_phi         = |phi|\ :sub:`M`
+ M0_sld        = $D_M M_0$
+ Up_theta      = $\theta_\text{up}$
+ M_theta       = $\theta_M$
+ M_phi         = $\phi_M$
  Up_frac_i     = (spin up)/(spin up + spin down) neutrons *before* the sample
  Up_frac_f     = (spin up)/(spin up + spin down) neutrons *after* the sample

src/sas/sasgui/perspectives/fitting/media/pd_help.rst

@@ -4 +4 @@
 .. by S King, ISIS, during SasView CodeCamp-III in Feb 2015.
 
-.. |inlineimage004| image:: sm_image004.gif
-.. |inlineimage005| image:: sm_image005.gif
-.. |inlineimage008| image:: sm_image008.gif
-.. |inlineimage009| image:: sm_image009.gif
-.. |inlineimage010| image:: sm_image010.gif
-.. |inlineimage011| image:: sm_image011.gif
-.. |inlineimage012| image:: sm_image012.gif
-.. |inlineimage018| image:: sm_image018.gif
-.. |inlineimage019| image:: sm_image019.gif
+.. |inlineimage004| image:: sm_image004.png
+.. |inlineimage005| image:: sm_image005.png
+.. |inlineimage008| image:: sm_image008.png
+.. |inlineimage009| image:: sm_image009.png
+.. |inlineimage010| image:: sm_image010.png
+.. |inlineimage011| image:: sm_image011.png
+.. |inlineimage012| image:: sm_image012.png
+.. |inlineimage018| image:: sm_image018.png
+.. |inlineimage019| image:: sm_image019.png
 
 
@@ -24 +24 @@
 form factor is normalized by the average particle volume such that
 
-*P(q) = scale* * \ <F*\F> / *V + bkg*
+.. math::
 
-where F is the scattering amplitude and the \<\> denote an average over the size
-distribution.
+    P(q) = \text{scale} \langle F^*F rangle V + \text{background}
+
+where $F$ is the scattering amplitude and $\langle\cdot\rangle$ denotes an average
+over the size distribution.
 
 Users should note that this computation is very intensive. Applying polydispersion
@@ -57 +59 @@
 .. image:: pd_image001.png
 
-where *xmean* is the mean of the distribution, *w* is the half-width, and *Norm* is a
-normalization factor which is determined during the numerical calculation.
+where $x_{mean}$ is the mean of the distribution, $w$ is the half-width, and $Norm$
+is a normalization factor which is determined during the numerical calculation.
 
-Note that the standard deviation and the half width *w* are different!
+Note that the standard deviation and the half width $w$ are different!
 
 The standard deviation is
@@ -81 +83 @@
 .. image:: pd_image005.png
 
-where *xmean* is the mean of the distribution and *Norm* is a normalization factor
+where $x_{mean}$ is the mean of the distribution and $Norm$ is a normalization factor
 which is determined during the numerical calculation.
 
@@ -100 +102 @@
 .. image:: pd_image007.png
 
-where |mu|\ =ln(*xmed*), *xmed* is the median value of the distribution, and
-*Norm* is a normalization factor which will be determined during the numerical
+where $\mu=\ln(x_{med})$, $x_{med}$ is the median value of the distribution, and
+$Norm$ is a normalization factor which will be determined during the numerical
 calculation.
 
@@ -107 +109 @@
 size parameter in the *FitPage*, for example, radius = 60.
 
-The polydispersity is given by |sigma|
+The polydispersity is given by $\sigma$
 
 .. image:: pd_image008.png
@@ -115 +117 @@
 .. image:: pd_image009.png
 
-The mean value is given by *xmean*\ =exp(|mu|\ +p\ :sup:`2`\ /2). The peak value
-is given by *xpeak*\ =exp(|mu|-p\ :sup:`2`\ ).
+The mean value is given by $x_{mean} =\exp(\mu + p^2 /2)$. The peak value
+is given by $x_{peak} =\exp(\mu-p^2)$.
 
 .. image:: pd_image010.jpg
 
-This distribution function spreads more, and the peak shifts to the left, as *p*
+This distribution function spreads more, and the peak shifts to the left, as $p$
 increases, requiring higher values of Nsigmas and Npts.
 
@@ -132 +134 @@
 .. image:: pd_image011.png
 
-where *xmean* is the mean of the distribution and *Norm* is a normalization factor
-which is determined during the numerical calculation, and *z* is a measure of the
+where $x_{mean}$ is the mean of the distribution and $Norm$ is a normalization factor
+which is determined during the numerical calculation, and $z$ is a measure of the
 width of the distribution such that
 
-z = (1-p\ :sup:`2`\ ) / p\ :sup:`2`
+.. math::
+
+    z = (1-p^2 ) / p^2
 
 The polydispersity is
@@ -156 +160 @@
 
 This user-definable distribution should be given as as a simple ASCII text file
-where the array is defined by two columns of numbers: *x* and *f(x)*. The *f(x)*
+where the array is defined by two columns of numbers: $x$ and $f(x)$. The $f(x)$
 will be normalized by SasView during the computation.
 
