diff --git a/docs/presentation2022/cache.pkl b/docs/presentation2022/cache.pkl
index 061fc4dcb97957a0b288a305632cd06858ed3b35..64ad91c84f59207afa2038e0f6d56910b25314e6 100644
Binary files a/docs/presentation2022/cache.pkl and b/docs/presentation2022/cache.pkl differ
diff --git a/docs/presentation2022/index.aux b/docs/presentation2022/index.aux
index 3dbfe028af878e33e552013122201b0d6e1af9ce..76779697301fac711bcf41357a21620467402aea 100644
--- a/docs/presentation2022/index.aux
+++ b/docs/presentation2022/index.aux
@@ -30,30 +30,40 @@
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\@writefile{nav}{\headcommand {\beamer@framepages {11}{11}}}
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\@writefile{nav}{\headcommand {\beamer@framepages {12}{12}}}
-\@writefile{nav}{\headcommand {\slideentry {0}{0}{13}{13/13}{}{0}}}
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\@writefile{nav}{\headcommand {\beamer@framepages {13}{13}}}
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+\@writefile{nav}{\headcommand {\gdef \inserttotalframenumber {18}}}
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diff --git a/docs/presentation2022/index.fdb_latexmk b/docs/presentation2022/index.fdb_latexmk
index 13ccf3cf768e8600c2a801b41282cd24102cea95..b1231764ebf775556d2f596bdda21a9fac2e602c 100644
--- a/docs/presentation2022/index.fdb_latexmk
+++ b/docs/presentation2022/index.fdb_latexmk
@@ -1,12 +1,14 @@
# Fdb version 3
-["pdflatex"] 1664187002 "index.tex" "index.pdf" "index" 1664187004
- "/dev/null" 1663937585 0 d41d8cd98f00b204e9800998ecf8427e ""
+["pdflatex"] 1667744725 "index.tex" "index.pdf" "index" 1667744727
+ "/dev/null" 1667731454 0 d41d8cd98f00b204e9800998ecf8427e ""
"/etc/texmf/web2c/texmf.cnf" 1661854897 475 c0e671620eb5563b2130f56340a5fde8 ""
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"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam10.tfm" 1246382020 916 f87d7c45f9c908e672703b83b72241a3 ""
+ "/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam5.tfm" 1246382020 924 9904cf1d39e9767e7a3622f2a125a565 ""
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam7.tfm" 1246382020 928 2dc8d444221b7a635bb58038579b861a ""
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm10.tfm" 1246382020 908 2921f8a10601f252058503cc6570e581 ""
+ "/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm5.tfm" 1246382020 940 75ac932a52f80982a9f8ea75d03a34cf ""
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm7.tfm" 1246382020 940 228d6584342e91276bf566bcf9716b83 ""
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"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmss10.tfm" 1136768653 1316 b636689f1933f24d1294acdf6041daaa ""
@@ -261,51 +263,76 @@
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"/usr/share/texmf/fonts/tfm/public/lm/rm-lmr10.tfm" 1254938640 11868 4f81e9b6033c032bdaf9884f4d7ef412 ""
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+ "dtucolours.tex" 1667744718 5683 ab2862d4c2b577922d042e90ebfdfadd ""
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+ "index.nav" 1667744727 2475 eef69288f09c5d6b3bf11c99649a2e79 "pdflatex"
+ "index.out" 1667744727 78 911585e410f14b893368b64f14952c2e "pdflatex"
+ "index.tex" 1667744713 9326 2a5658bdc2f2e1306df0705cfd18260f ""
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+ "tex_dtu_compute_a_uk.pdf" 1667744718 13504 7ae3ecb9b649001643f902e32d3a8cca ""
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"index.aux"
"index.log"
diff --git a/docs/presentation2022/index.fls b/docs/presentation2022/index.fls
index 49f37bdb41bdc300fe403d0b58fd23394592f79f..d9fa92590b77ab4ee55ea3002de0354d6896caef 100644
--- a/docs/presentation2022/index.fls
+++ b/docs/presentation2022/index.fls
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+INPUT /usr/share/texmf/fonts/tfm/public/lm/rm-lmr7.tfm
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INPUT /usr/share/texmf/tex/latex/lm/omllmm.fd
INPUT /usr/share/texmf/tex/latex/lm/omllmm.fd
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-INPUT /usr/share/texmf/fonts/tfm/public/lm/lmmi8.tfm
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+INPUT /usr/share/texmf/fonts/tfm/public/lm/lmmi7.tfm
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INPUT /usr/share/texmf/tex/latex/lm/omslmsy.fd
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+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
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+INPUT tex_dtu_logo.pdf
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+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
OUTPUT index.nav
OUTPUT index.toc
OUTPUT index.snm
@@ -1876,7 +2029,12 @@ INPUT index.aux
INPUT ./index.out
INPUT ./index.out
INPUT /usr/share/texmf/fonts/enc/dvips/lm/lm-ec.enc
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diff --git a/docs/presentation2022/index.nav b/docs/presentation2022/index.nav
index 00c131b28c95e06d4851a04dc84ad09af6bd95a3..a3be917ccc4053c525e0872d3ef98ef09cf26c91 100644
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+++ b/docs/presentation2022/index.nav
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diff --git a/docs/presentation2022/index.out b/docs/presentation2022/index.out
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..85cf4c60697078c98cf75de90f0e5a29f60f8d45 100644
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+++ b/docs/presentation2022/index.out
@@ -0,0 +1 @@
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diff --git a/docs/presentation2022/index.synctex.gz b/docs/presentation2022/index.synctex.gz
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diff --git a/docs/presentation2022/index.tex b/docs/presentation2022/index.tex
index 024effd9a59ba5c695f0ac82e42b7d84c15f41e2..5fc7c0c5e771d7004dbae31e36714e77a42ce363 100644
--- a/docs/presentation2022/index.tex
+++ b/docs/presentation2022/index.tex
@@ -4,20 +4,56 @@
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\newtoggle{overlabel_includelabels}
\toggletrue{overlabel_includesvgs}
-\toggletrue{overlabel_includelabels}
+%\toggletrue{overlabel_includelabels}
\input{beamer_slider_preamble.tex}
-\title{Example slide show}
-\author{Author}
-\date{April 1st, 2022}
+\title{Two alternative takes on autograding}
+\author{Tue Herlau}
+\date{\today}
\begin{document}
\begin{frame}
\maketitle
\end{frame}
+
+
+\begin{frame}
+\frametitle{Summary}
+\begin{description}
+ \item[Unitgrade:] Autograding solution used in 02465:
+ \begin{itemize}
+ \item Shallow extension of unittests
+ \item Student experience
+ \item Requires less work to set up than codejudge
+ \begin{itemize}
+ \item Vedranas exam from introduction to programming
+ \item Alcestes exam from the CPP course and exercise 6
+ \end{itemize}
+ \end{itemize}
+\item[CMU Autolab:] Platform used at CMU and many other universities
+\begin{itemize}
+ \item Functions like a container for tests
+ \item Fully text-configured
+\end{itemize}
+\end{description}
+\vspace{1cm}
+\begin{itemize}
+ \item \url{https://gitlab.compute.dtu.dk/tuhe/unitgrade}
+ \begin{itemize}
+ \item Videos: \url{https://youtu.be/jC9AzZA5FcQ}
+ \end{itemize}
+ \item \url{https://autolabproject.com/}
+\end{itemize}
+\end{frame}
+
+\begin{frame}\osvg{start}
+ \frametitle{Unitgrade: what got me started}
+
+\end{frame}
+
% This slideshow is made using slider. Install using: pip install beamer-slider
% check http://gitlab.compute.dtu.dk/tuhe/slider for more information.
\begin{frame}%\osvg{myoverlay} % Use the \osvg{labelname} - tag to create new overlays. Run the command `slider` in the terminal and check the ./osvgs directory for the svg files!
-\frametitle{Observations about online autograders}
+\frametitle{Online autograders}
\begin{itemize}
\item They do many things
\begin{itemize}
@@ -31,11 +67,6 @@
\item Various forms of automation/ideas about organizing exercises
\item A test system
\end{itemize}
-\item I find them hard to use
-\begin{itemize}
- \item First you parse these 5 numbers from stdin...
- \item Blackbox
-\end{itemize}
\end{itemize}
\end{frame}
%\begin{frame}
@@ -44,210 +75,235 @@
%\end{frame}
\begin{frame}
\frametitle{My goals}
-\begin{itemize}
-\item \redt{Best} allow students to find errors and solve their programming problems
-\item Make the course \redt{software} and \redt{written material} easily maintainable in anticipation of future changes
-\begin{itemize}
- \item Write things in one place
- \item Update concurrently
- \item Make sure things don't break
-\end{itemize}
+\begin{description}
+\item[User experience:] \greent{Best} allow students to solve their programming problems
+\item[Administrative ease:] Make the course \greent{software}, \greent{tests}, and \greent{written material} easy to write and maintain
+%\begin{itemize}
+% \item Fast development
+% \item Write things in one place
+% \item Avoid (or detect) breaking changes
+% \item (should still support autograding)
+%\end{itemize}
%\item In this presentation: Inspiration; I am fully aware I did not solve everything.
-\end{itemize}
-\end{frame}
-\begin{frame}
- \frametitle{Example: Problem 1 from the intro to python course}
- \begin{itemize}
- \item Show install: Git pull repository, pip install unitgrade
- \item Show files. Do simplest example first: Unittest (explicit) and problem script. Use the water height problem for this. Include various hints. Show the exercise description pdf.
- \item Then show the grade file. Explain this is how they evaluate their homework.
- \item Then show the unitgrade interface.
- \end{itemize}
+\end{description}
\end{frame}
+
+
\begin{frame}
- \frametitle{Best test system for students}
-\begin{itemize}
- \item Which test system best allows students to fix problems in their homework?
- \item Which test system best allow \redt{me} to fix problems in \redt{my code}
- \item Web-based tests
+ \frametitle{User experience}
\begin{itemize}
- \item No debugger
- \item Local/remote code (upload or edit in bad online IDE)
- \item Increased run-time (can tests be run in isolation?)
- \item Blackboxing (environment, packages, file locations, how code is called)
+ \item Which test system best allows \redt{students} to fix problems in \redt{their} homework? \pause
+ \item Which test system best allow \redt{me} to fix problems in \redt{my code}? \pause
+ \item \redt{Web-based tests}
\begin{itemize}
- \item Drivers
- \item Preprocessors
- \item Postprocessors
- \item Hacks (\textrm{cat}, \textrm{fix-floats}, etc.)
- \end{itemize}
- \item Tendency of tests to adopt conventions from the tool (is reading from stdin really something we do?)
- \end{itemize}
-\item Unittests
-\begin{itemize}
- \item Debugger
- \item Favorite IDE+autocomplete
- \item Plugins to all IDEs
- \item Student learns relevant skills (unittesting)
- \item Test runable in isolation
- \item Transparency; everything is python
- \item Speed
- \item Everything can be unittested
-\end{itemize}
-\end{itemize}
+ \item No debugger
+ \item Local/remote code (or use the bad online IDE)
+ \item Increased run-time (can tests be run in isolation?)
+ \item Blackboxing (environment, packages, file locations, how code is called)
+ \begin{itemize} % 548826
+ \item Drivers
+ \item Preprocessors
+ \item Postprocessors
+ \item Hacks (\textrm{cat}, \textrm{fix-floats}, etc.)
+ \end{itemize}
+ \item Adopt conventions from the tool (is reading from stdin optimal?)
+ \end{itemize} \pause
+ \item \redt{Unittests:}
+ \begin{itemize}
+ \item Best-practice for 25 years
+ \item Use your favorite IDE: Debugger + autocomplete + inline documentation
+ \item Test are runable in isolation
+ \item Transparency; everything is python
+ \item Everything can be unittested
+ \item Student learns relevant skills (unittesting)
+ \end{itemize}
+ \end{itemize}
\end{frame}
-\begin{frame}
- \frametitle{Casestudy: 02465}
- \begin{itemize}
- \item 13 exercise + 3 projects (3 group + individual)
- \item Fairly involved code (many dependencies)
- \item
- \end{itemize}
+
+\begin{frame}\osvg{intropython}
+\frametitle{Example: Intro to python exam}
+Setup: \texttt{pip install unitgrade}
+\vspace{8cm}
+\end{frame}
+
+
+\begin{frame}\osvg{intropython}
+ \frametitle{Example: Writing your own test}
+% Setup: \texttt{pip install unitgrade}
+% \vspace{8cm}
\end{frame}
+
\begin{frame}
\frametitle{Casestudy: Introduction to python (Vedrana)}
- \begin{itemize}
- \item Exam set with 4 problems (Python). Showcase automatic generation of test answers.
- \end{itemize}
-\begin{columns}
-\begin{column}{.5\linewidth}
-Codejudge
-\begin{itemize}
- \item 5 problems
- \item 11 tests per problem
- \item 60 files
- \item 282 lines of code
-\end{itemize}
- \end{column}
-\begin{column}{.5\linewidth}
-Unitgrade
-\begin{itemize}
- \item 5 problems
- \item 11 tests per problem
- \item 3 files
- \item n lines of code
-\end{itemize}
-Bonus: My version contains a handout stub for students to work with.
-\end{column}
-\end{columns}
+ \begin{columns}\begin{column}{.5\linewidth}\redt{ Codejudge}\end{column}
+ \begin{column}{.5\linewidth}\redt{ Unitgrade }\end{column}\end{columns}
+
+ \begin{columns}
+ \begin{column}{.5\linewidth}
+ \begin{itemize}
+ \item 5 problems
+ \item 11 tests per problem
+ \item 60 files
+ \item 282 lines of code
+ \end{itemize}
+ \end{column}
+ \begin{column}{.5\linewidth}
+
+ \begin{itemize}
+ \item 5 problems
+ \item 11 tests per problem
+ \item 3 files
+ \item 127 lines of code
+ \end{itemize}
+ Bonus: My version contains a handout stub for students to work with.
+ \end{column}
+ \end{columns}
\end{frame}
+\begin{frame} \osvg{grading}
+ \frametitle{Casestudy: Introduction to python (grading)}
+
+\end{frame}
+
+%\begin{frame}
+% \frametitle{Example 2: Writing an exam problem}
+% \begin{itemize}
+% \item The problem is about how to write a class representing a fraction
+% \item Must support addition and multiplication, plus import from string
+% \end{itemize}
+%\end{frame}
+%
+%\begin{frame}
+% \frametitle{Example 3: Grading and hidden tests}
+% \begin{itemize}
+% \item The problem is about how to write a class representing a fraction
+% \item Must support addition and multiplication, plus import from string
+% \end{itemize}
+%\end{frame}
+%
+%
+%
+%\begin{frame}
+% \frametitle{Casestudy: 02465}
+% \begin{itemize}
+% \item 13 exercise + 3 projects (3 group + individual)
+% \item Fairly involved code (many dependencies)
+% \item
+% \end{itemize}
+%\end{frame}
+\begin{frame} \osvg{ac1}
+ \frametitle{Casestudy: Problem set 6 (Alceste)}
+Class representing fractions
+\end{frame}
\begin{frame}
-\frametitle{Casestudy: Problem set 6}
+\frametitle{Casestudy: Problem set 6 (Alceste)}
+
\begin{itemize}
\item Problem set 6, create a Fraction class with addition
\end{itemize}
-
+ \begin{columns}\begin{column}{.5\linewidth}\redt{ Codejudge}\end{column}
+ \begin{column}{.5\linewidth}\redt{ Unitgrade }\end{column}\end{columns}
\begin{columns}
\begin{column}{.5\linewidth}
- Codejudge
\begin{itemize}
\item 1 problem
\item 8 files (.in, .ans)
\item 2 tests
- \item 12 lines of code (input, output; but more code in LaTeX)
+ \item 12 lines of code (only specifies input \& output; contains more code in LaTeX)
\end{itemize}
\end{column}
\begin{column}{.5\linewidth}
- Unitgrade
\begin{itemize}
\item 1 problems
\item 2 files
\item 6 tests
\item 86 lines of code
\end{itemize}
- Bonus: My version contains more specific tests, generates handout files, contains a solution, and allows automatic checks of implementation for later refactoring.
+ Bonus: Contains more specific tests, generates handout files, contains a solution, and allows automatic checks of implementation for later refactoring.
\end{column}
\end{columns}
+\end{frame}
+\begin{frame} \osvg{ac2}
+ \frametitle{Features: Automation}
+
\end{frame}
\begin{frame}
- \frametitle{Casestudy: Exam set 2021}
+ \frametitle{Casestudy: Exam in C++ Course 2021}
\begin{itemize}
\item Exam set for 2021
+ \item 4 problems
\end{itemize}
+\vspace{1cm}
\begin{columns}
\begin{column}{.5\linewidth}
- Codejudge
+ \redt{ Codejudge}
\begin{itemize}
- \item 4 problems
\item 72 files (!)
- \item 16 .yml files
- \item 18 .ans files
- \item N tests
+ \item 16 .yml files
+ \item 18 .ans files
\item 552 lines of code (excluding .ans files)
\end{itemize}
\end{column}
\begin{column}{.5\linewidth}
- Unitgrade
+ \redt{Unitgrade}
\begin{itemize}
- \item 4 problems
- \item 6 files (4 problems + 1 test + 1 deploy)
- \item N tests
+ \item 6 files (4 problems + 1 test + 1 deploy)
\item 116 lines of code
+ \item More tests
\end{itemize}
-Bonus: Automatic checks.
+%Bonus: Automatic checks.
\end{column}
\end{columns}
\end{frame}
+\section{Autolab}
+\begin{frame} \osvg{autolab1}
+\frametitle{CMU Autolab}
+
+
-\begin{frame}
-\frametitle{Unittests}
-\begin{itemize}
-\item asdf
-\end{itemize}
\end{frame}
-\begin{frame}
-\frametitle{Developing tests}
+
+\begin{frame} \osvg{autolab2}
+\frametitle{CMU Autolab}
\begin{itemize}
-\item Add a report class + deploy script and it works.
-\item Security and evaluation: Docker + scripts (Download from learn, evaluate/run automatic)
-\item Support hidden tests
+\item Classic autograder: Students, classes, assignments.
+\item Sign-up can be handled using student email (confirmation emails)
\end{itemize}
+\vspace{6cm}
\end{frame}
-\begin{frame}
+
+\begin{frame}\osvg{autolab3}
\frametitle{Test development}
\begin{itemize}
-\item No-configuration files approach
-\item Don't duplicate information
+\item An assignment is a single .tar file:
+\item tl;dr:
+\begin{itemize}
+ \item The container will copy your autograder files the students into the same directory
+\item Then it calls \texttt{autograde\_Makefile}
+\item You return json with the scores to stdout
+\end{itemize}
+\item Easy to call e.g. a unittest script
+\item Tests can be run locally
+\item Many examples online
\end{itemize}
\end{frame}
-\begin{frame}
-\frametitle{Test development}
+\begin{frame}\osvg{autolab4}
+\frametitle{Easy to automate}
\begin{itemize}
-\item No-configuration files approach
-\item Don't duplicate information
+ \item Unitgrade allows one-line deployment to an autolab \texttt{.tar} file for upload
\end{itemize}
-\end{frame}
-
-
-\begin{frame}
- \frametitle{Test development}
- \begin{itemize}
- \item No-configuration files approach
- \item Don't duplicate information
- \end{itemize}
-\end{frame}
-
-\begin{frame}
- * I think it is important to introduce simplest method first: Test and evaluation. Perhaps use the homework as an example?
- * you could also use the python course as an example (one problem).
- * Admin; grading. Setup automatically and evaluate.
- * Show automatic evaluation directly. print to excel file and .pkl. show autograding. show hidden tests. Show plagiarism checks with moss. Show failed evaluation+log+fix.
-
-
-Points of the examples: (seperate?)
- *
+\vspace{6cm}
\end{frame}
diff --git a/docs/presentation2022/index.toc b/docs/presentation2022/index.toc
index 9fbdd18a8c9adf55ec0285e8532d13207dc20bf7..6f17b2423c8c8c8c2702290a04a83c5f4f617d1e 100644
--- a/docs/presentation2022/index.toc
+++ b/docs/presentation2022/index.toc
@@ -1 +1,2 @@
\babel@toc {english}{}\relax
+\beamer@sectionintoc {1}{Autolab}{18}{0}{1}
diff --git a/docs/presentation2022/osvgs/ac1.svg b/docs/presentation2022/osvgs/ac1.svg
new file mode 100644
index 0000000000000000000000000000000000000000..cc1874771e75ffd5d12ff9e640e658ce8ea64595
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diff --git a/docs/presentation2022/osvgs/intropython.svg b/docs/presentation2022/osvgs/intropython.svg
new file mode 100644
index 0000000000000000000000000000000000000000..cb64179539987ba22063f1c0648f758366ecccf3
--- /dev/null
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+ xml:space="preserve"
+ style="font-style:normal;font-weight:normal;font-size:10.5702px;line-height:1.25;font-family:sans-serif;fill:#800000;fill-opacity:1;stroke:none;stroke-width:0.264255"
+ x="164.04022"
+ y="270.35043"
+ id="text3247"
+ transform="rotate(-12.451877)"><tspan
+ sodipodi:role="line"
+ id="tspan3245"
+ style="font-style:normal;font-variant:normal;font-weight:bold;font-stretch:normal;font-family:sans-serif;-inkscape-font-specification:'sans-serif Bold';stroke-width:0.264255;fill:#800000"
+ x="164.04022"
+ y="270.35043">10 years in python</tspan><tspan
+ sodipodi:role="line"
+ style="font-style:normal;font-variant:normal;font-weight:bold;font-stretch:normal;font-family:sans-serif;-inkscape-font-specification:'sans-serif Bold';stroke-width:0.264255;fill:#800000"
+ x="164.04022"
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+ id="tspan3249">and this is the first time </tspan><tspan
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+ style="font-style:normal;font-variant:normal;font-weight:bold;font-stretch:normal;font-family:sans-serif;-inkscape-font-specification:'sans-serif Bold';stroke-width:0.264255;fill:#800000"
+ x="164.04022"
+ y="296.77594"
+ id="tspan3251">i use sys.stdin</tspan></text>
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\gdef\svg@ink@ver@settings{{\m@ne }{inkscape}{1}}
-\gdef \@abspage@last{2}
+\gdef \@abspage@last{23}
diff --git a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.fdb_latexmk b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.fdb_latexmk
index 7d61dd258e3e19012bf59d7714f1ac961c4d44c1..38bfc7da52dbf166650be41c7fce6bad7a1eb1a5 100644
--- a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.fdb_latexmk
+++ b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.fdb_latexmk
@@ -1,12 +1,14 @@
# Fdb version 3
-["pdflatex"] 1664186997 "index_NO_SVGS.tex" "index_NO_SVGS.pdf" "index_NO_SVGS" 1664186999
- "/dev/null" 1663937585 0 d41d8cd98f00b204e9800998ecf8427e ""
+["pdflatex"] 1667744721 "index_NO_SVGS.tex" "index_NO_SVGS.pdf" "index_NO_SVGS" 1667744723
+ "/dev/null" 1667731454 0 d41d8cd98f00b204e9800998ecf8427e ""
"/etc/texmf/web2c/texmf.cnf" 1661854897 475 c0e671620eb5563b2130f56340a5fde8 ""
"/usr/share/texlive/texmf-dist/fonts/map/fontname/texfonts.map" 1577235249 3524 cb3e574dea2d1052e39280babc910dc8 ""
"/usr/share/texlive/texmf-dist/fonts/tfm/jknappen/ec/ecss1095.tfm" 1136768653 3584 8ece407347b270c252c46fdfaef5a9ef ""
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam10.tfm" 1246382020 916 f87d7c45f9c908e672703b83b72241a3 ""
+ "/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam5.tfm" 1246382020 924 9904cf1d39e9767e7a3622f2a125a565 ""
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam7.tfm" 1246382020 928 2dc8d444221b7a635bb58038579b861a ""
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm10.tfm" 1246382020 908 2921f8a10601f252058503cc6570e581 ""
+ "/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm5.tfm" 1246382020 940 75ac932a52f80982a9f8ea75d03a34cf ""
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm7.tfm" 1246382020 940 228d6584342e91276bf566bcf9716b83 ""
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr10.tfm" 1136768653 1296 45809c5a464d5f32c8f98ba97c1bb47f ""
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmss10.tfm" 1136768653 1316 b636689f1933f24d1294acdf6041daaa ""
@@ -261,50 +263,67 @@
"/usr/share/texlive/texmf-dist/tex/latex/xkeyval/xkeyval.sty" 1605910342 4902 efb3d66683a2da2a232f71e3a571a899 ""
"/usr/share/texlive/texmf-dist/web2c/texmf.cnf" 1644012257 39432 7155514e09a3d69036fac785183a21c2 ""
"/usr/share/texmf/fonts/enc/dvips/lm/lm-ec.enc" 1254938640 2375 baa924870cfb487815765f9094cf3728 ""
+ "/usr/share/texmf/fonts/enc/dvips/lm/lm-mathsy.enc" 1254938640 2840 216e6e45ad352e2456e1149f28885bee ""
+ "/usr/share/texmf/fonts/tfm/public/lm/ec-lmr9.tfm" 1254938640 12084 b7f5e4c003de6f57f07c7e9fee73a37c ""
"/usr/share/texmf/fonts/tfm/public/lm/ec-lmss10.tfm" 1254938640 11176 53ebf7a171df1f9447b387b178768bb5 ""
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"/usr/share/texmf/fonts/tfm/public/lm/ec-lmss8.tfm" 1254938640 11180 705632ac6b4fb69204ad970192cdf4e5 ""
+ "/usr/share/texmf/fonts/tfm/public/lm/ec-lmss9.tfm" 1254938640 11204 6ae1acdb5c7b9e57dc25853230e3cdae ""
"/usr/share/texmf/fonts/tfm/public/lm/ec-lmssbx10.tfm" 1254938640 11168 06d87f5698fd1b642d96449b7c8d90b0 ""
"/usr/share/texmf/fonts/tfm/public/lm/ec-lmtt10.tfm" 1254938640 1372 2ef2c2b492b3c4cd7879fe083abbb061 ""
"/usr/share/texmf/fonts/tfm/public/lm/lmex10.tfm" 1254938640 992 ce925c9346c7613270a79afbee98c070 ""
"/usr/share/texmf/fonts/tfm/public/lm/lmmi10.tfm" 1254938640 1528 6d36b2385e0ca062a654de6ac59cb34f ""
+ "/usr/share/texmf/fonts/tfm/public/lm/lmmi5.tfm" 1254938640 1508 198f5b7b99b5769126de3a533f6fc334 ""
"/usr/share/texmf/fonts/tfm/public/lm/lmmi6.tfm" 1254938640 1512 94a3fd88c6f27dbd9ecb46987e297a4e ""
+ "/usr/share/texmf/fonts/tfm/public/lm/lmmi7.tfm" 1254938640 1528 d5b028dd23da623848ef0645c96a1ed7 ""
"/usr/share/texmf/fonts/tfm/public/lm/lmmi8.tfm" 1254938640 1520 a3fe5596932db2db2cbda300920dd4e9 ""
+ "/usr/share/texmf/fonts/tfm/public/lm/lmmi9.tfm" 1254938640 1524 cdf05765c2a8bdb569ea0aa208fb0947 ""
"/usr/share/texmf/fonts/tfm/public/lm/lmsy10.tfm" 1254938640 1308 02cc510f9dd6012e5815d0c0ffbf6869 ""
+ "/usr/share/texmf/fonts/tfm/public/lm/lmsy5.tfm" 1254938640 1296 54ed1a711e2303d5282575278e3620b0 ""
"/usr/share/texmf/fonts/tfm/public/lm/lmsy6.tfm" 1254938640 1300 b0605d44c16c22d99dc001808e4f24ea ""
+ "/usr/share/texmf/fonts/tfm/public/lm/lmsy7.tfm" 1254938640 1304 32f22a15acc296b2a4e15698403dcb88 ""
"/usr/share/texmf/fonts/tfm/public/lm/lmsy8.tfm" 1254938640 1304 cdc9a17df9ef0d2dc320eff37bbab1c4 ""
+ "/usr/share/texmf/fonts/tfm/public/lm/lmsy9.tfm" 1254938640 1300 ca37bc0213808d24f74bf4d32f81f80d ""
"/usr/share/texmf/fonts/tfm/public/lm/rm-lmr10.tfm" 1254938640 11868 4f81e9b6033c032bdaf9884f4d7ef412 ""
+ "/usr/share/texmf/fonts/tfm/public/lm/rm-lmr5.tfm" 1254938640 11804 aefb10c002e6492c25236524a447f969 ""
"/usr/share/texmf/fonts/tfm/public/lm/rm-lmr6.tfm" 1254938640 11836 e3b6ce3e601aec94f64a536e7f4224d5 ""
+ "/usr/share/texmf/fonts/tfm/public/lm/rm-lmr7.tfm" 1254938640 11852 5a9022f105fd1ee2797df861e79ae9a0 ""
"/usr/share/texmf/fonts/tfm/public/lm/rm-lmr8.tfm" 1254938640 11864 309fd7f43e4a0ba39f6f7644d76e8edf ""
+ "/usr/share/texmf/fonts/tfm/public/lm/rm-lmr9.tfm" 1254938640 11884 c93929a6974dce79eabb778f219d7e18 ""
+ "/usr/share/texmf/fonts/type1/public/lm/lmr9.pfb" 1254938640 121065 50bbfa703ce7e11638752ef5a6d120c7 ""
"/usr/share/texmf/fonts/type1/public/lm/lmss10.pfb" 1254938640 97408 f595704ec2a07246c2d6f7b602587452 ""
"/usr/share/texmf/fonts/type1/public/lm/lmss8.pfb" 1254938640 94400 e33ecfb646a9f148e2e53da01a9168fe ""
+ "/usr/share/texmf/fonts/type1/public/lm/lmss9.pfb" 1254938640 95954 039cb8d6009e8fc5ea194e3e167ecc5f ""
"/usr/share/texmf/fonts/type1/public/lm/lmssbx10.pfb" 1254938640 119663 e82fa1a58f98ccd89bdbd77311ac9cf1 ""
+ "/usr/share/texmf/fonts/type1/public/lm/lmsy10.pfb" 1254938640 27863 09ce3735688ffde955e72da27c95b61a ""
+ "/usr/share/texmf/fonts/type1/public/lm/lmsy9.pfb" 1254938640 27835 16c2fa83351d4ef8cf5aebfab8a44bc1 ""
"/usr/share/texmf/fonts/type1/public/lm/lmtt10.pfb" 1254938640 113227 1010e11451afc2822c95dae77c390042 ""
"/usr/share/texmf/tex/latex/lm/lmodern.sty" 1256929440 1606 c17281c7cff2bbd7ff0173e1433487ec ""
"/usr/share/texmf/tex/latex/lm/omllmm.fd" 1256929440 888 44447a3a3af84a22454ef89500942d93 ""
"/usr/share/texmf/tex/latex/lm/omslmsy.fd" 1256929440 805 af340a8260c447aa315cfc740ff0152f ""
"/usr/share/texmf/tex/latex/lm/omxlmex.fd" 1256929440 566 a94661f7b66063f191960bb7935b6ba2 ""
"/usr/share/texmf/tex/latex/lm/ot1lmr.fd" 1256929440 1880 bae7b659316f7344a86218ad38b01d91 ""
+ "/usr/share/texmf/tex/latex/lm/t1lmr.fd" 1256929440 1865 afbfccbe7fda9c2dc5078ad7c486bbed ""
"/usr/share/texmf/tex/latex/lm/t1lmss.fd" 1256929440 1639 ba1c66ef577aa5cadc2c0fdc691a26ee ""
"/usr/share/texmf/tex/latex/lm/t1lmtt.fd" 1256929440 2681 354015af3b61e7be30009f084986375a ""
"/usr/share/texmf/web2c/texmf.cnf" 1644012257 39432 7155514e09a3d69036fac785183a21c2 ""
"/var/lib/texmf/fonts/map/pdftex/updmap/pdftex.map" 1661855397 4076253 38befb6d6b6e65b49c50e6f58e595c43 ""
"/var/lib/texmf/web2c/pdftex/pdflatex.fmt" 1661855409 1511258 48b331477fc99ed5ad6f4a5dd0889b17 ""
- "beamer_slider_preamble.tex" 1664186994 2728 dd84392bcc98cbdc080fd45d3291136a ""
- "beamercolorthemeDTU.sty" 1664186994 1181 7ab9734d3304a1004f2d9e1737bd3023 ""
- "beamerfontthemeDTU.sty" 1664186994 1259 711cf5a5686863499f78b39f42a55f2a ""
- "beamerinnerthemeDTU.sty" 1664186994 1413 443050b5e9bf0131334a4dd368ae135d ""
- "beamerouterthemeDTU.sty" 1664186994 2587 ef6b483247d69fb58cb5fae2db9f1840 ""
- "beamerthemeDTU.sty" 1664186994 7254 017a52b2de7ff8eb9becb7a433e0dca2 ""
- "departments.tex" 1664186994 9638 46ca44325622949c043b61db8bfa9b5e ""
- "dtucolours.tex" 1664186994 5683 ab2862d4c2b577922d042e90ebfdfadd ""
- "index_NO_SVGS.aux" 1664186999 1412 2d0a9582e28c65e3f8629db6ea0ea185 "pdflatex"
- "index_NO_SVGS.nav" 1664186999 395 640a03f4d3f0f705896c1d8375ddfa75 "pdflatex"
- "index_NO_SVGS.out" 1664186998 0 d41d8cd98f00b204e9800998ecf8427e "pdflatex"
- "index_NO_SVGS.tex" 1664186994 866 3d0378f228ccca1ee114e2d0d47816c2 ""
- "tex_dtu_compute_a_uk.pdf" 1664186994 13504 7ae3ecb9b649001643f902e32d3a8cca ""
- "tex_dtu_frise.pdf" 1664186994 32488 57c0f48ec5395d976ac1e57718922c22 ""
- "tex_dtu_logo.pdf" 1664186994 1830 e452da49133969a7656f3882c11e9b04 ""
+ "beamer_slider_preamble.tex" 1667744718 2728 dd84392bcc98cbdc080fd45d3291136a ""
+ "beamercolorthemeDTU.sty" 1667744718 1181 7ab9734d3304a1004f2d9e1737bd3023 ""
+ "beamerfontthemeDTU.sty" 1667744718 1259 711cf5a5686863499f78b39f42a55f2a ""
+ "beamerinnerthemeDTU.sty" 1667744718 1413 443050b5e9bf0131334a4dd368ae135d ""
+ "beamerouterthemeDTU.sty" 1667744718 2587 ef6b483247d69fb58cb5fae2db9f1840 ""
+ "beamerthemeDTU.sty" 1667744718 7254 017a52b2de7ff8eb9becb7a433e0dca2 ""
+ "departments.tex" 1667744718 9638 46ca44325622949c043b61db8bfa9b5e ""
+ "dtucolours.tex" 1667744718 5683 ab2862d4c2b577922d042e90ebfdfadd ""
+ "index_NO_SVGS.aux" 1667744723 4353 d1b46c1a8aa7d2323065a04a1328bd2f "pdflatex"
+ "index_NO_SVGS.nav" 1667744723 2463 04fa624daef0af6ae993e90801282c7e "pdflatex"
+ "index_NO_SVGS.out" 1667744723 78 911585e410f14b893368b64f14952c2e "pdflatex"
+ "index_NO_SVGS.tex" 1667744718 9409 ddb83dd0af32e4a5d0fd63cd7717f3fb ""
+ "tex_dtu_compute_a_uk.pdf" 1667744718 13504 7ae3ecb9b649001643f902e32d3a8cca ""
+ "tex_dtu_frise.pdf" 1667744718 32488 57c0f48ec5395d976ac1e57718922c22 ""
+ "tex_dtu_logo.pdf" 1667744718 1830 e452da49133969a7656f3882c11e9b04 ""
(generated)
"index_NO_SVGS.aux"
"index_NO_SVGS.log"
diff --git a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.fls b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.fls
index 291d4099c9057f0281f59b402364ec36ab7f228f..40c65e5846335cb7484780c2abce21e71301125d 100644
--- a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.fls
+++ b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.fls
@@ -1814,32 +1814,27 @@ INPUT tex_dtu_frise.pdf
INPUT ./tex_dtu_frise.pdf
INPUT ./tex_dtu_frise.pdf
INPUT /var/lib/texmf/fonts/map/pdftex/updmap/pdftex.map
-INPUT /usr/share/texmf/tex/latex/lm/t1lmtt.fd
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-INPUT /usr/share/texmf/tex/latex/lm/t1lmtt.fd
-INPUT /usr/share/texmf/fonts/tfm/public/lm/ec-lmtt10.tfm
INPUT /usr/share/texmf/tex/latex/lm/ot1lmr.fd
INPUT /usr/share/texmf/tex/latex/lm/ot1lmr.fd
INPUT /usr/share/texmf/tex/latex/lm/ot1lmr.fd
INPUT /usr/share/texmf/tex/latex/lm/ot1lmr.fd
INPUT /usr/share/texmf/fonts/tfm/public/lm/rm-lmr10.tfm
-INPUT /usr/share/texmf/fonts/tfm/public/lm/rm-lmr8.tfm
-INPUT /usr/share/texmf/fonts/tfm/public/lm/rm-lmr6.tfm
+INPUT /usr/share/texmf/fonts/tfm/public/lm/rm-lmr7.tfm
+INPUT /usr/share/texmf/fonts/tfm/public/lm/rm-lmr5.tfm
INPUT /usr/share/texmf/tex/latex/lm/omllmm.fd
INPUT /usr/share/texmf/tex/latex/lm/omllmm.fd
INPUT /usr/share/texmf/tex/latex/lm/omllmm.fd
INPUT /usr/share/texmf/tex/latex/lm/omllmm.fd
INPUT /usr/share/texmf/fonts/tfm/public/lm/lmmi10.tfm
-INPUT /usr/share/texmf/fonts/tfm/public/lm/lmmi8.tfm
-INPUT /usr/share/texmf/fonts/tfm/public/lm/lmmi6.tfm
+INPUT /usr/share/texmf/fonts/tfm/public/lm/lmmi7.tfm
+INPUT /usr/share/texmf/fonts/tfm/public/lm/lmmi5.tfm
INPUT /usr/share/texmf/tex/latex/lm/omslmsy.fd
INPUT /usr/share/texmf/tex/latex/lm/omslmsy.fd
INPUT /usr/share/texmf/tex/latex/lm/omslmsy.fd
INPUT /usr/share/texmf/tex/latex/lm/omslmsy.fd
INPUT /usr/share/texmf/fonts/tfm/public/lm/lmsy10.tfm
-INPUT /usr/share/texmf/fonts/tfm/public/lm/lmsy8.tfm
-INPUT /usr/share/texmf/fonts/tfm/public/lm/lmsy6.tfm
+INPUT /usr/share/texmf/fonts/tfm/public/lm/lmsy7.tfm
+INPUT /usr/share/texmf/fonts/tfm/public/lm/lmsy5.tfm
INPUT /usr/share/texmf/tex/latex/lm/omxlmex.fd
INPUT /usr/share/texmf/tex/latex/lm/omxlmex.fd
INPUT /usr/share/texmf/tex/latex/lm/omxlmex.fd
@@ -1850,19 +1845,115 @@ INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsa.fd
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsa.fd
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INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam7.tfm
+INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam5.tfm
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsb.fd
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsb.fd
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INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsb.fd
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm10.tfm
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+INPUT /usr/share/texmf/fonts/tfm/public/lm/ec-lmssbx10.tfm
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
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INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm7.tfm
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
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+INPUT tex_dtu_logo.pdf
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INPUT /usr/share/texmf/fonts/tfm/public/lm/ec-lmssbx10.tfm
INPUT ./tex_dtu_logo.pdf
INPUT tex_dtu_logo.pdf
INPUT ./tex_dtu_logo.pdf
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+INPUT /usr/share/texmf/tex/latex/lm/t1lmr.fd
+INPUT /usr/share/texmf/fonts/tfm/public/lm/ec-lmr9.tfm
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
+INPUT tex_dtu_logo.pdf
+INPUT ./tex_dtu_logo.pdf
OUTPUT index_NO_SVGS.nav
OUTPUT index_NO_SVGS.toc
OUTPUT index_NO_SVGS.snm
@@ -1870,7 +1961,12 @@ INPUT index_NO_SVGS.aux
INPUT ./index_NO_SVGS.out
INPUT ./index_NO_SVGS.out
INPUT /usr/share/texmf/fonts/enc/dvips/lm/lm-ec.enc
+INPUT /usr/share/texmf/fonts/enc/dvips/lm/lm-mathsy.enc
+INPUT /usr/share/texmf/fonts/type1/public/lm/lmr9.pfb
INPUT /usr/share/texmf/fonts/type1/public/lm/lmss10.pfb
INPUT /usr/share/texmf/fonts/type1/public/lm/lmss8.pfb
+INPUT /usr/share/texmf/fonts/type1/public/lm/lmss9.pfb
INPUT /usr/share/texmf/fonts/type1/public/lm/lmssbx10.pfb
+INPUT /usr/share/texmf/fonts/type1/public/lm/lmsy10.pfb
+INPUT /usr/share/texmf/fonts/type1/public/lm/lmsy9.pfb
INPUT /usr/share/texmf/fonts/type1/public/lm/lmtt10.pfb
diff --git a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.nav b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.nav
index 9033d8ba0cd2afbd30fe6ab857d8374468715862..47506c5837d0709d9320314ee1fc20b15e8d2401 100644
--- a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.nav
+++ b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.nav
@@ -2,8 +2,53 @@
\headcommand {\beamer@framepages {1}{1}}
\headcommand {\slideentry {0}{0}{2}{2/2}{}{0}}
\headcommand {\beamer@framepages {2}{2}}
-\headcommand {\beamer@partpages {1}{2}}
-\headcommand {\beamer@subsectionpages {1}{2}}
-\headcommand {\beamer@sectionpages {1}{2}}
-\headcommand {\beamer@documentpages {2}}
-\headcommand {\gdef \inserttotalframenumber {2}}
+\headcommand {\slideentry {0}{0}{3}{3/3}{}{0}}
+\headcommand {\beamer@framepages {3}{3}}
+\headcommand {\slideentry {0}{0}{4}{4/4}{}{0}}
+\headcommand {\beamer@framepages {4}{4}}
+\headcommand {\slideentry {0}{0}{5}{5/5}{}{0}}
+\headcommand {\beamer@framepages {5}{5}}
+\headcommand {\slideentry {0}{0}{6}{6/6}{}{0}}
+\headcommand {\beamer@framepages {6}{6}}
+\headcommand {\slideentry {0}{0}{7}{7/7}{}{0}}
+\headcommand {\beamer@framepages {7}{7}}
+\headcommand {\slideentry {0}{0}{8}{8/8}{}{0}}
+\headcommand {\beamer@framepages {8}{8}}
+\headcommand {\slideentry {0}{0}{9}{9/9}{}{0}}
+\headcommand {\beamer@framepages {9}{9}}
+\headcommand {\slideentry {0}{0}{10}{10/10}{}{0}}
+\headcommand {\beamer@framepages {10}{10}}
+\headcommand {\slideentry {0}{0}{11}{11/11}{}{0}}
+\headcommand {\beamer@framepages {11}{11}}
+\headcommand {\slideentry {0}{0}{12}{12/12}{}{0}}
+\headcommand {\beamer@framepages {12}{12}}
+\headcommand {\slideentry {0}{0}{13}{13/13}{}{0}}
+\headcommand {\beamer@framepages {13}{13}}
+\headcommand {\slideentry {0}{0}{14}{14/14}{}{0}}
+\headcommand {\beamer@framepages {14}{14}}
+\headcommand {\slideentry {0}{0}{15}{15/15}{}{0}}
+\headcommand {\beamer@framepages {15}{15}}
+\headcommand {\slideentry {0}{0}{16}{16/16}{}{0}}
+\headcommand {\beamer@framepages {16}{16}}
+\headcommand {\slideentry {0}{0}{17}{17/17}{}{0}}
+\headcommand {\beamer@framepages {17}{17}}
+\headcommand {\beamer@sectionpages {1}{17}}
+\headcommand {\beamer@subsectionpages {1}{17}}
+\headcommand {\sectionentry {1}{Autolab}{18}{Autolab}{0}}
+\headcommand {\slideentry {1}{0}{1}{18/18}{}{0}}
+\headcommand {\beamer@framepages {18}{18}}
+\headcommand {\slideentry {1}{0}{2}{19/19}{}{0}}
+\headcommand {\beamer@framepages {19}{19}}
+\headcommand {\slideentry {1}{0}{3}{20/20}{}{0}}
+\headcommand {\beamer@framepages {20}{20}}
+\headcommand {\slideentry {1}{0}{4}{21/21}{}{0}}
+\headcommand {\beamer@framepages {21}{21}}
+\headcommand {\slideentry {1}{0}{5}{22/22}{}{0}}
+\headcommand {\beamer@framepages {22}{22}}
+\headcommand {\slideentry {1}{0}{6}{23/23}{}{0}}
+\headcommand {\beamer@framepages {23}{23}}
+\headcommand {\beamer@partpages {1}{23}}
+\headcommand {\beamer@subsectionpages {18}{23}}
+\headcommand {\beamer@sectionpages {18}{23}}
+\headcommand {\beamer@documentpages {23}}
+\headcommand {\gdef \inserttotalframenumber {23}}
diff --git a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.out b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.out
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..85cf4c60697078c98cf75de90f0e5a29f60f8d45 100644
--- a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.out
+++ b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.out
@@ -0,0 +1 @@
+\BOOKMARK [2][]{Outline0.1}{\376\377\000A\000u\000t\000o\000l\000a\000b}{}% 1
diff --git a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.pdf b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.pdf
index f596647998da77ffc7f6255b9cede48f5f635a25..3c4ed1ea3313c08b1e5483d27c2cc94a31c13928 100644
Binary files a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.pdf and b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.pdf differ
diff --git a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.tex b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.tex
index 91128bf6bd18cc44088034f8a2b58d778165ade5..eed883e1a10305af535f5f5a86ce2d6a98e50417 100644
--- a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.tex
+++ b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.tex
@@ -7,9 +7,9 @@
\toggletrue{overlabel_includelabels}
\input{beamer_slider_preamble.tex}
-\title{Example slide show}
-\author{Author}
-\date{April 1st, 2022}
+\title{Two alternative takes on autograding}
+\author{Tue Herlau}
+\date{\today}
\togglefalse{overlabel_includesvgs}
\toggletrue{overlabel_includelabels}
@@ -17,11 +17,323 @@
\begin{frame}
\maketitle
\end{frame}
+
+
+\begin{frame}
+\frametitle{Summary}
+\begin{description}
+ \item[Unitgrade:] My own solution used in 02465 which I believe is
+ \begin{itemize}
+ \item Shallow extension of unittests
+ \item Better for students
+ \item Requires less work to set up than codejudge
+ \begin{itemize}
+ \item Vedranas exam from introduction to programming
+ \item Alcestes exam from the CPP course and exercise 6
+ \end{itemize}
+ \end{itemize}
+\item[CMU Autolab:] Platform used at CMU and many other universities
+\begin{itemize}
+ \item Functions like a container for tests (great flexibility; think CI/CD)
+ \item Fully text-configured
+\end{itemize}
+\end{description}
+\vspace{1cm}
+\begin{itemize}
+ \item \url{https://gitlab.compute.dtu.dk/tuhe/unitgrade}
+ \item \url{https://autolabproject.com/}
+\end{itemize}
+\end{frame}
+
+\begin{frame}\osvg{start}
+ \frametitle{Autolab: what got me started}
+
+\end{frame}
+
% This slideshow is made using slider. Install using: pip install beamer-slider
% check http://gitlab.compute.dtu.dk/tuhe/slider for more information.
