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peak plugin

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Kohlbrecher committed May 7, 2016
1 parent dbe0067 commit aebb470704b82f0603994cf48da8e409e90214b6
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@@ -1,3 +1,6 @@
+0.94.8 2016-MM-DD
+- reading ascii data from ALV-5000 for DLS-analysis
+
0.94.7 2016-04-25
- implementation of another cumulant formula for DLS
- Bug-fix in the unit conversion routine
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@@ -16,10 +16,9 @@ sasfit-core (core functionality of the sasfit program,
not complete, in progress)
Requirements:
-- Cmake >=2.8.0 (http://www.gnu.org/software/gsl/)
-- GSL library (http://www.gnu.org/software/gsl/)
- (for Windows: http://gnuwin32.sourceforge.net/packages/gsl.htm)
-- Tcl >=8.4 for sasfit-core
+- Cmake >=3.5.0 (http://www.gnu.org/software/gsl/)
+- C and C++ compiler (e.g. gcc)
+- standard compression software like bzip2, zip, tar, gz
Author Information:
@@ -43,6 +42,10 @@ For license information see COPYING.txt.
Documentation
=============
+A paper about SASfit has been published in
+J. Appl. Cryst. (2015). 48, 1587-1598
+doi:10.1107/S1600576715016544
+
Documentation is provided in HTML format in the directory
<your-sasfit-source-directory>/doc/html/
@@ -364,7 +364,7 @@ \subsection{Star polymer with Gaussian statistic according to
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\subsection{Polydisperse star polymer with Gaussian statistics \cite{burchard74}}
+\subsection{Polydisperse star polymer with Gaussian statistics \cite{Burchard74}}
\label{sect:PolydisperseStar}
~\\
\begin{figure}[htb]
@@ -375,7 +375,7 @@ \subsection{Polydisperse star polymer with Gaussian statistics \cite{burchard74}
\end{figure}
For a Schulz–Flory (most probable) distribution (Schulz–Zimm distribution
-with $z = 1$) for the mass distribution of the arms, Burchard \cite{burchard74} has given the form factor:
+with $z = 1$) for the mass distribution of the arms, Burchard \cite{Burchard74} has given the form factor:
\begin{align}
I_\text{PolydisperseStar}(Q) &= I_0
\frac{1+\frac{u^2}{3 f}}{\left(1+\frac{u^2(f +1)}{6 f }\right)^2}
View
@@ -126,6 +126,7 @@ \section{Log-Normal distribution}
\clearpage
\section{Schulz-Zimm (Flory) distribution}
+\label{sec:SchulzZimm}
\begin{figure}[htb]
\begin{center}
@@ -207,6 +208,7 @@ \section{Gamma distribution}
When $k$ is large, the gamma distribution closely approximates a normal distribution
with the advantage that the gamma distribution has density only for positive real
numbers. For small values of $k$ the distribution becomes a right tailed distribution.
+The gamm distribution is equivalent to the Schulz-Zimm distribution (sec.\ \ref{sec:SchulzZimm}), which is using the mean value instead of $\theta=x_\mathrm{mean}/k$ for the parametrization. Also the Pearson III \ref{sec:PearsonIIIdist} is just another name for this distribution.
The $m^\text{th}$ moment $\langle X^m\rangle$ of the size distribution is given by
\begin{align}
@@ -256,6 +258,7 @@ \section{Gamma distribution}
\clearpage
\section{PearsonIII distribution}
+\label{sec:PearsonIIIdist}
The Pearson distribution is a family of probability distributions
that are a generalisation of the normal distribution. The Pearson
@@ -317,23 +320,40 @@ \section{Gauss distribution}
\text{erf}\left(\frac{R_0}{\sqrt{2}\sigma}\right) \right)
\end{align}
\end{subequations}
-$c_\text{Gauss}$ is choosen so that $\int_0^\infty\!
+$c_\text{Gauss}$ is chosen so that $\int_0^\infty\!