@@ -172 +176 @@
 
 SasView only uses these array values during the computation, therefore any mean
-value of the parameter represented by *x* present in the *FitPage*
+value of the parameter represented by $x$ present in the *FitPage*
 will be ignored.
 
@@ -181 +185 @@
 
 Many commercial Dynamic Light Scattering (DLS) instruments produce a size
-polydispersity parameter, sometimes even given the symbol *p*! This parameter is
+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 parameters in the Lognormal

src/sas/sasgui/perspectives/fitting/media/residuals_help.rst

@@ -18 +18 @@
 also provides two other measures of the quality of a fit:
 
-*  |chi|\  :sup:`2` (or 'Chi2'; pronounced 'chi-squared')
+*  $\chi^2$ (or 'Chi2'; pronounced 'chi-squared')
 *  *Residuals*
 
@@ -32 +32 @@
 *Npts* such that
 
-  *Chi2/Npts* = { SUM[(*Y_i* - *Y_theory_i*)^2 / (*Y_error_i*)^2] } / *Npts*
+.. math::
 
-This differs slightly from what is sometimes called the 'reduced chi-squared'
+  \chi^2/N_{pts} =  \sum[(Y_i - \mathrm{theory}_i)^2 / \mathrm{error}_i^2] / N_{pts}
+
+This differs slightly from what is sometimes called the 'reduced $\chi^2$'
 because it does not take into account the number of fitting parameters (to
-calculate the number of 'degrees of freedom'), but the 'normalized chi-squared'
-and the 'reduced chi-squared' are very close to each other when *Npts* >> number of
-parameters.
+calculate the number of 'degrees of freedom'), but the 'normalized $\chi^2$
+and the 'reduced $\chi^2$ are very close to each other when $N_{pts} \gg
+\text{number of parameters}.
 
-For a good fit, *Chi2/Npts* tends to 0.
+For a good fit, $\chi^2/N_{pts}$ tends to 1.
 
-*Chi2/Npts* is sometimes referred to as the 'goodness-of-fit' parameter.
+$\chi^2/N_{pts}$ is sometimes referred to as the 'goodness-of-fit' parameter.
 
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
@@ -53 +55 @@
 value and its *true* value is its error).
 
-*SasView* calculates 'normalized residuals', *R_i*, for each data point in the
+*SasView* calculates 'normalized residuals', $R_i$, for each data point in the
 fit:
 
-  *R_i* = (*Y_i* - *Y_theory_i*) / (*Y_err_i*)
+.. math::
 
-For a good fit, *R_i* ~ 0.
+  R_i = (Y_i - Y_theory_i) / (Y_err_i)
+
+For a good fit, $R_i \sim 0$.
 
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ

src/sas/sasgui/perspectives/fitting/media/sm_help.rst

@@ -4 +4 @@
 .. by S King, ISIS, during SasView CodeCamp-III in Feb 2015.
 
-.. |inlineimage004| image:: sm_image004.gif
-.. |inlineimage005| image:: sm_image005.gif
-.. |inlineimage008| image:: sm_image008.gif
-.. |inlineimage009| image:: sm_image009.gif
-.. |inlineimage010| image:: sm_image010.gif
-.. |inlineimage011| image:: sm_image011.gif
-.. |inlineimage012| image:: sm_image012.gif
-.. |inlineimage018| image:: sm_image018.gif
-.. |inlineimage019| image:: sm_image019.gif
+.. |inlineimage004| image:: sm_image004.png
+.. |inlineimage005| image:: sm_image005.png
+.. |inlineimage008| image:: sm_image008.png
+.. |inlineimage009| image:: sm_image009.png
+.. |inlineimage010| image:: sm_image010.png
+.. |inlineimage011| image:: sm_image011.png
+.. |inlineimage012| image:: sm_image012.png
+.. |inlineimage018| image:: sm_image018.png
+.. |inlineimage019| image:: sm_image019.png
 
 
@@ -20 +20 @@
 ==================
 
-Sometimes the instrumental geometry used to acquire the experimental data has 
-an impact on the clarity of features in the reduced scattering curve. For 
-example, peaks or fringes might be slightly broadened. This is known as 
-*Q resolution smearing*. To compensate for this effect one can either try and 
-remove the resolution contribution - a process called *desmearing* - or add the 
-resolution contribution into a model calculation/simulation (which by definition 
-will be exact) to make it more representative of what has been measured 
+Sometimes the instrumental geometry used to acquire the experimental data has
+an impact on the clarity of features in the reduced scattering curve. For
+example, peaks or fringes might be slightly broadened. This is known as
+*Q resolution smearing*. To compensate for this effect one can either try and
+remove the resolution contribution - a process called *desmearing* - or add the
+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*. SasView will do the latter.
 
