diff --git a/doc/src/GaussianProcess/._GaussianProcess-bs000.html b/doc/src/GaussianProcess/._GaussianProcess-bs000.html new file mode 100644 index 000000000..b625ba045 --- /dev/null +++ b/doc/src/GaussianProcess/._GaussianProcess-bs000.html @@ -0,0 +1,166 @@ + + + + + + + +Data Analysis and Machine Learning: Machine learning with Gaussian Processes + + + + + + + + + + + + + + + + + + + + + + + +
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+ + Data Analysis and Machine Learning: Machine learning with Gaussian Processes +
+ +
+ +
+
+ + +
+ +

 

 

 

+ + + + + + +
+

Data Analysis and Machine Learning: Machine learning with Gaussian Processes

+ +

+ + +

+Christian Forssén [1] +
+ +
+Morten Hjorth-Jensen [2, 3] +
+ +

+ + +

[1] Department of Physics, Chalmers University of Technology, Sweden
+
[2] Department of Physics, University of Oslo
+
[3] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University
+
+

+

Mar 19, 2018

+
+

+ + +

Read »

+ + +
+ +

+ +

+ + +
+ + + + + + + +
+ © 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license +
+ + + + + + diff --git a/doc/src/GaussianProcess/._GaussianProcess-bs001.html b/doc/src/GaussianProcess/._GaussianProcess-bs001.html new file mode 100644 index 000000000..71542600a --- /dev/null +++ b/doc/src/GaussianProcess/._GaussianProcess-bs001.html @@ -0,0 +1,152 @@ + + + + + + + +Data Analysis and Machine Learning: Machine learning with Gaussian Processes + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + Data Analysis and Machine Learning: Machine learning with Gaussian Processes +
+ +
+ +
+
+ + +
+ +

 

 

 

+ + + + +

What is a Gaussian Process?

+ + + +require choice of somewhat arbitrary set of knots. + + + +

+ +

+ + +
+ + + + + + + +
+ +
+ + + + + + diff --git a/doc/src/GaussianProcess/._GaussianProcess-bs002.html b/doc/src/GaussianProcess/._GaussianProcess-bs002.html new file mode 100644 index 000000000..4faa348ba --- /dev/null +++ b/doc/src/GaussianProcess/._GaussianProcess-bs002.html @@ -0,0 +1,157 @@ + + + + + + + +Data Analysis and Machine Learning: Machine learning with Gaussian Processes + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + Data Analysis and Machine Learning: Machine learning with Gaussian Processes +
+ +
+ +
+
+ + +
+ +

 

 

 

+ + + + +

Gaussian process regression

+ + + +$$ +$$ + \mu(x_1), \ldots \mu(x_N) \sim \mathrm{N}\left( \left( m(x_1), + \ldots, m(x_N) \right), K(x_1, \ldots, x_N) \right), +$$ +$$ + + with mean \( m \) and covariance \( K \). + +

+

+ +

+ + +
+ + + + + + + +
+ +
+ + + + + + diff --git a/doc/src/GaussianProcess/._GaussianProcess-bs003.html b/doc/src/GaussianProcess/._GaussianProcess-bs003.html new file mode 100644 index 000000000..076f34e3a --- /dev/null +++ b/doc/src/GaussianProcess/._GaussianProcess-bs003.html @@ -0,0 +1,142 @@ + + + + + + + +Data Analysis and Machine Learning: Machine learning with Gaussian Processes + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + Data Analysis and Machine Learning: Machine learning with Gaussian Processes +
+ +
+ +
+
+ + +
+ +

 

 

 

+ + + + +

Topics

+ + + + +

+ +

+ + +
+ + + + + + + +
+ +
+ + + + + + diff --git a/doc/src/GaussianProcess/GaussianProcess-beamer-handouts2x3.pdf b/doc/src/GaussianProcess/GaussianProcess-beamer-handouts2x3.pdf new file mode 100644 index 000000000..8cdfa31ef Binary files /dev/null and b/doc/src/GaussianProcess/GaussianProcess-beamer-handouts2x3.pdf differ diff --git a/doc/src/GaussianProcess/GaussianProcess-beamer.pdf b/doc/src/GaussianProcess/GaussianProcess-beamer.pdf new file mode 100644 index 000000000..f7e5e3484 Binary files /dev/null and b/doc/src/GaussianProcess/GaussianProcess-beamer.pdf differ diff --git a/doc/src/GaussianProcess/GaussianProcess-beamer.tex b/doc/src/GaussianProcess/GaussianProcess-beamer.tex new file mode 100644 index 000000000..06eccf60f --- /dev/null +++ b/doc/src/GaussianProcess/GaussianProcess-beamer.tex @@ -0,0 +1,219 @@ + +% LaTeX Beamer file automatically generated from DocOnce +% https://github.com/hplgit/doconce + +%-------------------- begin beamer-specific preamble ---------------------- + +\documentclass{beamer} + +\usetheme{red_plain} +\usecolortheme{default} + +% turn off the almost invisible, yet disturbing, navigation symbols: +\setbeamertemplate{navigation symbols}{} + +% Examples on customization: +%\usecolortheme[named=RawSienna]{structure} +%\usetheme[height=7mm]{Rochester} +%\setbeamerfont{frametitle}{family=\rmfamily,shape=\itshape} +%\setbeamertemplate{items}[ball] +%\setbeamertemplate{blocks}[rounded][shadow=true] +%\useoutertheme{infolines} +% +%\usefonttheme{} +%\useinntertheme{} +% +%\setbeameroption{show notes} +%\setbeameroption{show notes on second screen=right} + +% fine for B/W printing: +%\usecolortheme{seahorse} + +\usepackage{pgf} +\usepackage{graphicx} +\usepackage{epsfig} +\usepackage{relsize} + +\usepackage{fancybox} % make sure fancybox is loaded before fancyvrb + +\usepackage{fancyvrb} +%\usepackage{minted} % requires pygments and latex -shell-escape filename +%\usepackage{anslistings} +%\usepackage{listingsutf8} + +\usepackage{amsmath,amssymb,bm} +%\usepackage[latin1]{inputenc} +\usepackage[T1]{fontenc} +\usepackage[utf8]{inputenc} +\usepackage{colortbl} +\usepackage[english]{babel} +\usepackage{tikz} +\usepackage{framed} +% Use some nice templates +\beamertemplatetransparentcovereddynamic + +% --- begin table of contents based on sections --- +% Delete this, if you do not want the table of contents to pop up at +% the beginning of each section: +% (Only section headings can enter the table of contents in Beamer +% slides generated from DocOnce source, while subsections are used +% for the title in ordinary slides.) +\AtBeginSection[] +{ + \begin{frame}[plain] + \frametitle{} + %\frametitle{Outline} + \tableofcontents[currentsection] + \end{frame} +} +% --- end table of contents based on sections --- + +% If you wish to uncover everything in a step-wise fashion, uncomment +% the following command: + +%\beamerdefaultoverlayspecification{<+->} + +\newcommand{\shortinlinecomment}[3]{\note{\textbf{#1}: #2}} +\newcommand{\longinlinecomment}[3]{\shortinlinecomment{#1}{#2}{#3}} + +\definecolor{linkcolor}{rgb}{0,0,0.4} +\hypersetup{ + colorlinks=true, + linkcolor=linkcolor, + urlcolor=linkcolor, + pdfmenubar=true, + pdftoolbar=true, + bookmarksdepth=3 + } +\setlength{\parskip}{0pt} % {1em} + +\newenvironment{doconceexercise}{}{} +\newcounter{doconceexercisecounter} +\newenvironment{doconce:movie}{}{} +\newcounter{doconce:movie:counter} + +\newcommand{\subex}[1]{\noindent\textbf{#1}} % for subexercises: a), b), etc + +\logo{{\tiny \copyright\ 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license}} + +%-------------------- end beamer-specific preamble ---------------------- + +% Add user's preamble + + + + +% insert custom LaTeX commands... + +\raggedbottom +\makeindex + +%-------------------- end preamble ---------------------- + +\begin{document} + +% matching end for #ifdef PREAMBLE + +\newcommand{\exercisesection}[1]{\subsection*{#1}} + + + +% ------------------- main content ---------------------- + + + +% ----------------- title ------------------------- + +\title{Data Analysis and Machine Learning: Machine learning with Gaussian Processes} + +% ----------------- author(s) ------------------------- + +\author{Christian Forssén\inst{1} +\and +Morten Hjorth-Jensen\inst{2,3}} +\institute{Department of Physics, Chalmers University of Technology, Sweden\inst{1} +\and +Department of Physics, University of Oslo\inst{2} +\and +Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University\inst{3}} +% ----------------- end author(s) ------------------------- + +\date{Mar 19, 2018 +% +\ \\ +{\tiny \copyright\ 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license} +} + +\begin{frame}[plain,fragile] +\titlepage +\end{frame} + +\begin{frame}[plain,fragile] +\frametitle{What is a Gaussian Process?} + +\begin{itemize} +\item We have considered splines and kernel regression methods. These +\end{itemize} + +\noindent +require choice of somewhat arbitrary set of knots. + +\begin{itemize} +\item Antoher possibility is to setup a prior distribution for the + regression function using a \emph{Gaussian Process}. + +\item This is a very flexible class of models that has distinct computational + and theoretical advantages. It can be viewed as a potentially + infinite-dimensional generalization of Gaussian distributions. + +\item See the excellent (and free) book \href{{http://www.gaussianprocess.org/gpml/}}{Gaussian Processes for Machine + Learning} by Carl Edward + Rasmussen and Christopher K. I. Williams. +\end{itemize} + +\noindent +\end{frame} + +\begin{frame}[plain,fragile] +\frametitle{Gaussian process regression} + +\begin{itemize} +\item Realizations from a Gaussian process correspond to random functions + +\item Let us first consider an unknown regression function $\mu(x)$ that + depends on a single, continuous variable $x$. + +\item The Gaussian process is written as $\mu \sim \mathrm{GP}(m,k)$, and + is parametrized in terms of a mean function $m(x)$ and a covariance + function $k(x,x')$. + +\item The GP prior on $\mu$ describes it as a random function for which + the values at any set of $N$ prespecified points $\{x_i\}_{i=1}^N$ + are a draw from a $N$-dimensional normal distribution +\end{itemize} + +\noindent +$$ + \mu(x_1), \ldots \mu(x_N) \sim \mathrm{N}\left( \left( m(x_1), + \ldots, m(x_N) \right), K(x_1, \ldots, x_N) \right), +$$ + with mean $m$ and covariance $K$. +\end{frame} + +\begin{frame}[plain,fragile] +\frametitle{Topics} + +\begin{itemize} +\item More matematical details + +\item The role of the covariance function (different kernels) + +\item multidimensional case + +\item examples. +\end{itemize} + +\noindent +\end{frame} + +\end{document} diff --git a/doc/src/GaussianProcess/GaussianProcess-bs.html b/doc/src/GaussianProcess/GaussianProcess-bs.html new file mode 100644 index 000000000..b625ba045 --- /dev/null +++ b/doc/src/GaussianProcess/GaussianProcess-bs.html @@ -0,0 +1,166 @@ + + + + + + + +Data Analysis and Machine Learning: Machine learning with Gaussian Processes + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + Data Analysis and Machine Learning: Machine learning with Gaussian Processes +
+ +
+ +
+
+ + +
+ +