-\begin{frame}\osvg{myoverlay} % Use the \osvg{labelname} - tag to create new overlays. Run the command `slider` in the terminal and check the ./osvgs directory for the svg files!
-\frametitle{Slide with an overlay}
-This is some example text!
+\begin{frame}%\osvg{myoverlay} % Use the \osvg{labelname} - tag to create new overlays. Run the command `slider` in the terminal and check the ./osvgs directory for the svg files!
+\frametitle{Online autograders}
+\begin{itemize}
+\item They do many things
+\begin{itemize}
+ \item Exercise descriptions
+ \item Administrative tasks (student onboarding, grading, exports)
+ \item Calendar-tasks (due-date, handling delays)
+ \item Assignment handin
+ \item Plagiarism checking
+ \item An IDE
+ \item A CI/CD system (upload code and run)
+ \item Various forms of automation/ideas about organizing exercises
+ \item A test system
+\end{itemize}
+\item I find them hard to use
+\begin{itemize}
+ \item Non-traditional workflow: First you parse these 5 numbers from stdin...
+ \item Blackbox
+\end{itemize}
+\end{itemize}
+\end{frame}
+%\begin{frame}
+%\frametitle{Advantages of automatic assessment}
+%Main advantage lies in feedback
+%\end{frame}
+\begin{frame}
+\frametitle{My goals}
+\begin{description}
+\item[User experience:] \greent{Best} allow students to solve their programming problems
+\item[Administrative ease:] Make the course \greent{software}, \greent{tests}, and \greent{written material} easy to write and maintain
+%\begin{itemize}
+% \item Fast development
+% \item Write things in one place
+% \item Avoid (or detect) breaking changes
+% \item (should still support autograding)
+%\end{itemize}
+%\item In this presentation: Inspiration; I am fully aware I did not solve everything.
+\end{description}
+\end{frame}
+
+
+\begin{frame}
+ \frametitle{User experience}
+ \begin{itemize}
+ \item Which test system best allows \redt{students} to fix problems in \redt{their} homework? \pause
+ \item Which test system best allow \redt{me} to fix problems in \redt{my code} \pause
+ \item \redt{Unittests:}
+ \begin{itemize}
+ \item Use your favorite IDE: Debugger + autocomplete + inline documentation
+ \item Best-practice for 25 years
+ \item Test are runable in isolation
+ \item Transparency; everything is python
+ \item Everything can be unittested
+ \item Student learns relevant skills (unittesting)
+ \end{itemize} \pause
+ \item \redt{Web-based tests}
+ \begin{itemize}
+ \item No debugger
+ \item Local/remote code (or use the bad online IDE)
+ \item Increased run-time (can tests be run in isolation?)
+ \item Blackboxing (environment, packages, file locations, how code is called)
+ \begin{itemize}
+ \item Drivers
+ \item Preprocessors
+ \item Postprocessors
+ \item Hacks (\textrm{cat}, \textrm{fix-floats}, etc.)
+ \end{itemize}
+ \item Adopt conventions from the tool (is reading from stdin optimal?)
+ \end{itemize}
+ \end{itemize}
+\end{frame}
+
+
+\begin{frame}\osvg{intropython}
+\frametitle{Example: Intro to python exam}
+Setup: \texttt{pip install unitgrade}
+\vspace{8cm}
+\end{frame}
+
+
+\begin{frame}\osvg{intropython}
+ \frametitle{Example: Writing your own test}
+% Setup: \texttt{pip install unitgrade}
+% \vspace{8cm}
+\end{frame}
+
+
+\begin{frame}
+ \frametitle{Casestudy: Introduction to python (Vedrana)}
+ \begin{itemize}
+ \item Exam set with 4 problems (Python). Showcase automatic generation of test answers.
+ \end{itemize}
+ \begin{columns}\begin{column}{.5\linewidth}\redt{ Codejudge}\end{column}
+ \begin{column}{.5\linewidth}\redt{ Unitgrade }\end{column}\end{columns}
+
+ \begin{columns}
+ \begin{column}{.5\linewidth}
+ \begin{itemize}
+ \item 5 problems
+ \item 11 tests per problem
+ \item 60 files
+ \item 282 lines of code
+ \end{itemize}
+ \end{column}
+ \begin{column}{.5\linewidth}
+
+ \begin{itemize}
+ \item 5 problems
+ \item 11 tests per problem
+ \item 3 files
+ \item 127 lines of code
+ \end{itemize}
+ Bonus: My version contains a handout stub for students to work with.
+ \end{column}
+ \end{columns}
+\end{frame}
+\begin{frame} \osvg{grading}
+ \frametitle{Casestudy: Introduction to python (grading)}
+
+\end{frame}
+
+\begin{frame}
+ \frametitle{Example 2: Writing an exam problem}
+ \begin{itemize}
+ \item The problem is about how to write a class representing a fraction
+ \item Must support addition and multiplication, plus import from string
+ \end{itemize}
+\end{frame}
+
+\begin{frame}
+ \frametitle{Example 3: Grading and hidden tests}
+ \begin{itemize}
+ \item The problem is about how to write a class representing a fraction
+ \item Must support addition and multiplication, plus import from string
+ \end{itemize}
+\end{frame}
+
+
+
+\begin{frame}
+ \frametitle{Casestudy: 02465}
+ \begin{itemize}
+ \item 13 exercise + 3 projects (3 group + individual)
+ \item Fairly involved code (many dependencies)
+ \item
+ \end{itemize}
+\end{frame}
+
+\begin{frame} \osvg{ac1}
+ \frametitle{Casestudy: Problem set 6 (Alceste)}
+Class representing fractions
+\end{frame}
+\begin{frame}
+\frametitle{Casestudy: Problem set 6 (Alceste)}
+
+\begin{itemize}
+ \item Problem set 6, create a Fraction class with addition
+\end{itemize}
+ \begin{columns}\begin{column}{.5\linewidth}\redt{ Codejudge}\end{column}
+ \begin{column}{.5\linewidth}\redt{ Unitgrade }\end{column}\end{columns}
+
+\begin{columns}
+ \begin{column}{.5\linewidth}
+ \begin{itemize}
+ \item 1 problem
+ \item 8 files (.in, .ans)
+ \item 2 tests
+ \item 12 lines of code (only specifies input \& output; contains more code in LaTeX)
+ \end{itemize}
+ \end{column}
+ \begin{column}{.5\linewidth}
+ \begin{itemize}
+ \item 1 problems
+ \item 2 files
+ \item 6 tests
+ \item 86 lines of code
+ \end{itemize}
+ Bonus: Contains more specific tests, generates handout files, contains a solution, and allows automatic checks of implementation for later refactoring.
+ \end{column}
+\end{columns}
+\end{frame}
+\begin{frame} \osvg{ac2}
+ \frametitle{Features: Automation and code-snippet generation}
+
+
+\end{frame}
+
+
+\begin{frame}
+ \frametitle{Casestudy: Exam in C++ Course 2021}
+ \begin{itemize}
+ \item Exam set for 2021
+ \item 4 problems
+ \end{itemize}
+\vspace{1cm}
+ \begin{columns}
+ \begin{column}{.5\linewidth}
+ \redt{ Codejudge}
+ \begin{itemize}
+ \item 72 files (!)
+ \item 16 .yml files
+ \item 18 .ans files
+ \item 552 lines of code (excluding .ans files)
+\end{itemize}
+ \end{column}
+ \begin{column}{.5\linewidth}
+ \redt{Unitgrade}
+ \begin{itemize}
+ \item 6 files (4 problems + 1 test + 1 deploy)
+ \item 116 lines of code
+ \item More tests
+\end{itemize}
+%Bonus: Automatic checks.
+ \end{column}
+ \end{columns}
+
+\end{frame}
+
+\section{Autolab}
+\begin{frame} \osvg{autolab1}
+\frametitle{CMU Autolab}
+
+
+
+\end{frame}
+
+
+\begin{frame} \osvg{autolab2}
+\frametitle{CMU Autolab}
+\begin{itemize}
+\item Classic autograder: Students, classes, assignments.
+\item Sign-up can be handled using student email (confirmation emails)
+\end{itemize}
+\vspace{6cm}
+\end{frame}
+
+
+\begin{frame}\osvg{autolab3}
+\frametitle{Test development}
+\begin{itemize}
+\item An assignment is a single .tar file:
+\item tl;dr:
+\begin{itemize}
+ \item The container will copy your autograder files the students into the same directory
+\item Then it calls \texttt{autograde\_Makefile}
+\item You return json with the scores to stdout
+\end{itemize}
+\item Easy to call e.g. a unittest script
+\item Tests can be run locally
+\item Many examples online
+\end{itemize}
+\end{frame}
+
+\begin{frame}\osvg{autolab4}
+\frametitle{Easy to automate}
+\begin{itemize}
+ \item Unitgrade allows one-line deployment to an autolab \texttt{.tar} file for upload
+\end{itemize}
+\vspace{6cm}
+\end{frame}
+
+\begin{frame}
+\frametitle{Student onboarding}
+
+ \end{frame}
+\begin{frame}
+% What is it?
+% How does it work?
+\begin{itemize}
+\item Text-based instead of GUI based:
+\begin{itemize}
+ \item You specify a docker file and upload a directory with a makefile
+ \item Students upload their code
+ \item The students code is moved into a copy of your directory
+ \item The makefile is run
+ \item Your makefile returns a \texttt{.json} string to stdout
+ \item The website display this \texttt{.json} string
+\end{itemize}
+
+\end{itemize}
+
\end{frame}
\end{document}
diff --git a/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.toc b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.toc
index 9fbdd18a8c9adf55ec0285e8532d13207dc20bf7..6f17b2423c8c8c8c2702290a04a83c5f4f617d1e 100644
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+++ b/docs/presentation2022/osvgs/tmp/no_svg_tmp/index_NO_SVGS.toc
@@ -1 +1,2 @@
\babel@toc {english}{}\relax
+\beamer@sectionintoc {1}{Autolab}{18}{0}{1}
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@@ -0,0 +1,4 @@
+\begin{Verbatim}[commandchars=\\\{\}]
+Result of 1 / 4 * 1 / 2 is 1 / 8
+Result of 5 / 2 div 10 / 3 is 15 / 20
+\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index/1C8C4C316CEECF02BD7FFC63EFD497326F77AD3888A7BF17566D124427769365.pygtex b/examples/presentation/Latex/_minted-index/38AB66A1F480DA59292A05C9BDF935696F77AD3888A7BF17566D124427769365.pygtex
similarity index 82%
rename from examples/presentation/Latex/_minted-index/1C8C4C316CEECF02BD7FFC63EFD497326F77AD3888A7BF17566D124427769365.pygtex
rename to examples/presentation/Latex/_minted-index/38AB66A1F480DA59292A05C9BDF935696F77AD3888A7BF17566D124427769365.pygtex
index 5c0dcd1195e6272c5a99925a9f378187ea516806..9729b80f088487043cf92563db68298ede71047d 100644
--- a/examples/presentation/Latex/_minted-index/1C8C4C316CEECF02BD7FFC63EFD497326F77AD3888A7BF17566D124427769365.pygtex
+++ b/examples/presentation/Latex/_minted-index/38AB66A1F480DA59292A05C9BDF935696F77AD3888A7BF17566D124427769365.pygtex
@@ -3,13 +3,13 @@
\PYGZgt{}\PYGZgt{}\PYGZgt{} \PYG{n+nv}{f1} \PYG{o}{=} Fraction\PYG{o}{(}\PYG{l+m}{1}, \PYG{l+m}{2}\PYG{o}{)} \PYG{c+c1}{\PYGZsh{} Represents 1/2}
\PYGZgt{}\PYGZgt{}\PYGZgt{} \PYG{n+nv}{f2} \PYG{o}{=} Fraction\PYG{o}{(}\PYG{l+m}{3}, \PYG{l+m}{5}\PYG{o}{)} \PYG{c+c1}{\PYGZsh{} Represents 3/5}
\PYGZgt{}\PYGZgt{}\PYGZgt{} print\PYG{o}{(}f\PYG{l+s+s2}{\PYGZdq{}Result of \PYGZob{}f1\PYGZcb{} + \PYGZob{}f2\PYGZcb{} is\PYGZdq{}}, f1 + f2\PYG{o}{)}
-Result of \PYG{o}{(}\PYG{l+m}{1} / \PYG{l+m}{2}\PYG{o}{)} + \PYG{o}{(}\PYG{l+m}{3} / \PYG{l+m}{5}\PYG{o}{)} is \PYG{o}{(}\PYG{l+m}{11} / \PYG{l+m}{2}\PYG{o}{)}
+Result of \PYG{l+m}{1} / \PYG{l+m}{2} + \PYG{l+m}{3} / \PYG{l+m}{5} is \PYG{l+m}{11} / \PYG{l+m}{2}
\PYGZgt{}\PYGZgt{}\PYGZgt{}
\PYGZgt{}\PYGZgt{}\PYGZgt{} \PYG{c+c1}{\PYGZsh{} Now do some compound tests:}
\PYGZgt{}\PYGZgt{}\PYGZgt{} \PYG{n+nv}{s} \PYG{o}{=} \PYG{l+s+s2}{\PYGZdq{} 1 / 4 * 1 / 2\PYGZdq{}}
\PYGZgt{}\PYGZgt{}\PYGZgt{} print\PYG{o}{(}\PYG{l+s+s2}{\PYGZdq{}Result of\PYGZdq{}}, s, \PYG{l+s+s2}{\PYGZdq{}is\PYGZdq{}}, from\PYGZus{}string\PYG{o}{(}s\PYG{o}{))}
-Result of \PYG{l+m}{1} / \PYG{l+m}{4} * \PYG{l+m}{1} / \PYG{l+m}{2} is \PYG{o}{(}\PYG{l+m}{1} / \PYG{l+m}{8}\PYG{o}{)}
+Result of \PYG{l+m}{1} / \PYG{l+m}{4} * \PYG{l+m}{1} / \PYG{l+m}{2} is \PYG{l+m}{1} / \PYG{l+m}{8}
\PYGZgt{}\PYGZgt{}\PYGZgt{} \PYG{n+nv}{s} \PYG{o}{=} \PYG{l+s+s2}{\PYGZdq{}5 / 2 div 10 / 3\PYGZdq{}}
\PYGZgt{}\PYGZgt{}\PYGZgt{} print\PYG{o}{(}\PYG{l+s+s2}{\PYGZdq{}Result of\PYGZdq{}}, s, \PYG{l+s+s2}{\PYGZdq{}is\PYGZdq{}}, from\PYGZus{}string\PYG{o}{(}s\PYG{o}{))}
-Result of \PYG{l+m}{5} / \PYG{l+m}{2} div \PYG{l+m}{10} / \PYG{l+m}{3} is \PYG{o}{(}\PYG{l+m}{15} / \PYG{l+m}{20}\PYG{o}{)}
+Result of \PYG{l+m}{5} / \PYG{l+m}{2} div \PYG{l+m}{10} / \PYG{l+m}{3} is \PYG{l+m}{15} / \PYG{l+m}{20}
\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index/617F95B3C9B5986EE47AB06464B25A4656A75F0008C42025054395883EB49E2F.pygtex b/examples/presentation/Latex/_minted-index/617F95B3C9B5986EE47AB06464B25A4656A75F0008C42025054395883EB49E2F.pygtex
deleted file mode 100644
index c93aef079dc1753a8f78bc969dd8d81b5c2da180..0000000000000000000000000000000000000000
--- a/examples/presentation/Latex/_minted-index/617F95B3C9B5986EE47AB06464B25A4656A75F0008C42025054395883EB49E2F.pygtex
+++ /dev/null
@@ -1,4 +0,0 @@
-\begin{Verbatim}[commandchars=\\\{\}]
-Result of 1 / 4 * 1 / 2 is (1 / 8)
-Result of 5 / 2 div 10 / 3 is (15 / 20)
-\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index/C337567ABBC0041A183DD819B579D62B0A1306BEF7ABBA8E6F738A7935C17A00.pygtex b/examples/presentation/Latex/_minted-index/E913FEE88811A4A3E6162925A57739C40A1306BEF7ABBA8E6F738A7935C17A00.pygtex
similarity index 74%
rename from examples/presentation/Latex/_minted-index/C337567ABBC0041A183DD819B579D62B0A1306BEF7ABBA8E6F738A7935C17A00.pygtex
rename to examples/presentation/Latex/_minted-index/E913FEE88811A4A3E6162925A57739C40A1306BEF7ABBA8E6F738A7935C17A00.pygtex
index b043bed919dc271835799a763924e3f553021d99..b98ec7552e4b9c0b87ea586cd0b9cc9d7b1bb654 100644
--- a/examples/presentation/Latex/_minted-index/C337567ABBC0041A183DD819B579D62B0A1306BEF7ABBA8E6F738A7935C17A00.pygtex
+++ b/examples/presentation/Latex/_minted-index/E913FEE88811A4A3E6162925A57739C40A1306BEF7ABBA8E6F738A7935C17A00.pygtex
@@ -6,7 +6,7 @@
\PYG{n+nb+bp}{self}\PYG{o}{.}\PYG{n}{m} \PYG{o}{=} \PYG{n}{m}
\PYG{k}{def} \PYG{n+nf+fm}{\PYGZus{}\PYGZus{}add\PYGZus{}\PYGZus{}}\PYG{p}{(}\PYG{n+nb+bp}{self}\PYG{p}{,} \PYG{n}{other}\PYG{p}{):}
- \PYG{c+c1}{\PYGZsh{} Computes f = f1 + f2 (where f1 and f2 are both Fraction\PYGZhy{}objects and f1=self, f2=other) }
+ \PYG{l+s+sd}{\PYGZdq{}\PYGZdq{}\PYGZdq{} Computes f = f1 + f2 (where f1 and f2 are both Fraction\PYGZhy{}objects and f1=self, f2=other), see (Assignment 6, eq. (1)) and (Har20) \PYGZdq{}\PYGZdq{}\PYGZdq{}}
\PYG{k}{return} \PYG{n}{f}
\PYG{k}{def} \PYG{n+nf+fm}{\PYGZus{}\PYGZus{}mul\PYGZus{}\PYGZus{}}\PYG{p}{(}\PYG{n+nb+bp}{self}\PYG{p}{,} \PYG{n}{other}\PYG{p}{):}
@@ -19,5 +19,5 @@
\PYG{k}{def} \PYG{n+nf+fm}{\PYGZus{}\PYGZus{}str\PYGZus{}\PYGZus{}}\PYG{p}{(}\PYG{n+nb+bp}{self}\PYG{p}{):}
\PYG{l+s+sd}{\PYGZdq{}\PYGZdq{}\PYGZdq{} Creates a string representation. You can use it as `print(str(Fraction(1,2))) to output 1/2\PYGZdq{}\PYGZdq{}\PYGZdq{}}
- \PYG{k}{return} \PYG{l+s+sa}{f}\PYG{l+s+s2}{\PYGZdq{}(}\PYG{l+s+si}{\PYGZob{}}\PYG{n+nb+bp}{self}\PYG{o}{.}\PYG{n}{n}\PYG{l+s+si}{\PYGZcb{}}\PYG{l+s+s2}{ / }\PYG{l+s+si}{\PYGZob{}}\PYG{n+nb+bp}{self}\PYG{o}{.}\PYG{n}{m}\PYG{l+s+si}{\PYGZcb{}}\PYG{l+s+s2}{)\PYGZdq{}}
+ \PYG{k}{return} \PYG{l+s+sa}{f}\PYG{l+s+s2}{\PYGZdq{}}\PYG{l+s+si}{\PYGZob{}}\PYG{n+nb+bp}{self}\PYG{o}{.}\PYG{n}{n}\PYG{l+s+si}{\PYGZcb{}}\PYG{l+s+s2}{ / }\PYG{l+s+si}{\PYGZob{}}\PYG{n+nb+bp}{self}\PYG{o}{.}\PYG{n}{m}\PYG{l+s+si}{\PYGZcb{}}\PYG{l+s+s2}{\PYGZdq{}}
\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index/D3ECD3ACDA87B14881FB480CA410F52E81B27360F55ECAEF0E03CEF63D4338FD.pygtex b/examples/presentation/Latex/_minted-index/F83721D063149FE208A44C60DB48484B81B27360F55ECAEF0E03CEF63D4338FD.pygtex
similarity index 56%
rename from examples/presentation/Latex/_minted-index/D3ECD3ACDA87B14881FB480CA410F52E81B27360F55ECAEF0E03CEF63D4338FD.pygtex
rename to examples/presentation/Latex/_minted-index/F83721D063149FE208A44C60DB48484B81B27360F55ECAEF0E03CEF63D4338FD.pygtex
index e622fcd83fb1abbd849929ab19667115e1f4d95d..9bc13e149b2a176b545792b7682643892557c9a3 100644
--- a/examples/presentation/Latex/_minted-index/D3ECD3ACDA87B14881FB480CA410F52E81B27360F55ECAEF0E03CEF63D4338FD.pygtex
+++ b/examples/presentation/Latex/_minted-index/F83721D063149FE208A44C60DB48484B81B27360F55ECAEF0E03CEF63D4338FD.pygtex
@@ -1,3 +1,3 @@
\begin{Verbatim}[commandchars=\\\{\}]
-Result of (1 / 2) + (3 / 5) is (11 / 2)
+Result of 1 / 2 + 3 / 5 is 11 / 2
\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index_NO_SVGS/00E2E804F1FA397D97A5909ABF9BDD7D274B6DF28E9ED4D1CDE2393BF3DE3CC8.pygtex b/examples/presentation/Latex/_minted-index_NO_SVGS/00E2E804F1FA397D97A5909ABF9BDD7D274B6DF28E9ED4D1CDE2393BF3DE3CC8.pygtex
new file mode 100644
index 0000000000000000000000000000000000000000..f25edf22822bdb41034c5bc27179abed1b011e33
--- /dev/null
+++ b/examples/presentation/Latex/_minted-index_NO_SVGS/00E2E804F1FA397D97A5909ABF9BDD7D274B6DF28E9ED4D1CDE2393BF3DE3CC8.pygtex
@@ -0,0 +1,4 @@
+\begin{Verbatim}[commandchars=\\\{\}]
+Result of 1 / 4 * 1 / 2 is 1 / 8
+Result of 5 / 2 div 10 / 3 is 15 / 20
+\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index_NO_SVGS/38AB66A1F480DA59292A05C9BDF93569802345CC0D356389FD291DC86A2BB929.pygtex b/examples/presentation/Latex/_minted-index_NO_SVGS/38AB66A1F480DA59292A05C9BDF93569802345CC0D356389FD291DC86A2BB929.pygtex
new file mode 100644
index 0000000000000000000000000000000000000000..9729b80f088487043cf92563db68298ede71047d
--- /dev/null
+++ b/examples/presentation/Latex/_minted-index_NO_SVGS/38AB66A1F480DA59292A05C9BDF93569802345CC0D356389FD291DC86A2BB929.pygtex
@@ -0,0 +1,15 @@
+\begin{Verbatim}[commandchars=\\\{\}]
+\PYGZgt{}\PYGZgt{}\PYGZgt{}
+\PYGZgt{}\PYGZgt{}\PYGZgt{} \PYG{n+nv}{f1} \PYG{o}{=} Fraction\PYG{o}{(}\PYG{l+m}{1}, \PYG{l+m}{2}\PYG{o}{)} \PYG{c+c1}{\PYGZsh{} Represents 1/2}
+\PYGZgt{}\PYGZgt{}\PYGZgt{} \PYG{n+nv}{f2} \PYG{o}{=} Fraction\PYG{o}{(}\PYG{l+m}{3}, \PYG{l+m}{5}\PYG{o}{)} \PYG{c+c1}{\PYGZsh{} Represents 3/5}
+\PYGZgt{}\PYGZgt{}\PYGZgt{} print\PYG{o}{(}f\PYG{l+s+s2}{\PYGZdq{}Result of \PYGZob{}f1\PYGZcb{} + \PYGZob{}f2\PYGZcb{} is\PYGZdq{}}, f1 + f2\PYG{o}{)}
+Result of \PYG{l+m}{1} / \PYG{l+m}{2} + \PYG{l+m}{3} / \PYG{l+m}{5} is \PYG{l+m}{11} / \PYG{l+m}{2}
+\PYGZgt{}\PYGZgt{}\PYGZgt{}
+\PYGZgt{}\PYGZgt{}\PYGZgt{} \PYG{c+c1}{\PYGZsh{} Now do some compound tests:}
+\PYGZgt{}\PYGZgt{}\PYGZgt{} \PYG{n+nv}{s} \PYG{o}{=} \PYG{l+s+s2}{\PYGZdq{} 1 / 4 * 1 / 2\PYGZdq{}}
+\PYGZgt{}\PYGZgt{}\PYGZgt{} print\PYG{o}{(}\PYG{l+s+s2}{\PYGZdq{}Result of\PYGZdq{}}, s, \PYG{l+s+s2}{\PYGZdq{}is\PYGZdq{}}, from\PYGZus{}string\PYG{o}{(}s\PYG{o}{))}
+Result of \PYG{l+m}{1} / \PYG{l+m}{4} * \PYG{l+m}{1} / \PYG{l+m}{2} is \PYG{l+m}{1} / \PYG{l+m}{8}
+\PYGZgt{}\PYGZgt{}\PYGZgt{} \PYG{n+nv}{s} \PYG{o}{=} \PYG{l+s+s2}{\PYGZdq{}5 / 2 div 10 / 3\PYGZdq{}}
+\PYGZgt{}\PYGZgt{}\PYGZgt{} print\PYG{o}{(}\PYG{l+s+s2}{\PYGZdq{}Result of\PYGZdq{}}, s, \PYG{l+s+s2}{\PYGZdq{}is\PYGZdq{}}, from\PYGZus{}string\PYG{o}{(}s\PYG{o}{))}
+Result of \PYG{l+m}{5} / \PYG{l+m}{2} div \PYG{l+m}{10} / \PYG{l+m}{3} is \PYG{l+m}{15} / \PYG{l+m}{20}
+\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index_NO_SVGS/4B904B38547539E6886F45285B55E17BDB5D774133F9C0C976BBAEB4EA3883A3.pygtex b/examples/presentation/Latex/_minted-index_NO_SVGS/4B904B38547539E6886F45285B55E17BDB5D774133F9C0C976BBAEB4EA3883A3.pygtex
new file mode 100644
index 0000000000000000000000000000000000000000..6dfa740abd97b8c43300bb43ca5ce25ac5eb4992
--- /dev/null
+++ b/examples/presentation/Latex/_minted-index_NO_SVGS/4B904B38547539E6886F45285B55E17BDB5D774133F9C0C976BBAEB4EA3883A3.pygtex
@@ -0,0 +1,3 @@
+\begin{Verbatim}[commandchars=\\\{\}]
+\PYG{n}{f1}\PYG{o}{.}\PYG{n+nf+fm}{\PYGZus{}\PYGZus{}add\PYGZus{}\PYGZus{}}\PYG{p}{(}\PYG{n}{f2}\PYG{p}{)}
+\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index_NO_SVGS/A9FD9E7563778CEBB343C798E256BFB3730D5FF657B94160965440866D75AAEF.pygtex b/examples/presentation/Latex/_minted-index_NO_SVGS/A9FD9E7563778CEBB343C798E256BFB3730D5FF657B94160965440866D75AAEF.pygtex
new file mode 100644
index 0000000000000000000000000000000000000000..049d43805e5243942620d90abada4340318effaa
--- /dev/null
+++ b/examples/presentation/Latex/_minted-index_NO_SVGS/A9FD9E7563778CEBB343C798E256BFB3730D5FF657B94160965440866D75AAEF.pygtex
@@ -0,0 +1,6 @@
+\begin{Verbatim}[commandchars=\\\{\}]
+\PYG{c+c1}{\PYGZsh{} cpp\PYGZus{}course/fractions.py}
+ \PYG{n}{f1} \PYG{o}{=} \PYG{n}{Fraction}\PYG{p}{(}\PYG{l+m+mi}{1}\PYG{p}{,} \PYG{l+m+mi}{2}\PYG{p}{)} \PYG{c+c1}{\PYGZsh{} Represents 1/2 }
+ \PYG{n}{f2} \PYG{o}{=} \PYG{n}{Fraction}\PYG{p}{(}\PYG{l+m+mi}{3}\PYG{p}{,} \PYG{l+m+mi}{5}\PYG{p}{)} \PYG{c+c1}{\PYGZsh{} Represents 3/5}
+ \PYG{n+nb}{print}\PYG{p}{(}\PYG{l+s+sa}{f}\PYG{l+s+s2}{\PYGZdq{}Result of }\PYG{l+s+si}{\PYGZob{}}\PYG{n}{f1}\PYG{l+s+si}{\PYGZcb{}}\PYG{l+s+s2}{ + }\PYG{l+s+si}{\PYGZob{}}\PYG{n}{f2}\PYG{l+s+si}{\PYGZcb{}}\PYG{l+s+s2}{ is\PYGZdq{}}\PYG{p}{,} \PYG{n}{f1}\PYG{o}{+}\PYG{n}{f2}\PYG{p}{)}
+\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index_NO_SVGS/BCD13D83EF8F0B75CF4482552AC78D62DB5D774133F9C0C976BBAEB4EA3883A3.pygtex b/examples/presentation/Latex/_minted-index_NO_SVGS/BCD13D83EF8F0B75CF4482552AC78D62DB5D774133F9C0C976BBAEB4EA3883A3.pygtex
new file mode 100644
index 0000000000000000000000000000000000000000..548aebfecad42db75f489dfc3b21312b5d1b9c06
--- /dev/null
+++ b/examples/presentation/Latex/_minted-index_NO_SVGS/BCD13D83EF8F0B75CF4482552AC78D62DB5D774133F9C0C976BBAEB4EA3883A3.pygtex
@@ -0,0 +1,3 @@
+\begin{Verbatim}[commandchars=\\\{\}]
+\PYG{n}{from\PYGZus{}string}
+\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index_NO_SVGS/C30DBA8197A1560649606EA4745E9D04DB5D774133F9C0C976BBAEB4EA3883A3.pygtex b/examples/presentation/Latex/_minted-index_NO_SVGS/C30DBA8197A1560649606EA4745E9D04DB5D774133F9C0C976BBAEB4EA3883A3.pygtex
new file mode 100644
index 0000000000000000000000000000000000000000..431ad9c667f5162a78e01919d9975b1cfcab5644
--- /dev/null
+++ b/examples/presentation/Latex/_minted-index_NO_SVGS/C30DBA8197A1560649606EA4745E9D04DB5D774133F9C0C976BBAEB4EA3883A3.pygtex
@@ -0,0 +1,3 @@
+\begin{Verbatim}[commandchars=\\\{\}]
+\PYG{o}{+}
+\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index_NO_SVGS/E913FEE88811A4A3E6162925A57739C4007A73800C83844C6BA6D5BDF1935AC3.pygtex b/examples/presentation/Latex/_minted-index_NO_SVGS/E913FEE88811A4A3E6162925A57739C4007A73800C83844C6BA6D5BDF1935AC3.pygtex
new file mode 100644
index 0000000000000000000000000000000000000000..b98ec7552e4b9c0b87ea586cd0b9cc9d7b1bb654
--- /dev/null
+++ b/examples/presentation/Latex/_minted-index_NO_SVGS/E913FEE88811A4A3E6162925A57739C4007A73800C83844C6BA6D5BDF1935AC3.pygtex
@@ -0,0 +1,23 @@
+\begin{Verbatim}[commandchars=\\\{\}]
+\PYG{c+c1}{\PYGZsh{} cpp\PYGZus{}course/fractions.py}
+\PYG{k}{class} \PYG{n+nc}{Fraction}\PYG{p}{:}
+ \PYG{k}{def} \PYG{n+nf+fm}{\PYGZus{}\PYGZus{}init\PYGZus{}\PYGZus{}}\PYG{p}{(}\PYG{n+nb+bp}{self}\PYG{p}{,} \PYG{n}{n}\PYG{p}{,} \PYG{n}{m}\PYG{p}{):}
+ \PYG{n+nb+bp}{self}\PYG{o}{.}\PYG{n}{n} \PYG{o}{=} \PYG{n}{n}
+ \PYG{n+nb+bp}{self}\PYG{o}{.}\PYG{n}{m} \PYG{o}{=} \PYG{n}{m}
+
+ \PYG{k}{def} \PYG{n+nf+fm}{\PYGZus{}\PYGZus{}add\PYGZus{}\PYGZus{}}\PYG{p}{(}\PYG{n+nb+bp}{self}\PYG{p}{,} \PYG{n}{other}\PYG{p}{):}
+ \PYG{l+s+sd}{\PYGZdq{}\PYGZdq{}\PYGZdq{} Computes f = f1 + f2 (where f1 and f2 are both Fraction\PYGZhy{}objects and f1=self, f2=other), see (Assignment 6, eq. (1)) and (Har20) \PYGZdq{}\PYGZdq{}\PYGZdq{}}
+ \PYG{k}{return} \PYG{n}{f}
+
+ \PYG{k}{def} \PYG{n+nf+fm}{\PYGZus{}\PYGZus{}mul\PYGZus{}\PYGZus{}}\PYG{p}{(}\PYG{n+nb+bp}{self}\PYG{p}{,} \PYG{n}{other}\PYG{p}{):}
+ \PYG{c+c1}{\PYGZsh{} Overwrite to implement f = f1 * f2 }
+ \PYG{k}{return} \PYG{n}{f}
+
+ \PYG{k}{def} \PYG{n+nf+fm}{\PYGZus{}\PYGZus{}truediv\PYGZus{}\PYGZus{}}\PYG{p}{(}\PYG{n+nb+bp}{self}\PYG{p}{,} \PYG{n}{other}\PYG{p}{):}
+ \PYG{c+c1}{\PYGZsh{} Overwrite to implement f = f1/f2, or more specifically self/other. }
+ \PYG{k}{return} \PYG{n}{f}
+
+ \PYG{k}{def} \PYG{n+nf+fm}{\PYGZus{}\PYGZus{}str\PYGZus{}\PYGZus{}}\PYG{p}{(}\PYG{n+nb+bp}{self}\PYG{p}{):}
+ \PYG{l+s+sd}{\PYGZdq{}\PYGZdq{}\PYGZdq{} Creates a string representation. You can use it as `print(str(Fraction(1,2))) to output 1/2\PYGZdq{}\PYGZdq{}\PYGZdq{}}
+ \PYG{k}{return} \PYG{l+s+sa}{f}\PYG{l+s+s2}{\PYGZdq{}}\PYG{l+s+si}{\PYGZob{}}\PYG{n+nb+bp}{self}\PYG{o}{.}\PYG{n}{n}\PYG{l+s+si}{\PYGZcb{}}\PYG{l+s+s2}{ / }\PYG{l+s+si}{\PYGZob{}}\PYG{n+nb+bp}{self}\PYG{o}{.}\PYG{n}{m}\PYG{l+s+si}{\PYGZcb{}}\PYG{l+s+s2}{\PYGZdq{}}
+\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index_NO_SVGS/F83721D063149FE208A44C60DB48484B4FA57F3091E618F07F5C20CE86415DED.pygtex b/examples/presentation/Latex/_minted-index_NO_SVGS/F83721D063149FE208A44C60DB48484B4FA57F3091E618F07F5C20CE86415DED.pygtex
new file mode 100644
index 0000000000000000000000000000000000000000..9bc13e149b2a176b545792b7682643892557c9a3
--- /dev/null
+++ b/examples/presentation/Latex/_minted-index_NO_SVGS/F83721D063149FE208A44C60DB48484B4FA57F3091E618F07F5C20CE86415DED.pygtex
@@ -0,0 +1,3 @@
+\begin{Verbatim}[commandchars=\\\{\}]
+Result of 1 / 2 + 3 / 5 is 11 / 2
+\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex b/examples/presentation/Latex/_minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex
new file mode 100644
index 0000000000000000000000000000000000000000..bb11e458741a03adc5264a48b860b1757a7f1967
--- /dev/null
+++ b/examples/presentation/Latex/_minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex
@@ -0,0 +1,7 @@
+\begin{Verbatim}[commandchars=\\\{\}]
+\PYG{c+c1}{\PYGZsh{} cpp\PYGZus{}course/fractions.py}
+ \PYG{n}{s} \PYG{o}{=} \PYG{l+s+s2}{\PYGZdq{} 1 / 4 * 1 / 2\PYGZdq{}}
+ \PYG{n+nb}{print}\PYG{p}{(}\PYG{l+s+s2}{\PYGZdq{}Result of\PYGZdq{}}\PYG{p}{,} \PYG{n}{s}\PYG{p}{,} \PYG{l+s+s2}{\PYGZdq{}is\PYGZdq{}}\PYG{p}{,} \PYG{n}{from\PYGZus{}string}\PYG{p}{(}\PYG{n}{s}\PYG{p}{))}
+ \PYG{n}{s} \PYG{o}{=} \PYG{l+s+s2}{\PYGZdq{}5 / 2 div 10 / 3\PYGZdq{}}
+ \PYG{n+nb}{print}\PYG{p}{(}\PYG{l+s+s2}{\PYGZdq{}Result of\PYGZdq{}}\PYG{p}{,} \PYG{n}{s}\PYG{p}{,} \PYG{l+s+s2}{\PYGZdq{}is\PYGZdq{}}\PYG{p}{,} \PYG{n}{from\PYGZus{}string}\PYG{p}{(}\PYG{n}{s}\PYG{p}{))}
+\end{Verbatim}
diff --git a/examples/presentation/Latex/_minted-index_NO_SVGS/default.pygstyle b/examples/presentation/Latex/_minted-index_NO_SVGS/default.pygstyle
new file mode 100644
index 0000000000000000000000000000000000000000..211763d1d4e4c090ba3a286634a9a96c7fae303b
--- /dev/null
+++ b/examples/presentation/Latex/_minted-index_NO_SVGS/default.pygstyle
@@ -0,0 +1,101 @@
+
+\makeatletter
+\def\PYG@reset{\let\PYG@it=\relax \let\PYG@bf=\relax%
+ \let\PYG@ul=\relax \let\PYG@tc=\relax%
+ \let\PYG@bc=\relax \let\PYG@ff=\relax}
+\def\PYG@tok#1{\csname PYG@tok@#1\endcsname}
+\def\PYG@toks#1+{\ifx\relax#1\empty\else%
+ \PYG@tok{#1}\expandafter\PYG@toks\fi}
+\def\PYG@do#1{\PYG@bc{\PYG@tc{\PYG@ul{%
+ \PYG@it{\PYG@bf{\PYG@ff{#1}}}}}}}
+\def\PYG#1#2{\PYG@reset\PYG@toks#1+\relax+\PYG@do{#2}}
+
+\@namedef{PYG@tok@w}{\def\PYG@tc##1{\textcolor[rgb]{0.73,0.73,0.73}{##1}}}
+\@namedef{PYG@tok@c}{\let\PYG@it=\textit\def\PYG@tc##1{\textcolor[rgb]{0.24,0.48,0.48}{##1}}}
+\@namedef{PYG@tok@cp}{\def\PYG@tc##1{\textcolor[rgb]{0.61,0.40,0.00}{##1}}}
+\@namedef{PYG@tok@k}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}}
+\@namedef{PYG@tok@kp}{\def\PYG@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}}
+\@namedef{PYG@tok@kt}{\def\PYG@tc##1{\textcolor[rgb]{0.69,0.00,0.25}{##1}}}
+\@namedef{PYG@tok@o}{\def\PYG@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}}
+\@namedef{PYG@tok@ow}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.67,0.13,1.00}{##1}}}
+\@namedef{PYG@tok@nb}{\def\PYG@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}}
+\@namedef{PYG@tok@nf}{\def\PYG@tc##1{\textcolor[rgb]{0.00,0.00,1.00}{##1}}}
+\@namedef{PYG@tok@nc}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.00,0.00,1.00}{##1}}}
+\@namedef{PYG@tok@nn}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.00,0.00,1.00}{##1}}}
+\@namedef{PYG@tok@ne}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.80,0.25,0.22}{##1}}}
+\@namedef{PYG@tok@nv}{\def\PYG@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}}
+\@namedef{PYG@tok@no}{\def\PYG@tc##1{\textcolor[rgb]{0.53,0.00,0.00}{##1}}}
+\@namedef{PYG@tok@nl}{\def\PYG@tc##1{\textcolor[rgb]{0.46,0.46,0.00}{##1}}}
+\@namedef{PYG@tok@ni}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.44,0.44,0.44}{##1}}}
+\@namedef{PYG@tok@na}{\def\PYG@tc##1{\textcolor[rgb]{0.41,0.47,0.13}{##1}}}
+\@namedef{PYG@tok@nt}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}}
+\@namedef{PYG@tok@nd}{\def\PYG@tc##1{\textcolor[rgb]{0.67,0.13,1.00}{##1}}}
+\@namedef{PYG@tok@s}{\def\PYG@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}}
+\@namedef{PYG@tok@sd}{\let\PYG@it=\textit\def\PYG@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}}
+\@namedef{PYG@tok@si}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.64,0.35,0.47}{##1}}}
+\@namedef{PYG@tok@se}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.67,0.36,0.12}{##1}}}
+\@namedef{PYG@tok@sr}{\def\PYG@tc##1{\textcolor[rgb]{0.64,0.35,0.47}{##1}}}
+\@namedef{PYG@tok@ss}{\def\PYG@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}}
+\@namedef{PYG@tok@sx}{\def\PYG@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}}
+\@namedef{PYG@tok@m}{\def\PYG@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}}
+\@namedef{PYG@tok@gh}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.00,0.00,0.50}{##1}}}
+\@namedef{PYG@tok@gu}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.50,0.00,0.50}{##1}}}
+\@namedef{PYG@tok@gd}{\def\PYG@tc##1{\textcolor[rgb]{0.63,0.00,0.00}{##1}}}
+\@namedef{PYG@tok@gi}{\def\PYG@tc##1{\textcolor[rgb]{0.00,0.52,0.00}{##1}}}
+\@namedef{PYG@tok@gr}{\def\PYG@tc##1{\textcolor[rgb]{0.89,0.00,0.00}{##1}}}
+\@namedef{PYG@tok@ge}{\let\PYG@it=\textit}
+\@namedef{PYG@tok@gs}{\let\PYG@bf=\textbf}
+\@namedef{PYG@tok@gp}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.00,0.00,0.50}{##1}}}
+\@namedef{PYG@tok@go}{\def\PYG@tc##1{\textcolor[rgb]{0.44,0.44,0.44}{##1}}}
+\@namedef{PYG@tok@gt}{\def\PYG@tc##1{\textcolor[rgb]{0.00,0.27,0.87}{##1}}}
+\@namedef{PYG@tok@err}{\def\PYG@bc##1{{\setlength{\fboxsep}{\string -\fboxrule}\fcolorbox[rgb]{1.00,0.00,0.00}{1,1,1}{\strut ##1}}}}
+\@namedef{PYG@tok@kc}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}}
+\@namedef{PYG@tok@kd}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}}
+\@namedef{PYG@tok@kn}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}}
+\@namedef{PYG@tok@kr}{\let\PYG@bf=\textbf\def\PYG@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}}
+\@namedef{PYG@tok@bp}{\def\PYG@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}}
+\@namedef{PYG@tok@fm}{\def\PYG@tc##1{\textcolor[rgb]{0.00,0.00,1.00}{##1}}}
+\@namedef{PYG@tok@vc}{\def\PYG@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}}
+\@namedef{PYG@tok@vg}{\def\PYG@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}}
+\@namedef{PYG@tok@vi}{\def\PYG@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}}
+\@namedef{PYG@tok@vm}{\def\PYG@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}}
+\@namedef{PYG@tok@sa}{\def\PYG@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}}
+\@namedef{PYG@tok@sb}{\def\PYG@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}}
+\@namedef{PYG@tok@sc}{\def\PYG@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}}
+\@namedef{PYG@tok@dl}{\def\PYG@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}}
+\@namedef{PYG@tok@s2}{\def\PYG@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}}
+\@namedef{PYG@tok@sh}{\def\PYG@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}}
+\@namedef{PYG@tok@s1}{\def\PYG@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}}
+\@namedef{PYG@tok@mb}{\def\PYG@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}}
+\@namedef{PYG@tok@mf}{\def\PYG@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}}
+\@namedef{PYG@tok@mh}{\def\PYG@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}}
+\@namedef{PYG@tok@mi}{\def\PYG@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}}
+\@namedef{PYG@tok@il}{\def\PYG@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}}
+\@namedef{PYG@tok@mo}{\def\PYG@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}}
+\@namedef{PYG@tok@ch}{\let\PYG@it=\textit\def\PYG@tc##1{\textcolor[rgb]{0.24,0.48,0.48}{##1}}}
+\@namedef{PYG@tok@cm}{\let\PYG@it=\textit\def\PYG@tc##1{\textcolor[rgb]{0.24,0.48,0.48}{##1}}}
+\@namedef{PYG@tok@cpf}{\let\PYG@it=\textit\def\PYG@tc##1{\textcolor[rgb]{0.24,0.48,0.48}{##1}}}
+\@namedef{PYG@tok@c1}{\let\PYG@it=\textit\def\PYG@tc##1{\textcolor[rgb]{0.24,0.48,0.48}{##1}}}
+\@namedef{PYG@tok@cs}{\let\PYG@it=\textit\def\PYG@tc##1{\textcolor[rgb]{0.24,0.48,0.48}{##1}}}
+
+\def\PYGZbs{\char`\\}
+\def\PYGZus{\char`\_}
+\def\PYGZob{\char`\{}
+\def\PYGZcb{\char`\}}
+\def\PYGZca{\char`\^}
+\def\PYGZam{\char`\&}
+\def\PYGZlt{\char`\<}
+\def\PYGZgt{\char`\>}
+\def\PYGZsh{\char`\#}
+\def\PYGZpc{\char`\%}
+\def\PYGZdl{\char`\$}
+\def\PYGZhy{\char`\-}
+\def\PYGZsq{\char`\'}
+\def\PYGZdq{\char`\"}
+\def\PYGZti{\char`\~}
+% for compatibility with earlier versions
+\def\PYGZat{@}
+\def\PYGZlb{[}
+\def\PYGZrb{]}
+\makeatother
+
diff --git a/examples/presentation/Latex/beamer_slider_preamble.tex b/examples/presentation/Latex/beamer_slider_preamble.tex
new file mode 100644
index 0000000000000000000000000000000000000000..02f19efc73e73bfd58d4c48a1651c90a36dc7746
--- /dev/null
+++ b/examples/presentation/Latex/beamer_slider_preamble.tex
@@ -0,0 +1,93 @@
+% WARNING! This file was automatically generated; see slider/DTU_Beamer_files for original version.