-Both smearing and desmearing rely on functions to describe the resolution 
+Both smearing and desmearing rely on functions to describe the resolution
 effect. SasView provides three smearing algorithms:
 
@@ -36 +36 @@
 *  *2D Smearing*
 
-SasView also has an option to use Q resolution data (estimated at the time of 
+SasView also has an option to use $Q$ resolution data (estimated at the time of
 data reduction) supplied in a reduced data file: the *Use dQ data* radio button.
 
@@ -43 +43 @@
 dQ Smearing
 -----------
- 
-If this option is checked, SasView will assume that the supplied dQ values 
+
+If this option is checked, SasView will assume that the supplied $dQ$ values
 represent the standard deviations of Gaussian functions.
 
@@ -57 +57 @@
 The slit-smeared scattering intensity is defined by
 
-.. image:: sm_image002.gif
+.. image:: sm_image002.png
 
 where *Norm* is given by
 
-.. image:: sm_image003.gif
+.. image:: sm_image003.png
 
 **[Equation 1]**
 
-The functions |inlineimage004| and |inlineimage005|
-refer to the slit width weighting function and the slit height weighting 
-determined at the given *q* point, respectively. It is assumed that the weighting
+The functions $W_v(v)$ and $W_u(u)$
+refer to the slit width weighting function and the slit height weighting
+determined at the given $q$ point, respectively. It is assumed that the weighting
 function is described by a rectangular function, such that
 
-.. image:: sm_image006.gif
+.. image:: sm_image006.png
 
 **[Equation 2]**
@@ -76 +76 @@
 and
 
-.. image:: sm_image007.gif
+.. image:: sm_image007.png
 
 **[Equation 3]**
 
-so that |inlineimage008| |inlineimage009| for |inlineimage010| and *u*\ .
-
-Here |inlineimage011| and |inlineimage012| stand for
-the slit height (FWHM/2) and the slit width (FWHM/2) in *q* space.
+so that $\Delta q_\alpha = \int_0^\infty d\alpha W_\alpha(\alpha)$
+for $\alpha = v$ and $u$.
+
+Here $\Delta q_u$ and $\Delta q_v$ stand for
+the slit height (FWHM/2) and the slit width (FWHM/2) in $q$ space.
 
 This simplifies the integral in Equation 1 to
 
-.. image:: sm_image013.gif
+.. image:: sm_image013.png
 
 **[Equation 4]**
 
-which may be solved numerically, depending on the nature of |inlineimage011| and |inlineimage012| .
+which may be solved numerically, depending on the nature of
+$\Delta q_u$ and $\Delta q_v$.
 
 Solution 1
 ^^^^^^^^^^
 
-**For** |inlineimage012| **= 0 and** |inlineimage011| **= constant.**
-
-.. image:: sm_image016.gif
-
-For discrete *q* values, at the *q* values of the data points and at the *q*
-values extended up to *q*\ :sub:`N`\ = *q*\ :sub:`i` + |inlineimage011| the smeared
+**For $\Delta q_v= 0$ and $\Delta q_u = \text{constant}$.**
+
+.. image:: sm_image016.png
+
+For discrete $q$ values, at the $q$ values of the data points and at the $q$
+values extended up to $q_N = q_i + \Delta q_u$ the smeared
 intensity can be approximately calculated as
 
-.. image:: sm_image017.gif
+.. image:: sm_image017.png
 
 **[Equation 5]**
 
-where |inlineimage018| = 0 for *I*\ :sub:`s` when *j* < *i* or *j* > *N-1*.
+where |inlineimage018| = 0 for $I_s$ when $j < i$ or $j > N-1$.
 
 Solution 2
 ^^^^^^^^^^
 
-**For** |inlineimage012| **= constant and** |inlineimage011| **= 0.**
+**For $\Delta q_v = \text{constant}$ and $\Delta q_u= 0$.**
 
 Similar to Case 1
 
-|inlineimage019| for *q*\ :sub:`p` = *q*\ :sub:`i` - |inlineimage012| and *q*\ :sub:`N` = *q*\ :sub:`i` + |inlineimage012|
+|inlineimage019| for $q_p = q_i - \Delta q_v$ and $q_N = q_i + \Delta q_v$
 
 **[Equation 6]**
 
-where |inlineimage018| = 0 for *I*\ :sub:`s` when *j* < *p* or *j* > *N-1*.
+where |inlineimage018| = 0 for $I_s$ when $j < p$ or $j > N-1$.
 