 

 

 

+ + + + + + +
+

Data Analysis and Machine Learning: Machine learning with Gaussian Processes

+ +

+ + +

+Christian Forssén [1] +
+ +
+Morten Hjorth-Jensen [2, 3] +
+ +

+ + +

[1] Department of Physics, Chalmers University of Technology, Sweden
+
[2] Department of Physics, University of Oslo
+
[3] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University
+
+

+

Mar 19, 2018

+
+

+ + +

Read »

+ + +
+ +

+ +

+ + +
+ + + + + + + +
+ © 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license +
+ + + + + + diff --git a/doc/src/GaussianProcess/GaussianProcess-minted.pdf b/doc/src/GaussianProcess/GaussianProcess-minted.pdf new file mode 100644 index 000000000..a0e2bce47 Binary files /dev/null and b/doc/src/GaussianProcess/GaussianProcess-minted.pdf differ diff --git a/doc/src/GaussianProcess/GaussianProcess-plain-minted.tex b/doc/src/GaussianProcess/GaussianProcess-plain-minted.tex new file mode 100644 index 000000000..10c1b645c --- /dev/null +++ b/doc/src/GaussianProcess/GaussianProcess-plain-minted.tex @@ -0,0 +1,206 @@ +%% +%% Automatically generated file from DocOnce source +%% (https://github.com/hplgit/doconce/) +%% +%% + + +%-------------------- begin preamble ---------------------- + +\documentclass[% +oneside, % oneside: electronic viewing, twoside: printing +final, % draft: marks overfull hboxes, figures with paths +10pt]{article} + +\listfiles % print all files needed to compile this document + +\usepackage{relsize,makeidx,color,setspace,amsmath,amsfonts,amssymb} +\usepackage[table]{xcolor} +\usepackage{bm,ltablex,microtype} + +\usepackage[pdftex]{graphicx} + +\usepackage[T1]{fontenc} +%\usepackage[latin1]{inputenc} +\usepackage{ucs} +\usepackage[utf8x]{inputenc} + +\usepackage{lmodern} % Latin Modern fonts derived from Computer Modern + +% Hyperlinks in PDF: +\definecolor{linkcolor}{rgb}{0,0,0.4} +\usepackage{hyperref} +\hypersetup{ + breaklinks=true, + colorlinks=true, + linkcolor=linkcolor, + urlcolor=linkcolor, + citecolor=black, + filecolor=black, + %filecolor=blue, + pdfmenubar=true, + pdftoolbar=true, + bookmarksdepth=3 % Uncomment (and tweak) for PDF bookmarks with more levels than the TOC + } +%\hyperbaseurl{} % hyperlinks are relative to this root + +\setcounter{tocdepth}{2} % levels in table of contents + +% --- fancyhdr package for fancy headers --- +\usepackage{fancyhdr} +\fancyhf{} % sets both header and footer to nothing +\renewcommand{\headrulewidth}{0pt} +\fancyfoot[LE,RO]{\thepage} +% Ensure copyright on titlepage (article style) and chapter pages (book style) +\fancypagestyle{plain}{ + \fancyhf{} + \fancyfoot[C]{{\footnotesize \copyright\ 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license}} +% \renewcommand{\footrulewidth}{0mm} + \renewcommand{\headrulewidth}{0mm} +} +% Ensure copyright on titlepages with \thispagestyle{empty} +\fancypagestyle{empty}{ + \fancyhf{} + \fancyfoot[C]{{\footnotesize \copyright\ 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license}} + \renewcommand{\footrulewidth}{0mm} + \renewcommand{\headrulewidth}{0mm} +} + +\pagestyle{fancy} + + +% prevent orhpans and widows +\clubpenalty = 10000 +\widowpenalty = 10000 + +% --- end of standard preamble for documents --- + + +% insert custom LaTeX commands... + +\raggedbottom +\makeindex +\usepackage[totoc]{idxlayout} % for index in the toc +\usepackage[nottoc]{tocbibind} % for references/bibliography in the toc + +%-------------------- end preamble ---------------------- + +\begin{document} + +% matching end for #ifdef PREAMBLE + +\newcommand{\exercisesection}[1]{\subsection*{#1}} + + +% ------------------- main content ---------------------- + + + +% ----------------- title ------------------------- + +\thispagestyle{empty} + +\begin{center} +{\LARGE\bf +\begin{spacing}{1.25} +Data Analysis and Machine Learning: Machine learning with Gaussian Processes +\end{spacing} +} +\end{center} + +% ----------------- author(s) ------------------------- + +\begin{center} +{\bf Christian Forssén${}^{1}$} \\ [0mm] +\end{center} + + +\begin{center} +{\bf Morten Hjorth-Jensen${}^{2, 3}$} \\ [0mm] +\end{center} + +\begin{center} +% List of all institutions: +\centerline{{\small ${}^1$Department of Physics, Chalmers University of Technology, Sweden}} +\centerline{{\small ${}^2$Department of Physics, University of Oslo}} +\centerline{{\small ${}^3$Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University}} +\end{center} + +% ----------------- end author(s) ------------------------- + +% --- begin date --- +\begin{center} +Mar 19, 2018 +\end{center} +% --- end date --- + +\vspace{1cm} + + +% !split +\subsection*{What is a Gaussian Process?} + +\begin{itemize} +\item We have considered splines and kernel regression methods. These +\end{itemize} + +\noindent +require choice of somewhat arbitrary set of knots. + +\begin{itemize} +\item Antoher possibility is to setup a prior distribution for the + regression function using a \emph{Gaussian Process}. + +\item This is a very flexible class of models that has distinct computational + and theoretical advantages. It can be viewed as a potentially + infinite-dimensional generalization of Gaussian distributions. + +\item See the excellent (and free) book \href{{http://www.gaussianprocess.org/gpml/}}{Gaussian Processes for Machine + Learning} by Carl Edward + Rasmussen and Christopher K. I. Williams. +\end{itemize} + +\noindent +% !split +\subsection*{Gaussian process regression} + +\begin{itemize} +\item Realizations from a Gaussian process correspond to random functions + +\item Let us first consider an unknown regression function $\mu(x)$ that + depends on a single, continuous variable $x$. + +\item The Gaussian process is written as $\mu \sim \mathrm{GP}(m,k)$, and + is parametrized in terms of a mean function $m(x)$ and a covariance + function $k(x,x')$. + +\item The GP prior on $\mu$ describes it as a random function for which + the values at any set of $N$ prespecified points $\{x_i\}_{i=1}^N$ + are a draw from a $N$-dimensional normal distribution +\end{itemize} + +\noindent +$$ + \mu(x_1), \ldots \mu(x_N) \sim \mathrm{N}\left( \left( m(x_1), + \ldots, m(x_N) \right), K(x_1, \ldots, x_N) \right), +$$ + with mean $m$ and covariance $K$. + +% !split +\subsection*{Topics} +\begin{itemize} +\item More matematical details + +\item The role of the covariance function (different kernels) + +\item multidimensional case + +\item examples. +\end{itemize} + +\noindent + +% ------------------- end of main content --------------- + +\end{document} + diff --git a/doc/src/GaussianProcess/GaussianProcess-reveal.html b/doc/src/GaussianProcess/GaussianProcess-reveal.html new file mode 100644 index 000000000..04a2f7976 --- /dev/null +++ b/doc/src/GaussianProcess/GaussianProcess-reveal.html @@ -0,0 +1,373 @@ +\ + + + + + + +Data Analysis and Machine Learning: Machine learning with Gaussian Processes + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + + + + + + + + + + + + + +
+ + + + +

Data Analysis and Machine Learning: Machine learning with Gaussian Processes

+ +

+ + +

+Christian Forssén [1] +
+ +
+Morten Hjorth-Jensen [2, 3] +
+ +

 
+ + +

[1] Department of Physics, Chalmers University of Technology, Sweden
+
[2] Department of Physics, University of Oslo
+
[3] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University
+
+

 
+

Mar 19, 2018

+
+

+ +

+ © 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license +
+
+ + +
+

What is a Gaussian Process?