+\usepackage[T1]{fontenc}
+\usepackage[utf8]{inputenc}
+\usepackage[english]{babel}
+\usepackage{pgfplots}
+\pgfplotsset{compat=newest}
+\usepackage{booktabs}
+\usepackage{siunitx}
+
+\usepackage[inkscape=true,inkscapeformat=pdf,inkscapelatex=true]{svg}
+\svgpath{osvgs/}
+
+\usepackage{url}
+\usepackage{pmboxdraw}
+\usepackage{amssymb}
+\usepackage{pgffor}
+
+\usetheme[department=compute]{DTU}
+\newcommand{\tabitem}{{\color{dtured}$\bullet$} }
+\usepackage[absolute,overlay]{textpos}
+\textblockorigin{0mm}{0mm}
+
+\setlength{\TPHorizModule}{\paperwidth}
+\setlength{\TPVertModule}{\paperheight}
+
+% Latin Modern
+\usepackage{lmodern}
+\newcommand{\overlabel}[1]{ \begin{textblock}{1}(0,0) \url{#1} \end{textblock} }
+
+% Verdana font type
+%\usepackage{verdana}
+% Helvetica
+%\usepackage{helvet}
+% Times (text and math)
+%\usepackage{newtx, newtxmath}
+
+% \usetheme[department=compute]{DTU}
+
+\makeatletter
+
+\def\osvg{\@ifnextchar[{\@with}{\@without} }
+\def\@with[#1]#2{
+ \foreach[count=\n] \x in {#1}{
+ \iftoggle{overlabel_includesvgs}{
+ \IfFileExists{osvgs/x_do_not_edit_#2-l\n_nofonts.pdf}{
+ \begin{textblock}{1}(0,0)
+ \includegraphics<\x>[width=1.0\linewidth]{osvgs/x_do_not_edit_#2-l\n_nofonts}
+ \end{textblock}
+ }{ File: \url{osvgs/x_do_not_edit_#2-l\n_nofonts.pdf} does not exist; bad layer import? Check \url{osvgs/#2.svg} including layer information.
+ }
+ }
+ }
+ \olabel{#2}
+}
+\def\@without#1{
+ % Try to include first 10 layer files if they are there.
+ \foreach[count=\n] \x in {1,...,10}{
+ \iftoggle{overlabel_includesvgs}{
+ \IfFileExists{osvgs/x_do_not_edit_#1-l\n_nofonts.pdf}{
+ \begin{textblock}{1}(0,0)
+ \includegraphics<\n->[width=1.0\linewidth]{osvgs/x_do_not_edit_#1-l\n_nofonts}
+ \end{textblock}
+ }{
+ }
+ }
+ }
+ \olabel{#1}
+}
+\newcommand{\olabel}[1]{
+ \iftoggle{overlabel_includelabels}{
+ \begin{textblock}{1}(0,0) \url{#1} \end{textblock}
+ }{
+ \begin{textblock}{1}(0,0) {\color{white} \url{#1} } \end{textblock}
+ }
+}
+
+\makeatother
+
+\makeatother
+\ifdefined\bluem
+% nothing.
+\else
+
+\newcommand\bluem[1]{{\textcolor[rgb]{0.20, 0.40, 0.80}{ #1 }}}
+\newcommand\redm[1]{{\textcolor[rgb]{0.60, 0.00, 0.00}{ #1 }}}
+\newcommand\greenm[1]{{\textcolor[HTML]{398E00}{ #1 }}}
+\newcommand\yellowm[1]{{\textcolor[rgb]{1.00, 0.80, 0.00}{ #1 }}}
+
+\newcommand\bluet[1]{{\textcolor[rgb]{0.20, 0.40, 0.80}{\textbf{#1}}}}
+\newcommand\redt[1]{{\textcolor[rgb]{0.60, 0.00, 0.00}{\textbf{#1}}}}
+\newcommand\greent[1]{{\textcolor[HTML]{398E00}{\textbf{#1}}}}
+\newcommand\yellowt[1]{{\textcolor[rgb]{1.00, 0.80, 0.00}{\textbf{#1}}}}
+\fi
\ No newline at end of file
diff --git a/examples/presentation/Latex/beamercolorthemeDTU.sty b/examples/presentation/Latex/beamercolorthemeDTU.sty
new file mode 100644
index 0000000000000000000000000000000000000000..c16cc4968c266afd2ddb82305dc861dfb48960bc
--- /dev/null
+++ b/examples/presentation/Latex/beamercolorthemeDTU.sty
@@ -0,0 +1,29 @@
+% beamercolorthemeDTU.sty
+% This file is a part of the DTU beamer package and makes sure that
+% the DTU colours are available. This file does neither redefine
+% beamer settings, nor does it add new configurations. It has to be
+% maintained for backward compatibility.
+%
+% Changelog
+% 2011-06-23 jowr Replaced the old colour definitions with the new ones from the design guide
+% 2011-07-05 jowr Added alternative colours for the graphs
+% 2011-08-16 jowr Moved colour definitions to resources folder, also used in poster class
+% 2014-09-27 jowr Added documentation and prepared merge to git repository
+%
+%
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Load the file if it exists, throw a warning otherwise
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+\InputIfFileExists{dtucolours}{
+ \PackageInfo{dtubeamer}{Successfully loaded the DTU colours.}
+ }{
+ \PackageWarning{dtubeamer}{Could not load the colours from dtucolours.sty. This compilation is likely to fail.}
+ }%
+
+\mode<presentation>
+
+% The new design does not need any adaption here, black is
+% the default colour.
+
+\mode<all>
\ No newline at end of file
diff --git a/examples/presentation/Latex/beamerfontthemeDTU.sty b/examples/presentation/Latex/beamerfontthemeDTU.sty
new file mode 100644
index 0000000000000000000000000000000000000000..2030ae7eadb1a09a8d125e99c39bd487a1ca0992
--- /dev/null
+++ b/examples/presentation/Latex/beamerfontthemeDTU.sty
@@ -0,0 +1,38 @@
+% Copyright 2014 by Remus Mihail Prunescu
+
+% LaTeX Support Group 2014
+% DTU Official Presentation
+
+% For PDFLATEX
+\usefonttheme{professionalfonts}
+
+% Title font
+\setbeamerfont{title}{size=\large, series=\bfseries}
+\setbeamercolor{title}{fg=black}
+
+% Subtitle font
+\setbeamerfont{subtitle}{size=\small, series=\normalfont}
+
+% Author font
+\setbeamerfont{author}{size=\small, series=\normalfont}
+
+% Footline
+\setbeamerfont{framecounter in head/foot}{size=\tiny}
+\setbeamerfont{department in head/foot}{size=\tiny, series=\bfseries}
+\setbeamerfont{title in head/foot}{size=\tiny}
+\setbeamerfont{date in head/foot}{size=\tiny}
+
+% Frametitle
+\setbeamerfont{frametitle}{size=\large, series=\bfseries}
+\setbeamerfont{block body}{size=\small}
+\setbeamerfont{section title}{size=\small}
+\setbeamerfont{block body alerted}{size=\small}
+\setbeamerfont{block body example}{size=\small}
+\setbeamerfont{block title}{size=\large,parent={structure,block body}}
+\setbeamerfont{block title alerted}{parent={block title,alerted text}}
+\setbeamerfont{block title example}{parent={block title,example text}}
+\setbeamerfont{itemize/enumerate body}{size=\small}
+
+% Colors
+\setbeamercolor{frametitle}{fg=black}
+\setbeamercolor{structure}{fg=black}
\ No newline at end of file
diff --git a/examples/presentation/Latex/beamerinnerthemeDTU.sty b/examples/presentation/Latex/beamerinnerthemeDTU.sty
new file mode 100644
index 0000000000000000000000000000000000000000..4a2124bf35dac879a71851c642f01433b16c35d6
--- /dev/null
+++ b/examples/presentation/Latex/beamerinnerthemeDTU.sty
@@ -0,0 +1,52 @@
+% Copyright 2007 by Till Tantau
+% Copyright 2010 by Remus Mihail Prunescu
+
+% LaTeX Support Group 2010
+% DTU Official Presentation
+
+
+\mode<presentation>
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Title page: DTU
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+\defbeamertemplate*{title page}{DTU}[1][]
+{
+ % Set bInTitle to true to make sure the right footline is printed
+ \global\edef\bInTitle{true}
+
+ \linespread{1.45}
+ % Content of the title page
+
+ % Title + Subtitle
+ \vspace{\dimTitleOffset}
+ \begin{beamercolorbox}[left]{title box}
+ \usebeamerfont{title}\usebeamercolor[fg]{title}\inserttitle\par
+ \ifx\insertsubtitle\@empty
+ \else
+ \vspace{\dimSubtitleOffset}
+ {\usebeamerfont{subtitle}\usebeamercolor[fg]{subtitle}\insertsubtitle\par}
+ \fi
+ \end{beamercolorbox}
+
+ \vspace{\dimAuthorOffset}
+ % Author
+ \begin{beamercolorbox}[left]{author box}
+ \usebeamerfont{author}\usebeamercolor[fg]{author}\insertauthor
+ \end{beamercolorbox}
+
+ \vspace{\dimInstituteOffset}% Institute
+ \begin{beamercolorbox}[left]{institute box}
+ \usebeamerfont{institute}\usebeamercolor[fg]{author}\insertinstitute
+ \end{beamercolorbox}
+
+ % Title graphic
+ {\usebeamercolor[fg]{titlegraphic}\inserttitlegraphic\par}
+
+ % Fill the space till bottom
+ \vskip0pt plus 1filll
+}
+
+\mode
+<all>
diff --git a/examples/presentation/Latex/beamerouterthemeDTU.sty b/examples/presentation/Latex/beamerouterthemeDTU.sty
new file mode 100644
index 0000000000000000000000000000000000000000..8c8df22022457b287d7328894527deab5bc94d9e
--- /dev/null
+++ b/examples/presentation/Latex/beamerouterthemeDTU.sty
@@ -0,0 +1,98 @@
+% Copyright 2014 by Remus Mihail Prunescu
+
+% LaTeX Support Group 2014
+% DTU Official Presentation
+
+\mode<presentation>
+
+\setbeamercolor*{framecounter in head/foot}{parent=palette tertiary}
+\setbeamercolor*{department in head/foot}{parent=palette tertiary}
+\setbeamercolor*{title in head/foot}{parent=palette tertiary}
+\setbeamercolor*{date in head/foot}{parent=palette tertiary}
+
+% No navigation symbols
+\setbeamertemplate{navigation symbols}{}
+
+% Header
+\setbeamertemplate{headline}
+{
+ \ifdefstring{\bDTUWhiteFrame}{true}
+ {
+ \insertFrameDTUWhiteLogo
+ }
+ {
+ \ifdefstring{\bInTitle}{true}
+ {
+ \insertTitleDTULogo
+ }
+ {
+ \insertFrameDTULogo
+ }
+ }
+}
+
+% Footer
+\setbeamertemplate{footline}
+{
+ \ifdefstring{\bInTitle}{true}
+ {
+ \vspace{-0.35\paperheight}
+ \begin{beamercolorbox}[wd=\paperwidth]{title bottom}
+ \vbox{%
+ \makebox[0pt][l]{\hspace{\dimDTUDepLogoXOffset}\insertdepartmentlogoA}%
+ \vbox{%
+ \hspace{\dimDTUFriseXOffset}%
+ \makebox[0pt][l]{\insertDTUFrise}%
+ \vspace{\dimDTUDepFriseOffset}%
+ }%
+ }%
+ \vspace{\dimDTUFriseYOffset}
+ \end{beamercolorbox}
+ \global\def\bInTitle{false}
+ }
+ {
+ \ifdefstring{\bDTUWhiteFrame}{true}
+ {
+ }
+ { %
+ \hbox{ %
+ \hspace{\dimTextLeftMargin}\hspace{-1.5pt}\insertframenumber %
+ \setlength{\widthframenumber}{2em + \widthof{\insertframenumber}} %
+ \setlength{\widthdepartment}{1em + \widthof{\insertdepartmentandinstitute}} %
+ \setlength{\widthdate}{1em + \widthof{00 00000000 0000}} % Tue: Added extra 0's (2 to 7) to prevent wrap
+ \setlength{\widthtitle}{\textwidth-\widthframenumber-\widthdepartment-\widthdate-\dimTextLeftMargin-\dimTextLeftMargin} %
+ %\parbox[t]{\widthframenumber}{\insertframenumber} %
+ \parbox[t]{\widthdepartment}{\insertdepartmentandinstitute} %
+ \parbox[t]{\widthtitle}{\raggedleft\insertshorttitleinfooter} %
+ \parbox[t]{\widthdate}{\raggedleft\DTUDateFormat\insertdate} %
+ \vspace{\dimFootlineYOffset} %
+ }
+ }
+ }
+}
+
+% Position the frame title so that it would get into the headline
+\setbeamertemplate{frametitle}
+{
+ \vspace{\dimPlaceTitleInHeader}
+ \ifdefstring{\inShowSection}{true}
+ {
+ \usebeamerfont{section title}\color{black!20}%
+ \ifnumcomp{\thesection}{=}{0}{%
+ \ \par%
+ }
+ {%
+ \insertsection\par
+ }
+ }
+ {
+ \vspace{\dimFrameTitleOffset}
+ }
+ \vspace{-1pt}\usebeamerfont{frametitle}%
+ \ifdefstring{\bDTUWhiteFrame}{true}{\color{white}}{\color{black}}%
+ \insertframetitle
+ \vspace{\dimAfterFrameTitleOffset}
+}
+
+\mode
+<all>
diff --git a/examples/presentation/Latex/beamerthemeDTU.sty b/examples/presentation/Latex/beamerthemeDTU.sty
new file mode 100644
index 0000000000000000000000000000000000000000..bafcd2e2eecb98490ef826c7e2cee0b5103d5c7b
--- /dev/null
+++ b/examples/presentation/Latex/beamerthemeDTU.sty
@@ -0,0 +1,255 @@
+% Copyright Remus Mihail Prunescu
+
+% LaTeX Support Group
+% DTU Official Presentation
+
+\mode<presentation>
+
+\RequirePackage{etoolbox}
+\RequirePackage{datetime}
+\RequirePackage{keyval}
+\RequirePackage{calc}
+
+% Enlarge slide size
+\beamer@paperwidth 1.09375\beamer@paperwidth%
+\beamer@paperheight 1.09375\beamer@paperheight%
+
+% Extra package
+\InputIfFileExists{departments}%
+ {\ClassInfo{}{The file departments.tex with department logo file naming has been loaded.}}%
+ {\ClassInfo{}{The file departments.tex is missing. Consult the manual.}%
+}%
+
+% Default values for options
+\newcommand{\inDepartmentShortName}{elektro}
+\newcommand{\inLanguage}{english}
+\newcommand{\inShowSection}{true}
+
+% Check language
+\@ifpackagewith{babel}{danish}{%
+ \renewcommand{\inLanguage}{danish}%
+}{}
+
+
+% Save options
+\DeclareOptionBeamer{department}{\renewcommand{\inDepartmentShortName}{#1}}
+\DeclareOptionBeamer{showsection}{\renewcommand{\inShowSection}{#1}}
+\ProcessOptionsBeamer
+
+% % % % % % % % % % % %
+% Define Dimensions
+% % % % % % % % % % % %
+
+\newcommand{\dimDTULogoWidth}{0.0394\paperwidth} % Percent
+\newcommand{\dimDTULogoHeight}{0.0777\paperheight} % Percent
+\newcommand{\dimDTULogoYOffset}{0.0404\paperheight} % Percent
+\newcommand{\dimDTULogoXOffset}{0.9176\paperwidth} % Percent
+
+\newcommand{\dimDTUDepLogoXOffset}{0.062\paperwidth} % Percent
+\newcommand{\dimDTUDepLogoHeight}{0.0897\paperheight} % Percent
+
+\newcommand{\dimDTUFriseYOffset}{0.03\paperheight} % Percent
+\newcommand{\dimDTUFriseXOffset}{0.418\paperwidth} % Percent
+\newcommand{\dimDTUFriseHeight}{0.3412\paperheight} % Percent
+\newcommand{\dimDTUDepFriseOffset}{0.018\paperheight} % Percent
+
+\newcommand{\dimTitleOffset}{0.148\paperheight}
+\newcommand{\dimSubtitleOffset}{0.0175\paperheight}
+\newcommand{\dimFrameTitleOffset}{0.033\paperheight}
+\newcommand{\dimAfterFrameTitleOffset}{-0.008\paperheight}
+\newcommand{\dimAuthorOffset}{0.06\paperheight}
+\newcommand{\dimInstituteOffset}{0.027\paperheight}
+
+\newcommand{\dimFootlineYOffset}{0.025\paperheight} % Tue: This was 0.0355 in original file
+
+\newcommand{\dimLeftMarginI}{0.02\paperwidth}
+\newcommand{\dimTextLeftMargin}{0.0669\paperwidth} % Percent
+
+\newcommand{\dimPlaceTitleInHeader}{-0.09\paperheight}
+
+
+\makeatletter
+\setbeamersize{text margin left=\dimTextLeftMargin, text margin right=\dimTextLeftMargin}
+\makeatother
+
+% % % % % % % % % % % %
+% End of Dimensions
+% % % % % % % % % % % %
+
+% New commands to be used in the DTU template
+%\newcommand{\insertdepartmentandinstitute}{\departmenttitle , \institutetitle}
+\newcommand{\insertdepartmentandinstitute}{\departmenttitle}
+\newcommand{\insertDTULogo}{\includegraphics[width=\dimDTULogoWidth]{tex_dtu_logo}}
+\newcommand{\insertDTUWhiteLogo}{}
+\newcommand{\inserttitlefootline}{}
+\newcommand{\inserttitleheadline}{}
+\newcommand{\institutetitle}{}
+
+% Internal variable to check if \titlepage was called: false by default
+\def\bInTitle{false}
+\def\bDTUWhiteFrame{false}
+
+% Process language
+% Is it DK or UK?
+\ifdefstring{\inLanguage}{danish}
+{
+ \renewcommand{\institutetitle}{Danmarks Tekniske Universitet}
+ \renewcommand{\insertDTUWhiteLogo}{\includegraphics[height=\dimDTULogoHeight]{tex_dtu_dk_a1_neg}}
+}
+{
+ \ifdefstring{\inLanguage}{english}
+ {
+ \renewcommand{\institutetitle}{Technical University of Denmark}
+ \renewcommand{\insertDTUWhiteLogo}{\includegraphics[height=\dimDTULogoHeight]{tex_dtu_uk_a1_neg}}
+ }
+ {
+ % Undefined language
+ % Default values are used
+ }
+}
+
+\ifcsdef{department@\inDepartmentShortName}
+{
+ \activateDepartmentInfo{\inLanguage}{\inDepartmentShortName}
+}
+{
+ \PackageError{DTU Beamer Template}{Department is undefined. Reverting to default (elektro).}{Check the user guide for defined departments. If you cannot find it then contact support group to add the department.}
+ \activateDepartmentInfo{\inLanguage}{elektro}
+}
+
+% Command for generating the department title
+\newcommand{\departmenttitle}{\thedepartmentNameText}
+% Command for inserting the department logo
+\newcommand{\insertdepartmentlogoA}{%
+ \ifdefstring{\inDepartmentShortName}{admin}
+ {
+ }
+ {
+ \includegraphics[height=\dimDTUDepLogoHeight]{\thedepartmentLogo}
+ }
+}
+% Command for inserting frise
+\newcommand{\insertDTUFrise}{\includegraphics[height=\dimDTUFriseHeight]{\thedepartmentFrise}}
+
+% Command used from frame DTU logo (headline)
+\newcommand{\insertFrameDTULogo}
+{
+ \vspace{\dimDTULogoYOffset}
+ \begin{beamercolorbox}[right]{logo in head/foot}%
+ \insertDTULogo\makebox[\dimDTULogoWidth][]{}
+ \end{beamercolorbox}
+}
+\newcommand{\insertFrameDTUWhiteLogo}
+{
+ \vspace{\dimDTULogoYOffset}
+ \begin{beamercolorbox}[right]{logo in head/foot}%
+ \insertDTUWhiteLogo\makebox[\dimDTULogoWidth][]{}
+ \end{beamercolorbox}
+}
+
+% Command used in title page for inserting the DTU logo in headline
+\newcommand{\insertTitleDTULogo}
+{
+ \insertFrameDTULogo
+}
+
+% Change themes
+\usefonttheme{DTU}
+\useoutertheme{DTU}
+\useinnertheme{DTU}
+\usecolortheme{DTU}
+
+% Left margin for list environment
+\setlength{\leftmargini}{\dimLeftMarginI}
+
+% Adjust bullets placement
+\setlength\labelsep{3pt}
+
+\setbeamersize{text margin left=\dimTextLeftMargin}
+
+% Itemize
+\setbeamertemplate{items}[circle]
+\setbeamercolor{itemize item}{fg=dtured}
+\setbeamercolor{itemize subitem}{fg=dtured}
+
+\setbeamerfont{section in toc}{size=\small}
+\setbeamerfont{subsection in toc}{size=\scriptsize}
+
+\setbeamertemplate{enumerate items}[circle]
+\setbeamercolor{item projected}{fg=white,bg=dtured}
+
+% Table of contents
+\setbeamertemplate{section in toc}{%
+ \color{dtured}$\bullet$ \inserttocsection \par}
+
+\setbeamertemplate{subsection in toc}{
+ \hskip1em{\color{dtured}$\bullet$} \inserttocsubsection \par}
+
+% Fix space between sections and subsections in toc
+\makeatletter
+\patchcmd{\beamer@sectionintoc}
+ {\vfill}
+ {\vskip\itemsep}
+ {}
+ {}
+\pretocmd{\beamer@subsectionintoc}
+ {\vskip0.5\itemsep}
+ {}
+ {}
+\makeatother
+
+
+% Date format
+\newcommand{\DTUDateFormat}{\DTUDate}
+\newdateformat{DTUDate}{\THEDAY.\THEMONTH.\THEYEAR}
+
+% Customize blocks
+\setbeamertemplate{blocks}[rounded][shadow=true]
+\setbeamercolor{block title}{fg=white,bg=dtured}
+\setbeamerfont{block title}{series=\bfseries\small}
+\setbeamercolor{block body}{fg=black,bg=white}
+
+
+\newcommand{\defaultDTUFrameStyle}{
+ \setbeamertemplate{background}{}
+ \color{black}
+}
+
+% White DTU frame
+\makeatletter
+\define@key{beamerframe}{dtuwhitelogo}[true]{%
+ \global\def\bDTUWhiteFrame{true}
+ \color{white}
+}
+\define@key{beamerframe}{bgfilename}{%
+ \setbeamertemplate{background}{
+ \includegraphics[width=\paperwidth,height=\paperheight,keepaspectratio]{#1}
+ }
+}
+% Default framestyle
+\pretocmd{\beamer@@@@frame}
+{
+ \global\def\bDTUWhiteFrame{false}
+ \defaultDTUFrameStyle
+}
+{}{}
+\makeatother
+
+% Lengths for footer
+\newlength{\widthframenumber}
+\newlength{\widthdepartment}
+\newlength{\widthtitle}
+\newlength{\widthdate}
+
+% Short title for the footer
+\makeatletter
+\newcommand\insertshorttitleinfooter{%
+ \beamer@shorttitle%
+}
+\makeatother
+
+% Description list
+\setbeamercolor{description item}{fg=dtured}
+
+\mode
+<all>
diff --git a/examples/presentation/Latex/blank.png b/examples/presentation/Latex/blank.png
new file mode 100644
index 0000000000000000000000000000000000000000..082daebc2e8b00d950bcd22987c75a26f0349d97
Binary files /dev/null and b/examples/presentation/Latex/blank.png differ
diff --git a/examples/presentation/Latex/cache.pkl b/examples/presentation/Latex/cache.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..0534847cf170aac0da2695a4d5e55ae21c59acf5
Binary files /dev/null and b/examples/presentation/Latex/cache.pkl differ
diff --git a/examples/presentation/Latex/departments.tex b/examples/presentation/Latex/departments.tex
new file mode 100644
index 0000000000000000000000000000000000000000..09eb3308e6ba9389bb20dadfb8712873235c1c89
--- /dev/null
+++ b/examples/presentation/Latex/departments.tex
@@ -0,0 +1,130 @@
+% departments.tex
+% This file is a part of the DTU letter package and contains the file path for
+% the grahic file, and text name for the different departments.
+%
+% Changelog
+% 2010-04-07 Added % at the end of each line to make it possible to use the definitions in the documentation
+% 2010-04-09 Added the 5th mandatory argument (long text name)
+% 2010-04-23 Moved the new argument, #6, to #4 and added all info. However two graphic files are missing and I have therefore made a test: if the graphic file is missing the administration logo is used.
+% 2013-02-11 Added compute and diplom department entries. Added check to see that the department macros are defined, otherwise an error is printed.
+%
+%\makeDepartmentInfo{<danish|english>}{<departmentname>}{<text graphic file name>}{<Big department logo file name>}{<department text name>}{<department long text name>}
+%
+
+\RequirePackage{etoolbox}
+
+\newcommand\setDepartmentNameLogo[1]{\def\@departmentNameLogo{#1}}%
+\newcommand\thedepartmentNameLogo{\@departmentNameLogo}%
+\newcommand\setDepartmentNameText[1]{\def\@departmentNameText{#1}}%
+\newcommand\thedepartmentNameText{\@departmentNameText}%
+\newcommand\setDepartmentLongNameText[1]{\def\@departmentLongNameText{#1}}%
+\newcommand\thedepartmentLongNameText{\@departmentLongNameText}%
+\newcommand\setDepartmentLogo[1]{\def\@departmentLogo{#1}}%
+\newcommand\thedepartmentLogo{\@departmentLogo}%
+\newcommand\setDepartmentFrise[1]{\def\@departmentFrise{#1}}%
+\newcommand\thedepartmentFrise{\@departmentFrise}%
+%
+\newcommand\createDepartment[1]{%
+\expandafter\def\csname department@#1\endcsname{#1}}%
+%
+\newcommand\aliasDepartment[2]{%
+\expandafter\def\csname department@#2\endcsname{#1}}%
+%
+\ifundef{\makeDepartmentInfo}{%
+ \newcommand\makeDepartmentInfo[7]{%
+ \def\@departmentcmd{\csname department@#2\endcsname}
+ \createDepartment{#2}
+ \expandafter\def\csname namelogo#1@\@departmentcmd\endcsname{\setDepartmentNameLogo{#3}}%
+ \expandafter\def\csname deplogo#1@\@departmentcmd\endcsname{\setDepartmentLogo{#4}}%
+ \expandafter\def\csname depfrise#1@\@departmentcmd\endcsname{\setDepartmentFrise{#5}}%
+ \expandafter\def\csname nametext#1@\@departmentcmd\endcsname{\setDepartmentNameText{#6}}%
+ \expandafter\def\csname namelongtext#1@\@departmentcmd\endcsname{\setDepartmentLongNameText{#7}}%
+
+ }%
+}{}%
+%
+\newcommand\activateDepartmentInfo[2]{%
+ \ifcsname department@#2\endcsname%
+ \def\@departmentcmd{\csname department@#2\endcsname}%
+ \else%
+ \def\@departmentcmd{\department@admin}%
+ \fi%
+ \csname namelogo#1@\@departmentcmd\endcsname% TODO test if command exists before executing it
+ \csname nametext#1@\@departmentcmd\endcsname%
+ \csname namelongtext#1@\@departmentcmd\endcsname%
+ \csname deplogo#1@\@departmentcmd\endcsname%
+ \csname depfrise#1@\@departmentcmd\endcsname%
+ % \fromdepartment{\thedepartmentLongNameText}
+}%
+%
+\makeDepartmentInfo{danish} {aqua}{tex_aqua_dk}{tex_dtu_aqua_a}{tex_dtu_aqua_frise}{DTU Aqua}{Institut for Akvatiske Ressourcer}%
+\makeDepartmentInfo{english}{aqua}{tex_aqua_uk}{tex_dtu_aqua_a_uk}{tex_dtu_aqua_frise}{DTU Aqua}{National Institute of Aquatic Resources}%
+
+\makeDepartmentInfo{danish} {byg}{tex_byg_dk}{tex_dtu_byg_a}{tex_dtu_byg_frise}{DTU Byg}{Institut for Byggeri og Anl\ae g}%
+\makeDepartmentInfo{english}{byg}{tex_byg_uk}{tex_dtu_byg_a_uk}{tex_dtu_byg_frise}{DTU Civil Engineering}{Department of Civil Engineering}%
+
+\makeDepartmentInfo{danish}{compute}{tex_compute_uk}{tex_dtu_compute_a}{tex_dtu_frise}{DTU Compute}{Institut for Matematik og Computer Science}
+\makeDepartmentInfo{english}{compute}{tex_compute_uk}{tex_dtu_compute_a_uk}{tex_dtu_frise}{DTU Compute}{Department of Applied Mathematics and Computer Science}
+
+\makeDepartmentInfo{danish} {elektro}{tex_elektro_dk}{tex_dtu_elektro_a}{tex_dtu_frise}{DTU Elektro}{Institut for Elektroteknologi}
+\makeDepartmentInfo{english}{elektro}{tex_elektro_uk}{tex_dtu_elektro_a_uk}{tex_dtu_frise}{DTU Electrical Engineering}{Department of Electrical Engineering}
+
+\makeDepartmentInfo{danish} {energi}{tex_energikonvertering_dk}{tex_dtu_energi_a}{tex_dtu_energi_frise}{DTU Energi}{Institut for Energikonvertering og -lagring}
+\makeDepartmentInfo{english}{energi}{tex_energikonvertering_uk}{tex_dtu_energi_a_uk}{tex_dtu_energi_frise}{DTU Energy}{Department of Energy Conversion and Storage}
+
+\makeDepartmentInfo{danish} {fotonik}{tex_fotonik_dk}{tex_dtu_fotonik_a}{tex_dtu_frise}{DTU Fotonik}{Institut for Fotonik}
+\makeDepartmentInfo{english}{fotonik}{tex_fotonik_uk}{tex_dtu_fotonik_a_uk}{tex_dtu_frise}{DTU Fotonik}{Department of Photonics Engineering}
+
+\makeDepartmentInfo{danish} {fysik}{tex_fysik_dk}{tex_dtu_fysik_a}{tex_dtu_fysik_frise}{DTU Fysik}{Institut for Fysik}
+\makeDepartmentInfo{english}{fysik}{tex_fysik_uk}{tex_dtu_fysik_a_uk}{tex_dtu_fysik_frise}{DTU Physics}{Department of Physics}
+
+\makeDepartmentInfo{danish} {food}{tex_fodevareinstituttet_dk}{tex_dtu_fdevareinstituttet_a}{tex_dtu_frise}{DTU F\o devareinstituttet}{F\o devareinstituttet}
+\makeDepartmentInfo{english}{food}{tex_fodevareinstituttet_uk}{tex_dtu_fdevareinstituttet_a_uk}{tex_dtu_frise}{DTU Food}{National Food Institute}
+
+\makeDepartmentInfo{danish} {kemi}{tex_kemi_dk}{tex_dtu_kemi_a}{tex_dtu_kemi_frise}{DTU Kemi}{Institut for Kemi}
+\makeDepartmentInfo{english}{kemi}{tex_kemi_uk}{tex_dtu_kemi_a_uk}{tex_dtu_kemi_frise}{DTU Chemistry}{Department of Chemistry}
+
+\makeDepartmentInfo{danish} {kemiteknik}{tex_kemiteknik_dk}{tex_dtu_kemiteknik_a}{tex_dtu_kemiteknik_frise}{DTU Kemiteknik}{Institut for Kemiteknik}
+\makeDepartmentInfo{english}{kemiteknik}{tex_kemiteknik_uk}{tex_dtu_kemiteknik_a_uk}{tex_dtu_kemiteknik_frise}{DTU Chemical Engineering}{Department of Chemical and Biochemical Engineering}
+
+\makeDepartmentInfo{danish} {management}{tex_management_dk}{tex_dtu_management_a}{tex_dtu_frise}{DTU Management}{Institut for Systemer, Produktion og Ledelse}
+\makeDepartmentInfo{english}{management}{tex_management_uk}{tex_dtu_management_a_uk}{tex_dtu_frise}{DTU Management Engineering}{Department of Management Engineering}
+
+\makeDepartmentInfo{danish} {mekanik}{tex_mekanik_dk}{tex_dtu_mekanik_a}{tex_dtu_mek_frise}{DTU Mekanik}{Institut for Mekanisk Teknologi}
+\makeDepartmentInfo{english}{mekanik}{tex_mekanik_uk}{tex_dtu_mekanik_a_uk}{tex_dtu_mek_frise}{DTU Mechanical Engineering}{Department of Mechanical Engineering}
+
+\makeDepartmentInfo{danish} {miljo}{tex_miljo_dk}{tex_dtu_milj_a}{tex_dtu_miljoe_frise}{DTU Milj\o}{Institut for Vand og Milj\o teknologi}
+\makeDepartmentInfo{english}{environmentalEng}{tex_miljo_uk}{tex_dtu_milj_a_uk}{tex_dtu_miljoe_frise}{DTU Environment}{Department of Environmental Engineering}
+
+\makeDepartmentInfo{danish} {nanotek}{tex_nanotek_dk}{tex_dtu_nanotek_a}{tex_dtu_frise}{DTU Nanotek}{Institut for Mikro- og Nanoteknologi}
+\makeDepartmentInfo{english}{nanotek}{tex_nanotek_uk}{tex_dtu_nanotek_a_uk}{tex_dtu_frise}{DTU Nanotech}{Department of Micro- and Nanotechnology}
+
+\makeDepartmentInfo{danish} {space}{tex_space_dk}{tex_dtu_space_a}{tex_dtu_space_frise}{DTU Space}{Institut for Rumforskning og Rumteknologi}
+\makeDepartmentInfo{english}{space}{tex_space_uk}{tex_dtu_space_a_uk}{tex_dtu_space_frise}{DTU Space}{National Space Institute}
+
+\makeDepartmentInfo{danish} {systembiologi}{}{tex_dtu_systembiologi_a}{tex_dtu_frise}{DTU Systembiologi}{Institut for Systembiologi}
+\makeDepartmentInfo{english}{systembiologi}{}{tex_dtu_systembiologi_a_uk}{tex_dtu_frise}{DTU Systems Biology}{Department of Systems Biology}
+
+\makeDepartmentInfo{danish} {transport}{tex_transport_dk}{tex_dtu_transport_a}{tex_dtu_transport_frise}{DTU Transport}{Institut for Transport}
+\makeDepartmentInfo{english}{transport}{tex_transport_uk}{tex_dtu_transport_a_uk}{tex_dtu_transport_frise}{DTU Transport}{Department of Transport}
+
+\makeDepartmentInfo{danish} {vaterinaerinstituttet}{tex_veterinaertinstituttet_dk}{tex_dtu_veterinerinstituttet_a}{tex_dtu_vet_frise}{DTU Veterin\ae rinstituttet}{Veterin\ae rinstituttet}
+\makeDepartmentInfo{english}{vaterinaerinstituttet}{tex_veterinaertinstituttet_uk}{tex_dtu_veterinerinstituttet_a_uk}{tex_dtu_vet_frise}{DTU Vet}{National Veterinary Institute}
+
+\makeDepartmentInfo{danish} {vindenergi}{tex_vindenergi_dk}{tex_dtu_vindenergi_a}{tex_dtu_vindenergi_frise}{DTU Vindenergi}{Institut for Vindenergi}
+\makeDepartmentInfo{english}{vindenergi}{tex_vindenergi_uk}{tex_dtu_vindenergi_a_uk}{tex_dtu_vindenergi_frise}{DTU Wind Energy}{Department of Wind Energy}
+
+
+% Extra
+\makeDepartmentInfo{danish} {bibliotek}{tex_bibliotek_dk}{tex_dtu_bibliotek_a}{tex_dtu_bibliotek_frise}{DTU Bibliotek}{Danmarks Tekniske Informationcenter}%
+\makeDepartmentInfo{english}{bibliotek}{tex_bibliotek_uk}{tex_dtu_bibliotek_uk_a}{tex_dtu_bibliotek_frise}{DTU Library}{Technical Information Center of Denmark}%
+
+\makeDepartmentInfo{danish} {admin}{tex_dtu_navn_dk}{}{tex_dtu_frise}{Danmarks Tekniske Universitet}{}%
+\makeDepartmentInfo{english}{admin}{tex_dtu_navn_uk}{}{tex_dtu_frise}{Technical University of Denmark}{}%
+
+\makeDepartmentInfo{danish} {riso}{tex_riso_dk}{tex_ris_dtu_a}{tex_dtu_frise}{Ris\o\ DTU}{Nationallaboratoriet for B\ae redygtig Energi}
+\makeDepartmentInfo{english}{riso}{tex_riso_uk}{tex_ris_dtu_a_uk}{tex_dtu_frise}{Ris\o\ DTU}{National Laboratory for Sustainable Energy}
+
+\makeDepartmentInfo{danish}{diplom}{tex_diplom_dk}{tex_dtu_diplom_a}{tex_dtu_frise}{Center for Diplomingeni\o ruddannelse}{DTU Diplom}
+\makeDepartmentInfo{english}{diplom}{tex_diplom_dk}{tex_dtu_diplom_a_uk}{tex_dtu_frise}{Center for Diplomingeni\o ruddannelse}{DTU Diplom}
+
diff --git a/examples/presentation/Latex/dtucolours.tex b/examples/presentation/Latex/dtucolours.tex
new file mode 100644
index 0000000000000000000000000000000000000000..731dcb44b697f7d88b6a1356886a33470bd4e3ae
--- /dev/null
+++ b/examples/presentation/Latex/dtucolours.tex
@@ -0,0 +1,83 @@
+% dtucolours.sty
+% This file has been a part of the DTU beamer package and is now
+% moved to the resources folder because there are other parts of the
+% DTU package that need the colours as well.