 Solution 3
 ^^^^^^^^^^
 
-**For** |inlineimage011| **= constant and** |inlineimage011| **= constant.**
+**For $\Delta q_u = \text{constant}$ and $\Delta q_v = \text{constant}$.**
 
 In this case, the best way is to perform the integration of Equation 1
@@ -138 +140 @@
 numerical integration for the slit width. Then
 
-.. image:: sm_image020.gif
+.. image:: sm_image020.png
 
 **[Equation 7]**
 
-for *q*\ :sub:`p` = *q*\ :sub:`i` - |inlineimage012| and *q*\ :sub:`N` = *q*\ :sub:`i` + |inlineimage012|
-
-where |inlineimage018| = 0 for *I*\ :sub:`s` when *j* < *p* or *j* > *N-1*.
+for *q_p = q_i - \Delta q_v$ and $q_N = q_i + \Delta q_v$
+where |inlineimage018| = 0 for *I_s$ when $j < p$ or $j > N-1$.
 
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
@@ -158 +159 @@
 Equation 6 becomes
 
-.. image:: sm_image021.gif
+.. image:: sm_image021.png
 
 **[Equation 8]**
@@ -171 +172 @@
 Thus
 
-.. image:: sm_image022.gif
+.. image:: sm_image022.png
 
 **[Equation 9]**
 
-In Equation 9, *x*\ :sub:`0` = *q* cos(|theta|), *y*\ :sub:`0` = *q* sin(|theta|), and
-the primed axes, are all in the coordinate rotated by an angle |theta| about
-the z-axis (see the figure below) so that *x'*\ :sub:`0` = *x*\ :sub:`0` cos(|theta|) +
-*y*\ :sub:`0` sin(|theta|) and *y'*\ :sub:`0` = -*x*\ :sub:`0` sin(|theta|) +
-*y*\ :sub:`0` cos(|theta|). Note that the rotation angle is zero for a x-y symmetric
-elliptical Gaussian distribution. The *A* is a normalization factor.
-
-.. image:: sm_image023.gif
-
-Now we consider a numerical integration where each of the bins in |theta| and *R* are
-*evenly* (this is to simplify the equation below) distributed by |bigdelta|\ |theta|
-and |bigdelta|\ R, respectively, and it is further assumed that *I(x',y')* is constant
+In Equation 9, $x_0 = q \cos(\theta)$, $y_0 = q \sin(\theta)$, and
+the primed axes, are all in the coordinate rotated by an angle $\theta$ about
+the z-axis (see the figure below) so that
+$x'_0 = x_0 \cos(\theta) + y_0 \sin(\theta)$ and
+$y'_0 = -x_0 \sin(\theta) + y_0 \cos(\theta)$.
+Note that the rotation angle is zero for a $xy$ symmetric
+elliptical Gaussian distribution. The $A$ is a normalization factor.
+
+.. image:: sm_image023.png
+
+Now we consider a numerical integration where each of the bins in $\theta$ and $R$ are
+*evenly* (this is to simplify the equation below) distributed by $\Delta \theta$
+and $\Delta R$, respectively, and it is further assumed that $I(x',y')$ is constant
 within the bins. Then
 
-.. image:: sm_image024.gif
+.. image:: sm_image024.png
 
 **[Equation 10]**
 
 Since the weighting factor on each of the bins is known, it is convenient to
-transform *x'-y'* back to *x-y* coordinates (by rotating it by -|theta| around the
-*z* axis).
+transform $x'y'$ back to $xy$ coordinates (by rotating it by $-\theta$ around the
+$z$ axis).
 
 Then, for a polar symmetric smear
 
-.. image:: sm_image025.gif
+.. image:: sm_image025.png
 
 **[Equation 11]**
@@ -205 +207 @@
 where
 
-.. image:: sm_image026.gif
-
-while for a *x-y* symmetric smear
-
-.. image:: sm_image027.gif
+.. image:: sm_image026.png
+
+while for a $xy$ symmetric smear
+
+.. image:: sm_image027.png
 
 **[Equation 12]**
@@ -215 +217 @@
 where
 
-.. image:: sm_image028.gif
+.. image:: sm_image028.png
 
 The current version of the SasView uses Equation 11 for 2D smearing, assuming
@@ -225 +227 @@
 -------------------------
 
-In all the cases above, the weighting matrix *W* is calculated on the first call
-to a smearing function, and includes ~60 *q* values (finely and evenly binned)
-below (>0) and above the *q* range of data in order to smear all data points for
-a given model and slit/pinhole size. The *Norm*  factor is found numerically with the
-weighting matrix and applied on the computation of *I*\ :sub:`s`.
+In all the cases above, the weighting matrix $W$ is calculated on the first call
+to a smearing function, and includes ~60 $q$ values (finely and evenly binned)
+below (>0) and above the $q$ range of data in order to smear all data points for
+a given model and slit/pinhole size. The $Norm$  factor is found numerically with the
+weighting matrix and applied on the computation of $I_s$.
 
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