+ +
    +

  • We have considered splines and kernel regression methods. These
    • +
+

+ +require choice of somewhat arbitrary set of knots. + +

    +

  • Antoher possibility is to setup a prior distribution for the + regression function using a Gaussian Process.
    • +

  • This is a very flexible class of models that has distinct computational + and theoretical advantages. It can be viewed as a potentially + infinite-dimensional generalization of Gaussian distributions.
    • +

  • See the excellent (and free) book Gaussian Processes for Machine + Learning by Carl Edward + Rasmussen and Christopher K. I. Williams.
    • +
+
+ + +
+

Gaussian process regression

+ +
    +

  • Realizations from a Gaussian process correspond to random functions
    • +

  • Let us first consider an unknown regression function \( \mu(x) \) that + depends on a single, continuous variable \( x \).
    • +

  • The Gaussian process is written as \( \mu \sim \mathrm{GP}(m,k) \), and + is parametrized in terms of a mean function \( m(x) \) and a covariance + function \( k(x,x') \).
    • +

  • The GP prior on \( \mu \) describes it as a random function for which + the values at any set of \( N \) prespecified points \( \{x_i\}_{i=1}^N \) + are a draw from a \( N \)-dimensional normal distribution
    • +
+

 
+$$ +$$ +

 
+ \mu(x_1), \ldots \mu(x_N) \sim \mathrm{N}\left( \left( m(x_1), + \ldots, m(x_N) \right), K(x_1, \ldots, x_N) \right), +

 
+$$ +$$ +

 
+ + with mean \( m \) and covariance \( K \). +

+ + +
+

Topics

+ +
    +

  • More matematical details
    • +

  • The role of the covariance function (different kernels)
    • +

  • multidimensional case
    • +

  • examples.
    • +
+
+ + + +
+
+ + + + + + + + + + + + diff --git a/doc/src/GaussianProcess/GaussianProcess-solarized.html b/doc/src/GaussianProcess/GaussianProcess-solarized.html new file mode 100644 index 000000000..9289ac673 --- /dev/null +++ b/doc/src/GaussianProcess/GaussianProcess-solarized.html @@ -0,0 +1,159 @@ + + + + + + + +Data Analysis and Machine Learning: Machine learning with Gaussian Processes + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Data Analysis and Machine Learning: Machine learning with Gaussian Processes

+ +

+ + +

+Christian Forssén [1] +
+ +
+Morten Hjorth-Jensen [2, 3] +
+ +

+ + +

[1] Department of Physics, Chalmers University of Technology, Sweden
+
[2] Department of Physics, University of Oslo
+
[3] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University
+
+

+

Mar 19, 2018

+
+

+









+ +

What is a Gaussian Process?

+ + + +require choice of somewhat arbitrary set of knots. + + + +









+ +

Gaussian process regression

+ + + +$$ +$$ + \mu(x_1), \ldots \mu(x_N) \sim \mathrm{N}\left( \left( m(x_1), + \ldots, m(x_N) \right), K(x_1, \ldots, x_N) \right), +$$ +$$ + + with mean \( m \) and covariance \( K \). + +

+









+ +

Topics

+ + + + + + + +
+ © 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license +
+ + + + + + diff --git a/doc/src/GaussianProcess/GaussianProcess.do.txt b/doc/src/GaussianProcess/GaussianProcess.do.txt new file mode 100644 index 000000000..2d1a99326 --- /dev/null +++ b/doc/src/GaussianProcess/GaussianProcess.do.txt @@ -0,0 +1,52 @@ +TITLE: Data Analysis and Machine Learning: Machine learning with Gaussian Processes +AUTHOR: Christian Forssén at Department of Physics, Chalmers University of Technology, Sweden +AUTHOR: Morten Hjorth-Jensen {copyright, 1999-present|CC BY-NC} at Department of Physics, University of Oslo & Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University +DATE: today + +!split +===== What is a Gaussian Process? ===== + +* We have considered splines and kernel regression methods. These +require choice of somewhat arbitrary set of knots. + +* Antoher possibility is to setup a prior distribution for the + regression function using a *Gaussian Process*. + +* This is a very flexible class of models that has distinct computational + and theoretical advantages. It can be viewed as a potentially + infinite-dimensional generalization of Gaussian distributions. + +* See the excellent (and free) book "Gaussian Processes for Machine + Learning": "http://www.gaussianprocess.org/gpml/" by Carl Edward + Rasmussen and Christopher K. I. Williams. + +!split +===== Gaussian process regression ===== + +* Realizations from a Gaussian process correspond to random functions + +* Let us first consider an unknown regression function $\mu(x)$ that + depends on a single, continuous variable $x$. + +* The Gaussian process is written as $\mu \sim \mathrm{GP}(m,k)$, and + is parametrized in terms of a mean function $m(x)$ and a covariance + function $k(x,x')$. + +* The GP prior on $\mu$ describes it as a random function for which + the values at any set of $N$ prespecified points $\{x_i\}_{i=1}^N$ + are a draw from a $N$-dimensional normal distribution + +!bt +$$ + \mu(x_1), \ldots \mu(x_N) \sim \mathrm{N}\left( \left( m(x_1), + \ldots, m(x_N) \right), K(x_1, \ldots, x_N) \right), +$$ +!et + with mean $m$ and covariance $K$. + +!split +===== Topics ===== +* More matematical details +* The role of the covariance function (different kernels) +* multidimensional case +* examples. diff --git a/doc/src/GaussianProcess/GaussianProcess.html b/doc/src/GaussianProcess/GaussianProcess.html new file mode 100644 index 000000000..a152ba8c0 --- /dev/null +++ b/doc/src/GaussianProcess/GaussianProcess.html @@ -0,0 +1,164 @@ + + + + + + + +Data Analysis and Machine Learning: Machine learning with Gaussian Processes + + + + + + + + + + + + + + + + + + + + + + + +

Data Analysis and Machine Learning: Machine learning with Gaussian Processes

+ +

+ + +

+Christian Forssén [1] +
+ +
+Morten Hjorth-Jensen [2, 3] +
+ +

+ + +

[1] Department of Physics, Chalmers University of Technology, Sweden
+
[2] Department of Physics, University of Oslo
+
[3] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University
+
+

+

Mar 19, 2018

+
+

+









+ +

What is a Gaussian Process?

+ + + +require choice of somewhat arbitrary set of knots. + + + +









+ +

Gaussian process regression

+ + + +$$ +$$ + \mu(x_1), \ldots \mu(x_N) \sim \mathrm{N}\left( \left( m(x_1), + \ldots, m(x_N) \right), K(x_1, \ldots, x_N) \right), +$$ +$$ + + with mean \( m \) and covariance \( K \). + +