\text{Gauss}(R,\sigma,R_0)\,dR = N$
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\clearpage
\section{Generalized exponential distribution (GEX)}
-\begin{subequations}
+The generalised exponential distribution is a three parameter distribution.
\begin{align}
-\text{GEX}(R,\beta,\lambda,\gamma))&= N
-\frac{\beta}{\gamma}\left(\frac{x}{\gamma}\right)^{\lambda+1}
-\frac{e^{-(x/\gamma)^{\beta}}}{\Gamma \left( {\frac
-{\lambda+2}{\beta}} \right)}
+\text{GEX} (x,\beta,\lambda,\gamma) &= N \frac{\abs{\beta}}{\gamma} \left(\frac{x}{\gamma}\right)^{\lambda+1}
+\frac{e^{-(x/\gamma)^\beta}}{\Gamma\left( \frac{\lambda+2}{\beta} \right)} \\
+\text{GEX}(x,\beta,p,\gamma) &= N
+\frac{\abs{\beta}}{\gamma}\left(\frac{x}{\gamma}\right)^{p-1}
+\frac{e^{-(x/\gamma)^{\beta}}}{\Gamma \left( {\frac{p}{\beta}} \right)}
+\end{align}
+For $\lambda+2=p=\beta$ it will transform in the Weibull distribution (eq.\ \ref{eq:Weibull}). For $\beta=1$ one yields the Schulz-Zimm distribution (eq.\ \ref{eq:SZn(M)}) or the equivalent gamma distribution (eq.\ \ref{eq:GammaDistr}). In The limit $\beta \rightarrow 0$ the GEX distribution transforms into a Lognormal distribution.
+The mode $x_\mathrm{mode}$, mean $x_\mathrm{mean}$, and variance $\sigma^2$ of this distribution are given by
+\begin{align}
+x_\mathrm{mode} &= \gamma \left( \frac{\lambda+1}{\beta}\right)^\frac{1}{\beta} \\
+x_\mathrm{mean} &=
+\begin{cases}
+\gamma \Gamma\left(\frac{\lambda+3}{\beta}\right)/\Gamma\left(\frac{\lambda+2}{\beta}\right) & \mbox{for } \beta > 0 \wedge \lambda > -3 \\
+\mbox{undefined} & \mbox{otherwise}
+\end{cases} \\
+\sigma^2 &=
+\begin{cases}
+\gamma^2 \left(
+\frac{\Gamma\left(\frac{\lambda+4}{\beta}\right)}{\Gamma\left(\frac{\lambda+2}{\beta}\right)} -
+\left(\frac{\Gamma\left(\frac{\lambda+3}{\beta}\right)}{\Gamma\left(\frac{\lambda+2}{\beta}\right)}\right)^2
+\right)& \mbox{for } \beta > 0 \wedge \lambda > -3 \\
+\mbox{undefined} & \mbox{otherwise}
+\end{cases}
\end{align}
-\end{subequations}
-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\clearpage
@@ -458,6 +478,7 @@ \section{Weibull distribution}
\label{fig:Weibull}
\end{figure}
\begin{align}
+\label{eq:Weibull}
\text{Weibull}(R,\alpha,\lambda,\mu) =
\frac{N \lambda}{\alpha}
\left(\frac{R-\mu}{\alpha}\right)^{\lambda-1}
@@ -13,7 +13,7 @@
\item a first version of a plugin for ordered mesoscopic and nano structures.
The plugin is providing a part of the structure factors available
in the software package "scatter" from S. Förster.
- \item plugin of a radial profile for a sphere resulting in a Porod law both below and above Q^-4
+ \item plugin of a radial profile for a sphere resulting in a Porod law both below and above $Q^{-4}$ (\texttt{Boucher Sphere})
\end{itemize}
\item[2014-12-14] \SASfit 0.94.6
\begin{itemize}
@@ -764,8 +764,7 @@ \subsection{BoucherSphere, radial profile for a sphere resulting in a Porod law
\end{align}
By this normalisation the excess scattering length is for all $\alpha$ equal to the one of a homogeneous sphere with a scattering contrast $\Delta\eta$, i.e. $\beta_\mathrm{sp}=\Delta\eta \frac{4}{3}\pi R^3$.
