[script] solutions of exercises at end of chapters
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@ -191,3 +191,7 @@ Estimate the statistical significance of a correlation coefficient.
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coefficient computed from the original data.
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\end{enumerate}
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\end{exercise}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\printsolutions
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@ -46,7 +46,7 @@ watchchapter :
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cleanchapter : cleanpythonplots cleangnuplots
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rm -f *~
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rm -f $(BASENAME).aux $(BASENAME).log
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rm -f $(BASENAME)-chapter.aux $(BASENAME)-chapter.log $(BASENAME)-chapter.out $(BASENAME)-chapter.idx
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rm -f $(BASENAME)-chapter.aux $(BASENAME)-chapter.log $(BASENAME)-chapter.out $(BASENAME)-chapter.idx $(BASENAME)-chapter-solutions.tex
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cleanallchapter : cleanchapter
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@ -505,3 +505,6 @@ The debugger offers some more (advanced) features but the
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functionality offered by the basic tools is often enough to debug a
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program.
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%\printsolutions
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@ -168,3 +168,7 @@ x = randi(6, 100, 1); % Some integer-valued data.
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h = h/sum(h); % Normalize to probability.
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bar(b, h); % Plot the probabilities.
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\end{lstlisting}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%\printsolutions
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53
header.tex
53
header.tex
@ -285,7 +285,6 @@
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\usepackage{mdframed}
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\usepackage{xstring}
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\newlistof{exercisef}{loe}{\tr{Exercises}{\"Ubungen}}
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\newcommand{\codepath}{}
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\DeclareFloatingEnvironment[
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fileext=loe,
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name={\tr{Exercise}{\"Ubung}},
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@ -293,38 +292,44 @@
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chapterlistsgaps=on,
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]{exercisef}
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\newboolean{showexercisesolutions}
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\setboolean{showexercisesolutions}{false}
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\setboolean{showexercisesolutions}{true}
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\newwrite\solutions % file descriptor for writing solutions
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% we need to know the name of the included file as \currentjobname:
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\usepackage{xpatch}
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\makeatletter
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\def\currentjobname{\jobname}%
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\xpretocmd{\include}{\def\currentjobname{#1}\immediate\openout\solutions=\currentjobname-solutions}{}{}
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\makeatother
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\usepackage{needspace}
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\newenvironment{exercise}[2]%
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{ \newcommand{\exercisesource}{#1}%
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\newcommand{\exercisefile}{\protect\StrSubstitute{#1}{_}{\_}}%
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\newcommand{\exerciseoutput}{#2}%
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\setlength{\fboxsep}{2mm}%
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{ \setlength{\fboxsep}{2mm}%
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\newcommand{\saveenumi}{\theenumi}\renewcommand{\labelenumi}{(\alph{enumi})}%
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\captionsetup{singlelinecheck=off,hypcap=false,labelfont={large,sf,it,bf},%
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font={large,sf,it,bf},skip={0.5ex}}%
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\begin{mdframed}[linewidth=0pt,backgroundcolor=exerciseback]%
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\captionof{exercisef}[\exercisefile]{}%
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\captionof{exercisef}[\protect\StrSubstitute{#1}{_}{\_}]{}%
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\captionsetup{font={normal,sf,it}}%
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\subsection}[Exercise \thechapter.\arabic{exercisef}]%
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{\unexpanded{\needspace{4\baselineskip}}Exercise \thechapter.\arabic{exercisef}}}%
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nolol=true, title={\textbf{Source code:} \protect\StrSubstitute{#1}{_}{\_}}]}{#1}}%
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\ifthenelse{\equal{#2}{}}{}%
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{\immediate\write\solutions{\unexpanded{\lstinputlisting[language={},%
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nolol=true, title={\textbf{Output:}}, belowskip=0ex, aboveskip=1ex]}{#2}}}%
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\immediate\write\solutions{}%
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}%
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{ \renewcommand{\theenumi}{\saveenumi}%
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{ \addtocounter{lstlisting}{-1}%
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\lstinputlisting[belowskip=0pt,aboveskip=1ex,nolol=true,%
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title={\textbf{\tr{Solution}{L\"osung}:} \exercisefile}]%
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{\codepath\exercisesource}%
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\ifthenelse{\equal{\exerciseoutput}{}}{}%
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{ \addtocounter{lstlisting}{-1}%
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\lstinputlisting[language={},title={\textbf{\tr{Output}{Ausgabe}:}},%
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nolol=true,belowskip=0pt]%
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{\codepath\exerciseoutput}%
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}%
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}%
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\hypersetup{hypertexnames=true}%
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}{}%
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{ \ifthenelse{\boolean{showexercisesolutions}}%
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{\hspace*{\fill}\hyperref[solution\arabic{exercisef}]{Solution}}{}%
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\renewcommand{\theenumi}{\saveenumi}%
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\end{mdframed}%
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}
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}
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\newcommand{\printsolutions}{\immediate\closeout\solutions%
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\ifthenelse{\boolean{showexercisesolutions}}{%
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\clearpage\section{Solutions to the exercises}%
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\input{\currentjobname-solutions}}{}}
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\setlength{\cftexercisefindent}{1.2em}
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\setlength{\cftexercisefnumwidth}{2.6em}
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@ -362,3 +362,7 @@ activity pattern in the population $r_1$, $r_2$, ... $r_n$ is thus
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\[ {\cal L}(\phi|r_1, r_2, \ldots r_n) = \sum_{i=1}^n \log p_i(r_i|\phi) \]
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The angle $\phi$ that maximizes this likelihood is then an estimate of
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the orientation of the edge.