+









+ +

Topics

+ + + + + + + +
+ © 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license +
+ + + + + + diff --git a/doc/src/GaussianProcess/GaussianProcess.ipynb b/doc/src/GaussianProcess/GaussianProcess.ipynb new file mode 100644 index 000000000..586703eed --- /dev/null +++ b/doc/src/GaussianProcess/GaussianProcess.ipynb @@ -0,0 +1,86 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "# Data Analysis and Machine Learning: Machine learning with Gaussian Processes\n", + "\n", + " \n", + "**Christian Forssén**, Department of Physics, Chalmers University of Technology, Sweden \n", + "\n", + " **Morten Hjorth-Jensen**, Department of Physics, University of Oslo and Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University\n", + "\n", + "Date: **Mar 19, 2018**\n", + "\n", + "Copyright 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license\n", + "\n", + "\n", + "\n", + "## What is a Gaussian Process?\n", + "\n", + "* We have considered splines and kernel regression methods. These\n", + "\n", + "require choice of somewhat arbitrary set of knots.\n", + "\n", + "* Antoher possibility is to setup a prior distribution for the\n", + " regression function using a *Gaussian Process*.\n", + "\n", + "* This is a very flexible class of models that has distinct computational\n", + " and theoretical advantages. It can be viewed as a potentially\n", + " infinite-dimensional generalization of Gaussian distributions.\n", + "\n", + "* See the excellent (and free) book [Gaussian Processes for Machine\n", + " Learning](http://www.gaussianprocess.org/gpml/) by Carl Edward\n", + " Rasmussen and Christopher K. I. Williams. \n", + "\n", + "## Gaussian process regression\n", + "\n", + "* Realizations from a Gaussian process correspond to random functions\n", + "\n", + "* Let us first consider an unknown regression function $\\mu(x)$ that\n", + " depends on a single, continuous variable $x$.\n", + "\n", + "* The Gaussian process is written as $\\mu \\sim \\mathrm{GP}(m,k)$, and\n", + " is parametrized in terms of a mean function $m(x)$ and a covariance\n", + " function $k(x,x')$.\n", + "\n", + "* The GP prior on $\\mu$ describes it as a random function for which\n", + " the values at any set of $N$ prespecified points $\\{x_i\\}_{i=1}^N$\n", + " are a draw from a $N$-dimensional normal distribution" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$$\n", + "$$\n", + " \\mu(x_1), \\ldots \\mu(x_N) \\sim \\mathrm{N}\\left( \\left( m(x_1),\n", + " \\ldots, m(x_N) \\right), K(x_1, \\ldots, x_N) \\right),\n", + "$$\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "with mean $m$ and covariance $K$.\n", + "\n", + "## Topics\n", + "* More matematical details\n", + "\n", + "* The role of the covariance function (different kernels)\n", + "\n", + "* multidimensional case\n", + "\n", + "* examples." + ] + } + ], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/doc/src/GaussianProcess/GaussianProcess.p.tex b/doc/src/GaussianProcess/GaussianProcess.p.tex new file mode 100644 index 000000000..fb9dbf644 --- /dev/null +++ b/doc/src/GaussianProcess/GaussianProcess.p.tex @@ -0,0 +1,234 @@ +%% +%% Automatically generated file from DocOnce source +%% (https://github.com/hplgit/doconce/) +%% +%% +% #ifdef PTEX2TEX_EXPLANATION +%% +%% The file follows the ptex2tex extended LaTeX format, see +%% ptex2tex: http://code.google.com/p/ptex2tex/ +%% +%% Run +%% ptex2tex myfile +%% or +%% doconce ptex2tex myfile +%% +%% to turn myfile.p.tex into an ordinary LaTeX file myfile.tex. +%% (The ptex2tex program: http://code.google.com/p/ptex2tex) +%% Many preprocess options can be added to ptex2tex or doconce ptex2tex +%% +%% ptex2tex -DMINTED myfile +%% doconce ptex2tex myfile envir=minted +%% +%% ptex2tex will typeset code environments according to a global or local +%% .ptex2tex.cfg configure file. doconce ptex2tex will typeset code +%% according to options on the command line (just type doconce ptex2tex to +%% see examples). If doconce ptex2tex has envir=minted, it enables the +%% minted style without needing -DMINTED. +% #endif + +% #define PREAMBLE + +% #ifdef PREAMBLE +%-------------------- begin preamble ---------------------- + +\documentclass[% +oneside, % oneside: electronic viewing, twoside: printing +final, % draft: marks overfull hboxes, figures with paths +10pt]{article} + +\listfiles % print all files needed to compile this document + +\usepackage{relsize,makeidx,color,setspace,amsmath,amsfonts,amssymb} +\usepackage[table]{xcolor} +\usepackage{bm,ltablex,microtype} + +\usepackage[pdftex]{graphicx} + +\usepackage[T1]{fontenc} +%\usepackage[latin1]{inputenc} +\usepackage{ucs} +\usepackage[utf8x]{inputenc} + +\usepackage{lmodern} % Latin Modern fonts derived from Computer Modern + +% Hyperlinks in PDF: +\definecolor{linkcolor}{rgb}{0,0,0.4} +\usepackage{hyperref} +\hypersetup{ + breaklinks=true, + colorlinks=true, + linkcolor=linkcolor, + urlcolor=linkcolor, + citecolor=black, + filecolor=black, + %filecolor=blue, + pdfmenubar=true, + pdftoolbar=true, + bookmarksdepth=3 % Uncomment (and tweak) for PDF bookmarks with more levels than the TOC + } +%\hyperbaseurl{} % hyperlinks are relative to this root + +\setcounter{tocdepth}{2} % levels in table of contents + +% --- fancyhdr package for fancy headers --- +\usepackage{fancyhdr} +\fancyhf{} % sets both header and footer to nothing +\renewcommand{\headrulewidth}{0pt} +\fancyfoot[LE,RO]{\thepage} +% Ensure copyright on titlepage (article style) and chapter pages (book style) +\fancypagestyle{plain}{ + \fancyhf{} + \fancyfoot[C]{{\footnotesize \copyright\ 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license}} +% \renewcommand{\footrulewidth}{0mm} + \renewcommand{\headrulewidth}{0mm} +} +% Ensure copyright on titlepages with \thispagestyle{empty} +\fancypagestyle{empty}{ + \fancyhf{} + \fancyfoot[C]{{\footnotesize \copyright\ 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license}} + \renewcommand{\footrulewidth}{0mm} + \renewcommand{\headrulewidth}{0mm} +} + +\pagestyle{fancy} + + +% prevent orhpans and widows +\clubpenalty = 10000 +\widowpenalty = 10000 + +% --- end of standard preamble for documents --- + + +% insert custom LaTeX commands... + +\raggedbottom +\makeindex +\usepackage[totoc]{idxlayout} % for index in the toc +\usepackage[nottoc]{tocbibind} % for references/bibliography in the toc + +%-------------------- end preamble ---------------------- + +\begin{document} + +% matching end for #ifdef PREAMBLE +% #endif + +\newcommand{\exercisesection}[1]{\subsection*{#1}} + + +% ------------------- main content ---------------------- + + + +% ----------------- title ------------------------- + +\thispagestyle{empty} + +\begin{center} +{\LARGE\bf +\begin{spacing}{1.25} +Data Analysis and Machine Learning: Machine learning with Gaussian Processes +\end{spacing} +} +\end{center} + +% ----------------- author(s) ------------------------- + +\begin{center} +{\bf Christian Forssén${}^{1}$} \\ [0mm] +\end{center} + + +\begin{center} +{\bf Morten Hjorth-Jensen${}^{2, 3}$} \\ [0mm] +\end{center} + +\begin{center} +% List of all institutions: +\centerline{{\small ${}^1$Department of Physics, Chalmers University of Technology, Sweden}} +\centerline{{\small ${}^2$Department of Physics, University of Oslo}} +\centerline{{\small ${}^3$Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University}} +\end{center} + +% ----------------- end author(s) ------------------------- + +% --- begin date --- +\begin{center} +Mar 19, 2018 +\end{center} +% --- end date --- + +\vspace{1cm} + + +% !split +\subsection{What is a Gaussian Process?} + +\begin{itemize} +\item We have considered splines and kernel regression methods. These +\end{itemize} + +\noindent +require choice of somewhat arbitrary set of knots. + +\begin{itemize} +\item Antoher possibility is to setup a prior distribution for the + regression function using a \emph{Gaussian Process}. + +\item This is a very flexible class of models that has distinct computational + and theoretical advantages. It can be viewed as a potentially + infinite-dimensional generalization of Gaussian distributions. + +\item See the excellent (and free) book \href{{http://www.gaussianprocess.org/gpml/}}{Gaussian Processes for Machine + Learning} by Carl Edward + Rasmussen and Christopher K. I. Williams. +\end{itemize} + +\noindent +% !split +\subsection{Gaussian process regression} + +\begin{itemize} +\item Realizations from a Gaussian process correspond to random functions + +\item Let us first consider an unknown regression function $\mu(x)$ that + depends on a single, continuous variable $x$. + +\item The Gaussian process is written as $\mu \sim \mathrm{GP}(m,k)$, and + is parametrized in terms of a mean function $m(x)$ and a covariance + function $k(x,x')$. + +\item The GP prior on $\mu$ describes it as a random function for which + the values at any set of $N$ prespecified points $\{x_i\}_{i=1}^N$ + are a draw from a $N$-dimensional normal distribution +\end{itemize} + +\noindent +$$ + \mu(x_1), \ldots \mu(x_N) \sim \mathrm{N}\left( \left( m(x_1), + \ldots, m(x_N) \right), K(x_1, \ldots, x_N) \right), +$$ + with mean $m$ and covariance $K$. + +% !split +\subsection{Topics} +\begin{itemize} +\item More matematical details + +\item The role of the covariance function (different kernels) + +\item multidimensional case + +\item examples. +\end{itemize} + +\noindent + +% ------------------- end of main content --------------- + +% #ifdef PREAMBLE +\end{document} +% #endif + diff --git a/doc/src/GaussianProcess/GaussianProcess.tex b/doc/src/GaussianProcess/GaussianProcess.tex new file mode 100644 index 000000000..10c1b645c --- /dev/null +++ b/doc/src/GaussianProcess/GaussianProcess.tex @@ -0,0 +1,206 @@ +%% +%% Automatically generated file from DocOnce source +%% (https://github.com/hplgit/doconce/) +%% +%% + + +%-------------------- begin preamble ---------------------- + +\documentclass[% +oneside, % oneside: electronic viewing, twoside: printing +final, % draft: marks overfull hboxes, figures with paths +10pt]{article} + +\listfiles % print all files needed to compile this document + +\usepackage{relsize,makeidx,color,setspace,amsmath,amsfonts,amssymb} +\usepackage[table]{xcolor} +\usepackage{bm,ltablex,microtype} + +\usepackage[pdftex]{graphicx} + +\usepackage[T1]{fontenc} +%\usepackage[latin1]{inputenc} +\usepackage{ucs} +\usepackage[utf8x]{inputenc} + +\usepackage{lmodern} % Latin