+%
+% Changelog
+% 2011-06-23 jowr Replaced the old colour definitions with the new ones from the design guide
+% 2011-07-05 jowr Added alternative colours for the graphs
+% 2011-08-16 jowr Moved colour definitions to resources folder, also used in poster class
+% 2012-06-19 jowr Added colours for cooperation with IPU
+% 2014-09-27 jowr Replaced definecolor with providecolor, do not overwrite custom colour definitions
+%
+%
+\RequirePackage{xcolor}
+%
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Define primary colours (designguide v2.3, page 13)
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\providecolor{dtured} {rgb}{0.60, 0.00, 0.00} % Primærfarve 1 - CMYK: 0/ 91/ 72/ 23 - RGB: 153/ 0/ 0
+\providecolor{dtugrey} {rgb}{0.60, 0.60, 0.60} % Primærfarve 2 - CMYK: 0/ 0/ 0/ 56 - RGB: 153/153/153
+%
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Define secondary colours (designguide v2.3, page 13)
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Please note that dtured and dtubrown have the same rgb and hex values and only differ in cmyk and pms notation.
+\providecolor{dtuyellow} {rgb}{1.00, 0.80, 0.00} % Sekundærfarve 12 - CMYK: 0/ 25/100/ 0 - RGB: 255/204/ 0 - HEX: FFCC00
+\providecolor{dtuorange} {rgb}{1.00, 0.60, 0.00} % Sekundærfarve 1 - CMYK: 0/ 50/100/ 0 - RGB: 255/153/ 0 - HEX: FF9900
+\providecolor{dtulightred} {rgb}{1.00, 0.00, 0.00} % Sekundærfarve 3 - CMYK: 0/100/100/ 0 - RGB: 255/ 0/ 0 - HEX: FF0000
+\providecolor{dtubrown} {rgb}{0.60, 0.00, 0.00} % Sekundærfarve 4 - CMYK: 0/100/100/ 50 - RGB: 153/ 0/ 0 - HEX: 990000
+\providecolor{dtupurple} {rgb}{0.80, 0.20, 0.60} % Sekundærfarve 6 - CMYK: 25/100/ 0/ 0 - RGB: 204/ 51/153 - HEX: CC3399
+\providecolor{dtuviolet} {rgb}{0.40, 0.00, 0.60} % Sekundærfarve 9 - CMYK: 75/ 75/ 0/ 0 - RGB: 102/ 0/153 - HEX: 660099
+\providecolor{dtudarkblue} {rgb}{0.20, 0.40, 0.80} % Sekundærfarve 13 - CMYK: 75/ 50/ 0/ 0 - RGB: 51/102/204 - HEX: 3366CC
+\providecolor{dtulightblue} {rgb}{0.20, 0.80, 1.00} % Sekundærfarve 10 - CMYK: 50/ 0/ 0/ 0 - RGB: 51/204/255 - HEX: 33CCFF
+\providecolor{dtulightgreen}{rgb}{0.60, 0.80, 0.20} % Sekundærfarve 11 - CMYK: 25/ 0/100/ 0 - RGB: 153/204/ 51 - HEX: 99CC33
+\providecolor{dtudarkgreen} {rgb}{0.40, 0.80, 0.00} % Sekundærfarve 14 - CMYK: 50/ 0/100/ 0 - RGB: 102/204/ 0 - HEX: 66CC00
+\providecolor{dtucoolgrey} {rgb}{0.59, 0.58, 0.57} % Farve til poster - CMYK: 0/ 1/ 5/ 39 - RGB: 150/148/145 - HEX: 969491
+%
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Define colours for drawings and graphs (designguide v2.3, page 14)
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\providecolor{graph01}{named}{dtuorange}
+\providecolor{graph02}{named}{dtupurple}
+\providecolor{graph03}{named}{dtulightblue}
+\providecolor{graph04}{named}{dtubrown}
+%
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Define alternate colours for drawings and graphs
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Define alternate colours for graphs, which are compatible with black
+% and white printers. The initial set of colours makes it hard to distinguish
+% between the two lighter and the two darker colours.
+\providecolor{graph01alt}{named}{dtuviolet}
+\providecolor{graph02alt}{named}{dtuyellow}
+\providecolor{graph03alt}{named}{dtulightred}
+\providecolor{graph04alt}{named}{dtulightgreen}
+\providecolor{graph05alt}{named}{dtugrey}
+%
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Define colours for IPU related documents, from IPU Designguide (16.09.2008)
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\providecolor{ipugreen} {rgb}{0.00, 0.40, 0.20} % Dark green, 1st standard colour - CMYK: 088/000/095/026 - RGB: 000/102/051
+\providecolor{ipugrey} {rgb}{0.45, 0.47, 0.49} % Dark grey, 2nd standard colour - CMYK: 015/000/000/075 - RGB: 114/121/126
+\providecolor{ipulightgreen}{rgb}{0.36, 0.67, 0.15} % Light green, 1sr secondary colour - CMYK: 070/000/100/000 - RGB: 091/172/038
+\providecolor{ipulightgrey} {rgb}{0.85, 0.86, 0.87} % Light grey, 2nd secondary colour - CMYK: 003/000/003/020 - RGB: 217/220/222
+%
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Old definitions
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% \providecolor{dtured} {cmyk}{0.00, 0.95, 0.72, 0.27}
+% \providecolor{dtudarkgray} {cmyk}{0.00, 0.00, 0.00, 0.56}
+% \providecolor{dtugray} {cmyk}{0.00, 0.00, 0.00, 0.37}
+% \providecolor{dtulightgray} {cmyk}{0.00, 0.00, 0.00, 0.19}
+% \providecolor{dtudarkblue} {cmyk}{1.00, 0.72, 0.00, 0.38}
+% \providecolor{dtublue} {cmyk}{0.60, 0.44, 0.00, 0.24}
+% \providecolor{dtulightblue} {cmyk}{0.30, 0.22, 0.00, 0.12}
+% \providecolor{dtudarkgreen} {cmyk}{1.00, 0.00, 0.83, 0.47}
+% \providecolor{dtugreen} {cmyk}{0.725,0.004,1.00, 0.004}
+% \providecolor{dtuyellow} {cmyk}{0.00, 0.00, 1.00, 0.00}
+% \providecolor{dtuorange} {cmyk}{0.00, 0.34, 0.91, 0.00}
+% \providecolor{dtudarkorange}{cmyk}{0.00, 0.51, 1.00, 0.00}
+% \providecolor{dtupurpur} {cmyk}{0.00, 0.94, 0.00, 0.43}
+% \providecolor{dtupurple} {cmyk}{0.83, 1.00, 0.00, 0.23}
+%
diff --git a/examples/presentation/Latex/index.aux b/examples/presentation/Latex/index.aux
index f23ca482232de422e9ae244e1c40e1cecbac91fc..41bba04d4dae45f225b74df5ba59d27d460cc845 100644
--- a/examples/presentation/Latex/index.aux
+++ b/examples/presentation/Latex/index.aux
@@ -24,19 +24,20 @@
\@writefile{toc}{\contentsline {section}{\numberline {1}Working with fractions (\texttt {fractions.py})}{1}{section.1}\protected@file@percent }
\newlabel{fractions}{{1}{1}{Working with fractions (\texttt {fractions.py})}{section.1}{}}
\newlabel{fractions@cref}{{[section][1][]1}{[1][1][]1}}
+\citation{bertsekasII}
\bibstyle{alpha}
\bibdata{pensum}
\gdef\minted@oldcachelist{,
default.pygstyle,
- C337567ABBC0041A183DD819B579D62B0A1306BEF7ABBA8E6F738A7935C17A00.pygtex,
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C30DBA8197A1560649606EA4745E9D048B9AA2C25CD7E542150F54FA151BF004.pygtex,
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+ F83721D063149FE208A44C60DB48484B81B27360F55ECAEF0E03CEF63D4338FD.pygtex,
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+ 00E2E804F1FA397D97A5909ABF9BDD7D56A75F0008C42025054395883EB49E2F.pygtex,
+ 38AB66A1F480DA59292A05C9BDF935696F77AD3888A7BF17566D124427769365.pygtex}
\newlabel{eq:fraction}{{1}{2}{Working with fractions (\texttt {fractions.py})}{equation.1.1}{}}
\newlabel{eq:fraction@cref}{{[equation][1][]1}{[1][2][]2}}
\gdef\svg@ink@ver@settings{{\m@ne }{inkscape}{1}}
diff --git a/examples/presentation/Latex/index.pdf b/examples/presentation/Latex/index.pdf
index 0a1c5ccd718870ca4501b780ebef55dd61b165b2..0f65bca4c0664df6446518c283b69c5166c61e94 100644
Binary files a/examples/presentation/Latex/index.pdf and b/examples/presentation/Latex/index.pdf differ
diff --git a/examples/presentation/Latex/index.synctex.gz b/examples/presentation/Latex/index.synctex.gz
deleted file mode 100644
index 08e39c4630eac66987ea8bd6fffdbfb957e68474..0000000000000000000000000000000000000000
Binary files a/examples/presentation/Latex/index.synctex.gz and /dev/null differ
diff --git a/examples/presentation/Latex/index.tex b/examples/presentation/Latex/index.tex
index 86f18fa742605fdbe2db55c432ec66071bbb4cc2..2cc306127e6e2e3678d9622b4eab2063b532c4a4 100644
--- a/examples/presentation/Latex/index.tex
+++ b/examples/presentation/Latex/index.tex
@@ -67,53 +67,6 @@
\usepackage{xr-hyper}
\usepackage{hyperref}
-%\IfFileExists{../../../../Lectures/Lecture_1/Latex/Lecture_1.aux}{
-% \externaldocument[l1]{../../../../Lectures/Lecture_1/Latex/Lecture_1}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_2/Latex/Lecture_2.aux}{
-% \externaldocument[l2]{../../../../Lectures/Lecture_2/Latex/Lecture_2}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_3/Latex/Lecture_3.aux}{
-% \externaldocument[l3]{../../../../Lectures/Lecture_3/Latex/Lecture_3}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_4/Latex/Lecture_4.aux}{
-% \externaldocument[l4]{../../../../Lectures/Lecture_4/Latex/Lecture_4}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_5/Latex/Lecture_5.aux}{
-% \externaldocument[l5]{../../../../Lectures/Lecture_5/Latex/Lecture_5}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_6/Latex/Lecture_6.aux}{
-% \externaldocument[l6]{../../../../Lectures/Lecture_6/Latex/Lecture_6}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_7/Latex/Lecture_7.aux}{
-% \externaldocument[l7]{../../../../Lectures/Lecture_7/Latex/Lecture_7}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_8/Latex/Lecture_8.aux}{
-% \externaldocument[l8]{../../../../Lectures/Lecture_8/Latex/Lecture_8}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_9/Latex/Lecture_9.aux}{
-% \externaldocument[l9]{../../../../Lectures/Lecture_9/Latex/Lecture_9}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_10/Latex/Lecture_10.aux}{
-% \externaldocument[l10]{../../../../Lectures/Lecture_10/Latex/Lecture_10}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_11/Latex/Lecture_11.aux}{
-% \externaldocument[l11]{../../../../Lectures/Lecture_11/Latex/Lecture_11}
-% }
-%
-%\IfFileExists{../../../../Lectures/Lecture_12/Latex/Lecture_12.aux}{
-% \externaldocument[l12]{../../../../Lectures/Lecture_12/Latex/Lecture_12}
-% }
@@ -145,7 +98,7 @@ When done, you should be able to create two fractions objects and add them using
This fragment will produce the terminal output:
\inputminted{text}{output/fractions_a.txt}
-You may find it convenient to use the formula:
+You may find it convenient to use the formula (see \cite{bertsekasII}):
\begin{align}
\frac{a}{b} + \frac{n}{m} = \frac{am + bn}{bm} \label{eq:fraction}
\end{align}
diff --git a/examples/presentation/Latex/index_NO_SVGS.aux b/examples/presentation/Latex/index_NO_SVGS.aux
new file mode 100644
index 0000000000000000000000000000000000000000..2c0cfe693508aa53049858a965d2ed3649d159d8
--- /dev/null
+++ b/examples/presentation/Latex/index_NO_SVGS.aux
@@ -0,0 +1,45 @@
+\relax
+\providecommand\hyper@newdestlabel[2]{}
+\providecommand\zref@newlabel[2]{}
+\providecommand{\transparent@use}[1]{}
+\providecommand\HyperFirstAtBeginDocument{\AtBeginDocument}
+\HyperFirstAtBeginDocument{\ifx\hyper@anchor\@undefined
+\global\let\oldcontentsline\contentsline
+\gdef\contentsline#1#2#3#4{\oldcontentsline{#1}{#2}{#3}}
+\global\let\oldnewlabel\newlabel
+\gdef\newlabel#1#2{\newlabelxx{#1}#2}
+\gdef\newlabelxx#1#2#3#4#5#6{\oldnewlabel{#1}{{#2}{#3}}}
+\AtEndDocument{\ifx\hyper@anchor\@undefined
+\let\contentsline\oldcontentsline
+\let\newlabel\oldnewlabel
+\fi}
+\fi}
+\global\let\hyper@last\relax
+\gdef\HyperFirstAtBeginDocument#1{#1}
+\providecommand\HyField@AuxAddToFields[1]{}
+\providecommand\HyField@AuxAddToCoFields[2]{}
+\providecommand\babel@aux[2]{}
+\@nameuse{bbl@beforestart}
+\babel@aux{english}{}
+\@writefile{toc}{\contentsline {section}{\numberline {1}Working with fractions (\texttt {fractions.py})}{1}{section.1}\protected@file@percent }
+\newlabel{fractions}{{1}{1}{Working with fractions (\texttt {fractions.py})}{section.1}{}}
+\newlabel{fractions@cref}{{[section][1][]1}{[1][1][]1}}
+\citation{bertsekasII}
+\bibstyle{alpha}
+\bibdata{pensum}
+\bibcite{bertsekasII}{Ber07}
+\gdef\minted@oldcachelist{,
+ default.pygstyle,
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+\newlabel{eq:fraction}{{1}{2}{Working with fractions (\texttt {fractions.py})}{equation.1.1}{}}
+\newlabel{eq:fraction@cref}{{[equation][1][]1}{[1][2][]2}}
+\gdef\svg@ink@ver@settings{{\m@ne }{inkscape}{1}}
+\gdef \@abspage@last{2}
diff --git a/examples/presentation/Latex/index_NO_SVGS.bbl b/examples/presentation/Latex/index_NO_SVGS.bbl
new file mode 100644
index 0000000000000000000000000000000000000000..d93cf0c188fcb4d97f975900dce6ab1bf5da2e73
--- /dev/null
+++ b/examples/presentation/Latex/index_NO_SVGS.bbl
@@ -0,0 +1,8 @@
+\begin{thebibliography}{Ber07}
+
+\bibitem[Ber07]{bertsekasII}
+Dimitri~P. Bertsekas.
+\newblock {\em Dynamic Programming and Optimal Control, Vol. II}.
+\newblock Athena Scientific, 3rd edition, 2007.
+
+\end{thebibliography}
diff --git a/examples/presentation/Latex/index_NO_SVGS.blg b/examples/presentation/Latex/index_NO_SVGS.blg
new file mode 100644
index 0000000000000000000000000000000000000000..7e6025af9c8e5fc2bc1cc5be9e7db299202621ca
--- /dev/null
+++ b/examples/presentation/Latex/index_NO_SVGS.blg
@@ -0,0 +1,46 @@
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new file mode 100644
index 0000000000000000000000000000000000000000..867d4260aa9819f51beb0e795c5f1d17b12fc3f9
--- /dev/null
+++ b/examples/presentation/Latex/index_NO_SVGS.fdb_latexmk
@@ -0,0 +1,316 @@
+# Fdb version 3
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+ "index_NO_SVGS.aux" 1667743448 2146 2f14c320e0217602459f0ff3726777df "pdflatex"
+ "pensum.bib" 1661518257 10852 bff544e86de004b5310c58ba5280fa2c ""
+ (generated)
+ "index_NO_SVGS.bbl"
+ "index_NO_SVGS.blg"
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+INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/latex-fonts/lasy8.tfm
+OUTPUT index_NO_SVGS.pyg
+INPUT ./index_NO_SVGS.pyg
+INPUT ./_minted-index_NO_SVGS/BCD13D83EF8F0B75CF4482552AC78D62DB5D774133F9C0C976BBAEB4EA3883A3.pygtex
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+INPUT _minted-index_NO_SVGS/BCD13D83EF8F0B75CF4482552AC78D62DB5D774133F9C0C976BBAEB4EA3883A3.pygtex
+INPUT ./_minted-index_NO_SVGS/BCD13D83EF8F0B75CF4482552AC78D62DB5D774133F9C0C976BBAEB4EA3883A3.pygtex
+INPUT _minted-index_NO_SVGS/BCD13D83EF8F0B75CF4482552AC78D62DB5D774133F9C0C976BBAEB4EA3883A3.pygtex
+INPUT ./_minted-index_NO_SVGS/BCD13D83EF8F0B75CF4482552AC78D62DB5D774133F9C0C976BBAEB4EA3883A3.pygtex
+INPUT _minted-index_NO_SVGS/BCD13D83EF8F0B75CF4482552AC78D62DB5D774133F9C0C976BBAEB4EA3883A3.pygtex
+INPUT ./output/fractions_b.py
+INPUT ./_minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex
+INPUT _minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex
+INPUT ./_minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex
+INPUT _minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex
+INPUT ./_minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex
+INPUT _minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex
+INPUT ./_minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex
+INPUT _minted-index_NO_SVGS/FEF03B3FE84AFC5182847D2D4A3A88C5CE8B8F87FE714DA0E730CFF193541D4B.pygtex
+INPUT ./output/fractions_b.txt
+INPUT ./_minted-index_NO_SVGS/00E2E804F1FA397D97A5909ABF9BDD7D274B6DF28E9ED4D1CDE2393BF3DE3CC8.pygtex
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+INPUT ./_minted-index_NO_SVGS/00E2E804F1FA397D97A5909ABF9BDD7D274B6DF28E9ED4D1CDE2393BF3DE3CC8.pygtex
+INPUT _minted-index_NO_SVGS/00E2E804F1FA397D97A5909ABF9BDD7D274B6DF28E9ED4D1CDE2393BF3DE3CC8.pygtex
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+INPUT _minted-index_NO_SVGS/00E2E804F1FA397D97A5909ABF9BDD7D274B6DF28E9ED4D1CDE2393BF3DE3CC8.pygtex
+INPUT ./_minted-index_NO_SVGS/00E2E804F1FA397D97A5909ABF9BDD7D274B6DF28E9ED4D1CDE2393BF3DE3CC8.pygtex
+INPUT _minted-index_NO_SVGS/00E2E804F1FA397D97A5909ABF9BDD7D274B6DF28E9ED4D1CDE2393BF3DE3CC8.pygtex
+INPUT ./output/fragment.shell
+INPUT ./_minted-index_NO_SVGS/38AB66A1F480DA59292A05C9BDF93569802345CC0D356389FD291DC86A2BB929.pygtex
+INPUT _minted-index_NO_SVGS/38AB66A1F480DA59292A05C9BDF93569802345CC0D356389FD291DC86A2BB929.pygtex
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+INPUT ./_minted-index_NO_SVGS/38AB66A1F480DA59292A05C9BDF93569802345CC0D356389FD291DC86A2BB929.pygtex
+INPUT _minted-index_NO_SVGS/38AB66A1F480DA59292A05C9BDF93569802345CC0D356389FD291DC86A2BB929.pygtex
+INPUT ./index_NO_SVGS.bbl
+INPUT index_NO_SVGS.bbl
+INPUT ./index_NO_SVGS.bbl
+INPUT index_NO_SVGS.bbl
+INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/xcharter/XCharter-Italic-tlf-t1.tfm
+INPUT /usr/share/texlive/texmf-dist/fonts/vf/public/xcharter/XCharter-Italic-tlf-t1.vf
+INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/xcharter/XCharter-Italic-tlf-t1--base.tfm
+INPUT index_NO_SVGS.aux
+INPUT ./index_NO_SVGS.out
+INPUT ./index_NO_SVGS.out
+INPUT ./index_NO_SVGS.pyg
+INPUT index_NO_SVGS.pyg
+INPUT /usr/share/texlive/texmf-dist/fonts/enc/dvips/xcharter/xch_rydp4l.enc
+INPUT /home/tuhe/.texlive2021/texmf-var/fonts/pk/ljfour/jknappen/ec/tcit1000.600pk
+INPUT /home/tuhe/.texlive2021/texmf-var/fonts/pk/ljfour/jknappen/ec/ectt1000.600pk
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+INPUT /home/tuhe/.texlive2021/texmf-var/fonts/pk/ljfour/jknappen/ec/ectt1440.600pk
+INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/xcharter/XCharter-Bold.pfb
+INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/xcharter/XCharter-Italic.pfb
+INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/xcharter/XCharter-Roman.pfb
+INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmmi12.pfb
+INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmmi6.pfb
+INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr12.pfb
+INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmsy6.pfb
diff --git a/examples/presentation/Latex/index_NO_SVGS.out b/examples/presentation/Latex/index_NO_SVGS.out
new file mode 100644
index 0000000000000000000000000000000000000000..975b635f770a49d8106292563c5b0bc731738dfd
--- /dev/null
+++ b/examples/presentation/Latex/index_NO_SVGS.out
@@ -0,0 +1 @@
+\BOOKMARK [1][-]{section.1}{\376\377\000W\000o\000r\000k\000i\000n\000g\000\040\000w\000i\000t\000h\000\040\000f\000r\000a\000c\000t\000i\000o\000n\000s\000\040\000\050\000f\000r\000a\000c\000t\000i\000o\000n\000s\000.\000p\000y\000\051}{}% 1
diff --git a/examples/presentation/Latex/index_NO_SVGS.pdf b/examples/presentation/Latex/index_NO_SVGS.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..b8e7b2cf52218281c19664d45f506c2635358436
Binary files /dev/null and b/examples/presentation/Latex/index_NO_SVGS.pdf differ
diff --git a/examples/presentation/Latex/index_NO_SVGS.tex b/examples/presentation/Latex/index_NO_SVGS.tex
new file mode 100644
index 0000000000000000000000000000000000000000..ecb57f364a93951a3712daed8224182fa7ae1e30
--- /dev/null
+++ b/examples/presentation/Latex/index_NO_SVGS.tex
@@ -0,0 +1,127 @@
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% DO NOT EDIT THIS FILE. IT WILL BE AUTOMATICALLY OVERWRITTEN
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+
+% TeX-command-extra-options: "-shell-escape"
+
+
+\documentclass[handout,12pt,twoside]{article}
+\usepackage[table]{xcolor} % important to avoid options clash.
+%\input{book_preamble}
+\input{02465shared_preamble}
+\usepackage{cleveref}
+\input{structure.tex}
+\usepackage{url}
+\usepackage{graphics}
+%\usepackage{fancybox}
+\usepackage{multicol}
+\usepackage{rotate}
+%\usepackage{epsf}
+\usepackage{rotating}
+%\usepackage{color}
+\usepackage{booktabs}
+\usepackage{hyperref}
+\usepackage{pifont}
+\usepackage{latexsym}
+\usepackage[english]{babel}
+\usepackage{epstopdf}
+\usepackage{etoolbox}
+%\usepackage{epsfig}
+\usepackage{amsmath}
+\usepackage{amssymb}
+\usepackage{multirow,epstopdf}
+%\usepackage{cite}
+\usepackage{fancyhdr}
+\usepackage{booktabs}
+%\usepackage[most]{tcolorbox}
+\definecolor{LightGray}{HTML}{EEEEEE}
+
+\usepackage{todonotes}
+\pagestyle{fancy}
+\usepackage{minted}
+%\usepackage{natbib}
+%\bibliographystyle{unsrtnat}
+
+\usepackage[inkscape=true,inkscapeformat=pdf,inkscapelatex=true]{svg}
+\svgpath{./}
+
+%\usepackage{xr}
+
+
+ % problem when citing sutton. I got no idea why.
+%\externaldocument{ ../../../Notes/Latex/02465_Notes}
+
+
+\setminted{
+ frame=lines,
+ framesep=2mm,
+ baselinestretch=1.2,
+ bgcolor=LightGray,
+ fontsize=\footnotesize,
+ linenos
+}
+%\newcommand*\lref[2]{lecture~#1~eq.~(\ref{l#1#2})}
+%\newcommand*\nref[1]{\cite[\cref{#1}]{herlau}}
+
+\usepackage{xr-hyper}
+\usepackage{hyperref}
+
+
+
+
+
+
+\fancyhf{}
+
+\lhead{ Unitgrade }
+
+
+ \rhead{ \today } %
+\title{ Examples }
+ \author{Tue Herlau\\ \texttt{tuhe@dtu.dk} } % Author name and email address
+
+%\date{University of Inaba --- \today} % University, school and/or
+
+
+ \togglefalse{overlabel_includesvgs}
+\toggletrue{overlabel_includelabels}
+
+\begin{document}
+ \maketitle
+
+
+\section{Working with fractions (\texttt{fractions.py})} \label{fractions}
+In this problem, you have to implement the methods in the following class:
+\inputminted{python}{output/fractions.py}
+
+When done, you should be able to create two fractions objects and add them using the \pyi{+}-operator, which will be transformed to a call of the form \pyi{f1.__add__(f2)} as so:
+\inputminted{python}{output/fractions_a.py}
+
+This fragment will produce the terminal output:
+\inputminted{text}{output/fractions_a.txt}
+
+You may find it convenient to use the formula (see \cite{bertsekasII}):
+\begin{align}
+\frac{a}{b} + \frac{n}{m} = \frac{am + bn}{bm} \label{eq:fraction}
+\end{align}
+%\input{project_body}
+
+When done, implement the \pyi{from_string} function, that can simplify string expressions to fractions:
+
+\inputminted{python}{output/fractions_b.py}
+This fragment will produce the following terminal output:
+\inputminted{text}{output/fractions_b.txt}
+
+
+\inputminted{shell}{output/fragment.shell}
+
+
+%\bibliographystyle{alpha}
+%\bibliography{pensum}
+
+
+\bibliographystyle{alpha}
+\bibliography{pensum}
+
+\end{document}
\ No newline at end of file
diff --git a/examples/presentation/Latex/output/fractions.py b/examples/presentation/Latex/output/fractions.py
index 9e1874a3f2452df2566126d3bf2ec63cad11b30b..cfa0e1452d7394a0e4fe271b732c9ab3592dd5f1 100644
--- a/examples/presentation/Latex/output/fractions.py
+++ b/examples/presentation/Latex/output/fractions.py
@@ -5,7 +5,7 @@ class Fraction:
self.m = m
def __add__(self, other):
- # Computes f = f1 + f2 (where f1 and f2 are both Fraction-objects and f1=self, f2=other)
+ """ Computes f = f1 + f2 (where f1 and f2 are both Fraction-objects and f1=self, f2=other), see (Assignment 6, eq. (1)) and (Har20) """
return f
def __mul__(self, other):
diff --git a/examples/presentation/Latex/tex_compute_uk.pdf b/examples/presentation/Latex/tex_compute_uk.pdf
new file mode 100644
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diff --git a/examples/presentation/Latex/tex_dtu_compute_a_uk.pdf b/examples/presentation/Latex/tex_dtu_compute_a_uk.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..d0d2f4efcdd8ace82a3d969627865501743c2671
Binary files /dev/null and b/examples/presentation/Latex/tex_dtu_compute_a_uk.pdf differ
diff --git a/examples/presentation/Latex/tex_dtu_frise.pdf b/examples/presentation/Latex/tex_dtu_frise.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..a099312f58e8adc076799f45f00699408020fcc2
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diff --git a/examples/presentation/Latex/tex_dtu_logo.pdf b/examples/presentation/Latex/tex_dtu_logo.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..862fbcd41103ab0c721cdcf46f52131c89dfbe03
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diff --git a/examples/presentation/instructor/cpp_course/Week6_handin_20_of_20.token b/examples/presentation/instructor/cpp_course/Week6_handin_20_of_20.token
deleted file mode 100644
index 5fd08540f6b6ce7e46d4e1f318cdaf8046d5f272..0000000000000000000000000000000000000000
--- a/examples/presentation/instructor/cpp_course/Week6_handin_20_of_20.token
+++ /dev/null
@@ -1,198 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
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\ No newline at end of file
diff --git a/examples/presentation/instructor/cpp_course/fractions.py b/examples/presentation/instructor/cpp_course/fractions.py
index c32cb9b42cd2742c1c4f49fa69a5457bccbbba7b..abb48c64c4e08eb670bd31be9c3e829cc989f60c 100644
--- a/examples/presentation/instructor/cpp_course/fractions.py
+++ b/examples/presentation/instructor/cpp_course/fractions.py
@@ -4,7 +4,7 @@ class Fraction: #!s
self.m = m
def __add__(self, other): #!f f should be the result of adding fraction 'other' to this fraction.
- # Computes f = f1 + f2 (where f1 and f2 are both Fraction-objects and f1=self, f2=other) #!s
+ """ Computes f = f1 + f2 (where f1 and f2 are both Fraction-objects and f1=self, f2=other), see \cref{eq:fraction} and \cite{aa203} """ #!s
f = Fraction(other.m * self.n + other.n * self.m, self.n * self.m)
return f #!s
diff --git a/examples/presentation/instructor/cpp_course/tests_ex6_grade.py b/examples/presentation/instructor/cpp_course/tests_ex6_grade.py
index fd11dbb77c1ef8459f783a76addc835596e4ecd1..7b7ec2382fce1f42c3ab58defa579f42eab1b96a 100644
--- a/examples/presentation/instructor/cpp_course/tests_ex6_grade.py
+++ b/examples/presentation/instructor/cpp_course/tests_ex6_grade.py
@@ -1,4 +1,4 @@
# cpp_course/tests_ex6.py
''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
+exec(bz2.decompress(base64.b64decode('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\ No newline at end of file
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-=.
\ No newline at end of file
diff --git a/examples/presentation/instructor/cpp_exam/tests_exam.py b/examples/presentation/instructor/cpp_exam/tests_exam.py
index b68bfbe3c62c770d66c894a06112d2d30f9c4b80..33d7c5a8f37379bba13a754729622a8552e5fab3 100644
--- a/examples/presentation/instructor/cpp_exam/tests_exam.py
+++ b/examples/presentation/instructor/cpp_exam/tests_exam.py
@@ -5,35 +5,6 @@ from cpp_exam.problem2_rle import Elem, rle_sum, reverse, concatenate, displayRL
from cpp_exam.problem3_groceries import GroceryList
from cpp_exam.problem4_filter import Buffer
-# class Q1Vectors_Examples(UTestCase):
-# def test_correct_format(self):
-# """ Test your field is in the right format.
-# Hints:
-# * If this test fails, all subsequent tests will fail. Make sure it works!
-# """
-# A = createField(3, 3, Vector(1, 2))
-# self.assertEqual(len(A), 3) # Check there are 3 rows in A
-# self.assertEqual(len(A[0]), 3) # Check there are 3 columns in A
-# v = A[1][1] # Should be a Vector(1, 2) element.