-To get feeling which part of the spherical contributes most to the scattering ones can define
-a fractional relative excess scattering length according to \cite{Boucher1983} which reads as
+To get a feeling which part of the spherical scattering length density profile contributes most to the scattering it is convenient to define a fractional relative excess scattering length according to \cite{Boucher1983} which reads as
\begin{align}
Z(x) = & \frac{
\int_{0}^{x}\! \left( 1-{\frac {{r}^{2}}{{R}^{2}}} \right) ^{\frac{\alpha}{2}-2} 4\pi\,{r}^{2}\,{\rm d}r
@@ -798,7 +797,7 @@ \subsection{BoucherSphere, radial profile for a sphere resulting in a Porod law
&= \beta \left(\frac{2}{QR}\right)^{\frac{\alpha-1}{2}} J_{\frac{\alpha-1}{2}}(QR) \, \Gamma\left(\frac{\alpha+1}{2}\right) \nonumber \\
&= \beta \;_0F_1\left(\frac{\alpha+1}{2};-\tfrac{(QR)^2}{4}\right)
\end{align}
-making use of the fact that the bessel function can be expressed in terms of generalised hypergeometric functions $J_\alpha(x)=\frac{(\frac{x}{2})^\alpha}{\Gamma(\alpha+1)} \;_0F_1 (\alpha+1; -\tfrac{x^2}{4})$. The scattering amplitude simplifies in case of $\alpha=4$ exactly the one of a homogenous spherical shell and in case of $\alpha=2$ to an infinitesimal thin spherical shell. For the scattering intensity $I(Q) = F^2(Q)$ we get in the Porod limit $Q\rightarrow\infty$
+making use of the fact that the bessel function can be expressed in terms of generalised hypergeometric functions $J_\alpha(x)=\frac{(\frac{x}{2})^\alpha}{\Gamma(\alpha+1)} \;_0F_1 (\alpha+1; -\tfrac{x^2}{4})$. The scattering amplitude simplifies in case of $\alpha=4$ exactly the one of a homogenous sphere and in case of $\alpha=2$ to an infinitesimal thin spherical shell. For the scattering intensity $I(Q) = F^2(Q)$ we get in the Porod limit $Q\rightarrow\infty$
\BE
\lim_{Q\rightarrow\infty} I(Q)= \lim_{Q\rightarrow\infty} F^2(Q) =
\beta^2 \frac{2^{\alpha-1}}{\pi} \Gamma^2\left(\frac{\alpha+1}{2}\right) \frac{1}{(QR)^\alpha}
@@ -825,7 +824,7 @@ \subsection{BoucherSphere, radial profile for a sphere resulting in a Porod law
\begin{description}
\item[\texttt{R}] radius $R$
\item[\texttt{alpha}] shape parameter of the profile $\alpha$, which is also equal to the potential law at large $Q$-values
-\item[\texttt{Delta\_eta}] average scattering length density so that the excess scattering length corresponds to that one of a homogeneous sphere with contrast $\Delta\eta$
+\item[\texttt{Delta\_eta}] is the average scattering length density so that the excess scattering length corresponds to the one of a homogeneous sphere with contrast $\Delta\eta$
\end{description}
\noindent\underline{Note for model \texttt{BoucherSphere2} and \texttt{Boucher profile}:}
View
@@ -127,12 +127,6 @@ B~Boucher, P~Chieux, P~Convert, and M~Tournarie.
order in the amorphous metallic alloy tbcu 3.54.
\newblock {\em Journal of Physics F: Metal Physics}, 13(7):1339, 1983.
-\bibitem{burchard74}
-W.~Burchard.
-\newblock Statistics of star-shaped molecules. i. stars with polydisperse side
- chains.