Modern fonts derived from Computer Modern + +% Hyperlinks in PDF: +\definecolor{linkcolor}{rgb}{0,0,0.4} +\usepackage{hyperref} +\hypersetup{ + breaklinks=true, + colorlinks=true, + linkcolor=linkcolor, + urlcolor=linkcolor, + citecolor=black, + filecolor=black, + %filecolor=blue, + pdfmenubar=true, + pdftoolbar=true, + bookmarksdepth=3 % Uncomment (and tweak) for PDF bookmarks with more levels than the TOC + } +%\hyperbaseurl{} % hyperlinks are relative to this root + +\setcounter{tocdepth}{2} % levels in table of contents + +% --- fancyhdr package for fancy headers --- +\usepackage{fancyhdr} +\fancyhf{} % sets both header and footer to nothing +\renewcommand{\headrulewidth}{0pt} +\fancyfoot[LE,RO]{\thepage} +% Ensure copyright on titlepage (article style) and chapter pages (book style) +\fancypagestyle{plain}{ + \fancyhf{} + \fancyfoot[C]{{\footnotesize \copyright\ 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license}} +% \renewcommand{\footrulewidth}{0mm} + \renewcommand{\headrulewidth}{0mm} +} +% Ensure copyright on titlepages with \thispagestyle{empty} +\fancypagestyle{empty}{ + \fancyhf{} + \fancyfoot[C]{{\footnotesize \copyright\ 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license}} + \renewcommand{\footrulewidth}{0mm} + \renewcommand{\headrulewidth}{0mm} +} + +\pagestyle{fancy} + + +% prevent orhpans and widows +\clubpenalty = 10000 +\widowpenalty = 10000 + +% --- end of standard preamble for documents --- + + +% insert custom LaTeX commands... + +\raggedbottom +\makeindex +\usepackage[totoc]{idxlayout} % for index in the toc +\usepackage[nottoc]{tocbibind} % for references/bibliography in the toc + +%-------------------- end preamble ---------------------- + +\begin{document} + +% matching end for #ifdef PREAMBLE + +\newcommand{\exercisesection}[1]{\subsection*{#1}} + + +% ------------------- main content ---------------------- + + + +% ----------------- title ------------------------- + +\thispagestyle{empty} + +\begin{center} +{\LARGE\bf +\begin{spacing}{1.25} +Data Analysis and Machine Learning: Machine learning with Gaussian Processes +\end{spacing} +} +\end{center} + +% ----------------- author(s) ------------------------- + +\begin{center} +{\bf Christian Forssén${}^{1}$} \\ [0mm] +\end{center} + + +\begin{center} +{\bf Morten Hjorth-Jensen${}^{2, 3}$} \\ [0mm] +\end{center} + +\begin{center} +% List of all institutions: +\centerline{{\small ${}^1$Department of Physics, Chalmers University of Technology, Sweden}} +\centerline{{\small ${}^2$Department of Physics, University of Oslo}} +\centerline{{\small ${}^3$Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University}} +\end{center} + +% ----------------- end author(s) ------------------------- + +% --- begin date --- +\begin{center} +Mar 19, 2018 +\end{center} +% --- end date --- + +\vspace{1cm} + + +% !split +\subsection*{What is a Gaussian Process?} + +\begin{itemize} +\item We have considered splines and kernel regression methods. These +\end{itemize} + +\noindent +require choice of somewhat arbitrary set of knots. + +\begin{itemize} +\item Antoher possibility is to setup a prior distribution for the + regression function using a \emph{Gaussian Process}. + +\item This is a very flexible class of models that has distinct computational + and theoretical advantages. It can be viewed as a potentially + infinite-dimensional generalization of Gaussian distributions. + +\item See the excellent (and free) book \href{{http://www.gaussianprocess.org/gpml/}}{Gaussian Processes for Machine + Learning} by Carl Edward + Rasmussen and Christopher K. I. Williams. +\end{itemize} + +\noindent +% !split +\subsection*{Gaussian process regression} + +\begin{itemize} +\item Realizations from a Gaussian process correspond to random functions + +\item Let us first consider an unknown regression function $\mu(x)$ that + depends on a single, continuous variable $x$. + +\item The Gaussian process is written as $\mu \sim \mathrm{GP}(m,k)$, and + is parametrized in terms of a mean function $m(x)$ and a covariance + function $k(x,x')$. + +\item The GP prior on $\mu$ describes it as a random function for which + the values at any set of $N$ prespecified points $\{x_i\}_{i=1}^N$ + are a draw from a $N$-dimensional normal distribution +\end{itemize} + +\noindent +$$ + \mu(x_1), \ldots \mu(x_N) \sim \mathrm{N}\left( \left( m(x_1), + \ldots, m(x_N) \right), K(x_1, \ldots, x_N) \right), +$$ + with mean $m$ and covariance $K$. + +% !split +\subsection*{Topics} +\begin{itemize} +\item More matematical details + +\item The role of the covariance function (different kernels) + +\item multidimensional case + +\item examples. +\end{itemize} + +\noindent + +% ------------------- end of main content --------------- + +\end{document} + diff --git a/doc/src/GaussianProcess/README.txt b/doc/src/GaussianProcess/README.txt new file mode 100644 index 000000000..27774856a --- /dev/null +++ b/doc/src/GaussianProcess/README.txt @@ -0,0 +1,2 @@ +This IPython notebook GaussianProcess.ipynb does not require any additional +programs. diff --git a/doc/src/GaussianProcess/beamerthemered_plain.sty b/doc/src/GaussianProcess/beamerthemered_plain.sty new file mode 100644 index 000000000..a6b2d33bd --- /dev/null +++ b/doc/src/GaussianProcess/beamerthemered_plain.sty @@ -0,0 +1,12 @@ +\mode +\usecolortheme[rgb={0.8, 0.2, 0}]{structure} +\usefonttheme[onlysmall]{structurebold} + +\setbeamertemplate{navigation symbols}{} +%\setbeamertemplate{footline}[frame number] + +\usepackage{tikz} +\usetikzlibrary{arrows,shapes,backgrounds,decorations,mindmap} + +\mode + diff --git a/doc/src/GaussianProcess/beamerthemered_shadow.sty b/doc/src/GaussianProcess/beamerthemered_shadow.sty new file mode 100644 index 000000000..eff5ac479 --- /dev/null +++ b/doc/src/GaussianProcess/beamerthemered_shadow.sty @@ -0,0 +1,15 @@ +\mode + +\useoutertheme{smoothbars} +\useinnertheme[shadow=true]{rounded} +\usecolortheme{orchid} +\usecolortheme{whale} +\usecolortheme[rgb={0.7, 0.2, 0}]{structure} % (darker red) +\useoutertheme{shadow} +\usefonttheme[onlysmall]{structurebold} + +\setbeamercolor{title}{use=structure,fg=white,bg=structure.fg} +\setbeamerfont{block title}{size={}} + +\mode + diff --git a/doc/src/GaussianProcess/clean.sh b/doc/src/GaussianProcess/clean.sh new file mode 100755 index 000000000..2e5da2c72 --- /dev/null +++ b/doc/src/GaussianProcess/clean.sh @@ -0,0 +1,3 @@ +#!/bin/sh +doconce clean +rm -rf *.pdf *.tex ipynb*.tar.gz *.html ._*.html *~ reveal.js Trash README.txt diff --git a/doc/src/GaussianProcess/ipynb-GaussianProcess-src.tar.gz b/doc/src/GaussianProcess/ipynb-GaussianProcess-src.tar.gz new file mode 100644 index 000000000..49f93becf Binary files /dev/null and b/doc/src/GaussianProcess/ipynb-GaussianProcess-src.tar.gz differ diff --git a/doc/src/GaussianProcess/make.sh b/doc/src/GaussianProcess/make.sh new file mode 100755 index 000000000..edfed7c87 --- /dev/null +++ b/doc/src/GaussianProcess/make.sh @@ -0,0 +1,118 @@ +#!/bin/sh +set -x + +function system { + "$@" + if [ $? -ne 0 ]; then + echo "make.sh: unsuccessful command $@" + echo "abort!" + exit 1 + fi +} + +if [ $# -eq 0 ]; then +echo 'bash make.sh slides1|slides2' +exit 1 +fi + +name=$1 +rm -f *.tar.gz + +opt="--encoding=utf-8" +# Note: Makefile examples contain constructions like ${PROG} which +# looks like Mako constructions, but they are not. Use --no_mako +# to turn off Mako processing. +opt="--no_mako" + +rm -f *.aux + + +html=${name}-reveal +system doconce format html $name --pygments_html_style=perldoc --keep_pygments_html_bg --html_links_in_new_window --html_output=$html $opt +system doconce slides_html $html reveal --html_slide_theme=beige + +# Plain HTML documents + +html=${name}-solarized +system doconce format html $name --pygments_html_style=perldoc --html_style=solarized3 --html_links_in_new_window --html_output=$html $opt +system doconce split_html $html.html --method=space10 + +html=${name} +system doconce format html $name --pygments_html_style=default --html_style=bloodish --html_links_in_new_window --html_output=$html $opt +system doconce split_html $html.html --method=space10 + +# Bootstrap style +html=${name}-bs +system doconce format html $name --html_style=bootstrap --pygments_html_style=default --html_admon=bootstrap_panel --html_output=$html $opt +system doconce split_html $html.html --method=split --pagination --nav_button=bottom + +# IPython notebook +system doconce format ipynb $name $opt + +# LaTeX Beamer slides +beamertheme=red_plain +system doconce format pdflatex $name --latex_title_layout=beamer --latex_table_format=footnotesize $opt +system doconce ptex2tex $name envir=minted +# Add special packages +doconce subst "% Add user's preamble" "\g<1>\n\\usepackage{simplewick}" $name.tex +system doconce slides_beamer $name --beamer_slide_theme=$beamertheme +system pdflatex -shell-escape ${name} +system pdflatex -shell-escape ${name} +cp $name.pdf ${name}-beamer.pdf +cp $name.tex ${name}-beamer.tex + +# Handouts +system doconce format pdflatex $name --latex_title_layout=beamer --latex_table_format=footnotesize $opt +system doconce ptex2tex $name envir=minted +# Add special packages +doconce subst "% Add user's preamble" "\g<1>\n\\usepackage{simplewick}" $name.tex +system doconce slides_beamer $name --beamer_slide_theme=red_shadow --handout +system pdflatex -shell-escape $name +pdflatex -shell-escape $name +pdflatex -shell-escape $name +pdfnup --nup 2x3 --frame true --delta "1cm 1cm" --scale 0.9 --outfile ${name}-beamer-handouts2x3.pdf ${name}.pdf +rm -f ${name}.pdf + +# Ordinary plain LaTeX document +rm -f *.aux # important after beamer +system doconce format pdflatex $name --minted_latex_style=trac --latex_admon=paragraph $opt +system doconce ptex2tex $name envir=minted +# Add special packages +doconce subst "% Add user's preamble" "\g<1>\n\\usepackage{simplewick}" $name.tex +doconce replace 'section{' 'section*{' $name.tex +pdflatex -shell-escape $name +pdflatex -shell-escape $name +mv -f $name.pdf ${name}-minted.pdf +cp $name.tex ${name}-plain-minted.tex + + + +# Publish +dest=../../pub +if [ ! -d $dest/$name ]; then +mkdir $dest/$name +mkdir $dest/$name/pdf +mkdir $dest/$name/html +mkdir $dest/$name/ipynb +fi +cp ${name}*.pdf $dest/$name/pdf +cp -r ${name}*.html ._${name}*.html reveal.js $dest/$name/html + +# Figures: cannot just copy link, need to physically copy the files +if [ -d fig-${name} ]; then +if [ ! -d $dest/$name/html/fig-$name ]; then +mkdir $dest/$name/html/fig-$name +fi +cp -r fig-${name}/* $dest/$name/html/fig-$name +fi + +cp ${name}.ipynb $dest/$name/ipynb +ipynb_tarfile=ipynb-${name}-src.tar.gz +if [ ! -f ${ipynb_tarfile} ]; then +cat > README.txt <\n\\usepackage{simplewick}" $name.tex +doconce replace 'section{' 'section*{' $name.tex +pdflatex -shell-escape $name +pdflatex -shell-escape $name +mv -f $name.pdf ${name}-minted.pdf +cp $name.tex ${name}-plain-minted.tex + +# Publish +dest=../../pub +if [ ! -d $dest/$name ]; then +mkdir $dest/$name +mkdir $dest/$name/pdf +fi +cp ${name}*.pdf $dest/$name/pdf diff --git a/doc/src/GaussianProcess/reveal.js/.gitignore b/doc/src/GaussianProcess/reveal.js/.gitignore new file mode 100644 index 000000000..a5df3133d --- /dev/null +++ b/doc/src/GaussianProcess/reveal.js/.gitignore @@ -0,0 +1,8 @@ +.DS_Store +.svn +log/*.log +tmp/** +node_modules/ +.sass-cache +css/reveal.min.css +js/reveal.min.js diff --git a/doc/src/GaussianProcess/reveal.js/.travis.yml b/doc/src/GaussianProcess/reveal.js/.travis.yml new file mode 100644 index 000000000..165d9ae9f --- /dev/null +++ b/doc/src/GaussianProcess/reveal.js/.travis.yml @@ -0,0 +1,5 @@ +language: node_js +node_js: + - 0.10 +before_script: + - npm install -g grunt-cli \ No newline at end of file diff --git a/doc/src/GaussianProcess/reveal.js/CONTRIBUTING.md b/doc/src/GaussianProcess/reveal.js/CONTRIBUTING.md new file mode 100644 index 000000000..c2091e88f --- /dev/null +++ b/doc/src/GaussianProcess/reveal.js/CONTRIBUTING.md @@ -0,0 +1,23 @@ +## Contributing + +Please keep the [issue tracker](http://github.com/hakimel/reveal.js/issues) limited to **bug reports**, **feature requests** and **pull requests**. + + +### Personal Support +If you have personal support or setup questions the best place to ask those are [StackOverflow](http://stackoverflow.com/questions/tagged/reveal.js). + + +### Bug Reports +When reporting a bug make sure to include information about which browser and operating system you are on as well as the necessary steps to reproduce the issue. If possible please include a link to a sample presentation where the bug can be tested. + + +### Pull Requests +- Should follow the coding style of the file you work in, most importantly: + - Tabs to indent + - Single-quoted strings +- Should be made towards the **dev branch** +- Should be submitted from a feature/topic branch (not your master) + + +### Plugins +Please do not submit plugins as pull requests. They should be maintained in their own separate repository. More information here: https://github.com/hakimel/reveal.js/wiki/Plugin-Guidelines diff --git a/doc/src/GaussianProcess/reveal.js/Gruntfile.js b/doc/src/GaussianProcess/reveal.js/Gruntfile.js new file mode 100644 index 000000000..b257e8f32 --- /dev/null +++ b/doc/src/GaussianProcess/reveal.js/Gruntfile.js @@ -0,0 +1,140 @@ +/* global module:false */ +module.exports = function(grunt) { + var port = grunt.option('port') || 8000; + // Project configuration + grunt.initConfig({ + pkg: grunt.file.readJSON('package.json'), + meta: { + banner: + '/*!\n' + + ' * reveal.js <%= pkg.version %> (<%= grunt.template.today("yyyy-mm-dd, HH:MM") %>)\n' + + ' * http://lab.hakim.se/reveal-js\n' + + ' * MIT licensed\n' + + ' *\n' + + ' * Copyright (C) 2014 Hakim El Hattab, http://hakim.se\n' + + ' */' + }, + + qunit: { + files: [ 'test/*.html' ] + }, + + uglify: { + options: { + banner: '<%= meta.banner %>\n' + }, + build: { + src: 'js/reveal.js', + dest: 'js/reveal.min.js' + } + }, + + cssmin: { + compress: { + files: { + 'css/reveal.min.css': [ 'css/reveal.css' ] + } + } + }, + + sass: { + main: { + files: { + 'css/theme/darkgray.css': 'css/theme/source/darkgray.scss', + 'css/theme/beigesmall.css': 'css/theme/source/beigesmall.scss', + 'css/theme/cbc.css': 'css/theme/source/cbc.scss', + 'css/theme/default.css': 'css/theme/source/default.scss', + 'css/theme/beige.css': 'css/theme/source/beige.scss', + 'css/theme/night.css': 'css/theme/source/night.scss', + 'css/theme/serif.css': 'css/theme/source/serif.scss', + 'css/theme/simple.css': 'css/theme/source/simple.scss', + 'css/theme/sky.css': 'css/theme/source/sky.scss', + 'css/theme/moon.css': 'css/theme/source/moon.scss', + 'css/theme/solarized.css': 'css/theme/source/solarized.scss', + 'css/theme/blood.css': 'css/theme/source/blood.scss' + } + } + }, + + jshint: { + options: { + curly: false, + eqeqeq: true, + immed: true, + latedef: true, + newcap: true, + noarg: true, + sub: true, + undef: true, + eqnull: true, + browser: true, + expr: true, + globals: { + head: false, + module: false, + console: false, + unescape: false + } + }, + files: [ 'Gruntfile.js', 'js/reveal.js' ] + }, + + connect: { + server: { + options: { + port: port, + base: '.' + } + } + }, + + zip: { + 'reveal-js-presentation.zip': [ + 'index.html', + 'css/**', + 'js/**', + 'lib/**', + 'images/**', + 'plugin/**' + ] + }, + + watch: { + main: { + files: [ 'Gruntfile.js', 'js/reveal.js', 'css/reveal.css' ], + tasks: 'default' + }, + theme: { + files: [ 'css/theme/source/*.scss', 'css/theme/template/*.scss' ], + tasks: 'themes' + } + } + + }); + + // Dependencies + grunt.loadNpmTasks( 'grunt-contrib-qunit' ); + grunt.loadNpmTasks( 'grunt-contrib-jshint' ); + grunt.loadNpmTasks( 'grunt-contrib-cssmin' ); + grunt.loadNpmTasks( 'grunt-contrib-uglify' ); + grunt.loadNpmTasks( 'grunt-contrib-watch' ); + grunt.loadNpmTasks( 'grunt-contrib-sass' ); + grunt.loadNpmTasks( 'grunt-contrib-connect' ); + grunt.loadNpmTasks( 'grunt-zip' ); + + // Default task + grunt.registerTask( 'default', [ 'jshint', 'cssmin', 'uglify', 'qunit' ] ); + + // Theme task + grunt.registerTask( 'themes', [ 'sass' ] ); + + // Package presentation to archive + grunt.registerTask( 'package', [ 'default', 'zip' ] ); + + // Serve presentation locally + grunt.registerTask( 'serve', [ 'connect', 'watch' ] ); + + // Run tests + grunt.registerTask( 'test', [ 'jshint', 'qunit' ] ); + +}; diff --git a/doc/src/GaussianProcess/reveal.js/LICENSE b/doc/src/GaussianProcess/reveal.js/LICENSE new file mode 100644 index 000000000..09623076f --- /dev/null +++ b/doc/src/GaussianProcess/reveal.js/LICENSE @@ -0,0 +1,19 @@ +Copyright (C) 2015 Hakim El Hattab, http://hakim.se + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in +all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +THE SOFTWARE. \ No newline at end of file diff --git a/doc/src/GaussianProcess/reveal.js/README.md b/doc/src/GaussianProcess/reveal.js/README.md new file mode 100644 index 000000000..573b19597 --- /dev/null +++ b/doc/src/GaussianProcess/reveal.js/README.md @@ -0,0 +1,1052 @@ +# reveal.js [![Build Status](https://travis-ci.org/hakimel/reveal.js.svg?branch=master)](https://travis-ci.org/hakimel/reveal.js) + +A framework for easily creating beautiful presentations using HTML. [Check out the live demo](http://lab.hakim.se/reveal-js/). + +reveal.js comes with a broad range of features including [nested slides](https://github.com/hakimel/reveal.js#markup), [Markdown contents](https://github.com/hakimel/reveal.js#markdown), [PDF export](https://github.com/hakimel/reveal.js#pdf-export), [speaker notes](https://github.com/hakimel/reveal.js#speaker-notes) and a [JavaScript API](https://github.com/hakimel/reveal.js#api). It's best viewed in a modern browser but [fallbacks](https://github.com/hakimel/reveal.js/wiki/Browser-Support) are available to make sure your presentation can still be viewed elsewhere. + + +#### More reading: +- [Installation](#installation): Step-by-step instructions for getting reveal.js running on your computer. +- [Changelog](https://github.com/hakimel/reveal.js/releases): Up-to-date version history. +- [Examples](https://github.com/hakimel/reveal.js/wiki/Example-Presentations): Presentations created with reveal.js, add your own! +- [Browser Support](https://github.com/hakimel/reveal.js/wiki/Browser-Support): Explanation of browser support and fallbacks. +- [Plugins](https://github.com/hakimel/reveal.js/wiki/Plugins,-Tools-and-Hardware): A list of plugins that can be used to extend reveal.js. + +## Online Editor + +Presentations are written using HTML or Markdown but there's also an online editor for those of you who prefer a graphical interface. Give it a try at [http://slides.com](http://slides.com). + + +## Instructions + +### Markup + +Markup hierarchy needs to be ``
`` where the ``
`` represents one slide and can be repeated indefinitely. If you place multiple ``
``'s inside of another ``
`` they will be shown as vertical slides. The first of the vertical slides is the "root" of the others (at the top), and it will be included in the horizontal sequence. For example: + +```html +
+
+
Single Horizontal Slide
+
+
Vertical Slide 1
+
Vertical Slide 2
+
+
+
+``` + +### Markdown + +It's possible to write your slides using Markdown. To enable Markdown, add the ```data-markdown``` attribute to your ```
``` elements and wrap the contents in a ``` +
+``` + +#### External Markdown + +You can write your content as a separate file and have reveal.js load it at runtime. Note the separator arguments which determine how slides are delimited in the external file. The ```data-charset``` attribute is optional and specifies which charset to use when loading the external file. + +When used locally, this feature requires that reveal.js [runs from a local web server](#full-setup). + +```html +
+
+``` + +#### Element Attributes + +Special syntax (in html comment) is available for adding attributes to Markdown elements. This is useful for fragments, amongst other things. + +```html +
+ +
+``` + +#### Slide Attributes + +Special syntax (in html comment) is available for adding attributes to the slide `
` elements generated by your Markdown. + +```html +
+ +