-# self.assertEqual(v.x, 1) # Check that first coordinate is 1
-# self.assertEqual(v.y, 2) # Check that first coordinate is 1
-#
-# def test_displayField(self):
-# A = createField(3, 3, Vector(1, 2))
-# A[1][1] = Vector(2, 2)
-# self.assertEqualC(displayField(A).strip())
-#
-# def test_addFields(self):
-# A = createField(3, 3, Vector(1, 2))
-# A[1][1] = Vector(2, 2)
-# B = createField(3, 3, Vector(2, -2))
-# B[0][0] = B[2][2] = Vector(9, 8)
-# self.assertEqualC(displayField(addFields(A, B)).strip())
-#
-# def test_scaleFields(self):
-# A = createField(3, 3, Vector(1, 2))
-# A[1][1] = Vector(2, 2)
-# self.assertEqualC(displayField(scaleField(A, 2)).strip())
def vector2string(v):
return f"({v.x},{v.y})"
diff --git a/examples/presentation/instructor/cpp_exam/tests_exam_grade.py b/examples/presentation/instructor/cpp_exam/tests_exam_grade.py
index d09bb1329d42fc29cd42b16524e54449d5669ae7..7276d87b97b23b2577e34f69d005aa30b7435b2c 100644
--- a/examples/presentation/instructor/cpp_exam/tests_exam_grade.py
+++ b/examples/presentation/instructor/cpp_exam/tests_exam_grade.py
@@ -1,4 +1,4 @@
# cpp_exam/tests_exam.py
''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
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+exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/presentation/instructor/cpp_exam/unitgrade_data/Q1Vectors.pkl b/examples/presentation/instructor/cpp_exam/unitgrade_data/Q1Vectors.pkl
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diff --git a/examples/presentation/instructor/cpp_exam/unitgrade_data/Q2RLE.pkl b/examples/presentation/instructor/cpp_exam/unitgrade_data/Q2RLE.pkl
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diff --git a/examples/presentation/instructor/cpp_exam/unitgrade_data/Q3Groceries.pkl b/examples/presentation/instructor/cpp_exam/unitgrade_data/Q3Groceries.pkl
index e894bd9fcebfad69241890258bd985c0f234a37b..0358822545a338398cffeb774eb42a8a0a23f5c2 100644
Binary files a/examples/presentation/instructor/cpp_exam/unitgrade_data/Q3Groceries.pkl and b/examples/presentation/instructor/cpp_exam/unitgrade_data/Q3Groceries.pkl differ
diff --git a/examples/presentation/instructor/cpp_exam/unitgrade_data/Q4FilterBuffer.pkl b/examples/presentation/instructor/cpp_exam/unitgrade_data/Q4FilterBuffer.pkl
index 8544aeb6c5ac91153ee70063ef229218461e7344..b6730d7f602086f60c14fb70641d5e0f94c0d2bc 100644
Binary files a/examples/presentation/instructor/cpp_exam/unitgrade_data/Q4FilterBuffer.pkl and b/examples/presentation/instructor/cpp_exam/unitgrade_data/Q4FilterBuffer.pkl differ
diff --git a/examples/presentation/instructor/deploy.py b/examples/presentation/instructor/deploy.py
index 08047525f884b01614b02b41be4615207b590972..bcf6e0a570d6aaab29e4e036578111eda0ce2b48 100644
--- a/examples/presentation/instructor/deploy.py
+++ b/examples/presentation/instructor/deploy.py
@@ -1,20 +1,15 @@
from unitgrade_private import setup_grade_file_report
from snipper import snip_dir
+from snipper.load_citations import get_aux, get_bibtex
from cpp_course.tests_ex6 import Week6
from cpp_exam.tests_exam import ExamMay2021
from intro_python.exam_complete import Exam2021
-# def setup_grade_file_report_hidden(Exam2021, name_without_hidden=None):
-# setup_grade_file_report(Exam2021) # Create report3_complete_grade.py which tests everything
-
if __name__ == "__main__":
setup_grade_file_report(Exam2021, remove_hidden=True)
setup_grade_file_report(Week6)
setup_grade_file_report(ExamMay2021)
- # setup_grade_file_report(Exam2021)
- # student_directory = "../../students/cs103"
- # snip_dir("./", student_directory, exclude=['*.token', 'deploy.py', 'report3_complete*.py', '.*']) # !s
snip_dir("./", "../students", clean_destination_dir=True, exclude=['*.token', 'deploy.py', '*_complete*'], output_dir="../Latex/output")
diff --git a/examples/presentation/instructor/deploy_with_references.py b/examples/presentation/instructor/deploy_with_references.py
new file mode 100644
index 0000000000000000000000000000000000000000..32b862682b43bacef6b35b2d12d242be56b87a4d
--- /dev/null
+++ b/examples/presentation/instructor/deploy_with_references.py
@@ -0,0 +1,16 @@
+from unitgrade_private import setup_grade_file_report
+from snipper import snip_dir
+from snipper.load_citations import get_aux, get_bibtex
+from cpp_course.tests_ex6 import Week6
+from cpp_exam.tests_exam import ExamMay2021
+from intro_python.exam_complete import Exam2021
+
+if __name__ == "__main__":
+ setup_grade_file_report(Exam2021, remove_hidden=True)
+ setup_grade_file_report(Week6)
+ setup_grade_file_report(ExamMay2021)
+
+ auxfile = get_aux('../Latex/index.aux')
+ references = dict(bibtex=get_bibtex('../Latex/pensum.bib'), aux=auxfile, commands=[dict(command='\\cref', output="(Assignment 6, %s)", aux=auxfile)])
+ snip_dir("./", "../students", clean_destination_dir=True, exclude=['*.token', 'deploy*.py', '*_complete*'], output_dir="../Latex/output", references=references)
+
diff --git a/examples/presentation/instructor/intro_python/exam.py b/examples/presentation/instructor/intro_python/exam.py
index f1d22b97f9bd8f98272e03e1efad41fc26a68b3a..586349019d666c37c681de1f2333dbe47f6317af 100644
--- a/examples/presentation/instructor/intro_python/exam.py
+++ b/examples/presentation/instructor/intro_python/exam.py
@@ -8,8 +8,8 @@ class Q1_WaterHeight(UTestCase):
h0 = 5
r = np.array([4.5, 0, 1.5, 0, 0, 0.5, 1, 2, 5])
h = water_height(h0, r)
- print("Water height computed to be", h, "should be", self.get_expected_test_value())
- self.assertEqual(h, 3.0) # Check the height is 3.0
+ print("Water height computed to be", h, "should be", 3.0)
+ self.assertEqual(h, 3.0) # Check that the height is 3.0
class Q2_AstronomicalSeason(UTestCase):
diff --git a/examples/presentation/instructor/intro_python/exam_complete.py b/examples/presentation/instructor/intro_python/exam_complete.py
index e8f63f3da5d2f0a85d4fb4925843c736c405e73c..60dfeb6d55f1f368bb79fa5882ad8711cdfa83fb 100644
--- a/examples/presentation/instructor/intro_python/exam_complete.py
+++ b/examples/presentation/instructor/intro_python/exam_complete.py
@@ -8,7 +8,7 @@ class Q1_WaterHeight(UTestCase):
h0 = 5
r = np.array([4.5, 0, 1.5, 0, 0, 0.5, 1, 2, 5])
h = water_height(h0, r)
- print("Water height computed to be", h, "should be", self.get_expected_test_value())
+ print("Water height computed to be", h, "should be", 3.0)
self.assertEqual(h, 3.0) # Check that the height is 3.0
@hide
diff --git a/examples/presentation/instructor/intro_python/exam_grade.py b/examples/presentation/instructor/intro_python/exam_grade.py
index 67b272c3fa4478273b3f9ea2a69d03e824a5ae17..94708204bf79f95b51421bd03febef3e80c86f16 100644
--- a/examples/presentation/instructor/intro_python/exam_grade.py
+++ b/examples/presentation/instructor/intro_python/exam_grade.py
@@ -1,4 +1,4 @@
# intro_python/exam.py
''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
import bz2, base64
-exec(bz2.decompress(base64.b64decode('QlpoOTFBWSZTWb+CjKMAa8H/gH/2xVZ7/////+///v////5ge973vHvPPp8rw5H0Ck97a++z51pQC7aFC+hiIH0PQPQeoIuwXnue9nvW2nnvrw9bbz5Drb2uMa1lvWUCjkAeg+nva23318etZ769wn3zvJPj5bmD6z3Xoc8AK8vbBvb3yL3nemHbkr77ydWx9CbmtLW3wNKH3XW66jrz2U+Pffe7ztuve7rd10Yh3t0vrKi9059nuHu47RVK98enPW51dRvfAK9N8wFs+fZ0c8nuffd4p1d67zj7hyemAj73Fud27q10apadj7hvb1dbhKpr11t7b3lgwmM+6bHaq7vfNtlPb2NzU+xo9fd6DkbPuaFd73fRXw+vnDbc58LjL7z1dKhKT3evn0XsPvsGd58jO1L7zj161vvaYHlXobWrunmeu9nnu+89U+2t9g6XMMlvc058rHewlNEEaAQAgTRDAg1Jsk8TUTepNqepkyHkjNEPUaNGJ6TQSmgIgkJoIEyMRo00UH6p5EYmmRptQGmgAyAAACQSIgiZSnpk9UB7RT2qep4oaeSBkyAe1QANGgaAD1DIBJpJCEAE0SbEaSfpTaj1MmjaSeKNqe1I9R6m1A9Q00ABoG1GgiSIQAjTEamIGgJoyamFNk0npE/UanknlPTINEGRpppk9TQSEhCBMVP00ACAnqVP2ij2kmyo9I9TNDUDaEfqgM1BkyA0cFf1kV9B8jSgiez2JSRIp74KquCjAgsCElJPuqLFVF+i/2X58LqoaY/p/0tE/9mRH9Lz/jt97n2bOT6f8Z/YPCDg/D6b4cduM4Of+kEileHCeZaEyQmTen88b7r/epF73HXWs6im7tS8JhFqIdoVR6wZLqbg8lOc7keHnKiBRn9X/Poru9wwuXdCW0T7YyefRwlQpRaxGofFEkOQJydxOZzy6QfuPuJTj7f8M8QXJ2fXjEREbrf4ypslTNWXdkhgVfdsNiKCpuIKIoPNQE9rEWQJBJEkCEGQVkWQQD8ZCxFkQRX9KTIAAGf9WFhIAMEgQFgEhtsyJ1m+MkBvX67zXo3sZdO3nvth3JwPSlqQdjNguuMCKA22hiFWWRoqoKKf3GFgxFQFUgqCAiqwFy0kf6vUf/O7m9gZ4dJ+r1i9nef1f9Z5ccNdYchGoyLGDKiPHedrPRK+H1JDxOCTXbM5PP3d3s9vgsVJAcbIR94KWJve23JxdO7MwvsBgWe/WYwinbyTn43saLo+9+GeXOb6883FGNlaLZ7s5MwYytNntbecovl6dx/5MypcKjN1MNfxXGzC2hn9Wkfz4/6fx1n149ffLeIlGv+Ur8sZh1bVUb9D5JH/yTBL9OkfrKYdb0cN+OUoTHcj3J+n0ez0e+S/c7egRiMxjY7F7nz074PjCcSY/yrpK+fuu4+9efOmLSEYLAkDlwh0fH2wYzlW6P88Igan26t2rR2P5ZMlA+6Gxs8+Yy61hYPX4DVbfs0WDsk0+41og2QG0mlTlEPT4Okz4wf1XrIypjMlP64kOQzuk7HSRETicHOWCvpMXtMvq6cYyMdxlJo/L6fOX7NR2k1Xm3oefvhnmz9mBMvT8a6+n3VIv/db07tJ+UvSRQc8qGRIm1uQ8kgTqI+HOVbnvXP9ljnxbn1iMBe6PK6ry1De22LQeqAzP0QUs89HDXItFSjlbtqiU8Mims2+zJ/nLEQuHw7rz4V4Ya6lNuA/vx3QT0cnKN2r/38iLtJ3zUg3CXLljrjfGt0p175cMp0pc92LUsPhx0lwrKTZY8VG8nrLLPbhLLQoR48J6YPNF6JXRu6PBnTnTCm6Za7b1ydE8fK4rNT8aKK7p0IWMTiXJyW8cO8lw4FCaNS96db0U35cZ3k79IJXaGFZl+mHTAJlWHtDQxne6LYQRojlaUKyRaIxvlFyF5vHeHGFVJpdynJpn+O29uJ6h+l5+5/EttKE7vVUiyS4+Zalyar5TxTE+aI7nkXJjcskyl6RWlyBepo+Q+Yj83pHbUm/r3kAiKRpG1ikMUF7xSJ4PEEGEBZgJ1yOl92pLGPJhqjjbNSBycRKG0vsz59kwgEnfbcLRxYJUL8GZ/Q0A5yiJEbe4nYb9u+wIr28ZcC43MxcCjFGRMjYsY2JvZ1XY3FJhvME7fDyOQxi3xw5k8EMSbkghIUDbesmeS2s5F+eIHBERFUE5NB/Cnc+Zem2/bMgctPY9tWDPVZsdCWO8IcXtrSZa+bRMpgP1oP1x6kcuq6paRiyIeeBxhuiPw+Grh0VCHAxOEE49e6pufci9KINz2TdSzaDNSIzvAtTIqZkC+kIz4esx8qjg+3NV4tzpSFRvRuxrhs91agfTtXfyqzzZuPJHLZhBsgQ/RAzldkHPFZj+LqR+2cIJd2qwmaBZx9rgg+qrnykcbiRrd8ZkhExfuBx9pGGLE2cfRtiYlNT3YQE5M/+ZzeCpyIpDEh9pYN2JphqjssJBcDYvC8/Fe+YxxOzXJc2xmMs7J9Kqz5yPfaDfTbGyT5CvbFPup6HtGbNvy3tzyqfwy/j2KA/KpyqgFT8ikJakE1Wmtxz6EE4HqIxK7XGO7c+lz4DrPALjExMCeEtbiWnstI91ts8qUsrGgmuhMYDkLrqHXTaRNbXmeE7cJk7PFXbSHPjwz6m9xC8dz3T8M/PX4iMTQfRokuCz0yk5tgp0bsSKRp9lLpOIUxOTztEJpnJOcOs4uMgsdlXadCrnXEnMym/61eeyn1Fq5Eh+m8IJSuJP16xnKud4bUDPftnkSTPKdhHAw+Zy4hpdco5H/XEcrLjKOGVNnkCw3U0kb9sypK1z3w5dhL14u3514Fv7bZtPLnuFcCOni22SMY2GLF+43NTm0/zaf1qCFf7R28zd9Y8CRgWG3G0smbSa6BBncxIjBB4F1QzRvm0qtyjKOJZxN4nItGBGl+Clm0H5EzysXXM7QdHdhM15eMGUT0KVKXls8898yvp3xqXlhezGNlhV9uYY73GD9sJtVYjRocsDyyjkWVxu01nwKWy9ioNZw5ZIO3xvxrx6Ju0Wcyn19B0ONUnHaHMGWfTefccOUTBUoryxqqNN5cjTbpug/d9TwbNMlxY4/4SyDr1H8DjKcqNG/fXQkJCv4aRbS+jTZsUPdJNUF2LtOvVtTWatxMi2Ne0ZlSJ03WyLxzX6cjVGWKSAEJCDNNXZXlqSZFKl75Yrm1kEq4T6eNoKduVbpDhyMa/LPY18XS4bFQs6vZcj6pMZI1ff4debskIwkof8osuz/lnVqM7tTlOZITNQPDwVtOKiYs45Dn42kzLjYSRV98pmiPbFlct08iDVfCJJutK0JKZGWL6zJsWOA+4t5wcrszb0amXVrnFvjH6ZEymtxT7ZSKeG1vOSNDWa3zPzNgUPv79szUc1DQXxNCeV3PfI0LNemWuEjHfv+8s9pNGIqVFSbrhBTrOWl1cbyHavYhptqEjqU1Qb4zZ09IfGdj51oPI8d99XwpmYmaJp8W+x05P0AZvpAc9uu0GMsOptPI12+xbbF+85z3zK1bnDwQHjltSShQDgkmXEEntB0EtiPbRX0I+rZ78vTujcG2HWm8vnW0HPd3uaNbsbXBOaLPd9Or2M58NrUO6B/z/brad35Pz3yLW42m+xMOor+a3RLNvLnA3+Bafztmc5+Y9DeHmuBDPuuTx67a61mbvbjqV1f4PK+7e+sdxkaNqKRm/jnhrdOVdG2rRn+yaZFCRMNUZmU3jedcDEq9yrLW8z0p2kW913Xf35JG1rag/VXzORwIk3ZkzZxoXu30WcYvS+8x/2un8YGc/D4CN01XMRp6VN8mV+ryNav5LMdez08OGu+mzg2d4tfHWAzdJ2I9q7eJoscqj9wmy7LIYdy2/HdUL2VckjiEIHQCFTTsFM9DoXOHFNuXirkRfQbe2094Gy757Z9+Oni+ccjEqb8+GbNLWZ4v4FdYoqFSkpwEp8hycybu26szet9VZ7EVxhpeGVMBxmTUKHgGR9Xe7Yc7ew92qCj6HA6IXc+qCDWakh0hSgTAiGJUjWXMfoSym2E6nHAtahULw1vxEwWrYrYsSW+HMleKN1c7UyESCHpdwcvlgThjUH6EfsVU0qRUvNTA1sx9tIp8tJREQbZR0OkwQVQk7uyUcPXU0V4lu4b4CtAmcKxKdozXrCaG73C8ICfIzHXjvirNvxNCTZbmHs05FpTLwzQXxobGJcEIVbHtri2CwIFdyloSKUzD4lGtSmEZtMhm1N99ByZrnab3Q1knol1oxLkqm6k2Z0rwiUgulhfHVCGo16FBfg6KwugoMGhiuh2rimlZQ7EiZ1STNOhhMfDWhfYbN8PYZ2aWJF0l3anxQQYDi00nO/hQdKjg6fnhtkssRW39xvNbgSdkby8eWhgG+T2k1d3A3GhdtrAmvKtKqluHUyb4GN7bQa6lM9+dxlPLtI24ZhYML7FdYkJg4I+ky9pXUuoby0JOJ05CLQjEUDQ8ogeSk3vecmk4Le7Xo0ESTI5EqkiQpIvl2cgUeUVt1G5uEqJB4Iton4yzsqsGsJorijdphVOmjrdHBXKCI2m9NKYQXEGtO9pGKxyDmrhFwrIEiedVNyk35Fb5a478G/IX2J37OcjR6HbKpnfnFYcezyobqEI0d2ME7HfUOUCyO1t06SEb7r9b25TOFr+8yxGu1s2BI36Y5E5137ZbQtZhkYIL6UDNlNkwyC244YwO6nE9Cb+xYTpzgJY65EkIXxu1INEIR7PWeDEWmuIkWinUx0J2NYi/ALhGFx7HKYP0qM+AfvfJxO1HDnsF7Ybdz4F2xHZFx71wmnxw3Tzr3c+tfLPZxo1oo3Xl+bN5XI/YKAx+OmrLrHB04TBRrKNnHLUZTtvz8HfurdeM8V8LduTYXCad9DxVfoylAl5xB6z6NhepEyGtvd8K8Fxk5nsiiEMOCruTKRrhFtWYOjG30Lhmqnr0iDyWPPt8tmm3rJJ7d5fji4CZoJU8aE0QYscCprv1D8e8kQ6K9yJA71sOkGpaUHVFwTYk77nqXFIRSaOBvwV90Px1euGUYYtPI37NdBl7ynGDGd9bYS8k17TJuaFTVSnsjW2N5sy+2TUy9wjBz1fWMr9X6J2e3xM8emzXQydN2ZXPaTuem6ARTRvPMuLrPlc19cyYaztqmGmirT79pdDS9s7CZ9+st0j1qd7sLLyhzp2NruXCyLXQszBzEylRrpZZddYvvo9FJsnfTasf4O2lJZy3yRKwn3Gu5i9827HnQuxegcZZY4+LQbCrdiaF8ifE5FQmIQEBRnMXFhXiKGvZH0nE9xkfM5M7jePf8DNjOTAceMvwXBU82G/N9sjC71V3+HlXbhuiKJsPae/RwIayinTXeDPw+RFcYxlzMFkfdDnrGe7Lbsz7zU6aPJPYdWzCMv6f8Q+Vqo0+BoO/RuqCm9WI75a+G5aMVoNilPntnMKWyEaYxDaWd7DxXBAu+Jx4+n4J6s+3uu9p2vt2WFXlI7Xcj1lXWSeRbY/KPfdTL/o9Z4N9du+PbPJY67bSnLfv7+EskeCi6mFFfL+HhfrSapv+j02jK12V/M02xlO+1TgdHRdHjrla1mlnp9mend78ZzxGvbp4nVpkLleVeUGvU+QMh+Zr33NlLzZA5Bs2JbrnfXoO/WRdc+znLzjSn0eZPGXHQNuJQg7P/FP5NN9vr7/D5sDTbLLDXHeomkafRuhhRfOnTHxrlpzffjxLnZqO+T34HcJYukOHJ4Xj0UZCm0TQJOeW678/eU2kKkRCWlDnklaSbxMGyMeRJyJH738MSuewql4ODRC2zJFUpZh07bKn7jPv5e5D0T0cZ6lsvOvuUXUOUq/v68t23zvgWVy6ft4fnkeO808NM9EzujoQoeXlApYUdBjhPSWIY0seFg05ogGCaSjokSqOMdEwT/V4QU/zofQC7G0iheKxfE629NY39yIxvN1LNyWamvluae9RjWNtNveqip1/X5lwenSjn3YRmtD0J3dTeNRV39Qmg/Veglax1DGFUjJVr66zcxF26dk7p3Sg4tUf6Ymi0kqTibjUXIj8mXyIiEhHZ3qdgbLgwa/bSUH1Ae4o953/zOJYwKT7TEpfZ4fJ5Pw/pQ8mv2kw93yXxVN8AlzfQlkMbQKVq/BuFkhbMj5W9TQ5fufDRjGqqisSHehDp0580r1b7qieQyiAsVVWSbcWAcIccbYhnd4OYGhQ/dVFIKH3oyFeisKzG2lRtlRtjEKoklVA6nGYwYgFYjCv9lphmVIbDOT63UtcA5iO5U0dQtIyfJ+wHBik0wNu+gbAwNmSIqKRGSaHtti2Ts1jeOWZGnnFfGhSRdqG3UqRRf9XDm9t7wf08dsTuU8vt6uI6xkmjmWRxTIRqMjYowct5HpommRY84nVDZ2ykeG2PH5WH68eFbp72QPXbqpUzFcPHVxS4rILMfMd7TltTlSv37llnrH7iHRYhYjdqZd+K8skqX3kSuh0lKbvXwaZ97FBcYFVeSHaD7MqnP9geqks7nIv0NNCpAjWgFGQQi652YTI/3R+Y8EUbTC79a44L3P4yJPAjvLw4HHxqt3vxZaElbx0Trmq44s9z7tp+XYIo98zfSGRU8eP4i2ai3OEXiG+aPMx5dY52ZK0pCxeh05HsCxDvMhxDu7cS6fRq9j73i959BkHFHFtI6JOG0ebkE40EoM5qHELtzq4NuRGOMXntcBh4pM4riH4bHbf9lro7dIur/CX+eLN+57M+6K74H9XRtwqxsbeBqX1tcYkFSXIRiGDIXr3Oy+UuJ3OB6OQwqGMUo+xz9GwuDgQ9BRTgh4svSrOeFZF5DRHgu8toNmYzeaHcada2bNJE3OiemHlBRNTqohE3zUZyd27jFeKHFcm0z285Ey9OsNesqxZw1VgxasWV0bbLzxBY4TGeeFjl1teciaua1Q5EaiUE/jpz6+BOVCv5Jjz+k49NcGNRWdKywcjjI7wuvBA+i6WSeigRB8pFfKL59tv33RI6bb7PuHJZHh94fw/y/p1J6d55eKLt3/xJzHNY8cE/GTktaxg79F8vtcrl6PVIjNeURGKUaLlpmqJyQ5BXxicxThR+peF0rvwfq92K1l2m6YX+onVIPmzfitsfCO1I2lflOI/eaJcZV7qlyr342h5mN7NzJPxUy+KwNkxi8v2w+LXWzpqZPd28OZu28eqVG82RoMM+YjNaOt28PRKxP0LouWM8R+/v+now5LRl17rt7Yk+CIeeiTRfwk8o2Lwua+JRCOhELmX6HNKLRiZViAnJW8pPm80Yr2q9MWm6QqOD6Y8st+GuWNsbTeeFHANyywWdPi3IlZuiKBYt8OHRfGSjihDcEPAsQ0tb58r+OkzRyQ1yPo50uXGFDo0mTaJuxfnyvNcZCoUueIFNHlf6qyPmT9X37PfjETwH5h+YNxypXyVRPcUxzVKZfff1TIuind1qp8KbGc2cHTbG2FQVmVXamta418cvk7INSCB3Ijo3Nc47+c64Obct6f5LuMVvMRLp8hl3qdDhdpc29NbAndfgzIIM3SthJF38vo6VpavCWi106ZydEpZO903/bGBzuousnS9T3Vkkqub+dDjnS6Srn87xNZMez1n4tTfZSwTvuVtHzU/Q+Xjj+i35fLlKhRKfslBEpwOXZWlWfGjl3ld358J0wTePGO0jw0Z1yXrtGBum6N1TZj1rKlay5JxXS6ybbxwIL+/4YGE6E88JXb+e1ZJXaVdQ8Vl28nkbnyq7pZYSLLGlFnfTipYLouvoppKvbLPd405ld9TFQtimEOSqoraIe12s/O++WHyGtqYc7cIv3U9m1fZKptJ2BxbezGJnhOKzeFOKwNjLnxkeauEVXKqq7ogT+2MJep8IvjDWRWil1zn1uendIVi6fsRzNPF64qKPxY0kKMr6JtEs5i839MEzrKkSi2Mo9Ly8noop6pbZK2r98ZwTQKKc6499Tzpmi5KUO6QkEV7++Ch7erc+U7ZtGzg0EuB9ZIG+n33VNocOojdUayEhTYZ0Z98MDaJmsJDaMxiGxjA7t164+eKu37ixAxzt17/r8EGiF1WGfr2Ja2WHGBq5RpNLs4Ve2GLGfsz44lsPXGO0vRLGdwp1HIF7/KTWndWT5yJJJj25dGuWIm4S/X4ecohoeIy7Q+L2zgylPW3/fdethy7/F5S437zn3N8EXJ+OFWbkrSiu3h5bLDCfBYX74adHm2SZYR1RE99QJS31KdxE+AU+bALtxpXQp0vu+e1+s3xayOOhSEZXXc1K6D6NbiVcpKIZYEmacp+z37jdTW7pDpMsE6daogwePKrFZB2JXQl3Eb5ak3mDjsLXl4ccSaMs3gTPcd2vjQwvfRc7oO0vfF+NP588s7yvmledL05uI022ujhNuIO5he+VR2NZ1MwlpnDzUiIOBc2eNZ15Z5yJd94Zt0z2rRvpeFVhk6a46aQwmxJ67TKmD8esM8qU2ZmZTzVNeTHxzwUxeMCtNIuikBiY2hScRt2uxXh41Mbhzltv5UQZ0axLOZ5WnR/n2uLx1woeLYXl9HH5ZGMp338PT2Vd0+115jpl0+w70Fb/VueAwwIbeI8EYmW6KYzg4XbZLLuZu++61sSKFKkijtWhWHsbQ0IIHfHzffewbsqtPhkQHbpdeSE/cUaTcuqPHCRejarhZDQizd2l28m91OO3hRtR09Vnl6k9TEZH99Gs9lwo0lEBr+Jk+u6dWL5obq7oMRcqNb7sT4VbmiDfj7jqWA69LrguR40GyMPMvuONwYCHpkd37yxMnPBWq8RgQOOJ3emj7K+snPsq81pCod5XgjmF+eGkqiClH7kEXLpdC19FNt4r1pWdGkwK1NTHttv5LUZHL6pm8MULevcfE6Pzq0ez6kfB/SOhQl/U5+SYZnuO3HUNwjggXJioToFlF0rewytLldLmBudcrk7dvTO6XmT9umqPn2SYuIfUmZ3hcmXPEbXfBo4Tb51l2+HnLC1DBpZenKMcB8fPThKfPO+XyTSTI96dhISSSBQ6DWx7BfLYjCq/yxJ8utpXSvYvUtDIM3Rraz7vPENGlK1GpFv38cRsNWawk6ziQGVpR5kEYM1Jo5ag3m0RaaW5EibJ0XcxwZoph4+M4OADO8nKeQMKZPixzi8kwXyGhO4M18TVFCER4XK1GNtVBfFNd8xhgGBmoNJll/Vy8NplsUIfsCA7EeLtKO3VkXHEKGqIMDaTtZJyMnI/FC5qy0OciHROE6H5nYoSENy7xPQVQxoRzMIIG4rViQaUMj9PN4wDFhAh56ytydNZuk2Q3ZHtu2Y69ivMr3MpMQfcyU9rA0HtO4LyDebcVQSQPPnM4d2OIx31wdYaUFwQnTpxkCEubS2RqwgqhJj2TqyvkUcCRusOWSkgdDrzKDjH9RwanBhB4OXYBa68O0k0XU3A2UpJL5q6+6+jwm0D0DHzh49JNaYwznd1Voy1Q8uzZRsY/bjMw1zX6A3x9O9nS5PwY/w5Nm576QJCFhcHu6yLI6kZUmYIuvoQENHcyuOreRc7u/tq+BOc/Q1pkwQtnaOx59c33BEHQnaMOQ0ThrQg+g0OJ4gbHA79QnefEY/ixDxPDcAoBwfc1cCgWJBxgaQPhPva8me/T4ha8uCDsG4IDUPMtxDAZvytyX7DnL7fX6qn+9ecqfclcEKJO82LfZeglLb63bG02ZrJkhmQ24+Un5nPQ+PK7a1KIPuzlbYLvJAmmCasA7EJyjA1NWqCjEYiMVR3pG2gyzzTScdl/2xhgyjFeEENeESOWJMYk3oj1UAtdhogctKVFuUphkYHv0Yhx4w3uME/NprHIoDdq+0tM8A+6MiNji8J50muNoWanQBqDx6j0FZ+v8nheo9zRxpTgYK1J3nwe7C0eRWs9xNp4ufU48fn1id6kVrxVTkTWuH1V49qR4RtQ8XJBuOOSdVRttr0pelKwmxYfXSjTMbCCFd12eNAizQo1TJJpS8MWwZri1uc+jvt153SzlWGXQ7i8hkZTTkJDJvtJswXGfUVjuDUYw/018hbdvCPjMrjOIN/0/nWYW1Q83VMk5FbdM9dPwuGXnVBZ8roOxITR9Xl/pJZBZDAF3fbm6EeWnsOyuHeVLed6yQZR7MZp8xnge88P2iGPp9JApVmx1cOQ1daImh/x51yTNtff1X3NrSBLnjj5+5K6hzH4qdxSNcXcQ66c1b5iNKtU3OxozhzcPV253xrV11rjQczyQ0c0CkNiFk40sRBFjPAaCoiMc0FzFhaoiUG0LFKl5lCwEQ4DgIYTJgXfHJuhKNOCGzkTm6waKlFbDzkl5aZ+Gzt1DQ2cIG7r7eb9tnVe04L2psGwXjG425RPZb+UhzyONzUtO6yvFakxnoWYwaWp5JJbJz5A87WTW7ciUrSfXYho0RtSVKQ9ZSlv0dab0x4lzalLgOHWxUwcILiMh1WPwqkyqfRqsta0sGQmZ3SSZNkXZeOJO+nmNZodkJD3UylSWXJLC0xOh5hUmqpJnKyioJqnqEXN7u1NSfPbzmWa27mVO+FN2aWkhMJS8qoqCsnRdWkbWBBjg7hSB4mMLx0MrbHqKEg2oMb3zurphum5EbYiEaTOJJmSZp3xV642/GVFxnFRcZOqnEp0Fe87ROdHWCxk85zUySZycpXKinhSFtz6AuhzCrFq4aMY6sktZeGoxnloVlcz6l5lNUZ2SQkkXqmIOMcFKljFGJN5QqupA05ApJtgVKpiiGJg2gx0NUQUNNRRSCiybQY1hYBknUQ2xZPChLIRtYlSGAUTPY89hvNRhpPZebU3OjpDidW55+HuHlPBWHelQ72E4E6xNtBVRFRYpw3saPi0VjwGi9p3azYFAUUQSOrK8klVJKIwZBOqyVIiwSW2CMBm1ow4S76gWGQp3dvZczu7zy353ZPnlDRJ1mxrIos26dNKREMxthdFr4RPAs9ZJNGG+98pWzzxJRwi4Vh2LODliiaAgk2TF18pxW3bcq1kZjkMHAqh6332RHOn53tjcaNBZvgIjfTNHHLy3CSpOtm9c1TrUM8PUy0FzBENowlNXZcovWYKdKsNXopIITPLGkXcES8dQ15qpKuMDZfemN0993Og53wxPtOiMfB2SCOuJ6URTUu5gvve9+O4ioyfi8kLipY71++89eDNvmjnrpjXn5xoIl+DfgQ7HdBlpUXDiaY2/MnnbDsaWqUsczxnD8cBsfkvx06Sai5KiG677yery+IvdPO6HWh2ZNvVC26dZ2c64Y2xaJpmcszliWEPf8xxxfl4tgwQF+Nfz7KlU9U+iR5nRMwbPHjfCBrJlEESOxkww7DMaSbUh7RTQsjVqNLTCw0FsEMWJ1CYE8PxOAgs3vm1BE843numaC203S1VwGCKU8DF1xVipzSnDrsJAu2XjANFGI1mESqO1OAwjBQ6OG83vlJMNrucnPEiajtiDBEX2JWoKiy9+2HrvO/hrpjwJimOOu+U37I0zLWMbGGGBnc2gVbehhIozBQRFSZhxgM2u7vkGiw4ZpamUueCLyhhMmzzJ9Vfst+dcTzLHim1GMQOmbwZ0oTEj5gzq0YzFDmuoTbU4g7UoaiUtah0RS79m11UOwc2mHlG+G2RzA3LCExOiExvvc1bPsfyK8Sw/PIrNFaAzlb4kSiDUHWkHM5LY2MLYOxuh7JTVLl2nTW4xoI672x/dQBbr9sMafWwzGhNi5sLyBGbN8bJuIBRBJUioy1O1u2iTGdbCw1JuBpwPCfd6bwFU1LHoC9iTIziuWJYmWbqhyEVy6JCKSWGLxwguzprWYmbRNepK9+Gl3cCybETJCzo0mK7BIGxL5rXQNXRSa7bDK6aMxSRuXexMrW24uhTLblimAkCRiCZEBzpEMw2nJhfZ6gz/pX2pI+L/yR9+Euv3Pej+/8H/JfiqST1X2x98WKfhA2PeiWCkSo8N9Duw2A58EQkd44vjDH4n6fm+Uv+6G8NxL7JYcOMWbPSGP4xQIakSg0clN3En3Ee3dfCp/mH+gZ/oH1wchPKZ9T+mO+L0zGI84KmLa0rvoMECeMDuZ35Z99jszjZpMyo14tAacQVURX39iZ1azKaaA8WBUPuJDplVcbybWva6ysU4eW+g+fXafPvt1o7Z327FyhAOkY8aqCX4uUzThLOcGSWxOCiHEOk9vCEY0ttT3RPNRpW1v5r9CCaHexOtP+yHSnbT2ysi6dfmlEpfTKnWUYilxfWQ6ndWvrUvwqbbX0xnvufOc4lZBKHU4rIyJnI8f5Efd/QDju9yOVTBc540+ov9/9GKEWEfx0i1kWSVX+YpYH+x0aoENAaLCKBAUArIGkUIVAWQFg42ACwkKgoYwMZFBSEMSQP1MgGh1qt2DITEkWAfOatge73tqw1vvjs6MKLXCl1zAlWeeisNGDbwPHL03q7DSuEzWCvp1GGy7SNbx8ltIeScTo9SImb44juIp8h6LcinlrqRRJEv9y9C8wy9D6jWjIVSi40OIh5Jjftqd5cKZeJlv4/Jz+suc5eOG6ExhhWlYKsTrkE/0mgbZ3F3LEzPLp6t9ybIaqwUgg221ntOJejTKV9y88GxC90FkTkbXErkox/kqYthvDVcQSvBs+WLSr0+8jVCQ3NnB9buyqjmMocl3jvreRgS8VkPMMJNoi+MFMdpIjzDvANiHL+0mlh/UaGmmMhfU02duvb1LaT2bM12+eqz16P50mjfnNTPWhd/ufn/9nx/G/3P+v6j7N+h1dBRVFFFB8yjgaCzzTmV22PI+ahzROSpkJ/F+UQYNi/OYDN30ZeQPENUOsQDSf3NpcAbbNeVh51iF9WhsYpPq/1GnjHe5OewaU+j1fKTZaqqBJJJ6MdwmajsCO9KChs+w7dx46KPEe77HfYPwSXD92Umq1wdbWP4NNmYnsQOEGykSwBNJCIgyEqx7rhgUqlCeI+Q4lmiiv3S4cnaW/aH/jWp56Nmf1hLs3B27iYUIR75BEIFzxPVJBQeBw8gbRfJptMbPQ4lFHtnmqJ1gHPeOHH2O3+Aem+BmP2ZzqNJSy6ZyE6w8x5X1JgmShMoSaRIZiij0LjDj51OIccQXzpJCIQgwiEBA0WoeR59+Brw1ifd2fM+frS1FHdffsOU+16vXPQMCeIaL+2J8VSKqq+GjmfL5/ITKjzc4+HUb74Y8gjtYbIfunXedIJb0bCu5h0wwLMT0enyhHZvDc7jQfKaXyRKhyAhcOt8xayQN/rsWzsjPP6l1OB8MNhuPAyPsN2O3Xwn8n2v8DoYshkYhauwz2jCXEudL84ZIGLGF+mOqmgiFSx/EwhRmvQLgmx++r1nebGwqn4Av3DIkkST5k+H0Eouh+DlqqqzNwnFAe4opLohPAIo95EtxCqt6EpGD8dhY0vbt/KOzi6siF+NG1uUQ3qmBsa+GTN80/uZBEyf5pE/fb/G6dX+9Mqwp/vxcm1RYbK8de7GmJxX6Fy4g7OPpEMHj0BJOQp4H2Bl6rs/aa9nJFVn7t4aNK2JlSKH8cotIu9R1bizRSie9J/7TwPardX/T5Yz7sZP9bbchJYN7+lm4YU/y000tXhii5tCQfL8eOpLveuUk73dJRHT67pm+nY4w59ksGR+yQ7f0YM3ZAd36Hy7HX189oJYYolvZ+/EMjFxP6B1Efi4YcSnu3abU3Tsf10HRv4x1FxMyHEtDOePEQeoMN4xEGvk0YwQPJDlMLqbHxwNYDP2/tKWnd+BmAL5uKQhqzKnPr+AYGUQGIHA/YB4rvg+Cc5L0rsnJqHhMb0Fip88pL+l5fzJqXkrvl8pE4zW/04cGkV2SizsVJN2AYzO2lGKBAJKPnftaPocfalfg/T1Vn5UZOAtvz9t3eqm17Ze6ceHLHVnn82jV16QcbiPSO4exc6mJhUnRK/ki7k79MT9TSSDpFoen9LuF+RZ4cnvU1JHL3J1EUXaXGZGXnFjaUoahKB9+kwa098VE6hiDuILwcpfppzOEOL7HLUJO4l6bgJduNeCZb3e/+XjV7MnqHSEQrc4U2mpNcPCM8OI1dnRKb4wF6iYh0X7R4SeLVlJXI91oiTQrPAk35HeROs97tPx/ZG8zxOUnUDv0K4Hs3ET9z9LU+jx5IkrtQGlx28aXV9Y8jq2WyIbEEeKaEwkJkwpSz7SM868kS/4pwvvpLNeNMhaVm0LIfaLU7VQ58rmLEPLPS7hnabjnzqGyYFcmomkw/0WRXNxnw1kur8tTV5OMJ8qXtyXrT8UlTvj5VeUOrH6To37PkIkFQ+4SxQuFahftfk47KoSUGoI/UeUU88ok/pp86704uucWN74e3biKy+q+WGXOMXtX8/M3nppV4wjZ1k+HrD05GNpuJvle4Swrp20dNr7fy3Ht5F5JEZH6WvKrViG3Z33BcNRrTHfqWnd+y/hZN6I2J/juXJXRB9mNyiU3Tpx+mzwo4ReiS9CGcWMlGk749b5ZvnszvhdZT39Vdo5naQtlQwY/xJBsfY3VnN6aqJGfc9WQ6MmkUYmy2i8r2jq3aK5QVPysR7z7uCt11mlE+HL6cfk25DJkszt1rnvZke+lIIxZjUXgcwqL0aiKqHaWbjQjqh0jHSMbDzXC3q0xrQJw+Vw4ko7Es7ilZPLf1D19n70FgojeDm9KKKUEJIo1OY89TwiRUvIPFBciwpN70noSm7Ou9Y47T2n65/hPWckkeOMXvOZ8VVEkb0zis90CP+D6W0xlSHb2o7Zy75BREkLCI+zfjBrXW66dEFFnSeGPcJ652sG81ZR9J6GrrftvJ25dC/G4d2Blg9k9bYToeXNz2kK8+VDfqXC7OB0LAiMtp+lSS+Dy6YGvLzrR5y2XttGKwwue2B1staDIyL1YRh2SdT31pyMriyeXZAVNU0jixGrz05uz5V3NpVUz7FUTU/W/qoj+K/oVE6+uMW17Yel9moq6nqJ8d19FWQDsrez2Z+HDop1ucrt6KVuuKYNfNpHOZdyXjDHf8ko84e5VO56YSifox/Vne856jmm7awUoxFDhr4zX1fHc3o9tdHn11l6KoHZ5HeB2cTnrG/qr1PTGuHC/i6TcV+r7qtiiRjHMg9fM4bVi7B0ivbug/uv32lW/u59Ol23TpcSN88IhD7oo8YrpRqhVMg3eDtB3uqsfPXqvItYTwntOkoewijiZVniZmKXn7P/Pz2S8QcYmuMkiH+c5n53UfQfnzvGYPqPKdx2mBpeTAdsd7CSSBrhPhXq+Fr9dsMhD4S/nKC5gwbNs0k0DSFcUqXFuLGNY0tMPg+UIHYgMfJPUlTPze5oYDAZAHVIjJG839T0FtRtESP5H2DEwgQAzwPbLAi4SCfc34heMN67AVG4Ev0XtNAtLYClimKIDSaWyLdrRqoiI0nQiUD5lwdBgaOhkmTl6zIOxEOmopnzpIpITWOcO0PzDt1Jm6zEdPiMcU5mEjJAkhq1UNRXIPtAstMbS2nqccBkI8hNag+i2eg2+YGMKWtCA38IXKLZ9B/r0XtifAvcXNvhhiOjeQIENakIQjsD6q0iR1D9Ltz0w6Bjgao6uqJcDWOC7sHN54sI6hytI0G0mJGDIdnZQbDZm8cw9ZkCXIQJmILrXa7OWRJkFUyEIzc6+U9S4DIUKH8vQks6HSnaGcutVFPahWMC2kX1Ug57TKlCGtMoQRJKC56HjQw7w8ioZhWpVjqnwYagCGQQwghWGIDsNRvDAcSIvENxAPQQAsIbnQtB8wiDAa9sWzw6BKIoMiOAQ2wybtp2bZr7xpb+xnig2LfhZ5psnRmbeQtUcYof8yJQ8vPPub1F2rO3pTY2MWL36mOcbLk7w2InMFIzJKHlkCjzsTPAkTiOKciI5cPXJhGqmjxONRtldjIwQVgo02jAURPoA9oHB7OoTGa8DUIag0jAajDh3HbQ3opkUq36gcNw2E6WpPXYFWCcHfYAe9DJoL9RRvtMDdRRh9MPwhvzYjwuSBr5IG1P6QyaHIcTrTmo9JIJ4eBhnoVhTuSB8Z2m+CxD+UyDzaUCqKO8T8sIREkQSERkVXgE0XfqKMQikUhEUsZz1frfW3juglG1fevuzGCDf6PF9Vn3dB7DcQJR/JVjdVxLAsUixiChDq49aqAP0TvgE2N2ERQYgJE8IbT1nJC/UcAggiaZV2SKqwKgIDGFpViF/ZsG08SKogIKqLD/WWE5Z76lBKopA6skgU0HCwawDYtV8EbdxDSr1Gzu/6yUUeVKIqD5CAMZo6NGUWjYUraRRYfGefvt+JRnG9gPw16fe9pm4wrN4mF4PYXHrEUTUlQu2W5Y7DrTrSILcb9IC0dKcSp3ipkKNnpDeB2z8hTQgSiCxSRYjGIQlKFCwOOITtlFBkYxntNDYz2TcDrxVfuIEIycYp5IpzdHUJMyENhI4OyJby9aE3em704YJA2/eJtSigDQlnkCSzC296U0onWhrUvAXWQ849x39yipKWHUE0nUUO47dH8giCeZ4h7j9aoCB72XaTdirGD5CbgD7fD9ZT+gNfJ2EGjF6g3Cn9gQU6BiEQkQawHS7ipYViM5oTeG8nZ0RSHM47g8RpD2ggFmCWZGGMLyxoXBV993nmY7QjB5iFm1VKlBEYUkQmIhyfywpRviDtPEiRgkhGIEgBFiCQAz9knrrVvDYhjFX7IwwPn/Ht0mqSget8WYIsA+AU3MN8aBcKLHmYV6bugQwyt2Fuwo9FQfA+L/Rf1UEmiWctsCA0FD2aDJCkMWDGNhBC6vDVe1B3F50Fpgz88DPA0MgO4XmxtAIbEflvSItQbd2yN1tttbsEuWrDULi3MXqLIhWZDEhkeVVxoD0DnEt1/h2lESvpC54tnPSRJUAvtD84Rdih7oD12kAqomzDEEFemHq9Il2PC7lOFJq5/wDpvrKorYaoj+Eemdis9H3FZ4CrBikMFjDr2XPw/Si//eev/IlmvAry/STRG1cswiOqlaV08d7f587hkHMVdLLv9hUp5y++SP8qOH3Se6MdDZRBoUk/bgXh6jn81jBkIHJKwZ2vkSgE+9JmiuBLgEXUQ3dv+VcMAd/q1h844IaZCaaGkkkE2FrFhkGAGZPXrs+FevdE0mfrDvEMxkHz+FfFuPeOxRPIbDsMoE0gTIDGuiKYO4qEfJn8DOI1riIqTCGexz9vnbfoktD5rxb8B+wQfx/b/tZhfFHqxSH6hl2v1MSaabosFcTP7eBxKOI+iBqYHp/Iz0Gvmf3XMCwP/tlRcqyUEYAqbWBiExkj80gNBEBnLmognWYajNBrJhDhlBSG9RikfSF7Tfk8lqqLNyJuy9vpr9EAx/darSHpQM75w6m0HgwbFUaID2tSRKhpQUAIUsbUvIQGLpiQkJAG/FM5VA6NvydR5W7A2GlOqRkuHA1oqFL7LIfC6enO45tu16w6bllzSEkhHXQlMSERgRAZYRxsH98M27gr++JQtm7o96fHfiFIEcKMvAUh1o+BVANtgw/ehRO+qJNfGKk+c+ULnLX89gY2yb1G8hdpEoFm9nQCoDUvKYENXgQzqAw7lF96uM4GA3fsMgSiA4j88sQjFjgTo7KuRLmKocj++1A3XpD/YLh6bn/j41oFhtJSGwKkNKRqAB7F6BZNJT8PRSED20SIjGm0MWSBAoGFAvY+EuLdG/gFqhcwCoZkzM1QPWWNxpFO8rfAeaYdexGRr1RWQlI2FNnB4bWlJJSpMJrC5GmDE1HHC7pmmjilWnCLIFZvcRJAbRjLDTomNGUgrkLXAGWpEenxpDcBrQ1rKMEJfl4qb2gDw5lFNN2DTiMcCQHCMY5XrFG3uuv55AwleZkNdKuNKfdjV60HhRlr5YpOKjo6mismPkfT7xosEJ/H9P4j4yQ+6D90V+uAQhbAfrgBndO2twGqhJRSFE3cAxTEuQpSYPC4byBgLWfZ9FNl2BmAZrQRkGbEXVOJFgYoBQ6D4JcHyaX29tjwj6t1sdEfNi5iJZgElUeYPNojQ17Brp8+LAc+bIPToYFB+AUpyHleuEOjnxKLYfF0ozMpRg5EPPKAkMTQIjUMBmANkiVhjgGAhBQhjQafa4NNHwdlm7HFJI5fN4pjOFKyo5q4o4Y5FUYrlbVG2VG0kci+Ng/Qz7MiHfuza2EDeUXA+G47xpRiGYDuBcHgHRR4jnzPzlzqebXTyr9sylprEgeBHQ/ENUW4kjbXZpc1wgWuwId4feGs6VzOajLGI/Z5yh9xAPFNISdahau+FD3Z1O7UmSuo+4IGP/N/dvNKa+3jY5ELh3hVEgECxGQ2kWjr7LGcj41VI+QmYcKNg5zxEOFNErwmAuCMpSeW7w+0wME/IJ69g5lgczQJmZpMEiAwaVhWKlGMvmz8Dv6xOW0fZabx+pVuSsb784JtMFCmHOEZDEuob+AZFiCpTUcxy6jDk+cJpIRbrMMOo5x7MyJQYiEcacaTT0kgQtrpo4N1xqljJ8I6jlhssX3RDeI+kUAuDTddDjiKL5zOOPpfCx3He/33Z9s9Nyjhb2/aOkcJk8c9HTl9I6EHC0qjoHMbiW0DoazQkmhWgVDiNbg/Ygz+HAjj2OPWV4rqR/MKF7En7nT9+ZpxWxTi8sfvzN4Vo2/RIYiBJNw7ifTmY3BuMOu93ybM2eaaKv1IGMGv3RoZIuKXJCaCmNdEZV2hiwZ2JSEUOIZg5yuJ8XoV3BxL2cokh1dnbIiSGxyeYFcCQ3BrpaMRwaMhatcIalpSqEWcjNmUeJ4gwRD09eDnvinbTlmD6F6Lg4gkOkIL0LEOw7ZHFhIo1TnnnicomQQHhjG9Sc8qD4OsNVLVm031KzztnrJCTEXs0YChYNb1ysX0OzrT5mlQ8qzRntdtpbxgQkqJqmDwy119R0nbrkOYc2GOWGbKdCe7u4bXXUNiXNM+G4IMvRBIYVBhJSa3fLpkFEhVr0krH8uc1XdkFvSEzLlSNPNEumqI3dNzla+hPrePqYIJQ56pmeAfhMv1HPWrvXE27Duh0MiHdMilUukmiZFspKLS6jJ1z33NpUcvPFc974USOjB30ow0iGi63OZUIWnIfn5ubbaxNS4g5jzTDiFHnERxCvqfKeXB7DTvljkD0ohtIhik+VXIVNwHD0YxnWiVALaN7jHOzpchbqkyD2VLQ9ya68SjcPrj8GR+ijlNeUXQ4q+TRPfg10q3BxNyYtgzkgQooTelMs8weflxcXYxbWCGpmj2nBY2gVDegWaEwgR0HVUmTAagpusBzxoNh9/8HxDED9QfXZoEsveJey/ymFBrIJ1yp9MFjLxqNDESFUZrmmcZzgcB4QlSiNEOTla75eeYk4eE2Zrn53FwW7vLVGLJl3ceScVNz8UmlGJrSW3H5HKRDy+jmD4JsXXzEHUGk7v1cEOCIg7eOmKIUJ0bRmOBsSa2tWldF/QsXs3ixkOGIcgwwmDiM0QK5nyRjBMtvqaME2QhWPSEfibxpHpl6h9UELnl6R6KtpelyuMSKJvh4jVcRxdQQU+32dSQo29D1D6LVxvI43jR6OPku6Sb+/JtEYzITIB0xCCEIBIuTDELgnQ5kpKDONwMk1QYESjY5DgDqcGgIMBISAG4IDXmdBco4DoupyCMBaRgcmIFAwVAoaUoRB7yZh3ILYuoxhEuQZ0EsKDPpCgvaC+OFSLEcIpnz4/0zY3E14v3lMhlYLmtXIM5/QEMD6CB1gReo1OxUxDrJDsYHPGDFEgiKDE4Mm/7MEKMISTMzdkAc8B0yYx3RtUS7QXJ+Y083ZbqyPWHzG84DGbHcW0CC0FwTDshCEoaWKbs0iS9AoL2kORSj4uJHSsoBgzI5dhxEjI5yvDIDgQNgYzdQdzcxYm5HcaDAB60nJOROU6ycsFJ2TwKew/YrZOA8qVc5BPjf+awp14bJrFFG/xM2Z6t5p1GwghsCDnQmQn64jIL8TQDpA+n6uRnj3x1GkjGAcQgjh4noe0vZunXFCQduWCZzIrPIBkmepmQzTPfd4UHBpWFBGElEKkIUgVEWuKTOfKenFQyhP4tQ/VKlcKMwY5h7P+XnBZqdih5FhmOrh9SUFHCdBhJQXLd8ALi5WKFqBolgzzPYDo7JgKaFGInEM/WxCW43kxCyQUOwiosggUYbBAuLWL3BhLIaMuQ/DWeHuv044ngUdsVTmQLVvqVSnWqOEQIlUaBDOYB1CFA5YKHxlCIOto1i45tt+tAGGbaA4MCGIK1BVGQ+ckIqokxiIwCBBQE2IAdGLNzBDDVqOnAQmKJdgaEo/VkbMi46SAGkh3FFQ2DaHfgU9ZRImMhpcuifi/NXRL81sFKFisS3zO7qKC82kOsD/mMCHaSQ8Y+xoCUP6e/47U+73yfb3k3ZrVSh7UFkk7gKEYO5+sDX2khQrtud74Z8ZvxMrTOyOCEGQkbt26UrZUORT/S5PG23PzRQjT7BtmDsxhYtoW8qccfM43eIpSC1ttuBBnV8vZt1HTjs0aMb2KOx9qwIxzGC0QQzxTCKSLCEggQyGI1YT5YrsCgpFYiRYrJECCRR7vTViJrBQx1LZCwXaGrp5lkiQjEYIGGZ/QQ6SEJ4f1WCyJiUEIkFDyjVm42R0gGYAiEondneSGHvEwDW2HjMIf5hFiAIRibQL4RnKj93e3PaQA6BQOmAkZiGAfEsB8205Q/jIFEOyPDzabOZ4Q/biDI7wLvAh70Vb1hkCfPI+Afzf4zorB8CzYfOTdMUD4CQKRKN9MKKGotdqp50WLgWSkO5XT/gUgyIPwPL1x5ZW9HrPkA+Y7IeyLoQS+A0wZSiWCMVtWj0tDGwQqEaQmssnaY3TIaQgqMEStGQCqISoFLKAolsKKDCAkYiKiRZba2Sh/0cLVhQYgiiYWkxmDDEsYU+fb0NsxcBFZ+JzPtMv4hs8A+Q6S4dnRkm7AmFV7MIGySTxQCQxhARAA6tjeTIAHzX3tw+z835wWfrRCwQYBKhSD+VKSljJCQPvDMoZGlqjVwLO+fhDgdQBUAYeD9lMCJ5ZENKVyHxfgngl9gugfHAhJGARTKB4gPqDSV9tfPo8U8exf4LM3CSuMM4AfL0+4pjTnXrsahkJPZ023Uafaa3NFpmpobpXNXMINHYYYXKDBhwhdqPsDJAw2ESIxnNpwamGklEESM/Od3do3J5niZz/pGxirEVkSLoTmTcOrPHKMeUGdbOSdR5WUVr+dPp/x7Gd1cbmofz/FNs2znJ8fM3Y3GkMNm7WZJjEU82t64JQ2MKG924pI8+vSt38826lauihQ4ZUW5nuKHqjebD9UTe8L3vQwnDCVkeZzhwHPwMZ11qYP0/jPMeBtHzMhC1FeqVC1UgbCCURMKSoExkhSMQGKKiHcMD4n3jhQfmGINsKHBVQg4k0loOTTzLCFoMGPRj17LMO2SBxjgLiEEjFFhRd/Qo2zxr8pz1S7twMB7xGraFJc2i6zaYmiXxuImJKFRJSiFZjD5em5ueJDyOcm/XNhSXFBkLqE6AuLVW2hBFAT4Db8OMp9oqeKFKgwEgxJ3Z2hSQnYbGuZ1oQIIyKkIEL0iabGbi9++zaFs1r3X0xg60FmFYBUtowSSxJF84abiCAe7leA15jio0gYQi7d1yLSO7NhA10ZTk44NZSAz1spz+xD+dgfjQMXYnMmE6iDIpCbMKiqBY1iKA1YgKIyQWFQowiJK0YtBQXrCKtMUA0aP16R/swSQkhBNBY9JgbANAaI84diDA4rGAZiiWUtYMmtC8Q12w2HrO4L3XNwnVHQl8AbHPnPRYMknh7Pb8a6niTeX+jfjCeMOuIiiKIIpGMRFGIyLBHsNeWJGQJtqkkMAn2szwqDBVs5QfKu81ms0Fi9Bz1JlnLn4dFJ9xHiYVuyV09JaDPeDD2e96ewRqquflIX0QrWpIo40bvZXAuU94QLnWd6/lW19HxEf41zwIkC5EfGdfPj4sD13tIISIXOso+bVsOSGsHPi0HzOIcPvemXD2yjy9K9w/YzJWKlSnKem/nMKVrCNQm/XJY8GRttzj15w8WF1zxrMbb1tcVGWKE+bjgWuXlNWIjg27N85a3CR73q5xCN7nRl9yG9BHOCDsRGEToSAcVO+LcOiUUmYSe55lU9J7LsljEniATmKeZgbjpA+I2DyfMOGA0vNc76r5w8RqE94ayKlg98xRP7SIlQV8ItiIgGENIRV3eMXPMgxsRJAkV6fA7A3YCgekgP556vnxKAxmw+Y9SXF+gwCQo74XHmE8JLaoaIsbrgoSBJFGovgihYmhbTXwzA0W8ED6jU6kwkPwF8UIKQGAeiIhISBIq/PEOaQvDzHubQEkFmQLuMTQxB8vdzH5nkHkVqGB1rQEbzVgyg9GwMSUUcsr39USjUo5xM0RkAKUFqD7C+rOe1/A6uEUTDhPQdD1XoT5YPYXsYxK17kvrDUs0tqGGcTnHpyGv1+seAGKn1eOkiVBcVxpIvkWChDLxLPHHlwEuRf9qOGEDXiEfNKiWjqAgZn6Q1ZyLAiQLlKJO4akgLOZaS2hC2n4S5m0WM/WWgaQToFsm+2xPQSSipPCe4JvPOL0vdGuCLPk0XcJ3oSIJFYKIoxYiqqgRZGMUggkAYDBFBkCBJBGJx1nxICfzp/uQaHse2w5i3NIYABwQD5dJAKFOYIawE3wIpGCwUjJEWEBjAVkYwYsioxYkDCux9q9rzR7iEJS5AdI6D9PYJdfT5g8xIUV7flgZCbHIYIz+BKOgTBu8myT1QvexTAuQTezqVpN9KftxHthSHlew+T04HAD8sqqJNGpB60B+wiHrg9G3o4cG6bQFOQHn0HsN2pbhJaghlAiMxCmmpBYH5HqzNiQhFbkj9Px4bKOUifYUBxUdphScwo3+XP29+JKYsodoEAkwbNSoKKmBzTDpEKUteaSErWFlAM/kwdkkRM4UBmQtGEDc0fYd8EofHsKwFWMY/UUpnWB4Btn/aYaLm0PoPEXEbmDp10Fm7sA/rUvZLl+j2+p9FViPqhWWT7q/VrxklFjtwOSOmkR6siOS6ocqcaESoZELEohsgYiF+JRUPkixpkdoLucKFik45nVuaXuumuChtRWlqB/InQWZ2iceFXRsuXeDOWRwPS9nwlxOey+Fk6Bgl5U6taJ1CUDQg5I2xvZzcO93tP9r4DqH6NAMkl4EPYwYMF0eOe5HkGKOQmHwjqeH5eSJCAQIxjGSRIMCIhAinLkY/+vtv7u/68f8oHdjhe70OsDYWOkgItuKO3AdLTaww7yyLC5dTrxp4C1HZJeMEbRoqy0q1R9jNjcs0bSwiw4yob1b9UtYcO6hhdsoA7UK1gtNjWQxdio1qIokohFKqU2aS2g5SVqhvaikc4mAkspuIsSw1kipRGg0tktSol5ct8d2owMimIBFKFgpig4BY6/2liBDcbDKGfw9G7UmT2xX4TuitocwgaSMDpSbopCAbAi1DWu8dRgvSYFhRR3nuLkCHS0Y6MV0idB4qJDx/MV8hcIF0pCfk78QwdbImfgzheKTmQ9SfDLO2SHj7TyJRYOk6OERRYCnoDDSDqhDxG7xLkYQoyeZt2fp1FM5BXUwKEwpV0lBZXOl+k40FjNYXmd/aYDm9baLZI5B90zPoD0Sz4u5FtRyEg5EA3/xcfte7YMezVoWGUJRtWgJtbI+Vgg7X2CQICQUYgER69cQSMAo0ZWRbIlYoNKBkrtG1jN0cus2FXhWqHiL0XKXJM9CTO0g71RJEY9yDZvXkOxl3VfXe+7fYgpdPnBM8rXXv3lDDoczc5BosRQWQdimrhBstLqCq8J3HchPAoVEdJYLAh2Z9TAw/EfAV7NrjdBObRWTGIhmn9okCn3Lw/OlSA3ok4fKlkxDOFPp1usL3gmal83tN5Y3nXU9VCfB2E8YfJPIZFh6fKGu8Re9LES20RCiWpFYyCJRBQaSKErCKRGJILKjayVsEgRDjzyU9zNe/pDoAQTCc1GDAaQxZGjFhhkbD3Qq8QW4zptZeByLU4VkBNeYa5KTqZw76zMvEzhv3iNEkcBWSzwQes2kCzLDa8DtKXFnjIXLVxeikfG2Qd8XibCA7cgjWCNLQif0RAE2kKIvi6oAKBcSypmTm479nuZt+D4N5UlGVqs995ZXjMJIbiBYHeRaIjtaeneNLvNcN/9jDDAzEcMYgMp4wzE+DtISl6ZXZzqYqCCC+g1nJk3Ng1myhsQ1hSaGRqhEhS+DKAQSmHtz8yIMWNbXQV/rEOXYnqRUw+tUrqEgMb4OrzDIARQW8xLONVNpYaWgwZgMIlpoatoQIQggZQqqKowiTbM06RWtrKNRSPRNHApHRJQirQrKAmaghENQ0rrYZ4o4KTJEyMG4hN3IAiUqYJzbMTdoOoFQowMGAYwVAZCpRBMzTM0oopZrMEaiheu6LrF6HivIMMycano5Jg+zOOJgzTOqatUFDIlEMHbcpijNasCKdUBf3D2sGh0nNPgWgs+RNHAJOXVMJgQk3STE6kkoxUvE0xULXoUS8RvbpKv5zApJAbJsFsXQDAzCpUGKiCIgEImmDFyxycr7Y9R+9eRYqgQgEmSJm4QCVzjo/GhjcwyQrpipJIRkjzuUPgnVbajuUwLeFToD0TDVDmgVZ4AlxTxF22fAcZFkAxhToKRKMaBLsEuxuXG7FIQqMbookzIDEUTgQWMqDaBVGAxFDYsClMaMlImIDECIsVBQUikFAWRYIIBEjFANywIJal1g0K0CmtuBwIONxiENEkc4kgQxCRVAkOcDlYHtMFoGCbfd8ub/FR470EZggOwOuDIRhm+ncFf5EV6WiADstsUJfdSdPPZ24H+JCPkXdqJAAk1MGMEmE2HLiER8ZoHh5UfSOhniyitgVBsGpJ7BgjIAKCPraz3oee3nvMNfw7BeFZgCboLjUfu1tgvp3SyeJD3ns8Z7QRPTDA9RYUWFQWAXNy7mrDajYBRFKT9+KhYQsBGBIhAUYBAgCACyQRIsBGEWQtESUNDQQQQRlIUKUloWkyM9hrUwsONWcOhgscpKxRjEBBEjIb2d/g9Quac4CqE9YYOCLgbJWbyhiA8yjr6jh65jJE+dCbfNcS28kv6bIIxG87rfWcfaNDgUEEoCEMUyPyHPxm6X5b59JHASMs9ET0TQ5Omg0Nl0gD95GLEZ8UKbsNJxTW1Ssjpr2vzH2W7SFe40KD7LV6u1JmmFRQauC62EkYGxHBuddrqGAH0vKJIAGR2fMHOlCiMhIwlU0pAupoKVeBz65NKGdAeRrU6xM6o/yfvRfZ9R0aSMFB3KQYSQhCMCMEdJ+AXOgunVieNgYPTKwXWi2OgvYLhRkSJEPfc4BZV+yIJ5R1BBU4e1IYRDAQZhcSS0LCIVClVHKQUWEEZFRBSTIIiLAC0HQdZVyJAYGARRxED+pXFyoSMrJpULRBbVQl0NDY98KDITNBHpx0w6CCURC6bS78J28DqDIxDadhY1o3kVPDoS0GlGiyvdTkgLAWC2uiERzhApOT7UhjDMC1CcICiIayhEZGDJjLbNIXSgK7Ukoj0SUUPGzaanJJBycEONBET9xhR0OjjJ1CiWAMw1J/D1oGIYpkEGgmJqDNJFkFOCCdhEEdpAECgIIhfywYbT1z2f10eiF4T6QsqUVXEko4xQWsnqk9hDpIgREM/CAHRxgA98IQBqIH9sULQTddSBXNOj1IQcw5EwChpIQGiitZbE+t5kGMCjloHnBxevsCRgQHRRmRcOwVcwPjTVpeZ/w+WySKl4SL2HtLfrl7QkqIrBZJGhRkL5n3/hgFT5uRa/l7QDy96/NQsvpiSCFcTrOJTMYWIHtpShFs2oIuB6l40mqRkV+793zuNexhRO5AN/4WsLOndiItyEJy1oGoSQUjYyZiDQSbASA6AcNJowoTk6Acrlp4JhsFDYntILNdzA5eIgHMeJHrCBQEEPila5f1Y+4SATIQaHYBAe0qQIYswvNHp/OD/PI82101ge/SV5pIS2HL0zWR3w40wq94mwxUaIC2vagc+RysWjwNNq6r2sbYUGhCbZyVN6nYQCPJ6FD86jRc5iHbZE3wzAyGekwSE2w0tEfR92sN0RNMQf0s5yyDEMNTecMC6odcbR4GNjWT8nXM9nCGQbOk3lJIFwinHaqXZO2HLc/mRdg8eUwym4qisIsBQEGEGRkFgCDAFkFBFCACKsWQSIyRIKRRGCMF0TXUPhyTvw9x4acvgn6MwcUa7RPzfLPH0sIUVEoycRPesDORDghm7ogWNOMQvKywmYdeFq7T9B+DbffcVF/VS8WsM3v9aaVNi0VLz2uuEbJQnvKZ4oKEQQ2lUOUje3CNujePD2ziuWh/ytuCz+SN3llo4RunhFaT8trUF6T6gORVBRVARaoo2kWK0I1/gdvV1dXxEsBZTkpnKEgU0pAhEKIlhXDMGeMSU5NexlS4FK3ADSsWEzFLCBRBJcMOYw75eAOAYfDvox8YYpUx84/ptY9sun5HiAkYLIp9dPpnyU09Er7HjZHDD9IOO11XRIcdP+AVC4NPqS3qlRPsXtaKEfjZTVmt3wtcp3TmP4QIyLOpfAoLjlt6LKbpLbabG0axp795U1+hVloS1CbFrEqOZ39yGxWUT+ckGvsdm9/R5FsBDIiHWBDFIDnxGZlpFgwRQR0hsXWSBpgMEsbsUgJIJKwoxtikWCjiFNOM9BiAmfVJQ49VDDE0QmFSRlhjRHGNrgoFuqEpC7OxrdM8G93UI+IrbvaMuGlXkq00aQxBBgmaKqDbHSDfXA2aWlqHLChhItAyGknX1FaukhoqbOKp0ZrCxo8GFDATZOhEhkVoPsCKfURhH0I/aQQMAA3ajh3V6t9GHeWw6dqaNrvC0AzmpOIU7fxqF0XIIQhxlEgDJISEPANOvZ3BxU2GDkIZwWQQL0GCYNKBBylB35TDDHHqDIELIOGoEIUbiLKoHpPHVmUZGKJ0JRha9lKEPqdwnbThCw/E5u9TB4et5dlzaRDd4JM2pqOxsyed4upjiJFi4JjeIt4G/4Q6Gz1Y/Sig9sUF5EO7Sd52Ih65EQMXXIh6MNxgOZDqHCgsY9PKUINjVULamwKGAyHR3SrqzQOUso0TVC9tC5QqMsxbQ0CB7vvmG6K9iVlHo949foa3WclkhYIT28HuuDQ9lOvX8KFtCxDomosY/cNtstNdEX8cKfJDZbuQ+EGGglEikgjTe5OxVQ9LevxpzQ0hRrJ3eNmmrx+KmoiImhoVr/AmY/1uOVtatkqbiXLmV4xvzL/MdTk5ePDoA9LDkeM8AoPIIp7Al5hhgk+uzfA0k92rvHFHLYwVgjCWMhTBbgCNyhH1gB8gD+phO4/TkBoQ0RYaD3QCDBZCxFgdu6lcAYl6iAkgk8FCtgQfibXQBmjUB0wjEQ+UV+9hucA45OyTt6y1p1aA+RBfx7vAOJuPgZ+CKfxshxIes9DANApGRVkBGS5KIiupmFfW6RJUbhhAUqkKKQNAwFoQdWAIYKXY3gNRKgsgNQIUGWlAsBgQRhFIxKktBsFhIshIKLFAsAsZZRAsGAhQEYFKEFSAQghGIRad4c0gsFJAJEc5q9RT74jthEg2h5CgtaJi98hOgfBO/cyQg4HfvVWGDUwQylPnbyHPpuqwOzMyx9x3247MqPr+uL8z0cZByQ283ISKxSHLY34zuvLjwvnzMvKHRkGTjlnC0F6Vhr9W8QoJb8tsJZB9DNud8i9+1xXyTZXidvAo0zT/cbDA2/VX7rZn5HbIjZI34XfbkjFb/dKkYNYwRnRDYdktBPsY8vsnEHWDqDM2HgQ4lc4JUDrLTkm6jjNRCTFB6ylFDMjm/NRTDl2QEgtJvNMOm6RSZuEdruR1odo6dRMF/ss1PoqTW2Odo3LagpFczRZLlTn94+gd226Sx88aqKoWphvHMHkyI9p3qR04eOqKVc4tZU4NcTC8UHeH1veb0E7020u8OEt4Zt9B9MN8TdHdSZsdVM9ZbjPiruZZNCH42KjJpXEW9LT0jbU7hRbQnrKx7t5tZWQ5eQZDQ7f1PfMEu5wTYHGsFjriJho43mqD82ZWI4to1NG+LrIJitGuLA4nbYeuhQ0GndJCqNq+alZaTsoZj7+T9tuC1w7bWUaih3QDAPMZ8+01NyGgNULKjlboC4OTnAXkXArDMNDMR6uhQkVLA4IEZeSbFtkT7acSaUB5oWep5VUiXuGFcdRGD44PDoVOoUNS9JPh68Xuj1EhcJ0I4lFQxuP/StrmrNFpXbhUM47jfGbNGW3hWkqTJJOyQ+RVuWrTJCTaJuBE5EHVvtpB0KnUkXPu9aiaS5fcGocowhaZVM+0vzQMEDCGGl3Aa8uw+g+LCa8QzHNgxdFz8ZLikDvWtXRZVu+xhrjh6f0cDINXbmzPQwtPpj8sA0qENOiC5PDzGku3cgpiFORwKQySMhNMpkEbpv3popMhYeuGJSzdKIipEEGAuFoCm9sFhHQCIygbbFgKQVAr2RGndK4ESgKCgab92uDPenQwbSrfClUXUvLRbQ3MZVDv+J1ELlwmgxISCfxeVFztzMZUKLhZbYR+vVEdtSwdgFSosGIDNUihcKVrCo1C6MAKGI6+MdaTUuLs0XEqmqFbkIpCacFSa1mamhtllovXZBQym7t2VlMxBuvKq1RqurLaRwikeOqgXCNoPitYsSSO9OXSe+J6MOQ7d1Clu58WIwgc0DogaIdDSQWhbfZ9d61PbhzxcpjMbVZbLCe07nwFTUhuGIZGLkWViYCj8sE7GB4qqIrFWPpezchfht/pcU07nt32N3x4ER6jyIebIRgydN1YeAW3EjGBAsWA4AtojQ40h1Ga3ehm+/qVbix2WcYgP2m17UDzSEimMM2X8oIEIZA60Nqvoo2kdzCjn7IdZ9ExFC7IheUs6GeCeZrAJw2JI1UbM5Y208TXPe1i6SLpMY2MgoIixiDER4FY3EMh9AmTIUiJRKNZWLCAhIggIAshBHzoVWHrhAsmQMsCyX0XGUxPQNReLSiVkS0XeIjWx4wg2mnlUKN1REYZaloWEwtcYTEAqSXMGrIIVC0IJgxaHEim0pXMVKddizsjRFqXrsfZZ2ppHaT6OPecjzDWnlacg0LsjWaeiSLkOh0gqcowox1w3BRpNiXgsMdFIxJQK80R3mixRdUqJRVUbXWEW7dv+LUKJexIBWkWj0T3ATKF8SSZs7KXdQ4pCHPNFh/STfphjbTKTOSlVAolkCLmBn4m85BoHBjBNAX0Dtgd7NhNIMLBt4XwZhmVA9NoFsR6KaCA6kbWCPkvJDTCx89na3tNRC6LamVIxx0K9yqCmgiYfV4a3v5+PG1zesS6tXjbKpeM4EOZ9Vt4419exx9J9/UdWC6WQz+xYHOlW5p+oliUwzmoPVbyy1qm/MMIOWYZMCXm5Lzx5iMNNGg0wTiJP1U2WhJNNhIvN50aiEam8ly3MNORvZcjgOh6+9w52cWxZl2T9dOBLCOOQcmqPOWJgdBaA78crowpeH563oymMduIwmS6Cmlmdx3bvxxAqBxM0rYmOxBy+dwYNHXEw61EgeNNdJwlc3DOqO9qGIycwy5yoKcc1dtHCGPrhpoic6jxhQpNxjhskTpU8w7wgompJIRRpQTa+/XFJXNGt97wLGAxggNjERiXQaCKNsSNeDO4E4qT3KMBzyTgQDljEG5cmcUCbswYok5qPIwOTK8cUDaGqlE6OHGx1BLPGFFMgbaIE2lSYoquJyfbFet3GhD6mOZqaKhJPUjijbv3b3cEY25I7UFPQhZMMSZMtMadjrYOzNg9nv2caws54cs52skZdVokt0dP4ltvFSOwyL7TkzHLHuhoaGJprZINNHBhuCMwUoTTBRiE0kZShnqDWhE6pTYwagbHUWjZ1EwDlMVVG5NEfDplkWa0nThVTO5eKI48pit8Q+VrKjHHvhhguGEhmxkdGggaELAqjY0JpXQVQaIgOy43XRKlkoe8k0hKPJyUbQ6zBwlKBzUuRNVlmxvSsunq10aw0SYLQIjTMIhMcTTGwZzM74xiTQdeia3BUYU3mUlDYihisUKyKIWFNgQJ4eHqbZwEYWNbA4oEcOJ0ad3ptouSYZYZ0DVx2fnqOJizSRs5pCIhY3gGIB+hI7o6emgvIQFkVcgzliw5tMxMuWRinSnJ3g3NAYIoQio2MNdKJfWUxMo5TDN3TA0IhplGMEiJYjhYUshYsFkVqZcRQTQMICxhJIDGkliKQFCiqVKHYOpod87uDlwSrNVbSoq0zIYJqU0ihjdVJQEFDoNDDEgpo8w6y62NfgrLDJEDmQDkUgc8pFwOxvweEex0yrR1gco0dBJ/GKPTg/f6U6KsA8wYxEShFpT4Pq2s1sXJaMYZ7LRDQA6iexUmEhXMo6EiEHYBg6OmhzwSsCt6ZOEkOW7eYHQg6Rgv0RQKVKgK0Q7YpSGZUCN1liRRHJ+/DBXX1DEIN1IFRJHh0IoM5Aw9s34ooPkoQDHlPwcE3VYxyoLkHvPV3BVgKhUOPK7NAhATuZyiCovUYbdZ2+7vpmksHaeOQnBBvBgXALUa422FTJAoVFGadOEpJo3wKIM0FhZujTJcjemkDsNJp0+Q4fm3dsMZDF6LEjRsaylFHPtfJNh013rF3wyQnbIdwMhuRU6wgHTept8BMDMmKQOya4CHGIOkhzKetVVXyEO0UdpOPmmLURhXZ/AdW2Gw8jzstsDbKqirDkQpRGHgJQGwQRH0pQIe83E7Az11rb6ZtTbs6Zj3m1RzhALKmmiwHZkZ4ZuJ2iZlDquWNBGCggIAyT4n5Dpt5KsGanG8h+gQ5JBNqEETgEAzC5g5bzSHyffv8Xko02YURoYyUzXYPE8fQwrXBlyHOVayINtGYSNc0I2wcacy7qqRWTSpIGqBWhwogl7oQu4SjCQqVelOqatvXmzL6DS87hEkGgWgomwShA9QbF1gcgxFvpm4VsohaAEgZAQCg2gb9iWNWU2RSHDsJCEMaMe2rksePpEOae/zqlB0IcqLL1onA5RzE7YrmhhW4KVMwwz2aIQuFC0gyLBUYxEYTaNQNNtqM5kRv/s2IREkBG/mzEQ5EAoJdDED1D7bgaxdQrnJyDIXnFSBJB95AWEHbCfz8dIQ94Gic4CE/4Gx2WiKhERpSMUJEDJBdURtTE0CwUC8g9WHvlC8PGJo9jiGxfTifD20UH2wuNVmNuQlqn/3o3ogtpfaWXxMn5kglrGiAYEc85odauTYfBYWHMK9cFXALJjXkYBIWSD2FWJEOQXQjw6urTbUVsKeFBVFiyR0mdVT80JQbEb86wJGEeZmO5MSJDXqrqgaggO4jD5QvlPd+R97fm75ANkYL/ytVmWzLJRYCgsRIEUiQ2oRmkDPGWSgyxEoBuy0gzyag1dXR9ZBCEzKFyfk7LJ5uNTBrmcaPqnxDAfSL9oRSRxOw7s6RmZeiRWJGffhzJ322344UYswBYMoWQsHz1lgAx4Nfo4kKZqfFMy8rBSF1tkibW5C/IvpgJMQVSMc4gM4YHJDhpPDMeV5lULkwgSLM30BYMs2NH5C6YsMhpMhsKNDqPiDkO6Ic54GYzB3mYwF5BH1mEIQoiKIiQsMsMApPrWkQfQ/1+M/Dz8XizH3fyYxi+kcpsR7EokXiOwA2lAZXwyocOguUtrMYh+whe1BE8nzU5TkcDxhqOPPvS1AR7pCX5SmoH0USKhBkgrIoFEIVCSid6AxRgoQFCYyHxigkNz3Hv1GWQgl2M/E40H6Pw7CZEbMt/ijZvKx0fYmKR+UWtwWjPuHbDdBijh9n2i8Ijt22OcjQy08xs0k3vb0osMEqDqmwaseASwZUQ9FObj9NzeEOiEyR4Q8lshUDiHMprN5ANLtGwaEi9BA8tkTxhcRN2lEywcoZ0MlFzmR0aclX3wXAPuOQGcgJtNnm9NHdzPbZ7oScR1Fy076WEP84fLAyiTzn0BYwffPwHhmbSu/gGoCCC1jyGcvefFojP9/AlR8xU+07eLXlS89Xn/cUqzh/YVJfKXGDGThmNRMv/1D/p7PT/vP/4u5IpwoSF/BRlGA')))
\ No newline at end of file
+exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/presentation/instructor/intro_python/unitgrade_data/Q1_WaterHeight.pkl b/examples/presentation/instructor/intro_python/unitgrade_data/Q1_WaterHeight.pkl
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diff --git a/examples/presentation/instructor/intro_python/unitgrade_data/Q2_AstronomicalSeason.pkl b/examples/presentation/instructor/intro_python/unitgrade_data/Q2_AstronomicalSeason.pkl
index 2d677c3561d435b085828c376c30118f918b7c5d..141e68b2ecfd7e8f1257dcad58ff995b45226811 100644
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diff --git a/examples/presentation/instructor/intro_python/unitgrade_data/Q3_TimeAngle.pkl b/examples/presentation/instructor/intro_python/unitgrade_data/Q3_TimeAngle.pkl
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diff --git a/examples/presentation/instructor/intro_python/unitgrade_data/Q4_TicTacToe.pkl b/examples/presentation/instructor/intro_python/unitgrade_data/Q4_TicTacToe.pkl
index 163e3b6bbf380c2ec67ca64c32d89bee735a97be..6a423050716cbdc910777b42e19a27badf016605 100644
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diff --git a/examples/presentation/instructor/intro_python/unitgrade_data/Q5_StandardizeAddress.pkl b/examples/presentation/instructor/intro_python/unitgrade_data/Q5_StandardizeAddress.pkl
index a55324933d96a979dce39176c27427e4ef8b5ea2..c04eb5ac0263290466e8e5ac540d4958af14a21d 100644
Binary files a/examples/presentation/instructor/intro_python/unitgrade_data/Q5_StandardizeAddress.pkl and b/examples/presentation/instructor/intro_python/unitgrade_data/Q5_StandardizeAddress.pkl differ
diff --git a/examples/presentation/instructor/intro_python_devel/exam_water_height.py b/examples/presentation/instructor/intro_python_devel/exam_water_height.py
new file mode 100644
index 0000000000000000000000000000000000000000..8d7f91130810effad0c673d2b49088832ae3d2e1
--- /dev/null
+++ b/examples/presentation/instructor/intro_python_devel/exam_water_height.py
@@ -0,0 +1,13 @@
+import numpy as np
+from unittest import TestCase
+from unitgrade import UTestCase, Report, hide
+import intro_python_devel
+from intro_python_devel.water_height import water_height
+
+class Q1_WaterHeight(TestCase):
+ def test1(self):
+ h0 = 5
+ r = np.array([4.5, 0, 1.5, 0, 0, 0.5, 1, 2, 5])
+ h = water_height(h0, r)
+ self.assertEqual(h, 3.0) # Check that the height is 3.0
+
diff --git a/examples/presentation/instructor/intro_python_devel/water_height.py b/examples/presentation/instructor/intro_python_devel/water_height.py
new file mode 100644
index 0000000000000000000000000000000000000000..a512d8cf00c5625a32628aafb0f0374051dc4416
--- /dev/null
+++ b/examples/presentation/instructor/intro_python_devel/water_height.py
@@ -0,0 +1,11 @@
+
+def water_height(h0, r):
+ """ Problem 1: Compute the water height.
+
+ Hints:
+ * Remember the height must be a non-negative number.
+ """
+ h = h0
+ for ri in r:
+ h = max(h + ri - 2, 0)
+ return h
diff --git a/examples/presentation/instructor/secret/scrab b/examples/presentation/instructor/secret/scrab
new file mode 100644
index 0000000000000000000000000000000000000000..fbebaf1b7ddaff41c7542b5676d94975c9b04cdb
--- /dev/null
+++ b/examples/presentation/instructor/secret/scrab
@@ -0,0 +1,19 @@
+
+class ReportWater(Report):
+ title = "Water height problem example"
+ questions = [(Q1_WaterHeight, 40)]
+ pack_imports = [intro_python_devel]
+
+if __name__ == "__main__":
+ from unitgrade import evaluate_report_student
+ evaluate_report_student(ReportWater())
+
+
+
+from unitgrade_private import setup_grade_file_report
+from snipper import snip_dir
+from intro_python_devel.exam_water_height import ReportWater
+
+if __name__ == "__main__":
+ setup_grade_file_report(ReportWater)
+ snip_dir("../intro_python_devel", "../../students/intro_python_devel", clean_destination_dir=True, exclude=['*.token', 'deploy_water.py', '*_complete*'], output_dir="../../Latex/output")
diff --git a/examples/presentation/student_handins/intro_python_exam/report/index.html b/examples/presentation/student_handins/intro_python_exam/report/index.html
index a990847bca94bd94089700baaeaca7455b91cdb2..a7148e9fcd6c21f2f6f6a8aa8e19f2bc82aba816 100644
--- a/examples/presentation/student_handins/intro_python_exam/report/index.html
+++ b/examples/presentation/student_handins/intro_python_exam/report/index.html
@@ -4,7 +4,7 @@
</head>
<body>
Moss Results<p>
-Wed Oct 12 07:50:30 PDT 2022
+Sun Nov 6 09:29:09 PST 2022
</p><p>
Options -l python -m 10
</p><hr/>
diff --git a/examples/presentation/student_handins/intro_python_exam/report/report.html b/examples/presentation/student_handins/intro_python_exam/report/report.html
index 0218ebbde0a63cf859789e32a55a4ea99c40c826..e031d8bb2571200f991b1ec0741bbb3769b9e06b 100644
--- a/examples/presentation/student_handins/intro_python_exam/report/report.html
+++ b/examples/presentation/student_handins/intro_python_exam/report/report.html
@@ -4,7 +4,7 @@
</HEAD>
<BODY>
Moss Results<p>
-Wed Oct 12 07:50:30 PDT 2022
+Sun Nov 6 09:29:09 PST 2022
<p>
Options -l python -m 10
<HR>
@@ -12,23 +12,23 @@ Options -l python -m 10
<HR>
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<HR>
diff --git a/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221000.txt b/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221000.txt
index f9f4351309473a5d62f166cca66b108b5a69eef2..0f5f53aa14a2fa4701a85cda8053706fdb755457 100644
--- a/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221000.txt
+++ b/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221000.txt
@@ -3,7 +3,7 @@
| | | |_ __ _| |_| | \/_ __ __ _ __| | ___
| | | | '_ \| | __| | __| '__/ _` |/ _` |/ _ \
| |_| | | | | | |_| |_\ \ | | (_| | (_| | __/
- \___/|_| |_|_|\__|\____/_| \__,_|\__,_|\___| v0.1.30.2, started: 12/10/2022 14:50:40
+ \___/|_| |_|_|\__|\____/_| \__,_|\__,_|\___| v0.1.30.2, started: 06/11/2022 17:29:18
Introduction to Python: Exam spring 2021
Question 1: Q1_WaterHeight
Question 1: Q1_WaterHeight: 0%| | [00:00<?]
Question 1: Q1_WaterHeight
@@ -97,7 +97,7 @@ Question 5: Q5_StandardizeAddress
Question 5: Q5_StandardizeAddress: 0%|
* q5.2) test_standardize_address_hidden: 0%| | [00:00<?]
* q5.2) test_standardize_address_hidden............................................................................PASS
* q5) Total.................................................................................................... 20/20
-Total points at 14:50:40 (0 minutes, 0 seconds)...................................................................40/100
+Total points at 17:29:18 (0 minutes, 0 seconds)...................................................................40/100
Including files in upload...
path.: _NamespacePath(['/home/intro_python'])
diff --git a/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221001.txt b/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221001.txt
index 8da72f29015d31aaa8c528e5ce677e40c85796ab..4cb2753a33fcd6f7e3ea4e360b84a69ba6c19f86 100644
--- a/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221001.txt
+++ b/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221001.txt
@@ -3,7 +3,7 @@
| | | |_ __ _| |_| | \/_ __ __ _ __| | ___
| | | | '_ \| | __| | __| '__/ _` |/ _` |/ _ \
| |_| | | | | | |_| |_\ \ | | (_| | (_| | __/
- \___/|_| |_|_|\__|\____/_| \__,_|\__,_|\___| v0.1.30.2, started: 12/10/2022 14:50:41
+ \___/|_| |_|_|\__|\____/_| \__,_|\__,_|\___| v0.1.30.2, started: 06/11/2022 17:29:20
Introduction to Python: Exam spring 2021
Question 1: Q1_WaterHeight
Question 1: Q1_WaterHeight: 0%| | [00:00<?]
Question 1: Q1_WaterHeight
@@ -53,7 +53,7 @@ AssertionError
* q5) Total..................................................................................................... 0/20
-Total points at 14:50:41 (0 minutes, 0 seconds)...................................................................80/100
+Total points at 17:29:20 (0 minutes, 0 seconds)...................................................................80/100
Including files in upload...
path.: _NamespacePath(['/home/intro_python'])
diff --git a/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221002.txt b/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221002.txt
index b6689e9b6631ea43b55e298a6a4958f03fc1d155..a87cc97c03c19b6e01dfe93a4fca3935473265fa 100644
--- a/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221002.txt
+++ b/examples/presentation/student_handins/intro_python_exam/verified_tokens/logs/s221002.txt
@@ -3,7 +3,7 @@
| | | |_ __ _| |_| | \/_ __ __ _ __| | ___
| | | | '_ \| | __| | __| '__/ _` |/ _` |/ _ \
| |_| | | | | | |_| |_\ \ | | (_| | (_| | __/
- \___/|_| |_|_|\__|\____/_| \__,_|\__,_|\___| v0.1.30.2, started: 12/10/2022 14:50:38
+ \___/|_| |_|_|\__|\____/_| \__,_|\__,_|\___| v0.1.30.2, started: 06/11/2022 17:29:16
Introduction to Python: Exam spring 2021
Question 1: Q1_WaterHeight
Question 1: Q1_WaterHeight: 0%| | [00:00<?]
Question 1: Q1_WaterHeight
@@ -75,7 +75,7 @@ Question 5: Q5_StandardizeAddress
Question 5: Q5_StandardizeAddress: 0%|
* q5.2) test_standardize_address_hidden: 0%| | [00:00<?]
* q5.2) test_standardize_address_hidden............................................................................PASS
* q5) Total.................................................................................................... 20/20
-Total points at 14:50:38 (0 minutes, 0 seconds)...................................................................60/100
+Total points at 17:29:16 (0 minutes, 0 seconds)...................................................................60/100
Including files in upload...
path.: _NamespacePath(['/home/intro_python'])
diff --git a/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221000/Exam2021_handin_40_of_100.token b/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221000/Exam2021_handin_40_of_100.token
index 5299c6053a962053214e5c413eb07cf9e9592588..7c8a0dabd12fa0202ca73f06c634540d1f78569b 100644
--- a/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221000/Exam2021_handin_40_of_100.token
+++ b/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221000/Exam2021_handin_40_of_100.token
@@ -1,6 +1,6 @@
# This file contains your results. Do not edit its content. Simply upload it as it is.
---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221001/Exam2021_handin_80_of_100.token b/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221001/Exam2021_handin_80_of_100.token
index c87bb157271e542dc8f868dbda320e8d100af525..14bd06d9e4e43875d90890687755bf909a0e9a96 100644
--- a/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221001/Exam2021_handin_80_of_100.token
+++ b/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221001/Exam2021_handin_80_of_100.token
@@ -1,8 +1,8 @@
# This file contains your results. Do not edit its content. Simply upload it as it is.
---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221002/Exam2021_handin_60_of_100.token b/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221002/Exam2021_handin_60_of_100.token
index 7d111a647d4a40c54f7c966dee1494e01db2218f..191a9013c281e658dc660d87e442d3535cf9fcf5 100644
--- a/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221002/Exam2021_handin_60_of_100.token
+++ b/examples/presentation/student_handins/intro_python_exam/verified_tokens/s221002/Exam2021_handin_60_of_100.token
@@ -1,8 +1,8 @@
# This file contains your results. Do not edit its content. Simply upload it as it is.
---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-fdc72a077b1cfde9954b1f6b1f90d0b66d5d7347ac04b6e88c626ae754db812420d7301f37a3da2f2e5fa16c4cb8af38c5c64cc0be494ce91910af5c7c92242f 70296
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---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/presentation/student_handins/token_evaluations.xlsx b/examples/presentation/student_handins/token_evaluations.xlsx
index 332ec899580c546cbe43b1fe5c1f1a08ef8c1807..3ed799577e458a3210d2747405b4664396c019cf 100644
Binary files a/examples/presentation/student_handins/token_evaluations.xlsx and b/examples/presentation/student_handins/token_evaluations.xlsx differ
diff --git a/examples/presentation/student_handins/unitgrade-docker/tmp/intro_python/Exam2021_handin_80_of_100.token b/examples/presentation/student_handins/unitgrade-docker/tmp/intro_python/Exam2021_handin_80_of_100.token
index c87bb157271e542dc8f868dbda320e8d100af525..14bd06d9e4e43875d90890687755bf909a0e9a96 100644
--- a/examples/presentation/student_handins/unitgrade-docker/tmp/intro_python/Exam2021_handin_80_of_100.token
+++ b/examples/presentation/student_handins/unitgrade-docker/tmp/intro_python/Exam2021_handin_80_of_100.token
@@ -1,8 +1,8 @@
# This file contains your results. Do not edit its content. Simply upload it as it is.
---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/presentation/students/cpp_course/fractions.py b/examples/presentation/students/cpp_course/fractions.py
index b13ef5894ff3236c5a3aa0775d1c7e46d93533b5..9b80a9bbd73c4cb3944d8030056d8f400b19d412 100644
--- a/examples/presentation/students/cpp_course/fractions.py
+++ b/examples/presentation/students/cpp_course/fractions.py
@@ -1,10 +1,15 @@
+"""
+References:
+ [Har20] James Harrison. Optimal and learning-based control combined course notes. (See AA203combined.pdf), 2020.
+"""
class Fraction:
def __init__(self, n, m):
self.n = n
self.m = m
def __add__(self, other):
- # TODO: 2 lines missing.
