adjusted some elements

.gitignore

@@ -0,0 +1,25 @@
+/2022-03-replication/Makefile
+/2022-03-replication/_minted-replication/
+/2022-03-replication/a.csv
+/2022-03-replication/all.csv
+/2022-03-replication/article.aux
+/2022-03-replication/article.log
+/2022-03-replication/article.pdf
+/2022-03-replication/article.tex
+/2022-03-replication/b.csv
+/2022-03-replication/c.csv
+/2022-03-replication/comb.py
+/2022-03-replication/gen.py
+/2022-03-replication/graph.png
+/2022-03-replication/graph.py
+/2022-03-replication/maketable.py
+/2022-03-replication/org/.eg.org.~undo-tree~
+/2022-03-replication/org/*.bbl
+/2022-03-replication/org/eg.tex
+/2022-03-replication/org/obipy-resources/
+/2022-03-replication/replication.bbl
+/2022-03-replication/replication.tex
+/2022-03-replication/result.tex
+/2022-03-replication/rs/.Rhistory
+/2022-03-replication/org/.ob-jupyter/
+/2022-03-replication/test/

2022-03-replication/org/eg.org

@@ -1,7 +1,7 @@
 #+title: Example research paper written with org mode
 #+author: James Brusey
 #+options: toc:nil
-#+property: header-args:ipython :session eg-sess :results output raw drawer :exports results
+#+property: header-args:jupyter-python :session eg-sess :results output raw drawer :exports results
 #+latex_class: IEEEtran
 #+latex_header: \input{header}
 #+begin_abstract
@@ -15,7 +15,7 @@ The introduction should not just repeat the abstract but should properly introdu
 Towards the end of the introduction, there should be a statement about what the contribution of the paper.
 In computer science these days, it is common to use a bullet pointed list with forward references to sections where that contribution can be found.
 * Related work
-When it comes to citing references, org-ref is pretty cool. For example, I can cite a work [[cite:&kitchinExamplesEffectiveData2015]], and this will then show up in the references [[cite:&wilkinsModellingUncontrolledSolar2018]]. 
+When it comes to citing references, org-ref is pretty cool. For example, I can cite a work [[cite:&kitchinExamplesEffectiveData2015]], and this will then show up in the references [[cite:&wilkinsModellingUncontrolledSolar2018]].
 * Methods and materials
 In the method section, you might have a diagram.
 
@@ -37,7 +37,17 @@ While you can manually enter tables in org-mode, such as in autoref:table1.
 
 A similar table can be produced using code, as in autoref:table2.
 
-#+BEGIN_SRC ipython
+#+begin_src shell :results raw drawer
+echo "hello"
+#+end_src
+
+#+RESULTS:
+:results:
+hello
+:end:
+
+
+#+BEGIN_SRC jupyter-python :results raw drawer
 import pandas as pd
 import numpy as np
 import tabulate
@@ -54,18 +64,17 @@ print(
 #+END_SRC
 
 #+RESULTS:
-:results:
+:
+: #+caption: This table was produced from the all.csv data-set. label:table2
+: #+attr_latex: :align lSS
+: | Class   |   \protect{mean} |   \protect{std} |
+: |---------+------------------+-----------------|
+: | a       |         4.3      |         3.16394 |
+: | b       |        -0.114247 |         1.00812 |
+: | c       |         4.72661  |         3.85745 |
 
-#+caption: This table was produced from the all.csv data-set. label:table2
-#+attr_latex: :align lSS
-| Class   |   \protect{mean} |   \protect{std} |
-|---------+------------------+-----------------|
-| a       |         4.3      |         3.16394 |
-| b       |        -0.114247 |         1.00812 |
-| c       |         4.72661  |         3.85745 |
-:end:
 
-#+BEGIN_SRC ipython
+#+BEGIN_SRC jupyter-python
 %matplotlib inline
 import pandas as pd
 import numpy as np
@@ -74,18 +83,10 @@ df = pd.read_csv("../all.csv")
 plt.figure()
 plt.plot(df['a'], df['b'], '.')
 plt.show()
-
 #+END_SRC
 
 #+RESULTS:
-:results:
-# Out [2]: 
-# text/plain
-: <Figure size 432x288 with 1 Axes>
-
-# image/png
-[[file:obipy-resources/2abc833ac46639e8c3c3db1b162ed52c45494cc7/2b10c27d7fec897b3ebf8364b6da6e8b674ac4e0.png]]
-:end:
+[[file:./.ob-jupyter/2b10c27d7fec897b3ebf8364b6da6e8b674ac4e0.png]]
 