+``` + + +### Configuration + +At the end of your page you need to initialize reveal by running the following code. Note that all config values are optional and will default as specified below. + +```javascript +Reveal.initialize({ + + // Display controls in the bottom right corner + controls: true, + + // Display a presentation progress bar + progress: true, + + // Display the page number of the current slide + slideNumber: false, + + // Push each slide change to the browser history + history: false, + + // Enable keyboard shortcuts for navigation + keyboard: true, + + // Enable the slide overview mode + overview: true, + + // Vertical centering of slides + center: true, + + // Enables touch navigation on devices with touch input + touch: true, + + // Loop the presentation + loop: false, + + // Change the presentation direction to be RTL + rtl: false, + + // Turns fragments on and off globally + fragments: true, + + // Flags if the presentation is running in an embedded mode, + // i.e. contained within a limited portion of the screen + embedded: false, + + // Flags if we should show a help overlay when the questionmark + // key is pressed + help: true, + + // Number of milliseconds between automatically proceeding to the + // next slide, disabled when set to 0, this value can be overwritten + // by using a data-autoslide attribute on your slides + autoSlide: 0, + + // Stop auto-sliding after user input + autoSlideStoppable: true, + + // Enable slide navigation via mouse wheel + mouseWheel: false, + + // Hides the address bar on mobile devices + hideAddressBar: true, + + // Opens links in an iframe preview overlay + previewLinks: false, + + // Transition style + transition: 'default', // none/fade/slide/convex/concave/zoom + + // Transition speed + transitionSpeed: 'default', // default/fast/slow + + // Transition style for full page slide backgrounds + backgroundTransition: 'default', // none/fade/slide/convex/concave/zoom + + // Number of slides away from the current that are visible + viewDistance: 3, + + // Parallax background image + parallaxBackgroundImage: '', // e.g. "'https://s3.amazonaws.com/hakim-static/reveal-js/reveal-parallax-1.jpg'" + + // Parallax background size + parallaxBackgroundSize: '', // CSS syntax, e.g. "2100px 900px" + + // Amount to move parallax background (horizontal and vertical) on slide change + // Number, e.g. 100 + parallaxBackgroundHorizontal: '', + parallaxBackgroundVertical: '' + +}); +``` + + +The configuration can be updated after initialization using the ```configure``` method: + +```javascript +// Turn autoSlide off +Reveal.configure({ autoSlide: 0 }); + +// Start auto-sliding every 5s +Reveal.configure({ autoSlide: 5000 }); +``` + + +### Dependencies + +Reveal.js doesn't _rely_ on any third party scripts to work but a few optional libraries are included by default. These libraries are loaded as dependencies in the order they appear, for example: + +```javascript +Reveal.initialize({ + dependencies: [ + // Cross-browser shim that fully implements classList - https://github.com/eligrey/classList.js/ + { src: 'lib/js/classList.js', condition: function() { return !document.body.classList; } }, + + // Interpret Markdown in
elements + { src: 'plugin/markdown/marked.js', condition: function() { return !!document.querySelector( '[data-markdown]' ); } }, + { src: 'plugin/markdown/markdown.js', condition: function() { return !!document.querySelector( '[data-markdown]' ); } }, + + // Syntax highlight for elements + { src: 'plugin/highlight/highlight.js', async: true, callback: function() { hljs.initHighlightingOnLoad(); } }, + + // Zoom in and out with Alt+click + { src: 'plugin/zoom-js/zoom.js', async: true }, + + // Speaker notes + { src: 'plugin/notes/notes.js', async: true }, + + // Remote control your reveal.js presentation using a touch device + { src: 'plugin/remotes/remotes.js', async: true }, + + // MathJax + { src: 'plugin/math/math.js', async: true } + ] +}); +``` + +You can add your own extensions using the same syntax. The following properties are available for each dependency object: +- **src**: Path to the script to load +- **async**: [optional] Flags if the script should load after reveal.js has started, defaults to false +- **callback**: [optional] Function to execute when the script has loaded +- **condition**: [optional] Function which must return true for the script to be loaded + + +### Ready Event + +A 'ready' event is fired when reveal.js has loaded all non-async dependencies and is ready to start navigating. To check if reveal.js is already 'ready' you can call `Reveal.isReady()`. + +```javascript +Reveal.addEventListener( 'ready', function( event ) { + // event.currentSlide, event.indexh, event.indexv +} ); +``` + + +### Presentation Size + +All presentations have a normal size, that is the resolution at which they are authored. The framework will automatically scale presentations uniformly based on this size to ensure that everything fits on any given display or viewport. + +See below for a list of configuration options related to sizing, including default values: + +```javascript +Reveal.initialize({ + + ... + + // The "normal" size of the presentation, aspect ratio will be preserved + // when the presentation is scaled to fit different resolutions. Can be + // specified using percentage units. + width: 960, + height: 700, + + // Factor of the display size that should remain empty around the content + margin: 0.1, + + // Bounds for smallest/largest possible scale to apply to content + minScale: 0.2, + maxScale: 1.5 + +}); +``` + + +### Auto-sliding + +Presentations can be configured to progress through slides automatically, without any user input. To enable this you will need to tell the framework how many milliseconds it should wait between slides: + +```javascript +// Slide every five seconds +Reveal.configure({ + autoSlide: 5000 +}); +``` +When this is turned on a control element will appear that enables users to pause and resume auto-sliding. Alternatively, sliding can be paused or resumed by pressing »a« on the keyboard. Sliding is paused automatically as soon as the user starts navigating. You can disable these controls by specifying ```autoSlideStoppable: false``` in your reveal.js config. + +You can also override the slide duration for individual slides and fragments by using the ```data-autoslide``` attribute: + +```html +
+

After 2 seconds the first fragment will be shown.

+

After 10 seconds the next fragment will be shown.

+

Now, the fragment is displayed for 2 seconds before the next slide is shown.

+
+``` + +Whenever the auto-slide mode is resumed or paused the ```autoslideresumed``` and ```autoslidepaused``` events are fired. + + +### Keyboard Bindings + +If you're unhappy with any of the default keyboard bindings you can override them using the ```keyboard``` config option: + +```javascript +Reveal.configure({ + keyboard: { + 13: 'next', // go to the next slide when the ENTER key is pressed + 27: function() {}, // do something custom when ESC is pressed + 32: null // don't do anything when SPACE is pressed (i.e. disable a reveal.js default binding) + } +}); +``` + +### Lazy Loading + +When working on presentation with a lot of media or iframe content it's important to load lazily. Lazy loading means that reveal.js will only load content for the few slides nearest to the current slide. The number of slides that are preloaded is determined by the `viewDistance` configuration option. + +To enable lazy loading all you need to do is change your "src" attributes to "data-src" as shown below. This is supported for image, video, audio and iframe elements. Lazy loaded iframes will also unload when the containing slide is no longer visible. + +```html +
+ + + +
+``` + + +### API + +The ``Reveal`` object exposes a JavaScript API for controlling navigation and reading state: + +```javascript +// Navigation +Reveal.slide( indexh, indexv, indexf ); +Reveal.left(); +Reveal.right(); +Reveal.up(); +Reveal.down(); +Reveal.prev(); +Reveal.next(); +Reveal.prevFragment(); +Reveal.nextFragment(); + +// Toggle presentation states, optionally pass true/false to force on/off +Reveal.toggleOverview(); +Reveal.togglePause(); +Reveal.toggleAutoSlide(); + +// Change a config value at runtime +Reveal.configure({ controls: true }); + +// Returns the present configuration options +Reveal.getConfig(); + +// Fetch the current scale of the presentation +Reveal.getScale(); + +// Retrieves the previous and current slide elements +Reveal.getPreviousSlide(); +Reveal.getCurrentSlide(); + +Reveal.getIndices(); // { h: 0, v: 0 } } +Reveal.getProgress(); // 0-1 +Reveal.getTotalSlides(); + +// State checks +Reveal.isFirstSlide(); +Reveal.isLastSlide(); +Reveal.isOverview(); +Reveal.isPaused(); +Reveal.isAutoSliding(); +``` + +### Slide Changed Event + +A 'slidechanged' event is fired each time the slide is changed (regardless of state). The event object holds the index values of the current slide as well as a reference to the previous and current slide HTML nodes. + +Some libraries, like MathJax (see [#226](https://github.com/hakimel/reveal.js/issues/226#issuecomment-10261609)), get confused by the transforms and display states of slides. Often times, this can be fixed by calling their update or render function from this callback. + +```javascript +Reveal.addEventListener( 'slidechanged', function( event ) { + // event.previousSlide, event.currentSlide, event.indexh, event.indexv +} ); +``` + +### Presentation State + +The presentation's current state can be fetched by using the `getState` method. A state object contains all of the information required to put the presentation back as it was when `getState` was first called. Sort of like a snapshot. It's a simple object that can easily be stringified and persisted or sent over the wire. + +```javascript +Reveal.slide( 1 ); +// we're on slide 1 + +var state = Reveal.getState(); + +Reveal.slide( 3 ); +// we're on slide 3 + +Reveal.setState( state ); +// we're back on slide 1 +``` + +### Slide States + +If you set ``data-state="somestate"`` on a slide ``
``, "somestate" will be applied as a class on the document element when that slide is opened. This allows you to apply broad style changes to the page based on the active slide. + +Furthermore you can also listen to these changes in state via JavaScript: + +```javascript +Reveal.addEventListener( 'somestate', function() { + // TODO: Sprinkle magic +}, false ); +``` + +### Slide Backgrounds + +Slides are contained within a limited portion of the screen by default to allow them to fit any display and scale uniformly. You can apply full page backgrounds outside of the slide area by adding a ```data-background``` attribute to your ```
``` elements. Four different types of backgrounds are supported: color, image, video and iframe. Below are a few examples. + +```html +
+