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\printsolutions
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@ -778,3 +778,7 @@ Key ingredients for a good data plot:
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thicker lines help.
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\item Error bars wherever they are appropriate.
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\end{itemize}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%\printsolutions
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@ -551,3 +551,7 @@ kernel.
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the same size as the original stimulus contained in file
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\file{sta\_data.mat}.
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\end{exercise}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\printsolutions
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@ -1,7 +1,7 @@
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%!PS-Adobe-2.0 EPSF-2.0
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@ -332,14 +329,9 @@ gnudict begin
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@ -428,7 +420,6 @@ Level1 {Level1PatternFill} {Level2PatternFill} ifelse
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@ -438,42 +429,14 @@ systemdict /pdfmark known not {
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@ -1,7 +1,7 @@
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Binary file not shown.
@ -1,5 +1,6 @@
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
\chapter{Programming in \matlab}\label{programming}
|
||||
\chapter{Programming in \matlab}
|
||||
\label{programming}
|
||||
|
||||
In this chapter we will cover the basics of programming in
|
||||
\matlab{}. Starting with the concept of simple variables and data
|
||||
@ -1768,3 +1769,7 @@ legend('show')
|
||||
duplication or it grows too large, it is high time to consider
|
||||
extracting features into separate functions.
|
||||
\end{ibox}
|
||||
|
||||
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
\printsolutions
|
||||
|
||||
@ -4,7 +4,6 @@
|
||||
more months might as well have been written by someone
|
||||
else.}{Eagleson's law}
|
||||
|
||||
%\selectlanguage{ngerman}
|
||||
Cultivating a good code style is not just a matter of good taste but
|
||||
rather is a key ingredient for readability and maintainability of code
|
||||
and, in the end, facilitates reproducibility of scientific
|
||||
@ -36,7 +35,7 @@ of the program but two questions remain: (i) How to organize the files
|
||||
on the file system and (ii) how to name them that the controlling
|
||||
script is easily identified among the other \codeterm{m-files}.
|
||||
|
||||
Upon installation ``MATLAB'' creates a folder called \file{MATLAB} in
|
||||
Upon installation \matlab{} creates a folder called \file{MATLAB} in
|
||||
the user space (Windows: My files, Linux: Documents, MacOS:
|
||||
Documents). Since this folder is already appended to the Matlab search
|
||||
path (Box~\ref{matlabpathbox}), it is easiest to stick to it for the
|
||||
@ -427,4 +426,5 @@ readability and comprehensibility pays off, even to the author!
|
||||
Johnson}
|
||||
|
||||
|
||||
\selectlanguage{english}
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
%\printsolutions
|
||||
|
||||
@ -1,6 +1,5 @@
|
||||
\chapter{\tr{Optimization and gradient descent}{Optimierung und Gradientenabstieg}}
|
||||
|
||||
% \selectlanguage{ngerman}
|
||||
To understand the behaviour of a given system sciences often probe the
|
||||
system with input signals and then try to explain the responses
|
||||
through a model. Typically the model has a few parameter that specify
|
||||
@ -356,7 +355,6 @@ large.
|
||||
iteration of the algorithm.} \label{gradientdescentfig}
|
||||
\end{figure}
|
||||
|
||||
\setboolean{showexercisesolutions}{false}
|
||||
\begin{exercise}{gradientDescent.m}{}
|
||||
Implement the gradient descent for the problem of the linear
|
||||
equation for the measured data in file \file{lin\_regression.mat}.
|
||||
@ -407,4 +405,6 @@ designed for optimizations in the least square error sense
|
||||
parameter increases complexity and is computationally expensive.
|
||||
\end{important}
|
||||
|
||||
\selectlanguage{english}
|
||||
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
\printsolutions
|
||||
|
||||
@ -368,7 +368,6 @@ Punkte in Abbildung \ref{gradientdescentfig} gro{\ss}.
|
||||
Optimierungsschritt an.} \label{gradientdescentfig}
|
||||
\end{figure}
|
||||
|
||||
\setboolean{showexercisesolutions}{false}
|
||||
\begin{exercise}{gradientDescent.m}{}
|
||||
Implementiere den Gradientenabstieg f\"ur das Problem der
|
||||
Parameteranpassung der linearen Geradengleichung an die Messdaten in
|
||||
|
||||
@ -67,7 +67,6 @@
|
||||
\lstset{inputpath=regression/code}
|
||||
\include{regression/lecture/regression}
|
||||
|
||||
\setboolean{showexercisesolutions}{false}
|
||||
\graphicspath{{likelihood/lecture/}{likelihood/lecture/figures/}}
|
||||
\lstset{inputpath=likelihood/code}
|
||||
\include{likelihood/lecture/likelihood}
|
||||
|
||||
@ -15,7 +15,7 @@ gausscdf = np.cumsum(gauss)*dx
|
||||
|
||||
# plot:
|
||||
plt.xkcd()
|
||||
fig = plt.figure( figsize=(6, 2.6) )
|
||||
fig = plt.figure( figsize=(6, 2.4) )
|
||||
ax = fig.add_subplot(1, 1, 1)
|
||||
ax.spines['right'].set_visible(False)
|
||||
ax.spines['top'].set_visible(False)
|
||||
|
||||
@ -500,3 +500,7 @@ insufficiently or not at all detected by the correlation coefficient
|
||||
coefficients close to zero. $\xi$ denote normally distributed
|
||||
random numbers.}
|
||||
\end{figure}
|
||||
|
||||
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
\printsolutions
|
||||
|
||||
Reference in New Issue
Block a user