-\newblock {\em Macromolecules}, 7:835--841, 1974.
-
\bibitem{Burchard1996}
W.~Burchard, E.~Michel, and V.~Trappe.
\newblock Conformational properties of multiply twisted ring systems and
View
@@ -4210,4 +4210,55 @@ @Article{Burchard1974
timestamp = {2016.04.20},
}
+@Article{Jakes1991,
+ author = {Jaromír Jakeš},
+ title = {A simple method of estimation of the polydispersity index of narrow molecular weight distributions by using quasielastic light scattering data},
+ year = {1991},
+ journal = {Collect. Czech. Chem. Commun.},
+ volume = {56},
+ issue = {8},
+ pages = {1642-1652},
+ doi = {http://dx.doi.org/10.1135/cccc19911642},
+ owner = {kohlbrecher},
+ timestamp = {2016.05.06},
+}
+
+@Article{Jakes1986,
+ author = {Jakeš, Jaromir and Saudek, Vladimir},
+ title = {Empirical molecular weight distribution functions as determined from gel permeation chromatography data},
+ year = {1986},
+ journal = {Makromol. Chem.},
+ volume = {187},
+ number = {9},
+ month = sep,
+ pages = {2223--2234},
+ issn = {0025-116X},
+ url = {http://dx.doi.org/10.1002/macp.1986.021870919},
+ abstract = {Two- and three-parameter functions commonly used for the description
+ of the molecular weight distribution of polymers were determined
+ from gel permeation chromatography data for 80 water-soluble samples
+ of polymers derived from glutamic acid. Two methods were applied:
+ the moment method in which two or three different molecular weight
+ averages are used, and a least squares adjustment method using the
+ whole chromatogram. Convergence difficulties observed in the past
+ were overcome, and a fully automated computer procedure was developed.
+ The moment method, although virtually the only one still in use,
+ often gives inexact results: sometimes the type of two-parameter
+ distribution is wrongly assigned, or the description of experimental
+ data cannot be improved by adding yet another parameter. On the other
+ hand, in all cases under study the least squares method gave a function
+ which describes the real distribution within the limits of experimental
+ error. Although the majority of samples could be described by employing
+ one of the common two-parameter functions, the more general three-parameter
+ function, encompassing all two-parameter ones as special cases, has
+ the advantage of wider applicability. It is shown that the standard
+ gel permeation chromatography data often cannot provide reliable
+ values of higher molecular weight moment averages, including Mz.
+ Hence, it may be inferred that in the description of the experimental
+ molecular weight distribution curves the least squares method should
+ be preferred over the moment method.},
+ owner = {kohlbrecher},
+ timestamp = {2016.05.06},
+}
+
@Comment{jabref-meta: databaseType:biblatex;}
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@@ -302,7 +302,7 @@ frame .openfile.layout2
frame .openfile.layout3
set format [tk_optionMenu .openfile.layout1.format tmpsasfit(actualdatatype) \
- Ascii BerSANS]
+ Ascii BerSANS ALV5000]
.openfile.layout1.format configure -highlightthickness 0
label .openfile.layout1.label -text "File Format:" -highlightthickness 0
pack .openfile.layout1.label .openfile.layout1.format -side left -fill x
@@ -785,13 +785,13 @@ set w .addfile.lay1
frame .addfile.layout3
set format [tk_optionMenu $w.layout1.format tmpsasfit(actualdatatype) \
- Ascii BerSANS]
+ Ascii BerSANS ALV5000]
$w.layout1.format configure -highlightthickness 0
label $w.layout1.label -text "File Format:" \
-width 12 -highlightthickness 0
button $w.layout1.option -text "Options..." -command ReadOptionsCmd \
-highlightthickness 0 -pady 1m
-button $w.layout1.read -text "Read File" \
+button $w.layout1.read -text "Read file" \
-command {
global tmpsasfit
set tmpfnlist $tmpsasfit(filename)
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