All CSS color formats are supported, like rgba() or hsl().

+
+
+

This slide will have a full-size background image.

+
+
+

This background image will be sized to 100px and repeated.

+
+
+

Video. Multiple sources can be defined using a comma separated list. Video will loop when the data-background-video-loop attribute is provided.

+
+
+

Embeds a web page as a background. Note that the page won't be interactive.

+
+``` + +Backgrounds transition using a fade animation by default. This can be changed to a linear sliding transition by passing ```backgroundTransition: 'slide'``` to the ```Reveal.initialize()``` call. Alternatively you can set ```data-background-transition``` on any section with a background to override that specific transition. + + +### Parallax Background + +If you want to use a parallax scrolling background, set the first two config properties below when initializing reveal.js (the other two are optional). + +```javascript +Reveal.initialize({ + + // Parallax background image + parallaxBackgroundImage: '', // e.g. "https://s3.amazonaws.com/hakim-static/reveal-js/reveal-parallax-1.jpg" + + // Parallax background size + parallaxBackgroundSize: '', // CSS syntax, e.g. "2100px 900px" - currently only pixels are supported (don't use % or auto) + + // Amount of pixels to move the parallax background per slide step, + // a value of 0 disables movement along the given axis + // These are optional, if they aren't specified they'll be calculated automatically + parallaxBackgroundHorizontal: 200, + parallaxBackgroundVertical: 50 + +}); +``` + +Make sure that the background size is much bigger than screen size to allow for some scrolling. [View example](http://lab.hakim.se/reveal-js/?parallaxBackgroundImage=https%3A%2F%2Fs3.amazonaws.com%2Fhakim-static%2Freveal-js%2Freveal-parallax-1.jpg¶llaxBackgroundSize=2100px%20900px). + + + +### Slide Transitions +The global presentation transition is set using the ```transition``` config value. You can override the global transition for a specific slide by using the ```data-transition``` attribute: + +```html +
+

This slide will override the presentation transition and zoom!

+
+ +
+

Choose from three transition speeds: default, fast or slow!

+
+``` + +You can also use different in and out transitions for the same slide: + +```html +
+ The train goes on … +
+
+ and on … +
+
+ and stops. +
+
+ (Passengers entering and leaving) +
+
+ And it starts again. +
+``` + + +Note that this does not work with the page and cube transitions. + + +### Internal links + +It's easy to link between slides. The first example below targets the index of another slide whereas the second targets a slide with an ID attribute (```
```): + +```html +Link +Link +``` + +You can also add relative navigation links, similar to the built in reveal.js controls, by appending one of the following classes on any element. Note that each element is automatically given an ```enabled``` class when it's a valid navigation route based on the current slide. + +```html + + + + + + +``` + + +### Fragments +Fragments are used to highlight individual elements on a slide. Every element with the class ```fragment``` will be stepped through before moving on to the next slide. Here's an example: http://lab.hakim.se/reveal-js/#/fragments + +The default fragment style is to start out invisible and fade in. This style can be changed by appending a different class to the fragment: + +```html +
+

grow

+

shrink

+

fade-out

+

visible only once

+

blue only once

+

highlight-red

+

highlight-green

+

highlight-blue

+
+``` + +Multiple fragments can be applied to the same element sequentially by wrapping it, this will fade in the text on the first step and fade it back out on the second. + +```html +
+ + I'll fade in, then out + +
+``` + +The display order of fragments can be controlled using the ```data-fragment-index``` attribute. + +```html +
+

Appears last

+

Appears first

+

Appears second

+
+``` + +### Fragment events + +When a slide fragment is either shown or hidden reveal.js will dispatch an event. + +Some libraries, like MathJax (see #505), get confused by the initially hidden fragment elements. Often times this can be fixed by calling their update or render function from this callback. + +```javascript +Reveal.addEventListener( 'fragmentshown', function( event ) { + // event.fragment = the fragment DOM element +} ); +Reveal.addEventListener( 'fragmenthidden', function( event ) { + // event.fragment = the fragment DOM element +} ); +``` + +### Code syntax highlighting + +By default, Reveal is configured with [highlight.js](http://softwaremaniacs.org/soft/highlight/en/) for code syntax highlighting. Below is an example with clojure code that will be syntax highlighted. When the `data-trim` attribute is present surrounding whitespace is automatically removed. + +```html +
+ 

+(def lazy-fib
+  (concat
+   [0 1]
+   ((fn rfib [a b]
+        (lazy-cons (+ a b) (rfib b (+ a b)))) 0 1)))
+
+
+``` + +### Slide number +If you would like to display the page number of the current slide you can do so using the ```slideNumber``` configuration value. + +```javascript +// Shows the slide number using default formatting +Reveal.configure({ slideNumber: true }); + +// Slide number formatting can be configured using these variables: +// h: current slide's horizontal index +// v: current slide's vertical index +// c: current slide index (flattened) +// t: total number of slides (flattened) +Reveal.configure({ slideNumber: 'c / t' }); + +``` + + +### Overview mode + +Press "Esc" or "o" keys to toggle the overview mode on and off. While you're in this mode, you can still navigate between slides, +as if you were at 1,000 feet above your presentation. The overview mode comes with a few API hooks: + +```javascript +Reveal.addEventListener( 'overviewshown', function( event ) { /* ... */ } ); +Reveal.addEventListener( 'overviewhidden', function( event ) { /* ... */ } ); + +// Toggle the overview mode programmatically +Reveal.toggleOverview(); +``` + +### Fullscreen mode +Just press »F« on your keyboard to show your presentation in fullscreen mode. Press the »ESC« key to exit fullscreen mode. + + +### Embedded media +Embedded HTML5 `