 
 * Conclusions
@@ -95,26 +96,16 @@ bibliography:~/Documents/zotero-export.bib
 bibliographystyle:plain
 * Needed for adding IEEEtran class                                 :noexport:
 
-#+BEGIN_SRC emacs-lisp
+#+BEGIN_SRC emacs-lisp :results silent
 (add-to-list 'org-latex-classes
              '("IEEEtran"
                "\\documentclass\[10pt\]\{IEEEtran\}"
                ("\\section\{%s\}" . "\\section*\{%s\}")
                ("\\subsection\{%s\}" . "\\subsection*\{%s\}")
                ("\\subsubsection\{%s\}" . "\\subsubsection*\{%s\}")
                ("\\paragraph\{%s\}" . "\\paragraph*\{%s\}")
-	       ))
+               ))
 
 #+END_SRC
 
-#+RESULTS:
-| IEEEtran            | \documentclass[10pt]{IEEEtran}        | (\section{%s} . \section*{%s}) | (\subsection{%s} . \subsection*{%s}) | (\subsubsection{%s} . \subsubsection*{%s}) | (\paragraph{%s} . \paragraph*{%s})         |                                            |
-| scrartcl            | \documentclass[10pt]{scrartcl}        | (\section{%s} . \section*{%s}) | (\subsection{%s} . \subsection*{%s}) | (\subsubsection{%s} . \subsubsection*{%s}) | (\paragraph{%s} . \paragraph*{%s})         |                                            |
-| scrreprt            | \documentclass[10pt,DIV=11]{scrreprt} | (\chapter{%s} . \chapter*{%s}) | (\section{%s} . \section*{%s})       | (\subsection{%s} . \subsection*{%s})       | (\subsubsection{%s} . \subsubsection*{%s}) | (\paragraph{%s} . \paragraph*{%s})         |
-| beamer              | \documentclass[presentation]{beamer}  | (\section{%s} . \section*{%s}) | (\subsection{%s} . \subsection*{%s}) | (\subsubsection{%s} . \subsubsection*{%s}) |                                            |                                            |
-| default-koma-letter | \documentclass[11pt]{scrlttr2}        |                                |                                      |                                            |                                            |                                            |
-| article             | \documentclass[11pt]{article}         | (\section{%s} . \section*{%s}) | (\subsection{%s} . \subsection*{%s}) | (\subsubsection{%s} . \subsubsection*{%s}) | (\paragraph{%s} . \paragraph*{%s})         | (\subparagraph{%s} . \subparagraph*{%s})   |
-| report              | \documentclass[11pt]{report}          | (\part{%s} . \part*{%s})       | (\chapter{%s} . \chapter*{%s})       | (\section{%s} . \section*{%s})             | (\subsection{%s} . \subsection*{%s})       | (\subsubsection{%s} . \subsubsection*{%s}) |
-| book                | \documentclass[11pt]{book}            | (\part{%s} . \part*{%s})       | (\chapter{%s} . \chapter*{%s})       | (\section{%s} . \section*{%s})             | (\subsection{%s} . \subsection*{%s})       | (\subsubsection{%s} . \subsubsection*{%s}) |
-
 [[elisp:(org-latex-export-to-pdf)]]

2022-03-replication/replication.org

@@ -18,7 +18,7 @@
 + There are few incentives to publish *better* papers
 + Penalties for negligence, bias, and fraud are minor even if offenders are found out
 
-#+attr_latex: :height 3cm  
+#+attr_latex: :height 3cm
 [[file:science-fictions-book.jpg]]
 
 * Our institutions are implicated
@@ -42,7 +42,7 @@ These ideas are focused on the /analysis/ rather than the experimental work itse
   - but why were they using Excel?
 + An analysis of genomics research shows that many studies have fallen prey to MARCH1 gene being altered by autocorrect in Excel
 + There are many reasons why you should not use Word but the number one reason is that it will stop you from automating parts of your research---you will tend to be relying on cutting and pasting in figures and tables rather than auto-generating them. /Convert away before it is too late./
-  
+
 * Use the command line and GNU Make
 + Analysis ends up having several steps
   - combining multiple data-sets into one
@@ -51,7 +51,7 @@ These ideas are focused on the /analysis/ rather than the experimental work itse
   - summarising data to produce a table
   - producing a graph
 
