org-mode-poster/src/org-mode-poster_poster.org

Preamble   ignore

General comments   ignore

Specific comments for this manuscript   ignore

org specific settings   ignore

Latex header   ignore

Authors and affiliations   ignore

Buffer-wide source code blocks   ignore

# # #

End preamble   ignore

The poster

Code   ignore

Left column   BMCOL

Background   B_block

• Here we show how org-mode (version

  org-version

  ) together with emacs (version

  emacs-version} {{{results(25.2.2)}}

  ) can be used to make decent looking scientific posters
• With org-mode we can populate the poster with code, graphs and numbers from inline code in languages such as R, python, Matlab and even shell scripting
• For example, this poster was created on
• Inline code could look like this (which will produce a graph; Fig. /emacs/org-mode-poster/src/commit/63176e438215fa992d1f554d4569bc3419816ca9/src/figcode1):

Block

set.seed(20180402)
x1 <- rnorm(100, 0, 1)
x2 <- rnorm(100, 0.5, 1)
hist(x1, col="red")
hist(x2, col="blue", add=TRUE)

This is the output.

Inline code and tables   B_block

• In addition to inline code, we can also produce tables
• Tables are very powerful in org-mode, they even include spreadsheet capabilities
• Some code to process the first vector from above to make a table out of its summary could look like this, which would result in a little table (Table /emacs/org-mode-poster/src/commit/63176e438215fa992d1f554d4569bc3419816ca9/src/tabcode2) :

Block

library(broom)
library(dplyr)
t1 <- tidy(round(summary(x1), 2)) 
t2 <- tidy(round(summary(x2), 2))

# This will export as a table
rbind(t1, t2) %>%
mutate(name=c("x1", "x2"))

\vspace{2cm}

minimum	q1	median	mean	q3	maximum	name
-2.29	-0.49	0.11	0.14	0.8	2.47	x1
-2.17	-0.45	0.07	0.13	0.85	2.23	x2

Right column   BMCOL

Graphics   B_block

• We can use shell scripting to grab an image with curl from the internet (Fig. /emacs/org-mode-poster/src/commit/63176e438215fa992d1f554d4569bc3419816ca9/src/figcode3):

Block

\footnotesize

# Download emacs icon from gnu.org
curl -0 https://www.gnu.org/software/emacs/images/emacs.png

\normalsize

\vspace{2cm}

This is the downloaded image.

Math   B_block

• We can easily include math
• For example, let's describe how to compute the distance between the two simulated distributions $x1$ and $x2$ from before:

Block

The Kullback-Leibler (KL) divergence measures the difference between two probability distributions (i.e., the loss of information when one distribution is used to approximate another). The KL divergence is thus defined as

\begin{align} \label{eq:KL} \DKLPQ{P}{Q}{\|} = \sumin \Xoi{P} \log \frakPQ{P}{Q} \end{align}

with $P$ and $Q$ being two probability distribution functions and $n$ the number of sample points. Since $\DKLPQ{P}{Q}{\|}$ is not equal to $\DKLPQ{Q}{P}{\|}$, a symmetric variation of the KL divergence can be derived as follows:

\begin{align} \label{eq:KL2} \DKLPQ{P}{Q}{,} = \sumin \Big(\Xoi{P} \log \frakPQ{P}{Q} + \Xoi{Q} \log \frakPQ{Q}{P} \Big). \end{align}

Columns   B_block

Left

∩tionsetup{justification=justified,width=.85\linewidth}

This is the left figure of a two-column block, showing the density of $x1$.

Right

∩tionsetup{justification=justified,width=.85\linewidth}

This is the right figure. It shows the density of $x2$.

Conclusions   B_block

• This little example is meant to show how versatile org-mode is
• Scientific posters can be produced with a simple text editor