+ """ Computes f = f1 + f2 (where f1 and f2 are both Fraction-objects and f1=self, f2=other), see (Assignment 6, eq. (1)) and (Har20) """
+ # TODO: 1 lines missing.
raise NotImplementedError("f should be the result of adding fraction 'other' to this fraction.")
return f
diff --git a/examples/presentation/students/cpp_course/fragment.py b/examples/presentation/students/cpp_course/fragment.py
index d213567d25faf0f13d3e8c4be32bedc353784bb9..0ea0ff6024d2b542ff17c3d3c86857289b8bacba 100644
--- a/examples/presentation/students/cpp_course/fragment.py
+++ b/examples/presentation/students/cpp_course/fragment.py
@@ -11,4 +11,3 @@ s = "5 / 2 div 10 / 3"
print("Result of", s, "is", from_string(s))
pass
#!i
-
diff --git a/examples/presentation/students/cpp_course/tests_ex6.py b/examples/presentation/students/cpp_course/tests_ex6.py
index 8cc6174659c097f70516cbf045da3ef8eb51ad8c..37279706929501fa4d17e92beae6a3a97385687a 100644
--- a/examples/presentation/students/cpp_course/tests_ex6.py
+++ b/examples/presentation/students/cpp_course/tests_ex6.py
@@ -3,7 +3,7 @@ from cpp_course.fractions import from_string, Fraction
class Fractions_from_string(UTestCase):
def test_from_string_manual(self):
- self.assertEqual(str(from_string("2 / 3 + 4 / 5")), "22/6")
+ self.assertEqual(str(from_string("2 / 3 + 4 / 5")), "22 / 6")
def test_from_string_smarter(self):
self.assertEqualC(str(from_string("2 / 3 + 4 / 5")))
diff --git a/examples/presentation/students/cpp_course/tests_ex6_grade.py b/examples/presentation/students/cpp_course/tests_ex6_grade.py
index fd11dbb77c1ef8459f783a76addc835596e4ecd1..7b7ec2382fce1f42c3ab58defa579f42eab1b96a 100644
--- a/examples/presentation/students/cpp_course/tests_ex6_grade.py
+++ b/examples/presentation/students/cpp_course/tests_ex6_grade.py
@@ -1,4 +1,4 @@
# cpp_course/tests_ex6.py
''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
import bz2, base64
-exec(bz2.decompress(base64.b64decode('QlpoOTFBWSZTWUiXnNoAakP/gH/2xFZ7/////+///v////5geX73u8vffZb4eBR9BJt6d3rnCgAoCiCoSqPY0HdYOqhUA5AnZjdvn2r3bXj6HWayopWm6ygk9AANCnbfd8+8PPsKHPrNmmTcH07Ty94GD1057a57ffe+LHt97J94Xa1m1b5gHfX1DpQXete973TkoN9fWfR9vu3tTV1y5mfW6hET5mbNVrjvcaHPvGnHtzXte03yqAPoC2d7eh950XX3H32d23zd73hvJ5qwbC997rd67ve7EGst17fXt595Pu97L31yqfXru73zffHgsT7dZ57vINe8eUnvbnc7sOahX3dFcj21XY27e9777mvnm+I3323xK9725dd0erglLnnx7YD3u4cd5oa3xvusDe17je+Bl9sIvTu4zV77vHN729Njuz3t0Xsdy23uauvmucuEpogQAgCBGQAjUzRNMU9Jk1PIm1MmnpqabUxMg0aaeUBKaAiETSZFNpiEZGTU9KZG1PU0bSDR6gyNBoAAAaAEgkhBExKemmqexT0ap40kbAmp6gaAPSBoNDQABtQaASaSJBEyGlPEaR+o1GTJM1NMnqGTTQyA00Gh6gAAA00ESQgQIaAmgEyaBNqPSNKeamk8R6pjI9U08pp6npMm1HqBoNBJqJEBNGQaFP0SepmVPU9T0R6ptEw0jI0ekNBpo00ADQGg61fuIr7mKKh80UfkYkYp9MQAA+SRgQUJCSkntUWKqL8F/NfHC6qGnH9n+lon/syI/oefk6f3cfXscH2f4z+seEHB9n2Xs36b5Uw/zgkKSzcJYSaEyQmTbf4RdlP/JSFzcdY2rjFN2tS8JhFqIdoVR6QZLqbg8lOc7keHnKiBRn73+bRXa9wwuXdCW0T6xk8+bhKhSi1iNQ+KJIcgTk7E5nPLpB+8+4lOPt/0zxBcnZ9eMRER1W/hKnGVNKz82aGCr9HE4gCKnQQURQe8kCHujCRQUgsFBEikkWRSAHzELEWRBFf20mBAAM/zYUAgESCoEiqJjEWG8ytFQlb+6tZNpXhDDFv6ei+UwV0nqs7IeEN499QCmgkkRIKssjRVQUU+8wsGIqAqkFQQEVWAt1RI/q6z/rn1PMF79c/JxF5u4/3/5zu33a5w4ByKMixgyojx3jZZ4pXu+ZIdpuSa6ZnB3+Xa9Hs9yxUkBkGyEfWIlib2kkq3mPZq0ntgxRenLWCb7eGcvAnY4Ok63353cZtz44uKMbK4xFk8s4MwYypkjdR5yi6XluP+5mVLCozdTDX+Rcb2FtDP6NI/ox//V/RanXj1+Et4iUa/6yuzymHVslRv1Pkkf+pMEv5tI/rKYdbkcN+OUoTHaj3p+nx9sz1ePwov3u3iIyGYyxO0wc+enfB9MJxJj/Wu0rp6W4/0fM/l0r7mzaYjK98igOYCHR8rQZTla6P4YxAmf6L8b7lI0d6s4fJzFI8/IRNsAkHu9YmjL43NQzDJHgy3vDR2Upl8jRwcEmZMq5Z7vzSfC17PKtlNTg4279GfT+E4yGh8LQyxvCQ9IhqTpc1J34XtBJFGwfGMPeR8u3rHeZ6cx5NH4/T6NZ/ud2k1Xm3k8/mhnmz+ZgTL0/VXX1fNUi799/s3aTj2DzHPlMxJE2u4jyXob1NARJTiXOVrnvXP915z4thviMBe2PF1XlqG9bYtB6JgzP24pZ40cNci0YW5W21WnhkU1m3lk/xLyIXD5+24+evDDXUptwH6Y7oJ6OTlG7V/8+RFtJ3TUg3CXLljrjdGtpTr2y4ZE6Us9sWpePhx0lwrKTZY8VG8nrntwrjmakd/CemDzRciVo3dHgzpzphTdMvtt7pOiePhYrNT8KKK7p0IWMTiXJyW8cO4lw4FCaNS56dbkU35cZ3E7tIJW0MKzLtMOmDTKsPxDQx326OOYI8ke7iYXCRw/W4jSF4eMN2TMmLqU5NM/vtr9XqH5Xj2v2ltpQnd8Vxwkvb9RxSyar5TxTE+aI7XkWTGyyTKXiK+XEF5NHoH9Yvt8h21N1I9cEAiKRpG15SAoL4ikTqPEEFSA2NwcfQjcMEdqFby3S0whnyMzBdOhg219u/lyTCASd9Ni2c2CVC+WZ+5oBzTIQyNvaTyHHdxsEV7uWXAuNzMXAo2VLEOkNKEhkrOG5LdneS5kZV+5VeZoLWOxztxl3HYk1JBCQoG09ZM8ltZyL9EQKBCEISSBFk4L5I0XEe+dM2hgtJZLN1UZ5635EY3vJXp0et2nv6ODMaA+ph9V8hfL48SRaxkWB5odibmE+Hw29XRSJ1GZ1JDhx3XW5+dGqog7X1nbVw0HCkRxqBlZFWbg/WEZ7vSfhKUcH7WarvbnSkKjejdjXDZ7a1A+navn72eGbjyRy2YQbIEP0QM5XYg54rMfvdSf76hBLzarCZoF7j7WCD6quesjjYka2+UyQiYv3g4+0jDFibOPo2xMSmp7sICcmf+BzeCpyEzCKCPwIDWhgjFNnAwhmmZjcZL65SsUoddclzbGYyzv0qr3zofNfBvptjgk+QrmxT7qed74zZrtLrnNKn6pfv7FAfnU5VQCp+RSExM6anHP20FQPgjErUw3bPnXWMCFngFxiYm4njLaxLX3XyPhfuzypS9XmomtCYwHIXXUOum0ia2uM8J33pk7PE6UaQYZ5s9pUuiFnlLKb3s+GPiRVNB5rEiwXvTKTm2CnRuwkUjT30tJxCRLO+ITVOac4c5xYyC87FXac1Qq51xKTMpv+1Xntp9BfXAkP03hBKViT9esZyrncG1Az37Z5EkzyneI4GHrcsQ0uuUcj/DEcrLjKOGVNnkCw3U9RrM4btCxLC574ctjL2ZO35V4F/91+bTy6bxWBHXzNtkjGNhi8u3G5qdGn+TT+1QQrveO3kbvxjwJGBeNuNpZM2k10CDOzEiMEHgWqGaN82lVuUZRxL3E3mORfGBGl2Clm0HyTPK8tZnaDo7sJmuPbL+LAYNKS2LXFMDHXXXjMr6uMbi4vFwqxcUCr7OYY73GD9mE2qsRo0OWB5ZR7iWoSl8D3ENjORDiaznKrB3eM90efR87ms9X8dDsOJVx2hzBln03n8Rw5RMFSiuLzVUaby5Gm3TdB+XeZlxZkr6Dj+RQgx3j5jjKOkp2lO4v5zyEhIVuOsX63UabNkh7STVBdhbXTq2prNX8TIvxr2RmVInTdkWMDX6MjVGWKSAEJCDNNXZXF9JMilS58ubXIIpfPp57oKdnKtpDhyN1fZPY18HS4bFQvdXMuR9MmMkavv7+vN2SEYSUP+MWXY/451ajO7Tcm5WQTNQPDwVtOKiYs45Dn3tJmXGwlGP6TR5I+EXqy3TyIH1f4ykm60rQkpxli+vWhRjA4j7zDxg53aG7z7GfY1nFwjH6JEymtin3ykU3bX+MkaGs1vmXfa2BU/Du2oajmoaC+o0J5W575Ghe1yZa4SMd+/8Dh+JaOhXgrp16wX76ny1nWyHbPnIam8BI6lNUG+M2S51jOx9Gg8jv27dZwpmYmaJg+6+Tej9QIvbgn9YUQCEQ5wWyl03P78RERfuOc90ytW5w8EB35bUkogECSZcQSeoOglsR60V9KPr2e7L07o3Bth1pvL6FtBz2u9zRrdja4JyxQ4+VqXMznO5Fod0D/D32uTu+B8KYCtdFyb2Jh1Ff7LdEs28ucDfyWn8WzOc/E8zeHhepDP7NJ49l+utZm73Y6ldX+Z5XW3vrHaZGjaikZv4Z4a2nKujbVoz/GaZFCRMNUZmU3jedcDEq9lWWtxnpTskX+/rv7skja67UH6rSZyOBEm7GTNnGhc7fivcYpZfWVf7cXzqFcOfMRdNp0lEWeam3ZWf2aFrU7KFXW7bNwtl02cGzti176wGbpOxHquzxNFjlUfrJsuyyGHctvy3VC9lXJI4hCB0AhU1cBffyPmNOcU25eCsiLqMb22nvZtl3T2z7sdPB845GJU358M2aXij6H+RniLVmGZVyFX7hyqKd29mUei9MXL8EVxhpd+VMBxmTUKHeGR9Hc7Yc7/ae/VBR9DgdELtfwgg8UpQ6QpgTAiGJt48P+If5ie1Nm+c2e2SuLMDYeN9CYOM4M4OCV6Q52WxR7Na78Z2ESEPm/VzieioY8A/zEfurE03GGzwQE0mXvUinspKIiDbKOh0mCCqLbYqOHsqX6PeU1iN+/fAX2CZwrEp4xqvYE0N3OFwQE8TIdeGkVZt+JoSbLcw97TkXymXBmgujQ2MSwQhVvPdXFsFgQK3KWhKlMw+ko19KYRm0yGbwem7HKPHfin1DcJPaXvtifcsPZdMzpbB2Z3G4oJ05uOXmFxAT2UEUbQgKFxSNFKuKaV6h2JEzqkmadDCY+GtC68bN8PaZ3tLEi0l26n0oIMBxaaTndwoOlRwdPzw2yWWIr9/abzWwJOyN5cPLQwDfJ75NXdwNxoW2c1a4q0qqW4dTJvgY3NtBrqUz352JY9kG3DILgv1vK6yJMHBH4jL3FdTjY8ZzrcHHCs51nUdFZlpMeL86axZAfCzoneJpiek1yNGh0nTXu0wc8cxXh4pdIkHgi2ifbLOiqwawmiuO+Hh3deHGs810cFcoIjdN6a0xgsQbU7mkYrHMOasIsK9AkTzqpuUm+hW6WuO/BvkXXk7tnORo9CXZlUtk9YcekzdMojN3YvTsd1wcoFidl+06SEb7XaXNymb77u4yxGtre2BI46Y5E5137ZbQtcjBBdOYZspsmGQX7jhhA7qcT0Jv7VhOnOAljrkSIQurtNBYhCPZ6ScGItNbyLRLqho6E54iN8hoRzo+5ymD9KjPgH1enmdlHDnsFzYbdr4FrhGRFI5K9NLPhunnXt59K+E9jjRrRRuvK9XPA/QKAt98tWXWODpwlBMtWZ7i/BplZu12umhnxpfTS2k+dHbEuC4TTvsPFV+jKUCXnEHpPsbC9SJkNbe38Vdy3u/SLIQw4doLhGcI4aswMbfQnqeI84g8ljz7fLZpt6ySezvL8cXATNBN/RZSIOmPUw8engP4fiSQ6M+CJB3zgdIPBxMHzI0FMS7+x8NFIRSaOBvrg910Px1e1cowxaeRv2a0GXwKcYMZ3Vvwn6U22opzyMPCmvNHjjrZsy+zJqZe0Rg56PrGVN74krjhnKV+1xbEZOmyKzPQP2q7NwHZ7krWJjdD55mHR6oMDsiEF1zVp/FtLoaXNm2znsXCrsLDzQ507DS3Lfei+0LEwcxN0qNaWWXXSLrqPRSbJ301rH+jtpSWct0kSvE+413MXPm3YeNC2L0Dslljj4NBsKtsTQukT4nIqExCAgKM5i4sK8RQ1zI/EcT3mR63Jnabx6XfMZsZzYDjxl+VcFTxYb8n3SMLeiu/v81d3HfEUTfp9582rgOYEEKE3eCPu+I7TEIRMsDVPqc54CPVXLG2pJr5G9HUwmmGTP/L+sW93SjT2mg8ujhUETivzWUeWrXz8i0YrQbFKe22dQpbIViIRZNeTKd85FDKVeunZ6n8ZfmpCjB8I4w8Qq85Hbbme4q6yTyL9j7D+Mi+6uf972ni324eEfNPNY7bt0py4cPDjIyR5lFqYUV0vz8LtaTVN/0+m+Mr7Za38zWMZTuvqcDExKTM8cFa1bKu3vrtlS7OuF8eq7jc8p3VTIWK1nrBb5j6AQ59qb2zMYbyQ4cQxxZs5nfHoFPqO3V/p5zm+lPp9BPGXHQNuJQg7f0T9eu+/7e/w9t5ptnlhrjvUT0+ncPdOnTHwrlpzfflxLOzUd8r07D2C9tUoem4+fqoyFNxNAyUelt15c+wpuQqREhaUOQ1AMiClR52DkSrD9/+KJZr94ql3NzFjFbFiTbZCBS/N2dHqTeqH0THJHJEJuK2XjX3qLUOUq/xa8t23xfAvVl0/x4fRI8N5p36Z6JndHQhnNdXCCHIFAIVL7hlgiGnRlGN2UDBNNHRIlUcR0TBPn80FPyIe0FyrIYGcsZPjcV2ml/msNLrjJNcW5d3f181t43UZpWKA7aqKnX9PEuD06Uc/HCM44JockebbrRra/rE0H6r0ErWOoYwqkZKtfZWbmIu3TsndPVw68Oz+nNbOFXbRnXnnFsPnTfIsKWlbzFq8A34CBH/Gy0TuA9hR7zz/0uRYwUn5jIpfzez6PT/R+xD08PmJj6Pnvkqc4BWDosLmQkVKvX91aMSE26D5cfVNR1fD01IiqqisYHQhDr16dEr2ccKieAyjIsVVWSb5WAckNGjK0L597dhgUPqKikFD2xkKdasKzG2lRtlRtjEKoklVA7HGVoaYBGmNEf/0hS2pDYZwfNzLXANKTeWYmwWsVCvn/mfqJoYVxFy6aAwEQ2wiKikRJND32guo6Zx5hukrHpFrbmVI01Dt5qopr6/Dyvs1qD+zfpidynHf+vtmobqW7Ody1suqVlSqLMt5nq0TTIrLbI5YpVDjLBO7LP30x6Y8It097IHrs6qVMxXDx1cUuKyCzHzHe05bU5Ur+vcss9I/Wh0WIWI3amXfivLJKl95E6h0lNO+fJqP1sWVZ+MhQ1n8yHaR9kc87j768YtXQ0xHEazAmyGtMwmRr9R8EY3Xsz+Vb2XufrIk7COsw4ND41W732stCSt46J1zVccWer7tp8tgij1mb6QyKnjv+wsCi3OEXiG03zz4NPTrTnY1K2pCxeZw5HsCxDvMhxDu7cSDp9Gr2PWvU+RcEnGlSM5HJdDuhTN1SUGcVDiF39Zy2mhtu7Ep0NVtgSd2ZGQ4h+Gx23/C10dnSLq/oKe+KF3F6FfhE8rx97oucKsbG3aal1b7GJukWJ8hGQYshere7L0FidnA1sEiGEIZ4FiW/loFwcCHcUU3IeJl5XHJsZIcI869wzgbKiNDsLdGwws7sk+d1zSJpp81EInEYKkrXQ3UdfBDi0m/kvy+mSjpOueX5FJKc4iy5i5amO0t9FuNfk961bX7Pcm+h3ZNc1qhyI1EoJ+ynPr4E5OFTpKNe04BwWO+/EuapO7NUKA5GNY0qUnqQPoulknooEQe8iveL47bfi6JHTbfZ+A5LI7vdU0/R+z57pm7O2ukylHf9icq5arxwT8pOS2rGDv1Xo9rlcvP4yIzXniIxSjRc9M1ROSHIK+aJzFOFH9a52lb8r9XtitZdk3TC/OTqk3Nv52f5tX5rfXPwlR90E85xH6WifdOdsNLPlzxD0c7ZvxEv7VRuMcOnu6evnc/Sm6I4w9Vn2bcjPLdzeHSsh0wUR9YjNaOt28PGV5PxXiuWM8R+/v+jow5LRl17bb2xJ8EQ8sSRYpzkaRsXdc18wohHQiFzL9cKDanF0tp0PuYC5WvPJ83mjJe9XYThIVHB8MeWUt8jDXLG/HB66nfI2DqHG5jr6eEdiWm6RQNGezv7te5vwq4oQZ6CBy6+X18Z+F72Y5MJuRx5w3Le5AoLnqgibsXZ8rjXGQqFLPECmjzXemsj2J+x9+z3YxE8B8IfCC6OVK+FUT2ijmqUy++31zIuind1qp7qbEbTGHXY5CoKzKrumtXXxc8uXwdo1MwUtIjo3Nc47+J1wc25bvUfC7jFjzES6fIZfJVZwtpZt6a/Ana7BmQQZulfhJFv93j0rS+vCWi106ZydEpZO9pv/jGBztRdZOl6XtWSSq5v50OOdLSVc/M8Snkx7PSfm1N9ilgnfcraPjT9D5eOzmu/wv2Ky0q90oIlOBy2V8qz40cp25QHfvv6yO7FnXBeznF5JI0oeOmNNqy4pxWl0k3DvwILu34YGE6E88JW3+W1ZJW0q6h4rLs8zyNz5Vd0ssJF6xpRZ3TpxU8F0XXz00lXsuz3eFOZXfUxULYphDkqqK3xD321n43XSw9JrfTDnfwi7dT27V9sqm0nYHFt7cYmd84rN4U4rA2MufGR4qwiq92LHdECf77nmvrfmKjnxJlqff3r36endIW8+TuR2fuImbeM3zUUfjxpIUZX0zaJZzF5v+SCj55uJXyh/M8lGS9EtsVdo/dGUE0CinOuPdU8aZoslKHdISCK93dBQ93VuXHlTDRiW52GglwPsJA30fC1Tdag8CHPMdoSEwjUOXjZB6IuxEJE0IzCQhAaZzjd56RNL0khwpyl019fz+DB+PBhutBH8+bNkiQnQGPJ0zJm7d8TlRDPS3ptwq8qvXKO7B6ipQcgXmhrWpA+NSSSY9GHRrLATcJLu52x6TZ8F1b/La2T6Dl//t5S33bHHtb4Isn34VZuCvlFdc+/0LDCfNYXfGGnR5tkmWEdURPfUCUt9SnYT4BT14BXcaaE+tq+e62s3zbFHHQpCMrW5qVoPjrYlXKSiGWBJmnKfs9+43U1t0h0mWCdOtUQYPHmqxWQdhK0LtI3xqTeYOOwteXhxxJoyzeBM9jt181DC59FztB2S98XY0yxysU+lKxzsnNiM9dbRvm3AHcwufKtlDGlLGYS0zh6UeZKDeWbGkqcc85Eu2wYNzy0m3xejDWdNY57wxJ67VKmCzvclrBBQlEObNBLVCrapBJs3CEyZiJjtiY3wrnEbdbYru76mNhzltv5UQZ0a8lnM8L50f5trFw64UO9sLi6jj8sjGU7ruHj2Ku6fZa4x0y6fYdyCt3lufDAdjvRgY7RPCcG/htise1m+O9ccdEWXhJbtlmQ/B5w0IIHfr6n9NsHs7Y1cMiA7OlriQn7SjSbl1R4YSLkbVcL0NCL27dLbyb2px276NibuENz9bHrZMMk37nMj3SBzAcQM/2sl+STHCjeKGSQYC4za74YH1VbkiDdh7joXgdOdrBZHhQbIw8S6xwsGAh6ZHZ8liZOdyvq8RgQOOJ3e/J9lfYTn21ea0hUO8ruRzC++GkqiClH3wRSTptGw0hJCpHuhpKC56DShM9PKWvBrypw972RRDOVv9m4+g6Pzs0e1vh7hITo+j6AzPcddNA2E8EJ4JMI4E5Weid6HLV2Z6G8C31XPB17nq/zvT5P59NUfLZJi4h9SZnbC5MueI2u3Bo4TbwtWlHw88sL6GDSy8coxwHx8+nCUznndL0TSTI96dhIVVCUc5sR2k9+2GcvL351Xv7WTKTLBldYo5BzcNbs9vTENGlK1GpFv2McRsNWaol1N5AZWlHmQRgzUmjhqDebIi00tpEhaZzb2K6NYQp4eC3NwC9wuF4waKLeyLqr3Jhf3GyeYNL5G+KEIj2XK3mVt7hKjGUrE5hMs4YFa/2c/ToVzZgR+wEDZsNybQc7sakhqA4zuIZBoLuZJcyrVPkiRjW8LhMHROE6H2UJCG5dwnmKoY0I5mEEDcVqxIMWCp+vsbkgKMhAj0PWObYPbcZo1qe+TQynNui6innZRLQfBko5MDAcjnCtIZzLRSgih69RqDwzMyM6a65zBsgSZQHhszUEUnkdjwwgtCTH3TbLUluBJ7Njm0pQOh14lBxj+04NTgwg73LYBfa4OySaLU2BspSSXrrr753KjJMCuCn1OeHQfBkILP284uTShzzdcYMULhVmYakp/OF1L/K6C7F8Dvs/PEvL5XYoEhCqUg49B2qc2KwyKDt00YBy5TKzFEvMTO3u7Iqxk+/cTKZoEDu3cVHr012CECkR3ExoTiOGtCD4mjMHE8ANjgd2oTuPpGN7Yh87V8Dv3gKYOD72uxKBiSDlA0gfKfc1xM+Gv0BfcWCDsDeEB+cPIv5hgB9bdF+c5S+320P6V2z/rSecOKV32MRGve5fabBZMkAgu1+/sz87zObHqpDMOWoMhE47rps3EeLGRIRYRyI0SLemm1NrPD97dy1yONDoNs8kIsdIzAQ+rKjNSFCrZxXjAjIhHaR0alEOUNwMqunPnDqbwT9Ex2FAbvsKmcA/NGRG3BODCzCO/cegelPw6eS6/pCgoCVPc1OFbZSip8HphaPArWesgvofQ48fl2ncptJJGFIh723R1A5tsJv1qAEURHdtBon4k8AMmhyMAWRRfFTOipMUuF79WrmEg4t1Y51W/r6raWyszmd5oWYbyFSDGyh3dZvWtTtDyju/05Ueo8a0fcT3ce2PpmV0ROHbh+L8ytJkyvcwbweUkO+l1sIVAn4dPs93a7Lc8wDTGj2+gzC0LSp6Kvej3Wov3c3hAJLWoTRshTudkMy7vboe13O93u9DQfdTJBJyOpOs6QNlERgqvlKWaevdMzXEJXspiiqsRYqJO43NkMBCFhxy5MWyWQpb1vB0TEdUy9QHhbt2Ikh008j3tV2+n1T1lV0vrYdWgUQet60PMdvNnWOYsONc0Nmx3rsTpaLtbcEm8M8c0l0zlEEsc+wr2b4N5mQTE5PhfeaHkjRFTfO63E5TRKh3q4DhnK2+EDjvUb2VLbmrfl94uNq1DYwhthSEQljwkG83d2ZV7lxaSEafU0ipSSlo3WTm9Ytp4fajayo3eXpjHRRj3jPvc5Atj6UvW2MsikBtM63Wk8xJJimx7UDtjM6SMfLdYyFWzrREyssTSWW1vd3GPVITIbHYZxmyXyc3d7L070RtZL0+hQGIBBiNQKXq7e1oWtLeIN9vb7gXqFg2MfFomgxJmOzubPRmAU2W5JIkYSMJwBqIZgkscCCZQZ4oQQUDLdB28tCmEiZIuQwAoeK5lKLIg4LkJi9tmW4GZpHud9VKhUCmCYOrROg6a2w576XFF7ZY2jSyse/rmDtpSWqqCoitLCVoMB76QsjBEBETgne3aTZwWm/dzcWz4buCGtB0uxkhgL0s0jlw35MnN7NBb5ss35Qli29r92WV+bwUknKycmw1XxYh15V3bU7q4XkSDcM/O4e7q3mYmeY3GrE+ONy0WwJjaQ8xqcqFJUQ+RJKTWRY8L2RhGVCyXlaZt74GwpcbbTDRLJHocTzw+LhzXEXKBODllsXjAmmoLOVv4m20zXzxX5uStvp4767dpv4tXOh7Bl0MWwODwwQ/jcIoneA0QuGDcWY725zoe1x1UcIWgVaPF8eXhmXTOC0Nau6txhJFptHfNcbv8N0ib99rmeQ6QTllpJKLiXVsl90znDANjE1n+EohsOuFtBGEReitjTYSA2gWg2ct7WOFkOMxwAwYoLQKE2WkLRpqg0c3RcnOIRgWQpdZn167dua6ZrtwHTZ0QiMuJS0JsSxzMV35JmLgUQzolUF8b43OUVJ07C3B6HZwtBgkNsl2bN4NdJ1b92MbOyGtwcbq6MmwgYqK0PjffnSBEZBZmcFdYq2I7YjIiB3GzbGWRsNDoh+qCG7vzN2X8mqvIiybMTnEzgFQ3jagNFgkGK6bBYtLRphFERDIbx0mJ7zxe8Yh6qoYpixCTsLwJMnXmpEm4GOkaButtY3VEk0zQY3TrJWZmINGmasvaWUK8kmo2KzUtE7PdDw6h1FMqB4q23rQTS+KvvQ36OmWNFHTOnSJx4MaXQSxKGc7cdHCtj+001vx1eixXwyx57OCAjvtuljEVbwc0dUnRsP1/EG37Z+SSHur+i32YS7fve5H+f8b/K7FUknqvuj74vKflgbH2IlgpEqPDfF3YbAc+ZEJHaOL8IY/2H6/X6z8Hbu+7eZfknjx5Rg2msMfpHRi2uU7oa05Bud416O/NR/kD/gOX0i99i3E9Zrvf7I84vVMoJ4wbQeEXE5GRQV6KDyw8NGnwx3aSjVWksKZ6kAw2gqoivq5kvZjMKabAeVkqT3Uh1yquN5trXudZWKKq1JB4yzI8aPihTjV7YuUIB0jHjVQS+xymacJ71B2S8yoLQ4h0nt4QjGltqe1E81GlbW/hfmQTQ72J1p/4odKuPL9qeEarPtmJn8Jv3zHQp9r+JHVazPuU/wYefnu+q9NP3qonhBMOqjJOxM5Hh/Kj7fzA47vZHKpgrm3Oe8f9PwhJhkmGX53ItZFklV/CUsD+p0asJDQGiwiyQBQCsgaRQhUBQgsHGySLCQqChjAxkUFIQxhA/fYAaHV6lYCyNojIgek23h7PbI3I9GMvDDOUN1iG6PQZota5pCYoZbHhXyuVsNK4TNYNBhset5pYnV92ExwcZ62XR4X13st1N7NG0LqYttYO4RL/gvMvMMvQ+o1oyFUouNDiIeSY361O8uFKTxKTf7dHPvWFcHi9sRMYYVpWCrE65BP/aaBtnYtyxMzzdPRvsmyGqsFIINttZ7TiXn0yldZeODYhc6DhFSeeidJR1+zDpsN4ariCV3Nnwi0q8/3SNUJDc2cH2O7KqOYyhyfiO/jZHJP0LsPQcy3kmq9jkVMJfkHIA3lGl/BGTB+gyGMRKL9UZDdtu9TksyMi+N31VWte3+dJtz1N7PkEu/vfwf+D4fkf3v+f3H5eewG8oKORmOWTKy+oyqQmZ9TR2jVc2Qor7f7qQyNH8ZkGkxrDFUHnDajuVYM+Ei+ASSG7Ow+Ssgvv2bGST6/8xp7Y83N1sGyHz/U+Ud11VIKq+efQQ00dwM6YUFEufVOWp5nHO0+b723wH5Ulw/flJqtYOt95/HpsDT2IHCDply+4I3IgyEqx9FwwUqlCeJ852lmhx/7FIEB5kujamH+If9dqldGzP+YS7G4O0gmOj4cgu0HjtPXhCw8Df6gWGWhixFPI4Fl+t/O0D9ADlqJzl7m0/gHrlMsfsuOBgOzKTFwhdA9Z6n3JhM1CZwk3CQ0KKPauUO34lO0MAvxJJCIQgwiEBA17qHuPi54OGOAn4O75p6+2F0UeGM+Y0z9x2cZ2BZJwDBX64+asN+C47eHUVHPLsTengb5TpzBNoybNAftXSS3AxHqzH8InBMi4w8/TyBm7pDonQap6mHypxATmDtlOwg3e2CLMky8vYzYNM+ieRoegqZzyx3r9H3t/A1ZBIZmQWruNbRhLia8sjpfvhqgaMYXxHKpQRCpY/bYQozTRNHyK9ho0Kp8oX1mRJIkn0U8fflF0Pi5aqqszgL5YB5EEM2Tj9oOzsJBifAiJechih9uJQ0ubr+sdnF0ZEL9FG1sohvKYGxr3ZM3qn9zIImT+yRP331lR/uTKkJUTFRr6Dr2XXG9fqXDeDs4uDIIFTeCGbgIRofIIfB5/yEuVkJJJvS9WjS15MqRQ/RKL5Fv5Dm3FmilE9yT/3naexX9X/m78Z9tKr+ZJJ3HeQar1ozEEL9t110o76QTMgdxa5j9rzwknenOURz+Vpm1Opvhz6pYMj90h2/pwZuiA6/qy6HP0+G0EsMUS3s/bgGRk4n8zQ/53DDiU9m7Tamb9V7oDTXc6h23Gko4GKNNeHAgfiBDoEhQr0tDGCB0ocKkxaPzaGUGvy/lISHi+61sBrhxSEOfBddnb5hmJZQMgNB/IB4zlRWxo7H5HvaMm3hDeiDgw/CZX8rz/EmvZOvy/TJTJpv80GEoSVJQs5lSTNgFsvdW1sYoGFYY8aydJ9Lj7Ur5fo6qz+wjJwFt+fvu71U2vWXunHhyx1Z4+OjV15wcbiPOO0PYudTEwqTolfyRdydvPE/U0kg6RaHp/O7hfmWd3J7ampI5e5Ooii7S4zIy84sbSlDUJQPvzmDWnvionUMQdogvBya+M3K3ocXscooSdxLb5v6uwfbKoWds8ZkpN06/4u2r3k+UOkKFbnCm01Jrh4Rnm4j0dnRNP1DHZkcKbEOm49Y+mXjnJ2j8OYjGhcPAk33O8idV6u0u73RdWucqzTqB3xFSB6F0RL4virS3PGiJK7KA0uOzxpdX1jyOrZbIhsQR3poTJCZd09VPylu/fPeiRBrVT2X1X0LvOJoXQ+0Wp2qhz5OYsQ8j11BDTcc+VQ2TArk1E1PwZT8MLzrUZ82sl1e9TV5OMJ8qXtyXrT8UlTvj5VeUOrH6To37PgRIKh9wlihcK1C/V9vHYqhJQagj6zSJvLBEj5J645WcWOFVVuUPR2viER5RrIlGb4vC+nM2zzUq7YRs5ye/zh5sjG03WbWPxDLCunejrunvfcuPdzLzSIyPxeFx6WcZYK2dm8Fw1GtMd8lq7H9d+1k20RsT9LnDfFp+h1solN06cfpueFHGLkSXnQzixko0ndHsVkUtgjrhdZT3tVdI5nSQtlQwY/HINj7HMi5PnikSM7+u4a2TCKMTJaoXTW4dOdS8tiFT8I9x+HBW66zSie7l9OPybchkyWR3md27Qy8tKQRizGovIcwqL1aiPJLNd1JCOqHSMdIxUlwu9GmGVAnD5WHEkymM7aDjqTpz6x283ugsFEa0Gp10KKUCKmcz4jz1O+JFS4g8EFkXikHwSehJTTOu5Y47T2n7J/hPWckkeGMXPOZ9KqiSN6ZxXvaBH9T6X6YypDt7kN8/efjIWiULmI/V6dQeM8a1VoLXe6klW4/5n5hxKah4Ft/JNFX6qX50oCPvTnSA7cvwnzjmdDzc3PcQrj1Ib9q4Wzh8CIy2f1qfBwvn5oqrnlWXlOExxVJnlAc0Sk4h0O3uQOjkmrDmj3bysxrRnzOzXLtKZj7EMcfU9+5Hq/abSqpk9iqKj7H3p/0z8ykSr6Ysr1wh5r2WidJyxifHddRVkA7K/2+3Pv4dFOtnK7eelbWKYNdNpHOZbkvCGO70yjxh7Kp2vTCUT8+P7M7nnPUc03bXhSjEUOGsvDpOJ1N88DTDCtLE5g7SUQOzic3Rd5T3GtWpDhdwdJuC/Z99WxRIxjkQezkcNqxbB7It17IP7r9+Eq39nPp0tt06WJGs8IhD7rzq9r25mgNDEOHKpZ8VNWfCvTCyVk+t9xwKJ4EUcjOtYmjFLz+3/p+CyXiDlE4RkkQ/7Ow+mbT5z6dU63KJonCITYzniKqGpH69en17x2XW4g+R56iBhpg2bM0k0DSFcUqW9uJhGYZMkPj+sEDmQGPOm9KS/v9rQWChFAl6GEWpNJ8s1eA8BPoPvEGBcKANMicKuCYC4Y+N/SGgj8WwGY9Zf7dXECd/XsHXaw4QNxk4LOMxhvIWFZHAslD8DmakAwamaZufsMw8EQ6qimuqSKSE4DqHyh+geW9NO8yHd4mrnmnkMpGSBJDfvoaiugfYBZbQkXQ+MrqyDMT5hjsHO+WokvcBds8y44JfWETA1n7D/ltvUZZ7m1EdpJY6LqhQpvdREZ3B817CDO0n6M7+lieYi0zG8cbHgmJgZDgu3FzeeDCOocr5Go2sxI3MKaZY6h5jmPeZAnSQgTQgvBeTx7sxeQWxRGPB28551wGQoUPv9SSzqdabgvTtVRTkheeZOYqc/txA7NxpuUUbYyyBSrQ9ux57EDyh6DMOQZ5maeErcjkBBQuCFushYdxtOoMiZjCTiG8QPMQCwhqsD6BIGw6O54beAXtbIYW7As9Ax8nHteh11G/Vshs8ruWTIVw1PIb+Y9FSoNH+JRKePv9PYvYbZp37tNmzFi+bUxzltcnmDZE1Cd40EIU03WyeoKPiYm0CRO7NO8iT1fGumWvZ2TdZbK7MjBBWCjTcYCQhHkB3AVOvYExmuA1CGoNI1ow4dp2954Jx5DjlPyBQ4DYnW1IkFYJwd9gB4oXMBX1SjkIZqKMNPHLvYjoXtPSBj9M+xjE1TcmxR2yQThwLL4lMKN6QPObjOxiBwHt6wC0o+Yh+siMILAgiSLIrzCa4fqKMgikUhEUsaHx/c+5vHlBKA4r9K0Pz3Qb/g8n1Wfn6T5DoIEo/RVjlVxLAsUixiChDo0diqAeVc8AmRmwiKDEBIm+GJxNKFe00AggiYZS5JFVYFQEBjC0qxC/k2G55yKogILxaiw/oLCc8+jUoJVFIHZkkCtB34G4B1XPWxG3oQ0r7Bs9z/KSlPTVYZA+sWRENnRhrJOApVkOA0fIeb4F85QzRnUB8sdn1OReYwpmcSytB2lW7RFGb0qF2y3LHgd6d6RBbjfqUGjqTtKnnGWRnZDOBun2yjAgShBYpIsRjEEaKCgoTPNHi0SBFjGPlLksa2ToB4ZKv5SBCMnbFPTFPI7dYk0CGoXKCmHLncjw0eGdBqSA69pHQvDABslnuBJZhbm9SbkTvQ4KXgLwIfEPmOL55Eo2BMJsKDnN2D7YiCdRwDwPyqgIHiyspM2KsYPSJmAPLf+Uo/pDHdImU6g6CQ/QCSG8jAYCwJ3l5k2ToKahTEZwQmaZrx3QkE2M+gOZQnlCAFMEswyhebLhV+mz46MegIwfFWzaqlSgiMKSITIQ8j9kKUfcYzeg8whGCSEYgSADIwIIBr+JfbXN1BzwtAVfnjCw8vtZa5iiUB2vSyxFgHeG6w30wJwsweRnMrVTAwgyfnJ+cg/I0B9p9z/Vf2UEmiWctsCA0FD2aDJCkMWDGNbA5TU5xUwHxKfyL1kaYMzAHgPphIgJIJ/v4qU6Bu37VJbdfdJdKwXtlGjA74L1FkQrRDIhmelVyoD0JqIX2fu95Qwr5wwd27t2DBpAxzh9IMm6QPlQnpakqmG+ELLNHbs+TyF7zlp7MrcTR3/gHTfpMRnA2CP6ot6kjW18CNWESFwwga8pb1YP5gW/8afdwKfxpjyn5NE3vVgKTss3q3Pp5SfXpgMw4DbnDE+4tVHU15VZ9kJY9Q+LGXJTQg0FEn67CtDsO332ZRRDrhWUe+eMKgB+ZJpFcEuARd5Do8f412YB5+3gHvHCG6QdlEqCqQ3F2WRSIBpIenNc9CajRxDzCGDIPf66++3HzDvUT0HtPAzgTcBMwJlPCZim+YdCb6t/nNiNa4iKkwhnsc/e034QUh7z45VqH2kD/JEfkfjBpPkQIziY+eHAm1BxMD8Ph9tngNfMffcwLA/LZUXKslBGAKm7A1qhNMkfoyA0EQGdOqh2mGozQayYQ5soKQ4qMUj4Qvccc3mqW0uYGGft9lfSgZfnurU9kA0zyDqlpPGIpLjRAfVqSJUaUFACFW3VL0CA20jYZISCkhftTUqgdvl5nobMDgbJw51GTAdZwFUKX3WQ+m6ezZy05cnuDquWXSQkY8aEpiQiMCIDLCOVg/fDTp6FP3QbDv3c/rjw6M6LgQ32aORKo4w9hdgKoIfZSieaqJOHbFSe8+cLndw99gY2zb1G8hdpFoLyb+QNgNnz1kJHFBRpaggeL8HAzsLjh/GZglEByH3yxCMWOCdPhVyJcyVDuqCWbsDpD/MMB7Ln8PfWYsOJKQ4BVUUfL1sOwAHtPavtDcZJnze2WlDeFsKjFhGRUEKEskPclIskyEcQ+mDdHpCIZkwzSRUD1l5vNYr3Fb4DxTDpsTToikhvDQU+E3OzZaUklqTCawuRpgxNRxwu1M00b0q04RZArNtoiSA2jGWGnRMaMpBXIWuAMtCPT30KA1oa3lGCEvs5VOLQB5OZRTTdhpxGOBIDhGMcr1ijb2rr+WQMJXmZDlFvin88avOg8KMte7FJyqOTqaKyY+B8v7DRYIT9QffUiQIn8Bf2wLQTDnureBpQkopCib+kMkyLkKUmHpuHIgYGOnZytIYgGgBo6iZhpBMNpSlwg00Ox9CXk8Nk9O2zyZ6+i89bPHOaRhcQFqjxDewpgr8A1y+TFgOfHkHp0MCg+wKU4DxzqhHNmE+BxRmZSjByIeGUBIYmgRGoYDMAbJErDHAMBCkpTfMY/eaMYexxNLg3ySHT9hztE6LmFRvFWo2W5FUQVytqjbKjbJG2fT0H3U/O5FO3OybEcNSCYHlmdomZ0MIoHcDNNuAbOdh3dx+QwdU7pXDjX5nQ28xBD7ozW+Aa6m4qqVnW6Zg44SmgHO4PkGBxbkcmdEFBvyeQ43uEB4zcEneoWrzwofMaliIZebNXcfYEDP7n9nSa4auXZZxEwHiFUKAhYxTcMlHb3WaiPoVUj6SaDijQ8SHXTRK6WwSWIRooeeJlPKWCxD8ZDtwGpSGtwirdC5YNmV4rypRjH1Zd529YnLrH13zeP+CrZKg30VvJUTBMUw5wjIYl1Df1hkWIKlNRzHLqMOT8YTSQi3WYYdRzj2ZkSgxEI4040mnpJAhHTPcWvvtNVZPUjGMGGrQXwiGzjyFAK8s2OI44ii+czjj8j4WO473+t2fbPTco4W9v2R0jhMnjDExcpijEQXqynGIOVa+TWB0NQsJJoVoFQ4jW4P40H9Gwfj2OPxld+oL8BQvYk/adP28GnFbFOLyx+3g3hWjb9EhiIEk3DuJ9OZjcG4w67bvk2Zs8Joq/QgY5bfsjyOyNF6SE0F9Z5I7Z5wxwHfgmRFnEMwc5XE970K7g4l7OUSQ6uzsyIkhscnlwjzHc7hzDbQx5obBuOXHOG3DQ47ad0dZHeeIMEQ9PXc57cU7acswfRD+a4OIKDpCDNCxDsOz8UECjNOeM7zlEyCA7sY3oTn02Py658KfDN5emGV347wPpmfgULht/bOzVnChMtPTQHlCKJ9nNs22MCEj1Cjwy118x0nTnkOIcWGOWGWQbKTlNtFDLiWezUEF4OQFkwWSUmx3y6ZBRIVa8pKztxmp6wgt6QmZcqRp5ol01RG7pucrX0p9bx9TBBKHPNMzwD8Jl+w561d64m3Yd0OmRDumRSqXSTRMi2UlFpdRk657dptKjl54rntvhRI6MHfSjDSIaLrc5lQhach/jxTaVoNucQwhCfyd9Sq4nvO3B7DTvljkD0ohtIhik+VWwqbgFJbF8YY6D4ZttGOc3S5C3VJkHsVLQ9pNct5RJz8wtGR+qjlNOEWhxV8zRPdg1pVsHA2TF+DOSCFFk3pTLPMHjy4uLsYtrBDUzan0ODBtgrG8ws2JhAjoN1SZMBqCm6wHO+g1E6V7H6my+QT9Kbm+IgQYj+kgGVzSc5xQ4E4I00Mo5Udc04yd/C7SaXQmTMa+FWsCT2tS4mSZoe1C0jKm590mlGJrSW3H6IaZZk4OlPI1u/MQ6dhw5J12pYDLTsl6oohQnRtGY4GxJra1xOo3jN3Y6HDgPQN7oHEdkQLsz9I5gmW3zNGCbIQrHpCPk3bS2vGs3D7oIXOPSPCraXi5XGJFE3w8RquI4uoIKfb7OpIUbeh6h9Fq43kRxvGn8Tj1LurPx6M6U1ykRiBWMBICICyaDATpc0pKDUbgZJvgwIlHFzHAO9w0BBgJCQA6AoI9JqOiZhq7GgJcFpGBwYgUDBUChpShEHnTMOpBbDsQgUugQ1FuUGu4O+wYvBfLCpFiOUU22y/fOTcTDiBRvVwGZ/WEMH3yB3gReZs7xTIOoU/wiGtokZCCQhIEYblW34qMIIY2xC7CgdOYdU0byM5PRjtBcn5TTzdlurI9YfMbxGNjuLaBBaC4MsTGMahywreNIk1QUF6iHkKo/BxI5NV2oWI59o4iRkc5XBkBwIGwMZuvSSO9uhOBzh5joBAO+DrDQdHgOliQeL1FIYDq6ixaOhBPpx9thTuxwm9EUb/SaaPX1G7ynEgh+wIOqEzE/tiMgvvNgdwHw+rvNY+iO82DHijQKCCQmXhN84mLmIdrICrDn5bBHoci9FAyTPoMyGaZ43iFBwaVhQQiLRAqEIUgVEWu1JqfOfZkoZwn17x/DKldlGgZaD4f2ewFm94qHpWGh19n4UoHOK2JpOEiPBwCY3CRA14Jh5Bax5AoO6tJNAYYS0hXAMdsYDfZhcwuCSB3CqLIIFFDjiIGB3D7QzXIiZ9ZPNuPN6p8abjvIOx2h+Q7SjWpVKdao4RAiVRoEM5gHvCpeRzgJP3JhEHW0axcc22/SgDDNtAcGBDEFagrHvOSEYoljo5CBBYJugA702e4II6ZlRwITJEuwNktY+7M45lybBANgngUUm4aoOiwo4lCRLZDC3dE+19yuiXxtgpQsViW+g8vYUF6NIdoH+QmBjNmZjZluaAkh9uXWilx5SPhlWVKFrTkh7UFkk7gKEYO5+oDX3khQrtud74Z8Zvxsi0zsjghBkJG7dulK2VDkU/5HJ4225+MUI0+wbZg7MYWNbDXMMnTrT5cY7PA41Wkk4OI4WlZadNzcd+OImBz3t97MgTJtG4SiQOiQ2gKREWACciMJcIfTFeIVUYisEIsVkiBBIA+b47FoROAKGW9bIWC7Q1dPWskSEYjCAb83SfiEoiP1PnwMgmJQQiQUPCNWcDZHSAZkRCUTvzykhh9ITANbs4SyH8wixAEIsOcDGTHjR/P4zB7hAN8kA4IQY5hkH2iwPm5zin4BChO5nX8m6zo9kMA/tjzAu9hD54ZvuDgErjwPoD9f/nGU2D3mubPlMqYZh7xQVhR01EoolJXKSHrRYuCyUh5ld3+RSDIg/fPV3x7s7e35D5wPlPcT5GTrAhrZLEZSiWCMVtWj1tDGwQqEaQmssncY3TIaQgqMEStGQCqJKkUClUoCiWwooMICRiIqJFltrQKH+ThasKDEEUTC0mMwYYljCnv79JvMWwRUPnbv8JdfONTeHca5VnNrYTNCSylnCwhiKvVEBS0RCEBXdgyWyAHorzyrH9WGz+gjh/QKfnb/qQj+sqhipZiFxiUsSAkQiEIhhQ1NzVG/sLPOfbDsOsAqAMPY/lpgRPVIhuSu4ftT2JbgSaiepBFYgMhmh3gfbDWV9+vhr7nx8p9bCZjM0xBZwD5/H5EITJ+mEi8Q47+fjLOCawee00Wmamhulc1cwg0dBhhcoMGG7C7o+sMkDDYiRGM6NORqYaSUQRIz8Jz8+DMnUcC9X6RqMVYisiRcCaicB2Z58ox5wZ2s5p2HhZRW/sU+L8ezO/GrdQ/F7JszZk4y/c4mrG40hhsbWsyTGIr4TatszOYoPhIdaaEMx49b40/Y+eDSjWBnN1YI39pyLDaN5xfugc3sve9DCdmJWRzlFSOh63YOI2Eyi6PZkN+P7jyPSaDeTCIcf2J0Q7jBmIJRTCkrAmMJKRiAwUVEO8YHvnsN1B94Yg2YUNyqhBxJpLQcGnmLootIkSb8+3dcTkqHYzIkzBIMZBYUXnNqSHnt/dXbtWJfpMg9om3ALL2xMOkUjC3z3ETGhUSUohWYw9nXg4POQ6TU9Gy9pcnCBoJxI2ZE13zWQKlBHeK+HCreQqcEKKQYCQYk5y9wUSE5jIxqNqCCQiyQRBMVCGyzT2Tx6blppq7k+KMHWgswrUAUtowSSxJF9EGoQB0tBnmGzBkBClnZ2zkTcO1OAga6MpzccGspAZ6mU6fMh+6wP0kDF2ToTCdhBkUhNsKiqBY1EUBqxAURkgsKhRhEZK0YtBQXvCABTFANtv9u4f3YSRhBPjLnEDeBwR6Q8iDA5VjAMxRLKWsGTyQNMDmvLce08AxiTT1vUzXDGQSzv73zsNEHf28vOnE4Ezlfoz0WThDbERRFEEUjGIijEZFgj5DXhiRkCb1SEMkh+BYowVacoPqOZwOBqWL0Hk3JnqXPt6aT9idJcrdkrp5i0GeoMPwerzdAjVVc+FC+tk7EhxRyo6PlqxBrE7jzL/KtsY+Ajqf611gRIgeBy6cOsz2yhIYEmCRyHPjjoYsJqHDcmD6jcHd958t+/3pT0fbvrH6mbrCyyuV6b+gwpWsI2ce/yu8OpEOkknz8s4paSK1lTKSVW2QxNihPn33Frh5TViI4NuzbjLW4SPbbVzeFXi9Ez0042FbyKOWFQrUUCju3ktw6JRSZhJ7nmVT0nsuyWLF8QGPnGY+pgdB1AfAbB8l7j9K+RdX476h4m8T3hwIqWD3zJE/4kRKgr7ItiIgGIbgirXR6iTU6AxYwUFknD2HcHRkAQ/I+nwyKAyew+M+BGCX3jQNkPRIYMyk6yW0hoixuuIhIEkUai96KFibCSGeq0Mk3EHsMTYlkh8xW9hBSAoHsSQFFBZJPgwO6CYTyPrS0IKTSUGTSRgkD3+vsF5jwDwIvEB0a4GNS+hVDbZhQTjnOspetMUb1HUTSIyAFAjsH3jG2leue07umimB5xH1CkXEwMvWz8ZFI9cyJv3PH5Qp/ExbYzlGcpzx6chr9jrHgCxU9vflIlQ0LQ0ka3MCyMMUumXPs5i9hj/mnPJCL3BH1yolo7wIGj+IN+pFgRIFylQeRKioSOpVCkgIkh8pLdJtNfhJAMYM5hIjMF5RJKFSb52yGU6ouqueNNiLO/BWYToQkQSKwURWLEVVWQiwWRjFIIMgDAYIoIQQVJIw7Np8CCn9Cf6EGh8HzWHRt5EhgAOxAPo3EAoU8gIcFQ5wIpGCwkGKwkRBjAVkYwYpFRixEMq7p7pOU7oTwIQlLmB1Lsfr8BLr8fpD1kSiScfFCyODSMEYI2DHKTCTqTGLKiGBIcI9MWk6qU/bkPjCkPS9583twdYH8sqqJNt6D3ID+UiHug9PLp59cbpyAU60PRyPUcdniK7A5VwvIYuGGi+QxIF4HtRaghCAPr+njm5zkT8hQHao8jFJ5Ao58fl38OgwmRgpsRZEORxjpo1lIcI8pYzEiJT3W2OdoVIA29GHlJETYKA0QtFEMi5+E6UhQeziUwFWMY+0oovaBwDof8HLXg5w+ycjBCYJthk4Q0mzA/5MxKGJEtuO84znVHohUKEuPop9d2nGGxuRdCGEawZ9pMvUmRHEN8GMjCpCxKIbQMRC/CUmB9azTErmSHkOTOQ7Oz5p+Pmd4tpUFYQFqpWlqB/BOgszsiceFXRsuXeDOWQuBUvT5pUI3SXsdm4CBE4h0zBdBkSwYOpORPWOdo9afYfjfeOw+zUDNHzlHxQIEB5ejTinqGKOYmPfHe9n7XEgIgIMYxirBIgwgIMhx4mf6vvY5eP28/9UPDPLGJvnMBuLOBQQxuLO/OdbFmaHIxDBOri3425hizuqsqYI1Q0KsqirVH1s2cFmjcsIsOWVDirfkLWHJ4UMLvKAKCyJozIYuio1qIokohFKqWJFBtJWqHFqKRzlMBJZTYixLDWSKlEaDS2S1KiXny4x4ajAyMOABkKSJIcQJsLO385YgnQbjQmr2efRtIaJyZJ9D4MktO8ENxGB1JOiKQgHEItQ4LzHeYXqMFkRR5n0FyBDqaMjbJdwnSeNEh6PpK+cuEC6UhP5PPkGHgyDr2LnJnQ6r0R7Ieq9PIBy5HSShYOE1tkRRYCnYDDCDighwGs4lXEkKGTqMub9vWWnUF8UCyIXL4kBJpnFeL7oCRZqN5zu7CgclgkxKrHAPk9jeHqXTqmCngnWKHWUB0fb1e+cd5Cb9tS5CwtWaoRZ219Ggo632kEEIJIRgAwe/hEEjAKNs7CtkSskGhXNXkNrFtufQzHkh8UdpJ2kOzkmehJnaQdyokiMe1Bs3sMh2Mu2r6733b7yClm84Jo3u6l4UZwi8uKHAYRaguLEh0hrBh3vxcbJ7yskJCuUdezPbzo+hYlO46HT9khwl3dN6ddK74jqYkUSZfdFBz+J8PoXOw6UxMvlhZbPQ0BsC5fNN4XvBMqX1/McyxzO+p7qE+/MEOpPB5kWRPT7A15RF8qWIltoiFEtSKxkESiCg0kUJWEUiMSQWo2sllJBBhn12aPNG/n2TYAoYFdrUCARSDmawcoGZvPZRbFIX7Z1WsvYdxanFZgThoV3KcK63s89tWXibBz5ibKm/qHC65lE4HEoLwuSPmPIWecPPVGC9drzpH0NkHhAO44kB5ZhGsI0tAp/XBVJFGkxlhsklyHAxLQ0Nbjlt9ic3o72cahRournjhuSdkxJDn0lBcGxFoiPJp7/IN/KdG7n+8BQWI4YxAZTxhmJ8HJCUvKVs51aEkCBAlyE7XDS2NBl02GhGUgsHgtVmBp+VOgwxom0PiZTd7rZbaDX9oyF2E9SKmHy1K6ISAxvc5vMMgBFBbZiWb6qbSw0tBoTQJUZNsGZmBQpSCBlCqoqjCJN5mnSK1tZRqOi7NbOo6KzDQzWzNjQGXVKyrSMfOwztRuUmSJKgthFzVAhcMiEbvMThJQ1AUKMDBgGMFQGQqUQTAzTM0sbGyLLRjjGwnWYTKcztXcGZm+s8XBMH0e+8wZpnNNWqChkFGFNbFK2NZlQIpsgL7DkwaDXNSeRVAs7kwaAZNO5sNkFcoLaG6C0RkS8TdFQtekcaQgy+BPWYaQ2CqO0WwuQGBmFSoJMIFhQKWMQSc0pvXTr2+4X3nxOpyQRAWKbPOIC86VPwcHGjfKBfOyQVRis78FE9kOq+eE6JDIv2U7w83LanfAKsOxAuKeJdtrgcpFkAyhTsUiUZUCXYJdjcuN2KQhUY3RpYXoIJYZAgsZQ2QKowGIoaIghCuDSgkxAYgRFioKCkUgoCyLCBABgxkAMikEhal4A0K0inBuB2EHK4xCG0kdRIoloiySKA6oaUgQhf4urSfCj0XoIzAA8A7oMhGGn4uQV/EivS0QAeNuKhL8qTp8OPjg/gQj6GdG0UAF2xIxJEK2nVwCofUrl40e0bE8EsvYF0KDJJ2jBGQAUEeLTPBD0b9HEw19nYXkrMAThFxqPtrbBfT3Sk3kPA7eM5AxOyyw6yoUsKQWQKS8y+DVhujYBRJCw/t4kDCBgDEFgIEIgIIDABZIIkWAjCLIWiJKGhoIIIIykKFKS0LSZGes1qYWHLVwBgsbSVijGICCJGQyKnRvdg8WjqHQGXRYHUmmQ2uuelwwPgOK/ZPR9XcFJ76TfjcS280v71kEYjejzcxn8InDBIEEoCEMUyPzHPvN0vuvnzkcCQzyOmF95fA5u6gpdwA/nIxYjPgNTmibDshzSqmCHXfrfjHux3lF+w1Fh82L+q4uJrk2LBt0vfAkjA4o4bnfa6hgD8T3RJAAzPD6Q8lKFEZCRhKppSBdTalXsNUMxB7Dcp2iZgL+n+9F+X6zl4kYKDyYJEVERiDEhNh+8GDoMQ6czxiGU3ysLwRbHSXsrcKMyRIh77lKv5YKHpJ2AkWeRIUiHIEGYXEktCwiFQpVVIYigSYCIyAYk6HqLJoGBgIo5CB/crk50JGVm0qFogtqoS6GrY98M0E6cbodBBKIhdOJd+/PHrOYZmQcTvLHFG8ip5eK6kWol3GGvKgYBgZ0pCI9qECpi/aYitFoSNC3YCiIayhEZGDJjLbNIXSgK7otEJtBokDspw3dFQ0Mys8BQV9sCxMOjUvUMJNAJo7YfVgG9sYcAkoOzcGckWQU6xE7yKg8SAIFAQRDXikTuPifj+en000j9QLKlFVxJKOMUFpk6pOJDXEBhA1dSAb+tAJ4IiA1ED90ULQToupArwTp+ZCDoOZMBQ0kIDRRXAtkfW//CDGBRfu2TyQc3v8AkYEB2o1RfAVdFfQm258h/P96ySKl4LJ7h9Yz+N1iLWEWCySNCjIX0Hy/BgKSk9Wkqn724A4eK+qoXJ6MFIFdZxO0qOzKMPuRIghKqwIu8+I1Gk1Ubl+b5/o0Oe1DC+yQF+6zic8domcUxGnDzIbFQpGxkzEGgk2AkBsDEzJiSAfRsDR0hLjAyB+NsZjM1C7XnCB3+UgHiPcM7gQoBIH7EK3ONufvFAYiHOd4CB7ipAhi9heKPL8Af55Hi2uDzPxYD+SSFE+frWQl42e1EyZjR2myQoMErlgLlueWla8h0s672scoUGyE5TuVOangQCPc9Kh/SKUXPIIeWyJzhoDIa0mEtanpGuUPp/L0We+GIxB+1nOWQYhhqbzhgWqHXGE3EpBkL8OiuhpoqHHqOZSSBcIpbt5AOFeKaZn80JMB1atjKcCqKwiwFgIMIMiQWAIMAWQWIoQARViyCRGSJBSKIwRguDGwd+lOizwN+G63p+K7G1GnKJ7Z9/lOnjUIUKiUJXSO+aBOsqiPBIcuigwaxH02cMMS3nvbxP0HvxllkSE/qorOqTEW/8yJSRQ7iT7p4xGyUJ7ymigopxENpVDlI3twjbo3jw9s473LS/523BZ/hjd5ZaOEbp4RWk/La1Bek/QH4h3Bx3AQe9BeFiHIixWhGv4Hl6+vr+AlgLKdympQkCmlIEIhREsK40DWMSU5tfMyiXWpAC6LwWDCaFLCBRBJcMeIp4uECZBy8ct4ZQpy9ZP4rs90rD3OiAkYLSbPz4fAvNDHzZH7b30x0p9YQi21rqYHPrO8UxXlntIo85qZLZcGiYj0sljaPBESHbVdg340EWA8ZPQoME0c++5DoW+a1FhsGPR0FnT3S4uRMomxdBKntHn9xDYsUT+iSDXxvS93iZsKcFg5sgktjfqjMy0iwYJEdIbLrAhpgMEsbspASQSVhRjbFIsFHEKacTuNQC69ZcDlk+DImmYmiEwqSMpDGiOMbW5QLdUJSF2OZramHXa6hHvFbdtkZcNKvJVpo3BIFEImzJgKjhRcDZqamqckKGEi0DNJWvkK1cSGEZp1ts5NZSMomZYoLBDGo0JZi0H5Qin1kYR/Mtig9bDfgIYCoAT65nLwf28HJ+YifDZjDZtAhAvUc0OIVN33pAxCTSCInFoUCKpIQ9obuHHzh3IcjDmIagsggalxIEIEcpQd+6YZjj1BkCFkHDUCEKNxFlUPzDt1ZlGRiidCQ1cqRBB9S7hPNTiFh+o8Xmph6/le7wuciIdXnkXoOgpOljzuF1McRIvLBMbzC3gb/nh2Ej3oXlBAel2ofQUeOteU8Eo+bMpCD31STWBxMg7SjuJRYYM/L1VZA2suyc0UCxAZDW5pS4qYDsIoODMgTtgSwIxmMXYHIIHv/TWa2X8kmJTqegdnkbG9NViQWCE5aDwqxoO2jbj4IVVBUQ1piLGPeBz3o2VvZPvJU+NN1+Ek1DJAZdk2qqHXVbN9GlDCFDTJ3eazTV5fNTURGJoaFa/YTMfyuOVtaWpKTMSrq7qdbMdxj5jpmiaPHLeB5xOw8Z6woeJCQ+MHTveCT69nGEPey8RxRxKwkgQkWERpgNMAMkUG5QL7gA+YB+5hPMfrzA2A2iw2PngEGCyFiLE8vRSuAYl6ggkgk+JQriEH4GrtENIFRSQjEQ+gV97EeT25PCTy95a056h8yC/k5ewOw5HvNetFPhFM0O07CwFwkFkVZARkuSiIrqZhX0ukSVG4YQFKpCiwNIsUEIhJSBO3YIYUuxvAaiVFZEaihQRqilpBgQRCKRiVJaDYLCRZCQUWKBSBYyyiBYMBCgMQsgIAwCEEIxCLT4B5EgsFJAJEXI6/CRfG0LxMaGKs9RAtiYveITkHrnXqZIQcDr1qrDBqYIZSnz59sc9mldh4yxI+k7pM3jjWD4fY7fjVydDid3MubkJFYpDl+N2M7XFjwunzMvPDoyBCLnC6CyaQg/T2DDOMeM6ceWD1R1qsKr4J2rGSI+k+Hgo0zT/ebDA2/VX62zPyO2bHG/G77coYvf6ypGDWMEZ0Q2HYloJ9jHkRaDmx1Bd6DsIMZ1GDOgOS05pwo4zUQkxQewpRwideO9zcKUoQEgVk2iYdNiiaZr0dFlYdnxdRSCn89C0+apNbY52RuW1BSK5miyXKnP4z6R3bbpLH75MyLIhu/MHkyI9TtqR0Ys4ZIdKMd0zpsJxoHxwVt7vwfzMcEeaMTN2c0zXJNrgXEl473FO82KGgn8xESjmu0yyaEPxsVGTSuIt6WnpG2p3Ci2hPWVj3bzayshy8gyGTfp90QU7nBYHOrFbriOYaOd64oPz5lYjm2jU0b4usgmK0a4sDidth7NChoNO6SFUefD51crTOSmWU+ref6ncZTanVZRwKHpgGA9Zrr0G9wZzDqypIW97wwIa1Q5F4B8xIXdiRno5lSRYwBwQIz9CbJriJcZuJNJAbIVeBrVSJe4YVx1EYPjg8OhU6hQ1L2SePTi90egkLhOhHEoqGNx/Mra5qzRaV24VDOO43vNmjLburSVJkknZIfIq3LVpkhJtE3AiciDq320g6FTqSIte30qJpLl9wah6MIWjMXv1nQZyAhYSCMu4G5b1cT8J8GE4ZhqeRgxdbn5CXFIHoWt/TZVu/Kw4Rx8f6uwzDfnm9BPLPxR+9ANyhDdgodDh0kV3byhq6KcDgUhkkZCaZSoY5jnsWEFURHqhiUs4SiIrEEGAuFoCnFsFhHQCqMoG9lgS0mBN6hWO4GwKWgaGg0PaziQJF6eiizanufRo8OBC2Dv7h6imzYXoIhJBPteFFzwzMZUKLhZbYR+vqiO9SwdgKlRYMQGapFC4UrWFRqGZo0AUNI6+GOtJqXF20XEqmqGLaWWl23C73rW7sVllovgsgoe5rDfN3ZWUzEG9eVVqjVcmszCtLLXTahoGYk4zDBVnhD1SdR74ntx3Dy6KFLeZ6owgoawDaAXU2LwgtBVV2++tqnKzvzmhzc7q5LkR9x4T2EkNsDoIwNBnNBckiWCj8UGQ4KqIrFWPZW3IhXll/Q2phzOWeRm79AiOs6SHUyEpYWTrwrDyhneLGIIYYB9ACKEJhnGo7BvLR4MFvz71WxedizoSxAjso1zVDxkJDLfZf1BxYNtTc41akU8kCx2+ujvOdZUuTQ7DeZ5KBN3MrGAA+2IDXwY2kZuqPg/qU5bCG5EVGQUERYoIiPIVjmBkPaJkyFIiUSjWVAghIggIAoSCPooVWHqhAsmQMsCyX0rjKYnpDdncyWTLZNmcahWcDpCixB1kpgtURGGWpaFhMLXGExgFYS5g3CQCpiJB3LYkZOBneWLpHhYs8WUQkqFb6Z308YXhML68/SaHWF8fEhwGC6I1mnoki4DkcoKnCMKMdcOKSsiiXkWGOikYkoFeiI8TRYsbyEYyEkPEuwGlixZ9HUBIyjYE6ElaiPm+8B05j2qyaeYydOV0OAujoTMPgz6bJTqxvJEoutrK0uYpgyIcwzDlCAxAtmHhQeZm8moMLBw674ZjRUD22gWyHlTQQDenXAT6HzpGBc+G/wk4GxRhL82WRjjotaLQrQRMPi8/R93k9HhmjuW00svfKsPN0bDnI8qNnhhd6Lxx7k9/kZUBZKsM+5VDrSrc0/aJYlMM5qD0W8stapvuGEHLMMmBLu5Lzx4EYaaNBpgnESfppstCSabCReHnRqIRFXA5TlmORvRcjgOh6/oOHOzi2LMssn66cCWEccg5NUeJYmB0Fpm78Lksldn451oymMc3GEyXQU0szuO7dduIFQOIaVsTHQg0tW4gTEcJkHEMO4doK2+JXNoZzR1tQxGTiGXOFBTfirpo3Qx88NNEXbL0HphQ2a6cQOZg43qZZKwyEJRJtQTa/oayB4T0VfaMGlAIQAFiYKyToMCyzoKc+85d2DR23jScgsQKENCKcZBXaAlBpsYuGx7kobtV7bQC2JdDidG3Gx1GKmgmSimQNpECbSpMUVW5yfWK9LuNCH1MczU0VCSepHFG3fq3u4IxtyQOS8iFcwxJcy0xjsc6B2ZsHs92zLKONuUcaWSMua0SW6OX7S23ipHYZG3VwzL0Y9qjQ0MTTWxINNG5htBGYKUJpg2NMFjE1CBfIGYMZ0UNFHGBo6FocxMA4TFVRuTRHu6ZZFmqZQY0KZ3LxRHHeYrfEPlayoxx74GAuGElc2G8wFBgRuFmpCIxbYCzREpA5bLhUSpZKHvJNISju5KNodZg4SlA5qXImIzSEtxnt/FzByG2ZA2w3DGgTDIbGIsGdDPLGMSah261wCowpqcTWCgUTQ0sKLEUhguoMPR6PYdk7xGlx0Z1IJ09Ry18fTwsYKrKFyHIjgl5qXqKm3YokQsdIBgA/U8adeigvIQFkVcw1LFh09UyM+7MyTpTueoG5sGEUIRUbGOFFEvqKYmUcphnDpgaEQ0yjGCREsRwsKWQsWCyK1MuIoJoEIkYwkkBjSSxFIChRVKlDoHR0PVO/kc+RK6VtKirTMhgmpTSMEbtkoEh4jkbMSCtHqD2zS6tfUsRTnA3LSCKINIFgOxfmZo3OmU6mVQvRIwEN8hI69B7tdGtVkm5OoGMREsIrQnk9edTWy5LRiGeu0Q0AOoyetWYl90p54RCDyAw7c6HWCVgrrTNxJDu6eswdSDuGC/VFApUqArRDyxSkNFQTK0LUpYTQ/VRcbY7S6IZWUGwicN5DAZ7gKnCVJEg4sDGcc3BNhXVjBQUkHvPR2hVgKhUOPK2aBCAnZnKIqLyMMduroXfq5EkOw7nnyE5EG8jAuAWo1xrBTJJhEm0MCsbGtPTooJYaoQYNYGVGKIlRHAzFSoBYd02GzZ8Z1/i6OSZqZzfYso2aylFHPwPgmx014rF4wyQnfIeQGQ6EVO8Ih1XqcvaJg0DJIHhOEFe2IO4gnqVVV8BDuFHUnHjMWojCu35TrvDY8z0WW2BvKqirDmQpRGHmEwDYQKh7ZKCjzOBXcGnZexeuuaK4bTPzOaQdQgFlTdRYDwzNYadp5RNBTruWNgIpIEAgBFfaf6jbHOSRI3Znkp+ggaQQeSEUHMXIO7qNg+f8/V4+mjyWgwhRGiDJWdMD0np902WaBmiHtS5iINtHASNcUKqDWN1nGTJDEu5haG8Axg0oiXuhC7iUYkKlXpTrm/l36aL7Tc+S4RJBoFoKJxEoQPcHEDgB3BkLfdOgVsDMEIASCoCAcNAN+bEGNVmmYRx6iiJnRnyrA2ergQO+HzeuE4shYcIF1Lk70TsO6OhPLFdIY6AipoMNbNEIYChlgyLBUYxEYTcagabbUZ0Ijf/22IREkBG/r0Ih3EA3WCsIZge4fmuBkjvFdSdwZi+SKkCSD72AsIPJH9eeyJ5wLjqhFP8TBwqiEkBhCUUVJS2AlpPVYeSd1JYE5GgniHyIfDcF6PTE0e84hsXs2nweulD5IaGrwNuQmWf+d3ekFtL8iy+LJ+dIJaxtAMEdZ4oeCubYfYsLGiL4QVcBZMq9LAJCyQfIVYkQ7guhHs6+vdbeVxKeygqixZI7jUAH88Gg3AGPirIWIzvNJ4wzGCc22upDaCE8pGHsC+E+l+o+LfHyyAbRgv+NqqmWzKBRGAoLESBFIkN0IzSBnnlkoECMIYjakfj2ht6t/4xICOkkMHuK+jyXT4u6phrxO6j658AwPuF+wIpI5HkPOGui9SqxIzvh0J5bbb8OFGLHAKwZQshUHs2GAAz8GfRwKLTW8Imj1YC4TtUqorZsL5L8UBJiCqRjnEBnDA4pCDSeGY8rjKq6ECRZp+ELBnplR/IXTJhmNJmNhRod58AcwPJPYZmYeczMC9wR+QxCEKIjSVITNMCAXHtmqoHB/J419z4/Fzwj3/TnnnlqZonFHvSiReweIByKAzvjOhx0lyltZjEPzCYugYfH81TQ+o6z1BtOzv8YXQDPBRxplGoHtoxUIMkFZFAohCskKJ5UBijBQgKEtkPOKCQzPA8cEdFoJdjPxuNB+j6thMiNmW/zRs3lY6b7UxSPuFrcFoz8B2w3QYo4fZ94u6I7O2xzkaGWlsV0k4vd1osMEqDqmw1Y8gSwZUy7Kc3H865vCHRCZI7oeS2QqBxDmU0NKQG55DYNki9JA9VkT0BcROjciZ4c4aoZqLqZnTuzES4fmO0DQivE4er20eXwPls+VF6ybTBb4VIif7p70NDpQr5D5ws0Hz19wc2amTJ8w2AUQMYPETq9h6MKT9PAq78zQfdO/zOplmanr9P8TPRoMf3mZj2Fzem1BxHKM//UP/r5Pb+Z//F3JFOFCQSJec2g')))
\ No newline at end of file
+exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/presentation/students/cpp_course/unitgrade_data/Fractions_Basics.pkl b/examples/presentation/students/cpp_course/unitgrade_data/Fractions_Basics.pkl
index 2d31d464ed020fd09e00880bef601fc4392ecb9e..0e68385e24a03205998543f12ac101717e27d880 100644
Binary files a/examples/presentation/students/cpp_course/unitgrade_data/Fractions_Basics.pkl and b/examples/presentation/students/cpp_course/unitgrade_data/Fractions_Basics.pkl differ
diff --git a/examples/presentation/students/cpp_course/unitgrade_data/Fractions_from_string.pkl b/examples/presentation/students/cpp_course/unitgrade_data/Fractions_from_string.pkl
index a0e39d1e2fab811d26708601122b4ec6c5dd3ec2..3147329ad019c86d5f37071f0c1c8c329e56328f 100644
Binary files a/examples/presentation/students/cpp_course/unitgrade_data/Fractions_from_string.pkl and b/examples/presentation/students/cpp_course/unitgrade_data/Fractions_from_string.pkl differ
diff --git a/examples/presentation/students/cpp_course/unitgrade_data/main_config_tests_ex6.artifacts.pkl b/examples/presentation/students/cpp_course/unitgrade_data/main_config_tests_ex6.artifacts.pkl
index 77cbbfcab4b630fddc890be3158e1cf5b05050b8..26bef65c6f66f812a362f373a346e0d1be60cc14 100644
Binary files a/examples/presentation/students/cpp_course/unitgrade_data/main_config_tests_ex6.artifacts.pkl and b/examples/presentation/students/cpp_course/unitgrade_data/main_config_tests_ex6.artifacts.pkl differ
diff --git a/examples/presentation/students/cpp_exam/tests_exam.py b/examples/presentation/students/cpp_exam/tests_exam.py
index b68bfbe3c62c770d66c894a06112d2d30f9c4b80..33d7c5a8f37379bba13a754729622a8552e5fab3 100644
--- a/examples/presentation/students/cpp_exam/tests_exam.py
+++ b/examples/presentation/students/cpp_exam/tests_exam.py
@@ -5,35 +5,6 @@ from cpp_exam.problem2_rle import Elem, rle_sum, reverse, concatenate, displayRL
from cpp_exam.problem3_groceries import GroceryList
from cpp_exam.problem4_filter import Buffer
-# class Q1Vectors_Examples(UTestCase):
-# def test_correct_format(self):
-# """ Test your field is in the right format.
-# Hints:
-# * If this test fails, all subsequent tests will fail. Make sure it works!
-# """
-# A = createField(3, 3, Vector(1, 2))
-# self.assertEqual(len(A), 3) # Check there are 3 rows in A
-# self.assertEqual(len(A[0]), 3) # Check there are 3 columns in A
-# v = A[1][1] # Should be a Vector(1, 2) element.
-# self.assertEqual(v.x, 1) # Check that first coordinate is 1
-# self.assertEqual(v.y, 2) # Check that first coordinate is 1
-#
-# def test_displayField(self):
-# A = createField(3, 3, Vector(1, 2))
-# A[1][1] = Vector(2, 2)
-# self.assertEqualC(displayField(A).strip())
-#
-# def test_addFields(self):
-# A = createField(3, 3, Vector(1, 2))
-# A[1][1] = Vector(2, 2)
-# B = createField(3, 3, Vector(2, -2))
-# B[0][0] = B[2][2] = Vector(9, 8)
-# self.assertEqualC(displayField(addFields(A, B)).strip())
-#
-# def test_scaleFields(self):
-# A = createField(3, 3, Vector(1, 2))
-# A[1][1] = Vector(2, 2)
-# self.assertEqualC(displayField(scaleField(A, 2)).strip())
def vector2string(v):
return f"({v.x},{v.y})"
diff --git a/examples/presentation/students/cpp_exam/tests_exam_grade.py b/examples/presentation/students/cpp_exam/tests_exam_grade.py
index d09bb1329d42fc29cd42b16524e54449d5669ae7..7276d87b97b23b2577e34f69d005aa30b7435b2c 100644
--- a/examples/presentation/students/cpp_exam/tests_exam_grade.py
+++ b/examples/presentation/students/cpp_exam/tests_exam_grade.py
@@ -1,4 +1,4 @@
# cpp_exam/tests_exam.py
''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
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+exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/presentation/students/cpp_exam/unitgrade_data/Q1Vectors.pkl b/examples/presentation/students/cpp_exam/unitgrade_data/Q1Vectors.pkl
index e5ab8f30ab6b477c352d83c3a1ea42450d158c0b..d6ed222553d6456decd2bec0585b5f59db93bf6f 100644
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diff --git a/examples/presentation/students/cpp_exam/unitgrade_data/Q2RLE.pkl b/examples/presentation/students/cpp_exam/unitgrade_data/Q2RLE.pkl
index 8bd8f93e1dcf62d022df12f97ee69a13daa3bd84..9a966a8af80f33ec36911261721c99c5026412d8 100644
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diff --git a/examples/presentation/students/cpp_exam/unitgrade_data/Q3Groceries.pkl b/examples/presentation/students/cpp_exam/unitgrade_data/Q3Groceries.pkl
index e894bd9fcebfad69241890258bd985c0f234a37b..0358822545a338398cffeb774eb42a8a0a23f5c2 100644
Binary files a/examples/presentation/students/cpp_exam/unitgrade_data/Q3Groceries.pkl and b/examples/presentation/students/cpp_exam/unitgrade_data/Q3Groceries.pkl differ
diff --git a/examples/presentation/students/cpp_exam/unitgrade_data/Q4FilterBuffer.pkl b/examples/presentation/students/cpp_exam/unitgrade_data/Q4FilterBuffer.pkl
index 8544aeb6c5ac91153ee70063ef229218461e7344..b6730d7f602086f60c14fb70641d5e0f94c0d2bc 100644
Binary files a/examples/presentation/students/cpp_exam/unitgrade_data/Q4FilterBuffer.pkl and b/examples/presentation/students/cpp_exam/unitgrade_data/Q4FilterBuffer.pkl differ
diff --git a/examples/presentation/students/intro_python/exam.py b/examples/presentation/students/intro_python/exam.py
index d0eaba4d28d7dd2792bed596c0ad62a8e20cd80a..90661cd95fe43e14ef2149c0a9c3eb080d10e692 100644
--- a/examples/presentation/students/intro_python/exam.py
+++ b/examples/presentation/students/intro_python/exam.py
@@ -8,8 +8,8 @@ class Q1_WaterHeight(UTestCase):
h0 = 5
r = np.array([4.5, 0, 1.5, 0, 0, 0.5, 1, 2, 5])
h = water_height(h0, r)
- print("Water height computed to be", h, "should be", self.get_expected_test_value())
- self.assertEqual(h, 3.0) # Check the height is 3.0
+ print("Water height computed to be", h, "should be", 3.0)
+ self.assertEqual(h, 3.0) # Check that the height is 3.0
class Q2_AstronomicalSeason(UTestCase):
diff --git a/examples/presentation/students/intro_python/exam_grade.py b/examples/presentation/students/intro_python/exam_grade.py
index 67b272c3fa4478273b3f9ea2a69d03e824a5ae17..94708204bf79f95b51421bd03febef3e80c86f16 100644
--- a/examples/presentation/students/intro_python/exam_grade.py
+++ b/examples/presentation/students/intro_python/exam_grade.py
@@ -1,4 +1,4 @@
# intro_python/exam.py
''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
+exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/presentation/students/intro_python/unitgrade_data/Q1_WaterHeight.pkl b/examples/presentation/students/intro_python/unitgrade_data/Q1_WaterHeight.pkl
index 834d08b7bbdcf8ebf2e06cfe57953e687871396a..a970fa62698d1a5f6ff1735ae4f68576580073b9 100644
Binary files a/examples/presentation/students/intro_python/unitgrade_data/Q1_WaterHeight.pkl and b/examples/presentation/students/intro_python/unitgrade_data/Q1_WaterHeight.pkl differ
diff --git a/examples/presentation/students/intro_python/unitgrade_data/Q2_AstronomicalSeason.pkl b/examples/presentation/students/intro_python/unitgrade_data/Q2_AstronomicalSeason.pkl
index 2d677c3561d435b085828c376c30118f918b7c5d..141e68b2ecfd7e8f1257dcad58ff995b45226811 100644
Binary files a/examples/presentation/students/intro_python/unitgrade_data/Q2_AstronomicalSeason.pkl and b/examples/presentation/students/intro_python/unitgrade_data/Q2_AstronomicalSeason.pkl differ
diff --git a/examples/presentation/students/intro_python/unitgrade_data/Q3_TimeAngle.pkl b/examples/presentation/students/intro_python/unitgrade_data/Q3_TimeAngle.pkl
index 8528aeef3c8c029a9a8af2b1bc198d19a0463555..172fddba0c837b90b00978833d54a6753f778025 100644
Binary files a/examples/presentation/students/intro_python/unitgrade_data/Q3_TimeAngle.pkl and b/examples/presentation/students/intro_python/unitgrade_data/Q3_TimeAngle.pkl differ
diff --git a/examples/presentation/students/intro_python/unitgrade_data/Q4_TicTacToe.pkl b/examples/presentation/students/intro_python/unitgrade_data/Q4_TicTacToe.pkl
index 163e3b6bbf380c2ec67ca64c32d89bee735a97be..6a423050716cbdc910777b42e19a27badf016605 100644
Binary files a/examples/presentation/students/intro_python/unitgrade_data/Q4_TicTacToe.pkl and b/examples/presentation/students/intro_python/unitgrade_data/Q4_TicTacToe.pkl differ
diff --git a/examples/presentation/students/intro_python/unitgrade_data/Q5_StandardizeAddress.pkl b/examples/presentation/students/intro_python/unitgrade_data/Q5_StandardizeAddress.pkl
index a55324933d96a979dce39176c27427e4ef8b5ea2..c04eb5ac0263290466e8e5ac540d4958af14a21d 100644
Binary files a/examples/presentation/students/intro_python/unitgrade_data/Q5_StandardizeAddress.pkl and b/examples/presentation/students/intro_python/unitgrade_data/Q5_StandardizeAddress.pkl differ
diff --git a/examples/presentation/students/intro_python/unitgrade_data/cache.db b/examples/presentation/students/intro_python/unitgrade_data/cache.db
deleted file mode 100644
index 8dd368fef0b15c12edfb4affc508d49a8b00b794..0000000000000000000000000000000000000000
Binary files a/examples/presentation/students/intro_python/unitgrade_data/cache.db and /dev/null differ
diff --git a/examples/presentation/students/intro_python_devel/exam_water_height.py b/examples/presentation/students/intro_python_devel/exam_water_height.py
new file mode 100644
index 0000000000000000000000000000000000000000..a498959242a04982f4cb5003f9ca5eb9729e9897
--- /dev/null
+++ b/examples/presentation/students/intro_python_devel/exam_water_height.py
@@ -0,0 +1,12 @@
+import numpy as np
+from unittest import TestCase
+from unitgrade import UTestCase, Report, hide
+import intro_python_devel
+from intro_python_devel.water_height import water_height
+
+class Q1_WaterHeight(TestCase):
+ def test1(self):
+ h0 = 5
+ r = np.array([4.5, 0, 1.5, 0, 0, 0.5, 1, 2, 5])
+ h = water_height(h0, r)
+ self.assertEqual(h, 3.0) # Check that the height is 3.0
diff --git a/examples/presentation/students/intro_python_devel/water_height.py b/examples/presentation/students/intro_python_devel/water_height.py
new file mode 100644
index 0000000000000000000000000000000000000000..7073d33f023cf6778354567b6a969a6ec7231800
--- /dev/null
+++ b/examples/presentation/students/intro_python_devel/water_height.py
@@ -0,0 +1,10 @@
+def water_height(h0, r):
+ """ Problem 1: Compute the water height.
+
+ Hints:
+ * Remember the height must be a non-negative number.
+ """
+ h = h0
+ for ri in r:
+ h = max(h + ri - 2, 0)
+ return h
diff --git a/examples/presentation/students/secret/scrab b/examples/presentation/students/secret/scrab
new file mode 100644
index 0000000000000000000000000000000000000000..fbebaf1b7ddaff41c7542b5676d94975c9b04cdb
--- /dev/null
+++ b/examples/presentation/students/secret/scrab
@@ -0,0 +1,19 @@
+
+class ReportWater(Report):
+ title = "Water height problem example"
+ questions = [(Q1_WaterHeight, 40)]
+ pack_imports = [intro_python_devel]
+
+if __name__ == "__main__":
+ from unitgrade import evaluate_report_student
+ evaluate_report_student(ReportWater())
+
+
+
+from unitgrade_private import setup_grade_file_report
+from snipper import snip_dir
+from intro_python_devel.exam_water_height import ReportWater
+
+if __name__ == "__main__":
+ setup_grade_file_report(ReportWater)
+ snip_dir("../intro_python_devel", "../../students/intro_python_devel", clean_destination_dir=True, exclude=['*.token', 'deploy_water.py', '*_complete*'], output_dir="../../Latex/output")
diff --git a/src/unitgrade_private/hidden_create_files.py b/src/unitgrade_private/hidden_create_files.py
index c9091383f9170cfe0511a73f83f48b4924690ade..d0e87980fda1856645010b407e9456df09f2140c 100644
--- a/src/unitgrade_private/hidden_create_files.py
+++ b/src/unitgrade_private/hidden_create_files.py
@@ -87,7 +87,8 @@ def setup_grade_file_report(ReportClass, execute=False, obfuscate=False, minify=
from unitgrade.evaluate import SequentialTestLoader
loader = SequentialTestLoader()
for q, points in report.questions:
- artifacts['questions'][q.__qualname__] = {'title': q.question_title(), 'tests': {} }
+
+ artifacts['questions'][q.__qualname__] = {'title': q.question_title() if hasattr(q, 'question_title') else q.__qualname__, 'tests': {} }
suite = loader.loadTestsFromTestCase(q)
from unitgrade.framework import classmethod_dashboard
@@ -103,17 +104,22 @@ def setup_grade_file_report(ReportClass, execute=False, obfuscate=False, minify=
'coverage_files': q()._get_coverage_files(),
}
for t in suite._tests:
- id = t.cache_id()
- cf = t._get_coverage_files()
- cf = [] if cf is None else cf
- artifacts['questions'][q.__qualname__]['tests'][id] = {'title': t.title,
- 'artifact_file': os.path.relpath(t._artifact_file(), root_dir), # t._artifact_file(),
- 'hints': t._get_hints(),
- 'coverage_files': cf
- }
+ try:
+ id = t.cache_id()
+ cf = t._get_coverage_files()
+ cf = [] if cf is None else cf
+ artifacts['questions'][q.__qualname__]['tests'][id] = {'title': t.title,
+ 'artifact_file': os.path.relpath(t._artifact_file(), root_dir), # t._artifact_file(),
+ 'hints': t._get_hints(),
+ 'coverage_files': cf
+ }
+ except Exception as e:
+ pass
a = 34
# s, _ = dict2picklestring(artifacts['questions'])
db['questions'] = artifacts['questions'] # ('questions', s)
+ if not os.path.isdir(os.path.dirname(report._artifact_file())):
+ os.makedirs(os.path.dirname(report._artifact_file()))
with open(report._artifact_file(), 'wb') as f:
pickle.dump(db, f)
diff --git a/src/unitgrade_private/hidden_gather_upload.py b/src/unitgrade_private/hidden_gather_upload.py
index d4f4983a4c98bde119b6a609c22c5ca3d3c63328..fbc75a82ea7b19edb630e599276d98054dbf3984 100644
--- a/src/unitgrade_private/hidden_gather_upload.py
+++ b/src/unitgrade_private/hidden_gather_upload.py
@@ -24,7 +24,7 @@ def gather_imports(imp):
print("im is a list")
print(im)
# the __path__ attribute *may* be a string in some cases. I had to fix this.
- print("path.:", __import__(m.__name__.split('.')[0]).__path__)
+ # print("path.:", __import__(m.__name__.split('.')[0]).__path__)
# top_package = __import__(m.__name__.split('.')[0]).__path__._path[0]
top_package = __import__(m.__name__.split('.')[0]).__path__[0]
module_import = False
@@ -89,7 +89,7 @@ def gather_report_source_include(report):
nimp['report_module_specification'] = module_import
nimp['name'] = m.__name__
sources[k] = nimp
- print(f" * {m.__name__}")
+ print(f" * {str(m.__name__)}")
return sources
def gather_upload_to_campusnet(report, output_dir=None, token_include_plaintext_source=False):
diff --git a/src/unitgrade_private/pipelines/dtulearn.py b/src/unitgrade_private/pipelines/dtulearn.py
index 77d5ac41034613256ce0ad70824b1ddae90bac3e..4a6f981b1d697113ee3ef2766cb0972d960ae1e2 100644
--- a/src/unitgrade_private/pipelines/dtulearn.py
+++ b/src/unitgrade_private/pipelines/dtulearn.py
@@ -315,6 +315,12 @@ def make_xlsx_file(rs):
d['Question'].append(" ")
d[id].append(" ")
+ d['Question'].append("Student total (obtained/possible)")
+ d[id].append(f"{rs[id]['student-token-total']}")
+
+ d['Question'].append("Verified total (obtained/possible)")
+ d[id].append(f"{rs[id]['verified-token-total']}")
+
import pandas as pd
df = pd.DataFrame.from_dict(d)
df.to_excel("token_evaluations.xlsx")