-* Method for using Make    
+* Method for using Make
 + Each step should be performed with a command or script (e.g., gnuplot)
 + Form multiple steps into a pipeline with GNU Make
 + Alongside much on-line sources, also see Data Science at the Command Line https://datascienceatthecommandline.com/
@@ -61,7 +61,7 @@ These ideas are focused on the /analysis/ rather than the experimental work itse
 * Example---generating data
 For example, say we have a script to generate some data =a.csv=, =b.csv=, =c.csv= called =gen.py=
 
-#+BEGIN_SRC ipython :exports code
+#+BEGIN_SRC python :tangle gen.py
 import pandas as pd
 import numpy as np
 
@@ -75,12 +75,9 @@ df = pd.DataFrame(np.random.normal(5, 3, size=SZ), columns=["value"])
 df.to_csv("c.csv", index=False)
 #+END_SRC
 
-#+RESULTS:
-:results:
-:end:
 * Example---combine data
 We might then have another script =comb.py= to combine them.
-#+BEGIN_SRC ipython
+#+BEGIN_SRC python :tangle comb.py
 import pandas as pd
 import numpy as np
 
@@ -97,7 +94,7 @@ df.to_csv("all.csv", index=False)
 :end:
 * Example---table
 We can produce a table using python tabulate in a script called =maketable.py=
-#+BEGIN_SRC ipython
+#+BEGIN_SRC python :tangle maketable.py
 import pandas as pd
 import numpy as np
 import tabulate
@@ -112,13 +109,10 @@ with open("result.tex", "w") as f:
     )
 #+END_SRC
 
-#+RESULTS:
-:results:
-:end:
 
 * Example---graph
 Finally, we might use =graph.py= to plot =a= versus =b= (ok, this is not a very meaningful graph!)
-#+BEGIN_SRC ipython
+#+BEGIN_SRC python :tangle graph.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -127,15 +121,12 @@ df.plot(x="a", y="b", kind="scatter")
 plt.savefig("graph.png")
 #+END_SRC
 
-#+RESULTS:
-:results:
-:end:
 #+attr_latex: :height 3cm
 [[file:graph.png]]
 
 * Example---LaTeX doc
 Naturally, we need a LaTeX document:
-#+BEGIN_SRC latex :exports code :file article.tex
+#+BEGIN_SRC latex :exports code :tangle article.tex
 \documentclass{article}
 \usepackage{siunitx}
 \usepackage{graphicx}
@@ -154,36 +145,33 @@ Blah blah blah.
 \end{document}
 #+END_SRC
 
-#+RESULTS:
-#+begin_export latex
-#+end_export
 * Example---Makefile
 Finally, we tie everything together with a =Makefile=
-#+BEGIN_SRC makefile
+#+BEGIN_SRC makefile :tangle Makefile
 article.pdf: article.tex result.tex graph.png
-	pdflatex article.tex
+        pdflatex article.tex
 
 graph.png: all.csv graph.py
-	python graph.py
+        python graph.py
 
 result.tex: all.csv maketable.py
-	python maketable.py	
+        python maketable.py
 
 all.csv: a.csv b.csv c.csv comb.py
-	python comb.py
+        python comb.py
 
 a.csv: gen.py
-	python gen.py
+        python gen.py
 #+END_SRC
 
-  
+
 * Using RStudio
 + RStudio allows you to put all the steps into a notebook form
 + The result can be exported to a LaTeX document
 + Best for R but difficult to format for a paper
 + A great resource for R and the tidyverse is R for Data Science https://r4ds.had.co.nz/
 + You can also use Pandoc separately from RStudio
-* RStudio example :noexport:  
+* RStudio example :noexport:
 [[file:rs/rs-eg.Rmd]]
 * RStudio example
 #+include: rs/rs-eg.Rmd src markdown
@@ -209,7 +197,7 @@ a.csv: gen.py
                ("\\subsection\{%s\}" . "\\subsection*\{%s\}")
                ("\\subsubsection\{%s\}" . "\\subsubsection*\{%s\}")
                ("\\paragraph\{%s\}" . "\\paragraph*\{%s\}")
-	       ))
+               ))
 
 #+END_SRC
 * Formatting numbers
@@ -221,7 +209,9 @@ a.csv: gen.py
 2. John Kitchin has a nice article on embedding data into PDFs. [[cite:&kitchinExamplesEffectiveData2015]]
 3. He also has a youtube describing org mode for research https://youtu.be/1-dUkyn_fZA
 
-bibliographystyle:plainnat 
+
+
+bibliographystyle:plainnat
 bibliography:~/Documents/zotero-export.bib
 * build :noexport:
 [[elisp:(org-beamer-export-to-pdf)]]